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Energy Efficient joint user association and power allocation using Parameterized Deep DQN 9

Energy Efficient joint user association and power allocation...

引用

9th International Conference on computer and Communication engineering, ICCCE 2023

作者： Mughees, Amna Tahir, Mohammad Sheikh, Muhammad Aman Amphawan, Angela Yap, Kian Meng Habaebi, Mohamed Hadi Islam, Md. Rafiqul Sunway University Dept. of Computing and Information Systems Petaling Jaya Malaysia University of Turku Dept. of Computing Turku Finland Cardiff Metropolitan University Dept. of Electronics and Computer Systems Engineering Cardiff United Kingdom International Islamic University Dept. of Electrical and Computer Engineering Kuala Lumpur Malaysia

ISBN: (纸本)9798350325218

Using small cells to create an ultra-dense network for 5G and beyond is a promising strategy to improve network coverage, data demands and reduce latency. Despite using small cells, these dense wireless networks result in performance degradation and increased energy consumption. Energy consumption is a crucial parameter for sustainable future wireless networks. In order to improve quality of service (QoS) and Energy Efficiency (EE), efficient resource allocation strategies are required. This paper investigates a Parameterized Double Deep Q-Network (PDDQN) based framework for joint user association and power allocation to improve EE and throughput. Apart from other conventional machine learning approaches, considering single state space of the joint optimization problem, our proposed framework considers both discrete and continuous state spaces. Our proposed PDDQN technique also solves the generalization problem that occurs due to similar states. The simulation results indicate that the proposed work significantly improves energy EE and throughput in large-scale learning problems. © 2023 IEEE.

关键词： Energy efficiency

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USRP-Based Single Anchor Positioning: AoA with 5G Uplink Signals, and UWB Ranging 11

USRP-Based Single Anchor Positioning: AoA with 5G Uplink Sig...

引用

11th Workshop on Satellite Navigation Technology, NAVITEC 2024

作者： Spanos, Thodoris Fabra, Fran Lopez-Salcedo, Jose A. Seco-Granados, Gonzalo Kanistras, Nikos Lapin, Ivan Paliouras, Vassilis University of Patras Dept. of Electrical and Computer Engineering Greece Loctio P.C Greece Dept. of Telecommunication and Systems Eng Spain Radio Navigation Systems and Techniques Section European Space Agency Netherlands

ISBN: (纸本)9798350356854

This paper presents a novel testbed designed for 5th-Generation (5G) positioning using Universal software Radio Peripherals (USRPs). The testbed integrates multiple units: an Operation Unit for test management, a User Unit equipped with an Ettus E312 USRP, and a Station Unit featuring an Ettus N310 USRP equipped with a three-element Uniform Linear Array for Angle of Arrival estimation. Alongside ultra wide-band ranging, the testbed estimates the user's position relative to the base station. Signal processing algorithms are executed in a dedicated processing unit. Key challenges addressed include phase misalignment between RX channel pairs due to different Local Oscillators in the Ettus N310, necessitating real-time calibration for precise signal alignment. High sampling rates (up to 61.44 MSps) result in large IQ sample files, managed efficiently using a snapshot technique to optimize storage without compromising testbed positioning capabilities. The testbed synchronizes angular measurements with ranging estimates allowing consistent performance evaluation for real-life cases of dynamic users (e.g. pedestrian). Experimental results demonstrate the testbed's effectiveness in achieving accurate pedestrian user localization. © 2024 IEEE.

关键词： Testbeds

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Enhancing Cybersecurity Through Advanced Fraud and Anomaly Detection Techniques: A Systematic Review

Enhancing Cybersecurity Through Advanced Fraud and Anomaly D...

引用

2024 International Conference on Science, engineering and Business for Driving Sustainable Development Goals, SEB4SDG 2024

作者： Olowe, Oluwambo Tolulope Adebiyi, Ayodele A. Marion, Adebiyi O. Tobi, Olowe Mofiyinfoluwa Olaniyan, Deborah Olaniyan, Julius Emmanuel, Aderemi Akindeji, Kayode Landmark University Dept of Computer Science Omuaran Nigeria University of Pretoria Dept. of Industrial & Systems Engineering Pretoria South Africa Durban University of Technology Dept. of Power Electric Engineering Durban South Africa

ISBN: (纸本)9798350358155

Fraud and anomaly detection in cybersecurity have become critical areas of research, prompting a comprehensive review of recent developments and model effectiveness. This study investigates prevalent trends and challenges in fraud and anomaly detection, focusing on data science approaches within e-commerce and smart cities. Through the analysis, key factors influencing detection efficacy, such as deep learning models and hybrid approaches, are examined. Findings highlight the multidimensional nature of cyber threats across various domains and underscore the importance of proactive security measures, including robust authentication, network fortification, and employee training. This paper contributes to enhancing awareness and understanding of evolving cyber threats while offering actionable insights for bolstering detection capabilities and mitigating risks. © 2024 IEEE.

