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arXiv 2025年

作者： Jasra, Ajay Wu, Amin School of Data Science The Chinese University of Hong Kong Shenzhen Shenzhen China Statistics Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia

In this article we consider Bayesian estimation of static parameters for a class of partially observed McKean-Vlasov diffusion processes with discrete-time observations over a fixed time interval. This problem features several obstacles to its solution, which include that the posterior density is numerically intractable in continuous-time, even if the transition probabilities are available and even when one uses a time-discretization, the posterior still cannot be used by adopting well-known computational methods such as Markov chain Monte Carlo (MCMC). In this paper we provide a solution to this problem by using new MCMC algorithms which can solve the aforementioned issues. This MCMC algorithm is extended to use multilevel Monte Carlo (MLMC) methods. We prove convergence bounds on our parameter estimators and show that the MLMC-based MCMC algorithm reduces the computational cost to achieve a mean square error versus ordinary MCMC by an order of magnitude. We numerically illustrate our results on two models. Copyright © 2025, The Authors. All rights reserved.

关键词： Channel estimation

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Improved Design Procedure for Two-Stage CMOS Op Amp Employing Current Buffer 17

Improved Design Procedure for Two-Stage CMOS Op Amp Employin...

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17th International Conference on electrical engineering/Electronics, Computer, Telecommunications and Information technology, ECTI-CON 2020

作者： Chanapromma, Chaiyan Mahattanakul, Jirayuth Mahanakhorn University of Technology Electrical Engineering Graduate Program Bangkok Thailand

ISBN: (数字)9781728164861

ISBN: (纸本)9781728164861

In this paper an improved version of the design procedure of two-stage CMOS operational amplifier employing a Miller capacitor and a current buffer is presented. Unlike the op amp obtained from the previously reported design procedure, in which the unity gain frequency is approximated by the gain bandwidth product, the resulting op amp from the proposed procedure has frequency response characteristics much closer to the desired values. Design example of the proposed procedure is given and the results compared to the previous method. © 2020 IEEE.

关键词： Operational amplifiers

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Design of an Assisted Learning System Based on ChatGPT 23

Design of an Assisted Learning System Based on ChatGPT

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Proceedings of the 2023 6th Artificial Intelligence and Cloud Computing Conference

作者： Chia-Chuan Tsao Yen-Hung Lin Chien-Hsing Chou Kuan-Ning Chang Ping-Hsuan Han Department of Mathematics and Information Education National Taipei University of Education Taiwan Department of Electrical and Computer Engineering Tamkang University Taiwan Doctoral Program in Design National Taipei University of Technology Taiwan Department of Interaction Design National Taipei University of Technology Taiwan

ISBN: (纸本)9798400716225

This paper describes a system that utilizes ChatGPT as an auxiliary learning tool to assist students in overcoming learning difficulties. By providing ChatGPT with relevant domain-specific knowledge in advance, the system enhances the accuracy of responses. Additionally, the interface design facilitates students in posing high-quality questions, thereby obtaining precise answers. This paper aims to use this system design to help students address learning challenges, increase motivation for learning, and reduce the cost of developing domain-specific chatbots, thus enabling its application in a broader range of educational fields.

关键词： ChatGPT chatbot computer-assisted instruction question-answering system teaching and learning

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Solid State Electrolyte to Enable Structural Supercapacitors

Solid State Electrolyte to Enable Structural Supercapacitors

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IEEE International Conference on Flexible and Printable Sensors and Systems (FLEPS)

作者： Nandu Koripally Lulu Yao Jason D. Azoulay Tse Nga Ng Department of Electrical and Computer Engineering University of California San Diego La Jolla CA USA Materials Science Engineering Program University of California San Diego La Jolla CA USA Chemisty Department Georgia Institute of Technology Atlanta GA USA

ISBN: (数字)9798350383263

ISBN: (纸本)9798350383270

Supercapacitors are known for longer cycle life and faster charging rate compared to batteries. However, the energy density of supercapacitors requires improvement to expand their application space. To raise the energy density of structural supercapacitors, this work demonstrates a low resistance and mechanically strong solid-state electrolyte.

关键词： Resistance Supercapacitors Electrolytes Sensor systems Sensors Batteries

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Resonance Behavior of an Obliquely-Oriented Conducting Wire Object Above a Halfspace

Resonance Behavior of an Obliquely-Oriented Conducting Wire ...

