• Journal of Korean Society of Industrial and Systems Engineering
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• v.47 no.1
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• pp.41-50
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• 2024

Korea is facing a significant problem with historically low fertility rates, which is becoming a major social issue affecting the economy, labor force, and national security. This study analyzes the factors contributing to the regional gap in fertility rates and derives policy implications. The government and local authorities are implementing a range of policies to address the issue of low fertility. To establish an effective strategy, it is essential to identify the primary factors that contribute to regional disparities. This study identifies these factors and explores policy implications through machine learning and explainable artificial intelligence. The study also examines the influence of media and public opinion on childbirth in Korea by incorporating news and online community sentiment, as well as sentiment fear indices, as independent variables. To establish the relationship between regional fertility rates and factors, the study employs four machine learning models: multiple linear regression, XGBoost, Random Forest, and Support Vector Regression. Support Vector Regression, XGBoost, and Random Forest significantly outperform linear regression, highlighting the importance of machine learning models in explaining non-linear relationships with numerous variables. A factor analysis using SHAP is then conducted. The unemployment rate, Regional Gross Domestic Product per Capita, Women's Participation in Economic Activities, Number of Crimes Committed, Average Age of First Marriage, and Private Education Expenses significantly impact regional fertility rates. However, the degree of impact of the factors affecting fertility may vary by region, suggesting the need for policies tailored to the characteristics of each region, not just an overall ranking of factors.

• Advances in materials Research
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• v.13 no.1
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• pp.63-86
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• 2024

Asphalt concrete (AC), is a mixture of bitumen and aggregates, which is very sensitive in the design of flexible pavement. In this study, the Marshall stability of the glass and carbon fiber bituminous concrete was predicted by using Artificial Neural Network (ANN), Support Vector Machine (SVM), Random Forest (RF), and M5P Tree machine learning algorithms. To predict the Marshall stability, nine inputs parameters i.e., Bitumen, Glass and Carbon fibers mixed in 100:0, 75:25, 50:50, 25:75, 0:100 percentage (designated as 100GF:0CF, 75GF:25CF, 50GF:50 CF, 25GF:75CF, 0GF:100CF), Bitumen grade (VG), Fiber length (FL), and Fiber diameter (FD) were utilized from the experimental and literary data. Seven statistical indices i.e., coefficient of correlation (CC), mean absolute error (MAE), root mean squared error (RMSE), relative absolute error (RAE), root relative squared error (RRSE), Scattering index (SI), and BIAS were applied to assess the effectiveness of the developed models. According to the performance evaluation results, Artificial neural network (ANN) was outperforming among other models with CC values as 0.9147 and 0.8648, MAE values as 1.3757 and 1.978, RMSE values as 1.843 and 2.6951, RAE values as 39.88 and 49.31, RRSE values as 40.62 and 50.50, SI values as 0.1379 and 0.2027 and BIAS value as -0.1 290 and -0.2357 in training and testing stage respectively. The Taylor diagram (testing stage) also confirmed that the ANN-based model outperforms the other models. Results of sensitivity analysis showed that the fiber length is the most influential in all nine input parameters whereas the fiber combination of 25GF:75CF was the most effective among all the fiber mixes in Marshall stability.

• Korean Journal of Remote Sensing
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• v.35 no.6_3
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• pp.1285-1298
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• 2019

Drought is one of the factors that can cause wildfires. Drought is related to not only the occurrence of wildfires but also their frequency, extent and severity. In South Korea, most wildfires occur in dry seasons (i.e. spring and autumn), which are highly correlated to drought events. In this study, we examined the relationship between wildfire occurrence and drought factors, and developed satellite-based new drought indices for assessing wildfire risk over South Korea. Drought factors used in this study were high-resolution downscaled soil moisture, Normalized Different Water Index (NDWI), Normalized Multi-band Drought Index (NMDI), Normalized Different Drought Index (NDDI), Temperature Condition Index (TCI), Precipitation Condition Index (PCI) and Vegetation Condition Index (VCI). Drought indices were then proposed through weighted linear combination and one-class support vector machine (One-class SVM) using the drought factors. We found that most drought factors, in particular, soil moisture, NDWI, and PCI were linked well to wildfire occurrence. The validation results using wildfire cases in 2018 showed that all five linear combinations produced consistently good performance (> 88% in occurrence match). In particular, the combination of soil moisture and NDWI, and the combination of soil moisture, NDWI, and precipitation were found to be appropriate for representing wildfire risk.

