Samir Elmougy

• Ph.D. in Computer Science
• Professor of Computer Science and the Vice Dean of Postgraduate Studies - Faculty of Computers and Information, Mansoura University, Egypt. at Mansoura University

Recommendation Systems (RS) play a crucial role in delivering personalized item suggestions, yet traditional methods often struggle with accuracy, scalability, efficiency, and cold-start challenges. This paper presents the HRS-IU-DL model, a novel hybrid recommendation system that advances the field by integrating multiple sophisticated techniques...

Nowadays, fingerprints as biometrics are among the most popular means of identity verification for various applications. However, they are susceptible to theft, tampering, or alteration by attackers after storage. Hence, it is critical to guarantee the privacy of these fingerprint templates because standard privacy techniques are not secure enough....

Optimizers are the bottleneck of the training process of any Convolutionolution neural networks (CNN) model. One of the critical steps when work on CNN model is choosing the optimal optimizer to solve a specific problem. Recent challenge in nowadays researches is building new versions of traditional CNN optimizers that can work more efficient than...

The primary objective of this paper is to develop a machine learning-based approach capable of predicting the treatment response of neoadjuvant chemotherapy (NAC) to enhance breast cancer treatment management. The proposed system aims to predict NAC outcomes across three categories: pathological complete response (CR), partial response (PR), and st...

Recommendation Systems (RS) are essential for personalized item suggestions, but traditional approaches face limitations in accuracy, scalability, efficiency, and cold-start problems. This paper introduces the HRS-IU-DL model, a hybrid RS that leverages advanced techniques to enhance accuracy and relevance. The model integrates user-based and item-...

Many security cameras have been put up in places like airports, roads, and banks for the safety of these public places. These cameras make a lot of video data, and most security camera recordings are only ever seen when something strange happens. This means that monitoring has to be done by people, which is time-consuming and often wrong, so automa...

This paper proposes an approach to enhance the differentiation task between benign and malignant Breast Tumors (BT) using histopathology images from the BreakHis dataset. The main stages involve preprocessing, which encompasses image resizing, data partitioning (training and testing sets), followed by data augmentation techniques. Both feature extr...

The genetic algorithm (GA) is a well-known metaheuristic approach for dealing with complex problems with a wide search space. In genetic algorithms (GAs), the quality of individuals in the initial population is important in determining the final optimal solution. The classic GA using the random population seeding technique is effective and straight...

In the healthcare sector, the health status and biological, and physical activity of the patient are monitored among different sensors that collect the required information about these activities using Wireless body area network (WBAN) architecture. Sensor-based human activity recognition (HAR), which offers remarkable qualities of ease and privacy...

This paper explores the use of chest CT scans for early detection of COVID-19 and improved patient outcomes. The proposed method employs advanced techniques, including binary cross-entropy, transfer learning, and deep convolutional neural networks, to achieve accurate results. The COVIDx dataset, which contains 104,009 chest CT images from 1,489 pa...

The proposed AI-based diagnostic system aims to predict the respiratory support required for COVID-19 patients by analyzing the correlation between COVID-19 lesions and the level of respiratory support provided to the patients. Computed tomography (CT) imaging will be used to analyze the three levels of respiratory support received by the patient:...

Genetic algorithms (GAs) are search algorithms based on population genetics and natural selection concepts. Maintaining population variety in GAs is critical for ensuring global exploration and mitigating the risks of premature convergence. Rapid convergence to local optima is one such challenge in the application of genetic algorithms. To address...

Nowadays, we face improvements in the field of the Internet of Things (IoT). The primary focus of the Internet of Medical Things (IoMT) is to gather health data from patients and provide healthcare services accordingly. Hence, researchers have been focusing on this wide-ranging system that causes the patient’s private data disclosure. This paper su...

Simple Summary Artificial intelligence (AI) has seamlessly integrated into the medical field, especially in diagnostic imaging, thanks to ongoing AI advancements. It is widely used in various medical applications. In the context of breast cancer (BC), machine learning and deep learning are extensively employed for automating diagnosis, segmenting r...

