• Proceedings of the Korean Society of Computer Information Conference
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• 2014.01a
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• pp.149-151
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• 2014

주의(attention)를 어떻게 할당하는가는 정신물리학뿐만 아니라, 컴퓨터 시각과정을 모델링하는데 중요한 주제 중 하나이다. 기존 연구는 saliency와 같은 활성화 값에 의해서 주의탐사 순위가 결정된다. 본 논문에서는 주의탐사과정을 병렬처리를 통한 활성화 값 추출과정과 순차적 처리를 통한 공간적 전략과정으로 구분하였다. 단서패러다임에 기초한 계산모형을 이용하여, 실제 인간의 수행결과를 AUC와 Levenshtein 척도를 이용하여 비교하였다. Fixation point 비교에서는 인간과 활성화를 기반으로 한 계산모형의 수행은 높은 상관성을 가지고 있었다. 주의궤적 혹은 scanpath 분석에서는 활성화기반 전략보다는 공간적 전략 모형이 더 높은 유사성을 보였다. 이는 주의탐사과정이 병렬처리과정을 통해 얻어진 saliency에 의해서만 결정되는 것이 아니라, 목표물간의 근접성 등의 공간적 전략을 통해 순차적 (sequential) 경로가 생성됨을 의미한다.

• International Area Studies Review
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• v.12 no.3
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• pp.341-365
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• 2008

This paper investigates the properties and relative importance of Apparel Textile industry of Busan in terms of both the number of employees and the value-added, and then analyzes the relative technical efficiencies from the perspectives of space closeness such as consumption market, suppliers, living standards and clustering environments using the DEA model. The main outcomes are as follows. The Apparel Textile industry is still a key industry in Busan with relatively high intensity and high LQ (greater than one) in spite of the recent decrease between 2000 and 2005 both in the number of employees and the value-added. Those firms with consumption market showed higher efficiency in all kinds of efficiencies than the firms without the market, and further relatively higher efficiency than the firms with suppliers. In addition, the firms located in the higher living standards also showed higher values of efficiency compared with the firms in lower living standards. The policy implication from the results is that the strategic and selective investment should be made according to the relative efficiency and thus the traditional industry should be transformed to the high value added one with additional investment to utilize the scale efficiency.

• Proceedings of the Korean Information Science Society Conference
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• 1999.10a
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• pp.317-319
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• 1999

공간 데이터베이스에서 공간 데이터간의 근접성을 알아보아야 할 필요가 많이 발생한다. 이를 위해, 본 연구에서는 방향 관계와 거리 관계가 혼합된 형태의 질의에서 공간적으로 가까운 객체를 순서적으로 추출해내는 방법을 제안한다. 점진적 거리 조인 알고리즘을 근간으로 섹터 기반 모델을 적용하여 객체들을 순서적으로 추출할 수 있도록 한다. 섹터의 분류와 섹터들간 정렬 순서에 따라 추출된 값을 필요에 따라 제한조건의 조절이 가능하다는 장점이 있다. 또한, 점진적 거리조인 알고리즘에 있어서의 데이터 크기에 따른 성능 저하 문제도 어느 정도 해결할 수 있음을 기술하고 있다.

• Journal of the Korean association of regional geographers
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• v.8 no.3
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• pp.396-411
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• 2002

This paper aims to explore organisational change and learning involving spatial processes and outcomes. In particular, it focuses on the context specific nature of corporate learning and organisational change that can be found in the case of a large Korean firm facing radical economic change. Drawing on the case study of a large Korean firm, the Samsung Electronics Company, three main claims can be followed. First, territorial sources of learning influence the way in which the firm makes use of space/place. Second, corporate learning practices, however, are not based merely on specific localised sources or geographical proximity but on bringing together the local and the global sources by harnessing the properties of relational proximities. It reveals that firms are concerned less on specialising specific local knowledge than promoting organisational knowledge and competences by integrating a variety of knowledge distributed in and out of the boundaries of the firm. Finally, to learn and innovate in a continual basis, firms would attempt to combine codified knowledge with tacit knowledge.

• The Korean Journal of Applied Statistics
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• v.29 no.5
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• pp.835-847
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• 2016

To analyze lattice or areal data, a conditionally autoregressive (CAR) model has been widely used in the eld of spatial analysis. The spatial neighborhoods within CAR model are generally formed using only inter-distance or boundaries between regions. Kyung and Ghosh (2010) proposed a new class of models to accommodate spatial variations that may depend on directions. The proposed model, a directional conditionally autoregressive (DCAR) model, generalized the usual CAR model by accounting for spatial anisotropy. Properties of maximum likelihood estimators of a Gaussian DCAR are discussed. The method is illustrated using a data set of median property prices across Greater Glasgow, Scotland, in 2008.

