Mohammed Eshtay

• PhD
• Professor (Assistant) at LTUC

Rapid developments in technology around the world require continuous efforts in academia to develop innovative solutions to enhance the learning of basic and advanced programming concepts. Educators understand the value of preparing highly skilled programmers to join the industry, and this puts a responsibility to develop and enhance teaching techn...

Predicting defect-prone software components can play a significant role in allocating relevant testing resources to fault-prone modules and hence increasing the business value of software projects. Most of the current software defect prediction studies utilize traditional supervised machine learning algorithms to predict defects in software applica...

Developing an effective classification model in the medical field is challenging due to limited datasets. To address this issue, this study proposes using a generative adversarial network (GAN) as a data-augmentation technique. The research aims to enhance the classifier’s generalization performance, stability, and precision through the generation...

Breast cancer is one of the leading causes of death among women worldwide. Many methods have been proposed for automatic breast cancer diagnosis. One popular technique utilizes a classification-based association called Association Classification (AC). However, most AC algorithms suffer from considerable numbers of generated rules. In addition, irre...

The failure rates in introductory programming courses still shows that there is a continuous need in research to investigate and propose new methods and techniques of teaching introductory to programming courses to attract more people to the information technology field and build more skilled programmers from their first course. This study investig...

p class="0abstract">Today, the influence of the social media on different aspects of our lives is increasing, many scholars from various disciplines and majors looking at the social media networks as the ongoing revolution. In Social media networks, many bonds and connections can be established whether being direct or indirect ties. In fact, Social...

Random Weight Networks have been extensively used in many applications in the last decade because it has many strong features such as fast learning and good generalization performance. Most of the traditional training techniques for Random Weight Networks randomly select the connection weights and hidden biases and thus suffer from local optima sta...

Extreme Learning Machine (ELM) is a learning algorithm proposed recently to train single hidden layer feed forward networks (SLFN). It has many attractive properties that include better generalization performance and very fast learning. ELM starts by assigning random values to the input weights and hidden biases and then in one step it determines t...

Nowadays, smartphones are an essential part of people’s lives and a sign of a contemporary world. Even that smartphones bring numerous facilities, but they form a wide gate into personal and financial information. In recent years, a substantial increasing rate of malicious efforts to attack smartphone vulnerabilities has been noticed. A serious com...

Software defect prediction is a promising approach aiming to improve software quality and testing efficiency by providing timely identification of defect-prone software modules before the actual testing process begins. These prediction results help software developers to effectively allocate their limited resources to the modules that are more pron...

Feature selection (FS) is considered asone of the most common and challenging tasks in Machine Learning. FS can be considered as an optimization problem that requires an efficient optimization algorithm to find its optimal set of features. This paper proposes a wrapper FS method that combines a time-varying number of leaders and followers binary Sa...

Extreme learning machine (ELM) is a novel and recent machine learning algorithm which was first proposed by Huang et al. (Proceedings of 2004 IEEE international joint conference on, pp 985–990, 2004). Over the last decade, ELM has gained a remarkable research interest with tremendous audiences from different domains in a short period of time due to...

NoSQL database systems have emerged and developed at an accelerating rate in the last years. Attractive properties such as scalability and performance, which are needed by many applications today, contributed to their increasing popularity. Time is very important aspect in many applications. Many NoSQL database systems do not offer built in managem...

The huge growth of the usage of internet increases the need to transfer and save multimedia files. Mammogram images are part of these files that have large image size with high resolution. The compression of these images is used to reduce the size of the files without degrading the quality especially the suspicious regions in the mammogram images....

Minimum vertex cover (MVC) is a well-known NP-Complete optimization problem. The importance of MVC in theory and practical comes from the wide range of its applications. This paper describes a polynomial time greedy algorithm to find near optimal solutions for MVC. The new algorithm NMVAS is a modification of already existed algorithm called MVAS w...