• Structural Engineering and Mechanics
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• 제63권2호
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• pp.237-249
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• 2017

The Self-Organization Feature Map as an unsupervised network is very widely used these days in engineering science. The applied network in this paper is the Self Organization Feature Map with constant weights which includes Kohonen Network. In this research, Reinforced Concrete Shear Wall buildings with different stories and heights are analyzed and a database consisting of measured fundamental periods and characteristics of 78 RC SW buildings is created. The input parameters of these buildings include number of stories, height, length, width, whereas the output parameter is the fundamental period. In addition, using Genetic Algorithm, the structure of the Self-Organization Feature Map algorithm is optimized with respect to the numbers of layers, numbers of nodes in hidden layers, type of transfer function and learning. Evaluation of the SOFM model was performed by comparing the obtained values to the measured values and values calculated by expressions given in building codes. Results show that the Self-Organization Feature Map, which is optimized by using Genetic Algorithm, has a higher capacity, flexibility and accuracy in predicting the fundamental period.

• 한국시스템다이내믹스연구
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• 제3권2호
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• pp.49-68
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• 2002

The intent of this study is to develop system dynamics model for assessment of organizational and human factors in nuclear power plant which can contribute to secure the nuclear safety. Previous studies are classified into two major approaches. One is engineering approach such as ergonomics and probability safety assessment(PSA). The other is social science approach such like sociology, organization theory and psychology. Both have contributed to find organization and human factors and to present guideline to lessen human error in NPP. But, since these methodologies assume that relationship among factors is independent they don't explain the interactions among factors or variables in NPP. To overcome these limits, we have developed system dynamics model which can show cause and effect among factors and quantify organizational and human factors. The model we developed is composed of 16 functions of job process in nuclear power, and shows interactions among various factors which affects employees' productivity and job quality. Handling variables such like degree of leadership, adjustment of number of employee, and workload in each department, users can simulate various situations in nuclear power plant in the organization side. Through simulation, user can get insight to improve safety in plants and to find managerial tools in the organization and human side. Analyzing pattern of variables, users can get knowledge of their organization structure, and understand stands of other departments or employees. Ultimately they can build learning organization to secure optimal safety in nuclear power plant.

• 경영과정보연구
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• 제4권
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• pp.409-441
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• 2000

The purpose of this study is to present the problem of the introduction and management and the method of activation of the team organization in college administrative systems through the theoretical study about the team systems and the actual proof study already introduced and operated in colleges and enterprises. The scopes of the subject of theoretical study are the concept of team systems, the type of systems, the strategy of introduction and management, the problem of management and the tactics of activation. The scopes of the theoretical study are the field of systematic structure and that of introduction and management. In order to activate the team organization of college administrative systems, we must study three points such as empowerment, construction of learning team and the method of personal management. For the sake of conducting the team organization efficiently, we must consider four fields. They are as follows: First, considering the continual efforts for reorganization is the most important precondition. Second, the device of supplement related with introduction of systems such as evaluation of merits, promotion and budget must be prepared as soon as possible. Third, in order to introduce the systems, the improvement of systems is needed. Fourth, it must be accompanied by redesigning the whole business process. Especially, in the introduction of team organization, it is important above all to introduce suitable constitution or situation of business. And making a constant effort and preparation for solving problems is essential to successful management of team organization.

• 한국정보시스템학회지:정보시스템연구
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• 제17권1호
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• pp.83-111
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• 2008

The purpose of this study is to identify which factors are important for learning performance and the moderating effects of self-regulated factors such as elaboration and organization between users characteristic(perceived usefulness, preparatory education, internet experience) and learning performance. To Accomplish these research purpose, this study performed a survey and 173 response were used for statistical analysis. The results of this study are as follows: First, 7 factors(ease of use, interactivity, accuracy, media richness, perceived usefulness, preparatory education, internet experience) had significant impacts on learning performance whereas reliability did not. Second, the moderating effects of self-regulated factors showed that Elaboration of self-regulated factors can be considered as a significant moderating variable between 2 factors(perceived usefulness, internet experience) and teaming performance.

