• Journal of Korea Multimedia Society
• /
• v.14 no.1
• /
• pp.121-132
• /
• 2011

A healthcare system is a type of medical information system that performs early detection and prevention in diseases by checking one's health condition periodically. Such a healthcare system is based on the signal obtained from the body. However, the developed existing system represents certain differences in the storage and description of vital signs according to medicare devices and the evaluation method of the system. It brings some disadvantages, such as lacks in the interoperability between systems, increases in the development cost of systems, and absence of a unified system. Thus, this study develops a healthcare system based on a meta model. For establishing this objective, this study describes and stores vital sign data based on the standard meta model of HL7 and applies OCL, which is a mathematical specification language, for defining wellness indexes and extracting data in order to evaluate health risk appraisals in health. In addition, this study implements components based on OSGi and assemble them in order to easily extend various devices and systems. By describing vital data based on the meta model, it represents some advantages that it makes possible to ensure the interoperability between systems and introduce the standardization of the evaluation method of health conditions through defining the wellness index using OCL. Also, it provides dear specifications.

• Journal of the Korean Society for Library and Information Science
• /
• v.57 no.3
• /
• pp.97-117
• /
• 2023

The purpose of this study is to suggest a mid- to long-term expansion plan to resolve the blind spot and alleviate the imbalance of public library services in Daegu City. The research methods for this purpose included literature review, related laws and statistical data analysis, case study, and opinion survey. As a result, the first service area was set as a total of 14 areas based on administrative districts(Jung-gu, Seo-gu, Nam-gu, and Dalseong-gun each have one, Dong-gu and Buk-gu each have two, and Suseong-gu and Dalseo-gu have three each). Second, the expansion scenario for public libraries in Daegu City was proposed to add 26 libraries by the final target year (2032) based on the trend of national library growth over the past 13 years (2008-2020) and the forecast for the next 10 years (2023-2032). Third, the construction scenarios for each basic local government, excluding the Daegu representative library, are as follows: One library each in Jung-gu, Seo-gu, and Nam-gu; two libraries in Suseong-gu; three libraries in Dalseong-gun; four libraries in Dong-gu; and seven libraries each in Buk-gu and Dalseo-gu. In terms of floor area, it is proposed to add a total of 17 branch libraries with a minimum legal standard of 330-2,499㎡, four central libraries with 2,500-4,999㎡ each, and four central libraries with 5,000-9,999㎡ each. On the premise of these conditions, Daegu City and public libraries should focus on creating an inclusive and open community space, creating a digital platform, strengthening the library operation and cooperation system centered on Daegu representative library, developing collections and specializing services for local hub libraries, enhancing various knowledge information and program services, managing key library indicators and improving social contribution.

• Journal of Intelligence and Information Systems
• /
• v.22 no.2
• /
• pp.57-79
• /
• 2016

It is a rising trend that the number of users using one of the social media channels, the Social Network Service, so called the SNS, is getting increased. As per to this social trend, more companies have interest in this networking platform and start to invest their funds in it. It has received much attention as a tool spreading and expanding the message that a company wants to deliver to its customers and has been recognized as an important channel in terms of the relationship marketing with them. The environment of media that is radically changing these days makes possible for companies to approach their customers in various ways. Particularly, the social network service, which has been developed rapidly, provides the environment that customers can freely talk about products. For companies, it also works as a channel that gives customized information to customers. To succeed in the online environment, companies need to not only build the relationship between companies and customers but focus on the relationship between customers as well. In response to the online environment with the continuous development of technology, companies have tirelessly made the novel marketing strategy. Especially, as the one-to-one marketing to customers become available, it is more important for companies to maintain the relationship marketing with their customers. Among many SNS, Facebook, which many companies use as a communication channel, provides a fan page service for each company that supports its business. Facebook fan page is the platform that the event, information and announcement can be shared with customers using texts, videos, and pictures. Companies open their own fan pages in order to inform their companies and businesses. Such page functions as the websites of companies and has a characteristic of their brand communities such as blogs as well. As Facebook has become the major communication medium with customers, companies recognize its importance as the effective marketing channel, but they still need to investigate their business performances by using Facebook. Although there are infinite potentials in Facebook fan page that even has a function as a community between users, which other platforms do not, it is incomplete to regard companies' Facebook fan pages as communities and analyze them. In this study, it explores the relationship among customers through the network of the Facebook fan page users. The previous studies on a company's Facebook fan page were focused on finding out the effective operational direction by analyzing the use state of the company. However, in this study, it draws out the structural variable of the network, which customer committment can be measured by applying the social network analysis methodology and investigates the influence of the structural characteristics of network on the business performance of companies in an empirical way. Through each company's Facebook fan page, the network of users who engaged in the communication with each company is exploited and it is the one-mode undirected binary network that respectively regards users and the relationship of them in terms of their marketing activities as the node and link. In this network, it draws out the structural variable of network that can explain the customer commitment, who pressed "like," made comments and shared the Facebook marketing message, of each company by calculating density, global clustering coefficient, mean geodesic distance, diameter. By exploiting companies' historical performance such as net income and Tobin's Q indicator as the result variables, this study investigates influence on companies' business performances. For this purpose, it collects the network data on the subjects of 54 companies among KOSPI-listed companies, which have posted more than 100 articles on their Facebook fan pages during the data collection period. Then it draws out the network indicator of each company. The indicator related to companies' performances is calculated, based on the posted value on DART website of the Financial Supervisory Service. From the academic perspective, this study suggests a new approach through the social network analysis methodology to researchers who attempt to study the business-purpose utilization of the social media channel. From the practical perspective, this study proposes the more substantive marketing performance measurements to companies performing marketing activities through the social media and it is expected that it will bring a foundation of establishing smart business strategies by using the network indicators.

