• Economic and Environmental Geology
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• v.55 no.3
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• pp.231-239
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• 2022

The irregular shape of the disturbances is a fundamental issue for mining engineers at the Sidi Chennane phosphate deposit in Morocco. A precise classification of disturbed areas is therefore necessary to understand their part in the overall volume of phosphate. In this paper, we investigate the theoretical and practical aspects of studying and measuring multifractal spectrums as a defining and representative parameter for distinguishing between the phosphate deposit of a low rate of disturbances and the deposit of a high rate. An empirical multifractal approach was used by analyzing the disturbed areas through the geoelectric images of an area located in the Sidi Chennane phosphate deposit. The Generalized fractal dimension, D(q), the Singularities of strength, α(q), the local dimension, f(α) and their conjugate parameter the mass exponent, τ(q) as well as f(α)-α spectrum were the common multifractal parameters used. The results reported show wide variations of the analyzed images, indicating that the multifractal analysis is an indicator for evaluate and characterize the disturbed areas within the phosphates deposits through the studied geoelectric images. This could be the starting point for future work aimed at improving phosphate exploration planning.

• Proceedings of the KSR Conference
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• 2011.10a
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• pp.119-127
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• 2011

This paper shows development of 1-3 dimensional hybrid mesh method to analysis flow induced by ultra-high speed vehicle inside a long distance tunnel. For three-dimensional analysis of the tunnel system many meshes are required. However it is not efficient to calculate the whole tunnel system in three-dimension. Therefore in this paper, three-dimension meshes was used to describe stations, shafts and around vehicle, and one-dimension meshes was used to describe the tunnel except these three sections. And unsteady flow analysis of the ultra-high speed vehicle was performed with UDFs in commercial software, Ansys vr. 12.0.

• Korean Journal of Soil Science and Fertilizer
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• v.42 no.1
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• pp.58-64
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• 2009

The objectives of this study were to investigate the aggregate fragmentation in wet-sieving and to evaluate the relationship between the aggregate fragmentation fractal dimension and macro-porosity of upland soils, using three different textural types of soils including Gopyeng series (Fine, Typic Hapludalfs), Gyuam series (Fine silty over coarse silty, Fluvaquentic Eutrudepts), and Jungdong series (Coarse loamy, Typic Udifluvents) located in Gyeonggi province. Undisturbed soil samples with five replicates were seasonally sampled and used for measuring water stable aggregate, macropores, and physico-chemical properties of soils. The aggregate stability in wet-sieving was digitalized as three types of fragmentation fractal dimension ($D_f$), geometric mean diameter (GMD), and mean weight diameter (MWD). $D_f$ had higher correlation with GMD than with MWD. Seasonal aggregate stability showed the highest values in summer, and decreased in the order of spring and autumn. The macroporosity had higher in topsoil, in autumn, and in ridge, than in plow pan layer, in summer, and in row, respectively. The relationship between $D_f$ and macroporosity, especially more than 99 m, showed high correlation only in soils with $D_f$ less than 3.1, which means more aggregated soils compared to soils with $D_f$ more than 3.1. Besides, in the soils with the fractal dimension less than 3.1, the power function relation between saturated hydraulic conductivity and macroporosity more than 99 m had relatively high determinant coefficient, and vice versa. Therefore, it could be thought that fragmentation fractal dimension is available for confirming macroporosity induced from aggregation.

• The Korean Journal of Applied Statistics
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• v.34 no.6
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• pp.905-922
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• 2021

Cluster analysis is one of unsupervised learning techniques used for discovering clusters when there is no prior knowledge of group membership. K-means, one of the commonly used cluster analysis techniques, may fail when the number of variables becomes large. In such high-dimensional cases, it is common to perform tandem analysis, K-means cluster analysis after reducing the number of variables using dimension reduction methods. However, there is no guarantee that the reduced dimension reveals the cluster structure properly. Principal component analysis may mask the structure of clusters, especially when there are large variances for variables that are not related to cluster structure. To overcome this, techniques that perform dimension reduction and cluster analysis simultaneously have been suggested. This study proposes probabilistic reduced K-means, the transition of reduced K-means (De Soete and Caroll, 1994) into a probabilistic framework. Simulation shows that the proposed method performs better than tandem clustering or clustering without any dimension reduction. When the number of the variables is larger than the number of samples in each cluster, probabilistic reduced K-means show better formation of clusters than non-probabilistic reduced K-means. In the application to a real data set, it revealed similar or better cluster structure compared to other methods.

