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International Conference on engineering, Applied Sciences, and technology (ICEAST)

作者： Nattapong Paenoi Suchada Sitjongsataporn The Electrical Engineering Graduate Program Mahanakorn Institute of Innovation (MII) Faculty of Engineering and Technology Mahanakorn University of Technology Bangkok Thailand Mahanakorn Institute of Innovation (MII) Faculty of Engineering and Technology Mahanakorn University of Technology Bangkok Thailand

ISBN: (纸本)9781665431057

This paper presents the automatic transfer function improvement based on the genetic algorithm for searching the optimal transfer function. A traditional genetic algorithm is modified to perform the searching process. The proposed chromosome design is presented in the form of 15-bit supported the resistance and inductance. Transfer function is used to design and control the systems. The optimal fitness function is used for the objective function of system to optimize the transfer function. Experiment results show that the second order of automatic transfer function performed by the genetic algorithm can achieve more accuracy than the traditional first order transfer function process. By the process improvement using the genetic algorithm, the time is used for searching transfer function with the chromosome design under the optimal fitness function by the genetic algorithm is approximately 13.35 seconds.

关键词： Resistance Inductance Transfer functions Mean square error methods Linear programming Control systems Approximation algorithms

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Application of brain wave signal in anisometropia examination

Application of brain wave signal in anisometropia examinatio...

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2021 International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2021

作者： Chen, Der-Chin Chang, Chao-Kai Chang, Shih-Tsung Liao, Jih-Yi Lin, Chern-Sheng Chung, Sheng-Fa Feng Chia University Department of Electrical Engineering Taichung Taiwan Yuanpei University of Medical Technology Department of Optometry Hsinchu Taiwan Feng Chia University Professional Master's Program of Optometry Science and Technology Taichung Taiwan Passion Lignt Inc. Taipei Taiwan Feng Chia University Department of Automatic Control Engineering Taichung Taiwan Department of Optometry Yuanpei University of Medical Technology Hsinchu Taiwan

ISBN: (纸本)9781665419512

Anisometropia is due to the different refractive power of the left and right eyes, resulting in uneven eye focus and different diopters of the two eyes, resulting in asymmetric hyperopia, myopia and astigmatism. At present, it is not completely clear what causes anisometropia, but it may be caused by different refractive power of both eyes. The difference of binocular refractive power of normal vision people may be as high as 5%, but people with difference more than 5% are prone to binocular vision. The purpose of this study is to measure the changes of clear and blurred brain wave signals of vision. Through the relationship between brain wave signals and visual response, we analyze the attention and meditation curve of brain wave, and complete the fitting prescription lenses of anisometropia. © 2021 IEEE.

关键词： Binocular vision

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Mapping Research Trends and Visualization of E-learning in Entrepreneurship in the Last Ten Years 1

Mapping Research Trends and Visualization of E-learning in E...

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1st International Conference on electrical and Information technology, IEIT 2021

作者： Maulana, Fairuz Iqbal Candra Pratama, Febby Permana, Frihandhika Khaeruddin Herasmara, Ridho School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia BINUS Business School Undergraduate Program Bina Nusantara University Entrepreneurship Department Jakarta11480 Indonesia Diploma III Electronic Technology Vocational Study Program University of Muhammadiyah Malang Malang Indonesia Electrical Engineering Faculty of Science and Technology Raden Rahmat Islamic University Malang Indonesia

ISBN: (纸本)9781665417860

E-learning is a system or concept of education or learning process that utilizes information technology in the teaching and learning process anywhere and anytime. E-learning is widely applied in various fields of science. In this study, we draw scientific efforts on e-learning and entrepreneurship from publications in the Scopus database. We reviewed 218 academic documents published over the last 10 years, from 2011 to 2020. Our method is a global bibliometric analysis by visualizing connected networks using Vosviewer. The method used consists of five stages: determining search keywords, initial search results, refinement of search results, initial compilation, and data analysis. We researched several countries, affiliations, authors, subject areas, to types of publications that have relations in this field. Among the most published and indexed articles by Scopus, papers published by researchers in the China have the highest number of publications is 36 academic documents, followed by United States 18 academic publications, and Italy with 16 academic publications. The results showed that it had a limited impact, and through visualization, the network presented research gaps that future researchers should fill. The processed data shows the pattern and trend of increasing the number of international publications on E-learning in the field of entrepreneurship indexed by Scopus. Finally, we address the limitations of this study. © 2021 IEEE.

