http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
Ci-Wen Luo(Ci-Wen Luo),Yu-Hsiang Kuan(Yu-Hsiang Kuan),Wen-Ying Chen(Wen-Ying Chen),Chun-Jung Chen(Chun-Jung Chen),Frank Cheau-Feng Lin(Frank Cheau-Feng Lin ),Stella Chin-Shaw Tsai(Stella Chin-Shaw Tsa 한국역학회 2023 Epidemiology and Health Vol.45 No.-
OBJECTIVES: This cohort study investigated the correlation between Parkinson’s disease (PD) risk and chronic obstructive pulmonary disease (COPD) risk under particulate matter with an aerodynamic diameter ≤2.5 μm (PM2.5) exposure. METHODS: Data from the National Health Research Institutes of Taiwan were used in this study. The Environmental Protection Administration of Taiwan established an air quality monitoring network for monitoring Taiwan’s general air quality. COPD was indicated by at least 3 outpatient records and 1 hospitalization for COPD. After the implementation of age, sex, and endpoint matching at a 1:4 ratio, 137 patients and 548 patients were included in the case group and control group, respectively. Based on the 2005 World Health Organization (WHO) standards, monthly air particle concentration data were classified into the following 4 groups in analyses of exposure–response relationships: normal level, and 1.0, 1.5, and 2.0 times the WHO level ([concentration ≥2]×25 μg/m3×number of exposure months). RESULTS: A multivariate logistic regression revealed that the 1.0 and 1.5 WHO level groups did not significantly differ from the normal level group, but the 2.0 WHO level did (odds ratio, 4.091; 95% confidence interval, 1.180 to 14.188; p=0.038). CONCLUSIONS: Elevated PM2.5 concentrations were significantly correlated with an increased risk of PD among patients with COPD. Furthermore, exposure to high PM2.5 levels can further increase the risk of PD.
Damage evaluation of seismic response of structure through time-frequency analysis technique
Chen, Wen-Hui,Hseuh, Wen,Loh, Kenneth J.,Loh, Chin-Hsiung Techno-Press 2022 Structural monitoring and maintenance Vol.9 No.2
Structural health monitoring (SHM) has been related to damage identification with either operational loads or other environmental loading playing a significant complimentary role in terms of structural safety. In this study, a non-parametric method of time frequency analysis on the measurement is used to address the time-frequency representation for modal parameter estimation and system damage identification of structure. The method employs the wavelet decomposition of dynamic data by using the modified complex Morlet wavelet with variable central frequency (MCMW+VCF). Through detail discussion on the selection of model parameter in wavelet analysis, the method is applied to study the dynamic response of both steel structure and reinforced concrete frame under white noise excitation as well as earthquake excitation from shaking table test. Application of the method to building earthquake response measurement is also examined. It is shown that by using the spectrogram generated from MCMW+VCF method, with suitable selected model parameter, one can clearly identify the time-varying modal frequency of the reinforced concrete structure under earthquake excitation. Discussions on the advantages and disadvantages of the method through field experiments are also presented.
The Neural-Network Approach to Recognize Defect Pattern in LED Manufacturing
Chen, Wen-Chin,Tsai, Chih-Hung,Hsu, Shou-Wen The Korean Society for Quality Management 2006 The Asian Journal on Quality Vol.7 No.3
This paper presents neural network-based recognition system for automatic light emitting diode (LED) inspection. The back-propagation neural network (BPNN) is proposed and tested. The current-voltage (I-V) characteristic data of LED from the inspection process is used for the network training and testing. This study selects 300 random samples as network training and employs 100 samples as network testing. The experimental results show that if the classification work is done well, the accuracy of recognition is 100%, and the testing speed of the proposed recognition system is almost one half faster than the traditional inspection system does. The proposed neural-network approach is successfully demonstrated by real data sets and can be effectively developed as a recognition system for a practical application purpose.
Wen-Chin Chen,Denni Kurniawan 한국정밀공학회 2014 International Journal of Precision Engineering and Vol. No.
This paper presents a two stage optimization system to find optimal process parameters of multiple quality characteristics in plasticinjection molding. Taguchi method, Back-Propagation Neural Network (BPNN), Genetic Algorithm (GA), and combination of ParticleSwarm Optimization and Genetic Algorithm (PSO-GA) are used in this study to find optimum parameter settings. Melt temperature,injection velocity, packing pressure, packing time, and cooling time are selected as initial process parameters in the experiment. First,experimental work is conducted using Taguchi orthogonal array. According to the result from the Taguchi experiment, S/N ratio iscalculated to find the best combination settings for product quality. Then, ANOVA is used to determine significant factors of the controlparameters. Moreover, the S/N ratio predictor and quality predictor are constructed using BPNN. In the first stage optimization, S/Nratio predictor and GA are used to reduce variance of quality characteristic. In the second stage optimization, the S/N ratio predictorand quality predictor with hybrid PSO-GA are used to find optimal parameter settings for quality characteristic and stability ofthe process. Finally, three confirmation experiments are conducted to assess the effectiveness of the proposed system. Uponoptimization, it is seen that the proposed system not only improves the quality of plastic parts, but also reduces variability of theprocess effectively.
