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Liver cancer is a major contributor to cancer-related mortality both in the United States and worldwide. A range of liver diseases, such as chronic liver disease, liver cirrhosis, hepatitis, and liver cancer, play a role in this statistic. Hepatitis, in particular, is the main culprit behind liver cancer. As a consequence, it is decisive to…

Data stream gained obvious attention by research for years. Mining this type of data generates special challenges because of their unusual nature. Data streams flows are continuous, infinite and with unbounded size. Because of its accuracy, decision tree is one of the most common methods in classifying data streams. The aim of classification is to…

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…

In this industry 4.0 and digital era, we are more dependent on the use of communication and various transaction such as financial, exchange of information by various means. These transaction needs to be secure. Differentiation between the use of benign and malware is one way to make these transactions secure. We propose in this work…

The main assets of universities are students. The performance of students plays a vital role in producing excellent graduate students who will be the future viable leader and manpower in charge of a country’s financial and societal progress. The purpose of this research is to develop a “University Students Result Analysis and Prediction System” that…

Screening the abnormal development of the zebrafish embryos before and after being hatched for a large number of samples is always carried out manually. The manual process is presented as a tedious work and low-throughput. The single female fish produce hundreds of eggs in every single mating process, the samples of the zebrafish embryos should…

An ensemble method is a Machine Learning (ML) algorithm that aggregates the predictions of multiple estimators or models. The purpose of an ensemble module is to provide better predictive performance than any single contributing model. This can be achieved by producing a predictive model with reduced variance using bagging, and bias using boosting. The Tree-Based…

Decision-makers must make a suitable sequence of decisions under uncertainty in a relatively long period for particular projects and situations. Conventional decision-making approaches under uncertainty are based on expected utility theory and do not sufficiently reflect the one-time nature of decisions. Similarly, the conventional approaches do not adequately incorporate the decision-maker’s intuitions in the decision-analysis…

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…

Precision agriculture in recent times had assumed a different dimension in order to improve on the poor standard of agriculture. Similarly, the upsurge in technological advancement, most especially in the aspect of machine learning and artificial intelligence, is a promising trend towards a positive solution to this problem. Therefore, this research work presents a decision…

Understanding and responding to customer feedback is critical for business success. Customer response data offers valuable insights into preferences, behaviours, and sentiment. By analysing this data, businesses can optimize strategies, enhance customer experiences, and drive growth. Many analysis have been conducted in this field, while the review covers a broad range of AI and ML…

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 builds on the realization that since mobile devices have become a common tool for researchers to collect, process, and analyze large quantities of data, we are now entering a generation where the creation of solutions to difficult real-world problems will mostly come in the form of mobile device apps. One such relevant real-life…

Predicting the credit card default is important to the bank and other lenders. The credit default risk directly affects the interest charged to the borrower and the business decision of the lenders. However, very little research about this problem used the Generalized Linear Model (GLM). In this paper, we apply the GLM to predict the…

The main objective and contribution of the paper is to describe the creation of a model to support recruitment using social media information and its deployment in practice. The model includes the design of an automated solution for downloading social media data and a proposal for the subsequent analysis and creation of a predictive model…

The study aims to assess the machine learning techniques in predicting students’ associated factors that affect their academic performance. The study sample consisted of 5084 middle and high school students between the ages of 10 and 17, attending public and UNRWA schools in the West Bank. The ‘Health Behaviors School Children’ questionnaire for the 2013-2014…

In research project, efficiency comparison study in prediction of normalization with data mining classification. The purpose of the research was to compare three normalization methods in term of classification accuracy that the normalized data provided: Z-Score, Decimal Scaling and Statistical Column. The six known classifications: K-Nearest Neighbor, Decision Tree, Artificial Neural Network, Support Vector Machine,…

In this article supervised classification methods for the analysis of local Panamanian rice crops using Near-Infrared (NIR) spectral signatures are assessed. Neural network ( Multilayer Perceptron-MLP) and Tree based (Decision Trees-DT and Random Forest-RF) algorithms are used as regression and supervised classification of the spectral signatures by rice varieties, against other crops and by plant…

Rated a high-risk cyber-attack type, Advanced Persistent Threat (APT) has become a cause for concern to cyber security experts. Detecting the presence of APT in order to mitigate this attack has been a major challenge as successful attacks to large organizations still abound. Our approach combines static rule anomaly detection through pattern recognition and machine…

Despite the significant progress made in data mining technologies in recent years, breast cancer risk prediction and diagnosis at an early stage using DNA microarray technology still a real challenging task. This challenge comes especially from the high-dimensionality in gene expression data, i.e., an enormous number of genes versus a few tens of subjects (samples).…

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…

To create a Virtual Reality (VR) system for Wing Chun’s basic hand movement training, capturing, and classifying movement data is an important step. The main goal of this paper is to find the best possible method of classifying hand movement, particularly Wing Chun’s basic hand movements, to be used in the VR training system. This…

There is a crisis in basic education during this pandemic which affected everyone worldwide, we see that teaching and learning have gone online which has effected student performance. Student’s academic performance needs to be predicted to help an instructor identify struggling students more easily and giving teachers a proactive chance to come up with supplementary…

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…