Kamal Eldahshan

Al-Azhar University · Department of Mathematics

Forecasting violence has become a critical obstacle in the field of video monitoring to guarantee public safety. Lately, YOLO (You Only Look Once) has become a popular and effective method for detecting weapons. However, identifying and forecasting violence remains a challenging endeavor. Additionally, the classification results had to be enhanced...

As data grow exponentially, the demand for advanced intelligent solutions has become increasingly urgent. Unfortunately, not all businesses have the expertise to utilize machine learning algorithms effectively. To bridge this gap, the present paper introduces a cost-effective, user-friendly, dependable, adaptable, and scalable solution for visualiz...

Motion prediction has gotten much attention in the past few years. It has endless uses either in real life or in virtual life (gaming). The current dynamic motion prediction models, such as the Markov model, depend only on the object motions’ history. They ignore the object’s direction and speed, which play a key role in dynamic motion prediction....

Respiratory genetic diseases are considered a major participant in the reasons of death worldwide nowadays and were one of the major participants in helping in increasing the numbers of COVID-19 patients. It is considered one of the most alarming diseases affecting in particular the respiratory system. The journey of early detection of respiratory...

Data Warehouses (DWs) are essential for enterprises, containing valuable business information and thus becoming prime targets for internal and external attacks. Data warehouses are crucial assets for organizations, serving critical purposes in business and decision-making. They consolidate data from diverse sources, making it easier for organizatio...

In the big data era, businesses are in dire need of intelligent solutions to rapidly extract valuable insights. However, not all companies possess the specialized expertise required to operate machine learning algorithms. To bridge this gap, this paper introduces a cost-effective, user-friendly, dependable, adaptable, and scalable solution for visu...

p>This paper presents a novel deep learning-based approach for anomaly detection in surveillance films. A deep network that has been trained to recognize objects and human activity in movies forms the foundation of the suggested approach. In order to detect anomalies in surveillance films, the proposed method combines the strengths of 3D-convolutio...

Cloud computing is an advanced technology that offers types of assistance on requests. Because of the huge measure of requests got from cloud clients, all requests should be managed efficiently. Therefore, the task scheduling is critical in cloud computing. The provision of computational resources in cloud is controlled by a cloud provider. It...

Cloud computing is an advanced technology that offers types of assistance on requests. Because of the huge measure of requests got from cloud clients, all requests should be managed efficiently. Therefore, the task scheduling is critical in cloud computing. The provision of computational resources in cloud is controlled by a cloud provider. It is n...

Some human diseases are recognized through of each type of White Blood Cell (WBC) count, so detecting and classifying each type is important for human healthcare. The main aim of this paper is to propose a computer-aided WBCs utility analysis tool designed, developed, and evalu- ated to classify WBCs into five types namely neutrophils, eosinophils,...

Rapid advancements in deep learning-based technologies have developed several synthetic video and audio generation methods producing incredibly hyper-realistic deepfakes. These deepfakes can be employed to impersonate the identity of a source person in videos by swapping the source's face with the target one. Deepfakes can also be used to clone the...

Flexible Manufacturing Systems (FMS) have gained recently the concern of researchers in the majority of real-world environments. One of the challenges for FMS is the existence of numerous alternatives for deciding how to allocate resources to jobs. Planning and schedule execution are handled by the FMS scheduling function. The Job Shop Scheduling P...

Numerous network cyberattacks have been launched due to inherent weaknesses. Network intrusion detection is a crucial foundation of the cybersecurity field. Intrusion detection systems (IDSs) are machine learning (ML) software proposed for making decisions without explicit programming and with little human intervention. Although ML-based IDS advanc...

Real-time task scheduling is a critical part of systems since processes must finish their work at a certain time. Large data streams require high energy efficiency and rapid response times. Real-time system performance must be improved through task scheduling on resources. Numerous researchers have recently and rapidly proposed enormous efforts wit...

