• Journal of KIISE
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• v.43 no.8
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• pp.910-918
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• 2016

A tensor is a multi-dimensional array that represents many data such as (user, user, time) in the social network system. A tensor generator is an important tool for multi-dimensional data mining research with various applications including simulation, multi-dimensional data modeling/understanding, and sampling/extrapolation. However, existing tensor generators cannot generate sparse tensors like real-world tensors that obey power law. In addition, they have limitations such as tensor sizes that can be processed and additional time required to upload generated tensor to distributed systems for further analysis. In this study, we propose TeT, a distributed tera-scale tensor generator to solve these problems. TeT generates sparse random tensor as well as sparse R-MAT and Kronecker tensor without any limitation on tensor sizes. In addition, a TeT-generated tensor is immediately ready for further tensor analysis on the same distributed system. The careful design of TeT facilitates nearly linear scalability on the number of machines.

• Water Engineering Research
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• v.1 no.2
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• pp.147-158
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• 2000

In this study, we characterized the seasonal variation of rainrate fields in the Han river basin using the WGR multi-dimensional precipitation model (Waymire, Gupta, and Rodriguez-Iturbe, 1984) by estimating and comparing the parameters derived for each month and for the plain area, the mountain area and overall basin, respectively. The first-and second-order statistics derived from observed point gauge data were used to estimate the model parameters based on the Davidon-Fletcher-Powell algorithm of optimization. As a result of the study, we can find that the higher rainfall amount during summer is mainly due to the arrival rate of rain bands, mean number of cells per cluster potential center, and raincell intensity. However, other parameters controlling the mean number of rain cells per cluster, the cellular birth rate, and the mean cell age are found invariant to the rainfall amounts. In the application to the downstream plain area and upstream mountain area of the Han river basin, we found that the number of storms in the mountain area was estimated a little higher than that in the plain area, but the cell intensity in the mountain area a little lower than that in the plain area. Thus, in the mountain area more frequent but less intense storms can be expected due to the orographic effect, but the total amount of rainfall in a given period seems to remain the same.

• Journal of the Institute of Convergence Signal Processing
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• v.7 no.3
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• pp.116-121
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• 2006

In this paper, we propose the dimension reduction method of multi-dimension speech feature vector for real-time adaptation procedure in various noisy environments. This method which reduces dimensions non-linearly to map the likelihood of speech feature vector and noise feature vector. The LRT(Likelihood Ratio Test) is used for classifying speech and non-speech. The results of implementation are similar to multi-dimensional speech feature vector. The results of speech recognition implementation of detected speech data are also similar to multi-dimensional(10-order dimensional MFCC(Mel-Frequency Cepstral Coefficient)) speech feature vector.

• 유체기계공업학회:학술대회논문집
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• 1998.12a
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• pp.42-48
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• 1998

Numerical study is presented for the analysis of three-dimensional incompressible turbulent flows in multiblade centrifugal fan. Reynolds-averaged Navier-Stokes equations with standard k - $\epsilon$ turbulence model are transformed to non-orthogonal curvilinear coordinates, and are discretized with finite volume approximations. Linear Upwind Differencing Scheme(LUDS) is used to approximate the convection terms in the governing equations. SIMPLEC algorithm is used as a velocity-pressure correction procedure. The computational area is divided into three blocks; core, impeller and scroll, which are linked by multi-block method. The flow inside of the fan is regarded as steady flow, and mathematical formula established from the cascade theory and empirical coefficient are employed to simulate tile flow through the impeller. From comparisons between the computational results and the experimental data, the validity of the mathematical formula for the blade forces was examined and good results were obtained qualitatively. Hence, we can get the flow characteristics of multi-blade centrifugal fan and it will be a corner stone of the development of the multiblade centrifugal fan.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.6
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• pp.674-677
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• 2004

This paper deals with a systematic approach for the construction of the fixed-delay tree search (FDTS) detector in the intersymbol interference channel. The approach is based on the efficient multi-dimensional space partitioning. The Voronoi diagram (VoD) and the Delaunay tessellation (DT) of the multi-dimensional space are applied to implement the algorithm. In the proposed approach, utilizing the geometric information contained in the VOD/DT, the relative location of the observation sequence is determined which has been shown to reduce the implementation complexity. Detailed construction procedures are discussed followed by an example from the intersymbol interference communication channel.

• Journal of Advanced Marine Engineering and Technology
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• v.28 no.7
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• pp.1063-1071
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• 2004

Accurate heat release analysis of cylinder pressure data is important for evaluating performance in the development of diesel engine However, traditional single zone first law heat release model(SZM) has significant limitations due to the simplified assumption of uniform charge and neglecting local temperature inside cylinder during combustion process. In this study. heat release rate based on single zone heat release model has been evaluated by comparison with computational analysis results using Fire code which is based on multi-dimensional model(MDM). To overcome limitations due to simplicity of single zone assumption. especially the influence of specific heat ratio on gross heat release has been esteemed and newly suggested were the equation $\gamma$= $\gamma$(${T/T}_{max}$) which describes the variations of gases thermodynamic properties with mean temperature and maximum mean temperature inside cylinder Single zone heat release model applied with this equation is shown to give very good results over whole range of operating conditions when compared with computational analysis results based on multi-dimensional model.

