• Journal of Ecology and Environment
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• v.46 no.4
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• pp.282-291
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• 2022

Background: The Arctic permafrost stores enormous amount of carbon (C), about one third of global C stocks. However, drastically increasing temperature in the Arctic makes the stable frozen C stock vulnerable to microbial decomposition. The released carbon dioxide from permafrost can cause accelerating C feedback to the atmosphere. Soil organic matter (SOM) composition would be the basic information to project the trajectory of C under rapidly changing climate. However, not many studies on SOM characterization have been done compared to quantification of SOM stocks. Thus, the purpose of our study is to determine soil properties and molecular compositions of SOM in four different Arctic regions. We collected soils in different soil layers from 1) Cambridge Bay, Canada, 2) Council, Alaska, USA, 3) Svalbard, Norway, and 4) Zackenberg, Greenland. The basic soil properties were measured, and the molecular composition of SOM was analyzed through pyrolysis-gas chromatography/mass spectrometry (py-GC/MS). Results: The Oi layer of soil in Council, Alaska showed the lowest soil pH and the highest electrical conductivity (EC) and SOM content. All soils in each site showed increasing pH and decreasing SOC and EC values with soil depth. Since the Council site was moist acidic tundra compared to other three dry tundra sites, soil properties were distinct from the others: high SOM and EC, and low pH. Through the py-GC/MS analysis, a total of 117 pyrolysis products were detected from 32 soil samples of four different Arctic soils. The first two-axis of the PCA explained 38% of sample variation. While short- and mid-hydrocarbons were associated with mineral layers, lignins and polysaccharides were linked to organic layers of Alaska and Cambridge Bay soil. Conclusions: We conclude that the py-GC/MS results separated soil samples mainly based on the origin of SOM (plants- or microbially-derived). This molecular characteristics of SOM can play a role of controlling SOM degradation to warming. Thus, it should be further investigated how the SOM molecular characteristics have impacts on SOM dynamics through additional laboratory incubation studies and microbial decomposition measurements in the field.

• Current Photovoltaic Research
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• v.10 no.3
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• pp.77-83
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• 2022

Renewable energy is receiving attention again as a way to realize carbon neutrality to overcome the climate change crisis. Among renewable energy sources, the installation of Photovoltaic is continuously increasing, and as of 2020, the global cumulative installation amount is about 590 GW and the domestic cumulative installation amount is about 17 GW. Accordingly, O&M technology that can analyze the power generation and fault diagnose about PV plants the is required. In this paper, a study was conducted to diagnose fault using I-V curves of PV strings and deep learning. In order to collect the fault I-V curves for learning in the deep learning, faults were simulated. It is partial shade and voltage mismatch, and I-V curves were measured on a sunny day. A two-step data pre-processing technique was applied to minimize variations depending on PV string capacity, irradiance, and PV module temperature, and this was used for learning and validation of deep learning. From the results of the study, it was confirmed that the PV fault diagnosis using I-V curves and deep learning is possible.

• International journal of advanced smart convergence
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• v.11 no.3
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• pp.222-228
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• 2022

As a means to cope with the climate change crisis caused by global warming, automobile manufacturers continue to make efforts to use the driving energy of vehicles as electricity. As a result, parts industry such as battery, motor, and controller are attracting attention. China is often seen in large cities, with electric vehicles such as electric bicycles, electric motorcycles, and small electric vehicles popularized and commercialized, mainly in large cities. However, small electric vehicles are not popular in Korea, which is why the country's topography is high in hills. In order to drive the hilly domestic roads, power performance including vehicle climbing ability should be improved. In order to improve the power performance and the climbing capacity of small electric vehicles, the capacity of the motor should be increased. However, when the performance of the motor is improved, the weight of the motor becomes heavy and the price competitiveness is likely to decrease. In addition, in order to operate a high-performance motor, the power consumption of the battery is rapidly increased, so various problems must be solved. In order to commercialize a small electric vehicle for one or two people who do not emit harmful exhaust gas to the human body in a hilly domestic terrain, it is effective to have a separate transmission system. In this study, we were conducted dynamometer test to produce a continuously variable transmission(CVT) system prototype using a spring that can be applied to a small electric vehicle and to install a CVT system prototype manufactured in a small electric vehicle. The dynamometer test results showed that the maximum speed performance, acceleration performance, and climbing performance were improved.

• Journal of the Korean earth science society
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• v.43 no.4
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• pp.511-519
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• 2022

Given the significant social and economic impact caused by heat waves, there is a pressing need to predict them with high accuracy and reliability. In this study, we analyzed the real-time forecast data from six models constituting the Subseasonal-to-Seasonal (S2S) prediction project, to elucidate the key mechanisms contributing to the prediction of the recent record-breaking Korean heat wave event in 2018. Weekly anomalies were first obtained by subtracting the 2017-2020 mean values for both S2S model simulations and observations. By comparing four Korean heat-wave-related indices from S2S models to the observed data, we aimed to identify key climate processes affecting prediction accuracy. The results showed that superior performance at predicting the 2018 Korean heat wave was achieved when the model showed better prediction performance for the anomalous anticyclonic activity in the upper troposphere of Eastern Europe and the cyclonic circulation over the Western North Pacific (WNP) region compared to the observed data. Furthermore, the development of upper-tropospheric anticyclones in Eastern Europe was closely related to global warming and the occurrence of La Niña events. The anomalous cyclonic flow in the WNP region coincided with enhancements in Madden-Julian oscillation phases 4-6. Our results indicate that, for the accurate prediction of heat waves, such as the 2018 Korean heat wave, it is imperative for the S2S models to realistically reproduce the variabilities over the Eastern Europe and WNP regions.