In this paper, we propose a Mean-Field Game (MFG) approach for modeling the flocking behavior of Unmanned Aerial Vehicles (UAVs) that might be used in massive attack-defense engagements and optimizing their trajectories in a way that minimizes the overall cost (i.e. energy consumption), which results in enhancing the overall performance of the swar...

Retinal optical coherence tomography (OCT) imaging is a valuable tool for assessing the condition of the back part of the eye. The condition has a great effect on the specificity of diagnosis, the monitoring of many physiological and pathological procedures, and the response and evaluation of therapeutic effectiveness in various fields of clinical...

Bitcoin becomes the focus of scientific research in the modern era. Blockchain is the underlying technology of Bitcoin because of its decentralization, transparency, trust-less and immutability features. However, blockchain can be considered the cause of Bitcoin scalability issues, especially storage. Nodes in the Bitcoin network need to store t...

There are several methods that have been discovered to improve the performance of Deep Learning (DL). Many of these methods reached the best performance of their models by tuning several parameters such as Transfer Learning, Data augmentation, Dropout, and Batch Normalization, while other selects the best optimizer and the best architecture for the...

The Internet of Medical Things (IoMT) uses wireless networks to help patients to communicate with healthcare professionals. Therefore, IoMT devices suffer from a lack of security controls, just like many Internet of Things (IoT) gadgets. Thus, in this paper, we develop a system that uses a blockchain to secure medical data for each transaction betw...

Counting number of triangles in the graph is considered a major task in many large-scale graph analytics problems such as clustering coefficient, transitivity ratio, trusses, etc. In recent years, MapReduce becomes one of the most popular and powerful frameworks for analyzing large-scale graphs in clusters of machines. In this paper, we propose two...

Blockchain is a Distributed Ledger Technology (DLT) that allows users to exchange values directly without a need for trusted third parties. Bitcoin is one of the most popular digital cryptocurrencies that is based on blockchain technology. However, it faces scalability problems including transaction throughput, latency, and starvation. Bitcoin tran...

Complex networks are a diverse set of networks found in various fields, such as social, technological, and biological networks. One important task in complex network analysis is link prediction, which involves detecting missing links or predicting future link formation. Many methods based on network structure analysis have been developed for link p...

Attributed Network Embedding (ANE) and the representation of its nodes in a low-dimensional space is a pivotal step in the analysis of real-world networks. One of the biggest challenges in the embedding process of nodes in complex networks is to capture any dynamic changes in both the node itself and in its adjacent. To address the above challenge,...

TSP is a well-known combinatorial optimization problem with several practical applications. It is an NP-hard problem, which means that the optimal solution for huge numbers of examples is computationally impractical. As a result, researchers have focused their efforts on devising efficient algorithms for obtaining approximate solutions to the TSP....

Nowadays, the Internet of Medical Things (IoMT) technology is growing and leading the revolution in the global healthcare field. Exchanged information through IoMT permits attackers to hack or modify the patient’s data. Hence, it is of critical importance to ensure the security and privacy of this information. The standard privacy techniques are no...

Bitcoin is a digital cryptocurrency which had become the focus of scientific research in the modern era. Blockchain is the underlying technology of Bitcoin because of its decentralization, transparency, trust-less, and immutability features. However, blockchain can be considered the cause of Bitcoin scalability issues especially storage. Nodes in B...

Numerous machine learning methods depend on distance measures. In both supervised and unsupervised learning, these distance measures are primarily employed to assess the degree of similarity between data points. One of the most recent distance metrics that comes highly recommended by several academics for its improved performance in machine learnin...

Optimization algorithms are used to improve model accuracy. The optimization process undergoes multiple cycles until convergence. A variety of optimization strategies have been developed to overcome the obstacles involved in the learning process. Some of these strategies have been considered in this study to learn more about their complexities. It...

