• Journal of Food Hygiene and Safety
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• v.33 no.6
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• pp.460-465
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• 2018

Deep sea water is deeper than 200 m in depth and maintains cool temperatures. It is clean seawater not contaminated by E. coli and other general bacteria. Because deep sea water is a recyclable resource with high industrial value, activities for commercial use are vigorously developing. We investigated safety, quality characteristics, and mineral contents of prototype products using deep sea water as a substitute for a curing agent and compared it with existing commercially processed products. This study examined the potential of deep sea water as an alternative to curing agent solution. As a result, safety and quality characteristics of processed meat products with deep sea water were not different from commercially processed meat products, but mineral contents were higher in processed meat products with deep sea water. Deep sea water could be widely used as purity salt and purity minerals that can replace chemical substances such as chemical salts. A new, active food market using deep sea water will emerge in the near future.

• Journal of the Korean Society of Marine Environment & Safety
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• v.24 no.7
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• pp.916-922
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• 2018

Recently, power plant effluent condensers received a Renewable Energy Certificate as components of hydrothermal energy (weighted 1.5 times) as one target item of the Renewable Portfolio Standard (RPS) policy. Accordingly, more attention is being paid to the value of thermal wastewater as a heat source. However, for utilization of thermal wastewater from power plants in high-turbidity areas like the West Sea of Korea, a turbidity reducing system is required to reduce system contamination. In this study, an experimental test was performed over a month on thermal wastewater from power plants located in the West Sea of Korea. It was found that water turbidity was reduced by more than 80 % and that the concentration of organic materials and nutrient salts was partially reduced due to the reduction of floating/drifting materials. To conduct a comparative analysis of the level of contamination of the heat exchanger when thermal wastewater flows in through a turbidity reducing system versus when the condenser effluent flows in directly without passing through the turbidity system, we disassembled and analyzed heat exchangers operated for 30 days. As a result, it was found that the heat exchanger without a turbidity reducing system had a higher level of contamination. Main contaminants (scale) that flowed in to the heat exchanger included minerals such as $SiO_2$, $Na(Si_3Al)O_8$, $CaCO_3$ and NaCl. It was estimated that marine sediment soil flowed in to the heat exchanger because of the high level of turbidity in the water-intake areas.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.6
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• pp.859-865
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• 2018

A construction of infrastructures and base station on the moon could be undertaken by linking with the regions where construction materials and energy could be supplied on site. It is necessary to detect craters on the lunar surface and gather their topological information in advance, which forms permanent shaded regions (PSR) in which rich ice deposits might be available. In this study, an effective method for automatic detection of lunar craters on the moon surface is taken into consideration by employing a latest version of deep-learning algorithm. A training of a deep-learning algorithm is performed by involving the still images of 90000 taken from the LRO orbiter on operation by NASA and the label data involving position and size of partly craters shown in each image. the Faster RCNN algorithm, which is a latest version of deep-learning algorithms, is applied for a deep-learning training. The trained deep-learning code was used for automatic detection of craters which had not been trained. As results, it is shown that a lot of erroneous information for crater's positions and sizes labelled by NASA has been automatically revised and many other craters not labelled has been detected. Therefore, it could be possible to automatically produce regional maps of crater density and topological information on the moon which could be changed through time and should be highly valuable in engineering consideration for lunar construction.

• Journal of Life Science
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• v.29 no.7
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• pp.785-791
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• 2019

In this study, we investigated the biological antioxidant and antibacterial activity of Chamaecyparis obtusa (C. obtuse) extracts by measuring DPPH radical scavenging and ABTS radical scavenging, and SOD-like activities. The DPPH and ABTS radical scavenging activities were increased in a dose-dependent manner, with maximum activities of 78% and 62% at an extract concentration of $50{\mu}l/ml$. The C. obtusa extracts also showed high SOD-like activity, with a maximum activity of 92.85% at a concentration of $50{\mu}l/ml$. The antibacterial activities of C. obtusa extracts were measured against six types of bacteria known to cause food poisoning and disease. Antibacterial activity was investigated against three gram-positive and three gram-negative bacteria using the paper disc agar diffusion method. The C. obtusa extracts showed antibacterial activities against B. cereus, E. coli, L. monocytogenes, S. aureus, S. typhi and V. parahaemolyticus, among which the activity against B. cereus was greatest. The minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) of C. obtusa extracts were $30-40{\mu}l/ml$ for the 6 strains that showed an antimicrobial response by the paper disc agar diffusion method. These results suggest that C. obtusa extracts could serve as potential antibacterial agents to inhibit the growth of pathogens responsible for food poisoning and disease.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.9
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• pp.551-557
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• 2019

Diagnosis of abnormal faults is essential for producing high quality products. The role of real-time diagnosis is quite increasing in the batch processes of producing high value-added products such as semiconductors, pharmaceuticals, and so forth. In this study, we evaluate the effect of variable selection and future-value estimation techniques on the performance of the diagnosis system, which is based on nonlinear classification and measurement data. The diagnostic performance can be improved by selecting only the variables that are important and have high contribution for diagnosis. Thus, the diagnostic performance of several variable selection techniques is compared and evaluated. In addition, missing data of a new batch, called future observations, should be estimated because the full data of a new batch is not available before the end of the cycle. In this work the use of different estimation techniques is analyzed. A case study on the polyvinyl chloride batch process was carried out so that optimal variable selection and estimation methods were obtained: maximum 21.9% and 13.3% improvement by variable selection and maximum 25.8% and 15.2% improvement by estimation methods.

