• Title/Summary/Keyword: Spatial-temporal combining

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Efficient CT Image Segmentation Algorithm Using both Spatial and Temporal Information

  • Lee, Sang-Bock;Lee, Jun-Haeng;Lee, Samyol
    • Proceedings of the Korea Contents Association Conference
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    • 2004.11a
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    • pp.505-510
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    • 2004
  • This paper suggests a new CT-image segmentation algorithm. This algorithm uses morphological filters and the watershed algorithms. The proposed CT-image segmentation algorithm consists of six parts: preprocessing, image simplification, feature extraction, decision making, region merging, and postprocessing. By combining spatial and temporal information, we can get more accurate segmentation results. The simulation results illustrate not only the segmentation results of the conventional scheme but also the results of the proposed scheme; this comparison illustrates the efficacy of the proposed technique. Furthermore, we compare the various medical images of the structuring elements. Indeed, to illustrate the improvement of coding efficiency in postprocessing, we use differential chain coding for the shape coding of results.

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Spatial Characteristics and Driving Forces of Cultivated Land Changes by Coupling Spatial Autocorrelation Model and Spatial-temporal Big Data

  • Hua, Wang;Yuxin, Zhu;Mengyu, Wang;Jiqiang, Niu;Xueye, Chen;Yang, Zhang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.2
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    • pp.767-785
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    • 2021
  • With the rapid development of information technology, it is now possible to analyze the spatial patterns of cultivated land and its evolution by combining GIS, geostatistical analysis models and spatiotemporal big data for the dynamic monitoring and management of cultivated land resources. The spatial pattern of cultivated land and its evolutionary patterns in Luoyang City, China from 2009 to 2019 were analyzed using spatial autocorrelation and spatial autoregressive models on the basis of GIS technology. It was found that: (1) the area of cultivated land in Luoyang decreased then increased between 2009 and 2019, with an overall increase of 0.43% in 2019 compared to 2009, with cultivated land being dominant in the overall landscape of Luoyang; (2) cultivated land holdings in Luoyang are highly spatially autocorrelated, with the 'high-high'-type area being concentrated in the border area directly north and northeast of Luoyang, while the 'low-low'-type area is concentrated in the south and in the municipal area of Luoyang, and being heavily influenced by topography and urbanization. The expansion determined during the study period mainly took place in the Luoyang City, with most of it being transferred from the 'high-low'-type area; (3) elevation, slope and industrial output values from analysis of the bivariate spatial autocorrelation and spatial autoregressive models of the drivers all had significant effects on the amount of cultivated land holdings, with elevation having a positive effect, and slope and industrial output having a negative effect.

Temporal and Spatial Distributions of PM10, NOx and O3 around the Road (도로 주변의 PM10, NOx 및 O3의 시공간적 농도 분포 연구)

  • Kwon O-Yul;An Young-Sang
    • Journal of Korean Society for Atmospheric Environment
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    • v.22 no.4
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    • pp.440-450
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    • 2006
  • PM10, NOx, and $O_3$ were measured at six locations, of which each three is horizontally and vertically distributed respectively, in an apartment complex around the heavily traffic road. Those were measured seven times a day with two hours interval starting from 8 o'clock in the morning for 15 days during May 2005 $\sim$ September 2005. PM10 and NOx showed high concentrations in rush hours while low concentrations in midday due to the direct emissions from automobiles in operation. Temporal variations of 01 showed very much similar trend appeared in normal urban atmospheres. The spatial distributions of PM10, NOx and $O_3$ showed that almost all of concentrations were higher in a row of Roadside > Surface at 130 m apart from the road > Surface at 230 m apart from the road > 3rd floor of apartment building > 15th floor of apartment building > 27th floor of apartment building. Model equations, which can project spatial concentration distributions, were constructed by combining the horizontal and the vertical linear regression equations derived from six mean values corresponding to six measuring locations. According to inter-comparison of PM10, NOx, and $O_3$ with the constructed model equations, concentration gradients were higher in a row of Vertical direction of NOx > Vertical direction of PM10 > Horizontal direction of NOx > Horizontal direction of PMIO > Vertical direction of $O_3$ > Horizontal direction of $O_3$. Why concentration gradient of particulate PM10 is lower than that of gaseous NOx is in question, and should be studied.

