In the context of forest modeling, it is often reasonable to assume a mukiplicative heteroscedastic error structure to the data. Under such circumstances ordinary least squares no longer provides minimum variance estimates of the model parameters. Through study of the error structure, a suitable error variance model can be specified and its parameters estimated. This error model is used to cons...

Introduction Patient set-up optimization is required in radiotherapy to fill the accuracy gap between personalized treatment planning and uncertainties in the irradiation set-up. In this study, we aimed to develop a new method based on neural network to estimate patient geometrical setup using 4-dimensional (4D) XCAT anthropomorphic phantom. Materials and Methods To access 4D modeling of motion...

orange (citrus cinensis) is one of the most important among citrus fruits. the thin layer drying kinetics of orange (thompson variety) slice was here experimentally investigated in a convective dryer and through mathematical modeling and by use of thin layer drying models. drying characteristics of oranges were determined using heated ambient air at temperatures from 40 to 80 °c and velocities ...

The present paper analyzes the existence of a long-run relationship between the trade balance and exchange rate of Iran and South Korea by a new approach. It proposes an asymmetric co-integrating NARDL model by two positive and negative partial sum decompositions which can use mixed I (0) and I (1) variables by bounds testing approach. The proposed tests are based on calculated F –statistics an...

Precipitation is a major input in hydrological models. Radar rainfall data compared with rain gauge measurements provide higher spatial and temporal resolutions. However, radar data obtained form reflectivity patterns are subject to various errors such as errors in reflectivity-rainfall Z-R relationships, variation in vertical profile of reflectivity, and spatial and temporal sampling among oth...

In this paper, a semiparametric modeling approach is introduced as a paradigm for addressing model error arising from unresolved physical phenomena. Our approach compensates for model error by learning an ancillary dynamical model for the unknown parameters. Practically, the proposed approach consists of the following steps. Given a physics-based model and a noisy data set of historical observa...

This paper presents a novel modeling and compensation approach for the angular transmission error in harmonic drive gearings. In the modeling, physical phenomena of the transmission error due to nonlinear elastic deformations in micro-displacement region are especially dealt with, as well as the synchronous component which has been discussed in a variety of conventional studies. Based on the an...