• Journal of the Korean Wood Science and Technology
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• v.49 no.6
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• pp.643-657
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• 2021

In order to establish a strategy for revitalizing wood culture, a survey was conducted on the level of public awareness of wood culture and the experience of wood cultural resources by type. According to the survey, 31.4% of respondents had the images of cultural heritage such as palaces, temples, Hanoks, and cultural assets for wood cultural resources. The main reasons for having no image of wood cultural resources were the ambiguous concept and lack of interest in wood cultural resources. The importance of wood cultural resources classified into seven categories was in the order of cultural heritage, architecture of wood, cultural facilities, cultural festivals, wood products, cultural education, cultural contents. In the survey on the necessity and sufficiency of information on wood cultural resources, 46.7% of respondents needed more information to experience of wood cultural resources, while 64.8% of them had lacked information about wood cultural resources. More than half of the respondents wanted to experience of wood culture within next year, but about 20% of respondents participated in seven kinds of wood cultural resources, except wood products used in daily life. Based on these results, a systematic strategy should be developed to expand the opportunity for the public to experience of wood cultural resources and to promote them to public.

• Industry Promotion Research
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• v.6 no.2
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• pp.1-10
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• 2021

The content of the information age does not simply convey content but includes all the transactions that arise from its interaction. The types and forms of information being traded through this interaction are recognized differently from the contents that have been passed on to mankind so far by creating new meaningful content. Because the distribution of interactive content transcending the concept of time-to-time in the network environment is an important component of access to added value in the new world, unlike the content of simple concepts seen in the products of communication so far. In this study, the purpose of this study is to recognize the current status and problems of the Korean digital content industry and to seek ways to revitalize the Korean digital content industry to lead the global market in the future. Specifically, first, we want to learn about the concept of digital content. Second, we would like to look at the industrial trends of digital content at home and abroad. Third, we present a plan to streamline digital content. Fourth, derive research results and implications. In this work, the following results are derived: First, in order for Korea to enter a digital content powerhouse, each government department must first break away from the selfishness of the ministry and actively cooperate to efficiently establish and implement various policies. Second, e-books should be introduced just as current paper and CD-ROM titles are exempt from VAT, and security solutions, related technology development, and copyright issues should be urgently addressed to revitalize the market. Third, the demand for high-quality content should increase as information infrastructure such as high-speed information and communication networks and satellite broadcasting is established.

• Journal of Life Science
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• v.31 no.3
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• pp.338-345
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• 2021

Zizania latifolia has long been used as a tea for both edible and medicinal purposes. However, research into the use of Z. latifolia as a high value-added edible material is lacking. In a previous study, we confirmed that tricin is the major component in Z. latifolia. In this study, we investigated the protective effect of a Z. latifolia extract (ZLE). Toxicity tests of ZLE or tricin on HepG2 cells revealed no toxicity due to ZLE or tricin at all concentrations used. The reduction in cell viability by tert-butyl hydroperoxide (t-BHP) was suppressed by treatment with ZLE or tricin. In addition, ZLE or tricin effectively inhibited the production of reactive oxygen species (generation of hydrogen peroxide, alkoxy free radicals, and peroxyl free radicals by t-BHP) and oxidative damage. ZLE or tricin treatments also increased the protein expression of superoxide dismutase 1 (SOD1), catalase, heme oxygenase-1 (HO-1), and nuclear factor erythroid-related factor 2 (Nrf2), which are known as antioxidant enzymes, suggesting that the protective effect of ZLE is related to activation of tricin. Taken together, the results indicate that Z. latifolia can be developed as a functional food material for improving liver function.

• Atmosphere
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• v.31 no.2
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• pp.241-249
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• 2021

A smart city utilizes data collected from various sensors through the internet of things (IoT) and improves city operations across the urban area. Recently substantial research is underway to examine all aspects of data that requires for the smart city operation. Atmospheric data are an essential component for successful smart city implementation, including Urban Air Mobility (UAM), infrastructure planning, safety and convenience, and traffic management. Unfortunately, the current level of conventional atmospheric data does not meet the needs of the new city concept. New and innovative approaches to developing high spatiotemporal resolution of observational and modeling data, resolving the complex urban structure, are expected to support the future needs. The geographic information system (GIS) integrates the atmospheric data with the urban structure and offers information system enhancement. In this study we proposed the necessity and applicability of the high resolution urban meteorological dataset based on heavy fog cases in the smart city region (e.g., Sejong and Pusan) in Korea.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.12
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• pp.291-306
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• 2020

Nowadays, Data-Network-AI (DNA)-based intelligent services and applications have become a reality to provide a new dimension of services that improve the quality of life and productivity of businesses. Artificial intelligence (AI) can enhance the value of IoT data (data collected by IoT devices). The internet of things (IoT) promotes the learning and intelligence capability of AI. To extract insights from massive volume IoT data in real-time using deep learning, processing capability needs to happen in the IoT end devices where data is generated. However, deep learning requires a significant number of computational resources that may not be available at the IoT end devices. Such problems have been addressed by transporting bulks of data from the IoT end devices to the cloud datacenters for processing. But transferring IoT big data to the cloud incurs prohibitively high transmission delay and privacy issues which are a major concern. Edge computing, where distributed computing nodes are placed close to the IoT end devices, is a viable solution to meet the high computation and low-latency requirements and to preserve the privacy of users. This paper provides a comprehensive review of the current state of leveraging deep learning within edge computing to unleash the potential of IoT big data generated from IoT end devices. We believe that the revision will have a contribution to the development of DNA-based intelligent services and applications. It describes the different distributed training and inference architectures of deep learning models across multiple nodes of the edge computing platform. It also provides the different privacy-preserving approaches of deep learning on the edge computing environment and the various application domains where deep learning on the network edge can be useful. Finally, it discusses open issues and challenges leveraging deep learning within edge computing.