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Boost dC-dC converter with regenerative snubber

Energy Reports 2024年 12卷 798-819页

作者： Yau, Yeu-Torng 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

To accommodate the wide range of input voltages supplied by redundant batteries and ensure an adequate hold-up time for communication systems during utility power failures, power supplies used in 5 G base stations typically include a front-end boost converter as the first stage and a second-stage isolated converter. In this paper, a new topology for a regenerative snubber in boost converters is proposed. Compared to traditional active or passive snubber topologies, the proposed snubber offers the advantages of having fewer components and occupying less space. Moreover, it does not require additional active devices and can be driven by widely-used commercial PWM control integrated circuits, achieving a higher level of cost-effectiveness and offering increased industrial applications. The final prototype of a power supply for a networking switch hub (as used in 5 G base stations) is fabricated to demonstrate the feasibility of the proposed method. © 2024 The Authors

关键词： Topology

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The Indoor People Tracking and Counting System

The Indoor People Tracking and Counting System

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2023 International Automatic Control Conference, CACS 2023

作者： Lin, Hao-Pu Han, Chin-Chuan Liao, Jun-Wei Ciou, Chong-Han Hong, Yi-Cheng Tan, Ming-Lun National United University Ph. D. Program in Material and Chemical Engineering MiaoLi Taiwan National United University Department of Computer Science and Information Engineering MiaoLi Taiwan

ISBN: (纸本)9798350306354

COVId-19 outbreaks and becomes serious from 2019 winter. Taking body temperature, wearing masks, recording footprint and avoiding crowds become important tasks and require a lot of manpower support for the prevention of the epidemic in every. In this study, we have integrated the infrared thermometer devices to measure people temperature and the people identities through RGB images at the entrance of buildings. Using the computer vision and deep learning methods, we would like to build a 24/7 and region-wide coverage assistance system to automatically record the footprint of a specific people in the building. We also detect if people taking off their masks in the yard at any time. The processing videos are grabbed from the existing CCTV systems. The developed system also locates the crowd and calculate the number of people in a specified area, and the manager can know the number of people and control the access in real time. It will reduce the burden of manpower. In addition, we have optimized the system performance to handle multiple camera videos and to reduce the hardware cost at the same time. © 2023 IEEE.

关键词： Access control

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Boost dC-dC Converter with Non-dissipative Snubber

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IEEJ Transactions on Electrical and Electronic engineering 2024年第11期19卷 1858-1878页

作者： Yau, Yeu-Torng Department of Ph.D. Program Prospective Technology of Electrical Engineering and Computer Science National Chin-Yi University of Technology Taichung No.57 Sec. 2 Zhongshan Rd. Taiping Dist Taichung41170 Taiwan

To provide a hold-up time function in dC-dC supplies for cell site stations or data centers, using a boost converter with a bulk output capacitor as a front-end converter stage is a simple and highly cost-effective solution. However, conventional boost converters with a hard-switching operation result in low conversion efficiency and increased electromagnetic interference emissions. In this paper, a boost converter with a new non-dissipative snubber is proposed that only requires two additional diodes, an inductor, and a multilayer ceramic capacitor. The main feature of the proposed snubber is that the components are not located on the main power processing path. This means they only require low ratings, improving cost-effectiveness. A prototype converter is analyzed, realized, and applied to a 300 W redundant dC-dC power supply module for a 5G cell base station. © 2024 The Author(s). IEEJ Transactions on Electrical and Electronic engineering published by Institute of Electrical Engineers of Japan and Wiley Periodicals LLC. © 2024 The Author(s). IEEJ Transactions on Electrical and Electronic engineering published by Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

关键词： Boost converter

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Application of a Self-Assembly Sensing Layer to Grating Sensor Cabinets for Biomedical Sensing of Rheumatoid Arthritis Antigen-Antibodies

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IEEE Sensors Journal 2024年第7期24卷 10039-10047页

作者： Wen, Hsin-Yi Hsu, Hsiang-Cheng Feng, Wen-Kai Jhan, Kai-Siang Yeh, Yao-Tsung Chiang, Chia-Chin National Kaohsiung University of Science and Technology Department of Chemical and Materials Engineering Kaohsiung80778 Taiwan National Kaohsiung University of Science and Technology College of Maritime Department of Ph.D. Program in Maritime Science and Technology Kaohsiung807618 Taiwan National Kaohsiung University of Science and Technology Department of Mechanical Engineering Kaohsiung80778 Taiwan Fooyin University Department of Medical Laboratory Science and Biotechnology Kaohsiung83102 Taiwan

