• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.2
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• pp.95-100
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• 2010

This paper proposes a new spatial regularization of Fisher linear discriminant analysis (LDA) to reduce the overfitting due to small size sample (SSS) problem in face recognition. Many regularized LDAs have been proposed to alleviate the overfitting by regularizing an estimate of the within-class scatter matrix. Spatial regularization methods have been suggested that make the discriminant vectors spatially smooth, leading to mitigation of the overfitting. As a generalized version of the spatially regularized LDA, the proposed regularized LDA utilizes the non-uniformity of spatial correlation structures in face images in adding a spatial smoothness constraint into an LDA framework. The region-dependent spatial regularization is advantageous for capturing the non-flat spatial correlation structure within face image as well as obtaining a spatially smooth projection of LDA. Experimental results on public face databases such as ORL and CMU PIE show that the proposed regularized LDA performs well especially when the number of training images per individual is quite small, compared with other regularized LDAs.

• Steel and Composite Structures
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• v.11 no.2
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• pp.115-130
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• 2011

Considering the randomness of material parameters in the laminated composite plate, a scheme of stochastic finite element method to analyze the displacement response variability is suggested. In the formulation we adopted the concept of the weighted integral where the random variable is defined as integration of stochastic field function multiplied by a deterministic function over a finite element. In general the elastic modulus of composite materials has distinct value along an individual axis. Accordingly, we need to assume 5 material parameters as random. The correlations between these random parameters are modeled by means of correlation functions, and the degree of correlation is defined in terms of correlation coefficients. For the verification of the proposed scheme, we employ an independent analysis of Monte Carlo simulation with which statistical results can be obtained. Comparison is made between the proposed scheme and Monte Carlo simulation.

• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.1
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• pp.155-166
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• 2008

The quantitative bivariate spatial pattern analysis was applied for the water quality and nutrients data of Masan Bay, and for this analysis Pearson's r as aspatial correlation measurement, Moran's I as spatial association measurement and L index as integration of aspatial and spatial measurement methods were used. To understand the aspatial and spatial characteristics implicated in L index, Pearson's r as well as Moran's I were classified into 3 types respectively, and Pearson's r and Moran's I were combined with 9 types, and also quantile of L index value was used for each of those 9 types. Finally, these types were defined as 5 groups having not overlapped L index range. According to the application result of L index groups, bivariate water quality and nutrients showed no aspatial correlation regardless of spatial association in February and July, but they showed aspatial correlation having clustered spatial pattern in May and November. The result of this study providing the guideline for the interpretation of aspatial correlation and spatial association using L index is expected to be helpful for the marine environment pattern analysis using quantitative index for further study.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.774-777
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• 2005

Dengue Fever(DF) and Dengue haemorrhagic fever(DHF) has become a major international public health concern. Dengue Fever(DF) and Dengue haemorrhagic Fever (DHF) is also still the major health problem of Thailand, although many campaigns against it have been conducted throughout the country. GIS and Remotely Sensed data are used to evaluate the relationships between socio-spatial, environmental factors/indicators and the incidences of viral diseases. The aim of the study is to identify the spatial risk factors in Dengue and Dengue Haemorrhagic Fever in Sukhothai province, Thailand using statistical, spatial and GIS Modelling. Preliminary results demonstrated that physical factors derived from remotely sensed data could indicate variation in physical risk factors affecting DF and DHF. The present study emphasizes the potential of remotely sensed data and GIS in spatial factors affecting Dengue Risk Zone analysis. The relationship between land cover and the cases of incidence of DF and DHF by information value method revaluated that highest information value is obtained for Built-up area. A negative relationship was observed for the forest area. The relations between climate data and cases of incidence have shown high correlation with rainfall factors in rainy season but poor correlation with temperature and relative humidity. The present study explores the potential of remotely sensed data and GIS in spatial analysis of factors affecting Dengue epidemic, strong spatial analysis tools of GIS. The capabilities of GIS for analyst spatial factors influencing risk zone has made it possible to apply spatial statistical analysis in Disease risk zone.

