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10,855 results on '"A. Ghanem"'

1. Thermal lens investigation of the CdSe quantum dots using dual beam z-scan technique

Author

M.D. Zidan, A. Allahham, A. Ghanem, N. Mousa, B. Abdallah, and A. Al Salman

Subjects
Thermal lens effect, CdSe Quantum dots, Thermo-optic coefficient, Optics. Light, QC350-467
Abstract

We highlighted on the thermal lens (TL) effect of Cadmium Selenide quantum dots (CdSe QDs) using dual beam z-scan technique. The thermal lens nonlinear optical properties of CdSe QDs were investigated by applying the two CW laser beams (λ = 532 nm and λ = 632.8 nm). The thermal lens parameters of the CdSe solutions, such as: the on-axis phase shift (θ), the thermal diffusivity (D), and thermal diffusion time (tc) were extracted using the theoretical thermal lens model. Our results give new insight into the CdSe QDs dissolved in toluene and are valuable for further development of semiconductor QDs optical devices.

Published
2024
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2. Diffraction ring patterns of the acid blue 29 in different solvents

Author

A. Ghanem, M.D. Zidan, and M.S. EL-Daher

Subjects
Diffraction ring patterns, Acid blue 29 dye, Thermo-optic coefficient, Nonlinear optical properties, Spatial self-phase modulation, Optics. Light, QC350-467
Abstract

The spatial self-phase modulation effect was exploited to study the nonlinear optical parameters of the acid blue 29 dye solutions. The acid blue 29 dye was used as samples and it was dissolved in four different alcohols. The trend in these experiments to investigate the influence of solvent structure on the formation and the temporal evolution of the far field self-diffraction ring patterns of the Gaussian laser beam passing through the studied samples. The nonlinear refractive index (n2), birefringence (Δn2) and thermo-optic coefficient [dn/dT] were determined from the obtained self-diffraction ring patterns. Our results have indicated that the difference between the numbers of diffraction rings is attributed to the type of the solvents and to the incident laser beam intensity.

Published
2022
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3. The Effect of Using the Connectivist Approach on Developing Secondary Stage Students' Cross-Cultural Awareness and Translation Performance

Author

Abdelkareem Ali Abdelnaeim Mehany and Asmaa Ghanem Gheith

Abstract

The present study attempted to examine the effect of using the connectivist approach on developing secondary-stage students' cross-cultural awareness and translation performance. The study comprised thirty-two first-year secondary stage students enrolled in El-Jalawea Institute, Sohag Governorate. The study adopted the quasi-experimental design. Thirty-two participants were randomly assigned to one group, and they were taught through a suggested web-based program. Data were gathered and analysed using both quantitative and qualitative instruments. A pre-post online translation and cross-cultural awareness test, an online questionnaire, and a web-based training program/blog were used in the study. Findings indicated that participants showed significantly higher levels of translation performance samples in the areas of reading comprehension, writing fluency, Computer-assisted Translation (CAT) tool usage, text analysis, and terminology search. Findings also showed significantly higher levels of cross-cultural awareness in both cognitive and affective aspects compared to students' achievement before the treatment. Participants also showed evidence of transition from word-for-word to meaning-for-meaning translation. The development of the students' performance was demonstrated by multiple measures that imply that the suggested web-based program is effective for developing secondary-stage students' translation performance and cross-cultural awareness skills.

Published
2024

5. Use of Pre- and Intensified Postprocedural Physiotherapy in Patients with Symptomatic Aortic Stenosis Undergoing Transcatheter Aortic Valve Replacement Study (the 4P-TAVR Study)

Author

M. Weber, U. Klein, A. Weigert, W. Schiller, V. Bayley-Ezziddin, D. C. Wirtz, A. Welz, N. Werner, E. Grube, G. Nickenig, J.-M. Sinning, and A. Ghanem

