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ElGamal, N., A. E. Bastawissy, and G. Galal-Edeen, "Data warehouse testing", Proceedings of the {Joint} {EDBT}/{ICDT} 2013 {Workshops}: ACM, pp. 1–8, 2013. Abstract
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Esheiba, L., I. M. A. Helal, A. Elgammal, and M. E. El-Sharkawi, "A Data Warehouse-Based System for Service Customization Recommendations in Product-Service Systems", Sensors, vol. 22, no. 6, 2022. AbstractWebsite
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Esheiba, L., I. M. A. Helal, A. Elgammal, and M. E. El-Sharkawi, "A Data Warehouse-Based System for Service Customization Recommendations in Product-Service Systems", Sensors, vol. 22, issue 6, pp. 27, 2022. sensors-22-02118-v2_2.pdf
Alwakeel, A. S., and A. H. Mehana, "Data-Aided Channel Estimation for Multiple-Antenna Users in Massive MIMO Systems", IEEE Transactions on Vehicular Technology, vol. 68, issue 11, pp. 10752 - 10760, 2019.
Gomaa, A., and L. Jalloul, "Data-Aided I/Q Imbalance Estimation and Compensation in OFDM Systems", IEEE Communications Letters, vol. 18, issue 3, pp. 459-462, 2014.
Salem, F., F. Schintke, T. Schütt, and A. Reinefeld, Data-flow scheduling for a scalable FLESnet, , Darmstadt, Zuse Insitute Berlin, pp. 130-131, 04/2018. Abstract

FLES is the first-level event selector of the CBM project. For the timeslice building, the FLESnet software uses
tightly coupled processes. Unfortunately, slow processes and network congestion cause a serious performance bottleneck, especially in large systems. We, therefore, developed a scheduling mechanism to minimize the synchronization overhead and enhance the scalability. We highlight the main components of our new scheduling mechanism and we show how it enhances the performance of FLESnet on large deployments.

