• Journal of the Korean Operations Research and Management Science Society
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• v.3 no.2
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• pp.75-90
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• 1978

The objective of this paper is to demonstrate how System Dynamics Approach may be used to develop new ways of analyzing and projecting manpower requirements and resources. For this purpose, a System Dynamics Model is presented as an example. An examination of the model will show that a System Dynamics modeling approach is an innovative and useful tool for manpower policy analysis and planning. Second, with minor modifications, the model may be used for manpower policy analysis and planning for any skilled personnel in Korea. For example, a similar model nay be built for engineers to analyze the effects of alternative policies about engineering education, sur as the number of available places in the various institutions of training, scholarships and loans, and the duration of training. An engineer's model may also be used to make the projections of the supply and requirements of engineers in the future according to various alternative assumptions where each assumption represents a policy option.

• Korean Journal of Head & Neck Oncology
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• v.39 no.2
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• pp.1-6
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• 2023

The aging population, particularly those aged 65 and above, is on the rise, with projections indicating a substantial increase in the elderly demographic. This demographic shift brings challenges in managing age-related diseases, including head and neck cancers (HNCs). Frailty, often characterized by physiological decline and vulnerability to stressors, is a crucial factor affecting treatment outcomes of elderly cancer patients. Accordingly, the significance of assessing frailty in elderly HNC patients before their treatment should be emphasized, but current frailty assessment tools may not fully capture the unique challenges faced by HNC patients. Specific indicators, including respiratory and swallowing functions, are proposed for a more tailored assessment. This comprehensive review explores the impact of frailty on various treatment modalities, including surgery, radiation, and chemotherapy, highlighting the need for personalized interventions. Furthermore, it suggests avenues for future research to enhance frailty assessment tools and investigate interventions aimed at improving treatment outcomes in elderly HNC patients.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.19 no.6
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• pp.19-30
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• 2016

The projection of climate-related range shift is critical information for conservation planning of Korean fir (Abies koreana E. H. Wilson). We first modeled the distribution of Korean fir under current climate condition using five single-model species distribution models (SDMs) and the pre-evaluation weighted ensemble method and then predicted the distributions under future climate conditions projected with HadGEM2-AO under four $CO_2$ emission scenarios, the Representative Concentration Pathways (RCP) 2.6, 4.5, 6.0 and 8.5. We also investigated the predictive uncertainty stemming from five individual algorithms and four $CO_2$ emission scenarios for better interpretation of SDM projections. Five individual algorithms were Generalized linear model (GLM), Generalized additive model (GAM), Multivariate adaptive regression splines (MARS), Generalized boosted model (GBM) and Random forest (RF). The results showed high variations of model performances among individual SDMs and the wide range of diverging predictions of future distributions of Korean fir in response to RCPs. The ensemble model presented the highest predictive accuracy (TSS = 0.97, AUC = 0.99) and predicted that the climate habitat suitability of Korean fir would increase under climate changes. Accordingly, the fir distribution could expand under future climate conditions. Increasing precipitation may account for increases in the distribution of Korean fir. Increasing precipitation compensates the negative effects of increasing temperature. However, the future distribution of Korean fir is also affected by other ecological processes, such as interactions with co-existing species, adaptation and dispersal limitation, and other environmental factors, such as extreme weather events and land-use changes. Therefore, we need further ecological research and to develop mechanistic and process-based distribution models for improving the predictive accuracy.

• Health Policy and Management
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• v.26 no.3
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• pp.185-194
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• 2016

Background: The purpose of this study is to forecast changes in the prevalence of chronic diseases and health expenditure by age group. Methods: Based on the Future Elderly Model, this study projects the size of Korean population, the prevalence of chronic diseases, and health expenditure over the 2014-2040 period using two waves (2012, 2013) of the Korea Health Panel and National Health Insurance Service database. Results: First, the prevalence of chronic diseases increases by 2040. The population with hypertension increases 2.04 times; the diabetes increases 2.43 times; and the cancer increases 3.38 times. Second, health expenditure on chronic diseases increases as well. Health expenditure on hypertension increases 4.33 times (1,098,753 million won in 2014 to 4,760,811 million won in 2040); diabetes increases 5.34 times (792,444 million won in 2014 to 4,232,714 million won in 2040); and cancer increases 6.09 times (4,396,223 million won in 2014 to 26,776,724 million won in 2040). Third, men and women who belong to the early middle-aged group (44-55 years old) as of 2014, have the highest increase rate in health spending. Conclusion: Most Korean literature on health expenditure estimation employs a macro-simulation approach and does not fully take into account personal characteristics and behaviors. Thus, this study aims to benefit medical administrators and policy makers to frame effective and targeted health policies by analyzing personal-level data with a microsimulation model and providing health expenditure projections by age group.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.268-272
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• 2010

