• Journal of Life Science
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• v.30 no.12
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• pp.1078-1084
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• 2020

Protaetia brevitarsis seulensis is an insect belonging to the order Coleoptera. This insect is reported to contain large amounts of physiologically active substances useful for liver protective effect and improvements in blood circulation as well as a broad source of edible protein. Antimicrobial peptides (AMPs) are found in a variety of species, from microorganisms to mammals, and play an important role in the innate immune systems of living things. Microglia are the main source of proinflammatory cytokines and nitric oxide (NO) in the central nervous system. Activated microglia secrete large amounts of neuroinflammatory mediators (e.g., TNF-α, NO, and ROS), which are the main cause of neuronal cell death. In the present study, we investigated the inhibitory effect of Protaetiamycine 6 (PKARKLQKLSAYKTTLRN-NH2), an AMP derived from Protaetia brevitarsis seulensis, on LPS-induced neuroinflammation in BV-2 microglia. Protaetiamycine 6 significantly inhibited NO production without cytotoxicity and decreased the expression levels of inducible NO synthase and cyclooxygenase-2. In addition, Protaetiamycine 6 also reduced the production of neuroinflammatory cytokines on activated BV-2 microglia. These results suggest that Protaetiamycine 6 could be a good source of functional substance to prevent neuroinflammation and neurodegenerative diseases.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.33 no.6
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• pp.265-274
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• 2021

Outlier detection research in ocean data has traditionally been performed using statistical and distance-based machine learning algorithms. Recently, AI-based methods have received a lot of attention and so-called supervised learning methods that require classification information for data are mainly used. This supervised learning method requires a lot of time and costs because classification information (label) must be manually designated for all data required for learning. In this study, an autoencoder based on unsupervised learning was applied as an outlier detection to overcome this problem. For the experiment, two experiments were designed: one is univariate learning, in which only SST data was used among the observation data of Deokjeok Island and the other is multivariate learning, in which SST, air temperature, wind direction, wind speed, air pressure, and humidity were used. Period of data is 25 years from 1996 to 2020, and a pre-processing considering the characteristics of ocean data was applied to the data. An outlier detection of actual SST data was tried with a learned univariate and multivariate autoencoder. We tried to detect outliers in real SST data using trained univariate and multivariate autoencoders. To compare model performance, various outlier detection methods were applied to synthetic data with artificially inserted errors. As a result of quantitatively evaluating the performance of these methods, the multivariate/univariate accuracy was about 96%/91%, respectively, indicating that the multivariate autoencoder had better outlier detection performance. Outlier detection using an unsupervised learning-based autoencoder is expected to be used in various ways in that it can reduce subjective classification errors and cost and time required for data labeling.

• Journal of Practical Agriculture & Fisheries Research
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• v.22 no.1
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• pp.113-129
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• 2020

In this study we examined the topic analysis and correlation analysis by text mining to extract meaningful information or rules from the self introduction letter of freshman at Korea National College of Agriculture and Fisheries in 2020. The analysis items are described in items related to 'academic' and 'in-school activities' during high school. In the text mining results, the keywords of 'academic' items were 'study', 'thought', 'effort', 'problem', 'friend', and the key words of 'in-school activities' were 'activity', 'thought', 'friend', 'club', 'school' in order. As a result of the correlation analysis, the key words of 'thinking', 'studying', 'effort', and 'time' played a central role in the 'academic' item. And the key words of 'in-school activities' were 'thought', 'activity', 'school', 'time', and 'friend'. The results of frequency analysis and association analysis were visualized with word cloud and correlation graphs to make it easier to understand all the results. In the next study, TF-IDF(Term Frequency-Inverse Document Frequency) analysis using 'frequency of keywords' and 'reverse of document frequency' will be performed as a method of extracting key words from a large amount of documents.

• Journal of Navigation and Port Research
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• v.46 no.1
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• pp.1-10
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• 2022

This study aims to investigate changes in the demand for ship officers in response to changes in the shipping industry environment in which Maritime Autonomous Surface Ships (MASS) emerge according to the application of the fourth industrial revolution technology to ships, and it looks into changes in the skill of ship officer. It also analyzes and proposes a plan for nurturing ship officers accordingly. As a result of the degree of recognition and AHP analysis, this study suggests that a new training system is required because the current training and education system may cover the job competencies of emergency response, caution and danger navigation, general sailing, cargo handling, seaworthiness maintenance, emergency response, and ship maintenance and management, but tasks such as remote control, monitoring diagnosis, device management capability, and big data analysis require competency for unmanned and shore-based control. By evaluating the importance of change factors in the duties of ship officers in Maritime Autonomous Surface Ships, this study provides information on ship officer educational institutions' response strategies for nurturing ship officers and prioritization of resource allocation, etc. The importance of these factors was compared and evaluated to suggest changes in the duties of ship officers and methods of nurturing ship officers according to the introduction of Maritime Autonomous Surface Ships. It is expected that the findings of this study will be meaningful as it systematically derives the duties and competency factors of ship officers of Maritime Autonomous Surface Ships from a practical point of view and analyzed the perception level of each relevant expert to diagnose expert-level responses to the introduction of Maritime Autonomous Surface Ships.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.67-88
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• 2018

