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Feature selection method applied on an intrusion dataset is used to classify the intrusion data as normal or intrusive. We have made an attempt to detect and classify the intrusion data using rank-based feature selection classifiers. A set of redundant features having null rank value are eliminated then the performance evaluation using various feature selection…

Brain tumor is such an abnormality of brain tissue that causes brain hemorrhage. Therefore, apposite detections of brain tumor, its size, and position are the foremost condition for the remedy. To obtain better performance in brain tumor and its stages detection as well as its position in MRI images, this research work proposes an advanced…

Discretization is the process of converting numerical values into categorical values. Contemporary literature study reveals that there are many techniques available for numerical data discretization. The performance of classification method is dependent on the exploitation of the data discretizing method. In this article, we investigate the effect of discretization methods on the performance of associative…

The proliferation of internet economies has given the corporate world manifold advantages to businesses, as they can now incorporate the latest innovations into their operations, thereby enhancing ease of doing business. For instance, financial institutions have leveraged credit card usage on the aforesaid proliferation. However, this exposes clients to cybercrime, as fraudsters always find ways…

Mental stress assessment remains riddled with biases caused by subjective reports and individual differences across societal backgrounds. To objectively determine the presence or absence of mental stress, there is a need to move away from the traditional subjective methods of self-report questionnaires and interviews. Previously, it has been evidence that EEG Oscillations can discriminate mental…

This paper extends the idea of creating a Quantum Machine Learning classifier and applying it to real weather data from the weather station behind the Pa Sak Jonlasit Dam. A systematic study of classical features and optimizers with different iterations of parametrized circuits is presented. The study of the weather behind the dam is based…

Aging is considered to be a complex process in almost every species’ life, which can be studied at a variety of levels of abstraction as well as in different organs. Not surprisingly, biometric characteristics from facial images play a significant role in predicting human’s age. Specifically, automatic age estimation in real-time situation has begun to…

Emotion is the most important component of being human, and very essential for everyday activities, such as the interaction between people, decision making, and learning. In order to adapt to the COVID-19 pandemic situation, most of the academic institutions relied on online video conferencing platforms to continue educational activities. Due to low bandwidth in many…

With the development of Internet of Things technology and the widespread use of smart devices, artificial intelligence is now being applied as a decision-making tool in a variety of fields. To make machine learning models, including deep neural network models, more interpretable, various techniques have been proposed. In this paper, a method for explaining the…

Data mined from social media can be used in a variety of methods. The goal of this paper is to explore some of the various methods of mining data from social media and the different areas of its applications. From the analysis of other studies, it was clear that methods such as text analysis, classification,…

A methodology of medical signal-based biometrics has been proposed in this paper for implementing a human identification system controlled by electroencephalogram in respect of different color stimuli. The advantage of biosignal based biometrics is that they provide more efficient operation in simple experimental condition to ensure accurate identification. Red, Green, Blue (primary colors) and Yellow…

Face Recognition (FR) is considered as a heavily studied topic in computer vision field. The capability to automatically identify and authenticate human’s faces using real-time images is an important aspect in surveillance, security, and other related domains. There are separate applications that help in identifying individuals at specific locations which help in detecting intruders. The…

Brain-computer interface (BCI) has extensively been used for rehabilitation purposes. Being in the research phase, the brainwave based wheelchair controlled systems suffer from several limitations, e.g., lack of focus on mental activity, complexity in neural behavior in different conditions, and lower accuracy. Being sensitive to the color stimuli, the EEG signal changes promises a better…

Addiction such as tobacco smoking affects the human brain and thus causes significant changes in the brainwaves. The changes in brain wave due to smoking can be identified by focusing on changes in electroencephalogram pattern, extracting different time-frequency domain features. In this aspect, a laboratory-based study has been presented in this paper, for assessing the…

The dramatic growth of social media during the last years has been associated with the emergence of a new bullying types. Platforms such as Facebook, Twitter, YouTube, and others are now privileged ways to disseminate all kinds of information. Indeed, communicating through social media without revealing the real identity has emerged an ideal atmosphere for…

Modulation type classification is a part of waveform estimation required to employ spectrum sharing scenarios like dynamic spectrum access that allow more efficient spectrum utilization. In this work multiple classification features, feature extraction, and classification algorithms for modulation type classification have been studied and compared in terms of classification speed and accuracy to suggest the…

Enrolment figures have been expanding in South African institutions of higher-learning, however, the expansion has not been accompanied by a proportional increase in the percent- age of enrolled learners completing their degrees. In a recent undergraduate-cohort-studies report, the DHET highlight the low percentage of students completing their degrees in the allotted time, having remained between…

The growing popularity of social media sites has generated a massive amount of data that attracted researchers, decision-makers, and companies to investigate people’s opinions and thoughts in various fields. Sentiment analysis is considered an emerging topic recently. Decision-makers, companies, and service providers as well-considered sentiment analysis as a valuable tool for improvement. This research paper…

One of the open domain challenges for Spoken Dialogue System (SDS) is to maintain a natural conversation for rarely visited domain i.e. domain with fewer data. Spoken Language Understanding (SLU) is a component of SDS that converts user utterance into a semantic form that a computer can understand. If we scale SDS open domain challenge…

In this paper we propose the application of supervised learning techniques to recognize stress situations in drivers by analyzing their Skin Potential Response (SPR) and the Electrocardiogram (ECG). A sensing device is used to acquire the SPR from both hands of the drivers, and the ECG from their chest. We also consider a motion artifact…

Several challenges like changes in brightness, dynamic background, occlusion and inconsistency of camera position make the recognition of hand gestures difficult in any vision-based method. Diversity in finger shape, size, distribution and motion dynamics is also a big constraint. This leads to the motivation in developing a dense Scale Invariant Feature Transform (SIFT) flow based…

Due to high failure rates many students end up spending unnecessary years struggling to qualify and subsequently accumulate unnecessary debt. In this paper, our principal contribution is to provide an expert system that statistically predicts the success of a first year student in an undergraduate Science programme given only academic merit in their subject matter.…

The ability to verify the critical risk factors related to an effective diagnosis is very crucial for improving accuracy on coronary heart disease prediction. The objective of this research is to find the best predictive model for coronary heart disease diagnosis. Three approaches are set up to achieve the goals (1) investigating the classifier algorithms…

Application in the field of medical development has always been one of the most important research areas. One of these medical applications is the early prediction system for heart diseases especially; coronary artery disease (CAD) also called atherosclerosis. The need for a medical diagnosis support system is to detect atherosclerosis at the earlier stages to…

Machine learning classifiers provide many promising solutions for data classification in different disciplines. However, data classification at run time is still a very challenging task for real-time applications. Acceleration of machine-learning hardware solutions is needed to meet the requirements of real-time applications. This paper proposes a new implementation of a machine learning classifier on Field…