• Title/Summary/Keyword: Cycle-based Signal

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Multicasting Multiple Description Coding Using p-cycle Network Coding

  • Farzamnia, Ali;Syed-Yusof, Sharifah K.;Fisal, Norsheila
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.7 no.12
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    • pp.3118-3134
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    • 2013
  • This paper deliberates for a multimedia transmission scheme combining multiple description coding (MDC) and network coding (NC). Our goal is to take advantage from the property of MDC to provide quantized and compressed independent and identically distributed (iid) descriptions and also from the benefit of network coding, which uses network resources efficiently to recover lost data in the network. Recently, p-cycle NC has been introduced to recover and protect any lost or distorted descriptions at the receiver part exactly without need of retransmission. So far, MDC have not been explored using this type of NC. Compressed and coded descriptions are transmitted through the network where p-cycle NC is applied. P-cycle based algorithm is proposed for single and multiple descriptions lost. Results show that in the fixed bit rate, the PSNR (Peak Signal to Noise Ratio) of our reconstructed image and also subjective evaluation is improved significantly compared to previous work which is averaging method joint with MDC in order to conceal lost descriptions.

Power Factor Correction Technique of Boost Converter Based on Averaged Model (평균화 모델을 이용한 역률개선 제어기법)

  • 정영석;문건우;이준영;윤명중
    • Proceedings of the KIPE Conference
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    • 1996.06a
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    • pp.85-88
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    • 1996
  • New power factor correction(PFC) technique based on the averaged model of boost converter is proposed. Without measurement of input current, power factor correction scheme derived from the averaged model is presented. With the measurements of input voltage and output voltage, the control signal is generated to make the shape of the line current same as the input voltage. The characteristics of input line current distortion is analyzed by considering the generation of duty cycle.

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A Development Plan for Core System of Urban Transit based on System Engineering Process (시스템엔지니어링 수명주기를 고려한 도시철도 핵심장치 개발 전략)

  • Han, Seok-Youn;Kim, Jin-Ho;An, Tae-Ki;Lee, Woo-Dong;Shin, Won-Sik
    • Proceedings of the KSR Conference
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    • 2008.11b
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    • pp.2005-2013
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    • 2008
  • Urban transit is a large scaled complex system which combines rolling stocks, power supply, signal communications, tracks & stations etc. KRRI develops nine key devices since July, 2007 as a part of the second phase of project on the standardization of urban rail transit system, which include information-communication system, station facilities, AC-DC current electric power system in urban transit. We promote the project under two directions, i.e. user-customer oriented standardization and strategic standardization for leading technologies in urban transit. In this paper, we present development plan of these key systems in view of system life cycle based on system engineering standards KSX ISO/IEC 15288 which supplies the common fundamental frame to describe the life cycle of artificial systems. System engineering process of KSX ISO/IEC 15288 are helpful to efficiently develop those key devices, although it is difficult to apply the standard identically to the key devices with the varieties and characteristics.

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Output Power Prediction of Combined Cycle Power Plant using Logic-based Tree Structured Fuzzy Neural Networks (로직에 기반 한 트리 구조의 퍼지 뉴럴 네트워크를 이용한 복합 화력 발전소의 출력 예측)

  • Han, Chang-Wook;Lee, Don-Kyu
    • Journal of IKEEE
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    • v.23 no.2
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    • pp.529-533
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    • 2019
  • Combined cycle power plants are often used to produce power. These days prediction of power plant output based on operating parameters is a major concern. This paper presents an approach to using computational intelligence technique to predict the output power of combined cycle power plant. Computational intelligence techniques have been developed and applied to many real world problems. In this paper, tree architectures of fuzzy neural networks are considered to predict the output power. Tree architectures of fuzzy neural networks have an advantage of reducing the number of rules by selecting fuzzy neurons as nodes and relevant inputs as leaves optimally. For the optimization of the networks, two-step optimization method is used. Genetic algorithms optimize the binary structure of the networks by selecting the nodes and leaves as binary, and followed by random signal-based learning further refines the optimized binary connections in the unit interval. To verify the effectiveness of the proposed method, combined cycle power plant dataset obtained from the UCI Machine Learning Repository Database is considered.

