• Journal of Information Technology Services
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• v.19 no.6
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• pp.177-189
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• 2020

The OECD has assessed Korea as the third highest in trade facilitation worldwide. The paperless trade of Korea is world class based on uTradeHub : national e-trade service's infrastructure for trade community. Over 800 trade-related document standards provide interoperability of message exchange and trade process automation among exporters, importers, banks, customs, airlines, shippers, forwarders and trade authorities. Most one-to-one unit processes are perfectly paperless & online; however, from the perspective of process flow, there is a lack of streamlining end-to-end trade processes spread over many different parties. This situation causes the trade community to endure repetitive-redundant load for handling trade documents. The trade community has a strong demand for seamless trade flow. For streamlining the trade process, processes with data should flow seamlessly to multilateral parties. Flowing data with an optimized process is the critical success factor to accomplish seamless trade. This study proposes four critical digital trade infrastructures as a platform service : (1) data-centric Intelligent Document Recognition(IDR), (2) data-driven Digital Document Flow (DDF), (3) platform based Digital Collaboration & Communication(DCC), and (4) new digital Trade Facilitation Index (dTFI) for precise assessment of K-Trade Digital Trade Framework. The results of new dTFI analyses showed that redundant reentry load was reduced significantly over the whole trade and logistics process. This study leads to the belief that if put into real-world application can provide huge economic gains by building a new global value chain of the K-trade eco network. A new digital trade framework will be invaluable in promoting national soft power for enhancing global competitiveness of the trade community. It could become the advanced reference model of next trade facilitation infrastructure for developing countries.

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.27 no.3
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• pp.175-180
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• 2021

Although it has recently been regulated for use as an eco-friendly policy in Korea, the use of EPS (Expanded Polystyrene) cooling boxes, which are used as cold chain delivery insulation boxes for fresh agricultural and livestock products, is also increasing rapidly as e-commerce logistics such as delivery have increased rapidly due to COVID-19. Studies were conducted to optimize the EPS cooling container through internal air heat flow of CFD (Computational Fluid Dynamics) analysis and FEM (Finite Element Method) random vibration analysis using domestic PSD (Power Spectral Density) profile of the EPS cooling box to which the refrigerant is applied in this study. In the analysis of the internal air heat flow by the refrigerant in the EPS cooling box, the application of vertical protrusions inside was excellent in volume heat flow and internal air temperature distribution. In addition, as a result of random vibration analysis, the internal vertical protrusion gives the rigid effect of the cooling box, so that displacement and stress generation due to vibration during transport are smaller than that of a general cooling container without protrusion. By utilizing the resonance point (frequency) of the EPS cooling box derived by the Model analysis of ANSYS Software, it can be applied to the insulation and cushion packaging design of the EPS product line, which is widely used as insulation and cushion materials.

• Journal of Korea Trade
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• v.23 no.2
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• pp.1-13
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• 2019

Purpose - This paper empirically investigates the competition effect of exports between Korea and China in their common-export markets considering market sophistication. Modern market sophistication includes an importing country's aggregate demand for products of high quality, design, novelty, eco-friendliness, and even IPR protection. Using an empirical analysis to identify the demand for product quality across countries, this paper estimates the effects of market sophistication on the competition between Korean exports and Chinese products. Design/Methodology - Our empirical model considers the relationship between an importing country's consumer sophistication and the export competition between Korea and China. This study employs the existing theoretical framework to identify the aggregate demand for product quality across countries. Using a quite direct measurement (the consumer sophistication index, our analysis investigates the differential effects of Korea's export market sophistication, particularly in markets where Korean exports are in competition with similar Chinese products. Findings - Our main findings can be summarized as follows: the negative effects of the export competition between Korea and China on Korea's exports are stronger in third markets where consumers are less sophisticated while the effects are not as pronounced in markets where consumers are more sophisticated. This result, however, best applies to differentiated goods which significantly vary in product quality. Originality/value - Existing studies focus on the supply side of production and make the assumption that the market preference for export quality is identical across countries. This paper attempts to evaluate the export competition between Korea and China from the demand-side perspective. This area of trade studies is underexplored both empirically and in theory, although the issue has long been important to Korean and world trade.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.3 no.2
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• pp.67-72
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• 2022