Subjects
Diseases of the circulatory (Cardiovascular) system, RC666-701
Abstract

Background. Physiotherapy prior to open-heart surgery lowers the rate of pneumonia and length of the hospital stay. Pneumonia is a major contributor to short-term mortality following transcatheter aortic valve replacement (TAVR). Hence, we hypothesized that pre- and intensified postprocedural physiotherapy in patients undergoing TAVR might impact the net functional and clinical outcome. Methods and Results. The 4P-TAVR study was a prospective, monocentric, randomized trial. The study was designed to compare the efficacy and safety of intensified periprocedural physiotherapy including inspiratory muscle training versus standard postprocedural physiotherapy. Patients were randomized in a 1 : 1 fashion. 108 patients were included and followed up for 90 days after TAVR. While patients in group A (control group: 50 patients, age: 81.7 ± 5.0 years, 52% male) did not receive physiotherapy prior to TAVR, group B (intervention group: 58 patients, age: 82.2 ± 5.82 years, 47% male) participated in intensive physiotherapy. Compared to the control group, patients in the interventional group showed a lower incidence of postinterventional pneumonia (10 [20.0%] vs. 3 [5.1%], p=0.016) and had a 3-day shorter mean hospital stay (13.5 ± 6.1 days vs. 10.1 ± 4.7 days, p=0.02). The primary composite endpoint of mortality and rehospitalization was not different between the groups. Conclusion. Intensified physiotherapy is safe and has positive effects on clinical outcomes up to 90 days after TAVR but has no impact on the primary combined endpoint of mortality and rehospitalization. Longer follow-up, a multicenter design, and a higher number of subjects are needed to confirm these preliminary results. This trial is registered with DRKS00017239.

Published
2021
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6. 3D external shape analysis and barycentremetry can provide early signs of progression in adolescent idiopathic scoliosis

Author

Langlais, Tristan, Vergari, Claudio, Mainard, Nicolas, du Cluzel, Xavier, Baudoux, Matthieu, Gajny, Laurent, Abelin-Genevois, Kariman, Bernard, Jean Claude, Hu, Zongshan, Cheng, Jack Chun Yiu, Chu, Winnie Chiu Wing, Assi, Ayman, Karam, Mohamad, Ghanem, Ismat, Bassani, Tito, Galbusera, Fabio, Sconfienza, Luca Maria, Brayda-Bruno, Marco, Courtois, Isabelle, Ebermeyer, Eric, Vialle, Raphael, Dubousset, Jean, and Skalli, Wafa

Published
2024
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20. Metabolic and Bariatric Surgeon Criteria—An International Experts’ Consensus

Author

Kermansaravi, Mohammad, Chiappetta, Sonja, Shikora, Scott A., Musella, Mario, Kow, Lilian, Aarts, Edo, Abbas, Syed Imran, Aly, Ahmad, Aminian, Ali, Angrisani, Luigi, Asghar, Syed Tanseer, Bashir, Ahmad, Behrens, Estuardo, Billy, Helmuth, Boza, Camilo, Brown, Wendy A., Caina, Daniel Oscar, Carbajo, Miguel A., Chevallier, Jean-Marc, Clapp, Benjamin, Cohen, Ricardo V., Jazi, Amir Hossein Davarpanah, De Luca, Maurizio, Dilemans, Bruno, Fried, Martin, Gagner, Michel, Neto, Manoel Galvao, Garneau, Pierre Y., Gawdat, Khaled, Ghanem, Omar M., Al Hadad, Mohammed, Haddad, Ashraf, ElFawal, Mohamad Hayssam, Herrera, Miguel F., Higa, Kelvin, Himpens, Jaques, Husain, Farah, Kasama, Kazunori, Kassir, Radwan, Khoursheed, Mousa, Khwaja, Haris, Kristinsson, Jon A., Kroh, Matthew, Kurian, Marina S., Lakdawala, Muffazal, LaMasters, Teresa, Lee, Wei-Jei, Madhok, Brijesh, Mahawar, Kamal, Mahdy, Tarek, Almomani, Hazem, Melissas, John, Miller, Karl, Neimark, Alexander, Omarov, Taryel, Palermo, Mariano, Papasavas, Pavlos K., Parmar, Chetan, Pazouki, Abdolreza, Peterli, Ralph, Pintar, Tadeja, Poggi, Luis, Ponce, Jaime, Prasad, Arun, Pratt, Janey S. A., Ramos, Almino C., Rezvani, Masoud, Rheinwalt, Karl, Ribeiro, Rui, Ruiz-Ucar, Elena, Sabry, Karim, Safadi, Bassem, Shabbir, Asim, ShahabiShahmiri, Shahab, Stenberg, Erik, Suter, Michel, Taha, Safwan, Taskin, Halit Eren, Torres, Antonio, Verboonen, Sergio, Vilallonga, Ramon, Voon, Kelvin, Wafa, Ala, Wang, Cunchuan, Weiner, Rudolf, Yang, Wah, Zundel, Natan, Prager, Gerhard, and Nimeri, Abdelrahman

