• Journal of KIISE:Computing Practices and Letters
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• v.15 no.3
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• pp.145-153
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• 2009

Trajectory data are ubiquitous in the real world. Recent progress on satellite, sensor, RFID, video, and wireless technologies has made it possible to systematically track object movements and collect huge amounts of trajectory data. Accordingly, there is an ever-increasing interest in performing data analysis over trajectory data. In this paper, we develop a data mining tool for massive trajectory data. This mining tool supports three operations, clustering, classification, and outlier detection, which are the most widely used ones. Trajectory clustering discovers common movement patterns, trajectory classification predicts the class labels of moving objects based on their trajectories, and trajectory outlier detection finds trajectories that are grossly different from or inconsistent with the remaining set of trajectories. The primary advantage of the mining tool is to take advantage of the information of partial trajectories in the process of data mining. The effectiveness of the mining tool is shown using various real trajectory data sets. We believe that we have provided practical software for trajectory data mining which can be used in many real applications.

• Korean Journal of Social Welfare Studies
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• no.39
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• pp.5-28
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• 2008

The purpose of this study is two-fold: 1) to identify different adolescent smoking trajectories in Korea; and 2) to examine predictors of those smoking trajectories within a social developmental frame. Data were from the Korea Youth Panel Survey(KYPS), a longitudinal study of 3,449 youths followed since 2003. Using semi-parametric group-based modeling, four smoking trajectories were identified: non initiators, late onsetters, experimenters, and escalators. Multinomial logistic regressions were then used to identify risk and protective factors that distinguish the trajectory groups from one another. Among non smokers at age 13, late onsetters were distinguished from non initiators by a variety of factors in every ecological domain. Among youths who already smoked at age 13, escalators who increased their smoking were distinguished from experimenters who almost desisted from smoking by age 17 by self-esteem and academic achievement. Finally, implications for youth welfare practice from this study were discussed.

• Journal of Advanced Marine Engineering and Technology
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• v.24 no.1
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• pp.10-17
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• 2000

본 논문은 우주 발사 비행체가 지구 재진입 할 때의 유도제어에 관한 것이다. 우주 발사 비행체의 재진입궤적은 재진입 할 때의 특징에 따라 여러 단계로 나누어진다. 저항가속도는 각 단계에 따라 알맞은 파라메터로 표현되며, 해석적인 저항가속도로 단순화된 궤적으로 표현한다. 본 연구는 현재의 이란적인 궤적방법과 예측방법의 각각의 장점에 의한 혼합유도방법을 표현하였다. 제안된 유도방법을 이용한 우주 발사 비행체의 재진입 모의실험의 결과는 혼합유도방법이 지구대기 재진입 할 때 간단하고 효과적인 유도방법임을 보여주었다.

• Journal of the Korean Home Economics Association
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• v.48 no.10
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• pp.89-103
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• 2010

The purpose of this study was to examine the developmental trajectories of adolescents' internalizing problem behaviors. The data came from 3,188 middle school students through their participation in the Korea Youth Panel Survey(KYPS). Adolescents with a high level of internalizing problem behaviors in the first year showed a rapid decline in these behaviors over time, whereas for adolescents with a low level of these behaviors in the first year the decline was slow. The predictors of the developmental trajectories were related to individual variables, such as gender, self-esteem, self-control, stress, self-stigmatization, and academic achievement. The developmental trajectories of adolescents' internalizing problem behaviors were classified into four groups. The predictors of the patterns of developmental trajectories in adolescents' internalizing problem behaviors appeared to be related to individual variables.

• Journal of the Korean Society of Child Welfare
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• no.54
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• pp.173-197
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• 2016

This study aims to examine developmental trajectories and predictor variables of problem behaviors and school adjustment trajectories among children from low-income families using latent growth modeling. The data was collected from the 2nd year to the 4th year (2012-2014) of a community child center child panel survey conducted by the National Youth Policy Institute. The major findings are as follows. First, as the grade went up, the problem behaviors of children from low-income families increased while school adjustment decreased. Second, multi-level domains, such as individual, school, and family variables influenced school adjustment trajectory, while only individual variables, such as depression, isolation, and motivation for achievement influenced problem behavior trajectory. Third, common protective factors between problem behaviors and school adjustment trajectories were motivation for achievement in and satisfaction of the community child center. Common risk factors between problem behaviors and school adjustment trajectories were isolation and aggression. Based on the results, the implications for child welfare practices were discussed.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.23 no.3
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• pp.28-34
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• 2015

