• Atmosphere
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• v.31 no.1
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• pp.73-83
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• 2021

Numerical weather prediction (NWP) models play an essential role in predicting weather factors, but using them is challenging due to various factors. To overcome the difficulties of NWP models, deep learning models have been deployed in weather forecasting by several recent studies. This study adapts long short-term memory (LSTM), which demonstrates remarkable performance in time-series prediction. The combination of LSTM model input of meteorological features and activation functions have a significant impact on the performance therefore, the results from 5 combinations of input features and 4 activation functions are analyzed in 9 Automated Surface Observing System (ASOS) stations corresponding to cities/islands/mountains. The optimized LSTM model produces better performance within eight forecast hours than Local Data Assimilation and Prediction System (LDAPS) operated by Korean meteorological administration. Therefore, this study illustrates that this LSTM model can be usefully applied to very short-term weather forecasting, and further studies about CNN-LSTM model with 2-D spatial convolution neural network (CNN) coupled in LSTM are required for improvement.

• Journal of Information Technology Services
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• v.21 no.6
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• pp.117-125
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• 2022

In respond to climate change caused by global environmental problems, countries around the world are actively promoting the advancement of new electricity industries. The new energy business is being applied to energy storage systems (ESS), electric vehicle charging business, and power demand response using cutting edge technologies. In 2022, the Korean government is also establishing a policy stance to foster new energy industries and making efforts to improve its responsiveness to power demand response with the innovative technologies. In Korea, attempts to commercialize energy power are also being made in the private and public sectors to control energy power in houses, buildings, and industries. For example, private companies, local governments, and central government are making all-out efforts to develop new energy industry models through joint investment. There are forms such as establishing energy-independent facilities by region, establishing an electric vehicle charging system, controlling urban lighting systems with Information technologies, and managing demand between power suppliers and power consumers. This study examined the business model applied with energy storage system, electric vehicle charging business, smart lighting, and power demand response based on information communication technology to examine the site where smart energy system was introduced. According to this study, company missions and government tasks are suggested to apply new energy business technologies as economical energy solutions that meet the purpose of use by region, industry, and company.

• Korean Journal of Artificial Intelligence
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• v.10 no.1
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• pp.27-32
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• 2022

As the need for eco-friendly transportation increases due to the deepening climate crisis, many local governments in Korea are introducing shared bicycles. Due to anxiety about public transportation after COVID-19, bicycles have firmly established themselves as the axis of daily transportation. The use of shared bicycles is spread, and the demand for bicycles is increasing by rental offices, but there are operational and management difficulties because the demand is managed under a limited budget. And unfortunately, user behavior results in a spatial imbalance of the bike inventory over time. So, in order to easily operate the maintenance of shared bicycles in Seoul, bicycles should be prepared in large quantities at a time of high demand and withdrawn at a low time. Therefore, in this study, by using machine learning, the linear regression algorithm and MS Azure ML are used to predict and analyze when demand is high. As a result of the analysis, the demand for bicycles in 2018 is on the rise compared to 2017, and the demand is lower in winter than in spring, summer, and fall. It can be judged that this linear regression-based prediction can reduce maintenance and management costs in a shared society and increase user convenience. In a further study, we will focus on shared bike routes by using GPS tracking systems. Through the data found, the route used by most people will be analyzed to derive the optimal route when installing a bicycle-only road.

• Journal of Wellbeing Management and Applied Psychology
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• v.5 no.3
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• pp.27-41
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• 2022

Purpose: In this study, pollutants generated in industrial areas were measured using a Portable Air Quality Measurement System(PAQMS). This study intends to examine in detail improvement measures and operational capabilities to operate a more efficient PAQMS. Research design, data and methodology: This study compares and analyzes the measurement values of the PAQMS and the measurement values of the national air quality measurement network. It is intended to develop a PAQMS corresponding to the data of the national measurement network by minimizing the errors that occur during comparative measurement and analysis and supplementing and improving the problems that occur during the current equipment calibration. Results: A PAQMS is an essential equipment for faster and more accurate measurement and analysis of pollutants in case of untimely measurement and civil complaints due to Micro Climate(local weather and environmental influences). Currently, there are many atmospheric measurement equipment in Korea, but only equipment for each item is produced and sold. Currently, these devices on the market must satisfy various conditions such as stable power, temperature, and humidity to calculate accurate measurement values. Conclusions: Therefore, there is no equipment that satisfies the conditions for performing detailed measurement in the field where accurate measurement is required. In this study, these field work conditions and contents for stable measurement were mentioned in the text.

