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168 results on '"Chen, Chih-Lin"'

1. Comparing Low- or Standard-Dose Alteplase in Endovascular Thrombectomy: Insights From a Nationwide Registry

Author

Chen, Chih-Hao, Lee, Chung-Wei, Hsieh, Yi-Chen, Lin, Chun-Jen, Chen, Yu-Wei, Lin, Kuan-Hung, Sung, Pi-Shan, Tang, Chih-Wei, Chu, Hai-Jui, Tsai, Kun-Chang, Chou, Chao-Liang, Lin, Ching-Huang, Wei, Cheng-Yu, Yen, Shang-Yih, Chen, Po-Lin, Yeh, Hsu-Ling, Chan, Lung, Sung, Sheng-Feng, Lee, Meng, Liu, Hon-Man, Lin, Yen-Heng, Lee, I-Hui, Yeh, Shin-Joe, Lien, Li-Ming, Chiou, Hung-Yi, Lee, Jiunn-Tay, Tang, Sung-Chun, Jeng, Jiann-Shing, Tang, Sung-Chun, Jeng, Jiann-Shing, Lee, Chung-Wen, Chen, Chih-Hao, Lin, Yen-Heng, Yeh, Shin-Joe, Lee, Bo-Ching, Chung, Tai-Chun, Lin, Chun-Jen, Lee, I-Hui, Chi, Nai-Fang, Hsu, Li-Chi, Chung, Chih-Ping, Liu, Hung-Yu, Luo, Chao-Bao, Chang, Feng-Chi, Lin, Chung-Jung, Wu, Chia-Hung, Yu, Kai-Wei, Hwang, Hsuen-En, Lin, Te-Ming, Chen, Yu-Wei, Chen, Chi-Jen, Wang, Ching-Yi, Kuo, Yeh-Lin, Lu, Ping-Sheng, Chao, Yen-Tung, Su, Yi-Hsin, Lin, Pei-Ju, Chen, Yi-Chun, Fan, Li-Ling, Yang, Ju-Fang, Lin, Kuan-Hung, Lin, Chien-Jen, Yang, Sheng-Hsiang, Yang, Chun-Ming, Lin, Huey-Juan, Yeh, Poh-Shiow, Chang, Chia-Yu, Cheng, Tian-Junn, Lee, Wei-Jia, Ko, Ching-Chung, Tsui, Yu-Kun, Shih, Yun-Ju, Wu, Te-Chang, Sung, Pi-Shan, Chang Chun-Min Wang, Yu-Ming, Huang, Chih-Yuan, Chen, Chih-Hung, Hsieh, Meng-Tsang, Ou, Chang-Hsien, Lin, Wan-Ching, Chen, Li-Ching, Ann, Bi-Shin, Tang, Chih-Wei, Lai, Yen-Jun, Huang, Lih-Wen, Kuo, Ya-Ling, Peng, Szu-Hsiang, Pai Lin, Yi-Chun, Chu, Hai-Jui, Lin, Cheng-Huai, Sun, Yu, Lu, Chien-Jung, Lee, Chun-Yu, Liu, Chang-Hsiu, Tsai, Kun-Chang, Chen, Kuo-Wei, Tsai, Li-Kai, Hsiue, Yen-Chung, Cheng, Ya-Wen, Fu, Chuan-Hsiu, Chen, Wen-Yu, Chou, Chao-Liang, Po, Helen L., Lin, Ya-Ju, Hwang, Yung-Pin, Kuo, Shu-Fan, Huang, Chun-Chao, Jhou, Zong-Yi, Yu, Hui-Fen, Lin, Hsiao-Chu, Wei, Cheng-Yu, Chen, Chih-Lin, Wu, Pei-han, Tsai, Yi-Ching, Yen, Shang-Yih, Lee, Jiunn-tay, Chou, Chung-Hsing, Ko, Chien-An, Chen, Po-Lin, Tsuei, Yuang-Seng, Chen, Wen-Hsien, Liao, Nien-Chen, Liaw, Yeng-Fung, Yeh, Hsu-Ling, Lien, Li-Ming, Hsiao, Chen-Yu, Lin, Kuan-Yu, Yang, Tsui-Hua, Chan, Lung, Chen, Jia-Hung, Yu, Shun-Fan, Su, I-Chang, Lu, Yueh-Hsun, Sung, Sheng-Feng, Yang, Tzu-Hsien, Hsu, Yung-Chu, Su, Yu-Hsiang, Hung, Ling-Chien, Lin, Mao-Hsun, Su, Chien-Yu, Liu, Hon-Man, Huang, Yung-Chuan, Wan, Chih-Cheng, Lin, Ching-Huang, Yen, Cheng- Chang, Shih, Ching-Sen, Lin, Chun-Shien, Lee, Meng, Tsai, Yuan-Hsiung, Huang, Yen-Chu, Hung, Wei-Tse, and Lee, Jiann-Der

Published
2024
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5. Automatic manpower allocation for public construction projects using a rough set enhanced neural network

Author

Chen, Jieh-Haur, Yang, Li-Ren, Wang, Jui-Pin, Lin, Shang-I, Cheng, Jiun-Yao, Lee, Meng-Hsueh, and Chen, Chih-Lin

Subjects
Industrial project management -- Methods, Project management -- Methods, Neural networks -- Usage, Construction workers -- Management, Neural network, Company business management, Engineering and manufacturing industries
Abstract

