• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.32-35
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• 2003

In this paper, we describe how to represent lower case hand-written English alphabets by a sequence of two to seven fuzzy sets. Each fuzzy set represents an arc segment of the character and each arc segment is assumed to be a part of an ellipse. The part of an ellipse is defined by five quantities: its short and long radii, its orientation angle, whether it is a part of the lower half or the upper half and whether it is the full half or a part of a half. Hence, we use the Cartesian product of five fuzzy sets to represent each arc segment. We show that this representation is a translation, rotation, and scaling invariant and that it can be used to generate the hand-written English alphabets. The representation we describe is different from the one proposed earlier by the author and when compared with the previous representation, the one described in this paper simulates more closely the behavior of how one writes English characters.

• Journal of Korea Game Society
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• v.2 no.2
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• pp.60-65
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• 2002

In the majority of today's computer games, the behaviour of characters are controlled by pre-defined game logic or pre-generated motion. As game developers strive for richer and more interactive games, they often encounter limitations with this approach. This paper attempts to construct a game model using Genetic Algorithms (GAs) in order to produce more intelligent and compelling computer games. Based on teaming ability, the use of GAs will enable the characters to continually evolve, providing a changing and dynamic game environment. A real-time game was implemented to investigate the performance and limitations of the system.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.111-114
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• 1997

Usually, Evolutionary Algorithms are considered more efficient for optimal system design, However, the performance of the system is determined by fitness function and system environment. In this paper, in order to overcome the limitation of the performance by this factor, we propose a co-evolutionary method that two populations constantly interact and coevolve. In this paper, we apply coevolution to neural network's evolving. So, one population is composed of the structure of neural networks and other population is composed of training patterns. The structure of neural networks evolve to optimal structure and, at the same time, training patterns coevolve to feature patterns. This method prevent the system from the limitation of the performance by random design of neural network structure and inadequate selection of training patterns. In this time neural networks are trained by evolution strategies that are able to apply to the unsupervised learning. And in the coding of neural networks, we propose the method to maintain nonredundancy and character preservingness that are essential factor of genetic coding. We show the validity and the effectiveness of the proposed scheme by applying it to the visual servoing of RV-M2 robot manipulators.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.7
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• pp.870-874
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• 2005

This paper presents capacitive tactile sensor that can detect normal and shear forces. This tactile sensor consists of index plate, sensing plate, and elastic dielectric layer. The calculated sensing character is based on the changes of space between two horizontal plate. Larger overlap areas and narrow space between top and bottom plate guarantees higher sensitivity. Tactile sense information can be calculated from the changes of phase of output signal. The symmetric arrangement of sensing plates makes the manufacturing process easier and guarantees the stability of the structure. In this paper, the sensor structure is designed, the mechanism of the Proposed sensor is theoretically explained, and the simulated result is presented.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.3
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• pp.270-279
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• 2000

This paper describes the on-chip learning algorithm of neural networks using the stochastic pulse arithmetic. Stochastic pulse arithmetic is the computation using the numbers represented by the probability of 1' and 0's occurrences in a random pulse stream. This stochastic arithmetic has the merits when applied to neural network ; reduction of the area of the implemented hardware and getting a global solution escaping from local minima by virtue of the stochastic characteristics. And in this study, the on-chip learning algorithm is derived from the backpropagation algorithm for effective hardware implementation. We simulate the nonlinear separation problem of the some character patterns to verify the proposed learning algorithm. We also had good results after applying this algorithm to recognize printed and handwritten numbers.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.4
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• pp.316-320
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• 2016

In this paper, we presents a pattern recognition by considering the spatial co-occurrence among micro-patterns of texture images. The micro-patterns of texture image have been extracted by local binary pattern based on median(MLBP) of block image, and the recognition process is based on co-occurrence among MLBPs. The MLBP is applied not only to consider the local character but also analyze the pattern in order to be robust noise, and spatial co-occurrence is also applied to improve the recognition performance by considering the global space of image. The proposed method has been applied to recognized 17 RGB images of 120*120 pixels from Mayang texture image based on Euclidean distance. The experimental results show that the proposed method has a texture recognition performance.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.2
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• pp.12-22
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• 2010

The variable message sign(VMS) is a facility to smoothen traffic flows and enable safe passing by providing real-time necessary information on roads, weather, transportation, and traffic regulations. The VMS also solves a feeling of uneasiness and gives a sense of psychological security by providing information to drivers. However, the VMS has a strong character of being a non-market product but a public product, so it has not normally been evaluated for its value. This research has evaluated a value of satisfaction level for traffic information users, using a contingent valuation method(CVM). As a result of evaluating the value of satisfaction level for users through division into an urban roadway and an urban highway for the cities where an intelligent transportation system(ITS) has been established, the urban highway had a value of 96.7 won/system and the urban roadway had a value of 76.3 won/system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.3
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• pp.1510-1532
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• 2017

In smart grid, privacy implications to individuals and their families are an important issue because of the fine-grained usage data collection. Wireless communications are utilized by many utility companies to obtain information. Network coding is exploited in smart grids, to enhance network performance in terms of throughput, delay, robustness, and energy consumption. However, random linear network coding introduces a new challenge for privacy preserving due to the encoding of data and updating of coefficients in forwarder nodes. We propose a distributed privacy preserving scheme for random linear network coding in smart grid that considers the converged flows character of the smart grid and exploits a homomorphic encryption function to decrease the complexities in the forwarder node. It offers a data confidentiality privacy preserving feature, which can efficiently thwart traffic analysis. The data of the packet is encrypted and the tag of the packet is encrypted by a homomorphic encryption function. The forwarder node random linearly codes the encrypted data and directly processes the cryptotext tags based on the homomorphism feature. Extensive security analysis and performance evaluations demonstrate the validity and efficiency of the proposed scheme.

• Journal of Intelligence and Information Systems
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• v.6 no.1
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• pp.65-72
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• 2000

In this paper we propose the new binary image matching algorithm called the Fuzzy logic induced Hausdorff Distance(FHD) for finding the maximally matched image with the query image. The membership histogram is obtained by normalizing the cardinality of the subset with the corresponding radius after obtaining the distribution of the minimum distance computed by the Hausdroff distance between two binary images. in the proposed algorithm, The fuzzy influence method Center of Gravity(COG) is applied to calculate the best matching candidate in the membership function described above. The proposed algorithm shows the excellent results for the face image recognition when the noise is added to the query image as well as for the character recognition.

• Journal of Arbitration Studies
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• v.23 no.3
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• pp.61-80
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• 2013

The U.S. Supreme Court delivered a decision on the case between AT&T and Concepcion, which confirmed the contractuality of a defense as a threshold to distinguish between what is a viable defense for invalidation of consumer arbitration agreement and what is not. In this paper, the adhesiveness of arbitration clause, which is a unique character for consumer arbitration, is investigated in the U.S. as a legal defense to invalidate the consumer arbitration agreements, and its contractuality and related legal doctrines are analyzed. The legal issues of consumer arbitration have been analysed in several legal perspectives including the voluntary, knowing and intelligent doctrine, doctrine of separation, contract of adhesion and the contractuality of defenses. Among all of these, the first three issues are related with arbitration clause, and the last one, the contractuality of defenses, reflects the nature of defenses invalidating the consumer arbitration agreement.