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- Adaptive Learning Environment (1)
- Adaptive Learning System (1)
- Churn prediction (1)
- Classification (1)
- Construction projects; Performance; Covid-19; Crisis (1)
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- Credit card fraud detection (1)
- Data mining and Prediction model. (1)
- Decision tree (1)
- Deep learning (1)
- F-PID (1)
- Frequency stability. (1)
- Functions as a Service (1)
- Information Systems Development (1)
- Intension to use (1)
- Internet (1)
- Machine learning (1)
- Microgrid (1)
- Microservice Architecture (1)
- Multilayer perceptron (1)
- Naïve Bayes (1)
- Pantograph Robot; Manipulator Dynamics; Flower Pollination (FP); Nonlinear PID (NLPID); Fractional Order PID (FOPID; Model reference adaptive control (MRAC) ); Fuzzy PD+I control. (1)
- Platform as a Service (1)
- Quality of service (1)
- RROSTF-PID (1)
- Random forest (1)
- Recommendation system (1)
- SVM (1)
- Self-Efficacy (1)
- Transmission tower; GP; cost optimization (1)
- Virtual inertial control (1)
Articles 1 - 10 of 10
Full-Text Articles in Computer Engineering
An Enhanced Adaptive Learning System Based On Microservice Architecture, Abdelsalam Helmy Ibrahim, Mohamed Eliemy, Aliaa Abdelhalim Youssif
An Enhanced Adaptive Learning System Based On Microservice Architecture, Abdelsalam Helmy Ibrahim, Mohamed Eliemy, Aliaa Abdelhalim Youssif
Future Computing and Informatics Journal
This study aims to enhance Adaptive Learning Systems (ALS) in Petroleum Sector in Egypt by using the Microservice Architecture and measure the impact of enhancing ALS by participating ALS users through a statistical study and questionnaire directed to them if they accept to apply the Cloud Computing Service “Microservices” to enhance the ALS performance, quality and cost value or not. The study also aims to confirm that there is a statistically significant relationship between ALS and Cloud Computing Service “Microservices” and prove the impact of enhancing the ALS by using Microservices in the cloud in Adaptive Learning in the Egyptian …
Visual Question Answering: A Survey, Gehad Assem El-Naggar
Visual Question Answering: A Survey, Gehad Assem El-Naggar
Future Computing and Informatics Journal
Visual Question Answering (VQA) has been an emerging field in computer vision and natural language processing that aims to enable machines to understand the content of images and answer natural language questions about them. Recently, there has been increasing interest in integrating Semantic Web technologies into VQA systems to enhance their performance and scalability. In this context, knowledge graphs, which represent structured knowledge in the form of entities and their relationships, have shown great potential in providing rich semantic information for VQA. This paper provides an abstract overview of the state-of-the-art research on VQA using Semantic Web technologies, including knowledge …
Performance Comparison Of Several Control Algorithms For Tracking Control Of Pantograph Mechanism, Laylaa Mahmoud Eng, Mohamed Shamseldin Dr, Mohamed Sallam Dr, Abdelghany Mohamed Prof
Performance Comparison Of Several Control Algorithms For Tracking Control Of Pantograph Mechanism, Laylaa Mahmoud Eng, Mohamed Shamseldin Dr, Mohamed Sallam Dr, Abdelghany Mohamed Prof
Future Engineering Journal
A sort of parallel manipulator known as a pantograph robot mechanism was created primarily for industrial requests that required high precision and satisfied speed. While tracking a chosen trajectory profile requires a powerful controller. Because it has four active robot links and one robot passive link in place of just two links like the open chain does, it can carry more loads than the open chain robot mechanism while maintaining accuracy and stability. The calculated model for a closed chain pantograph robot mechanism presented in this paper takes into account the boundary conditions. For the purpose of simulating the dynamics …
Relative Rate Observer Self-Tuning Of Fuzzy Pid Virtual Inertia Control For An Islanded Microgrid, Ahmed H. Mohamed, Helmy M. El Zoghby, Mohiy Bahgat, A. M. Abdel Ghany
Relative Rate Observer Self-Tuning Of Fuzzy Pid Virtual Inertia Control For An Islanded Microgrid, Ahmed H. Mohamed, Helmy M. El Zoghby, Mohiy Bahgat, A. M. Abdel Ghany
Future Engineering Journal
Expanding the usage of renewable energy in islanded microgrids leads to a reduction in its total inertia. Low inertia microgrids have difficulties in voltage and frequency control. That affected saving its stability and preventing a blackout. To improve low inertia islanded microgrids' dynamic response and save their stability, this paper presented relative rate observer self-tuning fuzzy PID (RROSTF-PID) based on virtual inertia control (VIC) for an islanded microgrid with a high renewable energy sources (RESs) contribution. RROSTF-PID based on VIC's success in showing remarkable improvement in the microgrid's dynamic response and enhancement of its stability. Moreover, it handles different contingency …
Credit Card Fraud Detection Using Machine Learning Techniques, Nermin Samy Elhusseny, Shimaa Mohamed Ouf, Amira M. Idrees Ami
Credit Card Fraud Detection Using Machine Learning Techniques, Nermin Samy Elhusseny, Shimaa Mohamed Ouf, Amira M. Idrees Ami
