• Structural Engineering and Mechanics
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• v.18 no.5
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• pp.591-607
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• 2004

The substance of the use of the derived non-linear creep constitutive equations under variable stress levels (see first part of the paper, Kmet 2004) is explained and the strategy of their application is outlined using the results of one-step creep tests of the steel spiral strand rope as an example. In order to investigate the creep strain increments of cables an experimental set-up was originally designed and a series of tests were carried out. Attention is turned to the individual main steps in the production and application procedure, i.e., to the one-step creep tests, definition of loading history, determination of the kernel functions, selection and definition of constitutive equation and to the comparison of the resulting values considering the product and the additive forms of the approximation of the kernel functions. To this purpose, the parametrical study is performed and the results are presented. The constitutive equations of non-linear creep of cable under variable stress history offer a strong tool for the real simulation of stochastic variable load history and prediction of realistic time-dependent response (current deflection and stress configuration) of structures with cable elements. By means of suitable stress combination and its gradual repeating various loads and times effects can be modelled.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.4
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• pp.797-802
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• 2010

In this paper, a systematic procedure to design a nonlinear controller for nonlinear active magnetic bearing (AMB) systems is presented. To do this, we effectively convert the AMB system into a polytopic quasi-linear parameter varying (LPV) system, which is a representation of nonlinear state-space models and is described by the convex combination of a set of precisely known vertices. Unlike the existing quasi-LPV systems, the nonlinear weighting functions, which construct the polytopic quasi-LPV model of the AMB system by connecting the vertices, include not only state variables but also the input ones. This allows us to treat the input nonlinearity effectively. By means of the derived polytopic quasi-LPV model and linear matrix inequality (LMI) conditions, nonlinear controller that stabilizes the AMB system is obtained. The effectiveness of the proposed controller design methodology is finally demonstrated through numerical simulations.

• Journal of Industrial Technology
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• v.24 no.A
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• pp.37-46
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• 2004

A performance analysis for newly being considered electric rail car office has been made in this study. The major purpose is to examine a proposed design in terms of its capacity and the proposed number of travels (82-84) per day. For this study we first examined the overall system configuration with detailed operational processes of cleaning and inspection. We then developed a simulation model using ARENA and designed input data from 12 selected factors and their interaction effects. A simulation run for each treatment combination of $L_{16}(2^{15})$ orthogonal array was run and 20 batch means were obtained. Through careful analyses of the results obtained, we drew a diversity of suggestions including the best factor level combination. Our confirmation experiments at the optimal level combination further validate the possibility of 82 runs and the consistency in the results.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2399-2413
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• 2021

A recommendation system is an information filter tool, which uses the ratings and reviews of users to generate a personalized recommendation service for users. However, the cold-start problem of users and items is still a major research hotspot on service recommendations. To address this challenge, this paper proposes a high-efficient hybrid recommendation system based on Fuzzy C-Means (FCM) clustering and supervised learning models. The proposed recommendation method includes two aspects: on the one hand, FCM clustering technique has been applied to the item-based collaborative filtering framework to solve the cold start problem; on the other hand, the content information is integrated into the collaborative filtering. The algorithm constructs the user and item membership degree feature vector, and adopts the data representation form of the scoring matrix to the supervised learning algorithm, as well as by combining the subjective membership degree feature vector and the objective membership degree feature vector in a linear combination, the prediction accuracy is significantly improved on the public datasets with different sparsity. The efficiency of the proposed system is illustrated by conducting several experiments on MovieLens dataset.

• Journal of Environmental Science International
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• v.20 no.12
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• pp.1541-1551
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• 2011

This study applied the Bayesian method for the quantification of the parameter uncertainty of spatial linear mixed model in the estimation of the spatial distribution of probability rainfall. In the application of Bayesian method, the prior sensitivity analysis was implemented by using the priors normally selected in the existing studies which applied the Bayesian method for the puppose of assessing the influence which the selection of the priors of model parameters had on posteriors. As a result, the posteriors of parameters were differently estimated which priors were selected, and then in the case of the prior combination, F-S-E, the sizes of uncertainty intervals were minimum and the modes, means and medians of the posteriors were similar to the estimates using the existing classical methods. From the comparitive analysis between Bayesian and plug-in spatial predictions, we could find that the uncertainty of plug-in prediction could be slightly underestimated than that of Bayesian prediction.

