• Journal of Applied Biological Chemistry
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• v.65 no.3
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• pp.121-128
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• 2022

This study explored plant-derived natural antioxidants by evaluating the antioxidant activity of Lamiaceae plant seed extracts. Plants with the percentage of filled seeds at or above 90% and seed germination at or above 50% were selected. Of the ten species studied, the total phenolic content of the seeds was high in the species Phlomis umbrosa Turcz. (6.2 mg GAEs/g of seeds) and Elsholtzia ciliata (Thunb.) Hyl. (4.5 mg GAEs/g of seeds). The total flavonoid content of the seeds was high in E. ciliata (1.0 mg QEs/g of seeds) and P. umbrosa (0.6 mg QEs/g of seeds). Based on the EC₅₀ value of the seed extracts, 2,2-diphenyl-1-picrylhydrazyl radical scavenging activity was high in the seeds of the plants E. ciliata (27.5 ㎍/mL), Mosla dianthera (Buch.-Ham. ex Roxb.) Maxim. (29.2 ㎍/mL), and Prunella vulgaris var. lilacina Nakai (33.3 ㎍/mL). In addition, 2,2'-Azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) radical scavenging activity was high in P. vulgaris var. lilacina (25.6 ㎍/mL), E. ciliata (25.9 ㎍/mL), and M. dianthera (27.6 ㎍/mL) seeds. The ferric reducing antioxidant power of the seed extracts was high in P. vulgaris var. lilacina (2910.4 µM Fe(II)/g of extract), E. ciliata (2836.2 µM Fe(II)/g of extract), and M. dianthera (2754.4 µM Fe(II)/g of extract). According to the cluster analysis based on antioxidant activity, the seeds of the ten species were classified into three groups, from group 1 with low antioxidant activity to group 3 with high antioxidant activity; E. ciliata, M. dianthera, and P. vulgaris var. lilacina were classified as group 3.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.5
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• pp.835-842
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• 2022

Several countries are establishing management systems for aquaculture environment, and fishery environment assessment is one of them. The fishery management law amended in 2013 stipulates that a fishery environment assessment should be performed when a fish cage farm's license is extended. The purpose of the fishery environment assessment is to promote sustainable fishery, increase the fishery production capacity, and increase the fishermen incoming by implementing evaluation and improvement measures through scientific methods. The analysis items of fishery environment assessment include the Benthic Health Index (BHI), which is a biological index based on the macrobenthic polychaetes community, and total organic carbon (TOC), and the two items are scored and used for evaluation as a single grade. This study explains the selection process of BHI and TOC, which are evaluation items for fishing ground, and ecological significance of the calculated evaluation grades.

• Journal of Korean Society of Archives and Records Management
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• v.23 no.3
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• pp.63-87
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• 2023

The study aims to investigate research trends in the UK records management field and compare the results with domestic research by analyzing research articles published in Archives and Records for the UK's research trends and The Korean Journal of Archival Studies (KJAS) for domestic ones. The study analyzed 318 articles published in KJAS and 142 articles published in Archives and Records since 2013, when the journal changed its title from Journal of the Society of Archivists, to investigate the distribution of authors, including the ratio of coauthorship and authors' affiliations. A set of 1,251 unique terms were extracted from KJAS, and 508 unique terms were extracted from Archives and Records for keyword co-occurrence network analyses. The result shows that the main research topics for KJAS include studies on (1) records management in general, such as archives, records, records management, and archival information service, (2) public records management, (3) personal or private records management, and (4) the techniques for records management, such as archival appraisal, selection, and disposition. In Archives and Records, (1) there are several case studies related to community and local archives, and (2) studies related to records management techniques, such as records description, appraisal, access, preservation, and service, have been performed continuously; furthermore, (3) studies on the digitization of oral history and audiovisual records are also one of the most researched areas.

• Design Convergence Study
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• v.15 no.3
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• pp.171-186
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• 2016

With the continuous rise of elderly population and rapid progression of aging in our society, greater emphasis is placed on the importance of local seniors welfare centers as representative service space that meets the diverse needs of local residents. In addition, there is a growing tendency among current users to seek high-quality service as their educational level, economic ability and lifestyle have changed for the better compared to past generations. Accordingly, this study analyzed the satisfaction of senior welfare centers according to life-style type of the elderly, using a lifestyle measurement tool which incorporates indicators of gerontographics. A survey was conducted with users of seven senior welfare centers located in Seoul. Analysis results are as follows: First, four types of lifestyle were derived through cluster analysis; independent activity type, protective activity type, active challenge type, and passive challenge type. Second, it was found that the overall satisfaction of seniors welfare centers by the life-style of the elderly is highest for the protective activity type followed by the passive challenge type, the active challenge type, and the independent activity type. Third, upon examining the effect of spatial characteristics of welfare centers on the satisfaction of elderly users by type of lifestyle, it was found that the independent activity type and the passive challenge type users are most influenced by intimacy, the protective activity type users by comfort, and the active challenge type users by convenience.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.311-320
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• 2023