关键词： Visualization

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Taguchi optimization and analysis of variance for thermoelectric generators with forced convection air cooling

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Applied Thermal engineering 2023年 231卷

作者： Chen, Wei-Hsin Carrera Uribe, Manuel Luo, Ding Jin, Liwen Huat Saw, Lip Lamba, Ravita Department of Aeronautics and Astronautics National Cheng Kung University Tainan701 Taiwan Research Center for Smart Sustainable Circular Economy Tunghai University Taichung407 Taiwan Department of Mechanical Engineering National Chin-Yi University of Technology Taichung411 Taiwan International Master Degree Program on Energy Engineering National Cheng Kung University Tainan701 Taiwan College of Electrical Engineering & New Energy China Three Gorges University Yichang443000 China Institute of Building Environment and Sustainable Technology School of Human Settlements and Civil Engineering Xi'an Jiaotong University Xi'an China Lee Kong Chian Faculty of Engineering and Science Tunku Abdul Rahman University Kajang43000 Malaysia Department of Electrical Engineering Malaviya National Institute of Technology Jaipur India

In recent years, humanity has experienced the effects of using unsustainable energy sources that pollute the environment while being inefficient. Most of the primary energy input used in energy conversion processes is lost in the form of heat. Thermoelectric generators (TEGs) have the potential to recover some of this wasted heat;however, their low energy conversion efficiency needs to be addressed. Previous literature has shown effective optimization of thermoelectric generation systems through statistical tools such as the Taguchi method that optimized all the parameters that affect the outcome of the system. To this date, no research has considered wind speed for convection heat transfer as one of the optimizable parameters. This study aims to optimize the operating conditions of commercially available TEGs that are cooled by forced convection simulating naturally occurring wind speeds and operate under low-quality waste heat temperatures to improve the TEG performance further. Two commercially available TEGs are optimized via the Taguchi method. The Taguchi method is implemented with three parameters and three levels, making an L9 orthogonal array. The objective function is the maximum output power. The optimized parameters are the hot side temperature, the heat sink size, and the wind airspeed. Analysis of variance (ANOVA) is used alongside the Taguchi orthogonal array for the statistical analysis of the results. The optimization results show that the hot side temperature is the most influential parameter to the output power. In addition, the change in the heat sink size also significantly influences the output power, whereas the impact of the wind speed is not as significant. In addition, interaction analysis between the parameters is performed. The Taguchi method yields satisfactory optimization results. The optimized system yields 0.65 W of power at 140 °C hot side temperature, Model K402 heat sink, and 3.7 m·s−1 wind speed. The influence of the air velocity

关键词： Design of experiments

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Parameter Estimation for Partially Observed McKean-Vlasov Diffusions

arXiv

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arXiv 2024年

作者： Jasra, Ajay Maama, Mohamed Tempone, Raul School of Data Science The Chinese University of Hong Kong CN Shenzhen China Applied Mathematics and Computational Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia Chair of Mathematics for Uncertainty Quantification RWTH Aachen University Aachen52062 Germany

In this article we consider likelihood-based estimation of static parameters for a class of partially observed McKean-Vlasov (POMV) diffusion process with discrete-time observations over a fixed time interval. In particular, using the framework of [5] we develop a new randomized multilevel Monte Carlo method for estimating the parameters, based upon Markovian stochastic approximation methodology. New Markov chain Monte Carlo algorithms for the POMV model are introduced facilitating the application of [5]. We prove, under assumptions, that the expectation of our estimator is biased, but with expected small and controllable bias. Our approach is implemented on several examples. Copyright © 2024, The Authors. All rights reserved.

关键词： Stochastic systems

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Effects of Fir-Wood Biochar on Ch4 Oxidation Rates and Methanotrophs in Landfill Cover Soils Packed at Three Different Proctor Compaction Levels

SSRN

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SSRN 2023年

作者： Yi, Susan C. Heijbroek, Anne Cutz, Luis Pillay, Stephanie de Jong, Wiebren Abeel, Thomas Gebert, Julia Delft University of Technology Faculty of Mechanical Maritime and Materials Engineering Leeghwaterstraat 39 Delft2628 CB Netherlands Delft University of Technology Faculty of Electrical Engineering Mathematics and Computer Science Van Mourik Broekmanweg 6 Delft2628 XE Netherlands Broad Institute of MIT and Harvard Infectious Disease and Microbiome Program 415 Main St. CambridgeMA02142 United States