Recent years have seen a significant increase in the data volumenarity, which has led to the emergence of Big Data. Therefore, it has become impossible to dispense with the term big data in dealing with many applications; one of these applications is the healthcare system.The healthcare system generates a vast amount of data that premise around dru...

This study focuses on meeting the challenges of big data visualization by using of data reduction methods based the feature selection methods. To reduce the volume of big data and minimize model training time (Tt) while maintaining data quality. We contributed to meeting the challenges of big data visualization using the embedded method based “Sele...

Rapid advances in deep learning models have made it easier for public and crackers to generate hyper-realistic deepfake videos in which faces are swapped. Such deepfake videos may constitute a significant threat to the world if they are misused to blackmail public figures and to deceive systems of face recognition. As a result, distinguishing these...

Industry 4.0 production environments and smart manufacturing systems integrate both the physical and decision-making aspects of manufacturing operations into autonomous and decentralized systems. One of the key aspects of these systems is a production planning, specifically, Scheduling operations on the machines. To cope with this problem, this pap...

Due to the rapid development in our world today, multiple data sources from various sources such as sensors, the internet of things, healthcare data, etc., have been increased. So, it is necessary to analyze these data to obtain valuable data and visualize it with visualization tools. Big data visualization plays an essential role in today's world...

The growth of the Internet of Things (IoT) generates new processing, networking infrastructure, data storage, and management capabilities. This massive volume of data may be used to provide high-value information for decision support and data-intensive science research, etc. However, owing to the nature of IoT in distribution, virtualisation, cloud...

Currently, relational database management systems (RDBMSs) face different challenges in application development due to the massive growth of unstructured and semi-structured data. This introduced new DBMS categories, known as not only structured query language (NoSQL) DBMSs, which do not adhere to the relational model. The migration from relational...

Within the exponential growth in raw data production, attributed in no small part to social media-Facebook, Youtube, and others. Video is proving to be the most important data type thanks to the substantial amount of raw data it contains, requiring an efficient way to be understood, organized, structured, and stored for ease of retrieval. Hence, an...

In this paper, we approach the problem of detecting and diagnosing COVID-19 infections using multisource scan images including CT and X-ray scans to assist the healthcare system during the COVID-19 pandemic. Here, a computer-aided diagnosis (CAD) system is proposed that utilizes analysis of the CT or X-ray to diagnose the impact of damage in the re...

Big data technologies are used majorly for computational biology research nowadays due to the emerge of massive amounts of biological data that have been generated and collected at an unprecedented speed and scale and with different structures. As an example, the processing of billions of DNA sequence data per day represents the new generation of s...

Nowadays, the world suffers a Coronavirus mutation in 2019 (COVID-19). The COVID-19 data sources possess three main characteristics: big volume, velocity, and variety. These challenges have compelled the authors to employ Big Data technology, data mining techniques, and Ontology-based approaches instead of using a statistics hypothesis. Big Data Fr...

Recently, the deepfake techniques for swapping faces have been spreading, allowing easy creation of hyper-realistic fake videos. Detecting the authenticity of a video has become increasingly critical because of the potential negative impact on the world. Here, a new project is introduced; You Only Look Once Convolution Recurrent Neural Networks (YO...

Blockchain technology offers several advantages to Human Resource Management (HRM); easier verification of job candidates’ education and skills, efficient recording of job candidates’ education, expertise, and training, easier payment of cross-border transfers, international expenses, and tax liabilities, elimination of fraud and improved cyber-sec...

Security attacks become daily news due to an exposure of a security threat in a widely used software. Taking software security into consideration during the analysis, design, and implementation phases is a must. A software application should be protected against any security threat such as unauthorized distribution or code retrieval. Due to the lac...

We live in a time where data stream by the second, which makes intrusion detection a more difficult and tiresome task, and in turn intrusion detection systems require an efficient and improved detection mechanism to detect the intrusive activities. Moreover, handling the size, complexity, and availability of big data requires techniques that can cr...

