• 대한기계학회논문집
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• 제18권3호
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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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• 제40권4호
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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.

• 한국운동역학회지
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• 제13권3호
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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.

• 천문학회보
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• 제42권2호
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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.

• 제어로봇시스템학회논문지
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• 제19권11호
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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.

• 천문학회지
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• 제55권3호
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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.

• 대한공간정보학회지
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• 제13권1호
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• pp.63-69
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• 2005

InSAR(Interferometric Synthetic Aperture Radar)는 급속히 발진하고 있는 기술이며 지표면의 수치지형모델 제작과 토지이용 분류뿐만 아니라, 지진, 화신, 지반침하와 빙하흐름의 모니터링과 같은 다양한 응용분야 적용은 그것의 장점을 강화시켜 주고 있다. InSAR는 원격탐측 기술의 한 부류이므로, 위성위치와 자세, 대기, 그리고 기타 요소에 의한 다양한 오차원인을 가지고 있으므로, 이 시스템의 정확도 검증, 특별히 SAR 영상으로부터 제작된 수치지형모델에 대해서는 중요하다. 본 연구에서는 RTK GPS와 Kinematic GPS 측위가 InSAR 기술로 제작된 수치지형모델의검증 도구로 이용되었다. 그 결과로서, Kinematic GPS는 실험지역에서 RTK GPS보다 많은 관측값을 얻을 수 있었지만, 안테나 주위 나무 등에 의한 위성추적 문제와 통신거리에 따른 기준국과 이동국사이의 자료전송 문제 등이 여전히 시급히 해결해야 할 과제로 나타났다.

• 천문학회보
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• 제30권1호
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• pp.47.2-47.2
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• 2005

• 한국전자파학회논문지
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• 제26권4호
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• pp.404-413
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• 2015

대공 레이다에서 표적의 분류는 대 탄도탄 모드 수행의 가장 중요한 부분 중 하나이다. 대 탄도탄 모드에서는 항공기와 탄도탄을 분류하여 각 표적에 따른 대응 방법을 결정한다. 표적 분류의 속도와 정확도는 적의 공격에 대한 대응 능력과 직접적인 관련이 있으므로, 효율적이고 정확한 표적 분류 알고리즘이 필수적이다. 일반적으로, 레이다는 표적 분류를 위해 JEM(Jet Engine Modulation) 및 HRR(High Range Resolution), ISAR(Inverse Synthetic Array Radar) 영상 등을 사용하는데, 이러한 기법들은 표적 분류를 위한 별도의(광대역 등) 레이다 파형과 DB(Data Base) 및 분류 알고리즘을 요구한다. 본 논문은 별도의 파형 없이 실제 다기능 레이다에서 적용 가능한 표적 분류 기법을 제안한다. 특징 벡터로 추적 시 얻은 표적의 운동학적인 특징(kinematics features)을 이용하여 레이다 하드웨어 및 시간 관점에서 레이다 자원을 아끼고, 구현이 간단하여 빠르고 상대적으로 정확한 퍼지 논리(fuzzy logic)를 분류 알고리즘으로 사용하여 실제 환경에서의 적용성을 높였다. 항공기의 실측 데이터와 탄도탄의 모의 신호를 사용하여 제안한 분류 알고리즘의 성능과 적합성을 증명하였다.

• 천문학회보
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• 제43권1호
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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.