• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1996.10a
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• pp.333-336
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• 1996

The sign language is a method of communication for deaf person. For sign communication, sign language and manual alphabet are used continuously. In this paper is proposed a system which recognize Korean sign language(KSL) and Korean manual alphabet(KMA) continuously. For recognizing KSL and KMA, basic elements for sign language, namely, the 14 hand directions, 23 hand postures, and 14 hand orientations are used. At first, this system recognize current motion state using speed and change of speed in motion by state automata. Using state, basic element classifiers using Fuzzy Min-Max Neural Network and Fuzzy Rule are executed. Meaning of signed gesture is selected by using basic elements which was recognized.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.03a
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• pp.71-74
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• 1998

In recent years, advances in construction techniques and materials have given rese to flexible light-weight structures like high-rise buildings and long-span bridges. Because these structures extremely susceptible to environmental loads, such as earthquakes and strong winds, these random loadings usually produce large deflection and acceleration on these structures. Vibration control system of structures are becoming an integral part of the structural system of the next generation of tall building. The proposed control system is applied to single degree of structure with mass damping and compared with conventional PID and neural network PID control system.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.1
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• pp.31-36
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• 2010

Many clustering algorithms have been used in diverse fields. When we need to group given data set into clusters, many clustering algorithms based on similarity or distance measures are considered. Most clustering works have been based on hierarchical and non-hierarchical clustering algorithms. Generally, for the clustering works, researchers have used clustering algorithms case by case from these algorithms. Also they have to determine proper clustering methods subjectively by their prior knowledge. In this paper, to solve the subjective problem of clustering we make empirical comparisons of popular clustering algorithms which are hierarchical and non hierarchical techniques using Silhouette measure. We use silhouette information to evaluate the clustering results such as the number of clusters and cluster variance. We verify our comparison study by experimental results using data sets from UCI machine learning repository. Therefore we are able to use efficient and objective clustering algorithms.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.1
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• pp.41-48
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• 2014

This paper analyzes the Monte Carlo localization (MCL) method, which estimates the pose of an indoor mobile robot. A mobile robot must know where it is to navigate in an indoor environment. The MCL technique is one of the most influential and popular techniques for estimation of robot position and orientation using a particle filter. For the analysis, we perform experiments in an indoor environment with a differential drive robot and ultrasonic range sensor system. The analysis uses MATLAB for implementation of the MCL and investigates the effects of the control parameters on the MCL performance. The control parameters are the uncertainty of the motion model of the mobile robot and the noise level of the measurement model of the range sensor.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2002.05a
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• pp.342-351
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• 2002

A personalized product recommendation is an enabling mechanism to overcome information overload occurred when shopping in an Internet marketplace. Collaborative filtering has been known to be one of the most successful recommendation methods, but its application to e-commerce has exposed well-known limitations such as sparsity and scalability, which would lead to poor recommendations. This paper suggests a personalized recommendation methodology by which we are able to get further effectiveness and quality of recommendations when applied to an Internet shopping mall. The suggested methodology is based on a variety of data mining techniques such as web usage mining, decision tree induction, association rule mining and the product taxonomy. For the evaluation of the methodology, we implement a recommender system using intelligent agent and data warehousing technologies.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.5
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• pp.539-544
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• 2003

The weapon-target assignment problem is solved using a genetic algorithm in this paper. The weapon-target assignment is an optimization problem which minimizes damages from enemy s attack or maximizes the kill probability of targets. Genetic algorithm is applied in this paper since it usually converges to a near global optimal solution. A specific structure of genetic algorithm which is suitable for the weapon-target assignment problem is proposed. A guideline selecting associated parameters is investigated through simulations. Comparition of the proposed method with several traditional optimization techniques for the weapon-target assignment problem shows the validity of the proposed method.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.903-906
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• 1993

Lipreading through visual processing techniques help provide some useful systems for the hearing impaired to learn communication assistance. This paper proposes a method to understand spoken words by using visual images taken by a camera with a video-digitizer. The image is processed to obtain the contours of lip, which is approximated into a hexagon. The pattern lists, consisting of lengths and angles of hexagon, are compared and computed to get the fuzzy similarity between two lists. By similarity matching, the mouth shape is recognized as the one which has the pronounced voice. Some experiments, exemplified by recognition of the Japanese vowels, are given to show feasibilities of this method.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.933-936
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• 1993

A high speed fuzzy processor using bipolar technology is proposed in this paper. The hardware system uses a high-speed current-mode membership function circuit and normalization technique. The new membership function circuit generates an ideal membership function of the fuzzy set and its circuit is also simple and available for VLSI implementation. Several techniques have been implemented to speed up response of the processor. The fuzzy processor has been designed and implemented in bipolar circuit technology. The experiments and simulations show that the response speed is below 100ms. It can also be expected that the fuzzy processor can be integrated on one chip and its response time is only about the order of nanoseconds.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.802-805
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• 1993

A method of automatic learning of fuzzy if-then rules with certainty factors from the given input-output data is developed. A certainty factor expresses the degree to which a fuzzy if-then rule is fitting to the given data. Fuzzy if-then rules with certainty factors are generated without optimization techniques. The obtained fuzzy if-then rules can be regarded as an approximator of a non-linear function. This method is applied to GMDH (Group Method of Data Handling) to cope with difficulty in approximating multi-input functions with fuzzy if-then rules.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1001-1004
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• 1993

The Multisensor Fusion Problem (MFP) deals with the methodologies involved in effectively combining together homogeneous or non-homegeneous information obtained from multiple redundant or disparate sensors in order to perform a task more accurately, efficiently, and reliably. The inherent uncertainties in the sensory information are represented using Fuzzy Numbers, -numbers, and the Uncertainty-Reductive Fusion Technique (URFT) is introduced to combine the multiple sensory information into one consensus -number. The MFP is formulated from the Information Theory perspective where sensors are viewed as information sources with a fixed output alphabet and systems are modeled as a network of information processing and processing and propagating channels. The performance of the URFT is compared with other fusion techniques in solving the 3-Sensor Problem.