• Title/Summary/Keyword: Spatio-temporal data

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Construction of a Spatio-Temporal Dataset for Deep Learning-Based Precipitation Nowcasting

  • Kim, Wonsu;Jang, Dongmin;Park, Sung Won;Yang, MyungSeok
    • Journal of Information Science Theory and Practice
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    • v.10 no.spc
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    • pp.135-142
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    • 2022
  • Recently, with the development of data processing technology and the increase of computational power, methods to solving social problems using Artificial Intelligence (AI) are in the spotlight, and AI technologies are replacing and supplementing existing traditional methods in various fields. Meanwhile in Korea, heavy rain is one of the representative factors of natural disasters that cause enormous economic damage and casualties every year. Accurate prediction of heavy rainfall over the Korean peninsula is very difficult due to its geographical features, located between the Eurasian continent and the Pacific Ocean at mid-latitude, and the influence of the summer monsoon. In order to deal with such problems, the Korea Meteorological Administration operates various state-of-the-art observation equipment and a newly developed global atmospheric model system. Nevertheless, for precipitation nowcasting, the use of a separate system based on the extrapolation method is required due to the intrinsic characteristics associated with the operation of numerical weather prediction models. The predictability of existing precipitation nowcasting is reliable in the early stage of forecasting but decreases sharply as forecast lead time increases. At this point, AI technologies to deal with spatio-temporal features of data are expected to greatly contribute to overcoming the limitations of existing precipitation nowcasting systems. Thus, in this project the dataset required to develop, train, and verify deep learning-based precipitation nowcasting models has been constructed in a regularized form. The dataset not only provides various variables obtained from multiple sources, but also coincides with each other in spatio-temporal specifications.

Tracking of Multiple Vehicles Using Occlusion Segmentation Based on Spatio-Temporal Association

  • Lim, Jun-Sik;Kim, Soo-Hyung;Lee, Guee-Sang;Yang, Hyung-Jeong;Na, In-Seop
    • International Journal of Contents
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    • v.7 no.4
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    • pp.19-23
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    • 2011
  • This paper proposes a segmentation method for overlapped vehicles based on analysis of the vehicle location and the spatiotemporal association information. This method can be used in an intelligent transport system. In the proposed method, occlusion is detected by analyzing the association information based on a vehicle's location in continuous images, and occlusion segmentation is carried out by using the vehicle information prior to occlusion. In addition, the size variations of the vehicle to which association tracking is applied can be anticipated by learning the variations according to the overlapped vehicles' movements. To assess the performance of the suggested method, image data collected from CCTVs recording traffic information is used, and average success rate of occlusion segmentation is 96.9%.

Proper Orthogonal Decomposition Analysis of Dynamic Wind Pressures Acting on a Tall Tower Model (고층 타워에 작용하는 동적 풍압력의 POD 방법을 이용한 시공간적 특성 해석)

  • Yi, Mee-Hwa;Ham, Hee-Jung
    • Journal of Industrial Technology
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    • v.24 no.B
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    • pp.29-36
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    • 2004
  • The wind and wind-induced dynamic wind pressures fluctuate irregularly according to time and space. In this study, the proper orthogonal decomposition(POD) technique is applied to wind pressures acting on a tall tower model, and the following results are found: the along-wind and across-wind forces can be reconstructed by only four dominant POD modes, and the reconstructed errors are 4.71% and 22%, respectively for across-wind and along-wind directions. The physical meanings for dominant modes are also presented in the paper. The POD analysis can compress complex wind pressure data only by a few dominant modes and interpret spatio-temporal characteristics of wind pressure by novel way while existing statistical methods do not have such benefits.

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Development of Spatio-Temporal Neural Network for Connected Korean Digits Recognition (한국어 연결 숫자음 인식을 위한 시공간 신경회로망의 개발)

  • 이종식
    • Proceedings of the Acoustical Society of Korea Conference
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    • 1995.06a
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    • pp.69-72
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    • 1995
  • In this paper, a new approach for Korean connected digits recognition using the spatio-temporal neural network is reported. The data of seven digits phone numbers are used in the recognition of connected words, and in the initial experiment, digit recognition rate of 28% was achieved. In this paper, to increase recognition rate, two different approaches are analyzed. In the first system, to compensate the STNN's own defect and to emphasize the Korean word's phonic characters, the starting point of phone is pointed by comparing the average magnitude and zero-crossing rate and the ending point is pointed by comparing only zero-crossing rate. The digit recoginiton rate increased to 61%. Also, in the second system, to consider fact that same word's phone is varied severally, the number of STNN's of each word is increased from one to five, and then the varied same word's phones can be included to the increased STNN's. The digit recogniton rate of connected words increased to 89%.

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gCRM and Spatial Data Mining (gCRM과 공간데이타마이닝)

  • Hwang, Jung-Rae;Li, Ki-Joune
    • 한국공간정보시스템학회:학술대회논문집
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    • 2002.03a
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    • pp.38-44
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    • 2002
  • 고객관계관리(CRM)나 마케팅과 같은 경영방식에서도 대용량의 공간 데이터베이스를 사용하는 지리정보시스템(GIS)과 같은 응용분야를 접목하고 있다. gCRM은 지리정보시스템과 고객관계관리를 결합한 것으로, 이러한 실정을 단적으로 보여 주고 있는 경영방식이다. gCRM은 대용량의 데이터베이스로부터 관심 있는 분야를 찾아내고 분석하게 된다. 그러기 위해서는 데이터마이닝이라는 기술이 필요하다. 하지만, gCRM은 일반적인 데이터베이스뿐만 아니라 공간 데이터베이스 역시 많이 사용되어진다. 이러한 공간데이터베이스로부터 관심 있는 부분이나 관계 그리고 특성 등을 찾아내기 위해서는 공간데이타마이닝이 요구된다. 본 논문에서는 gCRM 솔루션들의 기능을 중심으로 다양한 공간데이타마이닝 기법과 어떠한 관계가 있는지를 살펴봄으로써 gCRM과 공간데이타마이닝이 접목할 수 있는 부분에 대하여 정리하였다.

