• Journal of Korean Association for Spatial Structures
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• v.6 no.3 s.21
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• pp.77-86
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• 2006

The stress analysis of cold-formed channel section steel beams under transverse load is presented. The local buckling as well as the lateral buckling effects are included in the analysis. The analytical model is developed based on the thin-walled beam theory, and a one-dimensional finite element model is formulated to solve the analytical model. Numerical results are compared with AISI code. It shows that the proposed model is appropriate for predicting of stress as well as deflection of the cold-formed channel section beam.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.7
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• pp.22-30
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• 2015

For long-term evolution (LTE) MIMO transmission, codebooks are used to utilize the estimated channel information under the limited feedeback environment, and related study has been actively performed. Existing codebooks include codevectos constructed based on vector quantization (VQ) and discrete Fourier transform (DFT), and the LTE standard specifies codebooks modified from these examples to support up to 8 transmit antennas. As the number of antennas increases and as the spatial channel model is used as a standard environment to evaluate the LTE transmission performance, new beamforming methods as well as codebook designs are needed. In this paper, we implement the 3-dimensional spatial channel model (3D-SCM) to analyze the key statistical characteristics of the generated channel, and present efficient ways of determining corresponding codebooks. In particular, we propose a nonuniform-phase DFT-based codebook to improve the existing uniform-phase DFT-based codebook, and evaluate its performance under the given SCM transmission environment. There exists a strong tendancy in statistical distributions of the phase difference between adjacent antenna elements for the SCM, which can be appropriately exploited in codebook design to produce a performance gain over the existing design.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.1
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• pp.60-79
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• 2022

The U-Net architecture-based segmentation models attained remarkable performance in numerous medical image segmentation missions like skin lesion segmentation. Nevertheless, the resolution gradually decreases and the loss of spatial information increases with deeper network. The fusion of adjacent layers is not enough to make up for the lost spatial information, thus resulting in errors of segmentation boundary so as to decline the accuracy of segmentation. To tackle the issue, we propose a new deep learning-based segmentation model. In the decoding stage, the feature channels of each decoding unit are concatenated with all the feature channels of the upper coding unit. Which is done in order to ensure the segmentation effect by integrating spatial and semantic information, and promotes the robustness and generalization of our model by combining the atrous spatial pyramid pooling (ASPP) module and channel attention module (CAM). Extensive experiments on ISIC2016 and ISIC2017 common datasets proved that our model implements well and outperforms compared segmentation models for skin lesion segmentation.

• Korean Journal of Remote Sensing
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• v.17 no.4
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• pp.335-344
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• 2001

Texture is extensively studied in a variety of image processing applications such as image segmentation and classification because it is an important property to perceive regions and surfaces. This paper focused on the analysis and synthesis of textured single and multiband images using Markov Random Field model considering the existent spatial correlation. Especially, for multiband images, the cross-channel correlation existing between bands as well as the spatial correlation within band should be considered in the model. Although a local interaction is assumed between the specified neighboring pixels in MRF models, during the maximization process, short-term correlations among neighboring pixels develop into long-term correlations. This result in exhibiting phase transition. In this research, the role of temperature to obtain the most probable state during the sampling procedure in discrete Markov Random Fields and the stopping rule were also studied.

• ETRI Journal
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• v.39 no.2
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• pp.234-244
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• 2017

Research interest in three-dimensional multiple-input multiple-output (3D-MIMO) beamforming has rapidly increased on account of its potential to support high data rates through an array of strategies, including sector or user-specific elevation beamforming and cell-splitting. To evaluate the full performance benefits of 3D and full-dimensional (FD) MIMO beamforming, the 3D character of the real MIMO channel must be modeled with consideration of both the azimuth and elevation domain. Most existing works on the 2D spatial channel model (2D-SCM) assume a wide range for the distribution of elevation angles of departure (eAoDs), which is not practical according to field measurements. In this paper, an optimal FD-MIMO planar array configuration is presented for different practical channel conditions by restricting the eAoDs to a finite range. Using a dynamic network level simulator that employs a complete 3D SCM, we analyze the relationship between the angular spread and sum throughput. In addition, we present an analysis on the optimal antenna configurations for the channels under consideration.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.11C
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• pp.860-867
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• 2008

In this paper, we explain differences between SCM and extended SCM(SCME), and investigate how these channel models affects MIMO system level performance. System level simulation is performed according to the number of users and drifting-time intervals with SCM and SCME, respectively. The performance of SCME is slightly better than SCM since mid-paths and the drifting-time in SCME causes more fluctuations in MIMO channels.

• Journal of Communications and Networks
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• v.18 no.1
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• pp.95-104
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• 2016

Massive multiple-input multiple-output (MIMO) is a promising approach for cellular communication due to its energy efficiency and high achievable data rate. These advantages, however, can be realized only when channel state information (CSI) is available at the transmitter. Since there are many antennas, CSI is too large to feed back without compression. To compress CSI, prior work has applied compressive sensing (CS) techniques and the fact that CSI can be sparsified. The adopted sparsifying bases fail, however, to reflect the spatial correlation and channel conditions or to be feasible in practice. In this paper, we propose a new sparsifying basis that reflects the long-term characteristics of the channel, and needs no change as long as the spatial correlation model does not change. We propose a new reconstruction algorithm for CS, and also suggest dimensionality reduction as a compression method. To feed back compressed CSI in practice, we propose a new codebook for the compressed channel quantization assuming no other-cell interference. Numerical results confirm that the proposed channel feedback mechanisms show better performance in point-to-point (single-user) and point-to-multi-point (multi-user) scenarios.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.3A
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• pp.233-239
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• 2004

The capacity and the performance of the spatial filtering system depends on the spatial properties of wireless vector channel. In this paper, we have analyzed the wireless vector channel characteristics in the dense urban area using the data collected from the real environments. After analyzing the measurement data, it has been found out that the signals were received mainly from only a few directions (such as roads or commercial buildings) even if mobile users are randomly distributed in a cell. Moreover, the DOA(Direction-of-Arrival) of a received signal may not change continuously while a mobile is moving, it may jump from one direction to the other direction with fading.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.7
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• pp.434-441
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• 2003

This paper proposes a new quantitative and objective image quality metric which is essential to verify the performance of block-based DCT image coding. The proposed metric considers not only global distortion of coded image such as spatial frequency sensitivity and channel masking using HVS based multi-channel model, but also structural distortions caused block-based coding. The experimental results show a strong correlation between proposed metric and subjective metric.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.52 no.7
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• pp.434-434
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• 2003

This paper proposes a new quantitative and objective image quality metric which is essential to verify the performance of block-based DCT image coding The proposed metric considers not only global distortion of coded image such as spatial frequency sensitivity and channel masking using HVS based multi-channel model, but also structural distortions caused block-based coding. The experimental results show a strong correlation between propose(B metric and subjective metric.