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Elfadil Abdalla Mohamed Abdalla
- Assistant Professor
- Ext: 6041
Elfadil Abdalla Mohamed has received his MSc and Ph.D. in Computer Science from University of Technology Malaysia (UTM), Malaysia, in 2002. He is currently working as an Assistant Professor at College of Information Technology, Ajman University, United Arab Emirates. His main areas of research interest are in data mining and database.
Education
- Ph.D. in Computer Science-Faculty of Computer Science and Information Systems-University of Technology Malaysia, 2002, Malaysia.
- M.Sc. in Computer Science, Faculty of Computer Science and Information Systems, University of Technology Malaysia, 1997. Graduation degree: 3.55 out of 4.00
- B.Sc. Honour in Computer Sciences and Statistics, School of Mathematical Science, University of Khartoum, 1992, Khartoum, Sudan. Graduation Degree: Second class division one.
Ph.D. in Computer Science-Faculty of Computer Science and Information Systems-University of Technology Malaysia, 2002, Malaysia.
M.Sc. in Computer Science, Faculty of Computer Science and Information Systems, University of Technology Malaysia, 1997. Graduation degree: 3.55 out of 4.00
B.Sc. Honour in Computer Sciences and Statistics, School of Mathematical Science, University of Khartoum, 1992, Khartoum, Sudan. Graduation Degree: Second class division one.
Experience
- Assistant Professor at College of Information Technology, Ajman University , 6th of September, 2017 until now
- Assistant professor at the Department of Management Information Systems, College of Business Administration, Alain University of Science and Technology, UAE, February 2010 - 4th of September, 2017
- Assistant Professor at College of Information Technology, Ajman University, UAE, September 2002- 31 January 2010
Assistant Professor at College of Information Technology, Ajman University , 6th of September, 2017 until now
Assistant professor at the Department of Management Information Systems, College of Business Administration, Alain University of Science and Technology, UAE, February 2010 - 4th of September, 2017
Assistant Professor at College of Information Technology, Ajman University, UAE, September 2002- 31 January 2010
Teaching Area
- Database, Information system, Programming, Data mining and data warehouse, Knowledge Management, Change management
Database, Information system, Programming, Data mining and data warehouse, Knowledge Management, Change management
Research
- Data mining
- Data analysis
- Database
Data mining
Data analysis
Database
Publications
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1. Shorouq Eletter, Nasser Taleb, Elfadil A. Mohamed, Loay Alnaji (2017). “Exploring interns’ satisfaction: A case study of United Arab Emirates.” International Journal of Applied Business and Economic Research, Volume 15, Issue 22, 2017, Pages 547-560
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2. Elfadil A. Mohamed and Nasser Taleb (2017). “Framework for the Applications of Data Mining Technique in Viral Marketing Using Social Network.” 30th B&ESI CONFERENCE Abu Dhabi, UAE, January 8-11, 2017
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4. Nayla Alkhatri , Nazar Zaki, Elfadil Mohammed, Musa Shallal (2016). “Data Mining Techniques to Predict the Ranking of E- Government Services.” 2016 12th International Conference on Innovations in Information Technology (IIT), IEEE Xplore Digital Library, Pages: 1 - 6, DOI: 10.1109/INNOVATIONS.2016.7880047
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5. Alramzana Nujum Navaz, Elfadil Mohammed, Mohamed Adel Serhani, Nazar Zaki. (2016). “The Use of Data Mining Techniques to Predict Mortality and Length of Stay in an ICU.” 2016 12th International Conference on Innovations in Information Technology (IIT), IEEE Xplore Digital Library, Pages: 1 - 5, DOI: 10.1109/INNOVATIONS.2016.7880045 year: 2016
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6. Noura AlDarmaki, Elfadil A. Mohamed , Noura AlMansouri, Ibrahim Elsiddig Ahmed, Nazar Zaki (2016). “Prediction of the Closing Price in the Dubai Financial Market: A Data Mining Approach.” 2016 3rd MEC International Conference on Big Data and Smart City (ICBDSC), IEEE Xplore Digital Library, Pages: 1 – 7, year: 2016
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7. Elfadil A. Mohamed, Nasser Taleb, and Raed Ahmad Tawfeq Said (2016). “Evaluating the effectiveness of e-course delivery and e-assessment using Course Management System.” International Conference for Academic Disciplines, 31-January-2016, Al Ain, UAE