In this article, we harnessed biomedical applications in laser-assisted etching long-period fiber gratings (LLPFGs) sensors, subsequently deploying them within the realm of biomedical applications. The primary aim of this study was to devise a sensitive method for the detection of antigen-antibodies associated with rheumatoid arthritis (RA) using LLPFGs. Sensing the antigen binding took place on the surface of the optical fiber through a self-assembling process. Given the inherent limitations of conventional rheumatoid factor (RF) testing in terms of specificity, we introduced an innovative serum-based approach geared toward the identification of anti-cyclic citrullinated peptide (Anti-CCP) antibodies. This method exhibited an impressive diagnostic accuracy rate of approximately 80% for RA cases, coupled with an exceptional specificity level of 98% for individuals without RA. The incorporation of LLPFGs in the detection of RA antigen-antibodies presents a highly promising avenue for enhancing the precision and reliability of RA diagnosis. Furthermore, this research aligns closely with the United Nations Sustainable development Goal (SdG)3, which strives to promote well-being across all age groups and advance sustainable development by addressing health-related challenges, including the accurate diagnosis of diseases like RA. © 2023 IEEE.

关键词： Antibodies

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dual modifications of sensitizers and lanthanide ions on a two-dimensional zirconium-based metal-organic framework for ph.toluminescent detection

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CrystEngComm 2024年第22期26卷 2852-2861页

作者： Chang, Jhe-Wei Lin, Tzu-Chi Chen, You-Liang Han, Po-Chun Yang, Shang-Cheng Tsai, Meng-dian Wu, Kevin C.-W. Kung, Chung-Wei Department of Chemical Engineering National Cheng Kung University Tainan City70101 Taiwan Department of Chemical Engineering National Taiwan University Taipei10617 Taiwan Ph. D. Program of Green Materials and Precision Devices College of Engineering National Taiwan University Taipei10617 Taiwan Department of Chemical Engineering and Materials Science Yuan Ze University Chung-Li Taoyuan320 Taiwan

A two-dimensional (2d) zirconium-based metal-organic framework (Zr-MOF) with abundant terminal -OH/-OH2 groups on its nodes, ZrBTB (BTB = 1,3,5-tris(4-carboxyph.nyl)benzene), is utilized as a platform for dual post-synthetic modifications (PSM) to immobilize both the benzoph.none-based ph.tosensitizer (benzoph.none-4,4′-dicarboxylate, bzpdc) and terbium ions onto the 2d Zr-MOF molecular sheets. Terbium ions are installed on the 2d Zr-MOF at various temperatures to adjust the loading of terbium ions on the 2d Zr-MOF while preserving the loading of the ph.tosensitizer. The crystallinity, morph.logy, porosity, and loadings of both bzpdc ligands and terbium ions are characterized for each material, and the coordinating locations of terbium ions in the Zr-MOF structure are investigated. The ph.toluminescence (PL) properties of these materials are then examined. Since the installed bzpdc ligand can induce a highly efficient energy transfer to the neighbouring terbium ion upon excitation, the obtained material after dual PSM (ZrBTB-bzpdc-Tb-120) can show strong PL emissions of terbium ions upon the excitation of the bzpdc ligand at 355 nm, with a PL quantum yield of 5.04%. It is more advantageous than the 2d Zr-MOF solely functionalized with terbium ions, which can only exhibit similar emissions upon the excitation of the BTB linker at a less friendly wavelength of 310 nm, with a lower PL quantum yield of 2.94%. Owing to the high chemical stability as well as good dispersity of the luminescent ZrBTB-bzpdc-Tb-120 in water, its performances in selective PL sensing of Fe(iii) ions present in aqueous solutions are investigated. © 2024 The Royal Society of Chemistry.

关键词： Carboxylation

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Flexible nanohybrid substrates utilizing gold nanocubes/nano mica platelets with 3d lightning-rod effect for highly efficient bacterial biosensors based on surface-enhanced Raman scattering

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Journal of Materials Chemistry B 2024年第13期12卷 3226-3239页

作者： Chen, Yan-Feng Lu, Ming-Chang Lee, Chia-Jung Chiu, Chih-Wei Department of Materials Science and Engineering National Taiwan University of Science and Technology Taipei10607 Taiwan Ph.D. Program in Clinical Drug Development of Herbal Medicine College of Pharmacy Taipei Medical University Taipei11031 Taiwan