• Korean Journal of Weed Science
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• v.17 no.4
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• pp.382-389
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• 1997

Collated data from the 1995-1996 floristic surveys of weeds of arable peat in Selangor district were analysed to assess composition and dominance and spatial distribution pattern based on quantitative and dispersion indices. Forty eight weed species belonging to 19 families of which 31 were broad leaves, 10 grasses and 7 sedges were sampled and these ware translated as 77.8 and 15% of the total cover, respectively, The respective important values were 71.11 and 18%. Ten species in the onder of dominance were Fimbristylis acuminata, Murdannia nudiflora, Hedyotis corymbosa, Ageratum conyzoides, Asystasia gangetica, Cleome rutidosperma, Cyperus sphacelatus, Lindernia crustacea, Ludwigia hyssopifolia of spatial distribution based on variance-to-mean ratios, Llouds mean crowding or Lloyds patchiness indices. Other species were either random or regular in their spatial distribution. Differences in species-dominance and spatial distribution pattern may be attributed to inherent variations in patchiness and fecundity schedules of each weed species, crops, cropping patterns and agronomic practices prevailing in the area.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2008.04a
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• pp.114-119
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• 2008

A refined three-dimensional finite element interaction model between the high-speed train and railway bride deck has been developed in the present study. Analytical predictions of vertical deflections for a railway bridge are compared with in-situ test results and a good agreement is achieved. Then, input variables employed in the analytical comparisons are selected as random variables for the limit state functions. followed by risk assessment. For this purpose, a linear adaptive weighted response surface method has been developed and applied. A typical railway bridge has been selected and the limit state functions are employed from UIC and Korean specifications in the comparative studies. The results reveal that Korean specifications give significantly risky reliability indices in comparison with UIC specifications. It is thus encouraged from the above that the present linear adaptive weighted response surface method can be an alternative for the fast estimation of nonlinear structural systems.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.3
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• pp.486-495
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• 2009

This paper proposes a new methodology on reliability evaluation of a power system including solar cell generators (SCG). The SCGs using renewable energy resource such as solar radiation(SR) should be modeled as multi-state operational model because the uncertainty of the resource supply may occur an effect as same as the forced outage of generator in viewpoint of adequacy reliability of system. While a two-state model is well suited for modeling conventional generators, a multi-state model is needed to model the SCGs due to the random variation of solar radiation. This makes the method of calculating reliability evaluation indices of the SCG different from the conventional generator. After identifying the typical pattern of the SR probability distribution function(pdf) from SR actual data, this paper describes modelling, methodology and details process for reliability evaluation of the solar cell generators integrated with power system. Two test results indicate the viability of the proposed method.

• Structural Engineering and Mechanics
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• v.65 no.6
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• pp.751-760
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• 2018

Damages in concrete structures due to aging and other factors could be a serious and immense matter. Making the best selection of the most viable and practical repairing and strengthening techniques are relatively difficult tasks using traditional methods of structural analyses. This is due to the fact that the traditional methods used for assessing aging structure are not fully capable when considering the randomness in strength, loads and cost. This paper presents a reliability-based methodology for assessing reinforced concrete members. The methodology of this study is based on probabilistic analysis, using statistics of the random variables in the performance function equations. Principles of reliability updating are used in the assessment process, as new information is taken into account and combined with prior probabilistic models. The methodology can result in a reliability index ${\beta}$ that can be used to assess the structural component by comparing its value with a standard value. In addition, these methods result in partial safety factor values that can be used for the purpose of strengthening the R/C elements of the existing structure. Calculations and computations of the reliability indices and the partial safety factors values are conducted using the First-order Reliability Method and Monte Carlo simulation.

