• Journal of the Korean Regional Science Association
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• v.35 no.2
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• pp.73-86
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• 2019

The purpose of this paper is to empirically analyze the effects of related and unrelated varieties of industry and occupation on regional economic growth. Recent studies dealing with the mechanism of economic growth argue that occupation as well as industry act as the driving force of regional economic growth by inducing knowledge externalities. Therefore, this study comprehensively analyzed the effects of occupational diversity along with industrial diversity. For the empirical analysis, we set the regional labor market areas as the spatial units of analysis. Dependent variables include regional per capita GRDP and employment growth between 2010 and 2015, and related and unrelated variety of industry and occupations measured based on the entropy approach are used as key explanatory variables. Our empirical results show that the related variety of industry has a positive effect on per capita GRDP in the region, and the related variety of occupation has a positive effect on regional employment growth. On the other hand, the unrelated variety of industries shows a negative correlation with regional employment growth. Based on the empirical results, this paper provides regional policy implications for strengthening economic vitality by dividing the diversity of industry and occupation into related and unrelated varieties and analyzing how they affect regional economic growth.

• Journal of Yeungnam Medical Science
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• v.22 no.2
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• pp.199-210
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• 2005

Background: The role of obesity in prostate cancer etiology remains controversial. The aim of this study was to evaluate the relationship between obesity and prostate cancer risk. Materials and methods: Between January 2000 and June 2005, 286 patients suspected of having prostate cancer underwent prostate biopsy. The clinical records of the 286 study patients were retrospectively reviewed with regard to age, Body Mass Index (BMI), serum PSA, TRUS, and prostate biopsy results. They were stratified by BMI into three groups according to the cutoffs recommended for Asian populations: normal, BMI less than 23 $kg/m^2$; overweight, BMI 23 to 25 $kg/m^2$; and obese, BMI greater than 25 $kg/m^2$. Results: As for BMIs, 132 (46.2%) were normal, 95 (33.2%) overweight and 59 (20.6%) were obese. A total of 99 (34.6%) patients were diagnosed as having prostate cancer. In multivariate logistic regression analyses, no significant association was observed between BMI and prostate cancer detection. Conclusion: We initially hypothesized that obesity may be biologically associated with increased prostate cancer development. However, our study did not show a significant association between BMI and prostate cancer.

• Journal of Technology Innovation
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• v.30 no.4
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• pp.1-28
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• 2022

Arguably many studies point out that regional innovation capabilities are accepted as a major source of growth for the sustainable regional economy. Recently, a smart specialisation strategy that should reflect regional characteristics in the policy implementation process of the regional innovation system has been proposed, but empirical studies have only presented limited results. This study attempts to overcome limitations by approaching smart specialisation as a supplementary strategy for existing regional innovation research. To this end, smart specialisation was not an alternative strategy for the regional innovation system, but rather the institutional elements of regional innovation capabilities, and the relationship between regional innovation capabilities and the local economy was analyzed to identify the impact of smart specialisation on the local economy. A study was conducted through a panel model consisting of 16 cities and provinces in Korea and 10 years from 2009-2018, and the FGLS model was finally used through the process of searching for an appropriate panel model. As a result of the study, smart specialisation consisting of industry related variety and non-related variety had a positive effect on the local economy. In addition, other regional innovation capabilities measured by dividing them into base and facilitating factors also had a positive effect on the local economy, reaffirming the results of positive research between existing regional innovation and the local economy. This study is meaningful in that smart specialisation lacking in domestic research was viewed as an institutional element of regional innovation capabilities, and it was measured through regional industry-related variety and non-related variety.

• Journal of the Economic Geographical Society of Korea
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• v.25 no.3
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• pp.357-379
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• 2022

This study diagnoses the industrial varieties and innovation capacity of the Korean regional economy and discusses how the priority for autonomous regional development can be set. Since the late 1990s, regional development policies in Korea have been attempted from various angles to reduce the economic gap between the metropolitan area and non-metropolitan areas, but the establishment of a development strategy in consideration of regional industrial characteristics and innovation capabilities has been insufficient. With the advancement and diversification of technologies and industries, regions must seek strategic diversification to prepare for economic shocks, away from strategies that specialize in specific industries. In this study, industrial varieties in regional basis is characterized using unrelated and related varieties. Variety indices show different patterns between the metropolitan area and non-metropolitan areas and between manufacturing and service sectors, which raises the need to consider industrial characteristics in regional development. Lastly, using the variety index and the innovation capacity index as two dimensions, the regional economic status at the municipal level is categorized into four types, and proper regional development policy priorities are suggested for each type.

• Journal of the Korean Data and Information Science Society
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• v.22 no.6
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• pp.1113-1121
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• 2011

Recently, a variety of data mining techniques has been applied in various fields like healthcare, insurance, and internet shopping mall. Association rule mining is a popular and well researched method for discovering interesting relations among large set of data items. Association rule mining is the method to quantify the relationship between each set of items in very huge database based on the association thresholds. There are three primary quality measures for association rules; support and confidence and lift. In this paper we consider some similarity measures with negative co-occurrence frequencies which is widely used in cluster analysis or multi-dimensional analysis as association thresholds. The comparative studies with support, confidence and some similarity measures are shown by numerical example.

