• 한국지역지리학회지
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• 제13권3호
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• pp.235-253
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• 2007

본 연구에서는 우리나라 7대 대도시를 대상으로 지속가능발전성을 비교 평가하였다. 국가지속가능발전지표 목록 등을 참고하여 3개 부문, 14개 지표군, 42개 하위지표를 선정하여 정량적 지표체계를 구축하였다. 대도시간 비교분석을 위해 지표별로 7대 대도시의 평균값을 기준으로 지속가능성을 상대평가 하였으며, 이 때 필요시 역기능지표를 순기능 지표화 하여 모든 지표를 동일한 스케일로 비교 가능하도록 하였다. 그 결과 서울이나 울산과 같이 특정산업이 집중한 도시에서 경제적 지속가능성이 높았으나 환경적 지속가능성은 낮았고, 지역경제가 낙후된 광주에서 환경적 지속가능성이 높은 것으로 나타났다. 부산, 대구, 인천은 전반적으로 지속가능성이 낮은 반면, 대전은 3개 부문 모두에서 조화롭게 지속가능성이 높아 대도시 중 통합적 지속가능성이 제일 높은 것으로 나타났다.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2014년도 추계학술발표대회
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• pp.928-931
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• 2014

The detection of human behavior from social media revolutionized health, business, criminal and political prediction. Significance of it, in incentive transformation of public opinion had already proven for developed countries in improving democratic process of elections. In $3^{rd}$ World countries, voters poll votes for personal interests being unaware of party manifesto or national interest. These issues can be addressed by social media, resulting as ongoing process of improvement for presently adopted electoral procedures. On the optimistic side, people of such countries applied social media to garner support and campaign for political parties in General Elections. Political leaders, parties, and people empowered themselves with social media, in disseminating party's agenda and advocacy of party's ideology on social media without much campaigning cost. To study effectiveness of social media inferred from individual's political behavior, large scale analysis, sentiment detection & tweet classification was done in order to classify, predict and forecast election results. The experimental results depicts that social media content can be used as an effective indicator for capturing political behaviors of different parties positive, negative and neutral behavior of the party followers as well as party campaign impact can be predicted from the analysis.

• 대한간호학회지
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• 제21권2호
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• pp.195-203
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• 1991

Correlations among body weight and sociodemographic factors, including life - style were tested as social determinants of health in a sample of 5,201 adults in Korea. The aim of this study was to determine the extent to which sociodemographic variables and life-style associated health behaviors explain body weight distribution. A second aim was to explain the relation of body weight and health status to stress the importance of body weight as an early risk indicator of health status. The canonical correlation between the weight distribution(underweight and overweight) and the independent variables was 0.29, 17% of the total variance was explained. Perceived health level represented the highest contribution(canonical coefficient 0.82) to body weight. Sociodemographic factors such as sex, economic status, and life-style factors such as smoking, exercise, regular meais and sleep showed comparatively high contributions to body weight. The relevance of body weight for health status including the rate of chronic disease and the rate of medical utilization was significant. Especially, underweight was clarified as being mere important than overweight to morbidity level and medical utilization. These findings suggest that perceived body weight is an important indicator of health status and is thus a valuable variable to be considered for nursing intervention and health education related to the promotion of health.

• 국제학술발표논문집
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• The 3th International Conference on Construction Engineering and Project Management
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• pp.1324-1327
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• 2009

Social infrastructure is the basis of public welfare and should be recognized and managed as important assets. Bridge is one of the most important infrastructures to be managed systematically because the impact of the failure is critical. It is essential to monitor the performance of bridges in order to manage them as an asset. But current analytical methods such as predictive modeling and structural analysis are very complicated and difficult to use in practice. To apply these methods, structural and material condition data collection should be performed in each element of bridge. But it is difficult to collect these detailed data in large numbers and various kinds of bridges. Therefore, it is necessary to collect data of major measurement items and predict the life of bridges roughly with advanced information technologies. When certain measurement items reach predefined limits in the monitoring bridges, precise performance measurement will be done by detailed site measurement. This paper describes the selection of major measurement items that can represent the tendency of bridge life and introduces automated bridge data collection test-bed using wireless sensor network technology. The following will be major parts of this paper: 1) Examining the features of conventional bridge management system and data collection method 2) Mileage concept as a bridge life indicator and measuring method of the indicator 3) Test-bed of automated and real-time based bridge life indicator monitoring system using wireless sensor network

