• International Journal of Advanced Culture Technology
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• v.10 no.1
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• pp.265-273
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• 2022

The aim of this study is to investigate the relationship between the object ability, basic movement ability, and mathematical ability of young children. Next, through this study, the influence of young children's object manipulation ability and basic movement ability on mathematical ability was investigated. The subjects of this study were 80 children aged 5 years old. As a research tool, the non-mobile movement and mobile movement, the basic movement development test scale, and the young children's picture-mathematical ability test scale were used. This survey was conducted from October 2018 to January 2019. For data analysis, correlation analysis and hierarchical multiple regression analysis were performed using the spss program. As a result of the study, it was found that there was a significant positive correlation between the non-mobile ability, movement ability, object manipulation ability and mathematical ability of young children. It was found that young children's ability to manipulate objects and non-movement abilities had positive effect on their mathematical abilities. The movement ability of young children had both negative and positive effects on mathematical ability, but it was not found to be statistically significant. This study is meaningful in that it investigated the effects of non-mobile movement, mobile movement ability, and object manipulation ability, which are sub-capabilities of basic movement ability, which had not been investigated so far, on the mathematical ability of young children.

• Journal of Korea Multimedia Society
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• v.12 no.4
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• pp.492-501
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• 2009

Information on movement of objects in videos can be used as an important part in categorizing and separating the contents of a scene. This paper is proposing a shape-based movement-matching algorithm to effectively find the movement of an object in video streams. Information on object movement is extracted from the object boundaries from the input video frames becoming expressed in continuous 2D shape information while individual 2D shape information is converted into a lD shape feature using the shape descriptor. Object movement in video can be found as simply as searching for a word in a text without a separate movement segmentation process using the sequence of the shape descriptor listed according to order. The performance comparison results with the MPEG-7 shape variation descriptor showed that the proposed method can effectively express the movement information of the object and can be applied to movement search and analysis applications.

• The Journal of Korea Robotics Society
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• v.8 no.1
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• pp.20-28
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• 2013

Large workspace and strong grasping force are required when a robot manipulates big and/or heavy objects. In that situation, bimanual manipulation is more useful than unimanual manipulation. However, the control of both hands to manipulate an object requires a more complex model compared to unimanual manipulation. Learning by human demonstration is a useful technique for a robot to learn a model. In this paper, we propose an imitation learning method of bimanual object manipulation by human demonstrations. For robust imitation of bimanual object manipulation, movement trajectories of two hands are encoded as a movement trajectory of the object and a force trajectory to grasp the object. The movement trajectory of the object is modeled by using the framework of dynamic movement primitives, which represent demonstrated movements with a set of goal-directed dynamic equations. The force trajectory to grasp an object is also modeled as a dynamic equation with an adjustable force term. These equations have an adjustable force term, where locally weighted regression and multiple linear regression methods are employed, to imitate complex non-linear movements of human demonstrations. In order to show the effectiveness our proposed method, a movement skill of pick-and-place in simulation environment is shown.

• Journal of Korea Multimedia Society
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• v.20 no.7
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• pp.986-993
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• 2017

Object Tracking is a technique for tracking moving objects over time in a video image. Using object tracking technique, many research are conducted such a detecting dangerous situation and recognizing the movement of nearby objects in a smart car. However, it still remains a challenging task such as occlusion, deformation, background clutter, illumination variation, etc. In this paper, we propose a novel deep visual object tracking method that can be operated in robust to many challenging task. For the robust visual object tracking, we proposed a Convolutional Neural Network(CNN) which shares weight of the convolutional layers. Input of the CNN is a three; first frame object image, object image in a previous frame, and current search frame containing the object movement. Also we propose a method to consider the motion of the object when determining the current search area to search for the location of the object. Extensive experimental results on a authorized resource database showed that the proposed method outperformed than the conventional methods.

• Proceedings of the KIEE Conference
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• 1990.11a
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• pp.470-473
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• 1990

In this thesis, the recognition method of the movement of an 3D object is presented. The information about the movement of a 3D object is used to recognize the object. There are 2 kinds of movements which are translation and rotation. A difference picture is obtained from a sequence of images of a moving object or a scene which is taken by a monocular stationary observer. The 3D movement of an object is recognized by the Artificial Neural Network(ANN) using the difference picture.

