• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.7
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• pp.987-994
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• 2021

The Yellow sea, as described in article 123 of UNCLOS, is semi-enclosed sea surrounded by the Republic of Korea, the People's Republic of China and North Korea. In addition, the Yellow Sea is one of the 66 large marine ecosystems as it contains large amounts of marine resources. According to article 194 of UNCLOS, states should be aware of rights and duties with respect to the protection and preservation of the marine environment to be engaged with countries directly as regional entity or indirectly. Therefore, the legal blank is urgent in terms of trans-boundary environmental pollutant issues. The UNDP has conducted a project called Yellow Sea Large Marine Ecosystem (YSLME) which has reached the 2^nd phase. The project has some notable achievements, namely performing joint activities on analysis of diagnostic trans-boundary issues in collaboration with China and South Korea, developing a strategic action plan based on TDA, and establishing regional strategic action plan. However, on the other hand, the project could not reflect the full participation of North Korea as a state party. As a result, the project has a limitation on effective implementation of RSAP. Therefore, this study focuses on the suggestion of a legally-binding trilateral treaty as a blue print for the next, 3^rd phase of the project. By analyzing the best practice of the Wadden Sea Trilateral Treaty case, the study verifies the validity of legislative measures on establishing and managing a legally-binding trilateral YSLME Commission. By suggesting a three phase treaty, incorporating a joint declaration by establishing the commission, the signing of the treaty, and formulating an umbrella convention and implementation arrangement, the study expects to guarantee the consistency and sustainability of the trilateral treaty regardless of political issues pertaining to North Korea.

• Journal of Korea Water Resources Association
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• v.56 no.4
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• pp.235-243
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• 2023

Due to the revision of the River Act and the enactment of the Act on the Investigation, Planning, and Management of Water Resources, a regular bed change survey has become mandatory and a system is being prepared such that local governments can manage water resources in a planned manner. Since the topography of a bed cannot be measured directly, it is indirectly measured via contact-type depth measurements such as level survey or using an echo sounder, which features a low spatial resolution and does not allow continuous surveying owing to constraints in data acquisition. Therefore, a depth measurement method using remote sensing-LiDAR or hyperspectral imaging-has recently been developed, which allows a wider area survey than the contact-type method as it acquires hyperspectral images from a lightweight hyperspectral sensor mounted on a frequently operating drone and by applying the optimal bandwidth ratio search algorithm to estimate the depth. In the existing hyperspectral remote sensing technique, specific physical quantities are analyzed after matching the hyperspectral image acquired by the drone's path to the image of a surface unit. Previous studies focus primarily on the application of this technology to measure the bathymetry of sandy rivers, whereas bed materials are rarely evaluated. In this study, the existing hyperspectral image-based water depth estimation technique is applied to rivers with vegetation, whereas spatio-temporal hyperspectral imaging and cross-sectional hyperspectral imaging are performed for two cases in the same area before and after vegetation is removed. The result shows that the water depth estimation in the absence of vegetation is more accurate, and in the presence of vegetation, the water depth is estimated by recognizing the height of vegetation as the bottom. In addition, highly accurate water depth estimation is achieved not only in conventional cross-sectional hyperspectral imaging, but also in spatio-temporal hyperspectral imaging. As such, the possibility of monitoring bed fluctuations (water depth fluctuation) using spatio-temporal hyperspectral imaging is confirmed.

• Strategy21
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• s.46
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• pp.239-276
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• 2020

The failure of early economic sanctions aimed at hurting the overall economies of targeted states called for a more sophisticated design of economic sanctions. This paved way for the advent of 'smart sanctions,' which target the supporters of the regime instead of the public mass. Despite controversies over the effectiveness of economic sanctions as a coercive tool to change the behavior of a targeted state, the transformation from 'comprehensive sanctions' to 'smart sanctions' is gaining the status of a legitimate method to impose punishment on states that do not conform to international norms, the nonproliferation of weapons of mass destruction in this particular context of the paper. The five permanent members of the United Nations Security Council proved that it can come to an accord on imposing economic sanctions over adopting resolutions on waging military war with targeted states. The North Korean nuclear issue has been the biggest security threat to countries in the region, even for China out of fear that further developments of nuclear weapons in North Korea might lead to a 'domino-effect,' leading to nuclear proliferation in the Northeast Asia region. Economic sanctions had been adopted by the UNSC as early as 2006 after the first North Korean nuclear test and has continually strengthened sanctions measures at each stage of North Korean weapons development. While dubious of the effectiveness of early sanctions on North Korea, recent sanctions that limit North Korea's exports of coal and imports of oil seem to have an impact on the regime, inducing Kim Jong-un to commit to peaceful talks since 2018. The purpose of this paper is to add a variable to the factors determining the success of economic sanctions on North Korea: preventing North Korea's evasion efforts by conducting illegal transshipments at sea. I first analyze the cause of recent success in the economic sanctions that led Kim Jong-un to engage in talks and add the maritime element to the argument. There are three conditions for the success of the sanctions regime, and they are: (1) smart sanctions, targeting commodities and support groups (elites) vital to regime survival., (2) China's faithful participation in the sanctions regime, and finally, (3) preventing North Korea's maritime evasion efforts.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.23-46
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• 2021

