• Proceedings of the IEEK Conference
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• 2001.06c
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• pp.237-240
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• 2001

An image processing and decision making method for the Automatic Surveillance System is proposed. The aim of our Automatic Surveillance System is to detect a moving object and make a decision on whether it is human or not. Various object features such as the ratio of the width and the length of the moving object, the distance dispersion between the principal axis and the object contour, the eigenvectors, the symmetric axes, and the areas if the segmented region are used in this paper. These features are not the unique and decisive characteristics for representing human Also, due to the outdoor image property, the object feature information is unavoidably vague and inaccurate. In order to make an efficient decision from the information, we use a fuzzy rules base system ai an approximate reasoning method. The fuzzy rules, combining various object features, are able to describe the conditions for making an intelligent decision. The fuzzy rule base system is initially constructed by heuristic approach and then, trained and tasted with input/output data Experimental result are shown, demonstrating the validity of our system.

• Korean Journal of Hydrosciences
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• v.4
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• pp.65-79
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• 1993

Selection of the best operating rule among a set of alternatives for a multipurpose reservoir system operation requires to evaluate many minor criteria in addition to the major objectives assessed to the system. These problems are sufficiently complex and difficult that they are beyond heuristic decision rules and experiences in case several noncommensurable multiple criteria are included in the evaluation. With the assistance of multicriterion decision analysis techniques, it is possible to select the best one among various alternatives by systematically comparing and ranking the alternatives with respect to the criteria of choice. Evaluation criteria for multipurpose reservoir system operating rules were identified and defined, and the multicriterion decision analysis techniques were applied to evaluate the four existing operating rules of the Chungju multipurpose project according to the identified nine multiple criteria. The application results show that the methodology is very efficient to select the best operation alternative among a finite number of operating rules with many evaluation criteria for a large-scale reservoir system operation.

• The Mathematical Education
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• v.32 no.1
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• pp.75-90
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• 1993

Decision making in uncertain situations that preferences of decision maker is important consists of a series of related decisions. Rule-based expert system can not represent such a complex decision problems. For these decision problems, this paper suggests a new methods IDPI(Influence Diagram-based Probabilistic Inference) which combines model-based knowledge representation and probabilistic inference, and implements a career counsellor for the university students using the combined methods.

• Journal of Integrative Natural Science
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• v.5 no.3
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• pp.186-189
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• 2012

For the mean vector of a p-variate normal distribution ($p{\geq}3$), the optimal estimation within the class of James-Stein type decision rules under the quadratic loss are given when the underlying distribution is that of a variance mixture of normals and when the norm ${\parallel}\underline{{\theta}}{\parallel}$ in known. It also demonstrated that the optimal estimation within the class of Lindley type decision rules under the same loss when the underlying distribution is the previous type and the norm ${\parallel}{\theta}-\overline{\theta}\underline{1}{\parallel}$ with $\overline{\theta}=\frac{1}{p}\sum\limits_{i=1}^{n}{\theta}_i$ and $\underline{1}=(1,{\cdots},1)^{\prime}$ is known.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.45 no.7
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• pp.53-61
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• 2008

Consider a typical wireless sensor network in which stem nodes form the backbone network of mesh topology while each stem node together with leaf nodes in its vicinity forms a subnetwork of star topology. In such a wireless sensor network, we must heed the following when we design a MAC scheme supporting the packet delivery from a leaf node to a stem node. First, leaf nodes are usually battery-powered and it is difficult to change or recharge their batteries. Secondly, a wireless sensor network is often deployed to collect and update data periodically. Late delivery of a data segment by a sensor node causes the sink node to defer data processing and the data segment itself to be obsolete. Thirdly, extensive signaling is extremely limited and complex computation is hardly supported. Taking account of these facts, a MAC scheme must be able to save energy and support timeliness in packet delivery while being simple and robust as well. In this paper, we propose a version of ALOHA as a MAC scheme for a wireless sensor network. While conserving the simplicity and robustness of the original version of ALOHA, the proposed version of ALOHA possesses a distinctive feature that a sensor node decides between stop and continuation prior to each delivery attempt for a packet. Such a decision needs a stopping rule and we suggest a Bayes stopping rule. Note that a Bayes stopping rule minimizes the Bayes risk which reflects the energy, timeliness and throughput losses. Also, a Bayes stopping rule is practical since a sensor node makes a decision only using its own history of delivery attempt results and the prior information about the failure in delivery attempt. Numerical examples confirm that the proposed version of ALOHA employing a Bayes stopping rule is a useful MAC scheme in the severe environment of wireless sensor network.

