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Selfish Users in Listen-Before-Talk Co-existence of Cellular-Wi-Fi Networks: Counteraction Methods

Selfish Users in Listen-Before-Talk Co-existence of Cellular...

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International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt)

作者： Saibharath S Sudeepta Mishra Gazal Arora Anamika Sharma Chittaranjan Hota Dept. of Computer Science and Information systems BITS Pilani Hyderabad Campus India Dept. of Computer Science and Engineering IIT Ropar Punjab India

5G operates in the unlicensed spectrum to expand its capacity. This spectrum provides more uplink and downlink frequency bands in 5G to satisfy ultra-dense and scalability requirements. Wi-Fi is a prominent wireless technology that operates in unlicensed bands. Due to the proximity of cellular and Wi-Fi channels, utilization of both Wi-Fi and 5G New Radio (NR) can cause interference. The co-existence of 5G NR and Wi-Fi devices lacks the means of communication for negotiation and coordination among them. Listen-Before-Talk and Duty-cycling are standard Medium Access control (MAC) mechanisms to enable co-existence. Due to a lack of coordination, network utilization becomes unfair with the existence of selfish devices. The selfish users could maximize throughput and affect other Wi-Fi and NR users. Here, we investigate the effects of selfish nodes on this Wi-Fi Co-existence with 5G. These nodes disobey exponential backoff to boost their channel acquisition. We study the effect of misbehavior through the Order Gain metric. Through standard CSMA/CA settings with overall channel occupancy of 99.75%, we demonstrate that selfish users profoundly impact fair co-existence. We study the side effects through throughput, channel sensing, and acquisition for various backoff window access patterns. Finally, we go through counteraction methods to overcome the selfish user impact.

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Effectiveness of computer-based e-Learning and Virtual Reality Training System for the Preparatory Phase of a Training on Maintenance Procedure

Effectiveness of Computer-based e-Learning and Virtual Reali...

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IEEE International Conference on Consumer Electronics (ICCE)

作者： Filippo Gabriele Pratticò Debora Di Cosmo Matteo Piviotti Giuseppe La Rosa Fabrizio Lamberti Dept. of Control and Computer Engineering Politecnico di Torino Turin Italy Leonardo S.p.a Turin Italy

This work investigates the effectiveness of two training systems based on consumer hardware technologies, a first one using computer-Based Learning (CBL) and the other exploiting Virtual Reality (VR). A user study was executed in order to compare the two training and analyze the most suitable approach for the learning of preparatory material in the context of an industrial assembly and maintenance (IMA) procedure. The results highlighted that, although trainees using VR experienced higher levels of cognitive processing and attention, the knowledge gain of CBL was comparable to that of VR for the preliminary phase training. Nonetheless, VR was still able to provide better learning gains in terms of procedural skills compared to CBL.

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Predictive Analysis of Jordan Road Accidents Severity Using Machine Learning

Predictive Analysis of Jordan Road Accidents Severity Using ...

引用

International Symposium on Networks, computers and Communications (ISNCC)

作者： Dheya Mustafa Layan Sawaged Safaa M. Khabour Dept. of Computer Engineering Faculty of Engineering The Hashemite University Zarqa Jordan Dept. of Information Systems Faculty of Information Technology and Computer Sciences Yarmouk University Irbid Jordan

Jordan has a high and growing level of traffic accidents reaching 160,600) accidents in 2021, (11,241) of them had human injuries, (589) deaths, and (320) million JOD losses. Road traffic accidents are currently the 8th leading cause of death worldwide, accounting for about 1.35 million fatalities annually. Understanding the primary causes of these accidents and the circumstances in which they occur is essential if governments throughout the world are to put policies in place to limit the number of fatalities brought on by traffic accidents. This project has two objectives: (i) to learn more about Jordan's present road accident situation by performing an exploratory study on several road accident datasets, and (ii) to investigate the effectiveness of various machine-learning techniques in predicting the severity of road accidents in Jordan. The dataset entities were collected, collated, explored, and prepared for use in the model. To assess their predictive performance, five different classification algorithms were trained and tested. The findings of the present study demonstrate that the best algorithm was Logistic Regression, which had an accuracy of 98.1%.

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Coordinate Attention-enabled Ship Object Detection with Electro-optical Image 11

Coordinate Attention-enabled Ship Object Detection with Elec...

