• KDI Journal of Economic Policy
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• v.41 no.4
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• pp.67-99
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• 2019

This paper, focusing on the renewable portfolio standard (RPS), evaluates alternative renewable energy policies. We propose a tractable equilibrium model which provides a structural representation of Korea's electricity market, including its energy settlement system and renewable energy certificate (REC) transactions. Arbitrage conditions are used to define the core value of REC prices to identify relevant competitive equilibrium conditions. The model considers R&D investments and learning effects that may affect the development of renewable energy technologies. The model is parameterized to represent the baseline scenario under the currently scheduled RPS reinforcement for a 20% share of renewable generation, and then simulated for alternative scenarios. The result shows that the reinforcement of the RPS leads to higher welfare compared to weakening it as well as repealing it, though there remains room to enhance welfare. It turns out that subsidies are welfare-inferior to the RPS due to financial burdens and that reducing nuclear power generation from the baseline yields lower welfare by worsening environmental externalities.

• Journal of Families and Better Life
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• v.22 no.5
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• pp.303-318
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• 2004

This study was conducted to develop and propose a model for an organizational system and management strategies for Healthy Families Centers. As baseline research, the organization of comparable institutions such as the Social Welfare Center, Women's Development Center, Elderly Welfare Center, Child Welfare Center, and Childcare Information Center was analyzed. Based on the results of baseline research and the draft version of Healthy Families Act, this study proposed a management model for Healthy Families Centers. This proposed model suggests the city, county, and district level centers to be organized with three divisions: 1. family counseling team, 2. family education team, and 3. family life team. Concrete assignments for the teams are also proposed. Finally, a networking system for more effective management of the healthy families centers was also proposed.

• Journal of IKEEE
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• v.24 no.4
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• pp.1011-1016
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• 2020

We propose a framework called Stacked Gated Recurrent Unit - Infrequent Residual Analysis (SG-IRA) that detects anomalies in time-series data that can be trained on streams of raw sensor data without any pre-labeled dataset. To enable such unsupervised learning, SG-IRA includes an estimation model that uses a stacked Gated Recurrent Unit (GRU) structure and an analysis method that detects anomalies based on the difference between the estimated value and the actual measurement (residual). SG-IRA's residual analysis method dynamically adapts the detection threshold from the population using frequency analysis, unlike the baseline model that relies on a constant threshold. In this paper, SG-IRA is evaluated using the industrial control systems (ICS) datasets. SG-IRA improves the detection performance (F1 score) by 5.9% compared to the baseline model.

• Journal of The Korean Society of Agricultural Engineers
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• v.53 no.6
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• pp.75-84
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• 2011

The objective of this study is to evaluate the hydrologic impacts of climate and land use changes in a rural small watershed. HadCM3 (Hadley Centre Coupled Model, ver.3) A2 scenario and LARS-WG (Long Ashton Research Station - Weather Generator) were used to generate future climatic data. Future land use data were also generated by the CA-Markov (Cellular Automata-Markov) method. The Soil and Water Assessment Tool (SWAT) model was used to evaluate hydrologic impacts. The SWAT model was calibrated and validated with stream flow measured at the Baran watershed in Korea. The SWAT model simulation results agreed well with observed values during the calibration and validation periods. In this study, hydrologic impacts were analyzed according to three scenarios: future climate change (Scenario I), future land use change (Scenario II), and both future climate and land use changes (Scenario III). For Scenario I, the comparison results between a 30-year baseline period (1997~2004) and a future 30-year period (2011~2040) indicated that the total runoff, surface runoff, lateral subsurface runoff, groundwater discharge, and evapotranspiration increased as precipitation and temperature for the future 30-year period increased. The monthly variation analysis results showed that the monthly runoff for all months except September increased compared to the baseline period. For Scenario II, both the total and surface runoff increased as the built-up area, including the impervious surface, increased, while the groundwater discharge and evapotranspiration decreased. The monthly variation analysis results indicated that the total runoff increased in the summer season, when the precipitation was concentrated. In Scenario III, the results showed a similar trend to that of Scenario II. The monthly runoff for all months except October increased compared to the baseline period.

• The Korean Journal of Applied Statistics
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• v.26 no.6
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• pp.923-932
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• 2013

This paper proposes a method to predict the number of foodborne disease outbreaks by microbes. The weekly data of food poisoning occurrences by microbes in Korea contain many zero-valued observations and have dependency between outbreaks. In order to model both phenomena, the number of food poisonings is predicted by an autoregressive model and the probabilities of food poisoning occurrences by microbes (given the total of food poisonings) are estimated by the baseline category logit model. The predicted number of foodborne disease outbreaks by a microbe is obtained by multiplying the predicted number of foodborne disease outbreaks and the estimated probability of the food poisoning by the corresponding microbe. The mean squared error and the mean absolute value error are evaluated to compare the performances of the proposed method and the zero-inflated model.

• Korean Journal of Construction Engineering and Management
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• v.24 no.3
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• pp.3-11
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• 2023

This research examines the need for a quantitative and objective method of calculating baseline productivity in the construction industry, which is known for its high volatility in performance and productivity. The existing literature's baseline productivity calculation methods rely heavily on subjective criteria, limiting their effectiveness. Additionally, data collection methods such as the "Five-minute Rating" are costly and time-consuming, making it challenging to collect detailed data at construction sites. To address these issues, this study proposes an objective baseline calculation method using unimpacted productivity BP, a work check sheet to systematically record detailed data, and a data collection and utilization process that minimizes cost and time requirements. This paper also suggests using unimpacted productivity BP and comparative analysis to address the objectivity and reliability issues of existing baseline productivity calculation methods.

