• Title/Summary/Keyword: synthesis algorithm

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A Hardware Design for Realtime Correction of a Barrel Distortion Using the Nearest Pixels on a Corrected Image (보정 이미지의 최 근접 좌표를 이용한 실시간 방사 왜곡 보정 하드웨어 설계)

  • Song, Namhun;Yi, Joonhwan
    • Journal of the Korea Society of Computer and Information
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    • v.17 no.12
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    • pp.49-60
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    • 2012
  • In this paper, we propose a hardware design for correction of barrel distortion using the nearest coordinates in the corrected image. Because it applies the nearest distance on corrected image rather than adjacent distance on distorted image, the picture quality is improved by the image whole area, solve the staircase phenomenon in the exterior area. But, because of additional arithmetic operation using design of bilinear interpolation, required arithmetic operation is increased. Look up table(LUT) structure is proposed in order to solve this, coordinate rotation digital computer(CORDIC) algorithm is applied. The results of the synthesis using Design compiler, the design of implementing all processes of the interpolation method with the hardware is higher than the previous design about the throughput, In case of the rear camera, the design of using LUT and hardware together can reduce the size than the design of implementing all processes with the hardware.

Active Distribution System Planning for Low-carbon Objective using Cuckoo Search Algorithm

  • Zeng, Bo;Zhang, Jianhua;Zhang, Yuying;Yang, Xu;Dong, Jun;Liu, Wenxia
    • Journal of Electrical Engineering and Technology
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    • v.9 no.2
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    • pp.433-440
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    • 2014
  • In this study, a method for the low-carbon active distribution system (ADS) planning is proposed. It takes into account the impacts of both network capacity and demand correlation to the renewable energy accommodation, and incorporates demand response (DR) as an available resource in the ADS planning. The problem is formulated as a mixed integer nonlinear programming model, whereby the optimal allocation of renewable energy sources and the design of DR contract (i.e. payment incentives and default penalties) are determined simultaneously, in order to achieve the minimization of total cost and $CO_2$ emissions subjected to the system constraints. The uncertainties that involved are also considered by using the scenario synthesis method with the improved Taguchi's orthogonal array testing for reducing information redundancy. A novel cuckoo search (CS) is applied for the planning optimization. The case study results confirm the effectiveness and superiority of the proposed method.

The Flattening Algorithm of Speech Spectrum by Quadrature Mirror Filter (QMF에 의한 음성스펙트럼의 평탄화 알고리즘)

  • Min, So-Yeon
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.7 no.5
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    • pp.907-912
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    • 2006
  • Pre-emphasizing the speech compensates for falloff at high frequencies. The most common form of pre-emphasis is y(n)=s(n)-A${\cdot}$s(n-1), where A typically lies between 0.9 and 1.0 in voiced signal. And, this value reflects the degree of pre-emphasis and equals R(1)/R(0) in conventional method. This paper proposes a new flattening method to compensate the weaked high frequency components that occur by vocal cord characteristic. We used QMF(Quardrature Mirror Filter) to minimize the output signal distortion. After using the QMF to compensate high frequency components, flattening process is followed by R(1)/R(0) at each frame. Experimental results show that the proposed method flattened the weaked high frequency components effectively than auto correlation method. Therefore, the flattening algorithm will apply in speech signal processing like speech recognition, speech analysis and synthesis.

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Design of a Truncated Floating-Point Multiplier for Graphic Accelerator of Mobile Devices (모바일 그래픽 가속기용 부동소수점 절사 승산기 설계)

  • Cho, Young-Sung;Lee, Yong-Hwan
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.11 no.3
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    • pp.563-569
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    • 2007
  • As the mobile communication and the semiconductor technology is improved continuously, mobile contents such as the multimedia service and the 2D/3D graphics which require high level graphics are serviced recently. Mobile chips should consume small die area and low power. In this paper, we design a truncated floating-point multiplier that is useful for the 2D/3D vector graphics in mobile devices. The truncated multiplier is based on the radix-4 Booth's encoding algorithm and a truncation algorithm is used to achieve small area and low power. The average percent error of the multiplier is as small as 0.00003% and neglectable for mobile applications. The synthesis result using 0.35um CMOS cell library shows that the number of gates for the truncated multiplier is only 33.8 percent of the conventional radix-4 Booth's multiplier.

