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作者： Habib, Sami J. Marimuthu, Paulvanna N. Renold, Pravin Ganesh Athi, Balaji Computer Engineering Department Kuwait University Kuwait City Kuwait Electronic System Design Laboratory Velammal Engineering College Chennai India

We have developed an expert system comprising a self-aware framework for resource-efficient and accurate data transmission within a low-power lossy sensor network (LLN) deployed for indoor monitoring. We derived both individual and group awareness, which could ensure the awareness of each sensor regarding its resources, neighbours and network environment. The proposed expert system facilitates decision-making under dynamic environmental conditions and employs a multi-criteria decision-making (MCDM) model to determine the selection of the best path towards the sink node with awareness of the existing network environment. The proposed system is validated by constructing a 6LoWPAN network in the Contiki Cooja simulator. MCDM is applied to generate an adaptive objective function for the IPv6 routing protocol for the LLN (RPL) and to aid in ranking the nodes to select the best available neighbouring node, while the data accuracy is ensured by the cluster head through data correlation among its associated members. The network performance is assessed by analyzing the packet delivery rate, throughput and energy consumption against varying sensors and by comparing our proposed MCDM-RPL with a standard RPL and a fuzzy-based RPL, where the results show that our framework is found to be better with gains of 13, 25 and 13%, respectively. © 2020 John Wiley & Sons Ltd

关键词： Routing protocols

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Analytical Survey on the Security Framework of Cyber-Physical systems for Smart Power system Networks

Analytical Survey on the Security Framework of Cyber-Physica...

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2022 International Conference on Cyber Resilience, ICCR 2022

作者： Ali Al-Jumaili, Ahmed Hadi Muniyandi, Ravie Chandren Hasan, Mohammad Kamrul Singh, Mandeep Jit Siaw Paw, Johnny Koh Universiti Kebangsaan Malaysia Faculty of Information Science and Technology Bangi43600 Malaysia University of Fallujah Computer Centre Department Anbar00964 Iraq Universiti Kebangsaan Malaysia Faculty of Engineering and Built Environment Department of Electrical Electronic and System Engineering Selango Bangi43600 Malaysia Universiti Tenaga Nasional Department of Electronic and Communication Engineering Selango Kajang Malaysia

ISBN: (纸本)9781665461221

Cyber-Physical Power system (CPPS) is one of the most critical infrastructure systems due to deep integration between power grids and communication networks. In the power system, cascading failure is spreading more readily in CPPS, even leading to blackouts as well as there are new difficulties with the power system security simulation and faults brought by physical harm or network intrusions. The current study summarized the cross- integration of several fields such as computer and cyberspace security in terms of the robustness of Cyber-Physical systems, viewed as Interconnected and secure network systems. Therefore, the security events that significantly influenced the power system were evaluated in this study, besides the challenges and future directions of power system security simulation technologies were investigated for posing both challenges and opportunities for simulation techniques of power system security like building a new power system to accelerate the transformation of the existing energy system to a clean, low-carbon, safe, and efficient energy system which is used to assure power system stability through fusion systems that combine the cyber-physical to integrate the battery power station, power generation and renewable energy resources through the internet with the cyber system that contains Smart energy system control and attacks. © 2022 IEEE.

关键词： Cyber Physical system

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Investigation of Traffic Radar Coverage Efficiency under Different Placement Strategies

Investigation of Traffic Radar Coverage Efficiency under Dif...

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International Conference on Internet of Things 2024, ICIoT 2024

作者： Yao, Shun Zhou, Jin Chieng, David Kwong, Chiew Foong Lee, Boon Giin Li, Jianqiang Chen, Yusen Next-Generation Internet of Everything Laboratory Department of Electrical and Electronic Engineering University of Nottingham Ningbo China Ningbo China School of Computer Science University of Nottingham Ningbo China Ningbo China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Shenzhen China Zhejiang Communication Investment Group Co. Ltd. Zhejiang China

This paper presents a comprehensive investigation of traffic radar coverage efficiency under different placement strategies in collaboration with Zhejiang Communications Investment Group Company Limited (CICO). The overall goal is to maximise coverage while minimising blind spots and the number of radars, given the constraints of the road. The NSGA-II multi-objective optimisation algorithm is found to be capable of generating a set of optimal solutions for the proposed radar placement configurations. When aiming for 100% coverage, the results indicate that a multi-antenna radar configuration requires the lowest radar density. Overall, this study provides valuable insights to transportation infrastructure owners in determining the best radar placement strategies for road traffic monitoring. © The Institution of engineering & Technology 2024.

