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Advanced Electromagnetics 2022年第4期11卷 10-21页

作者： Al-Sabea, Zaid Saad Ibrahim, Abdullahi Abdu Abdulnabi, Saif Hasan Department of Electrical and Computer Engineering Altinbas University Mahmutbey Istanbul34218 Turkey Department of Computer Techniques Engineering Imam Ja’afar Al-Sadiq University Maysan Street Najaf54001 Iraq Department of Electrical Engineering University of Baghdad Al-Jadriya Baghdad10001 Iraq Department of Electronic and Communications Engineering University of Kufa Kufa Street Najaf54001 Iraq

This paper displays a design that realizes all optical logic gates (NOT, AND, OR, NAND, NOR, XOR, XNOR) and consisting of one nanoring and four strips Operates on the principle of resonance. the proposed design works at the wavelength of 1550 nm using insulator-metal-insulator (IMI) plasmonic waveguide. The basic principle of the operation of these gates is input and control signals’ constructive and destructive interference. The proposed transmission threshold’s value is 0.25 between OFF state and ON state. The proposed design has small dimensions (300 nm × 300 nm) and can realize seven logic gates with maximum transmission 134% at NOT gate, 223% at OR gate, 134% at NAND gate and 223% at XNOR gate where the design is optimum and the modulation depth is very high because it’s ranges in all gates more than 90%. The proposed structure contributes in building nanocircuits for integrated photonic circuits and optical signal processing. © 2022, Advanced Electromagnetics. All rights reserved.

关键词： Logic gates

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Enhancing Wireless Sensor Network Efficiency through Al-Biruni Earth Radius Optimization

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computers, Materials & Continua 2024年第6期79卷 3549-3568页

作者： Reem Ibrahim Alkanhel Doaa Sami Khafaga Ahmed Mohamed Zaki Marwa M.Eid Abdyalaziz A.Al-Mooneam Abdelhameed Ibrahim S.K.Towfek Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Computer Science and Intelligent Systems Research Center BlacksburgVirginia24060USA Delta Higher Institute for Engineering and Technology Mansoura35511Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Artificial Intelligence and Computational Intelligence Research Center MeridenConnecticut06450USA School of ICT Faculty of EngineeringDesign and Information&Communications Technology(EDICT)Bahrain PolytechnicP.O.Box 33349Isa TownBahrain

The networks of wireless sensors provide the ground for a range of applications,including environmental moni-toring and industrial *** the networks can overcome obstacles like power and communication reliability and sensor coverage is the crux of network *** infrastructure planning should be focused on increasing performance,and it should be affected by the detailed data about node *** work recommends the creation of each sensor’s specs and radius of influence based on a particular geographical location,which will contribute to better network planning and *** using the ARIMA model for time series forecasting and the Al-Biruni Earth Radius algorithm for optimization,our approach bridges the gap between successive terrains while seeking the equilibrium between exploration and *** implementing adaptive protocols according to varying environments and sensor constraints,our study aspires to improve overall network *** compare the Al-Biruni Earth Radius algorithm along with Gray Wolf Optimization,Particle Swarm Optimization,Genetic Algorithms,and Whale Optimization about performance on real-world *** the most efficient in the optimization process,Biruni displays the lowest error rate at *** two other statistical techniques,like ANOVA,are also useful in discovering the factors influencing the nature of sensor data and network-specific *** to the multi-faceted support the comprehensive approach promotes,there is a chance to understand the dynamics that affect the optimization outcomes better so decisions about network design can be *** delivering better performance and reliability for various in-situ applications,this research leads to a fusion of time series forecasters and a customized optimizer algorithm.