An Effective Method for Generating Images Using Genetic Algorithm (유전자 알고리즘을 이용한 효과적인 영상 생성 기법)

  • Cha, Joo Hyoung;Woo, Young Woon;Lee, Imgeun
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.23 no.8
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    • pp.896-902
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    • 2019
  • In this paper, we proposed two methods to automatically generate color images similar to existing images using genetic algorithms. Experiments were performed on two different sizes($256{\times}256$, $512{\times}512$) of gray and color images using each of the proposed methods. Experimental results show that there are significant differences in the evolutionary performance of each technique in genetic modeling for image generation. In the results, evolving the whole image into sub-images evolves much more effective than modeling and evolving it into a single gene, and the generated images are much more sophisticated. Therefore, we could find that gene modeling, selection method, crossover method and mutation rate, should be carefully decided in order to generate an image similar to the existing image in the future, or to learn quickly and naturally to generate an image synthesized from different images.

Vibration analysis and optimization of functionally graded carbon nanotube reinforced doubly-curved shallow shells

  • Hammou, Zakia;Guezzen, Zakia;Zradni, Fatima Z.;Sereir, Zouaoui;Tounsi, Abdelouahed;Hammou, Yamna
    • Steel and Composite Structures
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    • v.44 no.2
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    • pp.155-169
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    • 2022
  • In the present paper an analytical model was developed to study the non-linear vibrations of Functionally Graded Carbon Nanotube (FG-CNT) reinforced doubly-curved shallow shells using the Multiple Scales Method (MSM). The nonlinear partial differential equations of motion are based on the FGM shallow shell hypothesis, the non-linear geometric Von-Karman relationships, and the Galerkin method to reduce the partial differential equations associated with simply supported boundary conditions. The novelty of the present model is the simultaneous prediction of the natural frequencies and their mode shapes versus different curvatures (cylindrical, spherical, conical, and plate) and the different types of FG-CNTs. In addition to combining the vibration analysis with optimization algorithms based on the genetic algorithm, a design optimization methode was developed to maximize the natural frequencies. By considering the expression of the non-dimensional frequency as an objective optimization function, a genetic algorithm program was developed by valuing the mechanical properties, the geometric properties and the FG-CNT configuration of shallow double curvature shells. The results obtained show that the curvature, the volume fraction and the types of NTC distribution have considerable effects on the variation of the Dimensionless Fundamental Linear Frequency (DFLF). The frequency response of the shallow shells of the FG-CNTRC showed two types of nonlinear hardening and softening which are strongly influenced by the change in the fundamental vibration mode. In GA optimization, the mechanical properties and geometric properties in the transverse direction, the volume fraction, and types of distribution of CNTs have a considerable effect on the fundamental frequencies of shallow double-curvature shells. Where the difference between optimized and not optimized DFLF can reach 13.26%.

Machine Learning Algorithm Accuracy for Code-Switching Analytics in Detecting Mood

  • Latib, Latifah Abd;Subramaniam, Hema;Ramli, Siti Khadijah;Ali, Affezah;Yulia, Astri;Shahdan, Tengku Shahrom Tengku;Zulkefly, Nor Sheereen
    • International Journal of Computer Science & Network Security
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    • v.22 no.9
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    • pp.334-342
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    • 2022
  • Nowadays, as we can notice on social media, most users choose to use more than one language in their online postings. Thus, social media analytics needs reviewing as code-switching analytics instead of traditional analytics. This paper aims to present evidence comparable to the accuracy of code-switching analytics techniques in analysing the mood state of social media users. We conducted a systematic literature review (SLR) to study the social media analytics that examined the effectiveness of code-switching analytics techniques. One primary question and three sub-questions have been raised for this purpose. The study investigates the computational models used to detect and measures emotional well-being. The study primarily focuses on online postings text, including the extended text analysis, analysing and predicting using past experiences, and classifying the mood upon analysis. We used thirty-two (32) papers for our evidence synthesis and identified four main task classifications that can be used potentially in code-switching analytics. The tasks include determining analytics algorithms, classification techniques, mood classes, and analytics flow. Results showed that CNN-BiLSTM was the machine learning algorithm that affected code-switching analytics accuracy the most with 83.21%. In addition, the analytics accuracy when using the code-mixing emotion corpus could enhance by about 20% compared to when performing with one language. Our meta-analyses showed that code-mixing emotion corpus was effective in improving the mood analytics accuracy level. This SLR result has pointed to two apparent gaps in the research field: i) lack of studies that focus on Malay-English code-mixing analytics and ii) lack of studies investigating various mood classes via the code-mixing approach.

