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International Conference on Applied System Innovation (ICASI)

作者： Yun-Qi Li Hsuan-Jung Chen Hsi-Wen Yang Chih-Yuan Chen Shao-Fu Chang Ssu-Ying Chen Chien-Chon Chen College of Engineering and Science Ph.D. Program in Materials and Chemical Engineering National United University Miaoli Taiwan Department of Chemistry Michigan State University MI USA Department of Materials Engineering National United University Miaoli Taiwan Graduate Institute of Intellectual Property National Taipei University of Technology Taiwan Department of Energy Engineering National United University Miaoli Taiwan

ISBN: (数字)9798350394924

ISBN: (纸本)9798350394931

For how to store and transport hydrogen, the first thought is to store hydrogen directly in the cylinder. However, this method is not desirable, because generally at least 700 atm high pressure, the hydrogen contained in the cylinder to be useful. Therefore it is very unsafe at such high pressures. In This paper, we design and production of a new generation of solid-state hydrogen storage and discharge container. The goal of “development of solid-state hydrogen storage technology” is to break through the bottlenecks of hydrogen storage technology safety, hydrogen storage density, high-efficiency hydrogen absorption and release, transportation safety, and engineering practice.

关键词： Technological innovation Hydrogen storage Temperature Surface resistance Hydrogen Transportation Production

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A Review on Analytical Approaches for Ambient Ozone Open data in Taiwan

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Current Pollution Reports 2024年第3期10卷 374-386页

作者： Nguyen, duy-Hieu Liao, Chih-Hsiang Bui, Xuan-Thanh Yuan, Chung-Shin Lin, Chitsan Ph.D. Program in Maritime Science and Technology College of Maritime National Kaohsiung University of Science and Technology Kaohsiung Taiwan (R.O.C.) Department of Environmental Engineering and Science Chia-Nan University of Pharmacy and Science Tainan Taiwan (R.O.C.) Key Laboratory of Advanced Waste Treatment Technology & Faculty of Environment and Natural Resources Ho Chi Minh City University of Technology (HCMUT) Ho Chi Minh City Vietnam Vietnam National University Ho Chi Minh City (VNU-HCM) Ho Chi Minh City Vietnam Institute of Environmental Engineering National Sun Yat-Sen University Kaohsiung Taiwan (R.O.C.) Department of Marine Environmental Engineering National Kaohsiung University of Science and Technology Kaohsiung Taiwan (R.O.C.)

The air quality in Taiwan is significantly impacted by ambient ozone (O3) pollution, which poses a challenge in terms of control due to the involvement of precursors and influencing factors in its ph.tochemical process. This review investigates the measures that have been implemented in Taiwan over the past two decades to address this issue and evaluate their effectiveness in reducing O3 concentrations. Furthermore, it highlights relevant studies that have employed advanced methods to examine the O3 problem. Comprehending the complex formation of O3 and its driving factors is crucial in efficiently managing O3 pollution. Nevertheless, accurately quantifying the impacts of these factors can be challenging due to their interconnections. To bridge this gap in knowledge, conducting a robust causality analysis becomes imperative to accurately quantify the causal influence of major factors. Furthermore, eliminating seasonal variations can improve the precision and accuracy of trend analyses concerning long-term changes in O3 concentrations. deep learning, in particular, holds significant advantages in predicting O3 concentrations as it can capture non-linear and long-term memory characteristics effectively. In summary, attaining acceptable O3 levels in Taiwan is challenging due to its geograph.cal location, which makes it susceptible to air pollution from both local sources as well as distant upwind areas. The utilization of advanced methods is essential for comprehensively studying the evolution of O3 and formulating effective mitigation measures. While there is a necessity to develop new analytical methods, implementing existing robust methodologies can also provide valuable insights into the dynamics and impacts of O3. By leveraging these approaches, we can enhance our comprehension of O3 pollution in Taiwan and develop effective strategies to mitigate its harmful effects on air quality.

