• Proceedings of the KSR Conference
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• 2009.05a
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• pp.66-72
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• 2009

In order to forecast the progress of the track irregularity, we should observe the long-term track quality and divide a track into some separated divisions which have homogeneous property. For this, we define the division of track which has homogeneous property as a 'Segment' and manage the 'TQI(Track Quality Index)' using track induction data based on each segment. In this study, we introduce some methods of estimating track quality and figure out the TQIs of sample section using new FRA TQI method. In addition, we conducted a basic study of the forecasting model for the progress of track irregularity by analyzing track maintenance data.

• Proceedings of the KSR Conference
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• 2000.11a
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• pp.450-457
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• 2000

This paper establishes a scheme to estimate track quality using standard deviation and deterioration rate of track irregularities. To provide index of quality, standard deviation and deterioration rate of track irregularities are analyed. As an index, standard deviation and deterioration rate were applied to decision of corrective maintenance and replacement maintenance, respectively. Further, this paper proposes a basic scheme for a modernization of mechanize track maintenance that using MTT(Multiple Tie Tamper) and Ballast Cleaner.

• 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 the Korean Society for Railway
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• v.19 no.4
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• pp.547-554
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• 2016

This study considered how to estimate the deterioration rate of the track quality index, which represents track geometric irregularity. Most existing studies have used a simple linear regression and regarded the slope of the regression equation as the progress rate. In this paper, we present a Bayesian approach to estimate the track irregularity progress. This Bayesian approach has many advantages, among which the biggest is that it can formally include the prior distribution of parameters which can be derived from historic data or from expert experiences; then, the rate can be expressed as a probability distribution. We investigated the possibility of applying the Bayesian method to the estimation of the deterioration rate by comparing our bayesian approach to the conventional linear regression approach.

• Journal of the Korean GEO-environmental Society
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• v.19 no.2
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• pp.37-44
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• 2018

Ballasted track has been widely used due to its flexibility. However, the plastic deformation of ballasted track causes the evolution of track geometrical errors, and hence it requires continuous maintenance; increase in number of trains, weight, and speed expedites maintenance frequency and cost as well. Ballast stiffness is well-known as an indicator of design and maintenance. In this regard, this paper aims to suggest the method to measure ballast track stiffness using light-weight deflectometer (LWD) and thus verify its applicability as a maintenance measure. Preliminary field tests determined simple field testing protocol to measure track stiffness. The apparent ballast stiffness by LWD shows good corelation with TQI (Track Quality Index) and maintenance length. That is, as average of apparent stiffness increase, TQI and tamping length decrease exponentially. Therefore, apparent stiffness can be used as an index for ballast condition assessment.

• Journal of the Korean Society for Railway
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• v.8 no.2
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• pp.111-115
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• 2005

The Study provides the technical background and calculation method f3r the long wave track defect. On high speed railway, It is necessary to manage the long wave band up to 80m track defect fur improving a riding quality. For this reason, Track recording methods for highspeed railway are used 10m and 30m recording bases, these are covered middle wave band and long wave band successfully. Extended base recording data is calculated by geometrical model and this data provides a good result for KTX riding index.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.521-525
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• 2011

Although the Korean construction industry has risen rapidly, the quality of the buildings is not met with the industry standard compared to the potential of the technology development and the cost of maintenance has been increased. The user's request for quality have been increased, but in the current building construction, the contractors only follow the specifications of design, material and technology, and their main concern is whether they are in right track with the specification or not. Thus, the necessity of developing technology has been ignored and sufficient opportunities for the development have not been provided as well. In the developed countries, in contrast, the quality assurance and the payment regulation system has been utilized for the active response to the changes of users' request. As a result of this, the maintenance cost has been decreased and the development of construction technology has been improved. Therefore the pay adjustment system is needed to create the improvement of the quality of the buildings by the contractors' earnest building construction. In order to introduce the pay adjustment system suitable to the Korean construction industry, this study presented the logical method of adjusting the construction cost and making payment with the pay adjustment index that is created based on the result of the performance test, after making a set of the indicators of the building performance standard and applied them to the targeted building.

• Journal of Information Science Theory and Practice
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• v.6 no.3
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• pp.45-60
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• 2018

Research performance evaluation in Korean universities follows strict guidelines that specify scoring systems for publication venue categories and formulas for co-authorship credit allocation. To find out how the standards differ across universities and how they differ from bibliometric research evaluation measures, this study analyzed 25 standards from major Korean universities and rankings produced by applying standards and bibliometric measures such as publication and citation counts, normalized impact score, and h-index to the publication data of 195 tenure-track professors of library and information science departments in 35 Korean universities. The study also introduced a novel impact score normalization method to refine the methodology from prior studies. The results showed the university standards to be mostly similar to one another but quite different from citation-driven measures, which suggests the standards are not quite successful in quantifying the quality of research as originally intended.

• Journal of the Korean Society for Railway
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• v.20 no.2
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• pp.234-240
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• 2017

In this study, the influences of rail surface roughness on dynamic wheel-rail forces currently employed in conventional lines were assessed by performing field measurements according to grinding of rail surface roughness. The influence of the grinding effect was evaluated using a previous empirical prediction model for dynamic wheel-rail forces; model includes first-order derivatives of QI (Quality Index) and vehicle velocity. The theoretical dynamic wheel-rail force determined using the previous prediction equation was analyzed using the QI, which decreased due to rail grinding as determined through field measurements. At a constant track support stiffness, an increase in the QI caused an increase in dynamic wheel-rail forces. Further, it can be inferred that the results of dynamic wheel-rail analysis obtained using the measured data, such as the variation of QI due to rail grinding, can be used to predict the peak dynamic forces. Therefore, it is obvious that the optimum amount of rail grinding can be determined by considering the QI, that was regarding an operation characteristics of the target track (vehicle velocity and wheel load).

• The Journal of Asian Finance, Economics and Business
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• v.8 no.1
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• pp.145-156
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• 2021

The research purpose of this paper is to empirically examine the effects of technological readiness and innovation on logistics performance. To build up and maintain an important role in global supply chains, nowadays it is obvious that countries and logistics providers need to achieve competitive advantage in terms of digitalization. However, there is a lack of empirical studies about the impacts of information technologies and innovation potential on the logistics efficiency of countries. Hence, the study analyzes whether the corresponding pillars of the Global Competitiveness Index (GCI) matter for the Logistics Performance Index (LPI) and its dimensions. For determining the effects, the pooled regression approach is applied. The results show that technological readiness and innovation are positively and statistically significantly correlated with logistics performance: competence and quality of logistics services, efficiency of customs clearance processes, ability to track and trace consignments, frequency with which shipments reach consignee within scheduled or expected time, and ease of arranging competitively priced shipments. The findings of this study suggest that investments in innovations and technology progress improve countries' logistics efficiency, which is an important prerequisite for enabling Logistics 4.0 and thus, Industry 4.0 and the digital transformation of the economy and society.