The extensive use of Internet of Things (IoT) technology has recently enabled the development of smart cities. Smart cities operate in real-time to improve metropolitan areas’ comfort and efficiency. Sensors in these IoT devices are immediately linked to enormous servers, creating smart city traffic flow. This flow is rapidly increasing and is crea...

The continuous improvement of sequencing technologies has been paralleled by the development of efficient algorithms and data structures for sequencing data analysis and processing. Suffix array is one of data structures that are used to construct the Burrows-Wheeler transform (BWT) for long length genomes. Building a suffix array itself is an expe...

Infectious diseases are an imminent danger that faces human beings around the world. Malaria is considered a highly contagious disease. The diagnosis of various diseases, including malaria, was performed manually, but it required a lot of time and had some human errors. Therefore, there is a need to investigate an efficient and fast automatic diagn...

Early grading of coronavirus disease 2019 (COVID-19), as well as ventilator support machines, are prime ways to help the world fight this virus and reduce the mortality rate. To reduce the burden on physicians, we developed an automatic Computer-Aided Diagnostic (CAD) system to grade COVID-19 from Computed Tomography (CT) images. This system segmen...

COVID-19 virus (coronavirus) is causing a worldwide pandemic of severe respiratory illnesses (SARS-CoV-2). The unique virus was discovered in the Chinese city of Wuhan in December 2019 and has since spread throughout the world. For fear of spreading, the World Health Organization (WHO) issued a Public Health Emergency of International Concern. This...

Skin cancer is more treatable in the early stages since it spreads slowly to other parts of the body. Early detection is essential due to the rising number of cases of skin cancer, as well as the high fatality rate and high expense of medical treatment. Deep Learning algorithms have lately been used to improve the performance of a variety of biomed...

Network embedding plays a critical role in many applications. Node classification, link prediction, and network visualization are examples of such applications. Attributed network embedding aims to learn the low-dimensional representation of network nodes by integrating network architecture and attribute information. The network architectures of ma...

With the emergence of new information technology fields and various usages of internet applications, securing massive amounts and multiple varieties of multimedia data has become a significant challenge. Hence, it is essential to investigate and develop new cryptographic algorithms to ensure the protection and privacy of multimedia data at rest and...

Purpose To assess whether the integration between (a) functional imaging features that will be extracted from diffusion‐weighted imaging (DWI); and (b) shape and texture imaging features as well as volumetric features that will be extracted from T2‐weighted magnetic resonance imaging (MRI) can noninvasively improve the diagnostic accuracy of thyroi...

In recent years, the adoption of machine learning has grown steadily in different fields affecting the day-to-day decisions of individuals. This paper presents an intelligent system for recognizing human’s daily activities in a complex IoT environment. An enhanced model of capsule neural network called 1D-HARCapsNe is proposed. This proposed model...

Many previous research studies have demonstrated game strategies enabling virtual players to play and take actions mimicking humans. The Case-Based Reasoning (CBR) strategy tries to simulate human thinking regarding solving problems based on constructed knowledge. This paper suggests a new Action-Based Reasoning (ABR) strategy for a chess engine. T...

This study proposes a novel computer assisted diagnostic (CAD) system for early diagnosis of diabetic retinopathy (DR) using optical coherence tomography (OCT) B-scans. The CAD system is based on fusing novel OCT markers that describe both the morphology/anatomy and the reflectivity of retinal layers to improve DR diagnosis. This system separates r...

Due to the availability of a huge number of electronic text documents from a variety of sources representing unstructured and semi-structured information, the document classification task becomes an interesting area for controlling data behavior. This paper presents a document classification multimodal for categorizing textual semi-structured and u...

Nowadays, Coronavirus (COVID-19) considered one of the most critical pandemics in the earth. This is due its ability to spread rapidly between humans as well as animals. COVID_19 expected to outbreak around the world, around 70 % of the earth population might infected with COVID-19 in the incoming years. Therefore, an accurate and efficient diagnos...

