Background: Farmers often face challenges in accessing markets, leading to lower income due to middlemen. This gap restricts their ability to sell produce at fair prices. Description: Create a mobile application that connects farmers directly with consumers and retailers.
The app should include features for listing produce, negotiating prices, an...
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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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since 2000, various authorities like parliaments and government offices have introduced electronic petitions systems (e-petitions).
Compared to most other means of petitions made available by public institutions, e-petitions have moved past the test organization and are portrayed by a significant level of institutionalization and procedural devel...
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Nigeria's energy sector is plagued by poor, inadequate and disorganized electricity billing and consumer relations management.
Despite the introduction of prepaid billing meters, electricity billing and collection remains a major challenge in some communities in Nigeria.
Because the electricity consumer must first go to the bank to make the pay...
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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: In metro system OEM install the switches and bind these switches with their MAC address mostly so it is difficult to install or upgrade the different switch in network without compromising the cyber security. Retrofitting these systems with modern security protocols can he challenging and costly, particularly for organizations with limi...
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Background: Use of cryptocurrencies like bitcoin, USDT, Monero etc. for drug trafficking activities are increasingly becoming common. The relative anonymity and speed provided by cryptocurrencies are misused by drug traffickers as a mode of transaction for drug sales and also as an asset to amass the proceeds of crime.
Description: Drug trafficke...
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Background : Digital evidence has become increasingly crucial in forensic investigations. The recovery of deleted data from storage devices is essential for reconstructing timelines, identifying suspects, and uncovering critical information. Traditional file systems like FAT and NTFS have been extensively studied, and tools for recovering deleted d...
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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: 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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To design and develop an innovative digital forensics and incident response tool with an intuitive and accessible interface for investigators, that streamlines the process of importing evidence, conducting automated analysis, and generating detailed reports. The tool should feature an interface with clear navigation & real-time data visualization a...
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Description: Develop an application firewall for end-points that can identity and restrict access of application to external network/hosts. The application firewall should provide further granular control of restricting domains, IP addresses and protocols for each application.
The firewall should be manageable through a centralized web console wh...
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The covid-19 pandemic intensified the deployment of technology in Nigeria, particularly in the realm of public service delivery in Nigeria. While this has brought series of benefits, there are equally some factors undermining the utilisation of the full potential of new technologies.
This study focused on the effects of the deployment of technolo...
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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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Over the years students use manual ways to raise funds to support their election ambitions, help pay less privileged students school dues, sick friends and many other challenges which they face in the school.
To overcome the problems of manual fund raising, the researcher has developed “an Online Campus Fund Raiser System”.
The system which wil...
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Computerized lecture reminder is a tool that permites academic students and lectures to know like due dates and locations.
Lecture reminder has turned to be a very important tool in the time management and it is a common saying in the time management that it is better to keep track of things using a system rather than your memory.
A computerized...
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This application note addresses the design and implementation of a web-based RDBMS menu driven information system to provide the exhaustive information on existing farming systems prevailing in different Agro Climatic Zones in India (14) (29 centres across the country, India) .
information system also recommends the required technological interve...
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this project is to design a Web-based distance learning system, where instructors and students can participate fully in distance learning activities while geographically separated from each other.
This project is aimed to design and implement a distance learning system and use internet as the delivery mode. This report discusses in detail backgr...
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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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Voltage regulation is a main key factor for stable power system. Recent years the electronics equipment growth is rapidly increase. These electronics devices are voltage sensitive devices.
To maintain the grid system voltage equal or near to nominal level, the DVR plays major roll.
The 31 level inverter is proposed in this study to reduce number ...
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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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Online auction is a business model where the items are sold through price bidding. Bidding have the start price and ending time. Potential buyers in the auction and the winner is the one who bids the item for highest price within the stipulated time.
For buying product online user must provide his personal details like email address, contact numb...
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This project was developed in a way that the robot is controlled by voice commands. An android application with a microcontroller is used for required tasks. The connection between the android app and the vehicle is facilitated with Bluetooth technology.
The robot is controlled by buttons on the application or by spoken commands of the user. The ...
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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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Cloud computing technology will bring to banks such advantages as cost savings, enhanced data processing capacity and improved quality of financial services. To further promote the application of cloud computing in the banking industry, the first and foremost task is to solve the security problem.
Judging from the commercial banks, cloud computin...
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Frequently we tend to tend to pay our time interrelate with numerous chatterboxes on the net, mostly targeted at such functions or just amusement. The chatbots have embedded information that helps them acknowledge the user's question and provide an answer to it.
The college enquiry chatbot project is meant exploitation algorithms that interpret ...
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Weather forecasting has been an important application for predicting the weather changes and accordingly organizing human activities to prevent any loss. The Weathercast application notifies the user about the weather conditions like min-max temperature, humidity, windspeed, AQI (Air Quality Index), UVI (Ultraviolet Index) of any particular locatio...
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Mobile wallets have emerged as the most significant contributor in pushing cashless and electronic payments. The surge of smartphones and internet connectivity of 4G and 5G is reflected in the robust growth of Mobile-wallets in India.
