• Journal of The Geomorphological Association of Korea
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• v.19 no.3
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• pp.1-22
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• 2012

The classification scheme of estuaries can be divided into two categories: qualitative classification based on geomorphic characteristics and quantitative classification based upon the physical properties of water body. While simple and intuitive scheme of the former is difficult to quantify, the latter is not easy to apply due to the lack of data. A classification scheme based on morphological convergence is very promising because it only requires easily accessible data such as width and depth of channels, as well as it can characterize estuaries in terms of tidal propagation. Thus, this paper examines the classification scheme based on estuarine morphological convergence using depth and width data obtained from 19 major Korean estuaries. Morphological convergence for each estuary was estimated with the estuarine length, width and depth data to get the convergence parameters, which includes the degree of funneling ${\nu}$ and the dimensionless estuarine length $y_0$. The transfer function ${\xi}({\nu},ky)$ is then deduced analytically from 1D depth-integrated hydrodynamic momentum equation and continuity equation for estuarine shapes. Tidal response of each estuary is finally calculated using ${\nu}$, $y_0$ and ${\xi}({\nu},ky)$ for comparison and classification. The 19 Korean estuaries were classified into three groups: tidal amplitude-dominated estuaries with standing wave-like tidal response (group 1), current-dominated estuaries with progressive wave-like tidal response (group 2), and the intermediate group (group 3) between groups 1 and 2. The sensitivity analysis revealed that uncertainties in determining the estuarine length can have a critical effect upon the results of classification, which indicates that the reasonable determination of the estuarine length is of critical importance. Once the estuarine length is feasibly determined, depth-convergence can be neglected without any negative effect on the classification scheme, which has an important ramification on the wide applicability of the classification scheme.

• Korean Journal of Social Welfare Studies
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• no.36
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• pp.55-80
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• 2008

Research on the welfare state or income inequality has been concerned with variations in inequality between societies or families. These studies tend to view the family as a unit of shared interests where incomes are pooled and distributed equally. This study makes a theoretical and empirical case for why it is important to look at economic dependency within the family in comparative welfare state research. Using the Luxembourg Income Study data this study examined married women's dependency on their husbands' earnings in 16 western industrialized countries. The constructed measure for married women's level of economic dependency followed the procedure of Sørensen & McLanahan(1987), which stated : "her dependency is measured by the extent to which a woman's standard of living(as determined by her share of income) is derived from a transfer from her husband." The finding suggested that married women's economic dependence was lowest in Scandinavian countries. On the contrary, in Southern Europe countries most married women were dependent on husbands' earnings. In Netherlands, Austria, Germany where the share of part-time work among married women was high, married women's economic dependence was also high. This showed the women's labor force participation did not mean that the majority of couples were equal with respect to earnings, nor that a major shift in the sexual division of labour has taken place. This paper analysed the causal relationship between the married women's economic independence and the welfare state by using Ragin(2000)'s Fuzzy-Set Qualitative Comparative Analysis. This analysis considered the various conditions of the welfare state : namely, left power, union mobilization density, women's mobilization, public service sector employment and generous support on the family. The result showed that powerful union, high level of women's mobilization and the generous support on the family were necessary conditions for 'relatively high' level of married women's economic independence.

• Korean Journal of Heritage: History & Science
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• v.52 no.3
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• pp.56-73
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• 2019

This paper aims to establish the technical style of roof tiles by analyzing East Asian roof tile making techniques. It will examine the existing main research data, such as excavation results and the subsequent analysis of the roof tiles' production traces, as well as references and transmitted techniques. Regions are grouped according to technical similarity, then grouped again by artistic styles of pattern and shape and by the technical styles of tools, procedures, and manpower plans. Accordingly, intends to find out whether an understanding of technical style can facilitate an understanding of not only cultural aspects, but also the causality of techniques. Korean, Chinese and Japanese tools were examined, and procedures for making roof tiles were classified into 4 groups. In a superficial way, China, Okinawa, Korea, and Honshu share similar technical traits. Research of procedural details and manpower plans revealed characteristics of each region. As a result, comparisons were made between each region's technical characteristics attempting to investigate their causes. The groups were classified according to their possessing techniques, but it was revealed that East Asia's shared production techniques were based on architectural methodss. The skill of "Pyeon Jeol(Clay Cutting)" classified according to its possessing techniques, turned out to be one such technique. Also, the procedure of technical localization based on the skill of "Ta-nal(Tapping)" showed that the condition of this technique was the power to localize in response to a transfer of techniques. Previous comparison parameters of artifacts would have been a similarity of style originated from exchanges between regions and stylistic characteristics of regions decided by the demander's taste of beauty. This methodology enlarges cultural perception and affords a positive basis of historical facts. However, it suggests the possibility of finding cultural aspects' origins by understanding the technical style and seeing same result in view of "technology culture."

