• Title/Summary/Keyword: standard algorithm

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An Adaptive Color Enhancement Algorithm using the Preferred Color Reconstruction (선호색 보정을 이용한 화질 향상 알고리즘)

  • Yang, Kyoung-Ok;Hwang, Bo-Hyun;Lee, Seung-Jun;Yun, Jong-Ho;Chon, Myung-Ryul
    • The Transactions of the Korean Institute of Electrical Engineers P
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    • v.57 no.1
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    • pp.22-29
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    • 2008
  • In this paper, we propose an adaptive color enhancement algorithm. It is used for the flat panel displays (FPDs) such as LCD, PDP, and so on. The proposed algorithm consists of an adaptive linear approximation CDF(Cumulative Density Function) algorithm and an adaptive saturation enhancement algorithm. The one is for contrast enhancement which prevents an image from the distortion by luminance transient of an input image. The other is the algorithm which improves the saturation without the contour artifact and over-saturation, whose problems are generated during the enhancing saturation. In addition, it allows to achieve the high quality image using the saturation enhancement method for a preferred color of original image. Visual test and standard deviation of their histograms have been applied to evaluate the resultant output images of the proposed algorithm.

Genetic algorithm based optimum design of non-linear steel frames with semi-rigid connections

  • Hayalioglu, M.S.;Degertekin, S.O.
    • Steel and Composite Structures
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    • v.4 no.6
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    • pp.453-469
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    • 2004
  • In this article, a genetic algorithm based optimum design method is presented for non-linear steel frames with semi-rigid connections. The design algorithm obtains the minimum weight frame by selecting suitable sections from a standard set of steel sections such as European wide flange beams (i.e., HE sections). A genetic algorithm is employed as optimization method which utilizes reproduction, crossover and mutation operators. Displacement and stress constraints of Turkish Building Code for Steel Structures (TS 648, 1980) are imposed on the frame. The algorithm requires a large number of non-linear analyses of frames. The analyses cover both the non-linear behaviour of beam-to-column connection and $P-{\Delta}$ effects of beam-column members. The Frye and Morris polynomial model is used for modelling of semi-rigid connections. Two design examples with various type of connections are presented to demonstrate the application of the algorithm. The semi-rigid connection modelling results in more economical solutions than rigid connection modelling, but it increases frame drift.

Gamma ray interactions based optimization algorithm: Application in radioisotope identification

  • Ghalehasadi, Aydin;Ashrafi, Saleh;Alizadeh, Davood;Meric, Niyazi
    • Nuclear Engineering and Technology
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    • v.53 no.11
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    • pp.3772-3783
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    • 2021
  • This work proposes a new efficient meta-heuristic optimization algorithm called Gamma Ray Interactions Based Optimization (GRIBO). The algorithm mimics different energy loss processes of a gamma-ray photon during its passage through a matter. The proposed novel algorithm has been applied to search for the global minima of 30 standard benchmark functions. The paper also considers solving real optimization problem in the field of nuclear engineering, radioisotope identification. The results are compared with those obtained by the Particle Swarm Optimization, Genetic Algorithm, Gravitational Search Algorithm and Grey Wolf Optimizer algorithms. The comparisons indicate that the GRIBO algorithm is able to provide very competitive results compared to other well-known meta-heuristics.

APPLYING ELITIST GENETIC ALGORITHM TO RESOURCE-CONSTRAINED PROJECT SCHEDULING PROBLEM

  • Jin-Lee Kim;Ok-Kyue Kim
    • International conference on construction engineering and project management
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    • 2007.03a
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    • pp.739-748
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    • 2007
  • The objective of this research study is to develop the permutation-based genetic algorithm for solving the resource-constrained project scheduling problem in construction engineering by incorporating elitism into genetic algorithm. A key aspect of the algorithm was the development of the elitist roulette selection operator to preserve the best individual solution for the next generation so the improved solution can be obtained. Another notable characteristic is the application of the parallel schedule generation scheme to generate a feasible solution to the problem. Case studies with a standard test problem were presented to demonstrate the performance and accuracy of the algorithm. The computational results indicate that the proposed algorithm produces reasonably good solutions for the resource-constrained project scheduling problem.

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Fast and Scalable Path Re-routing Algorithm Using A Genetic Algorithm (유전자 알고리즘을 이용한 확장성 있고 빠른 경로 재탐색 알고리즘)

  • Lee, Jung-Kyu;Kim, Seon-Ho;Yang, Ji-Hoon
    • The KIPS Transactions:PartB
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    • v.18B no.3
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    • pp.157-164
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    • 2011
  • This paper presents a fast and scalable re-routing algorithm that adapts to dynamically changing networks. The proposed algorithm integrates Dijkstra's shortest path algorithm with the genetic algorithm. Dijkstra's algorithm is used to define the predecessor array that facilitates the initialization process of the genetic algorithm. After that, the genetic algorithm re-searches the optimal path through appropriate genetic operators under dynamic traffic situations. Experimental results demonstrate that the proposed algorithm produces routes with less traveling time and computational overhead than pure genetic algorithm-based approaches as well as the standard Dijkstra's algorithm for large-scale networks.

