المؤلفون: Almutiry, Muhannad, Alshehri, Mohammad Y., Sayed, Gary

المصدر: Athens Journal of Education. Aug 2022 9(3):413-428.

تمت مراجعته من قبل الزملاء: Y

Page Count: 16

الواصفات: Foreign Countries, Higher Education, Educational Practices, Competence, Competency Based Education, Success, Employment Qualifications, Public Colleges, Job Skills, Communication Skills, Organization, Knowledge Level, Creativity, Social Responsibility, Core Curriculum, Communities of Practice, First Year Seminars, Student Research, Undergraduate Students, Program Implementation, Sustainability, Engineering Education, Nursing Education, Educational Finance, College Faculty, Teacher Role, Administrator Role, Student Role

مصطلحات جغرافية: Saudi Arabia

مستخلص: Higher education is challenged by workforce needs to transform its outcomes from "knowledge-based" to "competency-based" outcomes. High-impact educational practices, commonly referred to as HIPs, provide, among other benefits, efficacious development of workforce-ready specific competencies. Strategic implementation of HIPs has yet to be diffused at Saudi universities. The Northern Border University (NBU) has identified a set of core competencies graduate workforce-ready graduates. To effectively realize the intended outcomes of its core competencies, NBU selected a set of HIPs to increase student success. This paper discusses NBU's processes and implementation strategies in selecting core competencies and HIPs with ultimate aim of translating both to the local higher education culture and norms in order to effectively achieve desired outcomes.

Abstractor: As Provided

المؤلفون: Shakhatreh, Hazim, Sawalmeh, Ahmad, Alenezi, Ali H, Abdel-Razeq, Sharief, Almutiry, Muhannad, Al-Fuqaha, Ala

مصطلحات موضوعية: Computer Science - Information Theory

الوصف: Prior research on intelligent reflection surface (IRS)-assisted unmanned aerial vehicle (UAV) communications has focused on a fixed location for the IRS or mounted on a UAV. The assumption that the IRS is located at a fixed position will prohibit mobile users from maximizing many wireless network benefits, such as data rate and coverage. Furthermore, assuming that the IRS is placed on a UAV is impractical for various reasons, including the IRS's weight and size and the speed of wind in severe weather. Unlike previous studies, this study assumes a single UAV and an IRS mounted on a mobile ground vehicle (M-IRS) to be deployed in an Internet-of-Things (IoT) 6G wireless network to maximize the average data rate. Such a methodology for providing wireless coverage using an M-IRS assisted UAV system is expected in smart cities. In this paper, we formulate an optimization problem to find an efficient trajectory for the UAV, an efficient path for the M-IRS, and users' power allocation coefficients that maximize the average data rate for mobile ground users. Due to its intractability, we propose efficient techniques that can help in finding the solution to the optimization problem. First, we show that our dynamic power allocation technique outperforms the fixed power allocation technique in terms of network average sum rate. Then we employ the individual movement model (Random Waypoint Model) in order to represent the users' movements inside the coverage area. Finally, we propose an efficient approach using a Genetic Algorithm (GA) for finding an efficient trajectory for the UAV, and an efficient path for the M-IRS to provide wireless connectivity for mobile users during their movement. We demonstrate through simulations that our methodology can enhance the average data rate by 15\% on average compared with the static IRS and by 25\% on average compared without the IRS system.
Comment: 11 pages, 8 figures

الوصول الحر: http://arxiv.org/abs/2207.03622Test

المؤلفون: Khan, Muhammad Zakir, Althobaiti, Turke, Almutiry, Muhannad, Ramzan, Naeem

الوصف: his study presents a novel computational radio frequency identification (RFID) system designed specifically for assisting blind individuals, utilising software-defined radio (SDR) with coherent detection. The system employs battery-less ultra-high-frequency (UHF) tag arrays in Gen2 RFID systems, enhancing the transmission of sensed information beyond standard identification bits. Our method uses an SDR reader to efficiently manage multiple tags with Gen2 preambles implemented on a single transceiver card. The results highlight the system’s real-time capability to detect movements and direction of walking within a four-meter range, indicating significant advances in contactless activity monitoring. This system not only handles the complexities of multiple tag scenarios but also delineates the influence of system parameters on RFID operational efficiency. This study contributes to assistive technology, provides a platform for future advancements aimed at addressing contemporary limitations in pseudo-localisation, and offers a practical, affordable assistance system for blind individuals.

