• The Journal of Korean Institute of Communications and Information Sciences
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• v.37B no.11
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• pp.1050-1057
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• 2012

Super Wi-Fi is a newly emerging wireless Internet technology, which constitutes Wi-Fi networks using TV white space. A key technical challenge in the Super Wi-Fi applications is how to provide a seamless Internet service even when a Super WiFi user should give up the channel in use to the active incumbent user which is activated in the same service area, preventing from the service continuity in Super Wi-Fi. In this paper, we propose a channel handover method to support service continuity of Super Wi-Fi, in which an AP selects a new operational channel and provides the channel information for MSs. Therefore, the AP and the MSs can carry out seamless handover for Super Wi-Fi service. A performance evaluation shows that the proposed scheme is superior to the conventional Wi-Fi in channel mobility delay.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.49 no.5
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• pp.59-65
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• 2012

In this paper, we investigate the compressed sensing (CS) algorithms for modeling a super-resolution near-field structure (super-RENS) disc system with a sparse Volterra filter. It is well known that the super-RENS disc system has severe nonlinear inter-symbol interference (ISI). A nonlinear system with memory can be well described with the Volterra series. Furthermore, CS can restore sparse or compressed signals from measurements. For these reasons, we employ the CS algorithms to estimate a sparse super-RENS read-out channel. The evaluation results show that the CS algorithms can efficiently construct a sparse Volterra model for the super-RENS read-out channel.

• Journal of Information Processing Systems
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• v.18 no.1
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• pp.12-25
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• 2022

In recent years, deep convolutional neural networks have made significant progress in the research of single image super-resolution. However, it is difficult to be applied in practical computing terminals or embedded devices due to a large number of parameters and computational effort. To balance these problems, we propose CSRNet, a lightweight neural network based on channel split residual learning structure, to reconstruct highresolution images from low-resolution images. Lightweight refers to designing a neural network with fewer parameters and a simplified structure for lower memory consumption and faster inference speed. At the same time, it is ensured that the performance of recovering high-resolution images is not degraded. In CSRNet, we reduce the parameters and computation by channel split residual learning. Simultaneously, we propose a double-upsampling network structure to improve the performance of the lightweight super-resolution network and make it easy to train. Finally, we propose a new evaluation metric for the lightweight approaches named 100_FPS. Experiments show that our proposed CSRNet not only speeds up the inference of the neural network and reduces memory consumption, but also performs well on single image super-resolution.

• Journal of the Korea Convergence Society
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• v.11 no.12
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• pp.15-22
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• 2020

In this paper, we proposed a deep learning based super-resolution method that combines Channel Attention and Spatial Attention feature enhancement methods. It is important to restore high-frequency components, such as texture and features, that have large changes in surrounding pixels during super-resolution processing. We proposed a super-resolution method using feature enhancement that combines Channel Attention and Spatial Attention. The existing CNN (Convolutional Neural Network) based super-resolution method has difficulty in deep network learning and lacks emphasis on high frequency components, resulting in blurry contours and distortion. In order to solve the problem, we used an emphasis block that combines Channel Attention and Spatial Attention to which Skip Connection was applied, and a Residual Block. The emphasized feature map extracted by the method was extended through Sub-pixel Convolution to obtain the super resolution. As a result, about PSNR improved by 5%, SSIM improved by 3% compared with the conventional SRCNN, and by comparison with VDSR, about PSNR improved by 2% and SSIM improved by 1%.

• Journal of the Optical Society of Korea
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• v.19 no.4
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• pp.334-339
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• 2015

Terabit-per-second (Tb/s) transmission capacity for the next generation of long-haul communication networks can be achieved using multicarrier optical super-channel technology. In an elastic orthogonal frequency division multiplexing (OFDM) super-channel transmission system, demultiplexing a portion of an entire spectrum in the form of a subband with minimum power is critically required. A major obstacle to achieving this goal is the analog-to-digital converter (ADC), which is power-hungry and extremely expensive. Without a proper ADC that can work with low power, it is unrealistic to design a 100G coherent receiver suitable for a commercially deployable optical network. Discrete Fourier transform (DFT) is often seen as a primary technique for understanding partial demultiplexing, which can be attained either optically or electronically. If fairly comparable performance can be achieved with an all-optical DFT circuit, then a solution independent of data rate and modulation format can be obtained. In this paper, we investigate two distinct OFDM super-channel receiver models, based on electronic and all-optical DFT-technologies, for partial carrier demultiplexing in a multi-Tb/s transmission system. The performance comparison of the receivers is discussed in terms of bit-error-rate (BER) performance.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.5
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• pp.70-75
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• 2014

