• 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.

• Journal of Korean Home Economics Education Association
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• v.32 no.3
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• pp.179-197
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• 2020

This study analyzed the trends in home economics education research using the language network analysis method, focusing on papers published in the KCI list for 20 years from 2000 to 2019. A total of 501 home economics education papers analyzed through word cloud, centrality analysis, and topic modeling using NetMiner 4.4, and the results are as follows. First, the number of papers in home economics education published in the KCI listing increased gradually to 186 in the 2000s and 315 in the 2010s. The academic journals in which home economics education papers were published have been diversified to 16 in the 2000s and 22 in the 2010s. 60% of all papers were published in the 'Journal of Korean Home Economics Education Association', and since 2018, the number of papers published in the 'Journal of Learner-Centered Curriculum and Instruction' has increased dramatically. Second, in the 2000s and 2010s, home economics education studies published in KCI were categorized into home economics education content analysis, home economics educational program development & application, curriculum analysis, perception survey & direction exploration. In the 2000s, 'Home Economics Teacher' appeared as the main keyword, and a lot of perception survey & direction exploration were conducted. Relatively, the influence of 'development' increased in the 2010s, and many studies were conducted to analyze home economics education contents and develop and apply home economics programs. This study has significance in that it analyzed the research trend of HEE by expanding the analysis target and analysis period of the existing studies.

• Journal of KIISE:Software and Applications
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• v.29 no.4
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• pp.270-277
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• 2002

Text filtering is a task of deciding whether a document has relevance to a specified topic. As Internet and Web becomes wide-spread and the number of documents delivered by e-mail explosively grows the importance of text filtering increases as well. The aim of this paper is to improve the accuracy of text filtering systems by using machine learning techniques. We apply AdaBoost algorithms to the filtering task. An AdaBoost algorithm generates and combines a series of simple hypotheses. Each of the hypotheses decides the relevance of a document to a topic on the basis of whether or not the document includes a certain word. We begin with an existing AdaBoost algorithm which uses weak hypotheses with their output of 1 or -1. Then we extend the algorithm to use weak hypotheses with real-valued outputs which was proposed recently to improve error reduction rates and final filtering performance. Next, we attempt to achieve further improvement in the AdaBoost's performance by first setting weights randomly according to the continuous Poisson distribution, executing AdaBoost, repeating these steps several times, and then combining all the hypotheses learned. This has the effect of mitigating the ovefitting problem which may occur when learning from a small number of data. Experiments have been performed on the real document collections used in TREC-8, a well-established text retrieval contest. This dataset includes Financial Times articles from 1992 to 1994. The experimental results show that AdaBoost with real-valued hypotheses outperforms AdaBoost with binary-valued hypotheses, and that AdaBoost iterated with random weights further improves filtering accuracy. Comparison results of all the participants of the TREC-8 filtering task are also provided.

• Informatization Policy
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• v.20 no.3
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• pp.3-17
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• 2013

As electronic marketplaces grow and a large number of consumers exchange their opinions on products and services on the Internet, many studies have been conducted in the area of online consumer reviews. This paper analyzes the research trend of the online consumer reviews by investigating those studies in an attempt to provide future research directions. Many researchers have focused on the effects of online reviews on consumer behaviors as well as the usefulness of the online reviews. In particular, review contents, characteristics of reviewers/consumers and features of products/services have been identified as influencing factors on the effects of the online consumer reviews. For the review contents, the number and the volume of the contents have increasing effects on the online reviews, while the direction (positive vs. negative) of the contents has resulted in conflicting effects of the review. The reputation and trustfulness of reviewers, consumers' prior knowledge on the products, consumers' product involvement, and types of the products were investigated as these factors influence the effectiveness of the online consumer reviews. Social media (such as Facebook and Twitter) nowadays play an important role to disseminate online reviews among consumers. Thus, it is necessary to study how social media influence the effects of online reviews on consumers. Since some firms abuse the online reviews for their own sakes, we recognize the necessity for empirical studies on the side effects of the online reviews.

