• Journal of the Korean Society of Industry Convergence
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• v.25 no.6_3
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• pp.1135-1145
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• 2022

Due to increase in concerns related to the climate change, state-wide promotion of the carbon neutrality has been in progress thus far. Smart City could be one of the measures as the initiative to mitigate the missions process. The primary purpose of Smart City can be summarized to be maximization of the social net-beneift to be returned for the local citizens and derivation of the optimal pattern of the energy consumption could belong to one of the elements included in the net-benefit. Currently, the energy consumption by the buildings has been determined to be responsible for the greatest consumption among the sectors considered to be energy-intensive. Moreover, considering the fact that the consumption by operations of HVAC is responsible for nearly 40% in the commercial buildings, it is virtually not possible to optimize schedules for the energy consumption with considerable deliverables from the perspective of the urban planners. Thus, the methods to implement the optimal schedules for the HVAC commissioned with the OHUs were concluded to be the suitable candidate resources for the simulation by EnergyPlus capable of monitoring the thermal changes in each subject space in the present research.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.2
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• pp.131-138
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• 2023

Globally, the eco-friendly industry is developing due to the climate crisis. Electric vehicles are an eco-friendly industry that is attracting attention as it is expected to reduce carbon emissions by 30~70% or more compared to internal combustion engine vehicles. As electric vehicles become more popular, charging stations have become an important factor for purchasing electric vehicles. Recent research is using artificial intelligence to identify local demand for charging stations and select locations that can maximize economic impact. In this study, in order to contribute to the improvement of the performance of the electric vehicle charging station demand prediction model, nationwide data that can be used in the artificial intelligence model was defined and a pre-processing technique was proposed. In addition, a preprocessor, artificial intelligence model, and service web were implemented for real charging station demand prediction, and the value of data as a location selection factor was verified.

• Journal of Animal Reproduction and Biotechnology
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• v.37 no.4
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• pp.298-302
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• 2022

South Korea has a temperate climate with four distinct seasons. However, summers are extremely hot and humid, which negatively affects industrial animal production. Hanwoo are native cattle that have traditionally been raised in the natural environment of Korea. The present study investigated the effects of birth and lactation season on the birth and weaning weights of Hanwoo calves. Data were collected from 100 local breeding farms between 2016 and 2021. A total of 56,970 (males, 29,530; females, 27,440) Hanwoo calves were classified according to sex or birth and weaning season (March-May, spring; June-August, summer; September-November, fall; and December-February, winter). The birth weight of Hanwoo calves differed according to the birth season. As such, birth weight of the summer-born calves was the lowest. Additionally, the 90-day weaning weight was positively correlated with birth weight. Interestingly, however, the 90-day weaning weight was not related to the birth season but was related to the 2-month seasonal effect during the lactation period. Furthermore, the 90-day weaning weight was the lowest during the summer lactation period. In the beef cattle industry, daily weight gain is an important economic characteristic related to feed efficiency and growth. Our findings will contribute the management of Hanwoo cattle and analysis of changes in economic characteristics due to high temperatures.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.272-275
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• 2009

Carbon finance is the investment in Greenhouse Gas (GHG) emission reduction projects in developing countries and countries with economies in transition within the framework of the Kyoto Protocol's Clean Development Mechanism (CDM) or Joint Implementation (JI) and with creation of financial instruments, i.e., carbon credits, which are tradable in carbon market. The additional revenue generated from carbon credits will increase the bankability of projects by reducing the risks of commercial lending or grant finance. Meantime, it has also demonstrated numerous opportunities for collaborating across sectors, and has served as a catalyst in bringing climate issues to bear in projects relating to rural electrification, renewable energy, energy efficiency, urban infrastructure, waste management, pollution abatement, forestry, and water resource management. Establishing additionality is essential for successful CDM project development. One of the key steps is the investment analysis. As guided by UNFCCC, financial indicators such as IRR, NPV, DSCR etc are most commonly used in both Option II & Option III. However, economic indicator such as Economic Internal Rate of Return(EIRR) are often overlooked in Option III even it might be more suitable for the project. This could be due to the difficulties in economic analysis. Although Asian Development Bank(ADB) has given guidelines in evaluating EIRR, there are still large amount of works have to be carried out in estimating the economic, financial, social and environmental benefits in the host country. This paper will present a case study of a CDM development of a 18 MW hydro power plant with carbon finance option in central Vietnam. The estimation of respective factors in EIRR, such as Willingness to Pay(WTP), shadow price etc, will be addressed with the adjustment to Vietnam local provincial factors. The significance of carbon finance to Vietnam renewable energy development will also be addressed.

• Journal of Technology Innovation
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• v.30 no.4
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• pp.29-56
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• 2022

This study is a review paper on the contents and policy direction of the 'Transformative regional innovation policy'. The transformative regional innovation policy is a policy that develops countermeasures against climate crisis, aging, and polarization with a vision of system transformation from the perspective of local residents. The structure of the study is as follows. First, it deals with the characteristics of transformative regional innovation policy theory, which is distinguished from existing regional innovation policies. Next, studies related to major elements of transformative regional innovation policies, types of system transformation, and industrial formation are reviewed. The elements that differentiate the transformative regional innovation policy from existing policies are summarized and issues to be addressed in order to develop future discussions are drawn.

