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检索条件"机构=Electrical and Computer Engineering Program. Computer"

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COMPARATIVE PERFORMANCE OF MACHINE LEARNING MODELS FOR TEMPERATURE PREDICTION IN VANADIUM REDOX FLOW BATTERIES

COMPARATIVE PERFORMANCE OF MACHINE LEARNING MODELS FOR TEMPE...

引用

International Conference on Green Energy, Computing and Intelligent Technology 2024, GEn-CITy 2024

作者： Zhang, Anxiu Juwono, Filbert H. Li, Hongfei Purwanto, Erick Wong, W.K. Liu, Linfeng Telecommunications Engineering Program Xi'an Jiaotong-Liverpool University Suzhou China Department of Electrical and Electronic Engineering Xi'an Jiaotong-Liverpool University Suzhou China Applied Mathematics Program Xi'an Jiaotong-Liverpool University Suzhou China Department of Computing Xi'an Jiaotong-Liverpool University Suzhou China Department of Electrical and Computer Engineering Curtin University Malaysia Miri Malaysia Sustainable Energy Technology Program Xi'an Jiaotong-Liverpool University Suzhou China

ISBN: (纸本)9781837242689

Vanadium Redox Flow Batteries (VRFB) are promising for large-scale energy storage due to their long life and environmental benefits. Accurate temperature prediction is key to optimizing VRFB performance and longevity. This study compares the performance of four machine learning models, i.e., 1D CNN, Particle Swarm Optimization - Support Vector Regressor (PSO-SVR), Decision Tree (DT), and K-Nearest Neighbors (KNN), using a publicly available dataset. Results show that KNN achieves the best results with test Root Mean Square Error (RMSE) of 0.0424 (average) and test R2 of 0.9746 (average), demonstrating strong predictive accuracy. 1D CNN, however, shows poor generalization. These findings suggest that non-parametric models like KNN and DT are highly effective for VRFB temperature prediction. © The Institution of engineering & Technology 2024.

关键词： machine learning prediction Vanadium redox flow battery

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Role of Consumption Pattern in Optimal Allocation of Distributed Generators in Electric Power and Energy Systems

Role of Consumption Pattern in Optimal Allocation of Distrib...

引用

2023 IEEE Texas Power and Energy Conference, TPEC 2023

作者： Mahdavi, Meisam Jurado, Francisco Schmitt, Konrad Chamana, Manohar Bayne, Stephen University of Jaén Linares Department of Electrical Engineering Jaén Spain Texas Tech University Electrical & Computer Engineering Department LubbockTX United States Texas Tech University Renewable Energy Program LubbockTX United States

ISBN: (纸本)9781665490719

The placement of distributed generation (DG) units in power systems is an efficient way for energy loss reduction, especially when the penetration of DG in modern systems is growing due to their impacts on environmental sustainability. On the other hand, load variations and methods of electricity consumption affect energy losses amount. Therefore, power demand variations have an essential role in the determination of energy loss amount and optimal generation of DG. However, considering the variability of load level in the DG allocation problem increases the burden and computational time, and neglecting it causes the energy losses to be calculated inaccurately. Therefore, this paper aims to evaluate the effect of load patterns on renewable DG allocation plans in order to find out the importance of considering load variations in energy loss minimization via DG placement. The analysis has been conducted on 7-, 12-, 16-, 28-, 30-, 33-, 59-, 69-, 70-, 84-, and 119-bus distribution systems by a classic optimization tool named AMPL. © 2023 IEEE.

关键词： Distributed power generation

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Smart Home Security System Using Face Recognition Based on IoT- CNN 2

Smart Home Security System Using Face Recognition Based on I...

引用

2nd International Conference on Information Technology Research and Innovation, ICITRI 2023

作者： Febriantono, M. Aldiki Zuhair, Alvin Khaeruddin School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia University of Islam Blitar Electrical Engineering Department Blitar Indonesia University of Muhammadiyah Malang Diploma III Electronic Technology Vocational Study Program Malang Indonesia

ISBN: (纸本)9798350324945

Home security is a crucial aspect that requires careful attention, particularly when it comes to addressing theft concerns. Hence, implementing smart door technology equipped with facial recognition holds promising potential for enhancing home security. This study aims to develop a more secure and regulated home entry system by leveraging Internet of Things (IoT) technology and Machine Learning computer Vision for facial recognition. The system integrates IoT devices, such as cameras and automatic doors, wherein facial image data is captured by the camera and processed using the Convolutional Neural Network (CNN) algorithm to identify individuals. Once an individual is recognized, the system grants access to the home through an automated door. By relying on facial features, the system effectively restricts unauthorized access and safeguards homes against theft risks. Therefore, the advancement of a safer and more controlled home entry system utilizing IoT technology and Machine Learning computer Vision holds tremendous benefits for homeowners. © 2023 IEEE.

