• 제어로봇시스템학회:학술대회논문집
• /
• 1996.10a
• /
• pp.275-278
• /
• 1996

This fault diagnosis system consists of qualitative models, qualitative interpreter, and inference engine. Qualitative models are formed by analysis of the relationships between faults and behaviors of sensor trends, which are described by state transition trees. Qualitative interpreter outputs confidence factors with three qualitative quantities which represent the states of sensor trends. And then, the possible faults are detected by inference module which matches the states of trends within a window size with the qualitative models using the well-known min-max operation.

• Journal of Fisheries and Marine Sciences Education
• /
• v.29 no.1
• /
• pp.306-314
• /
• 2017

The purpose of this study is to explore the possibility of qualitative evaluation and applicable models in the evaluation area of educational program. To this end, the concept and characteristics of qualitative evaluation are examined, and grounded theory is selected as a suitable methodology for evaluation, and its characteristics and procedures are described. Because qualitative evaluation focuses on the spontaneous practice elements of the site, it can supplement the quantitative evaluation of the variables set in advance. The researcher presented the theory of qualification as a methodology for qualitative evaluation, aiming to extract the theory explaining the phenomenon among the qualitative methodologies.

• Journal of the Korean Statistical Society
• /
• v.3 no.2
• /
• pp.103-115
• /
• 1974

During the last few years there has been an interest in models for qualitative attributes, where complex signifies that affection may be caused in two or more ways [1-3]. These models have in common the prediction of variable recurrence risks among families with given parental phenotpes. Segregation analysis has covered only a few cases [4,5]. The present paper extends segregation analysis to three complex models under two mode of ascertainment.

• Journal of Institute of Control, Robotics and Systems
• /
• v.10 no.5
• /
• pp.450-457
• /
• 2004

In this research, the automatic synthesis of knowledge models is proposed. which are the basis of the methods using qualitative models adapted widely in fault diagnosis and hazard evaluation of chemical processes. To provide an easy and fast way to construct accurate causal model of the target process, the Role-Behavior modeling method is developed to represent the knowledge of modularized process units. In this modeling method, Fault-Behavior model and Structure-Role model present the relationship of the internal behaviors and faults in the process units and the relationship between process units respectively. Through the multiple modeling techniques, the knowledge is separated into what is independent of process and dependent on process to provide the extensibility and portability in model building, and possibility in the automatic synthesis. By taking advantage of the Role-Behavior Model, an algorithm is proposed to synthesize the plant-wide causal model, Fault-Causality Graph (FCG) from specific Fault-Behavior models of the each unit process, which are derived from generic Fault-Behavior models and Structure-Role model. To validate the proposed modeling method and algorithm, a system for building FCG model is developed on G2, an expert system development tool. Case study such as CSTR with recycle using the developed system showed that the proposed method and algorithm were remarkably effective in synthesizing the causal knowledge models for diagnosis of chemical processes.

• Transactions of the Korean Society of Mechanical Engineers
• /
• v.16 no.7
• /
• pp.1351-1362
• /
• 1992

Qualitative models in model-based expert system needs modeling paradigm which provides intelligent control of modeling assumptions and extracts robust inferences without quantitative information about the system to be modeled. Qualitative reasoning methodologies has proved the property of the completeness but not the soundness to the corresponding quantitative model. We propose new methodology of qualitative reasoning by introducing the concept of Centroid-Oriented Composite Interval to improve the soundness problem. Arithmetic operations and equivalence classes were composed using this definition. Qualitative simulation results were compared to Kuipers's results and the improvements in the soundness problem is verified.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.14 no.3
• /
• pp.115-125
• /
• 2018

In order to examine the ways to improve the efficiency of R&D investment, this paper presents analysis on both quantitative and qualitative efficiency of R&D projects. As Korea's R&D investment has significantly increased in recent years, the efficiency of R&D investment has attracted attention. In this paper, a Data Envelopment Analysis(DEA) method is used to construct models for quantitative efficiency and qualitative efficiency analysis. Based on a cases of agricultural R&D projects of Korea, the efficiency of national R&D projects were analyzed and their quantitative and qualitative efficiencies are compared. As a result, statistically significant difference between quantitative and qualitative efficiency was found. Also, characteristics of Decision Making Units(DMUs) which can influence both quantitative and qualitative efficiency were identified. In particular, the stage of a R&D project has significant impact on R&D efficiency. This study suggests that in order to enhance R&D efficiency both quantitative and qualitative nature of outputs should be considered when measuring R&D efficiency.

• Journal of Educational Research in Mathematics
• /
• v.27 no.1
• /
• pp.23-49
• /
• 2017

This study examined two current learning models for covariational reasoning(Carlson et al.(2002), Thompson, & Carlson(2017)), applied the models to teaching two $9^{th}$ grade students, and analyzed the results according to the types of graphs(a quantitative graph or qualitative graph). Results showed that the model of Thompson and Carlson(2017) was more useful than that of Carlson et al.(2002) in figuring out the students' levels in their quantitative graphing activities. Applying Carlson et al.(2002)'s model made it possible to classify levels of the students in their qualitative graphs. The results of this study suggest that not only quantitative understanding but also qualitative understanding is important in investigating students' covariational reasoning levels. The model of Thompson and Carlson(2017) reveals more various aspects in exploring students' levels of quantitative understanding, and the model of Carlson et al.(2002) revealing more of qualitative understanding.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2001.10a
• /
• pp.363-366
• /
• 2001

It is very difficult to maintain the performance of estimation models for the new breed of projects since the computing environment changes so rapidly in terms of programming languages, development tools, and methodologies. So, we propose to use the relevant cases for a neural network model, whose cost is the decreased number of cases. To balance the relevance and data availability, the qualitative input factors are used as criteria of data classification. With the data sets that have the same value for certain qualitative input factors, we can eliminate the factors from the model making reduced neural network models. So we need to seek the optimally reduced neural network model among them. To find the optimally case-selective neural network, we propose the search techniques and sensitivity analysis between data points and search space.

• Nuclear Engineering and Technology
• /
• v.53 no.2
• /
• pp.376-385
• /
• 2021

Probabilistic risk assessment (PRA) has improved its elemental technologies used for assessing external events since the Fukushima Daiichi Nuclear Power Station Accident in 2011. HRA needs to be improved for analyzing tasks performed under extreme conditions (e.g., different actors responding to external events or performing operations using portable mitigation equipment). To make these improvements, it is essential to understand plant-specific and scenario-specific conditions that affect human performance. The Nuclear Risk Research Center (NRRC) of the Central Research Institute of Electric Power Industry (CRIEPI) has developed an HRA guide that compiles qualitative analysis methods for collecting plant-specific and scenario-specific conditions that affect human performance into "narratives," reflecting the latest research trends, and models for analysis of tasks under extreme conditions.

• IE interfaces
• /
• v.18 no.4
• /
• pp.418-430
• /
• 2005

We establish an efficient strategy for construction and operation of data consolidation center for multi-organization in public sector. First, we introduce important concepts on data consolidation center in public sector, and draw some success factors by analyzing several foreign and domestic cases. Second, we construct all the possible logical operational models of the center and investigate the properties and feasibility of the models. Third, we suggest a virtual operational environment for the two representative models selected by feasibility criteria among the possible logical models, and compare the two models in terms of operational cost. We also utilize AHP methodology to evaluate qualitative opinions on the two models from several experts in public information systems. As a result, we find the best alternative is the case in which all infrastructure and facilities for the center are provided by government, and common essential IT operations are integrated, associated data are consolidated and the whole operational work are outsourced to specialized IT operations service providers.