• The Bulletin of The Korean Astronomical Society
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• v.37 no.2
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• pp.234.2-234.2
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• 2012

As the accuracy in the measurement of cosmological parameters is ever-increasing in this era of precision cosmology, astrophysical constraints on high-redshift universe is also getting tighter. Three dimensional (3D) tomography of the high-redshift (z>~7) universe is expected to be made through the next-generation radio telescopes including various SKA pathfinders and SKA itself, which calls for extensive theoretical predictions. We present our new simulations of cosmic reionization covering the full dynamic range of radiation sources, and also the mock data for the (1) large-scale CMB polarization anisotropy for Planck mission, (2) small-scale, kinetic Sunyaev-Zel'dovich effect for South Pole Telescope project, and (3) 21-cm observations. We show that the new constraints on CMB from Planck will constrain the models of reionization significantly, which then should be tested by 3D tomography of high-redshift universe through the 21-cm observations by future radio telescopes.

• Proceeding of Spring/Autumn Annual Conference of KHA
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• 2008.11a
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• pp.442-447
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• 2008

With the advances in the high-tech knowledge and service industries, along with a high-flying economy, the industrial structures of many cities have changed. The subject of the successful cases of dimensional integrated complexes in Roppongi Hills, the actions and preferences of these complexes'users were surveyed and analyzed in this study to determine the factors that contribute to the success or failure of such development projects. The results of the survey that was conducted in this study regarding the satisfaction of the residents of Roppongi Hills with such complexes will be considered in the formulation of a construction plan and will be used as base data for designing a large-scale dimensional integrated complex in Korea.

• Proceedings of the KSME Conference
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• 2000.04b
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• pp.661-666
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• 2000

Near-wake flow field of a circular cylinder is studied by means of a cinematic PIV system with high sampling rate and large internal memory block. Experiments are conducted in a closed-cycle water tunnel system and a cross-correlation algorithm in conjunction with FFT (Fast Fourier Transform) analysis and an offset correlation technique is used for vector processing. With the help of very high sampling frequency compared to the shedding frequency, it is possible to obtain phase-averaged information of the three-dimensional wake, even though the shedding is not forced but natural. Phase-locked vortical structures observed simultaneously from the spanwise and cross-stream planes are displayed in the wake-transition regime where fine-scale secondary vortices have a spanwise wavelength or around one diameter. Spatial relations and temporal evolutions of the primary Karman vortex and the secondary vortex are also discussed schematically.

• Nuclear Engineering and Technology
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• v.53 no.10
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• pp.3207-3216
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• 2021

Three-dimensional structures of a vortical flow field and heat transfer characteristics in a partially blocked 7-pin fuel assembly mock-up of sodium-cooled fast reactor have been investigated through a numerical analysis using a commercial computational fluid dynamics code, ANSYS CFX. The simulation with the SST turbulence model agrees well with the experimental data of outlet and cladding wall temperatures. From the analysis on the limiting streamline at the wall, multi-scale vortexes developed in axial direction were found around the blockage. The vortex core has a high cladding wall temperature, and the attachment line has a low cladding wall temperature. The small-scale vortex structures significantly enhance the convective heat transfer because it increases the turbulent mixing and the turbulence kinetic energy. The large-scale vortex structures supply thermal energy near the heated cladding wall surface. It is expected that control of the vortex structures in the fuel assembly plays a significant role in the convective heat transfer enhancement. Furthermore, the blockage plate and grid spacer increase the pressure drop to about 36% compared to the bare case.

• Smart Structures and Systems
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• v.10 no.4_5
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• pp.411-426
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• 2012

The Canton Tower (formerly named Guangzhou New TV Tower) of 610 m high has been instrumented with a long-term structural health monitoring (SHM) system consisting of over 700 sensors of sixteen types. Under the auspices of the Asian-Pacific Network of Centers for Research in Smart Structures Technology (ANCRiSST), an SHM benchmark problem for high-rise structures has been developed by taking the instrumented Canton Tower as a host structure. This benchmark problem aims to provide an international platform for direct comparison of various SHM-related methodologies and algorithms with the use of real-world monitoring data from a large-scale structure, and to narrow the gap that currently exists between the research and the practice of SHM. This paper first briefs the SHM system deployed on the Canton Tower, and the development of an elaborate three-dimensional (3D) full-scale finite element model (FEM) and the validation of the model using the measured modal data of the structure. In succession comes the formulation of an equivalent reduced-order FEM which is developed specifically for the benchmark study. The reduced-order FEM, which comprises 37 beam elements and a total of 185 degrees-of-freedom (DOFs), has been elaborately tuned to coincide well with the full-scale FEM in terms of both modal frequencies and mode shapes. The field measurement data (including those obtained from 20 accelerometers, one anemometer and one temperature sensor) from the Canton Tower, which are available for the benchmark study, are subsequently presented together with a description of the sensor deployment locations and the sensor specifications.

