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International Conference on Computing, Electronics & Communications engineering (iCCECE)

作者： Chi-Hung Wei Chin-Chih Chang Chien-Hao Chu Sean Hsiao Ph.D. Program in Engineering Science Chung Hua University Hsinchu City Taiwan Department of Computer Science and Information Engineering Chung Hua University Hsinchu City Taiwan Bachelor Program in Applied Foreign Language and Smart Commerce Chung Hua University Hsinchu City Taiwan

VANET (Vehicular Ad Hoc Network) was developed to address the unique challenges of communication in a mobile vehicular environment. This technology can enhance driving safety and traffic control. Moreover, similar principles can be applied to unmanned aerial vehicles and robotics. When transmitting data in moving vehicles, it is challenging as access points and base stations keep changing, requiring handovers between different access points and base stations. Clustering is a popular approach used to address this challenge. Common clustering strategies are based on the proximity, communication range, the density, the application requirements of the moving vehicles, or hybrid of them. In this paper, we propose a clustering strategy based on the application sublayer in the vehicle communication protocol. If two computing devices on the move run the same application, they can be grouped together. The contribution of this research is to develop a clustering mechanism based on the application with very low overhead. We also validate the proposed method through simulations. The simulation results indicate that the proposed method is feasible.

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A Fitness Movement Evaluation System Using deep Learning

A Fitness Movement Evaluation System Using Deep Learning

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International Conference on Knowledge and Systems engineering (KSE)

作者： Chin-Chih Chang Chi-Hung Wei Hao-Wei Wu Sean Hsiao Department of Computer Science and Information Engineering Chung Hua University Hsinchu City Taiwan Ph.D. Program in Engineering Science Chung Hua University Hsinchu City Taiwan Bachelor Program in Applied Foreign Language and Smart Commerce Chung Hua University Hsinchu City Taiwan

This paper proposes a fitness movement evaluation system using deep learning. The system uses a deep convolutional neural network (CNN) to extract features from pictures of fitness movements. The features are then used to classify the movements into different categories. The system is evaluated on a dataset of pictures of fitness movements. The results show that the system can accurately classify the movements into different categories. The system is designed to provide feedback to users on their fitness movements. The proposed system is a valuable tool for fitness enthusiasts. The main contribution of this paper is to propose a way to give users a score for their fitness movement. It can help users improve their fitness and track their progress over time. The system is also a valuable tool for fitness professionals. It can help professionals develop new fitness programs and provide feedback to their clients.

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The Smart Analysis of Performing Scalable Inference for Big data Analytics

The Smart Analysis of Performing Scalable Inference for Big ...

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International Conference on Power Energy, Environment and Intelligent Control (PEEIC)

作者： Vishakha d Bhandarkar Aruna Sri Rongali Mohamed dawood Shamout Prof. Sachin Pund Gigih Forda Nama Shrishailappa Patil Applied Mathematics and Humanities Yeshwantrao Chavan College of Engineering India Graduate Doctoral Information Technology/Graduate (Information Technology Emphasis/Information Technology Ph.D.) University of The Cumberlands US Department of Management College of Business Administration University of Sharjah Sharjah United Arab Emirates Department of Industrial Engineering Shri Ramdeobaba College of Engineering and Management Nagpur Maharashtra India Department of Informatics Doctoral Program of Environtmental Science University of Lampung Bandar Lampung Computer engineering Vishwakarma Institute of Technology Pune

This paper examines the reproducibility of massive information analytics under particular factors. The paper proposes the “performing Scalable Inference” technique to cope with scalability troubles and to exploit current big statistics platforms for efficient computing and statistics garage of the statistics. In particular, the paper describes how to perform leak-free, parallelizable visible analytics over massive datasets using present extensive records analytics frameworks such as Apache Flink. This method presents an automated manner to execute analytics that preserves reproducibility and the ability to make adjustments without re-running the entire technique. The paper also demonstrates how these analytics may help several real-world use instances, explore affected person cohorts for studies, and develop stratified patient cohorts for hospital therapy. In the end, the paper observes how the proposed method may be exercised within the real world. Actively scalable inference for massive information analytics is pivotal in optimizing decision-making and allocation of assets. Typically, such inferences are made based on information accumulated from numerous sources, databases, unstructured data, and different digital sources. So one can ensure scalability, a complete cloud-primarily based platform has to be hired. This solution will permit the ***, deploying the essential records series and evaluation algorithms are prime here. It could permit the platform to recognize the styles inside the statistics and discover any ability correlations or traits. Additionally, predictive analytics and system mastering strategies may be incorporated to provide insights into the results of the information. In the long run, by leveraging those techniques, the platform can draw efficient inferences and appropriately compare situations in an agile and green way..

