• Communications for Statistical Applications and Methods
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• 제23권4호
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• pp.355-362
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• 2016

Ensemble methods often help increase prediction ability in various predictive models by combining multiple weak learners and reducing the variability of the final predictive model. In this work, we demonstrate that ensemble methods also enhance the accuracy of prediction under kernel ridge regression and kernel logistic regression classification. Here we apply bagging and random forests to two kernel-based predictive models; and present the procedure of how bagging and random forests can be embedded in kernel-based predictive models. Our proposals are tested under numerous synthetic and real datasets; subsequently, they are compared with plain kernel-based predictive models and their subsampling approach. Numerical studies demonstrate that ensemble approach outperforms plain kernel-based predictive models.

• International Journal of Industrial Entomology and Biomaterials
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• 제10권1호
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• pp.1-10
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• 2005

Parthenogenesis in mulberry silkworm, Bombyx mori L. acquires immense use in the development of outstanding homozygous lines with higher viability, hybrid vigour, combining ability and less phenotypic variability. It can serve as a powerful tool in controlling sex of the offsprings as well as a useful tool in selection. In fact India is the second largest silk producing country in the world next only to China and all the five types of natural silks viz., mulberry, oak tasar, tropical tasar, muga and eri are produced in India. However, little information is available on the role of artificial parthenogenesis in the development of superior silkworm breeds. This paper overviews some important studies carried out on artificial parthenogenesis, and outline of different types of parthenogenesis, methods of induction of artificial parthenogenesis, factors responsible for successful parthenogenetic development, cytogenetics of artificial parthenogenesis and role of artificial parthenogenesis in silkworm breeding. Besides, an attempt is made to describe briefly about parthenogenetic engineering which includes cloning in silkworm, artificial insemination, chimeras, hybridization, chromosomal substitution and recombinant DNA in silkworm.

• 제어로봇시스템학회논문지
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• 제17권2호
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• pp.102-107
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• 2011

In this paper we present cooperation of heterogeneous robot team, composed of a wheeled robot and a helicopter for localization and map building. This heterogeneous robot team can successfully fulfill task by combining the abilities of both robots than single robot because wheeled robot and helicopter have complementing ability. The scenario describes a tightly cooperative task, where the wheeled robot move carrying the helicopter and detect obstacles, if there are obstacles, helicopter take off for map building and land, then robot team move destination avoiding obstacles. We present PID controller for position control of helicopter and transformation algorithm to global coordinate from image pixel coordinate. Experimental result show that the proposed method is valid.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 합동 추계학술대회 논문집 정보 및 제어부문
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• pp.424-427
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• 2001

In this study, we introduce a concept of neurofuzzy polynomial networks (NFPN), a hybrid modeling architecture combining neurofuzzy networks (NFN) and polynomial neural networks(PNN). NFN contributes to the formation of the premise part of the rule-based structure of the NFPN. The consequence part of the NFPN is designed using PNN. The parameters of the membership functions, learning rates and momentum coefficients are adjusted with the use of genetic optimization. We introduce two kinds of NFPN architectures, namely the basic and the modified one. Owing to the specific features of two combined architectures, it is possible to consider the nonlinear characteristics of process system and to obtain the better output performance with superb predictive ability.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권8호
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• pp.3534-3549
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• 2020

The traditional method of smoke image recognition has low accuracy. For this reason, we proposed an algorithm based on the good group of IMFOA which is GMFOA to optimize the parameters of SVM. Firstly, we divide the motion region by combining the three-frame difference algorithm and the ViBe algorithm. Then, we divide it into several parts and extract the histogram of oriented gradient and volume local binary patterns of each part. Finally, we use the GMFOA to optimize the parameters of SVM and multiple kernel learning algorithms to Classify smoke images. The experimental results show that the classification ability of our method is better than other methods, and it can better adapt to the complex environmental conditions.

