• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.861-864
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• 1993

This research provides the results of a trial to generate the chaos by using nonlinear function constructed by fuzzy inference rules. The chaos generation function or chaotic behavior can be obtained by using Takagi-Sugeno fuzzy model with some constraint of the relationship of its parameters. Two examples are shown in this research. The first is simple example that construct of logistic image by fuzzy model. The second is more complicated one that provide the chaotic time series by non-linear autoregression based on fuzzy model. Simulated results are shown in these examples.

• Journal of Information Processing Systems
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• v.7 no.1
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• pp.173-186
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• 2011

Due to the disadvantages of signature-based computer virus detection techniques, behavior-based detection methods have developed rapidly in recent years. However, current popular behavior-based detection methods only take API call sequences as program behavior features and the difference between API calls in the detection is not taken into consideration. This paper divides virus behaviors into separate function modules by introducing DLLs into detection. APIs in different modules have different importance. DLLs and APIs are both considered program calling resources. Based on the calling relationships between DLLs and APIs, program calling resources can be pictured as a tree named program behavior resource tree. Important block structures are selected from the tree as program behavior features. Finally, a virus detection model based on behavior the resource tree is proposed and verified by experiment which provides a helpful reference to virus detection.

• Journal of Navigation and Port Research
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• v.31 no.4
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• pp.309-315
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• 2007

We've investigated the characteristics on mariner's behavior in the collision situation through a full-mission ship handling simulator and considered that it's necessary to model the standard avoiding behavior of mariners in order to apply the obtained results more widely and effectively. Thus we described the contents of standard avoiding behavior taken by mariners in the collision situation and established the concept of the standard model based on human factors for collision avoidance in a previous study. As a following study, this paper is to propose the method of modeling on mariners' standard behavior for collision avoidance by analyzing the contents of mariner's information processing and the related factors using regression analysis. As a result, we confirmed the influence of relating factors to avoiding behavior in mariner's deciding decisions and proposed the modeling method of mariners' standard behavior for collision avoidance with a example of recognition model.

• Journal of the Korean Institute of Intelligent Systems
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• v.9 no.6
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• pp.627-633
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• 1999

In this paper, we propose a method of cooperative control (T-cell modeling) and selection of group behavior strategy (B-cell modeling) based on immune system in distributed autonomous robotic system (DARS). Immune system is living body's self-protection and self-maintenance system. These features can be applied to decision making of optimal swarm behavior in dynamically changing environment. For applying immune system to DARS, a robot is regarded as a ？3-cell, each environmental condition as an antigen, a behavior strategy as an antibody and control parameter as a T-cell respectively. When the environmental condition (antigen) changes, a robot selects an appropriate behavior strategy (antibody). And its behavior strategy is stimulated and suppressed by other robot using communication (immune network). Finally much stimulated strateby is adopted as a swarm behavior strategy. This control scheme is based on clonal selection and immune network hypothesis, and it is used for decision making of optimal swarm strategy. Adaptation ability of robot is enhanced by adding T-cell model as a control parameter in dynamic environments.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.11a
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• pp.602-607
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• 2003

Sensors based bridge monitoring system (SBBMS) is designed to perform real-time monitoring and to store the performance history of in-service bridges. In general, visual inspections play a major role in maintenance of in-service bridges; however, they are not adequate to document the behavior of a bridge. Therefore, visual inspections and sensor based monitoring systems complement each other. Sensor based bridge monitoring systems consist of hardware and software systems. The hardware system contains the sensors and data-loggers to measure the behavior of a structure, the communicational equipment to transmit the measured data from the site to the monitoring center, and the computers to arrange and analyze the data. The software system controls data-loggers, arranges and analyzes the measured data, makes real-time display, stores the performance history.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.9
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• pp.4684-4705
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• 2019

Collaborative filtering recommender systems are vulnerable to shilling attacks in which malicious users may inject biased profiles to promote or demote a particular item being recommended. To tackle this problem, many robust collaborative recommendation methods have been presented. Unfortunately, the robustness of most methods is improved at the expense of prediction accuracy. In this paper, we construct a robust Bayesian probabilistic matrix factorization model for collaborative filtering recommender systems by incorporating the detection of user anomaly rating behaviors. We first detect the anomaly rating behaviors of users by the modified K-means algorithm and target item identification method to generate an indicator matrix of attack users. Then we incorporate the indicator matrix of attack users to construct a robust Bayesian probabilistic matrix factorization model and based on which a robust collaborative recommendation algorithm is devised. The experimental results on the MovieLens and Netflix datasets show that our model can significantly improve the robustness and recommendation accuracy compared with three baseline methods.

• Journal of Families and Better Life
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• v.18 no.1
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• pp.53-66
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• 2000

This study examined the relationships among resources demands financial management behavior and financial satisfaction of housewives based on the systems approach. The data were collected from 212 housewives living in Pusan and Kyungnam region by the self-administered questionnaire. The major findings of this study were as follows: (1) the communication frequency of husbands and wives was an important factor affecting financial satisfaction; (2) the perceived financial status such as comparison to reference groups and aspiration for financial status in the future had an influence on financial satisfaction as well as the objective variables such as monthly living costs and monthly savings; and (3)financial satisfaction was also affected by financial management behavior. These findings imply that the financial management program focusing on the ways to increase communication among family members and to implement financial behavior effectively should be developed.

• Asia pacific journal of information systems
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• v.21 no.3
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• pp.1-18
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• 2011

Blog have become very popular with Internet users as one of the latest forms of online communication as well as knowledge sharing tools. However, blogs generate growing concerns regarding information privacy issues. This study, based on social exchange theory, presents results about bloggers' information sharing behavior. The 157 surveys are collected from a large university in the eastern U.S. The survey results indicate that trust which has four second order factors: economy based trust, trust in reciprocity, trust in other bloggers and trust in social interaction positively affects bloggers' information sharing behavior. However, online information privacy concerns have a negative impact on the relationship between trust and bloggers' information sharing behavior.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.7
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• pp.527-535
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• 2003

A behavior-based control and learning architecture is proposed, where reinforcement learning is applied to learn proper associations between stimulus and response by using two types of memory called as short Term Memory and Long Term Memory. In particular, to solve delayed-reward problem, a knowledge-propagation (KP) method is proposed, where well-designed or well-trained S-R(stimulus-response) associations for low-level sensors are utilized to learn new S-R associations for high-level sensors, in case that those S-R associations require the same objective such as obstacle avoidance. To show the validity of our proposed KP method, comparative experiments are performed for the cases that (ⅰ) only a delayed reward is used, (ⅱ) some of S-R pairs are preprogrammed, (ⅲ) immediate reward is possible, and (ⅳ) the proposed KP method is applied.

• Asia pacific journal of information systems
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• v.29 no.2
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• pp.248-267
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• 2019

As merging online and offline channels into one single platform, individuals could easily and frequently switch between online and offline channels. In order for understanding such unique behaviors, this study attempts to explore why and how consumers choose their channels to search and purchase a product. We have drawn on multiple theories that have been used to explain individuals' judgment and decision making (i.e., construal level theory and regula-tory focus theory) in order to develop and tested two-way ANOVA based models of how both regulatory focus (e.g., promotion vs. prevention) and product types (e.g., experience goods vs. searching goods) including the psychological distance cue separately and jointly affect individuals' channel selection behavior (e.g., intention to use single channel vs. intention to use cross-channels). Our results have indicated that consumers with promotion-focus are more likely to use a single channel in experience goods rather than in searching goods when there exists the psychological cue. Based on our findings, the implication for both research and practice are discussed.