• Journal of the Korea Fashion and Costume Design Association
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• v.25 no.2
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• pp.111-122
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• 2023

This study aims to collect Big Data related to DIY clothing, analyze the results on a year-by-year basis, understand consumers' perceptions, the status, and reality of DIY clothing. The reference period for the evaluation of DIY clothing trends was set from 2012 to 2022. The data in this study was collected and analyzed using Textom, a Big Data solution program certified as a Good Software by the Telecommunications Technology Association (TTA). For the analysis of fabric-related DIY products, the keyword was set to "DIY clothing", and for data cleansing following collection, the "Espresso K" module was employed. Also, via data collection on a year-by-year basis, a total of 11 lists were generated and the collected data was analyzed by period. The following are the findings of this study's data collection on DIY clothing. The total number of keywords collected over a period of ten years on search engines "Naver" and "Google" between January 1, 2012 and December 31, 2022 was 16,315, and data trends by period indicate a continuous upward trend. In addition, a keyword analysis was conducted to analyze TF-IDF (Term Frequency-Inverse Document Frequency), a statistical measure that reflects the importance of a word within data, and the relationship with N-gram, an analysis of the correlation concerning the relationship between words. Using these results, it was possible to evaluate the popularity and growing tendency of DIY clothing products in conjunction with the evolving social environment, as well as the desire to explore DIY trends among consumers. Therefore, this study is valuable in that it provides preliminary data for DIY clothing research by analyzing the status and reality of DIY products, and furthermore, contributes to the development and production of DIY clothing.

• Journal of Nutrition and Health
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• v.56 no.3
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• pp.330-347
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• 2023

Purpose: This study identified words closely associated with the keyword "dietary supplement" (DS) using big data in Korean social media and investigated consumer perceptions and trends related to DSs before (2019) and after the coronavirus disease 2019 (COVID-19) pandemic (2021). Methods: A total of 37,313 keywords were found for the 2019 period, and 35,336 keywords were found for the 2021 period using blogs and cafes on Daum and Naver. Results were derived by text mining, semantic networking, network visualization analysis, and sentiment analysis. Results: The DS-related keywords that frequently appeared before and after COVID-19 were "recommend", "vitamin", "health", "children", "multiple", and "lactobacillus". "Calcium", "lutein", "skin", and "immunity" also had high frequency-inverse document frequency (TF-IDF) values. These keywords imply a keen interest in DSs among Korean consumers. Big data results also reflected social phenomena related to DSs; for example, "baby" and "pregnant woman" had lower TD-IDF values after the pandemic, suggesting lower marriage and birth rates but higher values for "joint", indicating reduced physical activity. A network centered on vitamins and health care was produced by semantic network analysis in 2019. In 2021, values were highest for deficiency and need, indicating that individuals were searching for DSs after the COVID-19 pandemic due to a lack an awareness of the need for adequate nutrient intake. Before the pandemic, DSs and vitamins were associated with healthcare and life cycle-related topics, such as pregnancy, but after the COVID-19 pandemic, consumer interests changed to disease prevention and treatment. Conclusion: This study provides meaningful clues regarding consumer perceptions and trends related to DSs before and after the COVID-19 pandemic and fundamental data on the effect of the pandemic on consumer interest in dietary supplements.

• The Journal of the Convergence on Culture Technology
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• v.9 no.5
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• pp.509-515
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• 2023

Despite the continued development of alternative energies, fuel consumption is increasing. In particular, the price of gasoline fluctuates greatly according to fluctuations in international oil prices. Gas stations adjust their gasoline inventory to respond to gasoline price fluctuations. In this study, news datasets is used to analyze the gasoline consumption patterns through fluctuations of the gasoline inventory. First, collecting news datasets with web crawling. Second, summarizing news datasets using KoBART, which summarizes the Korean text datasets. Finally, preprocessing and deriving the fluctuations factors through N-Gram Language Model and TF-IDF. Through this study, it is possible to analyze and predict gasoline consumption patterns.

• Journal of electromagnetic engineering and science
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• v.8 no.2
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• pp.84-89
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• 2008

In a wireless channel above microwave frequency, rain attenuation is very important. In order to predict rain attenuation, 1-min. rain rate distribution is required. This paper discusses appropriate conversion methods to estimate 1-minute rain rate from that of other integration time. Based on the measurement data filed in ITU-R WP3J including ETRI data for 6 consecutive years, distributions of rain rate with 1-, 5-, 10-, 20-, 30-minute integration time were analyzed, both on the global and regional basis, and the parametric relationship between the statistical characteristics of 1-minute and other measurement data were investigated to deduce the conversion methods. It is shown that the global model works good with good accuracy for 5-, 10-, 20-min integration time, and the global model is also applicable globally with good accuracy for 5-, 10-, 20-min integration time. The global conversion model was adopted last year as an ITU-R document for new recommendation. The regional conversion model would also be very useful for locations of similar climatic zone.

