• Title/Summary/Keyword: Space Partition

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A Study on the Diagnosis of Appendicitis using Fuzzy Neural Network (퍼지 신경망을 이용한 맹장염진단에 관한 연구)

  • 박인규;신승중;정광호
    • Proceedings of the Korean Society for Emotion and Sensibility Conference
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    • 2000.04a
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    • pp.253-257
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    • 2000
  • the objective of this study is to design and evaluate a methodology for diagnosing the appendicitis in a fuzzy neural network that integrates the partition of input space by fuzzy entropy and the generation of fuzzy control rules and learning algorithm. In particular the diagnosis of appendicitis depends on the rule of thumb of the experts such that it associates with the region, the characteristics, the degree of the ache and the potential symptoms. In this scheme the basic idea is to realize the fuzzy rle base and the process of reasoning by neural network and to make the corresponding parameters of the fuzzy control rules be adapted by back propagation learning rule. To eliminate the number of the parameters of the rules, the output of the consequences of the control rules is expressed by the network's connection weights. As a result we obtain a method for reducing the system's complexities. Through computer simulations the effectiveness of the proposed strategy is verified for the diagnosis of appendicitis.

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RHC for Nonlinear backlash system control (RHC를 이용한 비선형 Backlash 시스템 제어)

  • Yoo, Kyung-Sang
    • Proceedings of the KIEE Conference
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    • 2005.07d
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    • pp.2471-2473
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    • 2005
  • We present a receding horizon control [RHC] algorithm for compensation of backlash at the input of a stable linear system under control rate constraints. The problem is posed as a receding horizon optimal control [RHOptC] problem for a piecewise affine [PWA] system by modelling the backlash nonlinearity as a PWA system with a state space partition consisting of three regions. The RHC problem involves solving, at each step, $3^N$ quadratic programmes[QP], where N is the optimization horizon. This strategy leads, at the cost of some performance degradation, to much smaller computational load since a feasible rather than optimal solution has to be obtained at each step.

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The System of Non-Linear Detector over Wireless Communication (무선통신에서의 Non-Linear Detector System 설계)

  • 공형윤
    • Proceedings of the IEEK Conference
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    • 1998.06a
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    • pp.106-109
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    • 1998
  • Wireless communication systems, in particular, must operate in a crowded electro-magnetic environmnet where in-band undesired signals are treated as noise by the receiver. These interfering signals are often random but not Gaussian Due to nongaussian noise, the distribution of the observables cannot be specified by a finite set of parameters; instead r-dimensioal sample space (pure noise samples) is equiprobably partitioned into a finite number of disjointed regions using quantiles and a vector quantizer based on training samples. If we assume that the detected symbols are correct, then we can observe the pure noise samples during the training and transmitting mode. The algorithm proposed is based on a piecewise approximation to a regression function based on quantities and conditional partition moments which are estimated by a RMSA (Robbins-Monro Stochastic Approximation) algorithm. In this paper, we develop a diversity combiner with modified detector, called Non-Linear Detector, and the receiver has a differential phase detector in each diversity branch and at the combiner each detector output is proportional to the second power of the envelope of branches. Monte-Carlo simulations were used as means of generating the system performance.

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A Study on Special Education Facilities of the Elementary School in Seattle (미국 워싱턴주 시애틀시의 초등학교 특수교육시설에 관한 연구)

  • Kim, Jong-Young
    • Journal of the Korean Institute of Educational Facilities
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    • v.17 no.3
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    • pp.13-20
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    • 2010
  • Seattle Public School Authority implements Inclusive Education which allows handicapped children to study in ordinary schools. This research is to analyze Inclusive Education system and find characteristics of school network and school planning. Survey was performed on 9 school districts and 54 public schools. The found results are following; 1) 54 schools adopt special education programs and legal barrier free design. All handicapped children groups are divided into level I through Ⅳ including mild level (level I,II) at all schools and multi-handicapped(severe level, level III, IV) at schools specified by school district or Seattle City. 2) Each school groups are transformed into self-contained classroom, therapy room and general room as a set in consideration of user communication and special education program. Also, existing classrooms are rearranged into small study spaces by using partition system. It allows ordinary schools to accomodate Inclusive Education through school network, classroom rearrangement and space partitioning.

New Mutation Rule for Evolutionary Programming Motivated from the Competitive Exclusion Principle in Ecology

  • Shin, Jung-Hwan;Park, Doo-Hyun;Chien, Sung-I1
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.165.2-165
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    • 2001
  • A number of previous researches in evolutionary algorithm are based on the study of facets we observe in natural evolution. The individuals of species in natural evolution occupy their own niche that is a subdivision of the habitat. This means that two species with the similar requirements cannot live together in the same niche. This is known as the competitive exclusion principle, i.e., complete competitors cannot coexist. In this paper, a new evolutionary programming algorithm adopting this concept is presented. Similarly in the case of natural evolution , the algorithm Includes the concept of niche obtained by partitioning a search space and the competitive exclusion principle performed by migrating individuals. Cell partition and individual migration strategies are used to preserve search diversity as well as to speed up convergence of an ...

