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4,362 results on '"Abdullah, Muhammad"'

2. Viscous Instabilities in Transversely Strained Channel Flows

Author

Abdullah, Muhammad

Subjects
Physics - Fluid Dynamics, Mathematical Physics
Abstract

We investigate here linear stability in a canonical three-dimensional boundary layer generated by the superposition of a spanwise pressure gradient upon an otherwise standard channel flow. As the main result, we introduce a simple coordinate transformation that enables the complete description of modal and non-modal stability using previous results on Poiseuille flow. We leverage this insight to derive closed forms for some relevant stability metrics. In particular, the critical Reynolds number for exponential-in-time growth is found to monotonically decrease with the strength of the cross-flow. A suitably chosen re-scaling, however, shows that the stability characteristics ultimately approach those of channel flow, despite the presence of a non-zero spanwise shear. Unstable eigenmodes akin to the Tollmien-Schlichting wave are found to propagate along the direction of the net flow. From a non-modal perspective, the maximal transient (algebraic) growth increases quadratically with the spanwise pressure differential and, similar to two-dimensional flows, is fueled by the lift-up effect. In this regard, the linear energy budget highlights a dramatic increase in energy production against the spanwise shear.

Published
2024

3. Calculation of Femur Caput Collum Diaphyseal angle for X-Rays images using Semantic Segmentation

Author

Abdullah, Muhammad, Querfurth, Anne, Bhatia, Deepak, and Mantash, Mahdi

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition
Abstract

This paper investigates the use of deep learning approaches to estimate the femur caput-collum-diaphyseal (CCD) angle from X-ray images. The CCD angle is an important measurement in the diagnosis of hip problems, and correct prediction can help in the planning of surgical procedures. Manual measurement of this angle, on the other hand, can be time-intensive and vulnerable to inter-observer variability. In this paper, we present a deep-learning algorithm that can reliably estimate the femur CCD angle from X-ray images. To train and test the performance of our model, we employed an X-ray image dataset with associated femur CCD angle measurements. Furthermore, we built a prototype to display the resulting predictions and to allow the user to interact with the predictions. As this is happening in a sterile setting during surgery, we expanded our interface to the possibility of being used only by voice commands. Our results show that our deep learning model predicts the femur CCD angle on X-ray images with great accuracy, with a mean absolute error of 4.3 degrees on the left femur and 4.9 degrees on the right femur on the test dataset. Our results suggest that deep learning has the potential to give a more efficient and accurate technique for predicting the femur CCD angle, which might have substantial therapeutic implications for the diagnosis and management of hip problems.

Published
2024

4. Revisiting Crossflow-Based Stabilization in Channel Flows

Author

Abdullah, Muhammad and Park, George Ilhwan

Subjects
Physics - Fluid Dynamics
Abstract

Stabilization schemes in wall-bounded flows often invoke fluid transpiration through porous boundaries. While these have been extensively validated for external flows, their efficacy in channels, particularly from the standpoint of non-modal perturbations, is yet to be demonstrated. Here, we show that crossflow strengths previously considered ``ideal'' for optimizing stability in channels in fact admit strong non-modal energy amplification. We begin by supplementing existing modal calculations and then show via the resolvent that extremely strong and potentially unfeasible crossflows are required to suppress non-modal growth in linearly stable regimes. Investigation of unforced algebraic growth paints a similar picture. Here, a component-wise budget analysis reveals that energy redistribution through pressure-velocity correlations plays an important role in driving energy growth/decay. The superposition of a moving wall is also considered, and it is shown that while energy amplification generally worsens, it can potentially be suppressed beyond a regime shift in parameter space. However, these flows are marred by rapidly declining mass transport, rendering their ultimate utility questionable. Our results suggest that crossflow-based stabilization might not be useful in internal flows.

Published
2024

5. Linear Stability Analysis of Oblique Couette-Poiseuille flows

Author

Abdullah, Muhammad and Park, George Ilhwan

Subjects
Physics - Fluid Dynamics
Abstract

We perform a detailed numerical study of modal and non-modal stability in oblique Couette-Poiseuille profiles, which are among the simplest examples of three-dimensional boundary layers. Through a comparison with the Orr-Sommerfeld operator for the aligned case, we show how an effective wall speed succinctly characterizes modal stability. Large-scale parameter sweeps reveal that the misalignment between the pressure gradient and wall motion is, in general, destabilizing. For flows that are sufficiently oblique, the instability is found to depend exclusively on the direction of wall motion and not on its speed, a conclusion supported, in part, by the perturbation energy budget and the evolution of the critical layers. Closed forms for the critical parameters in this regime are derived using a simple analysis. Finally, a modified long-wavelength approximation is developed, and the resulting asymptotic eigenvalue problem is used to show that there is no cutoff wall speed for unconditional stability whenever the angle of wall motion is non-zero, in stark contrast to the aligned case. From a non-modal perspective, pseudo-resonance is examined through the resolvent and the $\epsilon$-pseudospectra. An analysis of the unforced initial value problem shows that the maximum energy gain is highly dependent on both the magnitude and direction of the wall velocity. However, the strongest amplification is always achieved for configurations that are only weakly skewed. Finally, the optimal perturbations appear to develop via a lift-up effect induced by an Orr-like mechanism.

