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International Conference on Mechatronics (ICOM)

作者： Mamoon M. Saeed Rashid A. Saeed Elmustafa Sayed Ali Rania A. Mokhtar Othman O. Khalifa Department of Communications and Electronics Engineering Faculty of Engineering University of Modern Sciences (UMS) Yemen Department of Computer Engineering College of Computers and Information Technology Taif University Taif Saudi Arabia Department of Electrical & Electronic Engineering Faculty of Engineering Red Sea University PortSudan Sudan Department of Electronics Engineering Faculty of Engineering Sudan University of Science and Technology Khartoum Sudan Dept of Elec and Comp Eng Inter. Islamic Uni. Malaysia KL Malaysia Libyan Center for Engineering Research and Info. Tech. Bani Walid Libya

ISBN: (数字)9798350349788

ISBN: (纸本)9798350349795

The emergence of the sixth generation (6G) wireless networks brings new challenges and opportunities for efficient computing offloading and resource allocation. This paper proposes a novel Deep Reinforcement Learning-based Computing Offloading and Resource Allocation (DRL-CORA) algorithm for 6G networks. The algorithm leverages the power of deep reinforcement learning to dynamically determine the optimal computing offloading decisions and resource allocation strategies. The Deep Reinforcement Learning-based DCORA algorithm for computation offloading and resource allocation is effective, as demonstrated by our simulations. When compared directly, the suggested DCORA algorithm performs 15% better than other baseline systems.

关键词： 6G mobile communication Energy consumption Mechatronics Heuristic algorithms Wireless networks Quality of service Deep reinforcement learning

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Evaluation of Response Time for Linked Data applications using CoAP and HTTP 2

Evaluation of Response Time for Linked Data applications usi...

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2nd IEEE International Conference on Computational Intelligence and Knowledge Economy, ICCIKE 2021

作者： Akre, Vishwesh Shahzad, Muhammad Nawaz, Asif Parkash, Om Ul Rehman, Anis Ali Khattak, Hasan Khan, Doulat Ahmed, Sheeraz Mohindru, Pankaj Higher Colleges of Technology Dubai Women's College Dubai United Arab Emirates Mns University of Engg. Tech. Deptt. of Elec. Engg. and Tech. Multan Pakistan Higher College of Technology Department of Electrical Engineering Dubai United Arab Emirates Comsats University Department of Computer Science Islamabad Pakistan Islamabad Pakistan Capital University of Science Technology Department of Computer Science Islamabad Pakistan Iqra National University Department of Computer Science Peshawar Pakistan Punjabi University Electronics Communications Engineering Patiala India

ISBN: (纸本)9781665429214

In internet of things we deal with real life objects so we use Constrained Application Protocol (CoAP) instead of the conventional HTTP (in web). Current Research in the WOT (Web of Things) generally takes things in broader sense of physical objects into consideration. Usually these considered things can be (but not necessarily) tagged objects (RFID, Barcodes, Image Recognition, NFC, QR codes) to Wireless Sensor Networks (WSN), vehicles and consuming electronics. This project aims to compare response time of the sensors (sensing temperature of CPU) if the request is to be launched from different type of resources from desktop, android or raspberry pi. © 2021 IEEE.

关键词： HTTP

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Double Deep RL-Based Strategy for UAV-Assisted Energy Harvesting Optimization in Disaster-Resilient IoT Networks

Double Deep RL-Based Strategy for UAV-Assisted Energy Harves...

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International Conference on Mechatronics (ICOM)

作者： Nahla Nur Elmadina Rashid A. Saeed Elsadig Saeid Elmustafa Sayed Ali Ibtehal Nafea Mayada A. Ahmed Rania A. Mokhtar Othman O. Khalifa Department of Electrical Engineering Alzaiem Alazhari University Khartoum Sudan Electronics Department Sudan University of Science and Technology Khartoum Sudan College of Computer Science and Engineering Taibah University Medina Saudi Arabia Faculty of Eng. School of ElecsEng. Sudan Uni. of Sci. and Tech. Khartoum Sudan Dept of Elec and Comp Eng Inter. Islamic Uni. Malaysia KL Malaysia Libyan Center for Engineering Research and Information Technology Bani Walid Libya