Accurate estimates of manpower are still heavily dependent on well-experienced personnel. The objectives of this study are to prove the feasibility of using rough set theory to classify and weigh the impact attributes, and to develop a model to assess the total quantities of labor needed for a construction project using a rough set enhanced artificial neural network (ANN). Experts suggest 14 attributes that influence the estimation of on-site manpower for construction projects. After trimming and analyzing the basic data, the rough set approach is used to classify and weigh the attributes into three levels of impact based on their frequency. A rough set enhanced ANN is accordingly developed that yields an accuracy rate of 91.903%, higher than that of a regular ANN. A practical and effective prediction model benefits personnel having to estimate on-site manpower needs for construction projects. Key words: prediction, manpower, construction project, rough set, artificial neural network (ANN). Les estimations precises de la main-d'oeuvre dependent encore fortement d'un personnel experimente. Les objectifs de cette etude sont de prouver la faisabilite d'utiliser la theorie des ensembles bruts pour classer et ponderer les attributs d'impact, et de developper un modele pour evaluer les quantites totales de travail necessaires pour un projet de construction utilisant un reseau de neurones artificiels (RNA) ameliore. Les experts suggerent 14 attributs qui influent sur l'estimation de la main-d'oeuvre sur place pour les projets de construction. Apres avoir reduit et analyse les donnees de base, l'approche des ensembles bruts est utilisee pour classer et ponderer les attributs en trois niveaux d'impact en fonction de leur frequence. Un RNA ameliore par un ensemble brut est donc developpe qui donne un taux de precision de 91,903 %, superieur a celui d'un RNA regulier. Un modele de prevision pratique et efficace est avantageux pour le personnel qui doit estimer les besoins en main-d'oeuvre sur place pour les projets de construction. [Traduit par la Redaction] Mots-cles : prevision, main-d'oeuvre, projet de construction, ensemble brut, reseau de neurones artificiels (RNA)., Introduction Manpower is always one of the most important keys to the successful completion of a construction project. It comprises one of the largest proportions of most project budgets and [...]

Published
2021
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9. Renal function is associated with 1-month and 1-year mortality in patients with ischemic stroke

Author

Liu, Chung-Hsiang, Tsai, Chon-Haw, Huang, Wei-Shih, Lu, Chung-Ta, Tsai, Tzung-Chang, Tseng, Chun-Hung, Lin, Kang-Hsu, Shyu, Woei-Cherng, Yang, Yu-Wan, Liu, Yen-Liang, Cho, Der-Yang, Chen, Chun-Chung, Jeng, Jiann-Shing, Tang, Sung-Chun, Tsai, Li-Kai, Yeh, Shin-Joe, Chen, Chih-Hao, Tsai, Hsin-Hsi, Li, Jie-Yuan, Chen, Han-Jung, Lu, Kan, Hsu, Shih-Pin, Kuo, Hung-Chang, Tsou, Jung-Chi, Wang, Yan-Tang, Tai, Yi-Cheng, Hsieh, Meng-Tsang, Liliang, Po-Chao, Liang, Cheng-Loong, Wang, Hao-Kuang, Tsai, Yu-Tun, Wang, Kuo-Wei, Chen, Jui-Sheng, Chen, Po-Yuan, Wang, Yi-Ching, Chen, Chih-Hung, Sung, Pi-Shan, Hsieh, Han-Chieh, Su, Hui-Chen, Chiu, Hou-Chang, Lien, Li-Ming, Chen, Wei-Hung, Bai, Chyi-Huey, Huang, Tzu-Hsuan, Lau, Chi-Ieong, Wu, Ya-Ying, Yeh, Hsu-Ling, Chang, Anna, Lin, Ching-Huang, Yen, Cheng-Chang, Lin, Ruey-Tay, Chen, Chun-Hung, Khor, Gim-Thean, Chao, A-Ching, Lin, Hsiu-Fen, Huang, Poyin, Lin, Huey-Juan, Ke, Der-Shin, Chang, Chia-Yu, Yeh, Poh-Shiow, Lin, Kao-Chang, Cheng, Tain-Junn, Chou, Chih-Ho, Yang, Chun-Ming, Shen, Hsiu-Chu, Chen, An-Chih, Tsai, Shih-Jei, Lu, Tsong-Ming, Kung, Sheng-Ling, Lee, Mei-Ju, Chou, Hsi-Hsien, Chang, Wei-Lun, Chiu, Pai-Yi, Hsu, Min-Hsien, Chan, Po-Chi, Pan, Chau-Hsiung, Shoung, Hai-Ming, Lo, Yi-Chen, Wang, Fu-Hwa, Chang, Wei-Chieh, Lai, Ta-Chang, Yin, Jiu-Haw, Wang, Chung-Jen, Wang, Kai-Chen, Chen, Li-Mei, Denq, Jong-Chyou, Sun, Yu, Lu, Chien-Jung, Lin, Cheng-Huai, Huang, Chieh-Cheng, Liu, Chang-Hsiu, Chan, Hoi-Fong, Lee, Siu-Pak, Sun, Ming-Hui, Ke, Li-Ying, Chen, Po-Lin, Lee, Yu-Shan, Sung, Sheng-Feng, Ong, Cheung-Ter, Wu, Chi-Shun, Hsu, Yung-Chu, Su, Yu-Hsiang, Hung, Ling-Chien, Lee, Jiunn-Tay, Lin, Jiann-Chyun, Hsu, Yaw-Don, Peng, Giia-Sheun, Hsu, Chang-Hung, Lin, Chun-Chieh, Yen, Che-Hung, Cheng, Chun-An, Sung, Yueh-Feng, Chen, Yuan-Liang, Lien, Ming-Tung, Chou, Chung-Hsing, Liu, Chia-Chen, Yang, Fu-Chi, Wu, Yi-Chung, Tso, An-Chen, Lai, Yu- Hua, Chiang, Chun-I., Tsai, Chia-Kuang, Liu, Meng-Ta, Lin, Ying-Che, Hsu, Yu-Chuan, Chiang, Tsuey-Ru, Huang, Pai-Hao, Liao, Pin-Wen, Lee, Mei-Ching, Chen, Jen-Tse, Lie, Sian-King, Sun, Mu-Chien, Hsiao, Pi-Ju, Chen, Wei-Liang, Chen, Ta-Cheng, Chang, Chen-Shu, Lai, Chien-Hsu, Chuang, Chieh-Sen, Chen, Yen-Yu, Lin, Shinn-Kuang, Su, Yu-Chin, Shiao, Jen-Lun, Yang, Fu-Yi, Liu, Chih-Yang, Chiang, Han-Lin, Chen, Guei-Chiuan, Hsu, Po-Jen, Chang, Chun-Yuan, Lin, I.-sheng, Chien, Chung-Hsien, Chang, Yang-Chuang, Chen, Ping-Kun, Hsiao, Yu-Jen, Fang, Chen-Wen, Chen, Yu-Wei, Lee, Kuo-Ying, Lin, Yun-Yu, Li, Chen-Hua, Tsai, Hui-Fen, Hsieh, Chuan-Fa, Yang, Chih-Dong, Liaw, Shiumn-Jen, Liao, How-Chin, Yeh, Shoou-Jeng, Wu, Ling-Li, Hsieh, Liang-Po, Lee, Yong-Hui, Chen, Chung-Wen, Hsu, Chih-Shan, Jhih, Ye-Jian, Zhuang, Hao-Yu, Pan, Yan-Hong, Shih, Shin-An, Chen, Chin-I., Sung, Jia-Ying, Weng, Hsing-Yu, Teng, Hao-Wen, Lee, Jing-Er, Huang, Chih-Shan, Chao, Shu-Ping, Yuan, Rey-Yue, Sheu, Jau-Jiuan, Yu, Jia-Ming, Ho, Chun-Sum, Lin, Ting-Chun, Yu, Shih-Chieh, Chen, Jiunn-Rong, Tsai, Song-Yen, Wei, Cheng-Yu, Hung, Chao-Hsien, Lee, Chia Fang, Yang, Sheng-Kung, Chen, Chih-Lin, Lin, Wei, Tseng, Hung-Pin, Liu, Chin-Hsiung, Lin, Chun-Liang, Lin, Hung-Chih, Chen, Pi-Tzu, Hu, Chaur-Jong, Chan, Lung, Chi, Nai-Fang, Chern, Chang-Ming, Lin, Chun-Jen, Wang, Shuu-Jiun, Hsu, Li-Chi, Wong, Wen-Jang, Lee, I-Hui, Yen, Der-Jen, Tsai, Ching-Piao, Kwan, Shang-Yeong, Soong, Bing-Wen, Chen, Shih-Pin, Liao, Kwong-Kum, Lin, Kung-Ping, Chen, Chien, Shan, Din-E., Fuh, Jong-Ling, Wang, Pei-Ning, Lee, Yi-Chung, Yu, Yu-Hsiang, Huang, Hui-Chi, Tsai, Jui-Yao, Wu, Ming-Hsiu, Chiang, Szu-Yi, Wang, Chiung-Yao, Hsu, Ming-Chin, Chen, Chien-Chung, Yeh, Po-Yen, Tsai, Yu-Tai, Wang, Ko-Yi, Chen, Tsang-Shan, Hsieh, Cheng-Yang, Chen, Wei-Fen, Yip, Ping-Keung, Wang, Vinchi, Wang, Kaw-Chen, Tsai, Chung-Fen, Chen, Chao-Ching, Liu, Yi-Chien, Chen, Shao-Yuan, Zhao, Zi-Hao, Wei, Zhi-Peng, Wu, Shey-Lin, Liu, Ching-Kuan, Lin, Ryh-Huei, Chu, Ching-Hua, Yan, Sui-Hing, Lin, Yi-Chun, Chen, Pei-Yun, Hsiao, Sheng-Huang, Yip, Bak-Sau, Tsai, Pei-Chun, Chou, Ping-Chen, Kuo, Tsam-Ming, Lee, Yi-Chen, Chiu, Yi-Pin, Tsai, Kun-Chang, Liao, Yi-Sheng, Tsai, Ming-Jun, Kao, Hsin-Yi, Wang, I-Kuan, Yen, Tzung-Hai, Tsai, I-Ju, Sung, Fung-Chang, and Hsu, Chung Y.