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8. Nazar Zaki and Elfadil A. Mohamed (2016). “A Combination of Protein-Protein Interaction Network Topological and Biological Process Features for Multiprotein Complex Detection.” Book chapter in a book titled “Emerging Trends in Applications and Infrastructures for Computational Biology, Bioinformatics, and Systems Biology Systems and Applications”. Publisher: Elsevier Morgan Kaufman. page 305-315 , March, 22, 2016
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9. Nasser Taleb and Elfadil Abdalla (2015). “Framework for Evaluating the Effectiveness of Data Mining in the Analysis of Dynamic Data for Supporting Financial Decision-Making,” 2015 Global Business & Economics Anthology, Vol. 1, USA. The paper also appeared in the Proceeding of the 26th B&ESI CONFERENCE Al Ain, UAE, March 1-4, 2015
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10. Nazar Zaki, Elfadil A. Mohamed, and Antonio Mora (2015). “Characterization of Protein Complexes and Sub-complexes in Protein-protein Interaction Databases.” Journal of Biochemistry Research International. Volume 2015, Article ID 245075, USA
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11. Elfadil A. Mohamed (2014). “Predicting Causes of Traffic Road Accidents Using Multi-class Support Vector Machines.” Journal of Communication and Computer, Vol. 11, Number 5, 2014, USA. The paper also appeared in the Proceeding of the 10th International Conference on Data Mining, July 23-24, 2014, Las Vegas, Nevada, USA
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12. Elfadil A. Mohamed, F. H. Saad, and Omer I. E. Mohamed (2014). “Effects of Classification Techniques on Medical Reports Classification.” International Journal of Computers & Technology. Volume 13, No 2.
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13. Omer I. E. Mohamed, F. H. Saad, and Elfadil A. Mohamed (2012). “Evaluation of Partitional Algorithms for Clustering Medical Documents.” International Journal of Emerging Technology and Advanced Engineering. Volume 2, Issue 4
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14. Nasser Taleb and Elfadil A/Alla Mohamed (2012) “Using Ticket History Method to Serialize Transactions In Distributed Databases.” Proceeding of the International conference on Excellence in Business, University of Sharjah, Sharjah, United Arab Emirates, May 2012.
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1. Elfadil A. Mohamed, Elgilani El. Elshareif, Omer Ishag Eldai Mohamed (2019). “Designing a Generic Information Systems Audit Framework to Improve the Quality of Audit in Higher Education.” Journal of Computer Science, Vol(15), Issue(5), PP. 664-672 May 10, 2019. DOI : 10.3844/jcssp.2019.664.672
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2. Mariam AlMarzooqi, Srikanth Bezawada, Asayel AlNaqbi, Elfadil A. Mohamed, AlMheiri, A., Nazar Zaki (2018). “Increase the exploitation of mars satellite images via deep learning techniques.” 2018 International Conference on Robotics, Control and Automation Engineering, RCAE 2018; Beijing; China
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3. Eiman Alothali, Nazar Zaki, Elfadil A. Mohamed, and Hany Alashwal (2018). “Detecting Social Bots on Twitter: A Literature Review. “ 2018 International Conference on Innovations in Information Technology (IIT). 18-19 Nov. 2018. IEEE Xplore Digital Library, DOI: 10.1109/INNOVATIONS.2018.8605995. Page : 175 – 180
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4. Mohammad Marjan, Nazar Zaki, and Elfadil A. Mohamed (2018). “Link Prediction in Dynamic Social Networks: A Literature Review.” IEEE CiSt'18 5th Edition International IEEE Congress on Information Science and Technology, Marrakech, Morocco, October 21 - 27, 2018. IEEE Xplore Digital Library, DOI: 10.1109/CIST.2018.8596511
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5. Maha Rahrouh, Nasser Taleb, and Elfadil A. Mohamed (2018). “Evaluating the Usefulness of E-Learning Management System Delivery in Higher Education.” Int. J. of Economics and Business Research 2018 - Vol. 16, No.2 pp. 162 – 181
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Nasser Taleb and Elfadil A. Mohamed (2020). “Cloud Computing Trends: A Literature Review.” Academic Journal of Interdisciplinary Studies, Vol (9), No (1), January 2020
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Balqis Al Breiki, Nazar Zaki, and Elfadil A. Mohamed (2019). “Using Educational Data Mining Techniques to Predict Student Performance.” The International Conference on Electrical and Computing Technologies and Applications, 2019, November 19 - 21, 2019, RAK, UAE. IEEE Xplore Digital Library, DOI: 10.1109/ICECTA48151.2019.8959676.
