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- 저자 : Li-Feng Tsai (검색결과 6 건)
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Tsai Li-Jen,Chung Chi-Hsiang,Lin Chien-Jung,Su Sheng-Chiang,Kuo Feng-Chih,Liu Jhih-Syuan,Chen Kuan-Chan,Ho Li-Ju,Kuo Chih-Chun,Chang Chun-Yung,Lin Ming-Hsun,Chu Nain-Feng,Lee Chien-Hsing,Hsieh Chang-H 한국한의학연구원 2022 Integrative Medicine Research Vol.11 No.2
Background: Diabetic patients are at high risk of developing cancer. Traditional Chinese medicine (TCM) has become increasingly popular as an adjuvant treatment for patients with chronic diseases, and some studies have identified its beneficial effect in diabetic patients with cancer. The purpoes of this study was to outline the potential of TCM to attenuate hospitalization and mortality rates in diabetic patients with carcinoma in situ (CIS). Methods: A total of 6,987 diabetic subjects with CIS under TCM therapy were selected from the National Health Insurance Research Database of Taiwan, along with 38,800 of 1:1 sex-, age-, and index year-matched controls without TCM therapy. Cox proportional hazard analysis was conducted to compare hospitalization and mortality rates during an average of 15 years of follow-up. Results: A total of 3,999/1,393 enrolled-subjects (28.62%/9.97%) had hospitalization/mortality, including 1,777/661 in the TCM group (25.43%/9.46%) and 2,222/732 in the control group (31.80%/10.48%). Cox proportional hazard regression analysis showed a lower rate of hospitalization and mortality for subjects in the TCM group (adjusted HR=0.536; 95% CI=0.367–0.780, P<0.001; adjusted HR=0.783; 95% CI=0.574– 0.974, P = 0.022). Kaplan-Meier analysis showed that the cumulative risk of hospitalization and mortality in the case and control groups was significantly different (log rank, P<0.001 and P = 0.011, respectively). Conclusions: Diabetic patients with CIS under TCM therapy were associated with lower hospitalization and mortality rates compared to those without TCM therapy. Thus, TCM application may reduce the burden of national medical resources.
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Feng Jia,Zi-Yi Li,David Y. H. Pui,Chuen-Jinn Tsai 한국화학공학회 2020 Korean Journal of Chemical Engineering Vol.37 No.3
A numerical model was used to study the homogeneous nucleation process of dibutyl phthalate (DBP) vapor in a laminar flow diffusion chamber (LFDC); the spatial and temporal evolution of DBP droplet size distribution was governed by the population balance equation (PBE). In the PBE, the nucleation rate was calculated by the selfconsistent correction nucleation theory (SCCNT), droplet coagulation, vapor and droplet deposition losses were considered. The simulation results showed that the nucleation rate predicted by the SCCNT improved the underestimation of that predicted by the classical nucleation theory. Due to vapor deposition before nucleation and droplet deposition after nucleation on the wall, the DBP mass loss was severe, accounting for about 86.3% of the total inlet vapor mass, and the droplet size distribution shifted towards larger diameters. The simulation results agreed well with the experimental data in terms of the droplet size distribution and average number concentration at the outlet of the LFDC because of the detailed droplet dynamic, transport and deposition mechanisms treated in this model. Based on this model, the number of molecules in the critical cluster was calculated using the first nucleation theorem and found to be larger about 50% than that calculated using the Gibbs-Thompson equation.
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Kuo, Chung-Feng Jeffrey,Su, Te-Li,Tsai, Cheng-Ping The Korean Fiber Society 2007 Fibers and polymers Vol.8 No.6
This study is intended for finding out the optimal processing parameters for needle punching nonwoven fabrics in order to work out its maximal strength. Taguchi method together with grey relational analysis is employed to resolve the problem as regards multiple-quality optimization, and further discover the optimal combination of processing parameters for needle punching nonwoven fabrics. Firstly, orthogonal array $L_{18}(2^1{\times}3^7)$ is used to deal with the processing parameters that may exert influence over the manufacturing of needle punching nonwoven fabrics. Then grey relational analysis is applied to resolve the deficiency of Taguchi method that focus on single quality characteristic. Next, the response table of grey relational analysis is used to obtain the optimal combination of processing parameters for multiple quality characteristics. In the current experiment quality characteristic refers to the tensile strength and tear strength of the nonwoven fabrics. Additionally, signal-to-noise ratio (SN ratio) calculation and analysis of variance (ANOVA) can be adopted to explore the experimental results. Through ANOVA, the significant factors that exert comparatively significant influence over the quality characteristic of the needle punching nonwoven fabrics, that is, the control factors are determined so that the quality characteristic of the needle punching nonwoven fabrics can be effectively controlled. Finally, confirmation experiment is conducted within 95 % confidence interval to verify the experimental reliability and reproducibility.
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Analysis and Construction of a Quality Prediction System for Needle-Punched Non-woven Fabrics
Kuo Chung-Feng Jeffrey,Su Te-Li,Chiu Chin-Hsun,Tsai Cheng-Ping The Korean Fiber Society 2007 Fibers and polymers Vol.8 No.1
In this study, polyester and polypropylene staple fibers were selected as the raw material, and then processed through roller-carder, cross-lapper and needle-punching machine to produce needle-punched non-woven fabrics. First, the experiment was planned using the Taguchi method to select processing parameters that affect the quality of the needle-punched non-woven fabric to act as the control factors for this experiment. The quality characteristics were the longitudinal and transverse tensile strength of the non-woven fabric as well as longitudinal and transverse tear strength. The $L_{18}(2^1{\times}3^7)$ orthogonal array was selected for the experiment as it offered an improvement on the traditional method that wastes a lot of time, effort and cost. By using the analysis of variance(ANOVA) technique at the same time, the effect of significant factors on the production process of needle-punched non-woven fabrics could be determined. Finally, the processing parameters were set as the input parameters of a back-propagation neural network(BPNN). The BPNN consists of an input layer, a hidden layer and an output layer where the longitudinal/transverse tensile and tear strength of the non-woven fabric were set as the output parameters. This was used to construct a quality prediction system for needle-punched non-woven fabrics. The experimental results indicated that the prediction system implemented in this study provided accurate predictions.
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A Design of Motion Control Law for UAV
Der-Cherng Liaw,Li-Feng Tsai 제어로봇시스템학회 2020 제어로봇시스템학회 국제학술대회 논문집 Vol.2020 No.10
In this paper, a study of the nonlinear dynamical behavior of unmanned aerial vehicles (UAV) is presented. Based on a given mathematical model of quad-rotor UAV, all of the possible operational modes with given control input is discussed. Motion control law is also proposed for achieving a given desired operation mode by using back-stepping control approach. Simulation results are obtained to demonstrate the success of the proposed design.
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