• Title/Summary/Keyword: ratios of random variables

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Probabilistic Optimization for Improving Soft Marine Ground using a Low Replacement Ratio (해상 연약지반의 저치환율 개량에 대한 확률론적 최적화)

  • Han, Sang-Hyun;Kim, Hong-Yeon;Yea, Geu-Guwen
    • The Journal of Engineering Geology
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    • v.26 no.4
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    • pp.485-495
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    • 2016
  • To reinforce and improve the soft ground under a breakwater while using materials efficiently, the replacement ratio and leaving periods of surcharge load are optimized probabilistically. The results of Bayesian updating of the random variables using prior information decrease uncertainty by up to 39.8%, and using prior information with more samples results in a sharp decrease in uncertainty. Replacement ratios of 15%-40% are analyzed using First Order Reliability Method and Monte Carlo simulation to optimize the replacement ratio. The results show that replacement ratios of 20% and 25% are acceptable at the column jet grouting area and the granular compaction pile area, respectively. Life cycle costs are also compared to optimize the replacement ratios within allowable ranges. The results show that a range of 20%-30% is the most economical during the total life cycle. This means that initial construction cost, maintenance cost and failure loss cost are minimized during total life cycle. Probabilistic analysis for leaving periods of shows that three months acceptable. Design optimization with respect to life cycle cost is important to minimize maintenance costs and retain the performance of the structures for the required period. Therefore, more case studies that consider the maintenance costs of soil structures are necessary to establish relevant design codes.

Prevalence and Factors Associated With Adolescent Pregnancy Among an Indigenous Ethnic Group in Rural Nepal: A Community-based Cross-sectional Study

  • Kusumsheela Bhatta;Pratiksha Pathak;Madhusudan Subedi
    • Journal of Preventive Medicine and Public Health
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    • v.57 no.3
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    • pp.269-278
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    • 2024
  • Objectives: The Chepang people, an indigenous ethnic group in Nepal, experience substantial marginalization and socioeconomic disadvantages, making their communities among the most vulnerable in the region. This study aimed to determine the prevalence and factors associated with adolescent pregnancy in the Chepang communities of Raksirang Rural Municipality, Makwanpur District, Bagmati Province, Nepal. Methods: A cross-sectional study was conducted from October 2022 to April 2023 among 231 Chepang women selected using simple random sampling from Raksirang Rural Municipality. A semi-structured questionnaire was used for interviewing the mothers. Bivariate and multivariate logistic regression analyses were performed, using odds ratios with 95% confidence intervals (CIs). Variables with a variation inflation factor of more than 2 and a p-value of more than 0.25 were excluded from the final model. Results: The study revealed that the prevalence rate of adolescent pregnancy among Chepang women was 71.4% (95% CI, 65.14 to 77.16). A large percentage of participants (72.7%) were married before the age of 18 years. Poor knowledge of adolescent pregnancy (adjusted odds ratio [aOR], 10.3; 95% CI, 8.42 to 14.87), unplanned pregnancy (aOR, 13.3; 95% CI, 10.76 to 19.2), and lack of sex education (aOR, 6.57; 95% CI, 3.85 to 11.27) were significantly associated with adolescent pregnancy. Conclusions: The prevalence of adolescent pregnancy among the Chepang community was high. These findings highlighted the importance of raising awareness about the potential consequences of adolescent pregnancy and implementing comprehensive sexuality education programs for preventing adolescent pregnancies within this community.

Why do Sovereign Wealth Funds Invest in Asia?

  • Zhang, Hongxia;Kim, Heeho
    • Journal of Korea Trade
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    • v.25 no.1
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    • pp.65-88
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    • 2021
  • Purpose - This paper aims to examine the determinants of SWFs' investment in Asian countries and to identify consistent investment patterns of SWFs in specific target firms from Asia, particularly China and South Korea. Design/methodology - This study extends the Tobin's Q model to examine the relationship between SWF investments in target firms and their returns with other firm-level control variables. We collect consistent data on SWF investments and the matched firm-level data on target firms, which of observation is 1,512 firms (333 in South Korea and 1,179 in China) targeted by 20 SWF sources during 1997-2017. The panel random effect model is used to estimate the extended Tobin's Q model. The robustness of the estimations is tested by the simultaneous equation models and the panel GEE model. Findings - The evidence shows that sovereign wealth funds are more inclined to invest in the financial sector with a monopoly position and in large firms with higher growth opportunity and superior cash asset ratios in China. In contrast to their investments in China, sovereign wealth funds in South Korea prefer to invest in strategic sectors, such as energy and information technology, and in large firms with high performance and low leverage. Sovereign wealth funds' investments tend to significantly improve the target firm's performance measured by sales growth and returns in both Korea and China. Originality/value - The existing literature focuses on examining the determination of SWFs investment in the developed countries, such as Europe and the United States. Our paper contributes to the literature in three ways; first, we analyzes case studies of SWF investments in Asian markets, which are less developed and riskier. Second, we examine whether the determination of SWF investment in Asian target firms depends on the different time periods, on types of sources of SWFs, and on acquiring countries. Third, our research uses vast sample data on target firms in longer time periods (1997-2017) than other previous studies on the SWFs for Asian markets.

