• Journal of Korea Society of Industrial Information Systems
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• v.21 no.4
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• pp.67-78
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• 2016

Recently many countries around the world are actively promoting smart city projects to address various urban problems such as traffic congestion, housing shortage, and energy scarcity. Due to development of the Internet of Things (IoT), the development of a smart city with sustainability, convenience, and environment-friendliness was enabled through the effective control and reuse of urban resources. The purpose of this study is to analyze the technical trends of IoT and present a development plan for smart city which is one of the applications of the IoT. To this end, the news articles of the Electronic Times between 2013 and 2015were analyzed using the text mining technique and smart city development cases of other countries were investigated. The analysis results revealed the close relationships of big data, cloud, platforms, and sensors with smart city. For the successful development of a smart city, first, all the interested parties in the city must work together to create new values throughout the entire process of value chain. Second, they must utilize big data and disclose public data more actively than they are doing now. This study has made academic contribution in that it has presented a big data analysis method and stimulated follow-up studies. For the practical contribution, the results of this study provided useful data for the policy making of local governments and administrative agencies for smart city development. This study may have limitations in the incorporation of the total trends because only the news articles of the Electronic Times were selected to analyze the technical trends of the IoT.

• Journal of the Korean Institute of Landscape Architecture
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• v.46 no.4
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• pp.21-35
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• 2018

In recent years, there has been a tendency to reuse 'landscapes of memory,' including industrial heritages, modern cultural heritages, and post-industrial parks, as public spaces in many cities. Among the various types of landscapes, 'modern historic landscapes', which were formed in the 19th and 20th centuries, are landscapes where the debate between conservation and removal is most frequent, according to the change of evaluation and recognition of modern history. This study examines conflicts between conservation and removal around modern historic landscapes and explores the value judgment criteria and the process of formation of those landscapes, as highlighted in the case of the demolition controversy of the old Japanese general government building in Seoul, which was dismantled in 1995. First, this study reviews newspaper articles, television news and debate programs from 1980-1999 and some articles related to the controversy of the Japanese general government building. Then it draws the following six factors as the main issues of the demolition controversy of the building: symbolic location, discoveries and responses of new historical facts, reaction and intervention of a related country, financial conditions, function and usage of the landscape, changes of urban, historical and architectural policies. Based on these issues, this study examines the conflicts between symbolic values that play an important role in the formation of modern historic landscapes and determines conservation or removal, and the utility of functional values that solve the problems and respond to criticisms that arise in the process of forming the modern historic landscape. Especially, it is noted that the most important factor that makes the decision is the symbolic values, although the determination of the conservation or removal of modern historic landscapes has changed according to changes in historical perceptions of modern history. Today, the modern historic landscape is an important site for urban design, and still has historical issues to be agreed upon and addressed. Thi study has contemporary significance from the point that it divides the many values of modern historic landscapes into symbolic values and functional values, evaluates these, and reviews the background social context.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.1-23
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• 2013