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Vasila Al Khaldi, Nazar Zaki, Essam Zaneldin, and Elfadil A. Mohamed (2019). “Using Data Mining Techniques to Identify Construction Claims Causes: A Case Study.” The International Conference on Electrical and Computing Technologies and Applications, 2019, November 19 - 21, 2019, RAK, UAE. IEEE Xplore Digital Library, DOI: 10.1109/ICECTA48151.2019.8959800
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Elfadil Abdalla Mohamed, Nazar Zaki, and Mohammad Marjan (2019). “Current Trends and Challenges in Link Prediction Methods in Dynamic Social Networks: A Literature Review.” Advances in Science, Technology and Engineering Systems Journal, Vol. 4, No. 6, 244-254 (2019). DOI: 10.25046/aj040631
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M. M. Yagoub, Aishah A. Alsereidi, Elfadil A. Mohamed, Punitha Periyasamy, Reem Alameri, Salama Aldarmaki, and Yaqein Alhashmi. (2020). Newspapers as a validation proxy for GIS modelling in Fujairah, United Arab Emirates: identifying flood‑prone areas. Natural Hazards Journal, 17 July 2020, DOI: https://doi.org/10.1007/s11069-020-04161-y
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Nazar Zaki and Elfadil A. Mohamed (2021). The Estimations of the COVID-19 Incubation Period: A Scoping Reviews of the Literature. Journal of Infection and Public Health, 8 February 2021, https://doi.org/10.1016/j.jiph.2021.01.019.
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Elfadil A. Mohamed, Ibrahim Ahmed Elsiddig, Riyadh A.K. Mehdi, and Hanan Hussain (2021). Impact of corporate performance on stock price predictions in the UAE markets: Neuro-fuzzy model. Intelligent Systems in Accounting, Finance and Management. 18 January 2021, https://doi.org/10.1002/isaf.1484.
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Elgilani Elshareif and Elfadil A. Mohamed (2021). The Effects of E-Learning on Students' Motivation to Learn in Higher Education. Online Learning Journal, Volume 25 Issue 3 , Sept, 2021, pp. 128-143.
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Nazar Zaki, Harsh Singh and Elfadil A. Mohamed (2021). Identifying Protein Complexes in Protein-protein Interaction Data Using Graph Convolutional Network. IEEE ACCESS, Vol (9), 2021, Pages 123717 – 123726
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JournalTETIANA HABUZA, NAZAR ZAKI, ELFADIL A. MOHAMED, and YAUHEN STATSENKO, Deviation From Model of Normal Aging in Alzheimer's Disease: Application of Deep Learning to Structural MRI Data and Cognitive Tests, IEEE Access, Vol: 10, pp.53234 - 53249, May 2022, doi: 10.1109/ACCESS.2022.3174601
1. Shorouq Eletter, Nasser Taleb, Elfadil A. Mohamed, Loay Alnaji (2017). “Exploring interns’ satisfaction: A case study of United Arab Emirates.” International Journal of Applied Business and Economic Research, Volume 15, Issue 22, 2017, Pages 547-560
2. Elfadil A. Mohamed and Nasser Taleb (2017). “Framework for the Applications of Data Mining Technique in Viral Marketing Using Social Network.” 30th B&ESI CONFERENCE Abu Dhabi, UAE, January 8-11, 2017