• Journal of Korean Society of Rural Planning
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• v.29 no.3
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• pp.69-78
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• 2023

Rural spaces are experiencing an increasing demand for novel functionalities and adaptations driven by technological advancements in agriculture and rural areas. This study aimed to investigate the public perception of rural spaces in the context of evolving agricultural technologies, specifically focusing on photovoltaic power generation, and the ensuing competition among various functions of rural spaces. A survey was conducted with a participant sample of 330, revealing that the majority of respondents prioritize agricultural production as the primary function of farmland. Furthermore, the survey results indicated that the installation of solar panels on farmland is perceived as a complex issue that affects multiple aspects, such as the landscape, local economy, ecological environment, climate change, and income. Additionally, disparities in responses to landscape-related questions were observed based on age, perception of agricultural land functions, and opinions on technological adoption. This finding suggests that the landscape is poised to become a significant factor in future agricultural and rural transformations. The findings of this survey can provide valuable contributions to the preparation of changes catalyzed by advancements in agricultural technology. Moreover, they offer guidance on the key factors that need to be taken into account when introducing new functions to rural spaces.

• Korea Trade Review
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• v.47 no.1
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• pp.115-130
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• 2022

In this study, I focus on analyzing how the effects of implementing ETS are different depending on whether Korean ETS linking with carbon markets in other countries. The global computable general equilibrium (CGE) model built in this study analyzes the chages in the production and trade of industrial sectors according to the international linkage of ETS compared to the reference scenario of emissions reduction targets and implementation of ETS. From the analysis of internatioanl linkage of carbon markets scenarios, Annex B countries-South Korea carbon market linkage with individual ETS in China worse the economic outcomes in South Korea the most. This means South Korea lose the international competitiveness compared to China in this scenario. On the other hand, Annex B-China carbon market linkage with Korean individual ETS implementation reduce the decreases in production and trading. The most effective way is to join a global emissions trading market with China. The results are consistent in most industries of South Korea. These results are caused by that the supply of emission allowance is increased and the price of emissions allowances is dropped by China's participation to the carbon market, which can be understood to reduce the carbon reduction cost for industrial sectors. In addition, it can be also concluded that the determinant of the negative impact of ETS on changes in production and trade is more sensitive to the price of emissions allowances than to the characteristics of production and trade structure.

• Steel and Composite Structures
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• v.50 no.4
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• pp.443-458
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• 2024

The construction industry, one of the biggest producers of greenhouse emissions, is under a lot of pressure as a result of growing worries about how climate change may affect local communities. Geopolymer concrete (GPC) has emerged as a feasible choice for construction materials as a result of the environmental issues connected to the manufacture of cement. The findings of this study contribute to the development of machine learning methods for estimating the properties of eco-friendly concrete, which might be used in lieu of traditional concrete to reduce CO₂ emissions in the building industry. In the present work, the compressive strength (f_c) of GPC is calculated using random forests regression (RFR) methodology where natural zeolite (NZ) and silica fume (SF) replace ground granulated blast-furnace slag (GGBFS). From the literature, a thorough set of experimental experiments on GPC samples were compiled, totaling 254 data rows. The considered RFR integrated with artificial hummingbird optimization (AHA), black widow optimization algorithm (BWOA), and chimp optimization algorithm (ChOA), abbreviated as ARFR, BRFR, and CRFR. The outcomes obtained for RFR models demonstrated satisfactory performance across all evaluation metrics in the prediction procedure. For R² metric, the CRFR model gained 0.9988 and 0.9981 in the train and test data set higher than those for BRFR (0.9982 and 0.9969), followed by ARFR (0.9971 and 0.9956). Some other error and distribution metrics depicted a roughly 50% improvement for CRFR respect to ARFR.

