• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권6호
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• pp.1599-1618
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• 2024

Access control has always been one of the effective methods to protect data security. However, in new computing environments such as big data, data resources have the characteristics of distributed cross-domain sharing, massive and dynamic. Traditional access control mechanisms are difficult to meet the security needs. This paper proposes CACM-MMSR to solve distributed cross-domain access control problem for massive resources. The method uses blockchain and smart contracts as a link between different security domains. A permission decision model migration method based on access control logs is designed. It can realize the migration of historical policy to solve the problems of access control heterogeneity among different security domains and the updating of the old and new policies in the same security domain. Meanwhile, a semantic reasoning-based permission decision method for unstructured text data is designed. It can achieve a flexible permission decision by similarity thresholding. Experimental results show that the proposed method can reduce the decision time cost of distributed access control to less than 28.7% of a single node. The permission decision model migration method has a high decision accuracy of 97.4%. The semantic reasoning-based permission decision method is optimal to other reference methods in vectorization and index time cost.

• Architectural research
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• 제12권2호
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• pp.85-92
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• 2010

In recent years, construction projects have been forced to cope with lack of skilled labor and increasing hazard circumstance of human operations. A construction robotic system has been frequently accomplished as one alterative for overcoming these difficulties in increasing construction quality, enhancing productivity, and improving safety. However, while the complexity of such a system increases, there are few ways to carry out an assessment of the system. This paper introduces a knowledge-based multi-criteria decision-making process to assist decision makers in systematically evaluating an automated system for a given project and quantifying its system performance index. The model employs linguistic terms and fuzzy numbers in attempts to deal with the vagueness inherent in experts' or decision makers' subjective opinions, considering the contribution resulted from their knowledge on a decision problem. As an illustrative case, the system, called Robotic-based Construction Automation, for constructing steel erection of high-rise buildings was applied into this model. The results show the model's capacities and imply the application to other extended types of construction robotic systems.

• 한국국방경영분석학회지
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• 제3권1호
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• pp.51-82
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• 1977

Decision making is a function of many variables, but among these, human burden (soft-ware) and machine burden (hard-ware) are critical. Decision Maker is rather concerned with the soft-ware and just wants to have machine calculate the quantitative arithmetic involved in the decision-making study, because he is responsible for that decision whether or not he knows details about the techniques used by his staffs. From the point of these considerations, computer-assisted war game model has its significance in military decision making. The major outcome of this model is time-phased FEBA movement. FEBA is moved mainly by the ratio of the Index of Combat Effectiveness (ICE). To calculate ICE, Ground Forces are concerning the Index of Firepower (IFP) of individual weapons and in the case of Air Force, sorties are allocated into each sector, and added to the Ground Force IFP. With the ratio of total ICE, FEBA is moved according to the War Game Tables and process is repeated after consideration of casualties. This model is used by IBM-370/135 in MND computer room and also tested by IBM-3741/3717 established at ROKA HQ.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2006년도 Asia Navigation Conference
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• pp.144-153
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• 2006

In order to take TC forecasts from different observatories into consideration, and make quantitative assessment and analysis for avoiding TC routes from the view of safety and cost, a new safe-economic decision making method of TC avoidance routing on ocean was put forward. This model is based on combining forecast of TC trace based on neural networks, technical method to determine the future TC wind and wave fields, technical method of fuzzy information optimization, risk analysis theory, and meteorological-economic decision making theory. It has applied to the simulation of MV Tianlihai's shipping on ocean. The result shows that the model can select the optimum plan from 7 plans, the selected plan is in accordance with the one selected by experienced captains.

• Journal of the Korean Data and Information Science Society
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• 제23권2호
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• pp.299-307
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• 2012

데이터마이닝은 주어진 데이터베이스에서 항목간의 흥미로운 관계를 찾아내는 기법으로서 의사결정나무는 데이터마이닝의 대표적인 알고리즘이라고 할 수 있다. 의사결정나무는 관심대상이 되는 집단을 몇 개의 소집단으로 분류하거나 예측을 수행하는 방법이다. 일반적으로 연구자가 의사결정나무 모형을 생성 할 때 모형 생성의 기준 및 입력 변수의 수에 따라 복잡한 모형이 생성되기도 한다. 특히 의사결정나무 모형에서 입력 변수의 수가 많을 경우 생성된 모형은 복잡한 형태가 될 수 있고, 모형 분석이 어려울 수도 있다. 만일 입력변수에서 주변조건부 변수 (매개변수, 외적변수)가 존재한다면 이 입력변수는 직접적인 관련성이 없는 것으로 판단한다. 이에 본 논문에서는 주변조건부 변수를 고려하여 의사결정나무모형을 생성하는 방법을 제시하고 그 효율성을 파악하기 위하여 실제 자료에 적용하고자 한다.