Application of biochar to landfill cover soils can purportedly improve methane (CH4) oxidation rates. However, understanding of the combined effects of soil texture, compaction, and biochar on activity and composition of the methanotrophs is limited. The amendment of wood biochar on two differently textured landfill cover soils at three compaction levels of the Proctor density were explored by analyzing changes in soil physical properties relevant to methane oxidation, the effects on CH4 oxidation rates and on the composition of the methanotrophic community. Loose soils with and without biochar were pre-incubated to equally elevate the CH4 oxidation rates. Hereafter, soils were compacted and re-incubated. Methane oxidation rates, gas diffusivity, water retention characteristics and pore size distribution were analyzed on the compacted soils. Abundance of methanotrophic bacteria (MOB) was determined at the end of both the pre-incubation tests and the incubation tests of the packed samples. Biochar significantly increased porosity at all compaction levels, resulting in enhanced diffusion coefficients. Also, a re-distribution in pore sizes was observed. Increased gas diffusivity from low compaction and amendment of biochar, however, did not reflect higher methane oxidation rates due to high diffusive oxygen fluxes over the limited height of the compacted soil specimens. All soils, with and without biochar, were strongly dominated by type II methanotrophs. In the sandy soil, biochar amendment strongly increased MOB abundance, which could be attributed to a corresponding increase in the abundance of Methylocystis species, while in the clayey soil no such response was observed. Compaction did not change the community composition in either soil. Biochar addition to landfill cover soils may not always enhance methanotrophic activity and hence reduce fugitive methane emissions with the effect being soil-specific. However, especially in finer and more compacted soils, biochar

关键词： Compaction

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Georeferencing System for Maneuvering of Autonomous Truck in Mining Environment

Georeferencing System for Maneuvering of Autonomous Truck in...

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International Carpathian Control Conference (ICCC)

作者： Emanuel Francisco Vicentini Carvalho Lucas Silva De Oliveira Murillo Ferreira Dos Santos Paolo Mercorelli Matheus Carvalho Gouveia Master Degree Program in Automation and Systems CEFET-MG Leopoldina Brazil Department of Mechatronics Engineering CEFET-MG Divinópolis MG Brazil Department of Electroelectronics CEFET-MG Leopoldina Brazil Institute for Production Technology and Systems (IPTS) Leuphana University of Lüneburg Lüneburg Germany Electrical Engineering B. Sc UFJF-MG Juiz de Fora MG Brazil

ISBN: (数字)9798350350708

ISBN: (纸本)9798350350715

Mining automation began in the 1960s to increase safety in underground mines. Today, robotic and autonomous systems perform specific mining activities, creating new oppor-tunities and a more efficient and safe industry. This paper proposes a novel solution for instrumentation for autonomous trucks working in open-pit mines, specifically during the parking maneuver to load ore. In this case, new hardware and firmware are developed to compute the future coordinates of the excavator bucket using two Global Positioning Systems (GPS) receivers. In this approach, employing the concept of geometry and information from the GPS receivers, the future coordinates of the excavator bucket are calculated and made available to control the system, parking the autonomous truck in the desired position. The results demonstrate the accurate positioning of the off-highway truck during the ore-loading process, allowing for the correct execution of the truck's autonomous positioning maneuver.

关键词： Automation Receivers Excavation Hardware Real-time systems Safety Vehicle dynamics

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FincGAN: A Gan Framework of Imbalanced Node Classification on Heterogeneous Graph Neural Network

FincGAN: A Gan Framework of Imbalanced Node Classification o...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Hung Chun Hsu Ting-Le Lin Bo-Jun Wu Ming-Yi Hong Che Lin Chih-Yu Wang Graduate Program of Data Science National Taiwan University and Academia Sinica Taiwan Department of Accounting and Statistics National ChengChi University Taiwan Department of Risk Management and Insurance National ChengChi University Taiwan Department of Electrical Engineering National Taiwan University Taiwan Graduate Institute of Communication Engineering National Taiwan University Taiwan Research Center for Information Technology Innovation Academia Sinica Taiwan

Graph Neural Networks (GNNs) frequently face class imbalance issues, especially in heterogeneous graphs. Existing GNNs often assume balanced class sizes, which isn’t true in many cases. Applying them directly to imbalanced data can lead to sub-optimal performance. Traditional oversampling methods, while effective, risk overfitting and face difficulties in reintegrating synthetic samples into the original graph. In this study, we introduce Framework of Imbalanced Node Classification on heterogeneous graph neural network with GAN (FincGAN), a new framework that utilizes oversampling techniques to address class imbalance in heterogeneous graphs. Instead of duplicating existing samples, FincGAN employs a Generative Adversarial Network (GAN) to create synthetic samples and uses deep learning-based edge generators to connect them back to the original graph. Our evaluations on spam user detection in the Amazon and Yelp Review datasets show that FincGAN outperforms baseline models in all essential metrics, including F-score and AUC-PRC score, showing its effectiveness in addressing class imbalance.

