• Food Science of Animal Resources
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• v.33 no.5
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• pp.640-645
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• 2013

The purpose of this study was to utilize the results as a basic data of benzoic acids in animal products that didn't mention in the quality standard of National Veterinary Research and Quarantine Service (NVRQS) to solve the conflict of international trade and administration. Set-Pak method listed in the quality standard of NVRQS, faster than auto distillation methods with same recovery selected as a pre treatment for the determination of benzoic acid. The regression curve of benzoic acid with Sep-Pak method was linear with the $R^2$ value of 0.999 and the limit of detection (LOD) and limit of quantitation (LOQ) was 0.058 mg/kg and 0.176 mg/kg, respectively. The benzoic acid in the fermented milk was detected after the fermentation stage by addition of starter culture with the level of 2.28~10.48 mg/kg and 0~16.5 mg/kg in the commercial fermented milk products without detection by the addition of syrup. In case of cheese products, the benzoic acids level was influenced by the curd formation (Camembert cheese) and the quality of natural cheese (processed cheese), by the way, the benzoic acid level of commercial natural cheese was 0~4.2 mg/kg, processed cheese was 0~20.8 mg/kg, respectively. Based on this result, it may be possible to utilize as a basic data for the systematic control the level of natural benzoic acids in raw material, processing and final products of animal origin.

• Journal of Satellite, Information and Communications
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• v.12 no.4
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• pp.78-86
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• 2017

Japan has a lot of interest about weapons systems development of surrounding national and has invested heavily in securing intelligence assets to get information about them, because of conflict issues between Japan and Russia with four northern islands, China with Senkaku Islands and entry policy into the Pacific. Japan has used a large budget to detect and intercept ballistic missile for reasons of the launch of the Taepodong missile in 1998. After took over SIGINT equipments which U.S. force had operated in 1950s~1960s, Japan made a technological analysis and advanced IT technology to produce superior equipments. Japan's SDF has installed them in 19 locations across Japan. In addition, Japan's JASDF has installed advanced early warning RADAR to detect aircraft and high speed ballistic missile entering JADIZ with S-band in 28 locations across Japan. It is possible to detect missile launch preparations, engine tests, and launch moments at any time for operation of 6 satellites high resolution reconnaissance system and 6 aegis ships. In close cooperation with the US, Japan is accessible to the SBIRS networks which detects the launch of a ballistic missile in neighboring countries. In the future, Because the United States wants Japan to act as part of the United States in East, south Asia, it is believed that the exchange of intelligence on the surrounding countries between two countries will be enhanced.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.279-292
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• 2011

Movie is a representative media that can transmit stories to audiences. Basically, a story is described by characters in the movie. Different from other simple videos, movies deploy narrative structures for explaining various conflicts or collaborations between characters. These narrative structures consist of 3 main acts, which are beginning, middle, and ending. The beginning act includes 1) introduction to main characters and backgrounds, and 2) conflicts implication and clues for incidents. The middle act describes the events developed by both inside and outside factors and the story dramatic tension heighten. Finally, in the end act, the events are developed are resolved, and the topic of story and message of writer are transmitted. When story information is extracted from movie, it is needed to consider that it has different weights by narrative structure. Namely, when some information is extracted, it has a different influence to story deployment depending on where it locates at the beginning, middle and end acts. The beginning act is the part that exposes to audiences for story set-up various information such as setting of characters and depiction of backgrounds. And thus, it is necessary to extract much kind information from the beginning act in order to abstract a movie or retrieve character information. Thereby, this paper proposes a novel method for extracting the beginning boundaries. It is the method that detects a boundary scene between the beginning act and middle using the accumulation graph of characters. The beginning act consists of the scenes that introduce important characters, imply the conflict relationship between them, and suggest clues to resolve troubles. First, a scene that the new important characters don't appear any more should be detected in order to extract a scene completed the introduction of them. The important characters mean the major and minor characters, which can be dealt as important characters since they lead story progression. Extra should be excluded in order to extract a scene completed the introduction of important characters in the accumulation graph of characters. Extra means the characters that appear only several scenes. Second, the inflection point is detected in the accumulation graph of characters. It is the point that the increasing line changes to horizontal line. Namely, when the slope of line keeps zero during long scenes, starting point of this line with zero slope becomes the inflection point. Inflection point will be detected in the accumulation graph of characters without extra. Third, several scenes are considered as additional story progression such as conflicts implication and clues suggestion. Actually, movie story can arrive at a scene located between beginning act and middle when additional several scenes are elapsed after the introduction of important characters. We will decide the ratio of additional scenes for total scenes by experiment in order to detect this scene. The ratio of additional scenes is gained as 7.67% by experiment. It is the story inflection point to change from beginning to middle act when this ratio is added to the inflection point of graph. Our proposed method consists of these three steps. We selected 10 movies for experiment and evaluation. These movies consisted of various genres. By measuring the accuracy of boundary detection experiment, we have shown that the proposed method is more efficient.

• Journal of Intelligence and Information Systems
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• v.27 no.4
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• pp.73-95
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• 2021

This study uses Node2vec graph embedding method and Light GBM link prediction to explore undeveloped export candidate countries in Korea's food and beverage industry. Node2vec is the method that improves the limit of the structural equivalence representation of the network, which is known to be relatively weak compared to the existing link prediction method based on the number of common neighbors of the network. Therefore, the method is known to show excellent performance in both community detection and structural equivalence of the network. The vector value obtained by embedding the network in this way operates under the condition of a constant length from an arbitrarily designated starting point node. Therefore, it has the advantage that it is easy to apply the sequence of nodes as an input value to the model for downstream tasks such as Logistic Regression, Support Vector Machine, and Random Forest. Based on these features of the Node2vec graph embedding method, this study applied the above method to the international trade information of the Korean food and beverage industry. Through this, we intend to contribute to creating the effect of extensive margin diversification in Korea in the global value chain relationship of the industry. The optimal predictive model derived from the results of this study recorded a precision of 0.95 and a recall of 0.79, and an F1 score of 0.86, showing excellent performance. This performance was shown to be superior to that of the binary classifier based on Logistic Regression set as the baseline model. In the baseline model, a precision of 0.95 and a recall of 0.73 were recorded, and an F1 score of 0.83 was recorded. In addition, the light GBM-based optimal prediction model derived from this study showed superior performance than the link prediction model of previous studies, which is set as a benchmarking model in this study. The predictive model of the previous study recorded only a recall rate of 0.75, but the proposed model of this study showed better performance which recall rate is 0.79. The difference in the performance of the prediction results between benchmarking model and this study model is due to the model learning strategy. In this study, groups were classified by the trade value scale, and prediction models were trained differently for these groups. Specific methods are (1) a method of randomly masking and learning a model for all trades without setting specific conditions for trade value, (2) arbitrarily masking a part of the trades with an average trade value or higher and using the model method, and (3) a method of arbitrarily masking some of the trades with the top 25% or higher trade value and learning the model. As a result of the experiment, it was confirmed that the performance of the model trained by randomly masking some of the trades with the above-average trade value in this method was the best and appeared stably. It was found that most of the results of potential export candidates for Korea derived through the above model appeared appropriate through additional investigation. Combining the above, this study could suggest the practical utility of the link prediction method applying Node2vec and Light GBM. In addition, useful implications could be derived for weight update strategies that can perform better link prediction while training the model. On the other hand, this study also has policy utility because it is applied to trade transactions that have not been performed much in the research related to link prediction based on graph embedding. The results of this study support a rapid response to changes in the global value chain such as the recent US-China trade conflict or Japan's export regulations, and I think that it has sufficient usefulness as a tool for policy decision-making.