• Journal of the Korean Society for Railway
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• v.12 no.6
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• pp.953-960
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• 2009

In the major operation section of urban railway, there has been occurred habitual delay, and delay propagation and spread to consecutive trains. Therefore, this delay cause the increase of operation time and irregular operation, also the increase of crowd and inconvenience to passengers. The railway operation plan is a promise to passengers and must have reliability. In the case of high frequency urban operation, dwell time have considerable influence on operational headway, so it is very important to efficiently plan and control the dwell time at stations. In this paper, the survey of the research on dwell time for urban railways is presented. The practical estimation model for minimum required dwell time, and the numerical example and validity are proposed.

• Journal of Korea Game Society
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• v.13 no.3
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• pp.47-54
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• 2013

In general, algorithms to find continuous k-nearest neighbors has been researched on the location based services monitoring periodically the moving objects such as vehicles and mobile phone. Those researches assume the environment that the number of query points is much less than that of moving objects and the query points are not moved but fixed. In gaming environments, cases to find k-nearest neighbors are when computing the next movement considering the neighbors such as flocking, crowd and robot simulations. Thus, every moving object becomes a query point so that the number of query point is same to that of moving objects and the query points are also moving. In this paper, we analyze the performance of the existing algorithms focused on location based services how they operate under the gaming environments.

• Journal of the Korea Computer Graphics Society
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• v.22 no.1
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• pp.1-8
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• 2016

We propose a novel framework for controlling various and complex models using primitive model. To control original model, first we correspond original model to simplified primitive model that contains original model. After doing deformable simulation with primitive model, we compute original model by inversion of result. Since existing method can only control one type formed models, our method - which can control all difference formed models by only one primitive model - has contribution. In conclusion, we show results that efficiently and intuitionally control the various deformable models by using one example primitive model.

• Journal of IKEEE
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• v.23 no.4
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• pp.1243-1249
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• 2019

People who gathered to enjoy a specific event or content are called audiences or spectators, and show various propensity according to the characteristics of the crowd. Although there is such a difference, in general, the number of attendance is directly related to the business aspect, which enables stable financial operation for the sale of contents through various incomes, such as the admission fee and the use of other facilities. Therefore, prediction of audience can be used as a major factor in marketing and budgeting strategies. In this study, we review several existing models for predicting the number of attendance and propose an efficient machine learning model. In addition, we studied daily attendance prediction and abnormal attendance prediction using combine DNN(Deep Neural Network) and RF(Random Forest) model.

• Journal of the Korean Society of Clothing and Textiles
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• v.40 no.3
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• pp.506-515
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• 2016

This study examines the digital era's fashion system and defines fashion leaders in the system. The study was based on a theoretical review and a research survey to verify the theoretical findings. The results are follows. The critical changes in the fashion system are expansion, cyclical direction and closer distance between producer and consumer. By inflow of media to a new channel, a layer of consumers was extended and the range of celebrities participating in the fashion industry has expanded dramatically. Simultaneously with the change from vertical communication to cyclical and interactive, the direction of communication was re-routed through diverse media. Crowd sourcing activated through two-way communication service has increased consumer opportunities to participate in production and consumption. Fashion leaders have changed significantly under this new system. The range of celebrities participating in the fashion system has increased and different fashion leaders have appeared. An interactive and cyclical fashion system has been established through media innovation; consequently, the influential power of celebrities and individuals for direct participation in the fashion system directly has increased significantly.

• Earthquakes and Structures
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• v.11 no.6
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• pp.1043-1060
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• 2016

The engineering background of this article is an ancient wooden building with extremely high historic and cultural values in Tibet. A full understanding of the dynamic behaviour of this historic building under in-service environments is the basis to assess the condition of the structure, especially its responses to earthquake, environmental and operational loading. A dynamic monitoring system has been installed in the building for over one year and the large amounts of high quality data have been obtained. The paper aims at studying the dynamic behaviour of the wooden building in seismic and operational conditions using the field monitoring data. Specifically the effects of earthquake and crowd loading on the structure's dynamic response are investigated. The monitoring data are decomposed into principal components using the Singular Spectrum Analysis (SSA) technique. The relationship between the average acceleration amplitude and frequencies of the principle components and operational conditions has been discussed. One main contribution is to understand the health condition of complex ancient building based on large databases collected on the field.

• Biomedical Science Letters
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• v.13 no.3
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• pp.231-237
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• 2007

Subway environments such as crowd, passenger's gab, or subway-generated mechanical noise may become a potential stressor. The present study was sought to determine whether subway noise with or without mental activity affects cerebral hemodynamics and sympathetic system. Fifty-four healthy volunteers were divided group I which underwent subway noise (n=24) and group II which underwent a combined mental activity (mental arithmetic) with subway noise (n=30). Sympathetic factors such as heart rate (HR), blood pressure (BP) and heart rate-systolic pressure product (RPP), and mean blood flow velocity in the middle cerebral artery (MCAV) were measured before (baseline), during and after the noise-exposure. Systolic and diastolic blood pressure, HR and RPP significantly increased in group II (P<0.05) but not in group I during the noise-exposure. Peak-MCAV, diastolic-MCAV and mean-MCAV in the both groups were elevated during the noise-exposure (P<0.05) and the increased ratios in group II were greater than those in group I. These results suggest that a combined mental activity with subway noise may be a stressor which affects cerebral hemodynamics and sympathetic system.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.9
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• pp.39-49
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• 2020

This study empirically examines herd behavior for fast moving consumer goods (FMCG) sector stocks under varied market return conditions and the period during the global financial crisis and its aftermath. We examine the sample of stocks trading on the Nifty FMCG Index of the Indian equity market from January 2008 up to December 2018 using the dispersion measure of cross sectional absolute deviation and examine its relationship with the market return to explore herd phenomenon. Quantile regression estimate is used and the results of the study validate rational asset pricing models as the sector does not display herding. In contrast, anti-herd behavior at lower and median quantile values is observed. A possible reason can be the non-cyclical nature of the industry where investors rely more on the fundamentals rather than crowd chasing. We also findthe absence of herd phenomenon during the market asymmetries of bull and bear phases, extreme movements, the period of the global financial crisis, and afterward. We further examine herding under the impact of the information technology (IT) industry and conclude that significant return movements in IT sector impact dispersions in the FMCG industry. Also, there is a co-varying risk between the two sectors confirming the spillover in an integrated market.

• Journal of Korea Multimedia Society
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• v.20 no.2
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• pp.196-204
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• 2017

Behavior of intelligent video surveillance system is recognized by analyzing the pattern of the object of interest by using the frame information of video inputted from the camera and analyzes the behavior. Detection of object's certain behaviors in the crowd has become a critical problem because in the event of terror strikes. Recognition of object's certain behaviors is an important but difficult problem in the area of computer vision. As the realization of big data utilizing machine learning, data mining techniques, the amount of video through the CCTV, Smart-phone and Drone's video has increased dramatically. In this paper, we propose a multiple-sliding window method to recognize the cumulative change as one piece in order to improve the accuracy of the recognition. The experimental results demonstrated the method was robust and efficient learning units in the classification of certain behaviors.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.415-418
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• 2008

This paper presents a method for moving objects detection, analysis and expression how much move as numerical value from the image which is captured by a network camera. To perform this method, we process few kinds of pre-processing to remove noise that are getting background image, difference image, binarization and so on. And to consider perspective effect, we propose modified ART2 algorithm. Finally, we express the result of ATR2 clustering as numerical value. This method is robust to size of object which is changed by perspective effect.