Abdel-Badeeh M.Salem

Ain Shams University · Faculty of Computers and Information Sciences

The deep fake faces generation using generative adversarial networks (GANs) has reached an incredible level of realism where people can’t differentiate the real from the fake. Text-to-face is a very challenging task compared to other text-to-image syntheses because of the detailed, precise, and complex nature of the human faces in addition to the t...

In the software development process, more than one developer may work on developing the same program and bugs in the program may be fixed by a different developer; therefore, understanding the source code is an important issue. Pseudocode plays an important role in solving this problem, as it helps the developer to understand the source code. Recen...

Generating source code is necessary especially as software evolves in complexity and demand. Finding a mechanism to generate the source code according to the requirements will save time for developers at the stage of development of the software. In this paper, a mechanism is proposed to generate the source code based on the database schema and user...

Due to the significant roles of O-glycosylation in the biological processes as well as its association with various human diseases, in this work we propose a machine learning model to improve O-glycosylation site prediction from the protein sequences. Different types of sequence-based feature extraction methods were used to encode the peptide seque...

Post-translational glycosylation and glycation are common types of protein post-translational modifications (PTMs) in which glycan binds to protein enzymatically or nonenzymatically, respectively. They are associated with various diseases such as coronavirus, Alzheimer’s, cancer, and diabetes diseases. Identifying glycosylation and glycation sites...

Smart healthcare systems play a vital role in people's everyday lives and hence, healthcare systems are expected to continue to improve and advance. AI and IoT techniques are employed in the prescription of medicine and in setting the different actions and procedures that need to be followed by patients by the health service providers. These techno...

The article is devoted to the institutions of dissemination and application of artificial intelligence in industry. Artificial intelligence (AI) is currently one of the most dynamically developing technologies and outcomes of the Fourth Industrial Revolution with a huge transformational impact on the economy. The article further confirms the inclus...

Machine learning algorithms can be applied on electromyographic (EMG) signals for neuromuscular disorders diagnosis. In this paper focuses on tunable-Q factor wavelet transform (TQWT) for feature extraction and compares various learning algorithms to classify ALS, myopathy and healthy EMG signals. Firstly, TQWT decomposes on the EMG signals of each...

The comprehension of source code is very difficult, especially if the programmer is not familiar with the programming language. Pseudocode explains and describes code contents that are based on the semantic analysis and understanding of the source code. In this paper, a novel retrieval-based transformer pseudocode generation model is proposed. The...

Currently, research in the field of smart education development is one of the dynamically growing scientific fields. At the same time, this field of research is new, opens up new opportunities and has certain limitations, which determines the importance of its further study. The presented article reveals the prerequisites for the development of sma...

N-linked glycosylation is one of the most common protein post-translation modifications (PTMs) in humans where the Asparagine (N) amino acid of the protein is attached to the glycan. It is involved in most biological processes and associated with various human diseases as diabetes, cancer, coronavirus, influenza, and Alzheimer’s. Accordingly, ident...

Multimodal biometric systems have been widely used to achieve high recognition accuracy. This paper presents a new multimodal biometric system using an intelligent technique to authenticate human by fusion of palm and dorsal hand veins pattern. We developed an image analysis technique to extract region of interest (ROI) from palm and dorsal hand ve...

Deep learning is a power machine learning algorithm in classification while extracting high-level features. This paper is proposed to predict Alzheimer’s disease (AlD) with a deep 3D convolutional neural network (3D-CNN), which can learn generic features capturing AlD biomarkers, classify Alzheimer’s brain from normal healthy brain based on Magneti...

Text-to-image synthesis is referring to converting textual features into pixels, which requires a full understanding of the connection between the natural language text and visual features. What this paper presents is an intelligent hybrid model for converting the textual description into an image; this model depends on the proposed models; AttnGAN...

Deep neural networks have accomplished enormous progress in tackling many problems. More specifically, convolutional neural network (CNN) is a category of deep networks that have been a dominant technique in computer vision tasks. Despite that these deep neural networks are highly effective; the ideal structure is still an issue that needs a lot of...

Background As sepsis is one of the life-threatening diseases, predicting sepsis with high accuracy could help save lives. Methods Efficiency and accuracy of predicting sepsis can be enhanced through optimal feature selection. In this work, a support vector machine model is proposed to automatically predict a patient’s risk of sepsis based on physi...

Understanding the content of the source code and its regular expression is very difficult when they are written in an unfamiliar language. Pseudo-code explains and describes the content of the code without using syntax or programming language technologies. However, writing Pseudo-code to each code instruction is laborious. Recently, neural machine...

Text-to-image synthesis or conditional image generation is referring to converting natural language text descriptions into realistic images, where both are semantically consistence. Deep convolutional generative adversarial networks (GANs) are rapidly changing field that have shown great revolution in the generative models. GANs are the recent wide...

