Predicting Market Performance Using Machine and Deep Learning Techniques

 Today, forecasting the stock market has been one of the most challenging issues for the ‘‘artificial intelligence’’ AI research community. Stock market investment methods are sophisticated and rely on analyzing massive volumes of data. In recent years, machine-learning techniques have come under increasing scrutiny to assess and improve market pred...

Predicting Market Performance Deep Learning Stock Market Prediction Predicting Economic Trends Forecasting Stock Market Prices

Identification of algorithm from the given dataset using AI/ML Techniques

 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...

Identification of algorithm Classification Algorithm in Machine Learning Artificial intelligence cryptographic algorithms AI/ML

Creating a cyber triage tool to streamline digital forensic investigation

 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...

digital forensic investigation cyber triage tool Digital Forensics Digital Forensics & Incident Response Using a Forensic Triage Tool for Rapid Digital Investigations

Crime rate prediction using machine learning

 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 ...

Resource Allocation Pattern Recognition Real-time Analysis human analysts Crime Rate ML algorithms

Covid-19 outbreak Prediction with the Base of Deep Learning Vgg16

 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...

Deep Learning Covid-19 outbreak

A REVIEW ON MACHINE LEARNING STYLES IN COMPUTER VISION—TECHNIQUES AND FUTURE DIRECTIONS

 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...

MACHINE LEARNING FUTURE DIRECTIONS

INFERENCE OF BRAIN STATES UNDER ANESTHESIA WITH META LEARNING BASED DEEP LEARNING MODELS

 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...

DEPTH SELECTION FOR DEEP RELU NETS IN FEATURE EXTRACTION AND GENERALIZATION

 Deep learning is recognized to be capable of discovering deep features for representation learning and pattern recognition without requiring elegant feature engineering techniques by taking advantage of human ingenuity and prior knowledge. Thus it has triggered enormous research activities in machine learning and pattern recognition. One of the mos...

DEEP LEARNING FEATURE EXTRACTION AND GENERALIZATION

INFERENCE OF BRAIN STATES UNDER ANESTHESIA WITH META LEARNING BASED DEEP LEARNING MODELS

 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...

DEEP LEARNING META LEARNING BASED

COVID-19 prediction using CNN Algorithm

 Deep learning (DL) has proved successful in medical imaging and, in the wake of the recent COVID-19 pandemic, some works have started to investigate DL-based solutions for the assisted diagnosis of lung diseases. While existing works focus on CT scans, this paper studies the application of DL techniques for the analysis of lung ultra sonography (LU...

Low-Power FPGA Design Using Memoization-Based Approximate Computing

 Field-programmable gate arrays (FPGAs) are increasingly used as the computing platform for fast and energyefficient execution of recognition, mining, and search applications. Approximate computing is one promising method for achieving energy efficiency. Compared with most prior works on approximate computing, which target approximate processors and...

A System of Two Coupled Oscillators With a Continuously Controllable Phase Shift

 We present a novel generalization of quadrature oscillators (QVCO) which we call “arbitrary phase oscillator” or APO for short. In contrast to a QVCO which generates only quadrature phases, the APO is capable of continuously generating any desired phase at its output. The proposed structure employs a novel coupling mechanism to generate arbitrary p...

Recognition of Handwritten Digit using Convolutional Neural Network in Python with Tensor flow and Comparison of Performance for Various Hidden Layers

  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...

Gesture control of drone using a motion controller

 In this study, we present our implementation of using a motion controller to control the motion of a drone via simple human gestures. We have used the Leap as the motion controller and the Parrot AR DRONE 2.0 for this implementation. The Parrot AR DRONE is an off the shelf quad rotor having an on board Wi-Fi system. The AR DRONE is connected to the...

DIAGONSTIC PREDICTION AFTER COVID

 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...

Face recognition using eigenfaces

 We tried to develop a real time face detection and recognition system which uses an “appearance-based” approach. For detection purpose we used Viola Jones algorithm. To recognize face we worked with Eigen Faces which is a PCA based algorithm. In a real time to recognize a face we need a data training set. For data training set we took five images o...

Progressive Self-Supervised Clustering With Novel Category Discovery

 These days, clustering is one of the most classical themes to analyze data structures in machine learning and pattern recognition. Recently, the anchor-based graph has been widely adopted to promote the clustering accuracy of plentiful graph-based clustering techniques. In order to achieve more satisfying clustering performance, we propose a novel ...

Multiple Flat Projections for Cross-Manifold Clustering

 Cross-manifold clustering is an extreme challenge learning problem. Since the low-density hypothesis is not satisfied in cross-manifold problems, many traditional clustering methods failed to discover the cross-manifold structures. In this article, we propose multiple flat projections clustering (MFPC) for cross-manifold clustering. In our MFPC, th...

Effective Parallelism for Equation and Jacobian Evaluation in Power Flow Calculation

 This letter investigates parallelism approaches for equation and Jacobian evaluations in power flow calculation. Two levels of parallelism are proposed and analyzed: inter-model parallelism, which evaluates models in parallel, and intra-model parallelism, which evaluates calculations within each model in parallel. Parallelism techniques such as mul...

Synchronized Waveforms a Frontier of Data-Based Power System and Apparatus Monitoring, Protection and Control

  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...

Evaluating User and Machine Learning in Short-and Long-term Pattern Recognition-based Myoelectric Control

  ? 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...

Classification of Kidney Images Using Cuckoo Search Algorithm and Artificial Neural Network

 Ultrasound (US) imaging is used to provide the structural abnormalities like stones, infections and cysts for kidney diagnosis and also produces information about kidney functions. The goal of this work is to classify the kidney images using US according to relevant features selection. In this work, images of a kidney are classified as abnormal i...