• Journal of the Korean Institute of Rural Architecture
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• v.23 no.4
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• pp.1-12
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• 2021

Recently, the use of unmanned aerial vehicles (UAVs) is increasing in the field of land information acquisition and terrain exploration through high-altitude aerial photography. High-altitude aerial photography is suitable for large-scale geographic information collection, but has the disadvantage that it is difficult to accurately collect small-scale geographic information. Therefore, this study used low-altitude UAV to monitor changes in small rural spaces around rural resources, and the results are as follows. First, the low-altitude aerial imagery had a very high spatial resolution, so it was effective in reading and analyzing topographic features. Second, an area with a large number of aerial images and a complex topography had a large amount of point clouds to be extracted, and the number of point clouds affects the three-dimensional quality of rural space. Third, 3D mapping technology using point cloud is effective for monitoring rural space and rural resources because it enables observation and comparison of parts that cannot be read from general aerial images. In this study, the possibility of rural space analysis of low-altitude UAV was verified through aerial photography and analysis, and the effect of 3D mapping on rural space monitoring was visually analyzed. If data acquired by low-altitude UAV are used in various forms such as GIS analysis and topographic map production it is expected to be used as basic data for rural planning to maintain and preserve the rural environment.

• Industrial Engineering and Management Systems
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• v.13 no.4
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• pp.454-462
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• 2014

Retention of possible churning customer is one of the most important issues in customer relationship management, so companies try to predict churn customers using their large-scale high-dimensional data. This study focuses on dealing with large data sets by reducing the dimensionality. By using six different dimension reduction methods-Principal Component Analysis (PCA), factor analysis (FA), locally linear embedding (LLE), local tangent space alignment (LTSA), locally preserving projections (LPP), and deep auto-encoder-our experiments apply each dimension reduction method to the training data, build a classification model using the mapped data and then measure the performance using hit rate to compare the dimension reduction methods. In the result, PCA shows good performance despite its simplicity, and the deep auto-encoder gives the best overall performance. These results can be explained by the characteristics of the churn prediction data that is highly correlated and overlapped over the classes. We also proposed a simple out-of-sample extension method for the nonlinear dimension reduction methods, LLE and LTSA, utilizing the characteristic of the data.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1999.04a
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• pp.50-57
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• 1999

Structural analysis of large-scale structures involving large amount of computational load and data storage requires high-performance computing resources. We have previously developed PC-level distributed structural analysis algorithms based on substructuring technique where each personal computer assigned to a slave node has been involved in the computations for single substructures. Recently, it has been proved by the authors that the performance of distributed structural analysis algorithm can be further enhanced by changing substructuring schemes. Therefore a new distributed structural analysis algorithm with one PC to multiple substructures scheme is presented in this paper. The algorithm is implemented on the network of multiple personal computers and applied to structural analysis of two dimensional frame structures.

• The Korean Journal of Applied Statistics
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• v.35 no.2
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• pp.217-227
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• 2022

Quantile regression is widely used in many fields based on the advantage of providing an efficient tool for examining complex information latent in variables. However, modern large-scale and high-dimensional data makes it very difficult to estimate the quantile regression model due to limitations in terms of computation time and storage space. Divide-and-conquer is a technique that divide the entire data into several sub-datasets that are easy to calculate and then reconstruct the estimates of the entire data using only the summary statistics in each sub-datasets. In this paper, we studied on a variable selection method using Bayes information criteria by applying the divide-and-conquer technique to the penalized quantile regression. When the number of sub-datasets is properly selected, the proposed method is efficient in terms of computational speed, providing consistent results in terms of variable selection as long as classical quantile regression estimates calculated with the entire data. The advantages of the proposed method were confirmed through simulation data and real data analysis.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.4
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• pp.1368-1389
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• 2014

Three-dimensional multiple-input multiple-output (3D MIMO) and large-scale MIMO are two promising technologies for upcoming high data rate wireless communications, since the inter-user interference can be reduced by exploiting antenna vertical gain and degree of freedom, respectively. In this paper, we derive the achievable sum rate of 3D MIMO systems employing zero-forcing (ZF) receivers, accounting for log-normal shadowing fading, path-loss and antenna gain. In particular, we consider the prevalent log-normal model and propose a novel closed-form lower bound on the achievable sum rate exploiting elevation features. Using the lower bound as a starting point, we pursue the "large-system" analysis and derive a closed-form expression when the number of antennas grows large for fixed average transmit power and fixed total transmit power schemes. We further model a high-building with several floors. Due to the floor height, different floors correspond to different elevation angles. Therefore, the asymptotic achievable sum rate performances for each floor and the whole building considering the elevation features are analyzed and the effects of tilt angle and user distribution for both horizontal and vertical dimensions are discussed. Finally, the relationship between the achievable sum rate and the number of users is investigated and the optimal number of users to maximize the sum rate performance is determined.