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7th International Conference on Environment Friendly Energies and Applications, EFEA 2022

作者： Anuraj, U. Hameed, S.H.I. Arunprakash, N. Sajeeva, J. Thanihaichelvan, T. Kokulavasan, T. Rajan, R. Yuvaraj, M. Thananjeyan, S. Ahilan, K. Atputharajah, A. Yaalini, B. Kiriparan, B. University of Jaffna Faculty of Engineering Department of Mechanical Engineering Kilinochchi Sri Lanka University of Jaffna Department of Electrical and Electronic Engineering Kilinochchi Sri Lanka University of Jaffna Faculty of Engineering Department of Computer Engineering Kilinochchi Sri Lanka University of Jaffna Faculty of Engineering Department of Civil Engineering Kilinochchi Sri Lanka

ISBN: (纸本)9798350333213

Even though research papers discussed increasing fossil fuel costs, it is proven in today's scenario. Therefore, it is confirmed that Renewable Energy (RE) technologies will take a primary role in generating electricity in this era. This has created real operational challenges for the grid operators. With technology transfer and new technology development, capacity building is potentially focused on through grants. The power system was preferred to have large inertia for its smooth operations. With the latest technologies and speedy responses, the modernized systems could create inertia by properly and instantly coordinating and controlling many small plants. Further, accurate prediction algorithms release stress by giving advanced information about the system. It is a new direction of modernized control, and it always starts with a small design. It then integrates with an extensive system through a supervisory control loop. These incorporated technologies are opening several new opportunities for RE-based technologies. The research on micro-grid was initiated about two decades ago. It has been developed parallel with the possible development of RE technologies and prediction algorithms. The recent hike in fossil fuel costs pushes the micro-grid-based RE power generation to the front. Accordingly, this paper presents the coordinated control of a few RE power plants, using a micro-grid concept while integrating the micro-grid with the primary grid through the supervisory control concept. The proposed idea is simulated using the EMTDC/PSCAD, and it shows an excellent result. Furthermore, it will become more attractive over expensive fossil fuel systems in this era. © 2022 IEEE.

关键词： Fossil fuels

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Accelerating Point-Voxel Representation of 3-D Object Detection for Automatic Driving

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第1期5卷 254-266页

作者： Cao, JieCheng Tao, Chongben Zhang, Zufeng Gao, Zhen Luo, Xizhao Zheng, Sifa Zhu, Yuan Suzhou University of Science and Technology School of Electronic and Information Engineering Suzhou215009 China Tsinghua University Suzhou Automobile Research Institute Suzhou215134 China College of Mechanical Engineering Tongji University Shanghai200092 China Tsinghua University Department of Automation Beijing100084 China Wuhan Electronic Information Institute Wuhan430019 China McMaster University Faculty of Engineering HamiltonONL8S 0A Canada Soochow University School of Computer Science and Technology Suzhou215009 China Tongji University College of Automotive Studies Shanghai200092 China

Current point-voxel fusion methods for 3-D object detection could not make full use of complementary information in the field of autonomous driving. Therefore, a novel two-stage 3-D object detection method, called accelerating point-voxel representation (APVR), is proposed. The advantages of point-based feature and voxel-based feature can be integrated into a single 3-D representation. Thereby, the proposed method retains more fine-grained information of an object while maintaining high efficiency. Specifically, the computational cost is reduced by adding offsets to query neighboring voxels of key-points. More fine-grained information can be obtained by calculating the matching probability between neighboring voxels and key-points. During the optimization of the prediction boxes, virtual grid points are set to capture the spatial information between key-points. The constraint of minimum enclosing rectangle is also added to optimize the directions of the prediction boxes. A large number of experiments on the KITTI, NuScenes, and Waymo datasets demonstrate great generalizability and portability of the proposed approach. The effectiveness and efficiency of APVR have been proved by comparisons with the state-of-the-art methods. APVR makes the real-time processing frame rate reach 40.4 Hz while ensuring high prediction accuracy. © 2020 IEEE.