This paper analyzes viewers' perception of investigative journalism before and after COVID-19, and examines the direction of investigative journalism using big data. Based on the previous research set as a social science model, the relationship between words related to big data TV current affairs programs and investigative journalism in this paper was investigated before and after the appearance of COVID-19. We visualized changes in viewers' perception of investigative journalism by analyzing text data obtained through the use of Textom, with TV current affairs programs and investigative journalism as keywords. Data was collected from 2017 to June 2022 and refined for analysis. We visualized connectivity centrality using Ucinet 6.0 and Netdraw, and clustered the number of keywords and their frequency using Concor analysis. Our study found a clear change in viewer perception before and after the pandemic. As an implication of this thesis, big data analysis was conducted with the investigative journalism as the main keyword, and the direction of the investigative journalism was presented based on the analysis. Furthermore, based on previous research, we suggest effective approaches for investigative journalism after the pandemic to better engage viewers.

• Journal of Internet of Things and Convergence
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• v.9 no.6
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• pp.99-110
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• 2023

This study analyzed 817 articles published in Korean professional journals over the past three years, from 2020 to 2022, using text mining techniques to identify trends in addiction research in Korea and explore development directions. The analysis results are as follows. First, as a result of the analysis of the top keywords, online addiction studies such as smartphones, games, Internet, gambling, and relationship addiction were prominent as the top keywords. Second, as a result of TF-IDF analysis, many addiction studies related to behavioral addiction such as smartphones, games, the Internet, and work addiction have been conducted over the past three years, and in particular, there are many studies on addiction problems such as smartphones, games, and the Internet that have not yet been clinically diagnosed as addiction problems. This is the same as the result of word frequency analysis, and it can be interpreted that recent studies have been remarkably conducted on more diverse addiction problems. Third, the 2-gram analysis shows that words that mainly correspond to behavioral addiction, such as smartphones, games, and the Internet, appear side by side with the keyword addiction, and among them, words paired with smartphones are mentioned a lot in research papers and are being studied. Fourth, as a result of the CONCOR analysis, there were five clusters: a study on universal addiction issues such as alcohol use disorders and the Internet, a study of recovery on drug and gambling addiction, a study on mobile devices and media addiction, a study on the latest trends related to behavioral addiction, and other addiction issues. Finally, based on the results of this study, a direction for future addiction-related research was suggested.

• Journal of the Economic Geographical Society of Korea
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• v.27 no.1
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• pp.38-52
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• 2024

Digital transformation industry contributes to the improvement of productivity in overall industrial production, the smart green industry for carbon neutrality and sustainable growth is growing as a future industry. The purpose of this paper is to explore the status and role of the industry in the future industry innovation ecosystem through the analysis of the growth drivers and location pattern changes of the smart green industry. The industry is on the rise in both metropolitan and non-metropolitan areas, and the growth of the industry can be seen in non-metropolitan and non-urban areas. In particular, due to the smart green industrial complex pilot project, the creation of Gwangju Jeonnam Innovation City, and the promotion of new and renewable energy policies, the emergence of core aggregation areas (HH type) in the coastal areas of Honam and Chungcheongnam-do, and the formation of isolated centers (HL type) in the Gyeongsang region, new and renewable energy production companies are being accumulated in non-metropolitan areas. Therefore, the smart green industry is expected to promote the formation of various specialized spokes in non-urban areas in the future industrial innovation ecosystem that forms a multipolar hub-spoke network structure, where policy factors are the triggers for growth.

