• Journal of The Korean Society of Grassland and Forage Science
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• v.41 no.1
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• pp.35-40
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• 2021

This study was conducted to evaluate the forage productivity and feed value of Sasa borealis (S. borealis) using growing black goats(S. borealis) in order to improve the utilization of S. borealis and to help mitigate the problem of reduced plant species diversity caused by S. borealis in Hanlla Mountain. One control and three treatments were made by the level of addition of S. borealis silage to the TMR feed. T1(10%), T2(20%), and T3(30%) treatments showed more daily weight gains than control group. Feed conversion ratio of T2 is 4.4g, which is significantly lower than control(P<0.05). The nitrogen retention in the control, which had relatively high dry matter intake, was 12.5g, which was significantly higher than that of T3. Sasa. borealis silage is considered to be able to use as a forage source for black goats, and if it is fed in an appropriate amount, it is considered that it will help improve livestock productivity, such as weight gain and feed conversion ratio.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.1
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• pp.68-81
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• 2021

The agricultural ecosystem is one of the major sources of greenhouse gas (GHG) emissions. In order to search for climate change adaptation options which mitigate GHG emissions while maintaining crop yield, it is advantageous to integrate multiple models at a high spatial resolution. The objective of this study was to develop a tool to support integrated assessment of climate change impact b y coupling the DSSAT model and the DNDC model. DNDC Regional Input File Tool(DRIFT) was developed to prepare input data for the regional mode of DNDC model using input data and output data of the DSSAT model. In a case study, GHG emissions under the climate change conditions were simulated using the input data prepared b y the DRIFT. The time to prepare the input data was increased b y increasing the number of grid points. Most of the process took a relatively short time, while it took most of the time to convert the daily flood depth data of the DSSAT model to the flood period of the DNDC model. Still, processing a large amount of data would require a long time, which could be reduced by parallelizing some calculation processes. Expanding the DRIFT to other models would help reduce the time required to prepare input data for the models.

• Korean Journal of Remote Sensing
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• v.36 no.6_3
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• pp.1635-1641
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• 2020

Air pollution is one of the most severe threats to society globally due to the rapid expansion of urbanization and industrialization. Particularly, particulate matter (PM) pollution was recently designated as a social disaster by the Korean government because of increases in public concerns and the accumulation of scientific evidence that links high levels of PM2.5 (PM smaller than 2.5 ㎛ in diameter) to a long list of adverse health effects. Atmospheric PM concentrations can also affect the indoor PM levels to which people are exposed most of the time. Thus, understanding the characteristics of indoor and ambient PM pollution based on measurements, model simulations, risk assessments, and management technologies is inevitable in establishing effective policies to mitigate social, economic, and health costs incurred by PM pollution. In this special issue, we introduce several interesting studies concerning indoor and outdoor PM from the perspective of monitoring, assessment, and management being conducted by i-SEED (School of Integrated Science for Sustainable Earth & Environmental Disaster at Pukyong National University) and SPMC (School Particulate Matter Center for Energy and Environmental Harmonization). We expect that this special issue can improve our understanding of the current and future of indoor and outdoor PM pollution, integrating the results from interdisciplinary research groups from various academic fields.

• Journal of Wetlands Research
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• v.23 no.3
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• pp.260-276
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• 2021

Wetlands are constantly affected by internal and external environments that make up the wetlands, and these effects make wetlands change. East Asia countries where about 15% of Ramsar's registered wetlands are located, is valuable conservation area due to various wetland types and biodiversity. However, due to climate change and other factors, the total area of wetlands has been reduced and biodiversity have been damaged. To mitigate these problems and to manage wetlands efficiently, it is important to identify the factors that change wetlands and to identify how each factor affects them. In this study, we conducted a wetland-related literature analysis in East Asia to derive factors that affect the changes in wetlands, and analyzed the relationships among the factors. Finally we presented research directions considering wetland change factors. In most of the East Asia countries, it was found that there is deficiency in research studies about extraction in direct factors and water-energy infrastructure, tourism & recreation in indirect factors. Also, we presented the necessity for future research using the result between connectivity & relationship analysis and indirect drivers of change and their influence on direct drivers of change. The results of this study could contribute to the establishment of an R&D cooperation system in East Asia region and strengthen wetland management.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.415-423
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• 2021