Published
2018
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11. Next‐generation pathology practices with mass spectrometry imaging.

Author

Chung, Hsin‐Hsiang, Huang, Penghsuan, Chen, Chih‐Lin, Lee, Chuping, and Hsu, Cheng‐Chih

Subjects
MATRIX-assisted laser desorption-ionization, MASS spectrometry, DESORPTION electrospray ionization, DRUG discovery, BIOMOLECULES, PATHOLOGY
Abstract

Mass spectrometry imaging (MSI) is a powerful technique that reveals the spatial distribution of various molecules in biological samples, and it is widely used in pathology‐related research. In this review, we summarize common MSI techniques, including matrix‐assisted laser desorption/ionization and desorption electrospray ionization MSI, and their applications in pathological research, including disease diagnosis, microbiology, and drug discovery. We also describe the improvements of MSI, focusing on the accumulation of imaging data sets, expansion of chemical coverage, and identification of biological significant molecules, that have prompted the evolution of MSI to meet the requirements of pathology practices. Overall, this review details the applications and improvements of MSI techniques, demonstrating the potential of integrating MSI techniques into next‐generation pathology practices. [ABSTRACT FROM AUTHOR]

Published
2023
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12. Real-time bottom-up characterization of protein mixtures enabled by online microdroplet-assisted enzymatic digestion (MAED).