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Smart Residential Parking

Smart Residential Parking

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International Conference on Informatics and Computational sciences (ICICoS)

作者： Suhartono Jung-Lung Chiang Maria Mahardini Sakanti C. Bambang dwi Kuncoro Ph.D. Program Prospective Technology of Electrical Engineering and Computer Science National Chin-Yi University of Technology Taichung Taiwan R.O.C Graduate Institute of Precision Manufacturing National Chin-Yi University of Technology Taichung Taiwan R.O.C Department of Refrigeration Air Conditioning and Energy Engineering National Chin-Yi University of Technology Taichung Taiwan R.O.C

ISBN: (数字)9798350375886

ISBN: (纸本)9798350375893

This research aims to create a smart residential system that will improve parking management in residential areas using mini-server technology. Another aim is to provide a safe and effective smart parking solution for residential areas with limited capacity. This research method uses mini-server technology and control to create smart system ideas. Apart from that, this research also uses servo motor technology, proximity sensors, cameras, and IoT applications for smart parking management. The result is the creation of intelligent residential parking management, which uses a Raspberry Pi 5 Model B as a server and control to improve the parking management system in residential areas, and the use of number plate recognition technology to be applied to Smart City. This further research offers a new perspective on creating intelligent parking solutions using two input validation parameters simultaneously, namely facial and license plate recognition

关键词： Smart cities Automated parking Servers Security Internet of Things Usability Servomotors

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Applications of Floquet-Magnus and Fer Expansion Approaches during Cross Polarization Radiation in Solid State NMR

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Journal of Modern ph.sics 2023年第7期14卷 1136-1156页

作者： Eugene Steph.ne Mananga Thibault Charpentier Program of Physics & Ph. D Program of Chemistry Graduate Center The City University of New York New York NY USA Department of Applied Physics New York University Brooklyn New York USA Department of Engineering Physics and Technology BCC The City University of New York Bronx New York USA CEA IRAMIS Service Interdisciplinaire sur les Systèmes Moléculaires et Matériaux LSDRM UMR CEA/CNRS Gif-sur-Yvette

This paper investigates the concept of Cross Polarization (CP) experiment in addition to revisiting the two potential expansion schemes recently developed in the field of solid-state nuclear magnetic resonance (SSNMR): namely, the Floquet-Magnus expansion and the Fer expansion. We use the aforementioned expansion schemes for the calculation of effective Hamiltonians and propagators when the spin system undergoes Cross Polarization radiation. CP is the gateway experiment into SSNMR. An in-depth comprehension of the underlying mechanics of spin dynamics during the cross-polarization experiment is pivotal for further experimental developments and optimization of more complex solid-state NMR experiments. The main contribution of this work is a prospect related to spin ph.sics;particularly regarding to generalization of the calculation. This work reports original yet interesting novel ideas and developments that include calculations performed on the CP experiment. In fact, the approach presented could play a major role in the interpretation of several fine NMR experiments in solids, which would in turn provide significant new insights in spin ph.sics. The generality of the work points towards potential applications in problems related in solid-state NMR and theoretical developments of spectroscopy as well as interdisciplinary research areas as long as they include spin dynamics concepts.

关键词： Cross Polarization Solid-State NMR Floquet-Magnus Expansion Fer Expansion Spin dynamics

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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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Export- and import-based economic models for predicting global trade using deep learning

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Expert Systems with Applications 2023年 218卷

作者： Yang, Cheng-Hong Lee, Cheng-Feng Chang, Po-Yin Department of Information Management Tainan University of Technology Tainan City710302 Taiwan Department of Electronic Engineering National Kaohsiung University of Science and Technology Kaohsiung80778 Taiwan Drug Development and Value Creation Research Center Kaohsiung Medical University Kaohsiung80708 Taiwan Ph. D. Program in Biomedical Engineering Kaohsiung Medical University Kaohsiung80708 Taiwan School of Dentistry Kaohsiung Medical University Kaohsiung80708 Taiwan Department of Business Administration National Kaohsiung University of Science and Technology Kaohsiung80778 Taiwan Department of Computer Science and Information Engineering National Quemoy University Kinmen County 892 Taiwan