An analysis method of trajectory prediction has been suggested and the developed trajectory prediction module, which is an important functional component of the Arrival Manager (AMAN) of Jeju airport, has been tested by applying the suggested method. The objective of this method is to improve prediction performance of the trajectory prediction module. The trajectory prediction module predicts the trajectories based on the real-time track data and flight plans. Therefore, the suggested analysis method includes the simulation framework which is based on real-time playback, recording, and graphic display systems for testing. Besides, the definition of time error, which is a important index for the time based scheduling system, such as AMAN, is included in the suggested analysis method. An example of arrival time prediction accuracy improvement through the suggested analysis method has also been presented.

• Journal of the Korea Society for Simulation
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• v.27 no.2
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• pp.35-48
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• 2018

The study of air defense against North Korean tactical ballistic missiles (TBM) should consider the rapidly changing battlefield environment. The study for target re-designation for intercept missiles enables effective operation of friendly defensive assets as well as responses to dynamic battlefield. The researches that have been conducted so far do not represent real-time dynamic battlefield situation because the hit probability for the TBM, which plays an important role in the decision making process, is fixed. Therefore, this study proposes a target re-designation algorithm that makes decision based on hit probability which considers real-time field environment. The proposed method contains a trajectory prediction model that predicts the expected trajectory of the TBM from the current position and velocity information by using random forest and moving window. The predicted hit probability can be calculated through the trajectory prediction model and the simulator of the intercept missile, and the calculated hit probability becomes the decision criterion of the target re-designation algorithm for the missile. In the experiment, the validity of the methodology used in the TBM trajectory prediction model was verified and the superiority of using the hit probability through the proposed model in the target re-designation decision making process was validated.

• Korean Journal of Social Welfare Studies
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• v.48 no.2
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• pp.303-329
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• 2017

This study aimed to explore the trajectories of computer game use of school age children and to identify the related predictors. The data for this study used Korean Children and Youth Panel data covering from the second year to the sixth year of elementary school. A total of 1,959 participants were analyzed. Latent class growth model was employed to explore the trajectories of computer game use and multinomial logistic regression was conducted to identify the significant predictors. Main results indicated that three types of trajectories were identified: low game using group, high initial using-fluctuating group, and high increasing game using group. Each group was found to be associated deferentially with sex, aggression, attention deficit, main caregiver's education, siblings, parent absence after-school, neglecting, family income, family trip, school grades, and peer relationship. Based on these findings, this study emphasized the importance of predictive intervention for the game user among early school age children and suggested useful practical strategies.

• Journal of the Korea Computer Graphics Society
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• v.25 no.3
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• pp.133-142
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• 2019

In physics-based character animation, trajectory optimization has been widely adopted for automatic motion synthesis, through the prediction of an optimal sequence of future states of the character based on its system dynamics model. In general, the system dynamics model is neither in a closed form nor differentiable when it handles the contact dynamics between a character and the environment with rigid body collisions. Employing smoothed contact dynamics, researchers have suggested efficient trajectory optimization techniques based on numerical differentiation of the resulting system dynamics. However, the numerical derivative of the system dynamics model could be inaccurate unlike its analytical counterpart, which may affect the stability of trajectory optimization. In this paper, we propose a novel method to derive the closed-form derivative for the system dynamics by properly approximating the contact model. Based on the resulting derivatives of the system dynamics model, we also present a model predictive control (MPC)-based motion synthesis framework to robustly control the motion of a biped character according to on-line user input without any example motion data.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.22 no.2
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• pp.1-8
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• 2014

This paper introduces a new framework of predicting the arrival time of an aircraft by incorporating the probabilistic information of what type of trajectory pattern will be applied by human air traffic controllers. The proposed method is based on identifying the major patterns of vectored trajectories and finding the statistical relationship of those patterns with various traffic complexity factors. The proposed method is applied to the traffic scenarios in real operations to demonstrate its performances.