With the development of cognitive computing, machine learning techniques, and big data analytics, cognitive support is crucial for automated industrial production. The real-time automated visual inspection in industrial production is a challenging task. Speed and accuracy are crucial factors for the process of automating the defect detection. Many...

Most of query translation disambiguation approaches rely on a parallel corpus to resolve the translation ambiguity. This is because parallel corpus are good resources for resolving translation ambiguity. However, they have limitations in translating with a low convergence, specific domain, handling multi-word expressions, and non-availability in al...

This paper handles the problem of intercepting a superior missile using a formation of lower-capabilities pursuers. The problem is formulated as multi-player differential game and solved using optimal control techniques. This approach makes use of the Apollonius circles as a final path constraint of the problem in order to achieve the capturing con...

We introduce a method for measuring the quantity of online content of a set of languages at domain level. This measurement is used for building a Multi-Lingual Information Retrieval (MLIR) system that identifies which languages are strongly represented on the internet about a specific query topic. The system architecture includes two modules; the o...

Deep learning (DL) approaches have demonstrated the ability to learn useful features directly from data for a wide variety. The difficulties in learning deep generative or discriminative models can be overcome by an initial unsupervised learning step that maps the inputs to useful intermediate representations. DL systems can automatically discover...

Semantic Relatedness (SR) defines a relation between linguistic items. These items could be words, phrases, or documents. There are many interesting related applications such as information extraction, words sense disambiguation, text summarization, and text clustering. The task of quantifying SR manually is fairly natural and axiomatic, whereas it...

The security of sensitive information is an urgent need in today’s communication, principally in cloud and Internet of Things (IoT) environments. Therefore, a well-designed security mechanism should be carefully considered. This paper presents a new framework for secure information in fog cloud IoT. In the framework, the user in one location embeds...

Semantic web provides information for humans as well as computers to semantically maintain a large-scale of data and provide a meaningful content of unstructured data. It offers new benefits for big-data research and applications. Big data is a new term refers to a massive collection of datasets from various sources in structured, semi-structured,...

Recently, increasing attention has been attracted to social networking sentiment analysis. Twitter is an online real-time social network and microblogging service that allows certified participants to distribute short posts called tweets. Twitter plays a major role in showing how consumers discover, research, and share information about brands and...

This paper presents a new approach for reinforcing a recent method named Evolution-Constructed (ECO). ECO is an ensemble learning approach which combines predictions of multiple weak classifiers. Our framework includes two enhancements. First, we utilize different linear/nonlinear base classifiers. Second, we employ different ensemble types such as...

The evolution of the Internet of things (IoT) and the continuing increase in the number of sensors connected to the Internet impose big challenges regarding the management of the resulting deluge of data and network latency. Uploading sensor data over the web does not add value. Therefore, an efficient knowledge extraction technique is badly needed...

Biometrics technology stands as one of the major backbones that had united biosciences and technology representing an instrument for security and forensics researchers to develop more accurate, robust and confidence systems. Starting from uni-modal biometrics as finger print , face , speech and iris passing through multimodal biometrics based on un...

A new efficient design of second-order spectral-null (2-OSN) codes is presented. The new codes are obtained by applying the technique used to design parallel decoding balanced (i.e., 1-OSN) codes to the random walk method introduced by some of the authors for designing 2-OSN codes. This gives new non-recursive efficient code designs, which are less...

Anti-aging and looking young with a full of vigor appearance with no Facial volume depletion and deepening lines of facial expression is a dream of every human being in life. Researchers in dermal and cosmetic fields had spent many years looking for solutions to aging signs and wrinkles other than surgeries. Botox is a skin rejuvenation cosmetic pr...

Grid task scheduling is one of the most important parts in Grid resource management system. In this paper, a new task scheduling algorithm is proposed and implemented based on Min-Min algorithm with taking into consideration load balancing. This proposed algorithm works by executing the small tasks by slower resources while executing the relatively...