Collaborative filtering, which is often used in personalization recommendations, is recognized as a very useful technique to find similar customers and recommend products to them based on their purchase history. However, the traditional collaborative filtering technique has raised the question of having difficulty calculating the similarity for new customers or products due to the method of calculating similaritiesbased on direct connections and common features among customers. For this reason, a hybrid technique was designed to use content-based filtering techniques together. On the one hand, efforts have been made to solve these problems by applying the structural characteristics of social networks. This applies a method of indirectly calculating similarities through their similar customers placed between them. This means creating a customer's network based on purchasing data and calculating the similarity between the two based on the features of the network that indirectly connects the two customers within this network. Such similarity can be used as a measure to predict whether the target customer accepts recommendations. The centrality metrics of networks can be utilized for the calculation of these similarities. Different centrality metrics have important implications in that they may have different effects on recommended performance. In this study, furthermore, the effect of these centrality metrics on the performance of recommendation may vary depending on recommender algorithms. In addition, recommendation techniques using network analysis can be expected to contribute to increasing recommendation performance even if they apply not only to new customers or products but also to entire customers or products. By considering a customer's purchase of an item as a link generated between the customer and the item on the network, the prediction of user acceptance of recommendation is solved as a prediction of whether a new link will be created between them. As the classification models fit the purpose of solving the binary problem of whether the link is engaged or not, decision tree, k-nearest neighbors (KNN), logistic regression, artificial neural network, and support vector machine (SVM) are selected in the research. The data for performance evaluation used order data collected from an online shopping mall over four years and two months. Among them, the previous three years and eight months constitute social networks composed of and the experiment was conducted by organizing the data collected into the social network. The next four months' records were used to train and evaluate recommender models. Experiments with the centrality metrics applied to each model show that the recommendation acceptance rates of the centrality metrics are different for each algorithm at a meaningful level. In this work, we analyzed only four commonly used centrality metrics: degree centrality, betweenness centrality, closeness centrality, and eigenvector centrality. Eigenvector centrality records the lowest performance in all models except support vector machines. Closeness centrality and betweenness centrality show similar performance across all models. Degree centrality ranking moderate across overall models while betweenness centrality always ranking higher than degree centrality. Finally, closeness centrality is characterized by distinct differences in performance according to the model. It ranks first in logistic regression, artificial neural network, and decision tree withnumerically high performance. However, it only records very low rankings in support vector machine and K-neighborhood with low-performance levels. As the experiment results reveal, in a classification model, network centrality metrics over a subnetwork that connects the two nodes can effectively predict the connectivity between two nodes in a social network. Furthermore, each metric has a different performance depending on the classification model type. This result implies that choosing appropriate metrics for each algorithm can lead to achieving higher recommendation performance. In general, betweenness centrality can guarantee a high level of performance in any model. It would be possible to consider the introduction of proximity centrality to obtain higher performance for certain models.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.19-38
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• 2017