ISBN: (数字)9798350349788

ISBN: (纸本)9798350349795

Unmanned Aerial Vehicles (UAVs) are increasingly crucial for emergency-response scenarios, including tasks like wireless power transfer (WPT) and data collection in disaster zones. This paper proposes a Double Deep Reinforcement Learning (DDRL) framework for energy harvesting (EH) in such scenarios. Our framework involves a UAV swarm navigating an area to provide WPT. The primary goal is to enhance service quality in critical areas while enabling dynamic swarm management for tasks like recharging. We formulate this as a nonlinear programming (NLP) optimization problem, maximizing EH from IoT devices and optimizing UAV trajectories under constraints like mission duration and energy limits. Due to the problem's complexity, we propose a lightweight DDRL solution capable of efficiently learning system dynamics. Extensive simulations and comparisons with Deep RL and DDPG algorithms demonstrate the superior performance of DDRL in enhancing EH, covering strategic locations effectively, and achieving high satisfaction and accuracy rates.

关键词： Wireless power transfer Programming Autonomous aerial vehicles Nonlinear dynamical systems Trajectory Internet of Things Energy harvesting

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Robust Charging Solutions for 400V EV Batteries: Implementing a Quasi Single-Stage Current-Fed Resonant Converter

Robust Charging Solutions for 400V EV Batteries: Implementin...

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IEEE Texas Power and Energy Conference (TPEC)

作者： Muhammad Furqan Waqar Uddin Kamran Zeb Muhammad Ashar Ayaz Irfan Khan Muhammad Khalid School of Electrical Engineering and Computer Science (SEECS) National University of Science and Technology (NUST) Islamabad Pakistan Interdisciplinary Research Center for Sustainable Energy Systems (IRC-SES) King Fahd University of Petroleum and Minerals (KFUPM) Dhahran Saudi Arabia IRC-SES KFUPM Dhahran Saudi Arabia Dept. of Electrical and Computer Engneering Texas A and M University College Station TX USA Dept. of Elec. and Comp. Engineering Texas A and M University College Station TX USA Electrical Engineering Department KFUPM and IRC-SES KFUPM Dhahran Saudi Arabia

ISBN: (数字)9798331541125

ISBN: (纸本)9798331541132

This work presents a high-performance AC-DC quasi single-stage current-fed resonant converter based electric vehicles (EVs) charger. A non-linear control technique is applied which has two main objectives i.e; Power factor correction (PFC) and regulation of DC output voltage. For this purpose, super twisting sliding mode control (ST-SMC) is suggested in this study for 400V batteries of EVs. To reduce switching losses and improve efficiency, the secondary side switch shows turn OFF with zero voltage switching (ZVS) while the primary ones exhibit ZVS at turn ON instant. Hardware-in-loop (HIL) experimental validation based on the Delfino F28369D dual-core microcontroller is used to verify the performance of the controller and converter simulated on PSIM and MATLAB/Simulink.

关键词： Microcontrollers Switching loss Switches Resonant converters Zero voltage switching Regulation Batteries Safety Voltage control Sliding mode control

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Parameter Estimation of Multiple Poles by Subspace-Based Method

Parameter Estimation of Multiple Poles by Subspace-Based Met...

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International Conference on Control, Decision and Information Technologies (CoDIT)

作者： Prabhu Vijayan Philippe Dreesen Ivan Markovsky Mariya Ishteva Department of Computer Science ADVISE-NUMA KU Leuven Geel Belgium Department ELEC Vrije Universiteit Brussel Brussel Belgium Department of Advanced Computing Sciences Maastricht University Maastricht The Netherlands Gran Capità International Centre for Numerical Methods in Engineering (CIMNE) Barcelona Spain Catalan Institution for Research and Advanced Studies (ICREA) Barcelona Spain

This work deals with the problem of estimating the parameters (i.e., pole multiplicity structure, pole locations, and complex amplitudes) of exponential polynomials for a given model order. We start from an exponential polynomial signal model and algebraically demonstrate the reasoning behind and the manner in which this model generalizes to the broader class of signals containing multiple poles. The poles and complex amplitudes are estimated by a subspace-based method. With the given model order as prior, a heuristic algorithm is developed to estimate the multiplicity structure of poles. Numerical simulations are conducted to study the performance of the subspace-based method and the sensitivity of poles and multiplicity estimation. Our simulations show that our pole estimation method is accurate for signals with poles of multiplicity greater than one, particularly for signals with lower orders. This allows for successful signal regeneration, producing estimates that closely match the original data. The estimation is sensitive, particularly in the presence of noise, and when the poles are complex and have a higher order of multiplicity.