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.1-17
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• 2019

Because stock price forecasting is an important issue both academically and practically, research in stock price prediction has been actively conducted. The stock price forecasting research is classified into using structured data and using unstructured data. With structured data such as historical stock price and financial statements, past studies usually used technical analysis approach and fundamental analysis. In the big data era, the amount of information has rapidly increased, and the artificial intelligence methodology that can find meaning by quantifying string information, which is an unstructured data that takes up a large amount of information, has developed rapidly. With these developments, many attempts with unstructured data are being made to predict stock prices through online news by applying text mining to stock price forecasts. The stock price prediction methodology adopted in many papers is to forecast stock prices with the news of the target companies to be forecasted. However, according to previous research, not only news of a target company affects its stock price, but news of companies that are related to the company can also affect the stock price. However, finding a highly relevant company is not easy because of the market-wide impact and random signs. Thus, existing studies have found highly relevant companies based primarily on pre-determined international industry classification standards. However, according to recent research, global industry classification standard has different homogeneity within the sectors, and it leads to a limitation that forecasting stock prices by taking them all together without considering only relevant companies can adversely affect predictive performance. To overcome the limitation, we first used random matrix theory with text mining for stock prediction. Wherever the dimension of data is large, the classical limit theorems are no longer suitable, because the statistical efficiency will be reduced. Therefore, a simple correlation analysis in the financial market does not mean the true correlation. To solve the issue, we adopt random matrix theory, which is mainly used in econophysics, to remove market-wide effects and random signals and find a true correlation between companies. With the true correlation, we perform cluster analysis to find relevant companies. Also, based on the clustering analysis, we used multiple kernel learning algorithm, which is an ensemble of support vector machine to incorporate the effects of the target firm and its relevant firms simultaneously. Each kernel was assigned to predict stock prices with features of financial news of the target firm and its relevant firms. The results of this study are as follows. The results of this paper are as follows. (1) Following the existing research flow, we confirmed that it is an effective way to forecast stock prices using news from relevant companies. (2) When looking for a relevant company, looking for it in the wrong way can lower AI prediction performance. (3) The proposed approach with random matrix theory shows better performance than previous studies if cluster analysis is performed based on the true correlation by removing market-wide effects and random signals. The contribution of this study is as follows. First, this study shows that random matrix theory, which is used mainly in economic physics, can be combined with artificial intelligence to produce good methodologies. This suggests that it is important not only to develop AI algorithms but also to adopt physics theory. This extends the existing research that presented the methodology by integrating artificial intelligence with complex system theory through transfer entropy. Second, this study stressed that finding the right companies in the stock market is an important issue. This suggests that it is not only important to study artificial intelligence algorithms, but how to theoretically adjust the input values. Third, we confirmed that firms classified as Global Industrial Classification Standard (GICS) might have low relevance and suggested it is necessary to theoretically define the relevance rather than simply finding it in the GICS.