Collaborative filtering (CF) algorithm has been popularly used for implementing recommender systems. Until now, there have been many prior studies to improve the accuracy of CF. Among them, some recent studies adopt 'hybrid recommendation approach', which enhances the performance of conventional CF by using additional information. In this research, we propose a new hybrid recommender system which fuses CF and the results from the social network analysis on trust and distrust relationship networks among users to enhance prediction accuracy. The proposed algorithm of our study is based on memory-based CF. But, when calculating the similarity between users in CF, our proposed algorithm considers not only the correlation of the users' numeric rating patterns, but also the users' in-degree centrality values derived from trust and distrust relationship networks. In specific, it is designed to amplify the similarity between a target user and his or her neighbor when the neighbor has higher in-degree centrality in the trust relationship network. Also, it attenuates the similarity between a target user and his or her neighbor when the neighbor has higher in-degree centrality in the distrust relationship network. Our proposed algorithm considers four (4) types of user relationships - direct trust, indirect trust, direct distrust, and indirect distrust - in total. And, it uses four adjusting coefficients, which adjusts the level of amplification / attenuation for in-degree centrality values derived from direct / indirect trust and distrust relationship networks. To determine optimal adjusting coefficients, genetic algorithms (GA) has been adopted. Under this background, we named our proposed algorithm as SNACF-GA (Social Network Analysis - based CF using GA). To validate the performance of the SNACF-GA, we used a real-world data set which is called 'Extended Epinions dataset' provided by 'trustlet.org'. It is the data set contains user responses (rating scores and reviews) after purchasing specific items (e.g. car, movie, music, book) as well as trust / distrust relationship information indicating whom to trust or distrust between users. The experimental system was basically developed using Microsoft Visual Basic for Applications (VBA), but we also used UCINET 6 for calculating the in-degree centrality of trust / distrust relationship networks. In addition, we used Palisade Software's Evolver, which is a commercial software implements genetic algorithm. To examine the effectiveness of our proposed system more precisely, we adopted two comparison models. The first comparison model is conventional CF. It only uses users' explicit numeric ratings when calculating the similarities between users. That is, it does not consider trust / distrust relationship between users at all. The second comparison model is SNACF (Social Network Analysis - based CF). SNACF differs from the proposed algorithm SNACF-GA in that it considers only direct trust / distrust relationships. It also does not use GA optimization. The performances of the proposed algorithm and comparison models were evaluated by using average MAE (mean absolute error). Experimental result showed that the optimal adjusting coefficients for direct trust, indirect trust, direct distrust, indirect distrust were 0, 1.4287, 1.5, 0.4615 each. This implies that distrust relationships between users are more important than trust ones in recommender systems. From the perspective of recommendation accuracy, SNACF-GA (Avg. MAE = 0.111943), the proposed algorithm which reflects both direct and indirect trust / distrust relationships information, was found to greatly outperform a conventional CF (Avg. MAE = 0.112638). Also, the algorithm showed better recommendation accuracy than the SNACF (Avg. MAE = 0.112209). To confirm whether these differences are statistically significant or not, we applied paired samples t-test. The results from the paired samples t-test presented that the difference between SNACF-GA and conventional CF was statistical significant at the 1% significance level, and the difference between SNACF-GA and SNACF was statistical significant at the 5%. Our study found that the trust/distrust relationship can be important information for improving performance of recommendation algorithms. Especially, distrust relationship information was found to have a greater impact on the performance improvement of CF. This implies that we need to have more attention on distrust (negative) relationships rather than trust (positive) ones when tracking and managing social relationships between users.

• Parasites, Hosts and Diseases
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• v.21 no.2
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• pp.246-256
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• 1983

As epidemiological parameters of human paragonimiasis, the positive rates of intradermal test and the sputum/stool ekaminations have long been employed in population surveys. However, both the specificity of the intradermal test and the sensitivity of sputumjstool examination have been gradually declined as the endemicity was lowered; thus the gap between above two parameters widened. In such context, the development of a new epidemiologic parameter or tool which makes it possible to accurately discriminate the active paragonimiasis cases was necessary. In the present study, the detection rate of Paragonimus-speclac IgG antibody by micro-ELISA was evaluated as an indicator of epidemiologic status of human paragonimiasis in a population. A total of 4, 285 students and inhabitants living in Bukpyeong Myeon and Bukil Myeon, Haenam Gun, Jeonlanam Do was surveyed in October, 1983 by intradermal test first. Out of them, 244 cases (5.7%) were found positively reacted to VBS antigen of F. westermani. Out of 168 positive reactors, 7 cases (4.2%) were egg positive either by two times of sputum examination or by one stool examination. That indicated that only 0. 16% of total surveyed were confirmed as active paragonimiasis by egg detection. When sera collected from 239 positive reactors of Intradermal test were tested by micro-ELISA for their specific IgG antibody, 40 cases(16.7%) were found to be positive. All of 7 egg positive cases were again positive for specific IgG antibody. Among remaining 232 intradermal test positive cases, 33 cases were positive for IgG antibody. In contrast to those, none of 42 positive reactors to intradermal test for Cloncrchis and of 128 intradermal test negative cases showed positive for Paragcnimus-specIfic IgG antibody. The rate of specific IgG antibody as detected by micro-ELISA appeared to be increased with the wheal size of the intradermal test. When the wheal sixte was over 13mm in diameter, about 50% of them were positive for specific IgG antibody. Thirty-one specific antibody positive cases were clinically evaluated by laboratory examinations (repeated sputum examination, peripheral eosinophil count and chest roentgenogram) and by history taking. Out of them 24 cases were associated with one or more positive laboratory findings: thus considered as active paragonimiasis cases. Out of 7 lab. finding-free cases 3 revealed past history of typical paragonimiasis symptoms, suggesting that they were in chronic or in convalescent stages. The remaining 4 cases were considered as either mild or ectopic infection cases; the possibility of cross-reaction with other helminthiases could not be ruled out. From the above results, it was inferred that the detection of Paragonimus-specIfic IgG antibody by micro-ELISA was very much helpful in detecting the active cases as well as in proper evaluation of the endemicity of human paragonimiasis in a population. The convenience of mass haildling of sera in micro-ELISA was considered another superiority as an epidemiologic tool.