An ESDA Tool for Time-series Spatial Association (지역분석을 위한 시계열 공간연관성 탐색도구)

  • Ahn Jae-Seong;Park Key-Ho;Lee Yang-Won
    • Spatial Information Research
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    • v.14 no.1 s.36
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    • pp.163-176
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    • 2006
  • The concept of 'spatial association' explains spatial distribution pattern of geographical phenomenon based on similarity with neighborhoods, as in the Tobler's Law of Geography: 'Everything is related to everything else, but near things are more related than distant things.' In this study, we develop a time-series exploratory analysis tool for discovering temporal patterns of spatial association by combining spatial statistics and geo-visualization, and thus present a possibility to support spatial decision-making process. As for the spatial proximity weight matrix indispensable to measuring global and local spatial association, we employ a variety of flexible weighting schemes using geometric characteristics of areal unit. In addition, we renovate the existing visualization methods for more effective understanding of the procedures and results of time-series analysis on spatial association: for instance, temporal parallel coordinate plot with box plot, animated map for spatial association, and 3D Moran scatterplot. The feasibility of our system is verified by time-series analysis experiments on the spatial association of land price fluctuation rate for all administrative units in Korea, $1995{\sim}2004$.

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On the Performance of Multi-User 2PPM-TH-UWB SIMO Systems in Multipath Channels

  • Baek, Sun-Young;Kang, Yun-Jeong;Kim, Sang-Choon
    • Journal of information and communication convergence engineering
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    • v.7 no.3
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    • pp.286-291
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    • 2009
  • In this paper, the performance of ultra-wideband (UWB) single input multiple output (SIMO) systems to achieve high data rate communications is studied in dense multipath environments. The effects of spatial and temporal diversities on the performance of multi-user time-hopping UWB systems using binary pulse position modulation (2PPM) are analyzed. The reduced-complexity Rake receivers based on the selective combining (called SRake) and partial combining (called PRake) are considered. The theoretical and simulation results show that the BER performance of the UWB system can be enhanced as the number of array elements and/or Rake fingers increases. Moreover, we observe that SRake is more effective for the IR-UWB systems to achieve a good BER performance, as compared with PRake.

Geo-spatial Analysis of the Seoul Subway Station Areas Using the Haversine Distance and the Azimuth Angle Formulas (다트판형 공간분할 기법을 이용한 서울지역 지하철 역세권 분석)

  • Cho, Jae Hee;Baik, Eui Young
    • Journal of Information Technology Services
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    • v.17 no.4
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    • pp.139-150
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    • 2018
  • This paper investigated the human distribution in subway station areas in Seoul, using geotweets and subway ridership data. Eight stations were selected from the districts of Gangnam and Gangbuk. Geotweets located within a 600-meter radius of the central coordinates of each station were extracted, and distances between the center of station and each tweet location were calculated. Donut-shaped dimension and pie-shaped dimension were generated, using the Haversine distance formula and the Azimuth angle formula respectively. By combining the two dimensions, Dartboard-shaped space division is created. Popular places within the subway station areas identified from this research are almost the same as the current well-known popular places, and this is an important case showing that people send tweets from various places where they engage in daily activities. We expect this study can be a methodological guideline for social scientists who use spatio-temporal or GPS data for their research.

