• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.45-48
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• 2008

This paper presents a brief overview of scalable video coding (SVC) with a focus on spatial scalability and its application to Advanced Terrestrial-DMB (AT-DMB). By adopting SVC with two spatial-layers and hierarchical modulation, AT-DMB provides standard definition (SD)-level video while maintaining compatability with the existing CIF-level video. In this paper, we suggest a layer-configuration and coding parameters of SVC which are well suit for an AT-DMB system. In order to reduce extremely large encoding time resulted by an exhaustive search of a macroblock coding mode in spatial scalability, we propose a fast mode decision method which excludes redundant modes in each layer. It utilizes the mode distribution of each layer and their correlations. Experimental results show that a simplified encoding model with the method reduces the computational complexity significantly with negligible coding loss.

• Journal of Environmental Impact Assessment
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• v.18 no.1
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• pp.31-39
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• 2009

A lot of data which are used in environment analysis of air pollution have characteristics that are distributed continuously in space. In this point, the collected data value such as precipitation, temperature, altitude, pollution density, PM10 have spatial aspect. When geostatistical data analysis are needed, acquisition of the value in every point is the best way, however, it is impossible because of the costs and time. Therefore, it is necessary to estimate the unknown values at unsampled locations based on observations. In this study, spatial interpolation method such as local trend surface model, IDW(inverse distance weighted), RBF(radial basis function), Kriging were applied to PM10 annual average concentration of Seoul in 2005 and the accuracy was evaluated. For evaluation of interpolation accuracy, range of estimated value, RMSE, average error were analyzed with observation data. The Kriging and RBF methods had the higher accuracy than others.

• Journal of The Korea Institute of Healthcare Architecture
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• v.24 no.2
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• pp.15-25
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• 2018

Purpose: The important things in space plan of a screening center are improving the spatial awareness by space systemization and minimizing the examination time for customers, and reducing the required time of screening work and maximizing the capacity for the screening center. Therefore, we tried to solve the problem of improving spatial awareness and reducing the examination time by using the pedestrian based discrete event simulation at the minimum cost. Methods: We have analyzed the drawbacks and the supplement points by comparing the floor plan at the time of opening and the current floor plan. Based on the analysis, we propose an improved plan which changes the location of the examination rooms and the number of services, and we also verify the improved plan based on simulation analyses. Results: 1) Through the analyses, we derived the drawbacks of the floor plan at the time of opening, and we realized that the current floor plan reflects the drawbacks. 2) The major reasons of the long examination time are the human traffic jam and the occurrence of queues due to unreasonable allocation of services. 3) Through the discrete event simulation analyses, it was possible to specify the place of the queues manually so as to use the given space fairly. 4) Using the discrete event simulation, it was possible to reduce the examination time and to improve the spatial awareness effectively at the minimum cost. Implications: Although the proposed simulation methodology in this paper is an analysis of the existing screening center, we expect that the proposed methodology will be used to develop a more efficient architectural design process by pre-applying the method to the course of designing a screening center and finding the suitability of the proposed method with the matched number of services.

• Journal of Life Science
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• v.28 no.2
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• pp.148-152
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• 2018

The patchiness of local environments within a habitat is assumed to be a primary factor affecting the spatial patterns of plants, and a randomization procedure is developed for testing the null hypothesis that only spatial association with patches determined the spatial patterns of plants. Chloranthus japonicus (Chloranthaceae) is an herbaceous perennial and a member of the genus Chloranthus in the family Chloranthaceae. The spatial pattern of C. japonicus was analyzed according to several patchiness indices, population uniformity or aggregation under different sizes of plots by dispersion indices, and spatial autocorrelation. Population densities (D) varied from 0.356 to 2.270, with a mean of 1.527. The values of dispersion indices ( at Mt. Ahop were lower than 1 at six plots ($2m{\times}2m$, $2m{\times}4m$, $4m{\times}4m$, $4m{\times}8m$, $8m{\times}8m$, and $8m{\times}16m$), but the two large plots ($16m{\times}16m$ and $16m{\times}32m$) were higher than 1. Thus, the aggregation indices ( were negative at Mt. Ahop, which indicates a uniform distribution. The two large plots ($16m{\times}16m$ and $16m{\times}32m$) had positive CIs. However, the values were not large (0.009 for the $16m{\times}16m$ plot and 0.038 for the $16m{\times}32m$ plot). The mean crowding ($M^{\ast}$) and patchiness index (PAI) showed positive values for all plots.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.5
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• pp.64-78
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• 2019

This paper explores key factors affecting taxi travel using global positioning system(GPS) data in Seoul, Korea, considering spatial dependence. We first analyzed the travel characteristics of taxis such as average travel time, average travel distance, and spatial distribution of taxi trips according to the time of the day and the day of the week. As a result, it is found that the most taxi trips were generated during the morning peak time (8 a.m. to 9 a.m.) and after the midnight (until 1 a.m.) on weekdays. The average travel distance and travel time for taxi trips were 5.9 km and 13 minutes, respectively. This implies that taxis are mainly used for short-distance travel and as an alternative to public transit after midnight in a large city. In addition, we identified that taxi trips were spatially correlated at the traffic analysis zone(TAZ) level through the Moran's I test. Thus, spatial regression models (spatial-lagged and spatial-error models) for taxi trips were developed, accounting for socio-demographics (such as the number of households, the number of elderly people, female ratio to the total population, and the number of vehicles), transportation services (such as the number of subway stations and bus stops), and land-use characteristics (such as population density, employment density, and residential areas) as explanatory variables. The model results indicate that these variables are significantly associated with taxi trips.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.1
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• pp.1-18
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• 2019

