The deployment of automated deep-learning classifiers in clinical practice has the potential to streamline the diagnosis process and improve the diagnosis accuracy, but the acceptance of those classifiers relies on both their accuracy and interpretability.
In general, accurate deep-learning classifiers provide little model interpretability, whi...
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In today’s rapidly evolving business landscape, the integration of robotics and automation into supply chain management has emerged as a transformative force reshaping the way goods and services are produced, stored, and delivered. As global markets demand higher speed, precision, and efficiency, companies are increasingly leveraging adv...
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In today’s rapidly evolving global marketplace, supply chains are no longer mere channels for moving goods from suppliers to customers; they have transformed into complex, interconnected ecosystems that drive organizational competitiveness and customer satisfaction. The concept of Supply Chain Excellence has gained paramount importance ...
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In recent years, supply chain management has witnessed a transformative shift driven by the adoption of advanced technologies, among which machine learning (ML) stands out as a revolutionary tool. Machine learning, a subset of artificial intelligence, enables systems to learn from data, identify patterns, and make decisions with minimal...
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The modern supply chain has evolved into a dynamic, data-driven ecosystem that demands real-time responsiveness, agility, and strategic foresight. In this transformative landscape, Artificial Intelligence (AI) and Machine Learning (ML) have emerged as powerful technologies reshaping how supply chains operate, adapt, and innovate. These technologies...
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In today’s rapidly evolving digital landscape, personalized marketing has emerged as a critical strategy for businesses aiming to connect with consumers more effectively. Unlike traditional marketing approaches that adopt a one-size-fits-all method, personalized marketing leverages data analytics, consumer insights, and technology to tai...
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The fashion industry, known for its fast-paced evolution and trend-sensitive nature, has undergone a significant transformation in recent years, largely driven by the advent and rise of digital marketing. With the proliferation of the internet, smartphones, and social media, fashion brands now operate in an environment where digital presence is not...
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The steel industry plays a pivotal role in the economic development of any nation, acting as a backbone for infrastructure, construction, manufacturing, and various other sectors. It is considered one of the core sectors due to its extensive use in producing machinery, automobiles, railways, and household appliances, among others. The financial hea...
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Job satisfaction is a crucial factor that influences the overall performance and productivity of employees in any industry. In today's competitive business environment, packaging industries play a vital role in the manufacturing and distribution sectors, providing essential services that ensure product safety, brand presentation, and customer conve...
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The steel industry has long been a cornerstone of industrial development and economic progress across the globe. It is fundamental to infrastructure, construction, transportation, and manufacturing sectors, providing essential raw materials used in diverse applications. The industry’s contribution to employment and technological advance...
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Employee motivation is one of the most crucial factors that determine the success of an organization, particularly in labor-intensive industries like spinning mills. These mills are a fundamental part of the textile industry, where the efficiency of operations is heavily reliant on the performance and dedication of the workforce. In spinning mills,...
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Asset and Liability Management (ALM) is a vital financial practice that focuses on managing the risks related to mismatches between assets and liabilities within an organization. It is a strategic approach that ensures a company maintains adequate liquidity, manages interest rate risks, and achieves financial stability by balancing its resources an...
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Cash management is one of the most vital functions in financial management, focusing on the efficient collection, disbursement, and usage of cash resources. In capital-intensive industries, where significant investment is required for equipment, effective cash management becomes even more critical. Equipment forms the backbone of operat...
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A large part of economic growth is driven by housing investment. The availability of better data permits more precise estimates of house price in developed countries, while the same is true in developing countries too. Thereby, a real estate sector’s profits are directly related to the price of the houses and lands, so setting the right price is e...
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Current face biometric systems are vulnerable to spoofing attacks. A spoofing attack occurs when a person tries to masquerade as someone else by falsifying data and thereby gaining illegitimate access.
Inspired by image quality assessment, characterization of printing artefacts, and differences in light reflection, we propose to approach the prob...
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Epilepsy is a serious chronic neurological disorder, can be detected by analyzing the brain signals produced by brain neurons. Neurons are connected to each other in a complex way to communicate with human organs and generate signals.
The monitoring of these brain signals is commonly done using Electroencephalogram (EEG) and Electrocorticography ...
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Agriculture forms the backbone of Indian economy and there is always a need of supporting and improving it . As a part of which some of Indian NGO's are with an initiative of supporting the farmers by facilitating them with the modern agricultural equipment's on rental basis .Modern agricultural equipment's make farmers work more efficient and easy...
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Traffic Squad is an app which helps the police as well as the police by means of time and efficiency. With the increasing importance of corruption has become major factor to be considered as a result the number of vehicles and the rapid development of population are growing in our everyday life.
Existing system makes the use of pen and paper that...
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Customers are the essential factor in the organization. The business has to support the customers' preferences and demands for creating the customer loyalty, which make the customer still purchases with the particular company.
The customer may feel dissatisfied with the service when he or she receives the delay of services and they do not know th...
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The Road Transport Office established the RTO Information System as an online information source to make it easier for users to register for different permits and registrations.
The purpose of this technology is to improve information flow inside the company. RTO offers the ability to apply for licences online, as well as the ability to receive p...
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A pharmacy management software is any system used in a pharmacy that helps automate the pharmacy workflow. This includes such tasks as reviewing physician orders and preparing medications, controlling the inventory and making drug orders, handling billing and insurance, providing counseling, identifying incompatibilities, and more -- all while foll...
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The Block chain-Based Online Loan Management System (BOLMS) is an innovative web application that leverages block chain technology to revolutionize the process of loan management for financial institutions.
By utilizing the decentralized and transparent nature of block chain, BOLMS aims to enhance security, trust, and efficiency in the loan manag...
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Credit card fraud is currently the most common problem in the modern world. This is because internet transactions and e-commerce sites are on the rise. Credit card fraud occurs when a credit card is stolen and used for unauthorized reasons, or when a fraudster exploits the credit card information for his own interests.
In today's environment, we'...
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Online product review on shopping experience in social media has promoted user to provide feedback. Nowadays, many e-commerce sites allow the customer to write their review or opinion on the product which they have bought from that site.
The review given by the customer can build the good name of the product or make the product famous. Due to thi...
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A smart voting system using face recognition is a technique to overcome the traditional voting and EVM i.e Electronic Voting Machines. The system uses an Androidbased application to cast their votes from anywhere in the world.
The face recognition technology increase the accuracy and security of the voting process. The proposed system would work ...
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We have developed an application that will give the patient emergency medical attention because ,in India, deaths occur every second of the day. This project's primary goal is to close the time gap between the patient's request and the ambulance's arrival.
An essential component of emergency medical care is ambulances. Patients typically only hav...
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The hospital's management system includes improved profitability, improved administration, and better patient care. The goal of this study is to create a digital management system that will boost the hospital's effectiveness and systems integration standards.
It was able to produce a module that would provide some facilities, like booking doctors...
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In this paper, we demonstrate a practical system for automatic weather-oriented clothing suggestion, given the weather information, the system can automatically recommend the most suitable clothing from the user s personal clothing album, or intelligently suggest the most pairing one with the userspecified reference clothing.
This is an extremely...
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The Placement Management System is an advanced platform designed for the effective tracking and evaluation of student placements in various businesses [10].
ReactJS, a web-based tool, has been utilized to develop an advanced platform known as the Placement Management System [9]. The PMS enables the placement cell to securely store student data in...
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Investment in India is a business-based idea. I will be in my project giving investors with a platform and connecting people with strong business concepts.
This will change how much you can invest and where the money can be invested. Good investment returns. Good investment returns. Here are two forms - one for investors and one for business pers...
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One of the most important features of any online service is the quality of its customer care. However, with the development of NLP tools, businesses are considering automated chatbot solutions to keep up with the increasing demand for their products and services.
In view of this, the chatbot was developed using AIML java interpreter library Progr...
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Farming is the Prime Occupation in India in spite of this, today the people involved in farming belongs to the lower class and is in deep poverty.
The Advanced techniques and the Automated machines which are leading the world to new heights, is been lagging when it is concerned to farming, either the lack of awareness of the advanced facilities o...
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Today, forecasting the stock market has been one of the most challenging issues for the ‘‘artificial intelligence’’ AI research community. Stock market investment methods are sophisticated and rely on analyzing massive volumes of data. In recent years, machine-learning techniques have come under increasing scrutiny to assess and improve market pred...
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Most companies nowadays are using digital platforms for the recruitment of new employees to make the hiring process easier. The rapid increase in the use of online platforms for job posting has resulted in fraudulent advertising. The scammers are making money through fraudulent job postings.
Online recruitment fraud has emerged as an important is...
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This paper presents a Blockchain-based framework for providing Blockchain services for purposes of stability in terms of consensus protocol infrastructure and governance mechanisms and accessible auxiliary services suitable for the vast majority of current business needs, including fundamental factors such as digital identity with autonomous identi...
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Deep learning (DL), a branch of machine learning (ML), is the core technology in today’s technological advancements and innovations. Deep learning-based approaches are the state-of-the-art methods used to analyse and detect complex patterns in large datasets, such as credit card transactions.
However, most credit card fraud models in the literatu...
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Vehicular edge computing (VEC) has emerged as a solution that places computing resources at the edge of the network to address resource management, service continuity, and scalability issues in dynamic vehicular environments. However, VEC faces challenges such as task offloading, varying communication conditions, and data security.
To tackle thes...
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The COVID-19 pandemic has reshaped education and shifted learning from in-person to online. While this shift offers advantages such as liberating the learning process from time and space constraints and enabling education to occur anywhere and anytime, a challenge lies in detecting student engagement during online learning due to limited interactio...
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This research explores the potential of technologies in human activity recognition among the elderly population. More precisely, using sensor data and implementing Active Learning (AL), Machine Learning (ML), and Deep learning (DL) techniques for elderly activity recognition.
Moreover, the study leverages the HAR70+ dataset, providing insight int...
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Diabetic retinopathy (DR) produces bleeding, exudation, and new blood vessel formation conditions. DR can damage the retinal blood vessels and cause vision loss or even blindness.
If DR is detected early, ophthalmologists can use lasers to create tiny burns around the retinal tears to inhibit bleeding and prevent the formation of new blood vess...
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Background: In today's competitive job market, graduates are encountering enormous challenges while their transition from education to employment. Most of the existing platforms do not provide access to a wide array of job opportunities comprehensively.
This limitation spans both the private and government sectors, as well as international employ...
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Background: This problem requires an innovative approach to enhance the efficiency and transparency of faculty self-appraisal in the university settings. Through a robust web-based platform, the system should address the complexities associated with traditional evaluation processes. It should capture and manages intricate details of faculty activit...
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Background: A lack of adequate career counselling and guidance in schools contributes to poor career choices among students, leading to mismatched skills, job dissatisfaction, and unemployment. In India, many students and their families are unaware of the diverse career opportunities available, often leading to choices based on limited information ...
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Background: Children with Specific Learning Disability (SLD)who faces challenge of writing during their academic life especially during examinations where they need the provisions of a scribe. The purpose of rehabilitating people with disabilities is to reduce the dependence on other people.
In order to achieve this fundamental right to be indepe...
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Learn while you play is considered the most effecting way of teaching. Internet/mobile based games could be one of the best ways to lure school kids, youth and water enthusiasts to learn the nuances of ground water management.
With this backdrop it is proposed to develop an internet/mobile based game that teaches good practices in groundwater con...
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Background: Education and awareness are critical components of the National Anti-Doping Agency’s mission to promote clean sport. Despite ongoing efforts, the reach and impact of current educational initiatives remain limited, particularly in remote and rural areas. The rapid advancement of technology presents an opportunity to bridge these gaps and...
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Background: Student dropout rates in India are influenced by socio-economic and educational factors, affecting marginalized communities the most. Addressing dropout rates is essential for equitable education and socio-economic development. The National Education Policy (NEP) 2020 emphasizes the importance of reducing dropout rates and ensuring qual...
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Background: Alumni associations play a pivotal role in fostering lifelong connections between graduates and their alma mater, facilitating networking, mentorship, and philanthropic support. However, many alumni associations face challenges in maintaining engagement, facilitating donations, and providing valuable services such as job networking and ...
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Background: India has a tremendous opportunity to harness the potential of its youth by addressing the skills gap between education and industry requirements. While vocational education programs exist, they are often undervalued compared to traditional academic paths and need enhancement to provide students with the skills demanded by today’s job m...
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Background: “Inclusivity” is the motto of Education department, Government of Gujarat. Opportunity for all is the new slogan and The Indian Government has come up with Indian Sign Language. There has been lot of work in done in American sign language and focusing on interpretation in English.
Majority schools in India adopt local language. In Guj...
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Background: For a much simplified and initial solution, input (publication record) can also be provided in a consolidated single .bibtex file. However, it is desirable to provide input as an excel sheet, as mentioned earlier.
Description: The proposed solution should be able. Instructor shall have educational resources files in different formats ...
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Background: For a much simplified and initial solution, input (publication record) can also be provided in a consolidated single .bibtex file. However, it is desirable to provide input as an excel sheet, as mentioned earlier.
Description: The proposed solution should be able. Instructor shall have educational resources files in different formats ...
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Problem Overview Innovation is a key driver of growth and success in educational institutions. Tracking and measuring innovation excellence is essential for fostering a culture of continuous improvement, recognizing achievements, and guiding strategic decisions. However, identifying, quantifying, and presenting innovation indicators can be challeng...
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Description: 1. Background: For a much simplified and initial solution, input (publication record) can also be provided in a consolidated single bibtex file. However, it is desirable to provide input as an excel sheet, as mentioned earlier.
2. Description: The proposed solution should be able to crawl different popular academic databases, like Go...
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Project Concept: Comprehensive Employment Platform/Portal The current employment portal lacks a personalized and adaptive approach to job matching and skill development. There is a need for an intelligent system that not only matches job seekers with potential employers but also identifies and suggests training courses to bridge skill gaps.
We wi...
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Background: There are numerous engineering and polytechnic institutes in Rajasthan running under the Department of Technical Education, Government of Rajasthan. Notably, during the admission process, there is a significant increase in enquiries from various groups, including students, their parents, and other stakeholders.
These enquiries cover a...
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Description: The world today has bought on a need to pay increased attention to safety and security issues, for example, search and rescue operations, surveillance, and protection of critical infrastructure. These tasks are often labour intensive and potentially dangerous. This provides an incentive to create systems that aid operators to gain situ...
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Breast cancer is one of the leading causes of death in women. Early detection through breast ultrasound images is important and can be improved using machine learning models, which are more accurate and faster than manual methods.
Previous research has shown that the use of the logistic regression, svm and random forest algorithms in breast can...
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Background: The use of Earth Observation Satellite (EOS) technology for estimation of seasonal Actual Evapotranspiration (AET) of crops at various growth stages is well establishd. Due to low levels of water metering in irrigation, it is challenging to control theft from canals and unauthorized ground water extractions.
Therefore, ET based techno...
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Cyberbullying is when someone is bullied using technology as an intermediary. Despite the fact that it has been a problem for many years, the impact on young people has just recently become more widely recognized.
Bullies thrive on social media platforms, and teens and children who use them are vulnerable to attacks. A copious amount of usergener...
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To help consumers enjoy healthy food, technology investigation for food freshness sensing is conducted. In this study meat is selected as the detection target based on a consumer survey CO2, TVOC, and MQ135 are investigated.
The results showed that CO2 and TVOC could be a used for food freshness sensing in a closed space such as box. In today's w...
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Background: Disaster response agencies often stuggle to gather timely and specific information about emergencies from various sources. Social media platforms serve as a valuable repository of such data, but manually monitoring and sorting through the vast amount of information is inefficient and resource-intensive.
Description: There is a pressin...
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Background: Milk is perishable product, it requires immediate processing after few hours (2-4Hrs) of production, otherwise, bacterial load increases and milk gets deteriorate. At present Methytene Blue Dye Reduction Test, commonly known as MBRT test is used as a quick method to assess the microbiological quality of raw and pasteurized milk.
This ...
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Background: During CSSR (Collapsed Structure Search and Rescue) operations, NDRF teams encounter challenges in identifying buried deceased bodies amidst rubble and debris. Traditional search methods are often time-consuming and labor-intensive, hampering the timely recovery of victims and increasing the risk of further casualties. Description: THe ...
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Background: Glacial Lake Outburst Floods (GLOFs) occur when the dam containing a glacial lake fails, releasing large volumes of water suddenly and causing catastrophic downstream flooding. Climate change is increasing the number and size of glacial lakes, heightening the risk of GLOFs. Curent monitoring and prediction methods can be improved with a...
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Background: Angiography is a common medical imaging technique used to visualize the inside of blood vessels and detect blockages. Description: However, typically medical tests like radionuclide angiography involve the use of radioactive contrast agents, which can pose risks to patients, including radiation exposure and allergic reactions.
There i...
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Background: Yoga has gained global recognition for its numerous health benefits, including physical fitness, mental well-being, and stress reduction. As part of India's ancient heritage, yoga is a key component of the AYUSH (Ayurveda, Yoga & Naturopathy, Unani, Siddha, and Homoeopathy) systems of medicine, promoting holistic health practices.
In ...
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In this paper, we demonstrate a practical system for automat ic weather-oriented clothing suggestion, given the weather information, the system can automatically recommend the most suitable clothing from the user s personal clothing album,or intelligently suggest the most pairing one with the user specified reference clothing.