Neural Network-Based System Identification and Controller Synthesis for an Industrial Sewing Machine

  • Kim, Il-Hwan;Stanley Fok;Kingsley Fregene;Lee, Dong-Hoon;Oh, Tae-Seok;David W. L. Wang
    • International Journal of Control, Automation, and Systems
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    • v.2 no.1
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    • pp.83-91
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    • 2004
  • The purpose of this paper is to obtain an accurate nonlinear system model to test various control schemes for a motion control system that requires high speed, robustness and accuracy. An industrial sewing machine equipped with a Brushless DC motor is considered. It is modeled by a neural network that is configured as an output-error dynamical system. The identified model is essentially a one step ahead prediction structure in which past inputs and outputs are used to calculate the current output. Using the model, a 2 degree-of-freedom PID controller to compensate the effects of disturbance without degrading tracking performance has been de-signed. In this experiment, it is not preferable for safety reasons to tune the controller online on the actual machinery. Experimental results confirm that the model is a good approximation of sewing machine dynamics and that the proposed control methodology is effective.

Image Enhancement Using Adaptive Weighted Sigma Filter (적응비중화 시그마필터에 의한 영상향상)

  • Hwang, Jae-Ho
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.44 no.2 s.314
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    • pp.19-26
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    • 2007
  • In the sigma filter, there is a specialized neighbours distribution scheme in which the sigma value is computed from local statistics. It is designed to modify a standard average filter to preserve edges. However this filter is vulnerable to details-enhancement and conventional sigma approaches have been focused on denoising, not enhancing the characteristic area. This paper proposes an adaptive image enhancement algorithm using local statistics and functional synthesis which are utilized for adaptive realization of the enhancement, so that not only image noise may be smoothed but also details may be enhanced. For the local adaptation, parameters are estimated and weighted at each moving window that satisfy the criteria. The experimental results illuminates the effectiveness of the proposed method.

Fast Single-Phase All Digital Phase-Locked Loop for Grid Synchronization under Distorted Grid Conditions

  • Zhang, Peiyong;Fang, Haixia;Li, Yike;Feng, Chenhui
    • Journal of Power Electronics
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    • v.18 no.5
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    • pp.1523-1535
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    • 2018
  • High-performance Phase-Locked Loops (PLLs) are critical for grid synchronization in grid-tied power electronic applications. In this paper, a new single-phase All Digital Phase-Locked Loop (ADPLL) is proposed. It features fast transient response and good robustness under distorted grid conditions. It is designed for Field Programmable Gate Array (FPGA) implementation. As a result, a high sampling frequency of 1MHz can be obtained. In addition, a new OSG is adopted to track the power frequency, improve the harmonic rejection and remove the dc offset. Unlike previous methods, it avoids extra feedback loop, which results in an enlarged system bandwidth, enhanced stability and improved dynamic performance. In this case, a new parameter optimization method with consideration of loop delay is employed to achieve a fast dynamic response and guarantee accuracy. The Phase Detector (PD) and Voltage Controlled Oscillator (VCO) are realized by a Coordinate Rotation Digital Computer (CORDIC) algorithm and a Direct Digital Synthesis (DDS) block, respectively. The whole PLL system is finally produced on a FPGA. A theoretical analysis and experiments under various distorted grid conditions, including voltage sag, phase jump, frequency step, harmonics distortion, dc offset and combined disturbances, are also presented to verify the fast dynamic response and good robustness of the ADPLL.