• KNOM Review
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• v.22 no.3
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• pp.25-30
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• 2019

For meteorological applications, meaningful results must be derived and provided within time and resource limits. Forecasts through numerous historical data are time-consuming and still have resource limitations in the case of disaster safety-related analyses/predictions such as local typhoon forecasts. Suitable forecasts should be provided without any problems caused by limited physical environmental conditions and when results are to be drawn under time constraints, such as typhoon forecasts and forecast services for flooded areas by road. In this paper, we analyze the application of weather and climate forecasting to provide a suitable forecasting service in both temporal and resource conditions. Through the analysis of execution time according to mesh sizes, it was confirmed that a mesh adjustment can cope with the case of the temporal constraint. In addition, by analyzing the execution time through memory resource control, we confirmed the minimum resource condition that does not affect the performance and the resource usage pattern of the application through the swap and mlock analysis.

• Animal Bioscience
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• v.36 no.7
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• pp.1067-1074
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• 2023

Objective: Better feed efficiency can be achieved by selecting rabbit genotypes with lower residual feed intake (RFI) under high ambient temperatures. Methods: Two genotypes of rabbits (Jabali, Saudi local breed and imported, Spanish V-line) were used to derive RFI and to investigate the relationship between RFI and productive traits. In total, 250 animals (125 each) were housed in individual wire mesh cages in a semi-closed rabbitry. Growth performance, feed criteria, carcass evaluation, biochemical blood analysis, and immune responses were determined. Results: Superiority in growth performance, feed efficiency, carcass characteristics, and cellular immunity was recorded in the Jabali breed compared to the V-line genotype. According to regression analysis, a significant effect of daily body weight gain was found, upon computing the expected feed intake in both genotypes. Moreover, mid-body weight^0.75 had a significant effect only in the Jabali breed. Positive correlation coefficients between RFI and dry matter feed intake or feed conversion ratio were found. The same trend in this relationship between RFI and productive traits was observed in some cases for both genotypes. An opposite trend in correlations was observed in the studied genotypes for some traits. Conclusion: The results suggest that the relationship between RFI and productive traits must be taken into consideration in rabbit breeding programs under the prevailing environment. However, further studies are required to investigate the effect of rabbit genotype and environmental factors on computing RFI.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.35-35
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• 2021

최근 우리나라는 기후변화로 인한 이상기후 현상으로 호우 및 홍수 등에 의한 수재해를 예방하기 위한 설계빈도 적용방안 개발이 필요하다. 과거 지방하천의 일률적인 설계빈도의 적용 및 간접·주관적인 하천의 중요도와 지역특성에 대한 등급의 결정은 하천사업의 효율적 관리와 수행에 있어서 저해요소로 작용되어 왔다. 또한, 미래 기후변화 시나리오에 따라 하천의 중요도 및 계획 규모가 적절히 적용되어야 한다. 본 연구는 충청남도의 492개 지방하천에 대하여 유역특성(유역면적, 형상계수), 하천특성(하도경사, 수계 및 하천차수, 배수영향 구간), 이상강우 특성(이상강우 발생빈도, 시가화 침수면적)에 대한 현재 설계빈도에 대한 적절성을 평가하였다. 설계빈도에 대한 정량적 추정은 베이즈 이론을 활용하여 가중치를 산정한 후 최적분포형을 선정하였다. 최적분포형의 중앙값을 일반적인 지방하천의 설계빈도인 80년 빈도로 설정하고 상·하위 0.5%가 각각 100년, 50년 빈도로 가정하여 492개 지방하천을 평가하였다. 이상강우의 발생빈도와 시가화 침수면적에 따라 하천의 설계빈도가 높게 산정되는 것으로 분석되었다. 미래 기후변화 시나리오를 적용할 경우 현재 설계빈도(설계수명)에 대한 시나리오별 미래 재현기간을 산정하여 미래 설계빈도에 대한 위험도를 평가하였다. 13개 기후변화 시나리오의 대표농도경로 4.5와 8.5를 분석한 결과, 평균 3.2%, 12.8%의 위험도가 증가하는 것으로 분석되었다. 본 연구결과는 객관적인 지방하천의 적정 설계빈도 결정방안을 제시하였으며, 미래 계획홍수량 증가로 인하여 효율적인 토지이용이 제한될 것으로 예상됨에 따라 하천사업의 예산절감 및 우선순위 결정 등에 활용 가능할 것으로 판단된다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.2B
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• pp.237-248
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• 2008

Precipitation variability in Korea is mainly influenced by climate circulation such as sea surface temperature, not a local convection. Therefore, this study investigates relationship between monthly precipitation of 61 station observed by Korea Meteorological Administration and global sea surface temperatures (SSTs). The main components of monthly precipitation in Korea are extracted by a method which consists of the principal analysis combined with the cluster analysis, to examine the correlation between monthly rainfalls and SSTs. The relationships between main components of monthly precipitation and SSTs exists in Pacific Ocean. At the result of Wavelet Transform analysis, The 2-4 year band have a strong wavelet power spectrum and the low frequency. the correlation coefficient between low frequency components of monthly rainfalls and SSTs calculated bigger then correlation coefficient between main components and SSTs. Hence, these results propose a prediction possibility of monthly precipitations using the varition of SSTs.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.2
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• pp.99-107
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• 2023

Recently, the abnormal weather events and crop damages occurred frequently likely due to climate change. The importance of meteorological data in agricultural research is increasing. Researchers can download weather observation data by accessing the websites provided by the KMA (Korea Meteorological Administration) and the RDA (Rural Development Administration). However, there is a disadvantage that multiple inquiry work is required when a large amount of meteorological data needs to be received. It is inefficient for each researcher to store and manage the data needed for research on an independent local computer in order to avoid this work. In addition, even if all the data were downloaded, additional work is required to find and open several files for research. In this study, data collected by the KMA and RDA were uploaded to GitHub, a remote storage service, and a package was created that allows easy access to weather data using Python. Through this, we propose a method to increase the accessibility and usability of meteorological data for agricultural personnel by adopting a method that allows anyone to take data without an additional authentication process.