وصف الملف: text

العلاقة: https://eprints.gla.ac.uk/326515/1/326515.pdfTest; Khan, M. Z. , Althobaiti, T., Almutiry, M. and Ramzan, N. (2024) Empowering the blind: contactless activity recognition with commodity software-defined radio and ultra-high-frequency radio frequency identification. Sensors , 24(11), 3645. (doi:10.3390/s24113645 ) (PMID:38894436) (PMCID:PMC11175189)

الإتاحة: https://doi.org/10.3390/s24113645Test
https://eprints.gla.ac.uk/326515Test/
https://eprints.gla.ac.uk/326515/1/326515.pdfTest

المؤلفون: Shakhatreh, Hazim, Malkawi, Waed, Sawalmeh, Ahmad, Almutiry, Muhannad, Alenezi, Ali

مصطلحات موضوعية: Computer Science - Information Theory

الوصف: Path loss is a significant component of wireless communication channel design and analysis and reflects the reduction in a transmitted signal's power density. Due to the differences in the propagation conditions, wireless aerial channels' features differ from those of terrestrial wireless channels; therefore, unmanned aerial vehicle path loss models are often different from conventional terrestrial wireless channel path loss models. A mathematical propagation model is proposed in this paper to estimate the Ground-to-Air path loss between a wireless device and a low-altitude platform using the frequency bands of the millimeter wave. The suggested model of Ground-to-Air path loss will assist academic researchers in formulating several vital problems.
Comment: 11 pages, 3 figures

الوصول الحر: http://arxiv.org/abs/2101.12024Test

المؤلفون: Almutiry, Muhannad Salem S.

مصطلحات موضوعية: Electrical Engineering, Born Approximation, Radar imaging, synthetic aperture radar, Microwave imaging, ground penetrating radar, Radio frequency tomography

الوصف: Radio Frequency (RF) Tomography is a mathematical process of 3D image reconstruction from a measurement using a multistatic distribution of transmitters and receivers. The geometric diversity of these elements increases the information in the measurements. The process of determining the permittivity and conductivity profile in the measurement domain, and, therefore, the shape of the target, from the scattered field measurements, is an inverse problem. To solve this problem, under conventional methods such as the Born approximation, we use the principles of linear scattering to determine a linear relationship between measured returns and target shape. The Born approximation is valid if the scatterer is small and does not interact strongly with other objects. However, strong scatterers within the domain may generate sidelobes masking weaker returns. This masking, in conjunction with multipath effects, may result in loss of features and subsequent failure to identify a target. In this research, a novel method is proposed to increase overall image quality and extend the capabilities of RF tomography by modeling the strong scatterers in the measurement domain as dipoles that behave as secondary sources (transmitters). Unlike conventional methods, the dipole model reduces the effects of the sidelobes from the strong scatterers and exploits the multipath of multiple targets or complex shapes. The multipath phenomena contains more information about the targets permitting illumination in the shadowed region and an increase to the radar aperture length. The electromagnetic characteristics for each modeled dipole are estimated by representing the cells in the measurement domain's image. The eigenvalue and eigenvector from each cell represent the phase and magnitude for the modeled dipole and also the spatial orientation of the target. The process of modeling large scatterers as dipoles can be iterated, addressing one strong scatterer at a time. This method effectively suppresses the sidelobes and exploits the multipath within the measurement domain. Using the Born approximation, the linear relationship between the scattered fields and the target is updated for simplicity. With iterations, the “extra” dipole will account for the multipath effects, thus removing some limitations caused by the Born approximation. This concept has been successfully demonstrated in software (FEKO© by Altair). In addition, this work also presents an innovative conversion using a back-projection algorithm for multipath effects and modeling of an “additional” source or transmitter in the measurement domain. The result of implementing this method of modeling strong scatterers as dipoles successfully demonstrated an increase in the resolution and enhanced radar imagery.

