• 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.

• Journal of Preventive Medicine and Public Health
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• v.11 no.1
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• pp.123-127
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• 1978

The major objective of this research is to identify those hospital characteristics that best explain cost variation among hospitals and to formulate linear models that can predict hospital costs. Specific emphasis is placed on hospital output, that is, the identification of diagnosis related patient groups (DRGs) which are medically meaningful and demonstrate similar patterns of hospital resource consumption. A casemix index is developed based on the DRGs identified. Considering the common problems encountered in previous hospital cost research, the following study requirements are estab-lished for fulfilling the objectives of this research: 1. Selection of hospitals that exercise similar medical and fiscal practices. 2. Identification of an appropriate data collection mechanism in which demographic and medical characteristics of individual patients as well as accurate and comparable cost information can be derived. 3. Development of a patient classification system in which all the patients treated in hospitals are able to be split into mutually exclusive categories with consistent and stable patterns of resource consumption. 4. Development of a cost finding mechanism through which patient groups' costs can be made comparable across hospitals. A data set of Medicare patients prepared by the Social Security Administration was selected for the study analysis. The data set contained 27,229 record abstracts of Medicare patients discharged from all but one short-term general hospital in Connecticut during the period from January 1, 1971, to December 31, 1972. Each record abstract contained demographic and diagnostic information, as well as charges for specific medical services received. The 'AUT-OGRP System' was used to generate 198 DRGs in which the entire range of Medicare patients were split into mutually exclusive categories, each of which shows a consistent and stable pattern of resource consumption. The 'Departmental Method' was used to generate cost information for the groups of Medicare patients that would be comparable across hospitals. To fulfill the study objectives, an extensive analysis was conducted in the following areas: 1. Analysis of DRGs: in which the level of resource use of each DRG was determined, the length of stay or death rate of each DRG in relation to resource use was characterized, and underlying patterns of the relationships among DRG costs were explained. 2. Exploration of resource use profiles of hospitals; in which the magnitude of differences in the resource uses or death rates incurred in the treatment of Medicare patients among the study hospitals was explored. 3. Casemix analysis; in which four types of casemix-related indices were generated, and the significance of these indices in the explanation of hospital costs was examined. 4. Formulation of linear models to predict hospital costs of Medicare patients; in which nine independent variables (i. e., casemix index, hospital size, complexity of service, teaching activity, location, casemix-adjusted death. rate index, occupancy rate, and casemix-adjusted length of stay index) were used for determining factors in hospital costs. Results from the study analysis indicated that: 1. The system of 198 DRGs for Medicare patient classification was demonstrated not only as a strong tool for determining the pattern of hospital resource utilization of Medicare patients, but also for categorizing patients by their severity of illness. 2. The wei틴fed mean total case cost (TOTC) of the study hospitals for Medicare patients during the study years was $11,27.02 with a standard deviation of $117.20. The hospital with the highest average TOTC ($1538.15) was 2.08 times more expensive than the hospital with the lowest average TOTC ($743.45). The weighted mean per diem total cost (DTOC) of the study hospitals for Medicare patients during the sutdy years was $107.98 with a standard deviation of $15.18. The hospital with the highest average DTOC ($147.23) was 1.87 times more expensive than the hospital with the lowest average DTOC ($78.49). 3. The linear models for each of the six types of hospital costs were formulated using the casemix index and the eight other hospital variables as the determinants. These models explained variance to the extent of 68.7 percent of total case cost (TOTC), 63.5 percent of room and board cost (RMC), 66.2 percent of total ancillary service cost (TANC), 66.3 percent of per diem total cost (DTOC), 56.9 percent of per diem room and board cost (DRMC), and 65.5 percent of per diem ancillary service cost (DTANC). The casemix index alone explained approximately one half of interhospital cost variation: 59.1 percent for TOTC and 44.3 percent for DTOC. Thsee results demonstrate that the casemix index is the most importand determinant of interhospital cost variation Future research and policy implications in regard to the results of this study is envisioned in the following three areas: 1. Utilization of casemix related indices in the Medicare data systems. 2. Refinement of data for hospital cost evaluation. 3. Development of a system for reimbursement and cost control in hospitals.

