Abstract Background: The daily usage of maxillofacial prostheses causes them to mechanically deteriorate with time. This study was aimed to evaluate the reinforcement of VST50F maxillofacial silicone by using yttrium oxide (Y2O3) nanoparticles (NPs) to resist aging and mechanical deterioration. Materials and Method: Y2O3 NPs (30–45nm) were loaded into VST50F maxillofacial silicone in two weight percentages (1 and 1.5 wt%), which were predetermined in a pilot study as the best rates for improving tear strength with minimum increase in hardness values. A total of 120 specimens were prepared and divided into the control and experimental groups (with 1 and 1.5 wt% Y2O3 addition). Each group included 40 specimens, 10 specimens for each paramet

In this study, we tackle the understudied area of Artificial Intelligence (AI) and its role in examining how modern revolutions may affect political systems across the Middle Eastern region. despite hundreds of studies documenting Middle Eastern uprisings over the past three decades, there has been little effort to harness AI to better understand or predict these multifaceted events. This study seeks to address this gap by assessing the performance of AI-intelligence in analyzing (broadly) revolutionary processes and their effects on regional political systems. The research uses a mixedmethod methodology that involves a systematic literature review of contemporary scholarly articles, and an analytics study using AI tools. Our results show t

In this work we present a technique to extract the heart contours from noisy echocardiograph images. Our technique is based on improving the image before applying contours detection to reduce heavy noise and get better image quality. To perform that, we combine many pre-processing techniques (filtering, morphological operations, and contrast adjustment) to avoid unclear edges and enhance low contrast of echocardiograph images, after implementing these techniques we can get legible detection for heart boundaries and valves movement by traditional edge detection methods.

In this paper, a fast lossless image compression method is introduced for compressing medical images, it is based on splitting the image blocks according to its nature along with using the polynomial approximation to decompose image signal followed by applying run length coding on the residue part of the image, which represents the error caused by applying polynomial approximation. Then, Huffman coding is applied as a last stage to encode the polynomial coefficients and run length coding. The test results indicate that the suggested method can lead to promising performance.

Features is the description of the image contents which could be corner, blob or edge. Corners are one of the most important feature to describe image, therefore there are many algorithms to detect corners such as Harris, FAST, SUSAN, etc. Harris is a method for corner detection and it is an efficient and accurate feature detection method. Harris corner detection is rotation invariant but it isn’t scale invariant. This paper presents an efficient harris corner detector invariant to scale, this improvement done by using gaussian function with different scales. The experimental results illustrate that it is very useful to use Gaussian linear equation to deal with harris weakness.

Video streaming is widely available nowadays. Moreover, since the pandemic hit all across the globe, many people stayed home and used streaming services for news, education,  and entertainment. However,   when streaming in session, user Quality of Experience (QoE) is unsatisfied with the video content selection while streaming on smartphone devices. Users are often irritated by unpredictable video quality format displays on their smartphone devices. In this paper, we proposed a framework video selection scheme that targets to increase QoE user satisfaction. We used a video content selection algorithm to map the video selection that satisfies the user the most regarding streaming quality. Video Content Selection (VCS) are classified in

Abstract

 This study investigated the optimization of wear behavior of AISI 4340 steel based on the Taguchi method under various testing conditions. In this paper, a neural network and the Taguchi design method have been implemented for minimizing the wear rate in 4340 steel. A back-propagation neural network (BPNN) was developed to predict the wear rate. In the development of a predictive model, wear parameters like sliding speed, applying load and sliding distance were considered as the input model variables of the AISI 4340 steel. An analysis of variance (ANOVA) was used to determine the significant parameter affecting the wear rate. Finally, the Taguchi approach was applied to determine

     The research aims to study and analysis of concurrent engineering (CE) and cost optimization (CO), and the use of concurrent engineering inputs to outputs to improve the cost, and the statement of the role of concurrent engineering in improving the quality of the product, and achieve savings in the design and manufacturing time and assembly and reduce costs, as well as employing some models to determine how much the savings in time, including the model (Lexmark) model (Pert) to determine the savings in design time for manufacturing and assembly time.

To achieve the search objectives, the General Company for Electrical and Electronic Industries \ Refrigerated Engine

The maximization of the net present value of the investment in oil field improvements is greatly aided by the optimization of well location, which plays a significant role in the production of oil. However, using of optimization methods in well placement developments is exceedingly difficult since the well placement optimization scenario involves a large number of choice variables, objective functions, and restrictions. In addition, a wide variety of computational approaches, both traditional and unconventional, have been applied in order to maximize the efficiency of well installation operations. This research demonstrates how optimization approaches used in well placement have progressed since the last time they were examined. Fol