Browsing by Author "Chu, Yian-Shu"

Now showing 1 - 7 of 7

A GA-based method to reduce material handling: the case of TFT-LCD array Fabs in Taiwan
(2011)
Tseng, Shian-Shyong
;
Chang, Fengming M.
;
Chu, Yian-Shu
;
Chi, Pi-Ju
;
資訊工程學系
This study proposes a genetic algorithm (GA)-based Material Handling Strategy Function (MHSF) method to increase the productivity of a TFT-LCD array fabrication to improve the traditional FIFO method in TFT-LCD fabrication by the reduction of the material handling for a Rail Guided Vehicle (RGV), because costs of material handling count up to about 50% of production costs. In this article, the MHSF is provided to help material handling commands choice, where a novel GA approach is used to adapt the weights of affecting factors in the function. Finally, to evaluate the performance of the proposed method, experiments using the data from a major TFT-LCD manufacturing plant in Taiwan have been carried out, and the results indicate that it can indeed reduce fabrication time and increase productivity.
Adaptively Learning and Assessing SPSS Operating Skills Using Online SPSS Simulator
(2010-01-01)
Chu, Yian-Shu
;
Tseng, Shian-Shyong
;
Weng, Jui-Feng
;
Lin, Huan-Yu
;
Wang, Nien-Chu
Online questionnaire is an emerging method for social science researchers to perform their survey. Although there are many data analysis software tools nowadays, such as SPSS, SAS, and Excel etc., to assist the students in analyzing the data of their surveys. However, the intentions of users for using the software tools cannot be probed and utilized to help the users operating them, so it will cause many errors on the students' analysis results due to the misusage of software and result in that learning how to use the data analysis software tools based upon the students' intentions becomes very time-consuming. Moreover, because the software operating procedures of the students are not recorded, the teachers cannot find out the students' misconceptions. In this paper, we acquire the knowledge of using SPSS software and then apply the Simulator Generator concept proposed in previous research to build an online web-based SPSS software simulator for the students to emulate the operating process of SPSS software. Based upon the acquired frequent patterns of misuse, the teacher can design action routines embedded in the simulator to instantly detect the frequent error action patterns and help the students to rectify their misconceptions. Moreover, the teacher can trace and analyze the students' learning statuses according to the logs generated from online SPSS Simulator. Using Simulator Generator, writing grammar rules is essential, but it is not easy for teachers. The knowledge of using SPSS software are largely identical but with minor differences. Thus, an SPSS Functional Ontology is proposed according to the features of SPSS software and the corresponding grammar rules are constructed in this research. Teachers just need to do some minor adjustments on the differences and the action routines, and then the new simulator will be generated automatically.
An intelligent questionnaire analysis expert system
(2009-03-01)
Chu, Yian-Shu
;
Tseng, Shian-Shyong
;
Tsai, Yu-Jie
;
Luo, Ren-Jei
;
資訊工程學系
In the questionnaire analysis, how to find a statistically significant difference between two or more groups in a continuous measure is one of the major problems in researches. However, it is difficult for researchers to solve the issue of finding possible statistically significant difference. There are two causes of this issue. The one is that the process of finding the statistically significant differences is highly dependent on researchers' intuition and experience, and the other is that the original questionnaire data may not be good enough to find the statistically significant differences. In this paper, we build a data warehouse and a forward-chaining rule-base expert system with three kinds of indicators, Increase, StepDown, and Dice, for drilling down the data warehouse to assist researchers in exploring the data to select appropriate statistics methods to find possible significant differences. The prototype of this expert system has been implemented, and the results of experiment about satisfaction survey showed finding the significant difference becomes easier, and users were interested in the idea of this system. (C) 2008 Elsevier Ltd. All rights reserved.
Implementation of a Model-Tracing-Based Learning Diagnosis System to Promote Elementary Students' Learning in Mathematics
(2014-04-01)
Chu, Yian-Shu
;
Yang, Haw-Ching
;
Tseng, Shian-Shyong
;
Yang, Che-Ching
;
資訊工程學系
Of all teaching methods, one-to-one human tutoring is the most powerful method for promoting learning. To achieve this aim and reduce teaching load, researchers developed intelligent tutoring systems (ITSs) to employ one-to-one tutoring (Aleven, McLaren, & Sewall, 2009; Aleven, McLaren, Sewall, & Koedinger, 2009; Anderson, Corbett, Koedinger, & Pelletier, 1995; Anderson & Reiser, 1985; Blessing, Gilbert, Ourada, & Ritter, 2009; Mitrovic et al., 2009; Mitrovic & Ohlsson, 1999; Suraweera, Mitrovic, & Martin, 2007; VanLehn et al., 2005). However, most ITSs have restricted user interfaces, which confine reasoning strategies of students during problem solving, thus ignoring the fact that students could use dissimilar strategies to solve a given question. Furthermore, student learning problems could be diagnosed from the derivation of their answers. In order to interpret students' mathematical problem-solving behaviors, this study developed a Model-tracing Intelligent Tutor (MIT) to diagnose students' learning problems and provide learning feedback for individual students. A quasi-experiment was conducted in an elementary school to evaluate the effectiveness of the proposed approach, in which 124 fifth graders participated. The experimental results show that the model-tracing-based learning diagnosis system is significantly more helpful to the students in learning mathematics than the conventional web-based test in terms of learning achievements.