To discover significant social issues such as unemployment, economy crisis, social welfare etc. that are urgent issues to be solved in a modern society, in the existing approach, researchers usually collect opinions from professional experts and scholars through either online or offline surveys. However, such a method does not seem to be effective from time to time. As usual, due to the problem of expense, a large number of survey replies are seldom gathered. In some cases, it is also hard to find out professional persons dealing with specific social issues. Thus, the sample set is often small and may have some bias. Furthermore, regarding a social issue, several experts may make totally different conclusions because each expert has his subjective point of view and different background. In this case, it is considerably hard to figure out what current social issues are and which social issues are really important. To surmount the shortcomings of the current approach, in this paper, we develop a prototype system that semi-automatically detects social issue keywords representing social issues and problems from about 1.3 million news articles issued by about 10 major domestic presses in Korea from June 2009 until July 2012. Our proposed system consists of (1) collecting and extracting texts from the collected news articles, (2) identifying only news articles related to social issues, (3) analyzing the lexical items of Korean sentences, (4) finding a set of topics regarding social keywords over time based on probabilistic topic modeling, (5) matching relevant paragraphs to a given topic, and (6) visualizing social keywords for easy understanding. In particular, we propose a novel matching algorithm relying on generative models. The goal of our proposed matching algorithm is to best match paragraphs to each topic. Technically, using a topic model such as Latent Dirichlet Allocation (LDA), we can obtain a set of topics, each of which has relevant terms and their probability values. In our problem, given a set of text documents (e.g., news articles), LDA shows a set of topic clusters, and then each topic cluster is labeled by human annotators, where each topic label stands for a social keyword. For example, suppose there is a topic (e.g., Topic1 = {(unemployment, 0.4), (layoff, 0.3), (business, 0.3)}) and then a human annotator labels "Unemployment Problem" on Topic1. In this example, it is non-trivial to understand what happened to the unemployment problem in our society. In other words, taking a look at only social keywords, we have no idea of the detailed events occurring in our society. To tackle this matter, we develop the matching algorithm that computes the probability value of a paragraph given a topic, relying on (i) topic terms and (ii) their probability values. For instance, given a set of text documents, we segment each text document to paragraphs. In the meantime, using LDA, we can extract a set of topics from the text documents. Based on our matching process, each paragraph is assigned to a topic, indicating that the paragraph best matches the topic. Finally, each topic has several best matched paragraphs. Furthermore, assuming there are a topic (e.g., Unemployment Problem) and the best matched paragraph (e.g., Up to 300 workers lost their jobs in XXX company at Seoul). In this case, we can grasp the detailed information of the social keyword such as "300 workers", "unemployment", "XXX company", and "Seoul". In addition, our system visualizes social keywords over time. Therefore, through our matching process and keyword visualization, most researchers will be able to detect social issues easily and quickly. Through this prototype system, we have detected various social issues appearing in our society and also showed effectiveness of our proposed methods according to our experimental results. Note that you can also use our proof-of-concept system in http://dslab.snu.ac.kr/demo.html.

• Korean journal of communication and information
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• v.19
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• pp.213-238
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• 2002

Ie is popular belief among the authorities concerned and their apologists that media coverage of terrorism promotes terrorism and is used as publicity by terrorists. Generally speaking, however, in reporting terrorism, the media become not terrorists' but state's means of publicity, and condemn terrorism, while rationalizing state's violence against terrorism. Terrorists may be successful in attracting public attention at the initial stage of terrorism, but usually fail in publicizing their cause. This fact notwithstanding, the authorities concerned and their apologists maintain thar media coverage of terrorism should be controlled, because it works as publicity for terrorists. Now it can be said that there is an intention to control the media when it is asserted that media coverage of terrorism works as publicity for terrorists. To present these arguments, this article discusses the news values and publicity aspect of terrorism, reviews some problems of and misunderstanding about media coverage of terrorism, and for illustrations, look into the American media's coverage of the 9-11 terrorism against the U. S. and "war on terror". that is, state terrorism taken as a countermeasure to it by the U. S.

• The Journal of the Acoustical Society of Korea
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• v.19 no.2
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• pp.101-105
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• 2000

A telegram has been used to transmit the emergency news or celebration message. So, it has been very important media in our life. Although the telegram processing is more and more convenient, on the other hand, the telegram service contains only text message. The voice telegram is that delivering user's voice with text message. So, the voice telegram can be delivered sender's emotions and feelings. However, since voice information contains lots of data, large memory size and high cost processor are needed to deliver itself. In this paper, we proposed a new speech waveform coding method that has low complexity and low cost implementation for the voice telegram system. First, we fixed one basic speech waveform per pitch period and measured the waveform similarity between basic and neighbor speech waveform. Second, if the similarity satisfied threshold values, we compress the neighbor speech waveform with pitch and magnitude value per pitch period and if not, we save speech waveform. When the compression is about 45%, we obtained about 4 point in MOS.

• The Journal of the Korea Contents Association
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• v.15 no.9
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• pp.134-145
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• 2015

It has been 1 year since Sewol Ferry disaster occurred in the Gwanmaedo sea of Jindo, Jeollanamdo, on Apr. 16, 2014. The Sewol Ferry Disaster which took 304 lives and had some victims still missed has become the largest tragic accident in Korea since 2010. Although one year has passed since the disaster, there is no psychological communication research on the trauma of the victims' families. This study first investigated the actual state of the Sewol Ferry victims' parents suffering from post-traumatic stress disorder (PTSD) after their losses of children by the disaster. This study revealed that the victims' families suffer from physical and psychological the PTSD but neglect treatment. The PTSD still influences their daily life. It was observed that the victims' families have a lot of difficulties with interpersonal relationship, relationship with co-workers, residence, values, and other kinds of daily life. Given that the victims' families have a great deal of PTSD after the disaster, the academic circle needs to make discussions of the issue actively in order to heal the pains of the Sewol Ferry victims' families who are unattended in our society.

