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22nd International Symposium on Power Electronics, Ee 2023

作者： Brandis, Andrej Knol, Kristian Pelin, Denis Topic, Danijel Computer Science and Information Technology Osijek Faculty of Electricity Engineering Department of Electromechanical Engineering Osijek Croatia Computer Science and Information Technology Osijek Faculty of Electrical Engineering Department of Power Engineering Osijek Croatia

ISBN: (纸本)9798350343175

In this paper, a brief overview of converter topologies used in stationary battery energy storage systems is given. A simulation model of converter was developed in MATLAB Simulink. A simulation is conducted to provide a preliminary understanding of the converter's bidirectional nature. The results indicate that the state of charge (SOC) increases during battery charging and decreases during discharging. The topology of non-isolated two-stage bidirectional converter is presented for proposed real-world prototype, including the high-level electrical schematic and mechanical layout. An 18-kW prototype converter for stationary battery energy storage systems was developed and presented. The converter housing with all installed ancillary components for proper operation is also described. At the time of writing this paper, the actual converter is still in the development phase. © 2023 IEEE.

关键词： Charging (batteries)

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Hybrid Optimisation with Black Hole Algorithm for Improving Network Lifespan

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Intelligent Automation & Soft Computing 2023年第2期35卷 1873-1887页

作者： S.Siamala Devi Chandrakala Kuruba Yunyoung Nam Mohamed Abouhawwash Department of Computer Science and Engineering Sri Krishna College of TechnologyCoimbatore641042India Department of Computer Science and Engineering Vignan Nirula Institute of Technology and ScienceGuntur522009India Department of Computer Science and Engineering Soonchunhyang UniversityAsan31538Korea Department of Mathematics Faculty of ScienceMansoura UniversityMansoura35516Egypt Department of Computational Mathematics Scienceand Engineering(CMSE)Michigan State UniversityEast LansingMI48824USA

Wireless sensor networks(WSNs)are projected to have a wide range of applications in the *** fundamental problem with WSN is that it has aﬁnite *** a network is a common strategy for increasing the life-time of WSNs and,as a result,allowing for faster data *** cluster-ing algorithm’s goal is to select the best cluster head(CH).In the existing system,Hybrid grey wolf sunﬂower optimization algorithm(HGWSFO)and optimal clus-ter head selection method is *** does not provide better competence and out-put in the ***,the proposed Hybrid Grey Wolf Ant Colony Optimisation(HGWACO)algorithm is used for reducing the energy utilization and enhances the lifespan of the *** hole method is used for selecting the cluster heads(CHs).The ant colony optimization(ACO)technique is used toﬁnd the route among origin CH and *** open cache of nodes,trans-mission power,and proximity are used to improve the CH *** grey wolf optimisation(GWO)technique is the most recent and well-known optimiser module which deals with grey wolves’hunting activity(GWs).These GWs have the ability to track down and encircle *** GWO method was inspired by this hunting *** proposed HGWACO improves the duration of the net-work,minimizes the power consumption,also it works with the large-scale *** HGWACO method achieves 25.64%of residual energy,25.64%of alive nodes,40.65%of dead nodes also it enhances the lifetime of the network.

关键词： Energy efﬁciency power consumption lifespan of the network black hole method ant colony optimisation routing and cluster heads(CHs)

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Monitoring energy losses of a residential building through thermographic assessments 17

Monitoring energy losses of a residential building through t...

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17th International Conference on Development and Application Systems, DAS 2024

作者： Eugen, Iavorschi Laurențiu, Milici Dan Faculty of Electrical Engineering and Computer Science Department of Electrical Engineering "Stefan cel Mare" University of Suceava Suceava Romania

