Manufacturing systems of the future foresee the use of intelligent vehicles, optimizing and navigating. The navigational problem is an important and challenging problem in the field of robotics. The robots often find themselves in a situation where they must find a trajectory to another position in their environment, subject to constraints posed by obstacles and the capabilities of the robot itself. On-line navigation is a set of algorithms that plans and executes a trajectory at the same time.         The system adopted in this research searches for a robot collision-free trajectory in a dynamic environment in which obstacles can move while the robot was moving toward the target. So, the ro

The rising prevalence of obesity-related glomerulopathy (ORG) occurs in accordance with the rising prevalence of obesity worldwide. Clinically ORG is manifested by slowly progressing microalbuminuria that may develop to clinically evident proteinuria. Pathological characteristics of ORG include glomerular hypertrophy in the presence or absence of focal segmental glomerulosclerosis (FSGS). ORG can develop into clinically overt chronic renal insufficiency or even end-stage kidney disease. This article reviews the most important mechanisms for the development of ORG; that are abnormal renal hemodynamics, stimulation of renin-angiotensin-aldosterone system (RAAS), impairment of insulin sensetivity, ectopic lipid deposition, adipose tissue cy

Abstract

Pneumatic processes sequence (PPS) is used widely in industrial applications. It is common to do a predetermined PPS to achieve a specific larger task within the industrial application like the PPS achieved by the pick and place industrial robot arm. This sequence may require change depending on changing the required task and usually this requires the programmer intervention to change the sequence’ sprogram, which is costly and may take long time. In this research a PLC-based PPS control system is designed and implemented, in which the PPS is programmed by demonstration. The PPS could be changed by demonstrating the new required sequence via the user by following simple series of manual steps without h

     The conventional procedures of clustering algorithms are incapable of overcoming the difficulty of managing and analyzing the rapid growth of generated data from different sources. Using the concept of parallel clustering is one of the robust solutions to this problem. Apache Hadoop architecture is one of the assortment ecosystems that provide the capability to store and process the data in a distributed and parallel fashion. In this paper, a parallel model is designed to process the k-means clustering algorithm in the Apache Hadoop ecosystem by connecting three nodes, one is for server (name) nodes and the other two are for clients (data) nodes. The aim is to speed up the time of managing the massive sc

In this study, He's parallel numerical algorithm by neural network is applied to type of integration of fractional equations is Abel’s integral equations of the 1^st and 2^nd kinds. Using a Levenberge – Marquaradt training algorithm as a tool to train the network. To show the efficiency of the method, some type of Abel’s integral equations is solved as numerical examples. Numerical results show that the new method is very efficient problems with high accuracy.

An automatic text summarization system mimics how humans summarize by picking the most ‎significant sentences in a source text. However, the complexities of the Arabic language have become ‎challenging to obtain information quickly and effectively. The main disadvantage of the ‎traditional approaches is that they are strictly constrained (especially for the Arabic language) by the ‎accuracy of sentence feature ‎functions, weighting schemes, ‎and similarity calculations. On the other hand, the meta-heuristic search approaches have a feature tha

This paper includes a comparison between denoising techniques by using statistical approach, principal component analysis with local pixel grouping (PCA-LPG), this procedure is iterated second time to further improve the denoising performance, and other enhancement filters were used. Like adaptive Wiener low pass-filter to a grayscale image that has been degraded by constant power additive noise, based on statistics estimated from a local neighborhood of each pixel. Performs Median filter of the input noisy image, each output pixel contains the Median value in the M-by-N neighborhood around the corresponding pixel in the input image, Gaussian low pass-filter and Order-statistic filter also be used.

Experimental results shows LPG-

     This paper presents a new RGB image encryption scheme using multi chaotic maps. Encrypting an image is performed via chaotic maps to confirm the properties of secure cipher namely confusion and diffusion are satisfied. Also, the key sequence for encrypting an image is generated using a combination of   1D logistic and Sine chaotic maps. Experimental results and the compassion results indicate that the suggested scheme provides high security against several types of attack, large secret keyspace and highly sensitive.   

This study deals with the subject of art criticism by using Erwin Panofsky's theory to analyze a few Saudi artists' works. The study aims to identify Panofsky's theory and provide criticism of some Saudi artworks using it. The importance of the study is that it enriches the field of art criticism in the Kingdom of Saudi Arabia and helps critics and artists in using Panofsky’s theory to analyze artworks.
The study sample consists of six artworks produced in 2021 by six contemporary Saudi artists. In the theoretical section, the study dealt with several topics; first, is art criticism, the second part presents Panofsky’s theory with its three stages, the final part deals with the beginning of Saudi art until present time and its

  This paper deals  the prediction of the process of  random spatial data of two properties, the first is called  Primary variables  and the second is called secondary  variables ,   the method  that were used in the  prediction process for this type  of data is technique Co-kriging  , the method is usually used when the number of primary variables  meant to predict for one of its elements is measured in a particular location a few (because of the cost or difficulty of obtaining them) compare with secondary variable which is the number of elements  are available and  highly correlated with primary variables, as was the&nbs