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IEEE Conference on Vehicular technology (VTC)

作者： Lydia Douaidi Sidi-Mohammed Senouci Ines El Korbi Fouzi Harrou DRIVE Lab University of Burgundy Nevers France Computer Electrical and Mathematical Sciences and Engineering (CEMSE) Division King Abdullah University of Science and Technology (KAUST) Thuwal Saudi Arabia

Electric vehicles (EVs) have long been recognized as a solution to the shortage of fossil fuels and the environmental problems associated with increasing CO2 emissions. However, charging an electric vehicle can take significant time at certain charging stations. Additionally, the limited deployment of charging stations is a significant barrier to the widespread adoption of electric mobility (e-mobility). In fact, many drivers struggle to locate a convenient charging station before their vehicle’s battery runs out. This study introduces a novel approach to addressing the issue of congestion at public charging stations and reducing the amount of time drivers spend waiting in line by predicting their occupancy. Previous research has relied on traditional Deep Learning (DL) techniques for prediction, which require centralized data collection. Nevertheless, each Charging Station Operator (CSO) holds sensitive data about its charging stations and users that cannot be shared with external parties. To address these privacy concerns, we propose a Federated Deep Learning approach where each CSO trains a DL model locally and then sends the model updates (or parameters) to a server for aggregation. Experiments on a real-world dataset demonstrate that predicting occupancy using the Federated Deep Learning approach achieves promising results (86,21% of accuracy and 91,49% of f1-score ), guarantees privacy, minimizes data transfer costs over the network, and allows individual CSOs to benefit from the rich datasets of others without sharing their sensitive data.

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From axioms over graphs to vectors, and back again: evaluating the properties of graph-based ontology embeddings

arXiv

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arXiv 2023年

作者： Zhapa-Camacho, Fernando Hoehndorf, Robert Computational Bioscience Research Center Computer Electrical & Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology 4700 KAUST Thuwal23955 Saudi Arabia

Several approaches have been developed that generate embeddings for Description Logic ontologies and use these embeddings in machine learning. One approach of generating ontologies embeddings is by first embedding the ontologies into a graph structure, i.e., introducing a set of nodes and edges for named entities and logical axioms, and then applying a graph embedding to embed the graph in Rn. Methods that embed ontologies in graphs (graph projections) have different formal properties related to the type of axioms they can utilize, whether the projections are invertible or not, and whether they can be applied to asserted axioms or their deductive closure. We analyze, qualitatively and quantitatively, several graph projection methods that have been used to embed ontologies, and we demonstrate the effect of the properties of graph projections on the performance of predicting axioms from ontology embeddings. We find that there are substantial differences between different projection methods, and both the projection of axioms into nodes and edges as well ontological choices in representing knowledge will impact the success of using ontology embeddings to predict axioms. © 2023, CC BY.

关键词： Ontology

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Unbiased Approximations for Stationary Distributions of McKean-Vlasov SDEs

arXiv

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arXiv 2024年

作者： Awadelkarim, Elsiddig Chada, Neil K. Jasra, Ajay Applied Mathematics and Computational Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia Department of Mathematics City University of Hong Kong Hong Kong School of Data Science The Chinese University of Hong Kong Shenzhen Shenzhen China

We consider the development of unbiased estimators, to approximate the stationary distribution of Mckean-Vlasov stochastic differential equations (MVSDEs). These are an important class of processes, which frequently appear in applications such as mathematical finance, biology and opinion dynamics. Typically the stationary distribution is unknown and indeed one cannot simulate such processes exactly. As a result one commonly requires a time-discretization scheme which results in a discretization bias and a bias from not being able to simulate the associated stationary distribution. To overcome this bias, we present a new unbiased estimator taking motivation from the literature on unbiased Monte Carlo. We prove the unbiasedness of our estimator, under assumptions. In order to prove this we require developing ergodicity results of various discrete time processes, through an appropriate discretization scheme, towards the invariant measure. Numerous numerical experiments are provided, on a range of MVSDEs, to demonstrate the effectiveness of our unbiased estimator. Such examples include the Currie-Weiss model, a 3D neuroscience model and a parameter estimation problem. © 2024, CC BY-NC-SA.

关键词： Stochastic systems

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Precision-Adaptive Task Offloading and Resource Allocation for Efficient Positioning and Sensing in Near-Field IoV Systems

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IEEE Internet of Things Journal 2025年第13期12卷 22635-22646页

作者： Dai, Cheng Bao, Song Chen, Songlin Garg, Sahil Kaddoum, Georges Sichuan University College of Computer Science Sichuan Chengdu China École de technologie supérieure Electrical Engineering Department MontréalQCH3C 1K3 Canada Chitkara University Institute of Engineering and Technology Chitkara University Centre for Research Impact and Outcome Punjab Rajpura140401 India École de technologie supérieure MontréalQCH3C1K3 Canada King Saud University College of Computer and Information Sciences Department of Information Systems Riyadh11543 Saudi Arabia