• Journal of the Korean housing association
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• v.16 no.2
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• pp.55-65
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• 2005

'Movement System' is made of the interaction of user and architectural spaces related to each other in order. 'Movement' meant in movement system is possible only in the status of user and architectural space together. Movement created and disappeared by the user is not subordinated to the existing architectural space but becomes the main element of formating movement system. It is required that movement conception applied to architecture should be derived from the essence of movement and this study presents the movement system. To explain the formating process of movement system, A. N. Whitehead's process philosophy theory is at the basis and transformed in architectural aspects. On basis of these theoretical backgrounds, the process of making movement system can be explained. There are unit movement, unit object, and elements for movement process as the basic requirements for movement system, each unit is apprehended by individual operation and the nexus is composed by associative operation of apprehended units. This nexus becomes the object of a new subject and forms multiple nexus. Relation of unit movement and unit object and nexus are apprehended as the continuation and extensive continuum is made. At that time, movement with multiple phases set inbetween systems and extended multiplied. Through above study, movement system is applied to Korean traditional houses.

• Korean Journal of English Language and Linguistics
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• v.4 no.1
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• pp.103-116
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• 2004

Chomsky (2001) and Kitahara's (2002) suggestion that object shift occurs prior to movement of the νP-subject to SPEC-T is not on the right track with respect to the Merge operation. According to the Merge operation, TP is necessarily created earlier than CP. Chomsky (2001) suggests that the probe-goal relation between T and SUBJ is evaluated in the CP after it is known whether the position of as has become a trace losing its phonological content. However, the FocP is not a phase (CP). So, Chomsky (2001) and Kitahara's (2002) suggestion is not correct in the case of the movement of OBJ to the spec of Foc in English, either. The aim of this paper is to show that the νP-subject must move to SPEC- T prior to the consecutive movement of the wh-object to SPEC-C via object shift in English. This derivation obeys Chomsky's (2001) so-called probe-goal matching condition.

• The KIPS Transactions:PartB
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• v.15B no.5
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• pp.391-396
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• 2008

Motion of object in a video clip often plays an important role in characterizing the content of the clip. A number of methods have been developed to analyze and retrieve video contents using motion information. However, most of these methods focused more on the analysis of direction or trajectory of motion but less on the analysis of the movement of an object itself. In this paper, we propose the shape sequence descriptor to describe and compare the movement based on the shape deformation caused by object motion along the time. A movement information is first represented a sequence of 2D shape of object extracted from input image sequence, and then 2D shape information is converted 1D shape feature using the shape descriptor. The shape sequence descriptor is obtained from the shape descriptor sequence by frequency transform along the time. Our experiment results show that the proposed method can be very simple and effective to describe the object movement and can be applicable to semantic applications such as content-based video retrieval and human movement recognition.

• Journal of Convergence for Information Technology
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• v.12 no.1
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• pp.15-21
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• 2022

In the content-based video retrieval applications, the information on the movement of an object can be used as important in classifying the content. In particular, analyzing and classifying human movement can be used for various purposes as well as retrieval. In this paper, a method to improve the performance of the shape variation descriptor and shape sequence to describe and classify movement using shape information that changes according to the movement of an object is proposed. By selecting a shape descriptor to more efficiently describe the shape information of an object and comparing the distance function used to measure the similarity, the description and retrieval efficiency of movement information can be increased. Through experiments, it was shown that the proposed method can describe movement information more efficiently and increase the retrieval efficiency compared to the previous method.

• Journal of the Korea Computer Industry Society
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• v.7 no.3
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• pp.253-262
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• 2006

There are some differences between the movements that are produced with closed system and opened system. When an object is moved by the force occurred inside the object, It is called closed movement on the other hand,when the object is moved by the external force. the system is called opened movement. The closed movement model is consist of a linear closed movement system and a nonlinear closed movement system. The approximate equations of the approximate model are derived from the principles and experimental devices of the linear closed movement systems. Various nonlinear closed movement modes and experimental devices are also compared. The results show that linear closed movement model can be derived from nonlinear system due to the couple of nonlinear closed movement model.