• Smart Media Journal
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• v.11 no.6
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• pp.18-29
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• 2022

This study proposes an evaluation item model for the avatar expression process, satisfaction and self-identification for each expression element in order to investigate the expression attributes on the influence on the user in setting the avatar. The evaluation of avatar expression method was composed of self-identification and satisfaction by ease of expression and expression elements on the avatar production and expression process. To evaluate the proposed evaluation model, 17 people participated in the experiment. As a result, it was found that most of the participants had a high level of understanding of the production process, and the more diverse the expression elements, the higher the satisfaction with the avatar expression process. Hair shape and face shape were the most important expression factors, and clothes and overall harmony was the most concerned facotrs. Most of them tried to express themselves as realistically as possible. However, in self-identification, there was no significant correlation between expression and production process. In this study identify the decision-making factors that appear in the avatar expression process, the direction in which satisfaction can be formed, and the factors that affect self-identification. In addition, it will be a basic study on how avatars have a lasting influence on users in the future.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.804-806
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• 1995

This paper discusses Self-organized Distributed Networks(SODN) as identifier of nonlinear dynamical systems. The structure of system identification employs series-parallel model. The identification procedure is based on a discrete-time formulation. The learning with the proposed SODN is fast and precise. Such properties arc caused from the local learning mechanism. Each local networks learns only data in a subregion. Large number of memory requirements and low generalization capability for the untrained region, which are drawbacks of conventional local network learning, are overcomed in the SODN. Through extensive simulation, SODN is shown to be effective for identification of nonlinear dynamical systems.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.384-387
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• 1999

In this paper, we have proposed a testing methodology for Speed-Independent asynchronous control circuits using the self-checking property where the circuit detects certain classes of faults during normal operation. To exploit self-checking properties of Speed-Independent circuits, the Proposed methodology generates tests from the specification of the target circuit which describes the behavior of the circuit. The generated tests are applied to a fault-free and a faulty circuit, and target faults can be detected by the comparison of the outputs of the both circuits. For the purpose of efficient comparison, reachability information of the both circuits in the form of BDD's is used and operations are conducted by BDD manipulations. The identification for undetectable faults in testing is also used to increase efficiency of the proposed methodology. The proposed identification uses only topological information of the target circuit and reachability information of the good circuit which was generated in the course of preprocess. Experimental results show that high fault coverage is obtained for synthesized Speed-Independent circuits and the use of the identification process decreases the number of tests and execution time.

• The Journal of the Korea Contents Association
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• v.9 no.11
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• pp.348-362
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• 2009

It is a tentative study on the influence of the consumers' motivation of charity impulse on their loyalty who donate to non-profit organizations. Based on the self-determination theory, this thesis paper analyzed the motivation of charity impulse on non-profit organizations which is the main factor influencing the donation loyalty with consumer-nonprofit identification as parametric variables. According to this study, it seems that the charity impulse caused by the concepts of autonomy of the self-determination theory has negative influence on consumer-nonprofit identification, donation loyalty. But relation-competence has positive influence to nonprofit organizations. Considering without any studies on donators' motivation of charity impulse from the aspect of psychology to non-profit organizations, as the very initial exploratory study, this study is conducted to analyze the possible factors to influence customers' motivation of chanty impulse on the basis of the self-determination theory so that it has a vital significance, which can furnish fundamental data to charitable organizations to carry out effective marketing strategies to guarantee the source of the money collection.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.2
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• pp.109-114
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• 2007

Fingerprints have been widely used in the biometric authentication because of its performance, uniqueness and universality. Lately, the speed of identification has become a very important aspect in the fingerprint-based security applications. Also, the reliability still remains the main issue in the fingerprint identification. A fast and reliable fingerprint matching algorithm based on the process of the 'self-nonself' discrimination in the biological immune system was proposed. The proposed algorithm is organized by two-matching stages. The 1st matching stage utilized the self-space and MHC detector string set that are generated from the information of the minutiae and the values of the directional field. The 2nd matching stage was made based on the local-structure of the minutiae. The proposed matching algorithm reduces matching time while maintaining the reliability of the matching algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.2
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• pp.209-214
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• 1998

