• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.2
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• pp.169-174
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• 2005

A neural networks (NN) saturation compensation scheme for DC motor systems is presented. The scheme that leads to stability, command following and disturbance rejection is rigorously proved. On-line weights tuning law, the overall closed loop performance and the boundness of the NN weights are derived and guaranteed based on Lyapunov approach. The simulation and experimental results show that the proposed scheme effectively compensate for saturation nonlinearity in the presence of system uncertainty.

• Journal of the Korean Operations Research and Management Science Society
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• v.25 no.4
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• pp.81-95
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• 2000

A knowledge-based system with fuzzy 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 strategy to reflect the dynamic nature of real system when we make inferences with a knowledge-based system. This paper proposes a strategy of dynamic inferencing for a knowledge-based system with fuzzy production rules. The strategy suggested in this paper applies weights of attributes of conditions of a rule in the knowledge-base. 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 AHP(Analytic Hierarcy Process) method. Then these weights are applied as exponents for the DM, and the DMs in a rule are combined, with MIN operator, into a single DM for the rule. In this way, overall DM for a rule changes depending on the importance of attributes of the rule. As a result, the dynamic nature of a real system can be incorporated in an inference with fuzzy production rules.

• Journal of Biosystems Engineering
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• v.32 no.5
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• pp.332-338
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• 2007

Yield mapping is necessary for precision farming. An on-site rice weighing system for a head-feed combine was developed to measure the total weight of rice grain harvested while the combine was operated. A load cell system was used to monitor rice weights accumulated into the combine grain tank using a load cell. This method gave cumulative grain weight readings as a function of time. The system consisted of a load cell, two supporting brackets, and a computer-based data acquisition system. The weights measured with the system from two fields were compared with those obtained with a commercially available electronic balance. The response of the load cell to varying grain weights was linearly modeled, showing a coefficient of determination of 0.998 and a standard error of ${\pm}4.09kg$.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.18 no.36
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• pp.1-11
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• 1995

Manual lifting, as a part of manual materials handling activities, is recognized by authorities in the fields of occupational health and safety as a major hazards to industrial workers. In order to minimize the injuries caused by manual material handling activities as well as maximize job productivity, it is important to determine the maximum weights. This paper presents the optimal combination of membership functions according to the high lifting frequency and determines the safe maximum acceptable weights in manual lifting activities through the actual experiment.

• Journal of applied mathematics & informatics
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• v.24 no.1_2
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• pp.343-355
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• 2007

Using the modulus of smoothness ${\omega}^2_{{\varphi}^{\lambda}(f,t)_{\omega}$ Stechkin-Marchaud-Type inequalities with Jacobi weights of Bernstein Operators is established.

• Journal of Internet Computing and Services
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• v.8 no.3
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• pp.99-107
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• 2007

In general, the reliabilities of the fuzzy system are represented and analyzed by real numbers between zero and one, fuzzy numbers, intervals of confidence, interval-valued fuzzy sets, vague sets, etc. This paper addresses the method to analyze the reliability of the fuzzy system for the weighted components with the weights reflected on the importance of weighted components in an system. The reliabilities and the weights of the weighted components in a fuzzy numbers and considers the weights of the weighted components in a fuzzy system, therefore, its execution is faster and more flexible than the conventional methods.

• Journal of the Korean Institute of Intelligent Systems
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• v.1 no.1
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• pp.9-25
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• 1991

This tutorial paper has been written for biologists, physicians or beginners in fuzzy sets theory and applications. This field is introduced in the framework of medical diagnosis problems. The paper describes and illustrates with practical examples, a general methodology of special interest in the processing of borderline cases, that allows a graded assignment of diagnoses to patients. A pattern of medical knowledge consists of a tableau with linguistic entries or of fuzzy propositions. Relationships between symptoms and diagnoses are interpreted as labels of fuzzy sets. It is shown how possibility measures (soft matching) can be used and combined to derive diagnoses after measurements on collected data. The concepts and methods are illustrated in a biomedical application on inflammatory protein variations. In the case of poor diagnostic classifications, it is introduced appropriate ponderations, acting on the characterizations of proteins, in order to decrease their relative influence. As a consequence, when pattern matching is achieved, the final ranking of inflammatory syndromes assigned to a given patient might change to better fit the actual classification. Defuzzification of results (i.e. diagnostic groups assigned to patients) is performed as a non fuzzy sets partition issued from a "separating power", and not as the center of gravity method commonly employed in fuzzy control. It is then introduced a model of fuzzy connectionist expert system, in which an artificial neural network is designed to build the knowledge base of an expert system, from training examples (this model can also be used for specifications of rules in fuzzy logic control). Two types of weights are associated with the connections: primary linguistic weights, interpreted as labels of fuzzy sets, and secondary numerical weights. Cell activation is computed through MIN-MAX fuzzy equations of the weights. Learning consists in finding the (numerical) weights and the network topology. This feed forward network is described and illustrated in the same biomedical domain as in the first part.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.11
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• pp.4207-4211
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• 2010

The goal of this paper is to set up the order list of performance measurement factors according to the its weights. For this purpose the AHP method were implied. The research of this paper is carried out in two steps. At first step, the performance measurement factors are crystallized through review of the korean and foreign researches. In second step, the weights and order list of critical success factors of Hospital Information System were complete. The AHP method were performed in second step. The order list of all CSFs will be determined according to their weights and priorities. This order list shows which factors have the most useful influence on the performance of HIS. This result could play the role as milestone for the effective management of Hospital Information System in Korea.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2001.09a
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• pp.13-18
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• 2001

The ECMO system, including umbilical cord and membrane type oxygenator was connected with extracorporeal circulation unit, was applied to the fetus growth model of goat. The maximum survival time of goat fetus was 48 hours. Average blood rate for the extracorporeal circulation was $223{\pm}15.2 ml/min.$ The survival time of fetus was deeply related to body temperature, blood circulation and water temperature, anesthetized time, and fetus weights. Extern variables that are composed of anesthetized time, fetus weights, change of hemoglobin, circuit pressure, related to the survival time for fetus corrected the problem of previous ECMO model that is controlled by roller pump. It is directly delivered to heart on load. Applying the results from new ECMO model, further research will provide to the system of ECMO for human.

• Biomolecules & Therapeutics
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• v.2 no.1
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• pp.54-58
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• 1994

BALB/C mice were intraperitoneally injected with methamphetamine (5 mg/kg) to observe the effect of methamphetamine on the immune system. Body weights were decreased in both acutely treated group (twice for 2 weeks with 7 days interval) and subchronically treated group (daily injection for 14 days). The relative spleen weights and the numbers of splenocytes were unexpectedly increased (p<0.05) in acutely treated group, but subchronically treated group showed the trend of decrease without significance. But there was no significant effect on antibody formation to hen egg Iysozyme which was immunized during the treatment of methamphetamine and on plaque forming cell number. The relative thymus weights of both groups were significantly decreased by the treatment of methamphetamine (acutely treated group, p<0.05; subchronically treated group, p<0.01). These results suggest that the effect of methamphetamine on the immune system may be caused by thymic dysfunction.