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Nonparametric Bayesian Multiple Comparisons for Geometric Populations

  • Ali, M. Masoom;Cho, J.S.;Begum, Munni
    • Journal of the Korean Data and Information Science Society
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    • v.16 no.4
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    • pp.1129-1140
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    • 2005
  • A nonparametric Bayesian method for calculating posterior probabilities of the multiple comparison problem on the parameters of several Geometric populations is presented. Bayesian multiple comparisons under two different prior/ likelihood combinations was studied by Gopalan and Berry(1998) using Dirichlet process priors. In this paper, we followed the same approach to calculate posterior probabilities for various hypotheses in a statistical experiment with a partition on the parameter space induced by equality and inequality relationships on the parameters of several geometric populations. This also leads to a simple method for obtaining pairwise comparisons of probability of successes. Gibbs sampling technique was used to evaluate the posterior probabilities of all possible hypotheses that are analytically intractable. A numerical example is given to illustrate the procedure.

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Analysis for computing heat conduction and fluid problems using cubic B-spline function (3차 B-spline 함수를 이용한 열전도 및 유체문제의 해석)

  • Kim, Eun-Pil
    • Journal of computational fluids engineering
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    • v.3 no.2
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    • pp.1-8
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    • 1998
  • We make use of cubic B-spline interpolation function in two cases: heat conduction and fluid flow problems. Cubic B-spline test function is employed because it is superior to approximation of linear and non-linear problems. We investigated the accuracy of the numerical formulation and focused on the position of the breakpoints within the computational domain. When the domain is divided by partitions of equal space, the results show poor accuracy. For the case of a heat conduction problem this partition can not reflect the temperature gradient which is rapidly changed near the wall. To correct the problem, we have more grid points near the wall or the region which has a rapid change of variables. When we applied the unequally spaced breakpoints, the results show high accuracy. Based on the comparison of the linear problem, we extended to the highly non-linear fluid flow problems.

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Antioxidant Activity of the Seagrass Zostera japonica (애기거머리말의 항산화 활성)

  • Kwak, Myoung Kuk;Kim, Da Seul;Oh, Kwang-Suk;Seo, Youngwan
    • KSBB Journal
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    • v.29 no.4
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    • pp.271-277
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    • 2014
  • In this study, crude extract of the seagrass Zostera japonica, and its solvent-partitioned fractions were evaluated for their antioxidant activity. The crude extract was successively fractionated into n-hexane, 85% aqueous methanol (85% aq.MeOH), n-butanol (n-BuOH), and water fractions by liquid-liquid partition. These include DPPH radical scavenging, hydroxyl radical scavenging in HT-1080 cells, peroxynitrite scavenging, and protective effect on DNA damage caused by hydroxyl radicals generated. In all assays, except for DPPH radical, 85% aq.MeOH and n-BuOH fraction showed the strong antioxidant activity. These results suggest that Z. japonica may be used as a potential source of natural antioxidants for the development of cosmetic product or functional food in the future.

Bayesian Multiple Comparisons for Normal Variances

  • Kim, Hea-Jung
    • Journal of the Korean Statistical Society
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    • v.29 no.2
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    • pp.155-168
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    • 2000
  • Regarding to multiple comparison problem (MCP) of k normal population variances, we suggest a Bayesian method for calculating posterior probabilities for various hypotheses of equality among population variances. This leads to a simple method for obtaining pairwise comparisons of variances in a statistical experiment with a partition on the parameter space induced by equality and inequality relationships among the variances. The method is derived from the fact that certain features of the hierarchical nonparametric family of Dirichlet process priors, in general, make it amenable to solving the MCP and estimating the posterior probabilities by means of posterior simulation, the Gibbs sampling. Two examples are illustrated for the method. For these examples, the method is straightforward for specifying distributionally and to implement computationally, with output readily adapted for required comparison.

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A Dynamically Reconfiguring Backpropagation Neural Network and Its Application to the Inverse Kinematic Solution of Robot Manipulators (동적 변화구조의 역전달 신경회로와 로보트의 역 기구학 해구현에의 응용)

  • 오세영;송재명
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.39 no.9
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    • pp.985-996
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    • 1990
  • An inverse kinematic solution of a robot manipulator using multilayer perceptrons is proposed. Neural networks allow the solution of some complex nonlinear equations such as the inverse kinematics of a robot manipulator without the need for its model. However, the back-propagation (BP) learning rule for multilayer perceptrons has the major limitation of being too slow in learning to be practical. In this paper, a new algorithm named Dynamically Reconfiguring BP is proposed to improve its learning speed. It uses a modified version of Kohonen's Self-Organizing Feature Map (SOFM) to partition the input space and for each input point, select a subset of the hidden processing elements or neurons. A subset of the original network results from these selected neuron which learns the desired mapping for this small input region. It is this selective property that accelerates convergence as well as enhances resolution. This network was used to learn the parity function and further, to solve the inverse kinematic problem of a robot manipulator. The results demonstrate faster learning than the BP network.