• Journal of Intelligence and Information Systems
• /
• v.21 no.2
• /
• pp.49-67
• /
• 2015

Recently, emerging the notion of big data and social media has led us to enter data's big bang. Social networking services are widely used by people around the world, and they have become a part of major communication tools for all ages. Over the last decade, as online social networking sites become increasingly popular, companies tend to focus on advanced social media analysis for their marketing strategies. In addition to social media analysis, companies are mainly concerned about propagating of negative opinions on social networking sites such as Facebook and Twitter, as well as e-commerce sites. The effect of online word of mouth (WOM) such as product rating, product review, and product recommendations is very influential, and negative opinions have significant impact on product sales. This trend has increased researchers' attention to a natural language processing, such as a sentiment analysis. A sentiment analysis, also refers to as an opinion mining, is a process of identifying the polarity of subjective information and has been applied to various research and practical fields. However, there are obstacles lies when Korean language (Hangul) is used in a natural language processing because it is an agglutinative language with rich morphology pose problems. Therefore, there is a lack of Korean natural language processing resources such as a sentiment lexicon, and this has resulted in significant limitations for researchers and practitioners who are considering sentiment analysis. Our study builds a Korean sentiment lexicon with collective intelligence, and provides API (Application Programming Interface) service to open and share a sentiment lexicon data with the public (www.openhangul.com). For the pre-processing, we have created a Korean lexicon database with over 517,178 words and classified them into sentiment and non-sentiment words. In order to classify them, we first identified stop words which often quite likely to play a negative role in sentiment analysis and excluded them from our sentiment scoring. In general, sentiment words are nouns, adjectives, verbs, adverbs as they have sentimental expressions such as positive, neutral, and negative. On the other hands, non-sentiment words are interjection, determiner, numeral, postposition, etc. as they generally have no sentimental expressions. To build a reliable sentiment lexicon, we have adopted a concept of collective intelligence as a model for crowdsourcing. In addition, a concept of folksonomy has been implemented in the process of taxonomy to help collective intelligence. In order to make up for an inherent weakness of folksonomy, we have adopted a majority rule by building a voting system. Participants, as voters were offered three voting options to choose from positivity, negativity, and neutrality, and the voting have been conducted on one of the largest social networking sites for college students in Korea. More than 35,000 votes have been made by college students in Korea, and we keep this voting system open by maintaining the project as a perpetual study. Besides, any change in the sentiment score of words can be an important observation because it enables us to keep track of temporal changes in Korean language as a natural language. Lastly, our study offers a RESTful, JSON based API service through a web platform to make easier support for users such as researchers, companies, and developers. Finally, our study makes important contributions to both research and practice. In terms of research, our Korean sentiment lexicon plays an important role as a resource for Korean natural language processing. In terms of practice, practitioners such as managers and marketers can implement sentiment analysis effectively by using Korean sentiment lexicon we built. Moreover, our study sheds new light on the value of folksonomy by combining collective intelligence, and we also expect to give a new direction and a new start to the development of Korean natural language processing.