• Journal of the Korean Society for Advanced Composite Structures
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• v.6 no.1
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• pp.59-66
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• 2015

In this study, structural stability of large diameter high density polyethylene (HDPE) pipe during installation was numerically investigated in order to investigate the effect of concrete collar dimension, water depth and tension (pulling force). From the numerical simulation results, the total stress of HDPE pipe with designed concrete collar was within 2.5%, so the total weight of concrete collar for sinking of HDPE is important rather than concrete collar dimension. Furthermore, the tension area for possible installation is decreased as the air filling rate is increased. Therefore, it is important to calculate the reasonable tension range before actual installation for safe installation of HDPE pipe.

• Korean System Dynamics Review
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• v.11 no.2
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• pp.5-28
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• 2010

The purpose of this paper is to review relationship between spatial characteristics of compact city and urban sustainabiliy from system dynamics perspective using causal loop analysis. It has been argued that spatial characteristics of compact city, high population density and mixed land use, are positively related to urban sustainability. However, research results that are not consistent with pros of compact city argument have been accumulated too. It is especially true when spatial characteristics of compact city are examined with regard to each dimension of sustainablility: economic, social, and environmental sustainability. Reviewing each dimension of sustainability with regard to spatial characteristics based on causal loop analysis, this paper provides more clear understanding on relationship between compact city and sustainability. Also this paper provides a base for system dynamics simulation for future study.

• Proceedings of the Korean Statistical Society Conference
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• 2003.10a
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• pp.9-14
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• 2003

A Bayesian model-based clustering method is proposed for clustering objects on the basis of dissimilarites. This combines two basic ideas. The first is that tile objects have latent positions in a Euclidean space, and that the observed dissimilarities are measurements of the Euclidean distances with error. The second idea is that the latent positions are generated from a mixture of multivariate normal distributions, each one corresponding to a cluster. We estimate the resulting model in a Bayesian way using Markov chain Monte Carlo. The method carries out multidimensional scaling and model-based clustering simultaneously, and yields good object configurations and good clustering results with reasonable measures of clustering uncertainties. In the examples we studied, the clustering results based on low-dimensional configurations were almost as good as those based on high-dimensional ones. Thus tile method can be used as a tool for dimension reduction when clustering high-dimensional objects, which may be useful especially for visual inspection of clusters. We also propose a Bayesian criterion for choosing the dimension of the object configuration and the number of clusters simultaneously. This is easy to compute and works reasonably well in simulations and real examples.

• Culinary science and hospitality research
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• v.14 no.4
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• pp.232-243
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• 2008

The purpose of this study is to investigate Korean wine consumers' perceived risk dimensions affecting wine purchasing behavior and identify the differences in the dimensions by wine involvement. Questionnaires were collected from the wine purchasers of wine retailer shops in Seoul. 230 data were analysed using SPSS package(v. 12.0). Findings were as follows: (1) There were 5 dimensions in the perceived risk of wine purchasing: functional, social, physical, psychological, financial. Social dimension was the most serious risk for wine consumers, then come psychological, functional, financial, and physical ones. (2) There were significant differences in the perceived risk dimensions by involvement level except the financial dimension. The perception level of wine purchasing risk was relatively low in the high involvement group while high in the middle and low involvement groups.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.1855-1858
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• 2003

In this paper, we propose image retrieval method more accurate and efficient than the conventional one. First of ail, we perform a shot detection and key frame extraction from the DC image constructed by DCT DC coefficients in the compressed video stream that is video compression standard such as MPEG[I][2]. We get principal axis applying PCA(Principal Component Analysis) to key frames for obtaining indexing information, and divide a domain. Video retrieval uses indexing information of high dimension. We apply KD-Trees(K Dimensional-Trees)[3] which shows efficient retrieval in data set of high dimension to video retrieval method. The proposed method can represent property of images more efficiently and property of domains more accurately using KD-Trees.

• KIEE International Transactions on Electrophysics and Applications
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• v.11C no.2
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• pp.18-22
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• 2001

The thin films of high permitivity in ferroelectric materials using a capacitor are applied to DRAMs and FRAMs. (Ba, Sr)TiO$_3$ thin as ferroelectric materials were prepared by the sol-gel method and made by spin-coating on the Pt/Sio$_2$/Si substrate at 4,000 [rpm] for 10 seconds. The structural characteristics of the surface were analyzed by fractal dimension. The thickness of BST ceramics thin films was about 260∼280 [nm]. The property of the leakage current was stable with 10-9∼10-11[A] when the applied voltage was 0∼3[V]. BST thin films ha low leakage current properties when fractal dimension was low and a coating area was high.