• The Journal of Korean Obstetrics and Gynecology
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• v.22 no.4
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• pp.122-134
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• 2009

Purpose: The purpose of this study is to know the blood stasis pattern for the patients who had hysterectomy. Methods: Among the patients who had hysterectomy in the department of obstetrics and gynecology, OO medical center from March 3rd 2009 to October 21st 2009, subjects who met inclusion criteria and submitted appropriate questionnaire. We compared blood stasis score and operational method, age, BMI, past operation history of abdominal and pelvic site, parity, whether adhesiolysis, oriental medicine intervention was done. For statistics, we used independent samples t-test, oneway analysis of variances(ANOVA) and SPSS version 13.0 for windows. Results: Blood stasis score of the subtotal hysterectomy group ($44.43{\pm}15.01$) is higher than that of the total hysterectomy group($39.04{\pm}12.46$). Blood stasis score under the age 40($51.88{\pm}12.68$) is higher than 40-49 age patients($40.34{\pm}14.24$) and over the age 50 patients($41.62{\pm}13.46$). There is no statistically significant difference between laparoscopic and abdominal trial, whether adhesiolysis, oriental medicine intervention was done, BMI, past operation history abdominal and pelvic site, parity, chief complaint before hysterectomy, oriental medicine intervention. Conclusion: Through the results showed, when traditional Korean medical doctors use static blood medication, history of hysterectomy and age should be considered as the history of subtotal hysterectomy and younger age tend to have a higher rate of a blood stasis pattern. We need a further study to develop blood stasis indicators with a validated questionnaire, and more subjects involved at multiple institutions.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.85-91
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• 2021

School violence has long been recognized as a social problem, and various efforts have been made to prevent it. In this study, we propose a system that can prevent school violence by analyzing data on the frequency of conversations between students, and identify peer relationships. The frequency of conversations between students in the class was quantified using a rating scale questionnaire, and this data was grouped into the appropriate number of clusters using the K-means algorithm. Additionally, the homeroom teacher observed the frequency and nature of conversations between students, and targeted specific individuals or groups for counseling and intervention, with the aim of reducing school violence. Data analysis revealed that the teachers' qualitative observations were consistent with the quantified data based on student questionnaires, and therefore applicable as quantitative data towards the identification and understanding of student relationships within the classroom. The study has potential limitations. The data used is subjective and based on peer evaluations which can be inconsistent as the students may use different criteria to evaluate one another. It is expected that this study will help homeroom teachers in their efforts to prevent school violence by understanding the relationships between students within the classroom.

• Journal of The Korean Society of Grassland and Forage Science
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• v.43 no.2
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• pp.95-102
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• 2023

This study was to investigate the cultivation technique previously conducted cultivation research for the stable production of alfalfa and to present further research. The data used in the study were 270 alfalfa cultivation experimental data from 1983 to 2008, indicating the cultivation region, field type, variety, sowing, cutting frequency, fertilization, and dry matter yield (DMY). The average DMY of alfalfa in the Republic of Korea was 12,536 kg/ha, which differed greatly depending on the cultivated region. Most of the field type was cultivated in upland. In order to increase alfalfa production, it is necessary to use reclaimed and unused land, and research on the soil amendment matter to improve the soil condition is needed. Alfalfa varieties cultivated an amount of 53, but collected data no studies considered fall dormancy, the criteria for selecting alfalfa varieties, so further research is required. The fertilizer did not consider each component at various levels, and research is needed as the demand for fertilizer. In particular, research on potassium is needed considering the increase in alfalfa production. The alfalfa cutting frequency differed in the estimated pasture production period depending on the region, and the DMY tended to increase with increasing cutting frequency. This suggests that the alfalfa DMY can be increased according to the cutting frequency in the Republic of Korea, so research is needed to present the appropriate cutting frequency.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.1A
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• pp.71-80
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• 2010

Bridge deck is directly influenced by environment and vehicle load, it is easily damaged so that it requires an appropriate repair and retrofit. Therefore, developing a bridge deck with high durability is necessary in order to minimize the maintenance of bridge deck and use it to its design life. In this study, static test was carried out to evaluate a fatigue capacity of steel-concrete composite deck, which was newly developed by supplementing problems of existing reinforced concrete deck. Based on results from the static test, fatigue load was decided, and fatigue test was conducted under the constant amplitude repeated load. From the fatigue tests, the S-N curve regarding principle structural details of composite deck was made, and characteristics of fatigue behavior was estimated by comparing and evaluating it with fatigue design criteria. In addition, fatigue design guideline was presented. As a result, it is found that each structural details of composite deck proposed by this study, such as upper flange of corrugated steel plate and middle section of it, shear connector and lower flange of corrugated steel plate, is satisfying the fatigue strength.