关键词： Wireless sensor networks optimization ARIMA model BER algorithm metaheuristic algorithms

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On Comparing Interference Impacts

On Comparing Interference Impacts

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2024 IEEE International Symposium on Electromagnetic Compatibility, Signal and Power Integrity, EMC+SIPI 2024

作者： Sanders, Aric Pirrone, Michelle Forsyth, M. Keith Wunderlich, Adam National Institute of Standards and Technology Communications Technology Laboratory BoulderCO United States University of Colorado Boulder Department of Electrical Computer and Energy Engineering BoulderCO United States

ISBN: (纸本)9798350360394

Interference between communication systems is a critical issue that can impact performance and operability of devices. A wide range of methods and testbeds have been developed to study susceptibility to interference, and each of these testbeds and their experimental test schedules can have different factors and responses. Although there is a variety in testbed design and measurement, it is common to choose a response that is assumed to vary with signal-to-noise ratio. A fundamental issue in any interference study of this type is the assignment of the power of the interference signal in a way that represents the desired environmental situation. This can be a challenging task for signals with disparate time, frequency and power dynamics. In particular, whether to assign a maximum (peak power) or a time averaged power becomes ambiguous for inter-interference signal comparisons. To address this problem we propose a quantitative scale based on the impact on the receiver of interest. We demonstrate how to form an interference signal agnostic scale and apply that scale for different interference situations. This scale, impact equivalent power ratio, can be transformed into an impact equivalent power with knowledge of the effective noise figure of the system under test. © 2024 IEEE.

关键词： Testbeds

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Local Features-Based Watermarking for Image Security in Social Media

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computers, Materials & Continua 2021年第12期69卷 3857-3870页

作者： Shady Y.El-mashad Amani M.Yassen Abdulwahab K.Alsammak Basem M.Elhalawany Department of Computer Systems Engineering Faculty of Engineering at ShoubraBenha UniversityEgypt Department of Communications and Electronics Engineering Faculty of Engineering at ShoubraBenha UniversityEgypt

The last decade shows an explosion of using social media,which raises several challenges related to the security of personal files including *** challenges include modifying,illegal copying,identity fraud,copyright protection and ownership of *** digital watermarking techniques embed digital information inside another digital information without affecting the visual quality for security *** this paper,we propose a hybrid digital watermarking and image processing approach to improve the image security ***,variants of the widely used Least-Significant Bit(LSB)watermarking technique are merged with a blob detection algorithm to embed information into the boundary pixels of the largest blob of a digital *** proposed algorithms are tested using several experiments and techniques,which are followed by uploading the watermarked images into a social media site to evaluate the probability of extracting the embedding *** results show that the proposed approaches outperform the traditional LSB algorithm in terms of time,evaluation criteria and the percentage of pixels that have changed.

关键词： Digital watermarking LSB social media blob detection image security

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Impact of Different Network Parameters on Federated Learning Performance in Vehicular Networks

Impact of Different Network Parameters on Federated Learning...

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Radio Frequency and Antenna Technologies (iWRF&AT), IEEE International Workshop on

作者： Tuliga Busqin Celimuge Wu Yangfei Lin Zhaoyang Du Department of Computer and Network Engineering The University of Electro-Communications Tokyo Japan

ISBN: (数字)9798350384765

ISBN: (纸本)9798350384772

This paper presents an in-depth examination of Federated Learning (FL) effectiveness in Vehicular Ad-Hoc Networks (VANETs) through systematic experimentation of road simulations. The paper methodically investigates the influence of various factors, such as communication range, client selection, vehicle density, and speed on FL performance within VANET systems. The findings emphasize that an increased communication range not only reduces communication overhead but also greatly enhances FL performance. Moreover, strategic client selection and optimal vehicular densities emerge as critical determinants for ensuring high-quality data and system efficiency. Remarkably, variations in vehicle speed are shown to have a minimal impact on FL performance, suggesting that vehicular speed has relatively limited effects on communication - efficiency. This paper offers a detailed understanding of the factors that affect FL performance in VANET systems, providing practical recommendations to optimize vehicular network systems.

关键词： Knowledge engineering Analytical models Systematics Federated learning Roads Vehicular ad hoc networks Transportation

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Prediction of Startup Performance Using Bidirectional Long Short-Term Memory with Parametric Switch Activation Function 1

Prediction of Startup Performance Using Bidirectional Long S...