Cloud computing is emerging as a replacement for traditional physical hardware computing in the area of parallel and distributed computing. Clouds consist of a collection of virtualized resources that can be provisioned on demand, depending on the users’ needs. Cloud computing faces the grand quantity of the user groups, as well as the quantity of...

In many communication media, optical systems, and some VLSI systems, only one errors type, either 0 → 1 or 1 → 0, can occur in any data word and the decoder knows a priori the error type. These types of errors are called asymmetric errors. Asymmetric Varshamov channels could be used to model some physical systems such as multilevel flash memories w...

A new efficient coding scheme is given for second-order spectral-null (2-OSN) codes. The new method applies the Knuth's optimal parallel decoding scheme for balanced (i.e., 1-OSN) codes to the random walk method introduced by Tallini and Bose to design 2-OSN codes. If k ∈ IN is the length of a 1-OSN code then the new 2-OSN coding scheme has length...

Web service composition denotes the design of new Web services by composing existing ones. An important challenge is to design a business model which makes Web service composition practical, by automating as much as possible the various composition steps. However, such a composition may generate undesirable behaviours, which are referred to as feat...

Vehicular networks are expected to enable vehicles on the road to exchange safety information; enhancing traffic flow and minimizing accidents. With vehicle positions being the most frequently exchanged information in vehicular networks, it becomes imperative to establish a strong level of trust in the announced positions before a vehicle initiates...

Vehicular networks will enable vehicles on the road to utilize wireless communication to exchange safety information; enhancing traffic flow and minimizing accidents. With vehicle positions being the most frequently exchanged information in vehicular networks; it becomes imperative to establish a strong level of trust in the announced positions bef...

Web services are the main stones of building and developing internal organization business workflow. If the connectivity of these web services is not well defined, companies that rely on them may face many problems especially when integration and composition are needed. Companies need a well-defined harmonic structure of the web service connectivit...

The error types in some VLSI systems and some communication media is of asymmetrie in nature. In this paper, for selective-repeat ARQ protocol over m(≥2)-ary asymmetrie channel, some analysis of the throughput when using All Asymmetric Error Detecting (AAED) codes are given. For these codes, the number of retransmissions needed to receive all codew...

Nowadays, service connectivity adaptation grows to be one of the most important topic in SOC (Service Oriented Computing). Due to the increasing in accessing the business processes of the information systems, there is a lot of traffic to a specific part of its business logic (BL) that causes Bottlenecked. To solve this traffic problem, we need to a...

Service oriented architecture (SOA) is a dominant architecture for today software development architecture. The companies must adapt their systems to face the changes in the business processes. In SOA, each business process may be represented by one or more services. To achieve greater automation of enterprises business processes, enterprises need...

This paper is concerned with recognition of isolated Arabic words by using a combined classifier. A combined classifier is based on a number of Back-Propagation/LVQ neural networks with different parameters and architectures. Some feature extraction methods are examined. The MFCC features resulted in the best performance. For the unseen test set, t...

Word Sense Disambiguation (WSD) is the process of selecting a sense of an ambiguous word in a given context from a set of predefined senses. Sense Inventory usually comes from a dictionary or thesaurus. In Arabic, the main cause of word ambiguity is the lack of diacritics of the most digital documents so the same word can occurs with different sens...

Some new classes of systematic t-unidirectional error-detecting codes over Z_m are designed. It is shown that the constructed codes can detect two errors using two check digits. Furthermore, the constructed codes can detect up to m^r-2 + r-2 errors using r ges 3 check bits. A bound on the maximum number of detectable errors usin...

In the automatic repeat request (ARQ) protocol, the sender keeps retransmitting a code word until it receives a positive acknowledgment from the receiver sent through the feedback channel. This correspondence proposes plain and diversity combining hybrid ARQ protocol communication schemes suitable for the m(ges2)-ary asymmetric channel using t-asym...