• Geomechanics and Engineering
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• 제1권2호
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• pp.155-168
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• 2009

Breakdown pressures obtained from the classic, linear elastic breakdown model are compared with the corresponding pressures obtained using a nonlinear material model. Compression test results obtained on sandstone and siltstone are used for that purpose together with previously formulated nonlinear model which introduces elasticity functions to address nonlinear stress-strain behaviour of rocks exhibiting stress-dependent mechanical properties. Linear and nonlinear collapse pressures are also compared and it is shown that material nonlinearities have significant effect on both breakdown and collapse pressures and on tangential stresses which control breakdown pressure around a borehole. This means that the estimates of ${\sigma}_H$ made using linear models give stress values which are different than the real values in the earth. Thus the importance of a more accurate analysis, such as provided by the nonlinear models, is emphasised. It is shown, however, that the linear elastic model does not necessarily over-predict borehole stresses and the opposite case can be true, depending on rock type and test interpretation.

• 물과 미래
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• 제19권3호
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• pp.267-276
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• 1986

본 연구에서는 정도높은 홍수유출모델을 결정함에 있어서, 선형모델과 비선형모델을 적용, 검토하므로서 홍수유출해석에 적합한 모델을 선정하는데 그 목적을 두었다. 분석에 사용된 모델은 선형모델로서는 Nash 모델과 유출함수법, 그리고 비선형모델로서는 Tank 모델과 저장함수법을 각각 적용하였다. 이들 각 모델들을 낙동강 유역의 대표시험유역인 위천유역의 홍수자료를 이용하여 분석한 결과, 비선형 모델이 선형모델보다 첨두유량, 첨두발생시간 및 홍수수문곡선에서 실측치와 잘 일치하였으며 홍수유출모델로서 비선형모델이 적합함을 알 수 있었다.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1995년도 추계학술대회 학술발표 논문집
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• pp.303-306
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• 1995

In this study we present the inverse correlation method to select the exploratory variables, while Sugeno used RC method in his paper[6] We assume linear model with measurement error variables as in Fuller's Book[9]. we provide possibilistic linear model and predict the fuzzy response variable in case of fuzzy exploratory variables. By plotting data we can divide them for piecewise plane and provide the piecwise possibilistic linear model. If the exploratory variable is fuzzy trapezoidal variable or interval variable, then we estimate fuzzy trapezoidal variable or interval variable, then we estimate fuzzy trapezoidal response variable respondent to it. We will illustrate using Nonlinear System data in Sugeno's paper

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.387-389
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• 2003

Rational function model (RFM) is a universal sensor model for remote sensing image restitution. It is able to substitute for models of all known sensors. In this paper, RFM generation by CCD linear image models is described in detail. A principle of RFM-based 3D reconstruction and its implementation in JX4 DPW is also described. Experiments using IKONOS and SPOT5 images are carried out on JX4 DPW. Results show that RFM generated is feasible for photogrammetric restitution of CCD linear images.

• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2020년도 제62차 하계학술대회논문집 28권2호
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• pp.139-142
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• 2020

NB-IoT(Narrow Band Internet of Things) is an emerging LPWAN(Low Power Wide Area Network) radio technology. NB-IoT has many advantages like low power, low cost, and high coverage. However low bandwidth and low sampling rates also lead to poor positioning accuracy. This paper proposed a solution to optimize positioning accuracy under the OTDOA(Observed Time Difference of Arrival) approach by utilizing MLR(Multiple Linear Regression) models. Through the MLR model to predict the influence degree of weather(temperature, humidity, light intensity and air pressure) on the arrival time of signal transmission to improve the measurement accuracy. The improvement of measurement accuracy can greatly improve IoT applications based on NB-IoT.

• International journal of advanced smart convergence
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• 제13권1호
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• pp.206-211
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• 2024

This study used a total of 205,565 datasets of 'voltage', 'current', '℃', and 'time(s)' to systematically analyze the properties and performance of solid electrolytes. As a method for characterizing solid electrolytes, a linear regression model, one of the machine learning models, is used to visualize the relationship between 'voltage' and 'current' and calculate the regression coefficient, mean squared error (MSE), and coefficient of determination (R^2). The regression coefficient between 'Voltage' and 'Current' in the results of the linear regression model is about 1.89, indicating that 'Voltage' has a positive effect on 'Current', and it is expected that the current will increase by about 1.89 times as the voltage increases. MSE found that the mean squared error between the model's predicted and actual values was about 0.3, with smaller values closer to the model's predictions to the actual values. The coefficient of determination (R^2) is about 0.25, which can be interpreted as explaining 25% of the data.