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11th International Conference on Computing and Pattern Recognition, ICCPR 2022

作者： Xu, Hongbin Jiang, Xiantao Yin, Tao Cen, Qi Zhang, Zhijian Song, Tian Yu, F. Richard Dept.Information Engineering Shanghai Maritime University Shanghai China Ningbo Special Equipment Inpection and Research Institute Ningbo China Dept. Electrical and Electronics Engineering Tokushima University Tokushima Japan Dept. Systems and Computer Engineering Carleton University Ottawa Canada

ISBN: (纸本)9781450397056

Shipping safety is one of the factors restricting the development of navigation. In particular, the route near the shore is prone to unknown risks due to the existence of multiple types of ships, the density of ships, the shielding between ships, and other reasons. This paper presents a method for detecting medium-range ships, which can improve security for ships. This method is based on the You Only Look Once Version 5 network (YOLOv5). To improve the accuracy, the coordinate attention model is integrated into the detection network. The main research content and experimental work of this paper are as follows. Firstly, the YOLOv5 network and spatial attention mechanism are analyzed. Then, detection experiments were carried out based on YOLOv5 and Singapore Maritime Data Set (SMD). Then, the coordinate attention model was used to improve the network. Finally, by adjusting training parameters and improving attention, the mAP of test results of the object detection network reaches 73%, and the feasibility of object detection of the YOLOv5 algorithm with coordinate attention is confirmed. © 2022 ACM.

关键词： Object detection

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Properties of singular solutions in optimal control problems under input dynamic extension

Properties of singular solutions in optimal control problems...

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IEEE Conference on Decision and control

作者： Paolo Di Giamberardino Daniela Iacoviello Dept. of Computer Control and Management Engineering Antonio Ruberti Sapienza University of Rome via Ariosto 25 Rome Italy

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

The paper addresses the problem of optimal control design in presence of singular solutions for single input dynamics. The dynamical extension for systems obtained adding an integrator on the input is addressed and analyzed. The possibility of computing the optimal control for dynamically extended systems from the solution of the initial ones is investigated, as well as the inverse procedure. These relationships are well evidenced for the singular solutions, showing the possibility of simplifying the optimal control computation. An example is introduced to better highlight the presented results.

关键词： Optimal control Cost function

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Neuromorphic computing by means of recurrent spectrum slicing for next generation high baud rate transmission systems

Neuromorphic computing by means of recurrent spectrum slicin...

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LEOS Summer Topical Meetings

作者： Adonis Bogris Kostas Sozos George Sarantoglou Stavros Deligiannidis Charis Mesaritakis Dept. Informatics and Computer Engineering University of West Attica Athens Greece Dept. of Informatics and Computer Engineering University of West Attica Athens Greece Dept. of Information and Communication Systems Engineering University of the Aegean Karlovassi Greece

In this paper we review our recent work in photonic neural networks based on recurrent optical spectrum slicing as potential accelerators for the mitigation of transmission impairments in short reach, high symbol rate...

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Power Loss Analysis of Energy Management System with Model Predictive control in Mae Hong Son Microgrid

Power Loss Analysis of Energy Management System with Model P...

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IEEE International Conference on Power Electronics, Intelligent control and Energy systems (ICPEICES)

作者： Nattakit Prapanwattana Donlapat Dechawatanapaisal David Banjerdpongchai Abhishek Rajan Dept. of Electrical Engineering Faculty of Engineering Center of Excellence in Intelligent Control Automation for Process Systems Chulalongkorn University Bangkok Thailand Dept. of Electrical Engineering National Institute of Technology Sikkim South Sikkim India

ISBN: (数字)9798350387193

ISBN: (纸本)9798350387209

Energy management system (EMS) is an important tool for energy efficiency and reliability of the power system. The optimal power dispatch of energy resources can be obtained using the nonlinear model predictive control (NMPC). It is formulated as an optimization problem subject to linear and nonlinear constraints. Although the existing system works well under the current conditions, power loss has not been considered. Power loss in transmission lines occurs due to their resistance and a high amount of power flow to loads connecting to the system. The power loss leads to decreased efficiency in the electrical system and reduces the lifespan of equipment because of the high temperature from loss. This paper aims to analyze the power loss in the Mae Hong Son (MHS) microgrid. To achieve the research objectives, we employ the EMS of MHS with NMPC and calculate power loss in transmission lines for a period of 7 days. EMS considers three objective functions, namely, total operating cost, total carbon dioxide emission, and combined economic and emission dispatch and take into account of three seasons consisting of rainy, winter, and summer.

关键词： Resistance Power transmission lines Microgrids Propagation losses Power system reliability Reliability Energy management systems Power generation Load flow Predictive control

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Blockchain Integration for Robust Intellectual Property Protection in New Product Development (NPD) 3

Blockchain Integration for Robust Intellectual Property Prot...

