• Proceedings of the Korea Information Processing Society Conference
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• 2019.05a
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• pp.485-486
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• 2019

Simulated driving behavior is an important aspect of realistic simulation systems. To simulate natural driving behavior, this paper proposes an imitation learning method based on active learning that combines demonstration and experience. Driving demonstrations are collected from human drivers in a driving simulator. A driving behavior policy is learned from these demonstrations. The driving demonstration dataset is augmented with new demonstrations that the original demonstrations did not contain, in the form of behaviors from another driving behavior policy learned from experience. The final driving behavior policy is learned from an augmented demonstration dataset.

• Steel and Composite Structures
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• v.36 no.5
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• pp.521-531
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• 2020

The behavior variation of concrete dam is investigated, based on a new method for analyzing the data model of concrete dam in service process for the limitation of wavelet transform for solving concrete dam service process model. The study takes into account the time and position of behavior change during the process of concrete dam service. There is no dependence on the effect quantity for overcoming the shortcomings of the traditional identification method. The panel data model is firstly proposed for analyzing the behavior change of composite concrete dam. The change-point theory is used to identify whether the behavior of concrete dams changes during service. The phase space reconstruction technique is used to reconstruct the phase plane of the trend effect component. The time dimension method is used to solve the construction of multi-transformation model of composite panel data. An existing 76.3-m-high dam is used to investigate some key issues on the behavior change. Emphasis is placed on conversion time and location for three time periods consistent with the practical analysis report for evaluating the validity of the analysis method of the behavior variation of concrete dams presented in this paper.

• Journal of Welding and Joining
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• v.25 no.3
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• pp.37-44
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• 2007

Mechanical and thermomechanical properties of the bulk metallic glass (BMG) are so unique that the deformation behavior is largely dependent on the temperature and the strain rate. Impacting behavior of NiTiZrSiSn bulk metallic glass powder during kinetic spraying was investigated in this study. Considering the impact behavior of the BMG, the kinetic spraying system was modified and attached the powder preheating system to make the transition from the inhomogeneous deformation to the homogeneous deformation of impacting BMG particle easy BMG splat formation is considered from the viewpoint of the adiabatic shear instability. It is suggested that the impact behavior of bulk metallic glass particle is determined by the competition between fracture and deformation. The bonding of the impacting NiTiZrSiSn bulk amorphous particle was primarily caused by the temperature-dependent deformation and fracture (local liquid formation) behavior.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.491-496
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• 2003

This paper proposes modeling of human behavior and a method of finding irregular human behavior. At first, human behavior model is proposed by paying attention to habitual human behavior at home. Generally, it is difficult to obtain the information of individual life pattern because of high cost for setting sensors such as cameras to observe human action. Therefore we capture turning on/off consumer electronic equipments as actual human behavior action, where some or many consumer electric equipments were used such as television, room light, video and so on in our daily life. Noting that are some relations between turning on/off those consumer electric equipments and our action, we proposes how to construct a human behavior knowledge by analyzing human behavior based on observation of human habitual life. Also an algorithm to identify on find irregular behavior different from habitual life behavior are described. Finally, the significance of the proposed method is shown by some experimental results.

• Journal of Engineering Education Research
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• v.19 no.6
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• pp.20-31
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• 2016

The purpose of this study was to explore factors predicting career exploration behavior of engineering students. Career decision making types(rational type, intuitive type, and dependent type) and career decision making self-efficacy were included as predictors for this study. 249 engineering students in Gyeonggi-do of South Korea participated in this study and 231 data analyzed as final samples through multiple regression and mediation analysis. Results showed as follows: first, rational and intuitive decision making significantly predicted career exploration behavior. Also, career decision making self-efficacy completely mediated between these career decision making types(rational and intuitive) and career exploration behavior. The implication of the findings on practice for career education are discussed in the paper.

• Journal of Communications and Networks
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• v.17 no.4
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• pp.384-393
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• 2015

This paper proposes an insect behavior-inspired routing algorithm for large-scale wireless mesh networks. The proposed algorithm is adapted from the behavior of an insect called Bombyx mori, a male silkmoth. Its unique behavior is its flying technique to find the source of pheromones. The algorithm consists of two steps: the shortest-path algorithm and the zigzag-path algorithm. First, the shortest-path algorithm is employed to transmit data. After half of the total hops, the zigzag-path algorithm, which is based on the movement of the male B. mori, is applied. In order to adapt the biological behavior to large-scale wireless mesh networks, we use a mesh topology for implementing the algorithm. Simulation results show that the total energy used and the decision time for routing of the proposed algorithm are improved under certain conditions.

