Localization is an essential demand in wireless sensor networks (WSNs). It relies on several types of measurements. This paper focuses on positioning in 3-D space using time-of-arrival- (TOA-) based distance measurements between the target node and a number of anchor nodes. Central localization is assumed and either RF, acoustic or UWB signals are used for distance measurements. This problem is treated by using iterative gradient descent (GD), and an iterative GD-based algorithm for localization of moving sensors in a WSN has been proposed. To localize a node in 3-D space, at least four anchors are needed. In this work, however, five anchors are used to get better accuracy. In GD localization of a moving sensor, the algo

Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d

In this research, the problem of multi- objective modal transport was formulated with mixed constraints to find the optimal solution. The foggy approach of the Multi-objective Transfer Model (MOTP) was applied. There are three objectives to reduce costs to the minimum cost of transportation, administrative cost and cost of the goods. The linear membership function, the Exponential membership function, and the Hyperbolic membership function. Where the proposed model was used in the General Company for the manufacture of grain to reduce the cost of transport to the minimum and to find the best plan to transfer the product according to the restrictions imposed on the model.

The study aims to achieve several objectives, including follow-up scientific developments and transformations in the modern concepts of the Holistic Manufacturing System for the purpose of identifying the methods of switching to the entrances of artificial intelligence, and clarifying the mechanism of operation of the genetic algorithm under the Holonic Manufacturing System, to benefit from the advantages of systems and to achieve the maximum savings in time and cost of machines Using the Holistic Manufacturing System method and the Genetic algorithm, which allows for optimal maintenance time and minimizing the total cost, which in turn enables the workers of these machines to control the vacations in th

This study aims to show, the strength of steel beam-concrete slab system without using shear connectors (known as a non-composite action), where the effect of the friction force between the concrete slab and the steel beam has been investigated, by using finite element simulation.

The proposed finite element model has been verified based on comparison with an experimental work. Then, the model was adopted to study the system strength with a different steel beam and concrete slab profile. ABAQUS has been adopted in the preparation of all numerical models for this study.

After validation of the numerical models, a parametric study was conducted, with linear and non-linear Regression analysis. An equation re

In this study, dependence of gamma-ray absorption coefficient on the size of Pb particle size ranging from 200µm up to 2.5mm, using different weights of each particle size. The results show that gamma-ray attenuation coefficient is inversely proportional with the size of Pb particle size due to the reduction of the spaces between the lead particles.

This work aimed to use effective, low-cost, available, and natural adsorbents like eggshells for removal of  hazardous organic dye result from widely number of  industries and study the influence of different eggshell particle size (75, 150) Mm.  The adsorbent was characterized by SEM, EDX, BET and FTIR . The initial pH of dye solutions  varying from 4 to 10 , the initial concentrations of methyl violet (MV) 2B range (20-80) mg/L, dosage range (0.5-10) g, contact time (30-180) min, and particles size of the adsorbent (75, 150) Mm were selected to be studied. Two adsorption isotherms models have been used to fit the experimental data. Langmuir and Freunlich models were found to more represent the experiments with high

Avery large numbers of articles are made by powder metallurgical methods using electrolytically reduced metal powders. Iron powder is one of these powders which play an important role in this field. Its preparation by electrolytic method is economic in comparison with the traditional methods (Atomization and carbonyl processes).

An electrochemical cell consisting of two electrodes (stainless steel cathode and iron anode, 99.9%) was used to study the electrolytic preparation of iron powder with particle size less than 106µm directly as powde1y form. Ferrous sulphate electrolyte was used containing sodium chloride as a stabilizing agent. The produced powder was thoroughly washed with an acidified distilled water and absolute ethan