• Korean Journal of Childcare and Education
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• v.15 no.6
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• pp.139-167
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• 2019

Objective: This study aims to investigate the effects of a learning cycle model-based early childhood education program using physical motion on young children's scientific inquiry ability, scientific attitude, object manipulation ability and spatial ability. Methods: The subjects of this study were 60 five-year-old children who were attending K-G City Childcare Center. The SPSS Window 21.0 program and content analysis method were used, and post-validation Tukey was conducted to examine the differences between the one-way ANOVA and the group. Results: Activities using body movement were practiced systematically based on the circle learning. Children could revise their pre-concept and concept of error by interacting with other children, teachers and the environment. Furthermore, children were attaining new knowledge while they were doing body movement activities, assessing and applying them to actual activities. Conclusion/Implications: This study is investigated a cyclic learning-based early childhood science education program using physical motion, which has significance in systematic and practical early childhood centered education for young children.

• Proceedings of the Korea Information Processing Society Conference
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• 2002.11c
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• pp.1791-1794
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• 2002

이동체데이터베이스((MODB : Moving Object Database)는 사람이나 또는 자동차와 같이 이동성을 가지는 객체를 저장하고 관리하는 시스템이다. LBS(Location-Based Services)의 활성화로 인해서 위치정보(Location Information)는 다양하고 고부가가치의 서비스를 가능하게 하였으며, 차세대 무선인터넷 서비스의 킬러 어플리케이션으로 확대될 전망에 있다. 이러한 LBS 시스템에서 대용량의 위치정보를 저장하고, 빠르게 접근하는 이동체데이터베이스는 LBS 플랫폼의 핵심 기능 중의 하나이다. 향후에 위치정보를 이용한 서비스가 확대되어, 일반인이 쉽게, 그리고 필수적으로 사용되는 기능으로 확대 되었을 때, 이동체데이터베이스의 중요성은 더욱 커질 것이며, 이동체데이터베이스의 시스템 부하는 그만큼 커지게 된다. 더군다나 대용량 이동체 정보를 획득하는 부분에서도 통신부하의 심각성은 미리 고려되어져야 함을 쉽게 예측할 수가 있다. 즉, 대용량의 위치정보를 다양한 디바이스를 통해서 무선인터넷환경에서 획득하려고 할 때, 그 수가 많으면 많을수록 통신부하는 점점 커지며, 획득한 정보는 이미 과거의 정보가 되어서 사용할 수 없는 정보가 될 수가 있다. 이에 본 논문에서는 이동체데이터베이스의 위치획득 부분에서 통신 부하를 줄이기 위한 다양한 모델에 대해서 논의하고 구현에 앞서 설계한다.

• Journal of the Optical Society of Korea
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• v.19 no.1
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• pp.29-37
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• 2015

The wavefront printer records a volume-reflection hologram as a two-dimensional array of elemental holograms from computer-generated holograms (CGHs) displayed on a spatial light modulator (SLM). The wavefront coming from the object is extracted by filtering in the spatial-frequency domain. This paper presents a method to improve color reproduction in a wavefront printer with spatial division of exposures at primary colors, by adaptive partitioning of the SLM in accordance with the color content encoded in the input CGHs, and by the controllable change of exposure times for the recording of primary colors. The method is verified with a color wavefront printer with demagnification of the object beam. The quality of reconstruction achieved by the proposed method proves its efficiency in eliminating the stripe artifacts that are superimposed on reconstructed images in conventional mosaic recording.

• Journal of Korea Spatial Information System Society
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• v.11 no.4
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• pp.85-88
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• 2009

In multimedia database systems, the nearest neighbor Query occurs frequently and requires the processing cost higher than other spatial Queries do. It needs the measurement of search distance that the number of searched nodes and the computation time in an index can be minimized for optimizing the cost of processing the nearest neighbor query. The circular location property of objects is considered to accurately select the nodes which will be searched in the nearest neighbor query. In this paper, we propose the processing method of nearest neighbor queries be considered a circular location property of object where the search space consists of a circular domain and show its characteristics. The proposed method uses the circular minimum distance and the circular optimal distance, the search measurement for optimizing the processing cost of nearest neighbor queries.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.2
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• pp.189-197
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• 2012

This research attempted to find possibilities of the practical use utilizing geospatial methods for the balanced promotion of sustainable coastal development and preservation through a case study of Jekyll Island, one of Georgia's barrier islands. In response, this research provided ways for practical use in sustainable development and preservation plans. First this research thoroughly investigated the 1996 master plan of Jekyll Island and tried to recalculate developed and undeveloped areas. Second, new estimations for developed areas were investigated through field survey. Third, this research proposed the use of the satellite images with different levels of spatial resolutions and tested different classification schemes to find possibilities for practical use. For these purposes, first, we classified developed and undeveloped features by manual digitization using an aerial photo image with 0.5m spatial resolution. Second, a Landsat 7 ETM+ and a QuickBird satellite images with mid- and high-levels of spatial resolutions were applied to identify developed and undeveloped areas using both the National Land Cover Data (NLCD) and the Coastal Change Analysis Program (CCAP) classification schemes. Also, GEOBIA (Geographic Object-Based Image Analysis) was conducted to accurately identify developed and undeveloped areas.