Published
2024

23. A Comparative Study of Seismic Characteristics Between Distributed Acoustic Sensing (DAS) and Geophones

Author

Chandran, Satishvaran Ragu, Mohamad, Hisham, Nasir, Muhammad Yusoff Mohd, Ghazali, Muhammad Farid, Abdullah, Muhammad Aizzuddin, Epin, Vorathin, di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Cui, Zhen-Dong, Series Editor, Nia, Elham Maghsoudi, editor, and Awang, Mokhtar, editor

Published
2024
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24. The Role of Art in Knowledge Transmission in the Muslim World

Author

Islam, Md Nurul, Abdullah, Muhammad, Striełkowski, Wadim, Editor-in-Chief, Black, Jessica M., Series Editor, Butterfield, Stephen A., Series Editor, Chang, Chi-Cheng, Series Editor, Cheng, Jiuqing, Series Editor, Dumanig, Francisco Perlas, Series Editor, Al-Mabuk, Radhi, Series Editor, Scheper-Hughes, Nancy, Series Editor, Urban, Mathias, Series Editor, Webb, Stephen, Series Editor, Hidayat, Agung, editor, Handoko, Chanel Tri, editor, Khoiriyah, Siti, editor, Arif, Akbarudin, editor, and Saptaningtyas, Haryani, editor

Published
2024
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25. Geo-Smart City Flood Mitigation and Monitoring Using Geospatial Technology

Author

Muhamad, Nurfashareena, Abed, Marwa Sultan, Shariff, Abdul Rashid Mohamed, Abdullah, Muhammad Firdaus Ammar, Lim, Choun-Sian, Al-Habshi, Mohammed, Sathyamoorthy, Dinesh, Shaharuddin, Nur Akma, Ahmad, Noordin, Negm, Abdelazim M., Series Editor, Chaplina, Tatiana, Series Editor, Yadava, Ram Narayan, editor, and Ujang, Muhamad Uznir, editor

Published
2024
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27. Deep Learning Algorithms for Recognition of Badminton Strokes: A Study Using SDNN, RNN, and RNN-GRU Models with Off-Court Video Capture

Author

Isa, Wan Hasbullah Mohd, Abdullah, Muhammad Amirul, Razman, Mohd Azraai Mohd, Majeed, Anwar P. P. Abdul, Khairuddin, Ismail Mohd, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Tan, Andrew, editor, Zhu, Fan, editor, Jiang, Haochuan, editor, Mostafa, Kazi, editor, Yap, Eng Hwa, editor, Chen, Leo, editor, Olule, Lillian J. A., editor, and Myung, Hyun, editor

Published
2024
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28. The Classification of Badminton Strokes: A Feature Importance Investigation

Author

Li, Qiyang, P. P. Abdul Majeed, Anwar, Musa, Rabiu Muazu, Abdullah, Muhammad Amirul, Teh, Sze-Hong, Liu, Chenguang, Yap, Eng Hwa, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Tan, Andrew, editor, Zhu, Fan, editor, Jiang, Haochuan, editor, Mostafa, Kazi, editor, Yap, Eng Hwa, editor, Chen, Leo, editor, Olule, Lillian J. A., editor, and Myung, Hyun, editor

Published
2024
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29. Road Signage and Road Obstacle Detection Using Deep Learning Method

Author

Juen, Lee Cheng, Khairuddin, Ismail Mohd, Majeed, Anwar P. P. Abdul, Abdullah, Muhammad Amirul, Nasir, Ahmad Fakhri Ab, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Tan, Andrew, editor, Zhu, Fan, editor, Jiang, Haochuan, editor, Mostafa, Kazi, editor, Yap, Eng Hwa, editor, Chen, Leo, editor, Olule, Lillian J. A., editor, and Myung, Hyun, editor

Published
2024
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43. Nearpod Use as a Learning Platform to Improve Student Learning Motivation in an Elementary School

Author

Abdullah, Muhammad Ilyas, Inayati, Dian, and Karyawati, Ninik Nurlaila

Abstract

Education sector is heavily affected by COVID-19 pandemic, leading to reduced learning motivation among students. Factors including dismal learning environment, stress, and anxiety are believed to be the reasons of students' lower motivation among students. This study investigated the use of Nearpod in an elementary school to improve student learning motivation during online learning. In this qualitative experimental research with thematic analysis, three classes with a total of 51 students and three teachers were participating for one week. The results of the study showed that gamification and interactivity of Nearpod help build up and develop students' learning interests, leading to greater attention, engagement, and improvement of student attendance rates. Some suggestions on how to effectively integrate gamification in learning are postulated.

