In this study, Laser Shock Peening (LSP) effect on the polymeric composite materials has been investigated experimentally. Polymeric composite materials are widely used because they are easy to fabricate and have many attractive features. Unsaturated polyester resin as a matrix was selected and Aluminum powder with micro particles as a reinforcement material was used with different volume fraction (2.5%, 5% and 7.5%). Hand lay-up process was used for preparation the composites. Fatigue test with constant amplitude with stress ratio (R =-1) was carried out before and after LSP process with two levels of energy (1Joule and 2Joule). The result showed an increase in the endurance strength of 25.448% at 7.5% volume fraction when peened is 1J

In the present research synthesis and study of biological activity a series of new polymers modified of chitosan with compounds containing azo group. Beginning diazonium salt produced from 3,3'-dimethyl-[1,1'-biphenyl]-4,4'-diamine reacted with concentrated HCl acid and sodium nitrite. The coupling reaction between diazonium salt with substituted aromatic aldehyde to produce Azo derivatives )1-6(. Azo Schiff bases Chitosan )7-12( were synthesized by condensation of Chitosan with Azo derivatives )1-6( in ethanol with some drops of glacial acetic acid. The structural modifications of Chitosan ring (linked to a bioactive azo moiety) were expected to give new derivatives )7-12( with a diverse range of biological functions. These compounds' st

Classifying an overlapping object is one of the main challenges faced by researchers who work in object detection and recognition. Most of the available algorithms that have been developed are only able to classify or recognize objects which are either individually separated from each other or a single object in a scene(s), but not overlapping kitchen utensil objects. In this project, Faster R-CNN and YOLOv5 algorithms were proposed to detect and classify an overlapping object in a kitchen area.  The YOLOv5 and Faster R-CNN were applied to overlapping objects where the filter or kernel that are expected to be able to separate the overlapping object in the dedicated layer of applying models. A kitchen utensil benchmark image database and

Deep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to

   Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct

The rapid development of telemedicine services and the requirements for exchanging medical information between physicians, consultants, and health institutions have made the protection of patients’ information an important priority for any future e-health system. The protection of medical information, including the cover (i.e. medical image), has a specificity that slightly differs from the requirements for protecting other information. It is necessary to preserve the cover greatly due to its importance on the reception side as medical staff use this information to provide a diagnosis to save a patient's life. If the cover is tampered with, this leads to failure in achieving the goal of telemedicine. Therefore, this work provides an in

Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise

Semi-parametric models analysis is one of the most interesting subjects in recent studies due to give an efficient model estimation. The problem when the response variable has one of two values either 0 ( no response) or one – with response which is called the logistic regression model.

We compare two methods Bayesian and . Then the results were compared using MSe criteria.

A simulation had been used to study the empirical behavior for the Logistic model , with  different sample sizes and variances. The results using represent that the Bayesian method is better than the   at small samples sizes.

The research examines the awareness of the components of responsible citizenship among primary schoolgirls in Jeddah using a descriptive approach. A test was then prepared, which consists of loyalty, affiliation to homeland, conscious citizenship based on the knowledge of rights, the fulfillment of duties, family roles in education and society revival, homeland and preservation of the components and gains, participation in achievements, and of national heritage. To maintain the validity and reliability of the study, 28-item test of multiple-choice and short essays type was applied to a random sample of (303) female students in the (fourth-fifth-sixth) primary school class in Jeddah. Results have shown that the level of awareness of schoo

 Abstract:

Typological analysis about  the negation marker  in different languages is one of the fields of research that has attracted much attention.  In Persian language, this constituent has been analysed from different aspects. This study aimed to analyse  different aspects of negation marker  in  the adjectives,  the noun phrases and  the verb phrases based on typological analysis.  Many studies have been revealed that  the negation in adjectives has shown lexically and morphologically. In the noun phrases, /hich/  has used as a negative marker necessarily marking the verb phrase as negative too. In the verb phrases, negation occurs morphologically by the addition of the prefix /n