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Robin K. Chou,George H. K. Wang,Yun-Yi Wang 한국재무학회 2012 한국재무학회 학술대회 Vol.2012 No.09
We investigate the investment strategies of individual day traders in the Taiwan Index Futures market, along with their impact on market liquidity and volatility. Our results indicate a tendency among most individual day traders to behave as irrational contrarian traders. We also present consistent evidence to show that most individual day traders provide market liquidity by reducing the bid-ask spread, temporary price volatility and the temporal price impacts. Our results, which are consistent with the experimental results of Bloomfield et al. (2009), provide no support for the general criticism that day trading destabilizes the market while also exacerbating market volatility.
Modelling Park-and-Ride Service in a Linear Monocentric City
Judith Y T Wang, Hai Yang, and Robin Lindsey 서울시립대학교 도시과학연구원 2004 International journal of urban sciences (IJUS) Vol. No.
This paper investigates the optimisation problem for the location and pricing of a Park-and-Ride facility in a linear monocentric city. A Logit-based multi-modal user equilibrium model is formulated for the city in the morning rush hours. The Logit approach enables the possibility to model users’ sensitivity to the cost differences between modes. The model developed can be applied to determine the optimal Park-and-Ride location and level of parking charge for profit maximisation and social cost minimisation subject to different levels of demand and users’sensitivity. A numerical experiment is conducted to test the model. The results indicate that by optimising the location and parking charge, there is a possibility of a‘ win-win’situation whereby profit and social cost can both be improved.
Jianling Wang,Robin Qiu 보안공학연구지원센터 2015 International Journal of u- and e- Service, Scienc Vol.8 No.8
The Chinese automotive industry is the largest in the world. Although after-sales services are known to be associated with profitability, it has not obtained its rightful prominence in the Chinese industry. To investigate how the quality of leader-member exchange can influence after-sales services in the Chinese automobile industry, we collected data from individual employees and customers and analyzed it using grey theory model. Based on the results, we proposed the industry to pay more attentions to tangible after-sales service. While previous studies tended to adopt an either customer or employee perspective, our research contributes to the literature by offering a more comprehensive perspective from both the standpoints of the organization and consumers, and our grey theory analytic approach offers a viable option for researchers who are interested in reducing biases in data due to the data aggregation process.
Pae, Chi-Un,Wang, Sheng-Min,Han, Changsu,Bahk, Won-Myong,Lee, Soo-Jung,Patkar, Ashwin A.,Masand, Prakash S.,Serretti, Alessandro,Emsley, Robin Ovid Technologies (Wolters Kluwer) - Lippincott Wi 2017 International clinical psychopharmacology Vol.32 No.5
<P>We investigated the relative efficacy and tolerability of aripiprazole once monthly (AOM) versus paliperidone palmitate (PP) for treating schizophrenia. Extensive databases searches on short-term, placebo-controlled, randomized studies of AOM and PP were performed. Indirect treatment comparisons were performed between the two long-acting injectable antipsychotics (LAIAs). The primary efficacy endpoint was the mean change in the Positive and Negative Syndrome Scale total score from baseline between each LAIA and placebo. The effect sizes were mean differences and odds ratio (ORs) with 95% confidence intervals (CIs) for the primary efficacy endpoint and safety/tolerability between two LAIAs, respectively. Mean difference in the primary efficacy endpoint was significantly different, favouring AOM over PP (OR: -6.4; 95% CI: -11.402 to -1.358); sensitivity analyses and noninferiority test (AOM vs. PP) confirmed the primary results. The overall early dropout rate was not significantly different between AOM and PP (OR: 1.223; 95% CI: 0.737-2.03). However, there was a significant difference in the early dropout rate in terms of lack of efficacy favouring AOM over PP (OR: 0.394; 95% CI: 0.185-0.841). Within the context of the inherent limitations of the current analysis, our results may suggest that there may be relative advantages for AOM over PP in the short-term treatment of schizophrenia. Copyright (C) 2017 Wolters Kluwer Health, Inc. All rights reserved.</P>
Molecular Engineering of Zinc Phthalocyanines with Phosphinic Acid Anchoring Groups
Ló,pez‐,Duarte, Ismael,Wang, Mingkui,Humphry‐,Baker, Robin,Ince, Mine,Martí,nez‐,Dí,az, M. Victoria,Nazeeruddin, Mohammad K.,Torres, Tomá,s,Grä,tzel, Mich WILEY‐VCH Verlag 2012 Angewandte Chemie Vol.124 No.8
<P><B>Zwei Zinkphthalocyanin‐Photosensibilisatoren</B> mit verschiedenen Phosphinsäure‐Ankergruppen (siehe Schema) wurden synthetisiert. Solarzellen mit diesen Verbindungen verfügen über eine Photostromdichte von (7.6±0.2) mA cm<SUP>−2</SUP> bei geschlossenem Stromkreis, eine Spannung von (559±30) mV bei offenem Stromkreis und einen Füllfaktor von 0.76±0.03; dies entspricht einem Gesamtwirkungsgrad von 3.24 % unter 1 sun.</P>
Purkayastha Subhanik,Xiao Yanhe,Jiao Zhicheng,Thepumnoeysuk Rujapa,Halsey Kasey,Wu Jing,Tran Thi My Linh,Hsieh Ben,Choi Ji Whae,Wang Dongcui,Vallières Martin,Wang Robin,Collins Scott,Feng Xue,Feldman 대한영상의학회 2021 Korean Journal of Radiology Vol.22 No.7
Objective: To develop a machine learning (ML) pipeline based on radiomics to predict Coronavirus Disease 2019 (COVID-19) severity and the future deterioration to critical illness using CT and clinical variables. Materials and Methods: Clinical data were collected from 981 patients from a multi-institutional international cohort with real-time polymerase chain reaction-confirmed COVID-19. Radiomics features were extracted from chest CT of the patients. The data of the cohort were randomly divided into training, validation, and test sets using a 7:1:2 ratio. A ML pipeline consisting of a model to predict severity and time-to-event model to predict progression to critical illness were trained on radiomics features and clinical variables. The receiver operating characteristic area under the curve (ROC-AUC), concordance index (C-index), and time-dependent ROC-AUC were calculated to determine model performance, which was compared with consensus CT severity scores obtained by visual interpretation by radiologists. Results: Among 981 patients with confirmed COVID-19, 274 patients developed critical illness. Radiomics features and clinical variables resulted in the best performance for the prediction of disease severity with a highest test ROC-AUC of 0.76 compared with 0.70 (0.76 vs. 0.70, p = 0.023) for visual CT severity score and clinical variables. The progression prediction model achieved a test C-index of 0.868 when it was based on the combination of CT radiomics and clinical variables compared with 0.767 when based on CT radiomics features alone (p < 0.001), 0.847 when based on clinical variables alone (p = 0.110), and 0.860 when based on the combination of visual CT severity scores and clinical variables (p = 0.549). Furthermore, the model based on the combination of CT radiomics and clinical variables achieved time-dependent ROC-AUCs of 0.897, 0.933, and 0.927 for the prediction of progression risks at 3, 5 and 7 days, respectively. Conclusion: CT radiomics features combined with clinical variables were predictive of COVID-19 severity and progression to critical illness with fairly high accuracy.