This is an extrem...
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Background: Himachal Pradesh, a northern state in India, is renowned for its apple production, contributing significantly to the local economy and livelihoods. With an annual apple production of approximately 600,000 metric tons, the region's apple orchards face challenges related to tree health monitoring, nutrient management, pest and disease con...
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The Department of Consumer Affairs monitors the daily prices of 22 essential food commodities through 550 price reporting centres across the country. The Department also maintains buffer stock of pulses, viz., gram, tur, urad, moon and masur, and onion for strategic market interventions to stabilize the volatility in prices.
Decisions for market ...
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Background: Crop diseases can devastate yields, leading to significant financial losses for farmers. Early detection and timely intervention are crucial for effective management. Description: Develop an AI-driven system that analyzes crop images and environmental data to predict potential disease outbreaks.
This system will provide farmers with a...
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Nowadays, home loan is a frequently accessed component of people’s financing activities. Homeowners wants to increase the probability of loan acceptance, however banks seek to borrow money to low risk customers.
This paper compared and examined the machine learning models to select when loan applicants evaluating their probability of success. Thi...
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Background: Critical Sector organisations uses a number of IT and OT equipment (e.g. Networking and hardware device, Operating Systems, Applications, Firmware etc.). These devices/application come with vulnerabilities from time to time.
There should be timely information sharing mechanism by which the concerned equipment users at critical sector ...
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Background: Use of encrypted messaging/social media apps like Telegram, WhatsApp and Instagram for drug trafficking are on the rise. Channels operating on Telegram and WhatsApp and Instagram handles are blatantly being misused by drug traffickers for offering various narcotic drugs and Psychotropic substances for sale. Description: WhatsApp and Tel...
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Background: There are large number of cryptographic algorithms available for ensuring data confidentiality and integrity in secure communication. Identification of the algorithm is a research activity that leads to better understanding of the weakness in its implementation, in order to make the algorithm more robust and secure.
Description: The a...
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Background: NCIIPC shares detail of cyber incidents to corresponding stakeholders in order to inform them about cyber activities related to their IT/OT infrastructure.
This empowers them to take necessary actions to mitigate further risk. Description: In order to achieve objective of protecting Critical Information Infrastructure (CIIs) of the Na...
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Background: Many organization are using Cloud for hosting their web applications. The attackers can try to attack these webservers for achieving Denial of Service attack. Specifically, Distributed Denial-of-Service (DDoS) attack is a malicious attempt to disrupt the normal traffic of a targeted server, service or network of Cloud infrastructure by ...
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Background: In today’s digital age, a wide variety of services and processes take place online. Users of these digital facilities are required to upload government-issued containing documents or provide data for successfully availing the services. However, the uploaded documents or data which are required to facilitate these digital services and pr...
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Sentiment analysis is defined as the process of mining of data, view, review or sentence to predict the emotion of the sentence through natural language processing (NLP). The sentiment analysis involve classification of text into three phase “Positive”, “Negative” or “Neutral”.
It analyzes the data and labels the ‘better’ and ‘worse’ sentiment as...
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The recent technological advancement in digital computers has provided a more robust computer based operations in modern industrial society, including manufacturing, transport and distribution, government, the military, health services, education and research.
This impact of modern digital computers as an irreplaceable tool for technological grow...
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Nowadays, detecting credit card fraud is a major social issue. Credit card usage on e-commerce and banking websites has quickly expanded in recent years. The usage of credit cards in online transactions has made it simple, but it has also increased the frequency of fraud transactions.
Modernization will have both beneficial and negative effects. ...
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Credit card fraud detection is a relevant problem that draws attention of machine learning. In the fraud detection task, there are some peculiarities present, such as the unavoidable condition of a strong class imbalance, the existence of unlabelled transaction, and the large number of records that must be processed.
The present paper aims to pro...
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Our society suffers a lot from the things that are thrown uselessly; these things may be beneficial to our society. On the other hand, communities suffer a lot of waste especially plastic waste; this has led to environmental pollution and depletion of natural resources.
Therefore, this research aims to achieve sustainable development and achieve ...
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Stock marketplace is a complicated and demanding system in which people make more money or lose their entire savings. The stock market prediction having high accuracy yields more profit for stock investors.
Stock market data is generated in a very large amount and it varies quickly every second. The decision making in stock marketplace is a very ...
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Variable frequency drive uses power electronics vary the frequency of input power to motor, thereby controlling motor speed.
AC motor drives are widely used to control the speed of ACs,pumps, blower speeds, machine tool speeds, conveyor systems speeds and others applications that require variable speed with variable torque.
This paper proposes ...
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The project work aims at designing a student attendance system which could effectively manage attendance of students of the department of Computer Science and Engineering at Jatiya Kabi Kazi Nazrul Islam University. In this project work, attendance is marked after student’s biometric identification.
For student identification, a fingerprint recog...
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As artificial intelligence (AI) develops quickly, Python has become the de facto fully object-oriented programming language. Python'ssimplicity, language variety, and vast library ecosystem make it a valuable tool for image processing .
This research study examines Python's role in image processing in detail, outlining its benefits, drawbacks, a...
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Day by day the cases of heart diseases are increasing at a rapid rate and it’s very Important and concerning to predict any such diseases beforehand. This diagnosis is a difficult task i.e. it should be performed precisely and efficiently.
The research paper mainly focuses on which patient is more likely to have a heart disease based on various m...
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Nowadays, detecting credit card fraud is a major social issue. Credit card usage on e-commerce and banking websites has quickly expanded in recent years. The usage of credit cards in online transactions has made it simple, but it has also increased the frequency of fraud transactions.
Modernization will have both beneficial and negative effects. ...
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Accurately classifying brain tumor types is critical for timely diagnosis and potentially saving lives. Magnetic Resonance Imaging (MRI) is a widely used non-invasive method for obtaining high-contrast grayscale brain images, primarily for tumor diagnosis.
The application of Convolutional Neural Networks (CNNs) in deep learning has revolutioniz...
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The purpose of this project is to detect the fraudulent transactions made by credit cards by the use of machine learning techniques, to stop fraudsters from the unauthorized usage of customers’ accounts.
The increase of credit card fraud is growing rapidly worldwide, which is the reason actions should be taken to stop fraudsters.
Putting a ...
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Online transactions have become a significant and crucial aspect of our lives in recent years. It's critical for credit card firms to be able to spot fraudulent credit card transactions so that customers aren't charged for things they didn't buy.
The number of fraudulent transactions is rapidly increasing as the frequency of transactions increa...
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: In this paper, we are implementing a credit card fraud detection system, by using big data technologies. Credit card is one of the most divisive products among all the financial tools available.
The usage of credit cards has become common in today’s world and huge volume of transaction happens online. The increase in these transactions has al...
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Frauds in credit card transactions are common today as most of us are using the credit card payment methods more frequently. This is due to the advancement of Technology and increase in online transaction resulting in frauds causing huge financial loss.
Therefore, there is need for effective methods to reduce the loss. In addition, fraudsters f...
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Health is very important for human life. In particular, the health of the brain, which is the executive of the vital resource, is very important. Diagnosis for human health is provided by magnetic resonance imaging (MRI) devices, which help health decision makers in critical organs such as brain health.
Images from these devices are a source of...
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Most of the smart phone users prefer to read the news via social media over internet. The news websites are publishing the news and provide the source of authentication.
The question is how to authenticate the news and articles which are circulated among social media like WhatsApp groups, Facebook Pages, Twitter and other micro blogs & social n...
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OCR is used to identify the character from human written text. To recognize the text segmentation of character is important stage. So here, we addressed different techniques to recognize the character.
This document also presents comparison of different languages for character and numeral recognition with its accuracy achieved by different writer...
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The main purpose of this project is to build a face recognition-based attendance monitoring system for educational institution to enhance and upgrade the current attendance system into more efficient and effective as compared to before.
The current old system has a lot of ambiguity that caused inaccurate and inefficient of attendance taking. Ma...
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Internet banking is now becoming the most commonly used form of banking transactions. Confidentiality can be compromised in the process of electronic purchases.
We therefore introduced a new approach to prevent theft during online transactions in order to protect information through a two-step mechanism of authentication.
The primary step o...
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As we are approaching modernity, the trend of paying online is increasing tremendously. It is very beneficial for the buyer to pay online as it saves time, and solves the problem of free money.
Also, we do not need to carry cash with us. But we all know that Good thing are accompanied by bad things.
The online payment method leads to frau...
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Brain tumor detection is a critical application in the field of medical imaging, aimed at aiding healthcare professionals in the early and accurate diagnosis of brain tumors. This project leverages machine learning and deep learning techniques in Python to developa robust and reliable brain tumor detection system.
The system undergoes sensitivi...
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In recent years, due to the booming development of online social networks, fake news for various commercial and political purposes has been appearing in large numbers and widespread in the online world.
With deceptive words, online social network users can get infected by these online fake news easily, which has brought about tremendous effects...
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Building a quantum analog of classical deep neural networks represents a fundamental challenge in quantum computing.
A key issue is how to address the inherent non-linearity of classical deep learning, a problem in the quantum domain due to the fact that the composition of an arbitrary number of quantum gates, consisting of a series of sequenti...
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The deployment of automated deep-learning classifiers in clinical practice has the potential to streamline the diagnosis process and improve the diagnosis accuracy, but the acceptance of those classifiers relies on both their accuracy and interpretability.
In general, accurate deep-learning classifiers provide little model interpretability, whi...
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predicting stock market is one of the challenging tasks in the field of computation. Physical vs. physiological elements, rational vs. illogical conduct, investor emotions, market rumors, and other factors all play a role in the prediction.
All of these factors combine to make stock values very fluctuating and difficult to forecast accurately. ...
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Decades of research have shown machine learning superiority in discovering highly nonlinear patterns embedded in electroencephalography (EEG) records compared with conventional statistical techniques.
However, even the most advanced machine learning techniques require relatively large, labeled EEG repositories.
EEG data collection and lab...
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This is a panel paper which discusses the use of Artificial Intelligence (AI) techniques to address production level problems in semiconductor manufacturing.
We have gathered a group of expert semiconductor researchers and practitioners from around the world who have applied AI techniques to semiconductor problems and the paper provides their a...
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Cerebrovascular diseases such as stroke are among the most common causes of death and disability worldwide and are preventable and treatable.
Early detection of strokes and their rapid intervention play an important role in reducing the burden of disease and improving clinical outcomes.
In recent years, machine learning methods have attracte...
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To meet the requirements of high accuracy and low cost of target classification in modern warfare, and lay the foundation for target threat assessment, the article proposes a human-machine agent for target classification based on active reinforcement learning (TCARL_H-M), inferring when to introduce human experience guidance for model and how to au...
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In India, there are continuously more criminal cases filed, which results in an increase in the number of cases still outstanding. These ongoing increases in criminal cases make them challenging to categorise and resolve.
Therefore, it's crucial to identify a location's patterns of criminal activity in order to stop it from happening in order to ...
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In the age of cloud computing, cloud users with limited storage can outsource their data to remote servers. These servers, in lieu of monetary benefits, offer retrievability of their clients’ data at any point of time.
Secure cloud storage protocols enable a client to check integrity of outsourced data. In this article, we explore the possibili...
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Machine learning (ML) can make use of agricultural data related to crop yield under varying Crop based nutrient levels, and climatic fluctuations to suggest appropriate crops or supplementary nutrients to achieve the highest possible production.
The aim of this study was to evaluate the efficacy of five distinct ML models for a dataset sourced ...
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In our day to day life we consume food and our survival is based on mainly food. A considerable amount of our food is coming from farms and other means too. These farmers do their hard work for growing and serving many lives across the country, which pays for their source of income. But due to intermediates in the selling of their final product...
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Social networks have become a powerful information spreading platform. How to limit rumor spread on social networks is a challenging problem.
In this article, we combine information spreading mechanisms to simulate real-world social network user behavior. Based on this, we estimate the risk degree of each node during the hazard period and analy...
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The present study aims to elucidate the main variables that increase the level of depression at the beginning of military conscription service using an artificial neural network (ANN)-based prediction model.
Random sample data were obtained from one battalion of the Lithuanian Armed Forces, and a survey was conducted to generate data for the tr...
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Hazards from landslides are everywhere. Landslides are more likely to occur on steeply sloped hillsides. For several case studies throughout the globe, researchers have performed landslide prediction, detection, and monitoring.
The major goal of researching landslide detection is to stop natural disasters by seeing their early movement. This wi...
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Fingerprint authentication is one of the most popular and accurate technology. Our project is a fingerprint attendance system that records the attendance of students based on their fingerprint matches them against the database to mark their attendance.
Fingerprint-based attendance system used for ensures that there is a minimal fault in gatheri...
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Epilepsy is a chronic neurological disorder with several different types of seizures, some of them characterized by involuntary recurrent convulsions, which have a great impact on the everyday life of the patients. Several solutions have been proposed in the literature to detect this type of seizures and to monitor the patient; however, these a...
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Nowadays, digital images are a main source of shared information in social media. Meanwhile, malicious software can forge such images for fake information. So, it’s crucial to identify these forgeries.
This problem was tackled in the literature by various digital image forgery detection techniques. But most of these techniques are tied to detec...
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Internet-of-Things (IoT) devices have a strict necessity for power consumption to achieve the expected battery life. Therefore, measuring and optimizing the energy consumption of IoT nodes are essential.
IoT nodes feature extreme current consumption range over 100 dB between their operating modes. The main focus of this article is to design and...
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Brain Computer Interface (BCI) sometimes called Brain-Machine Interface (BMI). It is a direct communication pathway between the Brain’s Electrical Activity and external device. Computer based system that acquires brainsignals, analyzes the man dtranslatesthemintocommandsthatarerelayed to an output device to carry out into desired action.
We can...
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Breast cancer is a deadly disease; an accurate and early diagnosis of breast cancer is the most efficient method to decrease the death rate.
But, in the early detection and diagnosis of breast cancer, differentiating abnormal tissues is a challenging task. In this paper, a weight-based AdaBoost algorithm is proposed for an effective detection a...
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The collapse of Dam I, owned by Vale S.A, in Brumadinho-MG (Brazil), among other serious socioenvironmental consequences, contaminated the waters of the Paraopeba River in a stretch of hundreds of kilometers. Considering the relevance of monitoring water quality, and knowing that field evaluation is a time-consuming and costly procedure, the use of...
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The collapse of Dam I, owned by Vale S.A, in Brumadinho-MG (Brazil), among other serious socioenvironmental consequences, contaminated the waters of the Paraopeba River in a stretch of hundreds of kilometers. Considering the relevance of monitoring water quality, and knowing that field evaluation is a time-consuming and costly procedure, the use of...
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The major obstacle for learning-based RF sensing is to obtain a high-quality large-scale annotated dataset. However, unlike visual datasets that can be easily annotated by human workers, RF signal is non-intuitive and non-interpretable, which causes the annotation of RF signals time-consuming and laborious. To resolve the rapacious appetite of anno...
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Permanent Magnet Synchronous Motor (PMSM) is widely used due to its advantages of high power density, high efficiency and so on. In order to ensure the reliability of a PMSM system, it is extremely vital to accurately diagnose the incipient faults. In this paper, a variety of optimization algorithms are utilized to realize the diagnosis of the faul...
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Over the years, there has been a global increase in the use of technology to deliver interventions for health and wellness, such as improving people’s mental health and resilience. An example of such technology is the Q-Life app which aims to improve people’s resilience to stress and adverse life events through various coping mechanisms, including ...
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Sell-side analysts’ recommendations are primarily targeted at institutional investors mandated to invest across many companies within client-mandated equity benchmarks, such as the FTSE/JSE All-Share index. Given the numerous sell-side recommendations for a single stock, making unbiased investment decisions is not often straightforward for portfoli...
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Machine learning is widely deployed in society, unleashing its power in a wide rangeof applications owing to the advent of big data.One emerging problem faced by machine learning is the discrimination from data, and such discrimination is reflected in the eventual decisions made by the algorithms. Recent study has proved that increasing the size of...
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Most State-Of-The-Art (SOTA) Neural Machine Translation (NMT) systems today achieve outstanding results based only on large parallel corpora. The large-scale parallel corpora for high-resource languages is easily obtainable. However, the translation quality of NMT for morphologically rich languages is still unsatisfactory, mainly because of the dat...
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Acute myelogenous leukemia (AML) is a subtype of acute leukemia, which is prevalent among adults.The average age of a person with AML is 65 years. The need for automation of leukemia detection arises since current methods involve manual examination of the blood smear as the first step toward diagnosis. This is time-consuming, and its accuracy depen...
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Automated Credit Scoring (ACS) is the process of predicting user credit based on historical data. It involves analyzing and predicting the association between the data and particular credit values based on similar data. Recently, ACS has been handled as a machine learning problem, and numerous models were developed to address it. In this paper, we ...
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The availability of digital technology in the hands of every citizenry worldwide makes an availableunprecedented massive amount of data. The capability to process these gigantic amounts of data in real-time with Big Data Analytics (BDA) tools and Machine Learning (ML) algorithms carries many paybacks. However, the highnumber of free BDA tools, plat...