Author

Ma, Cheng-Hua, Chen, Chih-Lin, and Hsu, Cheng-Chih

Subjects
*DIGESTION, *PROTEIN fractionation, *PROTEOMICS, *PROTEIN analysis, *MICRODROPLETS
Abstract

Enzymatic digestion remains one of the "rate-determining steps" in the bottom-up analysis of proteins. However, by performing digestion in microdroplets generated from electrosonic spray, the reaction could be accelerated to a timescale lower than milliseconds. Here, we describe a simple and rapid online digestion platform named online microdroplet-assisted enzymatic digestion (MAED). It involves the integration of intact protein separation with enzymatic digestion in microdroplets. Via online MAED, various protein standards, including an antibody standard, were characterized in a bottom-up manner without prior digestion, and high sequence coverages were obtained. We further extended the application of online MAED to a more complex sample, mouse brain extract, where protein identifications were successfully yielded. Compared with the conventional bottom-up approach, a more comprehensive characterization could be obtained particularly for low molecular weight proteins. In short, we provide a rapid and alternative bottom-up analysis in a top-down fashion as well as a new possibility for microdroplet chemistry. [ABSTRACT FROM AUTHOR]

Published
2023
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23. Impacts of Two-Type ENSO on Rainfall over Taiwan

Author

Chen-Chih Lin, Yi-Jiun Liou, and Shih-Jen Huang

Subjects
Meteorology. Climatology, QC851-999
Abstract

Impacts of two-type ENSO (El Niño/Southern Oscillation), canonical ENSO and ENSO Modoki, on rainfall over Taiwan are investigated by the monthly mean rainfall data accessed from Taiwan Central Weather Bureau. The periods of the two-type ENSO are distinguished by Niño 3.4 index and ENSO Modoki index (EMI). The rainfall data in variously geographical regions are analyzed with the values of Niño 3.4 and EMI by correlation method. Results show that the seasonal rainfalls over Taiwan are different depending on the effects of two-type ENSO. In canonical El Niño episode, the rainfall increases in winter and spring while it reduces in summer and autumn. On the contrary, the rainfall increases in summer and autumn but reduces in winter and spring in El Niño Modoki episode. Nevertheless, two types of La Niña cause similar effects on the rainfall over Taiwan. It increases in autumn only. The rainfall variations in different types of ENSO are mainly caused by the monsoon and topography.

Published
2015
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24. Distribution of Atmospheric Aerosol over the South China Sea

Author

Shih-Jen Huang and Chen-Chih Lin

Subjects
Meteorology. Climatology, QC851-999
Abstract

The satellite-derived aerosol optical depth (AOD) data is used to investigate the distribution of aerosol over the South China Sea (SCS). High correlation coefficients are found between in situ AERONET data and satellite AOD measurements around the SCS with the highest coefficient of 0.9 on the Dongsha Island (i.e., Pratas Island). The empirical orthogonal function (EOF) analysis of AOD over the SCS shows that high AOD is always found around offshore areas of China, Indochina, Sumatra, and Borneo. Besides, spring is the major season of occurring coarse aerosol particles (AOT_C) but fine aerosol particles (AOT_F) occur yearly. The biomass burning is found in Indochina during March and April, and so it is in Sumatra and Borneo from August to October. The results also show that the AOT_F are higher during El Niño events, but higher AOT_C are found in La Niña years.

Published
2015
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28. Next-Generation Design and Technology Co-optimization (DTCO) of System on Integrated Chip (SoIC) for Mobile and HPC Applications

Author

Chen Chih-Lin, Cheng Yun-Wei, K.-J. Chen, Douglas Yu, C.H. Tsai, Tsung-Ching Huang, M. F. Chen, C. T. Wang, F. Lee, and J. Yuan

Subjects
Reduction (complexity), Interconnection, business.product_category, Computer science, business.industry, Embedded system, Next-generation network, Stacking, Die (manufacturing), Small Outline Integrated Circuit, business, Chip
Abstract

This paper demonstrates the next-generation design and technology co-optimization (DTCO) of system on integrated chip (SoIC) for mobile and HPC applications, where the SoIC technology was proposed to integrate multichips with different functionality and technology into a single SoC chip. The new DTCO includes overall die partitioning, die integration, and interconnect. These methodologies can be used for improving time-to-market and trade-off between performance and cost. In this paper, two prototypes of stacking CPU and memory dies are demonstrated with 15% performance gain and 30% average point-to-point distance reduction.

Published
2020

31. Regional Flooding Induced by Tide and Warm Water Effects in Tuvalu

Author

Chen-Chih Lin, Chung-Ru Ho, Yu-Hsin Cheng, and and Shin-Jye Liang

Subjects
geophysics, geology, atmospheric science, space science, oceanic science, hydrology, Geology, QE1-996.5, Geophysics. Cosmic physics, QC801-809
Abstract

A statistical model for simulating flood inundation in Tuvalu is developed in this study. The model is based on the major regional inundation factors - spring tides and warm-water mass, integrated with the digital elevation. Nineteen years of sea level data from tide gauge and satellite altimetry are analyzed to predict regional flooding. Harmonic analysis is used in analyzing tidal variations to determine the major astronomical tidal constituent harmonic constants. Tidal variation prediction can be performed with these harmonic constants. The empirical mode decomposition (EMD) method is then applied to the sea level data derived from altimetry for extracting warm-water mass variation. Ninety percent of sea level data points are used for analysis, and the remaining 10% are used for testing the prediction accuracy. The sea level data derived from along-track satellite altimeter near Tuvalu is decomposed into eight modes and one local trend using the EMD method. The EMD mode periods found by fast Fourier transform (FFT) include monthly, intra-seasonally, half-yearly, yearly, bi-annually, and inter-annually oscillations. We apply these periods to harmonic analysis to predict the variations in warm-water mass. The sea level tide and warm-water mass combination predictions are compared to field measurements. The results show that the correlation coefficient is 0.988 with a root-mean-square error (RMSE) of 7.6 cm.