关键词：

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Voltage profile enhancement and harmonic reduction in power system network using fuzzy logic controller

Voltage profile enhancement and harmonic reduction in power ...

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2024 IEEE International Conference on Communication, Computing and Signal Processing, IICCCS 2024

作者： Garg, Raghav Joshi, Navneet Gondekar, Rajshree K. Joshi, Tripuresh Varshney, Niharika Das, Kailash Chandra Tula's Institute Deptt. of Computer Science & Engg. U.K. Dehradun India Graphic Era Hill University Department of Mathematics 263132 India G.H. Raisoni University Deptt. of Elec. & Telecom. Engg. Maharashtra Amravati444701 India Tula's Institute Deptt. of Electronics & Comm. Engg. U.K. Dehradun India Graphic Era Deemed to be University Deptt. of Electrical Engg. Dehradun India G H Raisoni University School of Engineering and Technology Maharashtra Amravati444701 India

ISBN: (纸本)9798350390759

This article investigates the condition of power in the power system network. High voltage profiles and elevated harmonics are the primary concerns associated with conventional power system networks. Total harmonic distortion is the metric used to quantify harmonics. The IEEE 14 bus system has been selected as the standard power system network. The IEEE 14 bus system has experienced unbalanced operation as a consequence of the 10% capacity increase on all buses. STATCOM was constructed to resolve these concerns, and its switching was managed by a fuzzy logic controller (FLC). In comparison to STATCOM without FLC, the voltage profile and THD (%) have been substantially enhanced when using the STATCOM-based FLC. © 2024 IEEE.

关键词： Static Var compensators

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Demagnetization analysis and magnet design of permanent magnet synchronous motor for electric power steering applications 1

Demagnetization analysis and magnet design of permanent magn...

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1st IEEE China International Youth Conference on electrical engineering, CIYCEE 2020

作者： Huang, Weihua Wang, Jin Zhao, Junchen Zhou, Libing Zhang, Zhiwei Huazhong University of Science and Technology State Key Laboratory of Advanced Elec-tromagnetic Engineering and Technology School of Electrical and Electronic Engineering Wuhan430074 China The Ohio State University Department of Electrical and Computer Engineering ColumbusOH43210 United States

ISBN: (纸本)9781728196596

The demagnetization analysis method of permanent magnet synchronous motor (PMSM) used in electric power steering (EPS) system is studied, and the size of permanent magnet (PM) is optimized considering demagnetization performance and manufacturing cost in this paper. PMSM has the advantages of high torque density and high efficiency, which is suitable for EPS system. However, the PMs may demagnetize at a high temperature or by a larger reverse magnetic field, which will affect the torque characteristics or output power of the motor, eventually resulting in the failure to drive the load and also reducing the reliability of the EPS system. In order to deal with these problems, it is necessary to consider demagnetization in the analysis stage. In addition, EPS systems are sensitive to cost since PM material is expensive, so it is necessary to restrain irreversible demagnetization under the condition of minimizing the volume of PM. A demagnetization analysis method based on 2D and 3D finite element analysis (FEA) for PMSM in EPS systems is proposed and the size of PM is mainly designed. Based on the computation of the distribution of magnetic flux density on the surface of PM, the demagnetization risk is evaluated. The simulation and experiment results clearly show that the proposed PMSM design can meet the requirements of EPS system. © 2020 IEEE.

关键词： Finite element method

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Facial Expression Recognition using Hand-Crafted Features and Supervised Feature Encoding 2

Facial Expression Recognition using Hand-Crafted Features an...

