• Computers and Concrete
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• v.18 no.6
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• pp.1113-1134
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• 2016

A methodology using neural networks has been proposed for rapid prediction of inelastic bending moments in reinforced concrete continuous beams subjected to service load. The closed form expressions obtained from the trained neural networks take into account cracking in concrete at in-span and at near the internal supports and tension stiffening effect. The expressions predict the inelastic moments (considering the concrete cracking) from the elastic moments (neglecting the concrete cracking) at supports. Three separate neural networks are trained since these have been postulated to represent all the beams having any number of spans. The training, validating, and testing data sets for the neural networks are generated using an analytical-numerical procedure of analysis. The proposed expressions are verified for example beams of different number of spans and cross-section properties and the errors are found to be small. The proposed expressions, at minimal input data and computation effort, yield results that are close to FEM results. The expressions can be used in preliminary every day design as they enable a rapid prediction of inelastic moments and require a computational effort that is a fraction of that required for the available methods in literature.

• Journal of the Korean Society for Precision Engineering
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• v.25 no.7
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• pp.79-86
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• 2008

This paper describes the development of wearing intelligent shoe system to measure applied forces and moments (ground reaction forces and moments) on the soles of feet during human walking. In order to walk safely, robot must get the intelligent feet with 6-axis force/moment sensors (Fx sensor (x-direction force sensor), Fy sensor, Fz sensor, Mx sensor (Mx : x-direction moment sensor), My sensor, and Mz sensor) and detect the forces and moments data from the sensors. And the feet must be controlled with the data and controllers. While a human is walking, the forces and moments should be measured and analyzed for robot's intelligent feet. Therefore, the wearing intelligent shoe system should be developed. In this paper, four 6-axis farce/moment sensors and two high speed measuring devices were designed and fabricated, and the wearing intelligent shoe system was made using these. The characteristic tests of the wearing intelligent shoe system were performed, and the forces and moments were detected using it.

• Structural Engineering and Mechanics
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• v.39 no.2
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• pp.267-285
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• 2011

There can be a significant amount of moment redistribution in composite frames consisting of steel columns and composite beams, due to cracking, creep and shrinkage of concrete. Considerable amount of computational effort is required for taking into account these effects for large composite frames. A methodology has been presented in this paper for taking into account these effects. In the methodology that has been demonstrated for moderately high frames, neural network models are developed for rapid prediction of the inelastic moments (typically for 20 years, considering instantaneous cracking, and time effects, i.e., creep and shrinkage, in concrete) at a joint in a frame from the elastic moments (neglecting instantaneous cracking and time effects). The proposed models predict the inelastic moment ratios (ratio of elastic moment to inelastic moment) using eleven input parameters for interior joints and seven input parameters for exterior joints. The training and testing data sets are generated using a hybrid procedure developed by the authors. The neural network models have been validated for frames of different number of spans and storeys. The models drastically reduce the computational effort and predict the inelastic moments, with reasonable accuracy for practical purposes, from the elastic moments, that can be obtained from any of the readily available software.

• Journal of Korean Academic Society of Home Health Care Nursing
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• v.25 no.2
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• pp.165-174
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• 2018

Purpose: The study investigated the knowledge and compliance on hand hygiene moments among nursing care workers in geriatric hospitals. Methods: A total of 143 nursing care workers at geriatric hospitals were selected. Data collection was conducted from February 20 to March 20, 2017. Results: For all hand hygiene scenarios, the total correct answer rate was 71.5%. On the necessary hand hygiene moments, the compliance rate was 68.3%. With respect to the general characteristics of the participants, knowledge on hand hygiene moments showed a statistically significant difference according to clinical career(p=.001), and existence of infection controller or infection control office in the nursing home(p=.038). Compliance showed differences according to clinical career(p=.023), existence of infection controller or infection control office in the nursing home(p=.033), and training experience in hand hygiene(number of times/year)(p=.035). Knowledge and compliance showed a statistically significant positive correlation(r=.90, p<.001). Conclusions: It is necessary to develop and operate an infection control education program that can improve the knowledge and awareness of hand hygiene moments and considers the individual characteristics geriatric hospitals's nursing care workers.

• Journal of the Korean Society of Safety
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• v.17 no.4
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• pp.189-195
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• 2002

The differential quadrature method (DQM) is applied to computation of the eigenvalues of out-of-plane bucking of curved beams. Critical moments including the effect of radial stresses are calculated for a single-span wide-flange beam subjected to equal and opposite in-plane bending moments with various end conditions, and opening angles. Results are compared with existing exact solutions where available. The differential quadrature method gives good accuracy even when only a limited number of grid points is used. New results are given for two sets of boundary conditions not previously considered for this problem: clamped-clamped and clamped-simply supported ends.

• East Asian mathematical journal
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• v.34 no.1
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• pp.59-67
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• 2018

We present new recurrence formulas for the raw and central moments of a compound binomial random variable. Our approach involves relating two compound binomial random variables that have parameters with a difference of 1 for the number of trials, but which have the same parameters for the success probability for each trial. As a consequence of our recursions, the raw and central moments of a binomial random variable are obtained in a recursive manner without the use of Stirling numbers.

• Journal of the Korean Data and Information Science Society
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• v.22 no.3
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• pp.505-513
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• 2011

In this paper, we obtain the derivations of moments of discrete probability distributions by using the backward difference operators. Also, we presents such derivations for several well-known distributions; they are the binomial, Poisson, geometric, hypergeometric and negative hypergeometric distributions.

• Bulletin of the Korean Mathematical Society
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• v.49 no.3
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• pp.495-510
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• 2012

Let $X_1$, $X_2$,${\ldots}$, $X_n$ be a sequence of independent and identically distributed random variables with common distribution function $F$. Convergence rates for the moments of extremes are studied by virtue of second order regularly conditions. A unified treatment is also considered under second order von Mises conditions. Some examples are given to illustrate the results.

• Communications for Statistical Applications and Methods
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• v.14 no.3
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• pp.679-686
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• 2007

Moment expressions are derived for the internally truncated normal distributions commonly applied to screening and constrained problems. They are obtained from using a recursive relation between the moments of the normal distribution whose distribution is truncated in its internal part. Closed form formulae for the moments can be presented up to $N^{th}$ order under the internally truncated case. Necessary theories and two applications are provided.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1997.06a
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• pp.113-118
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• 1997

This paper proposes a object tracking method based on the local moments, or moment based on the local moments, or moment of some restricted area, in which the idea of the viewpoint and the visual filed corresponding to the local area of an image is introduced. Using local moment with the optimally controlled viewpoint and visual field, the target position and its breadth are estimated robustly. By two experiments, the validity of the proposed method is shown.