Abdelmgeid A. Ali

• Professor
• Head of Faculty at Faculty of Computers and Information - Minia University

Electroencephalograms (EEG)-based technology for recognizing emotions has attracted a lot of interest lately. However, there is still work to be done on the efficient fusion of different temporal and spatial features of EEG signals to improve performance in emotion recognition. Therefore, this study suggests a new deep learning architecture that co...

This paper proposes a modified version of the weighted mean of vectors algorithm (mINFO), which combines the strengths of the INFO algorithm with the Enhanced Solution Quality Operator (ESQ). The ESQ boosts the quality of the solutions by avoiding optimal local values, verifying that each solution moves towards a better position, and increasing the...

Accurate and rapid disease detection is necessary to manage health problems early. Rapid increases in data amount and dimensionality caused challenges in many disciplines, with the primary issues being high computing costs, memory costs, and low accuracy performance. These issues will arise since Machine Learning (ML) classifiers are mostly used in...

Metaheuristic algorithms have wide applicability, particularly in wireless sensor networks (WSNs), due to their superior skill in solving and optimizing many issues in different domains. However, WSNs suffer from several issues, such as deployment, localization, sink node placement, energy efficiency, and clustering. Unfortunately, these issues neg...

Detecting tumors using gene analysis in microarray data is a critical area of research in artificial intelligence and bioinformatics. However, due to the large number of genes compared to observations, feature selection is a central process in microarray analysis. While various gene selection methods have been developed to select the most relevant...

Automatic Text Summarization (ATS) involves estimating the salience of information and creating coherent summaries that include all relevant and important information from the original text. Extensive research has been carried out on ATS since 1958, gradually evolving from simple to advanced techniques, including machine learning-based, neural netw...

Automatic Text Summarization (ATS) involves estimating the salience of information and creating coherent summaries that include all relevant and important information from the original text. Extensive research has been carried out on ATS since 1958, gradually evolving from simple to advanced techniques, including machine learning-based, neural netw...

Efficiently treating cardiac patients before the onset of a heart attack relies on the precise prediction of heart disease. Identifying and detecting the risk factors for heart disease such as diabetes mellitus, Coronary Artery Disease (CAD), hyperlipidemia, hypertension, smoking, familial CAD history, obesity, and medications is critical for devel...

Emotion recognition based on Electroencephalography (EEG) signals has garnered significant attention across diverse domains including healthcare, education, information sharing, and gaming, among others. Despite its potential, the absence of a standardized feature set poses a challenge in efficiently classifying various emotions. Addressing the iss...

An efficient variant of the recent sea horse optimizer (SHO) called SHO-OBL is presented, which incorporates the opposition-based learning (OBL) approach into the predation behavior of SHO and uses the greedy selection (GS) technique at the end of each optimization cycle. This enhancement was created to avoid being trapped by local optima and to im...

This study explores the potential of blockchain technology to redefine public administration, focusing on the integration of Ethereum, a blockchain platform, and the Interplanetary File System (IPFS) for notarial certification issuance. The core aim is to evaluate the capacity of this technology to augment governmental efficacy, ensure transparency...

In recent years, medical data analysis has become paramount in delivering accurate diagnoses for various diseases. The plethora of medical data sources, encompassing disease types, disease-related proteins, ligands for proteins, and molecular drug components, necessitates adopting effective disease analysis and diagnosis methods. Soft computing tec...

In the Era of Mega Low Earth Orbit (LEO) satellite constellation, the efficient networking through Inter-Satellite Links (ISLs) plays a vital role in its mission success. The deployed networking resources must be justified regarding the feasibility, reliability, and Quality of Service (QoS). The main challenge of such networks is the ISLs intermitt...

Blockchain technology has attracted a lot of attention lately because it is seen as an all-purpose method for conducting online transactions between unidentified parties without the need for a centralized authority. Modern developers and businesspeople think it will disrupt or even change both the government and industry. In this setting, governmen...

Machine learning algorithms need feature selection (FS) as a significant step toward filtering unnecessary data. This paper proposes a wrapper FS approach that combines the rat swarm optimization (RSO) algorithm with genetic operators to avoid local optimal. In the proposed approach the transfer functions (TFs) are added to balance local and global...