In this paper, we are dealing with the problem of controlling unknown nonlinear dynamical system by using neural networks. A novel error self-recurrent(ESR) neural model is presented to perform black-box identification. Through the various outcome of the experiment, a new neural network is seen to be considerably faster than the BP algorithm and has advantages of being less affected by poor initial weights and learning rate. These characteristics make it flexible to design the controller in real-time based on neural networks model. In addition, we design an adaptive PID controller that Keyser suggested by using ESR neural networks, and present a method on the implementation of adaptive controller based on neural network for practical applications. We obtained good results in the case of robot manipulator experiment.

• Journal of the Korea Society of Computer and Information
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• v.23 no.8
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• pp.107-114
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• 2018

This study was conducted for the purpose of examining the effects of team trust element of rugby players on self-determination motive and team performance. As for the study subjects, rugby players participated in the 97th national athletic meet in 2016 were selected. As for data collection, in the total of 221 copies of samples were collected through convenience sampling method and 182 copies were used for the final analysis. Using SPSS 18.0, the collected data were analyzed through frequency analysis, exploratory factor analysis, Cronbach's ${\alpha}$ test, correlation analysis and multiple regression analysis and the following conclusions have been obtained. First, as for the effects of rugby players' team trust element on self-determination motive, it was found that team trust influenced external moderation, internal moderation, integrated moderation and identification moderation, and teammate trust influenced internal moderation, integrated moderation and identification moderation. Second, as for the effects of rugby players' team trust element on team performance, it was found that team trust and teammate trust influenced team performance. Third, as for the effects of rugby players' self-determination motive on team performance, it was found that integrated moderation and internal moderation influenced team performance.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1993.04a
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• pp.140-146
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• 1993

Active noise control uses the intentional superposition of acoustic waves to create a destructive interference pattern such that a reduction of the unwanted sound occurs. In active noise control system the choice of a control structure and design of the controller are the main issues of concern. In real acoustic fields there are a vast number of noise sources with time-varying nature and the characteristics of transducers and the geometric set-up of control system are subject to change. Accordingly the control system should be designed to adapt such circumstances so that required level of performance is maintained. In this paper, the adaptive control algorithm for self-tuning adaptive controller is presented for the application in active noise control system. Self-tuning is a direct integration of identification and controller design algorithm in such a manner that the two processes proceed sequentially. The least mean square algorithm was used for the identification schemes and adaptive weighted minimum variance control algorithm was applied for self-tuning controller. Computer simulation results for self-tuning feedback controller are presented. And simulation results was shown to be useful for the situation in which the periodic noise sources act on the acoustic field.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.9 no.4
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• pp.61-70
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• 1999

In this paper we propose the verifiable self-certified schemes(key distribution scheme identification scheme digital signature scheme) based on ${\gamma}$th -residuosity which make up for defects of Girault's self-certified schemes allow the authenticity of public keys to be verified during the use of the keys. The security of our schemes is based on the difficulty of ${\gamma}$th -residuosity problem and discrete logarithm problem simultaneously.

• Journal of Gifted/Talented Education
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• v.17 no.2
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• pp.251-279
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• 2007

The purpose of this study was to develop a comprehensive model to identify underachieved gifted children in elementary schools by utilizing multiple methods. From March 1st, 2006 through September 30th, 2006, we developed and applied a 6-step comprehensive identification model for underachieved gifted children by examining 1980 children attending S elementary school located in Daegu Metropolitan City, starting from the first step of teacher nomination to the last step of committee's final decision. As a result, 4 students were identified as underachieved gifted children. For comprehensive and appropriate identification, we adopted, adjusted, or developed several standardized tests, teacher nomination form, parental questionnaire, self-report checklist, and school achievement tests, which were fine-tuned in the application process of this identification model. Based on this study, we suggest that a comprehensive identification model for underachieved gifted children in public elementary schools consist of 6 steps: a) teacher nomination, b) simplified standardized testing, c) student's self-report, d) multiple standardized tests, e) qualitative analysis, and f) a committee decision for the final identification.