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Stereo matching is one of the longest-standing problems in computer vision with close to 40 years of studies and research. Throughout the years the paradigm has shifted from local, pixel-level decision to various forms of discrete and continuous optimization to data-driven, learning-based methods.Recently, the rise of machine learning and the rapid...
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Even though machine learning (ML) applications are not novel, they have gained popularity partly due to the advance in computing processing.This study explores the adoption of ML methods in marketing applications through a bibliographic review of the period 2008–2022. In this period, the adoption of ML in marketing has grown significantly. This gro...
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We present the Interactive Classification System (ICS), a web-based application that supports the activity of manual text classification.The application uses machine learning to continuously fit automatic classification models that are in turn used to actively support its users with classification suggestions. The key requirement we have establishe...
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Traditionally, X-ray crystallography and NMR spectroscopy represent major workhorses of structural biologists, with the lion share of protein structures reported in protein data bank (PDB) being generated by these powerful techniques.Despite their wide utilization in protein structure determination, these two techniques have logical limitations, wi...
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Information security means protecting data, such as a database, from destructive forces and from the unwanted actions of unauthorized users. Information Security can be achieved by using cryptographic techniques. It is now very much demanding to develop a system to ensure better long lasting security services for message transaction over the Intern...
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In recent months, coronavirus disease 2019
(COVID-19) has infected millions of people worldwide. In
addition to the clinical tests like reverse transcription-
polymerase chain reaction (RT-PCR), medical imaging
techniques such as computed tomography (CT) can be used as a
rapid technique to detect and evaluate patients infected by
COVID...
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Emojis are used in Computer Mediated Communication (CMC) as a way to express paralinguistics otherwise missing from text, such as facial expressions or gestures. However, finding an emoji on the ever expanding emoji list is a linear search problem and most users end up using a small subset of emojis that are near the top of the emoji list. Current ...
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In multi-task learning, multiple tasks are solved jointly, sharing inductive bias between them. Multi-task learning is inherently a multi-objective problem because different tasks may conflict, necessitating a trade-off. A common compromise is to optimize a proxy objective that minimizes a weighted linear combination of pertask losses. However, thi...
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Machine learning has been increasingly applied in identification of fraudulent transactions. However, most application systems detect duplicitous activities after they have already occurred, not at or near real time. Since spurious transactions are far fewer than the normal ones, the highly imbalanced data makes fraud detection very challenging and...
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Feature selection is the task of choosing a small subset of features that is sufficient to predict the target labels well. Here, instead of trying to directly determine which features are better, we attempt to learn the properties of good features. For this purpose we assume that each feature is represented by a set of properties, referred to as me...
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This study aimed to develop accurate and explainable machine learning models for three psychomotor behaviors of delirium for hospitalized adult patients.A prospective pilot study was conducted with 33 participants admitted to a long-term care facility between August 10 and 25, 2020. During the pilot study, we collected 560 cases that included 33 cl...
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The rise of machine learning has unlocked new ways of analysing structural neuroimaging data, including brain age prediction. In this state-of-the-art review, we provide an introduction to the methods and potential clinical applications of brain age prediction. Studies on brain age typically involve the creation of a regression machine learning mod...
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Quantum computing is envisaged as an evolving paradigm for solving computationally complex optimization problems with a large-number factorization and exhaustive search.Recently, there has been a proliferating growth of the size of multi-dimensional datasets, the input-output space dimensionality, and data structures. Hence, the conventional machin...
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In the medical field, it is essential to predict diseases early to prevent them. Diabetes is one of the most dangerous diseases all over the world. In modern lifestyles, sugar and fat are typically present in our dietary habits, which have increased the risk of diabetes To predict the disease, it is extremely important to understand its symptoms. C...
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Meta-learning has been proposed as a framework to address the challenging few-shot learning setting. The key idea is to leverage a large number of similar few-shot tasks in order to learn how to adapt a base-learner to a new task for which only a few labeled samples are available. As deep neural networks (DNNs) tend to overfit using a few samples o...
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Machine learning (ML) algorithms are nowadays widely adopted in different contexts to perform autonomous decisions and predictions. Due to the high volume of data shared in the recent years, ML algorithms are more accurate and reliable since training and testing phases are more precise. An important concept to analyze when defining ML algorithms co...
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The usage of credit cards for online and regular purchases is exponentially increasing and so is the fraud related with it. A large number of fraud transactions are made every day. Various modern techniques like artificial neural network Different machine learning algorithms are compared, including Logistic Regression, Decision Trees, Random Forest...
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Machine learning and its subfield deep learning techniques provide opportunities for the development of operator mental state monitoring, especially for cognitive workload recognition using electroencephalogram (EEG) signals. Although a variety of machine learning methods have been proposed for recognizing cognitive workload via EEG recently, there...
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This paper presents a comparison of conventional and modern machine (deep) learning within the framework of anomaly detection in self-organizing networks. While deep learning has gained significant traction, especially in application scenarios where large volumes of data can be collected and processed, conventional methods may yet offer strong stat...
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Due to the advancement in the field of Artificial Intelligence (AI), the ability to tackle entire problems of machine intelligence. Nowadays, Machine learning (ML) is becoming a hot topic due to the direct training of machines with less interaction with a human.The scenario of manual feeding of the machine is changed in the modern era, it will lear...
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Thermal errors have the largest contribution, as much as about 70%, to the machining inaccuracy of computer-numerical-controlled (CNC) machining centers. The error compensation method so far plays the most popular and effective way to minimize the thermal error. How to accurately and quickly build an applicable thermal error model (TEM) is the kern...
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The availability of digital technology in the hands of every citizenry worldwide makes an availableunprecedented massive amount of data. The capability to process these gigantic amounts of data in real-time with Big Data Analytics (BDA) tools and Machine Learning (ML) algorithms carries many paybacks. However, the highnumber of free BDA tools, plat...
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The aim of our project is to design and fabricate a pneumatically operated tapping machine is called universal tapping machine. This device is operated by compressed air. It consists of the following main parts.
1. Barrel
2. Shaft
3. bearing
4. Couplings, etc.
A high pressure compressed air is forced on a fan and the fan is made...
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The aim of our project is to design and fabricate a pneumatically operated tapping machine is called universal tapping machine. This device is operated by compressed air. It consists of the following main parts.
1. Barrel
2. Shaft
3. bearing
4. Couplings, etc.
A high pressure compressed air is forced on a fan and the f...
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Knee osteoarthritis (KOA) as a disabling joint disease has doubled in prevalence since the mid-20th century. Early diagnosis for the longitudinal KOA grades has been increasingly important for effective monitoring and intervention. Although recent studies have achieved promising performance for baseline KOA grading, longitudinal KOA grading has bee...
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? In the last decade, researchers, practitioners and companies struggled for devising mechanisms to detect cyber-security threats. Among others, those efforts originated rule-based, signature-based or supervised Machine Learning (ML) algorithms that were proven effective for detecting those intrusions that have already been encountered and characte...
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The most vital information about the electrical activities of the brain can be obtained with the help of Electroencephalography (EEG) signals. It is quite a powerful tool to analyze the neural activities of the brain and various neurological disorders like epilepsy, schizophrenia, sleep related disorders, parkinson disease etc. can be investigated ...
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The most vital information about the electrical activities of the brain can be obtained with the help of Electroencephalography (EEG) signals. It is quite a powerful tool to analyze the neural activities of the brain and various neurological disorders like epilepsy, schizophrenia, sleep related disorders, parkinson disease etc. can be investigated ...
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Photonic crystal fibers (PCFs) are the specialized optical waveguides that led to many interesting applications ranging from nonlinear optical signal processing to high-power fiber amplifiers. In this paper, machine learning techniques are used to compute various optical properties including effective index, effective mode area, dispersion and conf...
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By redefining the conventional notions of layers, we present an alternative view on finitely wide, fully trainable deep neural networks as stacked linear models in feature spaces, leading to a kernel machine interpretation. Based on this construction, we then propose a provably optimal modular learning framework for classification that does not req...
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The detection and prevention of a network intrusion is a major concern. Machine Learning and Deep Learning methods detect network intrusions by predicting the risk with the help of training the data. Various machine learning and deep learning methods have been proposed over the years which are shown to be more accurate when compared to other networ...
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Breast Cancer comprises multiple subtypes implicated in prognosis. Existing stratification methods rely on the expression quantification of small gene sets. Next Generation Sequencing promises large amounts of omic data in the next years. In this scenario, we explore the potential of machine learning and, particularly, deep learning for breast canc...
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Monitoringthe depth of unconsciousnessduring anesthesia is beneficial in both clinical settings and neuroscience investigations to understand brain mechanisms. Electroencephalogram(EEG) has been used as an objective means of characterizing brain altered arousal and/or cognition states induced by anesthetics in real-time. Different general anestheti...
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The interpretation of deep neural networks (DNNs) has become a key topic as more and more people apply them to solve various problems and making critical decisions. Concept-based explanations have recently become a popular approach for post-hoc interpretation of DNNs. However, identifying human-understandable visual concepts that affect model decis...
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Cerebellar ataxia (CA) is concerned with the incoordination of movement caused by cerebellar dysfunction. Movements of the eyes, speech, trunk, and limbs are affected. Conventional machine learning approaches utilizing centralised databases have been used to objectively diagnose and quantify the severity of CA . Although these approaches achieved ...
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Deep learning is recognized to be capable of discovering deep features for representation learning and pattern recognition without requiring elegant feature engineering techniques by taking advantage of human ingenuity and prior knowledge. Thus it has triggered enormous research activities in machine learning and pattern recognition. One of the mos...
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As a high-tech strategic emerging comprehensive industry, the nuclear industry is committed to the research, production, and processing of nuclear fuel, as well as the development and utilization of nuclear energy. Nowadays, the nuclear industry has made remarkable progress in the application fields of nuclear weapons, nuclear power, nuclear medica...
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? In the last decade, researchers, practitioners and companies struggled for devising mechanisms to detect cyber-security threats. Among others, those efforts originated rule-based, signature-based or supervised Machine Learning (ML) algorithms that were proven effective for detecting those intrusions that have already been encountered and characte...
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COVID-19 is a life threatening disease which has a enormous global impact. As the cause of the disease is a novel coronavirus whose gene information is unknown, drugs and vaccines are yet to be found. For the present situation, disease spread analysis and prediction with the help of mathematical and data driven model will be of great help to initia...
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The interpretation of deep neural networks (DNNs) has become a key topic as more and more people apply them to solve various problems and making critical decisions. Concept-based explanations have recently become a popular approach for post-hoc interpretation of DNNs. However, identifying human-understandable visual concepts that affect model decis...
|
The detection and prevention of a network intrusion is a major concern. Machine Learning and Deep Learning methods detect network intrusions by predicting the risk with the help of training the data. Various machine learning and deep learning methods have been proposed over the years which are shown to be more accurate when compared to other networ...
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Automatic Leukemia or blood cancer detection is a challenging job and is very much required in healthcare centers. It has a significant role in early diagnosis and treatment planning. Leukemia is a hematological disorder that starts from the bone marrow and affects white blood cells (WBCs). Microscopic analysis of WBCs is a preferred approach for a...
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Automatic Leukemia or blood cancer detection is a challenging job and is very much required in healthcare centers. It has a significant role in early diagnosis and treatment planning. Leukemia is a hematological disorder that starts from the bone marrow and affects white blood cells (WBCs). Microscopic analysis of WBCs is a preferred approach for a...
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The recent advancement in internet 2.0 creates a scope to connect people worldwide using society 2.0 and web 2.0 technologies. This new era allows the consumer to directly connect with other individuals, business corporations, and the governmentPeople are open to sharing opinions, views, and ideas on any topic in different formats out loud. This cr...
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The recent advancement in internet 2.0 creates a scope to connect people worldwide using society 2.0 and web 2.0 technologies. This new era allows the consumer to directly connect with other individuals, business corporations, and the governmentPeople are open to sharing opinions, views, and ideas on any topic in different formats out loud. This cr...
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The recent advancement in internet 2.0 creates a scope to connect people worldwide using society 2.0 and web 2.0 technologies. This new era allows the consumer to directly connect with other individuals, business corporations, and the governmentPeople are open to sharing opinions, views, and ideas on any topic in different formats out loud. This cr...
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A novel reconfigurable intelligent surfaces (RISs)- based transmission framework is proposed for downlink nonorthogonal multiple access (NOMA) networks. We propose a quality-of-service (QoS)-based clustering scheme to improve the resource efficiency and formulate a sum rate maximization problem by jointly optimizing the phase shift of the RIS and t...
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As a high-tech strategic emerging comprehensive industry, the nuclear industry is committed to the research, production, and processing of nuclear fuel, as well as the development and utilization of nuclear energy. Nowadays, the nuclear industry has made remarkable progress in the application fields of nuclear weapons, nuclear power, nuclear medica...
|
Monitoringthe depth of unconsciousnessduring anesthesia is beneficial in both clinical settings and neuroscience investigations to understand brain mechanisms. Electroencephalogram(EEG) has been used as an objective means of characterizing brain altered arousal and/or cognition states induced by anesthetics in real-time. Different general anestheti...
|
By redefining the conventional notions of layers, we present an alternative view on finitely wide, fully trainable deep neural networks as stacked linear models in feature spaces, leading to a kernel machine interpretation. Based on this construction, we then propose a provably optimal modular learning framework for classification that does not req...
|
Photonic crystal fibers (PCFs) are the specialized optical waveguides that led to many interesting applications ranging from nonlinear optical signal processing to high-power fiber amplifiers. In this paper, machine learning techniques are used to compute various optical properties including effective index, effective mode area, dispersion and conf...
|
The most vital information about the electrical activities of the brain can be obtained with the help of Electroencephalography (EEG) signals. It is quite a powerful tool to analyze the neural activities of the brain and various neurological disorders like epilepsy, schizophrenia, sleep related disorders, parkinson disease etc. can be investigated ...
|
The recent incorporation of new Data Mining and Machine Learning services within Cloud Computing providers is empowering users with extremely comprehensive data analysis tools including all the advantages of this type of environment. Providers of Cloud Computing services for Data Mining publish the descriptions and definitions in many formats and o...
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Deep neural Network (DNN) is becoming a focal point in Machine Learning research. Its application is penetrating into different fields and solving intricate and complex problems. DNN is now been applied in health image processing to detect various ailment such as cancer and diabetes. Another disease that is causing threat to our health is the kidne...
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The present study aims to elucidate the main variables that increase the level of stress at the beginning of military conscription service using an artificial neural network (ANN)-based prediction model. Random sample data were obtained from one battalion of the Lithuanian Armed Forces, and a survey was conducted to generate data for the training a...
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Building Energy Management System (BEMS) has been a substantial topic nowadays due to its importance in reducing energy wastage. However, the performance of one of BEMS applications which is energy consumption prediction has been stagnant due to problems such as low prediction accuracy. Thus, this research aims to address the problems by developing...
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Drowsiness of drivers is one of the significant cause of road accidents. Every year, there is an increase in the amount of deaths and fatal injuries globally. By detecting the driver’s drowsiness, road accidents can be reduced. This paper describes a machine learning approach for drowsiness detection. Face detection is employed to locate the region...
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Deep learning (DL) has proved successful in medical imaging and, in the wake of the recent COVID-19 pandemic, some works have started to investigate DL-based solutions for the assisted diagnosis of lung diseases. While existing works focus on CT scans, this paper studies the application of DL techniques for the analysis of lung ultra sonography (LU...
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Twitter is among the most used microblogging and online social networking services. In Twitter, a name, phrase, or topic that is mentioned at a greater rate than others is called a "trending topic" or simply “trend”. Twitter trends has shown their powerful ability in many public events, elections and market changes. Nevertheless, there has been ver...
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Image processing has been a crucial tool for refining the image or to boost the image. With the improvement of machine learning tools, the image processing task has been simplified to great range. Generating a semantic and photographic face image, from a sketch image or text description has always been an extremely important issue. Sketch images ba...
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Since stroke disease often causes death or serious disability, active primary prevention and early detection of prognostic symptoms are very important. Stroke diseases can be divided into ischemic stroke and hemorrhagic stroke, and they should be minimized by emergency treatment such as thrombolytic or coagulant administration by type. First, it is...
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This Waste management is one of the serious challenges of the cities, the system now used in cities, we continue to use an old and outmoded paradigm that no longer serves the entail of municipalities, Still find over spilled waste containers giving off irritating smells causing serious health issues and atmosphere impairment. The Smart Waste Manage...
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Ports form a vital link in the global maritime supply chain, and adherence to the UN sustainable goals in each port development and operation is all-important. Improving the sustainability performance of port infrastructure requires identifying all relevant aspects of sustainability, defining suitable performance measures, applying tools for quanti...
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There is something that we still don’t see: food wasted by restaurants, shops or industries. There is also something we can see: food wasted by ourselves. This is the range focus of communities, through the management of wasted products of catering firms. Now a days people are aware of importance of food but there are no platform to share informati...
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Road lane detection systems play a crucial role in the context of Advanced Driver Assistance Systems (ADASs) and autonomous driving. Such systems can lessen road accidents and increase driving safety by alerting the driver in risky traffic situations. Additionally, the detection of ego lanes with their left and right boundaries along with the recog...
