• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.3
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• pp.100-117
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• 2022

This study examines the spatio-temporal characteristics of the macrobenthic community in the coastal areas of South Korea for the past six years(2015-2020). The relationship between the number of individuals of macrobenthic species and the benthic environments were investigated using data collected at a total of 154 stations located in the West (70), the South (61), and the East Seas (23), except for the Jeju Sea. We examined the benthic environmental characteristics such as water depth, sediment, grain size, ignition loss, and total organic carbon. A total of 1,614 macrobenthic species were found in the coastal area, with a mean density of 0.62 ind./m² by station. The mean density was relatively high in the spring and summer seasons (May to August) with more than 450 species. The most dominant species belong to Polychaetes and the top five of them accounted for more than 20% of the total number of populations. The top five species were Heteromastus filiformis, Scoletoma longifolia, Sigambra tentaculata, Sternaspis scutata, and Notomastus latericeus. Cluster analysis was performed on the top five dominant species. The stations were clustered into three groups with similar locations on the West, South, and East Sea. Cluster 1 and 3 represent Heteromastus filiformis (44% each), but cluster 2 represents Scoletoma longifolia (66%). Each cluster has different benthic environmental characteristics, especially in the sediment's sand (31.0%, 51.9%) and clay (15.9%, 9.7%) contents.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1507-1515
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• 2021

If chlorophyll-a is estimated through ocean color remote sensing, it is able to understand the global distribution of phytoplankton and primary production. However, there are missing data in the ocean color observed from the satellites due to the clouds or weather conditions. In thisstudy, the missing data of the GOCI (Geostationary Ocean Color Imager) chlorophyll-a product wasreconstructed by using DINEOF (Data INterpolation Empirical Orthogonal Functions). DINEOF reconstructs the missing data based on spatio-temporal data, and the accuracy was cross-verified by removing a part of the GOCI chlorophyll-a image and comparing it with the reconstructed image. In the study area, the optimal EOF (Empirical Orthogonal Functions) mode for DINEOF wasin 10-13. The temporal and spatialreconstructed data reflected the increasing chlorophyll-a concentration in the afternoon, and the noise of outliers was filtered. Therefore, it is expected that DINEOF is useful to reconstruct the missing images, also it is considered that it is able to use as basic data for monitoring the ocean environment.

• Asian Journal of Atmospheric Environment
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• v.6 no.2
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• pp.127-135
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• 2012

Urbanization has led to a reduction in green spaces and thus transformed the spatial pattern of urban land use. An increase in air temperature directly affects forest vegetation, phenology, and biodiversity in urban areas. In this paper, we analyze the changing land use patterns and urban heat distribution (UHD) in Seoul on the basis of a spatial assessment. It is necessary to monitor and assess the functions of green spaces in order to understand the changes in the green space. In addition, we estimated the influence of green space on urban temperature using Landsat 7 Enhanced Thematic Mapper Plus (ETM+) imagery and climatic data. Results of the assessment showed that UHD differences cause differences in temperature variation and the spatial extent of temperature reducing effects due to urban green space. The ratio of urban heat area to green space cooling area increases rapidly with increasing distance from a green space boundary. This shows that urban green space plays an important role for mitigating urban heating in central areas. This study demonstrated the importance of green space by characterizing the spatiotemporal variations in temperature associated with urban green spaces.

• Journal of Computational Design and Engineering
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• v.1 no.2
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• pp.96-102
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• 2014

In the field of design and manufacturing, there are many problems with managing dynamic states of three-dimensional (3D) objects. In order to solve these problems, the four-dimensional (4D) mesh model and its modeling system have been proposed. The 4D mesh model is defined as a 4D object model that is bounded by tetrahedral cells, and can represent spatio-temporal changes of a 3D object continuously. The 4D mesh model helps to solve dynamic problems of 3D models as geometric problems. However, the construction of the 4D mesh model is limited on the time-series 3D voxel data based method. This method is memory-hogging and requires much computing time. In this research, we propose a new method of constructing the 4D mesh model that derives from the 3D mesh model with continuous rigid body movement. This method is realized by making a swept shape of a 3D mesh model in the fourth dimension and its tetrahedralization. Here, the rigid body movement is a screwed movement, which is a combination of translational and rotational movement.

• 한국공간정보시스템학회:학술대회논문집
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• 2007.06a
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• pp.9-14
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• 2007

오늘날 모바일 장치 기술, 위치 측위 기술, 무선 통신 기술 등이 급속도로 발달하고 이동체 위치 데이타가 널리 활용됨에 따라 차량 관리 시스템, 차량 배차 및 제어 시스템 등과 같은 이동체 위치 데이타를 실시간으로 서비스하기 위한 시스템이 개발되고 있다. 그러나 이러한 시스템에서 기반 시스템으로 사용되는 MO(Moving Object) DBMS 같은 이동체 관리 시스템은 이동체의 실시간 스트림 관리에 비효율적이고, 기존의 DSMS(Data Stream Management System)와 같은 스트림 관리 시스템은 공간 데이터를 효율적으로 처리하지 못하고 있다. 따라서, 본 논문에서는 이동체 위치 데이타의 효율적인 실시간 관리를 위한 시공간 DSMS를 설계 및 구현하였다. 본 논문에서 구현한 시공간 DSMS는 스탠포드 대학의 STREAM(STanford stREam dAta Manager)을 기반으로 이동체 위치 데이타의 실시간 관리와 공간 및 시공간 질의 처리 기능을 지원하는 시스템이다. 특히, 시공간 DSMS에서 사용하는 시공간 함수는 호환성을 위해서 OGC에서 제시한 "SQL을 위한 심플 피쳐 명세"를 따르는 표준 인터페이스를 지원한다. 마지막으로 본 논문에서 구현한 시공간 DSMS를 이동체 위치 데이타의 실시간 관리가 필요한 실시간 모니터링 분야에 적용해 봄으로써 시스템의 효용성을 입증하였다.

