Buildings such as malls, offices, airports and hospitals nowadays have become very complicated which increases the need for a solution that helps people to find their locations in these buildings. GPS or cell signals are commonly used for positioning in an outdoor environment and are not accurate in indoor environment. Smartphones are becoming a common presence in our daily life, also the existing infrastructure, the Wi-Fi access points, which is commonly available in most buildings, has motivated this work to build hybrid mechanism that combines the APs fingerprint together with smartphone barometer sensor readings, to accurately determine the user position inside building floor relative to well-known lan

Abstract  

Magnetic abrasive finishing (MAF) process is one of non-traditional or advanced finishing methods which is suitable for different materials and produces high quality level of surface finish where it uses magnetic force as a machining pressure. A set of experimental tests was planned according to Taguchi orthogonal array (OA) L27 (3⁶) with three levels and six input parameters. Experimental estimation and optimization of input parameters for MAF process for stainless steel type 316 plate work piece, six input parameters including amplitude of tooth pole, and number of cycle between teeth, current, cutting speed, working gap, and finishing time, were performed by design of experiment

Due to the rapid advancement of technology and the technology of things, modern industries start to need a highprecision equipment and surface finishing, so many finishing processes began to develop. One of the modern processes is Magnetic Abrasive Finishing (MAF), which is a high-precision process for internal and external finishing under the influence of a magnetic field of abrasive particles. Boron Carbide (B4C) ceramics was tested by mixing it with iron (Fe) and produced abrasive particles to reduce the intensity of scraping on the surface, reduce the economic cost and achieve a high finishing addition to remove the edges at the same time. The material selected for the samples was mild steel (ASTM E415) under (Quantity of Abrasives, Mac

The effect of electrolysis operating parameters on the removal efficiency of cadmium from a simulated wastewater was studied by adopting response surface methodology combined with Box–Behnken Design. As a new electrode design, spiral-wound woven wire mesh rotating cylinder electrode was used for cadmium removal. Current (240–400 mA), rotation speed (200–1000 rpm), initial cadmium concentration (200–600ppm), and cathode mesh number (30–60) were chosen as independent variables while the removal efficiency of cadmium was considered as a response function. The results revealed that the rotation speed has the major effect on the removal efficiency of cadmium. Regression analysis showed good fit of the experimental data to the second-or

This work aims to provide a statistical analysis of metal removal during the Magnetic Abrasive Finishing process (MAF) and find out the mathematical model which describes the relationship between the process parameters and metal removal, also estimate the impact of the parameters on metal removal. In this study, the single point incremental forming was used to form the truncated cone made of low carbon steel (1008-AISI) based on the Z-level tool path. Then the finishing was accomplished using a magnetic abrasive process based on the Box-Behnken design of the experiment using Minitab 17 software was used to finish the surface of the formed truncated cone. The influences of different parameters (feed rate, machining step s

The Pulse Coupled Oscillator (PCO) has attracted substantial attention and widely used in wireless sensor networks (WSNs), where it utilizes firefly synchronization to attract mating partners, similar to artificial occurrences that mimic natural phenomena. However, the PCO model might not be applicable for simultaneous transmission and data reception because of energy constraints. Thus, an energy-efficient pulse coupled oscillator (EEPCO) has been proposed, which employs the self-organizing method by combining biologically and non-biologically inspired network systems and has proven to reduce the transmission delay and energy consumption of sensor nodes. However, the EEPCO method has only been experimented in attack-free networks without

Dust is a frequent contributor to health risks and changes in the climate, one of the most dangerous issues facing people today. Desertification, drought, agricultural practices, and sand and dust storms from neighboring regions bring on this issue. Deep learning (DL) long short-term memory (LSTM) based regression was a proposed solution to increase the forecasting accuracy of dust and monitoring. The proposed system has two parts to detect and monitor the dust; at the first step, the LSTM and dense layers are used to build a system using to detect the dust, while at the second step, the proposed Wireless Sensor Networks (WSN) and Internet of Things (IoT) model is used as a forecasting and monitoring model. The experiment DL system

In the current analysis, the effects of circumferential scratches along the inner surface of a 170ᵒ -arc partial journal bearing has been numerically investigated. Their impact on the thermo-elasto-hydrodynamic performance characteristics, including maximum pressure, temperature, deformation, and stress, has been examined thoroughly. The ANSYS Fluent CFD commercial code was employed to tackle the iterative solution of flow and heat transfer patterns in the fluid film domain. They are then applied to the ANSYS Static Structure solver to compute the deformation and stress resulted in the solid bearing zone. A wide range of operating conditions has been considered, including the eccentricity ratio ( ) and scratch depth (

Background: To investigate the effect of different types of storage media on enamel surface microstructure of avulsed teeth by using atomic force microscope.Materials and methods : Twelve teeth blocks from freshly extracted premolars for orthodontic treatment were selected . The study samples were divided into three groups according to type of storage media :A-egg white , B- probiotic yogurt , and C-bovine milk . All the samples were examined for changes in surface roughness and surface granularity distribution  using atomic force microscope, at two periods: baseline, and after 8 hours of immersing in the three types of storage media. Results: Milk group had showed a significant increase in the mean of the  roughness values at

The present paper deals with studying the effect of electrical discharge machining (EDM) and shot blast peening parameters on work piece fatigue lives using copper and graphite electrodes. Response surface methodology (RSM) and the design of experiment (DOE) were used to plan and design the experimental work matrices for two EDM groups of experiments using kerosene dielectric alone, while the second was treated by the shot blast peening processes after EDM machining. To verify the experimental results, the analysis of variance (ANOVA) was used to predict the EDM models for high carbon high chromium AISI D2 die steel. The work piece fatigue lives in terms of safety factors after EDM models were developed by FEM using ANSY