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International Conference on Applied System Innovation (ICASI)

作者： Fu-Nie Loo Tung-Shou Chen Chia-Wei Tsai Jason Lin Chun-Wei Yang Department of Computer Science and Information Engineering National Taichung University of Science and Technology Taichung City Taiwan Department of Computer Science and Engineering National Chung Hsing University Taichung City Taiwan Master Program for Digital Health Innovation China Medical University Taichung City Taiwan

ISBN: (数字)9798350394924

ISBN: (纸本)9798350394931

Industrial Control systems (ICS) automate industrial processes but also introduces cybersecurity threats. Intrusion Detection System (IDS) are crucial for detecting cyber-attacks on ICS, yet zero-day attacks are often inefficiently detecting with supervised learning. This study employs semi-supervised learning using one-class SVM, isolation forest, and Local Outlier Factor (LOF), to train IDS models. Utilizing dataset collected from a self-build virtual ICS environment, the study demonstrates the feasibility of these models in detecting common attack like Injection, ARP, and Man-in-the-Middle.

关键词： Training Support vector machines Technological innovation Supervised learning Intrusion detection Forestry Semisupervised learning

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Using textile capacitive sensors to train synchronized movement of hands

Using textile capacitive sensors to train synchronized movem...

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IEEE International Conference on Consumer Electronics (ICCE)

作者： Chang-Ming Yang Shu-Cing Wu Shih-Hung Chen Ze-We Wu Kuo-Cheng Liao Chi-Chun Chen Ming Young Biomedical Corp. Miaoli Taiwan Program Prospective Technology of Electrical Engineering and Computer Science National Chin-Yi University of Technology Taichung Taiwan Dept. of Computer Science and Information Engineering National Chin-Yi University of Technology Taichung Taiwan Dept. of Electronic Engineering National Chin-Yi University of Technology Taichung Taiwan

This study introduced a capacitive sensing interactive game platform aimed at promoting emotional stability, which we have named the “Sunrise and Sunset” game. This game primarily consists of two pieces of regular textile fabric enveloping conductive silver fabric. A microcontroller was employed to extract the sensed capacitive values, and a game named “Sunrise and Sunset” is designed to complement the slow raising and lowering of both hands. The development of this gaming platform has the potential to offer a novel method of emotional management, particularly in high-stress living environments. It can serve as an effective relaxation tool, aiding individuals in emotional balance, anxiety reduction, and stress alleviation. Simultaneously, this platform can contribute to the promotion of mental well-being, providing an engaging and beneficial means for people to manage their emotions and moods.

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In situ Observation of Lithium Stripping and Plating Process in an Open-cell All-solid-state Lithium Metal Battery

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Microscopy and microanalysis : the official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada 2023年第1期29卷 1287-1288页

作者： Wu, C. Zhao, L. Ai, Q. Risal, S. Lou, J. Yao, Y. Fan, Zheng Materials Science and Engineering Program and Texas Center for Superconductivity at the University of Houston University of Houston Houston TX United States Department of Electrical and Computer Engineering University of Houston Houston TX United States Department of Materials Science and Nano Engineering Rice University Houston TX United States Department of Engineering Technology University of Houston Houston TX United States

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Unbiased and Multilevel Methods for a Class of Diffusions Partially Observed via Marked Point Processes

arXiv

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arXiv 2023年

作者： Alvarez, Miguel Jasra, Ajay Ruzayqat, Hamza Applied Mathematics and Computational Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955 Saudi Arabia

In this article we consider the filtering problem associated to partially observed diffusions, with observations following a marked point process. In the model, the data form a point process with observation times that have its intensity driven by a diffusion, with the associated marks also depending upon the diffusion process. We assume that one must resort to time-discretizing the diffusion process and develop particle and multilevel particle filters to recursively approximate the filter. In particular, we prove that our multilevel particle filter can achieve a mean square error (MSE) of O(∈2) (∈ > 0 and arbitrary) with a cost of O(∈-2.5) versus using a particle filter which has a cost of O(∈-3) to achieve the same MSE. We then show how this methodology can be extended to give unbiased (that is with no time-discretization error) estimators of the filter, which are proved to have finite variance and with high-probability have finite cost. Finally, we extend our methodology to the problem of online static-parameter estimation. Key words: Unbiased Methods, Multilevel Monte Carlo, Non-Linear Filtering, Point Processes, Parameter *** Codes 60G55, 60G35, 62M20, 62F30 © 2023, CC BY.

