• Journal of Cadastre & Land InformatiX
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• v.47 no.1
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• pp.143-160
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• 2017

Since officially assessed land price system was introduced, it has functioned as the criterion for establishing and implementing real estate policies. However, there is a controversial issue about the adequacy of the officially assessed land price system. The problem is that it is difficult to establish a statistical model due to too many land characteristics. Also, local economy, macroeconomic environments and development plans are not reflected in the land price evaluation model. Considering longitudinal and cross-sectional variables, a two-way error component panel model was used in this study. This analysis model includes variables reflecting land characteristics, macroeconomic volatility, and development project. The Paju LCD Industrial Complex was selected as a analysis area and an empirical analysis was performed. According to the analysis, the number of significant land characteristic variables were 14(31%) under 5% significance level. Macroeconomic volatility has had an influence on the land price and year variable reflecting development project has consistently been significant since the industrial complex was designated. Therefore, this study suggests that the land price evaluation model should be improved by simplifying land characteristic variables and including macroeconomic and regional economic variables.

• The Journal of the Acoustical Society of Korea
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• v.7 no.4
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• pp.54-76
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• 1988

In Part Ⅰ of the paper, we have developed various block least mean-square (BLMS) adaptive digital filters (ADF's) based on a unified matrix treatment. In Part Ⅱ we analyze the convergence behaviors of the self-orthogonalizing frequency-domain BLMS (FBLMS) ADF and the unconstrained FBLMS (UFBLMS) ADF both for the overlap-save and overlap-add sectioning methods. We first show that, unlike the FBLMS ADF with a constant convergence factor, the convergence behavior of the self-orthogonalizing FBLMS ADF is governed by the same autocorrelation matrix as that of the UFBLMS ADF. We then show that the optimum solution of the UFBLMS ADF is the same as that of the constrained FBLMS ADF when the filter length is sufficiently long. The mean of the weight vector of the UFBLMS ADF is also shown to converge to the optimum Wiener weight vector under a proper condition. However, the steady-state mean-squared error(MSE) of the UFBLMS ADF turns out to be slightly worse than that of the constrained algorithm if the same convergence constant is used in both cases. On the other hand, when the filter length is not sufficiently long, while the constrained FBLMS ADF yields poor performance, the performance of the UFBLMS ADF can be improved to some extent by utilizing its extended filter-length capability. As for the self-orthogonalizing FBLMS ADF, we study how we can approximate the autocorrelation matrix by a diagonal matrix in the frequency domain. We also analyze the steady-state MSE's of the self-orthogonalizing FBLMS ADF's with and without the constant. Finally, we present various simulation results to verify our analytical results.

• The Journal of Society for e-Business Studies
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• v.22 no.1
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• pp.1-13
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• 2017

Though digital imaging devices such as smart phones, digital cameras and office scanners have improved significantly over the past years, they are seldom used for industrial application. This may be attributable to high level of quality and performance requirement for industrial application, but there lacks a test or an objective evaluation whether the upgraded performance of entry-level device is sufficiently enough to replace existing industrial equipments or not. If there exists an industrial application area where the applicability of entry-level equipment is proved by some objective tests, then companies will be able to reduce investment on expensive industrial equipment. In this study, applicability of entry-level digital devices for color difference discrimination of PVC (Polyvinyl chloride) color sheet is tested. By testing smart phone, digital camera, and office scanner for color difference discrimination, authors have found that office scanner shows consistent result with less measurement error. Additional experiment on comparing office scanner with industrial spectrophotometer has confirmed that there exists high correlation between the two devices' results. Based on this result, office scanner may be applicable to discriminate the color difference of PVC sheet instead of expensive industrial spectrophotometer if proper management criteria are established.

• Survey Research
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• v.10 no.3
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• pp.1-19
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• 2009

This study investigates the utilities of spatial analysis in the context of survey research using Geographical Information System(GIS) and Geographically Weighted Regression (GWR) which take account of spatial heterogeneity. Many social phenomena involve spatial dimension, and with the development of GIS, GPS receiver, and online location-based services, spatial information can be collected and utilized more easily, and thus application of spatial analysis in the survey research is getting easier. The traditional OLS regression models which assume independence of observations and homoscedasticity of errors cannot handle spatial dependence problem. GWR is a spatial analysis technique which utilizes spatial information as well as attribute information, and estimated using geographically weighted function under the assumption that spatially close cases are more related than distant cases. Residential survey data from a Primary Autonomous District are used to estimate a model of public service satisfaction. The findings show that GWR handles the problem of spatial auto-correlation and increases goodness-of-fit of model. Visualization of spatial variance of effects of the independent variables using GIS allows us to investigate effects and relationships of those variables more closely and extensively. Furthermore, GIS and GWR analyses provide us a more effective way of identifying locations where the effect of variable is exceptionally low or high, and thus finding policy implications for social development.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.12
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• pp.256-264
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• 2012

The directional algebraic reconstruction technique (DART) using the trigonometric current pattern is one of the image reconstruction algorithms in electrical impedance tomography (EIT). This method needs to compute resistances between electrode pairs as using relation between the injected currents and measured voltages for the reconstruction of the inner image. The delay time is incurred in this process. Therefore this paper proposes modified directional algebraic reconstruction technique (mDART) using the adjacent current pattern instead of the trigonometric current pattern to solve the delay time for initial resistance values. The proposed method uses measured voltages instead of computed resistances in the reconstruction algorithm. Hence this method can eliminate the delay time because it does not use the resistances. In conclusion, the proposed method improves image quality and image reconstruction time by using the adjacent current pattern. To prove performance of the proposed method, we carried on computer simulation of various cases.

