• Title/Summary/Keyword: Block-noise

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Case Study for Ship Ad-hoc Networks under a Maritime Channel Model in Coastline Areas

  • Su, Xin;Yu, HaiFeng;Chang, KyungHi;Kim, Seung-Geun;Lim, Yong-Kon
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.9 no.10
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    • pp.4002-4014
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    • 2015
  • ITU-R M.1842-1, as a well-known specification dedicated to maritime mobile applications, has standardized wireless transmission protocols according to the particular characteristics of a maritime communications scenario. A time division multiple access (TDMA) frame structure, along with modulation schemes to achieve a high data rate, has been described clearly in ITU-R M.1842-1. However, several specification items are still under "to be decided" status, which brings ambiguity to research works. In addition, the current version of ITU-R M.1842-1 is focused mainly on maritime transmissions in open-sea areas, where the cyclic prefix (CP) is set to zero and only 16-QAM is used in the multi-carrier (MC) system. System performance might be dramatically degraded in coastline areas due to the inter-symbol interference (ISI) caused by selective fading. This is because there is a higher probability that the signal will be reflected by obstacles in coastline areas. In this paper, we introduce the transmission resource block (TRB) dedicated to ITU-R M.1842-1 for a ship ad-hoc network (SANET), where the pilot pattern of TRB is based on the terrestrial trunked radio (TETRA). After that, we evaluated SANET performance under the maritime channel model in a coastline area. In order to avoid noise amplification and to overcome the ISI caused by selective fading, several strategies are suggested and compared in the channel estimation and equalization procedures, where the link-level simulation results finally validate our proposals.

CA Joint Resource Allocation Algorithm Based on QoE Weight

  • LIU, Jun-Xia;JIA, Zhen-Hong
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.5
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    • pp.2233-2252
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    • 2018
  • For the problem of cross-layer joint resource allocation (JRA) in the Long-Term Evolution (LTE)-Advanced standard using carrier aggregation (CA) technology, it is difficult to obtain the optimal resource allocation scheme. This paper proposes a joint resource allocation algorithm based on the weights of user's average quality of experience (JRA-WQOE). In contrast to prevalent algorithms, the proposed method can satisfy the carrier aggregation abilities of different users and consider user fairness. An optimization model is established by considering the user quality of experience (QoE) with the aim of maximizing the total user rate. In this model, user QoE is quantified by the mean opinion score (MOS) model, where the average MOS value of users is defined as the weight factor of the optimization model. The JRA-WQOE algorithm consists of the iteration of two algorithms, a component carrier (CC) and resource block (RB) allocation algorithm called DABC-CCRBA and a subgradient power allocation algorithm called SPA. The former is used to dynamically allocate CC and RB for users with different carrier aggregation capacities, and the latter, which is based on the Lagrangian dual method, is used to optimize the power allocation process. Simulation results showed that the proposed JRA-WQOE algorithm has low computational complexity and fast convergence. Compared with existing algorithms, it affords obvious advantages such as improving the average throughput and fairness to users. With varying numbers of users and signal-to-noise ratios (SNRs), the proposed algorithm achieved higher average QoE values than prevalent algorithms.

Design of a Wide Tuning Range DCO for Mobile-DTV Applications (Mobile-DTV 응용을 위한 광대역 DCO 설계)

  • Song, Sung-Gun;Park, Sung-Mo
    • Journal of Korea Multimedia Society
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    • v.14 no.5
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    • pp.614-621
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    • 2011
  • This paper presents design of a wide tuning range digitally controlled oscillator(DCO) for Mobile-DTV applications. DCO is the key element of the ADPLL block that generates oscillation frequencies. We proposed a binary delay chain(BDC) structure, for wide tuning range DCO, modifying conventional fixed delay chain. The proposed structure generates oscillation frequencies by delay cell combination which has a variable delay time of $2^i$ in the range of $0{\leq}i{\leq}n-1$. The BOC structure can reduce the number of delay cells because it make possible to select delay cell and resolution. We simulated the proposed DCO by Cadence's Spectre RF tool in 1.8V chartered $0.18{\mu}m$ CMOS process. The simulation results showed 77MHz~2.07GHz frequency range and 3ps resolution. The phase noise yields -101dBc/Hz@1MHz at Mobile-DTV maximum frequency 1675MHz and the power consumption is 5.87mW. The proposed DCO satisfies Mobile-DTV standards such as ATSC-M/H, DVB-H, ISDB-T, T-DMB.