• The Korean Journal of Archival Studies
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• no.54
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• pp.111-150
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• 2017

This paper examines the current situation of sources on Korean Class B and C war criminals attached as civilians to the Japanese military during the Asian Pacific War charged with cruelly treating Allied POWs in Japanese POW camps, and also explores the possibility of a joint Korean-Japanese archive of these sources. The Japanese government agreed to the judgement of war crimes by accepting the terms of the Potsdam Declaration, and the Allied troops carried out the judgement of Class B and C war crimes in each region of Asia and the International Military Tribunal for the Far East (also known as the Tokyo Trials). However, many non-Japanese such as Koreans and Taiwanese from the Japanese colonies were prosecuted for war crimes. The issues of reparations and restoring their reputations were ignored by both the Korean and Japanese governments, and public access to their records restricted. Most records on Korean Class B and C war criminals were transferred from each ministry to the National Archives of Japan. The majority are copies of the judgements of war crimes by the Allied nations or records prepared for the erasure of Japanese war crimes after each department operated independently of the Japanese government. In the case of the Diplomatic Archives of the Ministry of Foreign Affairs, such records focused mostly on their war crimes and the transfer of B and C war criminals within Japan and the diplomatic situation. In the case of Korea and Taiwan, these records were related to the negotiations on the repatriation of Class B and C war criminals. In addition, the purpose of founding of the Japan Center for Asian Historical Records and its activities demonstrate its tremendous utility as a facility for building a joint Korea-Japan colonial archive. Thus, the current flaws of the Japan Center for Asian Historical Records should be improved on in order to build a such a joint archive in the future.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.2
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• pp.221-233
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• 2019

In Korea, small and medium sized domestic enterprises(SMEs) play an pivotal role in the national economy, accounting for 99.9% of all enterprises, 87.9% of total employment, and 48.3% of production. and SMEs was driving a real force of the development of national economy in many respects such as innovation, job creation, industrial diversity, balanced regional development. Despite their crucial role in the national development, most of SMEs suffer from a lack of R&D capabilities and equipments as well as funding capacity. Public R&D institutes can provide SMEs with valuable supplementary technological knowledge and help them build technological capacity. so, In order to effectively support SMEs, government and public R&D institutes must be a priority to know about the factors influencing the performance related to technology transfer and technological collaborations. In particular, SMEs are not only taking up a large portion of the national economy, but also their influence in politics and economy so strong that raising the competitiveness of small and medium-sized companies is a national policy goal that must be achieved in order to achieve sustained economic growth. For this reason, it is necessary to look specifically at the relationship between concepts such as the environment, strategy, and organizational culture surrounding the enterprise to enhance the competitiveness of SMEs. The paper analyzes 665 companies to find out which organizational culture affects their performance by classification and type of business of SMEs. This study demonstrated that when SMEs seek consistency in their external environment, strategies, and organizational structure to maintain their continued competitiveness. According to three-way analysis of variance (3-way ANOVA) indicates that classification of industries in SMEs has statistically significant main effects, but the type of business and organizational culture do not have significant effects. However, the company's organizational performance (operating profit) of SMES were found to differ significantly in comparison between groups according to classification standards of industries, and therefore adopted some parts. In addition, an analysis of the effect of interaction between the three independent variables of small and medium-sized enterprises has shown that there are statistically significant interaction effects among classification, types of business, and organizational cultures. The results shows that there is an organizational culture suitable for each industry classification and type of business of an entity, and is expected to be used as a basis for establishing promotion policies related to the incubation and commerciality of small and medium-sized venture companies in the future.

• Journal of the Daesoon Academy of Sciences
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• v.40
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• pp.243-272
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• 2022

