Alginate from Large brown seaweeds act as natural polymer has been investigated as polymer and has been added to concrete in different percentages ( 0% , 0.5% , 1% and 1.5% ) by the cement weight and the study show the effect of using alginate biopolymer admixtures on  some of the fresh properties of the concrete (slump &  the density  fresh) also in the hardened state (  Compressive strength , Splitting tensile strength  and Flexural strength ) at 28 days. The mix proportion was (1:2.26:2.26) (cement: sand: gravel) respectively and at constant w/c equal to 0.47. The results indicate that the use of alginate as a percent of the cement weight possess a positive effect on fresh properties of co

Accelerates operating managements in the facilities contemporary business environment toward redefining processes and strategies that you need to perform tasks of guaranteeing them continue in an environment performance dominated by economic globalization and the circumstances of uncertainty attempt the creation of a new structure through multiple pages seek to improve profitability and sustainable growth in performance in a climatefocuses on the development of institutional processes, reduce costs and achieve customer satisfaction to meet their demands and expectations are constantly changing. The research was presented structural matrix performance combines methodology Alsigma in order to improve customer satisfaction significantly bet

In this research the hard chromium electroplating process, which is one of the common methods of overlay coating was used, by using chromium acid as source of chromium and sulphuric acid as catalyst since the ratio between chromic acid and sulphuric acid is (100 : 1) consequently. Plating process was made by applying current of density (40 Amp / dm²) and the range of solution temperature was (50 – 55^oC) with different time periods (1-5 hr). A  low carbon steel type (Ck₁₅) was used as substrate for hard chromium electroplating. Solid carburization was carried out for hard chromium plating specimen at temperature (925^oC) with time duration (2 hr) to be followed with quenching and tempering

Using an electrochemical polymerization technique at room temperature, poly nicotine amide (PNA) was produced from the monomer nicotine amide (NA) in aqueous solution. The structure of polymer layer generated on the stainless steel surface (316 L) (working electrode) is investigated by Fourier Transmission Infrared Region (FT-IR). The anti-corrosion activity of polymer coating on the stainless steel (SS 316 L) is investigated by electrochemical polarization in 0.20M solution of HCl at 293-323K. The graphene -modified polymer film-coated SS had greater protection efficiency (PE percent) when compared to Nano ZnO -modified polymer film-coated SS. For the corrosion process of SS 316 L, kinetic and thermo-dynamic parameters of activation are

The main objective of this study is to understand the work of the pile caps made of lightweight aerated foam concrete and study the many factors affecting the ability and the capacity of the shear. The study was done by analyzing previous practical and theoretical experiences on the reinforced concrete pile caps. The previous practical results indicated that all specimens failed by shear diagonal compression or tension modes except one specimen that failed flexural-shear mode. Based on test specimens' practical results and behavior, some theoretical methods for estimating the ultimate strength of reinforced concrete pile caps have been recommended, some of which evolved into the design documents available on the subject.

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

<span lang="EN-GB">Transmitting the highest capacity throughput over the longest possible distance without any regeneration stage is an important goal of any long-haul optical network system. Accordingly, Polarization-Multiplexed Quadrature Phase-Shift-Keying (PM-QPSK) was introduced lately to achieve high bit-rate with relatively high spectral efficiency. Unfortunately, the required broad bandwidth of PM-QPSK increases the linear and nonlinear impairments in the physical layer of the optical fiber network. Increased attention has been spent to compensate for these impairments in the last years. In this paper, Single Mode Fiber (SMF), single channel, PM-QPSK transceiver was simulated, with a mix of optical and electrical (Digi

      TV medium derives its formal shape from the technological development taking place in all scientific fields, which are creatively fused in the image of the television, which consists mainly of various visual levels and formations. But by the new decade of the second millennium, the television medium and mainly (drama) became looking for that paradigm shift in the aesthetic formal innovative fields and the advanced expressive performative fields that enable it to develop in treating what was impossible to visualize previously. In the meantime, presenting what is new and innovative in the field of unprecedented and even the familiar objective and intellectual treatments. Thus the TV medium has sought for work

This paper proposes improving the structure of the neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm n

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