关键词： Computational efficiency

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Performance Comparison of dSPACE and MCU MPC Implementation in PV Power Optimizer

Performance Comparison of dSPACE and MCU MPC Implementation ...

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2023 IEEE Energy Conversion Congress and Exposition, ECCE 2023

作者： Metry, Morcos Guler, Naki Rohouma, Wesam Balog, Robert S. Texas A&m University Department of Electrical and Computer Engineering Doha Qatar Gazi University Department of Electrical-Electronic Engineering Technology Faculty Ankara Turkey University of Doha for Science and Technology Department of Electrical Engineering Doha Qatar Texas A&m University Department of Electrical and Computer Engineering College StationTX United States

ISBN: (纸本)9798350316445

Finite control set model predictive control (MPC) can be computationally intensive especially when scaled up for more complicated converters since each state variable in the system is evaluated for all possible switching configurations. Multi-objective optimization of the cost function adds to the complexity of MPC. Much of the MPC literature in power electronics relies on expensive rapid prototyping (RP) platforms (RPP) such as dSPACE and OPAL RT. This paper aims to bridge the gap between expensive RPP and low-cost MCUs by exploring the feasibility of rapid prototyping (RP) on the low-cost F28379D launchpad. This paper is aimed toward the practitioner or researcher who desires to reduce to practice the MPC methods developed on a RPP to a lower-cost embedded controller. The suitability of a low-cost Texas Instrument (TI) launchpad to perform the same rapid-prototyping functions needed for MPC regulator development in a full-featured, high-end RPP is discussed. Experimental results using the dSPACE 1006 and the F28379D Launchpad showing steady-state performance and dynamic response are illustrated and compared. Comparative results show the F28379D launchpad and dSPACE 1006 offer similar performance markers. © 2023 IEEE.

关键词： Low-cost controller Model Predictive Control Power electronics rapid prototyping platforms

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Recent Progress οf Tapered Optical Fiber for Biosensing Applications

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Journal of engineering Science and Technology Review 2022年第5期15卷 204-209页

作者： Anbalagan, Thanigai Haroon, Hazura Zain, Huda Adnan Rafis, Hazli Harun, S.W. Center for Telecommunication Research and Innovation Faculty of Electronic and Computer Engineering Universiti Teknikal Malaysia Melaka Hang Tuah Jaya Durian Tunggal Melaka76100 Malaysia Department of Electrical Engineering University of Malaya Kuala Lumpur50603 Malaysia

The development of reliable, lightweight, and effective sensors is a vital step in effectively monitoring critical parameter changes. This review focuses on the utilization of tapered optical fiber as a material sensing platform. The fundamental concept of the tapered fiber sensor is based on the interaction of strong evanescent waves caused by the fiber's dimensional change. The primary goal of this review is to explore the potential of tapered optical fiber for biosensing applications. A number of tapered optical fiber configurations and operations have been reviewed in order to propose appropriate optical sensor designs for biosensing applications. Hence, this analysis could serve as a benchmark for a more thorough study of biosensing device development. © 2022 School of Science, IHU. All rights reserved.

关键词： Biosensors

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The Serbian Retrieval Augmented Generation System based on Hybrid Search

The Serbian Retrieval Augmented Generation System based on H...

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Automatics and Informatics (ICAI), International Conference

作者： Aleksandar Cenić Martin Jovanović Suzana Stojković Computer Science Department Faculty of Electronic Engineering University of Niš Niš Serbia

ISBN: (数字)9798350353907

ISBN: (纸本)9798350353914

This paper presents a hybrid search based retrieval-augmented generation (RAG) system in the domain of history, in Serbian language. The system was implemented in Python programming language, and is based on Google BERT embedding model, OpenSearch hybrid search, OpenAI GPT 3.5 large language model, and two original Serbian datasets for augmentation and system evaluation. The system performance was evaluated using ROGUE-1, cosine similarity and human evaluation, and its performance was compared to the purely semantic search based version. The system performance was satisfactory in human measurement, but estimated as low in automated metrics. In both metrics the hybrid search showed significantly better performance.

