Liquefied petroleum gases (LPG) consist of hydrocarbons obtained by refining crude oil, either from propane or butane or a mixture of the two. There are often other components such as propylene, butylene or other hydrocarbons, but they are not the main component. The study aims to review previous studies dealing with designing an LPG system to deliver gas to residential campuses and buildings. LPG is extracted from natural gas NG by several processes, passing through fractionation towers and then pressuring into CNG storage tanks. Gas contains several problems, including gas leakage through the pipes and leads to fires or explosions in LPG storage and distribution tanks, so safety conditions were taken in the design and implementation. T

Healthcare professionals routinely use audio signals, generated by the human body, to help diagnose disease or assess its progression. With new technologies, it is now possible to collect human-generated sounds, such as coughing. Audio-based machine learning technologies can be adopted for automatic analysis of collected data. Valuable and rich information can be obtained from the cough signal and extracting effective characteristics from a finite duration time interval that changes as a function of time. This article presents a proposed approach to the detection and diagnosis of COVID-19 through the processing of cough collected from patients suffering from the most common symptoms of this pandemic. The proposed method is based on adopt

According to the topics of study, The intensity of the news coverage of the Abu Ghraib scandal and the US soldiers' torture of Iraqi prisoners have become apparent since the scandal was revealed on April 29, 2004 until May 30, 2004 and the period in which the coverage of this scandal had intensified not only in Al-Zaman, but in all newspapers, magazines and other media locally and internationally. And according to a research taken from Al-Zaman magazine that showed great interest in highlighting the event, interpreting it, following up its roots and results, and showing contradictory claims and slogans between the US and Britain, particularly in respecting human rights and the spread of justice, equality and well-being in Iraq specifical

This paper describes a new proposed structure of the Proportional Integral Derivative (PID) controller based on modified Elman neural network for the DC-DC buck converter system which is used in battery operation of the portable devices. The Dolphin Echolocation Optimization (DEO) algorithm is considered as a perfect on-line tuning technique therefore, it was used for tuning and obtaining the parameters of the modified Elman neural-PID controller to avoid the local minimum problem during learning the proposed controller. Simulation results show that the best weight parameters of the proposed controller, which are taken from the DEO, lead to find the best action and unsaturated state that will stabilize the Buck converter system performan

Information security in data storage and transmission is increasingly important. On the other hand, images are used in many procedures. Therefore, preventing unauthorized access to image data is crucial by encrypting images to protect sensitive data or privacy. The methods and algorithms for masking or encoding images vary from simple spatial-domain methods to frequency-domain methods, which are the most complex and reliable. In this paper, a new cryptographic system based on the random key generator hybridization methodology by taking advantage of the properties of Discrete Cosine Transform (DCT) to generate an indefinite set of random keys and taking advantage of the low-frequency region coefficients after the DCT stage to pass them to

Recently, wireless charging based RF harvesting has interfered our lives [1] significantly through the different applications including biomedical, military, IoT, RF energy harvesting, IT-care, and RFID technologies. Wirelessly powered low energy devices become significantly essential for a wide spectrum of sensing applications [1]. Such devices require for low energy resources from sunlight, mechanical vibration, thermal gradients, convection flows or other forms of harvestable energy [2]. One of the emerging power extraction resources based on passive devices is harvesting radio frequency (RF) signals powers [3]–[5]. Such applications need devices that can be organized in very large numbers, so, making separate node battery impractical.

Functionalized Multi-Walled Carbon Nanotubes (MWCNTs-OH) network with thickness 4μm was made by the vacuum filtration from suspension (FFS) method. The morphology, structure and optical properties of the MWCNTs film were characterized by SEM and UV-Vis. spectra techniques. The SEM images reflected highly ordered network in the form of ropes or bundles with close-packing which looks like spaghetti. The absorbance spectrum revealed that the network has a good absorbance in the UV-Vis. region. The gas sensor system was used to test the MWCNT-OH network to detect NH₃gas at room temperature. The resistance of the sensor was increased when exposed to the NH₃gas. The sensitivities of the network w

The objective of this study was tointroduce a recursive least squares (RLS) parameter estimatorenhanced by using a neural network (NN) to facilitate the computing of a bit error rate (BER) (error reduction) during channels estimation of a multiple input-multiple output orthogonal frequency division multiplexing (MIMO-OFDM) system over a Rayleigh multipath fading channel.Recursive least square is an efficient approach to neural network training:first, the neural network estimator learns to adapt to the channel variations then it estimates the channel frequency response. Simulation results show that the proposed method has better performance compared to the conventional methods least square (LS) and the original RLS and it is more robust a