• Journal of dental hygiene science
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• v.12 no.3
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• pp.197-207
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• 2012

The purpose of this study was to examine the impact of the oral health status and health care of elderly people on their self-rated health(SRH). The subjects on this study were 479 senior citizens who were at the age of 65 and up and resided in the city of Busan. They got a dental checkup, and a survey was conducted by having an one-on-one interview. After the collected data were analyzed, the following findings were given: The senior citizens were diagnosed with a mean of 1.43 systemic diseases, and hypertension(51.8%) was the most prevalent disease among them, followed by diabetes(25.1%), arthritis(41.8%), oral diseases(75.6%), stroke(9.0%) and heart diseases(15.9%). Their self-rated health was better when they were male, when they were aged between 65 and 69, when there was someone with whom they lived, when they were better educated and when they owned their own houses. But their self-rated health was poorer when they felt more oral symptoms, when they had more missing teeth and when they needed both of maxillary and mandibular dentures. Their self-rated health was more positively affected when they were better educated($\beta$=0.894), when they owned their own houses($\beta$=4.220), when they got a dental checkup on a regular basis($\beta$=2.997) and when the rate of their functional tooth was larger($\beta$=0.081). And that was more negatively influenced when they had a denture($\beta$=-1.110), when they had more oral symptoms($\beta$=-1.590) and when they had more systemic diseases($\beta$=3.363). There is a close relationship between the oral health and self-rated health of elderly people. Therefore how to promote their oral health should carefully be considered.

• Journal of the Korean association of regional geographers
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• v.4 no.1
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• pp.135-155
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• 1998

The purpose of this study is to evaluate the environmental sustainability of new town development in metropolitan area, Korea and derive some policy implications for sustainable urban development. The case study area selected for empirical research is Jisan Bummul new town in Taegu. In the part of theoretical review, it is considered that the urban form suitable to sustainable development of a metropolis is the type of decentralized concentration. For the decentralized concentration form, we suggest developing suburban centers with self-sufficiency within a metropolis. This strategy is to develop a few suburban centers on the outskirts of a metropolis to decentralize urban activities of the central city, and to conserve the remaining. The empirical study evaluating the environmental sustainability of new town development shows that Jisan Bummul new town generally have low environmental sustain ability, because of the policy of mass housing provisions without consideration on overall natural conditions and environmental capacity of the area. To develop a new town. we must first select the locational site with minimum possibility of the destruction of natural environment, and then it is necessary to develop new towns into compact form to minimize the destruction of the natural environment. Second, a new town should be developed into a large scale to obtain urban self-sufficiency. Third plans must be established for decentralising both industrial and residential functions of a metropolis simultaneously. As more detailed policy implications, it is suggested that the policies are needed to improve the quality of educational conditions and enhance the level of services of public transport facilities. It is also necessary to establish the comprehensive development plan that takes the adjacent developmental area into consideration, and to prepare various action plans to bring up the facilities of self-sufficiency. In the selection of the location of a new town, the adaptability of public transportation planning must be emphasized. But, to take a program for short-term mass housing provisions must be restricted.

• Journal of the Korean Institute of Landscape Architecture
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• v.43 no.2
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• pp.1-12
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• 2015

This study explores urban gardening and garden culture in residential area as an everydayness that has been overlooked during the modern period urbanization and investigates the meaning and value of urban gardening from the perspective of urban formations and growth in spontaneous urban residential area, Haebangchon. The result identified that urban gardening as a meaning of contemporary culture is a new clue to improving the urban physical environment and changing the lives and community network of residents. Haebangchon is one of the few remaining spontaneous habitations in Seoul, and was created as a temporary unlicensed shantytown in 1940s. It became the representative habitation for common people in downtown Seoul through the revitalization of the 60s and the local reform through self-sustaining redevelopment projects during the 70s through the 90s. This area still contains the image of times during the 50s to the 60s, the 70s to the 80s and present, with the percentage of long-term stay residents high. Within this context, the site is divided into third quarters, and the research undertaken by observation and investigation to determine characteristics of urban gardening as an everydayness. It can be said that urban gardening and garden culture in Haebangchon is a unique location culture that has accumulated in the crevices of the physical condition and culture of life. These places are an expression of resident's desires that seeking out nature and gardening as revealed in densely-populated areas and the grounds of practical acting and participating in care and cultivation. It forms a unique, indigenous local landscape as an accumulation of everyday life of residents. Urban gardens in detached home has retained the original function of the dwelling and the garden, or 'madang', and takes on the characteristic of public space through the sharing of a public nature as well as semi-private spatial characteristic. Also, urban gardens including small kitchen garden and flowerpots that appear in the narrow streets provide pleasure as a part of nature that blossoms in narrow alley and functions as a public garden for exchanging with neighbors by sharing produce. This paper provides the concept of redefining the relationship between the private-public area that occurs between outside spaces that are cut off in a modern city.

