• Asian Pacific Journal of Cancer Prevention
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• v.13 no.10
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• pp.5171-5176
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• 2012

We here performed a systematic review of PBIC literature using terms analysis in a hope of both identifying potential trends and patterns and exploring methods leveraging traditional literature reviews in this specific area. Articles meeting inclusion criteria were retrieved from PUBMED and translated into dichotomized article records representing presence or non-presence of MeSH terms and a metric consisting of numbers of times of co-occurrence between all pairs of terms identified using a self-designed program. The occurrence of and relations among the terms were calculated and visualized using Excel2007 and UCINET respectively. A total of 1,742 terms were identified from 997 articles retrieved. Put in a descending order, the lines representing the times of term occurrence formed a typical hyperbolic curve; when plotted along the x-axis of whole MESH terms, the lines clustered within four specific regions. Comparison of term occurrence between 2002 and 2011 revealed priority changes in population and subjects (from general groups to priority groups), intervention approaches (from medicine to exercise and psychotherapy), methodology and techniques (from cohort studies to randomized controlled trials) and outcomes (from health and mental health to quality of life, depression etc.). Networks of the terms featured a number of closely linked groups of topics including method and questionnaires, therapy and outcomes, survival management, psychological assessment and intervention, behavioral intervention (individual and community oriented). Terms analysis revealed interesting trends and patterns about PBIC publications and both the analysis methods and findings have implications for future research and literature reviews.

• The Journal of the Korea Contents Association
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• v.19 no.4
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• pp.609-620
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• 2019

The purpose of this study is to examine the co-offending implementation process of robbery and burglary crime. To this end, interview data for research projects conducted by the Korea Institute of Criminology in 2013(Advancing Knowledge About Co-Offending - Burglary and Robbery in Korea) were used as secondary data. Using secondary data, we attempted a grounded theory approach. Based on the procedure presented by Strauss&Corbin (1990), the open coding stage was derived from 51 concepts, 22 subcategories and 8 upper categories. According to an analysis tool called "coding paradigm," the causal condition is the cause of the robbery and burglary crime. Contextual conditions are the formation of co-offending relationship and the reason for selecting co-offending. The central phenomenon is the co-offending implementation of robbery and burglary crime. Interventing conditions are conflict between co-offenders and occurrence of arrest factor. The action/interaction strategy is arrested all co-offenders. The consequence consisted of ending the co-offending relationship. Finally, the selective coding stage selected 'the development of conflict between formation and end of co-offending relationship' as the core category, and newly established the co-offending relationship of robbery and burglary crime through the process of 'formation-implementation-conflict-arrest-end'.

• Korean Journal of Environment and Ecology
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• v.33 no.1
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• pp.9-15
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• 2019

Artiodactyla, which is an even-toed mammal, widely inhabits worldwide. In recent years, wild Artiodactyla species have attracted public attention due to the rapid increase of crop damage and road-kill caused by wild Artiodactyla such as water deer and wild boar and the decrease of some species such as long-tailed goral and musk deer. In spite of such public attention, however, there have been few studies on Artiodactyla in Korea, and no studies have focused on the trend analysis of Artiodactyla, making it difficult to understand actual problems. Many recent studies on trend used text-mining and co-occurrence analysis to increase objectivity in the classification of research subjects by extracting keywords appearing in literature and quantifying relevance between words. In this study, we analyzed texts from research articles of three countries (Korea, China, and Japan) through text-mining and co-occurrence analysis and compared the research subjects in each country. We extracted 199 words from 665 articles related to Artiodactyla of three countries through text-mining. Three word-clusters were formed as a result of co-occurrence analysis on extracted words. We determined that cluster1 was related to "habitat condition and ecology", cluster2 was related to "disease" and cluster3 was related to "conservation genetics and molecular ecology". The results of comparing the rates of occurrence of each word clusters in each country showed that they were relatively even in China and Japan whereas Korea had a prevailing rate (69%) of cluster2 related to "disease". In the regression analysis on the number of words per year in each cluster, the number of words in both China and Japan increased evenly by year in each cluster while the rate of increase of cluster2 was five times more than the other clusters in Korea. The results indicate that Korean researches on Artiodactyla tended to focus on diseases more than those in China and Japan, and few researchers considered other subjects including habitat characteristics, behavior and molecular ecology. In order to control the damage caused by Artiodactyla and to establish a reasonable policy for the protection of endangered species, it is necessary to accumulate basic ecological data by conducting researches on wild Artiodactyla more.

