• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.3
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• pp.565-572
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• 1994

A method for the classification of kinematic chains according to the similarity in their structures is proposed. Classifcation code is defined from the contracted graph of the kinematic chain. This method of classifying kinematic chains can be effectively used for the systematic enumeration of structurally distinct kinematic chains given the number of links and degrees of freedom of the kinematic chains. Two separate steps for the enumeration are developed in the study. The first step is to generated all the possible classification codes and the next step is to generate individual kinematic chains belonging to each classification code generated. Using this two step procedure, kinematic chains up to 12 links are successfully enumerated in the present study. It is concluded that the two step method can be efficiently used for the type synthesis of mechanisms.

• ETRI Journal
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• v.40 no.4
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• pp.499-510
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• 2018

A vector space based augmented structural kinematic (VSASK) feature descriptor is proposed for human activity recognition. An action descriptor is built by integrating the structural and kinematic properties of the actor using vector space based augmented matrix representation. Using the local or global information separately may not provide sufficient action characteristics. The proposed action descriptor combines both the local (pose) and global (position and velocity) features using augmented matrix schema and thereby increases the robustness of the descriptor. A multiclass support vector machine (SVM) is used to learn each action descriptor for the corresponding activity classification and understanding. The performance of the proposed descriptor is experimentally analyzed using the Weizmann and KTH datasets. The average recognition rate for the Weizmann and KTH datasets is 100% and 99.89%, respectively. The computational time for the proposed descriptor learning is 0.003 seconds, which is an improvement of approximately 1.4% over the existing methods.

• Korean Journal of Applied Biomechanics
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• v.13 no.3
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• pp.181-197
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• 2003

The Purpose of this study was to examine the kinematic analysis of the upper-limb motion of wheelchair basketball free throw shooting. Three-dimensional kinematic data were obtained from 8 male wheelchair basketball players performing a successful free throw. Players were divided into three groups, according to their IWBF classification(Group 1: 1 point players, Group 2: 2-2.5point players and Group 3:3.5-4 point players) Wheelchair basketball free throw motions were taken by video camera. The three-dimensional coordinates was processed by DLT. Players from Group 1 and 2 tended to release the ball from a lower height, with greater velocity and release angle. Players from Group 1 showed greater shoulder horizontal adduction and horizontal abduction angle, wrist ulnar flexion and radial flexion angle, and trunk angle. but players from Group 2 appeared lower shoulder abduction. Upper limb angular velocity showed most greatly in hands from Group 1, upperarm from Group 2, and forearm from Group 3.

• The Bulletin of The Korean Astronomical Society
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• v.42 no.2
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• pp.61.4-62
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• 2017

In this study we have made a statistical investigation on the kinematic classification of coronal mass ejections (CMEs) using about 4,000 SOHO/LASCO CMEs from 1996 to 2015. For this we use their SOHO/LASCO C3 data and exclude all poor events. Using the constant acceleration model, we classify these CMEs into three groups: Acceleration group, Constant Velocity group, and Deceleration group. For classification we adopt four different methods: Acceleration method, Velocity Variation method, Height Contribution method, and Visual Inspection method. Our major results are as follows. First, the fractions of three groups depend on the method used. Second, the results of the Height Contribution method are most consistent with those of the Visual Inspection method, which is thought to be most promising. Third, the fractions of different kinematic groups for the Height contribution method are: Acceleration (35%), Constant speed (47%), and Deceleration (18%). Fourth, the fraction strongly depend on CME speed; the fraction of Acceleration decreases from 0.6 to 0.05 with CME speed; the fraction of Constant increases from 0.3 to 0.7; the fraction of Deceleration increases from 0.1 to 0.3. Finally we present dozens of CMEs with non-constant accelerations. It is found that about 40 % of these CMEs show quasi-periodic oscillations.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.11
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• pp.1043-1047
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• 2013

Smart mobile robot is a kind of Intelligent Robot. It means that operates manipulate autonomously and recognize the external environment. Smart mobile robot moving mechanism has many type and the type depend on the robot shape or purpose. Recently, research on the moving mechanism has been actively in many area. The moving mechanism divided to wheel type, crawler type, walking type, other type and the moving type choose by the kind of robot or the purpose robot. In this paper, describe the kind of moving mechanism on the smart mobile robot and the technical trend of moving mechanism of smart mobile robot.