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This paper describes the development of a multilingual, manually annotated dataset for three under-resourced Dravidian languages generated from social media comments. The dataset was annotated for sentiment analysis and offensive language identification for a total of more than 60,000 YouTube comments. The dataset consists of around 44,000 comments...
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Polycystic Ovary Syndrome (PCOS) is a medical condition which causes hormonal disorder in women in their childbearing years. The hormonal imbalance leads to a delayed or even absent menstrual cycle. Women with PCOS majorly suffer from excessive weight gain, facial hair growth, acne, hair loss, skin darkening and irregular periods leading to inferti...
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In today's technical era, every startup or a company attempt to establish a better sort of communication between their Plants and the users, and for that purpose, they require a type of mechanism which can promote their plant effectively, and here the recommender system serves this motive. It is basically a filtering system that tries to predict an...
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Knee osteoarthritis (KOA) is a leading cause of disability among elderly adults, and it causes pain and discomfort and limits the functional independence of such adults. The aim of this study was the development of an automated classification model for KOA, based on the Kellgren–Lawrence (KL) grading system, using radiographic imaging and gait anal...
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Medical Surveillance Solutions are the most important in the brief developing country populace enhances demands for caretaking. Covid-19 is as a substitute contagious it is very important to quarantine covid-19 humans but at the equal time medical examiners need to check fitness of covid-19 sufferers moreover. With the boosting kind of instances it...
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Cyber Supply Chain (CSC) system is complex which involves different sub-systems performing various tasks. Security in supply chain is challenging due to the inherent vulnerabilities and threats from any part of the system which can be exploited at any point within the supply chain. This can cause a severe disruption on the overall business continui...
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Motorcycle accidents have been rapidly growing through the years in many countries. In India more than 37 million people use two wheelers. Therefore, it is necessary to develop a system for automatic detection of helmet and triples wearing for road safety. Therefore, a custom object detection model is created using a Machine learning based algorith...
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This paper presents an effective approach for detecting abandoned luggage in surveillance videos. We combine short- and long-term background models to extract foreground objects, where each pixel in an input image is classified as a 2-bit code. Subsequently, we introduce a framework to identify static foreground regions based on the temporal transi...
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In present industry, communication is the key element to progress. Passing on information, to the right person, and in the right manner is very important, not just on a corporate level, but also on a personal level. The world is moving towards digitization, so are the means of communication. Phone calls, emails, text messages etc. have become an in...
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This paper investigates the applicability of machine-driven Speech Emotion Recognition (SER) towards the augmentation of theatrical performances and interactions (e.g. controlling stage color /light, stimulating active audience engagement, actors’ interactive training, etc.). For the needs of the classification experiments, the Acted Emotional Spee...
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This conceptual paper exclusively focused on how artificial intelligence (AI) serves as a means to identify a target audience. Focusing on the marketing context, a structured discussion of how AI can identify the target customers precisely despite their different behaviors was presented in this paper. The applications of AI in customer targeting an...
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Traffic control and vehicle owner identification has become major problem in every country. Sometimes it becomes difficult to identify vehicle owner who violates traffic rules and drives too fast. Therefore, it is not possible to catch and punish those kinds of people because the traffic personal might not be able to retrieve vehicle number from th...
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Due to Increase in the amount of data in the field of genomics, meteorology, biology, environmental research and many others, it has become difficult to find, analyse patterns, associations within such large data. Interesting association is to be found in the large data sets to draw the pattern and for knowledge purpose. The benefit of analysing th...
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Networking, which is one of the most significant aspects of information technology revolution, is developing increasingly day after day. This is because it offers a huge amount of knowledge, resources and human experiences. On the one hand, it contains a considerable amount of harmful content, because of misusing. On the other hand, sitting for a l...
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The agriculture sector faces many challenges such as crop diseases, pest infestation, water shortage, weeds and many more. These problems lead to substantial crop loss, economic loss and also causes severe environmental hazards due to the current agriculture practices. The AI and Robotics technologies have the potential to solve these problems effi...
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This study has evaluated the differentiating impact of MGNREGA on the extent of fulfilment of the basic entitlements such as days of employment, wages and earnings and the extent of coverage of social groups like dalits, adivasis and women and poverty alleviation. This study has disaggregated state level data to discern the factors that make a diff...
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Design of fishing boat for Pelabuhanratu fisherman as one of effort to increase production of capture fisheries. The fishing boat should be proper for the characteristic of its service area, as ;capacity of fishing boat up to 60 GT, the fishing boat has minimum 6 fish holds and location of fish hold in the middle body, the fishing boat hull has the...
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Image sensors are increasingly being used in biodiversity monitoring, with each study generating many thousands or millions of pictures. Efficiently identifying the species captured by each image is a critical challenge for the advancement of this field. Here, we present an automated species identification method for wildlife pictures captured by r...
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This paper presents the design and implementation of Modular Multilevel Inverter (MMI) to control the Induction Motor (IM) drive using intelligent techniques towards marine water pumping applications. The proposed inverter is of eleven levels and has the ability to control the speed of an IM drive which is fed from solar photovoltaics. It is estima...
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Epilepsy is a type of neurological disorder that causes abnormal brain activities and creates epileptic seizures.Traditionally epileptic seizure prediction is realized with a visual examination of Electroencephalogram (EEG) signals. But this technique needs a long time EEG monitoring. So, the automatic epileptic seizures prediction schemes become a...
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Epilepsy is a chronic neurological disorder with several different types of seizures, some of them characterized by involuntary recurrent convulsions, which have a great impact on the everyday life of the patients. Several solutions have been proposed in the literature to detect this type of seizures and to monitor the patient; however, these appro...
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Objective of the project is to fabricate a motorized high speed 4-way hacksaw machine and to automate and to modify the conventional power hacksaw machine in order to achieve high productivity of work-pieces than the power hacksaw machine using cam mechanism. The operator need not measure the length of the work-piece that is to be cut and to load a...
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As a personal assistant, this project is built with AI technologies, Artificial intelligence technologies are beginning to be actively used in human life, this is facilitated by the appearance and wide dissemination of the Internet of Things (IOT). Autonomous devices are becoming smarter in their way to interact with both a human and themselves. Th...
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This paper presents a fully pipelined color demosaicking design. To improve the quality of reconstructed images, a linear deviation compensation scheme was created to increase the correlation between the interpolated and neighboring pixels. Furthermore, immediately interpolated green color pixels are first to be used in hardware-oriented color demo...
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This brief presents a low-power architecture for the design of a one-dimension median filter. It is a word-level two-stage pipelined filter, receiving an input sample and generating a median output at each machine cycle. The power consumption is reduced by decreasing the number of signal transitions in the circuit. This can be done by keeping the s...
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This paper presents a novel approach to design obfuscated circuits for digital signal processing (DSP) applications using high-level transformations, a key-based obfuscating finite-state machine (FSM), and a reconfigurator. The goal is to design DSP circuits that are harder to reverse engineer. Highlevel transformations of iterative data-flow graph...
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Field-programmable gate arrays (FPGAs) are increasingly used as the computing platform for fast and energyefficient execution of recognition, mining, and search applications. Approximate computing is one promising method for achieving energy efficiency. Compared with most prior works on approximate computing, which target approximate processors and...
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This brief presents the key concept, design strategy, and implementation of reconfigurable coordinate rotation digital computer (CORDIC) architectures that can be configured to operate either for circular or for hyperbolic trajectories in rotation as well as vectoring-modes. It can, therefore, be used to perform all the functions of both circular a...
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AQFP (adiabatic quantum-flux-parametron) circuits are currently verified by analog-based simulation, which would be an obstacle for large-scale circuits design. In this paper, we present a logic simulation model for AQFP logic. We made a functional model based on a finite-state machine approach using a hardware description language (HDL), which ena...
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Portable automatic seizure detection system is very convenient for epilepsy patients to carry. In order to make the system on-chip trainable with high efficiency and attain high detection accuracy, this paper presents a very large scale integration (VLSI) design based on the nonlinear support vector machine (SVM). The proposed design mainly consist...
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Multiply–accumulate (MAC) computations account for a large part of machine learning accelerator operations. The pipelined structure is usually adopted to improve the performance by reducing the length of critical paths. An increase in the number of flip-flops due to pipelining, however, generally results in significant area and power increase. A la...
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India is the cultivating country and our country is the biggest maker in agricultural products. So, we have to classify and exchange our agricultural products. Manual arranging is tedious and it requires works. The automatic grading system requires less time for grading of the agricultural products. Image processing technique is helpful in exam...
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This paper aims to develop a tool for predicting accurate and timely traffic flow Information. Traffic Environment involves everything that can affect the traffic flowing on the road, whether it’s traffic signals, accidents, rallies, even repairing of roads that can cause a jam. If we have prior information which is very near approximate about a...
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Stress is one of the factors that affect human health in many aspects. It is considered as one of the culprits in increasing the risk of getting sick that could probably lead to critical physical or mental illnesses. Stress can be experienced everywhere and in different circumstances. Hence, stress should be controlled and managed by monitoring its...
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Tracking seizures is crucial for epilepsy monitoring and treatment evaluation. Current epilepsy care relies on caretaker seizure diaries, but clinical seizure monitoring may miss seizures. Wearable devices may be better tolerated and more suitable for long-term ambulatory monitoring. This study evaluates the seizure detection performance of custom-...
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Since its invention in 1974, the Rubik’s Cube has challenged users to solve a colorful puzzle in record time. While humans have managed to solve the puzzle in as little as 4.69 seconds, robots are able to do so in under a second. This seemingly impossible puzzle can be solved amazingly quickly through the use of algorithms - sequences of moves ...
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In recent times, with the increase of Artificial Neural Network (ANN), deep learning has brought a dramatic twist in the field of machine learning by making it more artificially intelligent. Deep learning is remarkably used in vast ranges of fields because of its diverse range of applications such as surveillance, health, medicine, sports, robo...
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Privacy-preserving distributed data fusion is a pretreatment process in data mining involving security models. In this paper, we present a method of implementing multiparty data fusion, wherein redundant attributes of a same set of individuals are stored by multiple parties. In particular, the merged data does not suffer from background attacks or ...
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As object recognition technology has developed recently, various technologies have been applied to autonomous vehicles, robots, and industrial facilities. However, the benefits of these technologies are not reaching the visually impaired, who need it the most. In this paper, we proposed an object detection system for the blind using deep learning t...
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Hemoglobin can be measured normally after the analysis of the blood sample taken from the body and this measurement is named as invasive. Hemoglobin must continuously be measured to control the disease and its progression in people who go through hemodialysis and have diseases such as oligocythemia and anemia. This gives a perpetual feeling of pain...
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One common interest in radiography is producing radiographs with as low as possible radiation exposures to patients. In clinical practices, radiation exposure factors are preset for optimal image qualities to avoid underexposures which will lead to repeating examinations hence increasing radiation exposures to patients. Underexposed radiographs mai...
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Wireless sensor networks (WSN) are integral part of Industrial Internet of Things (IIOT), the said networks comprise of elements possessing low power processors. WSNs are used for gathering data in the monitoring region, using which vital information about the sensor and the monitoring region can be attained (placement of the sensor node is critica...
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Epilepsy is a chronic neurological disorder with several different types of seizures, some of them characterized by involuntary recurrent convulsions, which have a great impact on the everyday life of the patients. Several solutions have been proposed in the literature to detect this type of seizures and to monitor the patient; however, these appro...
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Epilepsy is a type of neurological disorder that causes abnormal brain activities and creates epileptic seizures. Traditionally epileptic seizure prediction is realized with a visual examination of Electroencephalogram (EEG) signals. But this technique needs a long time EEG monitoring. So, the automatic epileptic seizures prediction schemes become ...
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With the increasing popularity of blockchain technology, it has also become a hotbed of various cybercrimes. As a traditional way of scam, the phishing scam has new means of scam in the blockchain scenario and swindles a lot of money from users. In order to create a safe environment for investors, an ecient method for phishing detection is urge...
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With population growth, the demand for vehicles has increased tremendously, which has created an alarming situation in terms of traffic hazards and road accidents. The road accidents percentage is growing exponentially and so are the fatalities caused due to accidents. However, the primary cause of the increased rate of fatalities is due to the del...
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With the rapid development of wireless communication technology, people's life has undergone great changes. In recent years, the comfort and safety of the building environment have become a universal concern. However, building fire is the greatest threat to building safety. In consideration of the current issues on building security, the design app...
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In this paper, we design a home outlet and a LED array lamp controlled by hand gesture recognition with a smart phone that has a system composed of two parts: a smart phone's application and a wireless remote control unit (WRCU). The application can read the accelerometer and gyroscope in a smart phone by means of hand gesture recognition and s...
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This paper aims at realization of the Automated Teller Machine network all around the globe using IPv6, thereby reducing the complexity and total number of transactions involved in the entire process of cash withdrawal. But the major challenge involved in connecting ATM network to public domain is the security. A Near-Field Communication (NFC) is p...
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In 1930's, Mr. Luther G. Simijian initiated building first of kind and not so successful version of Tellering machine. He did register related patents. He initially came up with an idea of machine fixed in a wall called as "Hole in the wall machine." It would allow customer to make financial transaction without entering the bank. John S. Barron had...
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The ability to remotely control a robotic arm through a human one is essential where human involvement is needed but physical presence is not possible. Control provided through vision-based approaches comes with advantage over non-vision schemes, as vision-based approaches are less intrusive. On the other hand, the problem of estimating the hand po...
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Shopping mall is a place where people get their daily necessities. There has been an emerging demand for quick and easy payment of bills in shopping malls. Quite often, when shopping in a supermarket shoppers are frustrated at locating the items on the shopping list and no assistance is available. To overcome these problems we hav...
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This paper presents the technical construction of the vehicle controlled by user mobile. The designed GSM based vehicle could be operated from almost anywhere if GSM network exists. The procedure commences with initiating a call from the cell phone which is auto received by GSM module stacked in the vehicle. In the course of a call, if any of the k...
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Biosensors integrated into the vehicle controller area network are used for detecting symptoms such as anxiety, pain, and fatigue that may affect driving safety. The proposed system provides a flexible option for implementation in a diverse range of mass-produced automotive accessories without affecting the driver’s movement.
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Robust and reliable detection of falls is crucial especially for elderly activity monitoring systems. In this letter, we present a fall detection system using wearable devices, e.g., smartphones, and tablets, equipped with cameras and accelerometers. Since the portable device is worn by the subject, monitoring is not limited to confined areas, and ...
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To review and critically appraise published and preprint reports of prediction models for diagnosing coronavirus disease 2019 (covid-19) in patients with suspected infection, for prognosis of patients with covid-19, and for detecting people in the general population at risk of being admitted to hospital for covid-19 pneumonia. Design Rapid systemat...
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Data mining plays the key role in crime analysis. There are various number of different algorithm in previous research papers like virtual identifier, pruning strategy, support vector machines and apriori algorithms. “VID” (Virtual ID) is to find relationship between record. Then the “Apriori algorithm is used to around six hundred seconds to detec...
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Agriculture is the backbone of Indian economy. Due to global warming and climate change traditional farming in the regular months have been distorted and crops have been ruined is the most common phrase seen today. This not only gives economic losses but also the main reason for farmer sucide. Now agriculture needs support, time has come for techno...
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Agriculture is the backbone of Indian economy. Due to global warming and climate change traditional farming in the regular months have been distorted and crops have been ruined is the most common phrase seen today. This not only gives economic losses but also the main reason for farmer sucide. Now agriculture needs support, time has come for techno...
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With the increased popularity of online social networks, spammers find these platforms easily accessible to trap users in malicious activities by posting spam messages. In this work, we have taken Twitter platform and performed spam tweets detection. To stop spammers, Google SafeBrowsing and Twitter’s BotMaker tools detect and block spam tweets. Th...
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The evolution of distributed architectures and programming paradigms for performance-oriented program development, challenge the state-of-the-art technology for performance tools. The area of high performance computing is rapidly expanding from single parallel systems to clusters and grids of heterogeneous sequential and parallel systems. Performan...
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In Petrol Pump management system, the main objective is to acquaint our user with various detail of our system. Ij which the software enables the manager of petrol pump to make reasonable decision made within a no time frame for sales, CNG, fuels like petrol, diesel, employee and should be updated towards system. In this Project, in which the proje...
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The Main Objective of this System is to plan a framework to keep up impressive data of the workers, offices, Customer points of interest for any BPO association. Call Center Executer is an undeniably vital ability as the utilization of call focuses turns into a well-known technique for concentrating data administrations, streamlining request taking...
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Machine learning is a powerful technique which can increase the efficiency and accuracy in disease prediction. In current scenario there is a need for efficient machine learning models that can be used in healthcare system to predict the specific diseases by monitoring the patient’s symptoms over a period. But there exist very few studies pertainin...
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The project is mainly aimed at providing a secured and user friendly Online Voting System. The problem of voting is still critical in terms of safety and security. This system deals with the design and development of a webbased voting system using fingerprint and aadhaar card in order to provide a high performance with high security to the voting s...
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The use of credit cards is prevalent in modern day society. But it is obvious that the number of credit card fraud cases is constantly increasing in spite of the chip cards worldwide integration and existing protection systems. This is why the problem of fraud detection is very important now. In this paper the general description of the developed f...
