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

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 this paper, SiO2 nanoparticles thin films were synthesised at different PH values of solution by sol gel method at fixed temperature (25oC) and molar ratio (R =H2O/precursor) of (Tetra Ethyl Ortho Silicate) TEOS as precursor at (R=1). The structure and optical properties of the thin films have been investigated. All thin films were tested by using X-RAY diffraction. All X-RAY spectrum can be indexed as monoclinic structure with strong crystalline (110) plane. The morphological properties of the prepared films were studied by SEM. The results indicate that all films are in nano scale and the particle size around (19-62) nm .The size of silica particles increases with increasing PH value of solution where both the rate of hydrolysis and

 An oil spill is a leakage of pipelines, vessels, oil rigs, or tankers that leads to the release of petroleum products into the marine environment or on land that happened naturally or due to human action, which resulted in severe damages and financial loss. Satellite imagery is one of the powerful tools currently utilized for capturing and getting vital information from the Earth's surface. But the complexity and the vast amount of data make it challenging and time-consuming for humans to process. However, with the advancement of deep learning techniques, the processes are now computerized for finding vital information using real-time satellite images. This paper applied three deep-learning algorithms for satellite image classification

   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

To maintain a sustained competitive position in the contemporary environment of  knowledge  economy,  organizations  as an open social systems must have an ability to learn and know  how to adapt to rapid changes  in a proper fashion so that organizational objectives will be achieved efficiently and effectively.  A multilevel approach is adopted proposing that organizational learning suffers from the lack of interest about the strategic competitive performance of the organization. This remains implicit almost in all models of organizational learning and there is little focus on how learning organizations achieve sustainable competitive advantage . A dynamic model that captures t

Most recent studies have focused on using modern intelligent techniques spatially, such as those
developed in the Intruder Detection Module (IDS). Such techniques have been built based on modern
artificial intelligence-based modules. Those modules act like a human brain. Thus, they should have had the
ability to learn and recognize what they had learned. The importance of developing such systems came after
the requests of customers and establishments to preserve their properties and avoid intruders’ damage. This
would be provided by an intelligent module that ensures the correct alarm. Thus, an interior visual intruder
detection module depending on Multi-Connect Architecture Associative Memory (MCA)

This Study aimed To know The relation between Types of blood and health problems which human Suffered from , and the effect of food intake on health.
Samples of study contained 269 person aged between 30 – 70 years which choiced randomly for sex , we are take all in formation about samples of study by form paper contian sex , age, type of blood , weight (kg) , height (cm) , smoking or.not , sporting or not, problems in digestive tract , sensitivity for foods , heart problems , ratio of cholesterol in blood , Sinusitis , Asthma , diabetic meliuts , arritable bowel syndrome , diaherra , problems in kidney and urination , hypertension , anemia , alternation in liver function , arthritis with form record in daily food intake and its ade

In this paper, experimental study has been done for temperature distribution in space conditioned with Ventilation Hollow Core Slab (TermoDeck) system. The experiments were carried out on a model room with dimensions of (1m 1.2m 1m) that was built according to a suitable scale factor of (1/4). The temperature distributions was measured by 59 thermocouples fixed in several locations in the test room. Two cases were considered in this work,  the first one during unoccupied period at night time (without external load) and the other at day period with external load of 800W/m² according to solar heat gain calculations during summer season in Iraq. All results confirm the use of TermoDeck system for ventilation and cooling/heat

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