Browsing Faculty Of Computer Science Research Paper by Title

Browsing Faculty Of Computer Science Research Paper by Title

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  • DIRA: A Framework Of Data Integration Using Data Quality 
    I Abdel Monem, Reham; H El-Bastawissy, Ali; M Elwakil, Mohamed (arXiv preprint, 2016)
    Data integration is the process of collecting data from different data sources and providing user withunified view of answers that meet his requirements. The quality of query answers can be ...
  • Directional Skyline Queries 
    El-Dawy, Eman; MO Mokhtar, Hoda; El-Bastawissy, Ali (SPRINGER, 2012)
    Continuous monitoring of queries over moving objects has become an important topic as it supports a wide range of useful mobile applications. A continuous skyline query involves both static and dynamic dimensions. In the ...
  • DRTX: A Duplicate Resolution Tool forXMLRepositories 
    Mohamed Abd El-ghfar, Randa; Hamed El-Bastawissy, Ali (International Journal of Computer Science and Network Security, 2012)
    Detecting duplicates in XMLis not trivial due to structural diversityand object dependency. This paper suggests a duplicate detection and resolution tool (DRTX) which is an efficient XMLduplicates detector and ...
  • E-commerce agents and online negotiation process 
    Fathey, A; Moawad, R (IEEE, 2005)
    E-commerce agents have become more powerful tools for buying, selling and searching for products through the internet. Significantly, making use of these computer agents reduces the time users spend on trading. E-commerce ...
  • E-Govemment multi-iayers maturity model 
    Abdelghany H.; Ei-Bastawissy A.; Osman M. (Institute of Electrical and Electronics Engineers Inc., 2017)
    e-Government implementation and applications have gained a growing attention in the last decade. Countries seek to apply and extend the use of e-Government, and international organizations evaluate e-Government implementation ...
  • Early Rheumatoid Arthritis Detection by miRNA Data Analysis Using a Hybrid CNN-LSTM Deep Learning Model 
    Ali, Nehal M (IEEE, 2023-07)
    Transcriptomic data analysis has significantly evolved thanks to the high throughput data technology. Analyzing this data can notably support the early detection of several diseases. At the same time, Rheumatoid arthritis ...
  • Embodied learning via tangible user interfaces: the impact of physical interaction on learning performance 
    Neila, Chettaoui; Atia, Ayman; Bouhlel, Med Salim (Inderscience Publishers, 2022-04)
    Tangible user interfaces have been introduced as a form of Human-Computer Interaction to promote embodied learning pedagogy. This interaction modality offers the possibility to support students' cognitive development through ...
  • Empowering MBTI Personality Classification through Transformer-Based Summarization Model 
    Elmoushy, Seif; Saeed, Mostafa; Gomaa, Wael H (IEEE, 2023-07)
    The Myers-Briggs Type Indicator (MBTI) is a popular personality classification tool that utilizes the work of Carl Jung. With individuals increasingly expressing themselves online rather than in person, social media has ...
  • Empowering Short Answer Grading: Integrating Transformer-Based Embeddings and BI-LSTM Network 
    Gomaa, Wael H; Nagib, Abdelrahman E; Saeed, Mostafa M; Algarni, Abdulmohsen; Nabil, Emad (MDPI AG, 2023-06)
    Automated scoring systems have been revolutionized by natural language processing, enabling the evaluation of students’ diverse answers across various academic disciplines. However, this presents a challenge as students’ ...
  • English-Arabic Hybrid Machine Translation System using EBMT and Translation Memory 
    Amer, Eslam; Gadallah, Mahmoud; Ehab, Rana (SCIENCE & INFORMATION SAI ORGANIZATION LTD, 2019-01)
    The availability of a machine translation to translate from English-to-Arabic with high accuracy is not available because of the difficult morphology of the Arabic Language. A hybrid machine translation system between ...
  • An Enhanced Deep Learning Approach for Breast Cancer Detection in Histopathology Images 