Jeongeup, Jeollabuk-do, is an area that requires attention from those who study the history of Korean thought. In addition, Jeongeup is an area wherein many works were recorded for the first time in literary history. This is the case with Jeongeupsa as a style of Baekje songs and the lyrics of the noble families of the Joseon Dynasty, Sangchungok. Jeongeup is likewise the location where Choi Chi-won (857~?) was selected to serve as a local taesu (viceroy) and where a unique tradition of music and style were passed down. In this paper, the relationship between Choi Chi-won's role in the process of establishing a silent Confucian academy in Jeongeup and the emergence of scholar culture was examined. When Choi Chi-won left after his term in office, a birth shrine called Taesansa Temple was built to repay the selection of the villagers, and it became the source that led to the opening of the Confucian academy Museongseowon in the future. Jeongeup will be shown to be the location where Choi Chi-won realized his aspirations and honed his capabilities. In particular, Choi Chi-won's played a crucial role in the mid-Joseon Dynasty by supporting the construction and securing the name of Museongseowon. That is why Choi Chi-won was able to be revived as a symbolic figure in the region. In addition, it can be seen that the shape of Choi Chi-won was more sedentary- in the form of a Confucian scholar- and Confucian scholars emphasized the transfer of portraits at Museongseowon. Through the poetry written by Choi Chi-won, readers can learn about the worries and perceptions of scholars during those times. Although his value in the field of poetry is diverse, he can especially be recognized as a Confucian intellectual. In a large number of his works, he expresses his anxiety, agony, and critical inner consciousness all of which came from his encounter with the realities of his time. In fact, Choi Chi-won showed his qualities as a prominent literary figure of his time who had extraordinary aspirations and an admirable work ethic. However, he failed to overcome his regional and mental alienation as a poet in neighboring countries. Therefore, he internalized a sort of fierceness in terms of his perception of the world. However, it seems that it was rather a factor that made his work exhibit a strong lyrical style. In addition, Choi Chi-won's collection of writings includes a number of works that strongly criticized various forms of pathological phenomena caused by terminal phenomena of the time. He also highlighted the wrong in society by realistically depicting the lives poor and needy people and their eventual sacrifice via distorted relationships. This can be read encapsulating the agony of intellectuals of that time. The dictionary definition of a 'Confucian scholar' is "a Confucian term referring to a person or class that embodies Confucian ideology," and in its contemporary meaning it suggests " ⋯ an example of a personality, but not an identity, and the conscience of one's time period as a source of human morality inwardly and social order outwardly." In this respect, it could even be said that Choi Chi-won could be considered the originator of scholar culture.

• Composites Research
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• v.36 no.1
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• pp.1-15
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• 2023

Demand for energy consumption reduction is increasing according to the development expectations of future mobility. Lightweight structural materials are known as a method to reduce greenhouse gas emissions and improve energy efficiency. In particular, fiber reinforced polymer composite (FRP) is attracting attention as a material that can replace existing metal alloys due to its excellent mechanical properties and light weight. In this paper, industrial applications and research trends of carbon fiber reinforced composites (CFRP, carbon FRP) and self-reinforced composites (SRC) were reviewed based on the reinforcement, polymer matrix, and manufacturing process. In order to overcome the expensive process cost and long manufacturing time of the epoxy resin-based autoclave method, which is mainly used in the aircraft field, mass production of CFRP-applied electric vehicles has been reported using a high-pressure resin transfer molding process including fast-curing epoxy. In addition, thermoplastic resin-based CFRP and interface enhancement methods to solve the recycling issue of carbon fiber composites were reviewed in terms of materials and processes. To form a perfect matrix-reinforcement interface, which is known as the major factor inducing the excellent mechanical properties of FRP, studies on SRC impregnated with the same matrix in polymer fibers have been reported. The physical and mechanical properties of SRC based on various thermoplastic polymers were reviewed in terms of polymer orientation and composite structure. In addition, a copolymer matrix strategy for extending the processing window of highly drawn polypropylene fiber-based SRC was discussed. The application of CFRP and SRC as lightweight structural materials can provide potential options for improving the energy efficiency of future mobility.

• Asia pacific journal of information systems
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• v.18 no.3
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• pp.123-145
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• 2008

