• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.1
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• pp.72-78
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• 2006

It is essential for robot to have the sensing and communication abilities in the swarm robot system. In general, as the number of robot goes on increasing, the limitation of communication capacity and information overflow occur in global communication system. Therefore a local communication is more effective than global one. In this paper, we propose the novel method for determining the optimal communication radius through the analyzing of the information propagation based on local communication. And we also propose a method of cooperative strategies and group behavior of swarm robot based on artificial immune system.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.11
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• pp.1017-1021
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• 2013

The traffic signal has been widely used in the transport system with a fixed time interval currently. This kind of setting time was determined based on experience for vehicles to generate a waiting time while allowing pedestrians crossing the street. However, this strict setting causes inefficient problems in terms of economic and safety crossing. In this research, we propose a monitoring algorithm to detect, track and check pedestrian crossing the crosswalk by the patterns of behavior. This monitoring system ensures the safety for pedestrian and keeps the traffic flow in efficient. In this algorithm, pedestrians are detected by using HOG feature which is robust to illumination changes in outdoor environment. According to a complex computation, the parallel process with the GPU as well as CPU is adopted for real-time processing. Therefore, pedestrians are tracked by the relationship of hue channel in image sequence according to the predefined pedestrian zone. Finally, the system checks the pedestrians' crossing on the crosswalk by its HOG based behavior patterns. In experiments, the parallel processing by both GPU and CPU was performed so that the result reaches 16 FPS (Frame Per Second). The accuracy of detection and tracking was 93.7% and 91.2%, respectively.

• The Journal of Information Systems
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• v.31 no.2
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• pp.289-320
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• 2022

Purpose The purpose of this study is to empirically investigate impacts of e-Commerce traits on intention to use platform extended services based on Value-Attitude-Behavior(VAB) framework as well as the moderating effect of network impact as the current e-Commerce platforms provide more extended services to their customers. Design/methodology/approach The research model was developed based on the literature review and VAB framework in order to empirically investigate impacts of e-Commerce platform characteristics. The survey was conducted in order to test proposed hypotheses. 298 collected responses were analyzed for the structural equational modeling(SEM) with SmartPLS 3.0. Findings Findings show that all proposed hypotheses were supported with exception of responsiveness. Among five constructs represented as e-Commerce platform characteristics, product variety had a highest impact on platform value. In addition, this study confirmed that the variable - network effect - strength the relationship between platform attitude and intention to use extended service.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.577-580
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• 1996

LQ-servo is a stability-robustness guaranteed multivariable controller design method based on the LQR structure to improve command following performance with output feedback. In this paper, a new type of PI controller based on LQ-servo is introduced. Then, Command following performance is improved using the limiting behavior of the control gain and weighting factors on the low frequency part of design parameter Q that is the state weighting matrix in the cost function.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.5
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• pp.712-717
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• 2008

In swarm robot systems, each robot must act by itself according to the its states and environments, and if necessary, must cooperate with other robots in order to carry out a given task. Therefore it is essential that each robot has both learning and evolution ability to adapt the dynamic environments. In this paper, reinforcement learning method with SVM based on structural risk minimization and distributed genetic algorithms is proposed for behavior learning and evolution of collective autonomous mobile robots. By distributed genetic algorithm exchanging the chromosome acquired under different environments by communication each robot can improve its behavior ability. Specially, in order to improve the performance of evolution, selective crossover using the characteristic of reinforcement learning that basis of SVM is adopted in this paper.

• 한국경영정보학회:학술대회논문집
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• 2008.06a
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• pp.135-140
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• 2008

Studies of recommender systems have focused on improving their performance in terms of error rates between the actual and predicted preference values. Also, many studies have been conducted to investigate the relationships between customer information processing and the characteristics of recommender systems via surveys and web-based experiments. However, the actual impact of recommendation on product pages for customer browsing behavior and decision-making in the commercial environment has not, to the best of our knowledge, been investigated with actual clickstream data. The principal objective of this research is to assess the effects of product recommendation on customer behavior in e-Commerce, using actual clickstream data. For this purpose, we utilized an online bookstore's clickstream data prior to and after the web site renovation of the store. We compared the recommendation effects on customer behavior with the data. From these comparisons, we determined that the relevant recommendations in product pages have positive relationships with the acquisition of customer attention and elaboration. Additionally, the placing of recommended items in shopping cart is positively related to suggesting the relevant recommendations. However, the frequencies at which the recommended items were purchased did not differ prior to and after the renovation of the site.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.2
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• pp.279-284
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• 2009

In swarm robot systems, each robot must behaves by itself according to the its states and environments, and if necessary, must cooperates with other robots in order to carry out a given task. Therefore it is essential that each robot has both learning and evolution ability to adapt the dynamic environments. In this paper, reinforcement learning method using many SVM based on structural risk minimization and distributed genetic algorithms is proposed for behavior learning and evolution of collective autonomous mobile robots. By distributed genetic algorithm exchanging the chromosome acquired under different environments by communication each robot can improve its behavior ability. Specially, in order to improve the performance of evolution, selective crossover using the characteristic of reinforcement learning that basis of Cascade SVM is adopted in this paper.

• Journal of Industrial Technology
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• v.10
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• pp.3-8
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• 1990

This paper presents a linear state feedback control approach to the stabilization of discrete-time uncertain systems with bounded uncertain parameters. The approach is based on the LQ(linear quadratic) regulator theory and Lyapunov's stability analysis. Asymptotically stable behavior is guaranteed in the presence of parameter uncertainties, and the upper bound of the performance index is determined.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.3
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• pp.965-983
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• 2014

Concurrent behaviors of multithreaded programs cannot be described effectively by automata-based models. Thus, concurrent program intrusion attempts cannot be detected. To address this problem, we proposed the process algebra-based detection model for multithreaded programs (PADMP). We generate process expressions by static binary code analysis. We then add concurrency operators to process expressions and propose a model construction algorithm based on process algebra. We also present a definition of process equivalence and behavior detection rules. Experiments demonstrate that the proposed method can accurately detect errors in multithreaded programs and has linear space-time complexity. The proposed method provides effective support for concurrent behavior modeling and detection.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.388-388
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• 2000

The complexity of nonlinear systems makes it difficult to ascertain their behavior using classical methods of analysis. Many efforts have been focused on the advanced algorithms and techniques that hold the promise of improving real-time optimal control while at the same time providing higher accuracy. In this paper, a fuzzy cell mapping method of real-time optimal control far nonlinear dynamical systems is proposed. This approach combines fuzzy logic with cell mapping techniques in order to find the optimal input level and optimal time interval in the finite set which change the state of a system to achieve a desired obiective. In order to illustrate this method, we analyze the behavior of an inverted pendulum using fuzzy cell mapping.