• Journal of Veterinary Clinics
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• v.20 no.1
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• pp.7-11
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• 2003

The selection of a test as a reference with no perfect sensitivity and specificity may lead to bias, yielding distortion of the diagnostic performance. This means it is inappropriate to use imperfect diagnostic tests as a reference method to identify infected patients in clinical environments. In this study, diagnostic performance of rapid urease test, polymerase chain reaction (PCR), and histology of gastric biopsy specimens for diagnosing Helicobacter pylori infection separately and in combination was estimated by using non-linear regression. Based on this approach, the sensitivity, specificity and likelihood ration positive and negative values for each test were as follows: urease test 99.9%, 99.9%, 99.9%, 99.6%, respectively; PCR 88.6%, 99.9%, 99.9%, 70.5%, respectively; histology 78.3%, 97%, 78.3%, 97%, respectively. Predictive values for positive and negative changes with varying Combination of three diagnostic tests employed in the study gives no substantial benefit for practitioners to screen infected patients, and urease test or PCR represents an appropriate single test in clinical environments.

• Bulletin of the Korean Chemical Society
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• v.13 no.2
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• pp.135-139
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• 1992

The mono(aryl)cyanoplatinum(II) complex $[Pt(CN)(C_6H_3{CH_2NMe_2}_2-26)]$, reacts with the dihalogens to yield the mono(aryl)cyanoplatinum complexes $[PtX_2(CN)(C_6H_3{CH_2NMe_2}_2-26)]$, (X = Cl, Br, I). The structural configuration of the two halogen atoms for a square planar platinum complex was studied by 1H-NMR spectroscopy and led to a mixture of trans and cis orientation. The trans orientation was found to be more stable in energy (1.33 kcal/mol) than the cis orientation by means of Extended H ckel calculations. On the base of a combination of the analysis of $^1H-NMR$, $^{13}C-NMR spectra and computational calculations it is assumed that the intermediate consists of an initial attack in the linear transition state, leading to the $S_{N}2$ type mechanism.

• Journal of Advanced Marine Engineering and Technology
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• v.28 no.2
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• pp.228-236
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• 2004

In this paper. we present a neuro-fuzzy controller which unifies both fuzzy logic and multi-layered feed forward neural networks. Fuzzy logic provides a means for converting linguistic control knowledge into control actions. On the other hand. feed forward neural networks provide salient features. such as learning and parallelism. In the proposed neuro-fuzzy controller. the parameters of membership functions in the antecedent part of fuzzy inference rules are identified by using the error back propagation algorithm as a learning rule. while the coefficients of the linear combination of input variables in the consequent part are determined by using the least square estimation method. Finally. the effectiveness of the proposed controller is verified through computer simulation for an inverted pole system.

• Journal of Advanced Marine Engineering and Technology
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• v.20 no.4
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• pp.11-19
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• 1996

Recently, fuzzy and neural network techniques have been successfully applied to control of complex and ill-defined system in a wide variety of areas, such as robot, water purification, automatic train operation system and automatic container crane operation system, etc. In this paper, we present a neuro-fuzzy controller which unifies both fuzzy logic and multi-layered feedforward neural networks. Fuzzy logic provides a means for converting linguistic control knowledge into control actions. On the other hand, feedforward neural networks provide salient features, such as learning and parallelism. In the proposed neuro-fuzzy controller, the parameters of membership functions in the antecedent part of fuzzy inference rules are identified by using the error backpropagation algorithm as a learning rule, while the coefficients of the linear combination of input variables in the consequent part are determined by using the least square estimation method. Finally, the effectiveness of the proposed controller is verified through computer simulation of an inverted pendulum system.

• Journal of Microbiology and Biotechnology
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• v.18 no.1
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• pp.118-123
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• 2008

A new method for antimicrobial susceptibility testing of vitro-cultured bacteria on an ordinary fluorescence spectrometer was developed. The viable bacteria reduced 3-(4,5 dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide (MTT) to produce insoluble particles that displayed intense resonance scattering light. The assay showed a linear relationship between the number of viable bacteria and the intensity of resonance scattering light. Dead bacteria were unable to reduce MTT. Methicillin-resistant Staphylococcus aureus exposed to flavonoids from Marchantia convoluta showed a flavonoids concentration-dependent inhibition of the ability to reduce MTT. In the assay, less than 12 h was required to attain susceptibility results and fewer bacteria were utilized than in traditional methods. The RLS technique could, in combination with the MTT assay, be a rapid and sensitive measuring method to determine the in vitro activity of new antimicrobials.