• The Journal of Economics, Marketing and Management
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• v.9 no.1
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• pp.1-14
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• 2021

Purpose: The article deals with the proposition that consumers' fashion consumption behavior will still follow the consumption behavior of fast fashion, despite recognizing the importance of slow fashion. Research design, data and methodology: The research model to verify this proposition is topic modelling with big data including unstructured textual data. we combined 5,506 news articles posted on Naver news search platform during the 2003-2019 period about fast fashion and slow fashion, high-frequency words have been derived, and topics have been found using LDA model. Based on these, we examined consumers' perception and consumption behavior on slow fashion through the analysis of Topic Network. Results: (1) Looking at the status of annual article collection, consumers' interest in slow fashion mainly began in 2005 and showed a steady increase up to 2019. (2) Term Frequency analysis showed that the keywords for slow fashion are the lowest, with consumers' consumption patterns continuing around 'brand.' (3) Each topic's weight in articles showed that 'social value' - which includes slow fashion - ranked sixth among the 9 topics, low linkage with other topics. (4) Lastly, 'brand' and 'fashion trend' were key topics, and the topic 'social value' accounted for a low proportion. Conclusion: Slow fashion was not a considerable factor of consumption behavior. Consumption patterns in fashion sector are still dominated by general consumption patterns centered on brands and fast fashion.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.15 no.3
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• pp.67-72
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• 2006

There are many modelling methods using theoretical and experimental data. Recently, fractal interpolation methods have been widely used to estimate and analyze various data. Due to the chaotic nature of dynamic roundness profile data in roundness some desirable method must be used for the analysis which is natural to time series data. Fractal analysis used in this paper is within the scope of the fractal interpolation and fractal dimension. Also, two methods for computing the fractal dimension has been introduced which can obtain the dimension of typical dynamic roundness profile data according to the number of data points in which the fixed data are generally lower than 200 data points. This fractal analysis result shows a possible prediction of roundness profile that has some different roundness profile in round shape operation.

• Magazine of the Korean Society of Agricultural Engineers
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• v.45 no.5
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• pp.110-116
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• 2003

A catchment modelling system is the summation of the numerous hydrologic, hydraulic and other process models necessary to simulate the response of a catchment to a storm event. Differences between the recorded catchment response and that predicted by a catchment modelling system can arise from structural errors within the catchment modelling system, evaluation errors in the control parameters, or measurement errors in the recorded data being used to assess the reliability of the evaluation of the control parameters. Presented herein is an investigation of the potential measurement errors within the recorded information, which was considered to occur from instrument error in the ultra sonic flow monitor. This investigation was undertaken using three available rating curves at the Musgrave Avenue Stormwater System in Centennial Park, Sydney, developed by Abustan (1997), Water Board (1994), and using Manning's equation.

• Journal of the Korean Operations Research and Management Science Society
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• v.16 no.1
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• pp.68-75
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• 1991

The purpose of this thesis is to develop the new technique for the analysis of seasonal time series by extending the vector sample auto-correlation function(VSACF), which was developed for ARMA modelling procedure. After the problems of VSACF for modelling seasonal time series are investigated, the adjacent variance is defined and used for decomposing the seasonal factor from the seasonal time series. The seasonal indices are calculated and the VSACF is applied to the transformed series. The automatic procedure for modelling seasonal time series is suggested and applied to the real data, the international airline passenger travel.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.3
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• pp.2097-2100
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• 2013

Background: To estimate the numbers and trends in cervix cancer cases visiting the Radiotherapy Department at Manipal Teaching Hospital, Pokhara, Nepal, statistical modelling from retrospective data was applied. Materials and Methods: A retrospective study was carried out on data for a total of 159 patients treated for cervix cancer at Manipal Teaching Hospital, Pokhara, Nepal, between $28^{th}$ September 2000 and $31^{st}$ December 2008. Theoretical statistics were used for statistical modelling and forecasting. Results: Using curve fitting method, Linear, Logarithmic, Inverse, Quadratic, Cubic, Compound, Power and Exponential growth models were validated. Including the constant term, none of the models fit the data well. Excluding the constant term, the cubic model demonstrated the best fit, with $R^2$=0.871 (p=0.004). In 2008, the observed and estimated numbers of cases were same (12). According to our model, 273 patients with cervical cancer are expected to visit the hospital in 2015. Conclusions: Our data predict a significant increase in cervical cancer cases in this region in the near future. This observation suggests the need for more focus and resource allocation on cervical cancer screening and treatment.