• New & Renewable Energy
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• v.20 no.1
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• pp.38-51
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• 2024

The rapid expansion of industrialization and population growth worldwide has led to a significant surge in energy demand, perpetuating heavy reliance on finite fossil fuel reserves. Although prevailing policies primarily target ground-mounted solar photovoltaics, there is a noticeable increase in the adoption of floating solar power generation systems on water surfaces. Nonetheless, adequate studies and legislative reviews on offshore solar photovoltaics in Korea are lacking. The absence of well-defined criteria for the economic analysis of floating solar photovoltaics presents hurdles to their economic feasibility. This study conducted a comprehensive cost-benefit analysis of offshore photovoltaics to evaluate their economic viability and compared four types of solar photovoltaics based on the operating area and technology: ground-mounted, floating on inland water, pontoon-based offshore, and flexible system offshore. Perspectives from both central and local government entities, emphasizing social aspects, as well as inputs from private companies with a financial focus were considered. The findings revealed variations in economic viability depending on the operating area and technology employed. This study aims to contribute to the advancement of market maturity and technology within the realm of offshore solar photovoltaics.

• The Journal of Fisheries Business Administration
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• v.54 no.4
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• pp.1-18
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• 2023

This study examines the significance and problems of the Fourth Amendment to the Fisheries Act, which went into effect in January 2023. Following the passage of the Aquaculture Industry Development Act, the fourth amendment to the Fisheries Act sought to reform the fisheries legislative framework, while also including significant changes. In particular, a number of new systems for managing fishing gear have been implemented, and local governments now have some autonomy in fisheries management, which has allowed for adjustments to be made to meet the needs of the fishing industry and changes in socioeconomic situations. However, as independent legislation for each fisheries sector continues, the subject of regulation under the Fisheries Act, as well as the Act's position as a basic legal system, has been continuously reduced, overshadowing the Act's objective. As a result, a full-fledged assessment of changing the legislation's name in the future is required, as well as addressing issues such as the lack of difference in the legislative purpose clause and the necessity for further revision of the definition clause. Therefore, any future revisions to the Fisheries Act should aim to overhaul the existing framework, including fishing licenses and permits.

• Korean Journal of Agricultural and Forest Meteorology
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• v.15 no.1
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• pp.1-8
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• 2013

This study was conducted to compare the local climate conditions and growth periods for the apple (Malus domestica 'Borkh') orchards at different altitudes (330, 500, and 670 m) in Jangsu-Gun, Korea. Observation data for the growth period show that the monthly mean air temperatures at the 'Hongro' apple orchard sites decrease with height at the rate of 1.0 to $3.0^{\circ}C$/100 m. The monthly minimum temperatures in April (blooming period for 'Hongro' apple) were 4.3, 2.9, and $0.4^{\circ}C$ at 330, 500, and 670 m, respectively. The monthly mean temperatures in September (i.e., the coloration and maturation period) were 20.6, 18.7, and $14.5^{\circ}C$, respectively. The annual precipitation range varied from 1,234 to 1,439 mm, which tended to increase with height. The heavy rainfall occurred in summer (June to August) and amounted to 827-933 mm. No significant differences in the duration of sunshine were observed amongst the orchards at three different altitudes. The earliest bud break was observed at the 330 m altitude (18 March 2009), which was 4 and 11 days earlier in comparison to those at 500 and 670 m, respectively. The time of full bloom at 330 m was 12 days ahead of that at 670 m. The optimal maturation of fruit (based on skin redness > 80%) was observed between 7 and 10 September at 330 m, 15 and 18 September at 500 m, and 21 and 23 September at 670 m.