Numerous digital wallet providers have risen. Technological advancement has made everything possible under one to...
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With the advancement of technology, it is imperative to exalt all the systems into a user-friendly manner. The Library Management system (LMS) acts as a tool to transform traditional libraries into digital libraries.
In traditional libraries, the students/user has to search for books which are hassle process and there is no proper maintenance of ...
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A software web application based on facial recognition is used to create a gate pass system. During college hours, it coordinates the student's gate pass request and leave. This system is ready for use and is simple to operate and manage.
A gate pass security system is what this system is called. Its main goal is to keep the campus safe from ou...
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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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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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Managing the result sheets using traditional approach is a cumbersome process. The person must maintain the result records in registers and files using pen and paper.
The problem with this approach is, it requires lot of paperwork which is the part of our non-renewable natural resources. We are in the age, where we must think about sustain...
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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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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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The Railway Reservation System (RRS) is a comprehensive software solution designed to facilitate the booking of train tickets for passengers.
With the ever-growing demand for rail travel, an efficient and user-friendly reservation system becomes indispensable for both passengers and railway authorities.
The RRS aims to streamline the ticket boo...
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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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In the ever-changing landscape of digital services and government initiatives, our project embarks on a mission to empower citizens with a revolutionary chatbot known as SchemeSetu.
This intelligent chatbot serves as a central information hub, consolidating crucial details on governmentsponsored loans and insurance schemes from various sources....
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The Flight Reservation System (FRS) is a comprehensive software solution designed to facilitate the booking of Flight tickets for passengers.
With the ever-growing demand for Flight travel, an efficient and user-friendly reservation system becomes indispensable for both passengers and Flight authorities.
The FRS aims to streamline the tic...
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In the ever-changing landscape of digital services and government initiatives, our project embarks on a mission to empower citizens with a revolutionary chatbot known as SchemeSetu.
This intelligent chatbot serves as a central information hub, consolidating crucial details on governmentsponsored loans and insurance schemes from various sources....
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Bus Pass Management System it is the web application that will manage all the records of pass which is issue by bus administrative.
Bus Pass Management System which is a automatic system which delivering data processing in a very high speed in the systematic manner. This system helps bus administrative to keep records of bus passes. Before this...
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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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In this paper, modifications in neoteric architectures such as VGG16, VGG19, ResNet50, and InceptionV3 are proposed for the classification of COVID-19 using chest X-rays.
The proposed architectures termed “COV-DLS” consist of two phases: heading model construction and classification.
The heading model construction phase utilizes four modified d...
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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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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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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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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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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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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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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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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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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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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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? 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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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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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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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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Person re-identification (Re-ID) aims at retrieving a person of interest across multiple non-overlapping cameras. With the advancement of deep neural networks and increasing demand of intelligent video surveillance, it has gained significantly increased interest in the computer vision community. By dissecting the involved components in developing a...
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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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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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Person re-identification (Re-ID) aims at retrieving a person of interest across multiple non-overlapping cameras. With the advancement of deep neural networks and increasing demand of intelligent video surveillance, it has gained significantly increased interest in the computer vision community. By dissecting the involved components in developing a...
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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 ...
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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 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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This paper focuses on changing the system of having ‘text’ as password as people tend to often forget their passwords and have to recover it. Proposing the system of having picture as a password which is kept encrypted in a database and decrypted and matched to check for authorization of user. It has been scientifically proven that it’s easier for ...
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The rapidly growing biofuel industry poses considerable challenges to its supply chain network design and operations. In this chapter, we introduce key characteristics of the biofuel supply chain that comprises of feedstock production, biomass logistics, biofuel production and distribution. We then discuss the recent literature on biofuel supply ch...
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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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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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Under most circumstances, cyber criminals will commit fraudulent transactions using proxy services which hide their real IP address and physical location. This is done in an effort to avoid being tracked and prosecuted by law enforcement agencies. This paper presents the investigation of a proxy detection methodology and efforts to implement such t...
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Blockchain’s foundations of decentralisation, cryptographic security and immutability make it a strong contender in reshaping the healthcare landscape worldwide. Blockchain solutions are currently being explored for: (1) securing patient and provider identities; (2) managing pharmaceutical and medical device supply chains; (3) clinical research and...
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This paper deals with milk processing with emphasis on pasteurization. The heat treatment of milk is important in terms of product quality and health safety. The goal of this paper is determination of heat consumption, inactivation effect and Pasteur criterion, by which pasteurization effectiveness is evaluated. The methodical part contains calcula...
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This study has been undertaken to develop Sustainable Waste Water treatment. Most of the river basins in India and elsewhere are closing or closed and experiencing moderate to severe water shortages, brought on by the simultaneous effects of agricultural growth, industrialization and urbanization. Current and future fresh water demand could be met ...
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The building permission process is to a large extent an analogue process where much information is handled in paper format or as pdf files. With the ongoing digitalisation in society, there is a potential to automate this process by integrating Building Information Models (BIM) of planned buildings and geospatial data to check if a building conform...