Ecological research relies on the interpretation of large amounts of visual data obtained from extensive wildlife surveys, but such large-scale image interpretation is costly and time-consuming. Using an artificial intelligence (AI) machine learning model, especially convolution neural networks (CNN), it is possible to streamline these manual tasks on image information and to protect wildlife and record and predict behavior. Ecological research using deep-learning-based object recognition technology includes various research purposes such as identifying, detecting, and identifying species of wild animals, and identification of the location of poachers in real-time. These advances in the application of AI technology can enable efficient management of endangered wildlife, animal detection in various environments, and real-time analysis of image information collected by unmanned aerial vehicles. Furthermore, the need for school education and social use on biodiversity and environmental issues using AI is raised. School education and citizen science related to ecological activities using AI technology can enhance environmental awareness, and strengthen more knowledge and problem-solving skills in science and research processes. Under these prospects, in this paper, we compare the results of our early 2013 study, which automatically identified African cichlid fish species using photographic data of them, with the results of reanalysis by CNN deep learning method. By using PyTorch and PyTorch Lightning frameworks, we achieve an accuracy of 82.54% and an F1-score of 0.77 with minimal programming and data preprocessing effort. This is a significant improvement over the previous our machine learning methods, which required heavy feature engineering costs and had 78% accuracy.

• Economic and Environmental Geology
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• v.56 no.2
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• pp.185-199
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• 2023

This study aimed to predict the effects of water ecology on the supply of hydrothermal energy to model a housing complex in Eco Delta Smart Village in Busan. Based on the results, engineering measures were recommended to minimize problems due to possible temperature variations on the supply of hydrothermal energy from the river. The current distribution of fish, benthic macroinvertebrates, and phytoplankton in the Pyeonggang Stream was monitored to determine their effects on water ecology. In the research area, five species and three families of fish were observed. The dominant species was Lepomis macrochirus, and the subdominant species was Carassius auratus. Twenty-five species and 21 families of benthic macroinvertebrates were found. The distribution of aquatic insects was poor in this area. The dominant species were Chironomidae sp., Lymnaea auricularia, Appasus japonicus, and Caridina denticulata denticulata in February, May, July, and October. Dominant phytoplankton were Aulacoseira ambigua and Nitzschia palea in February and May. Microcystis sp. was dominant in July and October. The health of the ecology the Pyeonggang Stream was assessed as D (bad) according to the benthic macroinvertebrate index (BMI). Shifts in the location of the discharge point 150 m downstream from intake points and discharge through embedded rock layer after adding equal amounts of stream water as was taken at the beginning were suggested to minimize water temperature variations due to the application of hydrothermal energy. When the scenario (i.e., quantity of water intake and dilution water, 1,600 m³/d and water temp. difference ±5 ℃) was realized, variations in water temperature were assessed at -0.19 ℃ and 0.59 ℃ during cooling and heating, respectively, at a point 10 m downstream. Water temperatures recorded at -0.20 ℃ and 0.68 ℃ during cooling and heating, respectively, at a point 10 m upstream. All stream water temperatures after the application of hydrothermal energy recovered within 24 hours. Future work on the long-term monitoring of ecosystems is suggested, particularly to analyze the influence of the water environment on hydrothermal energy supply operations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.4
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• pp.1123-1146
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• 2023

In South Korea, there have been many studies on efficient building-energy management using renewable energy facilities in single zero-energy houses or buildings. However, such management was limited due to spatial and economic problems. To realize a smart zero-energy city, studying efficient energy integration for the entire city, not just for a single house or building, is necessary. Therefore, this study was conducted in the eco-friendly energy town of Chungbuk Innovation City. Chungbuk successfully realized energy independence by converging new and renewable energy facilities for the first time in South Korea. This study analyzes energy data collected from public buildings in that town every minute for a year. We propose a smart city building-energy management model based on the results that combine various renewable energy sources with grid power. Supervised learning can determine when it is best to sell surplus electricity, or unsupervised learning can be used if there is a particular pattern or rule for energy use. However, it is more appropriate to use reinforcement learning to maximize rewards in an environment with numerous variables that change every moment. Therefore, we propose a power distribution algorithm based on reinforcement learning that considers the sales of Energy Storage System power from surplus renewable energy. Finally, we confirm through economic analysis that a 10% saving is possible from this efficiency.