Recently, as the information communication technology develops, the discussion regarding the ubiquitous environment is occurring in diverse perspectives. Ubiquitous environment is an environment that could transfer data through networks regardless of the physical space, virtual space, time or location. In order to realize the ubiquitous environment, the Pervasive Sensing technology that enables the recognition of users' data without the border between physical and virtual space is required. In addition, the latest and diversified technologies such as Context-Awareness technology are necessary to construct the context around the user by sharing the data accessed through the Pervasive Sensing technology and linkage technology that is to prevent information loss through the wired, wireless networking and database. Especially, Pervasive Sensing technology is taken as an essential technology that enables user oriented services by recognizing the needs of the users even before the users inquire. There are lots of characteristics of ubiquitous environment through the technologies mentioned above such as ubiquity, abundance of data, mutuality, high information density, individualization and customization. Among them, information density directs the accessible amount and quality of the information and it is stored in bulk with ensured quality through Pervasive Sensing technology. Using this, in the companies, the personalized contents(or information) providing became possible for a target customer. Most of all, there are an increasing number of researches with respect to recommender systems that provide what customers need even when the customers do not explicitly ask something for their needs. Recommender systems are well renowned for its affirmative effect that enlarges the selling opportunities and reduces the searching cost of customers since it finds and provides information according to the customers' traits and preference in advance, in a commerce environment. Recommender systems have proved its usability through several methodologies and experiments conducted upon many different fields from the mid-1990s. Most of the researches related with the recommender systems until now take the products or information of internet or mobile context as its object, but there is not enough research concerned with recommending adequate store to customers in a ubiquitous environment. It is possible to track customers' behaviors in a ubiquitous environment, the same way it is implemented in an online market space even when customers are purchasing in an offline marketplace. Unlike existing internet space, in ubiquitous environment, the interest toward the stores is increasing that provides information according to the traffic line of the customers. In other words, the same product can be purchased in several different stores and the preferred store can be different from the customers by personal preference such as traffic line between stores, location, atmosphere, quality, and price. Krulwich(1997) has developed Lifestyle Finder which recommends a product and a store by using the demographical information and purchasing information generated in the internet commerce. Also, Fano(1998) has created a Shopper's Eye which is an information proving system. The information regarding the closest store from the customers' present location is shown when the customer has sent a to-buy list, Sadeh(2003) developed MyCampus that recommends appropriate information and a store in accordance with the schedule saved in a customers' mobile. Moreover, Keegan and O'Hare(2004) came up with EasiShop that provides the suitable tore information including price, after service, and accessibility after analyzing the to-buy list and the current location of customers. However, Krulwich(1997) does not indicate the characteristics of physical space based on the online commerce context and Keegan and O'Hare(2004) only provides information about store related to a product, while Fano(1998) does not fully consider the relationship between the preference toward the stores and the store itself. The most recent research by Sedah(2003), experimented on campus by suggesting recommender systems that reflect situation and preference information besides the characteristics of the physical space. Yet, there is a potential problem since the researches are based on location and preference information of customers which is connected to the invasion of privacy. The primary beginning point of controversy is an invasion of privacy and individual information in a ubiquitous environment according to researches conducted by Al-Muhtadi(2002), Beresford and Stajano(2003), and Ren(2006). Additionally, individuals want to be left anonymous to protect their own personal information, mentioned in Srivastava(2000). Therefore, in this paper, we suggest a methodology to recommend stores in U-market on the basis of ubiquitous environment not using personal information in order to protect individual information and privacy. The main idea behind our suggested methodology is based on Feature Matrices model (FM model, Shahabi and Banaei-Kashani, 2003) that uses clusters of customers' similar transaction data, which is similar to the Collaborative Filtering. However unlike Collaborative Filtering, this methodology overcomes the problems of personal information and privacy since it is not aware of the customer, exactly who they are, The methodology is compared with single trait model(vector model) such as visitor logs, while looking at the actual improvements of the recommendation when the context information is used. It is not easy to find real U-market data, so we experimented with factual data from a real department store with context information. The recommendation procedure of U-market proposed in this paper is divided into four major phases. First phase is collecting and preprocessing data for analysis of shopping patterns of customers. The traits of shopping patterns are expressed as feature matrices of N dimension. On second phase, the similar shopping patterns are grouped into clusters and the representative pattern of each cluster is derived. The distance between shopping patterns is calculated by Projected Pure Euclidean Distance (Shahabi and Banaei-Kashani, 2003). Third phase finds a representative pattern that is similar to a target customer, and at the same time, the shopping information of the customer is traced and saved dynamically. Fourth, the next store is recommended based on the physical distance between stores of representative patterns and the present location of target customer. In this research, we have evaluated the accuracy of recommendation method based on a factual data derived from a department store. There are technological difficulties of tracking on a real-time basis so we extracted purchasing related information and we added on context information on each transaction. As a result, recommendation based on FM model that applies purchasing and context information is more stable and accurate compared to that of vector model. Additionally, we could find more precise recommendation result as more shopping information is accumulated. Realistically, because of the limitation of ubiquitous environment realization, we were not able to reflect on all different kinds of context but more explicit analysis is expected to be attainable in the future after practical system is embodied.