• Korea journal of population studies
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• v.9 no.2
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• pp.67-78
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• 1986

With Economic Development Plan, the Korean National Family Plan Program was introduced in early 1960's. The program, which has been a way for constraining population increase, has obtained excellent results. In other word, it has had an important role in controlling the increase in population. The purpose of this study is to analyze the change of fertility rates since 1970 and the lever of completed fertility of Korean women since 1960. There are Age-specific Fertility Rate(ASFR), Total Fertility Rate(TFR), Gross Reproduction Rate(GRR) and Net Reproduction Rate(NRR) etc. in indices of period fertility. It is also possible to be seen the completed fertility rates by using Parity Progression Ratio. The data necessary for this study were obtained from Population & Housing Census Report from the year of 1960 to 1980 and Vital Statistics from 1980 to 1984, which conducted by Economic Planning Board, Republic of Korea. The summarized results of this study were as follows : 1. Age-specific Fertility Fertility Rate(ASFR) has been continuously decreasing till now. The ASFR for the women aged 25 to 29 was higher than those of any other groups and the ASFR for the women aged 20 to 24 was higher than that of the women aged 30 to 34 since the mid 1970's. 2. There are Total Fertility Rate(TFR), Gross Reproduction Rate(GRR) and Ney Reproduction Rate(NRR) etc. in reproduction rates. First of all, TFR and GRR have been declining except late of 1970's and TFR showed 2.23 per ever-married women, GRR was 1.05 in 1982. Next, the change of NRR could not be found without life table by year and only NRR for the time of census was to be found. In 1980, NRR showed 1.27 per ever-married women and the level was still out of reach at replacement level of population. 3. Specific Fertility Rate by Birth Order(SFRBO) showed to be declined continually since 1972. Especially the SFRBO of the third live birth was decreased from about 22 per 1,000 ever-married women in 1972 to 12 or so in 1982. 4. To know the level of completed fertility, the mean number of completed live births per ever-married women was calculated from 1960 to 1980. The number of completed live births was more than 5 per ever-married women by the year of 1975 but have been declining and resulted in 4.69 in 1980.

• 기호학연구
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• no.56
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• pp.7-44
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• 2018

The objective of this paper is to propose a classification of Korean taste terms, especially Korean taste adjectives, from the perspective of cognitive science. The classification of Korean taste terms is here grounded in the definition of 'taste sense', 'flavor' and 'taste' which is usually employed in disciplines of cognitive science. There have been a large number of domestic researches in field of taste terms. Accordingly, a lot of research findings on the classification of taste terms have steadily been released showing the differences among researchers. These different classifications are largely based on the fact that researchers have applied their subjective criteria rather than their objective in order to categorize taste terms. According to previous studies, it is well-known that, in everyday usage, the term 'taste' covers a much wider range of qualities than those perceived through the taste receptor cells alone. In addition, we take it for granted that as much as 80~90% of taste comes from olfactory modality. It is also important to note that the texture and temperature of food, the color of food, the sounds of food, and atmospheric cues have an essential effect on taste perception. Many scientists have already pointed out that taste evaluations are influenced by a number of individual and sociocultural factors. Eating and tasting are important parts of our everyday life, so that linguistic approaches to taste perception seem to be of great significance. We can assume that a classification of taste terms from the perspective of cognitive sciences may shed light on the perceptive mechanism through which we perceive taste. It should be noted that this paper is an advanced work prepared for the follow-up study which will try to make a geometric model of word field 'taste terms' existing or probably existing in the mental lexicon of human beings.