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Mango, the king of tropical fruits had a great potential for value added products due to its greater impact on human health. Mango pulp is a preservation technique that overcomes the postharvest losses during the seasons. The current study was focused to develop a pulp from Kartha kolomban mango cultivar and evaluate its physical, biochemical, micr...
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As the name specifies “HOSTEL MANAGEMENT SYSTEM” is a software developed for managing various activities in the hostel. For the past few years the number of educational institutions are increasing rapidly. Thereby the number of hostels are also increasing for the accommodation of the students studying in this institution. And hence there is a lot o...
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Using a novel approach with video-recordings of sales interactions, this study focuses on a dynamic analysis of salesperson effectiveness in handling customer queries. We conceptualize salesperson behaviors, namely, resolving, relating, and emoting, as separate elements of customer query handling and empirically identify the distinct verbal and non...
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Biometrics technology is rapidly progressing and offers attractive opportunities. In recent years, biometric authentication has grown in popularity as a means of personal identification in ATM authentication systems. Fingerprint Based ATM is a desktop application where fingerprint of the user is used as an authentication. The finger print minutiae ...
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Shopping is an activity of buying goods from the shop. Shop is a place where a customer can fulfil all their needs. Android based systems should be technically implemented in such a way that ensures adequate user requirements. The proposed methodology is implemented to allow the person to do shopping using fingerprint authentication of customer and...
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The aim of making the marriage hall reservations and accounting system with online facility is to provide such generic software which could facilitate any kind of marriage hall with the best reservation and accounting system. It will be serving as the backbone of the marriage hall management system. With this software, the management team gets reli...
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Internet has become the biggest repository of information in the world. It can be considered as a global library where variety of information in different languages and formats is stored in digital form. The volume of information on web is enormous and it has become near to impossible to estimate its size. Because of its size and storing mechanism,...
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Due to their tight schedule nobody is going to the polls these days. There are numerous causes, some need to go to the polls, many of us may have to wait for long periods because of their strict schedules. So we created a voting system on the Internet. But there are some disadvantages to this system. Attackers legally receive customer passwords and...
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The Management Information System is a concept of the last decade or two. The role of MIS in an organization can be compared to the role of heart in the body. Most of the organizations be it small or large are using computer based information system with centralized, decentralized or distributed networks connecting data flow from and to the various...
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Appointment scheduling systems are used by primary and specialty care clinics to manage access to service providers, as well as by hospitals to schedule elective surgeries. Many factors affect the performance of appointment systems including arrival and service time variability, patient and provider preferences, available information technology and...
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Large amount of Twitter accounts are suspended. Over five year period, about 14% accounts are terminated for reasons not specified explicitly by the service provider. We collected about 120,000 suspended users, along with their tweets and social relations. This thesis studies these suspended users, and compares them with normal users in terms of th...
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Now a days Attacker’s launch attack campaigns targeting the zero day vulnerability, compromising internet users on a large scale. The first response to such campaigns is to detect them and collect sufficient information regarding tools, techniques used to exploit the vulnerability. Hence effective capturing of the attack data and its timely dissemi...
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Cloud computing is a major blooming technology which has numerous applications in today’s market and is rightly so hyped. Images are a major part of today’s internet data traffic, especially due to widespread social media, and hence, its security is crucial. However, in the present scenario, the images in cloud are a major issue in terms of securit...
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Since its invention in 1974, the Rubik’s Cube has challenged users to solve a colorful puzzle in record time. While humans have managed to solve the puzzle in as little as 4.69 seconds, robots are able to do so in under a second. This seemingly impossible puzzle can be solved amazingly quickly through the use of algorithms - sequences of moves ...
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Privacy-preserving distributed data fusion is a pretreatment process in data mining involving security models. In this paper, we present a method of implementing multiparty data fusion, wherein redundant attributes of a same set of individuals are stored by multiple parties. In particular, the merged data does not suffer from background attacks...
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Library management, its operation has never been easy to run effectively manually, lending of books, records of returned books, books in the library, its shift and many more. This research work will dwell more on developing and implementing a comprehensive library management system capable of handling the library operation, like book lending, retri...
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The Election Schedule for the conduct of General Elections as well as for the by-elections, as the case may be, is decided by the Chief Election Commissioner in Pakistan. The current system is being operated manually. Votes are polled manually. All the record of voters, candidates, polling stations, regions detail and parties’ information are store...
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The Java Application World application world soft- ware is totally user oriented and only users access the software programs. The user can use multiple applications that re made with the help of java. In the J Appsor the Java application world, the user can use calculator, word count tool, ip finder etc java run software. Any particular IDE can...
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In any developing country democracy plays an important role where a leader for a country is elected by the citizen. One of the main issues in the conventional voting system is that it consumes lots of man-power as well as resources and the preparation have been started many days before the commencement of the election. During this preparation some ...
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Wireless Networks are susceptible for a variety of malicious attacks because they use shared transmission medium. The transmission of information may be jammed by an attacker by introducing malicious packets into the network. These jammers create a lot of noise in the total network and create problems at both the ends of transmission and affect the...
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Federated Learning (FL) is a distributed learning framework that can deal with the distributed issue in machine learning and still guarantee high learning performance. However, it is impractical that all users will sacrifice their resources to join the FL algorithm. This motivates us to study the incentive mechanism design for FL. In this paper, we...
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In this paper, a multiple cluster-based transmission diversity scheme is proposed for asynchronous joint transmissions (JT) in private networks. The use of multiple clusters or small cells is adopted to reduce the transmission distance to users thereby increasing data-rates and reducing latency. To further increase the spectral efficiency and achie...
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Unmanned aerial vehicles (UAVs) have extensive civilian and military applications, but establishing a UAV network providing high data rate communications with low delay is a challenge. Millimeter wave (mmWave), with its high bandwidth nature, can be adopted in the UAV network to achieve high speed data transfer. However, it is difficult to establis...
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This paper proposes a communication strategy for decentralized learning in wireless systems that employs adaptive modulation and coding capability. The main objective of this work is to address a critical issue in decentralized learning based on the cooperative stochastic gradient descent (C-SGD) over wireless systems: the relationship between the ...
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The real power required for machine equipment depends on the resistance to the movement of it. Even now, in our country 98% of the contemporary machines use the power by burning of fossil fuels to run IC engines or external combustion engines. This evident has led to widespread air, water and noise pollution and most importantly has led to a realis...
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The Project report espouses the humble efforts of team which is more inspired than equipped. It covers the design aspects of “Solar Box Shifting Mechanism”. Box Shifting Mechanism is a small project for shifting of the boxes for the industrial purpose, used mainly in the packaging and filling department. A great many manufacturers of fancy wrapped ...
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The main target of project is to improved version of a mini pneumatic Slotting machine which will be more efficient for die makers and pattern makers. This machine is pneumatic powered which has low co-efficient of friction. A pneumatic cylinder erected at the top provides power of slotting operations. Compressed air is passed into the power for ...
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This project deals with the design and fabrication of hand operated garden cultivator. Our aim is to manufacture the simplest form of cultivator which can be used for all kind of domestic purpose. This project uses the human effort for operation. This hand operated garden cultivator consists of a wheel, three ploughs and support frames are used fo...
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The seed sowing machine is used to sowing the seeds into land for making lots of plant production in agricultural field. It is a mechanical device here no electrical or other power source is not required. The cost of this machine is very low and easy to operate simple in construction. This project is designed by following parts, wheels, lead screw,...
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Groundnut product demand is on the increase and the application is largely dependent on the cleanness of the nuts. The separation process from plant is usually an energy sapping task that requires a lot of time. In order to separate the nuts from its plant effectively a machine was developed. The machine basically comprises of chain drive, pedal, f...
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Here were fabricating the charcoal mixing and grinding machine. It is used for mixing the charcoal finely for the several purposes. Here were developing this concept for the main reason is, reducing the manual effort and also increasing the productivity. This project is made done by these components, motor, belt, pulley, bearings and the hopper. Th...
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The project “CAM HAMMER” being compact and Portable, handy equipment, which is skillful and is having something different from the ancient conventional hammering process. Most of the material is made available by our college. The sub-components we could easily manufacture in our college work- shop. It’s manufacturing price is also less. This pro...
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Introduced gearless power transmission arrangement used for skew shafts. In this transmission system no. of pins or links used must be odd..3,5,7,9.....& centers of any two pins or links whole must not be on that line which represents the diameter of the shaft. If more pins or links used motion will be smoother,but increase in no. of pins or links ...
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This project deals with the fabrication of pneumatic mobile crane. The aim of this project work is to acquire practical knowledge in the field of material handling equipment. The project work is concerned with the fabrication of the portable jib crane. This machine is very useful for lifting and transporting heavy jobs upto two tons for all types o...
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In this Pedal operated drilling machine which can be used for industrial applications and Household needs in which no specific input energy or power is needed. This project consists of a crank and slider mechanism. In the mechanism pedal is directly connected to the hacksaw through crank and slider mechanism for the processing of drilling the woode...
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Our project is designed to fabricate the multipurpose air cutter. The main aim of this project is to cut the vegetable by using pneumatic cylinder with the help of compressed air. Tray will be provided near that arrangement to collect the vegetable pieces. Pneumatic cylinder, solenoid valve, collecting tray and vegetable holder are the components o...
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In this project we are fabricate the automatic punching machine. This project we are using the motor, sensor, punch tool, supporting column, base and control unit. The project constructed by the simple arrangements so this project is easily operates to any worker in industries. Cost of the project is less so this project is suitable for small scale...
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A device, usually motor-driven, fitted with an end cutting tool that is rotated with sufficient power either to create a hole or to enlarge an existing hole in a solid material and also known as driller. Tapping is the process of making thread inside the drilled hole. This operation requires less force to operate. In this project the drilling machi...
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The aim of our project is to design and fabricate a pneumatically operated multipurpose grinder. With this device a number of operations can be performed. A high pressure compressed air is forced on a fan and the fan is made to rotate. This rotation is transmitted to the machining head by a shaft and the required operation is carried out. Furthe...
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This report deals with design and fabrications of pneumatic multipurpose presses which is used for bearings pressing of robots in the shaft, bearing removing, sheet metal bending and bend removing with the help of a compressor. Initially the shaft is held between two fixtures; top of the bearing is freely located on the step in the shaft and the ot...
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This is the new innovative concept mainly used for agricultural field. It is simple in construction and the working process is easy. And it is mostly used in the agricultural field for the cutting of crops etc.., In our project we are using the portable cutting for to cutting the crops in the field. It consists of simple manner and the using compon...
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Multi tool turret head is used to make more operations like drilling, facing, turning; chamfering, grooving etc… are done sequentially. It has proved to be the most versatile method to machining works on the work piece. This machine includes a first functional portion known as the work holder which helps to hold the work piece. This system is provi...
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The main aim of the project is to save the electrical power in house, hotels and fast food stalls. Pedal operated maxi is operated by chain and sprocket. The manual power is utilized to run the maxi. This project consists of a pedal, bevel gear arrangement, cutting blades, bearing blocks, arrangement for jar removing.The following working principle...
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This paper investigates the performance of a wireless network that consists of two pairs of transmitter-receiver sharing the same channel, modeled using two coupled queues. In this analysis, we use the power metric P , defined as the ratio of throughput and mean delay, to understand the compromise between these two metrics. We show that, when the u...
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Wireless charging coupled with computation offloading in edge networks offers a promising solution for realizing power-hungry and computation intensive applications on user-devices. We consider a multi-access edge computing (MEC) system with collocated MEC server and base-station/access point (AP), each equipped with a massive MIMO antenna array, s...
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The network control plays a vital role in the mega satellite constellation (MSC) to coordinate massive network nodes to ensure the effectiveness and reliability of operations and services for future space wireless communications networks. One of the critical issues in satellite network control is how to design an optimal network control structure (...
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Wireless Sensors Networks (WSN) is the self-configured wireless network which consists of a huge measure of resource-restrained Sensor Nodes (SN). In WSN, the key parameters are effectual energy utilization and security. The adversary could send false information because of the Malicious Nodes' (MNs') presence. Thus, to shun security threats, it is...
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Unmanned aerial vehicles (UAVs) are anticipated to be integrated into the next generation wireless networks as new aerial mobile nodes, which can provide various live streaming applications such as surveillance, reconnaissance, etc. For such applications, due to the dynamic characteristics of traffic and wireless channels, how to guarantee the qual...
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This paper presents a machine learning strategy that tackles a distributed optimization task in a wireless network with an arbitrary number of randomly interconnected nodes. Individual nodes decide their optimal states with distributed coordination among other nodes through randomly varying backhaul links. This poses a technical challenge in distri...
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With the evolution of the Internet of Things (IoT), smart cities have become the mainstream of urbanization. IoT networks allow distributed smart devices to collect and process data within smart city infrastructure using an open channel, the Internet. Thus, challenges such as centralization, security, privacy (e.g., performing data poisoning and in...
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The time series data generated by massive sensors in Internet of Things (IoT) is extremely dynamic, heterogeneous, large scale and time-dependent. It poses great challenges (e.g. accuracy, reliability, stability) on the real-time analysis and decision making for different IoT applications. In this paper, we design, implement and evaluate EdgeLSTM, ...
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Deep neural network (DNN) has become increasingly popular in industrial IoT scenarios. Due to high demands on computational capability, it is hard for DNN-based applications to directly run on intelligent end devices with limited resources. Computation offloading technology offers a feasible solution by offloading some computation-intensive tasks t...
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The increase in electronic loads connected to electrical network became relevant requirements of the quality of supply. Among the equipment used in the power distribution system stands out regulators medium voltage installed over the grid to maintain voltage levels within indifferent operating range of the oscillations. Therefore, the quality of su...
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The global healthcare industry and artificial intelligence has promoted the development of the diversified intelligent healthcare applications. IoT will play an important role in meeting the high throughput requirements of diversified intelligent healthcare applications. However, the healthcare big data transmission is vulnerable to a potential att...
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There has been an asymmetric shift towards harnessing cloud-based technologies as the world focuses on shifting operations remotely. Data security for remote operations is crucial for the protection and preservation of critical infrastructure. Furthermore, there has been an emerging trend to integrate IoT based devices with the expanding cloud infr...
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This paper studies an unmanned aerial vehicle (UAV)-assisted wireless powered IoT network, where a rotary-wing UAV adopts fly-hover-communicate protocol to successively visit IoT devices in demand. During the hovering periods, the UAV works on full-duplex mode to simultaneously collect data from the target device and charge other devices within its...
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Developing products and entering new markets in the Internet of Things (IoT) and industry 4.0 space are challenging because value propositions and business models are complex. IoT products are fundamentally platform products, whose embedded components can measure a disparate set of characteristics for several user types. Deciding in advance which c...
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Bio-features are fast becoming a key tool to authenticate the IoT devices; in this sense, the purpose of this investigation is to summaries the factors that hinder biometrics models’ development and deployment on a large scale, including human physiological (e.g., face, eyes, fingerprints-palm, or electrocardiogram) and behavioral features (e.g., s...
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This paper studies the interplay between device-to-device (D2D) communications and real-time monitoring systems in a cellular-based Internet of Things (IoT) network. In particular, besides the possibility that the IoT devices communicate directly with each other in a D2D fashion, we consider that they frequently send time-sensitive information/stat...
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In this paper, we study sensing data collection of IoT devices in a sparse IoT-sensor network, using an energy-constrained Unmanned Aerial Vehicle (UAV), where the sensory data is stored in IoT devices while the IoT devices may or may not be within the transmission range of each other. We formulate two novel data collection problems to fully or par...
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In recent years, Internet of Things (IoT) security has attracted significant interest by researchers due to new characteristics of IoT such as heterogeneity of devices, resource constraints, and new types of attacks targeting IoT. Intrusion detection, which is an indispensable part of a security system, is also included in these studies. In order t...
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This article analyzes the effectiveness of deploying the Blockchain technology in the implementation of the IoT ecosystem database. To this end, we assess the processing efficiency of transactions originated by smart devices and the storeddata integrity. The processing-efficiency evaluation is carried out through queue-theory-based analytical model...
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The ATM Fraudulence occurring in the society has become very common nowadays. Even though technology has boomed in various aspects it is being misused in different ways for stealing money through ATM’S. Skimming and Trapping of the ATM devices have been designed by many Burglars. Recognition based Verification system as been implemented for many AT...
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We develop a novel framework for efficiently and effectively discovering crowdsourced services that move in close proximity to a user over a period of time. We introduce a moving crowdsourced service model which is modelled as a moving region. We propose a deep reinforcement learning-based composition approach to select and compose moving IoT servi...
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Cloud computing is becoming an popular model of computing. Due to the increasing complexity of the cloud service requests, it often exploits heterogeneous architecture. Moreover, some service requests (SRs)/tasks exhibit real-time features, which are required to be handled within a specified duration. Along with the stipulated temporal management, ...
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With the rapid development of 5G, Mobile Edge Computing (MEC) paradigm has emerged to enable various devices or servers at the network edge to contribute their computing capacity for reducing communication delay. A fundamental problem is to preserve satisfactory quality-of-service (QoS) for mobile users in light of densely dispersed wireless commun...
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This paper presents V-Sight, a network monitoring framework for programmable virtual networks in clouds. Network virtualization based on software-defined networking (SDN-NV) in clouds makes it possible to realize programmable virtual networks; consequently, this technology offers many benefits to cloud services for tenants. However, to the best of ...