• Journal of the Korean Data and Information Science Society
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• v.27 no.5
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• pp.1133-1146
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• 2016

Counts or averages over arbitrary regions are often analyzed using conditionally autoregressive (CAR) models. The spatial neighborhoods within CAR model are generally formed using only the inter-distance or boundaries between the sub-regions. Kyung and Ghosh (2009) proposed a new class of models to accommodate spatial variations that may depend on directions, using different weights given to neighbors in different directions. The proposed model, directional conditionally autoregressive (DCAR) model, generalized the usual CAR model by accounting for spatial anisotropy. Bayesian inference method is discussed based on efficient Markov chain Monte Carlo (MCMC) sampling of the posterior distributions of the parameters. The method is illustrated using a data set of median property prices across Greater Glasgow, Scotland, in 2008.

• Journal of Digital Contents Society
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• v.16 no.2
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• pp.257-262
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• 2015

Recently, the interests of mobile GIS technology is increasing with the spread of wireless network, the improvement of mobile device's performances, and the growth of demands about mobile services. Providing services in a wireless environment with existing wired-based GIS solutions have many limitations such as slow communication, processing rates and screen size. In this paper, we propose a cache algorithm on client side to solve the above problems. The proposed algorithm demonstrates the performance improvement over known studies by utilizing unit time and spatial proximity. In addition, this paper conducts a performance evaluation to measure the improvement in algorithm efficiency and analyzes the results of the performance evaluation. When spatial data queries are conducted, according to our performance evaluation, hit rate has been improved over the existing algorithms.

• Proceedings of the Korean Information Science Society Conference
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• 2000.10c
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• pp.281-283
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• 2000

분산 가상 환경(DVE)의 사용자 수가 증대됨에 따라, 고려해야 할 사항 중 가장 중요한 것들 중 하나는 상호작용의 성능을 위한 확장성에 있다. DVE의 확장성을 지원하기 위한 방법들 중 하나는 사용자 인지도 관리 기법이다. 기존의 인지도 관리 기법은 사용자의 인지도를 일정한 공간으로 제한을 함으로써 사용자가 받는 메시지의 수를 줄이는 방법이다. 하지만 많은 사용자들이 근접한 곳에 운집한 경우, 사용자는 그 근접한 공간에서 발생하는 모든 메시지를 받아야 한다. 이것은 사용자들에게 통신에 따른 많은 부하가 걸리게 되며 따라서 시스템은 확장성이 떨어지게 된다. 본 연구에서는 각 사용자의 인지도 영역에 사용자가 관심 있는 사물의 타입을 표현하고 같은 관심을 가지고 있는 사용자들끼리 그룹을 생성하여 사용자의 관심도에 따른 선택적인 메시지를 받게 한다. 이를 통하여 각 사용자는 자신과 근접한 공간에 있는 모든 사용자로부터 생성되는 모든 메시지를 받지 않아도 된다. 본 연구를 통하여 확장성 있는 방법으로 사용자간의 상호 작용을 지원할 수 있다.

• Journal of the Economic Geographical Society of Korea
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• v.11 no.3
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• pp.334-349
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• 2008

In this study, the network formation process of personal actors in industries for the elderly was analyzed. This process is applied to the knowledge creation model of the SECI (Nonaka-Takeuchi learning cycle), that is socialization, externalization, combination, internalization. There are some kinds of opportunities to interact in these industries in the forms of field survey teams to overseas, some seminars and symposiums, many kinds of meetings, education and training programs, trade fairs and on-line forums. These palces(ba) - originating ba, interacting ba, cyber ba, exercising ba - played great roles in the formation of personal actor networks. Personal actors had opportunities to interconnect with distant actors through those places(ba). In the spatial perspective, personal actors could make face-to-face contact and build trust through temporary geographical proximity or temporary clusters with the help of personal mobility. Relations in the virtual spaces such as the Internet community did much toward building personal networks.

• Journal of the Korean association of regional geographers
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• v.12 no.4
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• pp.508-521
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• 2006

The results of environmental equity analysis vary dramatically depending on different methods used. The information and data available to the researcher are also often uncertain and imprecise in empirical studies. A sensitivity analysis approach was used too handle uncertainties and methodological inconsistencies in environmental equity analysis. This paper explores the sensitivity of environmental equity analysis to two spatial measures such as proximity and scale. Two experiments were implemented to evaluate the effects of two spatial measures on the environmental equity analysis using a combination of control and experimental factors. Fulton County, Georgia was selected as a case study area for these experiments. Two major data sets including demographic characteristics and toxic release inventory (TRI) database for the study area in 1990 were integrated into a GIS environment. Two statistical analyses such as independent samples t-test and coefficient of variation were performed to determine the environmental equity in the study area and to compare the relative variability in the socioeconomic characteristics of populations over different spatial measures. The findings from two experiments indicate that the outcomes of environmental equity analysis are slightly sensitive to the buffer distance used to determine the impact zones of TRI facilities, but not to the geographic scale used in the analysis. The findings also suggest that the consequences of these choices can alter spatially and statistically the results in environmental equity analysis.