• Journal of Environmental Policy
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• v.11 no.2
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• pp.17-54
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• 2012

This paper researched market responses for listed companies in several industries affected by the major oil spill accident off the coast of Taean, in December 7, 2007. The Taean accident triggered considerable concerns in people over the possibility of potential future regulation in shipbuilding and petroleum industries. However, the accident also provided an unexpected business opportunity for environmental clean-up industry and shipbuilding industry. The oil spill triggered the acceleration of the enactment of policies that require all new oil tankers to be constructed with double hull, which is interpreted as a good news for shipbuilding industry. Increased public pressure coupled with the prospect of tightened regulation is expected to decrease the market values of firms in the affected business fields. The stock prices of shipbuilding companies dropped after the incident but dramatically surged after the enactment of the policy in January 31, 2008. Our study also found that companies with more extensive prior environmental disclosure had less negative market reactions during the first sixteen days following the accident.

• Journal of Korea Society of Industrial Information Systems
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• v.17 no.1
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• pp.21-29
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• 2012

In this paper, we propose a new method to select colors representing the meaning of text contents based on the cognitive relation between words and colors, Our method is designed on the previous study revealing the existence of crucial words to estimate the colors associated with the meaning of text contents, Using the associative probability of each color with a given word and the strength of color association of the word, we estimate the probability of colors associated with a given text. The goal of this study is to propose a system to recommend the cognitively plausible colors for the meaning of the input text. To build a versatile and efficient database used by our system, two psychological experiments were conducted by using news site articles. In experiment 1, we collected 498 words which were chosen by the participants as having the strong association with color. Subsequently, we investigated which color was associated with each word in experiment 2. In addition to those data, we employed the estimated values of the strength of color association and the colors associated with the words included in a very large corpus of newspapers (approximately 130,000 words) based on the similarity between the words obtained by Latent Semantic Analysis (LSA). Therefore our method allows us to select colors for a large variety of words or sentences. Finally, we verified that our system cognitively succeeded in proposing the colors associated with the meaning of the input text, comparing the correct colors answered by participants with the estimated colors by our method. Our system is expected to be of use in various types of situations such as the data visualization, the information retrieval, the art or web pages design, and so on.

• Health Policy and Management
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• v.26 no.1
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• pp.51-62
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• 2016

Background: The publicness concept in healthcare has been built to its social consensus relying on historical context, with the result that the meaning of publicness has a great diversity and heterogeneous nature in Korea. Thus it needs to be addressed to clarify the meaning and boundary of the publicness concept in healthcare, so as to discuss its social implication. Methods: In order to investigate whether or how the publicness concept is used in healthcare, we conducted a text network analysis in 779 news articles from 8 Korean daily newspapers over a recent 5-year period. Results: The publicness concept was closely related to medicine and medical institution, and formed a conceptual network with public health, medicine, welfare, patient, government, Jin-ju city, and health. Keywords relating publicness tended to be similar between four major newspapers; however, the association with Jin-ju city, government, and society was noticeable in Kyunghyang Shinmun and Hankyoreh, and so was patient and service in Dong-A Ilbo. Conclusion: Publicness and medicine was closely associated, and government seemed to remain as a main actor for public interest. Publicness was related with a variety of actors and values, with its expanded boundary. The different contexts of publicness by newspapers might reflect each ideological inclination. The textual importance of publicness was relatively low in part, which suggests that publicness was used in a loose sense or as a routine.

• Korean journal of communication and information
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• v.49
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• pp.81-98
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• 2010

This study was executed with the aim of finding out how journalists accept the market-driven journalism. 24 journalists were selected from each conservative and progressive newspapers and held in-depth interviews. The result show journalists believe that news articles should be useful than interesting. Also the result show they think it is just market-driven journalism that making public issues to social dispute in Korea. And most of them thought newspaper should be made toward upgrading it‘s contents and quality. There were some differences in thinking about those study issue between journalists belong to conservative and progressive newspapers. But there were no differences between reporters and desks.