• Smart Structures and Systems
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• v.20 no.2
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• pp.127-137
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• 2017

Identification of damping characteristics is of significant importance for dynamic response analysis and condition assessment of structural systems. Damping is associated with the behavior of the energy dissipation mechanism. Identification of damping ratios based on the sensitivity of dynamic responses and the model updating technique is investigated with numerical and experimental investigations. The effectiveness and performance of using the sensitivity-based model updating method and vibration monitoring data for damping ratios identification are investigated. Numerical studies on a three-dimensional truss bridge model are conducted to verify the effectiveness of the proposed approach. Measurement noise effect and the initial finite element modelling errors are considered. The results demonstrate that the damping ratio identification with the proposed approach is not sensitive to the noise effect but could be affected significantly by the modelling errors. Experimental studies on a steel planar frame structure are conducted. The robustness and performance of the proposed damping identification approach are investigated with real measured vibration data. The results demonstrate that the proposed approach has a decent and reliable performance to identify the damping ratios.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.63-69
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• 1999

The purpose of this study is to develop Water Quality Management System(WQMS), which performs calculating pollutant discharge and forecasting water quality with water pollution model. Operational water quality management requires not only controlling pollutants but acquiring and managing exact information. A GIS software, ArcView was used to enter or edit geographic data and attribute data, and MapObject was used to customize the user interface. PCI, a remote sensing software, was used for deriving land cover classification from 20 m resolution SPOT data by image processing. WQMS has two subsystems, Database Subsystem and Modelling subsystem. Database subsystem consisted of watershed data from digital map, remote sensing data, government reports, census data and so on. Modelling subsystem consisted of NSPLM(NonStorm Pollutant Load Model)-SPLM(Storm Pollutant Load Model). It calculates the amount of pollutant and predicts water quality. This two subsystem was connected through graphic display module. This system has been calibrated and verified by applying to Mokhyun stream watershed.

• Computers and Concrete
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• v.25 no.4
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• pp.369-382
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• 2020

This paper presents a discussion of the Finite Element Analysis (FEA) when applied for the analysis of concrete elements reinforced with glass fibre reinforced polymer (GFRP) bars. The purpose of such nonlinear FEA model development is to create a tool that can be used for numerical parametric studies which can be used to extend the existing (and limited) experiment database. The presented research focuses on the numerical analyses of concrete beams reinforced with GFRP longitudinal and shear reinforcements. FEA of concrete members reinforced with linear elastic brittle reinforcements (like GFRP) presents unique challenges when compared to the analysis of members reinforced with plastic (steel) reinforcements, which are discussed in the paper. Specifically, the behaviour and failure of GFRP reinforced members are strongly influenced by the compressive response of concrete and thus modelling of concrete behaviour is essential for proper analysis. FEA was performed using the commercial software ABAQUS. A damaged-plasticity model was utilized to simulate the concrete behaviour. The influence of tension, compression, dilatancy, mesh, and reinforcement modelling was studied to replicate experimental test data of beams previously tested at the University of Waterloo, Canada. Recommendations for the finite element modelling of beams reinforced with GFRP longitudinal and shear reinforcements are offered. The knowledge gained from this research allows for the development of a rational methodology for modelling GFRP reinforced concrete beams, which subsequently can be used for extensive parametric studies and the formation of informed recommendations to design standards.

• 한국데이터정보과학회:학술대회논문집
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• 2005.04a
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• pp.200-201
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• 2005

• Geophysics and Geophysical Exploration
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• v.8 no.4
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• pp.251-261
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• 2005

The quality of MT (magnetotellurics) data highly depends on the level of artificial noise form industrial sources. We have conducted the feasibility study of MT noise modelling using digital spatial data and spatial modelling through the comparison between the predicted and the measured MT noises. A simple noise model predicting the intensity of electromagnetic field radiated from the latent noise sources, that is, the electric facilities in the building, road and high-voltage powerline, is developed in consideration of the propagation property of electromagnetic waves. From the analysis of correlation between the predicted and the measured noise power, the correlation coefficients of electric field are higher than those of magnetic field in whole frequency band. The magnetic field component has the high correlation in the narrow band near 60 Hz only. The spatial noise modelling proposed in this study would provide some useful informations for the MT surveys in the noisy environment like urban area.