• Structural Engineering and Mechanics
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• 제65권1호
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• pp.99-110
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• 2018

The focus of this paper is on the elements with stable open cracks. To analyze plane problems, two triangular elements with three and six nodes are formulated using force method. Flexibility matrices of the elements are derived by combining the non-cracked flexibility and the additional one due to crack, which is computed by utilizing the local flexibility method. In order to compute the flexibility matrix of the intact element, a basic coordinate system without rigid body motions is required. In this paper, the basic system origin is located at the crack center and one of its axis coincides with the crack surfaces. This selection makes it possible to formulate elements with inclined cracks. It is obvious that the ability of the suggested elements in calculating accurate natural frequencies for cracked structures, make them applicable for vibration-based crack detection.

• 전자공학회논문지B
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• 제32B권8호
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• pp.1119-1126
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• 1995

The construction of rule-base for a nonlinear time-varying system, becomes much more complicated because of model uncertainty and parameter variations. Furthemore, FLC does not have an ability of adjusting rule- base in responding to some sudden changes of control environments. To cope with these problems, an auto-tuning method of the fuzzy rule-base is required. In this paper, the GA-based Fuzzy-Neural control system combining Fuzzy-Neural control theory with the genetic algorithm(GA), which is known to be very effective in the optimization problem, will be proposed. The tuning of the proposed system is performed by two tuning processes(the course tuning process and the fine tuning/adaptive learning process). The effectiveness of the proposed control system will be demonstrated by computer simulations using a two degree of freedom robot manipulator.

• Journal of the Korean Data and Information Science Society
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• 제12권1호
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• pp.1-9
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• 2001

In this paper, the problem of information related to I binomial experiments, each having a distinct probability of success ${\theta}_i$, i = 1,2, $\cdots$, I, is considered. Instead of using a standard exchangeable prior for ${\theta}\;=\;({\theta}_1,\;{\theta}_2,\;{\cdots},\;{\theta}_I)$, we con-sider a partition of the experiments and take the ${\theta}_i$'s belonging to the same partition subset to be exchangeable and the ${\theta}_i$'s belonging to distinct subsets to be independent. And we perform Gibbs sampler approach for Bayesian inference on $\theta$ conditional on a partition. Also we illustrate the methodology with a real data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권10호
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• pp.5197-5218
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• 2019

Large-scale retrieval algorithm is problem for visual analyses applications, along its research track. In this paper, we propose a high-efficiency region division-based image retrieve approaches, which fuse low-level local color histogram feature and texture feature. A novel image region division is proposed to roughly mimic the location distribution of image color and deal with the color histogram failing to describe spatial information. Furthermore, for optimizing our region division retrieval method, an image descriptor combining local color histogram and Gabor texture features with reduced feature dimensions are developed. Moreover, we propose an extended Canberra distance method for images similarity measure to increase the fault-tolerant ability of the whole large-scale image retrieval. Extensive experimental results on several benchmark image retrieval databases validate the superiority of the proposed approaches over many recently proposed color-histogram-based and texture-feature-based algorithms.

• 한국약용작물학회:학술대회논문집
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• 한국약용작물학회 2010년도 심포지엄 및 추계학술발표회
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• pp.430-430
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• 2010

In this study ethanol extracts of aerial part of Geranium thunbergii Sieb. et Zucc. was investigated for their ability to inhibit a-glucosidase, and thus was fractionated using two organic solvents, including dichloromethane, ethyl acetate. The ethyl acetate-soluble fraction, which manifested potent enzyme inhibitory properties, was then followed by tracking down the active compound by combining HPLC micro-fractionation to an enzyme assay in 96-well plate. The ${\alpha}$-glucosidase inhibitory activity profile showed that two peaks exhibited potent inhibitory activity, and then the structural analyses of the two peaks were carried out by HPLC-UV-MS. The main ${\alpha}$-glucosidase inhibitory compounds in the ethyl acetate-soluble fractions of ethanol extracts of Geranium thunbergii Sieb. et Zucc. were tentatively identified as geraniin and kaempferol-7-rhamnoside.