Scaling Factor Design Based Variable Step Size Incremental Resistance Maximum Power Point Tracking for PV Systems

  • Ahmed, Emad M.;Shoyama, Masahito
    • Journal of Power Electronics
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    • v.12 no.1
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    • pp.164-171
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    • 2012
  • Variable step size maximum power point trackers (MPPTs) are widely used in photovoltaic (PV) systems to extract the peak array power which depends on solar irradiation and array temperature. One essential factor which judges system dynamics and steady state performances is the scaling factor (N), which is used to update the controlling equation in the tracking algorithm to determine a new duty cycle. This paper proposes a novel stability study of variable step size incremental resistance maximum power point tracking (INR MPPT). The main contribution of this analysis appears when developing the overall small signal model of the PV system. Therefore, by using linear control theory, the boundary value of the scaling factor can be determined. The theoretical analysis and the design principle of the proposed stability analysis have been validated using MATLAB simulations, and experimentally using a fixed point digital signal processor (TMS320F2808).

Combined Traffic Signal Control and Traffic Assignment : Algorithms, Implementation and Numerical Results

  • Lee, Chung-Won
    • Proceedings of the KOR-KST Conference
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    • 2000.02a
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    • pp.89-115
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    • 2000
  • Traffic signal setting policies and traffic assignment procedures are mutually dependent. The combined signal control and traffic assignment problem deals with this interaction. With the total travel time minimization objective, gradient based local search methods are implemented. Deterministic user equilibrium is the selected user route choice rule, Webster's delay curve is the link performance function, and green time per cycle ratios are decision variables. Three implemented solution codes resulting in six variations include intersections operating under multiphase operation with overlapping traffic movements. For reference, the iterative approach is also coded and all codes are tested in four example networks at five demand levels. The results show the numerical gradient estimation procedure performs best although the simplified local searches show reducing the large network computational burden. Demand level as well as network size affects the relative performance of the local and iterative approaches. As demand level becomes higher, (1) in the small network, the local search tends to outperform the iterative search and (2) in the large network, vice versa.

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Cycle-Consistent Generative Adversarial Network: Effect on Radiation Dose Reduction and Image Quality Improvement in Ultralow-Dose CT for Evaluation of Pulmonary Tuberculosis

  • Chenggong Yan;Jie Lin;Haixia Li;Jun Xu;Tianjing Zhang;Hao Chen;Henry C. Woodruff;Guangyao Wu;Siqi Zhang;Yikai Xu;Philippe Lambin
    • Korean Journal of Radiology
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    • v.22 no.6
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    • pp.983-993
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    • 2021
  • Objective: To investigate the image quality of ultralow-dose CT (ULDCT) of the chest reconstructed using a cycle-consistent generative adversarial network (CycleGAN)-based deep learning method in the evaluation of pulmonary tuberculosis. Materials and Methods: Between June 2019 and November 2019, 103 patients (mean age, 40.8 ± 13.6 years; 61 men and 42 women) with pulmonary tuberculosis were prospectively enrolled to undergo standard-dose CT (120 kVp with automated exposure control), followed immediately by ULDCT (80 kVp and 10 mAs). The images of the two successive scans were used to train the CycleGAN framework for image-to-image translation. The denoising efficacy of the CycleGAN algorithm was compared with that of hybrid and model-based iterative reconstruction. Repeated-measures analysis of variance and Wilcoxon signed-rank test were performed to compare the objective measurements and the subjective image quality scores, respectively. Results: With the optimized CycleGAN denoising model, using the ULDCT images as input, the peak signal-to-noise ratio and structural similarity index improved by 2.0 dB and 0.21, respectively. The CycleGAN-generated denoised ULDCT images typically provided satisfactory image quality for optimal visibility of anatomic structures and pathological findings, with a lower level of image noise (mean ± standard deviation [SD], 19.5 ± 3.0 Hounsfield unit [HU]) than that of the hybrid (66.3 ± 10.5 HU, p < 0.001) and a similar noise level to model-based iterative reconstruction (19.6 ± 2.6 HU, p > 0.908). The CycleGAN-generated images showed the highest contrast-to-noise ratios for the pulmonary lesions, followed by the model-based and hybrid iterative reconstruction. The mean effective radiation dose of ULDCT was 0.12 mSv with a mean 93.9% reduction compared to standard-dose CT. Conclusion: The optimized CycleGAN technique may allow the synthesis of diagnostically acceptable images from ULDCT of the chest for the evaluation of pulmonary tuberculosis.