• Journal of Wetlands Research
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• v.24 no.3
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• pp.204-212
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• 2022

The LID technique began to be applied in Korea after 2009, and LID facilities are installed and operated for rainwater management in business districts such as the Ministry of Environment, the Ministry of Land, Infrastructure and Transport, and LH Corporation, public institutions, commercial land, housing, parks, and schools. However, looking at domestic cases, the application cases and operation periods are insufficient compared to those outside the country, so appropriate design standards and measures for operation and maintenance are insufficient. In particular, LID facilities constructed using LID techniques need to maintain the environment inside LID facilities because hydrological and environmental effects are expressed by material circulation and energy flow. The LID facility is designed with the treatment capacity planned for the water circulation target, and the proper maintenance, vegetation, and soil conditions are periodically identified, and the efficiency is maintained as much as possible. In other words, the soil created in LID is a very important design element because LID facilities are expected to have effects such as water pollution reduction, flood reduction, water resource acquisition, and temperature reduction while increasing water storage and penetration capacity through water circulation construction. In order to maintain and manage the functions of LID facilities accurately, the current state of the facilities and the cycle of replacement and maintenance should be accurately known through various quantitative data such as soil contamination, snow removal effects, and vegetation criteria. This study was conducted to investigate the current status of LID facilities installed in Korea from 2009 to 2020, and analyze soil changes through the continuity and current status of LID facilities applied over the past 10 years after collecting soil samples from the soil layer. Through analysis of Saturn, organic matter, hardness, water contents, pH, electrical conductivity, and salt, some vegetation-type LID facilities more than 5 to 7 years after construction showed results corresponding to the lower grade of landscape design. Facilities below the lower level can be recognized as a point of time when maintenance is necessary in a state that may cause problems in soil permeability and vegetation growth. Accordingly, it was found that LID facilities should be managed through soil replacement and replacement.

• Korean Journal of Construction Engineering and Management
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• v.25 no.2
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• pp.23-35
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• 2024

This study analyzed the correlation between each of the 12 influencing factors in FAR 16.04 and the decision-making process for construction contract types, using data from a total of 2,406 DoD Construction Acquisitions spanning from 2008 to 2022. The study considered 12 independent variables, grouped into 4 Characteristics with 3 factors each. Meanwhile, all other contract types were categorized into two types: Firm-Fixed-Price (FFP) and Cost-Reimbursement Contract (CRC), which served as the dependent variables. The findings revealed that FFP contracts significantly dominated in terms of acquisition volume. In line with prevailing beliefs, logistic data analysis and Analytical Hierarchy Process (AHP) analysis of Relative Weights from Experts' Survey demonstrated that independent variables like Uncertainty of the Scope of Work and Complexity found out to be increasing the likelihood of selecting CRC. The number of contractors in the market does indeed influence the possibilities of contract decision-making between CRC and FFP. Meanwhile, the p-values of the top 3 influencing factors on CRC from the AHP analysis-namely, Appropriateness of CAS, Project Urgency, and Cost Analysis-exceeded 0.05 in the binominal regression results, rendering it inconclusive whether they significantly influenced the construction contract type decision, particularly with respect to payment methods. This outcome partly results from the fact that a majority of respondents possessed specific experiences related to the USFK relocation project. Furthermore, influencing factors in construction projects behave differently than common beliefs suggest. As a result, it is imperative to consider the 12 influencing factors categorized into 4 Characteristics areas before establishing acquisition strategies for targeted construction projects.