• Journal of Communications and Networks
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• v.9 no.3
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• pp.274-281
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• 2007

In this paper, we present a hybrid multi-antenna technique that can minimize the outage probability by combining the diversity and beamforming techniques. The hybrid technique clusters the transmission antennas into multiple groups and exploit diversity among different groups and beamforming within each group. We analyze the performance of the resulting hybrid technique for an arbitrary correlation among the transmission antennas. Through the performance analysis, we derive a closed-form expression of the outage probability for the hybrid technique. This enables to optimize the antenna grouping for the given spatial correlation. We show through numerical results that the hybrid technique can balance the trade-offs between diversity and beamforming according to the spatial correlation and that the optimally designed hybrid technique yields a much lower outage probability than the diversity or beamforming technique does in partially correlated fading channels.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2010.09a
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• pp.99-101
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• 2010

• International Journal of High-Rise Buildings
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• v.12 no.1
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• pp.83-91
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• 2023

Under the dual pressure of population growth and land shortage, threedimensional development is the inevitable choice for cities in China. In such a scenario, a mixed-use complex has considerable potential in its realization and research. Based on space syntax and the three-dimensional visibility graph analysis, this paper describes the spatial and functional layout of the Shanghai Super Brand Mall and studies the relationship between spatial visibility and user behaviour through linear regression analysis and correlation analysis. This paper studies three different types of user behaviour, namely, path selection, staying selection, and store selection, and finds that spatial visibility and accessibility have different effects on user behaviour depending on the type and purpose of the activity. This paper reveals the influence of spatial and functional layout on user behaviour and puts forward the corresponding design strategy under the three-dimensional environment.

• Journal of Korean Society for Geospatial Information Science
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• v.23 no.1
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• pp.23-29
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• 2015

In this study, the spatial relevance between the regional housing price data and the spatial distribution of the location-based social media data is explored. The spatial analysis with rasterization was applied to this study, because the both data have a different form to analyze. The geo-tagged Twitter data had been collected for a month and the regional housing price index about sales and lease were used. The spatial range of both data includes Seoul and the some parts of the metropolitan area. 2,000m grid was constructed to consider the different spatial measure between two data, and they were combined into the constructed grids. The Hotspot Analysis was operated using the combined dataset to see the comparison of spatial distribution, and the bivariate spatial correlation coefficients between two data were measured for the quantitative analysis. The result of this study shows that Seocho-gu area is detected as a common hotspot of tweet and housing sales price index data. though the spatial relevance is not detected between tweet and housing lease price index data.

• Journal of Environmental Impact Assessment
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• v.33 no.4
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• pp.155-163
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• 2024

The purpose is to explore the meaning of the open space land use space pattern from the perspective of urban heat reduction using the land-use scenario. The employed methods are as follows: (1) to calculate the cooling capacity Index for each of five land use scenarios, using the InVEST Urban Cooling Model, (2) to calculate open space entropy & morphological spatial pattern for each land use scenario, using the Guidos Spatial Pattern Toolbox, and (3) to perform a Spearman rank correlation analysis between the InVEST and Guidos results. It is found that the rank correlation is moderate between the cooling capacity Index and the open space area ratio (rho=0.50). However, other relations are low. It is observed that only the total amount of open space is likely to have a meaning from the perspective of urban heat reduction, and that other open space location spatial patterns may not have much meaning from the perspective of urban thermal environment management.

• Journal of Korean Society for Atmospheric Environment
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• v.27 no.5
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• pp.545-557
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• 2011

The objective of this study was to estimate the trends of each pollutant using the air pollution monitoring networks data from January 2005 to December 2008 in Daegu area. Also, the spatial characteristics of each pollutant were determined using the Pearson correlation coefficients and COD (coefficients of divergence). In this study, the trends of hourly, monthly, seasonal, and total average concentrations of each pollutant for the 10 sites were analyzed. The Ihyeon site showed highest concentration for the $SO_2$, $NO_2$, and PM10}. In the case of $O_3$, the Jisan site showed highest concentration among the other sites. Also, industrial area presented highest concentration for the $SO_2$, CO, and PM10. On the other hand, $NO_2$ showed highest in commercial area. The IDW (inverse distance weighting) method was used to estimate characteristics of spatial distribution. The results provide identify spatial distribution for each pollutant. Also, the Pearson correlation coefficients and COD values provide spatial variability among the monitoring sites. The COD of each pollutant showed very low values for all of the sites pairs. On the other hand, the Pearson correlation coefficients showed high values for all of the sites pairs. Finally, analysis of spatial variability can be used to characterize the spatial uniformity and similarity of concentrations from each pollutant.