• Journal of the Korean Geographical Society
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• v.48 no.6
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• pp.978-993
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• 2013

It can be advantage as well as disadvantage to use the spatial weight matrix in a spatial regression model; it would benefit from explicitly quantifying spatial relationships between geographical units, but necessarily involve subjective judgment while specifying the matrix. We took Incheon City as a study area and investigated how the fitness of a spatial regression model changed by constructing various spatial weight matrices. In addition, we explored neighborhood segmentation in the study area and analyzed any influence of it on the model adequacy of two basic spatial regression models, i.e., spatial lagged and spatial error models. The results showed that it can help to improve the adequacy of models to specify the spatial weight matrix strictly, that is, interpreting the neighborhood as small as possible when estimating land price. It was also found that the spatial error model would be preferred in the area with serious spatial heterogeneity. In such area, we found that its spatial heterogeneity can be alleviated by delineating sub-neighborhoods, and as a result, the spatial lagged model would be preferred over the spatial error model.

• Communications for Statistical Applications and Methods
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• v.18 no.1
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• pp.79-87
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• 2011

A spatial time series model was used for analyzing the method of spatial time series (not the ARIMA model that is popular for analyzing spatial time series) by using chicken pox data which is a highly contagious disease and grid data due to ARIMA not reflecting the spatial processes. Time series model contains a weighting matrix, because that spatial time series model influences the time variation as well as the spatial location. The weighting matrix reflects that the more geographically contiguous region has the higher spatial dependence. It is hypothesized that the weighting matrix gives neighboring areas the same influence in the study of the spatial time series model. Therefore, we try to present the conclusion with a weighting matrix in a way that gives the same weight to existing neighboring areas in the study of the suitability of the STARMA model, spatial time series model and STBL model, in the comparative study of the predictive power for statistical inference, and the results. Furthermore, through the Kalman-Filter method we try to show the superiority of the Kalman-Filter method through a parameter assumption and the processes of prediction.

• Journal of the Korean Data and Information Science Society
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• v.26 no.3
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• pp.561-568
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• 2015

In this study we predict apartment prices per unit in Daegu-Gyeongbuk areas by spatial lag and spatial error models, both of which belong to so-called spatial regression model. A spatial weight matrix is constructed by k-nearest neighbours method and then the models for the apartment prices in March, 2012 are fitted using the weight matrix. The apartment prices in March, 2013 are predicted by the fitted spatial regression models and then performances of two spatial regression models are compared by RMSE (root mean squared error), RRMSE (root relative mean squared error), MAE (mean absolute error).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.10 no.2
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• pp.93-103
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• 1985

The digital signal processing technique by bandwidth compression has been grown up ragidly owing to integrated circuit developments. In this project, we have proposed the Lee Weighted Hadamard (LWH) transform which retains the main properties of Hadamard matirx. The LWH matrix was weighted in the center of the spatial domain. The human visual of the mid spatial are emphasized more than the low and high spatial frequencies. The fast algorithms of the LWH transform has been studied for hardware realization. The result of this project are availabel to airplane photograph, X-Ray, CATV and the artificial satellite of the digital image processing.

• Journal of Korea Multimedia Society
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• v.17 no.12
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• pp.1446-1452
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• 2014

Existing LDA uses the transform matrix that maximizes distance between classes. So we have to convert from an image to one-dimensional vector as training vector. However, in 2D-LDA, we can directly use two-dimensional image itself as training matrix, so that the classification performance can be enhanced about 20% comparing LDA, since the training matrix preserves the spatial information of two-dimensional image. However 2D-LDA uses same calculation schema for transformation matrix and therefore both LDA and 2D-LDA has the heteroscedastic problem which means that the class classification cannot obtain beneficial information of spatial distances of class clusters since LDA uses only data correlation-based covariance matrix of the training data without any reference to distances between classes. In this paper, we propose a new method to apply training matrix of 2D-LDA by using WPS-LDA idea that calculates the reciprocal of distance between classes and apply this weight to between class scatter matrix. The experimental result shows that the discriminating power of proposed 2D-LDA with weighted between class scatter has been improved up to 2% than original 2D-LDA. This method has good performance, especially when the distance between two classes is very close and the dimension of projection axis is low.