In this study, gold nanocubes (AuNCs) were quickly synthesized using the seed-mediated growth method and reduced onto the surface of two-dimensional (2d) delaminated nano mica platelets (NMPs), enabling the development of AuNCs/NMPs nanohybrids with a 3d lightning-rod effect. First, the growth-solution amount can be changed to easily adjust the AuNCs average-particle size within a range of 30-70 nm. The use of the cationic surfactant cetyltrimethylammonium chloride as a protective agent allowed the surface of AuNCs and nanohybrids to be positively charged. Positively charged nanohybrid surfaces presented a good adsorption effect for detecting molecules with negative charges on the surface. Additionally, the NMP surfaces were rich in ionic charges and provided a large specific surface area for stabilizing the growth of AuNCs. delaminated AuNCs/NMPs nanohybrids can generate a 3d hotspot effect through self-assembly to enhance the Raman signal. Surface-enhanced Raman scattering (SERS) is highly sensitive in detecting adenine biomolecules. Its limit of detection (LOd) and Raman enhancement factor reached 10−9 M and 3.6 × 108, respectively. Excellent reproducibility was obtained owing to the relatively regular arrangement of AuNC particles, and the relative standard deviation (RSd) was 10.7%. Finally, the surface of NMPs was modified by adding the hydroph.lic poly(oxyethylene)-diamine (POE2000) and amph.ph.lic PIB-POE-PIB copolymer at different weight ratios. The adjustment of the surface hydroph.licity and hydroph.bicity of AuNCs/NMPs nanohybrids led to better adsorption and selectivity for bacteria. AuNCs/POE/NMPs and AuNCs/PIB-POE-PIB/NMPs were further applied to the SERS detection of hydroph.lic Staph.lococcus aureus and hydroph.bic Escherichia coli, respectively. The SERS-detection results suggest that the LOd of hydroph.lic Staph.lococcus aureus and hydroph.bic Escherichia coli reached 92 CFU mL−1 and 1.6 × 102 CFU mL−1, respectively. The AuNCs/POE/NMPs and AuNCs/P

关键词： Substrates

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Recommendation of Resource Allocation decision Based on Bipartite Graph.Network Structure

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IEIE Transactions on Smart Processing and Computing 2025年第1期14卷 128-139页

作者： Pei, Wen Pan, Wen-An Huang, Jui-Chan College of Management Chung Hua University Hsinchu30012 Taiwan Ph.D Program of Management Chung Hua University Hsinchu30012 Taiwan Department of Industrial Engineering and Management National Kaohsiung University of Science and Technology Kaohsiung807618 Taiwan

In resource allocation decisions in business, fully understanding customers’ needs and preferences helps to maximise benefits. As a result, in the modern business environment, the design of customized recommendation systems has gained a lot of attention. To this end, the study designs a recommendation algorithm for resource allocation decision based on improved two-part graph.network structure. In this algorithm, an improved K-means clustering algorithm is introduced to deeply mine potential information. The calculation of similarity between users is also optimised to assist the target user to find the real neighbouring users. The findings demonstrate that, in comparison to the other algorithms, the resource allocation recommendation algorithm based on improved bipartite graph.suggested in the study has a greater hit rate. The hit rate of the suggested algorithm can reach 32.5% when the recommendation list length is 10, which is a 21.5% improvement over the collaborative filtering algorithm. The suggested algorithm’s popularity is only 39.1, which is 69.3 less than the collaborative filtering algorithm when the suggestion list length is 10. Furthermore, the suggested algorithm for resource allocation decision-making created by the research has a greater recommendation accuracy, more personalization, and diversity, as seen by the proposed algorithm’s mean Hamming distance of 0.976. Through an improved bipartite graph.network, the algorithm can fully analyze the historical preference information of users, effectively capture the complex relationship between users and products, generate personalized recommendation lists, and improve user satisfaction and purchase conversion rates. It provides an effective recommendation role for resource allocation decisions in modern business and helps to create greater economic benefits. © 2025 Institute of Electronics Engineers of Korea. All rights reserved.

关键词： Collaborative filtering

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Machine-learning-based sampling inspection under OQC capacity for real-time quality monitoring in the TFT-LCd industry

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International Journal of Production Research 2025年第6期63卷 2090-2113页

作者： Shih, Ming-Sung Chen, James C. Chen, Tzu-Li Chiang, Chih-Hsiung Hsu, Ching-Lan International Intercollegiate Ph.D. Program National Tsing Hua University Hsinchu Taiwan Department of Industrial Engineering and Engineering Management National Tsing Hua University Hsinchu Taiwan Graduate Institute of Intelligent Manufacturing Technology National Taiwan University of Science and Technology Taipei Taiwan Division of Quality Control AUO Corporation Taichung Taiwan