Development of The Signal Control Algorithm Using Travel Time Informations of Sectional Detection Systems (구간검지체계의 통행시간정보를 이용한 신호제어 알고리즘 개발)

  • Jung, Young-Je;Kim, Young-Chan;Baek, Hyon-Su
    • Journal of Korean Society of Transportation
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    • v.23 no.8 s.86
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    • pp.181-191
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    • 2005
  • This study developed an algorithm for real-time signal control based on the detection system that can collect sectional travel time. The signal control variable is maximum queue length per cycle and this variable has a sectional meaning. When a individual vehicle pass through the detector, we can gather the vehicle ID and the detected time. Therefor we can compute the travel time of an individual vehicle between consecutive detectors. This travel time informations were bisected including the delay and not. We can compute queue withdrawing time using this bisection and the max queue length is computed using the deterministic delay model. The objective function of the real-time signal control aims equalization of queue length for all direction. The distribution of the cycle is made by queue length ratios.

A Study on Early Warning Model in the Dry Bulk Shipping Industry by Signal Approach (신호접근법을 이용한 건화물시장 해운조기경보모형에 관한 연구)

  • Yun, Jeong-No;KIm, Ga-Hyun;Ryoo, Dong-Keun
    • Journal of Navigation and Port Research
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    • v.42 no.1
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    • pp.57-66
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    • 2018
  • Maritime industry is affected by outside factors significantly due to its derivative demand characteristics. However, the supply side can not react to these changes immediately and due to this uniqueness, maritime industry repeats the boom-bust cycle. Therefore the government itself needs to operate early warning system in order to monitor the market and notice the upcoming risks by setting up a system to prepare for the situations. In this research, signal approach is used to establish early warning system. Overall leading index is composed of crisis index that is based on BDI(Baltic Dry Index) and various leading indexes such as finance, economy, shipping and the others. As a result of computing overall leading index which is early warning system in maritime through signal approach, the index showed a high correlation coefficient with actual maritime risk index by difference of 4 months. Also, the result was highly accurate with overall leading index's QPS(Quadratic Probability Score) at 0.37.

A DFT Based Filtering Technique to Eliminate Decaying dc and Harmonics for Power System Phasor Estimation

  • Oh Yong- Taek;Balamourougan V.;Sidhu T.S.
    • KIEE International Transactions on Power Engineering
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    • v.5A no.2
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    • pp.138-143
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    • 2005
  • During faults, the voltage and current signals available to the relay are affected by the decaying dc component and harmonics. In order to make appropriate and accurate decisions, most of the relaying algorithms require the fundamental frequency phasor information that is immune to decaying dc effect and harmonics. The conventional Fourier ph as or estimation algorithm is affected by the presence of decaying-exponential transients in the fault signal. This paper presents a modified Fourier algorithm, which effectively eliminates the decaying dc component and the harmonics present in the fault signal. The decaying dc parameters are estimated by means of an out-of-band filtering technique. The decaying dc offset and harmonics are removed by means of a simple computational procedure that involves the design of two sets of Orthogonal digital OFT filters tuned at different frequencies and by creating three off-line look-up tables. The technique was tested for different decay rates of the decaying dc component. It was also compared with the conventional mimic plus the full cycle OFT algorithm. The results indicate that the proposed technique has a faster convergence to the desired value compared to the conventional mimic plus OFT algorithms over a wide range of decay rates. In all cases, the convergence to the desired value was achieved within one cycle of the power system frequency.