• Journal of the Korean Geosynthetics Society
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• v.19 no.1
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• pp.45-53
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• 2020

There is an increasing tendency to try to make predictive analysis using measurement data based on machine learning techniques in the railway industries. In this paper, it was predicted that Track quality index (TQI) using vehicle acceleration data based on the machine learning method. The XGB (XGBoost) was the most accurate with 85% in the all data sets. Unlike the SVM model with a single algorithm, the RF and XGB model with a ensemble system were considered to be good at the prediction performance. In the case of the Surface TQI, it is shown that the acceleration of the z axis is highly related to the vertical direction and is in good agreement with the previous studies. Therefore, it is appropriate to apply the model with the ensemble algorithm to predict the track quality index using the vehicle vibration acceleration data because the accuracy may vary depending on the applied model in the machine learning methods.

• Journal of Environmental Impact Assessment
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• v.30 no.2
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• pp.75-88
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• 2021

Six locations in the automated monitoring network at the Geum River Basin were selected forthis study. The water quality characteristics at two of the locations in the water quality monitoring network that were identical, or nearby, were examined, and their correlations were evaluated through statistical analysis. The results of the water quality analysis were converted to the water quality index and expressed in grades for comparison. For the data necessary for the study, public data from four years, from 2016-2019 were used and the evaluation parameters were water temperature, pH, EC, DO, TOC, TN, and TP. Results of the analysis showed that the water quality concentrations measured in the automated monitoring network and the water quality monitoring network differed in some measured values, but they tended to register variation in a specified ratio in most of the locations in the network. The analysis of the correlations of the parameters between the two monitoring networks found that water temperature, EC, and DO showed high correlations between the two monitoring networks. The TOC, TN, and TP showed high correlations, with a 0.7 or higher (correlation coefficient r), with the exception of some of the monitoring networks, although their correlations were lower than those of the basic parameters. The water quality index analysis showed that the water quality index values of the automated monitoring network and the water quality monitoring network were similar. The water quality index decreased and the pollution degree increased in the downstream direction, in both networks.

• Journal of the Korean Society of School Health
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• v.25 no.1
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• pp.51-58
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• 2012

Purpose: This study aims to discover the relation between the sleep duration and quality of adolescents and their body mass index. Methods: The study used data obtained through the 2009 online survey on adolescents health behaviors, targeting a total of 75,066 middle and high school students (39,612 of male students and 35,454 of female students). We first performed t-test, ANOVA and Scheffe's test and then the potential variables which was possibly related to the body mass index are determined from the tests. Using the potential variable, we performed the multiple regression analysis to finally identify the relation between the duration and quality of sleep. Results: As a result, the 39.8% of male students and the 46.5% of female students most frequently respond that the sleep duration was less than 6 hours, and 36.4% of male students and the 45.3% of female students respond that the quality of sleep was not good enough. The body mass index of both the male and the female students portionally decreases to their sleep duration, but the better quality of sleep makes their body mass index higher. Conclusion: In conclusion, the body mass index has some notable relationship with the sleep duration and quality for adolescents. It is advised to consider the sleep duration and quality in the business plans for adolescents in order for the prevention of their body mass index.

• The Korean Journal of Applied Statistics
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• v.25 no.6
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• pp.977-985
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• 2012

Data quality and climate forecasting performance deteriorates because of long climate data contaminated by non-climatic factors such as the station relocation or new instrument replacement. For a trusted climate forecast, it is necessary to implement data quality control and test inhomogeneous data. Before the inhomogeneity test, a reference series was created by $d$ index to measure the temperature series relationship between the candidate and surrounding stations. In this study, a inhomogeneity test to each season and climatological station was performed on the daily mean temperatures, daily minimum temperatures and daily maximum temperatures. After comparing two inhomogeneity tests, the traditional and the adjusted SNHT method, we found the adjusted SNHT method was slightly superior to the traditional one.