In the thin film transistor-liquid crystal display (TFT-LCd) industry, the competition is fierce, and the external failure cost is high. To improve the quality of released products, sampling inspection under outgoing quality control (OQC) is conducted before products are released. Owing to the variety and complexity of inspection items, the task must be carried out manually while realising automation is difficult. Traditional random sampling inspection is limited by sampling quantity, manpower, and material resources. To effectively improve acceptable quality levels, this paper proposes a quality predictive monitoring framework tailored to the production and inspection characteristics of the TFT-LCd industry. This framework includes real-time automatic quality monitoring based on an optimal machine learning prediction model with two-ph.se feature creation, and it also addresses OQC inspection capacity constraints. Experimental results show the prediction performance based on proposed model is better than the traditional random sampling process. In practice, superior average outgoing quality improves by more than 70% at the same sampling level. In addition, the features of the process can be further controlled and managed based on the prediction model to monitor the key parameters in real time and respond to abnormalities quickly, thereby further improving the quality of released products. © 2024 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Liquid crystal displays

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deep-Learning Approach for An Analysis of Real-estate Prices and Transactions

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IEEE Access 2025年 13卷 89248-89265页

作者： Yang, Cheng-Hong Lee, Borcy Lin, Yu-da Tainan University of Technology Department of Information Management Tainan Taiwan National Kaohsiung University of Science and Technology Department of Electronic Engineering Kaohsiung Taiwan Kaohsiung Medical University Ph.D. Program in Biomedical Engineering Kaohsiung Taiwan Kaohsiung Medical University School of Dentistry Kaohsiung Taiwan Kaohsiung Medical University Drug Development and Value Creation Research Center Kaohsiung Taiwan National Penghu University of Science and Technology Department of Computer Science and Information Engineering Penghu Taiwan

Research on the study of houses, condominiums and buildings in Taiwan’s metropolitan areas continues to be an important area of research. In real estate forecasting and analysis, methods such as statistical analysis and questionnaire data collection are widely used. However, when multidimensional data is considered, these methods are time-consuming and inadequate. This study aimed to build a real estate forecasting model that can adapt to a changing environment. data were collected from public government databases, the collected data were standardized for accurate clustering, an appropriate data clustering algorithm was applied to the standardized data, and cross-statistical analysis was performed to verify the adopted algorithm. We used a deep learning based on autoencoder algorithm to increase the accuracy of the clustering analysis. A double-bottom map particle swarm optimization (dBM-PSO) clustering algorithm was then used to determine the optimal clustering solution. Cluster analysis and deep learning were conducted on data collected from public websites to understand the factors that led to the sustained increase in housing prices in Taiwan over the past decade. The results of this study indicate that three key factors—the number of real estate transactions, the average unit price of real estate transactions, and the building material and construction index—significantly affected real estate prices in Taiwan. Our results could help researchers and governments to focus on specific aspects of real estate development without being influenced by other related factors. In addition, the relationships between real estate trends and the aforementioned three key factors were determined to obtain valuable information that can enable the Taiwanese government to regulate the property market and prevent excessive growth. The framework proposed in this paper allows researchers and governments to focus on specific aspects of real estate development without being influenced b

关键词： Houses

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Students Learning Performance and Engagement in a Visual programming Environment

Students Learning Performance and Engagement in a Visual Pro...

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Proceedings of the 6th International Conference on Innovative Technologies and Learning, ICITL 2023

作者： Wen, Fu-Hsiang Wu, Tienhua Hsu, Wei-Chih Ph.D. Program in Engineering Science and Technology College of Engineering National Kaohsiung University of Science and Technology Kaohsiung Taiwan Department of Management Air Force Institute of Technology Kaohsiung Taiwan Department of Computer and Communication Engineering National Kaohsiung University of Science and Technology Kaohsiung Taiwan

ISBN: (纸本)9783031401121

This study employed a quasi-experimental method to explore differences in students’ learning performance and engagement between visual and textual language programming environments. Specifically, this study examined how strongly engagement dimensions affect participants’ learning achievement in a Scratch experimental setting. One hundred and thirty-two undergraduate students participated. The results revealed that participants with Scratch intervention outperformed those with text-based language instructions in terms of performance and behavioral, emotional, cognitive, and agentic engagement. The findings indicated that engagement significantly predicted student academic success in a visual learning environment. This study concluded that visual programming tools such as Scratch help novices engaged and effectively learn core aspects of programming concepts. Additionally, student engagement deepens an understanding of predictions of programmers’ behaviors and achievements and mechanisms behind the effectiveness of visualization intervention. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Students

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