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

• Journal of the Korean earth science society
• /
• v.31 no.2
• /
• pp.119-128
• /
• 2010

To make reliable interpretations on the sparse spatial data, the spatial distribution characteristics that are inevitable for spatial estimation should be properly analyzed. Variograms have been widely used for obtaining the spatial characteristics inherent to data in spatial estimation problems. But their applications were limited as the basic information for further data estimation. Therefore, the additional analysis of the meaning of variograms is required for more reliable data processing and interpretations. In this paper, we investigated the proper meaning of variogram values and the specific features of distributions which can be obtained through variogram analysis. Variograms can provide the information on both linearity and the strength changes of interrelationships between the data sets according to the direction and lag distance. First, sill and range values, which are main parameters of variograms, were analyzed. Then a similarity range using spatial auto-correlation values was introduced to verify the applicability of linearity analysis through the comparative study of spatial distribution features of gravity and magnetic data collected in Hwasan caldera. Through these analyses, we were able to identify the dissimilar patterns of gravity and magnetic data that became apparent according to the distribution and variation ranges of the data sets. It is inferred that the gravity and magnetic anomalous bodies are extended to the ground because linearity direction of gravity and magnetic data appear similarly with linearity derection of topography in Hwasan caldera.

• Journal of Korean Society of Rural Planning
• /
• v.10 no.3 s.24
• /
• pp.41-51
• /
• 2004

This study aims to develop a potential evaluation method for urban spatial expansion using remote sensing (RS) and geographic information system (GIS). A multi-criteria evaluation method with several criteria and their weighting values was introduced to evaluate the score and quantification of the potential surface around the existing cities. The six criteria with one geographic factor, slope, and five accessibility factors, time distance from center of the city, national road, interchange of expressway, a big city, and station, were defined for the potential. RS techniques were applied for classification of the actual urban expansion maps between two periods, and GIS functions were used for score of accessibility criteria with a distance decay function from geographic, road and several point maps, which was developed in this study. The new methodology was applied to a test area, Suwon, between 1986 and 1996. In order to optimize the six weighting values, this study made new findings to search the optimal combination of the weighting values from new methodology, weighted scenario method for intensity order (WSM), combined with intensity order and AHP method, including a trial and error method for sensitivity analysis to make the intensity order. The optimal combination of the weighting values by the new method generated the optimal potential surface, considering spatial trend of urban expansion in the test area.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.11 no.11
• /
• pp.2172-2178
• /
• 2007

In indoor environment, the combination of the two variations, large scale(path loss) and small scale(fading), leads to non-linear variation of RSSI(received signal strength indicator) values as distance varied. This has been one of the difficulties for indoor location estimation. This paper presents new findings on indoor RSSI characterization for more accurate model building. Experiments have been done statistically to find overall trend of RSSI values at different places and times within the same room. From experiments, it has been shown that the variation of RSSI values can be determined by both spatial and temporal factors. These two factors are directly indicated by the two main parameters of path loss model. The results show that all sensor nodes which are located at different places share the same characterization value for the temporal parameter whereas different values for the spatial parameters. The temporal parameter also has a large scale variation effect that is slowly time varying due to environmental changes. Using this relationship, the characterization for location estimation can be more efficient and accurate.

• Journal of Ginseng Research
• /
• v.18 no.1
• /
• pp.32-38
• /
• 1994

Male rats aged 15 months, which had been over-trained with 12 arm radial maze up to the criterion of 1 or 2 errors an average per trial, were divided into two groups and 7 months after the over-training and were studied the effect of red ginseng trial saponin fraction (PT) on the spatial memory function. The rats which could be improved the performance of 9.75$\pm$1.26 (within 185$\pm$8.2 1 sec) were classified into "normal group" (n=4) and the ones, which showed R-maze performance of 7.0$\pm$2.87 within 300 sec, "deteriorated memory group" (n=5). PT was dissolved in distilled water and injected into the deteriorated memory group intraperitoneally at 30 min before R-maze for 3 consecutive days. The injected amount of PT on the 1st day was 10mg/rat, 1mg/rat both on the 2nd the 3rd day. As results, the performance was restored to 9.4$\pm$2.0 after stopping ginseng administration, although the lower performance values (1.4$\pm$0.89, 2.8$\pm$0.83, 3.8$\pm$0.84, respectively) were exerted during the three days of PT administration than before PT administration (7.0$\pm$2.87) since 1 day after administratitan of PT. The restored performance values were continuously maintained up to the level of the "normal group". However, any lower performance values were not observed when PT was administered via intraperitoneal route to the normal group in about of 2 mg/rat except 10mg1ra1. The number of errors when the foods in arms were put at only 6 places was clearly reduced during the 9 days of consecutive administration of PT as compared with untreated control. These results indicated that PT administration may enhance their cognitive function after a long lapse of time not only in the memory deteriorated rats but also in normal ones. The reason exerted lower performance values during PT administration in this paper was discussed as compared with the results of T-maze behavior of another 3-month-aged rats. of another 3-month-aged rats.