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900 MHz RF Power Rectifier Based on Ultra-low Turn-on Voltage Quasi-vertical GaN Schottky diode

900 MHz RF Power Rectifier Based on Ultra-low Turn-on Voltag...

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Wireless Power Week (WPW)

作者： Xiaochen Yu Ya-Xun Lin Ivona Z. Mitrovic Steve Hall der-Sheng Chao Jenq-Horng Liang Yi Huang Ta-Jen Yen Jiafeng Zhou International Intercollegiate Ph.D. Program National Tsing Hua University Hsinchu Taiwan Department of Electrical Engineering and Electronics University of Liverpool Liverpool United Kingdom Nuclear Science and Technology Development Center National Tsing Hua University Hsinchu Taiwan Department of Engineering and System Science National Tsing Hua University Hsinchu Taiwan Department of Materials Science and Engineering National Tsing Hua University Hsinchu Taiwan

ISBN: (数字)9798350349139

ISBN: (纸本)9798350349146

This paper presents a 20 W high-power RF-to-dC rectifier that can be applied to wireless power transfer (WPT) systems. To address the power limitations of conventional diodes, a rectifier is designed based on a gallium nitride (GaN) integrated circuit (IC) quasi-vertical Schottky barrier diode (SBd). Leveraging the advantages of high mobility, wide bandgap, and saturation velocity of the GaN, significant benefits of the diode have been derived, with an ultra-low turn-on voltage of 0.23 ± 0.005 V (at 1 A/cm 2 ) and a high breakdown voltage of 180 V, to improve the rectification performance. Using this diode, a high-power rectifier with a wide input power range and high efficiency is developed. The proposed rectifier structure consists of a single-shunt self-developed diode and a topology with class-F harmonics control networks. It achieves a peak power conversion efficiency of 72.9% with an input power of 43 dBm at 900 MHz.

关键词： Wireless communication Integrated circuits Schottky diodes Wireless sensor networks Breakdown voltage Rectifiers Wireless power transfer

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Structure-guided identification and characterization of potent inhibitors targeting phoP and MtrA to combat mycobacteria

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Computational and Structural Biotechnology Journal 2024年 23卷 1477-1488页

作者： Su, Han-Li Lai, Shu-Jung Tsai, Keng-Chang Fung, Kit-Man Lung, Tse-Lin Hsu, Hsing-Mien Wu, Yi-Chen Liu, Ching-Hui Lai, Hui-Xiang Lin, Jiun-Han Tseng, Tien-Sheng Department of Emergency Medicine Ditmanson Medical Foundation Chia-Yi Christian Hospital Chiayi City600 Taiwan Graduate Institute of Biomedical Sciences China Medical University Taichung Taiwan Research Center for Cancer Biology China Medical University Taichung Taiwan National Research Institute of Chinese Medicine Ministry of Health and Welfare Taipei Taiwan Ph.D. Program in Medical Biotechnology College of Medical Science and Technology Taipei Medical University Taipei Taiwan Academia Sinica Taipei11529 Taiwan Institute of Molecular Biology National Chung Hsing University Taichung Taiwan Department of Industrial Technology Ministry of Economic Affairs Taipei Taiwan Food Industry Research and Development Institute Hsinchu City Taiwan