Published
2015
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33. Precision biomarker discovery powered by microscopy image fusion-assisted high spatial resolution ambient ionization mass spectrometry imaging

Author

Lin, Li-En, primary, Chen, Chih-Lin, additional, Huang, Ying-Chen, additional, Chung, Hsin-Hsiang, additional, Lin, Chiao-Wei, additional, Chen, Ko-Chien, additional, Peng, Yu-Ju, additional, Ding, Shih-Torng, additional, Wang, Ming-Yang, additional, Shen, Tang-Long, additional, and Hsu, Cheng-Chih, additional

Published
2020
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36. Investigation of the island-induced ocean vortex train of the Kuroshio Current using satellite imagery

Author

Po-Chun Hsu, Ming-Huei Chang, Shih Jen Huang, Chung-Ru Ho, and Chen Chih Lin

Subjects
010504 meteorology & atmospheric sciences, Meteorology, 010505 oceanography, Soil Science, Geology, 01 natural sciences, Vortex, European Remote-Sensing Satellite, Sea surface temperature, Spectroradiometer, Acoustic Doppler current profiler, Climatology, Upwelling, Satellite imagery, Satellite, Computers in Earth Sciences, 0105 earth and related environmental sciences, Remote sensing
Abstract

In this study, we used satellite imagery to conduct a statistical study of the ocean vortex train induced by the Kuroshio Current on the leeward side of Green Island, Taiwan. The spatial scale and characteristics of the ocean vortex train were analyzed using image datasets from five different high-resolution satellites, including optical imagery from the Satellite Pour l'Observation de la Terre and the Formosat-2 satellites and synthetic aperture radar imagery from the European Remote Sensing Satellite, Advanced Land Observing Satellite, and Sentinel-1. Satellite altimetry data and a moored acoustic Doppler current profiler (ADCP) were used to calculate the velocity of the Kuroshio Current. The ADCP data suggest that the velocity increases on the western side of the vortex train when it is formed on the leeward side of Green Island. Data from the moderate-resolution imaging spectroradiometer (MODIS) showed that the sea surface temperature of the recirculation water was over 2 °C colder and the chlorophyll-a concentration was two times higher than that of the surrounding waters. These phenomena suggested upwelling, mixing processes, and an island-mass effect. Wind forcing had a pronounced effect on the characteristics of the vortex train. High-resolution satellite images indicate that the averaged aspect ratio of the vortex train is 2.09 and the dimensionless width is 2.02 under southerly winds, compared to 1.91 and 2.76, respectively, under northerly winds.

Published
2017

37. Effects of Cold Eddy on Kuroshio Meander and Its Surface Properties, East of Taiwan

Author

Shih-Jen Huang, Po-Chun Hsu, Chen-Chih Lin, and Chung-Ru Ho

Subjects
Surface (mathematics), Atmospheric Science, cold eddy, 010504 meteorology & atmospheric sciences, Geophysics. Cosmic physics, 0211 other engineering and technologies, 02 engineering and technology, kuroshio meander, Atmospheric sciences, 01 natural sciences, Computers in Earth Sciences, TC1501-1800, 021101 geological & geomatics engineering, 0105 earth and related environmental sciences, Isopycnal, QC801-809, Chlorophyll-a (chl-a), Glider, Ocean engineering, Sea surface temperature, sea surface temperature (SST), Eddy, Climatology, Meander, Maximum duration, Geology
Abstract

Satellite remote-sensing data and glider data are used to study the Kuroshio meander and surface properties, east of Taiwan. The Kuroshio meandered eastward 13 times between 1993 and 2013 because of cold eddies propagating from the western Pacific. The maximum duration of the meanders was 80 days. The farthest eastward shift of the Kuroshio axis was approximately 270 km from its original position, depending on the size of the cold eddy. Cold eddies reduce the current speed at the Kuroshio axis to 84% of its seasonal average, which is approximately 0.75 m/s. According to glider data, isopycnal uplifting is produced when cold eddies impinge on the Kuroshio, and satellite observations show that the sea surface temperature (SST) drops $1{-}3\;^\circ{\text{C}}$ and that the chlorophyll-a (chl-a) concentration increases up to $0.54\text{ mg}/{\text{m}}^{3}$ .

Published
2016

39. Satellite observations of rainfall effect on sea surface salinity in the waters adjacent to Taiwan

Author

Shih Jen Huang, Po-Chun Hsu, Chung-Ru Ho, and Chen Chih Lin

Subjects
Salinity, Radiometer, Typhoon, Climatology, Special sensor microwave/imager, Precipitation, Water cycle, Rainband, WINDSAT, Geology
Abstract

Changes of oceanic salinity are highly related to the variations of evaporation and precipitation. To understand the influence of rainfall on the sea surface salinity (SSS) in the waters adjacent to Taiwan, satellite remote sensing data from the year of 2012 to 2014 are employed in this study. The daily rain rate data obtained from Special Sensor Microwave Imager (SSM/I), Tropical Rainfall Measuring Mission’s Microwave Imager (TRMM/TMI), Advanced Microwave Scanning Radiometer (AMSR), and WindSat Polarimetric Radiometer. The SSS data was derived from the measurements of radiometer instruments onboard the Aquarius satellite. The results show the average values of SSS in east of Taiwan, east of Luzon and South China Sea are 33.83 psu, 34.05 psu, and 32.84 psu, respectively, in the condition of daily rain rate higher than 1 mm/hr. In contrast to the rainfall condition, the average values of SSS are 34.07 psu, 34.26 psu, and 33.09 psu in the three areas, respectively at no rain condition (rain rate less than 1 mm/hr). During the cases of heavy rainfall caused by spiral rain bands of typhoon, the SSS is diluted with an average value of -0.78 psu when the average rain rate is higher than 4 mm/hr. However, the SSS was increased after temporarily decreased during the typhoon cases. A possible reason to explain this phenomenon is that the heavy rainfall caused by the spiral rain bands of typhoon may dilute the sea surface water, but the strong winds can uplift the higher salinity of subsurface water to the sea surface.

Published
2017

40. Optimization of Shape-Memory Effect in Fe-Mn-Si-Cr-Re Shape-Memory Alloys

Author

Cheng-Hsien Liu, Kun-Ming Lin, Jian-Hung Chen, Hsin-Chih Lin, and Chen-Chih Lin

Subjects
Materials science, chemistry, Mechanics of Materials, Mechanical Engineering, Diffusionless transformation, Metallurgy, %22">Fish , chemistry.chemical_element, Formability, General Materials Science, Shape-memory alloy, Crystal structure, Rhenium
Abstract

Fe-Mn-Si-Cr-based shape-memory alloys have excellent properties of formability, shape-memory effect, and low cost. These properties make Fe-Mn-Si-Cr SMAs ideal candidates for the application of pipe coupling and fish plates. In this study, we add slight Rhenium (Re, 0.05-0.3 wt.%) to Fe-30Mn-6Si-5Cr alloys to improve their shape-memory effect. The martensitic transformation, crystal structure, and aging precipitate of the Fe-30Mn-6Si-5Cr-Re alloys are analyzed. The optimization of shape-memory performance of Fe-30Mn-6Si-5Cr-Re alloys can be achieved efficiently by the proper combined treatments of pre-strain, aging, and shape-memory training.