The research presented here represents a collaborative effort with the SFWMD on developing scenarios for future climate for the SFWMD area. The project focuses on developing methodology for simulating precipitation representing both natural quasi-oscillatory modes of variability in these climate variables and also the secular trends projected by the IPCC scenarios that are publicly available. This study specifically provides the results for precipitation modeling. The starting point for the modeling was the work of Tebaldi et al that is considered one of the benchmarks for bias correction and model combination in this context. This model was extended in the framework of a Hierarchical Bayesian Model (HBM) to formally and simultaneously consider biases between the models and observations over the historical period and trends in the observations and models out to the end of the 21st century in line with the different ensemble model simulations from the IPCC scenarios. The low frequency variability is modeled using the previously developed Wavelet Autoregressive Model (WARM), with a correction to preserve the variance associated with the full series from the HBM projections. The assumption here is that there is no useful information in the IPCC models as to the change in the low frequency variability of the regional, seasonal precipitation. This assumption is based on a preliminary analysis of these models historical and future output. Thus, preserving the low frequency structure from the historical series into the future emerges as a pragmatic goal. We find that there are significant biases between the observations and the base case scenarios for precipitation. The biases vary across models, and are shrunk using posterior maximum likelihood to allow some models to depart from the central tendency while allowing others to cluster and reduce biases by averaging. The projected changes in the future precipitation are small compared to the bias between model base run and observations and also relative to the inter-annual and decadal variability in the precipitation.

• Journal of Climate Change Research
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• v.7 no.3
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• pp.325-334
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• 2016

We projected the distribution of Hedera rhombea, an evergreen broad-leaved climbing plant, under current climate conditions and predicted its future distributions under global warming. Inaddition, weexplained model uncertainty by employing 9 single Species Distribution model (SDM)s to model the distribution of Hedera rhombea. 9 single SDMs were constructed with 736 presence/absence data and 3 temperature and 3 precipitation data. Uncertainty of each SDM was assessed with TSS (Ture Skill Statistics) and AUC (the Area under the curve) value of ROC (receiver operating characteristic) analyses. To reduce model uncertainty, we combined 9 single SDMs weighted by TSS and resulted in an ensemble forecast, a TSS weighted ensemble. We predicted future distributions of Hedera rhombea under future climate conditions for the period of 2050 (2040~2060), which were estimated with HadGEM2-AO. RF (Random Forest), GBM (Generalized Boosted Model) and TSS weighted ensemble model showed higher prediction accuracies (AUC > 0.95, TSS > 0.80) than other SDMs. Based on the projections of TSS weighted ensemble, potential habitats under current climate conditions showed a discrepancy with actual habitats, especially in the northern distribution limit. The observed northern boundary of Hedera rhombea is Ulsan in the eastern Korean Peninsula, but the projected limit was eastern coast of Gangwon province. Geomorphological conditions and the dispersal limitations mediated by birds, the lack of bird habitats at eastern coast of Gangwon Province, account for such discrepancy. In general, potential habitats of Hedera rhombea expanded under future climate conditions, but the extent of expansions depend on RCP scenarios. Potential Habitat of Hedera rhombea expanded into Jeolla-inland area under RCP 4.5, and into Chungnam and Wonsan under RCP 8.5. Our results would be fundamental information for understanding the potential effects of climate change on the distribution of Hedera rhombea.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.486-486
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• 2018