关键词： Diffusion

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Bayesian Parameter Inference for Partially Observed Stochastic Volterra Equations

arXiv

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arXiv 2023年

作者： Jasra, Ajay Ruzayqat, Hamza Wu, Amin Applied Mathematics & Computational Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955 Saudi Arabia

In this article we consider Bayesian parameter inference for a type of partially observed stochastic Volterra equation (SVE). SVEs are found in many areas such as physics and mathematical finance. In the latter field they can be used to represent long memory in unobserved volatility processes. In many cases of practical interest, SVEs must be time-discretized and then parameter inference is based upon the posterior associated to this time-discretized process. Based upon recent studies on time-discretization of SVEs (e.g. [24]) we use Euler-Maruyama methods for the afore-mentioned discretization. We then show how multilevel Markov chain Monte Carlo (MCMC) methods [19] can be applied in this context. In the examples we study, we give a proof that shows that the cost to achieve a 4 mean square error (MSE) of O(ϵ2), ϵ > 0, is O(ϵ− 4/2H+1 ), where H is the Hurst parameter. If one uses a single level MCMC method then the cost is O(ϵ−2(2H+3)/ 2H+1 ) to achieve the same MSE. We illustrate these results in the context of state-space and stochastic volatility models, with the latter applied to real *** Codes 62F15, 62M20, 60J10, 60J22, 65C40 © 2023, CC BY.

关键词： Mean square error

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Relative magnetic field and slipping effect on Casson dusty fluid of two phase fluctuating flow over inclined parallel plate

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South African Journal of Chemical Engineering 2023年 44卷 135-146页

作者： khan, Dolat Kumam, Poom Kumam, Wiyada Suttiarporn, Panawan Rehman, Ali Fixed Point Research Laboratory Fixed Point Theory and Applications Research Group Center of Excellence in Theoretical and Computational Science (TaCS-CoE) Faculty of Science King Mongkut's University of Technology Thonburi (KMUTT) 126 Pracha Uthit Rd. Bang Mod Bangkok Thung Khru 10140 Thailand Center of Excellence in Theoretical and Computational Science (TaCS-CoE) Faculty of Science King Mongkut's University of Technology Thonburi (KMUTT) 126 Pracha Uthit Rd. Bang Mod Bangkok Thung Khru 10140 Thailand Applied Mathematics for Science and Engineering Research Unit (AMSERU) Program in Applied Statistics Department of Mathematics and Computer Science Faculty of Science and Technology Rajamangala University of Technology Thanyaburi (RMUTT) Pathum Thani 12110 Thailand Faculty of Science Energy and Environment King Mongkut's University of Technology North Bangkok Rayong Campus Rayong 21120 Thailand Special Interest Group for Modelling and Data Analytics Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu Terengganu Kuala Nerus 21030 Malaysia

Due to its significant applications in magnetic devices for cell separation, magnetic drugs for cancer tumor treatment, blood flow adjustment during surgery, magnetic endoscopy, and fluid pumping in industrial and engineering processes, magnetohydrodynamics (MHD) has a wide range of applications. Therefore, the aim of this study to investigate the Relative Magnetic Field and slipping effect on Casson dusty fluid of two-phase fluctuating flow over inclined parallel plate. More exactly, the relative magnetic phenomena are fixed relatively to the plate (MFFRP) or fixed relatively to the fluid (MFFRF). The mathematical modeling was established as the set of partial differential equations for dusty Casson fluid. Buckingham's pi theorem is used to find out the dimensionless variables, to make our system dimensionless. The solution in perturb form is to find out by incorporating Poincare–Lighthill perturbation technique (PLPT). To know in-depth different parameters the graphical results for both velocities are plotted with the help of software Mathcad- 15. It is clearly detected that the relative magnetic field performs a vital part in the fluid as well as particle motion. Moreover, the relative magnetic field play a vital role in the decreasing of skin friction of both plates. © 2023

关键词： Brinkman fluid Dust particles Fluctuating vertical plate Inclined relative magnetic field PLPT

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Cost-Efficient Snubbers for Boost Converters

Cost-Efficient Snubbers for Boost Converters

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Asia-Pacific Symposium on Electromagnetic Compatibility (APEMC)

作者： Yeu-Torng Yau Thanh-Phu. Luu Department of Ph.D. Program Prospective Technology of Electrical Engineering and Computer Science National Chin-Yi University of Technology Taichung Taiwan Department of Electrical Engineering National Chin-Yi University of Technology Taichung Taiwan

ISBN: (数字)9784885523472

ISBN: (纸本)9798350349498

Conventional boost converters operating with hard-switching result in low conversion efficiency and increased electromagnetic interference emissions. In this paper, a cost-efficient passive snubber is proposed with a few additional components: two diodes, one capacitor, and one inductor. Moreover, because these snubber components are not located on the main power processing path, they only require low ratings, resulting in improved cost-effectiveness.

关键词： Snubbers Electromagnetic interference Capacitors Switches Electromagnetic compatibility Inductors

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MERNet: Multimodal Emotion Recognition in Conversation Network via Cross-Modal Knowledge Distillation and Contrastive Learning

MERNet: Multimodal Emotion Recognition in Conversation Netwo...