• Journal of Korean Society of Forest Science
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• v.100 no.4
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• pp.672-680
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• 2011

The purpose of this study has been carried to develop a criterion for the selection of evaluation factors on Forest Carbon Cycle Community(F.C.C.C) based on the result of survey of 96 participants who were operation managers on mountain eco village(31), relevant experts(33), and officers of local government(32). For analysis of the results of survey, DHP(Delphi Hierarchy Process) method was used which is a combination of Delphi method and AHP(Analytic Hierarchy Process) method. The key factors on selection of a suitable area to launch F.C.C.C. project of Korea Forest Service was selected under three hierarchical classes. Class 1 comprises 3 indices(Physical resource index, Human resource index, Vision index), and Class 2 which contains 10 indices (Existing resource, Surroundings resource, Forest biomass resource, Humanities Social quality, Local resident participation, Leader's ability, External support, Planning of operation, Capability of operation, and Effect of operation). Class 3 is sub-level class of class which possess 38 indices. From the results of analysis, Consistency Index(C.I) of each index in the 3 classes was used as evaluation factor. In Class 1, index 'human resources' showed highest Consistency Index(0.454). In Class 2, index 'forest biomass resources' was the highest Consistency Index(0.376) in 'physical resources' of Class 1, index 'leader's ability' was the highest Consistency Index(0.326) in 'human resources' of Class 1, and index 'planning of operation' was the highest Consistency Index(0.346) in 'vision' of Class 1. In Class 3, relative importance of 38 index including 'Joint ownership land security(C.I.-0.266)' was evaluated. Based on the result of this study, a criterion for the selection of evaluation factors for F.C.C.C was developed and the evaluation criterion is expected to be use to select of a suitable area to launch F.C.C.C. project since 2011.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.177-193
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• 2014

Over the past decade, there has been a rapid diffusion of electronic commerce and a rising number of interconnected networks, resulting in an escalation of security threats and privacy concerns. Electronic commerce has a built-in trade-off between the necessity of providing at least some personal information to consummate an online transaction, and the risk of negative consequences from providing such information. More recently, the frequent disclosure of private information has raised concerns about privacy and its impacts. This has motivated researchers in various fields to explore information privacy issues to address these concerns. Accordingly, the necessity for information privacy policies and technologies for collecting and storing data, and information privacy research in various fields such as medicine, computer science, business, and statistics has increased. The occurrence of various information security accidents have made finding experts in the information security field an important issue. Objective measures for finding such experts are required, as it is currently rather subjective. Based on social network analysis, this paper focused on a framework to evaluate the process of finding experts in the information security field. We collected data from the National Discovery for Science Leaders (NDSL) database, initially collecting about 2000 papers covering the period between 2005 and 2013. Outliers and the data of irrelevant papers were dropped, leaving 784 papers to test the suggested hypotheses. The co-authorship network data for co-author relationship, publisher, affiliation, and so on were analyzed using social network measures including centrality and structural hole. The results of our model estimation are as follows. With the exception of Hypothesis 3, which deals with the relationship between eigenvector centrality and performance, all of our hypotheses were supported. In line with our hypothesis, degree centrality (H1) was supported with its positive influence on the researchers' publishing performance (p<0.001). This finding indicates that as the degree of cooperation increased, the more the publishing performance of researchers increased. In addition, closeness centrality (H2) was also positively associated with researchers' publishing performance (p<0.001), suggesting that, as the efficiency of information acquisition increased, the more the researchers' publishing performance increased. This paper identified the difference in publishing performance among researchers. The analysis can be used to identify core experts and evaluate their performance in the information privacy research field. The co-authorship network for information privacy can aid in understanding the deep relationships among researchers. In addition, extracting characteristics of publishers and affiliations, this paper suggested an understanding of the social network measures and their potential for finding experts in the information privacy field. Social concerns about securing the objectivity of experts have increased, because experts in the information privacy field frequently participate in political consultation, and business education support and evaluation. In terms of practical implications, this research suggests an objective framework for experts in the information privacy field, and is useful for people who are in charge of managing research human resources. This study has some limitations, providing opportunities and suggestions for future research. Presenting the difference in information diffusion according to media and proximity presents difficulties for the generalization of the theory due to the small sample size. Therefore, further studies could consider an increased sample size and media diversity, the difference in information diffusion according to the media type, and information proximity could be explored in more detail. Moreover, previous network research has commonly observed a causal relationship between the independent and dependent variable (Kadushin, 2012). In this study, degree centrality as an independent variable might have causal relationship with performance as a dependent variable. However, in the case of network analysis research, network indices could be computed after the network relationship is created. An annual analysis could help mitigate this limitation.

