• Journal of the Korean Society of Costume
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• v.67 no.3
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• pp.15-30
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• 2017

The purpose of this study is to analyze the formative characteristics of Hanbok among youngsters based on SNS proof shots, identify new characteristics of Hanbok as part of play and travel rather than as formal Hanbok, and provide information for the Hanbok market. As research methodology, our search was carried out by using '#Hanbok Travel' as the search word in Instagram, where the Hanbok proof shot phenomenon is actively under way. A total of 535 posts from March 21, 2016 to April 1, 2016 were selected as objects of this study, excluding posts containing Hanbok with indiscernible shape, Korean traditional costume manufacturers' promotional posts, and repetitive posts by one person. First, the 535 posts were analyzed by season, region, number of people, and gender, and after men's data were excluded, 644 Hanboks were left for analysis. Their formative characteristics were analyzed by using SPSS 21.0. The results showed that the formative characteristics of Hanbok shown in SNS proof shots included diversification of length in jeogori(Korean traditional jacket), skirt, and sleeve, use of pragmatic material and achromatic color, and reduced use of decorative technique. Hanboks shown in the Hanbok proof shots should be considered as significant data because each shots show clothes selected and worn directly by user's side, unlike the existing studies centering on Hanbok designers' works.

• Journal of Educational Research in Mathematics
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• v.21 no.1
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• pp.33-55
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• 2011

This study explores the characteristics of calculus students' and instructors' discourses on the derivative using a communicational approach to cognition. The data were collected from surveys, classroom observations, and interviews. The results show that the instructors did not explicitly address some aspects of the derivative such as the relationship between the derivative function (f'(x)) and the derivative at a point (f'(a)), and f'(x) as a function, and that students incorrectly described or used these aspects for problem solving. It is also found that both implicitness in the instructors' discourse, and students' incorrect descriptions were closely related to their use of the word, "derivative" without specifying it as "the derivative function" or "the derivative at a point." Comparison between instructors' and students' discourses suggests that explicit discussion about the derivative including exact use of terms will help students see the relationship that f'(a) is a number, a point-specific value of f'(x) that is a function, and overcome their mixed and incorrect notion "the derivative" such as the tangent line at a point.

• The Korea Journal of Herbology
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• v.30 no.3
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• pp.63-68
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• 2015

Objectives : We applied the term weighting method used in the field of data search to quantify relevancy between symptoms and medicinal herbs, and, based on this, we aim to introduce a method of visualizing the characteristics of medicinal herbs. Methods ： We proposed HF-IFF, an adaptation of TF-IDF, which is a term weighting measurement method adapted in the field of data search. Using this method, we deduced relevancy between symptoms and medicinal herbs In Cheongkangeuigam that was published in 1984 by organizing the medical theory of Cheongkang, Kim Younghoon, and visualized this as a graph in order to compare the characteristics of medicinal herbs used for different symptoms. Results ： HF-IFF is the product of HF and IFF, where HF is the frequency of the relevant medicinal herb for a set of symptoms, and IFF is the inverse of the number of formulations (FF) containing that herb. A total of 251 types of medicinal herb are used in Cheongkangeuigam, and 1538 formulations are classified according to 67 types of symptom. The overall mean for HF-IFF was 0.491, with a maximum of 4.566 and a minimum of 0.013. Conclusions ： In spite of several limitations, we were able to use HF-IFF to measure relevancy between symptoms and medicinal herbs, with formulations as an intermediate. We were able to use the quantified results to visually express the characteristics of the herbs used for symptoms by bubble chart and word-cloud from HF-IFF.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.3
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• pp.563-577
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• 2017

Due to the Internet and computing capability, new and variant malware are discovered around 1 Million per day. Companies use dynamic analysis such as behavior analysis on virtual machines for unknown malware detection because attackers use unknown malware which is not detected by signature based AV effectively. But growing number of malware types are not only PE(Portable Executable) but also non-PE such as MS word or PDF therefore dynamic analysis must need more resources and computing powers to improve detection effectiveness. This study elicits the pre-filtering system evaluation factor to improve effective dynamic malware analysis system and presents and verifies the decision making model and the formula for solution selection using AHP(Analytics Hierarchy Process)

• Journal of the Korean Society for Library and Information Science
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• v.23
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• pp.207-261
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• 1992

