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Nuclear Theranostics in Taiwan
Ko-Han Lin,Yi-Wei Chen,Rheun-Chuan Lee,Ling-Wei Wang,Fong-In Chou,Chi-Wei Chang,Sang-Hue Yen,Wen-Sheng Huang 대한핵의학회 2019 핵의학 분자영상 Vol.53 No.2
Boron neutron capture therapy and Y-90 radioembolization are emerging therapeutic methods for uncontrolled brain cancers and hepatic cancers, respectively. These advanced radiation therapies are heavily relied on theranostic nuclear medicine imaging before the therapy for the eligibility of patients and the prescribed-dose simulation, as well as the post-therapy scanning for assessing the treatment efficacy. In Taiwan, the Taipei Veterans General Hospital is the only institute performing the BNCT and also the leading institute performing Y-90 radioembolization. In this article, we present our single institute experiences and associated theranostic nuclear medicine approaches for these therapies.
Smart monitoring system with multi-criteria decision using a feature based computer vision technique
Chih-Wei Lin,Wen-Ko Hsu,Dung-Jiang Chiou,Cheng-Wu Chen,Wei-Ling Chiang 국제구조공학회 2015 Smart Structures and Systems, An International Jou Vol.15 No.6
When natural disasters occur, including earthquakes, tsunamis, and debris flows, they are often accompanied by various types of damages such as the collapse of buildings, broken bridges and roads, and the destruction of natural scenery. Natural disaster detection and warning is an important issue which could help to reduce the incidence of serious damage to life and property as well as provide information for search and rescue afterwards. In this study, we propose a novel computer vision technique for debris flow detection which is feature-based that can be used to construct a debris flow event warning system. The landscape is composed of various elements, including trees, rocks, and buildings which are characterized by their features, shapes, positions, and colors. Unlike the traditional methods, our analysis relies on changes in the natural scenery which influence changes to the features. The “background module” and “monitoring module” procedures are designed and used to detect debris flows and construct an event warning system. The multi-criteria decision-making method used to construct an event warring system includes gradient information and the percentage of variation of the features. To prove the feasibility of the proposed method for detecting debris flows, some real cases of debris flows are analyzed. The natural environment is simulated and an event warning system is constructed to warn of debris flows. Debris flows are successfully detected using these two procedures, by analyzing the variation in the detected features and the matched feature. The feasibility of the event warning system is proven using the simulation method. Therefore, the feature based method is found to be useful for detecting debris flows and the event warning system is triggered when debris flows occur.
Credit Rating Anomaly in the Taiwan Stock Market
Kuan-Cheng Ko,Hsiang-Hui Chu,Shinn-Juh Lin,Hsiao-Wei Ho 한국증권학회 2013 Asia-Pacific Journal of Financial Studies Vol.42 No.3
Rational asset-pricing theory asserts that higher risk should be accompanied by higher expected return. The credit risk puzzle, however, states a negative cross-sectional relationship between credit risk and future stock returns (Journal of Finance, 53, 1998, 1131; Journal of Finance, 57, 2002, 2317; Journal of Finance, 63, 2008, 2899; Journal of Financial Markets, 12, 2009, 469). This paper examines the credit risk puzzle using an independent dataset from Taiwan’s stock market. We document a significantly positive premium between highest- and lowest-rated stocks in both portfolios and individual stocks, and demonstrate that it cannot be explained by well-known asset-pricing models, including the CAPM, Journal of Financial Economics, 33, 1993, 3 three-factor model, and Journal of Financial Economics 82, 2006, 631 liquidity-augmented CAPM. Unlike the evidence collected from the US market, rating downgrades only have limited impact on the cross-sectional variation of stock returns in Taiwan. Further analysis indicates that credit rating serves as a better proxy for distress risk, and is thus priced in Taiwan’s stock market.
Credit Rating Anomaly in Taiwan Stock Market
Kuan-Cheng Ko,Shinn-Juh Lin,Hsiang-Hui Chu,Hsiao-Wei Ho 한국재무학회 2012 한국재무학회 학술대회 Vol.2012 No.09
Rational asset-pricing theory asserts that higher risk should be accompanied by higher expected return. The credit-risk puzzle, however, states a negative cross- sectional relationship between credit risk and future stock returns (Dichev, 1998; Grin and Lemmon, 2002; Campbell et al., 2008; Avramov et al., 2009). This pa- per examines the credit-risk puzzle using an independent dataset from Taiwan's stock market. We document the existence of the credit-risk premium in both portfolios and individual stocks, and demonstrate that it can not be explained by well-known asset-pricing models which include the CAPM, Fama and French's (1993) three-factor model, and Liu's (2006) liquidity-augmented CAPM. Unlike the evidence in the U.S. market, rating downgrades only have limited impact on stock returns in Taiwan. Further analysis indicates that credit rating serves as a better proxy for distress risk, and is thus priced in Taiwan's stock market.
Chi-Hsin Liu,Chin Shueh,Tien-Chi Lan,Ko-Wei Lin,Wen-Chen Chen,Te-Ho Wu,R. D. Desautels,J. van Lierop 한국물리학회 2013 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.62 No.12
The interplay between interlayer coupling and exchange bias coupling in [NiFe/Mn] multilayerbasedthin films was investigated by using ion-beam bombardment during deposition to control theconfigurations from superlattice to nanocomposite or hybrid-structured thin films. Results showedthat well-defined interfaces in the superlattice [NiFe/Mn] thin film exhibited an interlayer couplingbehavior. In contrast, an enhanced coercivity was observed in the nanocomposite [NiFe-Mn] thinfilm. However, the hybrid [NiFe-Mn]/[NiFe/Mn] thin film with an intermixed NiFeMn alloyed filmcomponent gave rise to unusual positive exchange bias coupling.