This research measured and visualized the spatial dependency and the spatial heterogeneity of the small business in Cheonan-si, Asan-si with $100m{\times}100m$ grids based on global and local spatial autocorrelation. First, we confirmed positive spatial autocorrelation of small business in the research area using Moran's I Index, which is ESDA(Exploratory Spatial Data Analysis). And then, through Getis-Ord $GI{\ast}$, one kind of LISA(Local Indicators of Spatial Association), local patterns of spatial autocorrelation were visualized. These verified that Spatial Regression Model is valid for the location factor analysis on small business commercial buildings. Next, GWR(Geographically Weighted Regression) was used to analyze the spatial relations between the distribution of small business, hourly mobile traffic-based floating population, land use attributes index, residence, commercial building, road networks, and the node of traffic networks. Final six variables were applied and the accessibility to bus stops, afternoon time floating population, and evening time floating population were excluded due to multicollinearity. By this, we demonstrated that GWR is statistically improved compared to OLS. We visualized the spatial influence of the individual variables using the regression coefficients and local coefficients of determinant of the six variables. This research applied the measured population information in a practical way. Reflecting the dynamic information of the urban people using the commercial area. It is different from other studies that performed commercial analysis. Finally, this research has a differentiated advantage over the existing commercial area analysis in that it employed hourly changing commercial service population data and it applied spatial statistical models to micro spatial units. This research proposed new framework for the commercial analysis area analysis.

• Journal of Korea Spatial Information System Society
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• v.9 no.2
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• pp.13-23
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• 2007

Recently there is growing Interest in LBS(Location Based Service) requiring real-time services and the spatial main memory DBMS for efficient Telematics services. In order to optimize existing disk-based multi-dimensional Indexes of the spatial main memory DBMS in the main memory, multi-dimensional index structures have been proposed, which minimize failures in cache access by reducing the entry size. However, because the reduction of entry size requires compression based on the MBR of the parent node or the removal of redundant MBR, the cost of MBR reconstruction increases in index update and the efficiency of search is lowered in index search. Thus, to reduce the cost of MBR reconstruction, this paper proposed the RSMBR(Relative-Sized MBR) compression technique, which applies the base point of compression differently in case of broad distribution and narrow distribution. In case of broad distribution, compression is made based on the left-bottom point of the extended MBR of the parent node, and in case of narrow distribution, the whole MBR is divided into cells of the same size and compression is made based on the left-bottom point of each cell. In addition, MBR was compressed using a relative coordinate and size to reduce the cost of search in index search. Lastly, we evaluated the performance of the proposed RSMBR compression technique using real data, and proved its superiority.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.2
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• pp.1-20
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• 2020

The purpose of this study was to analyze the distribution characteristics of spatial and temporal PM_2.5 in urban areas of Changwon-si, and to identify the causes of PM_2.5 by comparing the characteristics of land-use, and to suggest the direction of reduction measures. As the basic data, the every hour average from September 2017 to August 2018 of Airpro data, which has measurement points in kindergartens, elementary schools, and some middle and high schools in Changwon-si was used. Also, by using IDW method among spatial interpolation methods of GIS, monthly and time-slot distribution maps were constructed, and based on this, spatial and temporal PM_2.5 distribution characteristics were confirmed. First, to verify the accuracy of the Airpro data, the correlation with AirKorea data managed by the Ministry of Environment was confirmed. As a result of the analysis, R² was 0.75~0.86, showing a very high correlation and the data was judged that it was suitable for the study. In the monthly analysis, January was the highest year, and August was the lowest. As a result of analysis by time-slot, The clock-in time at 06-09 was the highest, and the activity time at 09-18 was the lowest. By administrative district, Sangnam-dong, Happo-dong, and Myeonggok-dong were the most severe regions of PM_2.5 and Hoeseong-dong was the lowest. As a result of analyzing the land-use characteristics by administrative area, it was confirmed that the ratio of traffic area and commercial area is high in the serious area of PM_2.5. In conclusion, the results of this study will be used as basic data to grasp the characteristics of PM_2.5 distribution in Changwon-si. Also, it is thought that the severe regions and the direction of establishing reduction measures derived from this study can be used to prepare more effective policies than before.

• Korean Journal of Remote Sensing
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• v.29 no.3
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• pp.315-324
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• 2013

Spatial information of snow cover and depth distribution is a key component for snowmelt runoff modeling. Wide snow cover areas can be extracted from NOAA AVHRR or Terra MODIS satellite images. In this study eight sets of annual snow cover data (1997-2006) in two mountainous watersheds (A: Chungju-Dam and B: Soyanggang-Dam) were extracted using NOAA AVHRR images. The distribution of snow depth within the Snow Cover Area (SCA) was generated using snowfall data from ground meteorological observation stations. Snow depletion characteristics for the two watersheds were analyzed snow distribution time series data. The decreased pattern of SCA can be expressed as a logarithmic function; the determination coefficients were 0.62 and 0.68 for the A and B watersheds, respectively. The SCA decreased over 70% within 10 days from the time of maximum SCA.

• The Journal of the Korea Contents Association
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• v.6 no.11
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• pp.202-216
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• 2006

A number of process algebras are not well suitable for real-time navigation/delivery systems due to the following reasons: 1) lack of representation of process distributivity over some geographical space and 2) the indistinction of representation of process mobility from process distributivity over the space. To make the process algebra suitable to the systems, it seems to be necessary to separate the space representation from the mobility representation. This paper presents a formal method for this purpose, namely, Calculus of Abstract Real-Time Distribution, Mobility, and Interaction (CARDMI). For analysis and verification of behavioral properties, CARDMI defines a set of the spatial, temporal and the interactive deduction rules and a set of equivalence relations. The rules and equivalences can be abstracted hierarchically due to the spatial abstraction, too. CARDMI can be applied to virtual navigation/delivery system for contents, too.