The purpose of this study is (1) to design and test a database which can be automatically classified, and (2) to generate automatic classification number by processing the keywords in titles using the code combination method of Colon Classification(CC) as well as an automatic recognition of subjects in order to develop an automatic classification system (Auto BC System) based on CC which can be applied to any research library. To conduct this study, 1,510 words in the fields of agricultrue and medicine were selected, analized in terms of [P], [M], [E], [S], [T] employed in CC, and included in a database for classification. For the above-mentioned subject fields, the principle of an automatic classification was specified in order to generate automatic classification codes as well as to perform an automatic subject recognition of the titles included. Whenever necessary, editing, deleting, appending and reindexing of a database can be made in this automatic classification system. Appendix 1 shows the result of the automatic classification of books in the fields of agriculture and medicine. The results of the study are summarized below. 1. The classification number for the title of a book can be automatically generated by using the facet principles of Colon Classification. 2. The automatic subject recognition of a book is achieved by designing a database making use of a globe-principle, and by specifying the subject field for each word. 3. The automatic subject-recognition of input data is achieved by measuring the number of searched words by each subject field. 4. The combination of classification numbers is achieved by flowcharting of classification formular of each subject field. 5. The efficient control of classification numbers is achieved by designing control codes on the database for classification. 6. The automatic classification by means of Auto BC has been proved to be successful in the research library concentrating on a Single field. The general library may have some problem in employing this system. The automatic classification through Auto BC has the following advantages: 1. Speed of the classification process can be improve. 2. The revision or updating of classification schemes can be facilitated. 3. Multiple concepts can be expressed in a single classification code. 4. The consistency of classification can be achieved with the classification formular rather than the classifier's subjective judgement. 5. A user's retrieving process can be made after combining the classification numbers through keywords relating to the material to be searched. 6. The materials can be classified by a librarian without subject backgrounds. 7. The large body of materials can be quickly classified by means of a machine processing. 8. This automatic classification is expected to make a good contribution to design of the total system for library operations. 9. The information flow among libraries can be promoted owing to the use of the same program for the automatic classification.

• Asia pacific journal of information systems
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• v.24 no.2
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• pp.233-253
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• 2014

Can the stock market really be predicted? Stock market prediction has attracted much attention from many fields including business, economics, statistics, and mathematics. Early research on stock market prediction was based on random walk theory (RWT) and the efficient market hypothesis (EMH). According to the EMH, stock market are largely driven by new information rather than present and past prices. Since it is unpredictable, stock market will follow a random walk. Even though these theories, Schumaker [2010] asserted that people keep trying to predict the stock market by using artificial intelligence, statistical estimates, and mathematical models. Mathematical approaches include Percolation Methods, Log-Periodic Oscillations and Wavelet Transforms to model future prices. Examples of artificial intelligence approaches that deals with optimization and machine learning are Genetic Algorithms, Support Vector Machines (SVM) and Neural Networks. Statistical approaches typically predicts the future by using past stock market data. Recently, financial engineers have started to predict the stock prices movement pattern by using the SNS data. SNS is the place where peoples opinions and ideas are freely flow and affect others' beliefs on certain things. Through word-of-mouth in SNS, people share product usage experiences, subjective feelings, and commonly accompanying sentiment or mood with others. An increasing number of empirical analyses of sentiment and mood are based on textual collections of public user generated data on the web. The Opinion mining is one domain of the data mining fields extracting public opinions exposed in SNS by utilizing data mining. There have been many studies on the issues of opinion mining from Web sources such as product reviews, forum posts and blogs. In relation to this literatures, we are trying to understand the effects of SNS exposures of firms on stock prices in Korea. Similarly to Bollen et al. [2011], we empirically analyze the impact of SNS exposures on stock return rates. We use Social Metrics by Daum Soft, an SNS big data analysis company in Korea. Social Metrics provides trends and public opinions in Twitter and blogs by using natural language process and analysis tools. It collects the sentences circulated in the Twitter in real time, and breaks down these sentences into the word units and then extracts keywords. In this study, we classify firms' exposures in SNS into two groups: positive and negative. To test the correlation and causation relationship between SNS exposures and stock price returns, we first collect 252 firms' stock prices and KRX100 index in the Korea Stock Exchange (KRX) from May 25, 2012 to September 1, 2012. We also gather the public attitudes (positive, negative) about these firms from Social Metrics over the same period of time. We conduct regression analysis between stock prices and the number of SNS exposures. Having checked the correlation between the two variables, we perform Granger causality test to see the causation direction between the two variables. The research result is that the number of total SNS exposures is positively related with stock market returns. The number of positive mentions of has also positive relationship with stock market returns. Contrarily, the number of negative mentions has negative relationship with stock market returns, but this relationship is statistically not significant. This means that the impact of positive mentions is statistically bigger than the impact of negative mentions. We also investigate whether the impacts are moderated by industry type and firm's size. We find that the SNS exposures impacts are bigger for IT firms than for non-IT firms, and bigger for small sized firms than for large sized firms. The results of Granger causality test shows change of stock price return is caused by SNS exposures, while the causation of the other way round is not significant. Therefore the correlation relationship between SNS exposures and stock prices has uni-direction causality. The more a firm is exposed in SNS, the more is the stock price likely to increase, while stock price changes may not cause more SNS mentions.