• Journal of IKEEE
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• v.25 no.4
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• pp.625-633
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• 2021

This paper describes a scalable architecture for flexible hardware implementation of Montgomery modular multiplication. Our scalable modular multiplier architecture, which is based on a one-dimensional array of processing elements (PEs), performs word parallel operation and allows us to adjust computational performance and hardware complexity depending on the number of PEs used, N_PE. Based on the proposed architecture, we designed a scalable Montgomery modular multiplier (sMM) core supporting eight field sizes defined in SEC2. Synthesized with 180-nm CMOS cell library, our sMM core was implemented with 38,317 gate equivalents (GEs) and 139,390 GEs for N_PE=1 and N_PE=8, respectively. When operating with a 100 MHz clock, it was evaluated that 256-bit modular multiplications of 0.57 million times/sec for N_PE=1 and 3.5 million times/sec for N_PE=8 can be computed. Our sMM core has the advantage of enabling an optimized implementation by determining the number of PEs to be used in consideration of computational performance and hardware resources required in application fields, and it can be used as an IP (intellectual property) in scalable hardware design of elliptic curve cryptography (ECC).

• Journal of Distribution Science
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• v.8 no.3
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• pp.49-56
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• 2010

At the initial stage of Internet advertising, banner advertising came into fashion. As the Internet developed into a central part of daily lives and the competition in the on-line advertising market was getting fierce, there was not enough space for banner advertising, which rushed to portal sites only. All these factors was responsible for an upsurge in advertising prices. Consequently, the high-cost and low-efficiency problems with banner advertising were raised, which led to an emergence of keyword advertising as a new type of Internet advertising to replace its predecessor. In the beginning of 2000s, when Internet advertising came to be activated, display advertisement including banner advertising dominated the Net. However, display advertising showed signs of gradual decline, and registered minus growth in the year 2009, whereas keyword advertising showed rapid growth and started to outdo display advertising as of the year 2005. Keyword advertising refers to the advertising technique that exposes relevant advertisements on the top of research sites when one searches for a keyword. Instead of exposing advertisements to unspecified individuals like banner advertising, keyword advertising, or targeted advertising technique, shows advertisements only when customers search for a desired keyword so that only highly prospective customers are given a chance to see them. In this context, it is also referred to as search advertising. It is regarded as more aggressive advertising with a high hit rate than previous advertising in that, instead of the seller discovering customers and running an advertisement for them like TV, radios or banner advertising, it exposes advertisements to visiting customers. Keyword advertising makes it possible for a company to seek publicity on line simply by making use of a single word and to achieve a maximum of efficiency at a minimum cost. The strong point of keyword advertising is that customers are allowed to directly contact the products in question through its more efficient advertising when compared to the advertisements of mass media such as TV and radio, etc. The weak point of keyword advertising is that a company should have its advertisement registered on each and every portal site and finds it hard to exercise substantial supervision over its advertisement, there being a possibility of its advertising expenses exceeding its profits. Keyword advertising severs as the most appropriate methods of advertising for the sales and publicity of small and medium enterprises which are in need of a maximum of advertising effect at a low advertising cost. At present, keyword advertising is divided into CPC advertising and CPM advertising. The former is known as the most efficient technique, which is also referred to as advertising based on the meter rate system; A company is supposed to pay for the number of clicks on a searched keyword which users have searched. This is representatively adopted by Overture, Google's Adwords, Naver's Clickchoice, and Daum's Clicks, etc. CPM advertising is dependent upon the flat rate payment system, making a company pay for its advertisement on the basis of the number of exposure, not on the basis of the number of clicks. This method fixes a price for advertisement on the basis of 1,000-time exposure, and is mainly adopted by Naver's Timechoice, Daum's Speciallink, and Nate's Speedup, etc, At present, the CPC method is most frequently adopted. The weak point of the CPC method is that advertising cost can rise through constant clicks from the same IP. If a company makes good use of strategies for maximizing the strong points of keyword advertising and complementing its weak