• Asia pacific journal of information systems
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• v.21 no.1
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• pp.103-122
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• 2011

Recently, numerous documents have been made available electronically. Internet search engines and digital libraries commonly return query results containing hundreds or even thousands of documents. In this situation, it is virtually impossible for users to examine complete documents to determine whether they might be useful for them. For this reason, some on-line documents are accompanied by a list of keywords specified by the authors in an effort to guide the users by facilitating the filtering process. In this way, a set of keywords is often considered a condensed version of the whole document and therefore plays an important role for document retrieval, Web page retrieval, document clustering, summarization, text mining, and so on. Since many academic journals ask the authors to provide a list of five or six keywords on the first page of an article, keywords are most familiar in the context of journal articles. However, many other types of documents could not benefit from the use of keywords, including Web pages, email messages, news reports, magazine articles, and business papers. Although the potential benefit is large, the implementation itself is the obstacle; manually assigning keywords to all documents is a daunting task, or even impractical in that it is extremely tedious and time-consuming requiring a certain level of domain knowledge. Therefore, it is highly desirable to automate the keyword generation process. There are mainly two approaches to achieving this aim: keyword assignment approach and keyword extraction approach. Both approaches use machine learning methods and require, for training purposes, a set of documents with keywords already attached. In the former approach, there is a given set of vocabulary, and the aim is to match them to the texts. In other words, the keywords assignment approach seeks to select the words from a controlled vocabulary that best describes a document. Although this approach is domain dependent and is not easy to transfer and expand, it can generate implicit keywords that do not appear in a document. On the other hand, in the latter approach, the aim is to extract keywords with respect to their relevance in the text without prior vocabulary. In this approach, automatic keyword generation is treated as a classification task, and keywords are commonly extracted based on supervised learning techniques. Thus, keyword extraction algorithms classify candidate keywords in a document into positive or negative examples. Several systems such as Extractor and Kea were developed using keyword extraction approach. Most indicative words in a document are selected as keywords for that document and as a result, keywords extraction is limited to terms that appear in the document. Therefore, keywords extraction cannot generate implicit keywords that are not included in a document. According to the experiment results of Turney, about 64% to 90% of keywords assigned by the authors can be found in the full text of an article. Inversely, it also means that 10% to 36% of the keywords assigned by the authors do not appear in the article, which cannot be generated through keyword extraction algorithms. Our preliminary experiment result also shows that 37% of keywords assigned by the authors are not included in the full text. This is the reason why we have decided to adopt the keyword assignment approach. In this paper, we propose a new approach for automatic keyword assignment namely IVSM(Inverse Vector Space Model). The model is based on a vector space model. which is a conventional information retrieval model that represents documents and queries by vectors in a multidimensional space. IVSM generates an appropriate keyword set for a specific document by measuring the distance between the document and the keyword sets. The keyword assignment process of IVSM is as follows: (1) calculating the vector length of each keyword set based on each keyword weight; (2) preprocessing and parsing a target document that does not have keywords; (3) calculating the vector length of the target document based on the term frequency; (4) measuring the cosine similarity between each keyword set and the target document; and (5) generating keywords that have high similarity scores. Two keyword generation systems were implemented applying IVSM: IVSM system for Web-based community service and stand-alone IVSM system. Firstly, the IVSM system is implemented in a community service for sharing knowledge and opinions on current trends such as fashion, movies, social problems, and health information. The stand-alone IVSM system is dedicated to generating keywords for academic papers, and, indeed, it has been tested through a number of academic papers including those published by the Korean Association of Shipping and Logistics, the Korea Research Academy of Distribution Information, the Korea Logistics Society, the Korea Logistics Research Association, and the Korea Port Economic Association. We measured the performance of IVSM by the number of matches between the IVSM-generated keywords and the author-assigned keywords. According to our experiment, the precisions of IVSM applied to Web-based community service and academic journals were 0.75 and 0.71, respectively. The performance of both systems is much better than that of baseline systems that generate keywords based on simple probability. Also, IVSM shows comparable performance to Extractor that is a representative system of keyword extraction approach developed by Turney. As electronic documents increase, we expect that IVSM proposed in this paper can be applied to many electronic documents in Web-based community and digital library.