Extractive summarization has recently gained significant attention as a classification problem at the sentence level. Most current summarization methods rely on only one way of representing sentences in a document (i.e., extracted features, word embeddings, BERT embeddings). However, classification performance and summary generation quality will be...

Heart disease remains the major cause of death, despite recent improvements in prediction and prevention. Risk factor identification is the main step in diagnosing and preventing heart disease. Automatically detecting risk factors for heart disease in clinical notes can help with disease progression modeling and clinical decision-making. Many studi...

This paper proposes an enhanced orca predation algorithm (OPA) called the Lévy flight orca predation algorithm (LFOPA). LFOPA improves OPA by integrating the Lévy flight (LF) strategy into the chasing phase of OPA and employing the greedy selection (GS) strategy at the end of each optimization iteration. This enhancement is made to avoid the entrap...

The multi-objective gorilla troops optimizer (MOGTO) is a new version of the gorilla troops optimizer (GTO) proposed in this paper to address multi-objective optimization issues. The Pareto optimum solutions acquired by the GTO are saved in an external archive. In the multi-objective search region, the archive was used to mimic the gorilla groups'...

Recently, image fusion has become one of the most promising fields in image processing since it plays an essential role in different applications, such as medical diagnosis and clarification of medical images. Multimodal Medical Image Fusion (MMIF) enhances the quality of medical images by combining two or more medical images from different modalit...

Many epidemics have afflicted humanity throughout history, claiming many lives. It has been noted in our time that heart disease is one of the deadliest diseases that humanity has confronted in the contemporary period. The proliferation of poor habits such as smoking, overeating, and lack of physical activity has contributed to the rise in heart di...

Feature selection (FS) is one of the basic data preprocessing steps in data mining and machine learning. It is used to reduce feature size and increase model generalization. In addition to minimizing feature dimensionality, it also enhances classification accuracy and reduces model complexity, which are essential in several applications. Traditiona...

Stroke is one of death causes and one the primary causes of severe long-term weakness in the world. In this paper, we compare different distributed machine learning algorithms for stroke prediction on the Healthcare Dataset Stroke. This work is implemented by a big data platform that is Apache Spark. Apache Spark is one of the most popular big data...

Disease diagnosis and prediction methods in biotechnology and medicine have significantly advanced over time. Consequently, analyzing raw gene expression is crucial for identifying diseases such as cancer. Interestingly, microarrays are a tool that records gene expression from deoxyribonucleic acid (DNA) or ribonucleic acid. This technique exhibits...

Stroke disease is one of the most prevalent diseases all over the world. This paper presents a powerful early stroke prediction system that uses medical records that describe whether a person is infected or not. We proposed an optimized DeepRNN based on different layers of A Recurrent Neural Network (RNN) and KerasTuner optimization technique for p...

When building medical diagnosis software, one of the most difficult challenges in disease prediction. Machine Learning (ML) approaches have proven to be effective in a range of applications, including medical diagnostics. ML applications that require a high level of speed and accuracy are becoming more frequent. With these applications, the curse o...

Breast cancer is the second leading cause of death in women; therefore, effective early detection of this cancer can reduce its mortality rate. Breast cancer detection and classification in the early phases of development may allow for optimal therapy. Convolutional neural networks (CNNs) have enhanced tumor detection and classification efficiency...

Due to great interest in the secure storage and transmission of color images, the necessity for an efficient and robust RGB image encryption technique has grown. RGB image encryption ensures the confidentiality of color images during storage and transmission. In the literature, a large number of chaotic-based image encryption techniques have been p...

Affective computing, a subcategory of artificial intelligence, detects, processes, interprets, and mimics human emotions. Thanks to the continued advancement of portable non-invasive human sensor technologies, like brain–computer interfaces (BCI), emotion recognition has piqued the interest of academics from a variety of domains. Facial expressions...