Recently, an R-based point time series data validation system has been established for the statistical post processing and improvement of the National Center for AgroMeteorology-Land Atmosphere Modeling Package (NCAM-LAMP) medium-range prediction data. The time series verification system was used to compare the NCAM-LAMP with the AWS observations and GDAPS medium-range prediction model data operated by Korea Meteorological Administration. For this comparison, the model latitude and longitude data closest to the observation station were extracted and a total of nine points were selected. For each point, the characteristics of the model prediction error were obtained by comparing the daily average of the previous prediction data of air temperature, wind speed, and hourly precipitation, and then we tried to improve the next prediction data using Support Vector Machine( SVM) method. For three months from August to October 2017, the SVM method was used to calibrate the predicted time series data for each run. It was found that The SVM-based correction was promising and encouraging for wind speed and precipitation variables than for temperature variable. The correction effect was small in August but considerably increased in September and October. These results indicate that the SVM method can contribute to mitigate the gradual degradation of medium-range predictability as the model boundary data flows into the model interior.

• Clean Technology
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• v.28 no.1
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• pp.9-17
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• 2022

Electrochemical carbon dioxide (CO₂) reduction technology, one of the promising solutions for climate change, can convert CO₂, a representative greenhouse gas (GHG), into valuable base chemicals using electric energy. In particular, carbon monoxide (CO), among various candidate products, is attracting much attention from both academia and industry because of its high Faraday efficiency, promising economic feasibility, and relatively large market size. Although numerous previous studies have recently analyzed the GHG reduction potential of this technology, the assumptions made and inventory data used are neither consistent nor transparent. In this study, a comparative life cycle assessment was carried out to analyze the potential for reducing GHG emissions in the electrochemical CO production process in a more transparent way. By defining three different system boundaries, the global warming impact was compared with that of a fossil fuel-based CO production process. The results confirmed that the emission factor of electric energy supplied to CO₂-electrolyzers should be much lower than that of the current national power generation sector in order to mitigate GHG emissions by replacing conventional CO production with electrochemical CO production. Also, it is important to disclose transparently inventory data of the conventional CO production process for a more reliable analysis of GHG reduction potential.

• Environmental and Resource Economics Review
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• v.30 no.4
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• pp.607-625
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• 2021

The objective of this study is to estimate the relationship between CO₂ emissions and both nuclear power and renewable energy generation, and compare the cost efficiencies of nuclear power and renewable energy generation in reducing CO₂ emissions in Korea. The results show that nuclear power and renewable energy generation should be increased by 1.344% and 7.874% to reduce CO₂ emissions by 1%, respectively. Using the estimated coefficients and the levelized costs of electricity by source including the external costs, if the current amount of electricity generation is one megawatt-hour, the range of generation cost of nuclear power generation to reduce 1% CO₂ emissions is $0.72~$1.49 depending on the level of external costs. In the case of renewable energy generation, the generation cost to reduce 1% CO₂ emissions is $6.49. That is, to mitigate 1% of CO₂ emissions at the total electricity generation of 353 million MWh in 2020 in Korea, the total generation costs range for nuclear power is $254 million~$526 million for the nuclear power, and the cost for renewable energy is $2.289 billion for renewable energy. Hence, we can conclude that, in Korea, nuclear power generation is more cost-efficient than renewable energy generation in mitigating CO₂ emissions, even with the external costs of nuclear power generation.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.4
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• pp.477-487
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• 2022