• Korea Trade Review
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• v.42 no.5
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• pp.183-211
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• 2017

Recently, as the environment-friendly factors has become more important than before. In other words, the new model in trade has emerged as an important issue. At the same time, environmental trade is emerging as a new barrier due to the increasing international trade environmental regulation linked with environment. International trade environmental regulation has a huge impact on the whole industry, so if you can not cope with it in a timely manner, you can suffer great damage. Therefore, global export and import companies are required to manage green supply chains, and companies need to reestablish strategic systems throughout supply chain management with renewed awareness of the importance of eco-friendliness in the international trade environment. In this study, we investigated how companies perceive international trade environment regulation and how this affects the use of Green SCM.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.3
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• pp.279-288
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• 2018

In this paper, we present the results of educational innovation case study using U-Learning Box and Ubiquitous-based Test(UBT) system for 6 sample primary schools in Nepal. As Nepal is considered to be a developing country with electricity problem to the school, the U-Learning Box, consisting of a small and easy-to-use tablet PC for teacher and a small smart beam with its own battery was evaluated as the optimum solution to support continuous basic English and hygiene education for these schools. And UBT technology using tablet PC was used to evaluate and analyze basic English learning ability of the students, which helped us realized that it is necessary to improve the educational environment and develop suitable educational contents. We hope that the global educational innovation using U-Learning Box and UBT technology will become a successful model for global equality of educational opportunity project for developing countries including Nepal.

• Journal of Radiation Protection and Research
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• v.48 no.4
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• pp.175-183
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• 2023

Background: Recently, biological adsorbents have been developed for removing radionuclides from radioactive liquid waste due to their high selectivity, eco-friendliness, and renewability. However, since they can be damaged by radiation in radioactive waste, a method for estimating the bio-adsorbent performance as a time should consider the radiation damages in terms of their renewability. This paper aims to develop a simulation method that applies a deep learning technique to rapidly and accurately estimate the adsorption performance of bio-adsorbents when inserted into liquid radioactive waste. Materials and Methods: A model that describes various interactions between a bio-adsorbent and liquid has been constructed using numerical methods to estimate the adsorption capacity of the bio-adsorbent. To generate datasets for machine learning, Monte Carlo N-Particle (MCNP) simulations were conducted while considering radioactive concentrations in the adsorbent column. Results and Discussion: Compared with the result of the conventional method, the proposed method indicates that the accuracy is in good agreement, within 0.99% and 0.06% for the R² score and mean absolute percentage error, respectively. Furthermore, the estimation speed is improved by over 30 times. Conclusion: Note that an artificial neural network can rapidly and accurately estimate the survival rate of a bio-adsorbent from radiation ionization compared with the MCNP simulation and can determine if the bio-adsorbents are reusable.

• The Research Journal of the Costume Culture
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• v.32 no.2
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• pp.247-259
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• 2024

This study assessed the effectiveness of brand image communication on consumer perceptions of cruelty-free fashion brands. Brand messaging data were gathered from postings on the official Instagram accounts of three cruelty-free fashion brands and consumer perception data were gathered from Tweets containing keywords related to each brand. Web crawling and natural language processing were performed using Python and sentiment analysis was conducted using the BERT model. By analyzing Instagram content from Stella McCartney, Patagonia, and Freitag from their inception until 2021, this study found these brands all emphasize environmental aspects but with differing focuses: Stella McCartney on ecological conservation, Patagonia on an active outdoor image, and Freitag on upcycled products. Keyword analysis further indicated consumers perceive these brands in line with their brand messaging: Stella McCartney as high-end and eco-friendly, Patagonia as active and environmentally conscious, and Freitag as centered on recycling. Results based on the assessment of the alignment between brand-driven images and consumer-perceived images and the sentiment evaluation of the brand confirmed the outcomes of brand communication performance. The study revealed a correlation between brand image and positive consumer evaluations, indicating that higher alignment of ethical values leads to more positive consumer assessments. Given that consumers tend to prioritize search keywords over brand concepts, it's important for brands to focus on using visual imagery and promotions to effectively convey brand communication information. These findings highlight the importance of brand communication by emphasizing the connection between ethical brand images and consumer perceptions.