关键词： Face recognition

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Performance of MIMO Visible Light Communication Under Consideration of Recommended Illumination Levels

Performance of MIMO Visible Light Communication Under Consid...

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Optics and Photonics Conference (SBFoton IOPC), SBFoton International

作者： David Esteban Farfán-Guillén Alexandre De Almeida Prado Pohl Graduate Program in Electrical and Computer Engineering (CPGEI) Federal University Technology-Parana Curitiba Brazil

This work compares illumination and communication performance of 2 × 2, 3 × 2 and 4 × 2 MIMO-OFDM VLC links. Results show that not every configuration complies with the recommended illumination levels (... 详细信息

ISBN: (数字)9798350388176

ISBN: (纸本)9798350388183

关键词： Spatial diversity Lighting Optics MIMO Robustness Photodetectors Indoor environment Antennas Visible light communication Photonics

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An autonomous robotic system for collecting garbage over small water bodies 6

An autonomous robotic system for collecting garbage over sma...

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6th International Conference on Automation, Control and Robotics engineering, CACRE 2021

作者： Hasany, Syed Nouman Zaidi, Saniya Shah Sohail, Syed Ahmad Farhan, Muhammad Electrical Engineering Program Habib University Karachi Pakistan Computer Science Program Habib University Karachi Pakistan Electrical and Computer Engineering Program Habib University Karachi Pakistan

ISBN: (纸本)9781665435765

Water pollution is a grave problem requiring utmost attention as it directly affects marine lives. In freshwater ecosystem, for example, lakes and ponds, a major chunk of water garbage is plastic floating on the surface of water which is labor intensive to collect manually. In this paper, we present a novel autonomous robotic system capable of navigating small water bodies and is equipped with computer vision that helps it to detect the garbage. The detection is followed by focusing on an area of interest to determine whether the garbage lies in the scope of robot for collection. Additionally, if WiFi communication is available, the robot has the provision of tracking the detected garbage to determine its path. The design of garbage collection unit of the robot ensures the garbage does not move outward once collected. The robot is tested in two different pools and with plastic bottles as main type of garbage. The results manifest the high degree of control of its locomotion as well as of detection and collection of the bottles. The deep neural network based detector onboard the robot can be retrained after self-collection of appropriate data to detect other types of garbage as well. © 2021 IEEE.

关键词： Plastic bottles

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Reconfiguration of Power Distribution Systems in the Presence of Voltage-Dependent Loads

Reconfiguration of Power Distribution Systems in the Presenc...

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2023 IEEE Texas Power and Energy Conference, TPEC 2023

作者： Mahdavi, Meisam Schmitt, Konrad Bayne, Stephen Chamana, Manohar University of Jaén Department of Electrical Engineering Jaén Linares Spain Texas Tech University Electrical and Computer Engineering Department LubbockTX United States Texas Tech University Renewable Energy Program LubbockTX United States

ISBN: (纸本)9781665490719

Load power can be changed by voltage fluctuation of network buses, in which reconfiguring the topology of distribution systems impacts the magnitude of bus voltages. Only a few papers have considered voltage-dependent loads in their reconfiguration models but introduced nonlinear formulations or highly approximated linear approaches. While nonlinear models can be solved by metaheuristic algorithms without guaranteeing the optimality of solutions or may be implemented by commercial nonlinear solvers, they require intensive and time-consuming computations. Moreover, linearized models are highly approximated by piecewise linear functions with many unknown parameters. Thus, this paper presents the effective design of the reconfiguration problems, including voltage dependency of loads, which can be solved using commercial linear solvers. The proposed models are precise enough to find accurate results for the reconfiguration problem and are adequately fast to converge to optimal solutions. The results show that the proposed solutions not only reduce active power losses significantly but increase the minimum voltage of the system effectively. © 2023 IEEE.

关键词： Power quality

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An Efficient Model for Optimal Allocation of Renewable Energy Sources in Distribution Networks with Variable Loads

An Efficient Model for Optimal Allocation of Renewable Energ...

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2023 IEEE Texas Power and Energy Conference, TPEC 2023

ISBN: (纸本)9781665490719

Operational costs are affected by energy losses of distribution systems, in which these losses are higher than those of the transmission system. The placement of distributed generation (DG) units in power distribution networks is an efficient way of energy loss reduction. Today, DG penetration in distribution systems is increasing because of the great effect of renewable energy resources on environmental sustainability. Power demand variations have an essential role in the determination of energy losses amount and optimal generation of DGs. Besides, considering the variability of load level in the DG allocation problem raises the burden and computational time substantially. Therefore, this paper proposes an effective DG allocation strategy for energy loss minimization in the presence of variable power demand. The evaluation of numerical results indicates the desired performance of the presented framework for the optimal placement of DG units in distribution systems with time-varying loads. © 2023 IEEE.

