• 아동학회지
• /
• 제31권1호
• /
• pp.163-177
• /
• 2010

The purpose of this study was to examine the maintenance of an evaluation accreditation indicator according to child care center teachers' participation in decision making. The subjects of this study were 139 teachers from 12 accredited national, public, private, and corporate child care centers in Seoul and North Gyeongsang Province. The TIP-2 (Teacher Involvement and Participation Scale V.2) and Accreditation Indicator for Child Care Centers were used to measure teachers' participation in decision making and accreditation indicator maintenance. Frequency, mean, standard deviation, one-way ANOVA and scheffe test were used for data analyses. The results revealed that the teachers who rated middle and high level in terms of their participation in decision-making showed higher levels of maintenance of the evaluation accreditation indicator than those with low levels of participation. This finding suggests that teachers' participation in decision making is an important factor for maintaining the quality of child care centers.

• Journal of Information Technology Applications and Management
• /
• 제11권1호
• /
• pp.117-135
• /
• 2004

Since human decision making behavior is likely to follow nonlinear strategy, it is conjectured that the human decision making behavior can be modeled better by nonlinear models than by linear models. All that linear models can do is to approximate rather than model the decision behavior. This study attempts to test this conjecture by analyzing human decision making behavior and combining the results of the analysis with predictive performance of both linear models and nonlinear models. In this way, this study can examine the relationship between the predictive performance of models and the existence of valid nonlinear strategy in decision making behavior. This study finds that the existence of nonlinear strategy in decision making behavior is highly correlated with the validity of the decision (or the human experts). The second finding concerns the significant correlations between the model performance and the existence of valid nonlinear strategy which is detected by Lens Model. The third finding is that as stronger the valid nonlinear strategy becomes, the better nonlinear models predict significantly than linear models. The results of this study bring an important concept, validity of nonlinear strategy, to modeling human experts. The inclusion of the concept indicates that the prior analysis of human judgement may lead to the selection of proper modeling algorithm. In addition, lens Model Analysis is proved to be useful in examining the valid nonlinearity in human decision behavior.

• Asia pacific journal of information systems
• /
• 제15권2호
• /
• pp.195-218
• /
• 2005

The emergence of ubiquitous computing environment will change the service architecture of business information systems such as Decision Support System(DSS), which will be a new application. Recent mobile DSSs allow the decision makers to be benefited from web and mobile technology. However, they seldom refer to context data, which are useful for proactive decision support. Meanwhile, ubiquitous applications so far provide restricted personalization service using context and preference of the user, that is, they do not fully make use of decision making capabilities. Hence, this paper aims to describe how the decision making capability and context-aware computing are jointly used to establish ubiquitous applications. To do so, an amended DSS paradigm: CKDDM(Context-Knowledge-Dialogue-Data-Model) is proposed in this paper. What will be considered for the future decision support systems when we regard ubiquitous computing technology as an inevitable impact that enforces the change of the way of making decisions are described. Under the CKDDM paradigm, a framework of ubiquitous decision support systems(ubiDSS) is addressed with the description of the subsystems within. To show the feasibility of ubiDSS, a prototype system, CAMA-myOpt(Context-Aware Multi Agent System-My Optimization) has been implemented as an illustrative example system.

• 산업공학
• /
• 제14권3호
• /
• pp.310-317
• /
• 2001

The purpose of this study is to investigate and to develop a decision support system for supporting the outworn facility replacement analysis in shipbuilding. This paper also provides an information system which can be effectively applied to various criteria in decision making. The modelbase of decision support system uses the concepts of the analytic hierarchy process along with an appropriate scoring methods. The AHP represents an improvement over other well-known scoring approaches since the criteria weights of priorities established by the AHP are not based on arbitrary scales, but use a ratio scale for human judgements. The proposed methodology in this research enables the decision maker to evaluate the investment alternatives based on qualitative data and quantitative data in a systematic way.

• 산업경영시스템학회지
• /
• 제29권1호
• /
• pp.87-93
• /
• 2006

In order to implement Artificial Intelligence, various technologies have been widely used. Artificial Intelligence are applied for many industrial products and machine tools are the center of manufacturing devices in intelligent manufacturing devices. The purpose of this paper is to present the design of Decision Support Agent that is applicable to machine tools. This system is that decision whether to act in accordance with machine status is support system. It communicates with other active agents such as sensory and dialogue agent. The proposed design of decision support agent facilitates the effective operation and control of machine tools and provides a systematic way to integrate the expert's knowledge that will implement Intelligent Machine Tools.

• 한국국방경영분석학회지
• /
• 제27권2호
• /
• pp.37-55
• /
• 2001

The main purpose of this study is to review the current system and to develop a decision support system for evaluating the priorities among those possible alternatives in the army facility enterprise. This paper also provides an information system which can be effectively applied to various criteria and stages in decision making process such as Planning and Programming phases in PPBEES. The model base of decision support systems uses the concepts of the analytic hierarchy process along with the supplementary techniques such as TOPSIS and 0-1 integer programming. Both AHP and TOPSIS are used scoring approaches in the Planning phase and IP is induced at the Programming phase to give GO/NO-GO solution for each project. We use Expert Choice, Excel and LINDO s/w's to implement a prototyped model. The proposed methodology in this paper enables the decision makers to evaluate the priority based on quantitative and qualitative data in a systematic way.