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Australian Microwave Symposium (AMS)

作者： Siyuan Li Chad Hargrave Hoi-Shun Lui School of Electrical and Data Engineering University of Technology Sydney Ultimo NSW Australia Sustainable Mining Research Program Commonwealth Scientific and Industrial Research Organisation Pullenvale QLD Australia

This paper examines the effect of a halfspace on the residues of the extracted resonant modes of an obliquely-oriented conductive wire target above it. Previous studies have focused on the case where the target is in free space, but in this case, the halfspace interacts electromagnetically with the target and alters the residue. The results show that the residue of the fundamental mode is affected by the dielectric properties of the halfspace, while the residues of higher-order modes remain similar as the properties change. These findings provide insights for designing automated recognition solutions for targets above halfspaces.

关键词： Target recognition Spaceborne radar Wires Radar scattering Microwave theory and techniques Dielectrics Behavioral sciences

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Heteroassociative Mapping with Self-Organizing Maps for Probabilistic Multi-output Prediction

Heteroassociative Mapping with Self-Organizing Maps for Prob...

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International Joint Conference on Neural Networks (IJCNN)

作者： Rewbenio A. Frota Marley M.B.R. Vellasco Guilherme A. Barreto Candida Menezes de Jesus PETROBRAS Rio de Janeiro Brazil Department of Electrical Engineering Pontifical Catholic University of Rio de Janeiro (PUC-Rio) Rio de Janeiro Brazil Graduate Program in Teleinformatics Engineering Center of Technology Federal University of Ceará (UFC) Fortaleza Brazil

ISBN: (数字)9798350359312

ISBN: (纸本)9798350359329

In recent years, Representation Learning (RepL) has experienced a surge, especially for cross-modal applications with mixed-type data. Most current cross-modal RepL approaches rely mainly on supervised deep learning models, with unsupervised models playing auxiliary roles. In this paper, we present a fully unsupervised approach to demonstrate the capabilities of such models for cross-modal RepL. Our method jointly learns representations into topologically coherent cross-modal heteroassociative mappings. We apply the proposed framework to a yet to be solved multi-output prediction problem in petroleum geoscience: generating a complete set of regular petrophysical well logs from acoustic borehole images in highly heterogeneous Brazilian pre-salt reservoirs.

关键词： Self-organizing feature maps Representation learning Deep learning Neural networks Geoscience Reservoirs Probabilistic logic

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Twenty years of e-learning in health science: A bibliometric

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Procedia Computer Science 2023年 216卷 604-612页

作者： Fairuz Iqbal Maulana M. Aldiki Febriantono Dwi Risza Budi Raharja Khaeruddin Ridho Herasmara Computer Science Department School of Computer Science Bina Nusantara University Jakarta 11480 Indonesia Diploma III Electronic Technology Vocational Study Program University of Muhammadiyah Malang Indonesia Electrical Engineering Faculty of Science and Technology Raden Rahmat Islamic University Malang Indonesia

Education about health sciences has historically been limited in the curriculum of health professionals and largely inaccessible to the public. In practice, most of the health science education is still running conventionally. Supposedly with the advancement of technology and the use of the internet everywhere, learning such as e-learning can be important, especially in the health sector. Until this research was conducted, only 514 academic documents about e-learning in health sciences were found for 20 years from 2001 to 2020, obtained in searching on the Scopus database. This study presents a comprehensive overview of studies related to E-learning in the Health Sciences sector. This study uses bibliometric analysis and indexed digital methods to map scientific publications throughout the world. This research employs the Scopus database to gather information, as well as the Scopus online analysis tool and Vosviewer to show the bibliometric network. The method consists with five stages: determining search keywords, initial search results, refinement of search results, initial compilation, and data analysis. Among the most published and indexed articles by Scopus, papers published by researchers in the United States have the highest number of publications (80), followed by United Kingdom (63) and Australia with 45 academic publications. The processed data shows the pattern and trend of increasing the number of international publications in E-learning in Health Sciences field, which Scopus index.

关键词： e-learning health science bibliometric vosviewer education

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Crack Catcher Ai – Enabling Smart Fracture Mechanics Approaches for Damage Control of Thin Silicon Cells or Wafers

SSRN

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SSRN 2024年

作者： Budiman, Arief Suriadi Putri, Dianing Novita Nurmala Candra, Henry Djuana, Endang Sari, Tyas Kartika Aji, Daisman P.B. Putri, Larasati Rizky Sitepu, Elioenai Speaks, Derrick Pasang, Tim Klamath FallsOR97601 United States Klamath FallsOR97601 United States Electrical Engineering Department Faculty of Industrial Technology Universitas Trisakti Jakarta11440 Indonesia Mechanical Engineering Department Faculty of Industrial Technology Universitas Trisakti Jakarta11440 Indonesia Industrial Engineering Department BINUS Graduate Program-Master of Industrial Engineering Bina Nusantara University Jakarta11480 Indonesia