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Information security is a vital aspect of Intelligent Transportation Systems (ITS) involving public data collection. Road images captured for use as a basis of traffic manipulation in ITS should take all precautions for encrypting the wirelessly transferred image. This paper presents an Enhanced Cipher Block Chaining (ECBC) operation mode to ensu...
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The term Web 2.0 describes web-based applications such as social networking sites, wikis, and blogs that facilitate collaboration, creativity, and sharing among users. Web 2.0 applications are often enabled by reusing content from other web-based applications or web services. This trend is largely parallel to the principles of service-oriented arch...
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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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One major advantage of cloud/centralized radio access network (C-RAN) is the ease of implementation of multicell coordination mechanisms to improve the system spectrum efficiency (SE). Theoretically, large number of cooperative cells lead to a higher SE, however, it may also cause significant delay due to extra channel state information (CSI) feedb...
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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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The reliability of NAND Flash memory deteriorates due to multi-level cell technique and advanced manufacturing technology. To deal with more errors, LDPC codes show superior performance to conventional BCH codes as ECC of NAND Flash memory systems. However, LDPC codec for NAND Flash memory systems faces problems of high redesign effort, high on-chi...
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This paper introduces a novel low-complexity multiple-input multiple-output (MIMO) detector tailored for single-carrier frequency division-multiple access (SC-FDMA) systems, suitable for efficient hardware implementations. The proposed detector starts with an initial estimate of the transmitted signal based on a minimum mean square error (MMSE) det...
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We propose a low-power Content-Addressable Memory (CAM) employing a new algorithm for associativity between the input tag and the corresponding address of the output data. The proposed architecture is based on a recently developed sparse clustered-network using binary connections that onaverage eliminates most of the parallel comparisons performed ...
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In this paper, we describe a new approach to reduce dynamic power, leakage, and area of application-specified integrated circuits, without sacrificing performance. The approach is based on a design of threshold logic gates (TLGs) and their seamless integration with conventional standard-cell design flow. We first describe a new robust, standard-cel...
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This paper presents a fixed-point reconfigurable parallel VLSI hardware architecture for real-time Electrical Capacitance Tomography (ECT). It is modular and consists of a front-end module which performs precise capacitance measurements in a time multiplexed manner using Capacitance to Digital Converter (CDC) technique. Another FPGA module performs...
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Content-addressable memory (CAM) is the hardware for parallel lookup/search. The parallel search scheme promises a high-speed search operation but at the cost of high power consumption. Parallel NOR- and NAND-type matchline (ML) CAMs are suitable for high-search-speed and low-power-consumption applications, respectively. The NOR-type ML CAM require...
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Ring oscillators (ROs) are popular due to their small area, modest power, wide tuning range, and ease of scaling with process technology. However, their use in many applications is limited due to poor phase noise and jitter performance. Thermal noise and flicker noise contribute jitter that decreases inversely with oscillation frequency. This paper...
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Ternary content-addressable memory (TCAM)-based search engines generally need a priority encoder (PE) to select the highest priority match entry for resolving the multiple match problem due to the don’t care (X) features of TCAM. In contemporary network security, TCAM-based search engines are widely used in regular expression matching across multip...
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With the joint considerations of reliability and performance, hybrid error correction code (ECC) becomes an option in the designs of solid-state drives (SSDs). Unfortunately, wear leveling (WL) might result in the early performance degradation to SSDs, which is common with a limited number of P/E cycles, due to the efforts to delay the bit-error-ra...
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Globalization of microchip fabrication opens the possibility for an attacker to insert hardware Trojans into a chip during the manufacturing process. While most defensive methods focus on detection or prevention, a recent method, called Randomized Encoding of Combinational Logic for Resistance to Data Leakage (RECORD), uses data randomization to pr...
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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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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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Subsequent to the introduction of Bit coin, the field of cryptocurrency has seen unprecedented growth. Mobile applications known as wallets often facilitate user interaction to these crypto currencies. With a perceived real world value these wallets are a target for attackers. Unlike mainstream financial services applications, cryptocurrency wallet...
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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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With the emergence of cloud native technology, the network slicing enables automatic service orchestration, flexible network scheduling and scalable network resource allocation, which profoundly affects the traditional security solution. Security is regarded as a technology independent of the cloud native architecture in the initial design, traditi...
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Nowadays, we are facing security issues in every aspect. So we have to resolve these issues by using updated technology. In this project, we are using the Face recognition module to capture human images and to compare with stored database images. The most important of feature of any home security system is to detect the people who enter or leave th...
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The elementary concept of a multilevel converter is to achieve high power by using a series of a power semiconductor switches with lower voltage D.C source. The output voltage waveform of a multi-level inverter is composed of the number of levels of voltages, typically obtained from capacitor voltage sources. In this paper, single phase diode cl...
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The motivation for this project came from the countries where economy is based on agriculture and the climatic conditions lead to lack of rains & scarcity of water . Irrigation is moreover the backbone of Agricultural industry .Due to inadequate knowledge of proper utilization of water resource, lots of water is wastage in the application of irriga...
