Foot-and-Mouth Disease Entrance Assessment Model Through Air Passenger Violations

This article aims to construct a risk model for the prediction of foot-and-mouth disease (FMD) entrance caused by passengers who illegally carry meat products of cloven-hoofed animals through international airports into a country. The risk that meat contaminated with the FMD virus is formulated as the probabilities of FMD factor events (the prevalence of FMD), the commodity factor event (the transportation, storage, and distribution (TSD) factor event), and the passenger event. Data used for analysis were records of illegal meat product carriers from areas A and B intercepted at an international airport in Taiwan. A risk model was proposed to simulate the probability distributions in disease prevalence, probability of FMD virus existing in the meat products after meat processing, and estimation of survival of virus and time period for TSD. The probability of the passenger event was hypothesized with the odds of intercepted passengers and estimated via logistic regression. The results showed that the odds of passengers being intercepted by beagles were higher than those intercepted by Customs. By conducting Monte Carlo simulations, the probability of FMD virus risk caused by FMD factors from area A was 149 times lower than that from area B. The probability of FMD virus risk caused by the passenger event from area A was four times lower than the corresponding probability from area B. The model provides a contribution to FMD prevention and can be a reference for developing models of other diseases.     

Effects of placement point of background music on shopping website

Consumer on-line behaviors are more important than ever due to highly growth of on-line shopping. The purposes of this study were to design placement methods of background music for shopping website and examine the effect on browsers' emotional and cognitive response. Three placement points of background music during the browsing, i.e. 2 min., 4 min., and 6 min. from the start of browsing were considered for entry points. Both browsing without music (no music) and browsing with constant music volume (full music) were treated as control groups. Participants' emotional state, approach-avoidance behavior intention, and action to adjust music volume were collected. Results showed that participants had a higher level of pleasure, arousal and approach behavior intention for the three placement points than for no music and full music. Most of the participants for full music (5/6) adjusted the background music. Only 16.7% (3/18) participants for other levels turn off the background music. The results indicate that playing background music after the start of browsing is benefit for on-line shopping atmosphere. It is inappropriate to place background music at the start of browsing shopping website. The marketer must manipulated placement methods of background music for a web store carefully.     

Estimation and Inference Procedures for Semiparametric Distribution Models with Varying Linear‐Index

More flexible semiparametric linear‐index regression models are proposed to describe the conditional distribution. Such a model formulation captures varying effects of covariates over the support of a response variable in distribution, offers an alternative perspective on dimension reduction and covers a lot of widely used parametric and semiparameteric regression models. A feasible pseudo likelihood approach, accompanied with a simple and easily implemented algorithm, is further developed for the mixed case with both varying and invariant coefficients. By justifying some theoretical properties on Banach spaces, the uniform consistency and asymptotic Gaussian process of the proposed estimator are also established in this article. In addition, under the monotonicity of distribution in linear‐index, we develop an alternative approach based on maximizing a varying accuracy measure. By virtue of the asymptotic recursion relation for the estimators, some of the achievements in this direction include showing the convergence of the iterative computation procedure and establishing the large sample properties of the resulting estimator. It is noticeable that our theoretical framework is very helpful in constructing confidence bands for the parameters of interest and tests for the hypotheses of various qualitative structures in distribution. Generally, the developed estimation and inference procedures perform quite satisfactorily in the conducted simulations and are demonstrated to be useful in reanalysing data from the Boston house price study and the World Values Survey.     

Multi-objectives exception management model for semiconductor back-end environment under turnkey service

On-time delivery is the need for customer satisfaction which is a critical factor in the survival of the semiconductor industry. The on-time-delivery performance of the whole semiconductor turnkey service depends on the performance of the back-end factories. Unfortunately, undesirable and inevitable production variations make it difficult to maintain and improve a factory's performance and more objectives such as cycle time, throughput rate and the due-date accuracy need to be simultaneously considered. This paper presents an exception management model in order to compromise the contradicting needs of delivery accuracy, throughput rate and cycle time. The exception model can be divided into three parts: (1) an integrated performance index is proposed to compromise multiple performance measures; (2) an AWDL (available WIP deviation level) determination model is designed to gather proper AWDLs for triggering exceptions and (3) a WIP correction action is proposed to make abnormal WIP levels back to normal levels as soon as possible. To evaluate the proposed WIP exception management model, a simulation model is constructed and experiments are then conducted. The simulation results show that the proposed model helps back-end factories to set proper exception triggering conditions, reduce uncertainty occurrences and achieve better performances on due dates.     

Additive Outlier Detection and Estimation for the Logarithmic Autoregressive Conditional Duration Model

This study investigates the influences of additive outliers on financial durations. An outlier test statistic and an outlier detection procedure are proposed to detect and estimate outlier effects for the logarithmic Autoregressive Conditional Duration (Log-ACD) model. The proposed test statistic has an exact sampling distribution and performs very well, in terms of size and power, in a series of Monte Carlo simulations. Furthermore, the test statistic is robust to several alternative distribution assumptions. An empirical application shows that parameter estimates without considering outliers tend to be biased.     

莫尔条纹图像处理和分析的研究

本文描述利用莫尔拓扑波(moire topography)原理和数字图像处理技术研制成的分析系的原理和组成及其在颜面三维形态测量中的应用.     

The Dynamics of Self-employment and Ethnic Business Ownership among Taiwanese in Australia

Taiwan‐born business and skilled migrants who settle in Australia have high unemployment rates despite being well educated and fairly affluent. This phenomenon, commonly found in Australia among new Asian immigrants, has seldom been researched. Using qualitative methodologies, including ethnographic interviews and participant observation, this paper examines economic integration of recent Taiwanese business and skilled migrants in three Australian cities: Sydney, Brisbane, and Melbourne. The results indicate that Taiwanese immigrants find it difficult to secure employment, start profitable businesses, and adapt to the host society. The integration challenges include: lack of fluency in English, different social and cultural milieu, lack of familiarity with Australian business culture and labour relations, complex rules and regulations governing the establishment of business enterprises, small size of the market, high taxes, and lack of willingness to take up work not commensurate with their education and economic background. Policy recommendations to foster early integration of skilled migrants from Taiwan are included.     

Rank-order tests for the parallelism of several regression surfaces

For testing the hypothesis that several (s?2) linear regression surfaces X_ki=α_k+β_kc_ki+Z_ki (k=1,…,s) are parallel to one another, i.e., β₁=?=β_s, a class of rank-order tests are considered. The tests are shown to be asymptotically distribution-free, and their asymptotic efficiency relative to the general likelihood ratio test is derived. Asymptotic optimality in the sense of Wald is also discussed.