• Communications for Statistical Applications and Methods
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• v.18 no.4
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• pp.445-455
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• 2011

Although misclassified binary data occur frequently in practice, the statistical methodology available for the data is rather limited. In particular, the interval estimation of population proportion has relied on the classical Wald method. Recently, Lee and Choi (2009) developed a new confidence interval by applying the Agresti-Coull's approach and showed the efficiency of their proposed confidence interval numerically, but a theoretical justification has not been explored yet. Therefore, a Bayesian model for the misclassified binary data is developed to consider the Agresti-Coull confidence interval from a theoretical point of view. It is shown that the Agresti-Coull confidence interval is essentially a Bayesian confidence interval.

• Smart Structures and Systems
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• v.14 no.3
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• pp.377-395
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• 2014

Vibration-based fault detection and condition monitoring of rotating machinery, using statistical process control (SPC) combined with statistical pattern recognition methodology, has been widely investigated by many researchers. In particular, the discrete wavelet transform (DWT) is considered as a powerful tool for feature extraction in detecting fault on rotating machinery. Although DWT significantly reduces the dimensionality of the data, the number of retained wavelet features can still be significantly large. Then, the use of standard multivariate SPC techniques is not advised, because the sample covariance matrix is likely to be singular, so that the common multivariate statistics cannot be calculated. Even though many feature-based SPC methods have been introduced to tackle this deficiency, most methods require a parametric distributional assumption that restricts their feasibility to specific problems of process control, and thus limit their application. This study proposes a nonparametric multivariate control chart method, based on multiscale wavelet scalogram (MWS) features, that overcomes the limitation posed by the parametric assumption in existing SPC methods. The presented approach takes advantage of multi-resolution analysis using DWT, and obtains MWS features with significantly low dimensionality. We calculate Hotelling's $T^2$-type monitoring statistic using MWS, which has enough damage-discrimination ability. A bootstrap approach is used to determine the upper control limit of the monitoring statistic, without any distributional assumption. Numerical simulations demonstrate the performance of the proposed control charting method, under various damage-level scenarios for a bearing system.

• Journal of Korean Society for Atmospheric Environment
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• v.22 no.4
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• pp.421-430
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• 2006

This paper explores a new methodology of socio-statistical survey to classify environmental perception characteristics and to quantify atmospheric environmental sensitivity of neighboring people around a large industrial complex. In order to compensate intrinsic inclination against environmental problems, Atmospheric Environmental Sensitivity Index (AESI) is proposed as the weighted-summation of four representative questions asking the current status of the local air quality, which are chosen by the factor analysis of questionnaire. Atmospheric environmental perception is tried to be classified into interest/indifference characteristics and rational/emotional perception on environmental issues, positive/negative opinion on the solution of environmental problems. According to the chi-square cross-correlation and two-way layout analyses, it was clearly shown that environmental perception is categorized into two major groups, i.e., the positive-rational group having lower AESI and the negative-emotional group having higher AESI which means more seriously senses the status of local air quality.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.46 no.5
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• pp.321-327
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• 2020

Objectives: This study is aimed to evaluate and compare the effect of moist heat fomentation therapy with ultrasound therapy in patients with the masticatory myalgia. Materials and Methods: The study was conducted on 42 patients with masticatory myalgia, dividing them into two groups; Group A (21 patients), received moist heat therapy and Group B (21 patients), received ultrasound therapy for seven effective days. Prior and after the treatment the numeric rating scale (NRS) and the electromyography (EMG) scores were recorded and compared. The observations were analyzed clinically and statistical support was taken to assess the NRS and EMG data. Results: Irrespective of the groups, patients testified a significant reduction in pain after the treatment. From the EMG readings; even though the standard deviation for each group was varied considerably, EMG recorded an improved muscle activity. Statistical analysis was used to assess and identify the best treatment methodology between the two modalities. Conclusion: From the statistical analysis, it is concluded that, though both the therapies had significantly reduced the symptomatic response, it is moist heat fomentation that improved muscle activity both statistically and clinically in comparison to ultrasound.

• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.823-826
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• 2008

Statistical methods were used in the analysis of data, which are the SNR and SDNR in describing the various natures, and the methodology relating the results with the operation was developed. Multiple regression analysis based on the results of statistics of data were SNR = 0.0219 + 0.000044BOD lording - 0.00600C/N ratio and SDNR = 0.0226 + 0.000044BOD lording - 0.00602C/N ratio. It were concluded that the variability of the process performance should be reflected to the operation condition procedure through the analysis based on the statistics methods.

