The current study aims to identify the level of adaptation of the curriculum for visually handicapped pupils from the point of view of their teachers as well as to identify the level of adaptation of the educational programs offered to visually handicapped pupils from the point of view of their teachers. In order to achieve the goals of the research, the researcher developed two tools to measure the adaptation of curricula and educational programs for pupils with visual handicapped from the point of view of teachers. The sample included (60) teachers from Al Noor Institute for Blinders in Baghdad, the two tools were applied to them, and then the Reliability and Validity coefficients were extracted. The results sh

          Sentiment analysis refers to the task of identifying polarity of positive and negative for particular text that yield an opinion. Arabic language has been expanded dramatically in the last decade especially with the emergence of social websites (e.g. Twitter, Facebook, etc.). Several studies addressed sentiment analysis for Arabic language using various techniques. The most efficient techniques according to the literature were the machine learning due to their capabilities to build a training model. Yet, there is still issues facing the Arabic sentiment analysis using machine learning techniques. Such issues are related to employing robust features that have the ability to discrimina

An experimental program was conducted to determine the residual of composite Steel Beams-Reinforced Concrete (SB-RC) deck floors fabricated from a rolled steel beam topped with a reinforced concrete slab, exposed to high temperatures (fire flame) of 300, 500, and 700ºC for 1 hour, and then allowed to cool down by leaving them in the lab condition to return to the ambient temperature. The burning results showed that, by exposing them to a fire flame of up to 300ºC, no serious permanent deflection occurred. It was also noticed that the specimen recovered 93% of 19.2 mm of the deflection caused by burning. The recovered deflection of burned composite SB-RC deck floor at 500ºC was 40% of 77.9 mm of the deflection caused by burning with a res

         The varied thermal conductivity (insulation) of silica aerogel with heating for different pH has been investigated, it has been depended on ambient pressure drying method in the preparing silica aerogel samples, also six different pH of samples (1, 2, 3, 7, 8 and 9) were treated under five degree of heating with (50,100,150,200 and 250) ᴼC. This technique is important to test the carry-outs hydrophobic silica to temperature without high-quality material changes in the basic characteristics. The hot-wire technique is used in this work to examine the thermal conductivity, Fourier Transform Infrared Spectroscopy (FTIR) depended to characterize the bonds and their artificial by heating. Resu

       The interest in green energy in recent years is very noticeable, as this energy is a very important alternative that can replace fuel in many applications, most notably electric power generation, so work must be done to develop a form of this energy such as wind energy by working on the development of turbines. The DMST method provided by Qblade software is an integrated tool for making a simulation of a vertical axis wind turbine (VAWT). The simulation was carried out on vertical axis wind turbines, designing turbine blades according to symmetrical NACA0018, and calculating some parameters such as power, torque and power coefficient. It is found that this type of turbine can be improved by treating the blade edges that cont

Wisconsin Breast Cancer Dataset (WBCD) was employed to show the performance of the Adaptive Resonance Theory (ART), specifically the supervised ART-I Artificial Neural Network (ANN), to build a breast cancer diagnosis smart system. It was fed with different learning parameters and sets. The best result was achieved when the model was trained with 50% of the data and tested with the remaining 50%. Classification accuracy was compared to other artificial intelligence algorithms, which included fuzzy classifier, MLP-ANN, and SVM. We achieved the highest accuracy with such low learning/testing ratio.

     This paper focuses on choosing a spatial mixture model with implicitly includes the time to represent the relative risks of COVID-19 pandemic using an appropriate model selection criterion. For this purpose, a more recent criterion so-called the widely Akaike information criterion (WAIC) is used which we believe that its use so limitedly in the context of relative risk modelling. In addition, a graphical method is adopted that is based on a spatial-temporal predictive posterior distribution to select the best model yielding the best predictive accuracy. By applying this model selection criterion, we seek to identify the levels of relative risk, which implicitly represents the determination of the number of the model components o