• 대한전자공학회논문지SP
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• 제40권5호
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• pp.417-425
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• 2003

ITU-T(International Telecommunication Union-Telecommunication standardization sector)와 MPEG(Moving Picture Experts Group)에 의해서 최근 표준화가 완성된 H.264는 가변 블록 크기 움직임 추정, 복수참조영상, 1/4화소 움직임 예측/보상, 4×4 정수 DCT(Integer Discrete Cosine Transform), 율-왜곡 최적화(Rate-Distortion Optimization) 등의 새로운 부호화 기술로 H.263, MPEG-4 등 기존 비디오 표준에 비해 더 좋은 부호화 효율을 제공하고 있다. 그러나 새로운 부호화 기술들은 H.264 의 전반적인 복잡도를 심화시키는 주된 요인이기도 하다. 따라서, H.254 의 실제 응용을 용이하게 하기 위해서는 이러한 기술에 대한 고속 알고리즘이 요구된다. 본 논문에서는 율-왜곡 최적화를 통한 부호화 모드 결정시 부호화기의 복잡도에서 가장 큰 비중을 차지하는 가변 블록 크기 움직임 추정 및 공간예측 부호화를 효율적으로 생략하여 부호화 모드 결정을 빠르게 수행하는 고속 모드 결정법을 제안한다. 실험결과, 제안된 방법은 부호화 효율의 손실이 거의 없으면서도 계산법을 약 4배 향상시킨다.

• 산업경영시스템학회지
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• 제40권2호
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• pp.129-136
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• 2017

Among the information technology and automation that have rapidly developed in the manufacturing industries recently, tens of thousands of quality variables are estimated and categorized in database every day. The former existing statistical methods, or variable selection and interpretation by experts, place limits on proper judgment. Accordingly, various data mining methods, including decision tree analysis, have been developed in recent years. Cart and C5.0 are representative algorithms for decision tree analysis, but these algorithms have limits in defining the tolerance of continuous explanatory variables. Also, target variables are restricted by the information that indicates only the quality of the products like the rate of defective products. Therefore it is essential to develop an algorithm that improves upon Cart and C5.0 and allows access to new quality information such as loss cost. In this study, a new algorithm was developed not only to find the major variables which minimize the target variable, loss cost, but also to overcome the limits of Cart and C5.0. The new algorithm is one that defines tolerance of variables systematically by adopting 3 categories of the continuous explanatory variables. The characteristics of larger-the-better was presumed in the environment of programming R to compare the performance among the new algorithm and existing ones, and 10 simulations were performed with 1,000 data sets for each variable. The performance of the new algorithm was verified through a mean test of loss cost. As a result of the verification show, the new algorithm found that the tolerance of continuous explanatory variables lowered loss cost more than existing ones in the larger is better characteristics. In a conclusion, the new algorithm could be used to find the tolerance of continuous explanatory variables to minimize the loss in the process taking into account the loss cost of the products.

• 한국데이타베이스학회:학술대회논문집
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• 한국데이타베이스학회 1999년도 춘계공동학술대회: 지식경영과 지식공학
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• pp.281-287
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• 1999

Decision class analysis (DCA) is viewed as a classification problem where a set of input data (situation-specific knowledge) and output data (a topological leveled influence diagram (ID)) is given. Situation-specific knowledge is usually given from a decision maker (DM) with the help of domain expert(s). But it is not easy for the DM to know the situation-specific knowledge of decision problem exactly. This paper presents a methodology fur sensitivity analysis of DCA under incomplete information. The purpose of sensitivity analysis in DCA is to identify the effects of incomplete situation-specific frames whose uncertainty affects the importance of each variable in the resulting model. For such a purpose, our suggested methodology consists of two procedures: generative procedure and adaptive procedure. An interactive procedure is also suggested based the sensitivity analysis to build a well-formed ID. These procedures are formally explained and illustrated with a raw material purchasing problem.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 1999년도 춘계공동학술대회-지식경영과 지식공학
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• pp.281-287
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• 1999

Decision class analysis (DCA) is viewed as a classification problem where a set of input data (situation-specific knowledge) and output data(a topological leveled influence diagram (ID)) is given. Situation-specific knowledge is usually given from a decision maker (DM) with the help of domain expert(s). But it is not easy for the DM to know the situation-specific knowledge of decision problem exactly. This paper presents a methodology for sensitivity analysis of DCA under incomplete information. The purpose of sensitivity analysis in DCA is to identify the effects of incomplete situation-specific frames whose uncertainty affects the importance of each variable in the resulting model. For such a purpose, our suggested methodology consists of two procedures: generative procedure and adaptive procedure. An interactive procedure is also suggested based the sensitivity analysis to build a well-formed ID. These procedures are formally explained and illustrated with a raw material purchasing problem.

• 한국태양에너지학회 논문집
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• 제24권4호
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• pp.55-63
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• 2004

The purpose of this study is to development of life cycle cost analysis methodology of HVAC system for decision maker. The results of this study are as follows; maintenance/management, equipment construction, planning/design, and demolition/sell phases (1) To develop the cost breakdown structure for LCC in HVAC system, this study apply the method of additional pertinent level, title, CBS number, block number and variable index. (2) LCC analysis order of HVAC system compose four phase. (3) Life cycle costing influence diagram can bring us to make the most efficient decision through a visual graphical diagram that is shown relationship among variables and that decision maker traces easily from life cycle cost analysis situation.