Mycobacteria are causative agents of tuberculosis (TB), which is a global health concern. drug-resistant TB strains are rapidly emerging, thereby necessitating the urgent development of new drugs. Two-component signal transduction systems (TCSs) are signaling pathways involved in the regulation of various bacterial behaviors and responses to environmental stimuli. Applying specific inhibitors of TCSs can disrupt bacterial signaling, growth, and virulence, and can help combat drug-resistant TB. We conducted a comprehensive pharmacophore-based inhibitor screening and biochemical and biophysical examinations to identify, characterize, and validate potential inhibitors targeting the response regulators phoP and MtrA of mycobacteria. The constructed pharmacophore model phar-PR-n4 identified effective inhibitors of formation of the phoP–dNA complex: ST132 (IC50 = 29 ± 1.6 µM) and ST166 (IC50 = 18 ± 1.3 µM). ST166 (Kd = 18.4 ± 4.3 μM) and ST132 (Kd = 14.5 ± 0.1 μM) strongly targeted phoP in a slow-on, slow-off manner. The inhibitory potency and binding affinity of ST166 and ST132 for MtrAC were comparable to those of phoP. Structural analyses and molecular dynamics simulations revealed that ST166 and ST132 mainly interact with the α8-helix and C-terminal β-hairpin of phoP, with functionally essential residue hotspots for structure-based inhibitor optimization. Moreover, ST166 has in vitro antibacterial activity against Macrobacterium marinum. Thus, ST166, with its characteristic 1,2,5,6-tetrathiocane and terminal sulphonic groups, has excellent potential as a candidate for the development of novel antimicrobial agents to combat pathogenic mycobacteria. © 2024 The Authors

关键词： Antimicrobial agents

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Cigarette smoke-induced dysbiosis: comparative analysis of lung and intestinal microbiomes in COPd mice and patients

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Respiratory Research 2024年第1期25卷 1-14页

作者： Laiman, Vincent Chuang, Hsiao-Chi Lo, Yu-Chun Yuan, Tzu-Hsuen Chen, You-Yin Heriyanto, didik Setyo Yuliani, Fara Silvia Chung, Kian Fan Chang, Jer-Hwa Department of Radiology Faculty of Medicine Public Health and Nursing Universitas Gadjah Mada – Dr. Sardjito Hospital Yogyakarta Indonesia School of Respiratory Therapy College of Medicine Taipei Medical University 250 Wuxing Street Taipei 11031 Taiwan Division of Pulmonary Medicine Department of Internal Medicine Shuang Ho Hospital Taipei Medical University New Taipei Taiwan Cell Physiology and Molecular Image Research Center Wan Fang Hospital Taipei Medical University Taipei Taiwan National Heart and Lung Institute Imperial College London London United Kingdom The Ph.D. Program for Neural Regenerative Medicine College of Medical Science and Technology Taipei Medical University Taipei Taiwan Department of Health and Welfare College of City Management University of Taipei Taipei Taiwan Industrial Ph.D. Program of Biomedical Science and Engineering National Yang Ming Chiao Tung University Taipei Taiwan Department of Biomedical Engineering National Yang Ming Chiao Tung University Taipei Taiwan Department of Anatomical Pathology Faculty of Medicine Public Health and Nursing Universitas Gadjah Mada – Dr. Sardjito Hospital Yogyakarta Indonesia Department of Pharmacology and Therapy Faculty of Medicine Public Health and Nursing Universitas Gadjah Mada Yogyakarta Indonesia Division of Pulmonary Medicine Departments of Internal Medicine Wan Fang Hospital Taipei Medical University Taipei Taiwan Collaboration Research Center for Precision Oncology based Omics- PKR Promics Universitas Gadjah Mada Yogyakarta Indonesia

Background: The impact of cigarette smoke (CS) on lung diseases and the role of microbiome dysbiosis in chronic obstructive pulmonary disease (COPd) have been previously reported;however, the relationships remain unclear. Methods: Our research examined the effects of 20-week cigarette smoke (CS) exposure on the lung and intestinal microbiomes in C57BL/6JNarl mice, alongside a comparison with COPd patients’ intestinal microbiome data from a public dataset. Results: The study found that CS exposure significantly decreased forced vital capacity (FVC), thickened airway walls, and induced emphysema. Increased lung damage was observed along with higher lung keratinocyte chemoattractant (KC) levels by CS exposure. Lung microbiome analysis revealed a rise in Actinobacteriota, while intestinal microbiome showed significant diversity changes, indicating dysbiosis. Principal coordinate analysis highlighted distinct intestinal microbiome compositions between control and CS-exposed groups. In the intestinal microbiome, notable decreases in Patescibacteria, Campilobacterota, defferibacterota, Actinobacteriota, and desulfobacterota were observed. We also identified correlations between lung function and dysbiosis in both lung and intestinal microbiomes. Lung interleukins, interferon-ɣ, KC, and 8-isoprostane levels were linked to lung microbiome dysbiosis. Notably, dysbiosis patterns in CS-exposed mice were similar to those in COPd patients, particularly of Global Initiative for Chronic Obstructive Lung disease (GOLd) stage 4 patients. This suggests a systemic impact of CS exposure. Conclusion: In summary, CS exposure induces significant dysbiosis in lung and intestinal microbiomes, correlating with lung function decline and injury. These results align with changes in COPd patients, underscoring the important role of microbiome in smoke-related lung diseases. © The Author(s) 2024.