• 제어로봇시스템학회논문지
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• 제13권8호
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• pp.760-768
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• 2007

This paper introduces an emotional behavior decision model based on linear system for intelligent service robots. An emotional model should make different behavior decisions according to the purpose of the robots. We propose an emotional behavior decision model which can change the character of intelligent service robots and make different behavior decisions although the situation and environment remain the same. We defined each emotional element such as reactive dynamics, internal dynamics, emotional dynamics, and behavior dynamics by state dynamic equations. The proposed system model is a linear dynamic system. If you want to add one external stimulus or behavior, you need to add just one dimensional vector to the matrix of external stimulus or behavior dynamics. The case of removing is same. The change of reactive dynamics, internal dynamics, emotional dynamics, and behavior dynamics also follows the same procedure. We implemented a cyber robot and an emotional head robot using 3D character for verifying the performance of the proposed emotional behavior decision model.

• Computers and Concrete
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• 제20권1호
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• pp.11-22
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• 2017

There are two methods to model the plastification of members comprising lumped and distributed plasticity. When a reinforced concrete member experiences inelastic deformations, cracks tend to spread from the joint interface resulting in a curvature distribution; therefore, the lumped plasticity methods assuming plasticity is concentrated at a zero-length plastic hinge section at the ends of the elements, cannot model the actual behavior of reinforced concrete members. Some spread plasticity models including uniform, linear and recently power have been developed to take extended inelastic zone into account. In the aforementioned models, the extended inelastic zones in proximity of critical sections assumed close to connections are considered. Although the mentioned assumption is proper for the buildings simply imposed lateral loads, it is not appropriate for the gravity load effects. The gravity load effects can influence the inelastic zones in structural elements; therefore, the plasticity models presenting the flexibility distribution along the member merely based on lateral loads apart from the gravity load effects can bring about incorrect stiffness matrix for structure. In this study, the linear flexibility distribution model is improved to account for the distributed plasticity of members subjected to both gravity and lateral load effects. To do so, a new model in which, each member is taken as one structural element into account is proposed. Some numerical examples from previous studies are assessed and outcomes confirm the accuracy of proposed model. Also comparing the results of the proposed model with other spread plasticity models illustrates glaring error produced due to neglecting the gravity load effects.

• 응용통계연구
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• 제28권2호
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• pp.221-230
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• 2015

전통적으로 반복 측정된 형제 쌍 연관 분석에서는 선형 혼합 모형이 사용되어 왔다. 그러나 그 모형은 관심있는 표현형과 연관된 유전자좌를 찾는 것에 있어서 검정력이 문제가 되는 것으로 지적되어 왔다. 본 연구에서 우리는 이러한 검정력 문제를 개선하는 방법으로 감마 혼합 모형을 고려하였고, 검정력과 제 1종 오류의 관점에서 선형 혼합 모형과 성능을 서로 비교하여 보았다. Genetic Analysis Workshop 13에서 제공된 자료를 이용하여 살펴본 결과, 감마 혼합 모형이 검정력에 있어서 큰 이득을 볼 수 있는 것으로 나타났다.

• 한국운동역학회지
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• 제28권2호
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• pp.127-134
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• 2018

Objective: In a statistical linear model estimating the center of rotation of a human hip joint, which is the parameter related to the mean of response vectors, assumptions of homoscedasticity and independence of position vectors measured repeatedly over time in the model result in an inefficient parameter. We, therefore, should take into account the variance-covariance structure of longitudinal responses. The purpose of this study was to estimate the efficient center of rotation vector of the hip joint by using covariance pattern models. Method: The covariance pattern models are used to model various kinds of covariance matrices of error vectors to take into account longitudinal data. The data acquired from functional motions to estimate hip joint center were applied to the models. Results: The results showed that the data were better fitted using various covariance pattern models than the general linear model assuming homoscedasticity and independence. Conclusion: The estimated joint centers of the covariance pattern models showed slight differences from those of the general linear model. The estimated standard errors of the joint center for covariance pattern models showed a large difference with those of the general linear model.