Autism spectrum disorder (ASD) is a developmental disorder associated with cognitive and neurobehavioral disorders. It affects the person's behavior and performance. Autism affects verbal and non-verbal communication in social interactions. Early screening and diagnosis of ASD are essential and helpful for early educational planning and treatment,...

Disease classification is one of the most difficult tasks when developing medical diagnosis software. Swarm Intelligence (SI) algorithms are used in the diagnosis and treatment of the disease. By combining ML classification algorithms and SI algorithms, we can improve the speed, performance, reliability, and accuracy of diagnosing a particular dise...

Massive data is generated as a result of technological innovations in various fields. Medical data sets often have extremely complex dimensions with limited sample sizes. The researchers face a difficult problem in classifying this high-dimensional data. We present a novel optimization approach for better feature selection in medical data classific...

Text summarization (TS) is considered one of the most difficult tasks in natural language processing (NLP). It is one of the most important challenges that stand against the modern computer system’s capabilities with all its new improvement. Many papers and research studies address this task in literature but are being carried out in extractive sum...

The widespread use of electronic health records (EHR) systems in health care provides a large amount of real-world data, leading to new areas for clinical research. Natural language processing (NLP) techniques have been used as an artificial intelligence strategy to extract information from clinical narratives in electronic health records since the...

Social networking sites in the most modernized world are flooded with large data volumes. Extracting the sentiment polarity of important aspects is necessary as it helps to determine people's opinions through what they write. The Coronavirus pandemic has passed the world and social media significantly. Tweets are showing an unpredicted increase of...

Recently, the remarkable growth of Internet technology, particularly on social media networking sites, enables gathering data for analyzing and gaining insights. It is challenging to analyze such a huge amount of information that causes time-consuming. So, it is necessary to make an intelligent system that automatically analyzes a great amount of d...

Thermography images are a helpful screening tool that can detect breast cancer by showing the body parts that indicate an abnormal change in temperature. Various segmentation methods are proposed to extract regions of interest from breast cancer images to enhance the classification. Many issues were solved using thresholding. In this paper, a new e...

Recently, the remarkable growth of Internet technology, particularly on social media networking sites, enables gathering data for analyzing and gaining insights. It is challenging to analyze such a huge amount of information that causes time-consuming. So, it is necessary to make an intelligent system that automatically analyzes a great amount of d...

Growing science and medical technologies have produced a massive amount of knowledge on different scales of biological systems. By processing various amounts of medical data, these technologies will increase the quality of disease detection and enhance the usability of health information systems. The integration of machine learning in computer-base...

Nowadays, Autism Spectrum Disorder (ASD) is one of the primary psychiatric disorders illness that rapidly increases. One of the main problems of medical diagnosis data and classification is the variance in symptoms between patients. Thus, finding the discriminative symptoms that distinguish the illness accurately is an important issue. This paper w...

Coronavirus disease 2019 (COVID-19) is pervasive worldwide, posing a high risk to people’s safety and health. Many algorithms were developed to identify COVID-19. One way of identifying COVID-19 is by computed tomography (CT) images. Some segmentation methods are proposed to extract regions of interest from COVID-19 CT images to improve the classif...

The Internet of Things (IoT) has penetrating all things and objects around us giving them the ability to interact with the Internet, i.e., things become Smart Things (SThs). As a result, SThs produce massive real-time data (i.e., big IoT data). Smartness of IoT applications bases mainly on services such as automatic control, events handling, and de...

Abstract. Breast cancer is the second leading cause of death for women, so accurate early detection can help decrease breast cancer mortality rates. Computer-aided detection allows radiologists to detect abnormalities efficiently. Medical images are sources of information relevant to the detection and diagnosis of various diseases and abnormalities...

The novel coronavirus disease (COVID-19) is regarded as one of the most imminent disease outbreaks which threaten public health on various levels worldwide. Because of the unpredictable outbreak nature and the virus’s pandemic intensity, people are experiencing depression, anxiety, and other strain reactions. The response to prevent and control the...

Healthcare mobile applications provide better care and quality of services: maintaining patient confidentiality, managing patient records, and storing and retrieving data. Using mobile applications with the cloud computing system reduces response time to secure and treat patients’ lives and give them the best professional healthcare service. This p...