4. Nayla Alkhatri , Nazar Zaki, Elfadil Mohammed, Musa Shallal (2016). “Data Mining Techniques to Predict the Ranking of E- Government Services.” 2016 12th International Conference on Innovations in Information Technology (IIT), IEEE Xplore Digital Library, Pages: 1 - 6, DOI: 10.1109/INNOVATIONS.2016.7880047
5. Alramzana Nujum Navaz, Elfadil Mohammed, Mohamed Adel Serhani, Nazar Zaki. (2016). “The Use of Data Mining Techniques to Predict Mortality and Length of Stay in an ICU.” 2016 12th International Conference on Innovations in Information Technology (IIT), IEEE Xplore Digital Library, Pages: 1 - 5, DOI: 10.1109/INNOVATIONS.2016.7880045 year: 2016
6. Noura AlDarmaki, Elfadil A. Mohamed , Noura AlMansouri, Ibrahim Elsiddig Ahmed, Nazar Zaki (2016). “Prediction of the Closing Price in the Dubai Financial Market: A Data Mining Approach.” 2016 3rd MEC International Conference on Big Data and Smart City (ICBDSC), IEEE Xplore Digital Library, Pages: 1 – 7, year: 2016
7. Elfadil A. Mohamed, Nasser Taleb, and Raed Ahmad Tawfeq Said (2016). “Evaluating the effectiveness of e-course delivery and e-assessment using Course Management System.” International Conference for Academic Disciplines, 31-January-2016, Al Ain, UAE
8. Nazar Zaki and Elfadil A. Mohamed (2016). “A Combination of Protein-Protein Interaction Network Topological and Biological Process Features for Multiprotein Complex Detection.” Book chapter in a book titled “Emerging Trends in Applications and Infrastructures for Computational Biology, Bioinformatics, and Systems Biology Systems and Applications”. Publisher: Elsevier Morgan Kaufman. page 305-315 , March, 22, 2016
9. Nasser Taleb and Elfadil Abdalla (2015). “Framework for Evaluating the Effectiveness of Data Mining in the Analysis of Dynamic Data for Supporting Financial Decision-Making,” 2015 Global Business & Economics Anthology, Vol. 1, USA. The paper also appeared in the Proceeding of the 26th B&ESI CONFERENCE Al Ain, UAE, March 1-4, 2015
10. Nazar Zaki, Elfadil A. Mohamed, and Antonio Mora (2015). “Characterization of Protein Complexes and Sub-complexes in Protein-protein Interaction Databases.” Journal of Biochemistry Research International. Volume 2015, Article ID 245075, USA
11. Elfadil A. Mohamed (2014). “Predicting Causes of Traffic Road Accidents Using Multi-class Support Vector Machines.” Journal of Communication and Computer, Vol. 11, Number 5, 2014, USA. The paper also appeared in the Proceeding of the 10th International Conference on Data Mining, July 23-24, 2014, Las Vegas, Nevada, USA
12. Elfadil A. Mohamed, F. H. Saad, and Omer I. E. Mohamed (2014). “Effects of Classification Techniques on Medical Reports Classification.” International Journal of Computers & Technology. Volume 13, No 2.
13. Omer I. E. Mohamed, F. H. Saad, and Elfadil A. Mohamed (2012). “Evaluation of Partitional Algorithms for Clustering Medical Documents.” International Journal of Emerging Technology and Advanced Engineering. Volume 2, Issue 4
14. Nasser Taleb and Elfadil A/Alla Mohamed (2012) “Using Ticket History Method to Serialize Transactions In Distributed Databases.” Proceeding of the International conference on Excellence in Business, University of Sharjah, Sharjah, United Arab Emirates, May 2012.