• Korean Journal of Medicinal Crop Science
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• v.10 no.3
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• pp.222-229
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• 2002

Ixeris dentata root were extracted with methanol and then fractionated with n-hexane, EtOAc and BuOH to get active fractions. and their antioxidant and antimicrobial activities in each fraction were determined. Ethyl acetate fraction of Ixeris dentata root showed strong antioxidant activities, but aqueous fraction did not show any activities. But in the antimicrobial test, aqueous fraction showed strong antimicrobial activities except to Escherichia coli. especially, aqueous fraction showed the strongest activities against Hypocrea nigricans. and butanol fraction showed the strongest activities against Cladosporium herbarum. This study was performed to determine the antimutagenic and cytotoxic effect of Ixeris dentata root methanol extract on Salmonella typhimurium TA98, TA100 and cancer cell lines using ames test and cytotoxicity assay, respectively. Cancer cell lines include human lung carcinoma(A549), human breast adenocarcinoma(MCF-7) and human hepatocellular carcinoma (Hep 3B). Futher fractionations with hexane, ethyl acetate, butanol and water from methanol extract of Ixeris dentata root were performed to obtain effective fraction, methanol extracts showed 79.94% inhibitory effect on the mutagenesis induced by N' -methyl- N' -nitro-N-nitrosoguanidine(MNNG) against TA100, while 89.99% inhibition was observed on the mutagenesis induced by 4-nitroquinoline-1-oxide(4NQO) against TA98. In the meanwhile, butanol fraction showed 89.92% and 71.01% inhibitory effect on the mutagenesis induced by benzo(a)pyrene(B(a)P) against TA98 and TA100, respectively. Ethyl acetate fraction showed the strongest effect against A549, MCF-7 and Hep3B at the same concentration compared to those of other fration.

• Korean Journal of Environmental Biology
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• v.17 no.4
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• pp.439-448
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• 1999

To investigate the population dynamics and survival of Genus Vibrio, population densities of aerobic saprophytic bacteria and Vibrio groups were measured 4 times in the intertidal waters of the Yellow Sea near Kunsan from November, 1997 to June, 1998. The distribution of heterotrophic bacteria during the survey periods by plate count and direct count method ranged from 1.2$\pm$0.6$\times$10$^3$~2.0$\pm$1.5$\times$10$^4$CFU ml­$^1$and from 6.0$\pm$4.0$\times$10$^{5}$ ~1.9$\pm$1.5$\times$10$^{7}$ cells ml­$^1$, respectively. Vibrio groups were distributed in the range of 1$\times$10 and 6$\pm$2.2$\times$10$^2$CFU ml­$^1$. The proportion of Vibrio groups to total heterotrophic bacteria was between 0.1 and 6% during the survey periods. A total of 51 isolates was obtained from TCBS agar plates and identified to species level by Biolog Identification System$^{TM}$. As a result, dominant genera were V, mediterranei, V aitguillarum, tr metschnikovii, and V. parahaemolyticus, and isolates were clustered into 26 groups based on the relatedness of average linkage clustering method at 70% level. As for the susceptibility of 51 isolates to 7 kinds of antibacterial agents (gentamicin, ampicillin, chlorarnphenicol, streptomycin, kanamycin, tetracycline, carbenicillin), 96% of isolates showed high resistance to more than one antibiotics and 65% of isolates contained a plasmid, of which size was observed greater than 12 kb, The number of cells of 3 tested strains (V. anguillarum, V. vulnificus, and V. metschnikovii) in filtered aged seawater decreased by approximately 1 to 5 orders of magnitude during 30-d incubation. In most cases, the numbers of cells decreased rapidly until day 3, then decreased slowly by day 30. The number of cells incubated at 15$^{\circ}C$ showed higher survival than those at 4$^{\circ}C$ and $25^{\circ}C$. These results may be considered for the basic supporting data in the risk assessment of vibriosis in summer.r.