关键词： Cigarette smoke Emphysema Inflammation Intestine Lung Microbiome

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Enhancement of Channel Capacity in 5G Ultra dense Network-UdN 2

Enhancement of Channel Capacity in 5G Ultra Dense Network-UD...

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2nd International Conference on Edge Computing and Applications, ICECAA 2023

作者： Rastogi, Ritesh Shanthi, T. Kumar Naik, Pramod Sheela, M. Sahaya Mishra, A.K. Nandhini, T.J. Delhi India Paavai Engineering College Department of Ece Chennai India Dayananda Sagar University Departmeny of Computer Science Engineering Bangalore India Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Department of Ece Chennai India Dhofar University Math Unit Foundation Program Salalah Oman Chennai India

ISBN: (纸本)9798350347579

A 5G ultra dense network architecture makes use of a high density of micro cell base stations to provide increased coverage, capacity, and performance for 5G communication systems. This is accomplished by the utilization of a very densely packed network. A 5G ultradense network is another name for this particular category of network. Ultradense networks are built to overcome the limitations of ordinary cellular networks. This is accomplished by increasing the number of base stations that are located inside a given area. This is performed by reducing the coverage area provided by each base station, which ultimately leads to an increase in the capacity of the entire network. The maximum data rate or capacity that may be obtained through a certain wireless channel is referred to as the 'channel capacity' in a 5G ultradense network, when the phrase 'channel capacity' is used. One possibility is that this represents the maximum quantity of data that can be transmitted across the channel. These criteria, which represent the capabilities of the channel, can be used to evaluate the performance of channels and equipment on 5G networks. This article presents for further research a model for improving the channel capacity of the 5G ultradense network. The model can be found at the end of the article. This change will result in an increase in both the usefulness of the channel and the amount of bandwidth that it consumes;both of these aspects will improve. The fact that it uses a very small quantity of energy and power in compared to other methods is the major trait that sets it apart from other methods. This technology is superior to others in terms of both the amount of data it can communicate and the amount of electricity it consumes in the process. © 2023 IEEE.

关键词： Energy efficiency

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diversity and Suitability of the State-of-the-Art Wearable and Wireless EEG Systems Review

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IEEE Journal of Biomedical and Health Informatics 2023年第8期27卷 3830-3843页

作者： He, Congying Chen, Yu-Yi phang, Chun-Ren Stevenson, Cory Chen, I-Ping Jung, Tzyy-Ping Ko, Li-Wei Institute of Bioinformatics and Systems Biology National Yang Ming Chiao Tung University Hsinchu30010 Taiwan Institute of Applied Arts National Yang Ming Chiao Tung University Hsinchu30010 Taiwan International Ph.D. Program in Interdisciplinary Neuroscience National Yang Ming Chiao Tung University Hsinchu30010 Taiwan Institute for Neural Computation and Institute of Engineering in Medicine University of California San DiegoCA90093 United States National Yang Ming Chiao Tung University Hsinchu30010 Taiwan Institute of Electrical and Control Engineering Department of Electronics and Electrical Engineering Department of Biological Science and Technology National Yang Ming Chiao Tung University Hsinchu30010 Taiwan Department of Biomedical Science and Environment Biology Drug Development and Value Creation Research Center Kaohsiung Medical University Kaohsiung80708 Taiwan