关键词： Measurement Accuracy Translation System performance Retrieval augmented generation Hybrid power systems Question answering (information retrieval) Data models Vectors History

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Generating Network Intrusion Image through IGTD Algorithm for CNN Classification 3

Generating Network Intrusion Image through IGTD Algorithm fo...

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3rd International Conference on Computing and Information Technology, ICCIT 2023

作者： Nazarri, Muhammad Nur Aman Ahmad Yusof, Mohammad Hafiz Mohd Almohammedi, Akram A. Universiti Teknologi Mara UiTM Faculty of Computer and Mathematical Sciences Tapah Malaysia Karabük University Electrical and Electronic Engineering Karabük78050 Turkey

ISBN: (纸本)9798350321487

Stealthy attacks make Intrusion Detection System (IDS) research perennial and notably important. From the literature, a few problems were identified in IDS studies particularly with regards to image generation. Image generation is the preprocessing phase during the development of CNN classifier. Simple feature extraction process that are applied in a few studies may lose features' details. They disregard spatial information such as pair pixels information. Secondly several public datasets suffer from realistic network traits. This study will apply the improvised version of IGTD algorithm to resolve image generation process. IGTD algorithm has been adopted in Cancer Cell Lines (CCLs) study. Realistic dataset of CIRA-CIC-DoHBrw-2020 and CICIDS2017 will be run over the algorithm. These dataset have been reviewed to be the closest realistic production network dataset. Result shows the generated image has notable difference between attack and benign traffic. The highest trained classification model has achieved almost 80% of accuracy rate. © 2023 IEEE.

关键词： Classification (of information)

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An Agent Based Travel Assistant for the Dutch Railway Network 37

An Agent Based Travel Assistant for the Dutch Railway Networ...

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37th International Conference on Information Technologies, InfoTech 2023

作者： Rothkrantz, Leon Beelen, Martijn Delft University of Technology Faculty of Electronic Engineering Mathematics and Computer Science Mekelweg 4 CD Delft2628 Netherlands Czech Technical University in Prague Faculty of Transportation Sciences Czech Republic

ISBN: (纸本)9798350338058

For many years the Dutch NS Railway Company runs all trains in the Netherlands. It can be expected that next year different transport companies will exploit the Dutch railway network. Possible that they will use different systems to design timetables, generate travel plans and to handle delays. In this paper we research the coordination between different systems. A prototype of distributed systems in different areas has been developed using agent technology. The system has been tested in simulation studies. © 2023 IEEE.

关键词： Intelligent agents

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2D-DOA for a Monostatic ULA EMVS-MIMO Radar Based on RC-PARAFAC

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IEEE Sensors Journal 2025年第12期25卷 21763-21774页

作者： Wang, Jianlong Shi, Junpeng Wen, Fangqing China Three Gorges University Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hvdroelectric Engineering College of Computer and Information Technology Yichang443002 China National University of Defense Technology College of Electronic Countermeasure Hefei230037 China City University of Macau College of Computer and Information Technology China Three Gorges University Faculty of Data Science 999078 China

The electromagnetic vector sensor (EMVS) embedded multiple-input multiple-output (MIMO) radar is an emerging technology capable of two-dimensional (2D) direction of arrival (DOA) estimation. In this paper, we propose a low-complexity algorithm for monostatic uniform linear array (ULA) EMVS-MIMO radar to rapidly estimate 2D-DOA. First, we decompose the received signal into a third-order tensor using parallel factor analysis (PARAFAC). Next, we eliminate data redundancy through a reduced complexity (RC) process. Then, we use the least squares method to extract ambiguous elevation angle information from the spatial response matrix and apply the vector cross-product (VCP) technique to the electromagnetic vector to achieve unambiguous 2D-DOA estimation. Finally, we combine these estimates to achieve high-resolution, unambiguous elevation angle estimation. The proposed algorithm is suitable for large-scale and sparse EMVS-MIMO radar systems. © 2001-2012 IEEE.