This review aims to present a survey of the technologies and methodologies used in the phonocardiogram (PCG) biometric systems. The phases used in the PCG which are explored in this paper include data acquisition, de-noising, extracting PCG peaks, feature extraction, feature reduction, classification, and evaluation. As part of this study, we perfo...

The digitalization of agriculture is much slower than in other industries, due to the high cost of digital solutions and their complex functionality. Recently, the situation is changing, and now agriculture can get real benefits from technology with simple software solutions. Technologies used in agriculture include sensors, mobile devices, communi...

Text-to-image synthesis is referring to converting textual features into pixels, which requires full understanding of the relation between the visual features and natural language. In contrast to most of the existing text-to-image methods, which ignore the information from the original images and only generates images based on input text, some mode...

This paper focuses on the problems of data clustering where the similarity between different objects is estimated with the use of the Euclidean distance metric. Also, K-Means is used to remove data noise, genetic algorithms are used for finding the optimal set of features and the Support Vector, Machine (SVM) is used as a classifier. The experiment...

One of the diseases which is life-threatening is Sepsis. The unbalanced body reaction to some chemicals which is released by the body into its blood stream in response to fighting an infection is the main cause of Sepsis. Early sepsis prediction is a necessity in order to decrease the mortality rates of ICU patients. The accuracy of early predictio...

Background Glycosylation is one of the most common post-translation modifications (PTMs) in organism cells. It plays important roles in several biological processes including cell-cell interaction, protein folding, antigen’s recognition, and immune response. In addition, glycosylation is associated with many human diseases such as cancer, diabetes...

In the last decades artificial intelligence techniques are used widely by researchers of neuromuscular disorders to increase the diagnostic performance and accuracy. The Electromyography (EMG) is a commonly used technique to record and analyse myoelectric signals. The processing and classification of EMG signals play a major role in the diagnosis o...

COVID-19 has become a pandemic affecting the most of countries in the world. One of the most difficult decisions doctors face during the Covid-19 epidemic is determining which patients will stay in hospital, and which are safe to recover at home. In the face of overcrowded hospital capacity and an entirely new disease with little data-based evidenc...

The term “fraud”, it always concerned about credit card fraud in our minds. And after the significant increase in the transactions of credit card, the fraud of credit card increased extremely in last years. So the fraud detection should include surveillance of the spending attitude for the person/customer to the determination, avoidance, and detect...

Nowadays, computers are extremely beneficial to music composers. Computer music generation tools are developed for aiding composers in producing satisfying musical pieces. The automation of music composition tasks is a challenging research point, specially to the field of Artificial Intelligence. Converting melodies that are played on a major scale...

Glycation is a nonenzymatic process for binding glycan with proteins. It is related to the development many of human diseases. Due to the importance of glycation and the limitations of experimental techniques, artificial intelligence (AI) and computational methods are necessary for glycation site prediction. In this paper, the glycation site predic...

Intelligent access control is one of the challenging tasks in the human identification, image analysis, and diagnoses disease and computer vision. The focus towards the intelligent access control has been increased in the last years due to its various, applications in different domains. For this reason, it was used intelligent access control to fac...

COVID-19 infection is one of the most dangerous respiratory viruses and the early detection of this disease reduces the speed of its spread among people. The goal of this virus is to infect the lung by creating white patchy shadows inside the lungs. This paper presents an intelligent method based on the deep learning technique to analyze the medica...

In the present paper, electroencephalogram (EEG) data have been used to human identification by computing sample entropy and graph entropy as feature extractions. Used two classifier types , which are K-Nearest Neighbors (K-NN) and Support Vector Machine (SVM). Python and Matlab software were used in this study and EEG data was collected by UCI rep...

Machine learning algorithms have been explored for the diagnosis of Alzheimer's disease (AD) in both clinical and research applications. Deep learning is a power machine learning algorithm in classification while extracting high-level features. This paper proposed to predict the AD with a deep 3D convolutional neural network (3D-CNN), which can lea...

Electroencephalogram (EEG) signals refer to distinctive neurons' electrical activity, depiction that upkeep biometric recognition. Usually in biometrics, the acquisition protocol has been important for EEG-based biometric system performance. Various acquisition protocols brain signals like evoked potentials besides relaxation, motor and non-motor i...

The present article focuses on the role that the artificial teaching and learning of mathematics could play for education in the forthcoming era of a new industrial revolution that will be characterized by the development of an advanced Internet of things and energy, and by the cyber-physical systems controlled through it. Starting with a brief rev...

The signals of the electroencephalogram (EEG) have been applied for detecting as well as registering the electrical efficiency in the human brain. In this paper, EEG signals have been utilized for human identification. The reliability regarding a lot of biometric systems aren't adequate due to the possibility of being copied or faked. Thus the brai...