Published
2014

41. Interpreting and analyzing King Tide in Tuvalu

Author

Chung-Ru Ho, Chen-Chih Lin, and Yu-Hsin Cheng

Subjects
lcsh:GE1-350, geography.geographical_feature_category, lcsh:QE1-996.5, Flooding (psychology), lcsh:Geography. Anthropology. Recreation, Atoll, Storm surge, Pacific ocean, lcsh:TD1-1066, lcsh:Geology, Oceanography, Geography, lcsh:G, Warm water, General Earth and Planetary Sciences, Tide gauge, lcsh:Environmental technology. Sanitary engineering, King tide, lcsh:Environmental sciences, Loss of life
Abstract

The spatial and temporal distribution of sea-level rise has the potential to cause regional flooding in certain areas, and low-lying island countries are severely at risk. Tuvalu, an atoll country located in the southwest Pacific Ocean, has been inundated by this regional flooding for decades. Tuvaluans call this regional flooding phenomenon King Tide, a term not clearly defined, blaming it for loss of life and property in announcing their intention to migrate. In this study, we clarified and interpreted King Tide, and analyzed the factors of King Tide in Tuvalu. Using tide gauge and topographical data, we estimated that 3.2 m could be considered the threshold of King Tide, which implied half of the island of Tuvalu was flooded with seawater. This threshold is consistent with the finding of the National Oceanic and Atmospheric Administration that King Tide events occur once or twice a year. We surveyed 28 King Tide events to analyze the factors of regional flooding. Tide gauge and satellite altimeter data from 1993 to 2012 were cross-validated and indicated that the King Tide phenomenon is significantly related to the warm-water effect. Warm water contributed to the King Tide phenomenon by an average of 5.1% and a maximum of 7.8%. The height of King Tide is affected by the combined factors of spring tide, storm surge, climate variability, and, significantly, by the warm-water effect.

Published
2014

42. Ultra-low-resistance 3D InFO inductors for integrated voltage regulator applications

Author

Victor C. Y. Chang, C. T. Wang, Alan Roth, Ying-Chih Hsu, Chen Chih-Lin, Eric Soenen, C.H. Tsai, Jeng-Shien Hsieh, and Douglas Yu

Subjects
010302 applied physics, Engineering, Form factor (electronics), business.industry, Voltage control, 020208 electrical & electronic engineering, Electrical engineering, 02 engineering and technology, Voltage regulator, Inductor, 01 natural sciences, Power (physics), Inductance, 0103 physical sciences, 0202 electrical engineering, electronic engineering, information engineering, business, Low resistance, Electrical efficiency
Abstract

A novel 3D InFO inductor is developed to integrate with TSMC 16nm FinFET devices for high efficiency integrated voltage regulator (IVR) design. The 3D InFO inductor is designed using thick through-InFO-via (TIV) copper, where the form factor is 1.4 × 2.2 × 0.15 mm3. It performs 2.14 nH inductance at 140 MHz and 3.2 mΩ resistance at DC. The resistance of power delivery network (PDN) between inductor and load is 1.1 mu. The InFO technology provides the low resistance 3D inductor and PDN concurrently for the IVR system design to achieve a peak power efficiency of 93%.