Super-resolution near-field structure (super-RENS) read-out samples are affected by a nonlinear and noncausal channel, which results in inter-symbol interference (ISI). In this study, we investigate asymmetry or domain bloom in super-RENS in terms of equalization. Domain bloom is caused by writing process in optical recording. We assume in this work that the asymmetry symbol conversion scheme is to generate asymmetric symbols, and then a linear finite impulse response filter can model the read-out channel. For equalizing this overall nonlinear channel, the read-out signals are deconvolved with the finite impulse response filter and its output is decided based on the decision rule table that is developed from the asymmetry symbol conversion scheme. The proposed equalizer is investigated with the simulations and the real super-RENS samples in terms of raw bit error rate.

• 한국전산유체공학회:학술대회논문집
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• 2008.03b
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• pp.671-674
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• 2008

We investigate the slippage effect in a micro-channel depending on the surface characteristics; hydrophilic, hydrophobic, and super-hydrophobic wettabilities. The micro-scale grooves are fabricated on the vertical wall to make the super-hydrophobic surfaces, which enable us visualize the flow fields near walls and directly measure the slip length. Velocity profiles are measured using micro-particle image velocimetry (Micro-PIV) and compared those in the hydrophilic glass, hydrophobic PDMS, and super-hydrophobic PDMS micro-channels. To directly measure the velocity in the super-hydrophobic micro-channel, the transverse groove structures are fabricated on the vertical wall in the micro-channel. The velocity profile near the wall shows larger slip length and, if the groove structure is high and wide, the liquid meniscus forms curves into the valley so that the wavy flow is created after the grooves.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.5
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• pp.120-124
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• 2017

The temporal super resolution is a method for increasing the frame rate. Electro-optical sensors are used in various surveillance and reconnaissance weapons systems, and the spatial resolution and temporal resolution of the required electro-optical sensors vary according to the performance requirement of each weapon system. Because most image sensors capture images at 30~60 frames/second, it is necessary to increase the frame rate when the target moves and changes rapidly. This paper proposes a method to increase the frame rate using color channel extrapolation. Using a DMD, one frame of a general camera was adjusted to have different consecutive exposure times for each channel, and the captured image was converted to a single channel image with an increased frame rate. Using the optical flow method, a virtual channel image was generated for each channel, and a single channel image with an increased frame rate was converted to a color channel image. The performance of the proposed temporal super resolution method was confirmed by the simulation.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.26 no.3
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• pp.305-310
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• 2015

In this paper, a wireless spectrum sensing receiver system is proposed. While a conventional Cognitive Radio(CR) system utilizes frequency down-conversion and demodulation to recognize wireless spectral signal, the proposed one is able to recover and sense valid signal at an RF front-end. It has been designed with a super-regeneration type circuit with a channel selectivity and variability for FDM applications with which a conventional single-channel super-regeneration circuit could not provide. From experimental evaluation, the implemented system has been optimized for channel allocation with quenching signal, and verified for 5 MHz-channel spacing.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.19 no.1
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• pp.33-39
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• 1983

Tidal exchange of sea water was studied by using drogue experiments and tidal current measurement data in Yeoja Bay which has a narrow channel. At the spring tide, the volume of tidal transport in the bay was estimated to be 43% of the mean volume of the sea water in Yeoja Bay, 1.96km super(3). Residual current was deduced to flow southward at the rate of 3,658$\times$10 super(4) m super(3) per tidal cycle. The mean tidal exchange of sea water during the flood flow was estimated to be approximately 5.0% of the volume of sea water at the mean high water level in the bay, 2.33km super(3), while that during the ebb flow was 6.3%. One dimensional diffusion coefficient of 1.69-1.97$\times$10 super(6) cm super(2)/sec was obtained at the channel in the bay.