• Journal of Environmental Impact Assessment
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• v.33 no.4
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• pp.143-154
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• 2024

Heat waves caused by climate change are rapidly increasing health damage to vulnerable groups, and to prevent this, the national, regional, and local governments are establishing climate crisis adaptation policy. A representative climate crisis adaptation policy to reduce heat wave damage is to expand the number of cooling centers. Because it is highly effective in a short period of time, most metropolitan local governments, except Jeonbuk, include the project as an adaptation policy. However, the criteria for selecting a cooling centers are different depending on the budget and non-budget, so the utilization rate and effectiveness of the cooling centers are all different. Therefore, in this study, we developed logistic regression models that can predict and evaluate areas with a high probability of expanding cooling centers in order to implement adaptation policy in local governments. In Incheon Metropolitan City, which consists of various heat wave-vulnerable environments due to the coexistence of the old city and the new city, a logistic model was developed to predict areas where heat waves can be cooling centered by dividing it into Ganghwa·Ongjin-gun and other regions, taking into account socioeconomic and environmental differences. As a result of the study, the statistical model for the Ganghwa·Ogjin-gun region showed that the higher the ground surface temperature and the more and more the number of elderly people over 65 years old, the higher the possibility of location of cooling centers, and the prediction accuracy was about 80.93%. The developed logistic regression model can predict and evaluate areas with a high potential as cooling centers by considering regional environmental and social characteristics, and is expected to be used for priority selection and management when designating additional cooling centers in the future.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.35-48
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• 2014

According to the 2013 construction market outlook report, the liquidation of construction companies is expected to continue due to the ongoing residential construction recession. Bankruptcies of construction companies have a greater social impact compared to other industries. However, due to the different nature of the capital structure and debt-to-equity ratio, it is more difficult to forecast construction companies' bankruptcies than that of companies in other industries. The construction industry operates on greater leverage, with high debt-to-equity ratios, and project cash flow focused on the second half. The economic cycle greatly influences construction companies. Therefore, downturns tend to rapidly increase the bankruptcy rates of construction companies. High leverage, coupled with increased bankruptcy rates, could lead to greater burdens on banks providing loans to construction companies. Nevertheless, the bankruptcy prediction model concentrated mainly on financial institutions, with rare construction-specific studies. The bankruptcy prediction model based on corporate finance data has been studied for some time in various ways. However, the model is intended for all companies in general, and it may not be appropriate for forecasting bankruptcies of construction companies, who typically have high liquidity risks. The construction industry is capital-intensive, operates on long timelines with large-scale investment projects, and has comparatively longer payback periods than in other industries. With its unique capital structure, it can be difficult to apply a model used to judge the financial risk of companies in general to those in the construction industry. Diverse studies of bankruptcy forecasting models based on a company's financial statements have been conducted for many years. The subjects of the model, however, were general firms, and the models may not be proper for accurately forecasting companies with disproportionately large liquidity risks, such as construction companies. The construction industry is capital-intensive, requiring significant investments in long-term projects, therefore to realize returns from the investment. The unique capital structure means that the same criteria used for other industries cannot be applied to effectively evaluate financial risk for construction firms. Altman Z-score was first published in 1968, and is commonly used as a bankruptcy forecasting model. It forecasts the likelihood of a company going bankrupt by using a simple formula, classifying the results into three categories, and evaluating the corporate status as dangerous, moderate, or safe. When a company falls into the "dangerous" category, it has a high likelihood of bankruptcy within two years, while those in the "safe" category have a low likelihood of bankruptcy. For companies in the "moderate" category, it is difficult to forecast the risk. Many of the construction firm cases in this study fell in the "moderate" category, which made it difficult to forecast their risk. Along with the development of machine learning using computers, recent studies of corporate bankruptcy forecasting have used this technology. Pattern recognition, a representative application area in machine learning, is applied to forecasting corporate bankruptcy, with patterns analyzed based on a company's financial information, and then judged as to whether the pattern belongs to the bankruptcy risk group or the safe group. The representative machine learning models previously used in bankruptcy forecasting are Artificial Neural Networks, Adaptive Boosting (AdaBoost) and, the Support Vector Machine (SVM). There are also many hybrid studies combining these models. Existing studies using the traditional Z-Score technique or bankruptcy prediction using machine learning focus on companies in non-specific industries. Therefore, the industry-specific characteristics of companies are not considered. In this paper, we confirm that adaptive boosting (AdaBoost) is the most appropriate forecasting model for construction companies by based on company size. We classified construction companies into three groups - large, medium, and small based on the company's capital. We analyzed the predictive ability of AdaBoost for each group of companies. The experimental results showed that AdaBoost has more predictive ability than the other models, especially for the group of large companies with capital of more than 50 billion won.