Published
2016

44. Renal function is associated with 1-month and 1-year mortality in patients with ischemic stroke

Author

Wang, I-Kuan, primary, Liu, Chung-Hsiang, additional, Yen, Tzung-Hai, additional, Jeng, Jiann-Shing, additional, Sung, Sheng-Feng, additional, Huang, Pai-Hao, additional, Li, Jie-Yuan, additional, Sun, Yu, additional, Wei, Cheng-Yu, additional, Lien, Li-Ming, additional, Tsai, I-Ju, additional, Sung, Fung-Chang, additional, Hsu, Chung Y., additional, Tsai, Chon-Haw, additional, Huang, Wei-Shih, additional, Lu, Chung-Ta, additional, Tsai, Tzung-Chang, additional, Tseng, Chun-Hung, additional, Lin, Kang-Hsu, additional, Shyu, Woei-Cherng, additional, Yang, Yu-Wan, additional, Liu, Yen-Liang, additional, Cho, Der-Yang, additional, Chen, Chun-Chung, additional, Tang, Sung-Chun, additional, Tsai, Li-Kai, additional, Yeh, Shin-Joe, additional, Chen, Chih-Hao, additional, Tsai, Hsin-Hsi, additional, Chen, Han-Jung, additional, Lu, Kan, additional, Hsu, Shih-Pin, additional, Kuo, Hung-Chang, additional, Tsou, Jung-Chi, additional, Wang, Yan-Tang, additional, Tai, Yi-Cheng, additional, Hsieh, Meng-Tsang, additional, Liliang, Po-Chao, additional, Liang, Cheng-Loong, additional, Wang, Hao-Kuang, additional, Tsai, Yu-Tun, additional, Wang, Kuo-Wei, additional, Chen, Jui-Sheng, additional, Chen, Po-Yuan, additional, Wang, Yi-Ching, additional, Chen, Chih-Hung, additional, Sung, Pi-Shan, additional, Hsieh, Han-Chieh, additional, Su, Hui-Chen, additional, Chiu, Hou-Chang, additional, Chen, Wei-Hung, additional, Bai, Chyi-Huey, additional, Huang, Tzu-Hsuan, additional, Lau, Chi-Ieong, additional, Wu, Ya-Ying, additional, Yeh, Hsu-Ling, additional, Chang, Anna, additional, Lin, Ching-Huang, additional, Yen, Cheng-Chang, additional, Lin, Ruey-Tay, additional, Chen, Chun-Hung, additional, Khor, Gim-Thean, additional, Chao, A-Ching, additional, Lin, Hsiu-Fen, additional, Huang, Poyin, additional, Lin, Huey-Juan, additional, Ke, Der-Shin, additional, Chang, Chia-Yu, additional, Yeh, Poh-Shiow, additional, Lin, Kao-Chang, additional, Cheng, Tain-Junn, additional, Chou, Chih-Ho, additional, Yang, Chun-Ming, additional, Shen, Hsiu-Chu, additional, Chen, An-Chih, additional, Tsai, Shih-Jei, additional, Lu, Tsong-Ming, additional, Kung, Sheng-Ling, additional, Lee, Mei-Ju, additional, Chou, Hsi-Hsien, additional, Chang, Wei-Lun, additional, Chiu, Pai-Yi, additional, Hsu, Min-Hsien, additional, Chan, Po-Chi, additional, Pan, Chau-Hsiung, additional, Shoung, Hai-Ming, additional, Lo, Yi-Chen, additional, Wang, Fu-Hwa, additional, Chang, Wei-Chieh, additional, Lai, Ta-Chang, additional, Yin, Jiu-Haw, additional, Wang, Chung-Jen, additional, Wang, Kai-Chen, additional, Chen, Li-Mei, additional, Denq, Jong-Chyou, additional, Lu, Chien-Jung, additional, Lin, Cheng-Huai, additional, Huang, Chieh-Cheng, additional, Liu, Chang-Hsiu, additional, Chan, Hoi-Fong, additional, Lee, Siu-Pak, additional, Sun, Ming-Hui, additional, Ke, Li-Ying, additional, Chen, Po-Lin, additional, Lee, Yu-Shan, additional, Ong, Cheung-Ter, additional, Wu, Chi-Shun, additional, Hsu, Yung-Chu, additional, Su, Yu-Hsiang, additional, Hung, Ling-Chien, additional, Lee, Jiunn-Tay, additional, Lin, Jiann-Chyun, additional, Hsu, Yaw-Don, additional, Peng, Giia-Sheun, additional, Hsu, Chang-Hung, additional, Lin, Chun-Chieh, additional, Yen, Che-Hung, additional, Cheng, Chun-An, additional, Sung, Yueh-Feng, additional, Chen, Yuan-Liang, additional, Lien, Ming-Tung, additional, Chou, Chung-Hsing, additional, Liu, Chia-Chen, additional, Yang, Fu-Chi, additional, Wu, Yi-Chung, additional, Tso, An-Chen, additional, Lai, Yu- Hua, additional, Chiang, Chun-I., additional, Tsai, Chia-Kuang, additional, Liu, Meng-Ta, additional, Lin, Ying-Che, additional, Hsu, Yu-Chuan, additional, Chiang, Tsuey-Ru, additional, Liao, Pin-Wen, additional, Lee, Mei-Ching, additional, Chen, Jen-Tse, additional, Lie, Sian-King, additional, Sun, Mu-Chien, additional, Hsiao, Pi-Ju, additional, Chen, Wei-Liang, additional, Chen, Ta-Cheng, additional, Chang, Chen-Shu, additional, Lai, Chien-Hsu, additional, Chuang, Chieh-Sen, additional, Chen, Yen-Yu, additional, Lin, Shinn-Kuang, additional, Su, Yu-Chin, additional, Shiao, Jen-Lun, additional, Yang, Fu-Yi, additional, Liu, Chih-Yang, additional, Chiang, Han-Lin, additional, Chen, Guei-Chiuan, additional, Hsu, Po-Jen, additional, Chang, Chun-Yuan, additional, Lin, I.-sheng, additional, Chien, Chung-Hsien, additional, Chang, Yang-Chuang, additional, Chen, Ping-Kun, additional, Hsiao, Yu-Jen, additional, Fang, Chen-Wen, additional, Chen, Yu-Wei, additional, Lee, Kuo-Ying, additional, Lin, Yun-Yu, additional, Li, Chen-Hua, additional, Tsai, Hui-Fen, additional, Hsieh, Chuan-Fa, additional, Yang, Chih-Dong, additional, Liaw, Shiumn-Jen, additional, Liao, How-Chin, additional, Yeh, Shoou-Jeng, additional, Wu, Ling-Li, additional, Hsieh, Liang-Po, additional, Lee, Yong-Hui, additional, Chen, Chung-Wen, additional, Hsu, Chih-Shan, additional, Jhih, Ye-Jian, additional, Zhuang, Hao-Yu, additional, Pan, Yan-Hong, additional, Shih, Shin-An, additional, Chen, Chin-I., additional, Sung, Jia-Ying, additional, Weng, Hsing-Yu, additional, Teng, Hao-Wen, additional, Lee, Jing-Er, additional, Huang, Chih-Shan, additional, Chao, Shu-Ping, additional, Yuan, Rey-Yue, additional, Sheu, Jau-Jiuan, additional, Yu, Jia-Ming, additional, Ho, Chun-Sum, additional, Lin, Ting-Chun, additional, Yu, Shih-Chieh, additional, Chen, Jiunn-Rong, additional, Tsai, Song-Yen, additional, Hung, Chao-Hsien, additional, Lee, Chia Fang, additional, Yang, Sheng-Kung, additional, Chen, Chih-Lin, additional, Lin, Wei, additional, Tseng, Hung-Pin, additional, Liu, Chin-Hsiung, additional, Lin, Chun-Liang, additional, Lin, Hung-Chih, additional, Chen, Pi-Tzu, additional, Hu, Chaur-Jong, additional, Chan, Lung, additional, Chi, Nai-Fang, additional, Chern, Chang-Ming, additional, Lin, Chun-Jen, additional, Wang, Shuu-Jiun, additional, Hsu, Li-Chi, additional, Wong, Wen-Jang, additional, Lee, I-Hui, additional, Yen, Der-Jen, additional, Tsai, Ching-Piao, additional, Kwan, Shang-Yeong, additional, Soong, Bing-Wen, additional, Chen, Shih-Pin, additional, Liao, Kwong-Kum, additional, Lin, Kung-Ping, additional, Chen, Chien, additional, Shan, Din-E., additional, Fuh, Jong-Ling, additional, Wang, Pei-Ning, additional, Lee, Yi-Chung, additional, Yu, Yu-Hsiang, additional, Huang, Hui-Chi, additional, Tsai, Jui-Yao, additional, Wu, Ming-Hsiu, additional, Chiang, Szu-Yi, additional, Wang, Chiung-Yao, additional, Hsu, Ming-Chin, additional, Chen, Chien-Chung, additional, Yeh, Po-Yen, additional, Tsai, Yu-Tai, additional, Wang, Ko-Yi, additional, Chen, Tsang-Shan, additional, Hsieh, Cheng-Yang, additional, Chen, Wei-Fen, additional, Yip, Ping-Keung, additional, Wang, Vinchi, additional, Wang, Kaw-Chen, additional, Tsai, Chung-Fen, additional, Chen, Chao-Ching, additional, Liu, Yi-Chien, additional, Chen, Shao-Yuan, additional, Zhao, Zi-Hao, additional, Wei, Zhi-Peng, additional, Wu, Shey-Lin, additional, Liu, Ching-Kuan, additional, Lin, Ryh-Huei, additional, Chu, Ching-Hua, additional, Yan, Sui-Hing, additional, Lin, Yi-Chun, additional, Chen, Pei-Yun, additional, Hsiao, Sheng-Huang, additional, Yip, Bak-Sau, additional, Tsai, Pei-Chun, additional, Chou, Ping-Chen, additional, Kuo, Tsam-Ming, additional, Lee, Yi-Chen, additional, Chiu, Yi-Pin, additional, Tsai, Kun-Chang, additional, Liao, Yi-Sheng, additional, Tsai, Ming-Jun, additional, and Kao, Hsin-Yi, additional

