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2. Bitcoin Prediction Analysis Using Deep Learning Techniques

Author

Muneeb, Muhammad, Islam, Noman, Al Reshan, Mana Saleh, Hamdi, Mohammed, Alshahrani, Hani, Soomro, Safeeullah, Celebi, Emre, Series Editor, Chen, Jingdong, Series Editor, Gopi, E. S., Series Editor, Neustein, Amy, Series Editor, Liotta, Antonio, Series Editor, Di Mauro, Mario, Series Editor, Shaikh, Asadullah, editor, Alghamdi, Abdullah, editor, Tan, Qing, editor, and El Emary, Ibrahiem M. M., editor

Published
2024
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8. Knowledge Incorporation in Requirements Traceability Recovery

Author

Ghannem, Adnane, Hamdi, Mohammed Salah, Kessentini, Marouane, Ammar, Hany, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zhang, Junjie James, Series Editor, Kim, Hyuncheol, editor, Kim, Kuinam J., editor, and Park, Suhyun, editor

Published
2021
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9. A Prudent-Precedence Concurrency Control Protocol for High Data Contention Database Enviornments

Author

Xiong, Weidong, Yu, Feng, Hamdi, Mohammed, and Hou, Wen-Chi

Subjects
Computer Science - Databases
Abstract

In this paper, we propose a concurrency control protocol, called the Prudent-Precedence Concurrency Control (PPCC) protocol, for high data contention database environments. PPCC is prudently more aggressive in permitting more serializable schedules than two-phase locking. It maintains a restricted precedence among conflicting transactions and commits the transactions according to the serialization order established in the executions. A detailed simulation model has been constructed and extensive experiments have been conducted to evaluate the performance of the proposed approach. The results demonstrate that the proposed algorithm outperforms the two-phase locking and optimistic concurrency control in all ranges of system workload., Comment: 14 pages, 16 figures, 1 table

Published
2016
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15. Social Media-Based Surveillance Systems for Health Informatics Using Machine and Deep Learning Techniques: A Comprehensive Review and Open Challenges.

Author

Amin, Samina, Zeb, Muhammad Ali, Alshahrani, Hani, Hamdi, Mohammed, Alsulami, Mohammad, and Shaikh, Asadullah

Subjects
DEEP learning, MEDICAL informatics, MACHINE learning, SOCIAL media, MASS surveillance
Abstract

Social media (SM) based surveillance systems, combined with machine learning (ML) and deep learning (DL) techniques, have shown potential for early detection of epidemic outbreaks. This review discusses the current state of SM-based surveillance methods for early epidemic outbreaks and the role of ML and DL in enhancing their performance. Since, every year, a large amount of data related to epidemic outbreaks, particularly Twitter data is generated by SM. This paper outlines the theme of SM analysis for tracking health-related issues and detecting epidemic outbreaks in SM, along with the ML and DL techniques that have been configured for the detection of epidemic outbreaks. DL has emerged as a promising ML technique that adapts multiple layers of representations or features of the data and yields state-of-the-art extrapolation results. In recent years, along with the success of ML and DL in many other application domains, both ML and DL are also popularly used in SM analysis. This paper aims to provide an overview of epidemic outbreaks in SM and then outlines a comprehensive analysis of ML and DL approaches and their existing applications in SM analysis. Finally, this review serves the purpose of offering suggestions, ideas, and proposals, along with highlighting the ongoing challenges in the field of early outbreak detection that still need to be addressed. [ABSTRACT FROM AUTHOR]

Published
2024
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27. Storing Join Relationships for Fast Join Query Processing

Author

Hamdi, Mohammed, Yu, Feng, Alswedani, Sarah, Hou, Wen-Chi, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Benslimane, Djamal, editor, Damiani, Ernesto, editor, Grosky, William I., editor, Hameurlain, Abdelkader, editor, Sheth, Amit, editor, and Wagner, Roland R., editor

Published
2017
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34. The Existence and the Stability of Weighted Pseudo Almost Periodic Solution of High-Order Hopfield Neural Network

Author

Aouiti, Chaouki, M’hamdi, Mohammed Salah, Chérif, Farouk, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Villa, Alessandro E.P., editor, Masulli, Paolo, editor, and Pons Rivero, Antonio Javier, editor

Published
2016
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36. Numerical Modeling of Stress Distribution in a Bi-Grain Small Scale Silicon Ingot Including Crucible Deformation

Author

Gouttebroze, Sylvain, M’Hamdi, Mohammed, Yurko, James A., editor, Allanore, Antoine, editor, Bartlett, Laura, editor, Lee, Jonghyun, editor, Zhang, Lifeng, editor, Tranell, Gabriella, editor, Meteleva-Fischer, Yulia, editor, Ikhmayies, Shadia, editor, Budiman, Arief Suriadi, editor, Tripathy, Prabhat, editor, and Fredrickson, Guy, editor