1. Elfadil A. Mohamed, Elgilani El. Elshareif, Omer Ishag Eldai Mohamed (2019). “Designing a Generic Information Systems Audit Framework to Improve the Quality of Audit in Higher Education.” Journal of Computer Science, Vol(15), Issue(5), PP. 664-672 May 10, 2019. DOI : 10.3844/jcssp.2019.664.672
2. Mariam AlMarzooqi, Srikanth Bezawada, Asayel AlNaqbi, Elfadil A. Mohamed, AlMheiri, A., Nazar Zaki (2018). “Increase the exploitation of mars satellite images via deep learning techniques.” 2018 International Conference on Robotics, Control and Automation Engineering, RCAE 2018; Beijing; China
3. Eiman Alothali, Nazar Zaki, Elfadil A. Mohamed, and Hany Alashwal (2018). “Detecting Social Bots on Twitter: A Literature Review. “ 2018 International Conference on Innovations in Information Technology (IIT). 18-19 Nov. 2018. IEEE Xplore Digital Library, DOI: 10.1109/INNOVATIONS.2018.8605995. Page : 175 – 180
4. Mohammad Marjan, Nazar Zaki, and Elfadil A. Mohamed (2018). “Link Prediction in Dynamic Social Networks: A Literature Review.” IEEE CiSt'18 5th Edition International IEEE Congress on Information Science and Technology, Marrakech, Morocco, October 21 - 27, 2018. IEEE Xplore Digital Library, DOI: 10.1109/CIST.2018.8596511
5. Maha Rahrouh, Nasser Taleb, and Elfadil A. Mohamed (2018). “Evaluating the Usefulness of E-Learning Management System Delivery in Higher Education.” Int. J. of Economics and Business Research 2018 - Vol. 16, No.2 pp. 162 – 181
Nasser Taleb and Elfadil A. Mohamed (2020). “Cloud Computing Trends: A Literature Review.” Academic Journal of Interdisciplinary Studies, Vol (9), No (1), January 2020
Balqis Al Breiki, Nazar Zaki, and Elfadil A. Mohamed (2019). “Using Educational Data Mining Techniques to Predict Student Performance.” The International Conference on Electrical and Computing Technologies and Applications, 2019, November 19 - 21, 2019, RAK, UAE. IEEE Xplore Digital Library, DOI: 10.1109/ICECTA48151.2019.8959676.
Vasila Al Khaldi, Nazar Zaki, Essam Zaneldin, and Elfadil A. Mohamed (2019). “Using Data Mining Techniques to Identify Construction Claims Causes: A Case Study.” The International Conference on Electrical and Computing Technologies and Applications, 2019, November 19 - 21, 2019, RAK, UAE. IEEE Xplore Digital Library, DOI: 10.1109/ICECTA48151.2019.8959800
Elfadil Abdalla Mohamed, Nazar Zaki, and Mohammad Marjan (2019). “Current Trends and Challenges in Link Prediction Methods in Dynamic Social Networks: A Literature Review.” Advances in Science, Technology and Engineering Systems Journal, Vol. 4, No. 6, 244-254 (2019). DOI: 10.25046/aj040631
M. M. Yagoub, Aishah A. Alsereidi, Elfadil A. Mohamed, Punitha Periyasamy, Reem Alameri, Salama Aldarmaki, and Yaqein Alhashmi. (2020). Newspapers as a validation proxy for GIS modelling in Fujairah, United Arab Emirates: identifying flood‑prone areas. Natural Hazards Journal, 17 July 2020, DOI: https://doi.org/10.1007/s11069-020-04161-y
Nazar Zaki and Elfadil A. Mohamed (2021). The Estimations of the COVID-19 Incubation Period: A Scoping Reviews of the Literature. Journal of Infection and Public Health, 8 February 2021, https://doi.org/10.1016/j.jiph.2021.01.019.
Elfadil A. Mohamed, Ibrahim Ahmed Elsiddig, Riyadh A.K. Mehdi, and Hanan Hussain (2021). Impact of corporate performance on stock price predictions in the UAE markets: Neuro-fuzzy model. Intelligent Systems in Accounting, Finance and Management. 18 January 2021, https://doi.org/10.1002/isaf.1484.
Elgilani Elshareif and Elfadil A. Mohamed (2021). The Effects of E-Learning on Students' Motivation to Learn in Higher Education. Online Learning Journal, Volume 25 Issue 3 , Sept, 2021, pp. 128-143.
