• 한국정보처리학회논문지
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• 제7권4호
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• pp.1150-1159
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• 2000

This paper presents an automatic text categorization model that improves the accuracy by combining statistical and knowledge-based categorization methods. In our model we apply knowledge-based method first, and then apply statistical method on the text which are not categorized by knowledge-based method. By using this combined method, we can improve the accuracy of categorization while categorize all the texts without failure. For statistical categorization, the vector model with Inverted Category Frequency (ICF) weighting is used. For knowledge-based categorization, Phrasal Patterns and Keyword Sets are introduced to represent sentence patterns, and then pattern matching is performed. Experimental results on new articles show that the accuracy of categorization can be improved by combining the tow different categorization methods.

• 한국정밀공학회지
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• 제16권8호
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• pp.59-70
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• 1999

This paper deals with automated computer-aided process planning by which designers can determine operation sequences even if they have little experience in the design of press working products. The computer-aided process planning in hot forging, deep drawing and blanking requires many kinds of technical and empirical skills based on investigation and collection of the knowledge of their processes. An approach to the CAPP system is based on the knowledge-based rules and the process knowledge base consisting of process planning rules is built. The methodology adopted to develop the system is elaborated in this paper. This system has been written in AutoLISP on the AutoCAD with a personal computer and provides powerful capabilities for process planning of hot forging, cold forging, deep drawing and blanking products.

• 한국국방경영분석학회지
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• 제26권2호
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• pp.55-74
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• 2000

A knowledge-based with production rules is a representation of static knowledge of an expert. On the other hand, a real system such as the stock market is dynamic in nature. Therefore we need a method to reflect the dynamic nature of a system when we make inferences with a knowledge-based system. This paper suggests a strategy of dynamic inference that can be used to take into account the dynamic behavior of decision-making with the knowledge-based system consisted of fuzzy production rules. A degree of match(DM) between actual input information and a condition of a rule is represented by a value [0,1]. Weights of relative importance of attributes in a rule are obtained by the AHP(Analytic Hierarchy Process) method. Then these weights are applied as exponents for the DM, and the DMs in a rule are combined, with the Min operator, into a single DM for the rule. In this way, the importance of attributes of a rule, which can be changed from time to time, can be reflected in an inference with fuzzy production systems.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2001년도 추계학술대회논문집 II
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• pp.633-639
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• 2001

This paper proposes a knowledge-based expert system. which is assembled into hardware organized with sensor module. AID converter, USB. data acquisition PC and software composed of monitoring and diagnosis module combined with a frame-based method using Sohre's chart and a rule-based method. Vibration signals using various sensors are acquired by AID converter. transferred into PC and processed to obtain a continuous monitoring of the machine status displayed into several plots. Through combining frame-base which covers wide vibration causes with rule-base which gives relatively specified diagnosis results, high accuracy of fault diagnosis can be guaranteed and knowledge base can be easily extended by adding new causes or symptoms. Some examples using experimental data show the good feasibility of the proposed algorithm for condition monitoring and diagnosis of industrial rotating machinery.

• 한국멀티미디어학회논문지
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• 제17권5호
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• pp.631-639
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• 2014

Recently, research on Media Access Control (MAC) techniques for underwater acoustic communication has been conducted actively. For successful acoustic communication in underwater conditions, development of environmentally adaptive MAC techniques, which is taking narrow bandwidth, distance, depth, noise level, salinity, multipath and etc into account, is an especially important work. In this paper, knowledge based system is introduced not only to obtain adaptive and optimal communication parameters but also increase network efficiency and availability by requesting change of MAC techniques based on decisions from knowledge-based system Smart Decision Block (SDB). Computer simulations were also conducted to verify the performance of the proposed system in underwater conditions.

• 무역학회지
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• 제45권2호
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• pp.31-49
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• 2020

The purpose of this study is to investigate the effects of knowledge-based resource and ambidextrous capability on their export performance of small and medium-sized enterprises (SMEs). Drawing on an extensive review of the literature on Knowledge-based resource and ambidextrous capability, hypotheses are developed and tested using a sample of 284 SMEs in South Korea. Structural equation modeling was applied. As a result of analysis, first, international entrepreneurship has a significant effect on ambidextrous capability. Second, human capital has significant influence on ambidextrous capability. Third, ambidextrous capability has a significant effect on export performance. The results indicate that their knowledge-based resources ware significant driver of their ambidextrous capability. and that their ambidextrous capability was significant driver of their export performance. In the final conclusion section, implications and limitations of research results and suggestions for future research are discussed.