• Steel and Composite Structures
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• v.18 no.3
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• pp.775-791
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• 2015

An analytical and experimental investigation is performed into the mechanical behavior of carbon-fiber/epoxy woven coned annular disk springs. An analytical approach is presented for predicting the deformation behavior of disk springs of specially orthotropic laminates with arbitrary geometric parameters. In addition, an analytical methodology is proposed for obtaining the deformation behavior of a stack of disk springs. The methodology is capable of accounting for parallel and series arrangements for uniform and irregular stacks. Element and assembly experimental results are used to validate the proposed method showing how to achieve flexible spring rates at various deflections ranges. This manuscript also provides guidelines for design and validation of disk spring assemblies.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.318-323
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• 2011

Illegal and unethical behaviors of the construction industry affect people's lives and health more than the same problems of the other industries. Among these behaviors, the construction industry is mostly criticized for bribery scandals. According to the survey of the Ministry of Justice in Taiwan over the past years, bribery cases involving public engineering projects and governmental procurements account for a rather large portion of the indicted corruption cases. Transparency International's "Bribe Payer Index" indicates people in construction-related industries are the most likely to pay bribes. Poor construction quality directly and indirectly caused by bribery poses a great threat to public safety, organizational reputation and economic development. However, there is a limited number of existing research on the bribery problem of the construction industry. This study is an empirical attempt to explore bribery intention and its affecting factors among the construction organizations in Taiwan by conducting a questionnaire survey. The theory of planned behavior was used in this study to build its research model (covering elements of attitude, subjective norm, perceived behavior control, and intention). Totally 431 valid samples were returned. To explore the factors affecting bribery intention, this study adopted Pearson's correlation analysis to discuss about the connections among the questionnaire respondents' attitudes to bribery, subjective norms, perceived behavior control, and bribery intention. A multi-regression analysis was then conducted to test if the planned behavior theory can effectively predict bribery intention. The research found (1) according to the results of Pearson's correlation analysis, the respondents' bribery intention, attitudes, subjective norms, and perceived behavior control are positively correlated with one another; (2) according to the results of the multi-regression analysis, bribery intention can be explained through attitudes, subjective norms, and perceived behavior control with an adjusted R² value of 0.591, meaning 59.1% of the bribery intention's variances can be explained through the three dimensions. In addition, each of the three dimensions has a significant influence on the respondents' behavior intentions.

• Journal of Korea Multimedia Society
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• v.10 no.6
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• pp.770-778
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• 2007

Fish schooling or group moving in cyber underwater is a part of beautiful and familiar ecosystem. It is not so easy to present the behavior of fish crowd naturally as a computer animation. Thanks to development of computer graphics in entertainment industry, the numbers of digital films and animations is increased and the scenes of numerous crowd are shown to us. Though there are many studies on the techniques to process the behavior of crowd effectively and the developments of crowd behavioral systems, there is not enough study on the development for an efficient crowd behavioral simulator. In this' paper, we smartly present the types offish behavior in cyber underwater and make up for the weak points of time and cost. We develop the fish schooling behavior simulator for the contents of cyber underwater, automating fish behavioral types realistically and efficiently.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.2
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• pp.659-679
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• 2015

Distributed applications are composed of multiple nodes, which exchange information with individual nodes through message passing. Compared with traditional applications, distributed applications have more complex behavior patterns because a large number of interactions and concurrent behaviors exist among their distributed nodes. Thus, it is difficult to detect anomalous behaviors and determine the location and scope of abnormal nodes, and some attacks and misuse cannot be detected. To address this problem, we introduce a method for detecting anomalous behaviors based on process algebra. We specify the architecture of the behavior detection model and the detection algorithm. The anomalous behavior detection and analysis demonstrate that our method is a good discriminator between normal and anomalous behavior characteristics of distributed applications. Performance evaluation shows that the proposed method enhances efficiency without security degradation.