Relational databases are usually used for data storage and retrieval. They are suitable for limited data volume. But when it comes to Bigdata, we need to use more flexible databases that satisfy the need to handle semi-structured and unstructured data. These databases are called NoSQL (Not only SQL) databases. This type of database was developed to...

Background As the COVID-19 crisis endures and the virus continues to spread globally, the need for collecting epidemiological data and patient information also grows exponentially. The race against the clock to find a cure and a vaccine to the disease means researchers require storage of increasingly large and diverse types of information; for doct...

Background As the COVID-19 crisis endures and the virus continues to spread globally, the need for collecting epidemiological data and patient information also grows exponentially. The race against the clock to find a cure and a vaccine to the disease means researchers require storage of increasingly large and diverse types of information; for doct...

Classification of human face images into emotion categories is a hard challenge. Deep learning is mostly effective for this task. In this paper, we propose a facial emotions recognition system based on Deep Belief Networks (DBNs) and Quantum Particle Swarm Optimization (QPSO). The proposed methodology is composed of four phases: first, the input im...

This paper presents a general Semantic Smart World framework (SSWF), to cover the Migratory birds’ paths. This framework combines semantic and big data technologies to support meaning for big data. In order to build the proposed smart world framework, technologies such as cloud computing, semantic technology, big data, data visualization, and the I...

Background Portable-devices applications (Android applications) are becoming complex software systems that must be developed quickly and continuously evolved to fit new user requirements and execution contexts. Applications must be produced rapidly and advance persistently in order to fit new client requirements and execution settings. However, cat...

Most authentication schemes are using passwords only to restrict access to services. Which are suffering from many weaknesses, such as key-logger attack and dictionary attack. Also, other authentication schemes are using physical token such as smart cards. These schemes are also impractical due to their infrastructure requirements. Since, many rese...

Software design has a main impact in the quality of the software systems. Anti-patterns are shortcomings exist in the software designs and impact negatively software quality. Mobile applications (apps) with anti-patterns have bad quality and short lifetime. Many empirical studies have assessed that the anti-patterns have a negative impact on change...

Background: Portable applications (Android applications) are becoming increasingly complicated by mind-boggling programming frameworks. Applications must be produced rapidly and advance persistently in order to fit new client requirements and execution settings. However, catering to these imperatives may bring about poor outline decisions on design...

Background: Portable applications (Android applications) are becoming increasingly complicated by mind-boggling programming frameworks. Applications must be produced rapidly and advance persistently in order to fit new client requirements and execution settings. However, catering to these imperatives may bring about poor outline decisions on design...

Scheduling is the process of allocating processes to the CPU in order to optimize some objective function. There are many algorithms used to schedule processes. The Round Robin (RR) CPU scheduling algorithm is one of these algorithms which is effective in time sharing and real time operating systems. It gives reasonable response time. But it...

This issue includes the following articles; P1130945914, author="Alaa Sheta and Mohammad Salamah", title="An Innovative NXT Mobile Robot System for Landmine Detection", P1111733578, author="Prof. Dr. Kamen M. Yanev", title="Advanced D-Partitioning Stability Analysis of Digital Control Systems with Multivariable Parameters", P1111748593, author="Ali...

This issue includes the following articles; P1130945914, author="Alaa Sheta and Mohammad Salamah", title="An Innovative NXT Mobile Robot System for Landmine Detection", P1111733578, author="Prof. Dr. Kamen M. Yanev", title="Advanced D-Partitioning Stability Analysis of Digital Control Systems with Multivariable Parameters", P1111748593, author="Ali...

Scheduling is the process of allocating processes to the CPU in order to optimize some objective function. There are many algorithms used to schedule processes. The Round Robin (RR) CPU scheduling algorithm is one of these algorithms which is effective in time sharing and real time operating systems. It gives reasonable response time. But it suffer...

The Round Robin algorithm is a CPU scheduling algorithm that is designed especially for time sharing systems. Each process is assigned a slice of time called time quantum to execute. To increase the performance of a Round Robin algorithm, it is important to choose an optimal time quantum. Many algorithms developed the Round Robin algorithm. This pa...

