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Communications, Computing, Cybersecurity, and Informatics (CCCI), International Conference on

作者： Mohammad S. Obaidat Chandrashekhar Meshram Deepak Kartikey Kuei-Fang Hsiao Agbotiname Lucky Imoize Sharad Kumar Barve King Abdullah II School of Information Technology The University of Jordan Amman Jordan School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China Department of Computational Intelligence School of Computing SRM University Kattankulathur TN India School of Engineering The Amity University Noida UP India Department of Post Graduation Studies and Research in Mathematics Jayawanti Haksar Government Post Graduation College College of Barkatullah University Betul M.P. India Department of Mathematics S.S.P. Govt. College Waraseoni Balaghat M.P. India Computer Science Department University of Texas-Permian Basin Odessa TX USA Department of Electrical and Electronics Engineering Faculty of Engineering University of Lagos Lagos Nigeria Department of Electrical Engineering and Information Technology Institute of Digital Communication Ruhr University Bochum Germany Department of Mathematics Pandit S. N. Shukla University Shahdol Shahdol Madhya Pradesh India

Smart cities are fast proliferating the global space in recent times. In order to achieve the envisioned next-generation cities, the smart city paradigm aspires to develop a completely integrated network-based infrastructure. With the development of innovative smart cities, ICT-based e-governance has made it possible for services to be delivered intelligently and interactively via online platforms. However, the communication between government agencies and other stakeholders in the smart city ecosystem is through open channels, which poses serious security concerns. In order to address this problem, this work proposes a robust remote client password authentication technique for e-governance applications in smart cities. The proposed authentication technique is lightweight, resistant to several attacks, and achieves low computational overhead.

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Network Traffic Prediction for Intelligent Transportation Systems: A Reinforcement Learning Approach

Network Traffic Prediction for Intelligent Transportation Sy...

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GLOBECOM 2022 - 2022 IEEE Global Communications Conference

作者： Jian Song Hua Liu Laisen Nie Zhaolong Ning Mohammad S. Obaidat Balqies Sadoun School of Electronics and Information Northwestern Polytechnical University Xi'an P.R.China School of Communication and Information Engineering Chongqing University of Posts and Telecommunications Chongqing China School of Computer Science and Engineering Macau University of Science and Technology Macau China Computer Science Department Director of Cybersecurity Center University of Texas-Permian Basin Odessa TX USA King Abdullah II School of Information Technology The University of Jordan Amman Jordan and University of Science and Technology Beijing Beijing China College of Engineering Al Balqa’ Applied University Al Salt Jordan

ISBN: (纸本)9781665435413

Vehicular Ad-Hoc Networks (VANETs), as the cru-cial support of Intelligent Transportation Systems (ITS), have received a great attention in recent years. Network traffic prediction is useful for network management and security in VANETs, such as network planning and anomaly detection. Due to the movement of nodes, the traffic flow in VANETs consists of a great number of irregular fluctuations, which is the main challenge for network traffic prediction. This paper proposes a novel algorithm, which combines Deep Q-Learning (DQN) and Generative Adversarial Networks (GAN) for network traffic prediction. We use DQN to carry out network traffic prediction, in which GAN is involved to represent Q-network. Meanwhile, the generative network can increase the number of samples to improve the prediction error. We evaluate the performance of our method by implementing it on two real network traffic data sets. Finally, we compare the two state-of-the-art competing methods with our method.

关键词： Training Q-learning Telecommunication traffic Prediction methods Generative adversarial networks Prediction algorithms Multitasking

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Strain-induced Differentiation of Mesenchymal Stem Cells

Strain-induced Differentiation of Mesenchymal Stem Cells

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Khalil Moussi Dina B. Abusamra Omar Yassine Jasmeen Merzaban Jürgen Kosel Computer Electrical and Mathematical Science and Engineering division King Abdullah University of Science and Technology Thuwal Saudi Arabia Biological Environmental Science and Engineering division King Abdullah University of Science and Technology Thuwal Saudi Arabia

ISBN: (数字)9781728119908

ISBN: (纸本)9781728119915

Directing the fate of human mesenchymal stem/stromal cells (hMSCs) toward bone formation using mechanical strain is a promising approach in regenerative medicine related to bone diseases. Numerous studies have evaluated the effects of vibration or cyclic tensile strain on MSCs towards developing a mechanically-based method for stimulating differentiation. Here, we study the differentiation of hMSCs cultured on elastic polydimethylsiloxane (PDMS) membrane, which is magnetically actuated to induce periodically varying strain. The strain distribution across the membrane was calculated by finite-element modeling and demonstrates three main areas of different strain amplitudes. The strain effect on the hMSCs was evaluated by measuring the mineralization of differentiated hMSCs using Alizarin S red stain. The results indicate a strain-dependent differentiation of hMSCs, where the highest region of strain on the membrane resulted in the most accelerated differentiation. Osteogenic differentiation was achieved as early as two weeks, which is significantly sooner than control hMSCs treated with osteogenic media alone.

