Linear Model Research Papers - Academia.edu (original) (raw)

Abstract: An iterative linear stochastic pavement management model is proposed that deploys a nonhomogenous discrete-time Markov chain for predicting the future pavement conditions for a given pavement network. A nonhomogenous transition... more

Abstract: An iterative linear stochastic pavement management model is proposed that deploys a nonhomogenous discrete-time Markov chain for predicting the future pavement conditions for a given pavement network. A nonhomogenous transition matrix is constructed to incorporate both the pavement deterioration rates and improvement rates. The pavement deterioration rates are simply the transition probabilities associated with the deployed pavement states. The improvement rates are mainly the maintenance and rehabilitation variables representing the deployed maintenance and rehabilitation actions. A decision policy is formulated to identify the optimal set of maintenance and rehabilitation actions and their respective timings, and to provide the optimal level of maintenance and rehabilitation funding over an analysis period. The nonhomogenous Markov chain allows for a distinct maintenance and rehabilitation plan ͑matrix͒ for each time interval ͑transition͒. However, the total number of ma...

Os modelos polinomiais são mais difundidos no meio florestal brasileiro na descrição do perfil de árvores devido à sua facilidade de ajuste e precisão. O mesmo não ocorre com os modelos não-lineares, os quais possuem maior dificuldade de... more

Os modelos polinomiais são mais difundidos no meio florestal brasileiro na descrição do perfil de árvores devido à sua facilidade de ajuste e precisão. O mesmo não ocorre com os modelos não-lineares, os quais possuem maior dificuldade de ajuste. Dentre os modelos não-lineares clássicos, na descrição do perfil, podem-se citar o de Gompertz, o Logístico e o de Weibull. Portanto, este estudo visou comparar os modelos lineares e não lineares para a descrição do perfil de árvores. As medidas de comparação foram o coeficiente de determinação (R²), o erro-padrão residual (s yx), o coeficiente de determinação corrigido (R²ajustado), o gráfico dos resíduos e a facilidade de ajuste. Os resultados ressaltaram que, dentre os modelos não-lineares, o que obteve melhor desempenho, de forma geral, foi o modelo Logístico, apesar de o modelo de Gompertz ser melhor em termos de erro-padrão residual. Nos modelos lineares, o polinômio proposto por Pires & Calegario foi superior aos demais. Ao comparar o...

Evaluation of emerging diesel-particulate emissions control technology will require analytical procedures capable of continuous measurement of transient organic and elemental carbon emissions. Procedures based on the flame ionization... more

Evaluation of emerging diesel-particulate emissions control technology will require analytical procedures capable of continuous measurement of transient organic and elemental carbon emissions. Procedures based on the flame ionization properties of organic carbon and ...

The aim of the research was to monitor and assess landslide hazards by remote sensing data processing and GIS spatial analysis. The automatic classification of remote sensing images provides many useful land use information to combine in... more

The aim of the research was to monitor and assess landslide hazards by remote sensing data processing and GIS spatial analysis. The automatic classification of remote sensing images provides many useful land use information to combine in a GIS environment with other spatial factors influencing the occurrence of landslide. The upper part of Susa Valley, in the Italian Western Alps, was chosen as test area because of a large variety of remote sensing data available by ISPRS WG VIII/2 with the aim to exchange information and experience in the field of geomatic techniques. It is well known that the occurrence of landslides is controlled by a lot of morphological, geological, and human factors. We have chosen, regarding the available data, the following factors: acclivity, aspect, lithology, land use and precipitations. We have built up a mathematical predictive model enabling actual/potential unstable slopes. It is a linear model where the hazard score depends on instability factors and...

A new nonlinear integral-equation model is derived in terms of hodograph variables for free-surface flow past an arbitrary bottom obstruction. A numerical method, carefully chosen to solve the resulting nonlinear algebraic equations and a... more

A new nonlinear integral-equation model is derived in terms of hodograph variables for free-surface flow past an arbitrary bottom obstruction. A numerical method, carefully chosen to solve the resulting nonlinear algebraic equations and a simple, yet effective radiation condition have led to some very encouraging results. In this paper, results are presented for a semi-circular obstruction and are compared with

The relationship between Fisher's fundamental theorem of natural selection and the ecological environment of density regulation is examined. Using a linear model, it is shown that the theorem holds when density regulation is caused by... more

The relationship between Fisher's fundamental theorem of natural selection and the ecological environment of density regulation is examined. Using a linear model, it is shown that the theorem holds when density regulation is caused by exploitative competition and that the theorem fails with interference competition. In the latter case the theorem holds only at the limit of zero population density and/or at the limit where the competitively superior individuals cannot monopolize the resource. The results are discussed in relation to population dynamics and life history evolution, where evidence suggests that the level of interference competition in natural populations is so high that the fundamental theorem does not apply.

