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7th Computational Methods in Systems and Software, CoMeSySo 2023

作者： Meghanathan, Natarajan Department of Electrical and Computer Engineering and Computer Science Jackson State University 1400 Lynch Street JacksonMS39217 United States

ISBN: (纸本)9783031548123

We propose a principal component analysis (PCA)-based approach to quantify (the node dissimilarity index, NDI) the extent of dissimilarity among nodes in a network with respect to values incurred for a suite of node-level metrics (like centrality metrics). We subject the dataset (n nodes and their values incurred for four commonly studied centrality metrics: degree, eigenvector, betweenness and closeness) to PCA and retain the m (≤4) principal components (with variance ≥ 1.0). We construct an n-node dissimilarity matrix whose entries are the absolute difference (if m = 1) or Euclidean distance (if m > 1) of the principal component coordinates of the corresponding nodes. We compute NDI (≥1.0) to be the ratio of the principal Eigenvalue of the node dissimilarity matrix and average of entries in the node dissimilarity matrix. The larger the NDI, the greater the dissimilarity among the node-level metrics (centrality metrics) values considered for analysis. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Principal component analysis

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Multiphysics Analysis of Screening Effects on Terahertz Photoconductive Devices

Multiphysics Analysis of Screening Effects on Terahertz Phot...

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2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio science Meeting, AP-S/URSI 2022

作者： Chen, Liang Dong, Ming Bagci, Hakan Electrical and Computer Engineering Program Computer Electrical and Mathematical Science and Engineering Division Thuwal23955-6900 Saudi Arabia

ISBN: (数字)9781665496582

ISBN: (纸本)9781665496582

Output saturation observed for high power levels of input optical pump is a well-known bottleneck in the operation of terahertz photoconductive devices (PCDs). This saturation is a result of various screening effects that stem from the interactions between electromagnetic fields and semiconductor charge carriers. To simulate these effects, this work uses a time-domain multiphysics approach that solves a coupled system of the Maxwell and the drift-diffusion equations to rigorously take into account the two-way nonlinear coupling between fields and carriers. Furthermore, an optical absorption-based model is used to correctly compute the carrier generation rate. The resulting multiphysics solver is used to simulate realistic PCDs, and excellent agreement is observed between the simulation and experimental results. © 2022 IEEE.

关键词： Multiphysics

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UAV-RIS Assisted Multiuser Communications Through Transmission Strategy Optimization: GBD Application

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IEEE Transactions on Vehicular Technology 2024年第6期73卷 8584-8597页

作者： Huroon, Aamer Mohamed Huang, Yu-Chih Wang, Li-Chun The Department of Electrical Engineering & Computer Science National Yang-Ming Chiao Tung University Hsinchu300 Taiwan The Institute of Communications Engineering National Yang-Ming Chiao Tung University Hsinchu300 Taiwan

In this article, we present a transmission strategy optimization technique for multiple unmanned aerial vehicles (UAVs) base stations assisted by a terrestrial reconfigurable intelligent surface (RIS). While each UAV is designed to serve a particular group of users, whether a UAV is assisted by RIS depends on the distance between the UAV and the terrestrial RIS. As such, a joint optimization problem of the allocation of RIS clusters for each associated UAV and the computation of phase rotations corresponding to terrestrial RIS elements is formulated. Based on the generalized Benders decomposition (GBD), we develop an algorithm to solve the problem efficiently for this mixed integer non-linear programming problem (MINLP) in two cases: 1) treating interference as noise (TIN) and 2) applying successive interference cancellation (SIC) at user terminals. Through extensive simulations, we provide evidence of our algorithm’s superiority over existing methods, including alternating optimization and multi-task learning. By checking the upper and lower bounds provided by the proposed algorithm, we show that our algorithm attains the global optimality for the considered simulations. Notably, our results also reaffirm the common belief that SIC decoding can provide performance enhancement over TIN decoding in the UAV-RIS-assisted systems. © 2024 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission.

关键词： Antennas

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Optimizing QoE in IoT-Based Video Streaming through Deep Learning Algorithms 6

Optimizing QoE in IoT-Based Video Streaming through Deep Lea...

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6th International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2024

作者： Darwich, Mahmoud Khalil, Kasem Bayoumi, Magdy University of Mount Union Department of Mathematics and Computer Science AllianceOH44601 United States University of Mississippi Department of Electrical and Computer Engineering MS38677 United States University of Louisiana Department of Electrical and Computer Engineering LafayetteLA70504 United States

ISBN: (纸本)9798350344349

The demand for video streaming services over Internet of Things (IoT) networks has surged, yet maintaining a high Quality of Experience (QoE) remains challenging due to network heterogeneity and resource constraints. This paper presents an innovative deep learning-based approach to optimize QoE in IoT-based video streaming. Leveraging convolutional neural networks (CNN) and long short-Term memory (LSTM) networks, the proposed framework dynamically adapts video streaming parameters in real-Time, such as bit rate, frame rate, and resolution, based on the existing network conditions and device capabilities. Through extensive simulations and real-world deployments, our approach exhibited a 24.5% reduction in re-buffering ratio, a 12.5% increase in average bitrate, and a 15% improvement in video quality measured by SSIM, compared to conventional methods. Furthermore, it reduced network bandwidth consumption by up to 150% without compromising on video quality. These results underscore the effectiveness of applying deep learning algorithms to optimize video streaming in complex IoT environments. © 2024 IEEE.