• Journal of the Korean Wood Science and Technology
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• v.22 no.3
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• pp.26-31
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• 1994

To provide further information for reutilization of the waste wood obtained after cultivating oak mushroom in Kangwon-do, the crystal structures of the waste wood were investigated and compared to those of normal woods by a series of x-ray diffraction analysis. The results obtained are as follows: 1. An x-ray diffraction diagram of cultivated wood for 5 years was same as that of typical cellulose with some orientation of cellulose crystallites, but that of cultivated wood for 8 years a random. 2. Crystallinity indices in normal and cultivated woods for 5 years ranged from 57% to 60%. In the cultivated wood for 8 years, however, the value showed about 40%. 3. Crystallite widths of cultivated woods for 5 years and for 8 years were 3 nm and 2.5 nm, respectively. 4. Intensity ratios of equatorial and meridional layers did not show any significant differences. From the above results, it is clear that the waste wood obtained after cultivating oak mush room for 5 years showed basically same crystal structures with normal wood. Therefore, we think that the waste wood may be used available for cellulosic material instead of normal wood.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.9
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• pp.3799-3803
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• 2015

Background: The Functional Assessment of Cancer Therapy - Breast (FACT-B) scale is widely used to measure health-related quality of life in cancer patients. The aim of the present study is to validate the FACT-B in a sample of Iranian women with breast cancer. Materials and Methods: The sample consisted of 300 women selected through non-random convenient sampling procedure from oncology hospitals and clinics in Kermanshah and Shiraz cities. They were asked to fill in the Persian versions of the FACT-B scale, Hospital Anxiety and Depression Scale, the European Organization for Research and Treatment of Cancer quality of life EORTC QLQ30. Confirmatory factorial analysis of the methods, concurrent validity and discriminant, and Cronbach's alpha for internal consistency were applied. Results: Internal consistency using Cronbach's alpha was 0.63 to 0.93 for the subscales and 0.92 for the total scale. Significant correlations between FACT-B and other measures indicate that this scale had concurrent and discriminant validity. The values of fit indices were satisfactory. Conclusions: The Persian version of the FACT-B scale is valid and reliable and, therefore, the scale can be used in research and clinical settings to assess health-related quality of life in Iranian patients with breast cancer.

• Honam Mathematical Journal
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• v.26 no.4
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• pp.463-469
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• 2004

In this paper we establish some recurrence relations satisfied by quotient moments of upper record values from the exponential distribution. Let $\{X_n,\;n{\geq}1\}$ be a sequence of independent and identically distributed random variables with a common continuous distribution function F(x) and probability density function(pdf) f(x). Let $Y_n=max\{X_1,\;X_2,\;{\cdots},\;X_n\}$ for $n{\geq}1$. We say $X_j$ is an upper record value of $\{X_n,\;n{\geq}1\}$, if $Y_j>Y_{j-1}$, j > 1. The indices at which the upper record values occur are given by the record times {u(n)}, $n{\geq}1$, where u(n)=min\{j{\mid}j>u(n-1),\;X_j>X_{u(n-1)},\;n{\geq}2\} and u(1) = 1. Suppose $X{\in}Exp(1)$. Then $\Large{E\;\left.{\frac{X^r_{u(m)}}{X^{s+1}_{u(n)}}}\right)=\frac{1}{s}E\;\left.{\frac{X^r_{u(m)}}{X^s_{u(n-1)}}}\right)-\frac{1}{s}E\;\left.{\frac{X^r_{u(m)}}{X^s_{u(n)}}}\right)}$ and $\Large{E\;\left.{\frac{X^{r+1}_{u(m)}}{X^s_{u(n)}}}\right)=\frac{1}{(r+2)}E\;\left.{\frac{X^{r+2}_{u(m)}}{X^s_{u(n-1)}}}\right)-\frac{1}{(r+2)}E\;\left.{\frac{X^{r+2}_{u(m-1)}}{X^s_{u(n-1)}}}\right)}$.