Published
2024
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21. Exploring the relationship between epicardial fat and coronary plaque burden and characteristics: insights from cardiac ct imaging

Author

Manubolu, Venkat Sanjay, Lu, Julia Ying, Montano, Brian, Kininger, April, Bainiwal, Jassimran, Verghese, Dhiran, Alalawi, Luay, Bitar, Jairo Aldana, Pourafkari, Leili, Fazlalizadeh, Hooman, Ichikawa, Keishi, Khadije, Ahmad, Denise, Javier, Ghanem, Ahmed, Hamal, Sajad, Mao, Song, Budoff, Matthew J., and Roy, Sion K.

Published
2024
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22. A Hierarchical Security Events Correlation Model for Real-time Cyber Threat Detection and Response

Author

Maosa, Herbert, Ouazzane, Karim, and Ghanem, Mohamed Chahine

Subjects
Computer Science - Cryptography and Security, Computer Science - Distributed, Parallel, and Cluster Computing
Abstract

Intrusion detection systems perform post-compromise detection of security breaches whenever preventive measures such as firewalls do not avert an attack. However, these systems raise a vast number of alerts that must be analysed and triaged by security analysts. This process is largely manual, tedious and time-consuming. Alert correlation is a technique that tries to reduce the number of intrusion alerts by aggregating those that are related in some way. However, the correlation is performed outside the IDS through third-party systems and tools, after the high volume of alerts has already been raised. These other third-party systems add to the complexity of security operations. In this paper, we build on the very researched area of correlation techniques by developing a novel hierarchical event correlation model that promises to reduce the number of alerts issued by an Intrusion Detection System. This is achieved by correlating the events before the IDS classifies them. The proposed model takes the best of features from similarity and graph-based correlation techniques to deliver an ensemble capability not possible by either approach separately. Further, we propose a correlation process for correlation of events rather than alerts as is the case in current art. We further develop our own correlation and clustering algorithm which is tailor-made to the correlation and clustering of network event data. The model is implemented as a proof of concept with experiments run on the DARPA 99 Intrusion detection set. The correlation achieved 87 percent data reduction through aggregation, producing nearly 21000 clusters in about 30 seconds., Comment: version 2.4

Published
2023
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30. A global survey on the use of the international classification of diseases codes for metabolic dysfunction-associated fatty liver disease

Author

Zhang, Huai, Targher, Giovanni, Byrne, Christopher D., Kim, Seung Up, Wong, Vincent Wai-Sun, Valenti, Luca, Glickman, Myer, Ponce, Jaime, Mantzoros, Christos S., Crespo, Javier, Gronbaek, Henning, Yang, Wah, Eslam, Mohammed, Wong, Robert J., Machado, Mariana Verdelho, Yu, Ming-Lung, Ghanem, Omar M., Okanoue, Takeshi, Liu, Jun-Feng, Lee, Yong-ho, Xu, Xiao-Yuan, Pan, Qiuwei, Sui, Meili, Lonardo, Amedeo, Yilmaz, Yusuf, Zhu, Li-Yong, Moreno, Christophe, Miele, Luca, Lupsor-Platon, Monica, Zhao, Lei, LaMasters, Teresa LeAnn, Gish, Robert G., Zhang, Huijie, Nedelcu, Marius, Chan, Wah Kheong, Xia, Ming-Feng, Bril, Fernando, Shi, Jun-Ping, Datz, Christian, Romeo, Stefano, Sun, Jian, Liu, Dan, Sookoian, Silvia, Mao, Yi-Min, Méndez-Sánchez, Nahum, Wang, Xiao-Yan, Pyrsopoulos, Nikolaos T., Fan, Jian-Gao, Fouad, Yasser, Sun, Dan-Qin, Giannini, Cosimo, Chai, Jin, Xia, Ze-Feng, Jun, Dae Won, Li, Guo-Jing, Treeprasertsuk, Sombat, Li, Ying-Xu, Cheung, Tan To, Zhang, Faming, Goh, George Boon-Bee, Furuhashi, Masato, Seto, Wai-Kay, Huang, Hui, Di Sessa, Anna, Li, Qing-Hong, Cholongitas, Evangelos, Zhang, Le, Silveira, Themis Reverbel, Sebastiani, Giada, Adams, Leon A., Chen, Wei, Qi, Xiaolong, Rankovic, Ivan, De Ledinghen, Victor, Lv, Wen-Jie, Hamaguchi, Masahide, Kassir, Radwan, Müller-Wieland, Dirk, Romero-Gomez, Manuel, Xu, Ying, Xu, Yi-Cong, Chen, Shi-Yao, Kermansaravi, Mohammad, Kuchay, Mohammad Shafi, Lefere, Sander, Parmar, Chetan, Lip, Gregory Y. H., Liu, Chun-Jen, Åberg, Fredrik, Lau, George, George, Jacob, Sarin, Shiv Kumar, Zhou, Jing-Ya, and Zheng, Ming-Hua