关键词： Video streaming

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Wide and fault diameter in Kneser graphs for enhanced fault tolerance in parallel computing

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International Journal of Networking and Virtual Organisations 2024年第3期31卷 169-190页

作者： Sundara Rajan, R. Kirithiga Nandini, G. Lin, Yuqing Reji, Remi Mariam Department of Mathematics Hindustan Institute of Technology and Science Chennai603 103 India Department of Computer Science and Engineering Hindustan Institute of Technology and Science Chennai603 103 India School of Electrical Engineering and Computing The University of Newcastle CallaghanNSW2308 Australia Department of Mathematics Christian College Kerala Chengannur689 122 India

A system’s fault tolerance is its capacity to function even if one or more of its components fail. Implementing a fault-tolerant network becomes an important criterion for reliable computing. Reliability measures play a significant part in recognising the role of faulty and non-faulty processors in a parallel computing system. Parallel computing is used primarily for saving time, solving big problems, and doing multiple tasks at once at the same time. Various reliability measures have been introduced to evaluate a network’s fault-tolerance capability. We have measured the wide diameter and fault diameter of the Kneser graphs in this study. Also, we have verified the fault diameter obtained using an experimental study. Further, we have described some applications of wide diameter and fault diameter in parallel and distributed computing. Copyright © 2024 Inderscience Enterprises Ltd.

关键词： Fault tolerant computer systems

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Quantum Computing Circuit Design: A Tutorial 15

Quantum Computing Circuit Design: A Tutorial

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15th International Conference on Advanced Scientific Computing, ICASC 2024

作者： Abdul Wahid, Seham Al Asad, Arghavan Kaur, Rupinder Mohammadi, Farah Toronto Metropolitan University Electrical and Computer Engineering Department Toronto Canada School of Computer Science and Technology Algoma University Brampton Canada

ISBN: (纸本)9798350356526

Recent advancements in computing speed and capacity of Artificial Intelligence (AI) algorithms have reached a saturation level in performance due to the continuous application of Moore's law which resulted in the memory wall phenomenon. Quantum computing (QC), based on the principles of quantum mechanics which include superposition and entanglement, has the potential to contribute to the advancements of AI by providing exponential speedup. Quantum computers use quantum bits, also known as qubits, as the metric to demonstrate the power of quantum technology. Qubits, the fundamental unit of quantum information can exist in two states, 0 and 1, simultaneously, leveraging the principle of superposition. Quantum gates are the building blocks of quantum circuits, operating on qubits to transform one quantum state into another, and are comparative to classical logic gates. Designing and simulating quantum circuits can be completed using the Qiskit library design by IBM. Qiskit is a cloud-based, open access platform to real quantum computers with 5 to 16 qubits. This paper offers a straightforward tutorial on implementing one, two and three-qubit quantum gates, as well as designing quantum circuits using the Qiskit library, illustrated with an example of a quantum half adder implementation. © 2024 IEEE.

关键词： Qubits

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Adversarial Encoder-Driven Filter for Targeted Image Tagging: A Novel Approach to Visual Content Manipulation 6

Adversarial Encoder-Driven Filter for Targeted Image Tagging...

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6th IEEE International Conference on Image Processing, Applications and Systems, IPAS 2025

作者： Mckee, Cole Flowers, Dominic Wood, Jesse Shafer, Ethan United States Military Academy Department of Electrical Engineering and Computer Science West PointNY10996 United States

ISBN: (纸本)9798331506520

computer vision, driven by artificial intelligence, has become pervasive in diverse applications such as self-driving cars and law enforcement. However, the susceptibility of these systems to attacks has raised significant concerns among researchers. This paper addresses the vulnerability of image tagging algorithms, particularly focusing on misclassifications induced by autoencoders. We present experiments conducted on Amazon Rekognition, where we developed a specialized autoencoder to manipulate the latent space, forcing it to align with specific tags. By integrating this manipulated latent space with other images, we demonstrate the ability to increase the confidence of a specific tag on Amazon Rekognition, leading to more false positives of the chosen tag. Our study showcases a practical method to exploit Amazon's Rekognition image tagging algorithm using a black box approach. © 2025 IEEE.

关键词： Adversarial machine learning

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Enhancing Healthcare Monitoring Systems: A Case Analysis in Optimization 18

Enhancing Healthcare Monitoring Systems: A Case Analysis in ...