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This paper presents the extensions added to the measurement and monitoring tool TestelDroid, to support remote control and instrumentation of Android devices. The extensions include support for Standard Commands for Programmable Instruments (SCPI), cOntrol and Management Framework (OMF) and OMF Measurement Library (OML). SCPI is the most widespread...
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The increasing importance in ubiquitous computing and context-dependent information has led in the last years to a growing interest in location-based applications and services. A considerable market demand concentrates on indoor localization tasks. In this setting, WiFi fingerprinting is currently one of the most popular and widespread techniques a...
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This paper deals with a novel sensor network system designed for gathering disaster information including physical environmental information and potential signals of survivers. The system consists of numerous sensor probes and a central database server. The sensor probes organize their own ZigBee network, which is managed by the central database se...
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In today’s world Automatic system is ubiquitous communication over manual system. The IoT can assist in integration of communications, control, and information processing across various systems. The Internet of Things allows objects to be sensed and controlled remotely. Wireless Home Automation system(WHAS) using I...
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Now a day, technology rapidly growth, but also people do not survive his/her life after road accident because there is no emergency facilities available in our country. So we design a technology which facilitates the emergency facilities. This project inform about an accident that is occurred to vehicle to rescue team and the family members of the ...
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The concept of a Smart City highlights the need to enhance quality, interconnection and performance of various urban services with the use of information and communication technologies (ICT). Smart City technologies promote cloud-based and Internet of Things (IoT) based services in which real-world user interfaces use smart phones, sensors and RFID...
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Many devices and solutions for remote ECG monitoring have been proposed in the literature. These solutions typically have a large marginal cost per added sensor and are not seamlessly integrated with other smart home solutions. Here we propose an ECG remote monitoring system that is dedicated to non-technical users in need of long-term health monit...
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Traditional top-k algorithms, e.g., TA and NRA, have been successfully applied in many areas such as information retrieval, data mining and databases. They are designed to discover k objects, e.g., top-k restaurants, with highest overall scores aggregated from different attributes, e.g., price and location. However, new emerging applications like q...
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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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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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Web Based Career Guidance is very important to our Educational System. We have an existing Manual Career Guidance System with human counselors in charge, but this system is plagued with the following problems: few number of human counselors, unavailability of a counselor in a good number of schools, few number of counselors attending to students du...
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The Test Laboratory Scheduling Problem (TLSP) is a real-world scheduling problem that extends the well-known Resource-Constrained Project Scheduling Problem (RCPSP) by several new constraints. Most importantly, the jobs have to be assembled out of several smaller tasks by the solver, before they can be scheduled. In this paper, we introduce differe...
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For lecturers who are used to presenting face-to-face, facilitating online classes through a virtual classroom interface proposes several new challenges. At the same time the affordances of the media offer many opportunities to improve the quality of students’ learning. This paper outlines the pedagogical lessons derived from convening a first year...
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Aspect-Oriented Programming (AOP) methodology has been investigated in the design and implementation of a representative Event Management System Software. Eclipse-AJDT environment has been used as open source enhanced IDE support for programming in AOP language – AspectJ. Twelve crosscutting concerns have been identified and modularized into highly...
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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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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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Chat applications have become one of the most important and popular applications on smartphones. It has the capability of exchange text messages, images and files which it cost free for the users to communicate with each other. All messages must be protected. The aim of the paper is to propose chat application that provides End-to-End security that...
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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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College is a place where student can learn method of developing their mind in right direction and build their future goals plan and research on them from college time onward they have to find the solutions of the problems they are getting from the real world and work on it. In our work, we have made cloud based college management system were studen...
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Online examination system is a web-based examination system where examinations are given online. either through the internet or intranet using computer system. The main goal of this online examination system is to effectively evaluate the student thoroughly through a totally automated system that not only reduce the required time but also obtain fa...
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Textual passwords are more commonly used in day to day life. They tend to be more vulnerable as far as security is concerned. Users tend to pick short password that are easy to remember which makes the password vulnerable for attackers to break. Furthermore, textual password is vulnerable to hidden camera, shoulder surfing, key loggers, spyware and...
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Multilevel Marketing is a very popular business model in the Western countries. It is a kind of hybrid of the method of distribution of goods and the method of building a sales network. It is one of the safest (Carries a very low risk) ways of conducting a business activity. The knowledge about functioning of this Business model, both among theoret...
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A hostel management system (HOMASY) was designed to provide a computerized process that is stress free, reliable and quick through the use of PHP computer programming language and MySQL database application to both the students and the staff in charge of the registration and hostel management processes. HTML would be at the front-end and provide th...
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Effective utilization of Radio Frequency Identification (RFID) technology between vehicle and base station over a wireless channel to facilitate vehicle maintenance monitoring and vehicle authentication is proposed. This system is able to automatically register the vehicles in highways or gas stations and inform the user about the vehicle maintenan...
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In today’s age, education is the most important way of achieving success. When we discuss education, it is imperative to mention tests and examination. Examinations prepare students in their quest for knowledge. So, having a proper examination paper and format is quite necessary. Now the traditional method of generating question paper has been manu...
