• Phonetics and Speech Sciences
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• v.1 no.3
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• pp.109-115
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• 2009

Many isolated word recognition systems may generate non-similar words for recognition candidates because they use only acoustic information. In this paper, we investigate several techniques which can exclude non-similar words from N-best candidate words by applying Levenstein distance measure. At first, word distance method based on phone and syllable distances are considered. These methods use just Levenstein distance on phones or double Levenstein distance algorithm on syllables of candidates. Next, word similarity approaches are presented that they use characters' position information of word candidates. Each character's position is labeled to inserted, deleted, and correct position after alignment between source and target string. The word similarities are obtained from characters' positional probabilities which mean the frequency ratio of the same characters' observations on the position. From experimental results, we can find that the proposed methods are effective for removing non-similar words without loss of system performance from the N-best recognition candidates of the systems.

• Journal of Information Technology Applications and Management
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• v.19 no.4
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• pp.97-113
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• 2012

In order to implement the real-time enterprise (RTE) and smart work effectively, many companies have introduced a mobile office. A mobile office improves employee productivity and increases ability to respond to business opportunities by helping employee manage their business anytime and anywhere. However, it also raises the user's stress level. We conducted in-depth interviews with users to assess user's perception of a mobile office according to Saaty's BOCR model. Based on the results of the interviews, we set variables affecting user's perception of the mobile office using factor analysis. This study revealed that support for real-time business, support for communication and collaboration, and information processing quality were positively related to continuous intention to use mobile office. Further study demonstrated that three variables have mediating effect between the psychological stress and continuous intention to use. This result implies that the system quality and function are the key elements of mobile office and may contribute to the continuous use.

• Management & Information Systems Review
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• v.4
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• pp.327-348
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• 2000

There are three major motives for M&A, financial synergy effect, operating & managerial synergy effect, and tax effect. The purpose of this study is to prove the operating & managerial synergy effect of M&A. To do this, we analyze the market-ripple effect of M&A, focusing on the increase in market power. Specifically we use cross-sectional data from 1985 to 1998 to show whether a market power of mergers is higher than that of a matched non-merging control group. we use time series data to show whether a market power of merger is higher than that of pre-merger. Also we use the event study using market model to show the stock price movement after mergers. The result is that although revenue increase after mergers, profit of the firms does not improve after mergers. Also there is sufficient evidence to say that there is a cumulative abnormal return for the firms after mergers.

• Journal of the Korean Data and Information Science Society
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• v.20 no.3
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• pp.593-599
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• 2009

We consider the problem of using control charts to monitor more than one parameter with emphasis on simultaneously monitoring the mean and variance. The fixed sampling interval (FSI) control charts are modified to use variable sampling interval (VSI) control charts depending on what is being observed from the data. In general, approaches of monitoring the mean and variance simultaneously is to use separate charts for each parameter and a combined chart. In this paper, we use three basic strategies which are separate Shewhart charts for each parameter, a combined Shewhart chart and a combined CUSUM chart. We showed that a combined VSI CUSUM chart is comparatively more efficient than any other chart if the shifts in both mean and variance are small.

• Journal of Information Processing Systems
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• v.8 no.4
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• pp.693-712
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• 2012

The paper presents three machine learning based keyphrase extraction methods that respectively use Decision Trees, Na$\ddot{i}$ve Bayes, and Artificial Neural Networks for keyphrase extraction. We consider keyphrases as being phrases that consist of one or more words and as representing the important concepts in a text document. The three machine learning based keyphrase extraction methods that we use for experimentation have been compared with a publicly available keyphrase extraction system called KEA. The experimental results show that the Neural Network based keyphrase extraction method outperforms two other keyphrase extraction methods that use the Decision Tree and Na$\ddot{i}$ve Bayes. The results also show that the Neural Network based method performs better than KEA.

• Annual Conference of KIPS
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• 2013.11a
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• pp.1442-1445
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• 2013

Portable devices are growth such as smart phone and smart pad and e-book market is also growing, but existing publishers have some problem of conversion paper book to e-book with technology. In this paper propose to solve this problem using HTML5 for E-book making tool. HTML5 is new version of HTML. It can be use video and audio element. Also a lot of web Browser can be use HTML5 format. If we have HTML5 compatible browser devices, we can use anywhere and anytime. We propose video book making tool using these HTML5 characteristics, it is available to support of text or images.

