This study aims at quantifying spatio-temporal dynamics of monthly mean dailyincident photosynthetically active radiation (PAR) over a vast and complex terrain such asTurkey. The spatial interpolation method of universal kriging, and the combination ofmultiple linear regression (MLR) models and map algebra techniques were implemented togenerate surface maps of PAR with a grid resolution of 500 ...

State-of-the-art passive microwave remote sensing-based snow water equivalent (SWE) algorithms correct for factors believed to most significantly affect retrieved SWE bias and uncertainty. For example, a recently developed semi-empirical SWE retrieval algorithm accounts for systematic and random error caused by forest cover and snow morphology (crystal size — a function of location and time of ...

Forecasting is a systematic attempt to examine the future by inference from known facts. Sales forecasting is an ballpark figure of sales during a specified future period. Formerly, it was a manual process using the mathematical formulas. Due to the advent of computer the process of sale forecasting is fast and accurate. Machine learning, a subfield of Artificial Intelligence, has many algorith...

INTRODUCTION This study aimed at investigating the applicability of a polynomial function laterally, combined with a parabola or hyperbolic cosine function in the front, for mandibular curve-fitting purposes in late mixed dentition patients with crowding. The possible advantages of using a bilateral center of gravity for curve construction were examined. METHODS After digitizing 30 mandibular...

Recently, Busch, Lahti, and Werner [1] claimed that Heisenberg’s error-disturbance relation can be proved in its original form with new formulations of error and disturbance, in contrast to the theory proposed by the present author [2–5] and confirmed by recent experiments [6–9]. Despite their claim, it is shown here that a class of solvable models of position measurement with explicit interact...

An improved system blind identification method based on secondorder cyclostationary statistics and the properties of group delay, has been proposed. This is achieved by applying a correction to the estimated phase (by the spectral correlation density of the system output) for the poles, in the group delay domain. The results indicate a significant improvement in system blind identification, in ...

This paper highlights the significance of Time-Delay ANN models for predicting shelf life of processed cheese stored at 7-8 o C. Bayesian regularization algorithm was selected as training function. Number of neurons in single and multiple hidden layers varied from 1 to 20. The network was trained with up to 100 epochs. Mean square error, root mean square error, coefficient of determination and ...

In this paper, a transform based methodology is presented for compression of electrocardiogram (ECG) signal. The methodology employs different transforms such as Discrete Wavelet Transform (DWT), Fast Fourier Transform (FFT) and Discrete Cosine Transform (DCT). A comparative study of performance of different transforms for ECG signal is made in terms of Compression ratio (CR), Percent root mean...

Changes in electromyographic (EMG) parameters are used to evaluate timing, amplitude, and fatigue of muscle actions during movement. Little published data describe the reliability and precision of multiple EMG parameters, how these parameters compare to one another, and how these parameters vary between muscles. The purpose of this study was to determine the reliability and precision of four EM...