The aim of this research is to construct a three-dimensional maritime transport model to transport nonhomogeneous goods (k) and different transport modes (v) from their sources (i) to their destinations (j), while limiting the optimum quantities v ijk x to be transported at the lowest possible cost v ijk c and time v ijk t using the heuristic algorithm, Transport problems have been widely studied in computer science and process research and are one of the main problems of transport problems that are usually used to reduce the cost or times of transport of goods with a number of sources and a number of destinations and by means of transport to meet the conditions of supply and demand. Transport models are a key tool in logistics and supply chain management to reduce costs, times or improve services, In this study Three algorithms were proposed to solve the transport matrix (Range(R), Arithmetic Mean(AM), Cost Slop(CO)), and this algorithm must meet the requirements of problem restrictions and goals to reach good solutions, and may sometimes be the optimal solutions so we will adopt any solutions that are the best and optimal through our findings in the application of heuristic algorithms and based on the final results can be based on the heuristic method., The research concluded that the best reasoning method is the (arithmetic mean(AM)) because it gave the best results in reducing the total (cost and time) before and after the optimization method (MODI), It also gave the cost inclination method less total costs and time higher than the method of arithmetic mean After conducting the optimization method(MODI)
The present study was conducted to estimate the antimicrobial activity and the potential biological control of the killer toxin produced by
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Abstract: Tin oxide thin films were deposited by direct current (DC) reactive sputtering at gas pressures of 0.015 mbar – 0.15 mbar. The crystalline structure and surface morphology of the prepared SnO2 films were introduced by X-ray diffraction (XRD) and atomic force microscopy (AFM). These films showed preferred orientation in the (110) plane. Due to AFM micrographs, the grain size increased non-uniformly as the working gas pressure increased.
The study aims to clarify the impact of growth in the industrial sector on economic growth in the Iraqi economics according to the methodology of Kaldor for (2017-2030) , taking into consideration the effect of the accumulation of capital in the calculation of growth rates in the economy through productivity estimate of Total Factor Productivity (TFP) to growth in the economy, which is why the study assumes a formula to comply with the laws of Kaldor growth models developed requirements. This study is the most important to find out the development of the laws of Kaldor among Arabic studies, especially the first and third, so that the relationship between the growth of industrial production and economic growth as represented
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Superconducting thin films of Bi1.6Pb0.4Sr2Ca2Cu2.2Zn0.8O10 system were prepared by depositing the film onto silicon (111) substrate by pulsed laser deposition. Annealing treatment and superconducting properties were investigated by XRD and four probe resistivity measurement. The analysis reveals the evolution of the minor phase of the films 2212 phase to 2223 phase, when the film was annealed at 820 °C. Also the films have superconducting behavior with transition temperature ≥90K.
Inferential methods of statistical distributions have reached a high level of interest in recent years. However, in real life, data can follow more than one distribution, and then mixture models must be fitted to such data. One of which is a finite mixture of Rayleigh distribution that is widely used in modelling lifetime data in many fields, such as medicine, agriculture and engineering. In this paper, we proposed a new Bayesian frameworks by assuming conjugate priors for the square of the component parameters. We used this prior distribution in the classical Bayesian, Metropolis-hasting (MH) and Gibbs sampler methods. The performance of these techniques were assessed by conducting data which was generated from two and three-component mixt
... Show MoreIn this work, a novel design for the NiO/TiO2 heterojunction solar cells is presented. Highly-pure nanopowders prepared by dc reactive magnetron sputtering technique were used to form the heterojunctions. The electrical characteristics of the proposed design were compared to those of a conventional thin film heterojunction design prepared by the same technique. A higher efficiency of 300% was achieved by the proposed design. This attempt can be considered as the first to fabricate solar cells from highly-pure nanopowders of two different semiconductors.
Background: Dentin removed during root canal system instrumentation for creating adequate geometry for the canal and cleaning the canal. A new instrument had been marketed with the aim of optimum shaping of all parts of the canal system, however, no information present about the amount of dentin removal compared to conventional rotary system. This study investigated the amount of dentin removal when the canal instrumented by SAF compared with ProTaper by using high resolution computed tomography (micro CT). Materials and Methods: Twenty extracted single canalled teeth were utilized for this study; and randomly divided into 2 groups. In the first group, the root canals were prepared by using protaper rotary system till F2 and the root canal
... Show MoreCorrect grading of apple slices can help ensure quality and improve the marketability of the final product, which can impact the overall development of the apple slice industry post-harvest. The study intends to employ the convolutional neural network (CNN) architectures of ResNet-18 and DenseNet-201 and classical machine learning (ML) classifiers such as Wide Neural Networks (WNN), Naïve Bayes (NB), and two kernels of support vector machines (SVM) to classify apple slices into different hardness classes based on their RGB values. Our research data showed that the DenseNet-201 features classified by the SVM-Cubic kernel had the highest accuracy and lowest standard deviation (SD) among all the methods we tested, at 89.51 % 1.66 %. This
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