This study aimed to investigate the influence of longitudinal steel embedded tubes located at the center of the column cross-section on the behavior of reinforced concrete (RC) columns. The experimental program consisted of 8 testing pin-ended square sectional columns of 150×150 mm, having a total height of 1400 mm, subjected to eccentric load. The considered variables were the steel square tube sizes of 25, 51 and 68 mm side dimensions and the load eccentricity (50 and 150) mm. RC columns were concealed steel tubes with hollow ratios of 3%, 12% and 20% depending on tube sizes used. The experimental results indicated an improvement in the overall behavior of eccentric columns when steel embedded tubes are used. The maximum gain in

The research utilizes data produced by the Local Urban Management Directorate in Najaf and the imagery data from the Landsat 9 satellite, after being processed by the GIS tool. The research follows a descriptive and analytical approach; we integrated the Markov chain analysis and the cellular automation approach to predict transformations in city structure as a result of changes in land utilization. The research also aims to identify approaches to detect post-classification transformations in order to determine changes in land utilization. To predict the future land utilization in the city of Kufa, and to evaluate data accuracy, we used the Kappa Indicator to determine the potential applicability of the probability matrix that resulted from

In this manuscript divide into two parts the first experimental and the second theoretical. The experimental part of polyvinyl chloride (PVC) can be used with aluminum (30%). Nanomaterials are synthesized by a laser pulse melting solution by ethanol. The effect of laser on the structural, morphological, optical, and electrical properties of nanoparticles (PVC) was examined by UV spectroscopy, x-ray diffraction (XRD), electron microscopy (TEM). The theoretical part of the DFT can be used to approximate the generalized gradient of the Perdew, Burke, and Ernzerhof (PBE) / 6-31G (d) groups, which were created using additional Gaussian 09 software through Gaussian 5.08. To build PVC nanocrystal pure which chemical formula [(C2H3Cl)n] and build (

This research includes synthesis of new 5-Nitro isatin derivatives starting from 5-nitro-3-(imino acetohydrazide)-2-oxo indole (1) namely 5-nitro-3-[iminoaceto(tetra hydropyridazin-3,6-dione)-2-yl]-2-oxo indole (2); 5-nitro-3-[iminoaceto(hexahydrodiazepine-3,7-dione)-2-yl]-2-oxo indole (3); 5-nitro-3-[iminoaceto (1,2-dihydro pyridiazin-3,6-dione)-2-yl]-2-oxo indole (4); 5-nitro-3-[iminoaceto (8-nitro- 1,2-dihydrophtalazin-3,10-dione)-2-yl]-2-oxo indole (5) and 5-nitro-3-[iminoaceto (1,2-dihydrophtalazin-3,10-dione)-2-yl]-2-oxo indole (6). The derivatives were characterized using FTIR, ¹HNMR, ¹³CNMR and C.H.N.S analy

In this paper, a compact multiband printed dipole antenna is presented as a candidate for use in wireless communication applications. The proposed fractal antenna design is based on the second level tent transformation. The space-filling property of this fractal geometry permits producing longer lengths in a more compact size. Theoretical performance of this antenna has been calculated using the commercially available software IE3D from Zeland Software Inc. This electromagnetic simulator is based on the method of moments (MoM). The proposed dipole antenna has been found to possess a considerable size reduction compared with the conventional printed or wire dipole antenna designed at the same design frequency and using the same substrate

    In data mining and machine learning methods, it is traditionally assumed that training data, test data, and the data that will be processed in the future, should have the same feature space distribution. This is a condition that will not happen in the real world. In order to overcome this challenge, domain adaptation-based methods are used. One of the existing challenges in domain adaptation-based methods is to select the most efficient features so that they can also show the most efficiency in the destination database. In this paper, a new feature selection method based on deep reinforcement learning is proposed. In the proposed method, in order to select the best and most appropriate features, the essential policies

It is well known that drilling fluid is a key parameter for optimizing drilling operations, cleaning the hole, and managing the rig hydraulics and margins of surge and swab pressures. Although the experimental works represent valid and reliable results, they are expensive and time consuming. In contrast, continuous and regular determination of the rheological fluid properties can perform its essential functions during good construction. The aim of this study is to develop empirical models to estimate the drilling mud rheological properties of water-based fluids with less need for lab measurements. This study provides two predictive techniques, multiple regression analysis and artificial neural networks, to determine the rheological

Productivity estimating of ready mixed concrete batch plant is an essential tool for the successful completion of the construction process. It is defined as the output of the system per unit of time. Usually, the actual productivity values of construction equipment in the site are not consistent with the nominal ones. Therefore, it is necessary to make a comprehensive evaluation of the nominal productivity of equipment concerning the effected factors and then re-evaluate them according to the actual values.

In this paper, the forecasting system was employed is an Artificial Intelligence technique (AI). It is represented by Artificial Neural Network (ANN) to establish the predicted model to estimate wet ready mixe

     Social media and news agencies are major sources for tracking news and events. With these sources' massive amounts of data, it is easy to spread false or misleading information. Given the great dangers of fake news to societies, previous studies have given great attention to detecting it and limiting its impact. As such, this work aims to use modern deep learning techniques to detect Arabic fake news. In the proposed system, the attention model is adapted with bidirectional long-short-term memory (Bi-LSTM) to identify the most informative words in the sentence. Then, a multi-layer perceptron (MLP) is applied to classify news articles as fake or real. The experiments are conducted on a newly launched Arabic dataset called the Ara

Social media is known as detectors platform that are used to measure the activities of the users in the real world. However, the huge and unfiltered feed of messages posted on social media trigger social warnings, particularly when these messages contain hate speech towards specific individual or community. The negative effect of these messages on individuals or the society at large is of great concern to governments and non-governmental organizations. Word clouds provide a simple and efficient means of visually transferring the most common words from text documents. This research aims to develop a word cloud model based on hateful words on online social media environment such as Google News. Several steps are involved including data acq