This work intends to illustrate the methods of using the authentic literary text in the process of spreading Italian, especially in Baghdad where there is a strong propensity to learn the Italian language. The concept of the language that arises from literature is an idea closely linked to the mentality of the Arab learner towards Italian culture: an idea also created by the first Arabisations of literary texts in the early years of the previous century. The research was carried out in Baghdad by two researchers, an Italianist from Baghdad and an Italian mother language linguist, with the aim of bringing together the two sectors in favor of the diffusion of the Italian language. The study also aims to clarify the models from Italian l

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

         This study involves the design of 24 mixtures of fiber reinforced magnetic reactive powder concrete containing nano silica. Tap water was used for 12 of these mixtures, while magnetic water was used for the others. The nano silica (NS) with ratios (1, 1.5, 2, 2.5 and 3) % by weight of cement, were used for all the mixtures. The results have shown that the mixture containing 2.5% NS gives the highest compressive strength at age 7 days. Many different other tests were carried out, the results have shown that the carbon fiber reinforced magnetic reactive powder concrete containing 2.5% NS (CFRMRPCCNS) had higher compressive strength, modulus of rupture, splitting tension, str

This paper proposes a novel finite-time generalized proportional integral observer (FTGPIO) based a sliding mode control (SMC) scheme for the tracking control problem of high order uncertain systems subject to fast time-varying disturbances. For this purpose, the construction of the controller consists of two consecutive steps. First, the novel FTGPIO is designed to observe unmeasurable plant dynamics states and disturbance with its higher time derivatives in finite time rather than infinite time as in the standard GPIO. In the FTGPO estimator, the finite time convergence rate of estimations is well achieved, whereas the convergence rate of estimations by classical GPIO is asymptotic and slow. Secondly, on the basis of the finite and fast e

ABSTRACT: Ultimate bearing capacity of soft ground reinforced with stone column was recently predicted using various artificial intelligence technologies such as artificial neural network because of all the advantages that they can offer in minimizing time, effort and cost. As well as, most of applied theories or predicted formulas deduced analytically from previous studies were feasible only for a particular testing environment and do not match other field or laboratory datasets. However, the performance of such techniques depends largely on input parameters that really affect the target output and missing of any parameter can lead to inaccurate results and give a false indicator. In the current study, data were collected from previous rel