Future Computing and Informatics Journal
This is a systematic literature review to reflect the previous studies that dealt with credit card fraud detection and highlight the different machine learning techniques to deal with this problem. Credit cards are now widely utilized daily. The globe has just begun to shift toward financial inclusion, with marginalized people being introduced to the financial sector. As a result of the high volume of e-commerce, there has been a significant increase in credit card fraud. One of the most important parts of today's banking sector is fraud detection. Fraud is one of the most serious concerns in terms of monetary …
The Effective Strategies For Mitigation The Impact Of Covid-19 On Construction Projects In Egypt, Nora Magdy Essa, Ibrahim Mahdi, Hassan Mohamed Ibrahim
The Effective Strategies For Mitigation The Impact Of Covid-19 On Construction Projects In Egypt, Nora Magdy Essa, Ibrahim Mahdi, Hassan Mohamed Ibrahim
Future Engineering Journal
From the time when the first narrated infections in Wuhan China, in late 2019, COVID-19 has had a substantial peal on human life and health. By the early of 2020, the World Health Organization (WHO) announced the eruption of COVID-19, a public health crisis of international concern. On 11 March 2020, the World Health Organization officially announced COVID-19 a pandemic. The first case was infected in Egypt of covid-19 on Feb 14, 2020 (Gilbert et al., 2020). On 16 March 2020, the Egyptian Government began issuing decisions as preventative courses as part of the country's inclusive plan to cope with …
Estimating The Weights Of Latticed Power Transmission Towers Using Genetic Programming, Ahmed M. Ebid Dr.
Estimating The Weights Of Latticed Power Transmission Towers Using Genetic Programming, Ahmed M. Ebid Dr.
Future Engineering Journal
The recent booming in the power network industry inspired a lot of researchers to develop models to estimate the optimum cost of transmission towers. Unlike previous researches which depended on design the tower from scratch, this research depends on collecting actual database from several projects around the globe and applying the well-known (GP) technique to develop a model to predict the tower weight. The accuracy of the developed formula was about 84%. The developed model could be used in early tender stage or to check design economy.
The Factors Influencing The Acceptance Of Web-Based E-Learning System Among Academic Staffs Of Saudi Arabia, Ikhlas Zamzami
The Factors Influencing The Acceptance Of Web-Based E-Learning System Among Academic Staffs Of Saudi Arabia, Ikhlas Zamzami
Future Computing and Informatics Journal
It is possible to learn more quickly and effectively with e-learning software development because it provides learners with convenient and flexible learning environments. This allows them to progress further in their careers. Reports on web-based e-learning systems for in-service education have frequently neglected to include the viewpoint of the instructor. In order to conduct quantitative research, a sample of 50 academic staff members was selected. The purpose of this study was to investigate various factors that influence the intention to use web-based e-learning, with the theoretical foundation being provided by university lecturers. According to the findings of the study, the …
Review Of Data Mining Techniques For Detecting Churners In The Telecommunication Industry, Mahmoud Ewieda, Mohamed Ismail Roushdy, Essam Shaaban
Review Of Data Mining Techniques For Detecting Churners In The Telecommunication Industry, Mahmoud Ewieda, Mohamed Ismail Roushdy, Essam Shaaban
Future Computing and Informatics Journal
The telecommunication sector has been developed rapidly and with large amounts of data obtained as a result of increasing in the number of subscribers, modern techniques, data-based applications, and services. As well as better awareness of customer requirements and excellent quality that meets their satisfaction. This satisfaction raises rivalry between firms to maintain the quality of their services and upgrade them. These data can be helpfully extracted for analysis and used for predicting churners. Researchers around the world have conducted important research to understand the uses of Data mining (DM) that can be used to predict customers' churn. This …
Multilayer Perceptron With Auto Encoder Enabled Deep Learning Model For Recommender Systems, Subhashini Narayan
Multilayer Perceptron With Auto Encoder Enabled Deep Learning Model For Recommender Systems, Subhashini Narayan
Future Computing and Informatics Journal
In this modern world of ever-increasing one-click purchases, movie bookings, music, health- care, fashion, the need for recommendations have increased the more. Google, Netflix, Spotify, Amazon and other tech giants use recommendations to customize and tailor their search engines to suit the user’s interests. Many of the existing systems are based on older algorithms which although have decent accuracies, require large training and testing datasets and with the emergence of deep learning, the accuracy of algorithms has further improved, and error rates have reduced due to the use of multiple layers. The need for large datasets has declined as well. …