• Journal of KIISE:Software and Applications
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• v.26 no.1
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• pp.157-157
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• 1999

Researches on the gesture recognition have become a very interesting topic in the computer vision area, Gesture recognition from visual images has a number of potential applicationssuch as HCI (Human Computer Interaction), VR(Virtual Reality), machine vision. To overcome thetechnical barriers in visual processing, conventional approaches have employed cumbersome devicessuch as datagloves or color marked gloves. In this research, we capture gesture images without usingexternal devices and generate a gesture trajectery composed of point-tokens. The trajectory Is spottedusing phase-based velocity constraints and recognized using the discrete left-right HMM. Inputvectors to the HMM are obtained by using the LBG clustering algorithm on a polar-coordinate spacewhere point-tokens on the Cartesian space .are converted. A gesture vocabulary is composed oftwenty-two dynamic hand gestures for editing drawing elements. In our experiment, one hundred dataper gesture are collected from twenty persons, Fifty data are used for training and another fifty datafor recognition experiment. The recognition result shows about 95% recognition rate and also thepossibility that these results can be applied to several potential systems operated by gestures. Thedeveloped system is running in real time for editing basic graphic primitives in the hardwareenvironments of a Pentium-pro (200 MHz), a Matrox Meteor graphic board and a CCD camera, anda Window95 and Visual C++ software environment.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.04a
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• pp.833-836
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• 2017

최근 블랙박스 및 CCTV 같은 영상 촬영 장치가 보편화되면서, 방대한 양의 영상 데이터가 실시간으로 생성되고 있다. 만약 이 대용량 데이터 안의 차량 정보를 추출할 수 있다면 범죄 차량 추적, 교통 혼잡도 측정 등의 활용이 가능할 것이다. 이를 구현하기 위해서는 수많은 자동차에서 실시간으로 생성되는 영상 데이터를 처리할 수 있는 시스템이 필수적이나, 이러한 시스템을 찾기 힘든 것이 현실이다. 이를 위해 이 논문에서는 아파치 카프카, Hbase를 이용한 영상 빅데이터 처리 시스템을 제안한다. 아파치 카프카는 시스템 내에서 영상 손실이 없는 전송과 영상 처리 노드의 스케줄링을 수행하며, Hbase는 처리된 데이터를 테이블로 저장하고 사용자가 보낸 쿼리를 처리한다. 더불어, Hbase에 인덱스를 구성하여 빠른 쿼리 처리가 가능하도록 만든다. 실험 결과, 제안된 시스템은 인덱스가 없을 때보다 뛰어난 쿼리 처리 성능을 보이는 것을 확인할 수 있었다.

• Journal of the Korea Society of Computer and Information
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• v.11 no.6 s.44
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• pp.9-17
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• 2006

Moving objects database systems manage a set of moving objects which changes its locations and directions continuously. The traditional spatial indexing scheme is not suitable for the moving objects because it aimed to manage static spatial data. Because the location of moving object changes continuously, there is problem that expense that the existent spatial index structure reconstructs index dynamically is overladen. In this paper, we analyzed the insertion/deletion costs for processing the movement of objects. The results of our extensive experiments show that the Dynamic Hashing Index outperforms the original R-tree and the fixed grid typically by a big margin.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.10
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• pp.2137-2142
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• 2012

Many studies in detection and classification of the targets in the underwater environments have been conducted for military purposes, as well as for non-military purpose. Due to the complicated characteristics of underwater acoustic signal reflecting multipath environments and spatio-temporal varying characteristics, active sonar target classification technique has been considered as a difficult technique. And it has a difficult in collecting actual underwater data. In this paper, we implemented the simulator to synthesize the active target signal, to extract feature and to classify the target in the underwater environment. In target signal synthesis, highlight and three-dimensional model are used and multi-aspect based hidden markov model is used for target classification.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.11
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• pp.2505-2511
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• 2013

Many studies in detection and classification of the targets in the underwater environments have been conducted for military purposes, as well as for non-military purpose. Due to the complicated characteristics of underwater acoustic signal reflecting multipath environments and spatio-temporal varying characteristics, active sonar target classification technique has been considered as a difficult technique. And it has difficulties in collecting actual underwater data. In this paper, we synthesized active target echoes based on ray tracing algorithm using target model having 3-dimensional highlight distribution. Then, Fractional Fourier transform was applied to synthesized target echoes to extract feature vector. Recognition experiment was performed using neural network classifier.