Analysis of factors influencing the travel mode choice of bicycle by trip purpose -a case study of Seoul (통행목적별 자전거 통행수단 선택에 영향을 미치는 요인 분석 -서울시를 대상으로)

  • Lee, Kyunghwan;Ko, Eunjeong
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.21 no.12
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    • pp.33-42
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    • 2020
  • This study analyzed the bicycle traffic patterns and identified the influence factors for each traffic purpose using the household traffic conditions survey for Seoul. The results are summarized as follows. First, as a result of surveying the bicycle traffic ratios according to the administrative dongs, there was a difference of 14.2% by region. Second, various personal characteristic variables, such as age, gender, income, occupation, and housing type, affect the bicycle mode choice, and bicycle passage increases when using facilities in residential areas. Third, among the neighborhood environments, the bicycle traffic for commuting purposes appeared to increase more in the areas of higher land use mix and lower crime rates. In addition, the bicycle road density and the inclination of the area commonly affect bicycle travel for commuting, shopping, exercising, and leisure.

Reliability Analysis on Stability of Armor Units for Foundation Mound of Composite Breakwaters (혼성제 기초 마운드의 피복재 안정성에 대한 신뢰성 해석)

  • Cheol-Eung Lee
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.35 no.2
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    • pp.23-32
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    • 2023
  • Probabilistic and deterministic analyses are implemented for the armor units of rubble foundation mound of composite breakwaters which is needed to protect the upright section against the scour of foundation mounds. By a little modification and incorporation of the previous empirical formulas that has commonly been applied to design the armor units of foundation mound, a new type formula of stability number has been suggested which is capable of taking into account slopes of foundation mounds, damage ratios of armor units, and incident wave numbers. The new proposed formula becomes mathematically identical with the previous empirical formula under the same conditions used in the developing process. Deterministic design have first been carried out to evaluate the minimum weights of armor units for several conditions associated with a typical section of composite breakwater. When the slopes of foundation mound become steepening and the incident wave numbers are increasing, the bigger armor units more than those from the previous empirical formula should be required. The opposite trends however are shown if the damage ratios is much more allowed. Meanwhile, the reliability analysis, which is one of probabilistic models, has been performed in order to quantitatively verify how the armor unit resulted from the deterministic design is stable. It has been confirmed that 1.2% of annual encounter probability of failure has been evaluated under the condition of 1% damage ratio of armor units for the design wave of 50 years return period. By additionally calculating the influence factors of the related random variables on the failure probability due to those uncertainties, it has been found that Hudson's stability coefficient, significant wave height, and water depth above foundation mound have sequentially been given the impacts on failure regardless of the incident wave angles. Finally, sensitivity analysis has been interpreted with respect to the variations of random variables which are implicitly involved in the formula of stability number for armor units of foundation mound. Then, the probability of failure have been rapidly decreased as the water depth above foundation mound are deepening. However, it has been shown that the probability of failure have been increased according as the berm width of foundation mound are widening and wave periods become shortening.

A Comparative Study on Failure Pprediction Models for Small and Medium Manufacturing Company (중소제조기업의 부실예측모형 비교연구)

  • Hwangbo, Yun;Moon, Jong Geon
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.11 no.3
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    • pp.1-15
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    • 2016
  • This study has analyzed predication capabilities leveraging multi-variate model, logistic regression model, and artificial neural network model based on financial information of medium-small sized companies list in KOSDAQ. 83 delisted companies from 2009 to 2012 and 83 normal companies, i.e. 166 firms in total were sampled for the analysis. Modelling with training data was mobilized for 100 companies inlcuding 50 delisted ones and 50 normal ones at random out of the 166 companies. The rest of samples, 66 companies, were used to verify accuracies of the models. Each model was designed by carrying out T-test with 79 financial ratios for the last 5 years and identifying 9 significant variables. T-test has shown that financial profitability variables were major variables to predict a financial risk at an early stage, and financial stability variables and financial cashflow variables were identified as additional significant variables at a later stage of insolvency. When predication capabilities of the models were compared, for training data, a logistic regression model exhibited the highest accuracy while for test data, the artificial neural networks model provided the most accurate results. There are differences between the previous researches and this study as follows. Firstly, this study considered a time-series aspect in light of the fact that failure proceeds gradually. Secondly, while previous studies constructed a multivariate discriminant model ignoring normality, this study has reviewed the regularity of the independent variables, and performed comparisons with the other models. Policy implications of this study is that the reliability for the disclosure documents is important because the simptoms of firm's fail woule be shown on financial statements according to this paper. Therefore institutional arragements for restraing moral laxity from accounting firms or its workers should be strengthened.

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Estimating the Determinants of Households' Monthly Average Income : A Panel Data Model Approach (패널 데이터모형을 적용한 가구당 월평균 가계소득 결정요인 추정에 관한 연구)

  • Yi, Hyun-Joo;Cheul, Hee-Cheul
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.11 no.6
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    • pp.2038-2045
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    • 2010
  • Households' monthly average income is composed of various factors. This study paper studies focuses on estimating the determinants of a households' monthly average income. The region for analysis consist of three groups, that is, the whole country, a metropolitan city(such as Busan, Daegu, Incheon, Gwangiu, Daejeon, Ulsan.) and Seoul. Analyzing period be formed over a 57 time points(2005. 01~2009. 09). In this paper the dependent variable setting up the households' monthly average income, explanatory (independent) variables are composed of the consumer price index, employment to population ratio, Index of housing sale price, the preceding composite index, loans of housing mortgage, spending rate for care medical expense and the composite stock price index. In looking at the factors which determine the monthly average income, evidence was produced supporting the hypothesis that there is a significant positive relationship between the composite index and housing loans. The study also produced evidence supporting the view that there is a significant negative relationship between employment ratios, the house sale pricing index and spending rates for care or medical needs. The study found that the consumer price index and composite stock price index were not significant variables. The implications of these findings are discussed for further research.