Mohammed Alrahmawy

• Doctor of Engineering
• Mansoura University

The most recent approach for measuring the image quality is the structural similarity index (SSI). This paper presents a novel algorithm based on the multi-scale structural similarity index for motion detection (MS-SSIM) in videos. The MS-SSIM approach is based on modeling of image luminance, contrast and structure at multiple scales. The MS-SSIM h...

The target of a focused crawler (FC) is to retrieve pages related to a specific domain of interest (DOI). However, FCs may be hasted if bad links were injected into their crawling queue. Hence, they will be gradually skewed away from their DOI. This paper introduces an effective modification on the behavior of FCs by adding a domain distiller. Henc...

World Wide Web is a continuously growing giant, and within the next few years, Web contents will surely increase tremendously. Hence, there is a great requirement to have algorithms that could accurately classify Web pages. Automatic Web page classification is significantly different from traditional text classification because of the presence of a...

The size and complexity of Cloud systems are growing more rapidly, and hence, the management of these cloud systems and its resources is a major research area. Resource provision with respect to SLA (Service Level Agreement) is directly tied up with customer satisfaction like providing the service with less Cost with less finshing time, for that, c...

Social media has emerged as a dominant platform where individuals freely share opinions and communicate globally. Its role in disseminating news worldwide is significant due to its easy accessibility. However, the increase in the use of these platforms presents severe risks for potentially misleading people. Our research aims to investigate differe...

The accurate classification of road surface conditions plays a vital role in ensuring road safety and effective maintenance. Vibration-based techniques have shown promise in this domain, leveraging the unique vibration signatures generated by vehicles to identify different road conditions. In this study, we focus on utilizing vehicle-mounted vibrat...

The majority of research on the Aspect-Based Sentiment Analysis (ABSA) tends to split this task into two subtasks: one for extracting aspects, Aspect Term Extraction (ATE), and another for identifying sentiments toward particular aspects, Aspect Sentiment Classification (ASC). Although these subtasks are closely related, they are performed independ...

The availability of large-scale facial datasets with the rapid progress of deep learning techniques, such as Generative Adversarial Networks, has enabled anyone to create realistic fake videos. These fake videos can potentially become harmful when used for fake news, hoaxes, and identity fraud. We propose a deep learning bagging ensemble classifier...

The interpretation of medical images into a natural language is a developing field of artificial intelligence (AI) called image captioning. This field integrates two branches of artificial intelligence which are computer vision and natural language processing. This is a challenging topic that goes beyond object recognition, segmentation, and classi...

Recently, deep neural networks (DNNs) have been used successfully in many fields, particularly, in medical diagnosis. However, deep learning (DL) models are expensive in terms of memory and computing resources, which hinders their implementation in limited-resources devices or for delay-sensitive systems. Therefore, these deep models need to be acc...

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...

Abstract: One of the issues in Computer Vision is the automatic development of descriptions for images, sometimes known as image captioning. Deep Learning techniques have made significant progress in this area. The typical architecture of image captioning systems consists mainly of an image feature extractor subsystem followed by a caption generati...

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,...

Egypt has been fighting the issue of ensuring road safety‚ reducing accidents‚ preserving the lives of citizens since its inception. For these reasons‚ precisely identifying the road condition‚ followed by effective and timely maintenance and rehabilitation measures‚ leads to an increase in the road network's safety level and lifespan. This paper p...

The Internet of things (IoT) has a variety of application domains including smart homes. A smart home is an automated intelligent home where IoT technologies are used to remotely control home appliances, manage home energy, enhance home security, and increase the comfort of home residents. On the other hand, renewable energy resources are highly sp...

Image captioning is an emerging field in machine learning. It refers to the ability to automatically generate a syntactically and semantically meaningful sentence that describes the content of an image. Image captioning requires a complex machine learning process as it involves two sub models: a vision sub-model for extracting object features and a...

Online social networks attract millions of users who post and read microblogs on a daily and even hourly basis. The most prominent of these networks is Twitter, which has more than 300 million users ranging from ordinary individuals up to heads of state, as well as news agencies and large organizations. First story detection (FSD) refers to locatin...

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...

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...

The chest X-ray is considered a signi cant clinical utility for basic examination and diagnosis. The human lung area can be affected by various infections, such as bacteria and viruses, leading to pneumonia. Ef cient and reliable classi cation method facilities the diagnosis of such infections. Deep transfer learning has been introduced for pneumon...

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...

The chest X-ray is considered a significant clinical utility for basic examination and diagnosis. The human lung area can be affected by various infections, such as bacteria and viruses, leading to pneumonia. Efficient and reliable classification method facilities the diagnosis of such infections. Deep transfer learning has been introduced for pneu...

Grey wolf optimizer (GWO) is a nature inspired optimization algorithm. It can be used to solve both minimization and maximization problems. The binary version of GWO (BGWO) uses binary values for wolves' positions rather than probabilistic values in the original GWO. Integrating BGWO with quantum inspired operations produce a novel enhanced quantum...

Automated visual inspection is becoming an important field of computer vision in many industries. The real-time inspection of flat surface products is a task full of challenges in industrial aspects that requires fast and accurate algorithms for detection and localisation of defects. Structural, statistical and filter-based approaches, such as Gabo...

Increasingly, more manufacturing companies are equipping their products with smart capabilities which allow them to provide more informed services to customers. Unfortunately, most of these companies lack enough technical capabilities to build scalable platforms to process data collected by the deployed devices. As a result, these device manufactur...

Cloud computing is a distributed computing paradigm that is deployed in many real-life applications. Many of these applications are real-time such as scientific computing, financial transactions, etc. Therefore, improving the dependability of cloud environments is extremely important to fulfill the reliability and availability requirements of diffe...

Traffic congestion is a big problem that influences the traffic flow in big cities, so better control of the traffic signals is always searched to solve this type of traffic problems. Fog computing is one of the most efficient paradigms for traffic system control as it enables connecting and analyzing big traffic data to help the control of traffic...

The growing use of cloud computing in various fields makes the dependability of clouds a major concern in both industry and academia, especially for real-time applications. In cloud computing, the processing is done on remote cloud nodes; therefore, the chances of errors occurring are increased because of the loose control over the remote nodes 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...

Cloud computing is emerging as a high performance computing environment with a large scale, heterogeneous collection of autonomous systems and flexible computational architecture. Many resource management methods may enhance the efficiency of the whole cloud computing system. The key part of cloud computing resource management is resource schedulin...

Abstract: Twitter is a social micro blogging, it has its own feature that it enables to tweet only a maximum of 140 characters per tweet. Even with this small number of characters per tweet, analyzing the tweets for billions of users faces the challenges of real-time data processing. One of the important aspects of social behavior is that we can de...

The Real-time Specification for Java provides predictable memory and scheduling models for developing real-time systems using the Java language. However, it is silent on providing communication mechanisms suitable for distributed real-time systems. In this paper we define a synchronous and asynchronous communication component model to support diffe...

The Real-time Specification of Java (RTSJ) has new memory management and scheduling models. These models require modification to existing software models and patterns or even the invention of new ones in order to be able to provide the patterns necessary to build reusable software components. In this paper we present a new memory model pattern asso...

Current technologies for mobility do not consider the real-time behavior and predictability in their implementation. So, there is a need for languages, tools, and patterns that help to develop such systems. Java has been used widely in many of those technologies. However, Java has many limitations that prevent using it for developing real-time dist...