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Ker H.-W.,Chihlee Institute of Technology
Transportation Research Record | Year: 2011

Multilevel data are common in many fields. Because of the hierarchical data structure, multilevel data are often analyzed with linear mixed-effects (LME) models. Exploratory analysis, statistical modeling, and examination of the model fit of LME models are more complex than those of standard multiple regressions. A systematic modeling approach that uses visual-graphical techniques and LME models is proposed and demonstrated with the original AASHO Road Test flexible pavement serviceability index data. The proposed approach includes exploring the growth patterns at both group and individual levels, identifying the important predictors and unusual subjects, choosing suitable statistical models, selecting a preliminary mean structure, selecting a random structure, selecting a residual covariance structure, model reduction, and examination of the model fit. Source


Lee C.-H.,Chihlee Institute of Technology | Liao C.-J.,National Taiwan University of Science and Technology | Chung T.-P.,Jilin University
International Journal of Production Economics | Year: 2014

This paper considers a real-life identical parallel scheduling problem originating from the manufacturing plant producing polyvinyl chloride leather products. In the considered scheduling problem, each job has some attributes and each attribute has several different levels. Because there is at least one different level of attribute between two adjacent jobs, it is necessary to make a setup adjustment whenever there is a switch from processing a job to a different job on each machine. The problem can be classified as a scheduling problem to minimize the makespan on two identical parallel machines with multi-attribute setup times. A constructive heuristic, named COIT, is first proposed for the problem and evaluated by comparing with the current scheduling method used by the case plant. To further improve the solution, a variable neighborhood search (VNS) metaheuristic is presented and compared with a mixed integer programming model. The computational results show that the COIT heuristic outperforms the current scheduling method with a significant improvement, and the VNS can further improve the solution. © 2014 Elsevier B.V. All rights reserved. Source


Hsieh C.-H.,Chihlee Institute of Technology
Natural Hazards | Year: 2014

Global environmental changes have led to frequent occurrences of climatic extremes. The increasingly frequent and high-magnitude natural disasters in Taiwan have caused significant mortality, injury, and property damage. In response, there have been requests to improve the capacity to cope with extreme climatic conditions through increased awareness and identification of vulnerability. Disruptions to transportation systems affect the resilience for sustaining daily operations. Among the various types of transportation systems, ports provide substantial employment and industrial activity, contributing to national and regional development. In addition, ports integrate the functions of supply chains such as services in logistics, information, and business, becoming the location of industrial clusters. Therefore, this study examines the risk of port failures from the perspective of vulnerability. Specifically, seven vulnerable factors derived from the extant literature and lessons learned from the previous disaster cases are evaluated using geographic information systems. The results reveal that port capacity and efficiency have a significant effect on port vulnerability in which the efficiency of gantry cranes, labor productivity, free trade zone business volume, and ground access networks play crucial roles in port failure. Moreover, the risks associated with port operation are evaluated by overlapping a hazard map of areas prone to debris flows and tsunami inundation. The risk maps can assist decision makers in understanding the vulnerability and adopting appropriate strategies to minimize disaster risks. © 2014, Springer Science+Business Media Dordrecht. Source


Hsieh C.-H.,Chihlee Institute of Technology | Feng C.-M.,National Chiao Tung University
Environment and Planning A | Year: 2014

Road networks are instrumental in resource allocation and preevacuation, and profoundly affect disaster response and recovery, particularly emergent-disaster logistics and island rescues. Disruptions to road networks impair daily operations, irrespective of whether they are damaged by external forces or failures in interacting elements. However, functional interdependency is absent from transportation vulnerability assessments. This study thus constructed a framework to assess the interdependent vulnerability of road network failures. Based on eleven fragile factors developed in the literature and an empirical case study in the Taipei metropolitan area, road network vulnerability is determined by fuzzy cognitive maps and geographic information systems for functional and spatial interactions, respectively. The analytical results indicate that road network vulnerability is underestimated if the interdependency is neglected. Delay time on the shortest substitution, level of service on adjacent links, and inaccessibility to hospital emergency centers significantly affect vulnerability. Whereas certain socioeconomic resilience is performed in the short term, spatial-functional interdependency dilutes those effects in the long term. The framework developed facilitates decision makers in understanding interdependent vulnerabilities and adopting appropriate strategies to improve vulnerability. Source


Tao Y.-H.,National University of Kaohsiung | Yeh C.R.,National Taiwan Normal University | Hung K.C.,Top BOSS International Corporation | Hung K.C.,Chihlee Institute of Technology
Computers and Education | Year: 2012

Previous studies on business simulation games (BSGs) have concluded that improved performance may not be the primary benefit of using BSGs, due to mixed results between student performance and perceptions. Two relevant and insightful issues attract our attention, namely, the impacts of the heterogeneous student population and the different complexity levels of BSG software. To address these issues, the present study aims to understand the relationship between student profile/characteristics and performance in the classroom with BSG-facilitated learning. An in-depth case study is conducted on a general college course designed to teach three different complexities of BSGs to students enrolled in different majors. Four student profile factors are individually tested for differences in performance scores as evaluated by the teacher. Additionally, the influences of 11 student characteristics are assessed with regard their self-reported perceived learning performances. Regression analysis and ANOVA are used to investigate the impacts of heterogeneous users and game complexity on student performance. Based on the regression analyses of the data collected from 43 respondents who participated in the general course, the study concludes that knowledge and skill may influence the heterogeneous student population; moreover, student participation and tacit learning preference improve performance, and students with an auditory learning preference or high learning motivation may not perform well in classroom BSG learning. However, the low value of adjusted R square implies that more dimensions or variables are needed to increase the explaining power of the performance scores in the regression analyses. In contrast, heterogeneous BSG software with different complexity levels present different results. The current research contributes practical and incremental knowledge on the complexity of heterogeneous BSG software on performance scores and the perceived learning performance of heterogeneous student populations. With the research limitations acknowledged, a series of suggestions for teachers pertaining to appropriate applications of BSGs in classes is offered as well as recommendations to BSG providers. Nevertheless, in-depth analyses are required, preferably with larger student population samples, to further explore the insignificant relationship between student perceptions and attitude under nonlinear extended complexity. © 2012 Elsevier Ltd. All rights reserved. Source

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