• Korean Journal of Agricultural and Forest Meteorology
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• v.12 no.2
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• pp.76-82
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• 2010

This study was carried out to compare and analyze control methods of the sunburn occurrence that affected 'Fuji'/M.9 planting systems in Korea from 2001 to 2003. It is very important to control temperature of the surface of fruits, because sunburn may occur when the temperature of fruit surfaces reaches $40^{\circ}C{\sim}45^{\circ}C$ due to high air temperature and sunlight during growing periods. As control methods of the sunburn occurrence, white coating materials such as $CaCO_3$ or kaolin were applied four times at two-week intervals from late June, and microspraying of water was conducted when air temperature was over $31^{\circ}C$ from late July to mid-August. Both methods were effective for preventing the sunburn occurrence and improving fruit quality by decreasing peel's temperature of fruits and increasing photosynthesis.

• Journal of Korea Water Resources Association
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• v.32 no.6
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• pp.627-636
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• 1999

In 60 years when the double $CO_2$concentration is anticipated the average annual rainfall depth is expected to be increased by 5 10% due to global warming. However, in the water resources area the frequency change of meteorological extremes such as droughts and floods attracts more interests than the increase of annual rainfall amount. Even though recent frequent occurrences of this kind of meteorological extremes are assumed as an indirect proof of global warming, the prediction of its overall tendency has not yet been made. Thus, in this research we propose a possible methodology to be used for its prediction. The methodology proposed is based on the frequency distribution of daily rainfall be Todorovie and Woolhiser(1975), and Katz(1977), where the input parameters are modified to consider the change of monthly or annual rainfall depth and, thus, to result in the change of frequency distribution. We adopt two values(10mm, 50mm) as thresholds and investigate the change of occurrence probability due to the change monthly and annual rainfall depth. these changes do not directly indicate the changes of occurrence probability of floods and droughts, but it may still be a very useful information for their prediction. Finally, the changes of occurrence probability were found to be greater when considering the monthly rainfall rather than the annual rainfall, and those in rainy season than those in dry season.

• Animal Bioscience
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• v.34 no.4
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• pp.734-742
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• 2021

Objective: The present study aimed to investigate the occurrence and species of coagulase-positive staphylococci (CoPS) and coagulase-negative staphylococci (CoNS) in retail pork meat samples collected during nationwide monitoring. The staphylococcal isolates were characterized for antimicrobial and zinc chloride resistance and enterotoxigenic potential. Methods: A total of 260 pre-packaged pork meat samples were collected from 35 retail markets in 8 provinces in Korea for isolation of staphylococci. Antimicrobial and zinc chloride resistance phenotypes, and genes associated with the resistance phenotypes were determined on the isolates. Furthermore, the presence and distribution of 19 staphylococcal enterotoxin (SE) genes and enterotoxin-like genes among the pork-associated staphylococci were determined by multiplex polymerase chain reaction-based assays using the specific primer sets. Results: A total of 29 staphylococcal strains (29/260, 11.1%) were isolated from samples of retail pork meat, 24 (83%) of which were CoNS. The four CoNS species identified were S. saprophyticus (n = 16, 55%), S. sciuri (n = 3, 10%), S. warneri (n = 3, 10%), and S. epidermidis (n = 2, 7%). Among the 29 isolates, four methicillin-resistant CoNS (MR-CoNS; three S. sciuri and one S. epidermidis) and one methicillin-resistant CoPS (MR-CoPS; one S. aureus) were identified. In addition, a relatively high level of tetracycline (TET) resistance (52%) was confirmed in CoNS, along with a predominant distribution of tet(K). The most prevalent SEs were sep (45%), and sen (28%), which were carried by 81% of S. saprophyticus. Conclusion: These findings suggest that CoNS, especially S. saprophyticus strains, in raw pork meat could be a potential risk factor for staphylococcal food poisoning (SFP), and therefore, requires further investigation to elucidate the role of SEls in SFP and virulence of the pathogen. Our results also suggest that CoNS from raw pork meat may act as a source for transmission of antimicrobial resistance genes such as staphylococcal cassette chromosome mec and tet(K).