• Journal of Digital Contents Society
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• v.12 no.1
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• pp.77-83
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• 2011

Providing services in a wireless environment with existing wired-based GIS solutions have many limitations such as slow communication, processing rates, and screen size. Among the components, data is considered to be the most important factor in GIS. In this paper, I describe MVF, the most recent technology pioneered by GIS researchers. MVF is a format for efficient usage of spatial object in order to express, save and transform in mobile GIS. First, I describe the definition of MVF syntax, then the implementation of Header Section Generation Module and Main Section Generation Module through the API. Since the issues of network traffic and Hangul processing in mobile GIS are important, I especially consider development of MVF in terms of spatial data size.

• The Journal of Korean Association of Computer Education
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• v.6 no.4
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• pp.49-59
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• 2003

In order to index exactly moving objects(vehicle, mobile phone, PDA, etc.) in a mobile database, continuous updates of their locations arc inevitable as well as time-consuming. In this paper, we propose a spatial indexing method of moving objects for the efficient mobile map services. In detail, we analyze the characteristics of both the method to re-index all the objects after each time period and the method to update immediately the locations on reporting their locations. We also newly propose a bucket split method using the properties of moving objects in order to minimize the number of database updates. The experiments conducted on the environments of moving object show that the proposed indexing method is appropriate to map services for mobile devices.

• Spatial Information Research
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• v.19 no.2
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• pp.57-64
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• 2011

This paper describes how to storing and querying trajectory information on PostgreSQL/PostGIS. Recently as technology of mobile devices is advancing, many researches for location-based services and moving object's trajectory have been studied. Trajectory is the set of information of the location by the time, and is one of the most im portant information for location-based services. Traditional spatial database systems do not support trajectory data types and functions. In this paper, we propose a trajectory data type and query functions for moving objects on PostgreSQL/PostGIS.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.07a
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• pp.317-318
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• 2019

가상/증강현실로 대표되는 공간정보 기반 실감형 콘텐츠에 대한 관심이 증대되면서 객체인식 등의 지능형 공간인지 기술에 대한 연구가 활발히 진행되고 있다. 특히 HMD등의 영상 시각화 장치의 발달 및 5G 통신기술의 출현으로 인해 실시간 대용량 영상정보의 송, 수신 및 가시화 처리 기술의 기반이 구축됨에 따라, $360^{\circ}$ 스트리밍 영상정보 처리와 같은 고자유도 콘텐츠를 위한 관련 연구의 필요성이 증대되고 있다. 하지만 지능형 영상정보 처리의 대표적 연구인 딥 러닝(Deep Learning) 기반 객체 인식 기술의 경우 대부분 일반적인 평면 영상(Planar Image)에 대한 처리를 다루고 있고, 파노라마 영상(Panorama Image) 특히, $360^{\circ}$ 스트리밍 영상 처리를 위한 연구는 미비한 상황이다. 본 논문에서는 딥 러닝을 이용하여 $360^{\circ}$ 스트리밍 영상에서의 객체인식 연구 방법에 대해 서술한다. 이를 위해 $360^{\circ}$ 카메라 영상에서 딥 러닝을 위한 학습 데이터를 획득하고, 실시간 객체 인식이 가능한 YOLO(You Only Look Once)기법을 이용하여 학습을 한다. 실험 결과에서는 학습 데이터를 이용하여 $360^{\circ}$영상에서 객체 인식 결과와, 학습 횟수에 따른 객체 인식에 대한 결과를 보여준다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.207-209
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• 2021

In recent years, with the development of artificial intelligence and IoT technology, automation and unmanned technology are in progress in various fields, and the importance of image processing such as object tracking, medical images and object recognition, which are the basis of this, is increasing. In particular, in systems requiring detailed data processing, noise reduction is used as a pre-processing step, but the existing algorithm has a disadvantage that blurring occurs in the filtering process. Therefore, in this paper, we propose a filter algorithm using modified spatial weights to minimize information loss in the filtering process. The proposed algorithm uses mask matching to remove AWGN, and obtains the output of the filter by adding or subtracting the output of the modified spatial weight. The proposed algorithm has superior noise reduction characteristics compared to the existing method and reconstructs the image while minimizing the blurring phenomenon.