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In this paper, we propose online learning methodologies for performance modeling and prediction of applications that run repetitively on multi-tenant clouds. Based on a few micro-benchmarks to probe in-situ perceivable performance of major components of the target VM, we proposed both periodic model retraining and progressive modeling approaches to...
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In a public blockchain system applying Proof of Work (PoW), the participants need to compete with their computing resources for reward, which is challenging for resource-limited devices. Mobile blockchain is proposed to facilitate the application of blockchain for mobile service, in which the lightweight devices can participate mining by renting re...
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Fog computing is an emerging computing paradigm that uses processing and storage capabilities located at the edge, in the cloud, and possibly in between. Testing and benchmarking fog applications, however, is hard since runtime infrastructure will typically be in use or may not exist, yet. While approaches for the emulation of infrastructure testbe...
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Due to the excessive concentration of computing resources in the traditional centralized cloud service system, there will be three prominent problems of management confusion, construction cost and network delay. Therefore, we propose to virtualize regional edge computing resources in intelligent buildings as edge service pooling, then presents a hi...
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Big data frameworks such as Apache Spark are becoming prominent to perform large-scale data analytics jobs. However, local or on-premise computing resources are often not sufficient to run these jobs. Therefore, public cloud resources can be hired on a pay-per-use basis from the cloud service providers to deploy a Spark cluster entirely on the clou...
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In recent years, edge computing has attracted significant attention because it can effectively support many delay-sensitive applications. Despite such a salient feature, edge computing also faces many challenges, especially for efficiency and security, because edge devices are usually heterogeneous and may be untrustworthy. To address these challen...
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This article surveys the interdisciplinary research of neuroscience, network science, and dynamic systems, with emphasis on the emergence of brain-inspired intelligence. To replicate brain intelligence, a practical way is to reconstruct cortical networks with dynamic activities that nourish the brain functions, instead of using only artificial comp...
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Global principal component analysis (PCA) has been successfully introduced for modeling distributed parameter systems (DPSs). In spite of the merits, this method is not feasible due to parameter variations and multiple operating domains. A novel multimode spatiotemporal modeling method based on the locally weighted PCA (LW-PCA) method is developed ...
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Tubulin is a promising target for designing anti-cancer drugs. Identification of hotspots in multifunctional Tubulin protein provides insights for new drug discovery. Although machine learning techniques have shown significant results in prediction, they fail to identify the hotspots corresponding to a particular biological function. This paper pre...
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Increasingly, the task of detecting and recognizing the actions of a human has been delegated to some form of neural network processing camera or wearable sensor data. Due to the degree to which the camera can be affected by lighting and wearable sensors scantiness, neither one modality can capture the required data to perform the task confidently....
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Ensembles, as a widely used and effective technique in the machine learning community, succeed within a key element--``diversity.'' The relationship between diversity and generalization, unfortunately, is not entirely understood and remains an open research issue. To reveal the effect of diversity on the generalization of classification ensembles, ...
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Linear discriminant analysis (LDA) is a classical statistical machine-learning method, which aims to find a linear data transformation increasing class discrimination in an optimal discriminant subspace. Traditional LDA sets assumptions related to the Gaussian class distributions and single-label data annotations. In this article, we propose a new ...
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These days, clustering is one of the most classical themes to analyze data structures in machine learning and pattern recognition. Recently, the anchor-based graph has been widely adopted to promote the clustering accuracy of plentiful graph-based clustering techniques. In order to achieve more satisfying clustering performance, we propose a novel ...
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Feature selection (FS) is an important step in machine learning since it has been shown to improve prediction accuracy while suppressing the curse of dimensionality of high-dimensional data. Neural networks have experienced tremendous success in solving many nonlinear learning problems. Here, we propose a new neural-network-based FS approach that i...
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This article proposes a novel modeling method for the stochastic nonlinear degradation process by using the relevance vector machine (RVM), which can describe the nonlinearity of degradation process more flexibly and accurately. Compared with the existing methods, where degradation processes are modeled as the Wiener process with a nonlinear drift ...
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Attention-based deep multiple-instance learning (MIL) has been applied to many machine-learning tasks with imprecise training labels. It is also appealing in hyperspectral target detection, which only requires the label of an area containing some targets, relaxing the effort of labeling the individual pixel in the scene. This article proposes an L1...
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Resource constraint job scheduling is an important combinatorial optimization problem with many practical applications. This problem aims at determining a schedule for executing jobs on machines satisfying several constraints (e.g., precedence and resource constraints) given a shared central resource while minimizing the tardiness of the jobs. Due ...
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Many deep-learning methods have been developed for fault diagnosis. However, due to the difficulty of collecting and labeling machine fault data, the datasets in some practical applications are relatively much smaller than the other big data benchmarks. In addition, the fault data come from different machines. Therefore, on some occasions, fault di...
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Calibration of agent-based models (ABM) is an essential stage when they are applied to reproduce the actual behaviors of distributed systems. Unlike traditional methods that suffer from the repeated trial and error and slow convergence of iteration, this article proposes a new ABM calibration approach by establishing a link between agent microbehav...
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Lithology identification plays an essential role in formation characterization and reservoir exploration. As an emerging technology, intelligent logging lithology identification has received great attention recently, which aims to infer the lithology type through the well-logging curves using machine-learning methods. However, the model trained on ...
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Detecting small low-contrast targets in the airspace is an essential and challenging task. This article proposes a simple and effective data-driven support vector machine (SVM)-based spatiotemporal feature fusion detection method for small low-contrast targets. We design a novel pixel-level feature, called a spatiotemporal profile, to depict the di...
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In recent years, the appearance of the broad learning system (BLS) is poised to revolutionize conventional artificial intelligence methods. It represents a step toward building more efficient and effective machine-learning methods that can be extended to a broader range of necessary research fields. In this survey, we provide a comprehensive overvi...
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Recently, the restricted Boltzmann machine (RBM) has aroused considerable interest in the multiview learning field. Although effectiveness is observed, like many existing multiview learning models, multiview RBM ignores the local manifold structure of multiview data. In this article, we first propose a novel graph RBM model, which preserves the dat...
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The cross-lingual sentiment analysis (CLSA) aims to leverage label-rich resources in the source language to improve the models of a resource-scarce domain in the target language, where monolingual approaches based on machine learning usually suffer from the unavailability of sentiment knowledge. Recently, the transfer learning paradigm that can tra...
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The broad learning system (BLS) has been identified as an important research topic in machine learning. However, the typical BLS suffers from poor robustness for uncertainties because of its characteristic of the deterministic representation. To overcome this problem, a type-2 fuzzy BLS (FBLS) is designed and analyzed in this article. First, a grou...
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Autonomous learning algorithms operate in an online fashion in dealing with data stream mining, where minimum computational complexity is a desirable feature. For such applications, parsimonious learning machines (PALMs) are suitable candidates due to their structural simplicity. However, these parsimonious algorithms depend upon predefined thresho...
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Federated learning (FL) is a machine-learning setting, where multiple clients collaboratively train a model under the coordination of a central server. The clients' raw data are locally stored, and each client only uploads the trained weight to the server, which can mitigate the privacy risks from the centralized machine learning. However, most of ...
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By training different models and averaging their predictions, the performance of the machine-learning algorithm can be improved. The performance optimization of multiple models is supposed to generalize further data well. This requires the knowledge transfer of generalization information between models. In this article, a multiple kernel mutual lea...
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Predicting attention-modulated brain responses is a major area of investigation in brain-computer interface (BCI) research that aims to translate neural activities into useful control and communication commands. Such studies involve collecting electroencephalographic (EEG) data from subjects to train classifiers for decoding users' mental states. H...
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Predictive analytics has a significant potential to support different decision processes. We aimed to compare various machine learning algorithms for the selected task, which predicts credit card clients' default based on the free available data. We chose Random Forest, AdaBoost, XGBoost, and Gradient Boosting algorithm and applied them to a prepar...
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This article presents a novel discriminative subspace-learning-based unsupervised domain adaptation (DA) method for the gas sensor drift problem. Many existing subspace learning approaches assume that the gas sensor data follow a certain distribution such as Gaussian, which often does not exist in real-world applications. In this article, we addres...
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Due to the development of convenient brain-machine interfaces (BMIs), the automatic selection of a minimum channel (electrode) set has attracted increasing interest because the decrease in the number of channels increases the efficiency of BMIs. This study proposes a deep-learning-based technique to automatically search for the minimum number of ch...
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Complex-valued neural network is a kind of learning model which can deal with problems in complex domain. Fully complex extreme learning machine (CELM) is a much faster training algorithm than the complex backpropagation (CBP) scheme. However, it is at the cost of using more hidden nodes to obtain the comparable performance. An upper-layer-solution...
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The popularity of mobile devices has led to an explosive growth in the number of mobile apps in which Android mobile apps are the mainstream. Android mobile apps usually undergo frequent update due to new requirements proposed by users. Just-In-Time (JIT) defect prediction is appropriate for this scenario for quality assurance because it can pr...
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Passwords are pervasively used to authenticate users' identities in mobile apps. To secure passwords against attacks, protection is applied to the password authentication protocol (PAP). The implementation of the protection scheme becomes an important factor in protecting PAP against attacks. We focus on two basic protection in Android, i.e., SSL/T...
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Data in modern industrial applications and data science presents multidimensional progressively, the dimension and the structural complexity of these data are becoming extremely high, which renders existing data analysis methods and machine learning algorithms inadequate to the extent. In addition, high-dimensional data in actual scenarios often sh...
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The rapid development of the Industrial Internet of Things (IIoT) has led to the explosive growth of industrial control data. Cloud computing-based industrial control models cause vast energy consumption. Most existing solutions try to reduce the overall energy consumption by optimizing task scheduling and disregard how to reduce the load of comput...
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It is a challenging task to deploy lightweight security protocols in resource-constrained IoT applications. A hardware-oriented lightweight authentication protocol based on device signature generated during voltage over-scaling (VOS) was recently proposed to address this issue. VOS-based authentication employs the computation unit such as adder...
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As 5G and mobile computing are growing rapidly, deep learning services in the Social Computing and Social Internet of Things (IoT) have enriched our lives over the past few years. Mobile devices and IoT devices with computing capabilities can join social computing anytime and anywhere. Federated learning allows for the full use of decentralized tra...
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An always-on video-based human action recognition (HAR) system on chip (SoC) integrated with a CMOS image sensor (CIS) is proposed for the Internet of Things (IoT) devices. The proposed SoC is the first always-on integrated circuit (IC) performing the full process of HAR in a single chip. To resolve large power consumption from vision sensor and co...
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Recent research has shown that large-scale Internet of Things (IoT)-based load altering attacks can have a serious impact on power grid operations such as causing unsafe frequency excursions and destabilizing the grid’s control loops. In this work, we present an analytical framework to investigate the impact of IoT-based static/dynamic load alterin...
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Fog/edge computing has been recently regarded as a promising approach for supporting emerging mission-critical Internet of Things (IoT) applications on capacity and battery constrained devices. By harvesting and collaborating a massive crowd of devices in close proximity for computation, communication and caching resource sharing (i.e., 3C resource...
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Performing deep neural network (DNN) inference in real time requires excessive network resources, which poses a great challenge to the resource-limited industrial Internet of things (IIoT) networks. To address the challenge, in this paper, we introduce an end-edge-cloud orchestration architecture, in which the inference task assignment and DNN mode...
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This paper presents a distributed and decentralized architecture for the implementation of Distributed Artificial Intelligence (DAI) using hardware platforms provided by the Internet of Things (IoT). A trained DAI system has been implemented over the IoT, where each IoT device acts as one or more of the neurons within the DAI layers. This is accomp...
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With the booming of smart grid, The ubiquitously deployed smart meters constitutes an energy internet of things. This paper develops a novel blockchain-based transactive energy management system for IoT-aided smart homes. We consider a holistic set of options for smart homes to participate in transactive energy. Smart homes can interact with the gr...
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Cloud Data Centers (CDCs) have become a vital computing infrastructure for enterprises. However, CDCs consume substantial energy due to the increased demand for computing power, especially for the Internet of Things (IoT) applications. Although a great deal of research in green resource allocation algorithms have been proposed to reduce the energy ...
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The interest of Industry 4.0 in Smart Contracts and blockchain technologies is growing up day by day. Smart Contracts have enabled new kinds of interactions whereby contractors can even fully automate processes they agree on. This technology is really appealing in Internet of Things (IoT) domain because smart devices generate events for software ag...
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We propose a novel generic trust management framework for crowdsourced IoT services. The framework exploits a multi-perspective trust model that captures the inherent characteristics of crowdsourced IoT services. Each perspective is defined by a set of attributes that contribute to the perspective’s influence on trust. The attributes are fed into a...
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Computationally expensive applications, including machine learning, chemical simulations, and financial modeling, are promising candidates for noisy intermediate scale quantum (NISQ) computers. In these problems, one important challenge is mapping a quantum circuit onto NISQ hardware while satisfying physical constraints of an underlying quantum ar...
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In current Data Science applications, the course of action has derived to adapt the system behavior for the human cognition, resulting in the emerging area of explainable artificial intelligence. Among different classification paradigms, those based on fuzzy rules are suitable solutions to stress the interpretability of the global systems. However,...
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Recently, there have been many studies attempting to take advantage of advancements in Artificial Intelligence (AI) in Analog and Mixed-Signal (AMS) circuit design. Automated circuit sizing optimization and improving the accuracy of performance models are the two predominant uses of AI in AMS circuit design. This paper first introduces and explains...
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Cloud Data Centers (CDCs) have become a vital computing infrastructure for enterprises. However, CDCs consume substantial energy due to the increased demand for computing power, especially for the Internet of Things (IoT) applications. Although a great deal of research in green resource allocation algorithms have been proposed to reduce the energy ...
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Cloud data centers provide services for an increasing number of applications. The virtual machines (VMs) that perform the corresponding application tasks need to be allocated to physical machines (PMs). For VM allocation, cloud service centers consider both energy consumption and quality of service (QoS), while cloud users are primarily concerned w...
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Cloud-assisted Internet of Medical Things (IoMT) is becoming an emerging paradigm in the healthcare domain, which involves collection, storage and usage of the medical data. Considering the confidentiality and accessibility of the outsourced data, secure and fine-grained data sharing is a crucial requirement for the patients. Attribute-based encryp...
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The long-term data record (LTDR) has the goal of developing a quality and consistent Advanced Very High Resolution Radiometer (AVHRR) surface reflectance and albedo products dating back to 1982 at 0.05° spatial resolution. Distinguishing between cloud and snow is of critical importance when analyzing global albedo trends, for they influence the Ear...
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The rapid growth of mobile device (e.g., smart phone and bracelet) has spawned a lot of new applications, during which the requirements of applications are increasing, while the capacities of some mobile devices are still limited. Such contradiction drives the emergency of computation migration among mobile edge devices, which is a lack of research...
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Cloud computing becomes a promising technology to reduce computation cost by providing users with elastic resources and application-deploying environments as a pay-per-use model. More scientific workflow applications have been moved or are being migrated to the cloud. Scheduling workflows turns to the main bottleneck for increasing resource utiliza...
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This work takes as a starting point a collection of patterns for engineering software for the cloud and tries to find how they are regarded and adopted by professionals. Existing literature assessed the adoption of cloud computing with a focus on business and technological aspects and fall short in grasping a holistic view of the underlying approac...
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This paper proposes a backup resource allocation model that provides a probabilistic protection for primary physical machines in a cloud provider to minimize the required total capacity. When any random failure occurs, workloads are transferred to preplanned and dedicated backup physical machines for prompt recovery. In the proposed model, a probab...
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The elasticity of cloud resources allow cloud clients to expand and shrink their demand of resources dynamically over time. However, fluctuations in the resource demands and pre-defined size of virtual machines (VMs) lead to lack of resource utilization, load imbalance and excessive power consumption. To address these issues and to improve the perf...
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Online non-intrusive load monitoring methods have captivated academia and industries as parsimonious solutions for household energy efficiency monitoring as well as safety control, anomaly detection, and demand-side management. However, despite the promised energy efficiency by providing appliance specific consumption information feed-backs, the co...
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Inappropriate service migrations can lead to undesirable situations, such as high traffic overhead, long service latency, and service disruption. In this paper, we propose an application-aware migration algorithm (AMA) with prefetching. In AMA, a mobile device sends a service offloading request to the controller. After receiving this request, the c...
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When dealing with traffic big data under the background of Internet of Things (IoT), traffic control under the single-machine computing environment is difficult to adapt to the massive and rapid analysis and decision-making. To tackle this problem, we propose a parallel computing approach of traffic network flow control based on the mechanism of mo...
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Aging-induced degradation imposes a major challenge to the designer when estimating timing guardbands. This problem increases as traditional worst-case corners bring over-pessimism to designers, exacerbating competitive and close-to-the-edge designs. In this work, we present an accurate machine learning approach for aging-aware cell library cha...
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With increasing of data size and development of multi-core computers, asynchronous parallel stochastic optimization algorithms such as KroMagnon have gained significant attention. In this paper, we propose a new Sparse approximation and asynchronous parallel Stochastic Variance Reduced Gradient (SSVRG) method for sparse and high-dimensional machine...
