The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Convolutional Neural Network (CNN) has been chosen as a better option for the training process because it produces a high accuracy. The final accuracy has reached 91.18% in five different classes. The results are discussed in terms of the probability of accuracy for each class in the image classification in percentage. Cats class got 99.6 %, while houses class got 100 %.Other types of classes were with an average score of 90 % and above.
NGC 6946 have been observed with BVRI filters, on October 15-18,
2012, with the Newtonian focus of the 1.88m telescope, Kottamia
observatory, of the National Research Institute of Astronomy and
Geophysics, Egypt (NRIAG), then we combine the BVRI filters to
obtain an astronomical image to the spiral galaxy NGC 6946 which
is regarded main source of information to discover the components of
this galaxy, where galaxies are considered the essential element of
the universe. To know the components of NGC 6946, we studied it
with the Variable Precision Rough Sets technique to determine the
contribution of the Bulge, disk, and arms of NGC 6946 according to
different color in the image. From image we can determined th
Experimental study has been conducted for laminar natural convection heat transfer of air flow through a rectangular enclosure fitted with vertical partition. The partition was oriented parallel to the two vertical isothermal walls with different temperatures, while all the other surfaces of the enclosure were insulated. In this study a test rig has been designed and constructed to allow studying the effect of Rayleigh number, aperture height ratio, partition thickness, the position of aperture according to the side walls and according to the height, the position of the partition according to the hot wall, and partition inclination. The experiments were carried out with air as the working fluid for Rayleigh number range (5*107 – 1.3*10
... Show MoreMalicious software (malware) performs a malicious function that compromising a computer system’s security. Many methods have been developed to improve the security of the computer system resources, among them the use of firewall, encryption, and Intrusion Detection System (IDS). IDS can detect newly unrecognized attack attempt and raising an early alarm to inform the system about this suspicious intrusion attempt. This paper proposed a hybrid IDS for detection intrusion, especially malware, with considering network packet and host features. The hybrid IDS designed using Data Mining (DM) classification methods that for its ability to detect new, previously unseen intrusions accurately and automatically. It uses both anomaly and misuse dete
... Show MoreCloth simulation and animation has been the topic of research since the mid-80's in the field of computer graphics. Enforcing incompressible is very important in real time simulation. Although, there are great achievements in this regard, it still suffers from unnecessary time consumption in certain steps that is common in real time applications. This research develops a real-time cloth simulator for a virtual human character (VHC) with wearable clothing. This research achieves success in cloth simulation on the VHC through enhancing the position-based dynamics (PBD) framework by computing a series of positional constraints which implement constant densities. Also, the self-collision and collision wit
... Show MoreThe research explain the analysis of finance investments through analyze the finance tables for commercial banks, by using the pointers to indicate the limits of economical benefit for these investments, and fix the negative deviations and as well positive, for the purpose of diagnostic the negative (disadvantage) and develop the advantage deviation, For the importance of finance investments in the development operation and economical growth, further to that the finance investments is represent one of the most activities in the commercial banks in which aim the adequate incomes as a result of the commercial banks act to receipt the banks deposits and then make it growth and develop through commercial advantage o
... Show MoreEach Intensity Modulated Radiation Therapy (IMRT) plan needs to be tested and verified before any treatment to check its quality. Octavius 4D-1500 phantom detector is a modern and qualified device for quality assurance procedure. This study aims to compare the common dosimetric criteria 3%/3 mm with 2%/2 mm for H&N plans for the IMRT technique. Twenty-five patients with head and neck (H&N) tumor were with 6MV x-ray photon beam using Monaco 5.1 treatment planning software and exported to Elekta synergy linear accelerator then tested for pretreatment verification study using Octavius 4D-1500 phantom detector. The difference between planned and measured dose were assessed by using local and global gamma index (GI) analysis method at
... Show MoreMany academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Deci
... Show MoreMany academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Decision Tre
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