ISBN: (纸本)9798350349290

One of the significant opportunities for reducing energy waste and carbon emissions is the renovation, modernization, and rehabilitation of existing buildings. Replacing the windows of existing residential buildings with new energy-efficient ones is an easy way to upgrade an existing home into a nearly zero-energy building, NZEB (nearly zero-energy building). There is a wide variety of methods to discover the thermal weak points of a building, and the continuous innovation of construction materials provides solutions to maximize energy savings and minimize heat transfer to the exterior. This document presents a methodology for visualizing and recording the temperature distribution on the investigated surface of the building envelope to identify and locate vulnerable points where heat losses to the exterior are substantial. The objective was to highlight the need for upgrading the insulation system and replacing the existing windows of the analyzed building based on a multi-objective approach to maximize the building's energy performance and increase thermal comfort indoors. Using a Fluke Ti300+ Thermal Camera, energy losses were visualized through thermographic assessments, which could provide an adequate picture for accurately assessing the building's condition before renovation, to evaluate the need for partial renovation. For the case study, a residential building with one floor and mansard roof located in a region with hot summers and cold winters in Romania was chosen. The results showed that there are several options for significantly reducing the building's energy consumption. Thus, multiple energy efficiency solutions were proposed for the building to reduce heat losses. ©2024 IEEE.

关键词： Heat transfer

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A survey of artificial intelligence models for wireless capsule endoscopy videos for superior automatic diagnosis: problems and solutions

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Multimedia Tools and Applications 2025年 1-35页

作者： El-Gammal, Eman M. El-Shafai, Walid Taha, Taha E. El-Fishawy, Adel S. Abd El-Samie, Fathi E. Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt Center of Advanced Software and Biomedical Clinical Engineering Consultations Faculty of Engineering Cairo University Giza Egypt Computer Science Department Prince Sultan University Riyadh11586 Saudi Arabia Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University 84428 Riyadh11671 Saudi Arabia

Wireless Capsule Endoscopy (WCE) emerged as an innovative and patient-centric approach for non-invasive and painless examination of the gastrointestinal (GI) tract. It serves as a pivotal tool in helping medical practitioners in the early detection of anomalies within the intricate domain of the human GI tract. The automated identification of aberrations assumes paramount significance, contributing not only to temporal efficiency but also to timely diagnosis. Within the realm of academic literature, a plethora of Artificial Intelligence (AI) methodologies have been proposed to effectuate the automatic classification, segmentation, and synthesis of anomalies inherent in WCE images. This scholarly endeavor undertakes a comprehensive and meticulous survey, elucidating the spectrum of anomaly classification, summarization, and detection techniques harnessed for computer-Aided Diagnosis (CAD) in the context of WCE images. The survey begins by delineating the methodologies underpinning WCE image classification and video processing. Subsequently, an exhaustive evaluation of techniques for analyzing WCE images is furnished, accompanied by an in-depth exploration of pertinent surveys, in addition to a judicious assessment of their merits and demerits. Furthermore, this study undertakes a rigorous evaluation of prevailing datasets utilized to benchmark the efficacy of various WCE techniques. In summary, this survey serves as a vanguard, delineating promising avenues for future investigations in the realm of WCE image analysis models. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2025.

关键词： Endoscopy

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Evolutionary Optimization Methods for High-Dimensional Expensive Problems:A Survey

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IEEE/CAA Journal of Automatica Sinica 2024年第5期11卷 1092-1105页

作者： MengChu Zhou Meiji Cui Dian Xu Shuwei Zhu Ziyan Zhao Abdullah Abusorrah Department of Electrical and Computer Engineering New Jersey Institute of TechnologyNewarkNJ 07102 USA School of Information and Electronic Engineering Zhejiang Gongshang UniversityHangzhou 310018China School of Intelligent Manufacturing Nanjing University of Science and TechnologyNanjing 210094China Institute of Systems Engineering Macao University of Science and TechnologyMacao 999078China School of Artificial Intelligence and Computer Jiangnan UniversityWuxi 214122China School of Information Science and Engineering Northeastern UniversityShenyang 110819China Center of Research Excellence in Renewable Energy and Power Systems Department of Electrical and Computer EngineeringFaculty of EngineeringKing Abdulaziz UniversityJeddah 21589Saudi Arabia K.A.CARE Energy Research and Innovation Center King Abdulaziz UniversityJeddah 21589Saudi Arabia