• Journal of Internet of Things and Convergence
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• v.8 no.3
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• pp.55-61
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• 2022

In order to reduce greenhouse gases, the main culprit of global warming, the United Nations signed the Climate Change Convention in 1992. Korea is also pursuing a policy to expand the supply of renewable energy to reduce greenhouse gas emissions. The expansion of renewable energy development using solar power led to the expansion of wind power and solar power generation. The expansion of renewable energy development, which is greatly affected by weather conditions, is creating difficulties in managing the supply and demand of the power system. To solve this problem, the power brokerage market was introduced. Therefore, in order to participate in the power brokerage market, it is necessary to predict the amount of power generation. In this paper, the prediction system was used to analyze the Yonchuk solar power plant. As a result of applying solar insolation from on-site (Model 1) and the Korea Meteorological Administration (Model 2), it was confirmed that accuracy of Model 2 was 3% higher. As a result of comparative analysis of the DNN and RNN models, it was confirmed that the prediction accuracy of the DNN model improved by 1.72%.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.1
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• pp.205-212
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• 2023

In the modern society, the extreme weather caused by climate change has brought about exceptional damage in succession over the world due to the use of fossil fuels, and infectious diseases such as COVID-19 worsen the quality of human life. It is urgently necessary to reduce green-house gas and use new renewable energy. The global environmental pollution should be decreased by reducing the use of fossil fuels and using new renewable energy. This paper suggests a system which can function for the environment of four seasons, safety and communication, through the photovoltaic power-based intelligent CCTV, internet and WiFi, and cooling and heating systems, and can optimally manage power, through the real-time monitoring of the production and the consumption of the photovoltaic power. It suggests a hybrid generation system supporting diesel generation without discontinuation in the case of emergency such as system power outage caused by cold waves, typhoons and natural disasters in which the photovoltaic power generating system cannot be used.

• Journal of Advanced Navigation Technology
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• v.27 no.1
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• pp.133-138
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• 2023

As a side effect of recent rapid climate change and global warming, the frequency and scale of flood disasters are increasing worldwide. In Korea, the water level of the Han River is a major management target for preventing flood disasters in Seoul, the capital of Korea. In this paper, to improve the water level prediction of the Han River based on machine learning, we perform a comprehensive assessment of the quality of related dataset and propose data preprocessing methods to improve it. Specifically, we improve the dataset in terms of completeness, validity, and accuracy through missing value processing and cross-correlation analysis. In addition, we conduct a performance evaluation using random forest and LightGBM to analyze the effect of the proposed data improvement method on the water level prediction performance of the Han River.

• Membrane Journal
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• v.32 no.6
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• pp.475-485
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• 2022

The continuous excessive consumption of fossil fuels is causing global warming, climate, and environmental crisis. Accordingly, hydrogen energy attracts attention among alternative energies of fossil fuels, because it has the advantage of not emitting pollutants and not having resource restrictions. Therefore, various studies are being conducted on a water electrolysis system for producing hydrogen and a fuel cell system for producing electricity by using hydrogen energy as a fuel. In this study, 3D ionomer models were produced by reflecting the excessive water condition of an anion-conductive ionomer material, which is one of the core materials of water electrolysis systems and fuel cells. Finally, by analyzing the structural stability and performance of the ionomer under an excessively hydrated condition, we suggested a performance improvement factor in the design of an anion conductive ionomer, a key material for water electrolysis systems and fuel cells.

• Journal of Navigation and Port Research
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• v.47 no.2
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• pp.106-119
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• 2023

Due to global decarbonization movement and tightening of maritime emissions restrictions, the shipping industry is going to switch to alternative fuels. Among candidates of alternative fuel, methanol is promising for decreasing SOx and CO2 emissions, resulting in minimum climate change and meeting the goal of green shipping. In this study, a novel combined system of direct methanol solid oxide fuel cells (SOFC), proton exchange membrane fuel cells (PEMFC), gas turbine (GT), and organic Rankine cycle (ORC) targeted for marine vessels was proposed. The SOFC is the main power generator of the system, whereas the GT and PEMFC could recover waste heat from the SOFC to generate useful power and increase waste heat utilizing efficiency of the system. Thermodynamics model of the combined system and each component were established and analyzed. Energy and exergy efficiencies of subsystems and the entire system were estimated with participation of the first and second laws of thermodynamics. The energy and exergy efficiencies of the overall multigeneration system were estimated to be 76.2% and 30.3%, respectively. The combination of GT and PEMFC increased the energy efficiency by 18.91% compared to the SOFC stand-alone system. By changing the methanol distribution ratio from 0.05 to 0.4, energy and exergy efficiencies decreased by 15.49% and 5.41%, respectively. During the starting up and maneuvering period of vessels, a quick response from the power supply system and propulsion plant is necessary. Utilization of PEMFC coupled with SOFC has remarkable meaning and benefits.

• Journal of Korean Society of Disaster and Security
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• v.16 no.1
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• pp.37-48
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• 2023

The possibility of a super-large disaster is increasing due to changes in national territory, urban space and social environment, extreme weather conditions due to climate change, and paralysis of national infrastructure due to natural disasters. In this study, in order to support the systematic establishment of national territorial disaster prevention strategies for future disasters, alternatives to intelligent national territorial disaster prevention policies for future disasters were considered. Changes in the national environment related to future disasters, domestic and foreign prior studies and policy trends related to national disaster prevention, and studies related to the national disaster management system were investigated, and institutional and technical policy alternatives were derived. As a policy alternative, it was suggested that the creation of a self-adapting national territory for future disasters should be systematized and continuously supported through a technically intelligent decision-making support system.