• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.23 no.1
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• pp.1-19
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• 2018

In order to compare significant wave height (SWH) data from multi-satellites (GFO, Jason-1, Envisat, Jason-2, Cryosat-2, SARAL) and SWH measurements from Ieodo Ocean Research Station (IORS), we constructed a 12 year matchup database between satellite and IORS measurements from December 2004 to May 2016. The satellite SWH showed a root mean square error (RMSE) of about 0.34 m and a positive bias of 0.17 m with respect to the IORS wave height. The satellite data and IORS wave height data did not show any specific seasonal variations or interannual variability, which confirmed the consistency of satellite data. The effect of the wind field on the difference of the SWH data between satellite and IORS was investigated. As a result, a similar result was observed in which a positive biases of about 0.17 m occurred on all satellites. In order to understand the effects of topography and the influence of the construction structures of IORS on the SWH differences, we investigated the directional dependency of differences of wave height, however, no statistically significant characteristics of the differences were revealed. As a result of analyzing the characteristics of the error as a function of the distance between the satellite and the IORS, the biases are almost constant about 0.14 m regardless of the distance. By contrast, the amplitude of the SWH differences, the maximum value minus the minimum value at a given distance range, was found to increase linearly as the distance was increased. On the other hand, as a result of the accuracy evaluation of the satellite SWH from the Donghae marine meteorological buoy of Korea Meteorological Administration, the satellite SWH presented a relatively small RMSE of about 0.27 m and no specific characteristics of bias such as the validation results at IORS. In this paper, we propose a conversion formula to correct the significant wave data of IORS with the satellite SWH data. In addition, this study emphasizes that the reliability of data should be prioritized to be extensively utilized and presents specific methods and strategies in order to upgrade the IORS as an international world-wide marine observation site.

• Journal of Food Hygiene and Safety
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• v.34 no.5
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• pp.454-462
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• 2019

A conventional Korean meal typically includes various roasted, steamed, stir-fried, and braised foods. For this study, we investigated the contents of water soluble vitamins, $B_1$ (thiamin), $B_2$ (riboflavin) and $B_3$ (niacin) in various roasted, steamed, stir-fried, and braised foods. Method validation for analytical data in this study showed a high linearity ($r^2$>0.999), and the limit of detection and quantification were 0.001-0.067 and $0.002-0.203{\mu}g/mL$, respectively. For accuracy and precision, analytical values using standard reference materials were in the certified ranges. Roasted foods contained 0.039-1.057 mg/100 g of thiamin, 0.058-0.686 mg/100 g of riboflavin and 0.021-21.772 mg/100 g of niacin. Steamed foods contained 0.049-1.066 mg/100 g of thiamin, 0.025-0.548 mg/100 g of riboflavin and 0.134-21.509 mg/100 g of niacin. Stir-fried foods contained 0.114-0.388 mg/100 g of thiamin, 0.014-1.258 mg/100 g of riboflavin and 0.015-2.319 mg/100 g of niacin. Braised foods contained 0.112-1.656 mg/100 g of thiamin, 0.024-0.298 mg/100 g of riboflavin and 0.322-2.157 mg/100 g of niacin. The data on water-soluble vitamins in this study can be used for a nutritional database of conventional Korean meals.

• 한국노년학
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• v.36 no.4
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• pp.1003-1024
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• 2016

The human rights of older people have gotten more attention recently in South Korea, a country that is in transition to a super-aged society. This study aimed to systematically review studies on elder abuse and related factors among community-dwelling older adults in South Korea over twenty years (1994-2016). We searched major databases (Riss, DBpia, KISS, KMbase, and PubMed) and identified published studies relevant to the topic. Based on inclusion and exclusion criteria related to study quality, a total of 31 studies were selected for this review. We examined types, measurements, and risk factors of elder abuse as well as study designs in the selected studies, guided by Johannesen's theoretical framework on elder abuse. All of the reviewed studies on elder abuse in Korea were cross-sectional studies, most of which focused on older people living in urban areas, using a non-random sampling method. All of the studies focused on certain types of elder abuse only. Some adopted elder-abuse instruments that were not validated, and others used self-developed instruments without psychometric tests. As for the risk factors of elder abuse in South Korea, the physical and mental health of the victims and aggressors impacted the risk of elder abuse, but general sociodemographic factors such as age, sex, and education were less likely to be related to the risk. In addition, decreasing caregiver burden and building elder-friendly communities are important for the prevention of elder abuse. Needed are further empirical studies on elder abuse with a theoretical framework that gives consideration to the unique sociocultural contexts of Korea. It is also recommended to develop instruments to measure elder abuse reflecting the sociocultural contexts of Korea, and to examine the multi-dimensional risk factors of elder abuse.