• The Transactions of the Korea Information Processing Society
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• v.7 no.12
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• pp.3874-3884
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• 2000

An information retrieval system has to retrieve all and only documents which are relevant to a user query, even if index terms and query terms are not matched exactly. However, term mismatches between index terms and qucry terms have been a serious obstacle to the enhancement of retrieval performance. In this paper, we discuss automatic term normalization between words in text corpora and their application to a Korean information retrieval system. We perform two types of term normalizations to alleviate semantic term mismatches: equivalence class and co-occurrence cluster. First, transliterations, spelling errors, and synonyms are normalized into equivalence classes bv using contextual similarity. Second, context-based terms are normalized by using a combination of mutual information and word context to establish word similarities. Next, unsupervised clustering is done by using K-means algorithm and co-occurrence clusters are identified. In this paper, these normalized term products are used in the query expansion to alleviate semantic tem1 mismatches. In other words, we utilize two kinds of tcrm normalizations, equivalence class and co-occurrence cluster, to expand user's queries with new tcrms, in an attempt to make user's queries more comprehensive (adding transliterations) or more specific (adding spc'Cializationsl. For query expansion, we employ two complementary methods: term suggestion and term relevance feedback. The experimental results show that our proposed system can alleviatl' semantic term mismatches and can also provide the appropriate similarity measurements. As a result, we know that our system can improve the rctrieval efficiency of the information retrieval system.

• Journal of The Korean Association For Science Education
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• v.40 no.1
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• pp.41-50
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• 2020

Looking at the understanding of scientific concepts from a linguistic perspective, it is very important for students to develop a deep and sophisticated understanding of words used in scientific concept as well as the ability to use them correctly. This study intends to provide the basis for productive knowledge education of scientific words by noting that the foundation of productive knowledge teaching on scientific words is not well established, and by exploring ways to teach the relationship among words that constitute scientific concept in a productive and effective manner. To this end, we extracted the relationship among the words that make up the scientific concept from the text of science textbook by using quantitative text analysis methods, second, qualitatively examined the meaning of the word relationship extracted as a result of each method, and third, we proposed a writing activity method to help improve the productive knowledge of scientific concept words. We analyzed the text of the "Force and motion" unit on first grade science textbook by using four methods of quantitative linguistic analysis: word cluster, co-occurrence, text network analysis, and word-embedding. As results, this study suggests four writing activities, completing sentence activity by using the result of word cluster analysis, filling the blanks activity by using the result of co-occurrence analysis, material-oriented writing activities by using the result of text network analysis, and finally we made a list of important words by using the result of word embedding.

• Journal of KIISE:Software and Applications
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• v.27 no.7
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• pp.769-783
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• 2000

In this paper, in order to disambiguate Korean noun word sense, we define a local context and explain how to extract it from a raw corpus. Following the intuition that two different nouns are likely to have similar meanings if they occur in the same local context, we use, as a clue, the word that occurs in the same local context where the target noun occurs. This method increases the usability of extracted knowledge and makes it possible to disambiguate the sense of infrequent words. And we can overcome the data sparseness problem by extending the verbs in a local context. The sense of a target noun is decided by the maximum similarity to the clues learned previously. The similarity between two words is computed by their concept distance in the sense hierarchy borrowed from WordNet. By reducing the multiplicity of clues gradually in the process of computing maximum similarity, we can speed up for next time calculation. When a target noun has more than two local contexts, we assign a weight according to the type of each local context to implement the differences according to the strength of semantic restriction of local contexts. As another knowledge source, we get a co-occurrence information from dictionary definitions and example sentences about the target noun. This is used to support local contexts and helps to select the most appropriate sense of the target noun. Through experiments using the proposed method, we discovered that the applicability of local contexts is very high and the co-occurrence information can supplement the local context for the precision. In spite of the high multiplicity of the target nouns used in our experiments, we can achieve higher performance (89.8%) than the supervised methods which use a sense-tagged corpus.

• Journal of the Korean Society for Library and Information Science
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• v.50 no.2
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• pp.289-307
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• 2016

Infectious diseases such as Ebola virus disease become a social issue and draw public attention to be a major topic on news or research. As a result, there have been a lot of studies on infectious diseases using text-mining techniques. However, there is no research on content analysis of two media channels that have distinct characteristics. Accordingly, in this study, we conduct topic analysis between news (representing a social perspective) and academic research paper (representing perspectives of bio-professionals). As text-mining techniques, topic modeling is applied to extract various topics according to the materials, and the word co-occurrence map based on selected bio entities is used to compare the perspectives of the materials specifically. For network analysis, topic map is built by using Gephi. Aforementioned approaches uncovered the difference of topics between two materials and the characteristics of the two materials. In terms of the word co-occurrence map, however, most of entities are shared in both materials. These results indicate that there are differences and commonalties between social and academic materials.