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.
Breast cancer is the most repeatedly detected cancer category and the second reason cause of cancer-linked deaths among women worldwide. Tumor bio-indictor is a term utilized to describe possible indicators for carcinoma diagnosis, development and progression. The goal of this study is to evaluate part of some cytokines and biomarkers for both serum and saliva samples in breast cancer then estimate their potential value in the early diagnosis of breast cancer by doing more researches in saliva, and utilizing saliva instead of blood (serum and plasma) in sample collection from patients. Serum and salivary samples were taken from 72 patients with breast cancer and 45 healthy controls, in order to investigate the following
... Show Moreتحقق القراءةُ التَّناصيَّة قيمة موضوعيَّة للدرسِ النَّقديّ المعاصر؛ بمؤثراتها الثَّقافيَّة، والمعرفيَّة، لأنَّ الإبداعَ من سمات التُّراث الشِّعري في العصر الوسيط، وهو مسرحٌ لتداخلات نصِّيَّة مع مصادر متعددة دينيَّة، وأدبيَّة، وتاريخيَّة أداء ومضامين؛ يأتي اختيارُ (التَّناص مع الحديث النَّبوي في شعر صفيّ الدِّين الحلّي)؛ بوصفه امتدادًا شعريَّا أصيلًا لحضارة راقية معطاء
... Show MoreDue to the vast using of digital images and the fast evolution in computer science and especially the using of images in the social network.This lead to focus on securing these images and protect it against attackers, many techniques are proposed to achieve this goal. In this paper we proposed a new chaotic method to enhance AES (Advanced Encryption Standards) by eliminating Mix-Columns transformation to reduce time consuming and using palmprint biometric and Lorenz chaotic system to enhance authentication and security of the image, by using chaotic system that adds more sensitivity to the encryption system and authentication for the system.
Everybody is connected with social media like (Facebook, Twitter, LinkedIn, Instagram…etc.) that generate a large quantity of data and which traditional applications are inadequate to process. Social media are regarded as an important platform for sharing information, opinion, and knowledge of many subscribers. These basic media attribute Big data also to many issues, such as data collection, storage, moving, updating, reviewing, posting, scanning, visualization, Data protection, etc. To deal with all these problems, this is a need for an adequate system that not just prepares the details, but also provides meaningful analysis to take advantage of the difficult situations, relevant to business, proper decision, Health, social media, sc
... Show More This paper introduces a relation between resultant and the Jacobian determinant
by generalizing Sakkalis theorem from two polynomials in two variables to the case of (n) polynomials in (n) variables. This leads us to study the results of the type: , and use this relation to attack the Jacobian problem. The last section shows our contribution to proving the conjecture.
This study uses an Artificial Neural Network (ANN) to examine the constitutive relationships of the Glass Fiber Reinforced Polymer (GFRP) residual tensile strength at elevated temperatures. The objective is to develop an effective model and establish fire performance criteria for concrete structures in fire scenarios. Multilayer networks that employ reactive error distribution approaches can determine the residual tensile strength of GFRP using six input parameters, in contrast to previous mathematical models that utilized one or two inputs while disregarding the others. Multilayered networks employing reactive error distribution technology assign weights to each variable influencing the residual tensile strength of GFRP. Temperatur
... Show MoreSuzanne Collins’ novel The Hunger Games suggests a new logic of victory and set a distinguished focus on the unique personality of her heroin which brings to the mind the permanent correlation between all moral values. The Hunger Games World seems to be much more like one big bowl as it links the past, present, and the future. An Intertextual reference is interwoven in the present research as it brings Golding’s Lord of the Flies to the surface, and it highlights certain similarities between the two texts. In which Ralph, Piggy and Simon in Golding’s Lord of the Flies are the incarnations of stable moral values and hope of surviving ethics and rules in a chaotic and turmoil world. The event
... Show MoreCurrent Thesis has aimed to identify : The Psychological barriers for university students , Differences in psychological barriers depending on the variable sex (Males – Females) , Adjustment to College life for university students, Differences in Adjustment to College at university life depending on the variable sex (Males – Females), and finally, The correlation between psychological barriers and Adjustment to College life. The researcher has prepared a sample consisted of (100) male and female students who were randomly selected from university students, The researcher has adopted a measure of (2002) to measure the psychological barriers, also the researcher adjustment scale with university life.
The results showed that universi
Computer systems and networks are increasingly used for many types of applications; as a result the security threats to computers and networks have also increased significantly. Traditionally, password user authentication is widely used to authenticate legitimate user, but this method has many loopholes such as password sharing, brute force attack, dictionary attack and more. The aim of this paper is to improve the password authentication method using Probabilistic Neural Networks (PNNs) with three types of distance include Euclidean Distance, Manhattan Distance and Euclidean Squared Distance and four features of keystroke dynamics including Dwell Time (DT), Flight Time (FT), mixture of (DT) and (FT), and finally Up-Up Time (UUT). The resul
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