关键词： Cyber attacks

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Predictive Analysis of Jordan Road Accidents Severity Using Machine Learning

Predictive Analysis of Jordan Road Accidents Severity Using ...

引用

2023 International Symposium on Networks, computers and Communications, ISNCC 2023

作者： Mustafa, Dheya Sawaged, Layan Khabour, Safaa M. The Hashemite University Faculty of Engineering Dept. of Computer Engineering Zarqa13133 Jordan Yarmouk University Faculty of Information Technology and Computer Sciences Dept. of Information Systems Irbid21163 Jordan

ISBN: (纸本)9798350335590

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%. © 2023 IEEE.

关键词： Machine learning

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MTDC Fault Detection and Localization Using High-Pass Filter 50

MTDC Fault Detection and Localization Using High-Pass Filter

引用

50th Annual Conference of the IEEE Industrial Electronics Society, IECON 2024

作者： Khan, Saad Ahmed Ukil, Abhisek Nair, Nirmal-Kumar C. Li, Dongyu Dept. of Electrical Computer and Software Engineering The University of Auckland Auckland New Zealand School of Electrical and Automation Engineering East China Jiaotong University Nanchang330013 China

ISBN: (纸本)9781665464543

The DC link capacitor discharge in the event of a DC fault is rapid and contains high frequencies. This rapid discharge of high current and frequency interface with DC bus, Voltage Source Converter (VSC), and AC source. This interface damages the equipment and possibly living beings in proximity. Therefore, it is necessary to develop a topology to detect and identify fault types promptly, along with the isolation and restoration of the system. This study introduces an improved novel fault detection technique using the Highpass Chebyshev type 2 filter due to its flatter pass-band response. Further, the polarities of peaks obtained from the fault detection calculation are used again for another proposed novel fault location method. It identifies fault types to locate and isolate the faulty system using only polarities of amplitude response peaks. In the simulation, both methods were fast and accurate in detecting, locating, and identifying appropriate fault types only by High Pass Filter (HPF) amplitude response peaks and their polarities. © 2024 IEEE.

关键词： Chebyshev filters

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Ensuring Electronic Health Record (EHR) Privacy using Zero Knowledge Proofs (ZKP) and Secure Encryption Schemes on Blockchain 5

Ensuring Electronic Health Record (EHR) Privacy using Zero K...

引用

5th International Conference on Advancements in Computing, ICAC 2023

作者： Ranaweera, T.A.V.Y. Hewage, H.N.H. Hapuhinna, H.K.D.W.M.C.B. Preethilal, K.L.K.T. Senarathne, Amila Ruggahakotuwa, Laneesha Sri Lanka Institute of Information Technology Dept. Computer Systems Engineering Malabe Sri Lanka

ISBN: (纸本)9798350358131

In the haste of EHR digitization, the protection of patient data becomes paramount, casting a spotlight on small healthcare clinics grappling with the threats of an ever more interconnected healthcare sector. That is due to the existing centralized system and traditional password-based authentications which cause a single point of failure. Besides this patient consent for EHR sharing is narrowed to a one-time consent. To overcome these problems, this study suggests a robust solution that makes data sharing utilizing blockchain while achieving privacy using web-based Zero Knowledge Proofs (ZKP) authentication and Homomorphic Encryption (HE). The research also considers securely outsourcing EHRs to research organizations to improve data exchange for research purposes. Along with patient-controlled encryption, consent control, and time-limited data access, it also explores dynamic consent management while complying with healthcare standards. Lastly, this study stream-lines secure data sharing with insurance providers while ensuring patient privacy and defending against insurance fraud. © 2023 IEEE.

关键词： Blockchain

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Does Sri Lanka Have a Good Maritime Strategy to Stop Cyber-Terrorist Attacks 14

Does Sri Lanka Have a Good Maritime Strategy to Stop Cyber-T...

引用

14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023

作者： Samaraweera, S.A.R.P. Siriwardana, S.M.D.N. Fernando, W.D.V. Rajakarunaratne, D.N. Sri Lanka Institute of Information Technology Dept. of Computer Systems Engineering Malabe Sri Lanka

ISBN: (纸本)9798350335095

Maritime cyber-terrorist attacks have become a major concern to the entire world in recent decades. Everyone should be more aware of marine strategies to prevent cyberterrorist attacks, both locally and globally. This study investigates how Sri Lanka and the Sri Lanka Navy (SLN) may successfully address maritime security concerns by utilizing current resources and developing a marine strategy to counter such maritime cyber-terrorism assaults. The literature review in this thesis primarily evaluates the level of understanding in Sri Lanka concerning when marine cyber terrorism strikes may occur. Furthermore, this thesis investigates if Sri Lanka has any maritime rules and regulations. The use of such laws and regulations will concentrate on how they can increase their expertise. © 2023 IEEE.