This study suggests a plan for revitalizing return-to-farming / fishing villages through the marine leisure industry by analyzing the practical problems faced by young and older adults who have returned to the marine leisure field. A case study was conducted to identify the problems faced by those returning to marine leisure, and to determine the measures for revitalizing return-to-farming / fishing villages. Interview participants were those returning to marine leisure and experts in related fields. The problems identified include the exclusive culture of fishing villages, difficulty in raising initial investment funds, and lack of marine leisure education programs for return-to-farming / fishing villages. The proposals to solve these problems and revitalize return-to-farming / fishing villages through the marine leisure industry include the introduction of an incentive system to mitigate barriers to entry; establishment of a matching system; use of idle land in fishing villages to promote return-to-farming / fishing villages; introduction of a consignment management system after the pre-investment of the fishing villages; and establishment of an education program, including in the fisheries field, and infrastructure for return-to-farming / fishing villages for marine leisure.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.7
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• pp.291-298
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• 2022

In this paper, we present a method for dependency parsing with chunking in Korean. Dependency parsing is a task of determining a governor of every word in a sentence. In general, we used to determine the syntactic governor in Korean and should transform the syntactic structure into semantic structure for further processing like semantic analysis in natural language processing. There is a notorious problem to determine whether syntactic or semantic governor. For example, the syntactic governor of the word "먹고 (eat)" in the sentence "밥을 먹고 싶다 (would like to eat)" is "싶다 (would like to)", which is an auxiliary verb and therefore can not be a semantic governor. In order to mitigate this somewhat, we propose a Korean dependency parsing after chunking, which is a process of segmenting a sentence into constituents. A constituent is a word or a group of words that function as a single unit within a dependency structure and is called a chunk in this paper. Compared to traditional dependency parsing, there are some advantage of the proposed method: (1) The number of input units in parsing can be reduced and then the parsing speed could be faster. (2) The effectiveness of parsing can be improved by considering the relation between two head words in chunks. Through experiments for Sejong dependency corpus, we have shown that the USA and LAS of the proposed method are 86.48% and 84.56%, respectively and the number of input units is reduced by about 22%p.

• Journal of Physiology & Pathology in Korean Medicine
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• v.36 no.2
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• pp.59-65
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• 2022

Rodent model for chronic cerebral hypoperfusion caused by bilateral carotid artery occlusion (BCAO) show clinically relevant evidences for vascular dementia and impairments of synaptic plasticity in the hippocampus. The purpose of this study was to evaluate effect of fermented garlic (F-Garlic) extract with NO metabolites on cognitive behaviors, synaptic plasticity, and molecular events in the hippocampus following BCAO. Adult male Sprague-Dawley rats were randomly divided three experimental groups into: control+water; BCAO+water; BCAO+F-Garlic. Animals were treated with oral administration of F-Garlic in tap water as a drinking water after surgery for 4 weeks. On passive avoidance test and Y-maze test, BCAO+water showed a significant decrease in step-through latency and spontaneous alteration, indicating deficit of hippocampal memory formation but the treatment of F-Garlic significantly increased these cognitive behaviors. In control+water, a robust increase in the amplitude of evoked field excitatory postsynaptic potentials was observed by theta burst stimulation to hippocampal neural circuit indicating formation of long-term potentiation (LTP) in the hippocampal CA1. BCAO+water showed a highly significant deficit in LTP induction 4 weeks after BCAO. On other hand, daily oral administration of F-Garlic extract caused the marked preservation of LTP induction. Moreover, parvalbumin was markedly reduced in the CA1, especially, in the stratum radiatum of BCAO+water. In contrast, BCAO+F-Garlic mitigate a significantly reduction of the parvalbumin. In summary, these results suggest that daily oral administration of F-Garlic extract can ameliorate cognitive memory deficit through the preservation of synaptic plasticity and interneurons integrity in the hippocampus in rodent model of chronic cerebral hypoperfusion.