Evolutionary computation is a rapidly evolving field and the related algorithms have been successfully used to solve various real-world optimization *** past decade has also witnessed their fast progress to solve a class of challenging optimization problems called high-dimensional expensive problems(HEPs).The evaluation of their objective fitness requires expensive resource due to their use of time-consuming physical experiments or computer ***,it is hard to traverse the huge search space within reasonable resource as problem dimension *** evolutionary algorithms(EAs)tend to fail to solve HEPs competently because they need to conduct many such expensive evaluations before achieving satisfactory *** reduce such evaluations,many novel surrogate-assisted algorithms emerge to cope with HEPs in recent *** there lacks a thorough review of the state of the art in this specific and important *** paper provides a comprehensive survey of these evolutionary algorithms for *** start with a brief introduction to the research status and the basic concepts of ***,we present surrogate-assisted evolutionary algorithms for HEPs from four main *** also give comparative results of some representative algorithms and application ***,we indicate open challenges and several promising directions to advance the progress in evolutionary optimization algorithms for HEPs.

关键词： computer optimization evolutionary

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Paillier Cryptography Based Message Authentication Code for IoMT Security

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computer Systems science & engineering 2023年第3期44卷 2209-2223页

Health care visualization through Internet of Things(IoT)over wireless sensor network(WSN)becomes a current research attention due to medical sensor evolution of *** digital technology-based communication system is widely used in all *** of medical thing(IoMT)assisted health-care application ensures the continuous health monitoring of a patient and provides the early awareness of the one who is suffered without human *** smart medical devices may consume with limited resources and also the data generated by these devices are large in *** IoMT based applications suffer from the issues such as security,anonymity,privacy,and *** overcome these issues,data aggregation methods are the solution that can concatenate the data generated by the sensors and forward it into the base station through fog node with efficient encryption and *** article proposed a well-organized data aggregation and secured transmission *** data generated by the sensor are collected and *** nodes(AN)received the compressed data and concatenate *** concatenated and encrypted data is forward to fog node using the enhanced Paillier cryptogra-phy-based encryption with Message Authentication code(MAC).Fog node extracts the forwarded data from AN using Fog message extractor method(FME)with *** proposed system ensures data integrity,security and also protects from security *** proposed model is simulated in Net-work Simulator 2.35 and the evaluated simulation results proves that the aggregation with MAC code will ensures the security,privacy and also reduces the communication *** node usages in between Aggregator and base station,will reduce the cloud server/base station computational overhead and storage *** proposed ideology is compared with existing data aggregation schemes in terms of computational cost,storage cost,communication cost and energy *** of communica

关键词： Fog IoMT wireless sensor network cloud aggregation encryption decryption energy

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A Deep Learning Approach for Lunar Impact Crater Detection Based on YOLO v7 and CBAM Attention Mechanism 8

A Deep Learning Approach for Lunar Impact Crater Detection B...

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8th International Conference on Intelligent Computing and Signal Processing, ICSP 2023

作者： Zhu, Jionghao Liang, Jiarui Tian, Xiaolin Yan, Pengcheng Macau University of Science and Technology School of Computer Science and Engineering Faculty of Innovation Engineering Macau China

ISBN: (纸本)9798350302455

Impact craters are the most common geomorphic unit on the lunar surface, and there are a large number of impact craters of different sizes and morphologies on the lunar surface. Lunar impact craters are a key basis for lunar geological studies, and their study allows for the exploration of the Moon and other planets. Therefore, this paper builds a convolutional neural network YOLO V7-CBAM based on YOLO V7 and the attention mechanism for identifying lunar impact craters. Based on the full-moon CCD images and DEM images provided by NASA, a comparison test was conducted and the precision of YOLO V7-CBAM based on both images was higher than that of YOLO V7, from 72.31% to 74.65% based on CCD images;and from 70.60% to 71.70% based on DEM images. © 2023 IEEE.

关键词： Object detection

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Eulerian-DL Forecasting of Wind Turbulence for Wind Turbines: Enabling Smart Sustainable Energy 10

Eulerian-DL Forecasting of Wind Turbulence for Wind Turbines...