الإتاحة: http://rave.ohiolink.edu/etdc/view?acc_num=dayton1470154676Test

المؤلفون: Khalil, Ruhul Amin, Saeed, Nasir, Almutiry, Muhannad, Alenezi, Ali Hamdan

المساهمون: United Arab Emirates University

المصدر: ICT Express ; volume 9, issue 5, page 815-820 ; ISSN 2405-9595

مصطلحات موضوعية: Artificial Intelligence, Computer Networks and Communications, Hardware and Architecture, Information Systems, Software

الإتاحة: https://doi.org/10.1016/j.icte.2023.01.004Test
https://api.elsevier.com/content/article/PII:S2405959523000048?httpAccept=text/xmlTest
https://api.elsevier.com/content/article/PII:S2405959523000048?httpAccept=text/plainTest

المؤلفون: Khalil, Ruhul Amin, Saeed, Nasir, Almutiry, Muhannad

المصدر: ICT Express ; volume 9, issue 4, page 677-682 ; ISSN 2405-9595

مصطلحات موضوعية: Artificial Intelligence, Computer Networks and Communications, Hardware and Architecture, Information Systems, Software

الإتاحة: https://doi.org/10.1016/j.icte.2022.04.011Test
https://api.elsevier.com/content/article/PII:S2405959522000674?httpAccept=text/xmlTest
https://api.elsevier.com/content/article/PII:S2405959522000674?httpAccept=text/plainTest

المؤلفون: Almutiry, Muhannad

المصدر: 2024 Integrated Communications, Navigation and Surveillance Conference (ICNS)

الإتاحة: https://doi.org/10.1109/icns60906.2024.10550557Test
http://xplorestaging.ieee.org/ielx8/10550189/10550451/10550557.pdf?arnumber=10550557Test

المؤلفون: Touti, Ezzeddine, Tlili, Ali Sghaier, Almutiry, Muhannad

المصدر: COMPEL -The international journal for computation and mathematics in electrical and electronic engineering, 2020, Vol. 39, Issue 4, pp. 801-821.

الوصول الحر: http://www.emeraldinsight.com/doi/10.1108/COMPEL-10-2019-0427Test

المؤلفون: Alenezi, Ali H., Nazzal, Mahmoud, Sawalmeh, Ahmed, Khreishah, Abdallah, Shao, Sihua, Almutiry, Muhannad

المصدر: Cluster Computing; Feb2024, Vol. 27 Issue 1, p299-311, 13p

مصطلحات موضوعية: MACHINE learning, OPTICAL communications, VISIBLE spectra, INTERNET of things

مستخلص: Many real-world applications require real-time and robust positioning of Internet of Things (IoT) devices. In this context, visible light communication (VLC) is a promising approach due to its advantages in terms of high accuracy, low cost, ubiquitous infrastructure, and freedom from RF interference. Nevertheless, there is a growing need to improve positioning speed and accuracy. In this paper, we propose and prototype a VLC-based positioning solution using retroreflectors attached to the IoT device of interest. The proposed algorithm uses the retroreflected power received by multiple photodiodes to estimate the euclidean and directional coordinates of the underlying IoT device. In particular, the relative relationship between reflected light magnitude and reflected power is used as input to trainable machine learning regression models. Such models are trained to estimate the coordinates. The proposed algorithm excels in its simplicity and fast computation. It also reduces the need for sensory devices and active operation. Additionally, after regression, Kalman filtering is applied as a post-processing operation to further stabilize the obtained estimates. The proposed algorithm is shown to provide stable, accurate, and fast. This has been verified by extensive experiments performed on a prototype in real-world environments. Experiments confirm a high level of positioning accuracy and the added benefit of Kalman filtering stabilization. [ABSTRACT FROM AUTHOR]

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