• The Korean Journal of Applied Statistics
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• v.37 no.1
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• pp.73-86
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• 2024

A radial chart of Excel is very useful graphical method in delivering information for numerical data. However, it is not easy to discriminate or classify many individuals. In this case, after shaping each individual of a radial chart, we need to apply shape analysis. For a radial chart, since landmarks for shaping are formed as many as the number of variables representing the characteristics of the object, we consider a shape that connects them to a line. If the shape becomes complicated due to the large number of variables, it is difficult to easily grasp even if visualized using a radial chart. Principal component analysis (PCA) is performed on variables to create a visually effective shape. The classification table and classification rate are checked by applying the techniques of traditional discriminant analysis, support vector machine (SVM), and artificial neural network (ANN), before and after principal component analysis. In addition, the difference in discrimination between the two coordinates of generalized procrustes analysis (GPA) coordinates and Bookstein coordinates is compared. Bookstein coordinates are obtained by converting the position, rotation, and scale of the shape around the base landmarks, and show higher rate than GPA coordinates for the classification rate.

• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.209-217
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• 2024

The purpose of this study is to explore development plans by analyzing social interests and perceptions of jiu-jitsu using big data analysis. Network analysis, centrality analysis, and CONCOR analysis were conducted by collecting data for the last 10 years of major domestic portal sites. First, 'judo' was found to be the most important related word in network analysis, and 'judo' was also an important word in the analysis of dgree centrality. In the closeness centrality analysis, "defender" was the most important word, and "sports" was the most important word in betweenness centrality. Finally, as a result of CONCOR analysis, four clusters (related sports and marketing, jiu-jitsu competitions, belt test, supplies and expenses) were formed. As a conclusion of the study, first, words such as 'judo', 'exercise', 'competition', 'dobok', 'gym', and 'graduation' should be actively used to promote jiu-jitsu.As a conclusion of the study, first, words such as 'judo', 'exercise', 'contest', 'dobok', 'gym', and 'graduation' should be actively used to promote jiu-jitsu. Second, it is necessary to share information on training costs through various routes, to make awareness of the graduation process or method common, and to develop safety products and create a safe training culture. Third, it is necessary to find ways to continuously increase the influx of new trainees by attracting steady competitions.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.111-125
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• 2011

Clustering is a process of grouping similar or relevant documents into a cluster and assigning a meaningful concept to the cluster. By this process, clustering facilitates fast and correct search for the relevant documents by narrowing down the range of searching only to the collection of documents belonging to related clusters. For effective clustering, techniques are required for identifying similar documents and grouping them into a cluster, and discovering a concept that is most relevant to the cluster. One of the problems often appearing in this context is the detection of a complex concept that overlaps with several simple concepts at the same hierarchical level. Previous clustering methods were unable to identify and represent a complex concept that belongs to several different clusters at the same level in the concept hierarchy, and also could not validate the semantic hierarchical relationship between a complex concept and each of simple concepts. In order to solve these problems, this paper proposes a new clustering method that identifies and represents complex concepts efficiently. We developed the Hierarchical Overlapping Clustering (HOC) algorithm that modified the traditional Agglomerative Hierarchical Clustering algorithm to allow overlapped clusters at the same level in the concept hierarchy. The HOC algorithm represents the clustering result not by a tree but by a lattice to detect complex concepts. We developed a system that employs the HOC algorithm to carry out the goal of complex concept detection. This system operates in three phases; 1) the preprocessing of documents, 2) the clustering using the HOC algorithm, and 3) the validation of semantic hierarchical relationships among the concepts in the lattice obtained as a result of clustering. The preprocessing phase represents the documents as x-y coordinate values in a 2-dimensional space by considering the weights of terms appearing in the documents. First, it goes through some refinement process by applying stopwords removal and stemming to extract index terms. Then, each index term is assigned a TF-IDF weight value and the x-y coordinate value for each document is determined by combining the TF-IDF values of the terms in it. The clustering phase uses the HOC algorithm in which the similarity between the documents is calculated by applying the Euclidean distance method. Initially, a cluster is generated for each document by grouping those documents that are closest to it. Then, the distance between any two clusters is measured, grouping the closest clusters as a new cluster. This process is repeated until the root cluster is generated. In the validation phase, the feature selection method is applied to validate the appropriateness of the cluster concepts built by the HOC algorithm to see if they have meaningful hierarchical relationships. Feature selection is a method of extracting key features from a document by identifying and assigning weight values to important and representative terms in the document. In order to correctly select key features, a method is needed to determine how each term contributes to the class of the document. Among several methods achieving this goal, this paper adopted the $x^2$�� statistics, which measures the dependency degree of a term t to a class c, and represents the relationship between t and c by a numerical value. To demonstrate the effectiveness of the HOC algorithm, a series of performance evaluation is carried out by using a well-known Reuter-21578 news collection. The result of performance evaluation showed that the HOC algorithm greatly contributes to detecting and producing complex concepts by generating the concept hierarchy in a lattice structure.