• The Journal of Korean Institute for Practical Engineering Education
• /
• v.3 no.2
• /
• pp.18-26
• /
• 2011

Computational chemistry is one of the chemistry fields that deals with the theoretical chemistry problem using computer calculations and can be described as the chemistry lab moved on computer space. In line with recent enhancement of processing capability of computers, utilization of high performance computer cannot be overemphasized in the field of computational chemistry in performing complex calculation of huge molecular structure and simulation. While they have to use commands and consoles for high performance computer to execute complex calculation of huge molecular structure and simulation, most of students in natural science and engineering, who are not experts in computer technically, are likely to be unaware of UNIX. Under the circumstances, web-based educational support system for computational chemistry is needed to enable them to practice computational chemistry, even not knowing UNIX command. In this study, e-Chem, one of such educational support systems, is developed by using Liferay portal platform, which is a Java open source more oriented to standard and outstanding in its content management and collaboration function than other web portals. By using this system, even students who are not familiar with computer, are expected to take part in lab classes and save time learning Unix command and also enhance the learning efficiency by using familiar interface.

• Journal of Digital Convergence
• /
• v.14 no.4
• /
• pp.163-171
• /
• 2016

This study derived the policy implications and market strategies by analysis the e-book companies requirements & the CPND value chain structure, in order to revitalize the e-book market in Korea. Specifically, we examined the prospect of e-book market in Korea, current situations of production and distribution, awareness of service utilization and requirements for support policy with targets of 30 companies. As a research, the most needed item for e-book companies is 'PR and marketing support to enter and open the markets'(27%), which is the highest. 'Financial support such as labor costs and business expenses', 'support for retraining personnel to develop the expertise in respective fields' are followed and they account for 22%. Currently, the most effective support item is the external support program(35%) and funding power(30%) is followed. Unlike a paper book market, e-book is turned into a platform business in terms of the value chain. Based on these research content, e-book market activation and corporate competitive strategy was derived as follows : 1)literacy reinforcement about SNS marketing and e-pub3 authoring tool. 2)statistical DB construction of retail sales channels. 3)diversification of the billing system. 4)The quality of the e-book content certification.

• Journal of Distribution Science
• /
• v.12 no.6
• /
• pp.5-13
• /
• 2014

Purpose - The purposes of this editorial review are twofold: firstly, to introduce the four flagship international journals of the Korea Distribution Science Association(KODISA): the Journal of Distribution Science(JDS), the Journal of Industrial Distribution & Business(JIDB), the East Asian Journal of Business Management(EAJBM), and the Journal of Asian Finance, Economics and Business(JAFEB), and secondly, to identify the direction of the KODISA journals and the roles and responsibilities of the editors of the KODISA journals. Research design, data, and methodology - To achieve the goals, firstly, this review paper addresses the current progress of the four KODISA journals: JDS, JIDB, EAJBM, and JAFEB. Secondly, this paper defines the aims and missions of the four KODISA journals. JDS publishes the articles of examining past, current, and emerging trends and concerns in the area of distribution science and economics, logistics and SCM, transportation, distribution channel management, distribution innovation and information technology, merchandising and procurement, distribution and marketing, consumer behavior, and manufacturing, wholesaling, and retailing. JDS publishes both quantitative and qualitative research as well as scholarly commentaries, case studies, book reviews and other types of reports relating to all aspects of distribution. JIDB publishes the articles of examining past, current, and emerging trends and concerns in the areas of industry and corporate behavior, industry policy making, industrial distribution and business, e-commerce, and service industry. EAJBM publishes empirical and theoretical research papers as well as scholarly commentaries, case studies, book reviews, and other types of reports relating to all aspects of East Asian business and economy. JAFEB publishes original research analysis and inquiry into the contemporary issues of finance, economics and business management in Asia, including Central Asia, East Asia, South Asia, Southeast Asia, and Middle East. The mission of JAFEB is to bring together the latest theoretical and empirical finance, economics and business management research in Asian markets. The audiences of the KODISA journals include higher education institutions, scholars, industry researchers and practitioners, scientists, economists, and policy makers throughout the world. The main mission of the KODISA journals is to provide an intellectual platform for international scholars, promote interdisciplinary studies in social sciences and economics, and become leading journals in the social science and economics category in the world. Thirdly, this paper addresses the current status of indexing in major databases of the KODISA journals, namely: Cabell's Directories, EBSCO, SCOPUS (Elsevier), and Social Sciences Citation Index^® (SSCI, Thomson Reuters). Fourthly, this paper identifies the roles and responsibilities of the editors of the KODISA journals as the following: (1) Make sure that the journal be published in a timely manner and in international standards both in print and online versions. (2) Maintain the online homepage of the journal is always accessible to, and (3) Make sure that every article should go through a peer review process that meets international standards. Findings and conclusion - To accomplish the goals and missions of the KODISA journals, the editors of the KODISA journals must work together to publish high scholarly journals that meet international standards of journal publications.

