• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.3
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• pp.157-163
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• 2013

Data mining is a useful technology that can support new discoveries based on the pattern analysis and a variety of linkages between data, and currently is utilized in various fields such as finance, marketing, medical. In this paper, we propose an effective utilization method of data based on analysis of spatial data mining. We make use of basic data of foreigners living in Seoul. However, the data has some features distinguished from other areas of data, classification as sensitive information and legal problem such as personal information protection. So, we use the basic statistical data that does not contain personal information. The main features and contributions of the proposed method are as follows. First, we can use Big Data as information through a variety of ways and can classify and cluster Big Data through refinement. Second. we can use these kinds of information for decision-making of future and new patterns. In the performance evaluation, we will use visual approach through graph of themes. The results of performance evaluation show that the analysis using data mining technology can support new discoveries of patterns and results.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.4
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• pp.74-84
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• 2016

Open Source Software (OSS) is a new paradigm for software development. The system is based on the notion of giving software (including sources) away for free, and making money on services, customizing and maintenance. For these reasons, many software companies have considered adopting and using OSS in Software R&D. A variety of factors may influence the use of decision making of OSS. The objective of this study was to explore the significant factors affecting the use decision of OSS and the job performance of OSS usage in software R&D. A research model was suggested based on the TOE Framework and Information Systems Success Model. These findings show that technical benefits of OSS have significant effects on OSS use. The technical benefits of OSS, and organization context, in turn, have significant effects on the use of OSS. On the other hand, the technical risks of OSS and the environment context have no effects on OSS use. In addition, OSS use and user satisfaction have significant effects on the individual job performance. This research contributes towards advancing the theoretical understanding of the OSS Benefits and Performance in Software Development.

• Journal of the Korean Data and Information Science Society
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• v.20 no.2
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• pp.329-338
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• 2009

The importance performance analysis is a simple and condensed analytic method for decision making based on the level of performance or satisfaction. Many researches already have witnessed usefulness of the importance performance analysis, but it also has some drawbacks from the statistical points of view. In this article, some additional techniques dealing the importance performance analysis are introduced and it is shown that these techniques would turn out to be very informative. The importance performance analysis uses the arithmetic average as the main statistic, but by the use of the median, the frequency and the cluster analysis it is shown that the importance performance analysis can be carried out with more crucial information. In addtion to that, it is demonstrated that the combination of the analytic hierarchy process and importance performance analysis could enable more reliable decision making.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.8
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• pp.3873-3887
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• 2018

In this paper, we propose a novel method to recover images corrupted by impulse noise. The proposed method uses two stages: noise detection and filtering. In the first stage, we use pixel values, rank-ordered logarithmic difference values, and median values to train a neural-network-based impulse noise detector. After training, we apply the network to detect noisy pixels in images. In the next stage, we use group-based weighted couple sparse representation to filter the noisy pixels. During this second stage, conventional methods generally use only clean pixels to recover corrupted pixels, which can yield unsuccessful dictionary learning if the noise density is high and the number of useful clean pixels is inadequate. Therefore, we use reconstructed pixels to balance the deficiency. Experimental results show that the proposed noise detector has better performance than the conventional noise detectors. Also, with the information of noisy pixel location, the proposed impulse-noise removal method performs better than the conventional methods, through the recovered images resulting in better quality.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.1
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• pp.97-112
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• 2023

The purpose of this study is to design and test a new way of public transportation route guidance system for persons with disabilities, including wheelchair users. The guidance system is smartphone app-based, using, routes that involve disabled-friendly facilities in the vicinity can be searched. A database that contains publicly available data on low-floor bus services, location and extent of disabled-friendly facilities, and suitable subways and stations, was developed for this purpose. The app uses the database to access and query the required information. A pilot study was conducted to test the effectiveness of the guidance system. It was found that the system was able to convey information about the disabled-friendly routes and related guidance information even inside subway stations, effectively. The performance of the system was compared with route guidance services that do not explicitly use data on disabled-friendly services. A notable difference was observed in the travel time estimated by this program and other guidance services. The difference was around 4 to 15 minutes. This is significant savings for persons with disabilities if they use the app and service. The study thus shows that exclusive use of disabled-friendly data in route guidance will bring more benefits for persons with disabilities.

• Journal of Digital Contents Society
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• v.18 no.8
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• pp.1543-1550
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• 2017

Previous research on smartphone has been focused on personal performance, accessibility, and information gaps in information system quality. In order to analyze the relationship between the use of smartphone information and personal characteristics, this study conducted a survey of 300 tourists at Jeju Airport, by using three variables of self-efficacy, 'impulsiveness and demographic variables (age, sex, education level, etc.) of smartphone use with personal characteristics. In conclusion, self-efficacy and impulsiveness seem to be positively related to the use of smartphone because it seems to be a living environment in which the desired information can be acquired within a desired time. In addition, there seems to be a difference between a mobile native environment in which online and offline boundaries are always connected and an environment in which 40 to 50 digital literacies are connected. This can be interpreted as a result of additional analysis.

• ETRI Journal
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• v.22 no.4
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• pp.1-12
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• 2000

Designing a reliable multicast-based network that scales to the size of a multicast group member is difficult because of the diversity of user demands. The loss inferences of internal nodes by end-to-end measurements do not require the use of complete statistics because of the use of maximum likelihood estimation. These schemes are very efficient and the inferred value converges fast to its true value. In the theoretical analysis, internal delay estimation is possible but the analysis is very complex due to the continuity property of the delay. In this paper, we propose the use of a bottleneck location estimator. This can overcome the analytical difficulty of the delay estimation using the power spectrum of the packet interarrival time as the performance metric. Both theoretical analysis and simulation results show that the proposed scheme can be used for bottleneck location inference of internal links in scalable multicasting.

• 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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.4C
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• pp.326-332
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• 2002

To transfer the large size of data more quickly among cluster nodes, the lightweight messaging scheme has been developed. VIA(Virtual Interface Architecture) allows that user can directly communicate with network devices without any interference of kernel and has become a communication protocol for clusters. But one must spend a lot of time to be skillful with it because of difficulties of programming. Therefore, we propose an easier library called EVIL(Easy-to-use Virtual Interface Library) that developers can easily deal with. We evaluated the performance of EVIL, Native VIA, TCP/IP respectively.

• Journal of the Korean Data and Information Science Society
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• v.28 no.4
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• pp.937-945
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• 2017

The purpose of using a control chart is to detect any change that occurs in the process. When control charts are used to monitor processes, we want to identify this changes as quickly as possible. Many problems in quality control involve a vector of observations of several characteristics rather than a single characteristic. Multivariate CUSUM or EWMA charts have been developed to address the problem of monitoring covariance matrix or the joint monitoring of mean vector and covariance matrix. However, control charts tend to work poorly when we use the highly correlatted variables. In order to overcome it, Hawkins (1991) proposed the use of regression adjustment variables. In this paper, to monitor covariance matrix, we investigate the performance of MEWMA-type control charts with and without the use of regression adjusted variables.