points, it is highly likely to turn its visitors into prospective customers. Accordingly, an advertiser should make an analysis of customers' behavior and approach them in a variety of ways, trying hard to find out what they want. With this in mind, her or she has to put multiple keywords into use when running for ads. When he or she first runs an ad, he or she should first give priority to which keyword to select. The advertiser should consider how many individuals using a search engine will click the keyword in question and how much money he or she has to pay for the advertisement. As the popular keywords that the users of search engines are frequently using are expensive in terms of a unit cost per click, the advertisers without much money for advertising at the initial phrase should pay attention to detailed keywords suitable to their budget. Detailed keywords are also referred to as peripheral keywords or extension keywords, which can be called a combination of major keywords. Most keywords are in the form of texts. The biggest strong point of text-based advertising is that it looks like search results, causing little antipathy to it. But it fails to attract much attention because of the fact that most keyword advertising is in the form of texts. Image-embedded advertising is easy to notice due to images, but it is exposed on the lower part of a web page and regarded as an advertisement, which leads to a low click through rate. However, its strong point is that its prices are lower than those of text-based advertising. If a company owns a logo or a product that is easy enough for people to recognize, the company is well advised to make good use of image-embedded advertising so as to attract Internet users' attention. Advertisers should make an analysis of their logos and examine customers' responses based on the events of sites in question and the composition of products as a vehicle for monitoring their behavior in detail. Besides, keyword advertising allows them to analyze the advertising effects of exposed keywords through the analysis of logos. The logo analysis refers to a close analysis of the current situation of a site by making an analysis of information about visitors on the basis of the analysis of the number of visitors and page view, and that of cookie values. It is in the log files generated through each Web server that a user's IP, used pages, the time when he or she uses it, and cookie values are stored. The log files contain a huge amount of data. As it is almost impossible to make a direct analysis of these log files, one is supposed to make an analysis of them by using solutions for a log analysis. The generic information that can be extracted from tools for each logo analysis includes the number of viewing the total pages, the number of average page view per day, the number of basic page view, the number of page view per visit, the total number of hits, the number of average hits per day, the number of hits per visit, the number of visits, the number of average visits per day, the net number of visitors, average visitors per day, one-time visitors, visitors who have come more than twice, and average using hours, etc. These sites are deemed to be useful for utilizing data for the analysis of the situation and current status of rival companies as well as benchmarking. As keyword advertising exposes advertisements exclusively on search-result pages, competition among advertisers attempting to preoccupy popular keywords is very fierce. Some portal sites keep on giving priority to the existing advertisers, whereas others provide chances to purchase keywords in question to all the advertisers after the advertising contract is over. If an advertiser tries to rely on keywords sensitive to seasons and timeliness in case of sites providing priority to the established advertisers, he or she may as well make a purchase of a vacant place for advertising lest he or she should miss appropriate timing for advertising. However, Naver doesn't provide priority to the existing advertisers as far as all the keyword advertisements are concerned. In this case, one can preoccupy keywords if he or she enters into a contract after confirming the contract period for advertising. This study is designed to take a look at marketing for keyword advertising and to present effective strategies for keyword advertising marketing. At present, the Korean CPC advertising market is virtually monopolized by Overture. Its strong points are that Overture is based on the CPC charging model and that advertisements are registered on the top of the most representative portal sites in Korea. These advantages serve as the most appropriate medium for small and medium enterprises to use. However, the CPC method of Overture has its weak points, too. That is, the CPC method is not the only perfect advertising model among the search advertisements in the on-line market. So it is absolutely necessary that small and medium enterprises including independent shopping malls should complement the weaknesses of the CPC method and make good use of strategies for maximizing its strengths so as to increase their sales and to create a point of contact with customers.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.1-18
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• 2016

