• Smart Structures and Systems
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• v.19 no.1
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• pp.33-38
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• 2017

This research tries to present a nonlinear thermo-elastic solution for a functionally graded spherical shell subjected to mechanical and thermal loads. Geometric nonlinearity is considered using the Lagrange or finite strain tensor. Non-homogeneous material properties are considered based on a power function. Adomian's decomposition method is used for calculation of nonlinear results. Nonlinear results such as displacement can be evaluated for sphere in terms of different indexes of non-homogeneity. A comprehensive comparison between linear and nonlinear results and evaluation of the percentage of difference between them can be performed in this paper. The obtained results indicate that the improvement of the results due to usage of nonlinear analysis is depending on the non-homogeneous index.

• Journal of Korean Society for Quality Management
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• v.41 no.2
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• pp.233-248
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• 2013

Purpose: This study develops heuristic process capability indices (PCIs) using distribution-decomposition methods and evaluates the performances. The heuristic methods decompose the variation of a quality characteristic into upper and lower deviations and adjust the value of the PCIs using decomposed deviations in accordance with the skewness. The weighted variance(WV), new WV(NWV), scaled WV(SWV), and weighted standard deviation(WSD) methods are considered. Methods: The performances of the heuristic PCIs are investigated under the varied situations such as various skewed distributions, sample sizes, and specifications. Results: WV PCI is the best under the normal populations, WSD and SWV PCIs are the best under the low skewed populations, NWV PCI is the best under the moderate and high skewed populations. Conclusion: Comprehensive analysis shows that the NWV method is most adequate for a practical use.

• Environmental and Resource Economics Review
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• v.19 no.2
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• pp.243-282
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• 2010

In this paper, we analyze the components and trends of carbon emissions using the Logarithmic Mean Divisia Index decomposition method in Korean electricity industry during the period 1991~2007. In the demand side, carbon emissions are affected by electricity intensity and structural shift and especially electricity intensity is identified as the major factor which has lead carbon emissions decreasing. In the supply side, the result in variations of carbon emission for electric power generation depends on the influences of fossil fuel mix, fuel intensity, generation mix and so on. As a result fuel intensity is the most negative effect on both carbon emission intensity and the amount of carbon emission while the change of generation mix has a positive effect on increasing carbon emissions. And to conclude it needs to make the strategic policies to improve electricity intensity in the demand and to rise emission efficiency as well as to substitute thermal power generation in supply side.

• Forest Science and Technology
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• v.14 no.4
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• pp.192-203
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• 2018

This study analyzed the distribution of forest income and other variable sources of rural household income and considered their importance for the reduction of income inequality and poverty. We employed Gini decomposition to measure the contribution of forest income and other sources of income to income equality and assess whether they were inequality-increasing or inequality-decreasing in the 14 villages. The forest income Gini correlation with total income was very high, $R_k=0.6960$, and the forest income share of total rural household income was 35% ($S_k=0.3570$). If the income earned from forest activities was removed, the Gini index would increase by 10.3%. Thus, if people could not access forest resources because of vast deforestation, perhaps from the limitations of government-managed forestry, unplanned clearing of forest land for agriculture or the granting of ELCs, there would be an increase in income inequality and poverty among rural households. The findings suggest that policy makers should look beyond agriculture for rural development, as forest resources provide meaningful subsistence income and perhaps contribute to both preventing and reducing poverty and inequality in rural communities. The study found that non-farm activities were inequality-increasing sources of income. The share of non-farm income to the total rural household income was $S_k=0.1290$ and the Gini index of non-farm income was very high, $G_k=0.8780$, compared with forest and farm income. This disagrees with other studies which have reported that non-farm income was inequality-decreasing for the rural poor.

• Journal of Preventive Medicine and Public Health
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• v.56 no.1
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• pp.50-58
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• 2023

Objectives: Socioeconomic inequality in metabolic syndrome (MetS) remains poorly understood in Iran. The present study examined the extent of the socioeconomic inequalities in MetS and quantified the contribution of its determinants to explain the observed inequality, with a focus on middle-aged adults in Iran. Methods: This cross-sectional study used data from the Ravansar Non-Communicable Disease cohort study. A sample of 9975 middleaged adults aged 35-65 years was analyzed. MetS was assessed based on the International Diabetes Federation definition. Principal component analysis was used to construct socioeconomic status (SES). The Wagstaff normalized concentration index (CI_n) was employed to measure the magnitude of socioeconomic inequalities in MetS. Decomposition analysis was performed to identify and calculate the contribution of the MetS inequality determinants. Results: The proportion of MetS in the sample was 41.1%. The CI_n of having MetS was 0.043 (95% confidence interval, 0.020 to 0.066), indicating that MetS was more concentrated among individuals with high SES. The main contributors to the observed inequality in MetS were SES (72.0%), residence (rural or urban, 46.9%), and physical activity (31.5%). Conclusions: Our findings indicated a pro-poor inequality in MetS among Iranian middle-aged adults. These results highlight the importance of persuading middle-aged adults to be physically active, particularly those in an urban setting. In addition to targeting physically inactive individuals and those with low levels of education, policy interventions aimed at mitigating socioeconomic inequality in MetS should increase the focus on high-SES individuals and the urban population.

