Mohamed Hamada

• Cairo University

As edge computing gains attention across various domains, the demand for lightweight deep learning models capable of running efffciently on resource-constrained edge devices has surged. This survey investigates the landscape of lightweight deep learning models tailored for edge computing environments. The survey explores various model compression t...

As edge computing gains attention across various domains, the demand for lightweight deep learning models capable of running efffciently on resource-constrained edge devices has surged. This survey investigates the landscape of lightweight deep learning models tailored for edge computing environments. The survey explores various model compression t...

Abstract—Stroke, a global leading cause of disability and mortality, places a significant burden on healthcare systems and individuals. It accounts for approximately 5 million of total global deaths, affecting millions of people annually. The early identification of stroke symptoms holds paramount significance as it not only facilitates immediate m...

This study delved into leveraging deep learning techniques to classify different types of cervical cancer images, recognizing the disease's prevalence and criticality. We employed a dataset comprising cervical images and investigated the utilization of the VGG16 model as a foundational architecture. To enhance performance, we incorporated various i...

The automated code evaluation system (AES) is mainly designed to reliably assess user-submitted code. The code is compiled and then tested in a unified environment with predefined input and output test cases. Due to their extensive range of applications and the accumulation of valuable resources, AESs are becoming increasingly popular. Research on...

Recommender systems (RSs) are increasingly recognized as intelligent software for predicting users’ opinions on specific items. Various RSs have been developed in different domains, such as e-commerce, e-government, e-resource services, e-business, e-library, e-tourism, and e-learning, to make excellent user recommendations. In e-learning technolog...

The volume of image data produced today is increasing, which makes storing and transferring them a difficult task. There are some fields where loss-less image compression can be valuable because it allows the compression of images without compromising their quality. In this paper, we propose a lossless image compression technique based on linear pr...

Recent breakthroughs in computer vision have led to the invention of several intelligent systems in different sectors. In transportation, this advancement led to the possibility of proposing autonomous vehicles. This recent technology relies heavily on wireless sensors and Deep learning. For an autonomous vehicle to navigate safely on highways, the...

Recent advances in computing allows researchers to propose the automation of hydroponic systems to boost efficiency and reduce manpower demands, hence increasing agricultural produce and profit. A completely automated hydroponic system should be equipped with tools capable of detecting plant diseases in real-time. Despite the availability of deep-l...

Cervical cancer is one of the leading causes of premature mortality among women worldwide and more than 85% of these deaths are in developing countries. There are several risk factors associated with cervical cancer. In this paper, we developed a predictive model for predicting the outcome of patients with cervical cancer, given risk patterns from...

Recently, researchers proposed the automation of hydroponic systems to improve efficiency and minimize manpower requirements. Thus increasing profit and farm produce. However, a fully automated hydroponic system should be able to identify cases such as plant diseases, lack of nutrients, and inadequate water supply. Failure to detect these issues ca...

With the recent advances in clinical technologies, a huge amount of data has been accumulated for breast cancer diagnosis. Extracting information from the data to support the clinical diagnosis of breast cancer is a tedious and time-consuming task. The use of machine learning and data mining techniques has significantly changed the whole process of...

With the advent of new technologies in the medical field, huge amounts of cancerous data have been collected and are readily accessible to the medical research community. Over the years, researchers have employed advanced data mining and machine learning techniques to develop better models that can analyze datasets to extract the conceived patterns...

Text compression is one of the most significant research fields, and various algorithms for text compression have already been developed. This is a significant issue, as the use of internet bandwidth is considerably increasing. This article proposes a Burrows–Wheeler transform and pattern matching-based lossless text compression algorithm that uses...

Accurate prediction of crude oil price can successfully be used to deviate from the negative impact of the crude oil price hike. Limitations of previous studies prompt the proposal of an alternative approach for the hybridization of Cuckoo Search Algorithm with lévy flight and Back-propagation neural network (CSBP) for the estimation of crude oil p...

Recommender Systems (RSs) are termed as web-based applications that make use of filtering methods and several machine learning algorithms to suggest relevant user objects. It can be said that some techniques are usually adopted or trained to develop these systems that generate lists of suitable recommendations. Conventionally, RS uses a single rati...

Recommender systems (RSs) are web-based tools that use various machine learning and filtering methods to propose useful items for users. Several techniques have been used to develop such a system for generating a list of useful recommendations. Traditionally, RSs use a single rating to represent preferences of a user on an item. A multi-criteria re...

Recommender systems are powerful online tools that help to overcome problems of information overload. They make personalized recommendations to online users using various data mining and filtering techniques. However, most of the existing recommender systems use a single rating to represent the preference of user on an item. These techniques have s...

We often make decisions on the things we like, dislike, or even don’t care about. However, taking the right decisions becomes relatively difficult from a variety of items from different sources. Recommender systems are intelligent decision support software tools that help users to discover items that might be of interest to them. Various techniques...

Accuracy improvement is among the primary key research focuses in the area of recommender systems. Traditionally, recommender systems work on two sets of entities, Users and Items, to estimate a single rating that represents a user's acceptance of an item. This technique was later extended to multi-criteria recommender systems that use an overall r...

Accuracy improvement has been one of the most outstanding issues in the recommender systems research community. Recently, multi-criteria recommender systems that use multiple criteria ratings to estimate overall rating have been receiving considerable attention within the recommender systems research domain. This paper proposes a neural network mod...

Achieving significant learning goals in computer science and engineering courses require practical interaction between course instructor and students, and also within class members through multimedia learning environment. This is because multimedia learning becomes the major pedagogical approach as a result of high advancement and usage of digital...

To achieve meaningful learning goals, both pedagogues and tutees need frequent supports on how to obtain relevant materials. Recommendation systems have been proved as important tools that assist learners in getting useful learning objects. Nowadays, various recommendation techniques are used to build a system that can find and suggests learning ob...

With advances in social network sites and easy access to internet services, many learners depend on suggestions from other people on the internet for easy access to very essential information concerning learning materials, and also to collaborate with each other in order to exchange ideas. Current recommender systems for learning focus on recommend...

Many factors can hinder learning process especially in the classroom, but the greatest among all is the student's learning preferences. This research work implemented a fuzzy-like mobile-based learning system that can be used to determine the learning preferences of engineering students based on their responses in answering 55 questions with multip...