• Journal of Korean Tunnelling and Underground Space Association
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• v.17 no.4
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• pp.457-471
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• 2015

A domestic cutterhead with the diameter of 3.6 m was designed and manufactured in this study. Then, it was attached to an existing earth-pressure balanced shield TBM to excavate a cable tunnel with the length of 1,275 m. Especially, the procedures for TBM cutterhead design and its corresponding performance prediction were also summarized. From field data analyses of the refurbished shield TBM, its maximum advance rate was recorded as 14.4 m/day. Penetration depths of disc cutters were found to be approximately 4 mm/rev, which is equal to the maximum penetration depth designed for the strongest rock strength condition in the target tunnel. Every TBM operating thrust and cutter normal force during TBM driving was much smaller than their corresponding maximum capacities. When cutter acting forces recorded in the field were analyzed, their prediction errors by the CSM model were very high for weak rock conditions. In addition, rock strength showed very close relationships with cutter normal force and penetration depth.

• Journal of the HCI Society of Korea
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• v.1 no.1
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• pp.53-61
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• 2006

In this paper, we propose a novel method for 3D reconstruction of an indoor scene using a multi-view camera. Until now, numerous disparity estimation algorithms have been developed with their own pros and cons. Thus, we may be given various sorts of depth images. In this paper, we deal with the generation of a 3D surface using several 3D point clouds acquired from a generic multi-view camera. Firstly, a 3D point cloud is estimated based on spatio-temporal property of several 3D point clouds. Secondly, the evaluated 3D point clouds, acquired from two viewpoints, are projected onto the same image plane to find correspondences, and registration is conducted through minimizing errors. Finally, a surface is created by fine-tuning 3D coordinates of point clouds, acquired from several viewpoints. The proposed method reduces the computational complexity by searching for corresponding points in 2D image plane, and is carried out effectively even if the precision of 3D point cloud is relatively low by exploiting the correlation with the neighborhood. Furthermore, it is possible to reconstruct an indoor environment by depth and color images on several position by using the multi-view camera. The reconstructed model can be adopted for interaction with as well as navigation in a virtual environment, and Mediated Reality (MR) applications.

• Journal of the Korean Geotechnical Society
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• v.20 no.8
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• pp.77-87
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• 2004

In this paper a back-propagation neural network model is developed to estimate the preconsolidation pressure of Korean soft soils based on 176 oedometer tests and 63 piezocone test results, which were compiled from 11 sites - western and southern parts of Korea. Only 147 data were used for the training of the neural network and 29 data, which were not used during the training phase, were used for the verification of trained network. Empirical and theoretical models were compared with the developed neural network model. A simple 4-4-9-1 multi-layered neural network has been developed. The cone tip resistance $q_T$ penetration pore pressure $u_2$, total overburden pressure $\sigma_{vo}$ and effective overburden pressure $\sigma'_{vo}$ were selected as input variables. The developed neural network model was validated by comparing the prediction results of the proposed neural network model for the new data which were not used for the training of the model with the measured preconsolidation pressures. It can also predict more precise and reliable preconsolidation pressures than the analytical and empirical model. Furthermore, it can be carefully concluded that neural network model can be used as a generalized model for prediction of preconsolidation pressure throughout Korea since developed model shows good performance for the new data which were not used in both training and testing data.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.12
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• pp.644-649
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• 2017

In the automobile industry, there is growing demand for lightweight vehicles due to environmental problems and rising oil prices. Therefore, aluminum alloys and special materials are being used to reduce the weight of vehicles, but there are still many difficulties to overcome in terms of cost and strength. Therefore, the application of advanced high strength steel (AHSS)is increasing. AHSS has good strength and formability.Safety regulations are becoming stricter, and 1.2-GPa super-high-strength steels are gradually being applied for the center pillar and roof rails. Thus, the application of different kinds of steels in automobile bodiesis also increasing gradually. This study evaluates the resistance point weldability and the characteristics of a welded part of SGAFC1180 1.2t steel. A simulation was used to observe the nugget formation and its growth behavior. The prediction performance showed a similar tendency within an error rate of 10%. Also, the effect of this behavior on the process resistance and dynamic resistance was investigated,along with the correlation between the shear tensile strength and nugget diameter.

• Analytical Science and Technology
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• v.23 no.3
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• pp.304-311
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• 2010

Near Infrared Spectroscopy (NIRs) has been applied for rapid and nondestructive paper measurement by replacing the current destructive method to the property of paper. Current standard methods for the property of paper were pH, moisture, breaking length, and folding endurance, which data were compared with spectrum of FT-NIR spectrometer. Various paper products such as copy, envelope, white, newspaper, as well as old paper produced around 1960~1980 were used as the sample. The correlation ($R^2$) and standard error of prediction (SEP) results for breaking length, folding endurance, moisture and pH are $R^2$=0.914, SEP=0.508, $R^2$=0.926, SEP=0.281, $R^2$=0.941, SEP=0.931, pH $R^2$=0.949, SEP= -0.0631, respectively. This result show that NIRs can be applied to practical application for nondestructive analysis of paper records materials.