High systolic blood pressure causes many problems, including stroke, brain attack, and others. Therefore, examining blood pressure and discovering issues related to it at the right time can help prevent the occurrence of health problems. Nowadays, health-based data brings a new dimension to healthcare by exploiting the real-time patients’ data to e...

Twitter is a virtual social network where people share their posts and opinions about the current situation, such as the coronavirus pandemic. It is considered the most significant streaming data source for machine learning research in terms of analysis, prediction, knowledge extraction, and opinions. Sentiment analysis is a text analysis method th...

Evolution of the Internet of Things (IoT) makes a revolution in connecting, monitoring, controlling, and managing things, objects, and almost surroundings through the Internet. To reveal the potential of IoT, rich knowledge has to be extracted, indexed, and shared securely in real-time. Recent comprehensive researches on IoT spot the light on main...

Extraction and description of image features is an active research topic and important for several applications of computer vision field. This paper presents a new noise-tolerant and rotation-invariant local feature descriptor called robust local oriented patterns (RLOP). The proposed descriptor extracts local image structures utilizing edge direct...

Network Intrusion Detection System (NIDS) is a hardware or software application that allows computer networks to detect, recognize and avoid the harmful activities, which attempt to compromise the integrity, privacy or accessibility of computer network. Two detection techniques are used by the NIDSs, namely, the signature-based and anomaly-based. S...

Dimensionality reduction is an interesting area of research in data mining. An effective way to reduce dimensions is feature selection that removes irrelevant information meanwhile helping to understand the learning model better and improving prediction accuracy. In this paper, we face a challenge of filter methods to determine number of significan...

Associative classification, as a branch of the classification, effectively integrates the main idea of association rule mining with the task of classification in order to improve the efficiency of the classifier. Associative classification suffers from producing a huge number of classification rules. Hence, reducing the number of classification rul...

Adrenaline hormone may effect on cholesterol and glucose levels in the human body which may cause different diseases such as stroke. On the other hand, numerous biomedical research relies on bioimpedance technique because it possesses a lot of features such as the ability to analyse the blood components to identify different diseases. Therefore, th...

Physical world integration with cyber world opens the opportunity of creating smart environments; this new paradigm is called the Internet of Things (IoT). Communication between humans and objects has been extended into those between objects and objects. Industrial IoT (IIoT) takes benefits of IoT communications in business applications focusing in...

Adrenaline hormone may effect on cholesterol and glucose levels in the human body which may cause different diseases such as stroke. On the other hand, numerous biomedical research relies on bioimpedance technique because it possesses a lot of features such as the ability to analyze the blood components to identify different diseases. Therefore, th...

The integration of Near Field Communication (NFC) in smartphones offered many applications in the market and in many other fields such as electronic ticketing, access control frameworks, etc.). On the other hand, virtual reality is another technology that has been on the rise recently and its applications span over many fields such as entertainment...

The progressive advancement of smartphone which offers precise customized configuration and varied capacity abilities has dramatically reshaped the way we use technology. Many applications in many fields have been provided by integration of Near Field Communication (NFC) into smartphones (for example electronic ticketing and access control framewor...

Heart diseases are one of the first causes of death worldwide. This paper presents a real-time system for predicting heart disease from medical data streams that describe a patient’s current health status. The main goal of the proposed system is to find the optimal machine learning algorithm that achieves high accuracy for heart disease prediction....

Steganography is the art and science of writing hidden messages in such a way that no one suspects the existence of the message, a form of security through obscurity. Many different carrier file formats can be used, but digital images are the most popular because of their frequency on the internet. In this paper explains the PIGPEN image steganogra...

During the last few years, Local Binary Patterns (LBP) has aroused increasing interest in image processing and computer vision. LBP was originally proposed for texture analysis, and has proved a simple yet powerful approach to describe local structures. It has been extensively exploited in many applications, for instance, face image analysis, image...

Identity recognition using local features extracted from ear images has recently attracted a great deal of attention in the intelligent biometric systems community. The rich and reliable information of the human ear and its stable structure over a long period of time present ear recognition technology as an appealing choice for identifying individu...