The recent COVID-19 pandemic has forced educational institutions worldwide to adopt e-learning. UAE higher education institutions have implemented e-learning systems and programs to cope with this unprecedented situation. This paper measured the strength of association between key aspects of e-learning systems and programs and students’ motivation to learn in Ajman University (AU). Cronbach’s coefficient alpha was used to test the internal consistency reliability of key aspects of e-learning (EL-8) and students’ motivation to learn (SML-16). Exploratory factor analysis was used to test the validity of, and coherence of patterns in, the data. Parametric and non-parametric methods were used to investigate the strength of association between key aspects of e-learning and students’ motivation to learn in AU. The results indicated that motivation variables were more strongly correlated with both e-teaching materials and e-assessments key aspects relative to others such as e-discussion, and e-grade checking and feedback
About the journal
Nazar Zaki, Harsh Singh and Elfadil A. Mohamed (2021). Identifying Protein Complexes in Protein-protein Interaction Data Using Graph Convolutional Network. IEEE ACCESS, Vol (9), 2021, Pages 123717 – 123726
Protein complexes are groups of two or more polypeptide chains that bind to form noncovalent networks of protein interactions. Over the past decade, researchers have created a number of means of computing the ways in which protein complexes and their members can be identied through these interaction networks. Although most of the existing methods identify protein functional complexes from the protein-protein interaction networks (PPIs) at a fairly decent level, the applicability of advanced graph network methods has not yet been adequately investigated. This paper proposes various graph convolutional network (GCN) methods to improve the detection of protein complexes. We rst formulate the protein complex detection problem as a node classication problem. Then, we developed a Neural Overlapping Community Detection (NOCD) model to cluster the nodes (proteins) using a complex afliation matrix. A representation learning approach, that combines a multi-class GCN feature extractor (to obtain the nodes' features) and a mean shift clustering algorithm (to perform the clustering), is also utilized. We convert the dense-dense matrix operations into dense-sparse or sparse-sparse matrix operations to improve the efciency of the multi-class GCN network by reducing space and time complexities. The proposed solution signicantly improves the scalability of the existing GCN. Finally, we apply clustering aggregation to nd the best protein complexes. A grid search is then performed on various detected complexes obtained via three well-known protein detection methods, namely ClusterONE, CMC, and PEWCC, with the help of the Meta-Clustering Algorithm (MCLA) and the Hybrid Bipartite Graph Formulation (HBGF). We test the proposed GCN-based methods on various publicly available datasets and nd that they perform signicantly better than previous state-of-the-art methods. The code/data are available for free download from https://github.com/Analystharsh/GCN_complex_detection.
About the journal
TETIANA HABUZA, NAZAR ZAKI, ELFADIL A. MOHAMED, and YAUHEN STATSENKO, Deviation From Model of Normal Aging in Alzheimer's Disease: Application of Deep Learning to Structural MRI Data and Cognitive Tests, IEEE Access, Vol: 10, pp.53234 - 53249, May 2022, doi: 10.1109/ACCESS.2022.3174601
Psychophysiological and cognitive tests as well as other functional studies can detect pre-symptomatic stages of dementia. When assembled with structural data, cognitive tests diagnose NDs more reliably thus becoming a multimodal diagnostic tool. Objective. Our main goal is to improve screening for dementia by studying an association between the brain structure and its function. Hypothetically, the brain structure-function association has features specific for either disease-related cognitive deterioration or normal neurocognitive slowing while aging. Materials and methods. We studied a total number of 287 cognitively normal cases, 646 of mild cognitive impairment, and 369 of Alzheimer's disease. To work out a new marker of neurodegeneration, we created a convolutional neural network-based regression model and predicted the cognitive status of the cognitively preserved examinee from the brain MRI data. This was a model of normal aging. A big deviation from the model suggests a high risk of accelerated cognitive decline. Results. The deviation from the model of normal aging can accurately distinguish cognitively normal subjects from MCI patients (AUC D 0.9957). We also achieved creditable performance in the MCI-versus-AD classification (AUC D 0.9793). We identified a considerable difference in the MMSE test between A-positive and A-negative demented individuals according to ATN-criteria ( 6.27 ± 1.82 vs 5.32 ± 1.9; p < 0:05). Conclusion. The deviation from the model of normal aging can be potentially used as a marker of dementia and as a tool for differentiating Alzheimer's disease from non-Alzheimer's dementia. To find and justify a reliable threshold levels, further research is required.