关键词： Direction of arrival

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Enhanced Coyote Optimization with Deep Learning Based Cloud-Intrusion Detection System

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computers, Materials & Continua 2023年第2期74卷 4319-4336页

作者： Abdullah M.Basahel Mohammad Yamin Sulafah M.Basahel E.Laxmi Lydia Faculty of Economics and Administration King Abdulaziz UniversityJeddahSaudi Arabia E-commerce Department College of Administrative and Financial SciencesSaudi Electronic UniversityJeddahSaudi Arabia Department of Computer Science and Engineering Vignan’s Institute of Information TechnologyVisakhapatnam530049India

Cloud Computing(CC)is the preference of all information technology(IT)organizations as it offers pay-per-use based and flexible services to its *** the privacy and security become the main hindrances in its achievement due to distributed and open architecture that is prone to *** Detection System(IDS)refers to one of the commonly utilized system for detecting attacks on *** proves to be an effective and promising technique,that identifies malicious activities and known threats by observing traffic data in computers,and warnings are given when such threatswere *** current mainstream IDS are assisted with machine learning(ML)but have issues of low detection rates and demanded wide feature *** article devises an Enhanced Coyote Optimization with Deep Learning based Intrusion Detection System for Cloud Security(ECODL-IDSCS)*** ECODL-IDSCS model initially addresses the class imbalance data problem by the use of Adaptive Synthetic(ADASYN)*** detecting and classification of intrusions,long short term memory(LSTM)model is *** addition,ECO algorithm is derived to optimally fine tune the hyperparameters related to the LSTM model to enhance its detection efficiency in the cloud *** the presented ECODL-IDSCS model is tested on benchmark dataset,the experimental results show the promising performance of the ECODL-IDSCS model over the existing IDS models.

关键词： Intrusion detection system cloud security coyote optimization algorithm class imbalance data deep learning

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Optimizing Resource Allocation in Mobile Edge Computing for IIoT through Reinforcement Learning and Multiobjective Particle Swarm Optimization 2

Optimizing Resource Allocation in Mobile Edge Computing for ...

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2nd IEEE International Conference on Integrated Circuits and Communication Systems, ICICACS 2024

作者： Avv, Sudhakar Mohan, M. Maharajan, K. Habelalmateen, Mohammed I. Naga Saranya, N. SR University Department of Electrical and Electronics Engineering Telangana India Nitte Meenakshi Institute of Technology Department of ISE Bengaluru India School of Computing Kalasalingam Academy of Research and Education Department of Computer Science and Engineering Krishnankoil Bangalore India Universiti Tun Hussein Onn Malaysia Parit Raja Faculty of Electrical and Electronic Engineering Johor Batu Pahat Malaysia College of Technical Engineering the Islamic University Department of Computer Technical Engineering Najaf Iraq Saveetha College of Liberal Arts and Science SIMATS Department of Computer Applications Chennai India

ISBN: (纸本)9798350317558

Mobile networks are flexible enough to support a range of resource allocation models and service-based choices in computing domains, which affects both virtual reality and the Industrial Internet of Things (IIOT). Virtual resource management is made easier by the Mobile Edge Computing (MEC) paradigm, which also makes edge connectivity between data terminals and execution in the core network under heavy load possible. Meeting customer requirements efficiently is achieved through thoughtful planning, aided by cognitive agents. User data, incorporating behavioral patterns, is amalgamated to cater to IIOT service types. Neural caching for memory during task execution is made easier by the use of swarm intelligence and reinforcement learning techniques. Prediction strategies optimize business operations and caching to reduce execution delays. Predictive models evaluate performance by taking into account variables like nearby user equipment and mobile edge computing resources. This method's efficacy is demonstrated by a cognitive agent model that manages resource distribution and creates networks of communication to improve service quality. For accurate resource distribution among end users, reinforcement learning techniques - more especially, Multi-Objective Particle Swarm Optimization (MOPSO) algorithms - are used. This includes building cost mapping tables and optimizing allocation in MEC. The proposed method outperforms existing algorithms like Task-Offloading and Resource Allocation Strategy and achieves a better throughput value of 785.32. © 2024 IEEE.

关键词： Communication Industrial Internet of Things Mobile Edge Computing Optimization Quality of Service Reinforcement Learning

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