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1st IEEE International Conference on Ambient Intelligence, Knowledge Informatics and Industrial Electronics, AIKIIE 2023

作者： Srivani, Putta Sowjanya, Gopu Kumar, Bura Vijay Al-Attabi, Kassem Mohammed, Ibraheem Hatem Hyderabad India Hyderabad India School of Computer Science and Artificial Intelligence Sr University Warangal India The Islamic University Najaf Iraq Al Rafidain University College Department of Computer Communications Engineering Bagdad Iraq

ISBN: (纸本)9798350316469

Predicting start-up success has garnered increasing attention in recent years. Numerous predictive models and methodologies have been devised to ascertain the probability of a start-up's triumph contingent on diverse aspects. Large datasets have been analysed using machine learning techniques like logistic regression, decision trees, and neural networks to find patterns that can help predict startup success. Predicting the success of a start-up, however, is a difficult undertaking because the business environment is unpredictable and changeable. Efficient resource utilization is crucial for economic development and has a direct impact on reducing unemployment rates. In order to minimize resource wastage and mitigate the risk of failure, the research identified and examined specific factors that influence the success or failure of small-scale companies. In the current research, the Crunch Base dataset is utilized to predict the failure or success of start-ups by employing the Bidirectional Long Short-Term Memory (Bi-LSTM) with Parametric Switch Activation (PSA) function model. The Bi-LSTM unit, a type of Recurrent Neural Network (RNN), incorporates the Feed Forward Neural (FFN) Network for classification purposes. The suggested Bi-LSTM model achieved a higher accuracy rate of 72.26% compared to existing methods. The suggested Bi-LSTM model achieved a higher accuracy rate of 72.26% compared to existing methods. © 2023 IEEE.

关键词： Bi-directional Long Short-Term Memory Crunch Base dataset Gross Domestic Product Recurrent Neural Network Start-up companies

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Universal Joint Source-Channel Coding for Modulation-Agnostic Semantic Communication

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IEEE Journal on Selected Areas in communications 2025年

作者： Huh, Yoon Seo, Hyowoon Choi, Wan Departement of Electrical and Computer Engineering Institute of New Media and Communications Seoul08826 Korea Republic of Sungkyunkwan University Department of Electrical and Computer Engineering Suwon16419 Korea Republic of

From the perspective of joint source-channel coding (JSCC), there has been significant research on utilizing semantic communication, which inherently possesses analog characteristics, within digital device environments. However, a single-model approach that operates modulation-agnostically across various digital modulation orders has not yet been established. This article presents the first attempt at such an approach by proposing a universal joint source-channel coding (uJSCC) system that utilizes a single-model encoder-decoder pair and trained vector quantization (VQ) codebooks. To support various modulation orders within a single model, the operation of every neural network (NN)-based module in the uJSCC system requires the selection of modulation orders according to signal-to-noise ratio (SNR) boundaries. To address the challenge of unequal output statistics from shared parameters across NN layers, we integrate multiple batch normalization (BN) layers, selected based on modulation order, after each NN layer. This integration occurs with minimal impact on the overall model size. Through a comprehensive series of experiments, we validate that the modulation-agnostic semantic communication framework demonstrates superiority over existing digital semantic communication approaches in terms of model complexity, communication efficiency, and task effectiveness. © 1983-2012 IEEE.

关键词： Vector quantization

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Optimizing Directed Spanning Trees for Enhanced Tolerance to Multiple Link Failures in SDN

Optimizing Directed Spanning Trees for Enhanced Tolerance to...

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OptoElectronics and communications Conference, OECC

作者： Hieu Tran The Nattapong Kitsuwan Department of Computer and Network Engineering The University of Electro-Communications Tokyo Japan

This paper utilizes integer linear programming to construct directed spanning trees for optimal network resilience to multiple link failures. By minimizing the number of trees, it significantly reduces the required fl... 详细信息

ISBN: (数字)9798350308396

ISBN: (纸本)9798350308402

关键词： Costs Network topology Process control Integer linear programming Control systems Robustness Hardware Topology Complexity theory Resilience

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Characterization of Vertical Wind Speed Profiles Based on Ward's Agglomerative Clustering Algorithm

