• Proceedings of the Korea Inteligent Information System Society Conference
• /
• 2003.05a
• /
• pp.338-346
• /
• 2003

Information Technology (IT) and the internet have been major drivers the changes in all aspects of the business processes and activities. They have brought major changes to the financial statements audit environment as well, which in turn has required modifications in audit procedures. There exist, however, certain difficulties with current audit procedures especially for the assessment of the level of control risk. This assessment is primarily based on the auditors' professional judgment and experiences, not based on the objective hies or criteria. To overcome these difficulties, this paper proposes a prototype decision support model named CRAS-CBR using case based reasoning (CBR) to support auditors in making their professional judgment on the assessment of the level of control risk of the general accounting system in the manufacturing industry. To validate the performance, we compare our proposed model with benchmark performances in terms of classification accuracy for the level of control risk. Our experimental results showed CRAS-CBR outperforms a statistical model (MDA) and staff auditor performance in average hit ratio.

• Safety and Health at Work
• /
• v.9 no.1
• /
• pp.30-41
• /
• 2018

Background: The purpose of the work is to develop a system that allows processing of information for analysis and industrial risk management, to monitor the level of industrial safety and to perform necessary measures aimed at the prevention of accidents, casualties, and development of professional diseases for effective management of industrial safety at hazardous industrial sites. Methods: Risk assessment of accidents and incidents is based on expert evaluations. Based on the lists of criteria parameters and their possible values, provided by the experts, a unified information and analytical database is compiled, which is included in the final interrogation questionnaires. Risk assessment of industrial injuries and occupational diseases is based on statistical methods. Results: The result of the research is the creation of Guidelines for risk management on hazardous industrial sites of the Republic of Kazakhstan. The Guidelines determine the directions and methods of complex assessment of the state of industrial safety and labor protection and they could be applied as methodological basis at the development of preventive measures for emergencies, casualties, and incidents at hazardous industrial sites. Conclusion: Implementation of the information-analytical system of risk level assessment allows to analyze the state of risk of a possible accident at industrial sites, make valid management decisions aimed at the prevention of emergencies, and monitor the effectiveness of accident prevention measures.

• PNF and Movement
• /
• v.16 no.3
• /
• pp.495-503
• /
• 2018

Purpose: This study analyzes the predictive power of upper extremity activity and the activities of daily living in patients with stroke using an easy-to-use evaluation tool. Methods: The Fugl-Meyer assessment (FMA) of the upper extremity and action research arm test (ARAT) are performed, and the Korean modified Barthel index (K-MBI) is measured. The predictive power of the upper extremity activity level and the daily activity level are analyzed using regression analysis. The statistical significance level is 0.05. Results: The coefficient of determination, R2, for predicting the ARAT using FMA was high at 0.88, but the regression equation for predicting the K-MBI using the FMA and ARAT did not show a statistically significant difference. Conclusion: The assessment of the upper extremity should be performed at the activity level, as well as the impairment level. The assessment for predicting the activities of daily living should be carried out for each level of the international classification of functioning (ICF), disability, and health, which can be linked to daily life, in addition to the assessment of the upper arm. Future research should conduct more diverse analyses using the ICF assessment tools at various levels.

• Earthquakes and Structures
• /
• v.23 no.4
• /
• pp.385-401
• /
• 2022

Uncertainty quantification is the most important challenge in seismic fragility assessment of structures. The precision increment of the quantification method leads to reliable results but at the same time increases the computational costs and the latter will be so undesirable in cases such as reliability-based design optimization which includes numerous probabilistic seismic analyses. Accordingly, the authors' effort has been put on the development and validation of an approach that has reduced computational cost in seismic fragility assessment. In this regard, it is necessary to apply the appropriate methods for consideration of two categories of uncertainties consisting of uncertainties related to the ground motions and structural characteristics, separately. Also, cable-stayed bridges have been specifically selected because as a result of their complexity and the according time-consuming seismic analyses, reducing the computations corresponding to their fragility analyses is worthy of studying. To achieve this, the fragility assessment of three case studies is performed based on existing and proposed approaches, and a comparative study on the efficiency in the estimation of seismic responses. For this purpose, statistical validation is conducted on the seismic demand and fragility resulting from the mentioned approaches, and through a comprehensive interpretation, sufficient arguments for the acceptable errors of the proposed approach are presented. Finally, this study concludes that the combination of the Capacity Spectrum Method (CSM) and Uniform Design Sampling (UDS) in advanced proposed forms can provide adequate accuracy in seismic fragility estimation at a significantly reduced computational cost.