This issue includes the following papers; P1121653529, AUTHOR="Sameh Magdy and Tarek Mahmoud and Mohamed Ibrahim", TITLE="Improved Face Recognition based on Hidden Markov Model" P1121705544, AUTHOR="Afaf Abd Elkader Abd Elhafiz", TITLE="Enhancing the Minimum Average Scheduling Algorithm (MASA) based on Makespan Minimizing", P1121711553, AUTHOR="Jim...

This issue includes the following papers; P1121653529, AUTHOR="Sameh Magdy and Tarek Mahmoud and Mohamed Ibrahim", TITLE="Improved Face Recognition based on Hidden Markov Model" P1121705544, AUTHOR="Afaf Abd Elkader Abd Elhafiz", TITLE="Enhancing the Minimum Average Scheduling Algorithm (MASA) based on Makespan Minimizing", P1121711553, AUTHOR="Jim...

The amount of videos over the internet and media storage systems has dramatically increased. This poses challenges in video content understanding and management. A video is a complex and resource consuming media. In addition, efficient use of video data requires the data to be understood and accessed without having to watch it entirely. For those r...

Coupling Biometrics with Quantum algorithms offers a new range of security. In this paper, we give a brief overview of the field of biometrics specially face authentication. Also, we propose a quantum face authentication method. The proposed method phases are detection face boundaries, image resizing, remove noisy, feature extraction, matching and...

Most authentication schemes are using physical token such as smart cards to restrict services. Although these schemes have been widely deployed for various kinds of daily applications; there are severe challenges regarding their infrastructure requirements and security. This paper proposes an efficient authentication protocol based on user's machin...

Scheduling is the process of allocating tasks to resources in order to optimize some objective function. There have been many algorithms used to schedule tasks on their resources .One of these scheduling algorithms is the Enhanced Max-min task scheduling algorithm which selects a task with average execution time(average or nearest greater than aver...

Recently, mobile crowd sensing (MCS) is an important approach for collecting data from the participants in the urban streets. The main problem in collecting data process is how to cover all segments the street sides and select a minimal number of participants in each street segment that preserves the energy of the mobile devices and prolongs the MC...

in the context of mobile computing and multimedia processing, video summarization plays an important role for video browsing, streaming, indexing and storing. In this paper, an effective and efficient video summarization approach for mobile devices is proposed. The goal of this approach is to generate a video summary (static and dynamic) based on V...

This issue includes the following articles; P1121521384, EL GRAOUI EL MEHDI and BENELALLAM IMADE and BOUYAKHF EL HOUSSINE, "A novel Hybrid Search for Minimal Perturbation Problems based on Backjumping and Dynamic backtracking methods", P1121517374, Sara Elsir M. Ahmed and Alaa F. Sheta and Hossam Faris, "Evolving Stock Market Prediction Models Usin...

This issue (DOI: 10.13140/RG.2.1.1578.1843) includes the following articles; P1120838366 B. S. ANAMI and D. G. SAVAKAR Improved Method for Identification and Classification of Foreign Bodies Mixed Food Grains Image Samples P1120841394 K.Sri Rama Krishna and J.Lakshmi Narayana and L.Pratap Reddy Performance Evaluation of ANN Models for the Analysis...

This issue includes four papers, they are; P1151424332 by Vishnu Murthy. G and Vakulabharanam Vijaya Kumar which entitled Overwriting Grammar Model to Represent 2D Image Patterns. P1151442347 by M.A. Fkirin and S.M. Badway and A.K. Helmy and S.A. Mohamed which entitled Measuring Sub Pixel Erratic Shift in Egyptsat-1 Aliased Images: proposed method....

RC4 is the most widely used stream cipher algorithm. It is used to protect valuable electronic information. How- ever, RC4 encryption algorithm su�ers from a secret key generation as a seed problems. This paper proposes an intelligent dynamic secret key generation as a seed by em- ploying an Evolutionary Algorithm (EA). The proposed RC4-EA method t...