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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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Education plays a vital role in human life. To encourage higher education, the Indian government has taken many initiatives. These include the disbursement of scholarships to financially help the students belonging to low-income families. Central Sector Scheme of Scholarship for College and University Students (CSS) is one such scheme that financia...
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This paper introduces a video copy detection system which efficiently matches individual frames and then verifies their spatio-temporal consistency. The approach for matching frames relies on a recent local feature indexing method, which is at the same time robust to significant video transformations and efficient in terms of memory usage and compu...
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B/S structure (Browser/Server) is one hidden client mode after WEB development. This kind of network structure mode unifies WEB browser as the client-side in order to integrate the core part of system function realization to the server. B/S model simplifies system development, maintenance, and usage. The client only needs one Browser under the B/S ...
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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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An organized and systematic office solution is essential for all universities and organizations. There are many departments of administration for the maintenance of college information and student databases in any institution. All these departments provide various records regarding students. Most of these track records need to maintain information ...
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The management and booking of Rooms in hotels is a tedious and complicated task especially if it is done manually. Keeping track of large customers and all their details requires an inordinate space for file cabinets, not to mention the time the hotel administrator would spend going back and forth to file cabinets so as to look up each customer’s i...
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The purpose of this thesis was to show how to use Zend Framework to connect PHP applications to the cloud.To find out how easy it is for developers with basic knowledge of the Zend Framework, to incorporate cloud computing in their applications. In order to do this, a blog application was developed using the Zend Framework and the upload files func...
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The elementary concept of a multilevel converter is to achieve high power by using a series of a power semiconductor switches with lower voltage D.C source. The output voltage waveform of a multi-level inverter is composed of the number of levels of voltages, typically obtained from capacitor voltage sources. In this paper, single phase diode cl...
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A college management registration system empowers colleges and educators to manage regular tasks such as campaigns, student enrolment, admissions, course registration, etc. Registering for courses while taking admission to a college is the most crucial step as it lays the foundation for an entire semester. Providing this information to thousands of...
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Jewellery shops sells various types of Jewellery items and it is very difficult to categorize these items on the basis of their manufacturing dates, type of gold used to manufacture it such as either using 24K or 22K. Which items comes under the category of ISI Gold Mark and which items are of local brand. It is also very difficult to analyze the o...
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To obtain information and knowledge of SNF (Solid not fat), feeding and milking management. System also included the management practices among the dairy farms at various state levels from District to Taluka level for maintaining daily records as well as effective payment system through digital transactions. This system recurring to information of ...
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Sales management is a key function which helps small and medium size enterprises (SMEs) in monitoring and tracking stock and co-ordinating transaction processing. The efficiency of sales management dependends on effective tools and facilities, especially mordern information and communication technologies. Despite this, majority of businesses in dev...
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This paper deals with development of inventory management system for a manufacturing Industry. The developed software System is easy to use, less time consuming & all detail about the inventory items & transaction status. Enterprise Resource Planning (ERP) software presents a frame work for organizations to better utilize their processes. The repor...
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Broadcasting is an essential operation for the source node to disseminate the message to all other nodes in the network. Unfortunately, the problem of Minimum Latency Broadcast Scheduling (MLBS) in duty-cycled wireless networks is not well studied. In existing works, the construction of broadcast tree and the scheduling of transmissions are conduct...
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This paper considers wireless link scheduling in a new setting: nodes with Energy Harvesting (EH) as well as energy sharing capabilities. We propose a Mixed Integer Linear Program (MILP) to determine 1) the shortest link schedule, whereby active links in the same slot adhere to the physical interference model; 2) the optimal transmission power of a...
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A novel carrier sense multiple access strategy with collision avoidance (CSMA/CA) balancing contention probability and channel access time is proposed. The approach can be applied to any context where the computational simplicity of the MAC must be preferred to the complexity of the channel access strategy. Our MAC, called Delay-Collision CSMA (DC-...
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As the core count in shared-memory manycores keeps increasing, it is becoming increasingly harder to design cache-coherence protocols that deliver high performance without an inordinate increase in complexity and cost. In particular, sharing patterns where a group of cores frequently reads and writes a shared variable are hard to support efficientl...
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In this paper, we consider a wireless-powered communication network (WPCN) where one mobile hybrid access point (HAP) coordinates the wireless energy transfer to sensor nodes and receives data from sensor nodes, which are powered exclusively by the harvested wireless energy. As the harvest-then-transmit protocol is employed by sensor nodes, a major...
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Intelligent reflecting surface (IRS) is a new and promising paradigm to substantially improve the spectral and energy efficiency of wireless networks, by constructing favorable communication channels via tuning massive low-cost passive reflecting elements. Despite recent advances in the link-level performance optimization for various IRS-aided wire...
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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 investigates a futuristic spectrum sharing paradigm for heterogeneous wireless networks with imperfect channels. In the heterogeneous networks, multiple wireless networks adopt different medium access control (MAC) protocols to share a common wireless spectrum and each network is unaware of the MACs of others. This paper aims to design a...
