• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2000년도 가을 학술발표회 논문집
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• pp.493-500
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• 2000

Rock Mass Rating has been widely applied to the underground tunnel excavation and many other practical problems in rock engineering. However, Rock Mass Rating is hard to make out because it is difficult to estimate each valuation items through all kind of field situations and items of RMR have interdependence. So the experts of tunnel assessment have problems with rating rock mass. In this study, using multivariate analysis based on domestic data(1011EA) of water conveyance tunnel, we presented rock mass rating system which is objective and easy to use. The constituents of RMR are decided to RQD, condition of discontinuities, groundwater conditions, orientation of discontinuities, intact rock strength, spacing of discontinuities in important order. In each step, we proposed the best multiple regression model for RMR system. And using data which have been collected at other site, we examined that presented multiple regression model was useful.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2001년도 봄 학술발표회 논문집
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• pp.273-280
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• 2001

In order to evaluate the stability of railway cut-slope under rainfall, explanatory variables and subordinate variables were selected for multivariate analysis. Furthermore the site which had occurred failure due to rainfall was investigated, and by executing multivariate analysis for 121 cases, critical rainfall was defined by the case that had high value of correlation factor. The 0.3 square value of maximum hourly rainfall during 24 hours before failure caused the collapse of railway cut-slope and could be used to estimate the stability of railway cut-slope. From the result of application to a collapse example, the evaluaton method by critical rainfall curve is satisfactory.

• Computers and Concrete
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• 제20권1호
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• pp.23-29
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• 2017

In this study engineered steel fibres used as reinforcement for concrete were characterized by number of key mechanical and spatial parameters, which are easy to measure and quantify. Such commonly used parameters as length, diameter, fibre intrinsic efficiency ratio (FIER), hook geometry, tensile strength and ductility were considered. Effective classification of various fibres was demonstrated using simple multivariate computations involving principal component analysis (PCA). Contrary to univariate data mining approach, the proposed analysis can be efficiently adapted for fast, robust and direct classification of engineered steel fibres. The results have revealed that in case of particular spatial/geometrical conditions of steel fibres investigated the FIER parameter can be efficiently replaced by a simple aspect ratio. There is also a need of finding new parameters describing properties of steel fibre more precisely.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2014년도 춘계학술발표대회
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• pp.582-585
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• 2014

Visualization is a science which makes the invisible to visible through the techniques of experimental visualization and computer-aided visualization. This paper presents the practical aspects of visualization of multivariate dataset. In this paper, we will briefly discuss a previous research work and introduce a new visualization technique which will help us to design and develop a visualization tool for experimental visualization of multivariate dataset. Our newly developed visualization tool can be used in various domains. In this paper, we have chosen a software industry as an application domain and we used the multivariate dataset of software components computed by VizzMaintenance. VizzMaintenance is software analysis tool which give us multiple software metrics of open source Java based programs. Main objective of this research is to develop a new visualization tool for large multivariate dataset which will be more efficient and easy to perceive by viewer. Perception is very important for our research work and we have decided to test the perception level of our proposed visualization approach by researchers of our research lab.

• 상하수도학회지
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• 제29권6호
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• pp.625-632
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• 2015

The study of water environment system using a multivariate analysis in Changnyeong-Haman weir section has been conducted. The purpose of this study is to establish better understanding related water qualities in the Changnyeong-Haman weir section which can provide useful information. The data were consisted of water quality data and algae data including WT(water temperature), pH, DO, EC, COD, SS, T-N, $NH_3-N$, T-P, $PO_4-P$, Chl-a, TOC, d-silica, t-silica, Cyanobacteria, Diatoms, and Green algae. Statistical analyses used in this study were correlation analysis, principal components, and factor analysis. According to correlation analysis on COD and TOC, it revealed that the each value of correlation coefficient was 0.843. On the other result, a negative correlation was observed between diatoms and d-silica. Furthermore, the results of principal component analysis to the overall water quality were classified into four main factors with contribution rate 81.071%.