• Journal of Educational Research in Mathematics
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• v.22 no.1
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• pp.53-68
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• 2012

This paper investigated the conceptual schemes four children constructed as they related division number sentences to various types of fraction: Proper fractions, improper fractions, and mixed numbers in both contextual and abstract symbolic forms. Methods followed those of the constructivist teaching experiment. Four fifth-grade students from an inner city school in the southwest United States were interviewed eight times: Pre-test clinical interview, six teaching / semi-structured interviews, and a final post-test clinical interview. Results showed that for equal sharing situations, children conceptualized division in two ways: For mixed numbers, division generated a whole number portion of quotient and a fractional portion of quotient. This provided the conceptual basis to see improper fractions as quotients. For proper fractions, they tended to see the quotient as an instance of the multiplicative structure: $a{\times}b=c$ ; $a{\div}c=\frac{1}{b}$ ; $b{\div}c=\frac{1}{a}$. Results suggest that first, facility in recall of multiplication and division fact families and understanding the multiplicative structure must be emphasized before learning fraction division. Second, to facilitate understanding of the multiplicative structure children must be fluent in representing division in the form of number sentences for equal sharing word problems. If not, their reliance on long division hampers their use of syntax and their understanding of divisor and dividend and their relation to the concepts of numerator and denominator.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.4
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• pp.1-13
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• 2009

VMS(Variable Message Sign) which makes the traffic flow smooth by providing traffic information to road users in real-time has been being installed or operated on the road as part of the detailed ITS system. However, some problems were found as a result of survey on express way currently. In the part of the phase operation, the message interpretation time wasn't defined so that the phase operation was difficult. In the part of the information service, not considering characteristic of the VMS section caused the confusion to drivers. In the part of the message exposure, font, alignment, conversion and composition of the information were not consistent and use of superfluous words and inconsistent use of word having the same meaning brought about the problem on information communication This study established the detailed exposure method based on instructions relative to VMS operation. The method established by defining the number of appropriate phase and setting required function of each individual VMS installation location. The method is as follow. the font type is the GULIM, the message conversion method is simple conversion method, the alignment method is centering alignment method and the color is defined according to each situation. In this study, the preference survey was performed to review the validity of the proposed improvement through the common driver. The results were similar with the pre-study except for the font type. This study established the detailed exposure method based on instructions relative to VMS operation. The method established by defining the number of appropriate phase and setting required function of individual VMS installation location. For the evaluation of status and improvement, preference survey of ordinary drivers and statistics analysis was carried.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.59-65
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• 2021

This is a case study on the use of Albert Camus' La Peste, which has gained its popularity in today's generation of post-COVID as well as the use of big data analysis tools for major and elective classes. First, we asked students majoring in French to compare the use of vocabulary and the number of appearances for characters using big data analysis, for about 400 pages of the original text. As a result, we were able to confirm a similar relationship between Camus' Absurdism and the vocabulary used within La Peste, in addition to noting the heavy frequency of resistant characters. Students in elective classes were asked to read the literature in a Korean-translated version to determine the frequency of vocabulary and characters' appearances. Students were able to strongly relate to La Peste due to its commonality between COVID and the plague in the literature. We also received high levels of class satisfaction regarding the use of big data analysis tools. The students showed a positive response both towards choosing La Peste as the work of literature and using big data, the main tool in the Fourth Industrial Evolution. We were able to identify good results even in a non-contact environment, as long as the literature does not rely on traditional methods but rather lectures to reflect current situations.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.4
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• pp.913-920
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• 2011

In this paper, a logic process based 1-kbit EEPROM IP for RFID tag chips of 900MHz is designed. The cell array of the designed 1-kbit EEPROM IP is arranged in a form of four blocks of 16 rows x 16 columns, that is in a two-dimensional arrangement of one-word EEPROM phantom cells. We can reduce the IP size by making four memory blocks share CG (control gate) and TG (tunnel gate) driver circuits. We propose a TG switch circuit to supply respective TG bias voltages according to operational modes and to keep voltages between devices within 5.5V in terms of reliability in order to share the TG driver circuit. Also, we can reduce the power consumption in the read mode by using a partial activation method to activate just one of four memory blocks. Furthermore, we can reduce the access time by making BL (bit line) switching times faster in the read mode from reduced number of cells connected to each column. We design and compare two 1-kbit EEPROM IPs, two blocks of 32 rows ${\times}$ 16 columns and four blocks of 16 rows ${\times}$ 16 columns, which use Tower's $0.18{\mu}m$ CMOS process. The four-block IP is smaller by 11.9% in the layout size and by 51% in the power consumption in the read mode than the two-block counterpart.