Published
2024
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33. Influence of a mixture of oligosaccharides and β-glucan on growth performance, feed efficacy, body composition, biochemical indices, combating Streptococcus iniae infection, and gene expression of Nile tilapia (Oreochromis niloticus)

Author

Eissa, El-Sayed Hemdan, Okon, Ekemini Moses, Abdel-Warith, Abdel-Wahab A., Younis, Elsayed M., Munir, Mohammad Bodrul, Eissa, Hoda A., Ghanem, Sara F., Mahboub, Heba H., Abd Elghany, Nadia A., Dighiesh, Hagar Sedeek, Eissa, Moaheda E. H., and Abd El-Aziz, Yasmin M.

Published
2024
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47. A Comprehensive Analysis of the Role of Artificial Intelligence and Machine Learning in Modern Digital Forensics and Incident Response

Author

Dunsin, Dipo, Ghanem, Mohamed C., Ouazzane, Karim, and Vassilev, Vassil

Subjects
Computer Science - Cryptography and Security, Computer Science - Artificial Intelligence, Computer Science - Networking and Internet Architecture
Abstract

In the dynamic landscape of digital forensics, the integration of Artificial Intelligence (AI) and Machine Learning (ML) stands as a transformative technology, poised to amplify the efficiency and precision of digital forensics investigations. However, the use of ML and AI in digital forensics is still in its nascent stages. As a result, this paper gives a thorough and in-depth analysis that goes beyond a simple survey and review. The goal is to look closely at how AI and ML techniques are used in digital forensics and incident response. This research explores cutting-edge research initiatives that cross domains such as data collection and recovery, the intricate reconstruction of cybercrime timelines, robust big data analysis, pattern recognition, safeguarding the chain of custody, and orchestrating responsive strategies to hacking incidents. This endeavour digs far beneath the surface to unearth the intricate ways AI-driven methodologies are shaping these crucial facets of digital forensics practice. While the promise of AI in digital forensics is evident, the challenges arising from increasing database sizes and evolving criminal tactics necessitate ongoing collaborative research and refinement within the digital forensics profession. This study examines the contributions, limitations, and gaps in the existing research, shedding light on the potential and limitations of AI and ML techniques. By exploring these different research areas, we highlight the critical need for strategic planning, continual research, and development to unlock AI's full potential in digital forensics and incident response. Ultimately, this paper underscores the significance of AI and ML integration in digital forensics, offering insights into their benefits, drawbacks, and broader implications for tackling modern cyber threats., Comment: version 2 post peer review Forensic Science International Digital Investigation

Published
2023
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48. G\ae{}nice: a general model for magnon band structure of artificial spin ices

Author

Alatteili, Ghanem, Martinez, Victoria, Roxburgh, Alison, Gartside, Jack C., Heinonen, Olle G., Gliga, Sebastian, and Iacocca, Ezio

Subjects
Condensed Matter - Mesoscale and Nanoscale Physics
Abstract

Arrays of artificial spin ices exhibit reconfigurable ferromagnetic resonance frequencies that can be leveraged and designed for potential applications.However, analytical and numerical studies of the frequency response of artificial spin ices have remained somewhat limited due to the need of take into account nonlocal dipole fields in theoretical calculations or by long computation times in micromagnetic simulations. Here, we introduce Gaenice, a framework to compute magnon dispersion relations of arbitrary artificial spin ice configurations. Gaenice makes use of a tight-binding approach to compute the magnon bands. It also provides the user complete control of the interaction terms included, e.g., external field, anisotropy, exchange, and dipole, making it useful also to compute ferromagnetic resonances for a variety of structures, such as multilayers and ensembles of weakly or non-interacting nanoparticles. Because it relies on a semi-analytical model, Gaenice is computationally inexpensive and efficient, making it an attractive tool for the exploration of large parameter spaces.

Published
2023
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