• 한국물환경학회지
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• 제23권6호
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• pp.814-821
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• 2007

This study was estimated water quality to raw water quality management of the Maeri intake station in the Nakdong River using Multivariate Analysis. The results of Principle Component Analysis was explained up to 76.9% of total water quality by three principle components. The 1st, 2nd was explained 44.7%, 17.9% and third was explained 14.3%. Also, the three factors was derived from Factor Analysis. The 1st factor was estimated as the matabolism and organic matter pattern related to algal growth. The 2nd factor was judged as the pollution of pattern related to the discharge from stream of the Nakdong River and 3rd factor was viewed as the hydrological variation pattern related to particle matter. The results of Cluster Analysis were classified into three groups.

• IEIE Transactions on Smart Processing and Computing
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• 제4권2호
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• pp.89-96
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• 2015

In this paper, time-frequency analysis algorithms, empirical mode decomposition and local mean decomposition, are reviewed and their applications to nonlinear and nonstationary real-world data are discussed. In addition, their generic extensions to complex domain are addressed for the analysis of multichannel data. Simulations of these algorithms on synthetic data illustrate the fundamental structure of the algorithms and how they are designed for the analysis of nonlinear and nonstationary data. Applications of the complex version of the algorithms to the synthetic data also demonstrate the benefit of the algorithms for the accurate frequency decomposition of multichannel data.

• 한국펄프종이공학회:학술대회논문집
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• 한국펄프종이공학회 2006년도 PAN PACIFIC CONFERENCE vol.2
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• pp.191-195
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• 2006

Multivariate data analysis tools were used to improve the understanding of the wet end chemistry and white water system of the Papermill at NorskeCanada Crofton Division. Specifically, the analysis was aimed at identifying what variables were contributing to increased retention aid use and wet end instability. Several models were developed using data sets with up to 88 process variables and over 3000 observations. It was found that increased retention aid use was driven primarily by PCC and TMP usage as well as the addition of Alaskan White Spruce to the TMP furnish.

• 한국환경과학회지
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• 제13권3호
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• pp.233-244
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• 2004

This study was conducted to evaluate water quality in the Mankyung River using multivariate analysis. The analysis data which was surveyed from January 1996 to December 2002 in Mankyung river was aquired by the ministry of environment. Twelve water quality parameters were determined on each survey. The results were summarized as follow; Water quality in the Mankyung River could be explained up to 74.90% by four factors which were included in loading of organic matter and nutrients by the tributaries(43.28%), seasonal variation(10.40%), loading of pathogenic bacteria by domestic sewage of Gapcheon (12.41%) and internal metabolism in river(8.81%). The result of cluster analysis by station was classified into three group that has different water quality characteristics. Especially, Iksan river was appeared to considerable water quality characteristics against other station. In monthly cluster analysis, three group was classified by seasonal characteristics. Also, in yearly cluster analysis, three group was classified. It is necessary to control the pollutant loadings by domestic sewage and livestock waste for water quality management of Mankyung river.

• Asian Pacific Journal of Cancer Prevention
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• 제13권4호
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• pp.1171-1176
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• 2012

Objective: The current study aimedto screen for possible factors which affect prognosis of chondrosarcoma. Methods: Thirty seven cases were selected and analyzed statistically. The patients received surgical treatment at our hospital between December 2005 and March 2008. All of them had complete follow-up data. The survival rates were calculated by univariate analysis using the Kaplan-Meier method and tested by Log-rank. ${\chi}^2$ or Fisher exact tests were carried out for the numeration data. The significant indexes after univariate analysis were then analyzed by multivariate analysis using COX regression model. Based on the literature, factors of gender, age, disease course, tumor location, Enneking grades, surgical approaches, distant metastasis and local recurrence were examined. Results: Univariate analysis showed that there were significant differences in Enneking grades, surgical approaches and distant metastasis related to the patients' 3-year survival rate after surgery (P<0.001). No significant difference was not found in gender, age, disease course, tumor location or local recurrence (P>0.05). Multivariate analysis showed that Enneking grade (P=0.007) and surgical approaches (P=0.010) were independent factors affecting the prognosis of chondrosarcoma, but distant metastasis was not (P=0.942). Conclusion: Enneking grades, surgical approaches and distant metastasis are risk factors for prognosis of chondrosarcoma, among which the former two are independent factors.