关键词： Multiobjective optimization

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AI-aided power electronic converters automatic online real-time efficiency optimization method

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Fundamental Research 2025年第3期5卷 1111-1116页

作者： Tang, Yuanhong Cao, Di Xiao, Jian Jiang, Chenying Huang, Qi Li, Yunwei Chen, Zhe Blaabjerg, Frede Hu, Weihao Power System Wide-area Measurement and Control Sichuan Provincial Key Laboratory School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Chengdu 611731 China MORNSUN Guangzhou Science & Technology Co. Ltd. Guangzhou 510663 China School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu 611731 China Yangtze Delta Region Institute (Quzhou) University of Electronic Science and Technology of China Quzhou 324000 China Department of Chengdu State Grid Corporation of China Chengdu 610599 China Southwest University of Science and Technology Mianyang 621010 China Department of Electrical and Computer Engineering University of Alberta Edmonton AB T6G 2V4 Canada Department of Energy Technology Aalborg University Aalborg 9220 Denmark

Energy losses during the conversion and supply of electric power are considered a significant issue and cannot be estimated. Improvement in the efficiency of energy conversion systems is highly restricted because of their internal nonlinearity and complexity. Thus, inspired by the successful utilization of robotic chemists, we demonstrate a pioneering concept of artificial intelligence (AI)-aided automatic online real-time optimization of a power electronics converter using a dual active bridge (DAB) converter as an example. An optimal modulation strategy was obtained through repeated automatic exploration experiments on a practical DAB converter platform. Specifically, the DAB experimental platform operated autonomously around the clock for approximately 71 h. It performed 120,000 consecutive experiments (12,000 episodes) within a six-variable experimental space driven by a deep deterministic policy gradient (DDPG) algorithm. The proposed AI-aided automatic online real-time optimization method achieved significantly improved efficiency of power conversion and supply. Consequently, zero carbon emissions may be obtained in the future. © 2023

关键词： Artificial intelligence Automatic online real-time exploration DC-DC converter Dual active bridge converter Energy conversion system Power electronics

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Range-Agnostic Multi-View Depth Estimation with Keyframe Selection

Range-Agnostic Multi-View Depth Estimation with Keyframe Sel...

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International Conference on 3D Imaging, Modeling, Processing, Visualization and Transmission (3DIMPVT)

作者： Andrea Conti Matteo Poggi Valerio Cambareri Stefano Mattoccia Department of Computer Science and Engineering University of Bologna Italy Advanced Research Center on Electronic System (ARCES) Brussels Belgium Sony Depthsensing Solutions University of Bologna Italy

ISBN: (数字)9798350362459

ISBN: (纸本)9798350362466

Methods for 3D reconstruction from posed frames require prior knowledge about the scene metric range, usually to recover matching cues along the epipolar lines and narrow the search range. However, such prior might not be directly available or estimated inaccurately in real scenarios – e.g., outdoor 3D reconstruction from video sequences – therefore heavily hampering performance. In this paper, we focus on multi-view depth estimation without requiring prior knowledge about the metric range of the scene by proposing RAMDepth, an efficient and purely 2D framework that reverses the depth estimation and matching steps order. Moreover, we demonstrate the capability of our framework to provide rich insights about the quality of the views used for prediction. Additional material can be found on our project page.

关键词： Measurement Three-dimensional displays Correlation Video sequences Memory management Estimation Cameras

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Optimizing the Deployment of an Aerial Base Station and the Phase-Shift of a Ground Reconfigurable Intelligent Surface for Wireless Communication systems Using Deep Reinforcement Learning

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Information (Switzerland) 2024年第7期15卷 386页

作者： Kabore, Wendenda Nathanael Juang, Rong-Terng Lin, Hsin-Piao Tesfaw, Belayneh Abebe Tarekegn, Getaneh Berie Department of Electronic Engineering National Taipei University of Technology Taipei10608 Taiwan Institute of Aerospace and System Engineering National Taipei University of Technology Taipei10608 Taiwan Department of Electrical Engineering and Computer Science National Taipei University of Technology Taipei10608 Taiwan Department of Electrical and Computer Engineering National Yang-Ming Chiao Tung University Hsinchu30010 Taiwan