关键词： Cybersecurity

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KinderEye: Kindergarten Child Performance Monitoring System 9

KinderEye: Kindergarten Child Performance Monitoring System

引用

9th International Conference on computer and Communication engineering, ICCCE 2023

作者： Rathnayaka, B. Rabel, W.T.S. Namasingha, C.N.W. Hettiarachchi, H.D. Hansika, Mahaadikara M.D.J.T. Wellalage, Sasini Nuwanthika Sri Lanka Institute of Information Technology Dept. of Computer Systems Engineering Malabe Sri Lanka

ISBN: (纸本)9798350325218

Kindergarten is the most important beginning of a child's formal education. Since the brain is rapidly developing in early childhood, a lack of brain development at kindergarten can create a weak foundation for learning, health, and behavioral problems throughout life. Digital learning and monitoring applications for young children are widely available but often lack opportunities for physical engagement, which can negatively impact executive function development. In this paper, we introduce a system for continuously monitoring mental development in terms of working memory, decision-making ability, language skills, and likelihood of having ADHD. The system consists of three physically playable games that collect performance data from digital sensors and encourage children to be involved in physical activities while increasing enthusiasm for evaluations. Continuous performance measurement allows teachers and parents to know the development of children and guide them or direct them to have suitable medical treatments. Memory development evaluation is done from the button-pressing game which allows giving inputs according to a pattern previously indicated. For decision-making ability measurement, we are using a remote controllable robot and maze in which children navigate the robot toward the winning point of the maze. Language development is measured by giving several activities through an attractive device that measures listening, speaking, reading, and writing. Furthermore, checking ADHD is done by lively tracking child behavior from a camera while playing a game and invalid game inputs. © 2023 IEEE.

关键词： Decision making

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Auto Disturbance Rejection Control Based on A Neural Network Predictive State Observer 15

Auto Disturbance Rejection Control Based on A Neural Network...

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15th International Conference on Intelligent Human-Machine systems and Cybernetics, IHMSC 2023

作者： Du, Shengzhi Van Wyk, B.J. Nahri, N.F.S. Tu, Chunling Tshwane University of Technology Dept. Electrical Engineering Pretoria South Africa Tshwane University of Technology Dept. Computer Systems Engineering Pretoria South Africa

ISBN: (纸本)9798350326178

This paper addresses the auto disturbance rejection control (ADRC) for systems with time delay. ADRC is an effective control for most linear or nonlinear systems with noises and disturbances, because of its advantage on disturbance estimation and compensation. The extended state observer (ESO) is a critical component of ADRC. However, this observer is usually designed for systems without time delay. The time delay in a system could lead the ADRC unstable when the phase delay of the response cannot be ignored. This paper proposes a neural network based predictive state observer (NNPSO) to predict the response of systems with time delay. The simulation results validate the proposed method when systems with time delay are controlled. © 2023 IEEE.

关键词： Time delay

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Deeper Anomaly Detection in Industrial Automation

Deeper Anomaly Detection in Industrial Automation

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IEEE Annual Computing and Communication Workshop and Conference (CCWC)

作者： Ho-Seok Jung Sung Won Jang Youngmi Baek Dept. of Computer Software Engineering Changshin University Korea Dept. of Computer Engineering Changshin University Korea

ISBN: (数字)9798331507695

ISBN: (纸本)9798331507701

The security of industrial networks, particularly in industrial automation systems, is critical for ensuring system reliability and protecting sensitive data. This paper proposes a deeper anomaly detection system using the ResNet34 (Residual Network) model to identify and detect cyber-attacks in industrial networks, specifically focusing on Controller Area Network (CAN) systems. The study highlights the vulnerabilities in industrial communication protocols, such as CAN, Modbus, and Ethernet/IP, which are susceptible to cyber-attacks including replay, modification, and fuzzing attacks. These attacks can disrupt the functioning of industrial systems and cause significant damage. Experimental results show that the proposed model achieves a 100 % detection rate for all types of cyber-attacks, demonstrating its effectiveness in recognizing abnormal patterns and responding to changes in network behavior. The results confirm that the ResNet34-based deep anomaly detection model can be a valuable tool for strengthening the security of industrial networks by providing real-time detection of cyber-attacks, thereby ensuring the stability and safety of industrial automation systems.

关键词： Automation Stability analysis Real-time systems Safety Controller area networks Security Reliability Cyberattack Anomaly detection Residual neural networks

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