• Journal of Preventive Medicine and Public Health
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• v.50 no.5
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• pp.303-310
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• 2017

Objectives: The aim of this study was to evaluate socioeconomic inequalities in the prevalence of dental caries among an urban population. Methods: This study was conducted among 2000 people 15-40 years of age living in Kurdistan, Iran in 2015. Using a questionnaire, data were collected by 4 trained dental students. The dependent variable was the decayed, missing, and filled teeth (DMF) index. Using principal component analysis, the socioeconomic status (SES) of families was determined based on their household assets. Inequality was measured using the concentration index; in addition, the Oaxaca analytical method was used to determine the contribution of various determinants to the observed inequality. Results: The concentration index for poor scores on the DMF index was -0.32 (95% confidence interval [CI], -0.40 to -0.36); thus, poor DMF indices had a greater concentration in groups with a low SES (p<0.001). Decomposition analysis showed that the mean prevalence of a poor DMF index was 43.7% (95% CI, 40.4 to 46.9%) in the least privileged group and 14.4% (95% CI, 9.5 to 9.2%) in the most privileged group. It was found that 85.8% of the gap observed between these groups was due to differences in sex, parents' education, and the district of residence. A poor DMF index was less prevalent among people with higher SES than among those with lower SES (odds ratio, 0.31; 95% CI, 0.19 to 0.52). Conclusions: An alarming degree of SES inequality in oral health status was found in the studied community. Hence, it is suggested that inequalities in oral health status be reduced via adopting appropriate policies such as the delivery of oral health services to poorer groups and covering such services in insurance programs.

• Journal of Korean Society on Water Environment
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• v.38 no.5
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• pp.240-246
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• 2022

Water and energy are inextricably linked and referred to as 'Water-Energy Nexus'. Recently, this topic has been drawing a lot of attention from various studies due to the exacerbated water availability. Korea's water and energy consumption has been increasing consistently, which calls for better management. This paper aims to identify changes in electricity consumption in relation to water intake and purification processes. Using Log Mean Divisia Index (LMDI) Decomposition Analysis method, this study attributes the changes to major factors such as; Total population (population effect), household/population (structure effect), GDP/household (economic effect), and water-related energy use/GDP (unit effect). The population effect, structure effect, and economic effect contributed to an increase in water-related electricity consumption, while the unit effect contributed to a decrease. As of 2019, the economic effect increased the water supply sector's electricity consumption by 534 GWh, the population effect increased by 73 GWh, and the structure effect increased by 243 GWh. In contrast, the unit effect decreased the electricity consumption by -461 GWh. We would like to make the following suggestions based on the findings of this study; first, the unit effect must be improved by increasing the energy efficiency of water intake and purification plants and installing renewable energy power generation facilities. Second, the structure effect is expected to increase over time, and to mitigate it, water consumption must be reduced through water conservation policies and the improvement of water facilities. Finally, the findings of this study are expected to be used as foundational data for integrated water and energy management.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.6
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• pp.276-286
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• 2013

SVD-based deconvolution algorithm has been known as the most effective technique for CT perfusion image analysis. In this algorithm, in order to reduce noise effects, SVD coefficients smaller than a certain threshold are removed. As the truncation threshold, either a fixed value or a variable threshold yielding a predetermined OI (oscillation index) is frequently employed. Each of these two thresholding methods has an advantage to the other either in accuracy or efficiency. In this paper, we propose a Monte Carlo simulation method to evaluate the accuracy of the two methods. An extension of the proposed method is presented as well to measure the effects of image smoothing on the accuracy of the thresholding methods. In this paper, after the simulation method is described, experimental results are presented using both simulated data and real CT images.

• Asia-Pacific Journal of Business
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• v.13 no.3
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• pp.183-208
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• 2022

Purpose - The main purpose of this study is to widely investigate the impact of recent pandemic crises on the synchronization of the world capital markets through 25 stock indices from major developed countries. Design/methodology/approach - This study collects 25 stock indices from major developed countries and the time period is between January 5, 2001 and February 24, 2022. The data sets used in the study include finance.yahoo.com and Investing.com.. The Granger causality analysis, unit-root test, VAR analysis, and forecasting error variance decomposition were hired in order to analyze the data. Findings - First, there are significant inter-relations among 25 countries around recent major pandemic crises(such as SARS, A(H1N1), MERS, and COVID19), which is consistent result with previous literature. Second, COVID19 shows much stronger impact on the world-wide synchronization than other pandemics. Third, the return volatility of each stock market varies, unit root tests show that daily stock index data are unstable while daily stock index returns are stable, and VAR(Vector Auto Regression) analyses presents significant inter-relations among 25 capital markets. Fourth, from the impulse response function analyses, we find that each market affects the other markets for short term periods, about 2~4 days, and no long term effect was not found. Fifth, Granger causality tests show one-side or two-sides synchronization between capital markets and we estimate, through forecasting error variance decomposition method, that the explanatory portions of each capital market on other markets vary from 10 to 80%. Research implications or Originality - The above results all together show that pandemic crises have strong effects on the synchronization of world capital markets and imply that these synchronizations should be carefully considered both in the investment decisions by individual investors and in the financial and economic policies by governments.

• Journal of the Korea Society for Simulation
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• v.20 no.2
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• pp.1-10
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• 2011

In queueing network analysis, arrival processes are usually modeled as renewal processes by matching mean and variance. The renewal approximation simplifies the analysis and provides reasonably good estimate for the performance measures of the queueing systems under moderate conditions. However, high variability in arrival process or in service process requires more sophisticated approximation procedures for the variability parameter of departure/arrival processes. In this paper, we propose an heuristic approach to refine Whitt's variability function with the k-interval squared coefficient of variation also known as the index of dispersion for intervals(IDI). Regression analysis is used to establish an empirical relationships between the IDI of arrival process and the IDI of departure process of a queueing system.