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Traditional ground wireless communication networks cannot provide high-quality services for artificial intelligence (AI) applications such as intelligent transportation systems (ITS) due to deployment, coverage and capacity issues. The space-air-ground integrated network (SAGIN) has become a research focus in the industry. Compared with traditional...
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Radio access network (RAN) slicing is a virtualization technology that partitions radio resources into multiple autonomous virtual networks. Since RAN slicing can be tailored to provide diverse performance requirements, it will be pivotal to achieve the high-throughput and low-latency communications that next-generation (5G) systems have long yearn...
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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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Due to resource constraints and working surroundings, many IIoT nodes are easily hacked and turn into zombies from which to launch attacks. It is challenging to detect such networked zombies. We combine federated learning (FL) and fog/edge computing to combat malicious codes. Our protocol trains a global optimized model based on distributed dataset...
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The dual mode technology has been adopted to support smart devices to connect to both the NB-IoT and the LTE simultaneously. How to reduce the power consumption of a smart device with limited battery capacity has been treated as an important issue. In this paper, we propose the Module Switching Mechanism (MSM) that consists of the PS scheme and the...
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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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For most Internet-of-Things (IoT) applications, embedded processors typically execute lightweight tasks such as sensing and communication. The typical IoT program senses some information and sends them via a channel, usually a wireless channel with an RF circuit. These IoT nodes often require a system with networking capabilities and a low-power ha...
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Deploying a mobile edge computing (MEC) server in the mobile blockchain-enabled Internet of things (IoT) system is a promising approach to improve the system performance, however, it imposes a significant challenge on the trust of the MEC server. To address this problem, we first propose an untrusted MEC proof of work (PoW) scheme in mobile blockch...
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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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The Software Defined Network in Internet of Things (SDN-IoT) is enjoying growing popularity due to its flexibility, automaticity and programmability. However, there still lack proper permission management on SDN-IoT applications (SIApps), especially when the SIApp’s required northbound interfaces are located in multiple heterogeneous controllers wi...
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The Internet of Things (IoT) edge network has connected lots of heterogeneous smart devices, thanks to unmanned aerial vehicles (UAVs) and their groundbreaking emerging applications. Limited computational capacity and energy availability have been major factors hindering the performance of edge user equipment (UE) and IoT devices in IoT edge networ...
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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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Cloud storage services allow data owners to outsource their potentially sensitive data (e.g., private genome data) to remote cloud servers in a ciphertext form. To enable data owners to further share the data encrypted in ciphertexts, many proxy re-encryption (PRE) schemes are proposed. However, most schemes only support single-recipient or coarse-...
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The instance price in the Amazon EC2 spot model is often much lower than in the on-demand counterpart. However, this price reduction comes with a decrease in the availability guarantees. To our knowledge, there is no work that accurately captures the short-term trade-off between spot price and availability, and does long-term analysis for spot pric...
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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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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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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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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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When a multiobjective evolutionary algorithm based on decomposition (MOEA/D) is applied to solve problems with discontinuous Pareto front (PF), a set of evenly distributed weight vectors may lead to many solutions assembling in boundaries of the discontinuous PF. To overcome this limitation, this article proposes a mechanism of resetting weight vec...
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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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Concept drift refers to changes in the underlying data distribution of data streams over time. A well-trained model will be outdated if concept drift occurs. Once concept drift is detected, it is necessary to understand where the drift occurs to support the drift adaptation strategy and effectively update the outdated models. This process, called d...
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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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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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Andriod malware poses a serious threat to users privacy, money, equipment and file integrity. A series of data-driven malware detection methods were proposed. However, there exist two key challenges for these methods: (1) how to learn effective feature representation from raw data; (2) how to reduce the dependence on the prior knowledge or human la...
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The increasing demand for wireless connectivity and the emergence of the notion of the Internet of Everything require new communication paradigms that will ultimately enable a plethora of new applications and new disruptive technologies. In this context, the present contribution investigates the use of the recently introduced intelligent reflecting...
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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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A sharded blockchain with the Proof-of-Stake (PoS) consensus protocol has advantages in increasing throughput and reducing energy consumption, enabling the resource-limited participants to manage transactions and in a decentralized way and obtain rewards at a lower cost, e.g., Internet-of-Things (IoT) users. However, the latest PoS (e.g., Casper) r...
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With the development of the Internet of Things, trust has become a limited factor in the integration of heterogeneous IoT networks. In this regard, we use the combination of blockchain technology and SDN/NFV to build a heterogeneous IoT network resource management model based on the consortium chain. In order to solve the efficiency problem caused ...
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Satisfying the software requirements of emerging service-based Internet of Things (IoT) applications has become challenging for cloud-centric architectures, as applications demand fast response times and availability of computational resources closer to end-users. As such, meeting application demands must occur at runtime, facing uncertainty and in...
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The Internet of Things (IoT) is an emerging paradigm and has penetrated deeply into our daily life. Due to the seamless connections of the IoT devices with the physical world through the Internet, the IoT applications use the cloud to store and provide ubiquitous access to collected data. Sharing of data with third party services and other users in...