• The Journal of Sustainable Design and Educational Environment Research
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• v.23 no.3
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• pp.1-13
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• 2024

This study aims to identify users' perceptions and needs to improve college teaching spaces in nursing education, and thus derive improvement measures. Therefore, group interviews (three to five participants per category) were conducted with professors (7), students (9), and administrative staff (8) at a college of nursing located in Seoul. All interviews were conducted face-to-face, with each interview taking approximately 60-90 min. The interview results were analyzed for professors, students, and administrative staff separately. The following implications were drawn by synthesizing the interview results for each group: (1) the physical environment and quality of interaction between professors and students need to be improved in order to enhance the quality of teaching and learning; (2) a well-designed practice environment that allows students to practice various skills with confidence needs to be provided; (3) classrooms need to be configured and arranged in a way that is appropriate the nursing curriculum and educational activities to maximize learning effectiveness; (4) spatial restructuring is necessary in terms of living and resting spaces to help nursing students manage stress and provide them with psychological stability; and (5) administrative support reflecting the nursing curriculum is needed in establishing classroom assignment criteria and space use regulations. Finally, the limitations of this study and suggestions for further research were discussed.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.151-176
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• 2021

As the information technology industry develops, various kinds of data are being created, and it is now essential to process them and use them in the industry. Analyzing and utilizing various digital data collected online and offline is a necessary process to provide an appropriate experience for customers in the industry. In order to create new businesses, products, and services, it is essential to use customer data collected in various ways to deeply understand potential customers' needs and analyze behavior patterns to capture hidden signals of desire. However, it is true that research using data analysis and UX methodology, which should be conducted in parallel for effective service development, is being conducted separately and that there is a lack of examples of use in the industry. In thiswork, we construct a single process by applying data analysis methods and UX methodologies. This study is important in that it is highly likely to be used because it applies methodologies that are actively used in practice. We conducted a survey on the topic to identify and cluster the associations between factors to establish customer classification and target customers. The research methods are as follows. First, we first conduct a factor, regression analysis to determine the association between factors in the happiness data survey. Groups are grouped according to the survey results and identify the relationship between 34 questions of psychological stability, family life, relational satisfaction, health, economic satisfaction, work satisfaction, daily life satisfaction, and residential environment satisfaction. Second, we classify clusters based on factors affecting happiness and extract the optimal number of clusters. Based on the results, we cross-analyzed the characteristics of each cluster. Third, forservice definition, analysis was conducted by correlating with keywords related to happiness. We leverage keyword analysis of the thumb trend to derive ideas based on the interest and associations of the keyword. We also collected approximately 11,000 news articles based on the top three keywords that are highly related to happiness, then derived issues between keywords through text mining analysis in SAS, and utilized them in defining services after ideas were conceived. Fourth, based on the characteristics identified through data analysis, we selected segmentation and targetingappropriate for service discovery. To this end, the characteristics of the factors were grouped and selected into four groups, and the profile was drawn up and the main target customers were selected. Fifth, based on the characteristics of the main target customers, interviewers were selected and the In-depthinterviews were conducted to discover the causes of happiness, causes of unhappiness, and needs for services. Sixth, we derive customer behavior patterns based on segment results and detailed interviews, and specify the objectives associated with the characteristics. Seventh, a typical persona using qualitative surveys and a persona using data were produced to analyze each characteristic and pros and cons by comparing the two personas. Existing market segmentation classifies customers based on purchasing factors, and UX methodology measures users' behavior variables to establish criteria and redefine users' classification. Utilizing these segment classification methods, applying the process of producinguser classification and persona in UX methodology will be able to utilize them as more accurate customer classification schemes. The significance of this study is summarized in two ways: First, the idea of using data to create a variety of services was linked to the UX methodology used to plan IT services by applying it in the hot topic era. Second, we further enhance user classification by applying segment analysis methods that are not currently used well in UX methodologies. To provide a consistent experience in creating a single service, from large to small, it is necessary to define customers with common goals. To this end, it is necessary to derive persona and persuade various stakeholders. Under these circumstances, designing a consistent experience from beginning to end, through fast and concrete user descriptions, would be a very effective way to produce a successful service.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.6
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• pp.21-35
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• 2022