• Journal of Korea Water Resources Association
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• v.49 no.3
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• pp.187-196
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• 2016

Standardized Precipitation Evapotranspiration Index (SPEI) considering evapotranspiration and precipitation is generally used to quantify the drought severity. Also, Reconnaissance Drought Index (RDI) has been frequently used in the arid regions which is suffering severe droughts, but drought analysis in association with RDI has been the focus of few studies in South Korea. Therefore, this study compared two meterological drought indices based on precipitation and evapotranspiration using Thornthwaite, Hargreaves, and Blaney-Criddle evaportranspiration calculation methods. Meteorological data of sixteen weather stations which are operated by Korea Meteorological Administration (KMA) were used to quantify drought and to compare characteristics of drought for the Han River Basin from 1992 to 2015. As a result, in case of Han River Basin, severe drought sharply increased in recent years. While the correlation coefficients are relatively high between the SPEIs and RDIs, the drought severity and year of severe drought are partially different. Therefore, it is necessary that RDI will be also measured to quantify severity and occurrence year of drought.

• Journal of the Korea institute for structural maintenance and inspection
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• v.25 no.5
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• pp.94-101
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• 2021

According to the Facility Management System (FMS) operated by the Korea Authority of Land & Infrastructure Safety, it is expected that the number of aging facilities that have been in use for more than 30 years will increase rapidly to 13.9% in 2019 and 34.5% in 2929, and end up with a social problem. In addition, with the revision of "Common Application of Seismic Design Criteria" by the Ministry of Public Administration and Security in 2017, it is mandatory to re-evaluate all existing road facilities and if necessary seismic reinforcement should be done to minimize the magnitude of earthquake damage and perform normal road functions. The seismic performance management-decision support technology currently used in seismic performance management practice in Korea only determines the earthquake-resistance reinforcement priority based on the qualitative index value for the seismic performance of individual facilities. However with this practice, normal traffic functions cannot be guaranteed. A new seismic performance management decision support technology that can provide various judgment data required for decision making is needed to overcome these shortcomings and better perform seismic performance management from a road network perspective.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1185-1193
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• 2023

The increasing interest in soil moisture data from satellite imagery for applications in hydrology, meteorology, and agriculture has led to the development of methods to produce variable-resolution soil moisture maps. Research on accurate soil moisture estimation using satellite imagery is essential for remote sensing applications. The purpose of this study is to generate a soil moisture estimation map for a test area using KOMPSAT-3/3A and KOMPSAT-5 SAR imagery and to quantitatively compare the results with soil moisture data from the Soil Moisture Active Passive (SMAP) mission provided by NASA, with a focus on accuracy validation. In addition, the Korean Environmental Geographic Information Service (EGIS) land cover map was used to determine soil moisture, especially in agricultural and forested regions. The selected test area for this study is the western part of Jeju, South Korea, where input data were available for the soil moisture estimation algorithm based on the Water Cloud Model (WCM). Synthetic Aperture Radar (SAR) imagery from KOMPSAT-5 HV and Sentinel-1 VV were used for soil moisture estimation, while vegetation indices were calculated from the surface reflectance of KOMPSAT-3 imagery. Comparison of the derived soil moisture results with SMAP (L-3) and SMAP (L-4) data by differencing showed a mean difference of 4.13±3.60 p% and 14.24±2.10 p%, respectively, indicating a level of agreement. This research suggests the potential for producing highly accurate and precise soil moisture maps using future South Korean satellite imagery and publicly available data sources, as demonstrated in this study.