Published
2018
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48. Process dependence of morphology and microstructure of cyanine dye J-aggregate film: correlation with absorption, photo- and electroluminescence properties

Author

Cheng-Chung Jaing, Cheng-Chung Lee, Jui Fen Chang, Ching Wei Cheng, Chen Chih Lin, Hung Sen Wei, Yang Han Lu, and Fan Ching Chien

Subjects
Photoluminescence, Materials science, Luminescence, business.industry, Spectrum Analysis, Absorption, Radiation, Electroluminescence, Carbocyanines, Microscopy, Atomic Force, Atomic and Molecular Physics, and Optics, chemistry.chemical_compound, Optics, chemistry, Electricity, Attenuation coefficient, Optoelectronics, Quantum efficiency, Glass, Cyanine, Thin film, Electronics, business, Coloring Agents, J-aggregate
Abstract

Cyanine dye J-aggregate films are a class of absorbing and luminescent materials which have been extensively applied in the polariton-based research. Here we systematically study the DEDOC cyanine dyes J-aggregate films made by layer-by-layer assembly and spin-coating processes to establish a clear correlation between the film structure and the absorption and luminescence properties. From detailed analyses of morphology, optical spectra, and light-emitting diode characteristics, we demonstrate that layer-by-layer assembled film has higher degrees of homogeneity and molecular packing quality than spin-coated film, leading to a higher absorption coefficient, more uniform luminescence, and a greater electroluminescence quantum efficiency with maximized thickness.

Published
2015

49. Distribution of Atmospheric Aerosol over the South China Sea

Author

Chen-Chih Lin and Shih-Jen Huang

Subjects
Atmospheric Science, South china, Article Subject, Empirical orthogonal functions, lcsh:QC851-999, AOD measurements, Pollution, AERONET, Aerosol, La Niña, Geophysics, Geography, Climatology, Submarine pipeline, lcsh:Meteorology. Climatology, Biomass burning
Abstract

The satellite-derived aerosol optical depth (AOD) data is used to investigate the distribution of aerosol over the South China Sea (SCS). High correlation coefficients are found between in situ AERONET data and satellite AOD measurements around the SCS with the highest coefficient of 0.9 on the Dongsha Island (i.e., Pratas Island). The empirical orthogonal function (EOF) analysis of AOD over the SCS shows that high AOD is always found around offshore areas of China, Indochina, Sumatra, and Borneo. Besides, spring is the major season of occurring coarse aerosol particles (AOT_C) but fine aerosol particles (AOT_F) occur yearly. The biomass burning is found in Indochina during March and April, and so it is in Sumatra and Borneo from August to October. The results also show that the AOT_F are higher during El Niño events, but higher AOT_C are found in La Niña years.

Published
2015

50. Predicting Breast Cancer by Paper Spray Ion Mobility Spectrometry Mass Spectrometry and Machine Learning

Author

Huang, Ying-Chen, Chung, Hsin-Hsiang, Dutkiewicz, Ewelina P., Chen, Chih-Lin, Hsieh, Hua-Yi, Chen, Bo-Rong, Wang, Ming-Yang, and Hsu, Cheng-Chih

Abstract

Paper spray ionization has been used as a fast sampling/ionization method for the direct mass spectrometric analysis of biological samples at ambient conditions. Here, we demonstrated that by utilizing paper spray ionization-mass spectrometry (PSI-MS) coupled with field asymmetric waveform ion mobility spectrometry (FAIMS), predictive metabolic and lipidomic profiles of routine breast core needle biopsies could be obtained effectively. By the combination of machine learning algorithms and pathological examination reports, we developed a classification model, which has an overall accuracy of 87.5% for an instantaneous differentiation between cancerous and noncancerous breast tissues utilizing metabolic and lipidomic profiles. Our results suggested that paper spray ionization-ion mobility spectrometry-mass spectrometry (PSI-IMS-MS) is a powerful approach for rapid breast cancer diagnosis based on altered metabolic and lipidomic profiles.

Published
2020
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