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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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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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In this paper, we propose and study an energy-efficient trajectory optimization scheme for unmanned aerial vehicle (UAV) assisted Internet of Things (IoT) networks. In such networks, a single UAV is powered by both solar energy and charging stations (CSs), resulting in sustainable communication services, while avoiding energy outage. In particular,...
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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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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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Robust road boundary extraction and completion play an important role in providing guidance to all road users and supporting high-definition (HD) maps. The significant challenges remain in remarkable and accurate road boundary recovery from poor road boundary conditions. This paper presents a novel deep learning framework, named BoundaryNet, to ext...
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Point clouds are the most general data representations of real and abstract objects, and have a wide variety of applications in many science and engineering fields. Point clouds also provide the most scalable multi-resolution composition for geometric structures. Although point cloud learning has shown remarkable results in shape estimation and sem...
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Most ground-based remote sensing cloud classification methods focus on learning representation features for cloud images while ignoring the correlations among cloud images. Recently, graph convolutional network (GCN) is applied to provide the correlations for ground-based remote sensing cloud classification, in which the graph convolutional layer a...
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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 computing is considered as one of the most prominent paradigms in the information technology industry, since it can significantly reduce the costs of hardware and software resources in computing infrastructure. At the first sight, by merely storing the shared data as plaintext in the cloud storage and protect them using an appropriate access ...
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Most UAVs depend on realtime 3D point clouds to navigate through unknown environments. However, both point clouds processing and trajectory planning are computationally expensive and will deplete UAV's battery quickly. There are also inevitable uncertainties in point clouds, which further makes collision-free trajectory planning a very challenging ...
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With the emergence of cloud native technology, the network slicing enables automatic service orchestration, flexible network scheduling and scalable network resource allocation, which profoundly affects the traditional security solution. Security is regarded as a technology independent of the cloud native architecture in the initial design, traditi...
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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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In recent years, the investigations on Cyber-Physical Systems~(CPS) have become increasingly popular in both academia and industry. A primary obstruction against the booming deployment of CPS applications lies in how to process and manage large amounts of generated data for decision making. To tackle this predicament, researchers advocate the idea ...
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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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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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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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Nowadays transceiver-free (also referred to as device-free) localization using Received Signal Strength (RSS) is a hot topic for researchers due to its widespread applicability. However, RSS is easily affected by the indoor environment, resulting in a dense deployment of reference nodes. Some hybrid systems have already been proposed to help RSS lo...
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The excessive use of nodes and communication links in a wireless control system (WCS) causes unnecessary utilization of resources. In this article, a strategic topological formation is studied for a WCS, where a previously proposed topology consisting of a plant system, a controller system, and an intermediate network system is further developed. M...
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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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Intelligent reflecting surface (IRS) is an enabling technology to engineer the radio signal propagation in wireless networks. By smartly tuning the signal reflection via a large number of low-cost passive reflecting elements, IRS is capable of dynamically altering wireless channels to enhance the communication performance. It is thus expected that ...
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With advances in wireless power transfer techniques, Battery-Free Wireless Sensor Networks (BF-WSNs) which can support long-term applications, has been attracting increasing interests in recent years. Unfortunately, the problem of Minimum Latency Aggregation Scheduling (MLAS) is not well studied in BF-WSNs. Existing works always have a rigid assump...
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This article presents a new approach to designing the Frobenius norm-based weighted unbiased finite impulse response (FIR) fusion filter for wireless sensor networks. The weighted Frobenius norm is employed as a cost function to design a local unbiased FIR filter. The design problem is converted into a constrained optimization problem subject to an...
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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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In real-world scenarios, a user's interactions with items could be formalized as a behavior sequence, indicating his/her dynamic and evolutionary preferences. To this end, a series of recent efforts in recommender systems aim at improving recommendation performance by considering the sequential information. However, impacts of sequential behavior o...
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Modern mobile OSes support to display Web pages in the native apps, which we call embedded Web pages. In this paper, we conduct, to the best of our knowledge, the first measurement study on browsing embedded Web pages on Android. Our study on 22,521 popular Android apps shows that 57.9% and 73.8% of apps embed Web pages on two popular app markets: ...
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Graph-based learning in semisupervised models provides an effective tool for modeling big data sets in high-dimensional spaces. It has been useful for propagating a small set of initial labels to a large set of unlabeled data. Thus, it meets the requirements of many emerging applications. However, in real-world applications, the scarcity of labeled...
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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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Resilient distributed coordination control is studied on multiarea power systems with low inertia under hybrid attacks, including denial-of-service (DoS) attack and deception attack. The communication among various areas under the DoS attack is deteriorated to switching residual topologies whose time characteristic is modeled by model-dependent ave...
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Multi-voltage domains are urgently needed in modern SoCs, while existing solutions such as switched DC-DC converter, switched capacitor converter and low-dropout regulator (LDO) do not generate multi-voltage domains conveniently and inexpensively. This paper presents a highly-efficient fully-integrated power management strategy to provide the ...