Published
2016
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39. EVALUATION OF THE ANTIFUNGAL ACTIVITY OF HYDROLYZED CAMEL WHEY PROTEIN AGAINST SOME FUNGI IN SOFT CHEESE

Author

Eman Nafei, Ekbal Ibrahim, Hend Elbarbary, and Hamdi Mohammed

Abstract

Purpose: The current study’s aim is to investigate the effect of hydrolyzed whey protein concentrate (WPC) derived from camel’s milk on growth of some fungi inoculated in soft cheese during refrigerated storage. Methodology: The pepsin-trypsin (P-T) camel´s WPC hydrolysate (20 mg/g) was incorborated in to soft cheese and their effects on the survival of Candida albicans, Asperigillus fumigatus Asperigillus flavus and Asperigillus niger (103-104cfu/g) were examined till cheese deterioration. Findings: The results revealed that P-T hydrolysate had the ability to decrease the viability of C.albicans, A.fumigatus A.flavus and A.niger in soft cheese. C.albicans was the most sensitive strain. Unique contribution to theory, practice and policy: Thus, camel´s WPC hydrolysates can be exploited as. This study was conducted to elaborate antifungals from camel´s WPC after enzymatic hydrolysis which could serve as a safe alternative of natural antifungal agents in soft cheese

Published
2022

42. IMPACT OF HYDROLYZED CAMEL´S WHEY PROTEIN CONCENTRATE ON SOFT CHEESE QUALITY

Author

Ekbal Adel, Eman Nafei, Hend Elbarbary, and Hamdi Mohammed

Abstract

Purpose: The current study’s aim is to investigate the effect of hydrolyzed whey protein concentrate (WPC) derived from camel’s milk on quality and organoleptic properties of soft cheese during refrigerated storage. Methodology: Two concentrations (10 and 20 mg/g) of camel´s WPC and its hydrolysates [pepsin (P) and pepsin-trypsin (P-T) hydrolysates] were incorborated in to soft cheese and their effects on total bacterial, phsychrophilic, aerobic spore formers, coliforms and yeast & mold counts were calculated till end of refrigerated storage peroid. Also, flavour, texture and appearance of treated cheese groups were evaluated compared to control one. Findings: The results revealed that the higher concentration of WPC and its hydrolysates, the more significant decrease in the microbial load and increase the shelf life up to 34th days with P-T hydrolysate (20 mg/g) compared with the control with a shelf-life of 18th days only at refrigerated temperature (4oC).This hydrolysate showed also the highest degree of hydrolysis (DH%) of 34.06% ± 1.53 and protein concentration of 30.72%± 3.16. The maximum score for body, and texture and appearance was recorded for the cheese sample containing P-T hydrolysate (20 mg/g), while the maximum flavour score was recorded to pepsin (P) hydrolysate (10 mg/g), compared with unhydrolyzed WPC concentrations and control soft cheese groups. Unique contribution to theory, practice and policy: This study was conducted to elaborate antimicrobials from camel´s WPC after enzymatic hydrolysis which could serve as a potential natural presrvatives in soft cheese without altering the sensory characteristics.

Published
2022

48. Accelerated material development for laser powder-bed fusion using the arc melting process

Author

Reiersen, Magnus, Gunnæs, Anette Eleonora, S. Azar, Amin, Diplas, Spyridon, Du, Qiang, M&#39, and hamdi, Mohammed

Subjects
General Medicine
Abstract

Metal additive manufacturing has in recent years gained an increasing amount of attention, especially the subgroup of laser powder-bed fusion and aluminium alloys. However, established alloys are designed for casting and forging and often require alterations to make them eligible for the challenging processing conditions. The material selection is limited and calls for new alloys tailored specifically for additive manufacturing. In this work, an analysis suite is proposed as a tool to investigate material systems quickly and in-expensively for use in additive manufacturing. The selected material system is the Al7075 aluminium alloy, which is susceptible to cracking caused by hot tearing. To resolve this issue, it is mixed with varying quantities of silicon. The effect of silicon on solidification, grain refinement, and the resulting crack susceptibility is investigated with thermodynamical calculations considering the columnar to equiaxed transition, optical microscopy, and scanning electron microscopy after being processed by arc melting. The thermodynamical calculations of the compositions indicated a trend between the decreased columnar to equiaxed transition point at elevated temperature gradients to the silicon concentration. The experimental results reflected a similar trend by observing the reduction of the average grain size in the material system from 2470 μm2 to 323 μm2 for a composition with 0 wt.% and 10.5 wt.% silicon respectively. A composition of interest from the result was further mixed with zirconium hydride to investigate its grain refining properties on the alloy. The average grain size was reduced from 1055 μm2 to 453 μm2 by the inclusion of 0.24 wt.% zirconium. As such, this work provides a new approach to investigating a material system for use in additive manufacturing.

Published
2023

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