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Journal of Modern Power Systems and Clean Energy 2023年第5期11卷 1437-1449页

作者： M.C.Bueso A.Molina-García A.P.Ramallo-González A.Fernández-Guillamón Department of Applied Mathematics and Statistics Universidad Politécnica de Cartagena30202 CartagenaSpain Department of Automatics Electrical Engineering and Electronic TechnologyUniversidad Politécnica de Cartagena30202 CartagenaSpain Department of Information and Communications Engineering Computer Science FacultyUniversity of Murcia30100 MurciaSpain Universidad de Castilla La-Mancha Campus Universitario02071 AlbaceteSpain

Wind turbine blades have been constantly increasing since wind energy becomes a popular renewable energy source to generate electricity. Therefore, the wind sector requires a more efficient and representative characterization of vertical wind speed profiles to assess the potential for a wind power plant site. This paper proposes an alternative characterization of vertical wind speed profiles based on Ward's agglomerative clustering algorithm, including both wind speed module and direction data. This approach gives a more accurate incoming wind speed variation around the rotor swept area, and subsequently, provides a more realistic and complete wind speed vector characterization for vertical profiles. Real wind database collected for 2018 in the Forschungsplattformen in Nordund Ostsee(FINO) research platform is used to assess the methodology. A preliminary pre-processing stage is proposed to select the appropriated number of heights and remove missing or incomplete data. Finally, two locations and four heights are selected, and 561588 wind data are characterized. Results and discussion are also included in this paper. The methodology can be applied to other wind database and locations to characterize vertical wind speed profiles and identify the most likely wind data vector patterns.

关键词： Clustering algorithm wind speed data management power generation

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Geofencing-based Congestion Control in Workplaces Environment using Sequential Pattern Mining 4

Geofencing-based Congestion Control in Workplaces Environmen...

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4th Novel Intelligent and Leading Emerging Sciences Conference, NILES 2022

作者： Abd El-Haleem, Ahmed M. Anany, Mohamed G. Abdelhakam, Mostafa M. Mohamed, Noor El-Deen M. Elmesalawy, Mahmoud M. Helwan University Faculty of Engineering Department of Electronics and Communications Engineering Cairo Egypt Electronics and Communications Engineering Department Cairo Egypt Helwan University Faculty of Engineering Computer and Systems Engineering Department Cairo Egypt

ISBN: (数字)9781665452410

ISBN: (纸本)9781665452410

To control congestion in the workplace environment especially in crises like the COVID-19 pandemic, this requires careful control of highly crowded workplace locations. Therefore, innovative technologies, such as geofencing and sequential pattern mining can be used to estimate people movement pattern and combat the spread of COVID-19. In this paper, the workplace area is divided into a set of geofences by using geofencing technology. Then, the movement profiles of each user are estimated to control the possible congestion in the workplace's enviroment. To accomplish this, the user's historical geofence transitions are used to anticipate the next time the user will leave the current geofence. The Sequential Pattern Discovery using Equivalence classes (CM-SPADE), Succinct BWT-based Sequence prediction model (SuBSeq) and Compact Prediction Tree + (CPT+) algorithms are adopted to predict the user's next geofence. In the CM-SPADE algorithm, a vertical database is obtained from the available database and the frequent sequence is found based on relative support, confidence, and lift measures. Meanwhile, in the training phase of the SuBSeq algorithm, Ferragina and Manzini (FM)-index and Burrows-Wheeler Transform string are generated. Then, in the ready-to-predict phase, the next geofence is anticipated. The CPT+ algorithm is based on generating Prediction Tree (PT), Lookup Table (LT), and Inverted Index (IIdx) for the training data. Then, Frequent Subsequence Compression (FSC) and Simple Branches Compression (SBC) are used to reduce the size of the PT. In addition, the Prediction with improved Noise Reduction (PNR) method is utilized to reduce the execution time. The results show remarkable superiority for SuBSeq algorithm over CM-SPADE and CPT+ with the accuracy greater than 90% withh an average of 8 input geofences to predict the next geofence. © 2022 IEEE.

关键词： COVID-19

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