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2nd International Conference on electrical, Communication and computer engineering, ICECCE 2020

作者： Noor, Jumana Daud, Muneeba Rashid, Raima Mir, Hira Nazir, Saima Velastin, Sergio A. Fatima Jinnah Women University Department of Software Engineering Rawalpindi Pakistan School of Elec. Eng. and Computer Science Queen Mary University of London and Zebra Technologies Corp. London United Kingdom

ISBN: (纸本)9781728171166

Facial Expression Recognition (FER) is an emerging field of research because of the latest advancement in the computing field making the user's experience a clear priority. The proposed framework focuses on facial expression recognition using state-of-the-art hand-crafted feature extraction algorithms. First, pre-processing of images is applied to reduce noise and faces are then extracted using Viola Jones algorithm. Then, salient features are extracted from the region of interest using different feature extraction methods. We compare the performance of methods such as Speed-Up Robust Features (SURF), Features from Accelerated Segment Test (FAST), Histogram of Oriented Gradients (HOG) and Harris Corner Detection. The high-dimensional extracted features are quantized using supervised k-mean clustering. Finally, the proposed method is evaluated on the publicly available CK+ dataset and the model suggested achieves 90.79 per cent predictive accuracy. Angry, disgust, fear, happy, sadness, surprise, contempt are the seven different emotions to be recognized in CK+ dataset. © 2020 IEEE.

关键词： Feature extraction

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UNCERTAINTY AWARE MULTITASK PYRAMID VISION TRANSFORMER FOR UAV-BASED OBJECT RE-IDENTIFICATION

arXiv

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arXiv 2022年

作者： Ferdous, Syeda Nyma Li, Xin Lyu, Siwei West Virginia University Lane Dept. of Comp. Sci. and Elec. Engr. MorgantownWV26506-6109 United States State University of New York at Buffalo Department of Computer Science and Engineering 317 Davis Hall BuffaloNY14260 United States

Object Re-IDentification (ReID), one of the most significant problems in biometrics and surveillance systems, has been extensively studied by image processing and computer vision communities in the past decades. Learning a robust and discriminative feature representation is a crucial challenge for object ReID. The problem is even more challenging in ReID based on Unmanned Aerial Vehicle (UAV) as the images are characterized by continuously varying camera parameters (e.g., view angle, altitude, etc.) of a flying drone. To address this challenge, multiscale feature representation has been considered to characterize images captured from UAV flying at different altitudes. In this work, we propose a multitask learning approach, which employs a new multiscale architecture without convolution, Pyramid Vision Transformer (PVT), as the backbone for UAV-based object ReID. By uncertainty modeling of intraclass variations, our proposed model can be jointly optimized using both uncertainty-aware object ID and camera ID information. Experimental results are reported on PRAI and VRAI, two ReID data sets from aerial surveillance, to verify the effectiveness of our proposed approach. © 2022, CC BY.

关键词： Cameras

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Physical-Layer Semantic-Aware Network for Zero-Shot Wireless Sensing

arXiv

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arXiv 2023年

作者： Zhu, Huixiang Xiao, Yong Li, Yingyu Shi, Guangming Saad, Walid School of Elect. Inform. & Commun. Huazhong Univ. of Science & Technology China Peng Cheng Laboratory Shenzhen China Guangzhou China School of Mech. Eng. and Elec. Info. China University of Geosciences Wuhan China School of Artificial Intelligence Xidian University Xi’an China Bradley Department of Electrical and Computer Engineering Virginia Tech VA United States

Device-free wireless sensing has recently attracted significant interest due to its potential to support a wide range of immersive human-machine interactive applications. However, data heterogeneity in wireless signals and data privacy regulation of distributed sensing have been considered as the major challenges that hinder the wide applications of wireless sensing in large area networking systems. Motivated by the observation that signals recorded by wireless receivers are closely related to a set of physical-layer semantic features, in this paper we propose a novel zero-shot wireless sensing solution that allows models constructed in one or a limited number of locations to be directly transferred to other locations without any labeled data. We develop a novel physical-layer semantic-aware network (pSAN) framework to characterize the correlation between physical-layer semantic features and the sensing data distributions across different receivers. We then propose a pSAN-based zero-shot learning solution in which each receiver can obtain a location-specific gesture recognition model by directly aggregating the already constructed models of other receivers. We theoretically prove that models obtained by our proposed solution can approach the optimal model without requiring any local model training. Experimental results once again verify that the accuracy of models derived by our proposed solution matches that of the models trained by the real labeled data based on supervised learning approach. Copyright © 2023, The Authors. All rights reserved.

关键词： Semantics

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