Single Image Haze Removal Algorithm using Dual DCP and Adaptive Brightness Correction (Dual DCP 및 적응적 밝기 보정을 통한 단일 영상 기반 안개 제거 알고리즘)

  • Kim, Jongho
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.19 no.11
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    • pp.31-37
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    • 2018
  • This paper proposes an effective single-image haze-removal algorithm with low complexity by using a dual dark channel prior (DCP) and an adaptive brightness correction technique. The dark channel of a small patch preserves the edge information of the image, but is sensitive to noise and local brightness variations. On the other hand, the dark channel of a large patch is advantageous in estimation of the exact haze value, but halo effects from block effects deteriorate haze-removal performance. In order to solve this problem, the proposed algorithm builds a dual DCP as a combination of dark channels from patches with different sizes, and this meets low-memory and low-complexity requirements, while the conventional method uses a matting technique, which requires a large amount of memory and heavy computations. Moreover, an adaptive brightness correction technique that is applied to the recovered image preserves the objects in the image more clearly. Experimental results for various hazy images demonstrate that the proposed algorithm removes haze effectively, while requiring much fewer computations and less memory than conventional methods.

Chaos based Communication System Using Reverse DCSK (역방향 DCSK를 이용한 카오스기반 통신 시스템)

  • Jang, Eun-Young
    • Journal of IKEEE
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    • v.23 no.3
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    • pp.934-940
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    • 2019
  • In this paper, we propose a Reverse Differential Chaos Shift Keying (RE-DCSK) system for low cost, high reliability and high data rate non-coherent chaos communication .In RE-DCSK, reference signals are transmitted in the first slot as in the conventional differential chaos shift modulation scheme (DCSK) and in the second slot a time inversion block strengthens the autocorrelation of the chaos signal and uses the orthogonality of the two signals to obtain the information signal. RE-DCSK enables relatively double the data rate compared to DCSK and also improves the security of communications without any additional cost of system complexity.To prove its effectiveness, we analyze it through Rayleigh fading channel and additional white Gaussian noise (AWGN) channel based on the derived BER expression. The BER performance of the proposed system is improved when compared with the CDSK and DCSK system using AWGN channel.

The Performance Advancement of Power Analysis Attack Using Principal Component Analysis (주성분 분석을 이용한 전력 분석 공격의 성능 향상)

  • Kim, Hee-Seok;Kim, Hyun-Min;Park, Il-Hwan;Kim, Chang-Kyun;Ryu, Heui-Su;Park, Young-Ho
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.20 no.6
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    • pp.15-21
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    • 2010
  • In the recent years, various researches about the signal processing have been presented to improve the performance of power analysis. Among these signal processing techniques, the research about the signal compression is not enough than a signal alignment and a noise reduction; even though that can reduce considerably the computation time for the power analysis. But, the existing compression method can sometimes reduce the performance of the power analysis because those are the unsophisticated method not considering the characteristic of the signal. In this paper, we propose the new PCA (principal component analysis)-based signal compression method, which can block the loss of the meaningful factor of the original signal as much as possible, considering the characteristic of the signal. Also, we prove the performance of our method by carrying out the experiment.

A Study on portable voice recording prevention device (휴대용 음성 녹음 방지 장치 연구)

  • Kim, Hee-Chul
    • Journal of Digital Convergence
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    • v.19 no.7
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    • pp.209-215
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    • 2021
  • This study is a system development for voice information protection equipment in major meetings and places requiring security. Security performance and stability were secured with information leakage prevention technology through generation of false noise and ultrasonic waves. The cutoff frequency band for blocking the leakage of voice information, which has strong straightness due to the nature of the radio wave to the recording prevention module, blocks the wideband frequency of 20~20,000Hz, and the deception jamming technology is applied to block the leakage of voice information, greatly improving the security. To solve this problem, we developed a system that blocks the recording of a portable smartphone using a battery, and made the installation of a separate device smaller and lighter so that customers do not recognize it. In addition, it is necessary to continuously study measures and countermeasures for efficiently using the output of the anti-recording speaker for long-distance recording prevention.