• International Journal of Contents
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• 제13권2호
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• pp.57-65
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• 2017

Recently, due to the significance of Industry 4.0, the manufacturing industry is developing globally. Conventionally, the manufacturing industry generates a large volume of data that is often related to process, line and products. In this paper, we analyzed causes of defective products in the manufacturing process using the decision tree technique, that is a well-known technique used in data mining. We used data collected from the domestic manufacturing industry that includes Manufacturing Execution System (MES), Point of Production (POP), equipment data accumulated directly in equipment, in-process/external air-conditioning sensors and static electricity. We propose to implement a model using C4.5 decision tree algorithm. Specifically, the proposed decision tree model is modeled based on components of a specific part. We propose to identify the state of products, where the defect occurred and compare it with the generated decision tree model to determine the cause of the defect.

• 한국경영과학회지
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• 제27권4호
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• pp.111-126
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• 2002

This paper presents an interactive decision procedure to aggregate each group member's preferences when each group member articulates his or her preference information incompletely. An index, an indicative for the preference strength between alternatives, is derived to aid each decision maker to articulate preference information about alternatives. We develop a mathematical programming model that can establish dominance relations when the preference information about values of alternatives, attribute weights, and group member's importance weights are provided incompletely. Also, the preference relation between alternatives is to be considered in the model. Based on the preference strength measure and mathematical model, we develop an interactive group decision support procedure.

• Asia pacific journal of information systems
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• 제11권2호
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• pp.181-203
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• 2001

As the Internet is used extensively, multimedia information becomes more prevailing and accessible. However, legacy decision support systems rarely mention how to put such multimedia contents into practical use for decision making and support. In particular, no proposals have yet been made on how to integrate the decision technologies and multimedia databases in model management systems. Hence, the aim of this paper is to propose a new model management method to integrating decision technologies and an image database management system to create a multimedia decision support. For this purpose, extended ARG and structured modeling techniques are adopted, to represent image contents and mathematical models respectively. A web-based prototype system is presented to illustrate the feasibility and usability of the methodology.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2008년도 춘계 학술발표회 초청강연 및 논문집
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• pp.1365-1371
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• 2008

Based on the data obtained from field investigation and soil testing to slope hazards occurrence section and non-occurrence section in gneiss area, a prediction technique was developed by the use of a decision tree model. The slope hazards data of Seoul and Kyonggi Province were 104 sections in gneiss area. The number of data applied in developing prediction model was 61 sections except a vacant value. The statistical analyses using the decision tree model were applied to the entrophy index. As the results of analyses, a slope angle, a degree of saturation and an elevation were selected as the classification standard. The prediction model of decision tree using entrophy index is most likely accurate. The classification standard of the selected prediction model is composed of the slope angle, the degree of saturation and the elevation from the first choice stage. The classification standard values of the slope angle, the degree of saturation and elevation are $17.9^{\circ}$, 52.1% and 320m, respectively.

• 제어로봇시스템학회논문지
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• 제13권8호
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• pp.760-768
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• 2007

This paper introduces an emotional behavior decision model based on linear system for intelligent service robots. An emotional model should make different behavior decisions according to the purpose of the robots. We propose an emotional behavior decision model which can change the character of intelligent service robots and make different behavior decisions although the situation and environment remain the same. We defined each emotional element such as reactive dynamics, internal dynamics, emotional dynamics, and behavior dynamics by state dynamic equations. The proposed system model is a linear dynamic system. If you want to add one external stimulus or behavior, you need to add just one dimensional vector to the matrix of external stimulus or behavior dynamics. The case of removing is same. The change of reactive dynamics, internal dynamics, emotional dynamics, and behavior dynamics also follows the same procedure. We implemented a cyber robot and an emotional head robot using 3D character for verifying the performance of the proposed emotional behavior decision model.