In cognitive radio system, the spectrum sensing has a major challenge in needing a sensing method, which has a high detection capability with reduced complexity. In this paper, a low-cost hybrid spectrum sensing method with an optimized detection performance based on energy and cyclostationary detectors is proposed. The method is designed such that at high signal-to-noise ratio SNR values, energy detector is used alone to perform the detection. At low SNR values, cyclostationary detector with reduced complexity may be employed to support the accurate detection. The complexity reduction is done in two ways: through reducing the number of sensing samples used in the autocorrelation process in the time domain and through using the Slid

The aim of this paper is to present method for solving ordinary differential equations of eighth order with two point boundary conditions. We propose two-point osculatory interpolation to construct polynomial solution.

Global Navigation Satellite System (GNSS) is considered to be one of the most crucial tools for different applications, i.e. transportation, geographic information systems, mobile satellite communications, and others. Without a doubt, the GNSS has been widely employed for different scientific applications, such as land surveying, mapping, and precise monitoring for huge structures, etc. Thus, an intense competitive has appeared between companies which produce geodetic GNSS hardware devices to meet all the requirements of GNSS communities. This study aims to assess the performance of different GNSS receivers to provide reliable positions. In this study, three different receivers, which are produced by different manufactur

Oxidation of sulfur compounds in fuel followed by an adsorption process were studied using two modes of operation, batch mode and continuous mode (fixed bed). In batch experiment oxidation process of kerosene with sulfur content 2360 ppm was achieved to study the effect of amount of hydrogen peroxide(2.5, 4, 6 and 10) ml at different temperature(40, 60 and 70)°C. Also the effect of amount acetic acid was studied  at the optimal conditions of the oxidation step(4ml H₂O₂ and 60 °C).Besides, the role of acetic acid different temperatures(40, 60, 70) °C and 4ml H₂O₂, effect of reaction time(5, 30, 60, 120, 300) minutes at temperatures(40,60) °C, 4ml H₂O₂ and 1 mlHAC)&

Simulation of direct current (DC) discharge plasma using
COMSOL Multiphysics software were used to study the uniformity
of deposition on anode from DC discharge sputtering using ring and
disc cathodes, then applied it experimentally to make comparison
between film thickness distribution with simulation results. Both
simulation and experimental results shows that the deposition using
copper ring cathode is more uniformity than disc cathode

Electrophoretic Deposition (EPD) process offers various advantages like the fabrication of the ceramic coatings and bodies with dense packing, good sinterability and homogenous microstructure. The variables namely (applied potential, deposition time and sintering temperature) affected the development of hydroxyapatite (HAP) coatings. The coating weight and thickness were found to increase with the increase in applied potential or coating time. Sintering temperature was found to affect in change phases of the metal, furthermore the firing shrinkage of the HAP coating on a constraining metal substrate leads to serve cracking. XRD Characterization indicates the formation of a contamination free phase pure, and the optical micrographs show th

This research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.