With the rapid advancement of sixth-generation (6G) network communication technology, improvements in data transmission rates, latency, and reliability have driven substantial growth in Internet of Vehicles (IoV) applications. Among these, the integration of 6G-enabled extremely large-scale antenna arrays (ELAAs) has extended the range of near-field (NF) communication, enabling their application in IoV to facilitate efficient and accurate environmental sensing. Through NF communication, vehicles can achieve high-accuracy localization and perception by analyzing the signal phase, channel state information, and beamforming calculations. However, positioning and sensing tasks place substantial computational and energy demands on edge devices, often exceeding traditional capacity limits. To address this challenge, task offloading has emerged as a solution, with mobile edge computing (MEC) offering a lower-latency alternative to centralized cloud computing by processing tasks at the network edge. Despite these advantages, MEC’s limited resources present challenges as the number of connected vehicles increases. Existing approaches to resource allocation often overlook the varied accuracy requirements of IoV tasks, where high-accuracy tasks like indoor navigation require stringent performance standards, while lower-accuracy tasks may tolerate reduced precision to save resources. Motivated by this, we propose an accuracy-based classification scheme for IoV positioning and sensing tasks, which dynamically adjusts accuracy requirements to reduce delay and energy consumption. Our approach maps total energy, accuracy loss, and delay to an overall quality of service (QoS) metric, and employs an optimization algorithm that leverages gradient descent and greedy strategies to balance resource allocation and accuracy selection. Extensive simulations demonstrate the effectiveness of the proposed scheme in reducing delay and energy consumption while maintaining high accuracy, signific

关键词： Resource allocation

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Ultra-Narrow-Linewidth Hybrid-Integrated Self-Injection Locked Laser at 780 nm

Ultra-Narrow-Linewidth Hybrid-Integrated Self-Injection Lock...

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IEEE Photonics Conference (IPC)

作者： Artem Prokoshin Michael Gehl Scott E. Madaras Weng W. Chow Yating Wan Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology (KAUST) Thuwal Kingdom of Saudi Arabia Photonic and Phononic Microsystems Sandia National Laboratories Albuquerque New Mexico USA

We demonstrate a hybrid-integrated self-injection locked laser operating at 780 nm with a linewidth of 103.8 Hz, and theoretically study the possibility of achieving Hz-level linewidth with this setup.

ISBN: (数字)9798350361957

ISBN: (纸本)9798350361964

关键词： Laser theory Laser mode locking Numerical models Photonics

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Silicon-Based Single Photon Avalanche Diode Technologies: Structures, Performance, and Challenges

IEEE Electron Devices Reviews

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IEEE Electron Devices Reviews 2025年 2卷 69-97页

作者： Sumaiya Hoque Md Anas abdullah Mrwan Alayed Mohamed Elamien M. Jamal Deen Department of Electrical and Computer Engineering McMaster University Hamilton ON Canada Microelectronics and Semiconductors Institute King Abdulaziz City for Science and Technology (KACST) Riyadh Saudi Arabia School of Biomedical Engineering McMaster University Hamilton ON Canada

Solid-state Single Photon Avalanche Diodes (SPADs) have emerged as versatile photodetectors, playing a pivotal role in cutting-edge technologies such as photon counting, timing, and imaging. Their exceptional characteristics — high timing resolution, fast response, high gain, excellent quantum efficiency, and immunity to magnetic fields — make them a compelling alternative to traditional Photomultiplier Tubes (PMTs). SPADs' unique ability to detect single photons, combined with their digital output and compact size, has positioned them as a superior choice for a wide range of applications in engineering, environmental monitoring, and healthcare. This review provides a comprehensive analysis of SPAD technology, focusing on its design principles, performance metrics, and applications. We begin by exploring the fundamental operating principles of SPADs and their key performance metrics. Next, we examine various SPAD structures across different technology nodes, offering a comparative analysis to highlight the latest advancements. Based on our review, we identify several techniques to enhance SPAD performance, including: doping profile engineering, such as using high-voltage layers and doping compensation layers, upgrading optical stacks, and integration of high-speed front-end circuitry. We then introduce application-specific figures-of-merit and assess their relevance to the reviewed structures. Additionally, we address emerging trends in SPAD design, such as leveraging mask layer technology to achieve significant advancements. Finally, we conclude with an overview of research challenges, potential solutions, and future directions in SPAD technology, providing valuable insights to drive further innovations in this dynamic field.

关键词： Single-photon avalanche diodes Photonics Silicon Absorption Timing Reviews Indium gallium arsenide CMOS technology Breakdown voltage P-n junctions

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A Multi-Stage Security Solution for Medical Color Images in Healthcare Applications

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computer Systems science & engineering 2023年第9期46卷 3599-3618页

作者： Walid El-Shafai Fatma Khallaf El-Sayed M.El-Rabaie Fathi E.Abd El-Samie Iman Almomani Security Engineering Lab Computer Science DepartmentPrince Sultan UniversityRiyadh11586Saudi Arabia Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Electrical Engineering Faculty of EngineeringAhram Canadian UniversityGizaEgypt Computer Science Department King Abdullah II School of Information TechnologyThe University of JordanJordan11942Jordan