• 한국지능시스템학회:학술대회논문집
• /
• 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
• /
• pp.208-212
• /
• 1998

This paper suggests the method to recognize the various defect patterns of cold mill strip using binary decision tree constructed by genetic algorithm automatically. In case of classifying the complex the complex patterns with high similarity like the defect patterns of cold mill strip, the selection of the optimal feature set and the structure of recognizer is important for high recognition rate. In this paper genetic algorithm is used to select a subset of the suitable features at each node in binary decision tree. The feature subset of maximum fitness is chosen and the patterns are classified into two classes by linear decision function. After this process is repeated at each node until all the patterns are classified respectively into individual classes. In this way , binary decision tree classifier is constructed automatically. After construction binary decision tree, the final recognizer is accomplished by the learning process of neural network using a set of standard p tterns at each node. In this paper, binary decision tree classifier is applied to recognition of the defect patterns of cold mill strip and the experimental results are given to show the usefulness of the proposed scheme.

• 대한간호학회지
• /
• 제37권6호
• /
• pp.863-871
• /
• 2007

Purpose: The purpose of this study was to investigate the factors influencing nurses' clinical decision making focusing on critical thinking disposition. Methods: The subjects of this study consisted of 505 nurses working at one of the general hospitals located in Seoul. Data was collected by a self-administered questionnaire between December 2006 and January 2007. Data was analyzed by one way ANOVA, Pearson correlation coefficients, and stepwise multiple regression using SPSS Win 14.0. Results: The mean scores of critical thinking disposition and clinical decision making were 99.10 and 134.32 respectively. Clinical decision making scores were significantly higher in groups under continuing education, with a master or higher degree, with clinical experience more than 5 years, or with experts. Critical thinking disposition and its subscales have a significant correlation with clinical decision making. Intellectual eagerness/curiosity, prudence, clinical experience, intellectual honesty, self-confidence, and healthy skepticism were important factors influencing clinical decision making(adjusted $R^2=33%$). Conclusion: Results of this study suggest that various strategies such as retaining experienced nurses, encouraging them to continue with education and enhancing critical thinking disposition are warranted for development of clinical decision making.

• 제어로봇시스템학회논문지
• /
• 제6권1호
• /
• pp.98-103
• /
• 2000

This paper suggests a method to recognize the various defect patterns of a cold mill strip using a binary decision tree automatically constructed by a genetic algorithm(GA). In classifying complex patterns with high similarity like the defect patterns of a cold mill stirp, the selection of an optimal feature set and an appropriate recognizer is important to achieve high recognition rate. In this paper a GA is used to select a subset of the suitable features at each node in the binary decision tree. The feature subset with maximum fitness is chosen and the patterns are classified into two classes using a linear decision function. This process is repeated at each node until all the patterns are classified into individual classes. In this way, the classifier using the binary decision tree is constructed automatically. After constructing the binary decision tree, the final recognizer is accomplished by having neural network learning sits of standard patterns at each node. In this paper, the classifier using the binary decision tree is applied to the recognition of defect patterns of a cold mill strip, and the experimental results are given to demonstrate the usefulness of the proposed scheme.

• 한국정보시스템학회지:정보시스템연구
• /
• 제5권
• /
• pp.21-41
• /
• 1996

Linear programming has become an important tool in decision-making of modern business management. This remarkable growth can be traced to the pioneering efforts of many individuals and research organizations. The popular using of personal computers make it very easy to process those complicated linear programming models. Furthermore advanced linear programming software packages assist us to solve L.P. models without any difficult process. Even though the advanced L.P. professional packages, the needs of more detailed deterministic elements for business decisions have forced us to apply dynamic approaches for more resonable solutions. For the purpose of these problems applying to the "Mathematica" packages which is composed of mathematic tools, the simplex processes show us the flexible and dynamic decision elements included to any other professional linear programming tools. Especially we need proper dynamic variables to analyze the shadow prices step by step. And applying SAS(Statistical Analysis System) packages to the L.P. problems, it is also one of the best way to get good solution. On the way trying to the other L.P. packages which are prepared for Spreadsheets i.e., MS-Excel, Lotus-123, Quatro etc. can be applied to linear programming models. But they are not so much useful for the problems. Calculating simplex tableau is an important method to interpret L.P. format for the optimal solution. In this paper we find out that the more detailed and efficient techniques to interpret useful software of mathematica and SAS for business decision making of linear programming. So it needs to apply more dynamic technique of using of Mathematica and SAS multiple software to get more efficient deterministic factors for the sophiscated L.P. solutions.