• Journal of Climate Change Research
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• v.7 no.3
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• pp.341-349
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• 2016

This study is intended to set a greenhouse gas emission scenario based on green remodeling pilot project (Annex building of Seoul Customs Office) using LEAP model, a long-term energy plan analysis model, to calculate the energy saving and greenhouse gas emission till year 2035 as well as to analyze the effect of electric power saving cost. Total 4 scenarios were made, Baseline scenario, assuming the past trend is to be maintained in the future, green remodeling scenario, reflecting actual green remodeling project of Seoul Customs Office, behavior improvement and renewable energy supply, and Total scenario. According to the analysis result, the energy demand in 2035 of Baseline scenario was 6.1% decreased from base year 2013, that of green remodeling scenario was 17.5%, that of behavior improvement and renewable energy supply scenario was 21.1% and that of total scenario was 27.3%. The greenhouse emission of base year 2013 was $878.2tCO_2eq$, and it was expected $826.3tCO_2eq$, approx. 5.9% reduced, in 2035 by Baseline scenario. the cumulative greenhouse gas emission saving of the analyzing period were $-26.5tCO_2eq$ by green remodeling scenario, $2.8k\;tCO_2eq$ by behavior improvement and renewable energy supply scenario, and $2.0k\;tCO_2eq$ by total scenario. In addition the effect of electricity saving cost through energy saving has been estimated, and it was approx. 634 million won by green remodeling scenario and appro. 726 million won by behavior improvement and renewable energy supply scenario. So it is analyzed that of behavior improvement and renewable energy supply scenario would be approx. 12.7% higher than that of green remodeling scenario.

• The Journal of the Acoustical Society of Korea
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• v.40 no.6
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• pp.578-586
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• 2021

We propose a semi-supervised learning method based on Variational AutoEncoder (VAE) and Unsupervised Data Augmentation (UDA) to improve the performance of an end-to-end speech recognizer. In the proposed method, first, the VAE-based augmentation model and the baseline end-to-end speech recognizer are trained using the original speech data. Then, the baseline end-to-end speech recognizer is trained again using data augmented from the learned augmentation model. Finally, the learned augmentation model and end-to-end speech recognizer are re-learned using the UDA-based semi-supervised learning method. As a result of the computer simulation, the augmentation model is shown to improve the Word Error Rate (WER) of the baseline end-to-end speech recognizer, and further improve its performance by combining it with the UDA-based learning method.

• Journal of Positioning, Navigation, and Timing
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• v.4 no.2
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• pp.79-85
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• 2015

Existing Differential GPS (DGPS) pseudorange correction (PRC) generation techniques based on a virtual reference station cannot effectively assign a weighting factor if the baseline distance between a user and a reference station is not long enough. In this study, a virtual reference station DGPS PRC generation technique was developed based on an enhanced inverse distance weighting method using an exponential function that can maximize a small baseline distance difference due to the dense arrangement of DGPS reference stations in South Korea, and its positioning performance was validated. For the performance verification, the performance of the model developed in this study (EIDW) was compared with those of typical inverse distance weighting (IDW), first- and second-order multiple linear regression analyses (Planar 1 and 2), the model of Abousalem (1996) (Ab_EXP), and the model of Kim (2013) (Kim_EXP). The model developed in the present study had a horizontal accuracy of 53 cm, and the positioning based on the second-order multiple linear regression analysis that showed the highest positioning accuracy among the existing models had a horizontal accuracy of 51 cm, indicating that they have similar levels of performance. Also, when positioning was performed using five reference stations, the horizontal accuracy of the developed model improved by 8 ~ 42% compared to those of the existing models. In particular, the bias was improved by up to 27 cm.

• Journal of Preventive Medicine and Public Health
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• v.53 no.4
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• pp.275-284
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• 2020

Objectives: Police officers may be at a greater risk for cardiovascular disease (CVD) than the general population due to their highstress occupation. This study evaluated how an educational program based on the health belief model (HBM) may protect police officers from developing CVD. Methods: In this single-group experimental study, 58 police officers in Iran participated in a 5-week intervention based on HBM principles. Outcomes included changes in scores on an HBM scale, time spent on moderate to vigorous physical activity (International Physical Activity Questionnaire), body mass index (BMI), blood lipid profile, blood glucose, and blood pressure. The intervention consisted of 5 HBM-based educational sessions. Follow-up was conducted at 3 months post-intervention. The paired t-test was used to examine differences between baseline and follow-up scores. Results: All aspects of the HBM scale improved between baseline and follow-up (p<0.05), except the cues to action subscale. Self-efficacy and preventive behaviors improved the most. BMI decreased from 26.7±2.9 kg/㎡ at baseline to 25.8±2.4 kg/㎡ at follow-up. All components of the lipid profile, including triglycerides, cholesterol, high-density lipoprotein, and low-density lipoprotein, showed significant improvements post-intervention. Blood glucose and blood pressure also decreased, but not significantly. Nearly 25% of participants who were not physically active at baseline increased their physical activity above or beyond the healthy threshold. Conclusions: A relatively brief educational intervention based on HBM principles led to a significant improvement in CVD risk factors among police officers. Further research is needed to corroborate the effectiveness of this intervention.