• 해양환경안전학회지
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• 제26권3호
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• pp.227-232
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• 2020

This paper develops a risk index based on an indicator of risk assessment in terms of coastal activity location and accident type. The risk index is derived from a formula which adds the consequence of failure to a vulnerability value, then subtracts the mitigation value. Specifically, the consequence of failure is the number of casualties in coastal activity locations. An indicator of vulnerability refers to coastal environment elements and social elements. A pointer of mitigation includes managerial and organizational elements that indicate the capabilities of coastal activities. A risk rating of coastal activity location is found from a risk matrix consisting of the accident location and type. The purpose of this study is to prevent accidents at coastal activity locations by allowing the Coastal police guard to monitor effectively and inform visitors of potential risks.

• 한국농공학회:학술대회논문집
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• 한국농공학회 2002년도 학술발표회 발표논문집
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• pp.33-36
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• 2002

The purpose of this study is to develope a indicator for agricultural water use. Agricultural water is challenged by the increase of water use in the sectors of urbanization and industry and social pressure to use water in sustainable and environmentally sound way. The development of agricultural environment indicators is divided into 13 sectors, among which agricultural water use indicators include amount and intensity of agricultural water use, efficiency of agricultural water use, shortage or surplus of water use, water stress, etc.. Agricultural water use indicators provide basic data for sustainable and environmentally sound agricultural development, and also help policy decision makers to solve water shortage problems through water policy and water management measures by making the most of the total available water resources.

• 한국데이터정보과학회:학술대회논문집
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• 한국데이터정보과학회 2005년도 추계학술대회
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• pp.59-69
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• 2005

Data mining technique is used to find hidden knowledge by massive data, unexpectedly pattern, relation to new rule. The methods of data mining are decision tree, association rules, clustering, neural network and so on. Clustering is the process of grouping the data into clusters so that objects within a cluster have high similarity in comparison to one another. It has been widely used in many applications, such that pattern analysis or recognition, data analysis, image processing, market research on off-line or on-line and so on. We analyze Gyeongnam social indicator survey data by 2001 using twostep clustering technique for environment information. The twostep clustering is classified as a partitional clustering method. We can apply these twostep clustering outputs to environmental preservation and improvement.

• 환경영향평가
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• 제15권1호
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• pp.13-22
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• 2006

The Korean government adopted the integrated stream water management policy recently with growing perception that natural disasters and pollution in Korea have been due not only to such human factors as urbanization and industrialization, but also to the policy of functionally separated management of irrigation, flood control and ecological management. Contrary to its good intention, research result shows that it is not realistic to expect that this new integrated policy in Korea will work well. In order to be an effective policy and program evaluation, this paper suggests that evaluation indicator on related programs and projects should be made through bottom-up process. For example, environmental benefit should be taken into account rather than just economic benefit, and cultural and social characteristics in the project region should be also considered seriously.

• Journal of the Korean Data and Information Science Society
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• 제17권1호
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• pp.1-11
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• 2006

Data mining technique is used to find hidden knowledge by massive data, unexpectedly pattern, relation to new rule. The methods of data mining are decision tree, association rules, clustering, neural network and so on. Clustering is the process of grouping the data into clusters so that objects within a cluster have high similarity in comparison to one another. It has been widely used in many applications, such that pattern analysis or recognition, data analysis, image processing, market research on off-line or on-line and so on. We analyze Gyeongnam social indicator survey data by 2001 using twostep clustering technique for environment information. The twostep clustering is classified as a partitional clustering method. We can apply these twostep clustering outputs to environmental preservation and improvement.

• Journal of Community Nutrition
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• 제8권1호
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• pp.38-43
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• 2006

There were numerous evidences that subjective health evaluation was a powerful indicator for morbidity and mortality in many countries. Since self-rated health (SRH) was a reasonable health measure, identifying predictors for SRH would be beneficial for assessment of overall health, monitoring health status, and development of health promotion programs. Health risks, health behavior, socioeconomic characteristics and social capital were potential indicators for SRH. We examined association. between SRH and indicators such as health risk factors, subjective living condition, income, education level and dietary variety score. Total 4,262 subjects, aged between 20 and 69 years old, were selected from KNHANES 2001; those who completed health examination, nutrition survey, and provided their socioeconomic information. Results of logistic regression showed that it was likely to have better SRH for those who were younger, male and have higher education, higher income, better living condition, no metabolic syndrome and higher dietary variety.