• Asia pacific journal of information systems
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• v.29 no.2
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• pp.248-267
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• 2019

As merging online and offline channels into one single platform, individuals could easily and frequently switch between online and offline channels. In order for understanding such unique behaviors, this study attempts to explore why and how consumers choose their channels to search and purchase a product. We have drawn on multiple theories that have been used to explain individuals' judgment and decision making (i.e., construal level theory and regula-tory focus theory) in order to develop and tested two-way ANOVA based models of how both regulatory focus (e.g., promotion vs. prevention) and product types (e.g., experience goods vs. searching goods) including the psychological distance cue separately and jointly affect individuals' channel selection behavior (e.g., intention to use single channel vs. intention to use cross-channels). Our results have indicated that consumers with promotion-focus are more likely to use a single channel in experience goods rather than in searching goods when there exists the psychological cue. Based on our findings, the implication for both research and practice are discussed.

• Journal of Korean Academy of Nursing Administration
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• v.11 no.4
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• pp.401-414
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• 2005

Purpose: This study was to evaluate the utilization of health care service and to provide supportive data for health care policy making in one urban area in Korea. Method: This study tested the significance of public health service using the database of an university hospital and public health center from Feb. 2000 to Dec. 2004. Data were analyzed by multidimensional analysis and data mining technique and produced the information on the classification of utilization characteristics by main disease and the total cost of use and disease association with the users of the public health center. Results: The Results were as follows: 1) Top 10 diseases in the area accounted for 22.4% of total frequency for the most recent 5 years in university hospital, while 59.0% in public health center. 2) There were significant correlations between university hospital and public health center user's insurance type and place of residence: It showed higher use of public health center for free service beneficiaries residing in Seoul than residents in nearby or local area. The medical insurance types for hospital users were more various than those for public health center users. 3) The use of hospital for patients of hypertension, diabetes mellitus and hyperlipidemia was tended to concentrate in mostly autumn and winter since August 2000, while the cost of using public health center for those patients has been steadily reduced since July 2000. 4) As a result of cluster analysis, there were classified into three homogeneous groups according to the total cost of using public health service, age, and the frequency of use. 5) The association analysis on patients with chronic disease in public health center produced a detailed information on accompanying diseases related to the incidence rate of disease of high frequency due to aging, information on drug abuse and immune disease. Conclusion: The health care policy for local community should be evaluated continuously. And the policy to build an integrated data warehousing by public health indicator system and to enhance the faithfulness of data is required.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.483-486
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• 2021

With the explosive increase in data, the 'big data era' has arrived, focusing on deriving new values and insights through data. With the development of data analysis technology, the importance of data analysis and utilization in the field of diagnosis and treatment as well as prevention is expanding, while the use of big data is emerging in the healthcare field. Moreover, as the three data-related laws (Personal Information Protection Act, Information and Communication Network Act, and Credit Information Act) were passed in January 2020, it became possible to use a wide range of big data through pseudonym information. However, the use of healthcare big data is still struggling due to various policies and regulations, inconsistent data quality, and the absence of specialized personnel. Therefore, in this study, examines the current state of use of big data in the healthcare field, and analyzes the challenges, overseas cases, plans, and expected effects for activation of healthcare big data.

• Journal of Information Technology Services
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• v.12 no.4
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• pp.1-23
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• 2013

This study examines whether key characteristics of cloud computing services would affect the intention of use for personalized cloud computing services. The research model was generated based on Technology Acceptance Model (TAM) with resistance variable, and verified statistically by undertaking a survey about the perception of personal users. As the results of this analysis, we could find the structural relationship among the factors affecting adoption of the cloud computing service. We found that the expectation of ubiquity as a representative function of the cloud computing service meaningfully affected the perceived ease of use and resistance, and that the relativeness with existing services also meaningfully affected the perceived ease of use, but not the resistance. In addition, the moderating effects of use experience in the path leading from the perceived ease of use and resistance to the intention of use were identified. This study will provide diverse implications for the companies providing personalized cloud computing services.