• Journal of Electrical Engineering and Technology
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• v.11 no.6
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• pp.1684-1692
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• 2016

In order to adapt the fast dynamic performances of Buck DC/DC converter, and reduce the influence on converter performance owing to uncertain factors such as the disturbances of parameters and load, a control strategy based on two-dimensional hybrid cloud model is proposed. Firstly, two cloud models corresponding to the specific control inputs are determined by maximum determination approach, respectively, and then a control rule decided by the two cloud models is selected by a rule selector, finally, according to the reasoning structure of the rule, the control increment is calculated out by a two-dimensional hybrid cloud decision module. Both the simulation and experiment results show that the strategy can dramatically improve the dynamic performances of the converter, and enhance the adaptive ability to resist the random disturbances, and its control effect is superior to that of the current-mode control.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.10a
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• pp.57-62
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• 1999

A disassembility assessment has mostly depend on the subjective decision making from the qualitative element. It is not useful in the practical assessement because it is not specified. The purpose of this paper is an assessmet based on Fuzzy-study-rule. This rule is definitely modified fromnon-fuzzy language of qualitative element. The new assessment method of design for disassembility assessment(DFDA) is practical to introduce the fuzzy number as the conversion of quantitative element from qualitative. It is appled to air-cleaner of passenger-vehicle for the usefulness.

• Proceedings of the KIEE Conference
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• 1998.07c
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• pp.1094-1096
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• 1998

An intelligent power transformer protective relaying algorithm based on fuzzy decision-making is proposed. To distinguish external faults with CT saturation, overexcitation and inrush conditions from internal faults, a newly designed fuzzy-rule base is used. The Dempster-Shafer's rule of combition is used for fuzzy inference. A series of the S/W and H/W tests show the proposed protection algorithm has practically sufficient sensitivity and selectivity.

• International Journal of Internet, Broadcasting and Communication
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• v.10 no.3
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• pp.88-97
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• 2018

Chronic diseases management can be effectively achieved through early detection, continuous treatment, observation, and self-management, rather than a radar approach where patients are treated only when they visit a medical facility. However, previous studies have not been able to provide integrated chronic disease management services by considering generalized services such as hypertension and diabetes management, and difficult to expand and link to other services using only specific sensors or services. This paper proposes clinical rule flow model based on medical data analysis to provide personalized care for chronic disease management. Also, we implemented that as Rule-based Smart Healthcare System (RSHS). The proposed system executes chronic diseases management rules, manages events and delivers individualized knowledge information by user's request. The proposed system can be expanded into a variety of applications such as diet and exercise service in the future.

• Journal of the Korean Data and Information Science Society
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• v.21 no.4
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• pp.709-717
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• 2010

The task of association rule mining is to find certain association relationships among a set of data items in a database. There are three primary measures for association rule, support and confidence and lift. In this paper we developed a association rule ranking function using conditional probability increment ratio. We compared our function with several association rule ranking functions by some numerical examples. As the result, we knew that our decision function was better than the existing functions. The reasons were that the proposed function of the reference value is not affected by a particular association threshold, and our function had a value between -1 and 1 regardless of the range for three association thresholds. And we knew that the ranking function using conditional probability increment ratio was very well reflected in the difference between association rule measures and the minimum association rule thresholds, respectively.