• 한국간호교육학회지
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• 제22권3호
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• pp.274-282
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• 2016

Purpose: This study is aimed at identifying factors influencing attitudes of Evidence-Based Practice among nursing students. Methods: 202 nursing students were recruited from B city and G district. The questionnaires included critical thinking dispositions, information retrieval skills, knowledge and attitudes of Evidence-Based Practice, and characteristics. Data were analyzed by SPSS/Win 21.0 using descriptive statistics, t-test, ANOVA, Pearson correlation, and stepwise multiple regressions. Results: The average score of undergraduate nursing students for Evidence-Based Practice attitudes was $32.92{\pm}4.57$. Evidence-Based Practice attitudes had positive correlation with critical thinking disposition (r=.53, p<.001), information retrieval skills (r=.45, p<.001) and Evidence-Based Practice knowledge (r=.42, p<.001). Factors influencing Evidence-Based Practice attitudes were critical thinking dispositions (${\beta}=.45$) and Evidence-Based Practice knowledge (${\beta}=.30$). Total variance was explained about 35.3% (F=55.80, p<.001). Conclusion: These results show that teaching strategies that enhance critical thinking dispositions are recommended to improve Evidence-Based Practice attitudes among nursing students. Also, nursing education should include a regular Evidence-Based Practice curriculum to improve Evidence-Based Practice knowledge as is necessary for students to improve information retrieval skill. Reading nursing articles can help nursing students comprehend the up-to-data evidence of clinical practice.

• 국제초고층학회논문집
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• 제4권1호
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• pp.85-90
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• 2015

Advances in the technology of computational design are giving architects and engineers the opportunity to analyze buildings with complex geometries. This study explores the optimization and automation process using the parametric design method, and uses digital tools to achieve surface representation and panelization for curved shaped office buildings. In this paper, we propose parametric algorithms of dimensional and geometric constraints using the Knowledge-ware scripts embedded in Gehry Technologies' Digital Project. The knowledge-based design methods proposed in this study can be used to systemize the knowledge possessed by experts in the form of data. Such knowledge is required to promote collaboration between designers and engineers in the process of CAD/CAE/CAM. The aim of this study is to integrate the process into design, which establishes an integrated process. This integration enables two-way feedback between design and construction data by combining the methods used in designing, engineering, and construction.

• 디지털융복합연구
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• 제7권2호
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• pp.51-62
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• 2009

Most studies of organizational effectiveness previously done, have measured financial performance such as productivity, efficiency or subjective performance such as a commitment, satisfaction, and turnover intention of employees. However, these measurements have limitations to evaluate a organizational effectiveness in recent knowledge information era because evaluation of organizational effectiveness in knowledge-based society needs measurements in various aspects such as financial, customer, internal business process, and learning and growth. The purpose of this study is to overcome these problems and to introduce an appropriate system for evaluation of organizational effectiveness under knowledge management paradigm. In this paper, we suggest a Balanced Scorecard(BSC) as a new measurement standard of organizational effectiveness in a knowledge information era. The balanced scorecard is designed to help firms that have historically overemphasized short-term financial performance. When measuring organizational effectiveness through Balanced Scorecard(BSC) suggested by Kaplan and Norton[31], it is to present the measurement indices that can cover the limitation of the past evaluation indices of organizational effectiveness.

• 한국경영과학회지
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• 제25권3호
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• pp.91-107
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• 2000

The linear programming model is a special form of useful knowledge that is embedded in a database. Since formulating models from scratch requires knowledge-intensive efforts, knowledge-based formulation support systems have been proposed in the Decision Support Systems area. However, they rely on the assumption that sufficient domain knowledge should already be captured as a specific knowledge representation form. Hence, the purpose of this paper is to propose a methodology that finds useful knowledge on building linear programming models from a database. The methodology consists of two parts. The first part is to find s first-cut model based on a data dictionary. To do so, we applied the General Problem Solver(GPS) algorithm. The second part is to discover a second-cut model by applying neural network technique. An illustrative example is described to show the feasibility of the proposed methodology.