• Journal of the Korea Safety Management & Science
• /
• v.25 no.4
• /
• pp.25-33
• /
• 2023

This study analyzed the factors affecting the effectiveness of the Chemical Hazard Risk Management (CHARM). A survey was conducted on 104 learners who participated in the Risk Assessment training course at Occupational Safety and Health Training Institute. Through a self-administered questionnaire, the effect of personal characteristics, corporate characteristics, and safety and health level of the company on the effectiveness of chemical risk assessment was investigated. As a result of statistical analysis, the safety and health level of the company had a positive (+) effect on the effectiveness of Chemical Hazard Risk Management(CHARM), but personal characteristics and corporate characteristics had no relation to it. This study can be used as basic data for further research related to chemical risk assessment in workplaces.

• Communications for Statistical Applications and Methods
• /
• v.22 no.6
• /
• pp.605-613
• /
• 2015

A three-arm parallel design has been proposed to assess the biosimilarity between a biological product and a reference product using relative distance (Kang and Chow, 2013). The three-arm parallel design consists of two arms for the reference product and one arm for the biosimilar product. This paper extended the three-arm parallel design to a (k + 1)-arm parallel design composed of k (${\geq}3$) arms for the reference product and one arm for the biosimilar product. A new relative distance was defined based on Euclidean distance; consequently, a corresponding test procedure was developed based on asymptotic distribution. Type I error rates and powers were investigated both theoretically and empirically.

• Journal of the Korean Data and Information Science Society
• /
• v.22 no.1
• /
• pp.125-136
• /
• 2011

Ground-level ozone, an air pollutant that is monitored by the Environmental Protection Agency (EPA), damages human health by irritating the respiratory system, reducing lung function, damaging lung cells, and aggravating asthma and other chronic conditions. In March 2008, the EPA strengthened ozone standards by lowering acceptable limits from 84 parts per billion to 75 parts per billion. Here epidemiologic data is used to study the effects of ozone regulation on human health and assessed how various regulatory standards for ozone may affect nonaccidental mortality, including respiratory-related deaths during ozone season. The assessment uses statistical methods based on hierarchical Bayesian models to predict the potential effects of the different regulatory standards. It also analyzes the variability of the results and ho they are impacted by different modeling assumptions. We focused on the technical an statistical approach to assessing relationship between new ozone regulations and mortality while other researches have detailed the relationship between ozone and human mortality. We shows a statistical correlation between ozone regulations and mortality, with lower limits of acceptable ozone linked to a decrease in deaths, and projects that mortality is expected to decrease by reducing ozone regulatory standards.

• Communications for Statistical Applications and Methods
• /
• v.7 no.2
• /
• pp.541-548
• /
• 2000

Various statistical methods for assessment of equivalence in average bioavailabilities have been developed under the assumption that the intra-subject variabilities for the test and reference formulations are the same. Without the assumption, assessing the equivalence in average bioavailabilites does not imply that the two formulations are therapeutically equivalent and exchangeable. The most commonly used test procedure for equality of variabilites in 2$\times$2 crossover experiment is the so called Pitman-Morgan's adjusted F test based on the model without carryover effects (Chow and Liu(1992)). In this paper, a Bayesian method based on the Intrinsic Bayes Factor is proposed, which can be applied to the model with carryover effects.

• KSTLE International Journal
• /
• v.2 no.1
• /
• pp.35-39
• /
• 2001

In this paper, statistical approach is undertaken to investigate the classification of wear debris which is the key function of objective assessment of wear debris morphology. Wear tests are run to produce various kinds of wear debris. The images of wear debris from wear tests are captured with image acquisition equipment. By thresholding, two-dimensional binary images of wear debris are made and, then, morphological parameters are used to quantify the images of debris. Parametric and nonparametric discriminant method are employed to classify wear debris into predefined wear conditions. It is demonstrated that classification accuracy of parametric and nonparametric discriminant method is similar. The selected use of morphological parameters by stepwise discriminant analysis can generally improve the classification accuracy of parametric and nonparametric discriminant method.

• Communications for Statistical Applications and Methods
• /
• v.27 no.3
• /
• pp.269-284
• /
• 2020

This study compares two teaching methods in an introductory statistics course at a large state university. The first method is the traditional lecture-based approach. The second method implements a flipped classroom that incorporates the recommendations of the American Statistical Association's Guidelines for Assessment and Instruction in Statistics Education (GAISE) College Report. We compare these two methods, based on student performance, illustrate the procedures of the flipped pedagogy, and discuss the impact of aligning our course to current guidelines for teaching statistics at the college level. Results show that students in the flipped class performed better than students in traditional delivery. Student questionnaire responses also indicate that students in flipped delivery aligned with the GAISE recommendations have built a productive mindset in statistics.