• Title/Summary/Keyword: Application Selection

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Automatic threshold selection for edge detection using a noise estimation scheme and its application (잡음추측을 이용한 자동적인 에지검출 문턱값 선택과 그 응용)

  • 김형수;오승준
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.21 no.3
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    • pp.553-563
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    • 1996
  • Detecting edges is one of issues with essentialimprotance in the area of image analysis. An edge in an image is a boundary or contour at which a significant change occurs in image intensity. Edge detection has been studied in many addlications such as imagesegmentation, robot vision, and image compression. In this paper, we propose an automatic threshold selection scheme for edge detection and show its application to noise elimination. The scheme suggested here applied statistical properties of the noise estimated from a noisy image to threshold selection. Since a selected threshold value in the scheme depends on not the characgreistic of an orginal image but the statistical feature of added noise, we can remove ad-hoc manners used for selecting the threshold value as well as decide the value theoretically. Furthermore, that shceme can reduce the number of edge pixels either generated or lost by noise. an application of the scheme to noise elimination is shown here. Noise in the input image can be eliminated with considering the direction of each edge pixedl on the edge map obtained by applying the threshold selection scheme proposed in this paper. Achieving significantly improved results in terms of SNR as well as subjective quality, we can claim that the suggested method works well.

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A Selection Transmit Diversity with Adaptive Modulation (적응변조를 이용한 선택적 송신 다이버시티 기술)

  • 김준오;권종만;임창헌
    • Proceedings of the IEEK Conference
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    • 2001.06a
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    • pp.65-68
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    • 2001
  • The selection transmit diversity is an effective way to avoid the deep fading in a wireless channel. However, it may not completely eliminate the SNR fluctuation of a received signal at the receiver. This letter presents an application of an adaptive modulation effectively exploiting the SNR variation over time for a higher spectral efficiency to the conventional selection transmit diversity. Numerical results show that the proposed scheme can achieve a SNR gain of about 7 dB over the conventional selection diversity in a flat Rayleigh fading environment, when a BER of 10$^{-3}$ and a spectral efficiency of 2 bps/Hz are required..

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Member Selection Procedure in the Steel Structural Design (강구조물설계에서 부재선정의 시스템화 방법론)

  • 이영호;김상철;김흥국;이병해
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 1995.10a
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    • pp.197-206
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    • 1995
  • In structural design procedure, The procedure of member selection manages complex data relationship and reflects structural expert's knowledge. It is a difficult problem to construct an effective system with the conventional l programming technique. Knowledge_based s!'stem is a software system capable of supporting the explicit representation of expert's knowledge in member selection process through member data and reasoning mechanisms. This study describes useful methodology for structuring knowledge and representing relation between member data and knowledge. And this study shows the application of this member for member selection in the steel structural design.

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Simulation Optimization with Statistical Selection Method

  • Kim, Ju-Mi
    • Management Science and Financial Engineering
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    • v.13 no.1
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    • pp.1-24
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    • 2007
  • I propose new combined randomized methods for global optimization problems. These methods are based on the Nested Partitions(NP) method, a useful method for simulation optimization which guarantees global optimal solution but has several shortcomings. To overcome these shortcomings I hired various statistical selection methods and combined with NP method. I first explain the NP method and statistical selection method. And after that I present a detail description of proposed new combined methods and show the results of an application. As well as, I show how these combined methods can be considered in case of computing budget limit problem.

Introduction to a Novel Optimization Method : Artificial Immune Systems (새로운 최적화 기법 소개 : 인공면역시스템)

  • Yang, Byung-Hak
    • IE interfaces
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    • v.20 no.4
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    • pp.458-468
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    • 2007
  • Artificial immune systems (AIS) are one of natural computing inspired by the natural immune system. The fault detection, the pattern recognition, the system control and the optimization are major application area of artificial immune systems. This paper gives a concept of artificial immune systems and useful techniques as like the clonal selection, the immune network theory and the negative selection. A concise survey on the optimization problem based on artificial immune systems is generated. The overall performance of artificial immune systems for the optimization problem is discussed.

Animal Breeding: What Does the Future Hold?