Owing to the extensive use of Web media and the development of the IT industry, a large amount of data has been generated, shared, and stored. Nowadays, various types of unstructured data such as image, sound, video, and text are distributed through Web media. Therefore, many attempts have been made in recent years to discover new value through an analysis of these unstructured data. Among these types of unstructured data, text is recognized as the most representative method for users to express and share their opinions on the Web. In this sense, demand for obtaining new insights through text analysis is steadily increasing. Accordingly, text mining is increasingly being used for different purposes in various fields. In particular, issue tracking is being widely studied not only in the academic world but also in industries because it can be used to extract various issues from text such as news, (SocialNetworkServices) to analyze the trends of these issues. Conventionally, issue tracking is used to identify major issues sustained over a long period of time through topic modeling and to analyze the detailed distribution of documents involved in each issue. However, because conventional issue tracking assumes that the content composing each issue does not change throughout the entire tracking period, it cannot represent the dynamic mutation process of detailed issues that can be created, merged, divided, and deleted between these periods. Moreover, because only keywords that appear consistently throughout the entire period can be derived as issue keywords, concrete issue keywords such as "nuclear test" and "separated families" may be concealed by more general issue keywords such as "North Korea" in an analysis over a long period of time. This implies that many meaningful but short-lived issues cannot be discovered by conventional issue tracking. Note that detailed keywords are preferable to general keywords because the former can be clues for providing actionable strategies. To overcome these limitations, we performed an independent analysis on the documents of each detailed period. We generated an issue flow diagram based on the similarity of each issue between two consecutive periods. The issue transition pattern among categories was analyzed by using the category information of each document. In this study, we then applied the proposed methodology to a real case of 53,739 news articles. We derived an issue flow diagram from the articles. We then proposed the following useful application scenarios for the issue flow diagram presented in the experiment section. First, we can identify an issue that actively appears during a certain period and promptly disappears in the next period. Second, the preceding and following issues of a particular issue can be easily discovered from the issue flow diagram. This implies that our methodology can be used to discover the association between inter-period issues. Finally, an interesting pattern of one-way and two-way transitions was discovered by analyzing the transition patterns of issues through category analysis. Thus, we discovered that a pair of mutually similar categories induces two-way transitions. In contrast, one-way transitions can be recognized as an indicator that issues in a certain category tend to be influenced by other issues in another category. For practical application of the proposed methodology, high-quality word and stop word dictionaries need to be constructed. In addition, not only the number of documents but also additional meta-information such as the read counts, written time, and comments of documents should be analyzed. A rigorous performance evaluation or validation of the proposed methodology should be performed in future works.

• Journal of Korean Society of Forest Science
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• v.106 no.4
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• pp.431-440
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• 2017

The 2016 Gyeongju Earthquake ($M_L$ 5.8) (occurred on September 12, 2016) and the 2017 Pohang Earthquake ($M_L$ 5.4) (occurred on November 15, 2017) caused unprecedented damages in South Korea. It is necessary to establish basic data related to earthquake-induced mountainous sediment-related disasters over worldwide. In this study, we analyzed previous international studies on the earthquake-induced mountainous sediment-related disasters, then classified research areas according to research themes using text-mining and co-word analysis in VOSviewer program, and finally examined spatio-temporal research trends by research area. The result showed that the related-researches have been rapidly increased since 2005, which seems to be affected by recent large-scale earthquakes occurred in China, Taiwan and Japan. In addition, the research area related to mountainous sediment-related disasters induced by earthquakes was classified into four subjects: (i) mechanisms of disaster occurrence; (ii) rainfall parameters controlling disaster occurrence; (iii) prediction of potential disaster area using aerial and satellite photographs; and (iv) disaster risk mapping through the modeling of disaster occurrence. These research areas are considered to have a strong correlation with each other. On the threshold year (i.e., 2012-2013), when cumulative number of research papers was reached 50% of total research papers published since 1987, proportions per unit year of all research areas should increase. Especially, the proportion of the research areas related to prediction of potential disaster area using aerial and satellite photographs is highly increased compared to other three research areas. These trends are responsible for the rapidly increasing research papers with study sites in China, and the research papers examined in Taiwan, Japan, and the United States have also contributed to increases in all research areas. The results are could be used as basic data to present future research direction related to mountainous sediment-related disasters induced by earthquakes in South Korea.