Until recently, as we recognize the significance of sustainable growth and competitiveness of small-and-medium sized enterprises (SMEs), governmental support for tangible resources such as R&D, manpower, funds, etc. has been mainly provided. However, it is also true that the inefficiency of support systems such as underestimated or redundant support has been raised because there exist conflicting policies in terms of appropriateness, effectiveness and efficiency of business support. From the perspective of the government or a company, we believe that due to limited resources of SMEs technology development and capacity enhancement through collaboration with external sources is the basis for creating competitive advantage for companies, and also emphasize value creation activities for it. This is why value chain network analysis is necessary in order to analyze inter-company deal relationships from a series of value chains and visualize results through establishing knowledge ecosystems at the corporate level. There exist Technology Opportunity Discovery (TOD) system that provides information on relevant products or technology status of companies with patents through retrievals over patent, product, or company name, CRETOP and KISLINE which both allow to view company (financial) information and credit information, but there exists no online system that provides a list of similar (competitive) companies based on the analysis of value chain network or information on potential clients or demanders that can have business deals in future. Therefore, we focus on the "Value Chain Network System (VCNS)", a support partner for planning the corporate business strategy developed and managed by KISTI, and investigate the types of embedded network-based analysis modules, databases (D/Bs) to support them, and how to utilize the system efficiently. Further we explore the function of network visualization in intelligent value chain analysis system which becomes the core information to understand industrial structure ystem and to develop a company's new product development. In order for a company to have the competitive superiority over other companies, it is necessary to identify who are the competitors with patents or products currently being produced, and searching for similar companies or competitors by each type of industry is the key to securing competitiveness in the commercialization of the target company. In addition, transaction information, which becomes business activity between companies, plays an important role in providing information regarding potential customers when both parties enter similar fields together. Identifying a competitor at the enterprise or industry level by using a network map based on such inter-company sales information can be implemented as a core module of value chain analysis. The Value Chain Network System (VCNS) combines the concepts of value chain and industrial structure analysis with corporate information simply collected to date, so that it can grasp not only the market competition situation of individual companies but also the value chain relationship of a specific industry. Especially, it can be useful as an information analysis tool at the corporate level such as identification of industry structure, identification of competitor trends, analysis of competitors, locating suppliers (sellers) and demanders (buyers), industry trends by item, finding promising items, finding new entrants, finding core companies and items by value chain, and recognizing the patents with corresponding companies, etc. In addition, based on the objectivity and reliability of the analysis results from transaction deals information and financial data, it is expected that value chain network system will be utilized for various purposes such as information support for business evaluation, R&D decision support and mid-term or short-term demand forecasting, in particular to more than 15,000 member companies in Korea, employees in R&D service sectors government-funded research institutes and public organizations. In order to strengthen business competitiveness of companies, technology, patent and market information have been provided so far mainly by government agencies and private research-and-development service companies. This service has been presented in frames of patent analysis (mainly for rating, quantitative analysis) or market analysis (for market prediction and demand forecasting based on market reports). However, there was a limitation to solving the lack of information, which is one of the difficulties that firms in Korea often face in the stage of commercialization. In particular, it is much more difficult to obtain information about competitors and potential candidates. In this study, the real-time value chain analysis and visualization service module based on the proposed network map and the data in hands is compared with the expected market share, estimated sales volume, contact information (which implies potential suppliers for raw material / parts, and potential demanders for complete products / modules). In future research, we intend to carry out the in-depth research for further investigating the indices of competitive factors through participation of research subjects and newly developing competitive indices for competitors or substitute items, and to additively promoting with data mining techniques and algorithms for improving the performance of VCNS.

• Korean Journal of Soil Science and Fertilizer
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• v.9 no.3
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• pp.211-220
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• 1976

The objective of this paper is to summarize and disicuss the results of studies for the prediction of fertilizer demands up to the year of 2000, from the agromic biew points. 1. The approximated demands of fertilizers figured out from the view point of nutrient requirement and fertilizer efficiency of major crops are 1,162,000M/T (N;554,100 M/T, $P_2O_5$; 360,100 M/T and $K_2O$, 247,000 M/T) at 1980, 1,471,400 M/T (N: 694,800 M/T, $P_2O_5$;465,400M/T and $K_2O$ ;311,200 M/T) at 1990 and 1,764,00 M/T (N;812,500 M/T, $P_2O_5$; 592,300 M/T and $K_2O$;359,200 M/T) at 2000${\cdots}{\cdots}$ (Approximation I) 2. Upon the basis of approximation on the yield levels of major crops per unit area and on the expansion of arable land, the demands of fertilizers at the years of 1980, 1990 and 2000 are predicted as 1,149,300 M/T (N;603,700 M/T $P_2O_5$; 305,500 M/T and $K_2O$, 240,100 M/T) 1,551,100 M/T(N:814,700M/T, $P_2O_5$;412,300 M/T and $K_2O$;324,00 M/T) and 2,253,800 M/T (N;1,183,800M/T, $P_2O_5$; 586,400M/T and $K_2O$, 470,900 M/T), respectively${\cdots}{\cdots}$(Approximation II) 3. When the recent relationships between the increases in yeid of major crops and the amounts of fertilizers for those crops per unit area are brought into consideration for the estimation of future demands of fertilizers, the predicted demands at the years of 1980, 1990 and 2000 are 1,287.600 M/T (N;677,100 M/T, $P_2O_5$; 342,000 M/T, and $K_2O$;268,500 M/T), 2,085,600M/T (N;1,096,700 M/T, $P_2O_5$;533,900 M/T, and $K_2O$;435,000 M/T and 3,380,600 M/T (N;1,777,800M/T, $P_2O_5$;897,800M/T and $K_2O$;705,000M/T) respectively (Approximation III) 4. Approximation I will be closer estimate under such condition that only rice will maintain self suficiency and other food crops will be covered by domestic production by around 50 percent, which is not desirable situation. 5. When higher self suficiency leveles of major food crops are sought through the introduction of improved varieties and expansion of cropping area and arable land by increased land utilization and reclamation of hillside land and tidal land, the Approximations II and III will become close to reality, If improved fertilizers and improved method of fertilizer applications are widely applied at the farmers fields to increase the fertilizer efficiency the former will be closer figure, if not, the latter may be better estimates.