In wireless networks, drone base stations (DBSs) offer significant benefits in terms of Quality of Service (QoS) improvement due to their line-of-sight (LoS) transmission capabilities and adaptability. However, LoS links can suffer degradation in complex propagation environments, especially in urban areas with dense structures like buildings. As a promising technology to enhance the wireless communication networks, reconfigurable intelligent surfaces (RIS) have emerged in various Internet of Things (IoT) applications by adjusting the amplitude and phase of reflected signals, thereby improving signal strength and network efficiency. This study aims to propose a novel approach to enhance communication coverage and throughput for mobile ground users by intelligently leveraging signal reflection from DBSs using ground-based RIS. We employ Deep Reinforcement Learning (DRL) to optimize both the DBS location and RIS phase-shifts. Numerical results demonstrate significant improvements in system performance, including communication quality and network throughput, validating the effectiveness of the proposed approach. © 2024 by the authors.

关键词： Base stations

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Smart Happy Device with IoT : For those who suffer anxiety, stress, and depression 12

Smart Happy Device with IoT : For those who suffer anxiety, ...

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12th IEEE Region 10 Humanitarian Technology Conference, R10-HTC 2024

作者： Yakub, Fitri Azizan, Azizul Dhamanti, Inge Khudzari, Ahmad Zahran Md. Govindan, Niranjana Muljono, Muljono UTM Malaysia-Japan International Institute of Technology Electronic System Engineering Department Kuala Lumpur Malaysia Universiti Teknologi Malaysia Cyberphysical Research Group Embedded AI & ML Science Lab Faculty of Artificial Intelligence Kuala Lumpur Malaysia Universitas Airlangga Faculty of Public Health Department of Health Policy and Administration Surabaya Indonesia UTM Faculty of Engineering Department of Biosciences & Medical Engineering Johor Bahru Malaysia SRMIST Faculty of Engineering & Technology Department of Computing Technologies Chennai India Universitas Dian Nuswantoro Faculty of Computer Science Semarang Indonesia

ISBN: (纸本)9798350340204

Due to the rising cases of Covid-19 in the world especially in Malaysia, the impact had been hit hard for many people. Due to this all people must be isolated in their home. It has affected the well-being and working life of millions of people across the world. Due to this disease, the mental health among people has increased significantly for the past 2 years. According to MoH, out of 983 Malaysian students, about 20.4%, 6.6%, and 2.8% are experienced minimal to moderate, marked to severe, and most extreme levels of anxiety, respectively. The main stressors are the remote online teaching, and uncertainty about the future regarding study and career which can affect mental health. Thus, the main objective of this project is to develop a product that may provide different medication methods to its users by helping people who suffer anxiety, stress, and depression. We used aromatherapy, positive quotes, and music therapy in order to release stress. The user can also check his or her pulse rate by only touching the fingerprint through the sensor. The microcontrollers used in this project are Arduino Uno and Arduino Mega to build the project circuit. The experimental results can improve body health, mind and spirit which enhances both physical and emotional health. © 2024 IEEE.

关键词： COVID-19

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Warped-Compaction: Maximizing GPU Register File Bandwidth Utilization via Operand Compaction

Warped-Compaction: Maximizing GPU Register File Bandwidth Ut...

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IEEE Symposium on High-Performance computer Architecture

作者： Eunbi Jeong Ipoom Jeong Myung Kuk Yoon Nam Sung Kim Department of Computer Science and Engineering Ewha Womans University Seoul Korea Department of System Semiconductor Engineering Yonsei University Seoul Korea Department of Electrical and Electronic Engineering Yonsei University Seoul Korea University of Illinois Urbana-Champaign Urbana U.S.A

