• Journal of Korea Multimedia Society
• /
• v.19 no.5
• /
• pp.918-923
• /
• 2016

IoT should be considered security risk environments such as various platforms and services including smart devices that can be mounted on household electric appliances, healthcare, car, and heterogeneous networks that are connected to the Internet, cloud services and mobile Apps.. In this paper, we provide analysis of new security threats, caused by open-platform of IoT and sensors via the Internet. Also, we present the key recovery mechanism that is applied to IoT. It results to have compatibility with given research, reduces network overhead, and performs key recovery without depending on key escrow agencies or authorized party.

• Communications for Statistical Applications and Methods
• /
• v.11 no.1
• /
• pp.93-106
• /
• 2004

Recently, many data of various types is gained with development of computer in many fields. Especially, web log data generating in web site furnish beneficial information on an organization. The enterprise's destiny is swayed by according as how these information gaining from the web site utilize. In this paper, for the purpose of obtaining useful information, we present a tool is called WebBizi for web log analysis. This will be helpful to enterprise working the web site.

• Communications for Statistical Applications and Methods
• /
• v.16 no.2
• /
• pp.373-381
• /
• 2009

Evidence of linkage is expressed as a decreasing trend of the squared trait difference of two siblings with increasing identical by descent scores. In contrast to successes in the application of a parametric approach of Haseman-Elston regression, notably low powers are demonstrated in the nonparametric linkage analysis methods for complex traits and diseases with sib-pairs data. We report that the Genehunter nonparametric linkage statistic is biased and furthermore the variance formula that they used is an inflated one, and this is one reason for a low performance. Thus, we propose bias-corrected nonparametric linkage statistics. Simulation studies comparing our proposed nonparametric test statistics versus the existing test statistics suggest that the bias-corrected new nonparametric test statistics are more powerful and attains efficiencies close to that of Haseman-Elston regression.

• Journal of Korean Society for Quality Management
• /
• v.38 no.3
• /
• pp.294-312
• /
• 2010

Data Technology (DT) is a new technology which deals with data collection, data analysis, information generation from data, knowledge generation from modelling and future prediction. DT is a newly emerged interdisciplinary science & technology in this 21st century knowledge society. Even though the main body of DT is applied statistics, it also contains management information system (MIS), quality management, process system analysis and so on. Therefore, it is an interdisciplinary science and technology of statistics, management science, industrial engineering, computer science and social science. In this paper, first of all, the definition of DT is given, and then the effects and the basic properties of DT, the differences between IT and DT, the 6 step process for DT application, and a DT example are provided. Finally, the relationship among DT, e-Statistics and Data Mining is explained, and the direction of DT development is proposed.

• Communications for Statistical Applications and Methods
• /
• v.19 no.6
• /
• pp.771-780
• /
• 2012

In the current analysis, we examine news coverage data widely used in media studies. News coverage data is usually time series data to capture the volume or the tone of the news media's coverage of a topic. We first describe the distributional properties of autoregressive conditionally heteroscadestic(ARCH) effects and compare two major American newspaper's coverage of U.S.-North Korea relations. Subsequently, we propose a change point detection model and apply it to the detection of major change points in the tone of American newspaper coverage of U.S.-North Korea relations.

• Proceedings of the Korean Society for Quality Management Conference
• /
• 2006.04a
• /
• pp.319-324
• /
• 2006

In this paper, we propose Bayesian procedure for the multiple change points analysis in a sequence of fractions nonconforming. We first compute the Bayes factor for detecting the existence of no change, a single change or multiple changes. The Gibbs sampler with the Metropolis-Hastings subchain is run to estimate parameters of the change point model, once the number of change points is identified. Finally, we apply the results developed in this paper to both a real and simulated data.

• Communications for Statistical Applications and Methods
• /
• v.28 no.6
• /
• pp.583-594
• /
• 2021

In this paper, we propose wavelet-based procedures to identify the difference between images, including portraits and handwriting. The proposed methods are based on a novel combination of multiscale methods with a regularization technique. The multiscale method extracts the local characteristics of an image, and the distinct features are obtained through the regularized regression of the local characteristics. The regularized regression approach copes with the high-dimensional problem to build the relation between the local characteristics. Lytle and Yang (2006) introduced the detection method of forged handwriting via wavelets and summary statistics. We expand the scope of their method to the general image and significantly improve the results. We demonstrate the promising empirical evidence of the proposed method through various experiments.

• Communications for Statistical Applications and Methods
• /
• v.25 no.6
• /
• pp.605-618
• /
• 2018

Risk management has been a crucial part of the daily operations of the financial industry over the past two decades. Value at Risk (VaR), a quantitative measure introduced by JP Morgan in 1995, is the most popular and simplest quantitative measure of risk. VaR has been widely applied to the risk evaluation over all types of financial activities, including portfolio management and asset allocation. This paper uses the implementations of multivariate GARCH models and copula methods to illustrate the performance of a one-day-ahead VaR prediction modeling process for high-dimensional portfolios. Many factors, such as the interaction among included assets, are included in the modeling process. Additionally, empirical data analyses and backtesting results are demonstrated through a rolling analysis, which help capture the instability of parameter estimates. We find that our way of modeling is relatively robust and flexible.

• Korean Journal of Oriental Medicine
• /
• v.13 no.1 s.19
• /
• pp.125-128
• /
• 2007

Objective : This study aims to review the current status and problems of Korean Medicine and attempts to come up with the means to present a comprehensive and effective set of statistical data. Methods : We have analyzed the current statistics and tried to show how to establish an effective system to gather and organize statistics related to Korean Medicine, including national surveys by the Ministry of Health and Welfare or other relevant insititutions. Results : The existing statistics in Korean Medicine were established not as a result of national demand based on comprehensive analysis but due to the demand of the government ministries such as the Ministry of Health and Welfare or other relevant institutions. Thus, the statistics have been revealed to possess limitations such as a lack of systemization and consistency. In addition, the statistics analyze only the current industrial status of Korean Medicine, and as a result the information in unable to show systematic data for innovation, which is indispensable for the advancement and development of the Korean Medicine industry. Conclusion : To improve the statistical data in Korean Medicine, the statistics need to get over not only the level of management or regulation in Korean Medicine, but also the production of fragmentary statistics. It has to ultimately reflect the innovative activities in Korean Medicine nationally, and show what we need to advance and develop the industry.

• Journal of the Korean Data and Information Science Society
• /
• v.26 no.3
• /
• pp.661-668
• /
• 2015

Them traffic accidents have been increased every year due to increasing of vehicles numbers as well as the gravitation of the population. The carelessness of drivers, many road weather factors have a great influence on the traffic accidents. Especially, the number of traffic accident is governed by precipitation, visibility, humidity, cloud amounts and temperature. The purpose of this paper is to analyse the effect of road weather factors on traffic accident. We use the data of traffic accident, AWS weather factors (precipitation, existence of rainfall, temperature, wind speed), time zone and day of the week in 2013. We did statistical analysis using logistic regression analysis and decision tree analysis. These prediction models may be used to predict the traffic accident according to the weather condition.