• Korean Journal of Health Education and Promotion
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• v.26 no.5
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• pp.57-70
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• 2009

Objectives: This purpose of this study was to make clear the fitness to data of the causality model related to father's child-rearing participation in a double-income household. Methods: Subjects of this survey consisted of the fathers of 2,006 households that use 21 day-care centers and 4 kindergartens whose cooperation was received via the city government departments that have jurisdiction over day-care centers and kindergartens in cities A and B in prefecture I and in city C in prefecture II (city A: 499 households; city B: 1,113 households; city C: 988 households). The surveyed items consisted of the father's age, the father's educational history, the number of children, the age of the youngest child, the father's parental-role awareness, the father's daily working hours, the father's return-home time, and child-rearing participation by the father. Results: The fit indices were found to be CFI = 0.912, GFI = 0.948, and RMSEA = 0.082. Regarding the path coefficients, the path coefficient of the pathway from the age of the youngest child to the father's parent positivity (0.08) and the path coefficient of the pathway from the father's parent positivity to child-rearing participation (0.19) were both at statistically significant levels. Also, the father's return-home time and the working hours, which were considered as disincentives exhibited a direct effect on child-rearing participation without being influenced by the father's parent positivity or parent negativity. The path coefficient of the pathway from return-home time to child-rearing participation was -0.43, and the path coefficient of the pathway from working hours to child-rearing participation was -0.13. The value of the path coefficient expressing the relationship between the return-home time and working hours was 0.80. Conclusion: Authors infered that it'll be the basic material to build a generation mechanism about vanity and father's child-rearing participation appropriately as a result of this research.

• Korean Journal of Environment and Ecology
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• v.36 no.3
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• pp.327-337
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• 2022

Ecological restoration is considered a good means to prevent biodiversity loss in terms of the ecosystem's health and sustainability. However, there are difficulties in putting it into practice as there is no comprehensive and objective standard for the selection of plant species, such as environmental, ecological factors, and restoration goal setting. Therefore, this study developed an evaluation index necessary for selecting plant species for restoration using the Delphi method that synthesizes the opinions of the expert group. A survey with 38 questionnaires was conducted twice for experts in ecological restoration, etc., and the importance and priority of evaluation indicators were analyzed by dividing the restoration targets into inland and island regions. The result of the importance analysis showed that "native plants" had the highest average of 4.9 among the evaluation indices in both inland and island regions, followed by "seed security", "propagation", and "root growth rate". In the inland region, the index priority was analyzed in the order of "native plants", "appearance frequency", "root growth rate", "distribution range", and "seed security" in the island region, it was analyzed in the order of "native plants", "root growth rate", "appearance frequency", "distribution range", and "tolerance", showing slight differences between the two indicators. As a result of the importance and priority indicator analysis, we set the mean importance and priority of 4.1 and 2.9, respectively, in the inland region and 4.2 and 2.9, respectively, in the island region. As for the criteria of selecting plant species for ecological restoration, the "native plants" had the highest importance and priority. "Seed securing", 'viability", "topography", "proliferation", "tolerance", "soil conditions", "growth characteristics", "early succession", "distribution range", "appearance frequency", and "germination rate" were classified into subgroups of low importance and priority. The lowest indicators were "final stage of succession", "transition period", 'transition stage", "root", "reproduction", "soil", "appearance", "technology", "landscape", "climate", and "germination rate". We expected that the findings through objective verification in this study would be used as evaluation indicators for selecting native plant species for ecological restoration.