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Motivation: Identifying differentially expressed genes (DEGs) in transcriptome data is a very important task. However, performances of existing DEG methods vary significantly for data sets measured in different conditions and no single statistical or machine learning model for DEG detection perform consistently well for data sets of different trait...
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A significant amount of distributed photovoltaic (PV) generation is invisible to distribution system operators since it is behind the meter on customer premises and not directly monitored by the utility. The generation essentially adds an unknown varying negative demand to the system, which causes additional uncertainty in determining the total loa...
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Deep learning (DL) based diagnosis models have to be trained by large quantities of monitoring data of machines. However, in real-case scenarios, machines operate under the normal condition in most of their life time while faults seldom happen. Therefore, though massive data are accessible, most are data of the normal condition while fault data are...
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Recently, wireless edge networks have realized intelligent operation and management with edge artificial intelligence (AI) techniques (i.e., federated edge learning). However, the trustworthiness and effective incentive mechanisms of federated edge learning (FEL) have not been fully studied. Thus, the current FEL framework will still suffer untrust...
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Next generation wireless systems have witnessed significant R&D attention from academia and industries to enable wide range of applications for connected environment around us. The technical design of next generation wireless systems in terms of relay and transmit power control is very critical due to the ever-reducing size of these sensor enabled ...
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Edge computing promises to facilitate the collaboration of smart sensors at the network edge, in order to satisfying the delay constraints of certain requests, and decreasing the transmission of large-volume sensory data from the edge to the cloud. Generally, the functionalities provided by smart sensors are encapsulated as services, and the satisf...
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With the development of sensor-clouds, the traditional WSN is expanded and the computing capacity is greatly improved. However, there are still challenges to be solved in sensor-clouds, such as how to disseminate codes to all nodes in a fast and energy-saving way. In this paper, an early wake-up ahead (EWA) code dissemination scheme is proposed to ...
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Lightly damping linear dynamic characteristics of a flexure-based stage mainly limit control bandwidth when its piezo-actuating hysteresis is well compensated. In this paper, a novel damped decoupled XY nanopositioning stage embedding graded local resonators (GLRs) is developed and optimized based on the maximization of motion range and first-order...
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Rotor position is essential in control of permanent magnet synchronous motors (PMSMs). In terms of resolution, structural complexity, occupied volume, anti- interference ability, environmental adaptability and cost, embedded magnetic encoder based on linear Halls owns strong competitiveness. When linear Hall sensors are selectively installed at sta...
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Parkinson's disease (PD) is known as an irreversible neurodegenerative disease that mainly affects the patient's motor system. Early classification and regression of PD are essential to slow down this degenerative process from its onset. In this article, a novel adaptive unsupervised feature selection approach is proposed by exploiting manifold lea...
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In this paper, we present an Online Learning Artificial Neural Network (ANN) model that is able to predict the performance of tasks in lower frequency levels and safely optimize real-time embedded systems' power saving operations. The proposed ANN model is supported by feature selection, which provides the most relevant variables to describe shared...
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Feature selection is of great importance to make prediction for process variables in industrial production. An embedded feature selection method, based on relevance vector machines with an approximated marginal likelihood function, is proposed in this study. By setting hierarchical prior distributions over the model weights and the parameters o...
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As a class of context-aware systems, context-aware service recommendation aims to bind high-quality services to users while taking into account their context requirements, including invocation time, location, social profiles, connectivity, and so on. However, current CASR approaches are not scalable with the huge amount of service data (QoS and con...
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Modern enterprises attach much attention to the selection of commercial locations. With the rapid development of urban data and machine learning, we can discover the patterns of human mobility with these data and technology to guide commercial district discovery. In this paper, we propose an unsupervised commercial district discovery framework via ...
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This article presents a comprehensive design methodology to improve the field weakening (FW) operation of low inductance slotless permanent magnet synchronous machines (PMSMs). The proposed concept of using a stator embedded inductor integrated with the torque producing machine windings helps achieve a wide constant power speed range (CPSR) and a d...
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This paper presents a comprehensive analysis of the impact that supplementary power control of an HVDC link has on the electromechanical dynamics of power systems. The presented work addresses an interesting phenomenon that may occur when an HVDC power controller is installed to support frequency stability. In specific cases, a high gain HVDC frequ...
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As a complex nonlinear system, the power system in operation may experience chaotic oscillation which can threaten the stability of the system for unexpected events and uncertain factors. Initially, through considering factors such as the generators, the power system node voltage amplitude and phase angle, this article establishes a fourth-orde...
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Providing sufficient damping over the full frequency range of low-frequency oscillation (LFO) is a challenge in modern power systems. The flexible excitation system with two damping channels, controlled by the power system stabilizer (PSS) and the reactive power damping controller (RPDC), respectively, provides a new way to solve this problem. The ...
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The problem of effective use of Phasor Measurement Units (PMUs) to enhance power systems awareness and security is a topic of key interest. The central question to solve is how to use this new measurements to reconstruct the state of the system. In this paper we provide the first solution to the problem of (globally convergent) state estimation...
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This article proposes a resilient reliable H8 load frequency control (LFC) design for power system involving the external load disturbances, stochastic actuator failures, and randomly occurring gain fluctuations. In this regard, the separate random variables are introduced which characterize the actuator failures and gain fluctuations in an individ...
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This letter investigates parallelism approaches for equation and Jacobian evaluations in power flow calculation. Two levels of parallelism are proposed and analyzed: inter-model parallelism, which evaluates models in parallel, and intra-model parallelism, which evaluates calculations within each model in parallel. Parallelism techniques such as mul...
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The diode bridge rectifier fed asymmetric halfbridge converter (AHBC) is conventionally employed to drive switched reluctance motors (SRMs), which leads to poor grid-side power quality. In the proposed system, a topology made up of a voltage-sourced converter (VSC) and an AHBC is employed to drive the high-speed SRM. Stable SRM operation can be obt...
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Voltage and current waveforms contain the most authentic and granular information on the behaviors of power systems. In recent years, it has become possible to synchronize waveform data measured from different locations. Thus largescale coordinated analyses of multiple waveforms over a wide area are within our reach. This development could unle...
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This paper presents an optimal transient-stability control strategy that modulates the real power injected and absorbed by distributed energy-storage devices. These devices are located at the high-voltage bus of several generators in a synchronous power system. The system is broken into areas based upon groupings of generators. The control stra...
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Power system cascading failures become more time variant and complex because of the increasing network interconnection and higher renewable energy penetration. High computational cost is the main obstacle for a more frequent online cascading failure search, which is essential to improve system security. We propose a more efficient search framework ...
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Accurate and fast event identification in power systems is critical for taking timely controls to avoid instability. In this paper, a synchrophasor measurementbased fast and robust event identification method is proposed considering different penetration levels of renewable energy. A difference Teager-Kaiser energy operator (dTKEO)-based algori...
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This paper proposes to utilize intentional time delays as part of controllers to improve the damping of electromechanical oscillations of power systems. Through stability theory, the control parameter settings for which these delays in Power System Stabilizers (PSSs) improve the small signal stability of a power system are systematically identi...
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Social media is a popular medium for the dissemination of real-time news all over the world. Easy and quick information proliferation is one of the reasons for its popularity. An extensive number of users with different age groups, gender, and societal beliefs are engaged in social media websites. Despite these favorable aspects, a significant disa...
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Graph node embedding aims at learning a vector representation for all nodes given a graph. It is a central problem in many machine learning tasks (e.g., node classification, recommendation, community detection). The key problem in graph node embedding lies in how to define the dependence to neighbors. Existing approaches specify (either explicitly ...
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In this paper, a video service enhancement strategy is investigated under an edge-cloud collaboration framework, where video caching and delivery decisions are made in the cloud and edge respectively. We aim to guarantee the user fairness in terms of video coding rate under statistical delay constraint and edge caching capacity constraint. A hy...
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With the enormous growth of wireless technology, and location acquisition techniques, a huge amount of spatio-temporal traces are being accumulated. This dataset facilitates varied location-aware services and helps to take real-life decisions. Efficiently handling and processing spatio-temporal queries are necessary to respond in real-time. Process...
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Vehicular cloud computing has emerged as a promising solution to fulfill users’ demands on processing computation-intensive applications in modern driving environments. Such applications are commonly represented by graphs consisting of components and edges. However, encouraging vehicles to share resources poses significant challenges owing to users...
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In this work we present a multi-modal machine learning-based system, which we call ACORN, to analyze videos of school classrooms for the Positive Climate (PC) and Negative Climate (NC) dimensions of the CLASS [1] observation protocol that is widely used in educational research. ACORN uses convolutional neural networks to analyze spectral audio feat...
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In this paper, we present an Online Learning Artificial Neural Network (ANN) model that is able to predict the performance of tasks in lower frequency levels and safely optimize real-time embedded systems' power saving operations. The proposed ANN model is supported by feature selection, which provides the most relevant variables to describe shared...
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Extreme learning machine (ELM) is suitable for nonlinear soft sensor development. Yet it faces an over-fitting problem. To overcome it, this work integrates bound optimization theory with Variational Bayesian (VB) inference to derive novel L1 norm-based ELMs. An L1 term is attached to the squared sum cost of prediction errors to formulate an object...
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We investigate the performance of multi-user multiple-antenna downlink systems in which a base station (BS) serves multiple users via a shared wireless medium. In order to fully exploit the spatial diversity while minimizing the passive energy consumed by radio frequency (RF) components, the BS is equipped with M RF chains and N antennas, where M <...
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We develop WiDE, a WiFi-distance estimation based group profiling system using LightGBM. Given the uploaded WiFi information by users, WiDE can automatically learn powerful hidden features from the proposed features for between-person distance estimation, and infer group membership with the estimated distance. For each group, WiDE classifies the mo...
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This paper presents an asset health index (HI) prediction methodology for high voltage transmission overhead lines (OHLs) using supervised machine learning and structured, unambiguous visual inspections. We propose a framework for asset HI predictions to determine the technical condition of individual OHL towers to improve grid reliability in a cos...
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A methodology for automating the identification of single-event transients (SETs) through Ionizing Radiation Effects Spectroscopy (IRES) and machine learning (ML) is provided. IRES enhances the identification of SETs through statistical analysis of waveform behavior, allowing for the capture of subtle circuit dynamics changes.Automated identificati...
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Gallium nitride (GaN) devices have been successfully commercialized due to their superior performance, especially their high-power transformation efficiency. To further reduce the power consumption of these devices, the optimization for the ohmic contacts is attracting more and more attention. In the light of the mature and powerful machine learnin...
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Wide-area protection scheme (WAPS) provides system-wide protection by detecting and mitigating small and large-scale disturbances that are difficult to resolve using local protection schemes. As this protection scheme is evolving from a substation-based distributed remedial action scheme (DRAS) to the control center-based centralized RAS (CRAS), it...
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Cold atmospheric plasmas (CAPs) have shown great promise for medical applications through their synergistic chemical, electrical, and thermal effects, which can induce therapeutic outcomes. However, safe and reproducible plasma treatment of complex biological surfaces poses a major hurdle to the widespread adoption of CAPs for medical applications....
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Millimeter-wave (mmWave) hybrid analog-digital beamforming is a promising approach to satisfy the low-latency constraint in multiple unmanned aerial vehicles (UAVs) systems, which serve as network infrastructure for flexible deployment. However, in highly dynamic multi-UAV environments, analog beam tracking becomes a critical challenge. The ove...
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IP Networks serve a variety of connected network entities (NEs) such as personal computers, servers, mobile devices, virtual machines, hosted containers, etc. The growth in the number of NEs and technical considerations has led to a reality where a single IP address is used by multiple NEs. A typical example is a home router using Network Address T...
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Machine learning is widely used in developing computer-aided diagnosis (CAD) schemes of medical images. However, CAD usually computes large number of image features from the targeted regions, which creates a challenge of how to identify a small and optimal feature vector to build robust machine learning models. In this study, we investigate feasibi...
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This paper presents a recursive feature elimination (RFE) mechanism to select the most informative genes with a least square kernel extreme learning machine (LSKELM) classifier.Describing the generalization ability of LSKELM in a way that is related to small norm of weights, we proposed a ranking criterion to evaluate the importance of genes by the...
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The current global pandemic crisis has unquestionably disrupted the higher education sector, forcing educational institutions to rapidly embrace technology-enhanced learning. However, the COVID-19 containment measures that forced people to work or stay at home, have determined a significant increase in the Internet traffic that puts tremendous pres...
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The synthesis of a metasurface exhibiting a specific set of desired scattering properties is a time-consuming and resource-demanding process, which conventionally relies on many cycles of full-wave simulations.It requires an experienced designer to choose the number of the metallic layers, the scatterer shapes and dimensions, and the type and the t...
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Machine Learning as a Service (MLaaS) allows clients with limited resources to outsource their expensive ML tasks to powerful servers. Despite the huge benefits, current MLaaS solutions still lack strong assurances on: 1) service correctness (i.e., whether the MLaaS works as expected); 2) trustworthy accounting (i.e., whether the bill for the MLaaS...
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Continuous monitoring of anaesthetics infusion is demanded by anaesthesiologists to help in defining personalized dose, hence reducing risks and side effects. We propose the first piece of technology tailored explicitly to close the loop between anaesthesiologist and patient with continuous drug monitoring. Direct detection of drugs is achieved...
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An efficient multilayer machine learning-assisted optimization (ML-MLAO)-based robust design method is proposed for antenna and array applications. Machine learning methods are introduced into multiple layers of the robust design process, including worst-case analysis (WCA), maximum input tolerance hypervolume (MITH) searching, and robust optimizat...
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Dynamic Security Assessment for the future power system is expected to be increasingly complicated with the higher level penetration of renewable energy sources and the widespread deployment of power electronic devices, which drive new dynamic phenomena. As a result, the increasing complexity and the severe computational bottleneck in real time ope...
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We propose a framework to analyze mm-wave baluns directly from physical parameters by adding a dimension of Machine Learning (ML) to existing electromagnetic (EM) methods.From a generalized physical model of mm-wave baluns, we train physical-electrical Machine Learning models that both accurately and quickly compute the electrical parameters of mm-...
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Objectives: Big data analytics can potentially benefit the assessment and management of complex neurological conditions by extracting information that is difficult to identify manually. In this study, we evaluated the performance of commonly used supervised machine learning algorithms in the classification of patients with traumatic brain injury (T...
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Appropriate allocation of system resources is essential for meeting the increased user-traffic demands in the next generation wireless technologies.Traditionally, the system relies on channel state information (CSI) of the users for optimizing the resource allocation, which becomes costly for fast-varying channel conditions.Considering that future ...
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In exercise gaming (exergaming), reward systems are typically based on rules/templates from joint movement patterns. These rules or templates need broad ranges in definitions of correct movement patterns to accommodate varying body shapes and sizes.This can lead to inaccurate rewards and, thus, inefficient exercise, which can be detrimental to prog...
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The communication-based train control (CBTC) system is a typical cyber physical system in urban rail transit.The train-ground communication system is a very important subsystem of the CBTC system and uses the wireless communication protocols to transmit control commands.However, it faces some potential information security risks.To ensure informati...
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Automated Machine Learning (AutoML) systems have been shown to efficiently build good models for new datasets. However, it is often not clear how well they can adapt when the data evolves over time. The main goal of this study is to understand the effect of concept drift on the performance of AutoML methods, and which adaptation strategies can ...
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The deficiency of water all throughout the planet compel us to limit the use of water. Over 75% of new water assets were utilizing for water system reason so productive use of water in water system framework with cutting edge strategy is required. This paper presents a cutting-edge innovation based savvy framework to anticipate the water system nec...
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Real-time forecasting of the financial time-series data is challenging for many machine learning (ML) algorithms. First, many ML models operate offline, where they need a batch of data, which may not be available during training. Besides, due to a fixed architecture of the majority of the offline-based ML models, they suffer to deal with the uncert...
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Stochastic unit commitment is an efficient method for grid operation in the presence of significant uncertainties.An example is an operation during a predicted hurricane with uncertain line out-ages.However, the solution quality comes at the cost of substantial computational burden, which makes its adoption challenging.This paper evaluates some pos...
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Automated Machine Learning (AutoML) has achieved remarkable progress on various tasks, which is attributed to its minimal involvement of manual feature and model designs. However, existing AutoML pipelines only touch parts of the full machine learning pipeline, e.g., Neural Architecture Search or optimizer selection.This leaves potentially importan...
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A significant amount of distributed photovoltaic (PV) generation is invisible to distribution system operators since it is behind the meter on customer premises and not directly monitored by the utility. The generation essentially adds an unknown varying negative demand to the system, which causes additional uncertainty in determining the total loa...
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This work aims to enhance our fundamental understanding of how the measurement setup used to generate training and testing datasets affects the accuracy of the machine learning algorithms that attempt solving electromagnetic inversion problems solely from data. A systematic study is carried out on a one-dimensional semi-inverse electromagnetic prob...
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? Proper training is essential to achieve reliable pattern recognition (PR) based myoelectric control.
? The amount of training is commonly determined by experience.
? The purpose of this study is to provide an offline validation method that makes the offline performance transferable to online control and find the proper amount of training tha...
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Quaternion random neural network trained by extreme learning machine (Q-ELM) becomes attractive for its good learning capability and generalization performance in 3 or 4-dimensional (3/4-D) hypercomplex data learning. But how to determine the optimal network architecture is always challenging in Q-ELM. To this end, a novel error-minimization based ...
