Convolutional Neural Networks (CNN) have high performance in the fields of object recognition and classification. The strength of CNNs comes from the fact that they are able to extract information from raw-pixel content and learn features automatically. Feature extraction and classification algorithms can be either hand-crafted or Deep Learning (DL) based. DL detection approaches can be either two stages (region proposal approaches) detector or a single stage (non-region proposal approach) detector. Region proposal-based techniques include R-CNN, Fast RCNN, and Faster RCNN. Non-region proposal-based techniques include Single Shot Detector (SSD) and You Only Look Once (YOLO). We are going to compare the speed and accuracy of Faster RCNN,

The nanocompsite of alumina (Al₂O₃) produced a number of beneficial effects in alloys. There is increasing in resistance of materials to surface related failures , such as the mechanical properties , fatigue and stress corrosion cracking .The experimental results observed that the adding of reinforced  nanomaterials  type Al₂O₃  enhanced the   HB hardness, UTS, 0.2 YS and ductility of 2014 Al/Al₂O₃ nano composites . the analysis of experiments, indicated that The maximum enhancement was observed at 0.4 wt.% Al₂O₃. The ultimate improvement percentage were 15.78% HB hardness, 18.1% (UTS), 12.86% (

Three new polyphosphates were synthesized in good yields by reacting diethylenetriamine with the appropriate phosphate ester in ethanol under acidic conditions. The polyphosphate structures were determined using FT-IR and 1H-NMR spectroscopies, and their elemental compositions were confirmed by EDX spectroscopy. Polyphosphates were added to poly(vinyl chloride) (PVC) at low concentrations to fabricate thin films. The PVC films were irradiated with ultraviolet light for long periods, and the effect of polyphosphates as the photostabilizer was investigated by determining changes in the infrared spectra (intensity of specific functional group peaks), reduction in molecular weight, weight loss, and surface morphology. Minimal changes we

Background: Radiation therapy has the ability to destroy healthy cells in addition to cancer cells in the area being treated. However, when radiation combines with doxorubicin, it becomes more effective on breast cancer treatment. Objective: This study aims to clarify the effect of X-ray from LINAC combined with amygdalin and doxorubicin on breast cancer treatment, and the possibility of using amygdalin with X-ray instead of doxorubicin for the breast cancer treatment. Method: Two cell lines were used in this study, the first one was MCF-7 cell line and second one was WRL- 68 normal cell line. These cells were preserved in liquid nitrogen, prepared, developed and tested in the (place). The effect of three x-ray doses combined with a

Radiation therapy plays an important role in improving breast cancer cases, in order to obtain an appropriateestimate of radiation doses number given to the patient after tumor removal; some methods of nonparametric regression werecompared. The Kernel method was used by Nadaraya-Watson estimator to find the estimation regression function forsmoothing data based on the smoothing parameter h according to the Normal scale method (NSM), Least Squared CrossValidation method (LSCV) and Golden Rate Method (GRM). These methods were compared by simulation for samples ofthree sizes, the method (NSM) proved to be the best according to average of Mean Squares Error criterion and the method(LSCV) proved to be the best according to Average of Mean Absolu

In this research, a study is introduced on the effect of several environmental factors on the performance of an already constructed quality inspection system, which was designed using a transfer learning approach based on convolutional neural networks. The system comprised two sets of layers, transferred layers set from an already trained model (DenseNet121) and a custom classification layers set. It was designed to discriminate between damaged and undamaged helical gears according to the configuration of the gear regardless to its dimensions, and the model showed good performance discriminating between the two products at ideal conditions of high-resolution images. So, this study aimed at testing the system performance at poo

In this research, a group of gray texture images of the Brodatz database was studied by building the features database of the images using the gray level co-occurrence matrix (GLCM), where the distance between the pixels was one unit and for four angles (0, 45, 90, 135). The k-means classifier was used to classify the images into a group of classes, starting from two to eight classes, and for all angles used in the co-occurrence matrix. The distribution of the images on the classes was compared by comparing every two methods (projection of one class onto another where the distribution of images was uneven, with one category being the dominant one. The classification results were studied for all cases using the confusion matrix between every

Nowadays, energy demand continuously rises while energy stocks are dwindling. Using current resources more effectively is crucial for the world. A wide method to effectively utilize energy is to generate electricity using thermal gas turbines (GT). One of the most important problems that gas turbines suffer from is high ambient air temperature especially in summer. The current paper details the effects of ambient conditions on the performance of a gas turbine through energy audits taking into account the influence of ambient conditions on the specific heat capacity ( , isentropic exponent ( ) as well as the gas constant of air . A computer program was developed to examine the operation of a power plant at various ambient temperature