• Journal of Korea Water Resources Association
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• v.55 no.spc1
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• pp.1295-1303
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• 2022

As the role of water distribution networks (WDNs) becomes more important, identifying abnormal events (e.g., pipe burst) rapidly and accurately is required. Since existing approaches such as field equipment-based detection methods have several limitations, model-based methods (e.g., machine learning based detection model) that identify abnormal events using hydraulic simulation models have been developed. However, no previous work has examined the impact of data uncertainties on the results. Thus, this study compares the effects of measurement error-induced pressure data uncertainty in WDNs. An artificial neural network (ANN) is used to predict nodal pressures and measurement errors are generated by using cumulative density function inverse sampling method that follows Gaussian distribution. Total of nine conditions (3 input datasets × 3 output datasets) are considered in the ANN model to investigate the impact of measurement error size on the prediction results. The results have shown that higher data uncertainty decreased ANN model's prediction accuracy. Also, the measurement error of output data had more impact on the model performance than input data that for a same measurement error size on the input and output data, the prediction accuracy was 72.25% and 38.61%, respectively. Thus, to increase ANN models prediction performance, reducing the magnitude of measurement errors of the output pressure node is considered to be more important than input node.

• Journal of Animal Science and Technology
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• v.52 no.5
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• pp.413-426
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• 2010

This study was conducted to investigate the effects on fermentation characteristics of rumen microorganism by different types and levels of lignosulfonate treated soybean meal (LSBM) in in vitro test and rumen simulation continuous culture (RSCC) system in dairy cows. The experiment I was control and 12 treatments (each with 3 replications) in vitro test to demonstrate composition of different types of treatments with lignosulfonate (Desulfonate, Na, Ca and solution) and levels (2, 4 and 8%) of soybean meal in the dairy cow diet. LSBM source treatments in the dairy cow diet showed pH value, $NH_3$-N concentration and total VFA concentration lower than control at all levels and incubation times (p<0.05). Dry matter digestibility of LSBM source treatments showed lower than control (p<0.05). Gas production and rumen microbial synthesis was decreased by rumen microbial fermentation for incubation times. Undegradable protein (UDP) concentration of all LSBM treatments was decreased for incubation times, and significantly higher than control (p<0.05). In the experiment II compared diets of the control, LSBM Na 2%, LSBM Sol 2%, which are high performance to undegradable protein (UDP) concentration experiment I in vitro test, and heated treatment lignosulfonate (LSBM Heat) 2% in the dairy cow diet from four station RSCC system ($4{\times}4$ Latin square). A rumen microbial fermentation characteristic was stability during 12~15 days of experimental period in all treatments. The pH value of LSBM treatments was higher than control treatment (p<0.05). The $NH_3$-N concentration, VFA concentration and rumen microbial synthesis of LSBM treatments were lower than control (p<0.05). The undegradable protein (UDP) showed LSBM Na 2% (45.28%), LSBM Sol 2% (43.52%) and LSBM Heat 2% (43.49%) higher than control (41.55%), respectively (p<0.05). Those experiments were designed to improve by-pass protein of diet and milk protein in the dairy cows. We will conduct those experiments the in vivo test by LSBM treatments in dairy cows diet.

• Journal of Korean Society of Forest Science
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• v.89 no.5
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• pp.655-665
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• 2000

Taking account of the structural variation on species composition by topography, the successional trends were comparatively analyzed for the three topographic positions (valley, mid-slope, and ridge) in the natural deciduous forest of Mt. Chumbong area. The analysis was based upon the subsequent process of generation replacement by understory saplings and seedlings over the overstory trees which will be eventually fallen down. This study adopted the plot sampling method, establishing twenty $20m{\times}20m$ quadrats and collecting vegetation and site data on each different topographic position. The transition matrix model, which was modified from the mathematical theory of Markov chain, was employed to analyze the successional trends and thereafter to predict the overstory species composition in the future for each different topographic position. In valley, the simulation indicated the remarkable decrease in the proportion of species composition of present dominants Quercus mongolica and Fraxinus mandshurica from current 23% and 21% to around 4% of each at the steady state, which is predicted to take less than 200 years. On the other hand, the proportion of such species as Abies holophylla, Acer mono, Tilia amurensis, and Ulmus laciniata will increase at the steady state. In mid-slope, the result showed the remarkable decrease in the proportion of Juglans mandshurica, Kalopanax pictus, and Tilia amurensis from current 15%, 8%, and 15% to 2%, 1%, and 5%, respectively, at steady state predicted to take more than 250 years. In ridge, the current dominant Quercus mongolica was predicted to be decreased dramatically from 58% to 8% at steady state which could be achieved about 200 years. On the contrary, the proportion of Acer mono and Tilia amurensis will be increased from current 4% and 3% to more than 20% and 40%, respectively, at the steady state. Overall results suggested that the study forest is more likely seral rather than climax community. Even though a lot of variation is inevitable due to various kinds of site and vegetation development, the study forest is considered to be more than 200 years away from the steady state or climax in terms of overstory species composition.