This paper presents a robust multi-stage security solution based on fusion,encryption,and watermarking processes to transmit color healthcare images,*** presented solution depends on the features of discrete cosine transform(DCT),lifting wavelet transform(LWT),and singular value decomposition(SVD).The primary objective of this proposed solution is to ensure robustness for the color medical watermarked images against transmission *** watermark embedding,the host color medical image is transformed into four sub-bands by employing three stages of *** resulting low-frequency sub-band is then transformed by employing three stages of DCT followed by SVD ***,a fusion process is used for combining different watermarks into a single watermark *** single fused image is then ciphered using Deoxyribose Nucleic Acid(DNA)encryption to strengthen the ***,the DNA-ciphered fused watermark is embedded in the host medical image by applying the suggested watermarking technique to obtain the watermarked *** main contribution of this work is embedding multiple watermarks to prevent identity *** the presence of different multimedia attacks,several simulation tests on different colormedical images have been *** results prove that the proposed security solution achieves a decent imperceptibility quality with high Peak Signal-to-Noise Ratio(PSNR)values and high correlation between the extracted and original watermark ***,the watermark image extraction process succeeds in achieving high efficiency in the presence of attacks compared with related works.

关键词： Medical images DNA encryption digital image watermarking fusion healthcare applications

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Intrusion detection system for malicious traffic using evolutionary search algorithm

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Recent Advances in computer science and Communications 2021年第5期14卷 1381-1389页

作者： Al-Saqqa, Samar Al-Fayoumi, Mustafa Qasaimeh, Malik Department of Information Technology King Abdullah II School of Information Technology The University of Jordan Amman Jordan Department of Computer Science King Hussein School of Computing Sciences Princess Sumaya University for Technology Amman Jordan Department of Software Engineering King Hussein School of Computing Sciences Princess Sumaya University for Technology Amman Jordan

Introduction: Intrusion detection systems play a key role in system security by identifying potential attacks and giving appropriate responses. As new attacks are always emerging, intrusion detection systems must adapt to these attacks, and more work is continuously needed to develop and propose new methods and techniques that can improve efficient and effective adaptive intrusion systems. Feature selection is one of the challenging areas that need more work because of its importance and impact on the performance of intrusion detection systems. This paper applies an evolutionary search algorithm in feature subset selection for intrusion detection systems. Methods: The evolutionary search algorithm for the feature subset selection is applied and two clas-sifiers are used, Naïve Bayes and decision tree J48, to evaluate system performance before and after features selection. NSL-KDD dataset and its subsets are used in all evaluation experiments. Results: The results show that feature selection using the evolutionary search algorithm enhances the intrusion detection system with respect to detection accuracy and detection of unknown attacks. Furthermore, time performance is achieved by reducing training time, which is reflected positively in overall system performance. Discussion: The evolutionary search applied to select IDS algorithm features can be developed by modifying and enhancing mutation and crossover operators and applying new enhanced techniques in the selection process, which can give better results and enhance the performance of intrusion detection for rare and complicated attacks. Conclusion: The evolutionary search algorithm is applied to find the best subset of features for the intrusion detection system. In conclusion, it is a promising approach to be used as a feature selection method for intrusion detection. The results showed better performance for the intrusion detection system in terms of accuracy and detection rate. © 2021 Bentham science Publisher

关键词： Feature Selection

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Correction:Highly Efficient Back-End-of-Line Compatible Flexible Si-Based Optical Memristive Crossbar Array for Edge Neuromorphic Physiological Signal Processing and Bionic Machine Vision

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Nano-Micro Letters 2024年第12期16卷 133-133页

作者： Dayanand Kumar Hanrui Li Dhananjay D.Kumbhar Manoj Kumar Rajbhar Uttam Kumar Das Abdul Momin Syed Georgian Melinte Nazek El-Atab Smart Advanced Memory Devices and Applications(SAMA)LaboratoryElectrical and Computer EngineeringComputer Electrical Mathematical Science and EngineeringKing Abdullah University of Science and Technology(KAUST)23955-6900 ThuwalSaudi Arabia

Following publication of the original article[1],the authors noticed a mistake in the Supplementary file,more specifically in figures S11 and S12 where they used by mistake the same *** original article[1]has been cor... 详细信息

关键词： Mem Crossbar Highly

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Electrothermal 1D Varifocal Metalens

Electrothermal 1D Varifocal Metalens

引用

Conference on Lasers and Electro-Optics (CLEO)

作者： Quentin A. A. Tanguy Hussein Hussein Shane Colburn Luocheng Huang Karl F. Böhringer Arka Majumdar Department of Electrical & Computer Engineering University of Washington Seattle Washington USA Department of Electrical & Computer Engineering King Abdullah University of Science and Technology Thuwal Saudi Arabia

We report a MEMS-based spatial light modulator which consists of an electrothermally actuated varifocal metasurface. The focal length can be tuned over a range of 40 µm with less than 10 V. The lens exhibits a hi... 详细信息

ISBN: (数字)9781957171050

ISBN: (纸本)9781665466660

关键词： Fabrication Modulation Lasers and electrooptics Electro-optic modulators Metasurfaces Laser tuning Lenses

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