关键词： Strain Biomembranes Stem cells Vibrations Electromagnetics Shape Two dimensional displays

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Mean-square Analysis of the NLMS Algorithm

arXiv

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arXiv 2021年

作者： Al-Naffouri, Tareq Y. Moinuddin, Muhammad Ali, Anum Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia Department of Electrical and Computer Engineering King Abdulaziz University Jeddah21589 Saudi Arabia King Abdulaziz University Jeddah21589 Saudi Arabia Standards and Mobility Innovation Laboratory Samsung Research America PlanoTX75023 United States

This work presents a novel approach to the mean-square analysis of the normalized least mean squares (NLMS) algorithm for circular complex colored Gaussian inputs. The analysis is based on the derivation of a closed-form expression for the Cumulative Distribution Function (CDF) of random variables of the form (||u||2D1)(||u||2D2)−1 where u is an isotropic vector and D1 and D2 are diagonal matrices and using that to derive some moments of these variables. These moments in turn completely characterize the mean-square behavior of the NLMS algorithm in explicit closed-form expressions. Specifically, the transient, steady-state, and tracking mean-square behavior of the NLMS algorithm is studied. © 2021, CC BY.

关键词： Factorization

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Polarization Insensitive and Transparent FSS for Flexible Electronics Applications

Polarization Insensitive and Transparent FSS for Flexible El...

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IEEE International Symposium on Antennas and Propagation

作者： Yiming Yang Weiwei Li Atif Shamim Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal KSA

ISBN: (数字)9781728166704

ISBN: (纸本)9781728166704;9781728166711

This paper proposes a polarization-insensitive, dual-band FSS reflector with a 45° maximum stable incident angle. A novel design, which evolved from fractal cross dipoles, is presented for GSM bands shielding. Due to the quadruple symmetry structure, the response of the proposed FSS is consistent for both TE and TM incident waves. A prototype, realized through a custom silver nanowires based transparent ink on a flexible PET sheet, demonstrates over 80% optical transparency. Simulations and measurements are in agreement, showing good reflection performance from 0.71 to 1.25 GHz and from 1.73 to 2.16 GHz. The printed FSS is a good candidate for various shielding applications in flexible transparent electronics.

关键词： Frequency selective surfaces GSM Silver Prototypes Dual band Reflection Nanowires

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Adaptive and Robust Control for Energy Efficiency Enhancement of a Solar-powered Desalination System ⁎

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IFAC-PapersOnLine 2020年第2期53卷 16543-16548页

作者： Mohammad Alharbi Fahad Aljehani Ibrahima N’Doye Taous-Meriem Laleg-Kirati Computer Electrical and Mathematical Sciences and Engineering Division (CEMSE) King Abdullah University of Science and Technology (KAUST) Thuwal 23955-6900 Saudi Arabia

In this paper, an adaptive control strategy is proposed to enhance the energy production efficiency under environmental changes. The control objective is to force the outlet temperature of a solar thermal collector fluid to track the desired reference temperature regardless of the solar irradiance variations. An adaptive nonlinear control that combines an inner loop feedback control and an outer loop model-free control strategy is proposed to ensure asymptotic convergence of the tracking error. The proposed adaptive control strategy is applied to an approximate bilinear model derived from the heat transfer equation. Numerical simulations are presented to illustrate the performance of the control strategy in terms of tracking accuracy and settling time. Furthermore, the improvement in energy production is highlighted through a powering thermal membrane distillation based desalination in increasing water production.

关键词： Parabolic solar collector plant water desalination system bilinear approximate model model-free control adaptive feedback controller

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Backflash Light as a Security Vulnerability in Quantum Key Distribution Systems

arXiv

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arXiv 2020年

作者： Vybornyi, Ivan Trichili, Abderrahmen Alouini, Mohamed-Slim Computer Electrical and Mathematical Sciences & Engineering King Abdullah University of Science and Technology Thuwal Makkah Province

Based on the fundamental rules of quantum mechanics, two communicating parties can generate and share a secret random key that can be used to encrypt and decrypt messages sent over an insecure channel. This process is known as quantum key distribution (QKD). Contrary to classical encryption schemes, the security of a QKD system does not depend on the computational complexity of specific mathematical problems. However, QKD systems can be subject to different kinds of attacks, exploiting engineering and technical imperfections of the components forming the systems. Here, we review the security vulnerabilities of QKD. We mainly focus on a particular effect known as backflash light, which can be a source of eavesdropping attacks. We equally highlight the methods for quantifying backflash emission and the different ways to mitigate this effect. Copyright © 2020, The Authors. All rights reserved.