• Journal of Korea Planning Association
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• v.54 no.3
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• pp.63-74
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• 2019

Korean government has implemented policies to strengthen the competitiveness of small and medium sized cities. However, since it is often difficult to enhance the competitiveness through individual projects, many local governments in metropolitan areas are working together to pursue local growth. On the other hand, small and medium sized cities that are not included in metropolitan areas due to their spatial limitations have difficulties in implementing effective growth policies. Given this background, the purpose of this study is to identify the functional correlation based on urban interactions and develop functional econometric model for the economic growth of small and medium sized cities. This study uses spatial econometrics models and functional weight matrix to identify the effects of functional networks on small and medium sized cities. The results show the effect of functional networks on the growth of small and medium sized cities and provide policy implications for regional spatial planning that addresses effective management of small and medium sized cities.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.11a
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• pp.320-322
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• 2002

A new simple spatial scheme for base station with adaptive antenna in Code Division Multiplexing Access (CDMA) systems is presented. In the proposed scheme, by applying the new spatial structure lot the receiver, the system can debate the problem of which the number of users exceeds the number of adaptive antenna elements existing in the conventional spatial scheme. An adaptive algorithm based on the Mean Square Error (MSE) criterion is also derived to update the weight matrix of the proposed scheme. The results of the system capacity enhancement can be achieved by using the proposed approach. Numerical simulations are included fer illustration and verification.

• Korea Trade Review
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• v.47 no.4
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• pp.35-52
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• 2022

Air transport is at the core of global economic growth. There is a close relationship between the flow of regional elements and the growth of the regional economy. It is easy to misestimate the impact of airports on the regional economy without considering spatial spillover effects. This study attempted to establish an asymmetric economic geographical weight matrix by applying the Spatial Durbin Model with cargo volume and passenger numbers as indicators. The influence of spillover effects on the regional economy, including direct spillover effects and indirect spillover effects are studied. The results revealed that passenger numbers and cargo volume have significant positive spillover effects on the regional economy. The driving effect of the airport on the regional economy was considered from a wider space scope. This study contributes to the scientific evaluation of the aviation economy.

• Asian Journal of Atmospheric Environment
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• v.11 no.3
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• pp.194-201
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• 2017

This study investigates the factors that affect China's air pollution using city-level panel data and spatial econometric models. We address three air pollutants ($PM_{10}$, $SO_2$, and $NO_2$) present in 30 cities in China between 2004-2012 using global OLS and spatial models. To develop the spatial econometric analysis, we create a spatial weights matrix to define spatial patterns based on two neighborhood criteria - the queen contiguity and k nearest neighbors. The results show that the estimated coefficients are relatively consistent across different spatial weight criteria. The OLS models indicate that the effect of green spaces is statistically significant in decreasing the concentrations of all air pollutants. In the $PM_{10}$ and $SO_2$ analyses, the OLS models find that the number of buses and population density are also positively related to a reduction in the concentration of air pollutants. In addition, an increase in the temperature and the presence of secondary industries increase $SO_2$ and $NO_2$ concentrations, respectively. All spatial models capture a positive and significant effect of green spaces on reducing the concentration of each air pollutant. Our results suggest that green spaces in cities should receive priority consideration in local planning aimed at sustainable development. Furthermore, policymakers need to be able to discern the differences among pollutants when establishing environmental policies.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.4
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• pp.333-339
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• 2017

Transmission signal in wireless environment receives a signal in which a source signal, interference, and noise are mixed. The goal of this study is to estimate the desired signal from the received signal. In this paper, we have studied a method correctly estimating a target in spatial by modified beamformer method. The modified bemaformer uses an adaptive array antenna and perturbation matrix to obtain the optimal weight, and estimate the desired signal by radiating the beam in spatial. We estimate a desired signal of the target by improving resolution with the modified beamformer method which does not have complicated calculation amount. Through simulation, we compare and analyze the modified beamformer method and the MUSIC method with good resolution. In result of simulation, we showed that modified beamformer method has better resolution of 10degree than classical beamformer method and showed similar performance as the MUSIC method. The resolution of this paper was estimated to be about 5 degrees.