In this paper, we consider constructing reliable confidence intervals for regression parameters using robust M-estimation allowing for the possibility of time series correlation among the errors. The change of variance function is used to... more

In this paper, we consider constructing reliable confidence intervals for regression parameters using robust M-estimation allowing for the possibility of time series correlation among the errors. The change of variance function is used to approximate the theoretical coverage ...

This work proposes a methodology of identifying linear parameter varying (LPV) models for nonlinear systems. First, linear local models in some operating points, by applying standard identifications procedures for linear systems in time... more

This work proposes a methodology of identifying linear parameter varying (LPV) models for nonlinear systems. First, linear local models in some operating points, by applying standard identifications procedures for linear systems in time domain, are obtained. Next, a LPV model with linear fractional dependence (LFR) with respect to measured variables is fitted with the condition of containing all the linear models identified in previous step (differential inclusion). The fit is carried out using nonlinear least squares algorithms. Finally, this identification methodology will then be applied to a nonlinear turbocharged diesel engine.

We tested the hypothesis that vibratory thresholds in the elderly are related to mobility. In all, 629 older persons without dementia underwent testing including 11 lower extremity performance measures and modified United Parkinson's... more

We tested the hypothesis that vibratory thresholds in the elderly are related to mobility. In all, 629 older persons without dementia underwent testing including 11 lower extremity performance measures and modified United Parkinson's Disease Rating Scale (UPDRS), summarized as composite mobility and global parkinsonian signs. Vibratory thresholds were measured at the ankle and toes bilaterally using the graduated Rydel–Seiffer tuning fork. In linear regression models adjusted for age, sex, and education, vibratory threshold was associated with composite mobility (estimate, 0.047, SE = 0.011, P < 0.001) and global parkinsonian signs score (estimate, −0.252, SE = 0.126, P = 0.047). These findings were primarily due to the association of vibratory threshold with gait and balance components of composite mobility and parkinsonian gait. These results were unchanged when we controlled for body mass index, physical activity, cognition, depression, vascular risk factors, vascular disease burden, joint pain, and falls. Vibratory thresholds are associated with mobility, supporting the link between peripheral sensory nerve function and mobility in the elderly. Muscle Nerve, 2009

In this paper, a new formulation of the problem of mass and energy balance equilibration in the case of unknown-but-bounded errors is proposed. The bounds of the errors are specified over both a measurement noise and the balance... more

In this paper, a new formulation of the problem of mass and energy balance equilibration in the case of unknown-but-bounded errors is proposed. The bounds of the errors are specified over both a measurement noise and the balance equations. Both bounds are mainly motivated by experimental considerations of the measurement precision; with a more general interpretation, they can be considered as parameters that the user has to adjust to make the reconciliation possible. The method is particularly suitable for linear models but has been extended to nonlinear ones as well. Simulations provide results that compare favorably with those of classical reconciliation methods involving maximum likelihood estimation based on statistical knowledge of the measurement errors.

Measurement error occurs when one or more regression model covariates are measured with error, and is a common problem in occupational health and other fields. If the effects of measurement error are not corrected, estimates of the... more

Measurement error occurs when one or more regression model covariates are measured with error, and is a common problem in occupational health and other fields. If the effects of measurement error are not corrected, estimates of the regression coefficients and their variances are biased. We consider the situation when an external validation study provides information about the measurement error process. Two related approaches for correcting measurement error, both called regression calibration, have been proposed. Although the estimators for the corrected regression coefficients can be shown to be the same under the two approaches, the asymptotic variances are derived using two different methods and have not been compared. In this paper, we show that these two methods give algebraically identical estimators for the corrected regression coefficients and their asymptotic variances, in the general case of multiple covariates measured with error, for a generalized linear model of exponen...

We discuss types of clustering problems where error information associated with the data to be clustered is readily available and where error-based clustering is likely to be superior to clustering methods that ignore error. We focus on... more

We discuss types of clustering problems where error information associated with the data to be clustered is readily available and where error-based clustering is likely to be superior to clustering methods that ignore error. We focus on clustering derived data (typically parameter ...

The growing demand for link bandwidth and node capacity is a frequent phenomenon in IP network backbones. Within this context, traffic prediction is essential for the network operator. Traffic prediction can be undertaken based on link... more

The growing demand for link bandwidth and node capacity is a frequent phenomenon in IP network backbones. Within this context, traffic prediction is essential for the network operator. Traffic prediction can be undertaken based on link traffic or on origin-destination (OD) traffic which presents better results. This work investigates a methodology for traffic prediction based on multidimensional OD traffic, focusing on the stage of short-term traffic prediction using Principal Components Analysis as a technique for dimensionality reduction and a Local Linear Model based on K-means as a technique for prediction and trend analysis. The results validated with data on a real network present a satisfactory margin of error for use in practical situations.