Silicon has been one among a few key technologically important materials especially in our modern world. Silicon, especially in its current most useful forms (thin layers), is a brittle material by nature. Thin silicon cells crack easily during manufacturing assembly. Every crack is a defect in any PV manufacturing lines, and if let to grow/propagate it will lead to reliability and quality issues with time. Nevertheless, the global silicon solar PV industry is aggressively reducing the cost of solar PV systems through cutting down the thickness of silicon solar cells. Cell cracks immediately lower PV module efficiency and can lead to premature aging of the entire module. The "Crack Catcher AI" was our research joint collaboration’s entry in the Department of Energy (DOE)’s American-Made Solar Innovation competition in 2022 (Round 6) which later was selected as the national semifinalists and won an award announced by DOE in December 2022. It uses smart stress sensing and smart fracture prediction approaches utilizing fundamental fracture mechanics and big data analytics to reduce crack defects and enhance long-term durability/reliability of PV products/devices. Smart Stress Sensing uses a novel laser-based curvature methodology for fast in-line stress metrology in manufacturing lines. Smart Fracture Prediction uses Artificial Intelligence (AI) for defect control metrology and yield enhancement in PV production lines. It is based on monocrystalline silicon used in solar PV industries, but all scientific principles utilized and technological innovations developed in this article would be applicable as well for single crystal silicon semiconductor wafers. © 2024, The Authors. All rights reserved.

关键词： Cracks

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Condition Assessment of Underground Cable System Using Fuzzy Logic and Scoring and Weighting Average Methods

Condition Assessment of Underground Cable System Using Fuzzy...

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Conference on Power, Energy and Innovations (ICPEI)

作者： Dineenath Romphoyen Nattapon Panmala Thanapong Suwanasri Cattareeya Suwanasri EPE Program The Sirindhorn International Thai-German Graduate School of Engineering King Mongkut’s University of Technology North Bangkok Bangsue Bangkok Thailand Department of Teacher Training in Electrical Engineering Faculty of Technical Education King Mongkut’s University of Technology North Bangkok Bangsue Bangkok Thailand Department of Electrical and Computer Engineering Faculty of Engineering King Mongkut’s University of Technology North Bangkok Bangsue Bangkok Thailand

In this paper, the overall health index of underground cable system is determined using Fuzzy Logic and Scoring and Weighting Average methods. The relevant data of 73 feeders has been collected in the prepared evaluation forms, divided into five major component groups: cable, joint, termination, manhole, and ductbank. In each component, various testing methods and diagnostic techniques are applied, and then the numerical score is determined according to the technical criteria for condition assessment. Subsequently, the obtained overall health index is multiplied with the conditional factor to incorporate the differences in installation type and configuration as well as the operating and environmental conditions. Finally, the overall health index based on these two methods is compared to verify the accuracy of the obtained results to properly plan the preventive and condition-based maintenance and to improve the reliability of the underground cable system.

关键词：

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Sodium-ion battery cycle life prediction using machine learning

Sodium-ion battery cycle life prediction using machine learn...

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International Conference on Green Energy, Computing and Intelligent technology 2024 (GEn-CITy 2024)

作者： Linfeng Liu Filbert H. Juwono W. K. Wong Erick Purwanto Tingyan Jin Yuyang Zhen Sustainable Energy Technology Program Xi'an Jiaotong-Liverpool University Suzhou People's Republic of China Department of Electrical and Electronic Engineering Xi'an Jiaotong-Liverpool University Suzhou People's Republic of China Department of Electrical and Computer Engineering Curtin University Malaysia Miri Malaysia Department of Computing Xi'an Jiaotong-Liverpool University Suzhou People's Republic of China School of Mechanical and Electrical Engineering Beijing Information Science and Technology University Beijing People's Republic of China School of Instrument Science and Technology Beijing University of Technology Beijing People's Republic of China

ISBN: (数字)9781837242863

In this study, we explore the classification and prediction capabilities of three models—Genetic programming (GP), Logistic Regression (LR), and the Kolmogorov-Arnold Network (KAN)—on the task of sodium-ion battery life prediction. By leveraging a dataset composed of multiple battery characteristics, we aim to determine the remaining power of sodium-ion batteries using these machine learning models. The KAN model, being a novel approach, demonstrates superior performance across various metrics, including accuracy, precision, recall, and F1 score, when compared to the other two models. This highlights the potential of KAN as a robust model for complex classification tasks in the field of battery life prediction.

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