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Spatio-Temporal Characteristics of the Ullung Warm Lens

  • KANG Hye-Eun;KANG Yong Q.
    • Korean Journal of Fisheries and Aquatic Sciences
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    • v.23 no.5
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    • pp.407-415
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    • 1990
  • We studied the spatio-temporal characteristics of the Ullung Warm Lens (UWL) using the historical oceanographic data of the National Fisheries Research and Development Agency of Korea in the East Sea from 1967 to 1983. The UWL is basically a subsurface phenomenin found in 100 to 300m depths, and its existence is not well posed in the distribution of the sea surface temperature. The UWL has a typical size of 100 km diameter, and its center migrates within the region of 150 by 150 km south of the Ullung Island. The UWL is almost a permanent feature, and the probability of its occurence within our study area ($129\~132^{\circ}E,\;36\~38^{\circ}N)\;was\;86\%$.

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Design of User Interface for Query and Visualization about Moving Objects in Mobile Device

  • Lee, Jai-Ho;Nam, Kwang-Woo;Kim, Min-Soo
    • Proceedings of the KSRS Conference
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    • 2002.10a
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    • pp.832-837
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    • 2002
  • As diverse researches are working about location acquisition, storing method, data modeling and query processing of moving objects, the moving object database systems, which can gain, store and manage location information and query processing, are tuning up. As the mobile device is moving but have constraints, the convenience user interface for spatio-temporal query and viewing query result needs. In this paper, we designed user Interface for spatio-temporal query related moving objects, viewing query result, tracing current and past location of those and monitoring. And we designed system for implementation of these interfaces.

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Design of Recovery Protocol for Synchronization of Spatio-Temporal Data on a Mobile Environments (모바일 환경에서 시공간데이터의 동기화를 위한 회복프로토콜 설계)

  • Kim, Hong-Ki;Kim, Dong-yun;Cho, Dae-Soo
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2009.10a
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    • pp.253-256
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    • 2009
  • Synchronization system which applies to two-way synchronization of spatio-temporal in the mobile environment maintains a consistence of DB from some defect during synchronization. This study analyzes defects that are generated at the mobile client-server environment and proposes recovery protocol which can rerun consistence of DB and synchronization.

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Spatio-Temporal Trends in Temperature, Acidification and Dissolved Oxygen in Lower Mekong Basin for 1985-2005

  • Ratanavong, Nilapha;Lim, Sam-Sung;Lee, Hyung-Seok
    • Journal of Korean Society for Geospatial Information Science
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    • v.19 no.4
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    • pp.3-12
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    • 2011
  • Understanding of water sediment trends is an important part of water quality monitoring. Water quality variables change over time and space, and cannot be modeled or explained clearly by either temporal or spatial analysis alone. This research analysed the trends of temperature, pH levels and dissolved oxygen levels based on the sediment records and spatial data obtained in Lower Mekong Basin (LMB) during 1985-2005. Our aim is to evaluate spatio-temporal trends and graphical analyses using an Inverse Distance Weighting (IDW) interpolation method. The main results from this research can be summarized as follows. The maximum temperature and pH have been stable during the study period and the maximum dissolved oxygen has been increasing gradually until 2002. The minimum pH and dissolved oxygen have been changing in an unsteady trend during the period. A spatial analysis shows that the water temperature in this region has been increasing over time. The pH trend shows that it is decreasing during 1993-2005. Dissolved oxygen concentration has been increasing from 1989 onwards and stays in that track.

Application of Remote Sensing and Geographic Information System in Forest Sector (원격탐사와 지리정보시스템의 산림분야 활용)

  • Lee, Woo-Kyun;Kim, Moonil;Song, Cholho;Lee, Sle-gee;Cha, Sungeun;Kim, GangSun
    • Journal of Cadastre & Land InformatiX
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    • v.46 no.2
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    • pp.27-42
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    • 2016
  • Forest accounts for almost 64 percents of total land cover in South Korea. For inventorying, monitoring, and managing such large area of forest, application of remote sensing and geographic information system (RS/GIS) technology is essential. On the basis of spectral characteristics of satellite imagery, forest cover and tree species can be classified, and forest cover map can be prepared. Using three dimensional data of LiDAR(Light Detection and Ranging), tree location and tree height can be measured, and biomass and carbon stocks can be also estimated. In addition, many indices can be extracted using reflection characteristics of land cover. For example, the level of vegetation vitality and forest degradation can be analyzed with VI (vegetation Index) and TGSI (Top Grain Soil Index), respectively. Also, pine wilt disease and o ak w ilt d isease c an b e e arly detected and controled through understanding of change in vegetation indices. RS and GIS take an important role in assessing carbon storage in climate change related projects such as A/R CDM, REDD+ as well. In the field of climate change adaptation, impact and vulnerability can be spatio-temporally assessed for national and local level with the help of spatio-temporal data of GIS. Forest growth, tree mortality, land slide, forest fire can be spatio-temporally estimated using the models in which spatio-temporal data of GIS are added as influence variables.