Enhancement of Aggregation-Induced Emission in Dye-Encapsulating Polymeric Micelles for Bioimaging
Wu, Wen-Chung,Chen, Ching-Yi,Tian, Yanqing,Jang, Sei-Hum,Hong, Yuning,Liu, Yang,Hu, Rongrong,Tang, Ben Zhong,Lee, Yi-Ting,Chen, Chin-Ti,Chen, Wen-Chang,Jen, Alex K.-Y. WILEY-VCH Verlag 2010 Advanced Functional Materials Vol.20 No.9
<P>Three amphiphilic block copolymers are employed to form polymeric micelles and function as nanocarriers to disperse hydrophobic aggregation-induced emission (AIE) dyes, 1,1,2,3,4,5-hexaphenylsilole (HPS) and/or bis(4-(N-(1-naphthyl) phenylamino)-phenyl)fumaronitrile (NPAFN), into aqueous solution for biological studies. Compared to their virtually non-emissive properties in organic solutions, the fluorescence intensity of these AIE dyes has increased significantly due to the spatial confinement that restricts intramolecular rotation of these dyes and their better compatibility in the hydrophobic core of polymeric micelles. The effect of the chemical structure of micelle cores on the photophysical properties of AIE dyes are investigated, and the fluorescence resonance energy transfer (FRET) from the green-emitting donor (HPS) to the red-emitting acceptor (NPAFN) is explored by co-encapsulating this FRET pair in the same micelle core. The highest fluorescence quantum yield (∼62%) could be achieved by encapsulating HPS aggregates in the micelles. Efficient energy transfer (>99%) and high amplification of emission (as high as 8 times) from the NPAFN acceptor could also be achieved by spatially confining the HPS/NPAFN FRET pair in the hydrophobic core of polymeric micelles. These micelles could be successfully internalized into the RAW 264.7 cells to demonstrate high-quality fluorescent images and cell viability due to improved quantum yield and reduced cytotoxicity.</P> <B>Graphic Abstract</B> <P>Highly efficient fluorescence probes are achieved through the encapsulation of aggregation-induced emission molecules, 1,1,2,3,4,5-hexaphenylsilole (HPS) and/or bis(4-(N-(1-naphthyl) phenylamino)-phenyl)fumaronitrile (NPAFN) in the core of polymeric micelles. Bright fluorescence cell images are shown with tunable colors of green directly from HPS aggregates and red through efficient fluorescence resonance energy transfer (FRET) from HPS aggregates to NPAFN aggregates. <img src='wiley_img_2010/1616301X-2010-20-9-ADFM200902043-content.gif' alt='wiley_img_2010/1616301X-2010-20-9-ADFM200902043-content'> </P>
Developing a Data Model of Product Manufacturing Flow for an IC Packaging WIP System
Lin, Long-Chin,Chen, Wen-Chin,Sun, Chin-Huang,Tsai, Chih-Hung The Korean Society for Quality Management 2005 The Asian Journal on Quality Vol.6 No.3
The IC packaging industry heavily relies on shop floor information, necessitating the development of a model to flexibly define shop floor information and timely handle manufacturing data. This study presents a novel data model of product manufacturing flow to define shop floor information to effectively respond to accelerated developments in IC package industry. The proposed data model consists of four modules: operation template setup, general process setup, enhanced bill of manufacture (EBOMfr) setup, and work-order process setup. The data model can flexibly define the required shop floor information and decision rules for shop floor product manufacturing flow, allowing one to easily adopt changes of the product and on the shop floor. However, to handle floor dynamics of the IC packaging industry, this work also proposes a WIP (i.e. work-in-process) system for monitoring and controlling the product manufacturing flow on the shop floor. The WIP system integrates the data model with a WIP execution module. Furthermore, an illustrative example, the MIRL WIP System, developed by Mechanical Industrial Research Laboratories of Industrial Technology Research Institute, demonstrates the effectiveness of the proposed model.
Chin-Sheng Huang,Su-Wen Kuo,Chia-Cheng Chen 한국증권학회 2010 Asia-Pacific Journal of Financial Studies Vol.39 No.4
The minimum price variation on the Taiwan Stock Exchange reduced for most price categories on March 1, 2005. The present paper simultaneously examines the institutional and endogenous impacts of tick size changes on transaction costs, market liquidity, and trading activity. The empirical evidence suggests that following a reduction in tick size, uniform declines are discernible in transaction costs and market liquidity. In particular, those stocks with a larger relative tick size reduction, higher trading volume, and higher order handling cost components have greater reductions in spread and market depth. Moreover, endogenous tick size reductions have an adverse effect on the trading activity for low-price stocks, due to the relative disadvantage in explicit transaction costs. Finally, the present study observes a general diminution in trade size resulting from a reduction in tick size in the Taiwan Stock Exchange. This study attributes plausible rationales to the fact that after tick size reductions, informed traders employ a smaller trade size to hide private information, or front-runners place a smaller trade size to avoid market turbulence.