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Data query comparison of large data should process a large number of datasets, which is the core for basic research projects. In the selection of analysis factors, how to choose a better way to provide data analysis library can be very helpful for quickly analysis and search comparison. In this study, we try to design and study, improve the speed of data query and comparison in big datasets, and find...
In current years, the binate codify of facial features, being local binary patterns (LBP) and local ternary patterns (LTP) has grown into face recognition. Those confined facet descriptors subsidize a smooth and influential way for texture description. With this, we conclude an innovative process, LTP with Genetic Algorithm to extricate feature vector and segregated features through Support Vector...
In this article, we present an application of metaheuristics optimization approaches to improve medical classifier performance. Genetic Algorithm (GA), Simulated Annealing (SA) and Particle Swarm Optimization (PSO) have been applied in conjunction with Least Square Support Vector Machine (LS-SVM) approach to optimize the total misclassification error in term of False Positive and False Negative rates...
The feature subset selection, along with the parameters of classifier significantly influences the classification accuracy. In order to ensure the optimal classification performance, the artificial bee colony (ABC) algorithm is proposed to simultaneously optimize the feature subset and the parameters of support vector machines (SVM), meanwhile for improving the optimizing performance of ABC algorithm,...
To diagnose and classify the dysarthric speech, speech language pathologist (SLP) conducts a listening test. On the basis of the scores given by listeners the dysarthria is diagnosed and assessed. The above mentioned method is costly, time consuming and not very accurate. Unlike the traditional method, this research proposes an automatic diagnosis and assessment of dysarthria. The aim of this paper...
Analyzing cardiovascular activity under abnormal heart beat is an intricate and vital job to the medical experts and complicated to novice persons. Electrocardiogram is a way to measure or diagnose abnormal heart rhythms to spot heart disease in human beings. These streaming medical signals can be well analyzed or diagnosed only with the prior knowledge. This paper deals with ECG signal analysis based...
Specific crime in the banking system is credit card fraud. Credit card usage has been increased due to the rapid growth of E-commerce techniques. Credit card fraud also increased at the same time. Prevention is better than detection. So the existing system prevented the credit card fraud by identifying fraud in the application of the Credit card. Due to the limitation of the existing system, this...
Cardiac arrhythmia is one of the most important indicators of heart disease. Premature ventricular contractions (PVCs) are a common form of cardiac arrhythmia caused by ectopic heartbeats. The detection of PVCs by means of ECG (electrocardiogram) signals is important for the prediction of possible heart failure. This study focuses on the classification of PVC heartbeats from ECG signals and, in particular,...
Regarding to the impress of speech in community relations establishment and the effect of the larynx in speech, correct and timely diagnosis of diseases of vocal cords have particular importance. Since the Conventional methods for diagnosis of vocal cords are usually slow, expensive and annoying, so the purpose of this paper is to analysis and classify of vocal fold disorders with the help of audio...
the objective to develop clinical decision support system (CDSS) tools is to help physicians making faster and more reliable clinical decisions. The first step in their development is choose a machine learning classifier as the system core. Previous works reported implementation of artificial neural networks, support vector machines, genetic algorithms, etc. as core classifiers for CDSS; however,...
In order to enhance the accuracy rate of video classification, this article proposes a support SVM classification of using genetic algorithm to optimize features weighting (GA-SVM). First, this article extracts the colors and textural features of video, then adopts improved genetic algorithm to determine features weighting, and at last uses support SVM to establish video classifier and implements...
In some practical classification problems in which the number of instances of a particular class is much lower/higher than the instances of the other classes, one commonly adopted strategy is to train the classifier over a small, balanced portion of the training data set. Although straightforward, this procedure may discard instances that could be important for the better discrimination of the classes,...
Feature selection is considered an important step for gait pattern recognition. The task of a gait classifier could be simplified by eliminating redundant and irrelevant attributes for classification. With that, the size of the feature set could be reduced and subsequently a more comprehensible analysis of the extracted patterns could be carried out. In this paper, we present a feature selection method...
Proteins are macromolecules that have a high molecular weight, and make up, along with water, most of the composition of cells. The functions they perform are extremely important, such as the catalysis of biochemical reactions, cytoskeleton formation, and the transportation and storage of substances. With the completion of genome sequencing, protein discovery has been growing exponentially, and the...
Face Recognition is among the most widely studied problems in computer vision and Pattern Recognition. Face has many advantages like permanence, accessibility and universality. It is still now not solved in literature. Several approaches are proposed to overcome with problems including; changing posed, emotional states, and illumination variation, etc. Geometric approaches which used as example distance...
Correct detection and classification of ventricular fibrillation (VF) and rapid ventricular tachycardia (VT) is of pivotal importance for an automatic external defibrillator and patient monitoring. In this paper, a VF/VT classification algorithm using a machine learning method, a support vector machine, is proposed. A total of 14 metrics were extracted from a specific window length of the electrocardiogram...
This paper proposes the application of a new binary particle swarm optimization (BPSO) method to feature selection problems. Two enhanced versions of binary particle swarm optimization, designed to cope with premature convergence of the BPSO algorithm, are proposed. These methods control the swarm variability using the velocity and the similarity between best swarm solutions. The proposed PSO methods...
This paper presents the results achieved by fault classifier ensembles based on supervised learning for diagnosing faults on oil rigs motor pumps. The main goal is to apply two feature-based ensemble construction methods to a real-world problem. Recent studies have shown that the use of ensembles of classifiers that are accurate and at the same time have diversifying results can improve the final...
This paper presents the results achieved by fault classifier ensembles based on a model-free supervised learning approach for diagnosing faults on oil rigs motor pumps. The main goal is to compare two feature-based ensemble construction methods, and present a third variation from one of them. The use of ensembles instead of single classifier systems has been widely applied in classification problems...
With the development of internet, network is playing an increasingly important part in people's lives, but it is bringing a variety of problems, especially computer security, which has become a serious practical trouble now days. Security audit system is an essential component of computer security mechanisms underlying the firewall and intrusion detection system for computer security. Due to the fact...
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