• Journal of Applied Reliability
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• v.14 no.1
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• pp.21-28
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• 2014

This paper presents an accelerated life test to estimate the lifetime of thermoelectric module for home water purifier. Clamping force and thermal cycle are selected as accelerating variables through the technical review about failure mechanism. It is assumed that its lifetime follows weibull distribution. The relationship, acceleration factor, and BP life at design condition are estimated by analyzing the accelerated life test data.

• Journal of Microbiology
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• v.39 no.3
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• pp.181-185
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• 2001

The morphological characteristics of newly isolated Cordyceps hepialidicola were characterized, and the phylogenetic relationships with other Cordyceps species were investigated using a sequence analysis of the internal transcribed spacer (ITS). The PCR product of 592 bp showed a homology of 92 and 91% with C. militaris and C. nutans, respectively, In an in vitro model using mouse peripheral blood mononuclear cells (PBMC), a methanol extract of C. hepialidicola induced multiple cytokines, including IFN-${\gamma}$ IL-4, and IL-18. The extract also enhanced the percentages of the CD4$\^$+/ and CD8$\sub$+/ T cells in the healthy murine PBMCs to 56.1% and 13.0%,respectively. The percentages of CD4$\^$+/ and CD8$\^$+/ in the untreated controls were 28.4 and 7.3%, and concanavalin A-treated positive controls were 62.4 and 18.3%, respectively.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.772-777
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• 1993

This paper presents a neuro-fuzzy modelling method that determines chemicals dosing model based on historical operation data for effective water quality control in water treatment system and calculates automatically the amount of optimum chemicals dosing against the changes of raw water qualities and flow rate. The structure identification in the modelling by means of neuro-fuzzy reasing is performed by Genetic Algorithm(GA) and Complex Method in which the numbers of hidden layer and its hidden nodes, learning rate and connection pattern between input layer and output layer are identified. The learning network is implemented utilizing Back Propagation(BP) algorithm. The effectiveness of the proposed modelling scheme and the feasibility of the acquired neuro-fuzzy network is evaluated through computer simulation for chemicals dosing control in water treatment system.

• Korean Journal of Adult Nursing
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• v.17 no.5
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• pp.772-782
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• 2005

Objectives: The purpose of this study was to investigate the relationship between Korean lifestyle characteristics and health status and to identify the variables influencing health in Korea. Methods: A cross-sectional descriptive correlational design was used to explore the lifestyle characteristics and health status of 397 Korean adults. Correlational analysis calculated the correlation between lifestyle and health status. To examine the relationship among demographic characteristics, lifestyle, and health status we used the t-test and one-way ANOVA. Stepwise multiple regression was conducted to examine the significant predictors of general health among subjects. Results: Positive correlations were seen between general health (GH) and the overall score and subscales of the Lifestyle. The stepwise regression model showed that vitality (VA), body pain (BP), nutrition, and occupation were significant variables influencing general health (GH). Conclusions: These findings provide evidence regarding the lifestyle patterns and healthstatus among Koreans. When planning intervention strategies for this population, exercise and physical activity should be principal focus areas.

• Structural Engineering and Mechanics
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• v.45 no.6
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• pp.779-802
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• 2013

In this paper, adaptive neuro-fuzzy inference system (ANFIS) and artificial neural networks (ANNs) techniques are developed and applied to identify damage in a model steel girder bridge using dynamic parameters. The required data in the form of natural frequencies are obtained from experimental modal analysis. A comparative study is made using the ANNs and ANFIS techniques and results showed that both ANFIS and ANN present good predictions. However the proposed ANFIS architecture using hybrid learning algorithm was found to perform better than the multilayer feedforward ANN which learns using the backpropagation algorithm. This paper also highlights the concept of ANNs and ANFIS followed by the detail presentation of the experimental modal analysis for natural frequencies extraction.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.260-264
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• 1998

In this paper, we implemented the neuro-computer called MY-NEUPOWER in our research to carry out the artificial neural networks (ANN) calculating. An application software was developed based on a neural network using back-propagation (BP) algorithm under the UNIX platform by the specified computer language named MYPARAL. This neural network model was used as an auxiliary controller in the temperature control of sinter cooler system in steel plant which is a nonlinear system. The neural controller was trained off-line using the real input-output data as training pairs. We also made the system description of adaptive neural controller on the same temperature control system. We will carry out the whole system simulation to verify the suitability of neural controller in improving the system features.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.972-974
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• 1993

This paper presents a new method to automatically design fuzzy logic controller(FLC). The main problems of designing FLC are how to optimally and automatically select the control rules and the parameters of membership function (MF). Cell state space algorithms (CSS), differential competitive learning (DCL) and multialyer neural network are combined in this paper to solve the problems. When the dynamical model of a control process is known. CSS can be used to generate a group of optimal input output pairs(X, Y) used by a controller. The(X, Y) then can be used to determine the FLC rules by DCL and to determine the optimal parameters of MF by DCL and to determine the optimal parameters of MF by multilayer neural network trained by BP algorithm.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2004.05b
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• pp.100-103
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• 2004

In this paper, BP learning algorithm is studied to apply as a PD source classification in GIS specimens. For occurred partial discharge, three defected models are made; floating particle, surface discharge of spacer, needle to plane. And PD data for discrimination were acquired from PD detector. And these data making use of a computer-aided discharge analyser, statistical and other discharge parameters is calculated to discrimination between different models of discharge sources. And also these parameter is applied to classify PD sources by neural networks. Neural Networks has good recognition rate for three PD sources.

• Proceedings of the Korea Water Resources Association Conference
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• 2001.05a
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• pp.45-51
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• 2001

The daily inflow is apparently one of nonlinear and complicated phenomena. The nonlinear and complexity make it difficult to model the prediction of daily flow, but attractive to try the neural networks approach which contains inherently nonlinear schemes. The study focuses on developing the forecasting models of daily inflows to a large dam site using neural networks. In order to reduce the error caused by high or low outliers, the back propagation algorithm which is one of neural network structures is modified by combining a regression algorithm. The study indicates that continuous forecasting of a reservoir inflow in real time is possible through the use of modified neural network models. The positive effect of the modification using tole regression scheme in BP algorithm is showed in the low and high ends of inflows.

• Advances in concrete construction
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• v.10 no.6
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• pp.499-507
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• 2020

In current study, utilizing the Kelvin's theory with polynomial, exponential and trigonometric volume fraction laws for functionally graded cylindrical shell vibrations. Effects of different parameters for ratios of length- and height-to-radius and angular speed versus fundamental natural frequencies been determined for two categories of cylindrical shells with clamped-free edge condition. By increasing different value of height-to-radius ratio, the resulting backward and forward frequencies increase and frequencies decrease on increasing length-to-radius ratio. Moreover, on increasing the rotating speed, the backward frequencies increases and forward frequencies decreases. The frequencies are same when the cylinder is stationary. The frequencies increases and decreases on changing the constituent materials. The frequency results are verified with the earlier literature for the applicability of present model.