• Communications for Statistical Applications and Methods
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• v.28 no.5
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• pp.425-445
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• 2021

A generalization of the log-logistic (LL) distribution called exponentiated log-logistic (ELL) distribution on lines of exponentiated Weibull distribution is considered. In this paper, based on progressive type-II censored samples, we have derived the maximum likelihood estimators and Bayes estimators for three parameters, the survival function and hazard function of the ELL distribution. Then, under the balanced squared error loss (BSEL) and the balanced linex loss (BLEL) functions, their corresponding Bayes estimators are obtained using Lindley's approximation (see Jung and Chung, 2018; Lindley, 1980), Tierney-Kadane approximation (see Tierney and Kadane, 1986) and Markov Chain Monte Carlo methods (see Hastings, 1970; Gelfand and Smith, 1990). Here, to check the convergence of MCMC chains, the Gelman and Rubin diagnostic (see Gelman and Rubin, 1992; Brooks and Gelman, 1997) was used. On the basis of their risks, the performances of their Bayes estimators are compared with maximum likelihood estimators in the simulation studies. In this paper, research supports the conclusion that ELL distribution is an efficient distribution to modeling data in the analysis of survival data. On top of that, Bayes estimators under various loss functions are useful for many estimation problems.

• The Journal of Economics, Marketing and Management
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• v.8 no.4
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• pp.37-45
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• 2020

Purpose: This study aims to clarify the concept of entrepreneurial leadership by reviewing the relevant existing studies, and to examine changes in entrepreneurial leadership research through review and statistical analysis on the articles published in Korean and international journals. Research Design, Data, and Methodology: Among the papers published between 2010 and 2020, 8 Korean studies and 42 international studies (UK and US) that clearly identify entrepreneurial leadership as research topic were analyzed. Results: Examinations on the yearly trends, keywords, and research methods reveal that research on entrepreneurial leadership is increasing recently with the emphasis on the statistical analysis. Keyword analysis shows high frequency of team and innovation for domestic research, while overseas research focuses on entrepreneurship, leadership, and gender associated keywords. Conclusions: This study has confirmed that overseas studies employ various methodologies, focusing on statistical analysis and that the effect of entrepreneurial leadership are in progress. For domestic cases, studies on entrepreneurial leadership are limited in number. Research topics and methods are areas that need further improvements. Research on entrepreneurial leadership has recently begun, requiring diversity in the subjects and methods for future development

• The Journal of Industrial Distribution & Business
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• v.13 no.6
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• pp.9-18
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• 2022

Purpose: The government around the world is still highlighting the effect of the new variant of Covid-19. The government continues to make efforts to restore the economy through several programs, one of them is National Economic Recovery. This program is expected to increase public and investor confidence in handling Covid-19. This study aims to capture public sentiment on the economic growth rate in Indonesia, especially during the third wave of the omicron variant of the covid-19 virus, that is at the time in the fourth quarter of 2021. Research design, data, and methodology: The approach used in this research is to collect crowdsourcing data from twitter, in the range of 1st to 10th October 2021. The analysis is done by building model using Deep Learning Neural Network method. Results: The result of the sentiment analysis is that most of the tweets have a neutral sentiment on the Economic Growth discussion. Several central figures who discussed were Minister of Coordinating for the Economy of Indonesia, Minister of State-Owned Enterprises. Conclusions: Data from social media can be used by the government to capture public responses, especially public sentiment regarding economic growth. This can be used by policy makers, for example entrepreneurs to anticipate economic movements under certain conditions.

• The Journal of Industrial Distribution & Business
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• v.13 no.7
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• pp.17-25
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• 2022

Purpose: Environmental contamination has lately been seen as a consequence of the rise in environmental challenges brought on by rapid industrial expansion. At this point, the current research asks an important question about what the factors are to motivate employees' green performance, increasing corporate sustainability. Research design, data and methodology:The current author selected total 19 items to obtain real data and achieve the purpose of this research. For measuring of the causality between the worker's innovative capability and green performance, the current author used the multiple regression statistical tool using U.S. 215 responses in four industry. Results: The statistical finding definitely indicated that there exists the causal linkage between two key factors (Innovation capability and green performance) as well as the strong direction between two constructs. As a result, the current author could accept all hypotheses, checking no existing the multicollinearity of the present constructs with 'TOL' and 'VIF' values. Conclusions: The present research concluded that literature and business management scholars and practitioners will benefit from this study's statistical results. Furthermore, rewarding staff creativity, encouraging quick answers to market movements, and incorporating technology into everyday operations are all ways that companies may cultivate an environmental stewardship culture.

• East Asian Journal of Business Economics (EAJBE)
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• v.11 no.2
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• pp.91-108
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• 2023

Purpose - This research paper empirically analyzes the effect of changes in the employment environment due to the 4th industrial revolution on the turnover intention of cosmetic employers and employees and seeks the necessary measures for job instability in the industrial field. Research design, data, and methodology - A self-report questionnaire was conducted on 513 cosmetic implementers. Statistical processing of the data collected by the data analysis method was analyzed using the Statistical Package for Social Science (SPSS) WIN23.0 statistical package program through data coding and data organizing process. Results - Changes in the employment environment were found to have a significant effect on the effect of job instability (t=13.218, p<0.05). As for the effect of organizational commitment on turnover intention, the higher the organizational commitment, which is a parameter, has a negative (-) effect on turnover intention, a dependent variable (p<0.05). Conclusions - Our results are based on an analysis that allows cosmetic employers and workers to explore ways to address job insecurity. Based on the analysis results, it will help the growth of the cosmetics industry by providing basic data for the identity of the cosmetics industry and the development of the cosmetics service organization.