Super-Resolution Transmission Electron Microscope Image of Nanomaterials Using Deep Learning (딥러닝을 이용한 나노소재 투과전자 현미경의 초해상 이미지 획득)

  • Nam, Chunghee
    • Korean Journal of Materials Research
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    • v.32 no.8
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    • pp.345-353
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    • 2022
  • In this study, using deep learning, super-resolution images of transmission electron microscope (TEM) images were generated for nanomaterial analysis. 1169 paired images with 256 × 256 pixels (high resolution: HR) from TEM measurements and 32 × 32 pixels (low resolution: LR) produced using the python module openCV were trained with deep learning models. The TEM images were related to DyVO4 nanomaterials synthesized by hydrothermal methods. Mean-absolute-error (MAE), peak-signal-to-noise-ratio (PSNR), and structural similarity (SSIM) were used as metrics to evaluate the performance of the models. First, a super-resolution image (SR) was obtained using the traditional interpolation method used in computer vision. In the SR image at low magnification, the shape of the nanomaterial improved. However, the SR images at medium and high magnification failed to show the characteristics of the lattice of the nanomaterials. Second, to obtain a SR image, the deep learning model includes a residual network which reduces the loss of spatial information in the convolutional process of obtaining a feature map. In the process of optimizing the deep learning model, it was confirmed that the performance of the model improved as the number of data increased. In addition, by optimizing the deep learning model using the loss function, including MAE and SSIM at the same time, improved results of the nanomaterial lattice in SR images were achieved at medium and high magnifications. The final proposed deep learning model used four residual blocks to obtain the characteristic map of the low-resolution image, and the super-resolution image was completed using Upsampling2D and the residual block three times.

Single Image Super Resolution Method based on Texture Contrast Weighting (질감 대조 가중치를 이용한 단일 영상의 초해상도 기법)

  • Hyun Ho Han
    • Journal of Digital Policy
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    • v.3 no.1
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    • pp.27-32
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    • 2024
  • In this paper, proposes a super resolution method that enhances the quality of results by refining texture features, contrasting each, and utilizing the results as weights. For the improvement of quality, a precise and clear restoration result in details such as boundary areas is crucial in super resolution, along with minimizing unnecessary artifacts like noise. The proposed method constructs a residual block structure with multiple paths and skip-connections for feature estimation in conventional Convolutional Neural Network (CNN)-based super resolution methods to enhance quality. Additional learning is performed for sharpened and blurred image results for further texture analysis. By contrasting each super resolution result and allocating weights through this process, the proposed method achieves improved quality in detailed and smoothed areas of the image. The experimental results of the proposed method, evaluated using the PSNR and SSIM values as quality metrics, show higher results compared to existing algorithms, confirming the enhancement in quality.

Dose Distribution and Image Quality in the Gantry Aperture for CT Examinations (전산화단층촬영 검사 시 Gantry Aperture 내의 선량분포와 영상의 질)

  • Cho, Pyong-Kon;Kim, You-Hyun;Choi, Jong-Hak;Lee, Ki-Yeol;Kim, Hyung-Cheol;Kim, Jang-Seob;Shin, Dong-Chul;Lee, Sung-Hyun;Lee, Jun-Hyub;Shin, Gwi-Soon
    • Journal of radiological science and technology
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    • v.32 no.4
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    • pp.453-460
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    • 2009
  • The purpose of this study was to determine the dose distribution and image quality according to slice thickness and BC(beam collimation) in the gantry aperture. CT scans were performed with a 64-slice MDCT(Brilliance 64, Philips, Cleveland, USA) scanner. To determine the dose distribution according to BC, a ionization chamber was placed at isocenter and 5, 10, 15, 20, 25 and 30 cm positions from the isocenter in the 12, 3, 6 and 9 o'clock directions. The dose distribution for phantom scan was also measured using CT head and body dose phantom with five holes at the center of the phantom and the positions of the 12, 3, 6 and 9 o'clock directions. The image noise measurement for different BCs was performed using an AAPM CT phantom. Water-filled block of the phantom was moved by 5 cm or 10 cm to the 12 o'clock direction, and the image noise was measured at the center of the phantom, and the points of 12, 3, 6 and 9 o'clock direction respectively. Some points were placed beyond the scan field of view (SFOV), so that measurement was not possible at that points. The results are as follows: The CTDIw showed a larger decrease as the source goes farther from the iso-center or the BC became wider. The CTDIw depends on the BC width more than the number of the channel of a detector array. The value of CTDIW decreased with increasing BC, but the value decreased 16.6~31.9% in the head phantom scan in air scan and 51.0~64.5% in the body phantom scan. The value of the noise was 3.9~5.9 in the head and 5.3~7.4 in the body except for BC of $2{\times}0.5\;mm$, regardless of the degree of deviation from the iso-center. When a subject was located within the SFOV, the position did not significantly affect image quality even if the subject was out of the center.

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