The revolutionary digital transformations of society have led to the need for formulating a smart higher education system, adequate to modern conditions and based on the integrated use of intelligent digital solutions. The paper substantiates that the creations of such systems requires the solution of a whole complex of technological, institutional...

Machine learning algorithms have been explored for the diagnosis of Alzheimer's disease (AD) in both clinical and research applications. Deep learning is a power machine learning algorithm in classification while extracting high-level features. This paper proposed to predict the AD with a deep 3D convolutional neural network (3D-CNN), which can lea...

The article focuses on the potential role of Probability Theory and Artificial Intelligence in the battle against the pandemic of COVID-19, which, starting from China on December 2019, has created a chaos in the world economy and the lives of people, causing hundreds of thousands of deaths until now. After discussing the importance of the reproduct...

Biometric development depends on electroencephalography (EEG) distinguishes people by utilizing individual qualities in human brainwaves. Tow Essential features of EEG signals are Liveliness strength against adulteration. However , far reaching study on human authentication utilizing EEG signals is still remain. In this paper we propose a two-phase...

Demand Response (DR) programs play a significant role for developing energy management solutions. Gaining home residents trust and respecting their appliances usage preferences are essential factors for promoting these programs. Extracting resident's usage behaviour is a challenging task with the infinite massive amount of data being generated from...

Ever expanding utilization of the internet and online activities such as booking, blogging, e-commerce and conferencing, leads us to analyze very large quantities of structured data and unstructured data through Sentiment Analysis (SA). SA refers to the application of Natural Language Processing (NLP), computational linguistics, and data mining to...

The importance of using machine learning techniques in the field of medical imaging technologies have increased in both research and clinical care over the recent years. So, detecting Alzheimer's disease in precise way and early phase is essential for patient care. Researchers have been dedicating their efforts to evaluate compulsive changes that h...

Malignant melanoma is one of the most dangerous types of skin cancers, which may grow on any part of the body. Medical Informatics utilized computer technology such as Computer Aided Diagnosis (CAD) to diagnose the disease. Many researchers developed CAD systems for melanoma diagnosis. Early diagnosis of melanoma is a main strategy to reduce melano...

Sentiment classification is the most rising research areas of sentiment an alysis and text mining, especially with the massive amount of opinions available on social media. Recent results and efforts have demonstrated that there is no single strategy can mutually accomplish the best prediction performance on various datasets. The re is a lack...

Source Code Generation (SCG) is the sub-domain of the Automatic Programming (AP) that helps programmers to program using high-level abstraction. Recently, many researchers investigated many techniques to access SCG. The problem is to use the appropriate technique to generate the source code due to its purposes and the inputs. This paper introduces...

Cloud Communication Environment is an internet-based computing, where shared resources, software, and information are provided with computers and devices on-demand. They guarantee a way to share distributed resources and services that belong to different organizations. In order to develop cloud computing applications, security and trust to share da...

Cloud computing technology is a modern emerging trend in the distributed computing technology that is rapidly gaining popularity in network communication field. Despite the advantages that the cloud platforms bolstered, it suffers from many security issues such as secure communication, consumer authentication, and intrusion caused by attacks. These...

The increase of age average led to an increase in the demand of providing and improving the service of healthcare. The advancing of the information and communication technology (ICT) led to the development of smart cities which have a lot of components. One of those components is Smart Health (s-Health), which is used in improving healthcare by pro...

The constructed medical ontologies need to be updated in order to reflect the changes occurred on the medicine such as the clinical findings, treatments and their side effects. Various researchers defined the ontology maintenance as the process of updating the ontology or the evolution of the ontology. Other researches consider the ontology mainten...

Sentiment analysis (SA) is a scholarly process of extricating and classifying individuals’ emotions and feedbacks expressed in source text content. It is one of the pursued subfields of Computational Linguistics (CL) and Natural Language Processing (NLP). The evolution of social media based applications has generated a big amount of personalized re...

Biometrics has been defined as the inevitable recognition of users according to the quality acquired from behavioral and/or physiological properties. Through few years, some works have explore the biometric utilize of human /animal brain signals that, for various reasons, have traditional received little attention by the security community. Bio sig...

The huge amount of clinical signals and measurements in Intensive Care Units (ICU) will simply overwhelm the person responsible for healthcare support and may cause treatment delays, or clinical errors. This paper analyzes the recent Machine Learning (ML) and Computational Intelligence (CI) techniques which are applied to ICU equipment data in the...

Ontological engineering (OE) is a subset of knowledge science. Ontology is a powerful technique for knowledge management and reasoning tasks. Recently, most research of OE is related to developing robust, smart, knowledge-based systems in different domains. Nowadays, e-business, or electronic business, is the integrated execution of all business an...