• Journal of the Korea Convergence Society
• /
• v.12 no.10
• /
• pp.19-25
• /
• 2021

This study contains the results obtained after two and a half years of developing a knitting customization website using a knitting machine. Recently in the fashion world, various services using customization are being provided, and devices that users can design directly using knitting machines are being developed. However the existing website for knitting machine does not provide a certain usability or layout, so it is difficult for users to use open source and custom design. Therefore, this study was conducted for the purpose of developing a website that provides ease of use to users who will use the knitting customizing service using a knitting machine. As a research method, the first usability evaluation was conducted by synthesizing the studies conducted for the knit customization website development work. As a result of the study, found the problems of the initial custom screen and the initial output screen were found, and convenience, intuition, and readability were improved. Secondary usability evaluation was conducted on the modified website and it was confirmed that the problem was corrected. Through the website finally derived from this study, it is expected that the new platform in the domestic knit market will be popularized and the usability of the custom website will be improved.

• The Journal of the Acoustical Society of Korea
• /
• v.40 no.5
• /
• pp.523-529
• /
• 2021

In this paper, we designed and developed an Emotional Speech Synthesis Markup Language (SSML) processor. Multi-speaker emotional speech synthesis technology that can express multiple voice colors and emotional expressions have been developed, and we designed Emotional SSML by extending SSML for multiple voice colors and emotional expressions. The Emotional SSML processor has a graphic user interface and consists of following four components. First, a multi-speaker emotional text editor that can easily mark specific voice colors and emotions on desired positions. Second, an Emotional SSML document generator that creates an Emotional SSML document automatically from the result of the multi-speaker emotional text editor. Third, an Emotional SSML parser that parses the Emotional SSML document. Last, a sequencer to control a multi-speaker and emotional Text-to-Speech (TTS) engine based on the result of the Emotional SSML parser. Based on SSML which is a programming language and platform independent open standard, the Emotional SSML processor can easily integrate with various speech synthesis engines and facilitates the development of multi-speaker emotional text-to-speech applications.

• Journal of Intelligence and Information Systems
• /
• v.20 no.2
• /
• pp.109-122
• /
• 2014

People are nowadays creating a tremendous amount of data on Social Network Service (SNS). In particular, the incorporation of SNS into mobile devices has resulted in massive amounts of data generation, thereby greatly influencing society. This is an unmatched phenomenon in history, and now we live in the Age of Big Data. SNS Data is defined as a condition of Big Data where the amount of data (volume), data input and output speeds (velocity), and the variety of data types (variety) are satisfied. If someone intends to discover the trend of an issue in SNS Big Data, this information can be used as a new important source for the creation of new values because this information covers the whole of society. In this study, a Twitter Issue Tracking System (TITS) is designed and established to meet the needs of analyzing SNS Big Data. TITS extracts issues from Twitter texts and visualizes them on the web. The proposed system provides the following four functions: (1) Provide the topic keyword set that corresponds to daily ranking; (2) Visualize the daily time series graph of a topic for the duration of a month; (3) Provide the importance of a topic through a treemap based on the score system and frequency; (4) Visualize the daily time-series graph of keywords by searching the keyword; The present study analyzes the Big Data generated by SNS in real time. SNS Big Data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. In addition, such analysis requires the latest big data technology to process rapidly a large amount of real-time data, such as the Hadoop distributed system or NoSQL, which is an alternative to relational database. We built TITS based on Hadoop to optimize the processing of big data because Hadoop is designed to scale up from single node computing to thousands of machines. Furthermore, we use MongoDB, which is classified as a NoSQL database. In addition, MongoDB is an open source platform, document-oriented database that provides high performance, high availability, and automatic scaling. Unlike existing relational database, there are no schema or tables with MongoDB, and its most important goal is that of data accessibility and data processing performance. In the Age of Big Data, the visualization of Big Data is more attractive to the Big Data community because it helps analysts to examine such data easily and clearly. Therefore, TITS uses the d3.js library as a visualization tool. This library is designed for the purpose of creating Data Driven Documents that bind document object model (DOM) and any data; the interaction between data is easy and useful for managing real-time data stream with smooth animation. In addition, TITS uses a bootstrap made of pre-configured plug-in style sheets and JavaScript libraries to build a web system. The TITS Graphical User Interface (GUI) is designed using these libraries, and it is capable of detecting issues on Twitter in an easy and intuitive manner. The proposed work demonstrates the superiority of our issue detection techniques by matching detected issues with corresponding online news articles. The contributions of the present study are threefold. First, we suggest an alternative approach to real-time big data analysis, which has become an extremely important issue. Second, we apply a topic modeling technique that is used in various research areas, including Library and Information Science (LIS). Based on this, we can confirm the utility of storytelling and time series analysis. Third, we develop a web-based system, and make the system available for the real-time discovery of topics. The present study conducted experiments with nearly 150 million tweets in Korea during March 2013.