• Journal of the Korea Society for Simulation
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• v.5 no.1
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• pp.13-27
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• 1996

The management of blood inventory is very important within the medical care system. The efficient management of blood supplies and demands for transfusion is of great economic and social importance to both hospitals and patients. Fro any blood type, there is a complex interaction among the optimal inventory level, daily demand level , daily supply level, transfusion to crossmatch ratio, crossmatch release period, issuing policy and the age of arriving units that determine the shortage and outdate rate. In this paper, we develop an efficient decision rule for blood inventory management in a hospital blood bank which can support efficient hospital blood inventory management using simulation, The primary use of the efficient decision rule will be to establish minimum cost function which consists of inventory levels , period in inventory, outdate and shortage rate for whole blood and various component inventories for a hospital blood bank or a transfusion service, If the adminstrator compute the mean daily demand for each blood type, the mean daily supply for each blood type, the length of the crossmatch release period and the average transfusion to crossmatch ratio , then it is possible to apply the efficient decision rule to compute the optimal inventory level, inventory period , outdate and shortage rate. This rule can also be used as a decision support system that allows the blood bank adminstrator to do sensitivity analysis related to controlled blood inventory parameters.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.30 no.3 s.246
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• pp.219-230
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• 2006

Digital CAD models are one of the most important assets the manufacturer holds. The trend toward concurrent engineering and outsourcing in the distributed development and manufacturing environment has elevated the importance of high quality CAD model and its efficient exchange. But designers have spent a great deal of their time repairing CAD model errors. Most of those poor quality models may be due to designer errors caused by poor or incorrect CAD data generation practices. In this paper, we propose a rule-based approach for healing CAD model errors. The proposed approach focuses on the design history data representation from a commercial CAD model, and the procedural method for building knowledge base to heal CAD model. Through the use of rule-based approach, a CAD model healing system can be implemented, and experiments are carried out on automobile part models.

• IE interfaces
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• v.10 no.1
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• pp.119-134
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• 1997

The management of blood inventory is very important within the medical care system. The efficient management of blood supplies and demands for transfusions is of great economic and social importance to both hospitals and patients. For any blood type, there is a complex interaction among the optimal inventory level, daily demand level, daily supply level, transfusion to crossmatch ratio, crossmatch release period, issuing policy and the age of arriving units that determine the shortage and outdate rate. In this paper, we develop an efficient decision rule for blood inventory management in a hospital blood bank which can support efficient hospital blood inventory management using simulation. The primary use of the efficient decision rule will be to establish minimum cost function which consists of inventory levels, period in inventory, outdate and shortage rate for whole blood and various component inventories for a hospital blood bank or a transfusion service. If the administrator compute the mean daily demand for each blood type, the mean daily supply for each blood type, the length of the crossmatch release period and the average transfusion to crossmatch ratio, then it is possible to apply the efficient decision rule to compute the optimal inventory level, inventory period, outdate and shortage rate. This rule can also be used as a decision support system that allows the blood bank administrator to do sensitivity analysis related to controllable blood inventory parameters.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1993.10a
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• pp.1254-1263
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• 1993

Representing knowledge uncertainty , aggregating evidence confidences , and propagation uncertainties are three key elements that effect the ability of a rule-based expert system to represent domains with uncertainty . Fuzzy set theory provide a good mathematical tool for representing the vagueness associated with a variable when , as the condition of a rule , it only partially corresponds to the input data. However, the aggregation of ANDed and Ored confidences is not as simple as the intersection and union operators defined for fuzzy set membership. There is, in fact, a certain degree of compensation that occurs when an expert aggregates confidences associated with compound evidence . Further, expert often consider individual evidences to be varying importance , or weight , in their support for a conclusion. This paper presents a flexible approach for evaluating evidence and conclusion confidences. Evidences may be represented as fuzzy or nonfuzzy variables with as associat d degree of certainty . different weight can also be associated degree of certainty. Different weights can also be assigned to the individual condition in determining the confidence of compound evidence . Conclusion confidence is calculated using a modified approach combining the evidence confidence and a rule strength. The techniques developed offer a flexible framework for representing knowledge and propagating uncertainties. This framework has the potention to reflect human aggregation of uncertain information more accurately than simple minimum and maximum operator do.

