• Ocean and Polar Research
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• v.44 no.2
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• pp.179-190
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• 2022

Data missing in optical satellite images caused by natural variations have been a crucial barrier in observing the status of marine surfaces. Although there have been many attempts to fill the gaps of non-observation, there is little research to analyze the ratio of missing grids to overall sea grids and their seasonal patterns. This report introduces the method of quantifying the distribution of missing points and then shows how the missing points have spatial correlation and seasonal trends. Both temporal and spatial integration methods are compared to assess the effectiveness of reducing missing data. The temporal integration shows more outstanding performance than the spatial integration. Moran's I and K-function with statistical hypothesis testing show that missing grids are clustered and there is a non-random distribution from daily integration. The result of the seasonality test for Moran's I through a periodogram shows dependency on full-year, half-year, and quarter-year periods respectively. These analysis results can be used to deduce appropriate integration periods with permissible estimation errors.

• The Korean Journal of Applied Statistics
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• v.19 no.3
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• pp.599-617
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• 2006

Recently many LBS(Location Based Service) systems are issued in mobile computing systems. Spatial-Temporal Moving Sequence Pattern Mining is a new mining method that mines user moving patterns from user moving path histories in a sensor network environment. The frequent pattern mining is related to the items which customers buy. But on the other hand, our mining method concerns users' moving sequence paths. In this paper, we consider the sequence of moving paths so we handle the repetition of moving paths. Also, we consider the duration that user spends on the location. We proposed new Apriori_msp based on the Apriori algorithm and evaluated its performance results.

• The KIPS Transactions:PartD
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• v.11D no.4
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• pp.893-900
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• 2004

This paper is to define the method that develops the software In proper to application areas of Geographic Information Systems and design patterns according to functions and roles that implement the system for safety evaluation of the groundwater well based on an object oriented spatial model. In order to design the user interface of the groundwater well, this paper proposes the framework that should classify only requisite components adaptable to various application areas. By specifying De pattern appropriate to the application domain and designing the analysis pattern using the UML based on the object oriented methodology. this paper shah contribute to enhance the reuse of components that can develop and distribute a .large scale open system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.6
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• pp.3121-3143
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• 2019

Segmentation plays an important role in the field of image processing and computer vision. Intuitionistic fuzzy C-means (IFCM) clustering algorithm emerged as an effective technique for image segmentation in recent years. However, standard fuzzy C-means (FCM) and IFCM algorithms are sensitive to noise and initial cluster centers, and they ignore the spatial relationship of pixels. In view of these shortcomings, an improved algorithm based on IFCM is proposed in this paper. Firstly, we propose a modified non-membership function to generate intuitionistic fuzzy set and a method of determining initial clustering centers based on grayscale features, they highlight the effect of uncertainty in intuitionistic fuzzy set and improve the robustness to noise. Secondly, an improved nonlinear kernel function is proposed to map data into kernel space to measure the distance between data and the cluster centers more accurately. Thirdly, the local spatial-gray information measure is introduced, which considers membership degree, gray features and spatial position information at the same time. Finally, we propose a new measure of intuitionistic fuzzy entropy, it takes into account fuzziness and intuition of intuitionistic fuzzy set. The experimental results show that compared with other IFCM based algorithms, the proposed algorithm has better segmentation and clustering performance.

• 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.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2013.05a
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• pp.1349-1350
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• 2013

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1242-1242
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• 2003

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.1260-1264
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• 2009

Precipitation time series is a mixture of complicate fluctuation and changes. The monthly precipitation data of 61 stations during 36 years (1973-2008) in Korea are comprehensively analyzed using the EOFs technique and CSEOFs technique respectively. The main motivation for employing this technique in the present study is to investigate the physical processes associated with the evolution of the precipitation from observation data. The twenty-five leading EOF modes account for 98.05% of the total monthly variance, and the first two modes account for 83.68% of total variation. The first mode exhibits traditional spatial pattern with annual cycle of corresponding PC time series and second mode shows strong North South gradient. In CSEOF analysis, the twenty-five leading CSEOF modes account for 98.58% of the total monthly variance, and the first two modes account for 78.69% of total variation, these first two patterns' spatial distribution show monthly spatial variation. The corresponding mode's PC time series reveals the annual cycle on a monthly time scale and long-term fluctuation and first mode's PC time series shows increasing linear trend which represents that spatial and temporal variability of first mode pattern has strengthened. Compared with the EOFs analysis, the CSEOFs analysis preferably exhibits the spatial distribution and temporal evolution characteristics and variability of Korean historical precipitation.

• Journal of architectural history
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• v.3 no.2 s.6
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• pp.47-66
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• 1994

Chosun dynasty had accepted the Confucianism as a means of governing whole society and in its practical aspect ${\ulcorner}$Garye${\lrcorner}$ and the ceremonies of family ritual regarded as important. As a result, after mid-Chosun dynasty family ritual was begun to popularized on a national scale, and the socio-culture system which was interrelated with it changed into confucian ones. These fill-scaled change, on the other hand, resulted into the change of spatial use and plan type of yangban houses. In this aspect, this study intends to clarify the influence of family ritual on spatial use of yangban houses through the comparison between ideal pattern and behavioral one of family ritual. And this study made Gwanhonrye except Sangjerye an object because these two ceremonies were peformed in sucession in those day's behavior. The research setting is the Korean traditional society prior to modernization. The collected materials are based on ethnographic information as well as personal documents, public records, field works and the books on family ritual. The methodology for the present study is primarily based on the comparison study between available documents and field work. Especially, as the books on family ritual include some explanatory diagrams of the ideal pattern, these diagrams are compared with another ones made by the author of the behavioral pattern. The major findings are as follows. Firstly, in the aspect of Gwanhonrye's process, the ideal pattern is similar to the behavioral one. But even the essential course of the ideal pattern of Honrye is 'chinyoung', it has never been accepcted in Chosun dynasty on account of 'seoryubuga'. Secondly, even though the names of the performing space of family ritual are different each pattern, the methods of spatial use in processing these two ceremonies are similar. In other words, according to the books on family ritual the major performing spaces of Gwanhonrye are 'chungsa' and 'jungchim', but in practical process of both ceremonies 'sarangchae' and 'anche' are used. Lastly, as family ritual like Gwanrye and Honrye had been practiced at yangban houses after mid-Chosun dynasty as mentioned above, the spatial arrangement had to be changed to a certain extent.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.5
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• pp.871-876
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• 2006

In this thesis, to accurately measure 3D face information using the spatial encoding patterns, the new algorithm to segment the pattern images from initial face pattern image is proposed. If the obtained images is non-homogeneous texture and ambiguous boundary pattern, the pattern segmentation is very difficult. Furthermore. the non-encoded areas by accumulated error are occurred. In this thesis, the FCM(fuzzy c-means) clustering method is proposed to enhance the robust encoding and segmentation rate under non-homogeneous texture and ambiguous boundary pattern. The initial parameters for experiment such as clustering class number, maximum repetition number, and error tolerance are set with 2, 100, 0.0001 respectively. The proposed pattern segmentation method increased 8-20% segmentation rate with conventional binary segmentation methods.