Performance Evaluation for Linear Space-time Coded MIMO-OFDM System considering Diversity-Spatial Multiplexing (다이버시티와 공간 다중화를 고려하여 선형 STBC를 사용한 OFDM 시스템 성능 분석)

  • 이해정;양청해;곽경섭
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.29 no.3A
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    • pp.240-247
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    • 2004
  • In order to transmit data at high speed in the wireless environment, OFDM is selected as the transmission method of various high-speed wireless communication system since it has the advantage to deal easily the serious selective frequency fading channel by the multiple path. We evaluate STBC-OFDM and linear STBC-OFDM combining with a class of recently proposed linear scalable space-time block codes and OFDM in MIMO channel environments, and demonstrate the performance for spatial multiplexing and diversity gain. The codes are able to use jointly transmit diversity in combination with spatial multiplexing, and achieve spatial and temporal diversity. Frequency diversity of frequency selective channels can be utilized by combining the linear STBC and OFDM. Simulation results are shown to demonstrate the better performance of proposed approach in comparison with STBC-OFDM.

Ensemble Method for Predicting Particulate Matter and Odor Intensity (미세먼지, 악취 농도 예측을 위한 앙상블 방법)

  • Lee, Jong-Yeong;Choi, Myoung Jin;Joo, Yeongin;Yang, Jaekyung
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.42 no.4
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    • pp.203-210
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    • 2019
  • Recently, a number of researchers have produced research and reports in order to forecast more exactly air quality such as particulate matter and odor. However, such research mainly focuses on the atmospheric diffusion models that have been used for the air quality prediction in environmental engineering area. Even though it has various merits, it has some limitation in that it uses very limited spatial attributes such as geographical attributes. Thus, we propose the new approach to forecast an air quality using a deep learning based ensemble model combining temporal and spatial predictor. The temporal predictor employs the RNN LSTM and the spatial predictor is based on the geographically weighted regression model. The ensemble model also uses the RNN LSTM that combines two models with stacking structure. The ensemble model is capable of inferring the air quality of the areas without air quality monitoring station, and even forecasting future air quality. We installed the IoT sensors measuring PM2.5, PM10, H2S, NH3, VOC at the 8 stations in Jeonju in order to gather air quality data. The numerical results showed that our new model has very exact prediction capability with comparison to the real measured data. It implies that the spatial attributes should be considered to more exact air quality prediction.

A Study on Video Object Segmentation using Nonlinear Multiscale Filtering (비선형 다중스케일 필터링을 사용한 비디오 객체 분할에 관한 연구)

  • 이웅희;김태희;이규동;정동석
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.28 no.10C
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    • pp.1023-1032
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    • 2003
  • Object-based coding, such as MPEG-4, enables various content-based functionalities for multimedia applications. In order to support such functionalities, as well as to improve coding efficiency, each frame of video sequences should be segmented into video objects. In this paper. we propose an effective video object segmentation method using nonlinear multiscale filtering and spatio-temporal information. Proposed method performs a spatial segmentation using a nonlinear multiscale filtering based on the stabilized inverse diffusion equation(SIDE). And, the segmented regions are merged using region adjacency graph(RAG). In this paper, we use a statistical significance test and a time-variant memory as temporal segmentation methods. By combining of extracted spatial and temporal segmentations, we can segment the video objects effectively. Proposed method is more robust to noise than the existing watershed algorithm. Experimental result shows that the proposed method improves a boundary accuracy ratio by 43% on "Akiyo" and by 29% on "Claire" than A. Neri's Method does.

Continuous Query Modelling for Various Kinds of Monitoring Services for Stream Data (다양한 응용의 스트림 데이터 모니터링을 위한 연속질의 모델링)

  • Cho, Dae-Soo
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.15 no.7
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    • pp.1525-1530
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    • 2011
  • Techniques for processing continuous queries are required to developing the various types of application services (monitoring services) in ubiquitous environment where the real-time data acquisition from a lot of sensors, analysis, and processing are required. In the previous works of the continuous queries, they have represented all of the continuous queries as the interval queries or region queries, and proposed some methods for processing theses queries. The types of continuous queries, however, are very various, and could be presented by combining the attribute conditions, spatial conditions, and temporal conditions. In this paper, I have classify the types of continuous queries, and have proposed the continuous query model which could be presented by combining those conditions. The contributions of this paper include that it proposes the query model representing the continuous queries and suggests future research directions.