Image compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye

This study employs evolutionary optimization and Artificial Intelligence algorithms to determine an individual’s age using a single-faced image as the basis for the identification process. Additionally, we used the WIKI dataset, widely considered the most comprehensive collection of facial images to date, including descriptions of age and gender attributes. However, estimating age from facial images is a recent topic of study, even though much research has been undertaken on establishing chronological age from facial photographs. Retrained artificial neural networks are used for classification after applying reprocessing and optimization techniques to achieve this goal. It is possible that the difficulty of determining age could be reduce

A new and hybrid deep learning-based approach for diagnosing faults in electric vehicle (EV) drive motors is proposed in this article. This article presents a new and hybrid deep learning-based method of diagnosing faults in the drive motors of electric vehicles (EV). In contrast to standard CNNLSTM approaches that depend on SoftMax classification, the introduced framework combines a Random Forest (RF) classifier to enhance the generalization, interpretability, and robustness of fault prediction. Furthermore meant for use on edge computing equipment with IoT integration, the design allows for real-time monitoring in resource-limited settings. The introduced algorithm utilizes a Random Forest (RF) classifier for accurate fault classification

In this paper, chip and powder copper are used as reinforcing phase in polyester matrix to form composites. Mechanical properties such as flexural strength and impact test of polymer reinforcement copper (powder and chip) were done, the maximum flexural strength for the polymer reinforcement with copper (powder and chip) are (85.13 Mpa) and (50.08 Mpa) respectively was obtained, while the maximum observation energy of the impact test for the polymer reinforcement with copper (powder and chip) are (0.85 J) and (0.4 J) respectively  

Mechanical degradation hampers the practical usage of polymers for turbulent drag reduction
application. Mechanical degradation refers to the chemical process in which the activation energy of
polymer chain scission is exceeded by mechanical action on the polymer chain, and bond rupture
occurs. When a water-soluble polymer and surfactant are mixed in water solution, the specific structures
(aggregates) are formed, in which polymer film is formed around micelle. In this work, Xanthan gum (XG) –
Sodium lauryl ether sulfate (SELS) complex formation and its effect on percentage viscosity reduction
(%VR) was studied. It was found that SELS surfactant reduced the mechanical degradation of XG much
more efficiently than th

Background: Facial disfigurement can be the result of a congenital anomaly, trauma or tumor surgery, in many cases the prosthetic rehabilitation is indicated. Maxillofacial prosthetic materials should have desirable and ideal physical, aesthetic, and biological properties and those properties should be kept for long period of time in order to reach patient acceptance. Silicone elastomer are the most commonly used material for facial restoration because of its favorable properties mechanically and physically as the biocompatibility and good elasticity. Aim of this study: This study aimed to evaluate the effect of addition of Aluminum oxide (Al2O3) Nano fillers in different concentrations on tear strength and hardness of VST 50F room tempe

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% (

A friction stir spot welding (FSSW) process is an emerging solid state joining process in which the material that is being welded does not melt. In this investigation an attempt has been made to understand the effect of tool shoulder diameter on the mechanical properties of the joint. For this purpose four welding tools diameter (10,13, 16 and 19) mm at constant preheating time and plunging time were used to carry
out welding process. Effect of tool diameter on mechanical properties of welded joints was investigated using shear stress test and Microhardness of joint which welded was studied. Based on the stir welding experiments conducted in this study the results show that aluminum alloy (1200) can be welded using (FSSW) process with

Background: Polymethyl methacrylate (PMMA) is the most commonly used material in denture fabrication. The material is far from ideal in fulfilling the mechanical requirements. Midline fracture; poor thermal conductivity and water sorption, are common problem in this material. The purpose of this study was to evaluate the effect of addition of surface treated Aluminum oxide nano fillers on some properties of heat cured (PMMA). Materials and methods: In addition to controlled group of heat cured PMMA the silanized (Al2O3) nanoparticles was added to PMMA powder by weight in three different percentages 1wt%, 2wt% and 3wt%, mixed by probe ultra-sonication machine. 200 specimens were constructed and divided into 5 groups according to the test (e