In this study, six square reinforced concrete flat plates with dimensions of (1500×1500×100) mm were tested under a concentrated load applied on a column located at the center of the slabs. One of these slabs was the control specimen, whereas, in the others, steel angles (steel collars) were used, fixed at the connection region between the slab and the column to investigate the effect of the presence of these collars on punching shear strength. Five thicknesses were used (4, 5, 6, 8, 10mm) with constant legs of angles (75×75) mm of the steel collars to investigate the effects on the punching shear resistance with respect to the control slab. The results of the experimental study show that the punching shear resistance increased b

High performance self-consolidating concrete HP-SCC is one of the most complex types of concrete which have the capacity to consolidated under its own weight, have excellent homogeneity and high durability. This study aims to focus on the possibility of using industrial by-products like Silica fumes SF in the preparation of HP-SCC enhanced with discrete steel fibers (DSF) and monofilament polypropylene fibers (PPF). From experimental results, it was found that using DSF with volume fraction of 0.50 %; a highly improvements were gained in the mechanical properties of HP-SCC. The compressive strength, splitting tensile strength, flexural strength and elastic modulus improved about 65.7 %, 70.5 %, 41.7 % and 80.3 % at 28 days age, respectively

Organic soil is problematic soils in geotechnical engineering due to its properties, as it is characterized by high compressibility and low bearing capacity. Therefore, several geotechnical techniques tried to stabilize and improve this soil type. In this study, sodium silicate was used to stabilize sand dune columns. The best sodium silicate concentration (9%) was used, and the stabilized sand dune columns were cured for seven days. The results for this soil were extracted using a numerical analysis program (Plaxis 3D, 2020).In the case of studying the effect of (L/D) (where ‘’L” and ‘’D’’ length and diameter of sand dune columns) of a single column of sand dunes stabilized with sodium silicate with a diff

Background/Objectives: The purpose of this study was to classify Alzheimer’s disease (AD) patients from Normal Control (NC) patients using Magnetic Resonance Imaging (MRI). Methods/Statistical analysis: The performance evolution is carried out for 346 MR images from Alzheimer's Neuroimaging Initiative (ADNI) dataset. The classifier Deep Belief Network (DBN) is used for the function of classification. The network is trained using a sample training set, and the weights produced are then used to check the system's recognition capability. Findings: As a result, this paper presented a novel method of automated classification system for AD determination. The suggested method offers good performance of the experiments carried out show that the

Analyzing sentiment and emotions in Arabic texts on social networking sites has gained wide interest from researchers. It has been an active research topic in recent years due to its importance in analyzing reviewers' opinions. The Iraqi dialect is one of the Arabic dialects used in social networking sites, characterized by its complexity and, therefore, the difficulty of analyzing sentiment. This work presents a hybrid deep learning model consisting of a Convolution Neural Network (CNN) and the Gated Recurrent Units (GRU) to analyze sentiment and emotions in Iraqi texts. Three Iraqi datasets (Iraqi Arab Emotions Data Set (IAEDS), Annotated Corpus of Mesopotamian-Iraqi Dialect (ACMID), and Iraqi Arabic Dataset (IAD)) col

Monaural source separation is a challenging issue due to the fact that there is only a single channel available; however, there is an unlimited range of possible solutions. In this paper, a monaural source separation model based hybrid deep learning model, which consists of convolution neural network (CNN), dense neural network (DNN) and recurrent neural network (RNN), will be presented. A trial and error method will be used to optimize the number of layers in the proposed model. Moreover, the effects of the learning rate, optimization algorithms, and the number of epochs on the separation performance will be explored. Our model was evaluated using the MIR-1K dataset for singing voice separation. Moreover, the proposed approach achi

The proliferation of many editing programs based on artificial intelligence techniques has contributed to the emergence of deepfake technology. Deepfakes are committed to fabricating and falsifying facts by making a person do actions or say words that he never did or said. So that developing an algorithm for deepfakes detection is very important to discriminate real from fake media. Convolutional neural networks (CNNs) are among the most complex classifiers, but choosing the nature of the data fed to these networks is extremely important. For this reason, we capture fine texture details of input data frames using 16 Gabor filters indifferent directions and then feed them to a binary CNN classifier instead of using the red-green-blue

The electrical properties of the AlNiCo thin films with thickness (1000oA) deposited on glass substrates using Ion – Beam sputtering (IBS) technique under vacuum <10-6 torr have been studied . Also it studied the effect of annealing temperature from this films , It is found that the effective energy decrease with increase of temperature and the conductivity decrease with increase temperature 323oK but after this degree the conductivity increasing .

Objective: The aim of this work was to detect terpenes other than boswellic acid derivatives in olibanum of Boswellia Serrata found in Iraq. Methods: The olibanum of Boswellia Serrata was macerated in methanol for one day, then filtration. Filter at was concentrated till reddish brown syrupy residue was gained, (3%) potassium hydroxide was added till basification. This basic solution was stirred continuously until a uniform emulsion was formed, then extracted with chloroform in a separatory funnel; the chloroform fraction was analyzed by GC /MS spectrometry. Results: GC /MS analysis reveal the presence of terpenes and non-terpenes constituents. Conclusion: Most of the detected terpenes were sesquiterpenes and the least one was di-terpenes.