• Journal of Environmental Impact Assessment
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• v.23 no.5
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• pp.379-392
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• 2014

This study was performed to predict the future climate envelope of Pinus pumila, a subalpine plant and a Climate-sensitive Biological Indicator Species (CBIS) of Korea. P. pumila is distributed at Mt. seorak in South Korea. Suitable habitat were predicted under two alternative RCPscenarios (IPCC AR5). The SDM used for future prediction was a Maxent model, and the total number of environmental variables for Maxent was 8. It was found that the distribution range of P. pumila in the South Korean was $38^{\circ}7^{\prime}8^{{\prime}{\prime}}N{\sim}38^{\circ}7^{\prime}14^{{\prime}{\prime}}N$ and $128^{\circ}28^{\prime}2^{{\prime}{\prime}}E{\sim}128^{\circ}27^{\prime}38^{{\prime}{\prime}}E$ and 1,586m~1,688m in altitude. The variables that contribute the most to define the climate envelope are altitude. Climate envelope simulation accuracy was evaluated using the ROC's AUC. The P. pumila model's 5-cv AUC was found to be 0.99966. which showed that model accuracy was very high. Under both the RCP4.5 and RCP8.5 scenarios, the climate envelope for P. pumila is predicted to decrease in South Korea. According to the results of the maxent model has been applied in the current climate, suitable habitat is $790.78km^2$. The suitable habitats, are distributed in the region of over 1,400m. Further, in comparison with the suitable habitat of applying RCP4.5 and RCP8.5 suitable habitat current, reduction of area RCP8.5 was greater than RCP4.5. Thus, climate change will affect the distribution of P. pumila. Therefore, governmental measures to conserve this species will be necessary. Additionally, for CBIS vulnerability analysis and studies using sampling techniques to monitor areas based on the outcomes of this study, future study designs should incorporate the use of climatic predictions derived from multiple GCMs, especially GCMs that were not the one used in this study. Furthermore, if environmental variables directly relevant to CBIS distribution other than climate variables, such as the Bioclim parameters, are ever identified, more accurate prediction than in this study will be possible.

• Health Policy and Management
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• v.34 no.3
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• pp.334-346
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• 2024

Background: Research on the link between subjective health and unmet healthcare needs is limited. This study examines whether experiences of subjective healthcare needs and unmet needs are related to subjective health in South Korea, where the rate of poor subjective health is notably high. Methods: This analysis utilized data from the Korea Health Panel (2014-2018), incorporating 68,930 observations from 16,535 adults aged 19 or older. The dependent variable, subjective health, was dichotomized into poor (bad or very bad) and non-poor (fair, good, or very good) categories. The primary variables of interest were the experiences of subjective healthcare needs and unmet needs, while control variables included 14 socio-demographic, health, and functional characteristics. The study employed population proportion analysis and multivariable two-level binary logistic regression analysis for each gender, accounting for the complex sampling design. Results: In 2018, the rate of reporting poor health was 8.7% (95% confidence interval [CI], 8.0%-9.5%) for men and 14.7% (95% CI, 13.8%-15.6%) for women. For both genders, compared to individuals whose healthcare needs were met, those without healthcare needs were less likely to report poor subjective health (adjusted odds ratio [AOR], 0.58; 95% CI, 0.39-0.86 for men; AOR, 0.59; 95% CI, 0.37-0.93 for women). Conversely, individuals whose healthcare needs were not met were more likely to report poor subjective health (AOR, 2.31; 95% CI, 2.01-2.65 for men; AOR, 2.19; 95% CI, 1.98-2.43 for women). A policy simulation indicated that reducing the experience of subjective healthcare needs would be approximately 5 times more effective in reducing poor subjective health than a policy focused on reducing the experience of unmet needs. Conclusion: South Korea must make significant efforts to reduce the deterioration of subjective health and promote appropriate healthcare utilization. To achieve this, a set of policies is recommended to address subjective healthcare needs. These policies should include (1) prompting individuals to proactively manage their own health, (2) providing primary healthcare similar to that in advanced countries, (3) ensuring the healthcare delivery system operates effectively, (4) decentralizing the healthcare management system, and (5) reducing the likelihood of people being misled into thinking they have a healthcare need.