During the post green revolution era, wheat and rice were the main crops of concern to cater the food security issues of Pakistan. The use of semi dwarf high yielding varieties along with extensive use of fertilizers and surface and ground water lead to substantial increase in crop production. However, the higher crop productivity came at the cost of over exploitation of the precious land and water resources, which ultimately has resulted in the dwindling production rates, loss of soil fertility, and qualitative and quantitative deterioration of both surface and ground water bodies. Recently, during the past two decades, severe climate changes are further pushing the Pakistan's wheat-rice system towards its limits. This necessitates a careful analysis of the current crop water requirements and water footprints (both green and blue) to project the future trends under the most likely climate change phenomenon. This was done by using the FAO developed CROPWAT model v 8.0, coupled with the statistically-downscaled climate projections from the 8 Global Circulation Models (GCMs), for the two future time slices, 2030s (2021-2050) and 2060s (2051-2080), under the two Representative Concentration Pathways (RCPs): 4.5 and 8.5. The wheat-rice production system of Punjab, Pakistan was considered as a case study in exploration of how the changing climate might influence the crop water requirements and water footprints of the two major crops. Under the worst, most likely future scenario of temperature rise and rainfall reduction, the crop water requirements and water footprints, especially blue, increased, owing to the elevated irrigation demands originating from the accelerated evapotranspiration rates. A probable increase in rainfall as envisaged by some GCMs may partly alleviate the adverse impacts of the temperature rise but the higher uncertainties associated with the predicated rainfall patterns is worth considering before reaching a final conclusion. The total water footprints were continuously increasing implying that future climate would profoundly influence the crop evapotranspiration demands. The results highlighted the significance of the irrigation water availability in order to sustain and improve the wheat-rice production system of Punjab, Pakistan.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.199-199
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• 2017

Sustainable wheat production is of paramount importance for attaining/maintaining the food self-sufficiency status of the rapidly growing nation of Pakistan. However, the average wheat yield per unit area has been dwindling in recent years and the climate-induced variations in rainfall patterns and temperature regimes, during the wheat growth period, are believed to be the reason behind this decline. Crop growth simulation models are powerful tools capable of playing pivotal role in evaluating the climate change impacts on crop yield or productivity. This study was aimed to predict the plausible variations in the wheat yield for future climatic trends so that possible mitigation strategies could be explored. For this purpose, Aquacrop model v. 4.0 was employed to simulate the wheat yield under present and future climatology of the largest agricultural province of Punjab in Pakistan. The data related to crop phenology, management and yield were collected from the experimental plots to calibrate and validate the model. The future climate projections were statistically downscaled from five general circulation models (GCMs) and compared with the base line climate from 1980 to 2010. The model was fed with the projected climate to simulate the wheat yield based on the RCP (representative concentration pathways) 4.5 and 8.5. Under the worst, most likely future scenario of temperature rise and rainfall reduction, the crop yield decreased and water footprint, especially blue, increased, owing to the elevated irrigation demands due to accelerated evapotranspiration rates. The modeling results provided in this study are expected to provide a basic framework for devising policy responses to minimize the climate change impacts on wheat production in the area.

• The Korean Journal of Applied Statistics
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• v.28 no.4
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• pp.643-661
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• 2015

Korea Teachers Pension (private school pension) is a mandatory pension and a social security system for private school teachers to ensure the stability of subscribers by a supplying pension when they (and their dependents) face future economic risk due to retirement or death. Therefore, the Teachers Pension must provide stability and sustainability in regards to adequacy of income and to function as a pension. However, the Government Employees Pension System (GEPS) of Korea (the most representative special occupation pension) recorded a fiscal deficit in 2001 and with an accumulated deficit that is expected to grow; subsequently, various plans for the reform of GEPS have been actively discussed. The Korea Teachers Pension system is based on the GEPS scheme and is not free from the GEPS discussions on reforms of national pension. The current system for the Teachers Pension needs to be improved because it is expected to be depleted within the next 30 years due to low fertility and an aging population in Korea. This study discusses existing Teachers Pension schemes problems and suggests a projection method and revised plans to improve it. We use long-term financial projections of the Teachers Pension to estimate the fund exhaustion point and the minus balance of the financial scale as well as analyze the supply-demand burden structure that reflects the future population structure to propose Teachers Pension reforms that will improve stability and adequacy.

• Journal of Korea Water Resources Association
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• v.49 no.2
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• pp.107-119
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• 2016

Since future climate scenarios indicate that extreme precipitation events will intensity, probable maximum precipitations (PMPs) without being taken climate change into account are very likely to be underestimated. In this study future PMPs in accordance with the variation of future rainfall are estimated. The hydro-meteorologic method is used to calculate PMPs. The orographic transposition factor is applied in place of the conventional terrain impact factor which has been used in previous PMPs estimation reports. Future DADs are indirectly obtained by using bias-correction and moving-averaged changing factor method based on daily precipitation projection under KMA RCM (HEDGEM3-RA) RCP 8.5 climate change scenario. As a result, future PMPs were found to increase and the spatially-averaged annual PMPs increase rate in 4-hour and $25km^2$ was projected to be 3 mm by 2045. In addition, the increased rate of future PMPs is growing increasingly in the future, but it is thought that the uncertainty of estimating PMPs caused by future precipitation projections is also increased in the distant future.