• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.3
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• pp.1026-1042
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• 2020

People are increasingly demanding to experience realistic behavior of virtual characters in computer games. In this article, we build a computer model for simulating a bicycle rider's behavior in a virtual riding system. A method to calculate the speed of a bicycle rider is proposed to improve the reality in a virtual riding system. In this method, the property of physical energy is introduced, and the bicycle-riding speed is calculated in real time according to the relationship between the rider's physical energy and bicycle-riding speed. Then based on the analysis of the behavior of a cyclist in a real competition, various behaviors of the virtual rider are designed and a behavior-tree for the virtual bicycle rider is constructed accordingly. On the basis of these, a virtual riding system is developed. The experiments results show that our system can simulate the behavior of a virtual bicycle rider, and thus encourage exercise on a stationary bicycle.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.425-428
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• 2004

In this paper, we study the discretization behaviors of the equivalent control based sliding-mode control (SMC) systems. The investigation is carried out via studying the second order linear system and some interesting dynamic properties are explored. Especially, according to the variation of system parameters, the inherent dynamical behavior of the trajectories within some specified boundaries are studied. From this result, the boundaries of system state using symbolic dynamics approach are first proposed. Simulations are presented to verify the theoretical results.

• Knowledge Management Research
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• v.18 no.4
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• pp.97-118
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• 2017

Thanks to the development of social media, general users become information and knowledge providers. But customers also feel difficulty to decide their purchases due to numerous information. Although recommender systems are trying to solve these information/knowledge overload problem, it may be asked whether they can honestly reflect customers' preferences. Especially, customers in book market consider contents of a book, recency, and price when they make a purchase. Therefore, in this study, we propose a methodology which can reflect these characteristics based on topic modeling and provide proper recommendations to customers in book market. Through experiments, our methodology shows higher performance than traditional collaborative filtering systems. Therefore, we expect that our book recommender system contributes the development of recommender systems studies and positively affect the customer satisfaction and management.

• International Journal of Control, Automation, and Systems
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• v.5 no.1
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• pp.1-7
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• 2007

In this paper, the necessary and sufficient conditions for strict positive realness of the rational transfer functions directly from basic definitions in the frequency domain are studied. A new frequency domain approach is used to check if a rational transfer function is a strictly positive real or not. This approach is based on the Taylor expansion and the Maximum Modulus Principle which are the fundamental tools in the complex functions analysis. Four related common statements in the strict positive realness literature which is appeared in the control theory are discussed. The drawback of these common statements is analyzed through some counter examples. Moreover a new necessary condition for strict positive realness is obtained from high frequency behavior of the Nyquist diagram of the transfer function. Finally a more simplified and completed conditions for strict positive realness of single-input single-output linear time-invariant systems are presented based on the complex functions analysis approach.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2004.11a
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• pp.203-210
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• 2004

Due to the explosion of e-commerce, recommender systems are rapidly becoming a core tool to accelerate cross-selling and strengthen customer loyalty. There are two prevalent approaches for building recommender systems - content-based recommending and collaborative filtering. Collaborative filtering recommender systems have been very successful in both information filtering domains and e-commerce domains, and many researchers have presented variations of collaborative filtering to increase its performance. However, the current research on recommendation has paid little attention to the use of time related data in the recommendation process. Up to now there has not been any study on collaborative filtering to reflect changes in user interest. This paper proposes dynamic fuzzy clustering algorithm and apply it to collaborative filtering algorithm for dynamic recommendations. The proposed methodology detects changes in customer behavior using the customer data at different periods of time and improves the performance of recommendations using information on changes. The results of the evaluation experiment show the proposed model's improvement in making recommendations.

• Ocean Systems Engineering
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• v.5 no.3
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• pp.199-220
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• 2015

The paper described the nonlinear dynamic motion behavior of a barge equipped with the portable outboard Dynamic Positioning(DP) control system in short-crested waves. The DP system based on the fuzzy theory is applied to control the thrusters to optimally adjust the ship position and heading in waves. In addition to the short-crested waves, the current, wind and nonlinear drifting force are also included in the calculations. The time domain simulations for the six degrees of freedom motions of the barge with the DP system are solved by the $4^{th}$ order Runge-Kutta method. The results show that the position and heading deviations are limited within acceptable ranges based on the present control method. When the dynamic positioning missions are needed, the technique of the alternative portable DP system developed here can serve as a practical tool to assist those ships without equipping with the DP facility.