Implementation of a Model-Tracing-Based Learning Diagnosis System to Promote Elementary Students\' Learning in Mathematics
(2014-04-01)
Chu, Yian-Shu
;
Yang, Haw-Ching
;
Tseng, Shian-Shyong
;
Yang, Che-Ching
;
資訊工程學系
Of all teaching methods, one-to-one human tutoring is the most powerful method for promoting learning. To achieve this aim and reduce teaching load, researchers developed intelligent tutoring systems (ITSs) to employ one-to-one tutoring (Aleven, McLaren, & Sewall, 2009; Aleven, McLaren, Sewall, & Koedinger, 2009; Anderson, Corbett, Koedinger, & Pelletier, 1995; Anderson & Reiser, 1985; Blessing, Gilbert, Ourada, & Ritter, 2009; Mitrovic et al., 2009; Mitrovic & Ohlsson, 1999; Suraweera, Mitrovic, & Martin, 2007; VanLehn et al., 2005). However, most ITSs have restricted user interfaces, which confine reasoning strategies of students during problem solving, thus ignoring the fact that students could use dissimilar strategies to solve a given question. Furthermore, student learning problems could be diagnosed from the derivation of their answers. In order to interpret students\' mathematical problem-solving behaviors, this study developed a Model-tracing Intelligent Tutor (MIT) to diagnose students\' learning problems and provide learning feedback for individual students. A quasi-experiment was conducted in an elementary school to evaluate the effectiveness of the proposed approach, in which 124 fifth graders participated. The experimental results show that the model-tracing-based learning diagnosis system is significantly more helpful to the students in learning mathematics than the conventional web-based test in terms of learning achievements.
Online generation of association rules under multi-dimensional consideration based on negative-border
(2007-01-01)
Wang, Ching-Yao
;
Tseng, Shian-Shyong
;
Hong, Tzung-Pei
;
Chu, Yian-Shu
;
資訊工程學系
Recently, some researchers have developed incremental and online mining approaches to maintain association rules without having to re-process the entire database whenever the database is updated or user specified thresholds are changed. However, they usually can not flexibly obtain association rules or patterns from portions of data, consider problems with different aspects, or provide online decision support for users. We earlier developed an online mining approach for generation of association rules under multidimensional consideration. The multidimensional online mining approach may, however, get loose upper-bound support of candidate itemsets and thus cause excessive I/O and computation costs. In this paper, we attempt to apply the concept of a negative border to enlarge the mining information in the multidimensional pattern relation to help get tighter upper-bound, and thus reduce the number of candidate itemsets to consider. Based oh the extended multidimensional pattern relation, a corresponding online mining approach called Negative-Border Online Mining (NOM) is proposed to efficiently and effectively utilize the information of negative itemset in the negative border. Experiments for heterogeneous datasets are also performed to show the effectiveness of the proposed approach.
Program Peer Assessment Using Tagging Approach
(2008)
Liu, Yi-Li
;
Tseng, Shian-Shyong
;
Lin, Huan-Yu
;
Weng, Jui-Feng
;
Chu, Yian-Shu
Most of die programming novices feel hard to learn programming skills, such as coding, tracing, debugging and testing. To help them learn programming well, computer program assessments which can find out the novices' programming misconception have been proposed. Although traditional computer program assessment can scow die student's program by executing die program with test cases, it is ineffective because die novices' programming misconception in the coding mistakes and tracing mistakes can not be singled out In die peer assessment activity, die learners can discuss their works with each other, so every learner can get die comments; about his/her work together with die score. This paper proposes a new computer program peer assessment to help die novices easily find out their programming misconception in the coding mistakes and tracing mistakes. An experiment has been done to evaluate the effectiveness of die new assessment. We may conclude that die process is useful to single out die leamer's coding and tracing problems, and that the tracing guidance is useful to direct the novice to trace peer's program.