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18th INDIAcom;11th International Conference on Computing for Sustainable Global Development, INDIACom 2024

作者： Lalit, Mohit Bathla, Gaurav Singh, Surender Chandigarh University Computer Science and Engineering Department Mohali India Career Program Code Quotient Mohali India

ISBN: (纸本)9789380544519

In the past few years, fog computing (FC) has emerged as a promising complement to cloud computing. It offers reduced latency, minimal bandwidth consumption, and real-time data transfer. In healthcare, particularly in IoT-enabled systems, FC integration has become pivotal for real-time monitoring and immediate data transfer to health experts. The researchers all around the world proposed and developed various communication frameworks and come up with certain outputs in terms of quality-of-service parameters (QoS). However, these QoS parameters are not always appropriate for effective execution of the application. Following that, this study explores the integration of FC with multi-objective Optimization Algorithms (such as FFLY and GWO) to optimize crucial quality of service (QoS) metrics using a proposed linear function to optimize multi objectives, essential for sustained communication. The research focuses on optimizing multi objectives in healthcare monitoring systems. Experimental results reveal the superiority of the Grey Wolf Optimizer (GWO) over the Firefly Algorithm (FFLY). This study emphasizes the crucial significance of multi-objective optimisation algorithms in optimizing critical parameters for successful healthcare communication frameworks, which can lead to improvements in healthcare monitoring efficiency. © 2024 Bharati Vidyapeeth, New Delhi.

关键词： Fog Computing Healthcare 4.0 Industry 4.0 IoT Optimization

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An Integrated Demand Side Management Framework Utilizing Smart Grid Technologies and IoT for Enhanced Residential Energy Efficiency

An Integrated Demand Side Management Framework Utilizing Sma...

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2024 IEEE International Women in engineering (WIE) Conference on electrical and computer engineering, WIECON-ECE 2024

作者： Venkatesan, P. Gopinath, C. Prabhavathy, P. Department of Electrical and Electronics Engineering India Center for Integrated Smart Waste Management System Department of Electrical and Electronics Engineering Sriperumbudur India Anna University Department of Computer Science and Engineering College of Engineering Guindy Chennai India

ISBN: (纸本)9798331535476

Increasing energy demands and the need for efficient management necessitate innovative solutions. This study introduces an integrated Demand Side Management (DSM) framework tailored for residential buildings within smart grid systems. The proposed methodology employs Earth Worm Optimization Algorithm (EWOA) and Virulence Optimization Algorithm (VOA) to optimize scheduling for household appliance using integration of Renewable Energy Storage (RES) and Renewable Energy Resources (RERs). Real-Time Electricity Scheduling (RTES) is implemented using IoT technologies to enable adaptive energy management. This system demonstrates significant performance improvements, achieving a 76.19% reduction in the Peak-to-Average Ratio (PAR) using VOA and a 73.8% reduction with EWOA when RES is included. Comparative analyses highlight substantial cost reductions, enhanced grid stability, and improved energy efficiency. This work not only showcases the novelty of integrating advanced optimization algorithms with IoT but also provides a robust approach to achieve sustainable and cost-effective energy management. © 2024 IEEE.

关键词： Smart power grids

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MagFingerprint: A Magnetic Based Device Fingerprinting in Wireless Charging 42

MagFingerprint: A Magnetic Based Device Fingerprinting in Wi...

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42nd IEEE International Conference on computer Communications, INFOCOM 2023

作者： Li, Jiachun Meng, Yan Zhang, Le Chen, Guoxing Tian, Yuan Zhu, Haojin Shen, Xuemin Sherman Shanghai Jiao Tong University Department of Computer Science and Engineering Shanghai China University of California Electrical and Computer Engineering Department Los Angeles United States Department of Electrical and Computer Engineering University of Waterloo Waterloo Canada

ISBN: (纸本)9798350334142

Wireless charging is a promising solution for charging battery-driven devices pervasively. However, the wide deployment of wireless charging stations is vulnerable to the device masquerade attack, which causes financial loss when billing or charging system damages like overheating and explosion. Device fingerprinting is a classical technique to thwart the device masquerade attack. But existing works either are vulnerable to forging or require specialized equipment, which is not suitable for wireless *** this paper, we design a magnetic based fingerprinting system MagFingerprint, which utilizes the alternating magnetic signals as the fingerprint and is compatible with existing wireless charging systems. MagFingerprint is convenient for the user since it only employs commercial-off-the-shelf (COTS) magnetic sensors and requires no action from users. In particular, for the charging device, based on its intrinsic manufacturing errors, MagFingerprint generates a unique fingerprint according to the distinct magnetic changes during the wireless charging process. It is shown that MagFingerprint can achieve an accuracy of 98.90% on wireless charging exposed coils, while it is also effective on different commercial wireless charging pads of Apple, Huawei, and Xiaomi. © 2023 IEEE.

关键词： Losses

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