• Journal of The Korean Astronomical Society
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• v.55 no.3
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• pp.67-74
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• 2022

In this study, we perform a statistical investigation of the kinematic classification of 4,264 coronal mass ejections (CMEs) from 1996 to 2015 observed by SOHO/LASCO C3. Using the constant acceleration model, we classify these CMEs into three groups: deceleration, constant velocity, and acceleration motion. For this, we devise three different classification methods using fractional speed variation, height contribution, and visual inspection. The main results of this study can be summarized as follows. First, the fractions of three groups depend on the method used. Second, about half of the events belong to the groups of acceleration and deceleration. Third, the fractions of three motion groups as a function of CME speed are consistent with one another. Fourth, the fraction of acceleration motion decreases as CME speed increases, while the fractions of other motions increase with speed. In addition, the acceleration motions are dominant in low speed CMEs whereas the constant velocity motions are dominant in high speed CMEs.

• Journal of Korean Society for Geospatial Information Science
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• v.13 no.1 s.31
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• pp.63-69
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• 2005

Interferometric Synthetic Aperture Radar(InSAR) is a rapidly evolving technique. Spectacular results obtained in various fields such as the monitoring of earthquakes, volcanoes, land subsidence and glacier dynamics, as well as in the construction of Digital Elevation Models(DEMs) of the Earth's surface and the classification of different land types have demonstrated its strength. As InSAR is a remote sensing technique, it has various sources of errors due to the satellite positions and attitude, atmosphere, and others. Therefore, it is important to validate its accuracy, especially for the DEM derived from Satellite SAR images. In this study, Real Time Kinematic(RTK) GPS and Kinematic GPS positioning were chosen as tools for the validation of InSAR derived DEM. The results showed that Kinematic GPS positioning had greater coverage of test area in terms of the number of measurements than RTK GPS. But tracking the satellites near and/or under trees md transmitting data between reference and rover receivers are still pending tasks in GPS techniques.

• The Bulletin of The Korean Astronomical Society
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• v.30 no.1
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• pp.47.2-47.2
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• 2005

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.26 no.4
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• pp.404-413
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• 2015

The target classification for ballistic target(BT) is one of the most critical issues of ballistic defence mode(BDM) in multi-function radar(MFR). Radar responds to the target according to the result of classifying BT and air breathing target(ABT) on BDM. Since the efficiency and accuracy of the classification is closely related to the capacity of the response to the ballistic missile offense, effective and accurate classification scheme is necessary. Generally, JEM(Jet Engine Modulation), HRR(High Range Resolution) and ISAR(Inverse Synthetic Array Radar) image are used for a target classification, which require specific radar waveform, data base and algorithms. In this paper, the classification method that is applicable to a MFR system in a real environment without specific waveform is proposed. The proposed classifier adopts kinematic data as a feature vector to save radar resources at the radar time and hardware point of view and is implemented by fuzzy logic of which simple implementation makes it possible to apply to the real environment. The performance of the proposed method is verified through measured data of the aircraft and simulated data of the ballistic missile.

• The Bulletin of The Korean Astronomical Society
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• v.43 no.1
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• pp.54.3-54.3
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• 2018

In this study, we perform a statistical investigation on the kinematic classication of 4264 coronal mass ejections (CMEs) from 1996 to 2015 observed by SOHO/LASCO C3. Using the constant acceleration model, we classify these CMEs into three groups; deceleration, constant velocity, and acceleration motion. For this, we devise four dierent classication methods by acceleration, fractional speed variation, height contribution, and visual inspection. Our major results are as follows. First, the fractions of three groups depend on the method used. Second, about half of the events belong to the groups of acceleration and deceleration. Third, the fractions of three motion groups as a function of CME speed classied by the last three methods are consistent with one another. Fourth, according to the last three methods, the fraction of acceleration motion decreases as CME speed increases, while the fractions of other motions increase with speed. In addition, the acceleration motions are dominant in low speed CMEs whereas the constant velocity motions are dominant in high speed CMEs.