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10th International Conference on engineering and Emerging Technologies, ICEET 2024

作者： Hassanian, Reza Riedel, Morris University of Iceland The Faculty of Industrial Engineering Mechanical Engineering and Computer Science Reykjavik Iceland Juelich Supercomputing Centre Germany

ISBN: (纸本)9798331532895

Currently, wind power is the fastest-growing sus-tainable energy resource, and accurately predicting wind velocity for individual turbines is essential. Wind behavior is turbulent, with variable patterns, characteristics, and unpredictable extreme events. Moreover, the wind reaching each turbine is impacted by wake loss effects from surrounding turbines, which underscores the need for a precise local prediction model for each turbine to enhance accuracy in smart wind power production. This study proposes a novel approach using local measurements at fixed points, adopting the Eulerian perspective in fluid dynamics to forecast wind turbulence for the coming hour using a deep learning model. A long short-term memory (LSTM) forecasting model is tuned and applied. Laboratory data from wind tunnel tests are utilized to account for velocity fluctuations and wake loss effects, aiming to establish similarity to an affected single wind turbine. Model training and inference run on the high-performance computing (HPC) DEEP-DAM systems at the Julich Supercomputing Centre. Three train-test datasets are employed to evaluate the model. The measured metrics indicate that the mean absolute error is 0.048, the root mean square error is approximately 0.065, and the Pinball loss for the 90th percentile is 0.0042. The model demonstrates a robust predictive capability, supporting the development of advanced instruments for individ-ual turbines and facilitating smart, clean, and sustainable energy production. © 2024 IEEE.

关键词： Wakes

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A Transformation Matrix Explains the Sequential Forecasting Data-Driven Deep Learning Model

A Transformation Matrix Explains the Sequential Forecasting ...

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2024 International Conference on computer and Applications, ICCA 2024

作者： Hassanian, Reza Helgadóttir, Ásdís Riedel, Morris University of Iceland The Faculty of Industrial Engineering Mechanical Engineering and Computer Science Reykjavik Iceland Juelich Supercomputing Centre Germany

ISBN: (纸本)9798350367560

Deep learning (DL) data-driven models (DDMs) offer significant potential for predicting nonlinear events, particularly in the absence of an analytical or known mathematical foundation. This study provides the first empirical evidence of a transformation matrix derived from a data-driven DL model for the sequential prediction of physical properties, where both the input and output are single-variable time series. The matrix's performance is tested on two different datasets to evaluate its effectiveness, demonstrating substantial proficiency in prediction modeling. The mathematical approach is explained, and the results are presented. Different portions of the training sets (60% and 80%) are examined, showing significant prediction accuracy. Furthermore, the DDM DL transformation matrix is square, has eigenvalues, and is able to reveal the correlations, stability, and limits of the system in which the model is used. This approach has the potential to provide explainable insights into data-driven DL models. © 2024 IEEE.

关键词： Prediction models

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A Comprehensive Review for Optimizing the Design of Cluster Head Selection to Enhance the Network Lifetime in WSN

A Comprehensive Review for Optimizing the Design of Cluster ...

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2022 OPJU International Technology Conference on Emerging Technologies for Sustainable Development, OTCON 2022

作者： Bhuvaneswari, S. Abirami, A. Suvetha Sri, R.P. Srinithy, R. Swathi, R. Easwari Engineering College Faculty of Dept. of Computer Science and Engineering Chennai India

ISBN: (纸本)9781665492942

Large numbers of cooperative sensor nodes make up wireless sensor networks (WSNs). Sensors are the integral component in WSN IoT. Sensors separate and organize in the clusters by similar characteristics. A cluster head is in charge of gathering information from the nodes in every cluster and transmitting it to its base station (BS). Because every node are powered by batteries, lessens energy usage and elongating lifetime of network are crucial concerns for WSN. The primary goals of this analysis are to address issues that previous writers have not addressed and to provide beginning researchers with a fundamental understanding of how to choose cluster head (CH) based on various methodologies. To designate a node as CH, some enhancing parameters are chosen, such as residual energy, packet transmission rate, throughput, distance between BS and Cluster Node (CN), and betweenness centrality. Data packets are transferred using the optimized protocol to reduce delay time and increase transmission rate after many CH are chosen. Analysis of the many literatures was done. An Optimization Algorithm is needed to enhance network lifetime from this analysis. A comparison of various algorithm based on the features and difficulties from the analysis is done. There are many drawbacks, such as a cluster head is chosen at random, data transmission rate is not considered, no proper formation of clusters, importance for load and temperature is not given, stability is not taken into account. Thus, there is a need for optimized algorithm to overcome all the mentioned issues. © 2023 IEEE.

关键词： Packet networks

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