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International Conference on Big Data and Smart Computing (BIGCOMP)

作者： Sooyeon Hwang Gahgene Gweon Eunseong Kwon Interdisciplinary Program in Artificial Intelligence Seoul National University South Korea Graduate School of Convergence Science and Technology Seoul National University South Korea Dept. of Computer Science and Engineering POSTECH South Korea

ISBN: (数字)9798331529024

ISBN: (纸本)9798331529031

Multimodal Emotion Recognition in Conversation (ERC) is a task of predicting the emotion of each utterance in a conversation by utilizing both verbal and non-verbal modalities. However, existing approaches often struggle to bridge cross-modal gaps, resulting in misaligned features and frequent misclassification of minority emotions into semantically similar majority emotions. To address these challenges, we propose MERNet, a framework that employs cross-modal knowledge distillation and contrastive learning to align multimodal features and effectively distinguish subtle emotions in conversations. Our framework consists of two stages: 1) guiding non-verbal modalities with the text modality to transfer knowledge and align their features, and 2) applying contrastive learning with emotion labels as anchors to distinguish subtle differences between similar emotions and address the class imbalance problem. Experiments conducted on two benchmark datasets, IEMOCAP and MELD, demonstrate that our MERNet outperforms existing state-of-the-art models.

关键词： Knowledge engineering Bridges Emotion recognition Visualization Computational modeling Contrastive learning Benchmark testing Linguistics Big Data

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MERNet: Multimodal Emotion Recognition in Conversation Network via Cross-Modal Knowledge Distillation and Contrastive Learning

MERNet: Multimodal Emotion Recognition in Conversation Netwo...

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2025 IEEE International Conference on Big Data and Smart Computing, BigComp 2025

作者： Hwang, Sooyeon Gweon, Gahgene Kwon, Eunseong Seoul National University Interdisciplinary Program in Artificial Intelligence Korea Republic of Seoul National University Graduate School of Convergence Science and Technology Korea Republic of POSTECH Dept. of Computer Science and Engineering Korea Republic of

关键词： Contrastive Learning

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The reliability of deep learning models in assessing the shoulder arthroscopic field's visual clarity in relation to bleeding

JSES International

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JSES International 2025年第3期9卷 864-870页

作者： Tran, Son Quang Bui, Minh Cong Nguyen, Dat Tien Itthipanichpong, Thun Limskul, Danaithep Thamrongskulsiri, Napatpong Tanpowpong, Thanathep Clinical Sciences Program Faculty of Medicine Chulalongkorn University Bangkok Thailand Faculty of Medicine Department of Orthopaedics Cantho University of Medicine and Pharmacy Can Tho Viet Nam Faculty of Computer Science University of Information Technology Ho Chi Minh City National University Ho Chi Minh City Viet Nam Sports Medicine Research Group Faculty of Medicine Chulalongkorn University Bangkok Thailand

Background: The clarity of visualization in shoulder arthroscopy is significantly influenced by intraoperative bleeding. This study aims to develop deep learning models to classify the visual clarity of arthroscopic shoulder images and evaluate their reliability compared to rater assessment. Methods: We retrospectively reviewed videos from 113 shoulder arthroscopies, using 63 patients’ videos to create a 3750-image training dataset and 50 patients’ videos to evaluate the reliability and agreement of the trained models. Images extracted from the videos were assessed for visual clarity with a 3-grade scale. Subsequently, we implemented transfer learning techniques for the pretrained deep learning models involving DensetNet169, DenseNet201, Xception, InceptionResNetV2, VGG16, and ViT. The reliability and agreement of the trained predictive models compared with raters in classifying the visual clarity of shoulder arthroscopic images were reported with percent agreement and weighted kappa coefficients. Similarly, for quantifying the visual clarity of surgical videos, the reliability and agreement were evaluated through intraclass coefficients, bias, and limits of agreement. Results: Most models achieved over 90% accuracy in validation step, with InceptionResNetV2, DenseNet169, and ViT exhibiting good percent agreements of 82.3%, 79.2%, and 77.8%, respectively, and their weighted kappa coefficients above 0.8. DenseNet169 model had the highest reliability for evaluating the visual clarity of surgical videos with an intraclass correlation coefficient of 0.9, a bias of 0.027, and the narrowest limits of agreement. Conclusion: The trained DenseNet169 predictive model was reliable enough to be utilized as an objective measure of the visual clarity of the shoulder arthroscopic field for further research. © 2025 The Authors

关键词： Basic science Study Bleeding Convolutional neural network Deep learning model Grading scale Shoulder arthroscopy Validation of Artificial Intelligence Software Visual clarity Visualization

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