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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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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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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 hydrophilic poly(oxyethylene)-diamine (POE2000) and amphiphilic PIB-POE-PIB copolymer at different weight ratios. The adjustment of the surface hydrophilicity and hydrophobicity 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 hydrophilic Staphylococcus aureus and hydrophobic Escherichia coli, respectively. The SERS-detection results suggest that the LOd of hydrophilic Staphylococcus aureus and hydrophobic 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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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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Enhanced deep Learning Model Performance in 3d Multimodal Brain Tumor Segmentation with Gabor Filter 10

Enhanced Deep Learning Model Performance in 3D Multimodal Br...

引用

10th International Conference on Applied System Innovation, ICASI 2024

作者： Ahmad, Nisar Chen, Yao-Tien International Ph.D. Program in Innovative Technology of Biomedical Engineering and Medical Devices Ming Chi University of Technology New Taipei City Taiwan

ISBN: (纸本)9798350394924

Medical image segmentation plays a crucial role in identifying and analyzing anatomical structures in medical images. This requires an accurate medical segmentation tool to delineate and quantitatively analyze the target regions, diagnose any abnormality, and assist in treatment planning. deep learning approaches have emerged as a promising solution for automating medical segmentation. However, challenges arise when dealing with the complex shapes and spatial variations of some target regions, especially in 3d MRI scans. To deal with such transformations, specific techniques are required to properly analyze and preprocess the dataset and perform image filtering to provide better features for improved prediction performance of deep learning architectures. This study focuses on improving brain tumor segmentation in multimodal 3d MRI images. We observed significant improvements in multimodal brain tumor segmentation results (accuracy, IoU, and mIoU) using an optimized 3d Gabor filter, which helps extract meaningful features. Multichannel input images were preprocessed to remove noise and select an appropriate resolution to reduce computational complexity. An improvement in mean Intersection over Union (mIoU) from 0.714 to 0.804 and accuracy from 0.982 to 0.991 were achieved, which shows a major improvement. This work contributes to the field of medical image segmentation by offering an improved and efficient approach for brain tumor analysis in 3d MRI scans, potentially aiding in diagnosis and treatment planning. © 2024 IEEE.

关键词： Magnetic resonance imaging

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Integration of the PEMFC with a hydrogen production device adopting sodium borohydride and metal cobalt catalyst

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International Journal of Hydrogen Energy 2024年第PartB期52卷 905-916页

作者： Chang, Pai-Chun Lai, Jyun-Lin Huang, Ching-His Kuan, Yean-der Department of Refrigeration and Air Conditioning and Energy Engineering National Chin-Yi University of Technology 411 Taichung Taiwan Ph.D. Program Intelligent Machinery and Smart Manufacturing National Chin-Yi University of Technology 411 Taichung Taiwan

Hydrolysis technology that releases hydrogen from chemical hydrogen storage materials is a method to produce hydrogen. Hydrogen storage has excellent development potential and is also one of the sources of large amounts of hydrogen. A sodium borohydride hydrogen production experiment was carried out based on steam hydrolysis technology. The system reaction tank is divided into a water-carrying bed and a catalyst bed. A mixed aqueous solution with a concentration of 1 wt% sodium hydroxide (NaOH) + 10 wt% sodium borohydride (NaBH4) was used for the hydrogen production reaction test. These experiments determined the appropriate aqueous solution and water vapor combination, and optimal parameters for hydrogen production. The hydrogen production catalyst powder, blend ratio, different steel ball ratios, and ball milling time at the steam hydrogen production end will all affect the powder's fineness and hydrogen production stability. Under catalyst temperature control, the by-products solidify at a specific temperature, which affects the gas passage and causes blockage. Increasing the hydrogen production in an aqueous solution requires a Co2+/Al2O3 catalyst, or a temperature control method to catalyze hydrogen production to obtain stable hydrogen production suitable for emergencies without hydrogen storage containers. This experiment built a hydrogen production system combined with a fuel cell for power generation testing. The test process and results indicate whether the aqueous solution and steam technology can be an effective solution when the hydrolysis hydrogen production technology is matched. © 2023 Hydrogen Energy Publications LLC

关键词： Hydrogen production

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design and fabrication of composite current collector used in 2-cell stacks for portable power generator

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International Journal of Hydrogen Energy 2024年 54卷 294-304页

作者： Wang, Chong-Kai Kuan, Yean-der Ph.D. Program Intelligent Machinery and Smart Manufacturing National Chin-Yi University of Technology Taichung411 Taiwan Department of Refrigeration and Air Conditioning and Energy Engineering National Chin-Yi University of Technology Taichung411 Taiwan

This study designed a planar carbon fiber composite collector plate with excellent conductivity and mechanical strength for use in the proton exchange membrane fuel cell (PEMFC). The collector plate is made of phenolic resin mixed with conductive particles such as graphite powder, and coated onto carbon fiber cloth. After the solvent is allowed to evaporate, the prepreg is cut and stacked layer by layer into a mold for the heat pressing process at 150 °C. The resin in the carbon fiber prepreg cloth is cured into a carbon fiber composite board. A computer numerical control (CNC) engraving machine was used to engrave the carbon fiber composite board into the current collector shape. The carbon fiber composite current collectors were placed into a high temperature furnace for the carbonization process. The resin between the carbon fibers is removed by the high temperature to increase conductivity. The carbon fiber composite collectors were assessed for conductivity, mechanical strength, and performance. Afterwards, a planar two cell fuel cell stack was assembled for testing performance and stability. A printed circuit board (PCB) was used to design the circuit and the planar two cell fuel cell module made using the heat pressing process. The planar two cell module was combined with a small hydrogen storage tank to form a portable power generation device. © 2023 Hydrogen Energy Publications LLC

关键词： Carbon fibers

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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-phase 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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Evaluating cooling tube effects on defect formation and distribution in Czochralski crystal growth

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Journal of Materials science: Materials in Electronics 2024年第19期35卷 1315页

作者： Huang, Yi-Jen dezfoli, Amir Reza Ansari Department of Chemical and Materials Engineering National Chin-Yi University of Technology Taichung41170 Taiwan Department of Intelligent Automation Engineering National Chin-Yi University of Technology Taichung Taiwan Ph.D. Program at Graduate Institute of Precision Manufacturing National Chin-Yi University of Technology Taichung Taiwan

The quality of silicon ingots is paramount in semiconductor manufacturing as defects profoundly influence the crystal integrity and device performance. This study investigates the impact of cooling-tube configurations on defect formation during the Czochralski process. Comprehensive modeling and simulation elucidated the intricate relationship between the presence of a cooling tube and the evaluation of point defects within silicon ingots. The results show that cooling tubes augment the axial temperature gradient and shift the point-defect behavior from vacancy-rich to interstitial-dominated regions with an increase in the axial temperature gradient of up to 1.6 times. Additionally, cooling tubes impede the formation of agglomerated defects by reducing point-defect mobility and propagation time, resulting in a reduction of the agglomerated defect count by up to 30% compared to processes without cooling tubes. Experiments validated the simulation findings, demonstrating a notable decrease in agglomerated defect counts. These insights underscore the potential of optimized cooling-tube designs for enhancing semiconductor device performance and manufacturing yield, thereby driving progress in electronics and beyond. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Agglomeration

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