• Proceedings of the Korean Society for Quality Management Conference
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• 1998.11a
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• pp.419-428
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• 1998

In this paper, we analyzed two methodologies to evaluate the total quality management activities comparatively. One of them is the traditional scoring system (TSS) by analytic hierarchy process (AHP) and the other is the efficiency measuring system (EMS) by data envelop analysis (DEA), It is demonstrated that the index by TSS and the efficiency index by EMS are not correlated. Also, the efficiency index by EMS in terms of company characteristics such as the size of company and ISO certifications is different from the index by TSS. The result implies that to evaluate the quality activities by EMS is needed as a supplementory methodology.

• Journal of Korean Society for Quality Management
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• v.27 no.2
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• pp.47-56
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• 1999

In this paper, we analyzed two methodologies to evaluate the total quality management activities comparatively. One of them is the traditional scoring system (TSS) by analytic hierarchy process (AHP) and the other is the efficiency measuring system (EMS) by data envelop analysis (DEA). It is demonstrated that the index by TSS and the efficiency index by EMS are not correlated. Also, the efficiency index by EMS in terms of company characteristics such as the size of company and ISO certifications is different from the index by TSS. The result implies that to evaluate the quality activities by EMS is needed as a supplementary methodology.

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.473-478
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• 2007

We analyze competitiveness of material and component industry(MCI) of Korea, China and Japan using trade data, OECD ITCS database with HS-code system. We use unit price indices, export unit price index, import unit price index, and TOT unit price index. These indices provide quality information from trade data of value and quantity. Our results show that there are quality gaps among three countries, and that China expand development potential, and the results vary as sectors. It implies that R&D investment to improve quality of MCI products is essential and that sector-specific policy is necessary.

• Proceedings of the Korean Society for Quality Management Conference
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• 2010.04a
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• pp.33-48
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• 2010

The purpose of this study is to empirically analyze the productivity change of the 10 Single PPM Certification Company in the 3 Industry(Electronics, Motor-Parts, Machines). In this study, Productivity change over the time in Korean small and medium sized firms in the 3 industries by the bootstrapped Malmquist Productivity Index(MPI). The traditional Malmquist Productivity Index(MPI) and Data Envelopment they could lead to wrong evaluations of the efficiency and productivity scores. In this paper, DEA and a MPI are combined with a bootstrap method in order to provide statistical inferences that analyze the performance of the Single PPM Certification Company. The data cover the period between 2004 and 2007. The result of this paper reveals : 1) The electronic industries(Motor-Parts, Machines). 2) average productivity Progress of the 7DMU(Electronics), 1DMU(Motor-Parts) and none(Machines).

• The Journal of Korean Association of Computer Education
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• v.19 no.4
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• pp.59-66
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• 2016

It has been studied to reflect the number of co-rated items for solving data sparsity problem in collaborative filtering systems. A well-known method of Jaccard index allowed performance improvement, when combined with previous similarity measures. However, the degree of performance improvement when combined with existing similarity measures in various data environments are seldom analyzed, which is the objective of this study. Jaccard index as a sole similarity measure yielded much higher prediction quality than traditional measures and very high recommendation quality in a sparse dataset. In general, previous similarity measures combined with Jaccard index improved performance regardless of dataset characteristics. Especially, cosine similarity achieved the highest improvement in sparse datasets, while similarity of Mean Squared Difference degraded prediction quality in denser sets. Therefore, one needs to consider characteristics of data environment and similarity measures before combining Jaccard index for similarity use.

• Journal of the Korea Safety Management & Science
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• v.8 no.3
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• pp.11-25
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• 2006

It is necessary to deal with the process capability index carefully because it has been developed with certain assumptions. Companies make a decision on processes through the results obtained by using and treating data extracted from the processes. However if they have incorrect or wrong results, they cannot lead to proper outputs but also bring to loss of the competition in quality. Therefore, this study will show a method to analysis Cp (process capability ; CP) and an idea of mass-production on Pp (process performance ; PP) based on the Sigma Estimate which is one of the uncertainty in the process capability index and makes a lot of error. To apply this method, it is essential to understand and to analyze the processes exactly. Especially, it is required to establish the more accurate process capability index that can quickly and properly respond to changes on processes to recognize the small changes on the process which lies in specification in mass production system that the continual monitoring of quality managers is required.