    Ouf, Mahmoud; Abdul-Hamid, Yasser; Mohammed, Ammar (Springer, 2023-03)
    An Enhanced Deep Learning Approach for Breast Cancer Detection in Histopathology Images Mahmoud Ouf, Yasser Abdul-Hamid & Ammar Mohammed Conference paper First Online: 01 March 2023 129 Accesses Part of the Lecture ...
  • Enhanced Leukemia Cancer Classifier Algorithm 
    Abd El-Nasser, Ahmed; Shaheen, Mohamed; El-Deeb, Hesham (IEEE, 2014)
    The development of data mining applications such as classification and clustering has shown the need for machine learning algorithms to be applied to large scale data. Cancer classification has improved over the past 20 ...
  • Enhanced Parallel NegaMax Tree Search Algorithm on GPU 
    Elnaggar, Ahmed A.; Gadallah, Mahmoud; Aziem, Mostafa Abdel; El-Deeb, Hesham (IEEE, 2014)
    Parallel performance for GPUs today surpasses the traditional multi-core CPUs. Currently, many researchers started to test several AI algorithms on GPUs instead of CPUs, especially after the release of libraries such as ...
  • Enhancing AGDE Algorithm Using Population Size Reduction for Global Numerical Optimization 
    Khater Mohamed, Ali; Wagdy Mohamed, Ali; Zaki Elfeky, Ehab; Saleh, Mohamed (SPRINGER, 2018)
    Adaptive guided differential evolution algorithm (AGDE) is a DE algorithm that utilizes the information of good and bad vectors in the population, it introduced a novel mutation rule in order to balance effectively the ...
  • Evaluating the performance of meta-heuristic algorithms on CEC 2021 benchmark problems 
    Mohamed, Ali Wagdy; Sallam, Karam M; Agrawal, Prachi; Hadi, Anas A; Mohamed, Ali Khater (Springer London, 2022-09)
    To develop new meta-heuristic algorithms and evaluate on the benchmark functions is the most challenging task. In this paper, performance of the various developed meta-heuristic algorithms are evaluated on the recently ...
  • Exam Cheating Detection System with Multiple-Human Pose Estimation 
    Samir, Mohamed Amr; Maged, Youssef; Atia, Ayman (Institute of Electrical and Electronics Engineers, 19/11/2021)
    Cheating in exams is a persistent problem that contributes to academic dishonesty. In this paper we explore a variety of related work proposed as a solution for exam cheating, then we propose an exam cheating detection ...
  • Examining the Effects of Embodied Interaction Modalities on Students' Retention Skills in a Real Classroom Context 
    Chettaoui, Neila ; Atia, Ayman ; Bouhlel, Med. Salim  (SPRINGER HEIDELBERG, TIERGARTENSTRASSE 17, D-69121 HEIDELBERG, GERMANY, 06/01/2022)
    Embodied cognition theory denotes that knowledge is incorporated into the body's sensorimotor system, which facilitates learning and understanding abstract concepts. In this context, several interaction modalities have ...
  • Exploring and Classifying Beef Retail Cuts Using Transfer Learning 
    Abuzaid, Abdallah; Atia, Ayman (Institute of Electrical and Electronics Engineers Inc., 2022-09)
    An evaluation of the deep learning neural network in artificial intelligence (AI) technologies is proposed to provide a rapid recognition and immediate proper classification of the different beef retail cuts (Liver, Roast ...
  • Exploring the Impact of Interaction Modality on Students’ Learning Performance 
    Chettaoui, Neila; Atia, Ayman; Bouhle, Med Salim (SAGE Publications Inc., 2021)
    Embodied learning pedagogy highlights the interconnections between the brain, body, and the concrete environment. As a teaching method, it provides means of engaging the physical body in multimodal learning experiences ...
  • Exploring the Impact of Multimodal Adaptive Learning with Tangible Interaction on Learning Motivation 
    Chettaoui, N; Atia, A; Bouhlel, M.S (Institute of Electrical and Electronics Engineers Inc., 12/15/2020)
    Embodied learning defines a contemporary pedagogical theory focusing on ensuring an interactive learning experience through full-body movement. Within this pedagogy, several studies in Human-Computer Interaction have been ...

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