Published
2022

44. Open and Distance Learning during the COVID-19 Pandemic: University Students' Learning Experiences and Academic Achievements

Author

Tew Abdullah, Muhammad Hakimi, Roslim, Norwati, and Mohd Salleh, Mohd Idzwan

Abstract

Universiti Teknologi MARA (UiTM) has taken an approach of Open and Distance Learning (ODL) system as a way to ensure the continuity of its education during the COVID-19 pandemic. This transformation leads to various challenges in teaching and learning. Hence, this study aimed to describe the ODL in terms of university students' learning experiences and their academic achievements during the COVID-19 pandemic. This study involved a total of 3283 students during March-August 2020 semester in UiTM Negeri Sembilan. Data were collected via online surveys and were descriptively and statistically analysed using Statistical Package for the Social Sciences (SPSS). Findings showed that students were given sufficient information regarding the assessments of the course (mean=3.64) and the delivery of the course content (mean=3.65). The success factors on the students' academic achievements were due to the support from lecturers (mean=2.78), peers (mean=2.79) and family (mean=2.55). Thus, it can be concluded that the majority of the students are satisfied with their ODL learning experiences and academic achievements. This study suggests that academic management should continue to provide effective support in the form of resources and services to increase performances by their students.

Published
2022

50. Monitoring SARS-CoV-2 incidence and seroconversion among university students and employees: a longitudinal cohort study in California, June–August 2020

Author

Hunter, Lauren A, Wyman, Stacia, Packel, Laura J, Facente, Shelley N, Li, Yi, Harte, Anna, Nicolette, Guy, Consortium, the IGI SARS-CoV-2 Testing, Di Germanio, Clara, Busch, Michael P, Reingold, Arthur L, Petersen, Maya L, Urnov, Fyodor, McDevitt, Shana, Hirsch, Ariana, Ehrenberg, Alexander, Doudna, Jennifer A, Amen, M, Barry, Kerrie W, Boyle, John M, Brook, Cara E, Choo, Seunga, Cornmesser, Dilworth, David J, Fedrigo, Indro, Friedline, Skyler E, Graham, Thomas GW, Green, Ralph, Hamilton, Jennifer R, Hochstrasser, Megan L, Hockemeyer, Dirk, Krishnappa, Netravathi, Lari, Azra, Li, Hanqin, Lin-Shiao, Enrique, Lu, Tianlin, Lyons, Elijah F, Mark, Kevin G, Martell, Lisa Argento, Martins, A Raquel O, Mitchell, Patrick S, Moehle, Erica A, Naca, Christine, Nandakumar, Divya, O’Brien, Elizabeth, Pappas, Derek J, Pestal, Kathleen, Quach, Diana L, Rubin, Benjamin E, Sachdeva, Rohan, Stahl, Elizabeth C, Syed, Abdullah Muhammad, Tan, I-Li, Tollner, Amy L, Tsuchida, Connor A, Tsui, C Kimberly, Turkalo, Timothy K, Warf, M Bryan, Whitney, Oscar N, and Witkowsky, Lea B

Subjects
Biodefense, Emerging Infectious Diseases, Infectious Diseases, Vaccine Related, Prevention, Clinical Research, Infection, Good Health and Well Being, Humans, SARS-CoV-2, COVID-19, Incidence, COVID-19 Testing, Longitudinal Studies, Universities, Seroconversion, Phylogeny, Prospective Studies, California, Cohort Studies, EPIDEMIOLOGY, Public health, Infection control, Epidemiology, PUBLIC HEALTH, IGI SARS-CoV-2 Testing Consortium, Clinical Sciences, Public Health and Health Services, Other Medical and Health Sciences
Abstract

ObjectivesTo identify incident SARS-CoV-2 infections and inform effective mitigation strategies in university settings, we piloted an integrated symptom and exposure monitoring and testing system among a cohort of university students and employees.DesignProspective cohort study.SettingA public university in California from June to August 2020.Participants2180 university students and 738 university employees.Primary outcome measuresAt baseline and endline, we tested participants for active SARS-CoV-2 infection via quantitative PCR (qPCR) test and collected blood samples for antibody testing. Participants received notifications to complete additional qPCR tests throughout the study if they reported symptoms or exposures in daily surveys or were selected for surveillance testing. Viral whole genome sequencing was performed on positive qPCR samples, and phylogenetic trees were constructed with these genomes and external genomes.ResultsOver the study period, 57 students (2.6%) and 3 employees (0.4%) were diagnosed with SARS-CoV-2 infection via qPCR test. Phylogenetic analyses revealed that a super-spreader event among undergraduates in congregate housing accounted for at least 48% of cases among study participants but did not spread beyond campus. Test positivity was higher among participants who self-reported symptoms (incidence rate ratio (IRR) 12.7; 95% CI 7.4 to 21.8) or had household exposures (IRR 10.3; 95% CI 4.8 to 22.0) that triggered notifications to test. Most (91%) participants with newly identified antibodies at endline had been diagnosed with incident infection via qPCR test during the study.ConclusionsOur findings suggest that integrated monitoring systems can successfully identify and link at-risk students to SARS-CoV-2 testing. As the study took place before the evolution of highly transmissible variants and widespread availability of vaccines and rapid antigen tests, further research is necessary to adapt and evaluate similar systems in the present context.

Published
2023

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