• Journal of Korean Society on Water Environment
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• v.35 no.6
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• pp.574-579
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• 2019

As interest in health issues increases, it is imperative to ensure good water quality from wastewater treatment plant effluent to preserve environmental health. In particular, currently there is a lack of water ecosystem risk assessment on pharmaceutical substances remaining in effluent. In this study, antidepressant escitalopram (ESC), antiepileptic carbamazepine (CBZ) and lead, which impact the behavior of aquatic organisms, were used to test their impact on the potential behavior of zebrafish. Zebrafish have been widely used in toxicological assessment studies due to the ease of handlinggenerically and genetically. It was possible to observe changes in the growth of organisms through monitoring the embryos' cognitive and behavior assessment. In this study, the embryo lethal dose test showed that the lethal concentration of ESC and CBZ was at 10 ppb, which is below the water quality criterion (100 ppb), increased by 32.5 % and 40 %, respectively. In the cognitive test, it was found that the cognitive ability function decreased by 22 % and 17% for ESC(500 ppb) and CBZ(1,000 ppb) respectively relative to control. Based on these results, it is necessary to initiate efforts to remove these trace pollutants from sewage treatment facilities to protect the health of aquatic organisms.

• The Journal of Information Systems
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• v.16 no.1
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• pp.135-158
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• 2007

The purpose of this research is to identify multidimensional motivation factors that determine the piracy of copyrighted digital music. The model is based on TPB(theory of planned behavior) as well as other models in consumer behavior. An empirical study resulted in the following findings. first Both individual's attitude toward music piracy and individual's perceived behavior control have positive impacts on the individual's behavioral intention of piracy. It turned out that perceived behavior control has a stronger impact on behavioral intention than attitude does. Second, the level of individual's moral judgment has negative impacts on both the attitude and behavioral intention toward music piracy. Third, individual's experience in music piracy positively affects the attitude, but does not directly or indirectly affect the behavior intention. Fourth, an economic gain from music piracy is not a significant factor in determining both attitude and behavioral intention. Fifth, the risk of being prosecuted for music piracy is a major factor in determining one's attitude, although the risk is not significant enough to change one's behavioral intention. This research found that individuals' intention to pirate digital music is mainly affected by the moral and ethical standards of the individuals and by the extra resources and abilities they possess. Such factors as economic gain and law enforcement were not significant enough to alter one's behavioral intention. This research is significant in that it established a behavioral model to understand the piracy of copyrighted digital music and that it empirically tested the model with Internet users in Korea. This is one of the first empirical studies in Korea to touch such ethically and perhaps politically sensitive issues as online music piracy.

• The Journal of Information Systems
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• v.25 no.3
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• pp.61-90
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• 2016

Purpose Recently the usage of Mobile Instant Messenger(MIM) has been increased all over the world. With the development of Mobile Internet, a large amount of mobile application came into being, such as WeChat, the most popular MIM now in China. It has a huge number of registered users, but just only half of them are the "active users". This study intends to examine what factors affect MIM user's continuance intention and actual usage behavior. Design/Methodology/Approach Based on the framework of Perception/Emotion-Behavior and the extended ECM-ISC (Expectation Confirmation Model of IS Continuance), this research introduced some unique variables to a user satisfaction model focusing on perceived/emotional factors in WeChat. In this model, perceived/emotional factors have been divided into enabler factors and inhibitor factors to analyze the effect on continuance intention and actual usage behavior. Also, the moderate effect of the habits was discussed. An online questionnaire survey of 203 WeChat users was conducted and the empirical validation was employed to test the research model. Findings From the empirical results, perceived usefulness, expectation confirmation, and needs for affiliation significantly affected satisfaction. Also, satisfaction influenced continuance intention which led to actual usage behavior. We found that the habit moderates the relationship between satisfaction and continuance intention. The result of this study provides guidance to the developers and operators of WeChat on how to improve enhance users' satisfaction and loyalty.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.4
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• pp.35-42
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• 2024

In this study, we propose a method for real-time recognition and analysis of dog behavior using a motion sensor and deep learning techonology. The existing home CCTV (Closed-Circuit Television) that recognizes dog behavior has privacy and security issues, so there is a need for new technologies to overcome them. In this paper, we propose a system that can analyze and care for a dog's behavior based on the data measured by the motion sensor. The study compares the MLP (Multi-Layer Perceptron) and CNN (Convolutional Neural Network) models to find the optimal model for dog behavior analysis, and the final model, which has an accuracy of about 82.19%, is selected. The model is lightened to confirm its potential for use in embedded environments.