• Journal of the Korean Data and Information Science Society
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• v.21 no.6
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• pp.1147-1154
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• 2010

One of the important goals in data mining is to discover and decide the relationships between different variables. Association rules are required for this technique and it find meaningful rules by quantifying the relationship between two items based on association measures such as support, confidence, and lift. In this paper, we presented the evaluation criteria of weighted association rule considering item RFM scores as importance of items. Original RFM technique has been used most widely applied method using customer information to find the most profitable customers. And then we compared general association rule technique with weighted association rule technique through the simulation data.

• Journal of the Korea Safety Management & Science
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• v.4 no.2
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• pp.71-81
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• 2002

Today's environment of enterprise is changing. They have to face customer' demands with the right product, the right service and supply them at the right time. And also cut down logistics and inventory cost and bring up the profit as much as they can. This means the change of putting enterprise first in importance to putting customer first importance. therefore to correspond to customer's demand, shorting lead time is becoming a essential condition. The answer to this changes of environment is supply chain management. In the Supply chain, The ATP function doesn't only give customers to conformation of delivery. It can be used by the core function with ATP rule that can reconcile supplies and demands on the supply chain. Therefore We can be acquire the conformation about on the due date of supplier by using the ATP function of management about real and concurrent access on the supply chain, also decide the affect about product availability due to forecasting or customer's orders through the ATP. In this paper, It consolidates the necessity on a CTP and analyzes data which is concerned of ATP. Under the these environments, defines the ATP rule that can improve the customer value and data flow related the LTV(Life Time Value) and builds on a algorithm.

• Journal of the Korea Society for Simulation
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• v.18 no.4
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• pp.107-116
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• 2009

Overcrowding in an Emergency Department (ED) of hospital is a common phenomenon. To improve the service quality and system performance of the ED, a task assignment rule for the Registered Nurses (RNs) is proposed in this paper. At each task assignment point, the rule prioritizes all treatment requests based on the urgency which is determined by the multiple attributes such as accomplishment time of treatment task, elapsed time of treatment request, total remain time to patient discharge, and number of remain treatments. The values of partial urgency with a single criterion are determined and then overall urgency is computed to find the most urgent one among current requests with the importance weights assigned to the criteria. Through computer simulation, the performance of the proposed rule is compared with current rule in terms of the length of stay and system throughput in a simplified ED system of the hospital M.

• The Transactions of the Korea Information Processing Society
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• v.6 no.8
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• pp.2072-2087
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• 1999

As software size ever increases and user's requirements become more and more sophisticated., the importance of software quality is more and more emphasized. However, we are not satisfied for the present techniques on detecting errors and checking consistency in the object-oriented design model. This paper proposes a systematic approach which produces implementable rules to detect errors and check consistency. At first, the meta-models for UML diagrams are constructed, generalized meta-rules are reduced from the meta-models, and then the meta-rules are applied to produce the implementable rules. This approach enables to pursue the completeness of the rules and the automation of rule application. An example of rule application shows the feasibility of the rule application.

• Journal of the Korea Convergence Society
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• v.9 no.12
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• pp.9-15
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• 2018

The main goal of extended data expression is to develop a data structure suitable for common problems in ubiquitous environments. The greatest feature of this method is that the attribute values can be represented with probability. The next feature is that each event in the training data has a weight value that represents its importance. After this data structure has been developed, an algorithm has been devised that can learn it. In the meantime, this algorithm has been applied to various problems in various fields to obtain good results. This paper first introduces the extended data expression technique, UChoo, and rule refinement method, which are the theoretical basis. Next, this paper introduces some examples of application areas such as rule refinement, missing data processing, BEWS problem, and ensemble system.

• Journal of the Korean Operations Research and Management Science Society
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• v.13 no.1
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• pp.57-57
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• 1988

This paper develops an adaptive scheduling policy for flexible manufacturing systems. The inductive learning methodology used for constructing this state-dependent scheduling policy provides and understanding of the relative importance of the various system parameters in determining the appropriate scheduling rule. Experimental studies indicated the superiority of the suggested approach over the alternative approach involving the repeated application of a single scheduling rule for randomly generated test problems as well as a real system, and under both stationary and nonstationary conditions. In particular, its relative performance improves further when there are frequent disruptions, and when disruptions are caused by the introduction of tiiight due date jobs, one of the most common surces of disruptions in most manufacturing systems.