• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.6A
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• pp.435-447
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• 2011

This paper discusses the problems in application of a parallel wire strand with high performance steel wires, which have the tensile strength of 1960 MPa grade, as a major component of the main cables in suspension bridges. Construction methods of main cables in suspension bridges are briefly reviewed by comparing the pros and cons of available methods. Required items for performance and quality of parallel wire strands are described based on the established references. Ultimate tensile strength tests are carried out for seven specimens in order to analyze the behavior of high-performance parallel wire strands. The test results demonstrate that the properties of test specimens are satisfied with performance indexes specified in this paper. The high-performance parallel wire strands are acceptable for application in main cables of suspension bridges.

• Journal of Community Nutrition
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• v.1 no.2
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• pp.81-87
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• 1999

Body mass index(BMI) is recognized as one of the most useful indexes for adiposity in children and adults. This study was conducted to provide information on BMI distribution by age and sex in Korean children, and to identify sociodemographic factors that affected BMI among children. The study was conducted on 2376 children(boys 1184, girls 1192) living in a middle-size city in Korea. Subjects were selected from the primary schoolchildren in grades 1-6 using the two-stage sampling method. Their mean age was 9.4 years. The percentile of BMI tended to increase as age increased in both sexes. The 85th percentile for boys, aged 6-12 years, was 19.8kg/㎡, and the 95th percentile was 22.5kg/㎡. The 85th percentile for girls, aged 6-12 years, was 18.9kg/㎡, and the 95th percentile was 21.5kg/㎡. Multiple regression analysis was carried out to predict BMI from percent ideal body weight (PIBW), age and sex. After adjusting PIBW and age, BMI for boys was 0.062kg/㎡ lower than that for girls. One year of age increased BIM by 0.55kg/㎡. The prevalence rate of overweight and obesity based on PIBW was 15.8% and 15.0% for boys, and 14.0% and 11.0% for girls, respectively. Demographic factors such as sex, age, and parents' obesity influenced children's BMI. After adjusting for sex, age and parents' BMI, the presence of another children in family, and mother's employment status showed a strong effect on children's BMI. The results suggest an age-sex specific BMI distribution of Korean children. The present study also provides direct evidence of a correlation between early life environmental factors, such as presence of siblings or mother's employment, and BMI level in Korean children.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.3D
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• pp.469-476
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• 2011

The purposes of research is to understand the need of and the effectiveness of multilevel model to evaluate community support program in watershed areas. If the properties of policy target have hierarchical characteristics, the multilevel analysis is an adequate method to evaluate and test the effectiveness of policy. Also, the technique of multilevel modeling is extended to testing the relevance between performance appraisal and policy effectiveness. The case study of watershed region's community support program was estimated using satisfaction and economic aid level of policy target. This research has three results. First, the multilevel analysis should be used in nested data structure to estimate the effect of policy intervention. Second, the indexes of multilevel modeling should be used complementally to that of the traditional index approach. Third, the spatial hierarchical structure should be considered as the hierarchical structure in policy evaluation.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.9
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• pp.1333-1342
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• 2013

New & renewable energy becomes a crucial subject to solve the problems inherent in the current energy resources, which results in the fast development of the new & renewable energy industry worldwide. However, not only its base is still weak but the high initial investment for technology development and certain scale of an energy market are required in many cases. For this reason, many countries in the world, including Korea, run the energy policies to foster the new & renewable energy industry such as RSP and FIT. In general, a policy should be established to take various, intertwined interests as well as a number of variables related to economic, social, environmental, and international matters into comprehensive consideration. For new & renewable energy industry, there are many variables to be considered and indexes necessary for evaluation but it is hard to take all of them into account. Even though they were considered, no criteria are available for use in a consistent manner. Therefore, this study plans to develop an evaluation model for the Korean new & renewable energy policy.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.2
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• pp.1490-1499
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• 2015

The purpose of this study is to improve Biotope Area Ratio(BAR) systems used in the various fields. Recently, there has been increasing demand in urban agriculture as well as more residents cultivating farms on a small scale. However, there are few measures in terms of architecture and urban planning to respond to this trend. In this sense, this research is effective as it can respond to these demands by using BAR systems. Yet, the environmental indexes are not enough since BAR systems only take account of vegetation. Therefore, this study proposes an alternative way that includes the capacity factor of the plant growth by expanding the existing BAR systems. Thus, the study analyzes the complementary possibility of BAR systems, including elements of daylight, planting interval, area and soil depth with existing BAR elements.

• Journal of the Korean Society of Marine Environment & Safety
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• v.24 no.7
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• pp.907-915
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• 2018

With the increase of metal usage in various industries, metal pollution and ecological toxicity in the environmental system have become a significant concern. A geo-statistical index has been widely used to determine contamination level with normalization through a background value. In this study, geo-statistical indexes such as an enrichment factor, accumulation index, and potential ecological risk index were used to assess metal pollution in soil at locations associated with shipbuilding manufacturing industries. Metal contamination, especially of Cu and Pb, was observed in some samples located closer to manufacturing sites. Enrichment factor and accumulation (IGEO) values were indicative of concerning levels of soil contamination in specific samples, and the soil contamination could be induced by anthropogenic sources. In further study, after more detailed sampling for soil and potential pollution sources, high interpretation techniques such as Pb isotope analysis and X-ray analysis will be needed to investigate source identification.