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3rd International Conference on Electronics and Renewable systems, ICEARS 2025

作者： Chinnasamy, P. Subashini, B. Nijanthan, Nijanthan Madasamy Raja, G. Swetha, Devulapally Sreenivasulu Reddy, L. School of Computing Kalasalingam Academy of Research and Education Department of Computer Science and Engineering Tamilnadu India School of Computing Srmist Department of Data Science and Business Systems Kattankulathur India Paavai Engineering College Tamilnadu Namakkal India Paavai Engineering College Tamilnadu Namakkal India Vaagdevi Engineering College Dept. of Computer Science and Engineering Warangal Dist. Telangana Bolli Kunta506005 India School of Advanced Sciences Kalasalingam Academy of Research and Education Department of Mathematics Tamilnadu Krishnankoil India

ISBN: (纸本)9798331509675

The rapid advancement of Blockchain technology has led to its widespread application in several domains of digital activities, such as e-government concerns and monetary security. This article presents a smart contract-based Blockchain solution for protecting intellectual property rights in new product development. The proposed solution effectively tackles the challenges associated with the confidentiality of personally identifiable information, efficiency in storing transaction-related information, as well as cooperation and monitoring in IPR. Initially, we create a mathematical model based on smart contract enabled Blockchain and intelligent contracts. Subsequently, we develop algorithms for Blockchain generation, and intelligent contracts. The system is suitable for protecting IPR in a blockchain network, by implementation of distributed identity authentication and real-time extensible storage. These features enhance the security and expandability of circuit copyright protection based on blockchain technology. The experimental results demonstrate that the suggested algorithm has decreased the cost for communication and enhanced the effectiveness of storing information and administration. Furthermore, it demonstrates resilience against many common attacks such as double-spending assaults, while maintaining low cost and overhead. Additionally, it exhibits a superior level of security in comparison to three other competing algorithms. © 2025 IEEE.

关键词： Smart contract

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Surrogate-Assisted Multi-Class Collaborative Teaching and Learning Optimizer for High-Dimensional Industrial Optimization Problems

Surrogate-Assisted Multi-Class Collaborative Teaching and Le...

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2024 IEEE International Conference on systems, Man, and Cybernetics, SMC 2024

作者： Bi, Jing Wang, Ziqi Yuan, Haitao Yang, Jinhong Zhang, Jia College of Computer Beijing University of Technology Beijing100124 China Beijing University of Technology Beijing Laboratory of Smart Environmental Protection Beijing100124 China School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Cssc Systems Engineering Research Institute Beijing China Lyle School of Engineering Southern Methodist University Dept. of Computer Science DallasTX United States

ISBN: (纸本)9781665410205

Swarm intelligence and evolutionary algorithms are widely applied in industrial scheduling, mobile edge computing, etc due to their strong robustness and fast optimization speed. However, some real-world industrial optimization problems involve numerous decision variables, known as high-dimensional problems. Current algorithms often require considerable computational resources to evaluate objective function values because of high-dimensional decision spaces. Moreover, they are also prone to be trapped in local optima. To solve the above problems, this work proposes an improved algorithm named Surrogate-assisted Multi-class Collaborative Teaching and learning optimizer (SMCT). A multi-class collaborative teaching and learning optimizer is proposed as a base optimizer to improve exploration and exploitation abilities. Furthermore, an autoencoder-assisted radial basis function is proposed as the surrogate model to replace true function evaluations, thereby saving computational resources and balancing the complexity and accuracy in fitting true models. Finally, experimental results demonstrate that SMCT surpasses its existing peers in both search accuracy and convergence speed across eight high-dimensional benchmark functions. © 2024 IEEE.

关键词： Scheduling algorithms

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FedStar Caching: Decision Center Assisted Federated Cooperative Edge Caching

FedStar Caching: Decision Center Assisted Federated Cooperat...

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IEEE International Conference on Human-Machine systems

作者： Sirvan Gharib Mohammad Mansour Kesargheh S. Jamal Seyedmohammadi Zohreh Hajiakhondi Jamshid Abouei Konstantinos N. Plataniotis Dept. of Electrical Engineering Yazd University Yazd Iran Inst. of Information Systems Engineering Concordia University Montreal Canada Dept. of Electrical Engineering Concordia University Montreal Canada Dept. of Electrical and Computer Engineering University of Toronto Toronto Canada

ISBN: (数字)9798350315790

ISBN: (纸本)9798350315806

With the explosion of data, Wireless Edge Caching (WEC) has become a promising approach for locally accessing cached contents. Due to the limited storage capacity of local caching devices and the varying preferences of humans for content, it is necessary to predict popular contents. In this article, we will address two distinct objectives: 1) Popularity prediction of the content that should be cached at the edge to effectively utilize edge device memory. 2) Edge devices collaboration for efficient content delivery. Accordingly, we propose an FL-based Star Cooperative Caching (FedStar Caching), utilizing a Star network topology for realizing an efficient cooperation among Femto-cell Access Points (FAPs) using a Decision Center (DC) to enhance power efficiency and delay performance. Considering human sensitivity to privacy, collecting users’ data on a central server is not desirable, therefore, we leverage Federated Learning (FL) to alleviate this challenge. Simulation results demonstrate that the proposed method outperforms alternatives in terms of cache efficiency, as well as delay and power consumption.

关键词： Wireless communication Wireless sensor networks Power demand Network topology Cooperative caching Simulation Stars

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