The efficiency evaluation of the railway lines performance is done through a set of indicators and criteria, the most important are transport density, the productivity of enrollee, passenger vehicle production, the productivity of freight wagon, and the productivity of locomotives. This study includes an attempt to calculate the most important of these indicators which transport density index from productivity during the four indicators, using artificial neural network technology. Two neural networks software are used in this study, (Simulnet) and (Neuframe), the results of second program has been adopted. Training results and test to the neural network data used in the study, which are obtained from the international in

The permeability estimates for the uncored wells and a porosity function adopting a modified flow zone index-permeability crossplot are given in this work. The issues with implementing that approach were mostly crossplots, due to the influence of geological heterogeneity, did not show a clear connection (scatter data). Carbonate reservoir flow units may now be identified and characterized using a new approach, which has been formally confirmed. Due to the comparable distribution and flow of clastic and carbonate rock fluids, this zoning method is most effective for reservoirs with significant primary and secondary porosity. The equations and correlations here are more generalizable since they connect these variables by combining cor

Channel estimation (CE) is essential for wireless links but becomes progressively onerous as Fifth Generation (5G) Multi-Input Multi-Output (MIMO) systems and extensive fading expand the search space and increase latency. This study redefines CE support as the process of learning to deduce channel type and signal-tonoise ratio (SNR) directly from per-tone Orthogonal Frequency-Division Multiplexing (OFDM) observations,with blind channel state information (CSI). We trained a dual deep model that combined Convolutional Neural Networks (CNNs) with Bidirectional Recurrent Neural Networks (BRNNs). We used a lookup table (LUT) label for channel type (class indices instead of per-tap values) and ordinal supervision for SNR (0–20 dB,5-dB steps). T

The content of fatty acid methyl esters (FAME) is a crucial property of biodiesel and serves as an indicator of the transesterification reaction that converts vegetable oil into biodiesel. To facilitate the rapid estimation of FAME quickly in the biodiesel industries, simple methods such as measuring refractive index, density, and dynamic viscosity measurements were employed to monitor the progress of transesterification of castor oil to biodiesel. Blends of castor oil and biodiesel were mixed at different weights to find correlations between FAME content and refractive index, density, and dynamic viscosity measurements. The transesterification of castor oil with methanol was carried out to examine how the refractive index, density,

Regression Discontinuity (RD) means a study that exposes a definite group to the effect of a treatment. The uniqueness of this design lies in classifying the study population into two groups based on a specific threshold limit or regression point, and this point is determined in advance according to the terms of the study and its requirements. Thus , thinking was focused on finding a solution to the issue of workers retirement and trying to propose a scenario to attract the idea of granting an end-of-service reward to fill the gap ( discontinuity point) if it had not been granted. The regression discontinuity method has been used to study and to estimate the effect of the end -service reward on the cutoff of insured workers as well as t

Background: Speckle tracking echocardiography (STE)-derived mitral annular displacement (MAD) utilizes the speckle tracking technique to measure strain vectors, which provides accurate estimates of left ventricular ejection fraction (LVEF).Objectives: To validate the accuracy of mitral annular displacement (MAD), assessed by Speckle Tracking Echocardiography (STE), as a surrogate for determination of left ventricular systolic function in comparison to 2-Dimensions Simpson method in patients with different heart diseases.Methods : This cross-sectional study included patients who referred to outpatient department of Ibn Albitar Center for Cardiac Surgery, Baghdad, Iraq, between October 2012 and April 2013. STE continuously tracked annular

Use of lower squares and restricted boxes
In the estimation of the first-order self-regression parameter
AR (1) (simulation study)

Abstract

The analysis of Least Squares: LS is often unsuccessful in the case of outliers ​​in the studied phenomena. OLS will lose their properties and then lose the property of Beast Linear Unbiased Estimator (BLUE), because of the Outliers have a bad effect on the phenomenon. To address this problem, new statistical methods have been developed so that they are not easily affected by outliers. These methods are characterized by robustness or (resistance). The Least Trimmed Squares: LTS method was therefore a good alternative to achieving more feasible results and optimization. However, it is possible to assume weights that take into consideration the location of the outliers ​​in the data and det