• International Journal of Reliability and Applications
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• v.17 no.2
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• pp.149-158
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• 2016

We are enjoying a very comfortable life thanks to modern civilization, however, comfort is not guaranteed to us. Development of software system is a difficult and complex process. Therefore, the main focus of software development is on improving the reliability and stability of a software system. We have become aware of the importance of developing software reliability models and have begun to develop software reliability models. NHPP software reliability models have been developed through the fault intensity rate function and the mean value functions within a controlled testing environment to estimate reliability metrics such as the number of residual faults, failure rate, and reliability of the software. In this paper, we present a new NHPP software reliability model with Burr Type III fault detection rate, and present the goodness-of-fit of the fault detection rate software reliability model and other NHPP models based on two datasets of software testing data. The results show that the proposed model fits significantly better than other NHPP software reliability models.

• Communications for Statistical Applications and Methods
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• v.29 no.2
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• pp.177-191
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• 2022

This paper addresses the use of machine learning methods for causal estimation of treatment effects from observational data. Even though conducting randomized experimental trials is a gold standard to reveal potential causal relationships, observational study is another rich source for investigation of exposure effects, for example, in the research of comparative effectiveness and safety of treatments, where the causal effect can be identified if covariates contain all confounding variables. In this context, statistical regression models for the expected outcome and the probability of treatment are often imposed, which can be combined in a clever way to yield more efficient and robust causal estimators. Recently, targeted maximum likelihood estimation and causal random forest is proposed and extensively studied for the use of data-adaptive regression in estimation of causal inference parameters. Machine learning methods are a natural choice in these settings to improve the quality of the final estimate of the treatment effect. We explore how we can adapt the design and training of several machine learning algorithms for causal inference and study their finite-sample performance through simulation experiments under various scenarios. Application to the percutaneous coronary intervention (PCI) data shows that these adaptations can improve simple linear regression-based methods.

• The Korean Journal of Applied Statistics
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• v.31 no.4
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• pp.529-538
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• 2018

Tuberculosis causes high morbidity and mortality. However, Korea still has the highest tuberculosis (TB) incidence and mortality among OECD countries despite decreasing incidence and mortality due to the development of modern medicine. Korea has now implemented various policy projects to prevent and control tuberculosis. This study analyzes the effects of public-private mix (PPM) tuberculosis control program on treatment outcomes and identifies the factors that affecting the success of TB treatment. We analyzed 130,000 new tuberculosis patient cohort from 2012 to 2015 using data of tuberculosis patient reports managed by the Disease Control Headquarters. A cumulative incidence function (CIF) compared the cumulative treatment success rates for each factor. We compared the results of the analysis using two popular types of competition risk models (cause-specific Cox's proportional hazards model and subdistribution hazard model) that account for the main event of interest (treatment success) and competing events (death).

• Journal of the Korea Fashion and Costume Design Association
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• v.14 no.3
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• pp.93-109
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• 2012

The purpose of this study is to examine the modern men's fashion coordination to see the image in the center of TV dramas in terms of Habitu that is formed within hierarchy and class. The subjects range is included fashion style, color, accessories, hairstyle and appearance. 950 pictures used in the analysis sheet. In research methods, content analysis and basic statistics were used. The results of this study were as follows. First, the hierarchy image formed by Habitus is significant difference. The upper layer is coordinating elite luxurious and prestigious image of the fashion styles. The middle layer is coordinating neat and capable image. The lower layer does not care about the appearance and image appearing weary life is coordinating. Second, the class image formed by Habitus, CEO often interests in fashion image coordination. Senior executive is represented clean and luxurious image. General white color dresses in a suite such as office look. Blue color does not care about the fashion coordination and is expressed an easy dress for labor. Architects of the unstructured free-spirited image is represented. Physician and resident physician dress in shirts, no pattern tie, pants, robe. And they is coordinating neat and tidy attire to represent professional and reliable image.

• Journal of Fashion Business
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• v.17 no.4
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• pp.164-176
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• 2013

The study aims to find differences in clothing image preferences according to gender-roleidentity. The questionnaire developed by the researchers was distributed to 533 men and women who aged between 20 and 59. Fourhundred eight questionnaires were used for the final analysis. The data were analyzed by ANOVA, and Tukey's test using SPSS 18.0/Windows. As results, both male and female participant groups of the study were classified into 4 groups according to their gender-role identity: masculinity, femininity, androgyny, and the undifferentiated. For men, the masculinity group showed a higher preference for flamboyant, sexy, expressive, cold, mature, hard, strong, weighty, heavy, sharp images, while the femininity group showed a stronger preference for flamboyant, bold, luxurious clothing images. The male androgyny group preferred masculine, sexy, cold, mature, hard, strong, weighty, luxurious, heavy, artificial images, whereas the undifferentiated group preferred flamboyant, sexy and mature images. On the other hand, for women, the masculinity group showed a higher preference for luxurious image, while the femininity group showed a stronger preference for sexy, urban, decorative, modern, complicated, luxurious images. The female androgyny group preferred expressive, modern, mature, complicated, and luxurious images, whereas the undifferentiated group preferred bold, decorative, rational, and complicated clothing images.

