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

This study discussed a biased estimator of the Negative Binomial Regression model known as (Liu Estimator), This estimate was used to reduce variance and overcome the problem Multicollinearity between explanatory variables, Some estimates were used such as Ridge Regression and Maximum Likelihood Estimators, This research aims at the theoretical comparisons between the new estimator (Liu Estimator) and the estimators

Poverty phenomenon is very substantial topic that determines the future of societies and governments and the way that they deals with education, health and economy. Sometimes poverty takes multidimensional trends through education and health. The research aims at studying multidimensional poverty in Iraq by using panelized regression methods, to analyze Big Data sets from demographical surveys collected by the Central Statistical Organization in Iraq. We choose classical penalized regression method represented by The Ridge Regression, Moreover; we choose another penalized method which is the Smooth Integration of Counting and Absolute Deviation (SICA) to analyze Big Data sets related to the different poverty forms in Iraq. Euclidian Distanc

In this investigation, deep eutectic solvent based on propionic acid and choline chloride was used to prepare polyaniline, polypyrrole, and poly(aniline-co-pyrrole) samples using chemical oxidation and polymerization. Quantum mechanical calculations were conducted using time-dependent density functional theory to determine the electronic, spectroscopic properties and structure of homopolymers and the copolymer which were compared with the respective experimental data. Furthermore, the synthesized materials were characterized using Fourier transform IR spectroscopy, scanning electron microscopy (SEM), UV-visible spectroscopy, and thermogravimetric analysis. IR and UV-visible spectra confirmed copolymerization, and SEM revealed that the copol

This paper introduces a non-conventional approach with multi-dimensional random sampling to solve a cocaine abuse model with statistical probability. The mean Latin hypercube finite difference (MLHFD) method is proposed for the first time via hybrid integration of the classical numerical finite difference (FD) formula with Latin hypercube sampling (LHS) technique to create a random distribution for the model parameters which are dependent on time [Formula: see text]. The LHS technique gives advantage to MLHFD method to produce fast variation of the parameters’ values via number of multidimensional simulations (100, 1000 and 5000). The generated Latin hypercube sample which is random or non-deterministic in nature is further integ

This study rigorously investigates three 3d transition metal carbide (TMC) structures via LDA and GGA approximations. It examines cohesive energy (Ecoh), Vickers hardness (Hv), mechanical stability, and electronic properties. Notably, most 3d TMCs exhibit higher cohesive energy than nitrides, and rs-TiC demonstrates a Vickers hardness of 25.66 GPa, outperforming its nitride counterpart. The study employs theoretical calculations to expedite research, revealing mechanical stability in CrC and MnC (GGA) and CrC (LDA in cc structure), while all 3d TMCs in rs and seven in zb structures show stability. Charge transfer and bonding analysis reveal enhanced covalency along the series, influenced by the interplay between p orbitals of carbon and d o

Mature oil reservoirs surrounded with strong edge and bottom water drive aquifers experience pressure depletion and water coning/cresting. This laboratory research investigated the effects of bottom water drive and gas breakthrough on immiscible CO2-Assisted Gravity Drainage (CO2-AGD), focusing on substantial bottom water drive. The CO2-AGD method vertically separates the injected CO2 to formulate a gas cap and Oil. Visual experimental evaluation of CO2-AGD process performance was performed using a Hele-Shaw model. Water-wet sand was used for the experiments. The gas used for injection was pure CO2, and the “oleic” phase was n-decane with a negative spreading coefficient. The aqueous phase was deionized water. To evaluate the feasibilit