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

The growth curves of the children are the most commonly used tools to assess the general welfare of society. Particularity child being one of the pillars to develop society; through these tools, we can path a child's growth physiology. The Centile line is of the important tools to build these curves, which give an accurate interpretation of the information society, also respond with illustration variable age. To build standard growth curves for BMI, we use BMI as an index. LMSP method used for finding the Centile line which depends on four curves represents Median, Coefficient of Variation, Skews, and Kurtosis. These can be obtained by modeling four parameters as nonparametric Smoothing functions for the illustration variable. Ma

The Iraqi marshes are considered the most extensive wetland ecosystem in the Middle East and are located in the middle and lower basin of the Tigris and Euphrates Rivers which create a wetlands network and comprise some shallow freshwater lakes that seasonally swamped floodplains. Al-Hawizeh marsh is a major marsh located east of Tigris River south of Iraq. This study aims to assess water quality through water quality index (WQI) and predict Total Dissolved Solids (TDS) concentrations in Al-Hawizeh marsh based on artificial neural network (ANN). Results showed that the WQI was more than 300 for years 2013 and 2014 (Water is unsuitable for drinking) and decreased within the range 200-300 in years 2015 and 2016 (Very poor water). The develope

The Iraqi marshes are considered the most extensive wetland ecosystem in the Middle East and are located in the middle and lower basin of the Tigris and Euphrates Rivers which create a wetlands network and comprise some shallow freshwater lakes that seasonally swamped floodplains. Al-Hawizeh marsh is a major marsh located east of Tigris River south of Iraq. This study aims to assess water quality through water quality index (WQI) and predict Total Dissolved Solids (TDS) concentrations in Al-Hawizeh marsh based on artificial neural network (ANN). Results showed that the WQI was more than 300 for years 2013 and 2014 (Water is unsuitable for drinking) and decreased within the range 200-300 in years 2015 and 2016 (Very poor water). The

Abstract. In this scientific work, we investigate the problem of the practical necessity of achieving the adequacy of translation activities with active translation from Russian into Arabic in various fields of translation. Based on the material of the latest suffix vocabulary, a serious attempt is made to clarify and specify the rules for the development of translator's intuition when translating from Russian into Arabic and vice versa. Based on the material collected by the latest suffix vocabulary, we try to make an attempt to reveal the role of suffix word creation in highlighting the general rules for achieving translation equivalence. The paper examines the process of creating words in multi-family languages, the difference between th

In this research, Artificial Neural Networks (ANNs) technique was applied in an attempt to predict the water levels and some of the water quality parameters at Tigris River in Wasit Government for five different sites. These predictions are useful in the planning, management, evaluation of the water resources in the area. Spatial data along a river system or area at different locations in a catchment area usually have missing measurements, hence an accurate prediction. model to fill these missing values is essential.
The selected sites for water quality data prediction were Sewera, Numania , Kut u/s, Kut d/s, Garaf observation sites. In these five sites models were built for prediction of the water level and water quality parameters.

A long-span Prestressed Concrete Hunched Beam with Multi-Opening has been developed as an alternative to steel structural elements. The commercial finite element package ABAQUS/CAE version 2019 has been utilized. This article has presented the results of three-dimensional numerical simulations investigating the flexural behaviour of existing experimental work of supported Prestressed Concrete Hunched Beams with multiple openings of varying shapes under static monotonic loads. Insertion openings in such a beam lead to concentrate stresses at the corners of these openings; as a result, extensive cracking would appear. Correlation between numerical models and empirical work has also been discussed regarding load displacemen

The adsorption behavior of Bismarck brown (BB) dye from aqueous solutions onto graphene oxide GO and graphene oxide-g-poly (n-butyl methacrylate-co-methacrylic acid) GO-g-pBCM as adsorbents was investigated. The prepared GO and GO-g-pBCM were characterized by Fourier transform infrared spectroscopy FTIR, which confirmed the compositions of the prepared adsorbents. Adsorption of BB dye onto GO and GO-g-pBCM was explored in a series of batch experiments under various conditions. The data were examined utilizing Langmuir and Freundlich isotherms. The Langmuir isotherm was seen as increasingly reasonable from the experimental information of dye on formulating adsorbents. Kinetic investigations showed that the experimental data were fitted ve

In the beta decay process, a neutron converts into a proton, or vice versa, so the atom in this process changes to a more stable isobar. Bethe-Weizsäcker used a quasi-experimental formula in the present study to find the most stable isobar for isobaric groups of mass nuclides (A=165-175). In a group of isobars, there are two methods of calculating the most stable isobar. The most stable isobar represents the lowest parabola value by calculating the binding energy value (B.E) for each nuclide in this family, and then drawing these binding energy values as a function of the atomic number (Z) in order to obtain the mass parabolas, the second method is by calculating the atomic number value of the most stable isobar (ZA). The results show