• 한국통신학회논문지
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• 제17권12호
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• pp.1362-1370
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• 1992

• International Journal of Quality Innovation
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• 제2권2호
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• pp.145-150
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• 2001

The revised ISO9000 family of standards represents a significant improvement on the 1994 version and, if implemented well within organizations, should facilitate the development of effective, process-oriented Quality Management Systems. This paper describes how the International Standardized Testing Organization (ISTO) tests the understanding of ISO9000 : 2000, and presents an analysis of the results of the first examinations held in the UK, USA, Mexico and Hong Kong, in February and March 2001.

• 한국항공운항학회지
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• 제14권4호
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• pp.48-59
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• 2006

This Study focused on the process of technology transfer for the aircraft development program by the strategic alliance. Especially, this study showed how the learning firms absorb new technology from the foreign leading company. This case study concludes that teachability, asset specificity, relation capital with partner, information sharing system in organization and knowledge base are key factors for absorbing the new technology from the technology leading partner.

• 간호행정학회지
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• 제11권4호
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• pp.469-476
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• 2005

Purpose: This study is to identify the effect of organizational characteristics on knowledge sharing in a general hospital nurses. Method: The objects of this study were 358 nurses who had worked in a general Hospital. Data were collected from May, 3rd to May, 10th in 2004 through questionnaire. Five structured Instruments were used to collect the data. Result: The knowledge sharing of nurses was the positive correlation with openness of communication, learning orientation, the support of director of nursing department, and application of information technology(r=.431${\sim}$.611, p=.000). The degree of nurse's knowledge sharing showed a significant difference according to nurses' education level, duration of working, duty shift, working field, position in Hospital(p=.05). Openness of communication appeared into a most important predictor in knowledge sharing of Nurses, and then was learning orientation, the support of director of nursing department, application of information technology in order(p=.000). All of these variables explained 55.1% of knowledge sharing of nurses. Conclusion: To increase knowledge sharing of nurses, nursing organization will have to make up organization culture of opening communication and learning orientation of nurse, promote up the support of director of nursing department and application of information technology.

• Journal of Information Technology Applications and Management
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• 제17권2호
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• pp.19-45
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• 2010

This research has analyzed the differentiated influence of organizational variables(an organization's learning culture and organizational support networks) and personal variables(the individual's motivation to learn and self-efficacy) on the process of gaining and using of knowledge. These two variables have been regarded as the major variables for the successful learning of 6Sigma, according to Social Cognitive Theory. In addition, this research has proven the role structure of the abovementioned two variables through a suitable methodology(Hierarchical Linear Model). In regard to this methodology, the different hierarchical level of the personal variable and organizational variable was especially focused on, and the effect of interaction between the high level and the low level was considered in detail. Considering the current situation, in that the importance of organizational factor and personal factor has been emphasized but the accurate role of each variable has not been verified, the research model is thought to help to establish an effective strategy to implement 6 Sigma.

• Soft Computing and Machine Intelligence
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• 제1권1호
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• pp.1-10
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• 2021

Analysis and Tracking of bug reports is a challenging field in software repositories mining. It is one of the fundamental ways to explores a large amount of data acquired from defect tracking systems to discover patterns and valuable knowledge about the process of bug triaging. Furthermore, bug data is publically accessible and available of the following systems, such as Bugzilla and JIRA. Moreover, with robust machine learning (ML) techniques, it is quite possible to process and analyze a massive amount of data for extracting underlying patterns, knowledge, and insights. Therefore, it is an interesting area to propose innovative and robust solutions to analyze and track bug reports originating from different open source projects, including Mozilla and Eclipse. This research study presents an ML-based classification model to analyze and track bug defects for enhancing software engineering management (SEM) processes. In this work, Artificial Neural Network (ANN) and Naive Bayesian (NB) classifiers are implemented using open-source bug datasets, such as Mozilla and Eclipse. Furthermore, different evaluation measures are employed to analyze and evaluate the experimental results. Moreover, a comparative analysis is given to compare the experimental results of ANN with NB. The experimental results indicate that the ANN achieved high accuracy compared to the NB. The proposed research study will enhance SEM processes and contribute to the body of knowledge of the data mining field.