• International Journal of Computer Science & Network Security
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• v.22 no.7
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• pp.21-28
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• 2022

The increase in the number of large cities and the size of their population sharpens attention to the new role of cities as entities to ensure a high-quality, safe and modern life of citizens, which has become significantly more active in recent years. The rapid spread of smart cities in the modern world has actualized the issue of analyzing their success and assessing the role of various factors in this. Every success of a smart city is always the result of a unique combination of the most modern technologies, environmental and social initiatives, skillful and consistent management, as well as available human potential. The purpose of the article is to analyze the success factors of smart cities based on the generalization of the results of the most famous ratings. In order to identify the impact of various factors, primarily intellectual, on the success and leadership positions of smart cities, the following ratings were consistently analyzed: Smart City Index (SCI), City in Motion Index (CIMI), Global Power City Index (GPCI), Global Cities Index (GCI), Global Cities Outlook (GCO). They have a different list of indicators and main pillars (dimensions), but all ratings take into account aspects such as: governance, ICT, mobility, functionality, human capital, etc. The highest correlation coefficient, that is, the strongest linear relationship of the CIMI index was found with such factors as: Human capital, Economy, Governance and Technologies. Summarizing the results of the TOP 20 smart cities according to different ratings allowed us to confirm that the list of leaders is very similar in all ratings. Among those cities that are in the TOP-20 in all five indexes are: London, Sydney and Singapore. There are four indices: New York, Paris, Tokyo, Copenhagen, Berlin, Amsterdam, Melbourne. Achieving leadership positions in smart city rankings is always the result of a combination and synergy of certain factors, and first of all, it is the quality of human capital. The intensity and success of the use of information and communication technologies in locality management processes, city planning and improvement of the city's living conditions depend on it.

• Korean Journal of Remote Sensing
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• v.39 no.4
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• pp.425-440
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• 2023

Monitoring water surface has become one of the most prominent areas of research in addressing environmental challenges.Accurate and automated detection of watersurface in remote sensing imagesis crucial for disaster prevention, urban planning, and water resource management, particularly for a country where water plays a vital role in human life. However, achieving precise detection poses challenges. Previous studies have explored different approaches,such as analyzing water indexes, like normalized difference water index (NDWI) derived from satellite imagery's visible or infrared bands and using k-means clustering analysis to identify land cover patterns and segment regions based on similar attributes. Nonetheless, challenges persist, notably distinguishing between waterspectralsignatures and cloud shadow or terrain shadow. In thisstudy, our objective is to enhance the precision of water surface detection by constructing a comprehensive water database (DB) using existing digital and land cover maps. This database serves as an initial assumption for automated water index analysis. We utilized 1:5,000 and 1:25,000 digital maps of Korea to extract water surface, specifically rivers, lakes, and reservoirs. Additionally, the 1:50,000 and 1:5,000 land cover maps of Korea aided in the extraction process. Our research demonstrates the effectiveness of utilizing a water DB product as our first approach for efficient water surface extraction from satellite images, complemented by our second and third approachesinvolving NDWI analysis and k-means analysis. The image segmentation and binary mask methods were employed for image analysis during the water extraction process. To evaluate the accuracy of our approach, we conducted two assessments using reference and ground truth data that we made during this research. Visual interpretation involved comparing our results with the global surface water (GSW) mask 60 m resolution, revealing significant improvements in quality and resolution. Additionally, accuracy assessment measures, including an overall accuracy of 90% and kappa values exceeding 0.8, further support the efficacy of our methodology. In conclusion, thisstudy'sresults demonstrate enhanced extraction quality and resolution. Through comprehensive assessment, our approach proves effective in achieving high accuracy in delineating watersurfaces from satellite images.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.590-598
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• 2022

Benchmarking is an important tool to assess the performance of capital projects in the construction industry. Incorporating cost-related metrics into a benchmarking system requires an effective cost normalization process to enable meaningful comparisons among projects that were executed at different locations and times. Projects in the downstream and chemicals sector have unique characteristics compared to other types of construction projects, they require a distinctive cost normalization framework to be developed to benchmark their absolute cost performance. The purpose of this study is to develop such a framework to be used for the case of benchmarking the downstream and chemical projects for their performance assessment. The research team started with a review of existing cost normalization methodologies adopted in benchmarking systems and conducted 7 interviews to identify the current cost normalization practices used by industrial professionals. A panel of 12 experts was then convened and it held 6 review sessions to accomplish the framework development. The cost normalization framework for benchmarking downstream and chemical projects was established as a three-step procedure and it adopts a 4-element cost breakdown structure to accommodate projects submitted by both owners and contractors. It also incorporated 5 published cost indexes that are compatible with downstream and chemical projects and they were embedded into 2 options to complete the normalization process. The framework was then pilot-tested on 4 completed projects to validate its functional practicality and the downstream and chemical use case in the benchmarking system.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1B
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• pp.27-38
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• 2006

The storage function model (SFM) has been used for the flood forecasting in Korea. The SFM has a simple calculation process and it is known that the model is more reasonable than linear model because it considers non-linearity of flood runoff. However, the determination of parameters is very difficult. In general, the trial and error method which is an manual calibration by the decision of a model manager. This study calibrated the parameters by the trial and error method and optimization technique. The calibrated parameters were compared with the representative parameters which are used in the Flood Control Centers in Korea. Also, the evaluation indexes on objective functions and calibration methods for the comparative analysis of simulation efficiency. As a result, the Genetic Algorithm showed the smallest variation in objective functions and, in this study, it is known that the objective function of SSR (Sum of Squared of Residual) is the best one for the flood forecasting.