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Hot Carrier Injection (HCI) Reliability of Fabricated Y-gate HEMT with Various Top Length

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ECS Journal of Solid State Science and technology 2023年第3期12卷 035001-035001页

作者： Chen, Yu-Lin Yeh, Wen-Kuan Chen, Ke-Horng Hsu, Heng-Tung Hsu, Chin-Tsai Godwin Raj, D. Chou, Hung-Ting Wu, Jui-Sheng Yu, Tien-Han Godfrey, D. Graduate Degree Program of College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu Taiwan International College of Semiconductor Technology National Yang Ming Chiao Tung University Hsinchu Taiwan National Applied Research Laboratories Hsinchu Taiwan Dept of ECE Amal Jyothi College of Engineering Kerala India National Chung Shan Institute of Science and Technology Taoyuan Taiwan Deparment of Materials Science and Engineering National Yang Ming Chiao Tung University Hsinchu Taiwan Dept of Electronics and Communication Engineering Dayananda Sagar University Bengaluru India

Device degradation due to hot carrier injection (HCI) in different Y-gate HEMT devices is thoroughly analyzed. To further understand the HCI reliability of the Y-gate HEMT devices, the device is fabricated with AlGaN/GaN structure with different top lengths (Ltop). An HCI stress time of 6000 s was conducted on these devices, while V t stability in other stress time domains, leakage current, and transconductance degradation are also discussed. In this work, we have demonstrated that increasing the LTop length could avoid the virtual gate effect and disperse the influence of the electric field under HCI stress. Furthermore, the effects of trapping in various locations, such as in the bulk SiN or AlGaN/GaN interface has been discussed. These trapping effects caused by the HCI stress might be the source of the Vth shift. Overall, The large Y-gate HEMT showed the lowest degradation of DC characteristics after the long HCI stress test. © 2023 The Electrochemical Society ("ECS"). Published on behalf of ECS by IOP Publishing Limited.

关键词： High electron mobility transistors

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Generative AI-enabled Vehicular Networks: Fundamentals, Framework, and Case Study

arXiv

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arXiv 2023年

作者： Zhang, Ruichen Xiong, Ke Du, Hongyang Niyato, Dusit Kang, Jiawen Shen, Xuemin Poor, H. Vincent The Engineering Research Center of Network Management Technology High Speed Railway of Ministry of Education School of Computer and Information Technology Beijing Jiaotong University Beijing100044 China The Collaborative Innovation Center of Railway Traffic Safety Beijing Jiaotong University Beijing100044 China The National Engineering Research Center of Advanced Network Technologies Beijing Jiaotong University Beijing100044 China The School of Computer Science and Engineering The Energy Research Institute @ NTU Interdisciplinary Graduate Program Nanyang Technological University Singapore The School of Automation Guangdong University of Technology China The Department of Electrical and Computer Engineering University of Waterloo Canada The Department of Electrical and Computer Engineering Princeton University PrincetonNJ08544 United States

Recognizing the tremendous improvements that the integration of generative AI can bring to intelligent transportation systems, this article explores the integration of generative AI technologies in vehicular networks, focusing on their potential applications and challenges. Generative AI, with its capabilities of generating realistic data and facilitating advanced decision-making processes, enhances various applications when combined with vehicular networks, such as navigation optimization, traffic prediction, data generation, and evaluation. Despite these promising applications, the integration of generative AI with vehicular networks faces several challenges, such as real-time data processing and decision-making, adapting to dynamic and unpredictable environments, as well as privacy and security concerns. To address these challenges, we propose a multi-modality semantic-aware framework to enhance the service quality of generative AI. By leveraging multi-modal and semantic communication technologies, the framework enables the use of text and image data for creating multi-modal content, providing more reliable guidance to receiving vehicles and ultimately improving system usability and efficiency. To further improve the reliability and efficiency of information transmission and reconstruction within the framework, taking generative AI-enabled vehicle-to-vehicle (V2V) as a case study, a deep reinforcement learning (DRL)-based approach is proposed for resource allocation. Finally, we discuss potential research directions and anticipated advancements in the field of generative AI-enabled vehicular networks. Copyright © 2023, The Authors. All rights reserved.

关键词： Reinforcement learning

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