• Journal of Ocean Engineering and Technology
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• v.18 no.4 s.59
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• pp.71-76
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• 2004

A Study of the traditional Korean fishing boat is based on a report on an investigation of the Korean fishing boats, conducted in 1921. The report was completed in 1927 with the conclusion of the Southern Sea region and West Sea region studies, which included the investigation oj the entire region. It was a very thorough and scientific investigation of Korean fishing boats, which has been published in three volumes. Based on this report, this paper surveys the characteristics and the hull form of the traditional Korean fishing boats. As a result, we find ${\cdot}out$ that the hull form of the traditional Korean fishing boat is very similar to that of modern sailing boat. Thus, it is a good candidate for the development of the modern sailing boats for the Korean Sea.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.4
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• pp.304-310
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• 2023

With the development of information and communication technology, modern people are receiving various benefits, and knowledge and use of information and communication technology are becoming essential qualities in modern people's lives. There are people who do not enjoy the rich benefits of this information and communication society, and the so-called 'digital divide' acts as an obstacle that prevents the information and communication from enjoying a rich life. Currently, there are four major information underprivileged classes in Korea, the disabled, the elderly, low-income class and farmers and fishermen, respectively. The purpose of this study is to identify the current status of the digital divide for the low-income class and to analyze the causes of the digital divide. To this end, in this study, we analyze statistics on digital divide at the national level and analyzed the digital divide of low-income class from three perspectives: information access, information capability, and information use. As a result of the analysis, it was found that the lack of information capability was the biggest cause of the digital divide, and in particular, information management ability was the most insufficient among information capabilities.

• International Journal of Computer Science & Network Security
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• v.21 no.5
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• pp.151-159
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• 2021

This article addresses the issue of finding optimal solutions using the information technologies of accounting and analysis in modern companies. The aim of the study is to reveal available information technologies for the needs of small, medium and large businesses operating in modern conditions. This goal is achieved by using systematization, comparison, and analysis of information, obtained under the survey and open management statistics. For the first time, the paper systematizes up-to-date information of 2021 about the most popular programs, online services, platforms and cloud services that are used to improve accounting and analytical processes in enterprises of various sizes. The main global trends in software development in terms of COVID-19 pandemic have been identified. In particular, the study defines the countries that occupy the leading positions in the informatization of business processes. An attempt was made to classify information technologies by their use by various volume of businesses. The analysis of research results of the Internet search query frequency regarding the use of information technologies enabled to determine the most popular software products worldwide. The peculiarities of information technologies, their advantages and disadvantages were examined and the common and distinctive features were compared. It was determined that for the new enterprises to implement information technologies, it is necessary to conduct a step-by-step study of all available software products. The software evaluation algorithm was described to help select the optimal software for the specific business processes. The paper also describes the way to solve the problem of using accounting and analysis software for the businesses of a specific kind of activity.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.8
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• pp.727-732
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• 2008

In this paper, the state-space representation of generalized complimentary filter is proposed. Complementary filter has the suitable structure to merge information from sensors whose frequency regions are complementary. First, the basic concept and structure of complementary filter is introduced. And then the structure of the generalized filter and its state-space representation are proposed. The state-space representation of complementary filter is able to design the complementary filter by applying modern filtering techniques like Kalman filter and $H_{\infty}$ filter. To show the usability of the proposed state-space representation, the design of Inertial Navigation System(INS) vertical channel damping loop using Global Positioning System(GPS) is described. The proposed GPS/INS damping loop lends the structure of Baro/INS(Barometer/INS) vertical channel damping loop that is an application of complementary filter. GPS altitude error has the non-stationary statistics although GPS offers navigation information which is insensitive to time and place. Therefore, $H_{\infty}$ filtering technique is selected for adding robustness to the loop. First, the state-space representation of GPS/INS damping loop is acquired. And next the weighted $H_{\infty}$ norm proposed in order to suitably consider characteristics of sensor errors is used for getting filter gains. Simulation results show that the proposed filter provides better performance than the conventional vertical channel loop design schemes even when error statistics are unknown.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.7
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• pp.241-249
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• 2020

The role of money in the modern economy highly determines the intensity and the development of the macroeconomy. The money supply is assumed to be as much as money demand, which reflects the economic character of a country and indicates the growth and development of macroeconomy. In Indonesia, the money supply (M1) is related to the economic dynamics in either the monetary market or the goods market. This research aims at analyzing factors that influence the money supply and to what extent the economic factors affect the money supply in Indonesia. The analysis method used in this research was Vector Autoregressive (VAR) with some variables, such as money supply (M1), interest rate, and Gross Domestic Product (GDP) from the 1st quarter of 2001 until the 1st quarter of 2013. The data collection method was in the form of data compilation from credible sources, such as Bank of Indonesia (BI), Central Bureau of Statistics (CBS), and International Financial Statistics (IFS). To obtain adequate analysis results, several tests were taken, such as unit-root test, Granger causality test, and optimal lag. VAR analysis formulates the correlation among independent variables, so it also sees the study of impulse response and matrix decomposition.