Gaussian noise estimation using adaptive filtering (적응적 필터링을 이용한 가우시안 잡음 예측)

  • Joh, Beom Seok;Kim, Young Ro
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.8 no.4
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    • pp.13-18
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    • 2012
  • In this paper, we propose a noise estimation method for noise reduction. It is based on block and pixel-based noise estimation. We assume that an input image is contaminated by the additive white Gaussian noise. Thus, we use an adaptive Gaussian filter and estimate the amount of noise. It computes the standard deviation of each block and estimation is performed on pixel-based operation. The proposed algorithm divides an input image into blocks. This method calculates the standard deviation of each block and finds the minimum standard deviation block. The block in flat region shows well noise and filtering effects. Blocks which have similar standard deviation are selected as test blocks. These pixels are filtered by adaptive Gaussian filtering. Then, the amount of noise is calculated by the standard deviation of the differences between noisy and filtered blocks. Experimental results show that our proposed estimation method has better results than those by existing estimation methods.

Evaluation of Recursive PIV Algorithm with Correlation Based Correction Method Using Various Flow Images

  • Daichin;Lee, Sang-Joon
    • Journal of Mechanical Science and Technology
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    • v.17 no.3
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    • pp.409-421
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    • 2003
  • The hierarchical recursive local-correlation PIV algorithm with CBC (correlation based correction) method was employed to increase the spatial resolution of PIV results and to reduce error vectors. The performance of this new PIV algorithm was tested using synthetic images, PIV standard images of Visualization Society of Japan, real flows including ventilation flow inside a vehicle passenger compartment and wake behind a circular cylinder with riblet surface. As a result, most spurious vectors were suppressed by employing the CBC method, the hierarchical recursive correlation algorithm improved the sub-pixel accuracy of PIV results by decreasing the interrogation window size and Increased spatial resolution significantly. However, with recursively decreasing of interrogation window size, the SNR (signal-to-noise ratio) in the correlation plane was decreased and number of spurious vectors was increased. Therefore, compromised determination of optimal interrogation window size is required for given flow images, the performance of recursive algorithm is also discussed from a viewpoint of recovery ratio and error ratio in the paper.

An Algorithm for Generating an Optimal Laser-Torch Path to Cut Multiple Parts with Their Own Set of Sub-Parts Inside (2차부재가 포함된 다수의 1차부재를 가공하기 위한 레이저 토치의 절단경로 최적화 알고리즘)

  • Kwon Ki-Bum;Lee Moon-Kyu
    • Journal of Institute of Control, Robotics and Systems
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    • v.11 no.9
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    • pp.802-809
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    • 2005
  • A hybrid genetic algorithm is proposed for the problem of generating laser torch paths to cut a stock plate nested with free-formed parts each having a set of sub-parts. In the problem, the total unproductive travel distance of the torch is minimized. The problem is shown to be formulated as a special case of the standard travelling salesman problem. The hybrid genetic algorithm for solving the problem is hierarchically structured: First, it uses a genetic algorithm to find the cutting path f3r the parts and then, based on the obtained cutting path, sequence of sub-parts and their piercing locations are optimally determined by using a combined genetic and heuristic algorithms. This process is repeated until any progress in the total unproductive travel distance is not achieved. Computational results are provided to illustrate the validity of the proposed algorithm.

Implementation of Rijndael Block Cipher Algorithm

  • Lee, Yun-Kyung;Park, Young-Soo
    • Proceedings of the IEEK Conference
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    • 2002.07a
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    • pp.164-167
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    • 2002
  • This paper presents the design of Rijndael crypto-processor with 128 bits, 192 bits and 256 bits key size. In October 2000 Rijndael cryptographic algorithm is selected as AES(Advanced Encryption Standard) by NIST(National Institute of Standards and Technology). Rijndael algorithm is strong in any known attacks. And it can be efficiently implemented in both hardware and software. We implement Rijndael algorithm in hardware, because hardware implementation gives more fast encryptioN/decryption speed and more physically secure. We implemented Rijndael algorithm for 128 bits, 192 bits and 256 bits key size with VHDL, synthesized with Synopsys, and simulated with ModelSim. This crypto-processor is implemented using on-the-fly key generation method and using lookup table for S-box/SI-box. And the order of Inverse Shift Row operation and Inverse Substitution operation is exchanged in decryption round operation of Rijndael algorithm. It brings about decrease of the total gate count. Crypto-processor implemented in these methods is applied to mobile systems and smart cards, because it has moderate gate count and high speed.

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Adaptive Update Rate Tracking Using IMM Algorithm (IMM 알고리듬을 이용한 적응 최신화 빈도 추적)

  • 신형조;홍선목
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.30B no.12
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    • pp.59-66
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    • 1993
  • In this paper we propose an adaptive update rate tracking algorithm for a phased array radar, based on the interacting multiple model(IMM) algorithm. The purpose of the IMM algorithm hers is twofold: 1) to estimate and predict the target states, and 2) to estimate the level of the process noise. Using the estimate of the process noise level adapted to target dynamics, the update interval is determined to maintain a desired prediction accuracy so that the radar system load is minimized. The adaptive update rate tracking algorithm is implemented for a phased array radar and evaluated with Monte Carlo simulations on various trajectories. The evaluation results of the proposed algorithm and a standard Kalman filter without the adaptive update rate control are presented to compare.

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