• 한국융합학회논문지
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• 제11권2호
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• pp.93-100
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• 2020

본 연구는 성인의 행복한 삶에 영향을 미치는 요인으로 진로결정 자기효능감, 성격강점, 감사가 어떤 관련이 있는 지를 알아보고자 하였다. 조사대상자는 대학교와 대학원에 재학 중인 89명의 성인학습자를 대상으로 하였다. 자료분석을 위해 SPSS 23.0과 PROCESS Macro를 사용하였다. 본 연구에서 설정한 변인들인 진로결정 자기효능감, 성격강점, 감사, 행복한 삶 간에는 유의미한 상관이 나타났다. 또한 독립변인인 진로결정 자기효능감이 종속변인인 행복한 삶에 영향을 미치는 직접효과는 유의미 하지 않았다. 한편 매개변인인 성격강점과 감사는 유의미하여, 간접효과와 총효과는 유의한 결과가 나타났다. 진로결정 자기효능감이 행복한 삶을 직접적으로 예측하지 못하지만 성격강점과 감사를 매개한다면 행복한 삶을 예측할 수 있다는 것을 의미한다.

• 대한산업공학회지
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• 제30권4호
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• pp.267-276
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• 2004

Much of previous attention on researches of the decision tree focuses on the splitting criteria and optimization of tree size. Nowadays the quantity of the data increase and relation of variables becomes very complex. And hence, this comes to have plenty number of unnecessary node and leaf. Consequently the confidence of the explanation and forecasting of the decision tree falls off. In this research report, we propose some decision tree algorithms considering the interaction of predictor variables. A generic algorithm, the k-1 Algorithm, dealing with the interaction with a combination of all predictor variable is presented. And then, the extended version k-k Algorithm which considers with the interaction every k-depth with a combination of some predictor variables. Also, we present an improved algorithm by introducing control parameter to the algorithms. The algorithms are tested by real field credit card data, census data, bank data, etc.

• The Journal of Asian Finance, Economics and Business
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• 제7권6호
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• pp.417-425
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• 2020

This paper investigates the potential impact of external factors on bid/no-bid decision for supervision consultant service on construction project in Hanoi, the capital of Vietnam. The data used in this study are secondary data taken from annual reports and sourced from the Department of Public Procurement, Ministry of Planning and Investment in Hanoi. Besides, to identify the impact of external factors on bid/no-bid decision for supervision consultant service on construction project in Hanoi, the study collected data from 272 qualified questionnaires from bidders doing business in Hanoi. Cronbach's Alpha, EFA and regression model are used to explore the impact of each independent variable on bid/no-bid decision for supervision consultant service on construction project. The results show that three external determinants, including Project characteristic (PC), Legal codes (LC) and Competition (C) are affecting bid/no-bid decision for supervision consultant service on construction project in Hanoi. Among them, Project characteristic (PC) and Legal codes (LC) have positive relationships with bid/no-bid decision for supervision consultant service on construction project, whereas Competition (C) negatively affects bid/no-bid decision for supervision consultant service on construction project. It means the more contractors actually participate in a bid, the less bid/ no-bid decisions are made.

• 산업공학
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• 제12권4호
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• pp.551-556
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• 1999

In this paper, we compare the performance of three data mining classification algorithms(neural network, decision tree, logistic regression) in consideration of various characteristics of categorical input and output data. $2^{4-1}$. 3 fractional factorial design is used to simulate the comparison situation where factors used are (1) the categorical ratio of input variables, (2) the complexity of functional relationship between the output and input variables, (3) the size of randomness in the relationship, (4) the categorical ratio of an output variable, and (5) the classification algorithm. Experimental study results indicate the following: decision tree performs better than the others when the relationship between output and input variables is simple while logistic regression is better when the other way is around; and neural network appears a better choice than the others when the randomness in the relationship is relatively large. We also use Taguchi design to improve the practicality of our study results by letting the relationship between the output and input variables as a noise factor. As a result, the classification accuracy of neural network and decision tree turns out to be higher than that of logistic regression, when the categorical proportion of the output variable is even.

• Journal of Information Technology Applications and Management
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• 제17권3호
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• pp.163-189
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• 2010

The purpose of this research is to develop a decision-making model for the calculation of the National Disaster Management System's standard prevention workforce quota. The final purpose of such model is to support in arranging a rationally sized prevention workforce for local authorities by providing information about its calculation in order to support an effective and efficient disaster management administration. In other words, it is to establish and develop a model that calculates the standard disaster prevention workforce quota for basic local governments in order to arrange realistically required prevention workforce. In calculating Korea's prevention workforce, it was found that the prevention investment expenses, number of prevention facilities, frequency of flood damage, number of disaster victims, prevention density, and national disaster recovery costs have positive influence on the dependent variable when the standard prevention workforce was set as the dependent variable. The model based on the regression analysis-which consists of dependent and independent variables-was classified into inland mountainous region, East coast region, Southwest coastal plain region to reflect regional characteristics for the calculation of the prevention workforce. We anticipate that the decision-making model for the standard prevention workforce quota will aid in arranging an objective and essential prevention workforce for Korea's basic local authorities.