Face detection is considered as a one of the most important issues in the identification and authentication systems which use biometric features. Face detection is not straightforward as long as it has lots of dissimilarity of image appearance. Some challenges are required to be resolved to improve the detection process. These challenges include en...

Feature keypoint descriptors have become indispensable tools and have been widely utilized in a large number of computer vision applications. Many descriptors have been proposed in the literature to describe regions of interest around each keypoint and each claims distinctiveness and robustness against certain types of image distortions. Among thes...

Stroke is one of death causes and one the primary causes of severe long-term weakness in the world. In this paper, we compare different distributed machine learning algorithms for stroke prediction on the Healthcare Dataset Stroke. This work is implemented by a big data platform that is Apache Spark. Apache Spark is one of the most popular big data...

The educational database holds on the massive amount of data and it is increasing rapidly. Data mining provides effective techniques for discovering useful knowledge and pattern from students’ data. The discovered patterns can be used to understand many problems in the educational field. This paper proposes a framework to predict the achievement of...

The educational database holds on the massive amount of data and it is increasing rapidly. Data mining provides effective techniques for discovering useful knowledge and pattern from students' data. The discovered patterns can be used to understand many problems in the educational field. This paper proposes a framework to predict the achievement of...

The educational database holds on the massive amount of data and it is increasing rapidly. Data mining provides effective techniques for discovering useful knowledge and pattern from students’ data. The discovered patterns can be used to understand many problems in the educational field. This paper proposes a framework to predict the achievement of...

Recently, intensive research efforts are conducted on the human ear as a promising biometric modality for identity recognition. However, one of the main challenges facing ear recognition systems is to find robust representation for the image information that is invariant to different imaging variations. Recent studies indicate that using the distri...

Data that is obtained from various information sources needs excessively handling for managing, analyzing and monitoring. Data warehouse consolidates data coming from different data sources. Data warehousing technology has made a huge effect in the world of business; it transforms information into data that helps analysts to make strategic decision...

IoT has been shown as a big potential for qualifying and improving healthcare services; such as monitoring at anytime and anyplace. These services acquire various bio-signals using different sensors, including electroencephalogram (EEG), electrocardiogram (ECG), electrical signal of the heart, electromyogram (EMG), electrical signal of muscles, Res...

Data that is obtained from various information sources needs excessively handling for managing, analyzing and monitoring. Data warehouse consolidates data coming from different data sources. Data warehousing technology has made a huge effect in the world of business; it transforms information into data that helps analysts to make strategic decision...

In this presentation, a comprehensive performance evaluation of the current state-of-the-art binary descriptors; namely, BRIEF, ORB, BRISK, FREAK, and LATCH is presented in the context of image matching. This performance evaluation highlights several points regarding the performance characteristics of binary descriptors under various geometric and...

Efficient and compact representation of local image patches in the form of features descriptors that are distinctive/robust as well as fast to compute and match is an essential and inevitable step for many computer vision applications. One category of these representations is the binary descriptors which have been shown to be successful alternative...

is considered one of the branches of data hiding. It is the science of hiding sensitive information in a cover such as image, audio, video to achieve secure and secret communication. The word steganography derived from two Greek words: steganos means covered and graphien means writing and often refers to secret writing. The most common use of stega...

Nowadays, due to the increasing need for providing secrecy in an open environment such as the internet, data hiding has been widely used. Steganography is one of the most important data hiding techniques which hides the existence of the secret message in cover files or carriers such as video, images, audio or text files. In this chapter; steganogra...

Network Intrusion Detection Systems (NIDSs) are systems that monitor computer networks to detect, identify and prevent the malicious events, which attempt to compromise the integrity, confidentiality or availability of computer networks. The NIDS may be classified according to the detection technique into two types, the "Signature-Based" and "Anoma...

Today, internet made it easier to send the data more accurately and faster to the destination with the increasing unauthorized access of confidential data. So that, the issue nowadays reduces detection of information during transmission. To hide the secret information during transmission, there are two methods cryptography and steganography. Crypto...