Forecasting global foreign trade is essential for developing government trade policies and management strategies for multinational corporations. However, achieving an accurate trade forecast is challenging because of the complex structural relationships between exports, imports and other economic variables. Many traditional forecasting models, such as time series, econometric, and machine learning, provide less accurate forecasts for trade data. This paper proposes an ensemble learning approach to improve forecasting performance by hybridizing the structural relationships between trade and deep learning models to predict foreign trade for ten major countries. The proposed method first establishes a cointegration relationship between exports and imports and their structural variables. The cointegrated models are then used to predict the future of trade, which is used as a benchmark model for comparison. A hybrid deep learning algorithm uses the cointegrated variables as input variables to predict trade data, and then are compared with time-series forecasts and economic structural models. The experimental results reveal that the ensemble learning method can achieve excellent forecasting performance for the tested periods of trade data. In most cases, the root means square error and mean absolute percentage error values are smaller than the time series and economic structural models. © 2023 Elsevier Ltd

关键词： Forecasting

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Characterization of VOCs during diesel oil composting process

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Bioresource technology Reports 2023年 22卷

作者： Lin, Tachen Kuo, Shulung Hussain, Adnan Chen, Zhigui Huang, Manlin Lin, Chitsan School of Food and Chemical Engineering Liuzhou Institute of Technology Guangxi Liuzhou545000 China Kelee Environmental Consultants Corporation Kaohsiung City806040 Taiwan Ph.D. Program of Aquatic Science and Technology National Kaohsiung University of Science and Technology Kaohsiung811213 Taiwan Continental Water Engineering Corporation Taipei City103018 Taiwan School of Food Science and Engineering Beibu Gulf University Guangxi Qinzhou535011 China Department of Marine Environmental Engineering National Kaohsiung University of Science and Technology Kaohsiung City811213 Taiwan

By composting kitchen waste, deisel-contaminated soil was treated and volatile organic compound (VOC) emissions were assessed. Composting kitchen waste reduces contamination volume due to gas emissions. An aerobic treatment period of 12 days was conducted for the measurements of VOC emissions from different ph.ses, such as gaseous, solid, and leachate, were conducted throughout the experiment. The results show that VOC concentrations were high during the mesoph.lic ph.se and reduced with increasing temperature during the composting period. It has been observed that at least 314 VOCs have been detected during the mesoph.lic, thermoph.lic, and cooling ph.ses. Compost odor was mainly caused by NH3, methanethiol, carbon disulfide, dimethyl sulfide, and dimethyl disulfide, and most of these compounds appeared in thermoph.lic ph.se. Furthurmore, emissions of VOCs from composting kitchen waste reduces total diesel concentration in the soil to achieve a green and clean environment. © 2023 Elsevier Ltd

关键词： Gas emissions

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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 ph.ng, 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 electroenceph.lograph. (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： Electroenceph.lograph.

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design of sonochemical assisted synthesis of Zr-MOF/g-C3N4-modified electrode for ultrasensitive detection of antipsychotic drug chlorpromazine from biological samples

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Microchimica Acta 2024年第4期191卷 182-182页

作者： Ashkar, M.A. Kutti Rani, S. Vasimalai, N. Kuo, Chih-Yu Yusuf, Kareem Govindasamy, Mani Department of Chemistry B.S. Abdur Rahman Crescent Institute of Science and Technology Vandalur Chennai600 048 India Department of Chemical Engineering & amp Biotechnology National Taipei University of Technology Taipei10608 Taiwan International Ph.D. Program in Innovative Technology of Biomedical Engineering and Medical Devices Ming Chi University of Technology New Taipei City243303 Taiwan Department of Chemistry College of Science King Saud University Riyadh11451 Saudi Arabia Department of Research and Innovation Saveetha School of Engineering SIMATS Chennai6021055 India Research Center for Intelligence Medical Devices Ming Chi University of Technology New Taipei City243303 Taiwan