Wireless electroencephalography (EEG) systems have been attracting increasing attention in recent times. Both the number of articles discussing wireless EEG and their proportion relative to general EEG publications have increased over years. These trends indicate that wireless EEG systems could be more accessible to researchers and the research community has recognized the potential of wireless EEG systems. To explore the development and diverse applications of wireless EEG systems, this review highlights the trends in wearable and wireless EEG systems over the past decade and compares the specifications and research applications of the major wireless systems marketed by 16 companies. For each product, five parameters (number of channels, sampling rate, cost, battery life, and resolution) were assessed for comparison. Currently, these wearable and portable wireless EEG systems have three main application areas: consumer, clinical, and research. To address this multitude of options, the article also discussed the thought process to find a suitable device that meets personalization and use cases specificities. These investigations suggest that low-price and convenience are key factors for consumer applications, wireless EEG systems with FdA or CE-certification may be more suitable for clinical settings, and devices that provide raw EEG data with high-density channels are important for laboratory research. This article presents an overview of the current state of the wireless EEG systems specifications and possible applications and serves as a guide point as it is expected that more influential and novel research will cyclically promote the development of such EEG systems. © 2023 IEEE.

关键词： Electroencephalography

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ROBUST FEATURE LEARNING AGAINST NOISY LABELS

arXiv

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arXiv 2023年

作者： Tai, Tsung-Ming Jhang, Yun-Jie Hwang, Wen-Jyi Free University of Bozen-Bolzano Italy NVIDIA AI Technology Center Taiwan International Intercollegiate Ph.D. Program National Tsing Hua University Taiwan Department of Computer Science and Information Engineering National Taiwan Normal University Taiwan

Supervised learning of deep neural networks heavily relies on large-scale datasets annotated by high-quality labels. In contrast, mislabeled samples can significantly degrade the generalization of models and result in memorizing samples, further learning erroneous associations of data contents to incorrect annotations. To this end, this paper proposes an efficient approach to tackle noisy labels by learning robust feature representation based on unsupervised augmentation restoration and cluster regularization. In addition, progressive self-bootstrapping is introduced to minimize the negative impact of supervision from noisy labels. Our proposed design is generic and flexible in applying to existing classification architectures with minimal overheads. Experimental results show that our proposed method can efficiently and effectively enhance model robustness under severely noisy labels. Copyright © 2023, The Authors. All rights reserved.

关键词： Image classification

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Self-Healable Sandfish Scale-Inspired Scalable Triboelectric Layer for Hybrid Energy Harvesting in desert Environment

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Small 2024年第4期21卷 e2404637页

作者： Chen, An-Rong Parashar, Parag Sharma, Manish Kumar Shih, Jing-Siang Yeh, Hsuan-Yu Lin, Yen-Jui Kaswan, Kuldeep Fan, Kai-Po Chen, Po-Yu Lin, Zong-Hong Department of Materials Science and Engineering National Tsing Hua University Hsinchu30013 Taiwan Department of Biomedical Engineering National Taiwan University Taipei10617 Taiwan Institute of Biomedical Engineering National Tsing Hua University Hsinchu30013 Taiwan International Intercollegiate Ph.D. Program National Tsing Hua University Hsinchu30013 Taiwan

In deserts, sedimentation from frequent dust activities on solar cells poses a substantial technical challenge, reducing efficiency and necessitating advanced cost-inefficient cleaning mechanisms. Herein, a novel sandfish scale-inspired self-healing fluorinated copolymer-based triboelectric layer is directly incorporated on top of the polysilicon solar cell for sustained hybrid energy harvesting. The transparent biomimetic layer, with distinctive saw-tooth microstructured morphology, exhibits ultra-low sand adhesion and high abrasion-resistant properties, inhibits sedimentation deposition on solar cells, and concurrently harvests kinetic energy from wind-driven sand particles through triboelectric nanogenerator (TENG). The film exhibits a low friction coefficient (0.149), minimal sand adhesion force (27 nN), and a small wear area (327 µm2). In addition, over 2 months, a solar cell with the sandfish scale-inspired structure demonstrates only a 16% decline in maximum power output compared to the bare solar cell, which experiences a 60% decline. Further, the sandfish scale-based TENG device's electrical output is fully restored to its original value after a 6-h self-healing cycle and maintains consistent stable outputs. These results highlight the exceptional advantages of employing biomimetic self-healing materials as robust triboelectric layers, showcasing sustained device stability and durability for prolonged use in harsh desert environments, ultimately contributing to a low cost-of-electricity generation paradigm. © 2024 Wiley-VCH GmbH.

关键词： Nanogenerators

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