• Structural Engineering and Mechanics
• /
• v.73 no.6
• /
• pp.651-666
• /
• 2020

In this study, the spatial variation mechanisms of large far-field earthquakes at engineering scales are first investigated with data from the 2008 Ms 8.0 Wenchuan earthquake. And a novel 'coherency cut-off frequency' is proposed to distinguish the spatial variations in ground motions in the low-frequency and high-frequency ranges. Then, a practical piecewise coherency model is developed to estimate and characterize the spatial variation in earthquake ground motions, including the effects of source-to-site distances, site conditions and neighboring topography on these variations. Four particular earthquake records from dense seismograph arrays are used to investigate values of the coherency cut-off frequency for different source-to-site distances. On the basis of this analysis, the model is established to simulate the spatial variations, whose parameters are suitable for both near- and far-field earthquake conditions. Simulations are conducted to validate the proposed model and method. The results show that compared to the existing models, the proposed model provides an effective method for simulating the spatial correlations of ground motions at local sites with known source-to-site distances.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.34 no.2
• /
• pp.111-120
• /
• 2016

Prior knowledge about the SNS (Social Network Services) datasets is often required to conduct valuable analysis using social media data. Understanding the characteristics of the information extracted from SNS datasets leaves much to be desired in many ways. This paper purposes on analyzing the detail of the target social network services, Twitter, Instagram, and YouTube to establish the spatial informatization process to integrate social media information with existing spatial datasets. In this study, valuable information in SNS datasets have been selected and total 12,938 data have been collected in Seoul via Open API. The dataset has been geo-coded and turned into the point form. We also removed the overlapped values of the dataset to conduct spatial integration with the existing building layers. The resultant of this spatial integration process will be utilized in various industries and become a fundamental resource to further studies related to geospatial integration using social media datasets.

• Journal of Electrical Engineering and Technology
• /
• v.9 no.4
• /
• pp.1418-1425
• /
• 2014

In ultrasonic medical imaging, spatial compounding of images is a technique where ultrasonic beam is steered to examine patient tissues in multiple angles. In the conventional ultrasonic diagnostic imaging, the steering of the ultrasonic beam is achieved electronically using the phased array transducer elements. In this paper, a spatial compounding approach is presented where the ultrasonic probe element is rotated mechanically and the beam steering is achieved mechanically. In the spatial compounding, target position is computed using the value of the rotation axis and the transducer array angular position. However, in the process of the rotation mechanism construction and the control system there arises the inevitable uncertainties in these values. These geometric parameter errors result in the target position error, and the consequence is a blurry compounded image. In order to reduce these target position errors, we present a spatial compounding scheme where error correcting transformation matrices are computed and applied to the raw images before spatial compounding to reduce the blurriness in the compounded image. The proposed scheme is illustrated using phantom and live scan images of human knee, and it is shown that the blurriness is effectively reduced.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.54 no.3
• /
• pp.55-63
• /
• 2012

Soil properties are not random values which is represented by mean and standard deviation but show spatial correlation. Especially, soils are highly variable in their properties and rarely homogeneous. Thus, the accuracy and reliability of probabilistic analysis results is decreased when using only one random variable as design parameter. In this paper, to consider spatial variability of soil property, one-dimensional random fields of coefficient of consolidation ($C_v$) were generated based on a Karhunen-Loeve expansion. A Latin hypercube Monte Calro simulation coupled with finite difference method for Terzaghi's one dimensional consolidation theory was then used to probabilistic analysis. The results show that the failure probability is smaller when consider spatial variability of $C_v$ than not considered and the failure probability increased when the autocorrelation distance increased. Thus, the uncertainty of soil can be overestimated when spatial variability of soil property is not considered, and therefore, to perform a more accurate probabilistic analysis, spatial variability of soil property needed to be considered.

• Spatial Information Research
• /
• v.23 no.6
• /
• pp.9-17
• /
• 2015

The convergence industry is a combination of technologies or industries of the same type or various types, thereby maintaining and/or expanding the existing values or creating fresh values. As the industry is drawing greater attention over the world, each country is making huge efforts to provide support for it. GeoSpatial Information is a representative convergence industry characterized by being utilized as a basis for other industrial fields by being linked and fused with other industries and technologies. It is well recognized as being a promising industry that will likely lead the national economy in the future. GeoSpatial Information is necessary to analyze the distinctive features and obstacle factors of the convergence industry. Because it will be able to induce a smooth convergence among different industries. In this paper, we has segmented the support elements through a comparative analysis of the legal system related to (Nano Technology, Information and Communication Technology, Culture Technology, etc)the convergence industry. Based on this proposed policy support for GeoSpatial Information Convergence industry. We expect that this study will be used as basic data of the policy established to effectively support for the GeoSpatial Information convergence industry.