The rapid fabrication is described of binary electrocatalyst based on a highly porous metal–organic framework with zirconium metal core (Zr-MOF) decorated over the graph.tic carbon nitride (g-C3N4) nanosheets via facile ultrasonication method. It is used for the robust determination of antipsychotic drug chlorpromazine (CLP) from environmental samples. The electrochemical behaviour of 2d Zr-MOF@g-C3N4 was characterized by cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) studies. The crystalline and porous nature of the composite was characterized by XRd and SEM analysis. The functional groups and surface characteristics were investigated by FT-IR, Raman and XPS. The major electrochemical properties of the Zr-MOF@g-C3N4 composite towards CLP detection were analyzed by CV, chronocoulometric (CC), chronoamperometric (CA) and differential pulse voltammetry (dPV) techniques. The composite exhibits a low detection limit (LOd) of 2.45 nM with a linear range of 0.02 to 2.99 µM and attractive sensitivity for CLP. The sensor system shows higher selectivity towards the possible interferences of CLP drug and exhibits better repeatability and stability. Finally, the fabricated sensor system shows a high recovery range varying from 96.2 to 98.9% towards the real samples. The proposed electrochemical probe might be a promising alternative to the prevailing diagnostic tools for the detection of CLP. Graph.cal Abstract: (Figure presented.) © The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature 2024.

关键词： Cyclic voltammetry

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Sensing property of Ga2O3-based extended-gate field-effect transistors for a living cell viability sensor

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Sensors and Actuators A: ph.sical 2023年 349卷

作者： Chou, Hsin-Yu Chiang, Jung-Lung Yu, Chang-Tze Ricky Chen, Jo-Mei Maureen Wuu, dong-Sing Department of Materials Science and Engineering National Chung Hsing University Taichung40227 Taiwan Ph.D. Program Prospective Technology of Electrical Engineering and Computer Science National Chin-Yi University of Technology Taichung411030 Taiwan Department of Applied Chemistry National Chi-Nan University Nantou54561 Taiwan Department of Applied Materials and Optoelectronic Engineering National Chi Nan University Nantou54561 Taiwan

In this study, gallium oxide (Ga2O3) nanorods were deposited onto an indium tin oxide (ITO) glass substrate to develop a real-time living cell viability sensor. Ga2O3 nanorods had characteristics of cell population sensing based on cellular metabolism to detect cell viability. The ph.sensing characteristics of Ga2O3-based extended-gate field-effect transistors (EGFETs) with and without the annealing process were measured from ph.1–11. Three different sensor heads, ITO/glass, GaOOH/ITO/glass, and Ga2O3/ITO/glass, were produced as EGFETs and immersed into a ph.standard buffer and high-glucose dulbecco's modified Eagle's medium (dMEM) to investigate hydrogen ion sensing. Results showed that the Ga2O3/ITO/glass probe had the best hydrogen ion sensing sensitivity and stability in different sample buffers. In contrast, GaOOH/ITO/glass had instability and lower sensitivity due to interference with other components in the medium. The drift characteristic of sensors was analyzed to detect long-term stability. The Ga2O3/ITO/glass probe showed lower drift properties, which can potentially monitor the dMEM situation in real-time for a long-term period. during in vitro detection, the Ga2O3/ITO/glass probe revealed a 70 μA/cells change in IdS-VdS analysis and a 10 μV/cells change in IdS-VGS analysis, which was superior linearly dependent within 10,000 cells. The biocompatibility of the Ga2O3/ITO/glass probe was also detected by 3-(4,5-dimethylthiazol-2-yl)− 2,5-diph.nyltetrazolium bromide assay and showed no cytotoxicity. Overall, the Ga2O3/ITO/glass EGFET sensor has potential applications as a living cell viability device in microenvironmental studies in the future. © 2022 Elsevier B.V.

关键词： Nanorods

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