In this paper, the memorization capability of a multilayer interpolative neural network is exploited to estimate a mobile position based on three angles of arrival. The neural network is trained with ideal angles-position patterns distributed uniformly throughout the region. This approach is compared with two other analytical methods, the average-position method which relies on finding the average position of the vertices of the uncertainty triangular region and the optimal position method which relies on finding the nearest ideal angles-position pattern to the measured angles. Simulation results based on estimations of the mobile position of particles moving along a nonlinear path show that the interpolative neural network approach outperf

Wellbore instability and sand production onset modeling are very affected by Sonic Shear Wave Time (SSW). In any field, SSW is not available for all wells due to the high cost of measuring. Many authors developed empirical correlations using information from selected worldwide fields for SSW prediction. Recently, researchers have used different Artificial Intelligence methods for estimating SSW. Three existing empirical correlations of Carroll, Freund, and Brocher are used to estimate SSW in this paper, while a fourth new empirical correlation is established. For comparing with the empirical correlation results, another study's Artificial Neural Network (ANN) was used. The same data t

The objective of this study was to develop neural network algorithm, (Multilayer Perceptron), based correlations for the prediction overall volumetric mass-transfer coefficient (k_La), in slurry bubble column for gas-liquid-solid systems. The Multilayer Perceptron is a novel technique based on the feature generation approach using back propagation neural network. Measurements of overall volumetric mass transfer coefficient were made with the air - Water, air - Glycerin and air - Alcohol systems as the liquid phase in bubble column of 0.15 m diameter. For operation with gas velocity in the range 0-20 cm/sec, the overall volumetric mass transfer coefficient was found to decrease w

This paper experimentally investigates the heating process of a hot water supply using a neural network implementation of a self-tuning PID controller on a microcontroller system. The Particle Swarm Optimization (PSO) algorithm employed in system tuning proved very effective, as it is simple and fast optimization algorithm. The PSO method for the PID parameters is executed on the Matlab platform in order to put these parameters in the real-time digital PID controller, which was experimented with in a pilot study on a microcontroller platform. Instead of the traditional phase angle power control (PAPC) method, the Cycle by Cycle Power Control (CBCPC) method is implemented because it yields better power factor and eliminates harmonics

Alzheimer's disease (AD) increasingly affects the elderly and is a major killer of those 65 and over. Different deep-learning methods are used for automatic diagnosis, yet they have some limitations. Deep Learning is one of the modern methods that were used to detect and classify a medical image because of the ability of deep Learning to extract the features of images automatically. However, there are still limitations to using deep learning to accurately classify medical images because extracting the fine edges of medical images is sometimes considered difficult, and some distortion in the images. Therefore, this research aims to develop A Computer-Aided Brain Diagnosis (CABD) system that can tell if a brain scan exhibits indications of

        The Rivest–Shamir–Adleman (RSA) and the Diffie-Hellman (DH) key exchange are famous methods for encryption. These methods  depended on selecting the primes p and q in order  to be secure enough . This paper shows that the named methods used the primes which are found by some arithmetical function .In the other sense, no need to think about getting primes p and q and how they are secure enough, since the arithmetical function enable to build the primes in such complicated way to be secure. Moreover, this article   gives  new construction  of the  RSA  algorithm and DH key  exchange using the

primes p,qfrom areal number x.

The task of an educational institution such as kindergartens need to run by managers possess the knowledge to manage the administration of the importance in the development of kindergarten has been the goal of research to identify knowledge management at Riyadh managers, and achieve the objectives of Search selected sample of directors of kindergartens in the city of Baghdad was (160) director was Akhtarhn simple random way, been building measure for knowledge management and presented to the group of experts and extracted stability in a way re-testing and Alvakronbach and reach search to a discrepancy between managers Riyadh in knowledge management and put the researcher set of recommendations including the establishment of seminars and

       Most of the literature on the management and application terkzat waved the last period on large organizations was the negligence  of  knowledge management in small organizations where research aims to find out knowleddge management, small projects  In oxygen Ahli plant in Iraq, and the fact the role of knowledge management in small projects from the standpoint of employees in order to achieve this used production method results.  The results showed that knowledge management has a role in the high level of productivity during the years 2010-2013. The results showed that knowledge management has a role in the high level of productivity during the years 2

An Intelligent Internet of Things network based on an Artificial Intelligent System, can substantially control and reduce the congestion effects in the network. In this paper, an artificial intelligent system is proposed for eliminating the congestion effects in traffic load in an Intelligent Internet of Things network based on a deep learning Convolutional Recurrent Neural Network with a modified Element-wise Attention Gate. The invisible layer of the modified Element-wise Attention Gate structure has self-feedback to increase its long short-term memory. The artificial intelligent system is implemented for next step ahead traffic estimation and clustering the network. In the proposed architecture, each sensing node is adaptive and able to