With the support of local and central governments, various incentive policies for "green" cars have been established, and the number of electric vehicle users has been rapidly increasing in recent years. As a result, much attention is being given to establishing a user-centered charging infrastructure. A standard for the number of electric vehicle chargers to be supplied is being prepared based on building characteristics, but there is quite limited research on the appropriate ratio of slow and fast chargers based on the characteristics of each place. Therefore, this study derived an appropriate penetration ratio based on data about the distribution ratio of common slow chargers. These data were collected using a survey of actual electric vehicle users. Next, an analysis was done on how to categorize the needs of charging environments and to determine what criteria or characteristics to use for categorization. Based on the results of the survey analysis, three types of places were derived. Type-1 places require 10% of chargers to be slow chargers, Type-2 places require 40-60% of chargers to be slow chargers (i.e., around equal distribution of slow and fast chargers), and Type-3 places require more than 80% of chargers to be slow chargers. The required levels of slow chargers were classified by place type and by individual using latent class cluster analysis, which made it possible to categorize them into five clusters related to socioeconomic variables, vehicle characteristics, traffic, and charging behaviors. It was found that there was a high correlation between charging behavior, weekend travel behavior, gender, and income. The results and insights from this study could be used to establish charging infrastructure policies in the future and to prepare standards for supplying charging infrastructure according to changes in the electric vehicle market.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.19 no.1
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• pp.8-34
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• 2014

We reviewed foreign evaluation systems based on the macrobenthic and macroalgal communities and developed a system, composed of a set of ecological indices able to evaluate the functionality (FI, Functional Index; estimation of stability and productivity) and maturity (MI, Maturity Index; comparisons with biological parameters of natural reefs) of artificial reefs by comparing the status in the adjacent natural reefs in Korean coastal waters. The evaluation system was applied to natural and artificial reefs/reef-planned areas (natural reefs), established in the 5 marine ranching areas (Bangnyeong-Daechung, Yeonpyung, Taean, Seocheon and Buan) in the west coast of Korea. The FI ranged between 31.6 (Bangnyeong-Daechung) and 72.5% (Buan) and MI did between 53.1 (Seocheon) and 76.9% (Taean) in average. The evaluation of artificial reefs by the two indices, showed the most appropriate status in Taean. The FI between the adjacent artificial and natural reefs were in significant linear relationship ($r^2=0.83$, p=0.01). This indicated the local status of biological community may be critical in determining the functionality of the artificial reefs. We have suggested an integrative but preliminary evaluation system of artificial reefs in this study. The output from the evaluation system may be utilized as a tool for environment/resource managers or policy makers, responsible for effective use of funds and decision making. Given the importance, we need to use the options to enhance and improve the accuracy as follows: (1) continuous validation of the evaluation system and rescaling the criteria of indicators, (2) vigorous utilization of observation and experience through the application and data accumulation and (3) development and testing of brand-new indicators.

• Food Science and Preservation
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• v.24 no.8
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• pp.1094-1102
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• 2017

Hazardous metals leaching experiment was carried out in accordance with various usage environments for camping cooking utensils distributed in the market. There was a significant difference in the degree of migration for lead, arsenic, cadmium and nickel defending on the solvent and how to use, although they were all appropriate for criteria. In general, the migrated amount of aluminum was increased in acidic condition, and the migrated amount of arsenic was increased in salty condition. Physical scratches increased the overall release of hazardous metals from the portable pots and pans for camping in all solvents. Especially, in 0.5% citric acid solution, cadmium was migrated by physical scratch in stainless steel and hard aluminum pots and pans. The longer the leaching time, the higher the migration of aluminum in acid condition and arsenic in basic condition. From these results, it is desirable to use the cooking utensil for camping without being exposed to strong acidic or basic solution and scratches in order to reduce the migration of hazardous metals from them.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.59-83
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• 2018