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Traffic control optimization is a challenging task for various traffic centers around the world and the majority of existing approaches focus only on developing adaptive methods under normal (recurrent) traffic conditions. Optimizing the control plans when severe incidents occur still remains an open problem, especially when a high number of lanes ...
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? Curriculum learning (CL) is a training strategy that trains a machine learning model from easier data to harder data, which imitates the meaningful learning order in human curricula.
? As an easy-to-use plug-in, the CL strategy has demonstrated its power in improving the generalization capacity and convergence rate of various models in a wide r...
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Multi-task learning technique is widely utilized in machine learning modeling where commonalities and differences across multiple tasks are exploited. However, multiple conflicting objectives often occur in multi-task learning. Conventionally, a common compromise is to minimize the weighted sum of multiple objectives which may be invalid if the obj...
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? Automated Machine Learning (AutoML) seeks to automatically find so-called machine learning pipelines that maximize the prediction performance when being used to train a model on a given dataset. One of the main and yet open challenges in AutoML is an effective use of computational resources: An AutoML process involves the evaluation of many candi...
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Stereo matching is one of the longest-standing problems in computer vision with close to 40 years of studies and research. Throughout the years the paradigm has shifted from local, pixel-level decision to various forms of discrete and continuous optimization to data-driven, learning-based methods. Recently, the rise of machine learning and the rapi...
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? Due to the additive property of most machine learning objective functions, the training can be distributed to multiple machines.
? Distributed machine learning is an efficient way to deal with the rapid growth of data volume at the cost of extra inter-machine communication.
? One common implementation is the parameter server system which cont...
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? This work aims to enhance our fundamental understanding of how the measurement setup used to generate training and testing datasets affects the accuracy of the machine learning algorithms that attempt solving electromagnetic inversion problems solely from data.
? A systematic study is carried out on a one-dimensional semi-inverse electromagneti...
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? Wafer test is carried out after integrated circuits (IC) fabrication to screen out bad dies.
? In addition, the results can be used to identify problems in the fabrication process and improve manufacturing yield.
? However, the wafer test itself may induce defects to otherwise good dies.
? Test-induced defects not only hurt overall manufact...
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Phishing is the act of attempting to acquire information such as usernames, passwords, and credit card details by masquerading as a trust worth entity in an electronic communication there are several different techniques to control phishing, including legislation and technology created specifically to protect against phishing. This project provides...
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Phishing is the act of attempting to acquire information such as usernames, passwords, and credit card details by masquerading as a trust worth entity in an electronic communication there are several different techniques to control phishing, including legislation and technology created specifically to protect against phishing. This project provide...
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Using various sensors like the accelerometer, GPS module, 3 Axis gyroscope, compass and an ultrasonic range finder, the primary guidance and navigation functions of the UAV can be automated. Additional stabilization controls should be programmed into the Raspberry Pi which is serving as the heart of the System which will provide additional security...
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Single phase and three phase induction machines are very popular in the industries because of their vast applications. Hence it becomes necessary to protect them against faults so as to ensure uninterrupted operation and functioning. Various parameter controlling and monitoring systems are present for other types of machine, but in case the of indu...
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Present industry is increasingly shifting towards automation. Two principle components of today’s industrial automations are programmable controllers and robots. In order to aid the tedious work and to serve the mankind, today there is a general tendency to develop an intelligent.
As the name signifies, an embedded system is embedded or builds int...
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Our project proposes a secured ATM (Automated Teller Machine) system using a card scanning system along with LINK system for improved security. Usual ATM systems do not contain the LINK feature for money withdrawal. If an attacker manages to get hold of ATM card and the pin number, he may easily use it to withdraw money fraudulent. So our propose...
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Grass cutter machines have become very popular today. Most of the times grass cutter machines are used for soft grass furnishing. In a time where technology is merging with environmental awareness, consumers are looking for ways to contribute to the relief of their own carbon footprints. Pollution is man-made and can be seen in our own daily lives,...
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The Blind person navigation system can be used in house, hospitals where the blind people are living. The system consists of indoor transmitter section and blind person receiver section. The transmitter section is kept in the indoor and receiver section given to blind person. Whenever the Li-Fi receiver receives the data from transmitter section, i...
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In today’s technically advanced world, autonomous systems are gaining rapid popularity. As the social computerization and automation has been increased and the ATM and credit card has been installed and spread out to simplify the activity for financial activity, the banking activity has been simplified, however the crime related with financial orga...
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The main objective of the project is to implement the “Automatic grinder” which will do all the process of the normal grinder automatically.
Microcontroller is used to control all the process of the grinder.
In automatic grinder there is no need of man power,
the only work is to drop the rice in the grinder, like
washing machine.
Th...
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The main objective of the project is to implement the “Automatic grinder” which will do all the process of the normal grinder automatically.
Microcontroller is used to control all the process of the grinder.
In automatic grinder there is no need of man power,
the only work is to drop the rice in the grinder, like
washing machine.
Th...
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The main objective of the project is to implement the “Automatic grinder” which will do all the process of the normal grinder automatically.
Microcontroller is used to control all the process of the grinder.
In automatic grinder there is no need of man power,
the only work is to drop the rice in the grinder, like
washing machine.
Th...
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Recommender system algorithms are widely used in e-commerce to provide personalized and more accurate recommendations to online users and enhance the sales and user stickiness of e-commerce. This paper discusses several recommendation algorithms and the challenge of tradition recommender system in big data situation, and then proposes a framework o...
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The identification of network attacks which target information and communication systems has been a focus of the research community for years. Network intrusion detection is a complex problem which presents a diverse number of challenges. Many attacks currently remain undetected, while newer ones emerge due to the proliferation of connected devices...
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The recent incorporation of new Data Mining and Machine Learning services within Cloud Computing providers is empowering users with extremely comprehensive data analysis tools including all the advantages of this type of environment. Providers of Cloud Computing services for Data Mining publish the descriptions and definitions in many formats and o...
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The traditional single minimum support data mining algorithm has some problems, such as too much space occupied by data, resulting in insufficient accuracy of the algorithm, which is difficult to meet the needs of the development of the times. Therefore, an intrusion data mining algorithm based on multiple minimum support is proposed. First, the fe...
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Representation learning has been proven to play an important role in the unprecedented success of machine learning models in numerous tasks, such as machine translation, face recognition and recommendation.The majority of existing representation learning approaches often require large amounts of consistent and noise-free labels. However, due to var...
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For the path coverage testing of a Message-Passing Interface (MPI) program, test data generation based on an evolutionary optimization algorithm (EOA) has been widely known. However, during the use of the above technique, it is necessary to evaluate the fitness of each evolutionary individual by executing the program, which is generally computation...
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With the fast development of various positioning techniques such as Global Position System (GPS), mobile devices and remote sensing, spatio -temporal data has become increasingly available nowadays.Mining valuable knowledge from spatio - temporal data is critically important to many real-world applications including human mobility understanding, sm...
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The advancement of several significant technologies, such as artificial intelligence, cyber intelligence, and machine learning, has made big data penetrate not only into the industry and academic field but also our daily life along with a variety of cyber-enabled applications. In this article, we focus on a deep correlation mining method in heterog...
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Matrix factorization (MF), a popular unsupervised learning technique for data representation, has been widely applied in data mining and machine learning.
According to different application scenarios, one can impose different constraintson the factorization to find the desired basis, which captures high-level semantics for the given data, and lea...
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To assess the performance of electrification in an aircraft, multi-physics modeling becomes a good choice for the design of more-electric equipment. The high computational cost and huge design space of this complex model lead to difficulties in the optimal design of the electrical power system, thus, model simplification is mandatory. This paper f...
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The expanding number of road mishaps is because of an expanding populace and a huge number of vehicles on the street. We can't stop mishaps yet we can find a way to forestall it. As indicated by the statistics, an enormous number of individuals lose their life since they don't get legitima...
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Biometric Fingerprint systems are used in the Voting machine for voter confirmation. fingerprint voting machine is designed where there is no need for the user to carry his ID which contains his essential details, so that the controller fetches the data from the fingerprint module and then compares it with already registered fingerprints of the vot...
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Many predictive techniques have been widely applied in clinical decision
Making such as predicting occurrence of a disease or diagnosis, evaluating
Prognosis or outcome of diseases and assisting clinicians to recommend
Treatment of diseases. However, the conventional predictive models or techniques are still not effective enough in capturing the...
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Malaria is one of the deadliest diseases ever exists in this planet. Automated evaluation process can notably decrease the time needed for diagnosis of the disease. This will result in early onset of treatment saving many lives. As it poses a serious global health problem, we approached to develop a model to detect malaria parasite accurately from ...
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Agriculture is a profession of many tedious processes and practices, one of which is the spraying of insecticides in the vineyards. A typical vineyard requires extensive spraying every 4-5 days in the summer and every 3-4 days in the rainy season. The conventional methods are: a person carrying a sprayer and manually actuating a lever to generate p...
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In WSN network there is Cyber Attack occurs are one of the most common and most dangerous attacks among cybercrimes. The aim of these attacks is to steal the information used by individuals and organizations to conduct transactions. Phishing websites contain various hints among their contents and web browser-based information. The purpose of this s...
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Fault tolerance is a major concern to guarantee availability and reliability of critical services as well as application execution. In order to minimize failure impact on the system and application execution, failures should be anticipated and proactively handled. Fault tolerance techniques are used to predict these failures and take an appropriate...
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Ultrasound (US) imaging is used to provide the structural abnormalities like stones, infections and cysts for kidney diagnosis and also produces information about kidney functions.
The goal of this work is to classify the kidney images using US according to relevant features selection. In this work, images of a kidney are classified as abnormal i...
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Multi tool turret head is used to make more operations like drilling, facing, turning; chamfering, grooving etc… are done sequentially. It has proved to be the most versatile method to machining works on the work piece. This machine includes a first functional portion known as the work holder which helps to hold the work piece. This system is provi...
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This project deals with the fabrication of pneumatic mobile crane. The aim of this project work is to acquire practical knowledge in the field of material handling equipment. The project work is concerned with the fabrication of the portable jib crane. This machine is very useful for lifting and transporting heavy jobs up to two tons for all types ...
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A device, usually motor-driven, fitted with an end cutting tool that is rotated with sufficient power either to create a hole or to enlarge an existing hole in a solid material and also known as driller. Tapping is the process of making thread inside the drilled hole. This operation requires less force to operate.
In this project the drilling mach...
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A device, usually motor-driven, fitted with an end cutting tool that is rotated with sufficient power either to create a hole or to enlarge an existing hole in a solid material and also known as driller. Tapping is the process of making thread inside the drilled hole. This operation requires less force to operate.
In this project the drilling mach...
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The recent scientific advances in understanding the hierarchical nature of the lithosphere and its dynamics based on systematic monitoring and evidence of its space-energy similarity at global, regional, and local scales did result the design of reproducible inter mediate term middle-range earthquake prediction technique. The real-time experimental...
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Deep learning (DL) has proved successful in medical imaging and, in the wake of the recent COVID-19 pandemic, some works have started to investigate DL-based solutions for the assisted diagnosis of lung diseases. While existing works focus on CT scans, this paper studies the application of DL techniques for the analysis of lung ultra sono graphy (L...
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Cloud-based data storage service has drawn increasing interests from both academic and industry in the recent years due to its efficient and low cost management. Since it provides services in an open network, it is urgent for service providers to make use of secure data storage and sharing mechanism to ensure data confidentiality and service user p...
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Machine learning (ML) methods has recently contributed very well in the advancement of the prediction models used for energy consumption. Such models highly improve the accuracy, robustness, and precision and the generalization ability of the conventional time series forecasting tools. This article reviews the state of the art of machine learning ...
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Potato is one of the prominent food crops all over the world. In Bangladesh, potato cultivation has been getting remarkable popularity over the last decades. Many diseases affect the proper growth of potato plants. Noticeable diseases are seen in the leaf region of this plant. Two common and popular leaf diseases of the potato plants are Early Blig...
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Cancer is a major threat to the lives of human beings. Around 74% of the people who get affected by cancer lost their lives. But early detection of cancer cells can prevent death rates. CT(Computerized Tomography) is one of the major used for cancer cell identifications by the oncologist. Computer-aided cancer detection plays a major role in the de...
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India is the cultivating country and our country is the biggest maker in agricultural products. So, we have to classify and exchange our agricultural products. Manual arranging is tedious and it requires works. The automatic grading system requires less time for grading of the agricultural products. Image processing technique is helpful in examinat...
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Potato is one of the prominent food crops all over the world. In Bangladesh, potato cultivation has been getting remarkable popularity over the last decades. Many diseases affect the proper growth of potato plants. Noticeable diseases are seen in the leaf region of this plant. Two common and popular leaf diseases of the potato plants are Early Blig...
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Potato is one of the prominent food crops all over the world. In Bangladesh, potato cultivation has been getting remarkable popularity over the last decades. Many diseases affect the proper growth of potato plants. Noticeable diseases are seen in the leaf region of this plant. Two common and popular leaf diseases of the potato plants are Early Blig...
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Air pollution affects human skin in many ways. Skin diseases are common in densely populated regions. These diseases have a devastating impact on people's lives by creating a huge need for the disease diagnosis. The proposed work on skin disease determination system aims for an accurate diagnosis leveraging image processing. The methodology outline...
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Air pollution affects human skin in many ways. Skin diseases are common in densely populated regions. These diseases have a devastating impact on people's lives by creating a huge need for the disease diagnosis. The proposed work on skin disease determination system aims for an accurate diagnosis leveraging image processing. The methodology outline...
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Injuries due to road accidents are one of the most prevalent causes of death apart from health related issues. The World Health Organization states that road traffic injuries caused an estimated 1.35 million deaths worldwide in the year 2016. That is, a person is killed every 25 seconds. This calls for the need to analyse road accidents and the fac...
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Tumour is the undesired mass in the body. Brain tumour is the significant growth of brain cells. Manual method of classifying is time consuming and can be done at selective diagnostic centers only. Brain tumour classification is crucial task to do since treatment is based on different location and size of it. Magnetic Resonance Imaging (MRI) is mos...
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Machine learning techniques have been widely used for abnormality detection in medical images. Chest X-ray images (CXR) are among the non-invasive diagnostic tools used to detect various disease pathologies. The ambiguous anatomical structure of soft tissues is one of the major challenges for segregating normal and abnormal images. The main objecti...
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With the advancementofweb technology and its growth, there is huge volume of data present in the web for internet users and a lot of data is generated too. Internet has become a platform for online learning, exchanging ideasandsharing opinions. Social networkingsiteslike Twitter, Face book, Google are rapidly gaining popularity as they allow people...
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The combination of pervasive edge computing and block chain technologies opens up significant possibilities for Industrial Internet of Things (IIoT) applications, but there are several critical limitations regarding efficient storage and rapid response for large-scale low-delay IIoT scenarios. To address these limitations, we propose a hierarchical...
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Cloud computing systems fail in complex and unexpected ways, due to unexpected combinations of events and interactions between hardware and software components. Fault injection is an effective means to bring out these failures in a controlled environment. However, fault injection experiments produce massive amounts of data, and manually analyzing t...
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The remarkable advances of Machine Learning (ML) have spurred an increasing demand for ML-as-a-Service on public cloud: developers train and publish ML models as online services to provide low-latency inference for dynamic queries. The primary challenge of ML model serving is to meet the response-time Service-Level Objectives (SLOs) of inference wo...
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Rapid growth in numbers of connected devices including sensors, mobile, wearable, and other Internet of Things (IoT) devices, is creating an explosion of data that are moving across the network. To carry out machine learning (ML), IoT data are typically transferred to the cloud or another centralized system for storage and processing; however, this...
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Powered by virtualization, the cloud computing has brought good merits of cost effective and on-demand resource sharing among many users. On the other hand, cloud users face security risks from co-residence attacks when using this virtualized platform. Particularly, a malicious attacker may create side channels to steal data from a target user’s vi...
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Distributed cloud computing environments rely on sophisticated communication and sharing paradigms for ease of access, information processing, and analysis. The challenging characteristic of such cloud computing environments is the concurrency and access as both the service provider and end-user rely on the common sharing platform. In this manuscri...
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Security issues have resulted in severe damage to the cloud computing environment, adversely affecting the healthy and sustainable development of cloud computing. Intrusion detection is one of the technologies for protecting the cloud computing environment from malicious attacks. However, network traffic in the cloud computing environment is charac...
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Cloud firewalls stand as one of the major building blocks of the cloud security framework protecting the Virtual Private Infrastructure against attacks such as the Distributed Denial of Service (DDoS). In order to fully characterize the cloud firewall operation and gain actionable insights on the design of cloud security, performance models for the...
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Cloud Computing has assumed a relevant role in the ICT, profoundly influencing the life-cycle of modern applications in the manner they are designed, developed, deployed and operated. In this paper, we tackle the problem of supporting the design-time analysis of Cloud applications to identify a cost-optimized strategy for allocating components onto...
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Containers are lightweight and provide the potential to reduce more energy consumption of data centers than Virtual Machines (VMs) in container-based clouds. The on-line resource allocation is the most common operation in clouds. However, the on-line Resource Allocation in Container-based clouds (RAC) is new and challenging because of its two-level...
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