关键词： Energy dissipation

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An Environmentally Friendly Fishing Android-Based Mobile Device App for Penghu Islands (Pescadores), Taiwan

An Environmentally Friendly Fishing Android-Based Mobile Dev...

引用

Consumer Technology (ICCT-Pacific), International Conference on

作者： Hung-Tu Lin Ke-Qing Yan Ying-Zun Fang Xiang-Rui Huang Liang-Bi Chen Department of Computer Science and Information Engineering National Penghu University of Science and Technology Penghu Taiwan Department of Electrical Engineering Master Program in Electrical Engineering and Computer Science National Penghu University of Science and Technology Penghu Taiwan

ISBN: (数字)9798331504120

ISBN: (纸本)9798331504137

Penghu Islands (Pescadores), Taiwan's outlying islands surrounded by the sea, boast rich fishing resources that attract many anglers. However, successful fishing requires more than just gear: it involves understanding the varying fish species available in different locations, times, and climates, as well as adhering to relevant laws and regulations. To address these needs, this paper proposes an environmentally friendly fishing Android-based mobile device App specifically for the Penghu Islands. The proposed Android-based mobile device App aims to gather essential information, including local fishing regulations, aquatic safety tips, and important precautions. Its goal is to equip fishermen with the resources necessary to fish successfully and with peace of mind.

关键词： Sea measurements Length measurement Fish Regulation Mobile applications Tides Protection Smart phones Meteorology Lenses

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Comparative Analysis of The Effective Grounding System on External LPS Modeling in PV Fields 7

Comparative Analysis of The Effective Grounding System on Ex...

引用

7th International Conference on electrical, Telecommunication and computer engineering, ELTICOM 2023

作者： Rohana, Rohana Hardi, Surya Nasaruddin, Nasaruddin Away, Yuwaldi Doctoral Program School of Engineering Universitas Syiah Banda Aceh Indonesia Universitas Muhammadiyah Sumatera Utara Indonesia Universitas Sumatera Utara Dept. of Electrical Engineering Medan Indonesia Universitas Syiah Kuala Dept. of Electrical and Computer Engineering Banda Aceh Indonesia

ISBN: (纸本)9798350385526

Solar energy is environmentally friendly energy and is available in large quantities. The energy produced is commonly converted into electricity by using solar panel (PV) systems for utilization. PV systems are generally located in open areas such as hillsides, deserts, and water surfaces, so they become more sensitive against lightning strikes. Commonly, the PV is equipped with a lightning protection system (LPS). This paper discusses the grounding system at the solar power center (PLTS) Weh Island, Sabang City. Evaluation and comparison under certain conditions are carried out through measurements, calculations, and simulations. The grounding system is modeled for one rod, four rods in parallel, and plate rod. The measurement process during field observations and the induce voltage simulation are carried out to get the results of the analysis calculations. The result obtained shows that the grounding system fulfills the PUIL standard, namely being smaller than 5 Ω. When using plate electrodes, the resistance value is greater than that of rod electrodes. So that the lower conductor can be more resistant and easier to maintain. Improving the quality of the protection system, this research is used as a reference to evaluate LPS conditions in PV fields. © 2023 IEEE.

关键词： Solar energy

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Automatic Cataract and Cholesterol Detection System Based on Recurrent Neural Network (RNN): A Comparison with Convolutional Neural Network (CNN) and Siamese Neural Network (SNN) 1

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19th International Conference of Intelligent Unmanned Systems, ICIUS 2023

作者： Lie, Zener S. Widodo, Jatmiko A. F. Hanesi, Isabel K. P. Moningka, Matthew R. N. Mariana, Y. Astuti, Winda Akmeliawati, Rini Automotive and Robotics Program Computer Engineering Department BINUS ASO School of Engineering Bina Nusantara University Jakarta11480 Indonesia Product Design program Industrial Engineering Department BINUS ASO School of Engineering Bina Nusantara University Jakarta11480 Indonesia Robotics and Automation Research Group School of Electrical and Mechanical Engineering The University of Adelaide North Terrace Campus Adelaide Australia

ISBN: (数字)9789819765911

ISBN: (纸本)9789819765904

In Indonesia, the majority of blindness cases, approximately 81%, are attributed to cataract. Additionally, 35% of the population has higher cholesterol levels than the standard normal range. The lack of specialized medical equipment, such as the slit-lamp (Ruparelia in Dalhousie Med J 49(1), [1]) bio-microscope, and trained professionals, especially in rural areas, make it difficult to detect these conditions through eye examinations. To address this issue, a supervised machine learning method, the Recurrent Neural Network (RNN), has been utilized to create an iris scanner system that can identify cataract and high cholesterol in a patient. This system will classify eyes into three categories, i.e., cataract, high cholesterol, and normal iris. The computer simulations indicate that this technique is more accurate and requires less training time compared to the existing Convolutional Neural Network (ANN) and Siamese Neural Network (SNN)-based method, while achieving 100% accuracy. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Convolutional neural networks

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