Zigbee, which has the standard IEEE 802.15.4. It is advisable method to build wireless personal area network (WPAN) which demands a low power consumption that can be produced by Zigbee technique. Our paper gives measuring efficiency of Zigbee involving the Physical Layer (PL) and Media Access Control (MAC) sub-layer , which allow a simple interaction between the sensors. We model and simulate two different scenarios, in the first one, we tested the topological characteristics and performance of the IEEE802.15.4 standard in terms of throughput, node to node delay and figure of routers for three network layouts (Star, Mesh and Cluster Tree) using OPNET simulator. The second scenario investigates the self-healing feature on a mesh

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Fabrication of porous clay refractory insulating specimens from Iraqi kaolin with different percentage of Expanded Polystyrene (EPS) waste crumbs additions were investigated. After mixing and forming by hand molding, the specimens was dried and fired at 1300 oC. The structural, physical, mechanical and thermal properties of the refractory insulating products were measured. Maximum addition of EPS (1.25 wt%) lead to reduce the linear shrinkage to less than 1.7% and increased apparent porosity up to 50 %. As well as, the density, Modulus of rupture and thermal conductivity were reduced to 1.39 g/cm3, 4.1 MPa and 0.21 W/m.K, respectively. The final outcome, addition of EPS showed good results in the formation of pores without distorting the

In this study many specimen s were prepared from 2024-T3 Aluminum alloy for corrosion test by the dimensions of (15*15*3) mm according to ASTM G71-31 and then subjected to shot peening process at different time (15, 30, 45) minutes using steel ball having a diameter of 2.75 mm and Rockwell Hardness of 55R_C to induce compressive residual stress which were measured using X-Ray diffraction method, surface roughness and   hardness were tested before and after peening. Electrochemical corrosion test by Tafel extrapolation method was carried out in an environment of 3 .5% NaCl solutions (sea water) where Corrosion rate calculated using Tafle equation.

The obtained results show a favorable influence of SP treatment

Furfural is a toxic aromatic aldehyde that can cause a severe environmental problem especially the wastewater drown from petroleum refinery units. In the present work, a useless by-product from local furniture manufacturing industry; sawdust was used as raw material for the preparation of activated carbon which is chemically activated with phosphoric acid. The effect of adsorption variables which include initial pH of solution (2-9), agitation speed (50-250) rpm, agitation time (15-120) min, initial concentration of furfural (50-250) ppm, and amount of adsorbent material (0.5-2.5) g for the three adsorbents used (prepared activated carbon, commercial activated carbon and raw sawdust) were investigated in a batch process

The main aim of this paper is studied the punching shear and behavior of reinforced concrete slabs exposed to fires, the possibility of punching shear failure occurred as a result of the fires and their inability to withstand the loads. Simulation by finite element analysis is made to predict the type of failure, distribution temperature through the thickness of the slabs, deformation and punching strength. Nonlinear finite element transient thermal-structural analysis at fire conditions are analyzed by ANSYS package. The validity of the modeling is performed for the mechanical and thermal properties of materials from earlier works from literature to decrea

This study introduced the effect of using magnetic abrasive finishing method (MAF) for finishing flat surfaces. The results of experiment allow considering the MAF method as a perspective for finishing flat surfaces, forming optimum physical mechanical properties of surfaces layer, removing the defective layers and decreasing the height of micro irregularities. Study the characteristics which permit judgment parameters of surface quality after MAF method then comparative with grinding

Background/Objectives: The purpose of this study was to classify Alzheimer’s disease (AD) patients from Normal Control (NC) patients using Magnetic Resonance Imaging (MRI). Methods/Statistical analysis: The performance evolution is carried out for 346 MR images from Alzheimer's Neuroimaging Initiative (ADNI) dataset. The classifier Deep Belief Network (DBN) is used for the function of classification. The network is trained using a sample training set, and the weights produced are then used to check the system's recognition capability. Findings: As a result, this paper presented a novel method of automated classification system for AD determination. The suggested method offers good performance of the experiments carried out show that the