• Korean Journal of Agricultural and Forest Meteorology
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• v.17 no.4
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• pp.358-383
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• 2015

The concept of 'carbon footprint' has been developed as a means of quantifying the specific emissions of the greenhouse gases (GHGs) that cause global warming. Although there are still neither clear definitions of the term nor rules for units or the scope of its estimation, it is broadly accepted that the carbon footprint is the total amount of GHGs, expressed as $CO_2$ equivalents, emitted into the atmosphere directly or indirectly at all processes of the production by an individual or organization. According to the ISO/TS 14067, the carbon footprint of a product is calculated by multiplying the units of activity of processes that emit GHGs by emission factor of the processes, and by summing them up. Based on this, 'carbon labelling' system has been implemented in various ways over the world to provide consumers the opportunities of comparison and choice, and to encourage voluntary activities of producers to reduce GHG emissions. In the agricultural sector, as a judgment basis to help purchaser with ethical consumption, 'low-carbon agricultural and livestock products certification' system is expected to have more utilization value. In this process, the 'cradle to gate' approach (which excludes stages for usage and disposal) is mainly used to set the boundaries of the life cycle assessment for agricultural products. The estimation of carbon footprint for the entire agricultural and forestry sector should take both removals and emissions into account in the "National Greenhouse Gas Inventory Report". The carbon accumulation in the biomass of perennial trees in cropland should be considered also to reduce the total GHG emissions. In order to accomplish this, tower-based flux measurements can be used, which provide a direct quantification of $CO_2$ exchange during the entire life cycle. Carbon footprint information can be combined with other indicators to develop more holistic assessment indicators for sustainable agricultural and forestry ecosystems.

• Clinical and Experimental Pediatrics
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• v.49 no.11
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• pp.1216-1222
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• 2006

Purpose : Though atopic and nonatopic asthma have different clinical manifestations, bronchial hyperresponsiveness (BHR) and airway inflammations are common characteristics of them. We investigated BHR to both methacholine and adenosine 5'-monophosphate (AMP), and their relationships with blood eosinophil markers in nonatopic asthma as well as atopic asthma. Methods : We studied 116 children (82 atopics; 34 nonatopics) with mild to moderate asthma. Methacholine and AMP challenge tests were performed and bronchial responsiveness was expressed as $PC_{20}$ (provocative concentration causing a 20 percent fall in $FEV_1$); blood eosinopil counts (ETCs) and serum eosinophil cationic protein (ECP) levels were gauged. Results : In atopics, 95.1 percent and 90.2 percent showed hyperreactivity to methacholine ($PC_{20}$<16 mg/mL) and AMP ($PC_{20}$<200 mg/mL), respectively. Meanwhile, in nonatopics, 94.1 percent and 52.9 percent displayed hyperreactivity to methacholine and AMP, respectively. The geometric mean of AMP $PC_{20}$ was lower in atopics (31.6 mg/mL) than in nonatopics (125.9 mg/mL); that of methacholine $PC_{20}$ was similar in the two groups. AMP $PC_{20}$ correlated with blood ETCs in both atopics(r=-0.30, P<0.01) and nonatopics (r=-0.57, P<0.01), and correlated with serum ECP levels (r=-0.23, P<0.01) in atopics, but not in nonatopics. Apart from AMP, methacholine $PC_{20}$ was not associated with blood eosinophil markers in either group. Conclusion : Atopics more frequently displayed BHR to AMP than nonatopics. Furthermore, BHR to AMP was associated with not only blood ETCs, but serum ECP levels in atopics but was correlated with only blood ETCs in nonatopics. Those results suggest that BHR to AMP reflects airway inflammation in asthma and is more related to atopy.