With the increasing importance of sentiment analysis to grasp the needs of customers and the public, various types of deep learning models have been actively applied to English texts. In the sentiment analysis of English texts by deep learning, natural language sentences included in training and test datasets are usually converted into sequences of word vectors before being entered into the deep learning models. In this case, word vectors generally refer to vector representations of words obtained through splitting a sentence by space characters. There are several ways to derive word vectors, one of which is Word2Vec used for producing the 300 dimensional Google word vectors from about 100 billion words of Google News data. They have been widely used in the studies of sentiment analysis of reviews from various fields such as restaurants, movies, laptops, cameras, etc. Unlike English, morpheme plays an essential role in sentiment analysis and sentence structure analysis in Korean, which is a typical agglutinative language with developed postpositions and endings. A morpheme can be defined as the smallest meaningful unit of a language, and a word consists of one or more morphemes. For example, for a word '예쁘고', the morphemes are '예쁘(= adjective)' and '고(=connective ending)'. Reflecting the significance of Korean morphemes, it seems reasonable to adopt the morphemes as a basic unit in Korean sentiment analysis. Therefore, in this study, we use 'morpheme vector' as an input to a deep learning model rather than 'word vector' which is mainly used in English text. The morpheme vector refers to a vector representation for the morpheme and can be derived by applying an existent word vector derivation mechanism to the sentences divided into constituent morphemes. By the way, here come some questions as follows. What is the desirable range of POS(Part-Of-Speech) tags when deriving morpheme vectors for improving the classification accuracy of a deep learning model? Is it proper to apply a typical word vector model which primarily relies on the form of words to Korean with a high homonym ratio? Will the text preprocessing such as correcting spelling or spacing errors affect the classification accuracy, especially when drawing morpheme vectors from Korean product reviews with a lot of grammatical mistakes and variations? We seek to find empirical answers to these fundamental issues, which may be encountered first when applying various deep learning models to Korean texts. As a starting point, we summarized these issues as three central research questions as follows. First, which is better effective, to use morpheme vectors from grammatically correct texts of other domain than the analysis target, or to use morpheme vectors from considerably ungrammatical texts of the same domain, as the initial input of a deep learning model? Second, what is an appropriate morpheme vector derivation method for Korean regarding the range of POS tags, homonym, text preprocessing, minimum frequency? Third, can we get a satisfactory level of classification accuracy when applying deep learning to Korean sentiment analysis? As an approach to these research questions, we generate various types of morpheme vectors reflecting the research questions and then compare the classification accuracy through a non-static CNN(Convolutional Neural Network) model taking in the morpheme vectors. As for training and test datasets, Naver Shopping's 17,260 cosmetics product reviews are used. To derive morpheme vectors, we use data from the same domain as the target one and data from other domain; Naver shopping's about 2 million cosmetics product reviews and 520,000 Naver News data arguably corresponding to Google's News data. The six primary sets of morpheme vectors constructed in this study differ in terms of the following three criteria. First, they come from two types of data source; Naver news of high grammatical correctness and Naver shopping's cosmetics product reviews of low grammatical correctness. Second, they are distinguished in the degree of data preprocessing, namely, only splitting sentences or up to additional spelling and spacing corrections after sentence separation. Third, they vary concerning the form of input fed into a word vector model; whether the morphemes themselves are entered into a word vector model or with their POS tags attached. The morpheme vectors further vary depending on the consideration range of POS tags, the minimum frequency of morphemes included, and the random initialization range. All morpheme vectors are derived through CBOW(Continuous Bag-Of-Words) model with the context window 5 and the vector dimension 300. It seems that utilizing the same domain text even with a lower degree of grammatical correctness, performing spelling and spacing corrections as well as sentence splitting, and incorporating morphemes of any POS tags including incomprehensible category lead to the better classification accuracy. The POS tag attachment, which is devised for the high proportion of homonyms in Korean, and the minimum frequency standard for the morpheme to be included seem not to have any definite influence on the classification accuracy.