关键词： Quantum cryptography

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Enhancing PV performance of Al/ZnO/CdS/GaAs/NiO/Au solar cells through diverse layer combinations by SCAPS-1D

Next Research

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Next Research 2025年第1期2卷

作者： Md. Salman Shah Md. Kamrul Hasan Sharat Chandra Barman Jubaer Ahamed Bhuiyan Hayati Mamur Mohammad Ruhul Amin Bhuiyan Department of Electrical and Electronic Engineering Islamic University Kushtia 7003 Bangladesh Department of Electrical and Electronic Engineering Teesta University Rangpur Bangladesh Postdoctoral Associate King Abdullah University of Science and Technology (KAUST) Saudi Arabia Department of Computer Science and Engineering International University of Business Agriculture and Technology Dhaka 1230 Bangladesh Department of Electrical and Electronics Engineering Manisa Celal Bayar University Manisa 45140 Türkiye

Gallium arsenide (GaAs)-based photovoltaic (PV) cells are widely recognized for their outstanding efficiency and excellent light absorption capabilities, making them a preferred option in advanced solar energy technologies. Despite these advantages, their widespread application is limited by high production costs, thermal management issues, and inefficient charge carrier transport. This study aims to overcome these challenges by developing and optimizing a multilayer solar cell with the configuration Al/ZnO/CdS/GaAs/NiO/Au using SCAPS-1D simulation software. Key parameters, such as layer thickness, donor and acceptor densities, series and shunt resistances, and operating temperature, were systematically optimized to boost the device's performance. Under standard AM1.5 G illumination, the optimized solar cell achieved an open-circuit voltage (V OC ) of 1.0825 V, a short-circuit current density (J SC ) of 31.42 mA/cm², a fill factor (FF) of 87.43 %, and a power conversion efficiency (PCE) of 29.74 %, with quantum efficiency (QE) nearing 100 % within the visible spectrum. These enhancements demonstrate not only the potential for achieving high efficiency but also practical strategies for addressing key limitations in GaAs PV technology. The study highlights the promise of these optimized cells for high-performance applications, including space PVs, concentrated solar power systems, and other scenarios requiring compact and efficient energy solutions.

关键词： Gallium arsenide (GaAs) solar cells SCAPS-1D simulation High-efficiency photovoltaic cells (PV cells) Power conversion efficiency (PCE) Quantum efficiency (QE)

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IoT-Driven Regression Tree Models for Efficient Microwave Dielectric Material Characterization: Addressing Non-Linear Cavity Sensing

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IEEE Internet of Things Journal 2025年

作者： Khusro, Ahmad Akhter, Zubair Jha, Abhishek K. Shamim, Atif Hashmi, Mohammad S. Nazarbayev University School of Engineering and Digital Sciences Dept. of Electrical and Computer Engineering Astana000010 Kazakhstan King Abdullah University of Science and Technology Impact Lab CEMSE Division Jeddah Saudi Arabia Abu Dhabi United Arab Emirates Indian Institute of Technology Tirupati Department of Electrical Engineering India

Interconnected microwave dielectric sensing nodes have the potential to revolutionize microwave material processing and design, where microwave dielectric materials characterization (MDMC) with high precision and rapid circuit design are crucial. This research presents an Internet of Things (IoT)-enabled automated MDMC system designed to tackle the non-linearity challenges in the extended cavity perturbation regime. Utilizing a cylindrical cavity operating in TE111 mode at 5 GHz, the proposed MDMC system is extensively trained on a diverse range of materials through numerous full-wave 3D electromagnetic simulations. The outputs, i.e., relative permittivity and loss tangent, are derived using advanced machine learning models, including Decision Tree (DT) and Ensemble Learning (EL). A comparative analysis that incorporates simulation, measurement, and predicted permittivity values across varying sample dimensions demonstrates the robustness and accuracy of the DT and EL model. This validates the effectiveness of our high-quality sensor node and sophisticated data processing techniques within an IoT-centric framework. © 2014 IEEE.

关键词： Microwave materials processing

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Schrödinger Spectrum Based PPG Features for the Estimation of the Arterial Blood Pressure

Schrödinger Spectrum Based PPG Features for the Estimation ...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Peihao Li Taous-Meriem Laleg-Kirati Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology (KAUST) KSA

ISBN: (数字)9781728119908

ISBN: (纸本)9781728119915

In this paper, photoplethysmogram (PPG) features are combined with supervised machine learning algorithms to estimate arterial blood pressure (ABP). Three algorithms for the estimation of cuffless ABP using PPG signals are compared. Since PPG signals are measured non-invasively, this method guarantees an individuals comfort while not omitting important ABP information. The proposed framework predicts the ABP values by processing PPG signals with semi-classical signal analysis (SCSA) method, extracting several categories of features, which reflect the PPG signal morphology variations. Then, regression algorithms are selected for the ABP estimation. The proposed method is evaluated based on a virtual dataset with more than four thousand subjects and MIMIC II database with over eight thousand subjects for model training and testing. Mean average error (MAE) and standard deviation (STD) are evaluated for different machine learning algorithms during the prediction and estimation process. Multiple linear regression (MLR) meets the AAMI standard in terms of estimation accuracy, which proves that the ABP can be accurately estimated in a nonintrusive fashion. Given the easy implementation of the ABP estimation method, we regard that the proposed features and machine learning algorithms for the cuffless estimation of the ABP can potentially provide the means for mobile healthcare equipment to monitor the ABP continuously.

关键词： Feature extraction Estimation Standards Support vector machines Databases Eigenvalues and eigenfunctions Machine learning algorithms

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