  • Eisen, E.J.
    • Asian-Australasian Journal of Animal Sciences
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    • v.20 no.3
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    • pp.453-460
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    • 2007
  • An overview of developments important in the future of animal breeding is discussed. Examples from the application of quantitative genetic principles to selection in chickens and mice are given. Lessons to be learned from these species are that selection for production traits in livestock must also consider selection for reproduction and other fitness-related traits and inbreeding should be minimized. Short-term selection benefits of best linear unbiased predictor methodology must be weighed against long-term risks of increased rate of inbreeding. Different options have been developed to minimize inbreeding rates while maximizing selection response. Development of molecular genetic methods to search for quantitative trait loci provides the opportunity for incorporating marker-assisted selection and introgression as new tools for increasing efficiency of genetic improvement. Theoretical and computer simulation studies indicate that these methods hold great promise once genotyping costs are reduced to make the technology economically feasible. Cloning and transgenesis are not likely to contribute significantly to genetic improvement of livestock production in the near future.

A Study on the Application of Analytic Hierarchy Process to the selection of Airliners (계층화의사결정법(AHP)을 이용한 여객기의 기종선정에 관한 연구)

  • Eun, Hee-Bong;Kim, Bong-Sun
    • IE interfaces
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    • v.14 no.1
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    • pp.47-53
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    • 2001
  • This paper was studied to present a model for the application of AHP to the selection of airliners. For this study, a questionnaire was developed in respect to the criteria of airliner and given to 80 airline pilots and 30 maintenances in airlines to ask their opinions about the candidates for the middle-range airliners. The AHP software developed by Korean Advanced Institute of Science Technology (KAIST) was used to process the data. The result was analyzed by the criteria of selecting airliners and the several alternatives for the middle-range airliners.

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An Application of the Clustering Threshold Gradient Descent Regularization Method for Selecting Genes in Predicting the Survival Time of Lung Carcinomas

  • Lee, Seung-Yeoun;Kim, Young-Chul
    • Genomics & Informatics
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    • v.5 no.3
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    • pp.95-101
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    • 2007
  • In this paper, we consider the variable selection methods in the Cox model when a large number of gene expression levels are involved with survival time. Deciding which genes are associated with survival time has been a challenging problem because of the large number of genes and relatively small sample size (n<

Evaluating the Performance of Four Selections in Genetic Algorithms-Based Multispectral Pixel Clustering

  • Kutubi, Abdullah Al Rahat;Hong, Min-Gee;Kim, Choen
    • Korean Journal of Remote Sensing
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    • v.34 no.1
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    • pp.151-166
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    • 2018
  • This paper compares the four selections of performance used in the application of genetic algorithms (GAs) to automatically optimize multispectral pixel cluster for unsupervised classification from KOMPSAT-3 data, since the selection among three main types of operators including crossover and mutation is the driving force to determine the overall operations in the clustering GAs. Experimental results demonstrate that the tournament selection obtains a better performance than the other selections, especially for both the number of generation and the convergence rate. However, it is computationally more expensive than the elitism selection with the slowest convergence rate in the comparison, which has less probability of getting optimum cluster centers than the other selections. Both the ranked-based selection and the proportional roulette wheel selection show similar performance in the average Euclidean distance using the pixel clustering, even the ranked-based is computationally much more expensive than the proportional roulette. With respect to finding global optimum, the tournament selection has higher potential to reach the global optimum prior to the ranked-based selection which spends a lot of computational time in fitness smoothing. The tournament selection-based clustering GA is used to successfully classify the KOMPSAT-3 multispectral data achieving the sufficient the matic accuracy assessment (namely, the achieved Kappa coefficient value of 0.923).

An application of BP-Artificial Neural Networks for factory location selection;case study of a Korean factory

  • Hou, Liyao;Suh, Eui-Ho
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • 2007.05a
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    • pp.351-356
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    • 2007
  • Factory location selection is very important to the success of operation of the whole supply chain, but few effective solutions exist to deliver a good result, motivated by this, this paper tries to introduce a new factory location selection methodology by employing the artificial neural networks technology. First, we reviewed previous research related to factory location selection problems, and then developed a (neural network-based factory selection model) NNFSM which adopted back-propagation neural network theory, next, we developed computer program using C++ to demonstrate our proposed model. then we did case study by choosing a Korean steelmaking company P to show how our proposed model works,. Finnaly, we concluded by highlighting the key contributions of this paper and pointing out the limitations and future research directions of this paper. Compared to other traditional factory location selection methods, our proposed model is time-saving; more efficient.and can produce a much better result.

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