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With the introduction of massive renewable energy sources and storage devices, the traditional process of grid operation must be improved in order to be safe, reliable, fast responsive and cost efficient, and in this regard power flow solvers are indispensable. In this paper, we introduce an Interior Point-based (IP) Multi-Period AC Optimal Pow...
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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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Recently, several convex relaxations have been successfully applied to solve the AC optimal power flow (OPF) problem, which has caught the attention of the research community. Among these relaxations, a relaxation based on semidefinite programming (SDP) stands out. Accordingly, in this work a methodology to solve the optimal reactive power dispatch...
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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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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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Querying and reporting from large volumes of structured, semi-structured, and unstructured data often requires some flexibility. This flexibility provided by fuzzy sets allows for categorization of the surrounding world in a flexible, human mind-like manner. Apache Hive is a data warehousing framework working on top of the Hadoop platform for Big D...
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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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The development of vehicular Internet of Things (IoT) applications, such as E-Transport, Augmented Reality, and Virtual Reality are growing progressively. The mobility aware services and network-based security are fundamental requirements of these applications. However, multiside offloading enabling blockchain and cost-efficient scheduling in heter...
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Robust road boundary extraction and completion play an important role in providing guidance to all road users and supporting high-definition (HD) maps. The significant challenges remain in remarkable and accurate road boundary recovery from poor road boundary conditions. This paper presents a novel deep learning framework, named BoundaryNet, to...
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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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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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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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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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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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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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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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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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? 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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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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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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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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ALTEC defined and developed a framework with the main aim to process a big amount of data allowing a seamless connection between the collected information and the analyses performed by end users.This is the ASDP environment, that allows to organize data in the most adapt domain data store in order to have data ready for complex analyses. In particu...
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So far, there is no literature to evaluate the fault level of sensitive equipment(FLSE) caused by voltage sag from the perspective of the power grid. In practice, although the FLSE are dominated by the voltage sag of node, the voltage sag of the node is associated with whole power grid, including the voltage grade and location of the node, the di...
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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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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 Soil Moisture and Ocean Salinity (SMOS) andSoil Moisture Active Passive (SMAP) missions provide Level-1brightness temperature (Tb) observations that are used for global soil moisture estimation.The nature of these Tb data differs: the SMOS Tb observations contain atmospheric and select reflected extraterrestrial (“Sky”) radiation, whereas the S...
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Experience mining is considered a substantial extension of opinion mining. Experience mining covers the description of all events that are related to the user's perception in the interaction with the object.
There is information about the user`s experience that cannot be obtained with polarity analysis or sentiment analysis. The information obtai...
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The Vehicle-to-Grid (V2G) network is, where the battery-powered vehicles provide energy to the power grid, is highly emerging. A robust, scalable, and cost-optimal mechanism that can support the increasing number of transactions in a V2Gnetwork is required.
Existing studies use traditional block chain as to achieve this requirement. Block chain-en...
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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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In this paper, the concept o 2-Layer routing for wireless 5G networks is presented. New fifth generations of the network along with the platform known asthe Internet of Things (IoT) are an upcoming trend not only in the commercial market but also in the research area. The 5G networks and IoT will be part of smart homes, smart cities and every aspec...
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To keep pace with the developments in medical informatics, health medical data is being collected continually. But, owing to the diversity of its categories and sources, medical data has become so complicated in many hospitals needs a clinical decision support (CDS) system for its management. To effectively utilize the accumulating health data, we ...
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For the emerging mobility-on-demand services, it is of great significance for predicting passenger demands based on historical mobility trips to achieve better vehicle distribution. Prior works have focused on predicting next-step passenger demands at selected locations or hotspots. However, we argue that multi-step citywide passenger demands encap...
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Hostel Management is an application developed to manage the various activities in hostel. The particular project is deal with the problems on managing the a hostel and avoids the problem occurs when carried out manually. Identification of the drawbacks of the existing system leads to the designing of computerized system that will be compatible t...
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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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With the rapid development of communication technology in recent years, Wireless Sensor Network (WSN) has become a promising research project. WSN is widely applied in a number of fields such as military, environmental monitoring, space exploration and so on. The non-line-of-sight (NLOS) localization is one of the most essential techniques for WSN....
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This paper presents a technique for detection of kidney stones through different steps of image processing. The first step is the image pre-processing using filters in which image gets smoothed as well as the noise is removed from the image. Image enhancement is a part of preprocessing which is used to enhance the image which is achieved with power...
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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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The ubiquitous adoption of Internet-of-Things (IoT) based applications has resulted in the emergence of the Fog computing paradigm, which allows seamlessly harnessing both mobile-edge and cloud resources. Efficient scheduling of application tasks in such environments is challenging due to constrained resource capabilities, mobility factors in IoT, ...
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This paper presents a technique for detection of kidney stones through different steps of image processing. The first step is the image pre-processing using filters in which image gets smoothed as well as the noise is removed from the image. Image enhancement is a part of preprocessing which is used to enhance the image which is achieved with power...
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