El-HossinyShemis, E., A. M. Gadallah, and H. A. Hefny, "A Data-Sensitive Approach for Fuzzy Concept Extraction", International Journal of Intelligent Engineering and Systems, vol. 11, issue 5, pp. 194-204, 2018. a_data-sensitive_approach_for_fuzzy_concept_extraction.pdf
, Database and Expert Systems Applications - 26th International Conference, {DEXA} 2015, Valencia, Spain, September 1-4, 2015, Proceedings, Part {II}, , vol. 9262: Springer, 2015. Abstract
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, Database and Expert Systems Applications - 29th International Conference, {DEXA} 2018, Regensburg, Germany, September 3-6, 2018, Proceedings, Part {II}, , vol. 11030: Springer, 2018. Abstract
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, Database and {XML} Technologies, 6th International {XML} Database Symposium, XSym 2009, Lyon, France, August 24, 2009. Proceedings, , vol. 5679: Springer, 2009. Abstract
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Korany, M., M. Boraiy, Y. Eissa, Y. Aoun, and A. - M. M. Wahab, "A database of multi-year (2004–2010) quality-assured surface solar hourly irradiation measurements for the Egyptian territory.", Earth System Science Data, Copernicus Publications, vol. 8, pp. 105-113, 2016.
, Database Systems for Advanced Applications - 22nd International Conference, {DASFAA} 2017, Suzhou, China, March 27-30, 2017, Proceedings, Part {I}, , vol. 10177: Springer, 2017. Abstract
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Abdalla, M. M. F., "Date of boll opening and its association with agronomic characters in some Egyptian cotton varieties [Egypt].", Bulletin of Faculty of Agriculture, Cairo Univ., 1985. Abstract
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Hassan, H. M. M., O. K. Ahmed, H. A. El-Shemy, and A. S. Afify, "Date pollen extracts as plant growth substances for banana tissue culture", The Role of Biochemistry in Environment and Agriculture, Giza, Egypt, 3 May, 2006.
Malik, M. R., A. Mnzava, E. Mohareb, A. Zayed, A. H. A. Al Kohalani, and H. El Bushra, Date: Friday, April 4, 2014, , Submitted. Abstract
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Helmi, F. M., S. M. Ismael, and N. M. Ali, "Dating and creative restoration of a cartonage mask from the late period in Saqqara ", 5th International conference on Archaeology and heritage in a changing world, Cairo, Egypt, 29-31 October, 2017.
Afifi, H., S. A. M. Hamed, S. Mohamedy, and M. Dawod, "A dating approach of a refundable wooden Egyptian coffin lid", SCIENTIFIC CULTURE, vol. 5, issue 1, pp. 15-22, 2019. 5_1_2_affifi-et-al.pdf
Afifi, H., S. A. El-Kader, Samia Mohamedy, and M. Dawod, "A Dating Approach Of A Refundable Wooden Egyptian Coffin Lid ", scientific culture, vol. , Vol.5 , issue 1, pp. 15-22., 2019.
Mahmoud, A. S., A. M. Fahmy, A. M. Mahmoud, A. A. Bayomi, and A. Y. E. - Amir, "Dating of Long Bone Fracture Healing among Egyptian Pediatrics by Radiography (X-Ray)", indian journal of forensic medicine & toxicology, vol. 14, issue 3, pp. 1048-1052, 2020.
Ali, M. A., and E. Hanin, "DATING VINTAGE HAND-COLORED REAL PHOTO POSTCARDS: A REVIEW AND APPLIED STUDY", International Journal of Conservation Science , vol. 12, issue 2, pp. 335-349, 2021.
Helmi, F. M., G. A. Mahgoub, and N. M. Ali, "Dating, restoration,and coservation of an archaeological wooden door No.760, Coptic museum, Cairo, Egypt", 4th International Congress on Science and technology for the safeguard for cultura heritage in the Mediterranean Basin, Cairo, Egypt, 6-8 Decmber, 2009.
Nivin, G., M. A. Salem, and B. Meffert, "Daubechies Versus Biorthogonal Wavelets for Moving Object Detection in Traffic Monitoring Systems ", Informatik-Berichte, 2009.
Amr Abdalla, "Day +100 Platelet Count Predicts Survival After Allogeneic Hematopoietic Stem Cell Transplantation in Children With Hematologic Malignancies", Clinical Lymphoma, Myeloma & Leukemia, vol. 19, issue 5, pp. e221-7, 2019.
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Hisham Moneib, H. Hafez, Amr Abdalla, O. Hassanain, L. Lehmann, and A. Elhaddad, "Day+ 100 Platelet Count Predicts Survival Post Allogeneic Hematopoietic Stem Cell Transplantation in Children with Hematologic Malignancies", Clinical Lymphoma Myeloma and Leukemia, 2019.
M.Fawzy, A.Badr, M.Reda, and I.Farag, "DBCLUM: Density based Clustering and Merging Algorithm", International Journal of Computer Applications, vol. 79, pp. 1-6, 2013. Abstract

Clustering is a primary method for DB mining. The clustering process becomes very challenge when the data is different densities, different sizes, different shapes, or has noise and outlier. Many existing algorithms are designed to find clusters. But, these algorithms lack to discover clusters of different shapes, densities and sizes. This paper presents a new algorithm called DBCLUM which is an extension of DBSCAN to discover clusters based on density. DBSCAN can discover clusters with arbitrary shapes. But, fail to discover different-density clusters or adjacent clusters. DBCLUM is developed to overcome these problems. DBCLUM discovers clusters individually then merges them if they are density similar and joined. By this concept, DBCLUM can discover different-densities clusters and adjacent clusters. Experiments revealed that DBCLUM is able to discover adjacent clusters and different-densities clusters and DBCLUM is faster than DBSCAN with speed up ranges from 11% to 52%.