• Journal of Food Hygiene and Safety
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• v.34 no.4
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• pp.404-411
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• 2019

This study was carried out to investigate the antioxidant effects of extracts from 9 species of forest plants in Korea. DPPH, ABTS, $NaNO_2$, hydrogen peroxide radical scavenging activity and reducing power activity were evaluated to measure the antioxidant activities of plant extracts. As a result, Geranium thunbergii has been identified as the most effective antioxidant resource. Also, total phenolic content was highest in Geranium thunbergii ($303.94{\pm}0.63mg\;GAE/g$) among 9 species extracts. Total flavonoid content was highest in Rosa multiflora ($24.32{\pm}0.22mg\;QE/g$) and proanthocyanidin content was highest in Vitis ficifolia ($279.00{\pm}4.58mg\;CE/g$) among 9 species extracts. In addition, the protective effect of plant extracts in $H_2O_2-induced$ human dermal fibroblast (HDF) cell systems were also assessed. Significant protective effects in $H_2O_2-induced$ human dermal fibroblast (HDF) cell systems were found in all plant extracts, especially in Geranium thunbergii. These results suggest that Geranium thunbergii could be a potential natural resource for antioxidant activity.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1505-1514
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• 2022

Image matching is a crucial preprocessing step for effective utilization of multi-temporal and multi-sensor very high resolution (VHR) satellite images. Deep learning (DL) method which is attracting widespread interest has proven to be an efficient approach to measure the similarity between image pairs in quick and accurate manner by extracting complex and detailed features from satellite images. However, Image matching of VHR satellite images remains challenging due to limitations of DL models in which the results are depending on the quantity and quality of training dataset, as well as the difficulty of creating training dataset with VHR satellite images. Therefore, this study examines the feasibility of DL-based method in matching pair extraction which is the most time-consuming process during image registration. This paper also aims to analyze factors that affect the accuracy based on the configuration of training dataset, when developing training dataset from existing multi-sensor VHR image database with bias for DL-based image matching. For this purpose, the generated training dataset were composed of correct matching pairs and incorrect matching pairs by assigning true and false labels to image pairs extracted using a grid-based Scale Invariant Feature Transform (SIFT) algorithm for a total of 12 multi-temporal and multi-sensor VHR images. The Siamese convolutional neural network (SCNN), proposed for matching pair extraction on constructed training dataset, proceeds with model learning and measures similarities by passing two images in parallel to the two identical convolutional neural network structures. The results from this study confirm that data acquired from VHR satellite image database can be used as DL training dataset and indicate the potential to improve efficiency of the matching process by appropriate configuration of multi-sensor images. DL-based image matching techniques using multi-sensor VHR satellite images are expected to replace existing manual-based feature extraction methods based on its stable performance, thus further develop into an integrated DL-based image registration framework.

• Korean Journal of Psychosomatic Medicine
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• v.30 no.2
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• pp.155-164
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• 2022

Objectives : A growing body of evidence links type 2 diabetes (T2D) with a neurodegenerative disease (ND) such as Alzheimer's disease and Parkinson's disease. The purpose of this study is to investigate the relationship between NDs and the development of T2D by comparing the incidence of T2D in a group of various NDs (ND group) and control group. Methods : A population-based 10-year follow-up study was conducted using the Korean National Health Information Database for 2002-2015. We used a retrospective cohort study design to investigate the association of ND with T2D occurrence. The study population included ND (n=8,814) and control (n=37,970) groups, all aged 60 years or over. The Kaplan-Meier method was used to estimate the risk of developing T2D as a function of time. Cox proportional hazards regression models were used to evaluate the relationship between ND and T2D. Results : T2D was developed in a significantly higher percentage of patients in the ND group (53.6%) than in the control group (44.7%). The ND group increased the risk of T2D (HR, 1.43; 95% CI, 1.38-1.47). About one-third of patients in both groups were additionally diagnosed with another ND before the occurrence of T2D during a 10-year follow-up period. When compared to those who did not have another ND during the follow-up period, the incidence of T2D in those who were additionally diagnosed with another ND was higher in both the ND and control groups. Conclusions : The ND group had about 1.4 times higher risk of developing T2D than the control group. Our results showed a positive association between ND and T2D.