• Journal of the Korean Society of Clothing and Textiles
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• v.22 no.3
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• pp.374-383
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• 1998

Apparel Quality was one of the most important elements to evaluate the reputations of companies and products which affect the consumer's purchasing behavior. From researches on apparel quality, there was no common concept of quality as well as no common dimensions. The purposes of this study were to identify apparel quality concept and to classify the multi-dimensional concept of apparel quality. The research was carried out in theoretical as well as empirical studies. The theoretical study was conducted to find out apparel quality concept and divide apparel quality concept into four dimensions groups. The empirical study followed the theoretical study to confirm the multi-dimensional concept of apparel quality. The empirical study was investigated that the questionnaire was administered to 634 housewives in Seoul, Kwangju, and Busan during the fall of 1996. The data were analysed by LISREL analysis. This study identified that apparel quality was characteristics of consumer's desires for apparel. The results of the theoretical study verified that apparel quality concept was organized into four different dimensions: physical attribute, physical function, instrumental performance, and expressive performance.

• Geophysics and Geophysical Exploration
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• v.7 no.1
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• pp.7-13
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• 2004

In this paper, we demonstrate that Common Mid-Point (CMP) cross-correlation gathers of multi-channel and multi-shot surface waves give accurate phase-velocity curves, and enable us to reconstruct two-dimensional (2D) velocity structures with high resolution. Data acquisition for CMP cross-correlation analysis is similar to acquisition for a 2D seismic reflection survey. Data processing seems similar to Common Depth-Point (CDP) analysis of 2D seismic reflection survey data, but differs in that the cross-correlation of the original waveform is calculated before making CMP gathers. Data processing in CMP cross-correlation analysis consists of the following four steps: First, cross-correlations are calculated for every pair of traces in each shot gather. Second, correlation traces having a common mid-point are gathered, and those traces that have equal spacing are stacked in the time domain. The resultant cross-correlation gathers resemble shot gathers and are referred to as CMP cross-correlation gathers. Third, a multi-channel analysis is applied to the CMP cross-correlation gathers for calculating phase velocities of surface waves. Finally, a 2D S-wave velocity profile is reconstructed through non-linear least squares inversion. Analyses of waveform data from numerical modelling and field observations indicate that the new method could greatly improve the accuracy and resolution of subsurface S-velocity structure, compared with conventional surface-wave methods.

• Nuclear Engineering and Technology
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• v.52 no.2
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• pp.287-295
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• 2020

Group method of data handling (GMDH) is considered one of the earliest deep learning methods. Deep learning gained additional interest in today's applications due to its capability to handle complex and high dimensional problems. In this study, multi-layer GMDH networks are used to perform uncertainty quantification (UQ) and sensitivity analysis (SA) of nuclear reactor simulations. GMDH is utilized as a surrogate/metamodel to replace high fidelity computer models with cheap-to-evaluate surrogate models, which facilitate UQ and SA tasks (e.g. variance decomposition, uncertainty propagation, etc.). GMDH performance is validated through two UQ applications in reactor simulations: (1) low dimensional input space (two-phase flow in a reactor channel), and (2) high dimensional space (8-group homogenized cross-sections). In both applications, GMDH networks show very good performance with small mean absolute and squared errors as well as high accuracy in capturing the target variance. GMDH is utilized afterward to perform UQ tasks such as variance decomposition through Sobol indices, and GMDH-based uncertainty propagation with large number of samples. GMDH performance is also compared to other surrogates including Gaussian processes and polynomial chaos expansions. The comparison shows that GMDH has competitive performance with the other methods for the low dimensional problem, and reliable performance for the high dimensional problem.

• The Journal of the Korea Contents Association
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• v.18 no.1
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• pp.222-231
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• 2018

This study aims to examine the effect of food therapy on multi-dimensional health and to suggest valuable information for diet of today's people. The participants were adults over 30 years old, living in Seoul and Gyeonggi district. To examine the effect of food therapy, the study sampled 220 questionnaire out of 230. The multi-dimensional health was measured by Huangdi Neijing's principle on food therapy. And the food therapy was measured by participants' experience, the dosage and the period of the dosage. The data has analyzed by independent sample t-test and multiple regression analysis. The results are as follows: First, the dosage and the period dosage showed significant effect on medical health. Second, no variable showed significant effect on functional health. Third, no variable showed significant effect on subjective health. Therefore, the food therapy showed significant effect on participants' medical health. The result shows that the food therapy has significant effect on people's health.