• The KIPS Transactions:PartA
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• v.12A no.1 s.91
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• pp.31-40
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• 2005

In this paper, we propose XMDR(XML Metadata Registry) to guarantee the interoperability of data in distributed database, and describe a data synchronizing agent system using it. The proposal of XMDR is to solve the data heterogeneity problem in the sharing and exchanging data. Data heterogeneity problem is generated by different definition or mismatching expression of the same information. Therefore, we define XMDR with XML document by analyzing data elements based on MDR specification. The proposed synchronizing agent system using XMDR not only solves data heterogeneity for data interoperability in synchronizing data but also provides more efficient the agent system by offering errors of low frequency in the number of systems and requests of synchronizing data.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.4
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• pp.149-154
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• 2014

A user should pick up relevant answers by himself from various search results when using user participation question answering community like Knowledge-iN. If refined answers are automatically provided, usability of question answering community must be improved. This paper divides questions in Q&A documents into 4 types(word, list, graph and text), then proposes summarizing methods for each question type using document statistics. Summarized answers for word, list and text type are obtained by question clustering and calculating scores for words using frequency, proximity and confidence of answers. Answers for graph type is shown by extracting user opinion from answers.

• Journal of Korean Physical Therapy Science
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• v.16 no.2
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• pp.45-55
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• 2009

Background: This thesis aims at suggesting the direction for the introduction of public free treatment support system according to the establishment of [Special Education Law] and the right settlement of therapeutic support service. Method: It introduced the characteristics and the contents of school based PT & OT, diagnosis and evaluation, and operation method. It set up question items and presented intervention plan, and substantial intervention, beginning from the request of whole process. The diagnostic evaluation was described from 4 aspects, which are consideration matters in the time of document drawing and diagnostic evaluation, chiefly centering around SOAP. The flow of overall treatment support service, the allocation of 16 handicapped children for 1 therapist, and the weekly treatment frequency according to the treatment support location and environment were suggested in the concrete operation method. Result: The concrete method should be explored in order to provide handicapped students with requisite services, which are offered by various experts in the amended 'Special Education Law'. In addition, work condition and social welfare, which are equal to school teachers, should be provided for all experts. Conclusion: Along with these things, special education support center should establish the road-map for the education rehabilitation of the handicapped children from the evaluation of early diagnosis of the handicapped children to treatment support and lifelong education.

• Journal of the Korean Society for information Management
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• v.17 no.2
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• pp.155-170
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• 2000

In this research, several ways of creating effective STI(Scientific ＆ Technological Information) databases were suggested. We put emphasis on the selection of input data, while on the other was handled, such factors as standardization for data entry, data entry system, etc.. In order to decide priority of target data, the status of document delivery service was analyzed. The result shows that conference proceedings were given priority to academic journals. In case of journals, ranking in the number of documents requested at KORDIC (Korea R＆D Information Center) and 16 Specialized Information Centers was compared with the ranking in citation frequency and impact factor, appeared at SCI.

• The Journal of Information Systems
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• v.20 no.3
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• pp.63-79
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• 2011

Deducting the risk level of infrastructure and buildings based on past human disaster risk cases and implementing prevention measures are important activities for disaster prevention. The object of this study is to measure the confidence to proceed quantitative analysis of various disaster risk cases through text mining methodology. Indeed, by examining confidence calculation process and method, this study suggests also a basic quantitative framework. The framework to measure the confidence is composed into four stages. First step describes correlation by categorizing basic elements based on human disaster ontology. Secondly, terms and cases of Term-Document Matrix will be created and the frequency of certain cases and terms will be quantified, the correlation value will be added to the missing values. In the third stage, association rules will be created according to the basic elements of human disaster risk cases. Lastly, the confidence value of disaster risk cases will be measured through association rules. This kind of confidence value will become a key element when deciding a risk level of a new disaster risk, followed up by preventive measures. Through collection of human disaster risk cases related to road infrastructure, this study will demonstrate a case where the four steps of the quantitative framework and process had been actually used for verification.

• Journal of the Korea Computer Industry Society
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• v.3 no.8
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• pp.1039-1048
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• 2002

It is difficult and laborious to distinguish between the original and the plagiarism about the electrical documents or on-line received documents, specially student homeworks because in many case, the homeworks are written on the same subject. Existing methods are not appropriate to solve this problem, which find the most appropriate category using the expression frequency of index term in documents to be classified. In this paper, a new classification method was proposed to distinguish between the original and the plagiarism about documents which were written similarly which is based on the syntagma vector - except the similar syntagma tree structure and non-index term.