ISBN: (数字)9798331506476

ISBN: (纸本)9798331506483

The GPU has been successfully used for diverse emerging compute-intensive applications, including imaging, computer vision, and more recently, deep learning, to name a few. To offer high performance for such applications, it is provisioned with massive Register Files (RFs) to exploit high Thread-Level Parallelism (TLP). As RFs are designed to store thousands of contexts and provide very high bandwidth for uninterrupted supply of operands to hundreds of compute units for high TLP, they have become one of the most power-hungry components in the GPU. Meanwhile, faced with the end of Dennard scaling, it is more important than ever to innovate the microarchitecture of (power-constrained) GPUs to continuously improve the performance of future compute-intensive *** this work, we propose a GPU microarchitecture, WarpedCompaction, designed to utilize given RFs more efficiently, instead of relying on larger-capacity and/or higher-bandwidth RFs to further improve GPU performance. Specifically, first, we reverse-engineer the latest GPU’s RF organization through microbenchmarking. This uncovers that each sub-core within a streaming multiprocessor contains only two dual-ported RF banks, and accesses to these banks are arbitrated solely based on register IDs. We also reveal that, despite the modest configurations, RF banks are largely underutilized, staying inactive for 33.5% of the time. Second, we observe that previously proposed RF optimization techniques, data forwarding and dead register elimination, cannot address this underutilization problem. This is mainly due to the (R1) insufficient RF access requests from a limited number of Operand Collector Units (OCUs) and (R2) inefficient operand distribution by the conventional RF bank arbitration. Third, we present two architectural solutions to tackle the observed inefficiency: (S1) OCU sharing and (S2) skewed arbitrator. Building on enhanced OCU early allocation for partially ready instructions and operand forwardin

关键词： Radio frequency Microarchitecture Graphics processing units Bandwidth Organizations Parallel processing Hardware Energy efficiency Registers Resource management

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Numerical Analysis of Bi-fluid PV/T Hybrid Collector Using the Finite Difference Method 6th

Numerical Analysis of Bi-fluid PV/T Hybrid Collector Using t...

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6th International Conference on Wireless Technologies, Embedded and Intelligent systems, WITS 2020

作者： El Manssouri, Oussama Hajji, Bekkay Gagliano, Antonio Tina, Giuseppe Marco Renewable Energy Embedded System and Data Processing Laboratory National School of Applied Sciences Mohamed First University Oujda Morocco DIEEI: Department of Electric Electronic and Computer Engineering University of Catania Catania Italy

ISBN: (纸本)9789813368927

The PV/T is called as a hybrid bi-fluid type solar collector when both fluids (water and air) are used as working fluids. This type of collector provide a wide range of thermal applications and several modes can be executed depending on energy needs and applications: air mode, water mode and simultaneous mode (air and water). This paper presents a numerical analysis of PV/T bi-fluid collector using the finite difference method. Energy balance equations were established for each layer and solved using the Gauss–Seidel iteration method. The performance of the PV/T hybrid is evaluated according to the operating mode of the fluid (independently and simultaneously). The simulation results are compared with literature (Modeling and performances assessments of PV/T bifluid hybrid collector: Three cooling modes operation case. https://***/10.1109/iceit48248.2020.9113233, [10]), and indicate that when both fluids are used simultaneously, the overall electrical and thermal performance of the hybrid collector is considered satisfactory compared to the situation where two fluids operate independently. © 2022, Springer Nature Singapore Pte Ltd.

关键词： Finite difference method

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Derivative-Free Data-Driven Control of Continuous-Time Linear Time-Invariant systems

arXiv

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arXiv 2024年

作者： Bosso, Alessandro Borghesi, Marco Iannelli, Andrea Notarstefano, Giuseppe Teel, Andrew R. Department of Electrical Electronic and Information Engineering University of Bologna Italy Institute for System Theory and Automatic Control University of Stuttgart Germany Department of Electrical and Computer Engineering University of California Santa BarbaraCA United States

This paper develops a data-driven stabilization method for continuous-time linear time-invariant systems with theoretical guarantees and no need for signal derivatives. The framework, based on linear matrix inequalities (LMIs), is illustrated in the state-feedback and single-input single-output output-feedback scenarios. Similar to discrete-time approaches, we rely solely on input and state/output measurements. To avoid differentiation, we employ low-pass filters of the available signals that, rather than approximating the derivatives, reconstruct a non-minimal realization of the plant. With access to the filter states and their derivatives, we can solve LMIs derived from sample batches of the available signals to compute a dynamic controller that stabilizes the plant. The effectiveness of the framework is showcased through numerical examples. © 2024, CC BY.

关键词： Continuous time systems

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