This research is concerned to investigate the behavior of reinforced concrete (RC) deep beams strengthened with carbon fiber reinforced polymer (CFRP) strips. The experimental part of this research is carried out by testing seven RC deep beams having the same dimensions and steel reinforcement which have been divided into two groups according to the strengthening schemes. Group one was consisted of three deep beams strengthened with vertical U-wrapped CFRP strips. While, Group two was consisted of three deep beams strengthened with inclined CFRP strips oriented by 45^o with the longitudinal axis of the beam. The remaining beam is kept unstrengthening as a reference beam. For each group, the variable considered

Features is the description of the image contents which could be corner, blob or edge. Corners are one of the most important feature to describe image, therefore there are many algorithms to detect corners such as Harris, FAST, SUSAN, etc. Harris is a method for corner detection and it is an efficient and accurate feature detection method. Harris corner detection is rotation invariant but it isn’t scale invariant. This paper presents an efficient harris corner detector invariant to scale, this improvement done by using gaussian function with different scales. The experimental results illustrate that it is very useful to use Gaussian linear equation to deal with harris weakness.

Starting from 4, - Dimercaptobiphenyl, a variety of phenolic Schiff bases (methylolic, etheric, epoxy) derivatives have been synthesized. All proposed structure were supported by FTIR, 1H-NMR, 13C-NMR Elemental analysis all analysis were performed in center of consultation in Jordan Universty.

Objective: The goal of this research was to evaluate where selenium nanoparticles impact the activity of antibodies in immunized lambs with foot and mouth vaccines by modulating the immune system. Materials and Methods: Two groups of lambs of 3–4 months of age were injected with 1 ml of ARRIAH-VAC vaccine intramuscularly in the neck, five Lambs were given selenium nanoparticles (size 100 nm) oral administration of selenium nano dose of 0.1 mg/kg of body mass once every day for sixty days considered as group one (G1) while the other five used as control Group 2 (G2). Results: This resulted in the establishment of an immune response, as evidenced by a rise in antibody titer in the blood using the ELISA test for three serotypes A,

In this research Artificial Neural Network (ANN) technique was applied to study the filtration process in water treatment. Eight models have been developed and tested using data from a pilot filtration plant, working under different process design criteria; influent turbidity, bed depth, grain size, filtration rate and running time (length of the filtration run), recording effluent turbidity and head losses. The ANN models were constructed for the prediction of different performance criteria in the filtration process: effluent turbidity, head losses and running time. The results indicate that it is quite possible to use artificial neural networks in predicting effluent turbidity, head losses and running time in the filtration process, wi

chronic obstructive pulmonary disease (COPD) is a common respiratory disease with episodes of exacerbation. Variable factors including infectious pathogen can predispose for this exacerbation. The aim of this study is to evaluate the role of intestinal protozoa in COPD exacerbation. A total of 56 patients with COPD were included in this study. Patients were categorized into two groups based on the frequency of exacerbation during the last 6 months: those with ≤1 exacerbation (32 patients) and those with ≥2 exacerbations (24 patients). Stool specimens from each patient were collected two times (one week interval) examined for intestinal parasite. In univariate analysis, rural residence and parasitic infection were more common among patie

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

Micro metal forming has an application potential in different industrial fields. Flexible tool-assisted sheet metal forming at micro scale is among the forming techniques that have increasingly attracted wide attention of researchers. This forming process is a suitable technique for producing micro components because of its inexpensive process, high quality products and relatively high production rate. This study presents a novel micro deep drawing technique through using floating ring as an assistant die with flexible pad as a main die. The floating ring designed with specified geometry is located between the process workpiece and the rubber pad. The function of the floating ring in this work is to produce SS304 micro cups with profile