• Journal of the Daesoon Academy of Sciences
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• v.27
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• pp.201-243
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• 2016

This paper analyzes the research trends from 358 scholarly articles published in the Journal of Daesoon Academy of Sciences from the first published journal in 1996 to the most recent journal published on the 25^th of 2015 and proposes ideas for improvement. First of all, "The Journal of Daesoon Academy of Sciences" does not meet the standards required by the National Research Foundation, falling short of the most important conditions for the registration such as the periodicity and punctuality expected from academic journals. Furthermore, in terms of the Bibliometrical analysis, the number of articles published by the journal is decreasing and the consistency, with regards to rules and principles regulating publication details and bibliography formats, is nonexistent. Although various authors seemed to be meeting these criteria on the surface, the ratio of co-authored articles is too small. Securing researchers specializing in Daesoon Thought for expanding the size of the journal is important, but it is also important to diversify the research topics through exchanging ideas among researchers from various organizations. Here are some ideas for the improvement of the Journal of Daesoon Academy of Sciences: First, in order to meet the standards for punctuality and periodicity, it would be best to publish the journal twice a year with 12 to 15 articles. Second, the journal must become searchable through the creation of a database. Third, the key words and abstracts of articles must be written in Korean and English to facilitate the sharing of articles among researchers. Fourth, the journal must have a diverse and outstanding editorial board which takes into account the geographical situations of its board members. Fifth, the Journal must include articles on relevant topics that reflect the core topics of the Daesoon Thought and other studies. Sixth, articles must have a front page that contains bibliographical items to convey information to the reader. Seventh, it is essential that the journal have a clear publication date detailing the year, month, and day as well as a standard numbering scheme (i.e, Vol. and no).

• Journal of Wetlands Research
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• v.25 no.4
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• pp.335-344
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• 2023

Brachydiplax chalybea flavovittata, a climate-sensitive biological indicator species, was first observed and recorded at Jeju Island in Korea in 2010. Overwintering was recently confirmed in the Yeongsan River area. This study was aimed to predict the potential distribution patterns for the larvae of B. chalybea flavovittata and to understand its ecological characteristics as well as changes of population under global climate change circumstances. Data was collected both from the Global Biodiversity Information Facility (GBIF) and by field surveys from May 2019 to May 2023. We used for the distribution model among downloaded 19 variables from the WorldClim database. MaxEnt model was adopted for the prediction of potential and future distribution for B. chalybea flavovittata. Larval distribution ranged within a region delimited by northern latitude from Jeju-si, Jeju Special Self-Governing Province (33.318096°) to Yeoju-si, Gyeonggi-do (37.366734°) and eastern longitude from Jindo-gun, Jeollanam-do (126.054925°) to Yangsan-si, Gyeongsangnam-do (129.016472°). M type (permanent rivers, streams and creeks) wetlands were the most common habitat based on the Ramsar's wetland classification system, followed by Tp type (permanent freshwater marshes and pools) (45.8%) and F type (estuarine waters) (4.2%). MaxEnt model presented that potential distribution with high inhabiting probability included Ulsan and Daegu Metropolitan City in addition to the currently discovered habitats. Applying to the future scenarios by Intergovernmental Panel on Climate Change (IPCC), it was predicted that the possible distribution area would expand in the 2050s and 2090s, covering the southern and western coastal regions, the southern Daegu metropolitan area and the eastern coastal regions in the near future. This study suggests that B. chalybea flavovittata can be used as an effective indicator species for climate changes with a monitoring of their distribution ranges. Our findings will also help to provide basic information on the conservation and management of co-existing native species.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.53-77
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• 2012

This study analyses the difference of contents and tones of arguments among three Korean major newspapers, the Kyunghyang Shinmoon, the HanKyoreh, and the Dong-A Ilbo. It is commonly accepted that newspapers in Korea explicitly deliver their own tone of arguments when they talk about some sensitive issues and topics. It could be controversial if readers of newspapers read the news without being aware of the type of tones of arguments because the contents and the tones of arguments can affect readers easily. Thus it is very desirable to have a new tool that can inform the readers of what tone of argument a newspaper has. This study presents the results of clustering and classification techniques as part of text mining analysis. We focus on six main subjects such as Culture, Politics, International, Editorial-opinion, Eco-business and National issues in newspapers, and attempt to identify differences and similarities among the newspapers. The basic unit of text mining analysis is a paragraph of news articles. This study uses a keyword-network analysis tool and visualizes relationships among keywords to make it easier to see the differences. Newspaper articles were gathered from KINDS, the Korean integrated news database system. KINDS preserves news articles of the Kyunghyang Shinmun, the HanKyoreh and the Dong-A Ilbo and these are open to the public. This study used these three Korean major newspapers from KINDS. About 3,030 articles from 2008 to 2012 were used. International, national issues and politics sections were gathered with some specific issues. The International section was collected with the keyword of 'Nuclear weapon of North Korea.' The National issues section was collected with the keyword of '4-major-river.' The Politics section was collected with the keyword of 'Tonghap-Jinbo Dang.' All of the articles from April 2012 to May 2012 of Eco-business, Culture and Editorial-opinion sections were also collected. All of the collected data were handled and edited into paragraphs. We got rid of stop-words using the Lucene Korean Module. We calculated keyword co-occurrence counts from the paired co-occurrence list of keywords in a paragraph. We made a co-occurrence matrix from the list. Once the co-occurrence matrix was built, we used the Cosine coefficient matrix as input for PFNet(Pathfinder Network). In order to analyze these three newspapers and find out the significant keywords in each paper, we analyzed the list of 10 highest frequency keywords and keyword-networks of 20 highest ranking frequency keywords to closely examine the relationships and show the detailed network map among keywords. We used NodeXL software to visualize the PFNet. After drawing all the networks, we compared the results with the classification results. Classification was firstly handled to identify how the tone of argument of a newspaper is different from others. Then, to analyze tones of arguments, all the paragraphs were divided into two types of tones, Positive tone and Negative tone. To identify and classify all of the tones of paragraphs and articles we had collected, supervised learning technique was used. The Na$\ddot{i}$ve Bayesian classifier algorithm provided in the MALLET package was used to classify all the paragraphs in articles. After classification, Precision, Recall and F-value were used to evaluate the results of classification. Based on the results of this study, three subjects such as Culture, Eco-business and Politics showed some differences in contents and tones of arguments among these three newspapers. In addition, for the National issues, tones of arguments on 4-major-rivers project were different from each other. It seems three newspapers have their own specific tone of argument in those sections. And keyword-networks showed different shapes with each other in the same period in the same section. It means that frequently appeared keywords in articles are different and their contents are comprised with different keywords. And the Positive-Negative classification showed the possibility of classifying newspapers' tones of arguments compared to others. These results indicate that the approach in this study is promising to be extended as a new tool to identify the different tones of arguments of newspapers.

• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.57-77
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• 2013

Social media has become one of the most popular media in web and mobile application. In 2011, social networks and blogs are still the top destination of online users, according to a study from Nielsen Company. In their studies, nearly 4 in 5active users visit social network and blog. Social Networks and Blogs sites rule Americans' Internet time, accounting to 23 percent of time spent online. Facebook is the main social network that the U.S internet users spend time more than the other social network services such as Yahoo, Google, AOL Media Network, Twitter, Linked In and so on. In recent trend, most of the companies promote their products in the Facebook by creating the "Facebook Page" that refers to specific product. The "Like" option allows user to subscribed and received updates their interested on from the page. The film makers which produce a lot of films around the world also take part to market and promote their films by exploiting the advantages of using the "Facebook Page". In addition, a great number of streaming service providers allows users to subscribe their service to watch and enjoy movies and TV program. They can instantly watch movies and TV program over the internet to PCs, Macs and TVs. Netflix alone as the world's leading subscription service have more than 30 million streaming members in the United States, Latin America, the United Kingdom and the Nordics. As the matter of facts, a million of movies and TV program with different of genres are offered to the subscriber. In contrast, users need spend a lot time to find the right movies which are related to their interest genre. Recent years there are many researchers who have been propose a method to improve prediction the rating or preference that would give the most related items such as books, music or movies to the garget user or the group of users that have the same interest in the particular items. One of the most popular methods to build recommendation system is traditional Collaborative Filtering (CF). The method compute the similarity of the target user and other users, which then are cluster in the same interest on items according which items that users have been rated. The method then predicts other items from the same group of users to recommend to a group of users. Moreover, There are many items that need to study for suggesting to users such as books, music, movies, news, videos and so on. However, in this paper we only focus on movie as item to recommend to users. In addition, there are many challenges for CF task. Firstly, the "sparsity problem"; it occurs when user information preference is not enough. The recommendation accuracies result is lower compared to the neighbor who composed with a large amount of ratings. The second problem is "cold-start problem"; it occurs whenever new users or items are added into the system, which each has norating or a few rating. For instance, no personalized predictions can be made for a new user without any ratings on the record. In this research we propose a clustering method according to the users' genre interest extracted from social network service (SNS) and user's movies rating information system to solve the "cold-start problem." Our proposed method will clusters the target user together with the other users by combining the user genre interest and the rating information. It is important to realize a huge amount of interesting and useful user's information from Facebook Graph, we can extract information from the "Facebook Page" which "Like" by them. Moreover, we use the Internet Movie Database(IMDb) as the main dataset. The IMDbis online databases that consist of a large amount of information related to movies, TV programs and including actors. This dataset not only used to provide movie information in our Movie Rating Systems, but also as resources to provide movie genre information which extracted from the "Facebook Page". Formerly, the user must login with their Facebook account to login to the Movie Rating System, at the same time our system will collect the genre interest from the "Facebook Page". We conduct many experiments with other methods to see how our method performs and we also compare to the other methods. First, we compared our proposed method in the case of the normal recommendation to see how our system improves the recommendation result. Then we experiment method in case of cold-start problem. Our experiment show that our method is outperform than the other methods. In these two cases of our experimentation, we see that our proposed method produces better result in case both cases.