• Journal of Korean Traditional Oncology
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• v.15 no.1
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• pp.119-128
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• 2010

항암치료는 현재 암환자의 주요한 치료임에도 불구하고 항암제내성과 같은 문제점을 가지고 있다. 약물내성은 다양한 기전에 의해 발생하는데 수송단백질의 과발현, 비독성화발현, 손상유전자의 복구, 세포사멸신호의 변화, STAT-3와 NF-${\kappa}B$의 발현 등이 포함된다. 암세포는 저산소환경에서 발생하며 일반세포에 비해 무산소해당에 상대적 의존도가 높고 이는 암세포의 성장과 전이를 촉진하는 인자가 된다. 항암제가 효과를 내기 위해서는 산소가 필요한데 저산소환경은 이를 방해하며 또한 유전자의 불안정화로 인해 약물내성이 유도된다. NF-${\kappa}B$는 주요 전사인자 중 하나로서 각종 염증과 암에서 지속적으로 활성화되며 암세포의 변화, 증식, 침윤, 전이에 관여한다. 환경적 스트레스 등과 대부분의 항암약제들이 NF-${\kappa}B$를 활성화시키며 임상적으로도 암환자의 생존과 연관된 중요한 예후인자이다. NF-${\kappa}B$의 발현은 항암제로 인한 암세포의 자멸을 회피하게 만들고 수송단백질을 활성화시켜 항암제내성을 유도한다. 강황, 적포도, 고추, 건칠 등 다양한 천연물에서 NF-${\kappa}B$를 억제시키는 효능이 발견되었으며 이는 항암제내성을 억제시키고 항암제의 효과를 증대시킨다. 저산소환경의 개선과 NF-${\kappa}B$의 억제는 상호연관성을 가지고 있으며 항암제내성의 개선뿐만 아니라 암치료제 개발의 새로운 연구목표가 될 수 있다.

• Proceedings of the Korea Information Processing Society Conference
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• 2004.05a
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• pp.43-46
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• 2004

웹상에서 제공되는 영상정보 자원의 양이 급증하고 이용자들의 문화적인 수요가 높아진 것에 비해 영상정보를 포괄적으로 기술할 수 있는 체계적인 서지기술은 부족한 실정이다. 기존의 영상정보 기술 메타데이터 요소로는 이용자가 탐색하고자 하는 정보자원을 적절하게 검색하거나 혹은 검색된 자원 중에서 서로 연관성이 있는 정보를 그룹화하여 보여주는 것이 불가능하다[1]. 따라서 영상정보 자원이 지니는 다양한 수준과 다양한 측면의 특성을 표현해 내기 위해 국내에서 제안된 영상정보 분야의 새로운 메타데이터 표준이 제시되었다. 본 논문에서는 제안된 영상정보 분야의 메타데이터를 기반으로 하는 영화 Context 검색 엔진을 개발하였고, 이에 따라 추후에 적절한 정보자원의 검색과 연관성 있는 정보의 그룹화로의 확장을 가능하게 할 것이다.

• Proceedings of the Korean Information Science Society Conference
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• 2004.04b
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• pp.208-210
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• 2004

오늘날 인터넷상에서 존재하는 않은 정보들은 다양한 사용자의 개인 특성에 안게 새로운 정보의 지식으로 제공되어지기를 원한다. 기존의 연구는 단일 학술 기법을 통해 정보를 추출했으나 사용자에게 보다 의미 있는 정보를 제공하기 위해 다중 전략 학습 기법인 PMSL(Personalized Multi-Strategy Learning) 모듈 시스템을 제안하고자 한다. PMSL 모듈은 인터넷의 정보를 여과하여 필터링하고, 사용자 개인화의 키워드를 중심으로 연관된 객체를 추출한다. 이때 연관된 객체 추출시 대용량 데이터에서 시간적, 공간적면에서 효율적인 연관 탐색 기법인 Fp-Tree와 Fp-Growth 알고리즘을 적용시킴으로 결과의 효율성을 높이고자 하였으며, 연관규칙의 문제점을 보완하기 위해 가중치 기법인 TF＊IDF 학습 기법을 적용시켰다. PMSL 모듈을 실행한 결과 기존 학습 기법에 비해 보다 더 의미 있는 연관 지식을 추출하게 되었다.

• The Korean Journal of Applied Statistics
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• v.30 no.4
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• pp.567-578
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• 2017

Grouped multivariate data can be tested for differences between two or more groups using multivariate analysis of variance (MANOVA). However, this method cannot be used if several assumptions of MANOVA are violated. In this case, multidimensional scaling (MDS) and analysis of distance (AOD) can be applied to grouped dissimilarities based on the various distances. A permutation test is a non-parametric method that can also be used to test differences between groups. MDS is used to calculate the coordinates of observations from dissimilarities and AOD is useful for finding group structure using the coordinates. In particular, AOD is mathematically associated with MANOVA if using the Euclidean distance when computing dissimilarities. In this paper, we study the between and within group structure by applying MDS and AOD to the grouped dissimilarities. In addition, we propose a new test statistic using the group structure for the permutation test. Finally, we investigate the relationship between AOD and MANOVA from dissimilarities based on the Euclidean distance.

• Journal of the Korea Society of Computer and Information
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• v.11 no.1 s.39
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• pp.27-34
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• 2006

Recently, the study about the technology which effectively manage spatial information is actively conducted. For the effective knowledge inquiry, various extended data mining methods are applied in spatial data mining. However, former spatial association rule system appears the problem that does not reflect various non-spatial property along the inquiries because it searches the rule from the calculation among predicates. To resolve the problem, present study suggests the system that extends the inquiries using in spatial database, searches the association rule among non-spatial object property after setting the data based on space information. Especially, the model which is applicable to geographical information system is embodied. Embodied system with this method enables to search more useful spatial association rule in real life since it shows high migration property with extended spatial database and considers spatial property and various non-spatial property.