After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings

Amino acids are the basic building block for peptides and proteins. They are raw materials for generating hormones, purines, pyrimidines and vitamins. Amino acids also provide the body with energy through their carbon structures. The study analyzed the amino acid in the kidneys of the albino mice embryo at 17 and 19 gestation days, using a high-performance liquid chromatography device (HPLC). Samples were obtained after removing them from the embryo and placing them in an ice bath to prevent cell lysis and acid loss. The study found 18 amino acids in the kidneys of the albino mice embryo. They are Asparagine (Asn), Glutamine (Glu), Serine (Ser), Glycine (Gly), Threonine (Thr), Histidine (His), Cysteine (Cys), Alanine (Ala), Proline

In light of the limited sources of funding suffered by the Iraqi economy, it highlights the importance of enhancing the efficiency of public expenditure, and if the measurement of the efficiency of public expenditure and identify benchmarks first step of promoting efficiency, the adoption of scientific methods of analysis imperative in promoting the efficiency. Under this framework, the focus was on the methodologies used to measure the efficiency of public spending and supply analysis with trying statement strengths and weaknesses, and make use of it in the measurement of the efficiency of public spending in the Iraqi economy. As well as devise measurable indicators take into account the specificity of the Iraqi economy and the

Image is an important digital information that used in many internet of things (IoT) applications such as transport, healthcare, agriculture, military, vehicles and wildlife. etc. Also, any image has very important characteristic such as large size, strong correlation and huge redundancy, therefore, encrypting it by using single key Advanced Encryption Standard (AES) through IoT communication technologies makes it vulnerable to many threats, thus, the pixels that have the same values will be encrypted to another pixels that have same values when they use the same key. The contribution of this work is to increase the security of transferred image. This paper proposed multiple key AES algorithm (MECCAES) to improve the security of the tran

Renewable energy technology is growing fast especially photovoltaic (PV) system to move the conventional electricity generation and distribution towards smart grid. However, similar to monthly electricity bill, the PV energy producers can only monitor their energy PV generation once a month. Any malfuntion in PV system components may reduce the performance of the system without notice. Thus, developing a real-time monitoring system of PV production is very crucial for early detection. In addition, electricity consumption is also important to be monitored more frequently to increase energy savings awareness among consumers. Hardware based Internet-of-Thing (IoT) monitoring and control system is widely used. However, the implementation of

Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

This work was conducted to study the extraction of eucalyptus oil from natural plants (Eucalyptus camadulensis leaves) by organic solvents. the effects of the main operating parameters were studied; type of solvent (n-hexane and ethanol), time to reach equilibrium, the temperature (45°C to 65°C) for n-hexane and (45°C to 75°C) for ethanol, solvent to solid ratio (5:1 to 8:1 (v/w)), agitation speed (0 to 900 rpm) and the particle size (0.5 to 2.5 cm) of fresh leaves to find the best processing conditions for the achieving maximum oil yield. The concentration of eucalyptus oil in solvent was measured by using UV-spectrophotometer. The results (for n-hexane) showed that the agitation speed of 900 rpm, temperature 65°C with solvent to soli

Chlorinated volatile organic compounds (CVOCs) are toxic chemical entities emitted invariably from stationary thermal operations when a trace of chlorine is present. Replacing the high-temperature destruction operations of these compounds with catalytic oxidation has led to the formulation of various potent metal oxides catalysts; among them are ceria-based materials. Guided by recent experimental measurements, this study theoretically investigates the initial steps operating in the interactions of ceria surface CeO2(111) with three CVOC model compounds, namely chloroethene (CE), chloroethane (CA) and chlorobenzene (CB). We find that, the CeO2(111) surface mediates fission of the carbon–chlorine bonds in the CE, CA and CB molecules via mo

Iron–phthalocyanine (FePc) organic photoconductive detector was fabricated using pulsed laser deposition (PLD) technique to work in ultraviolet (UV) and visible regions. The organic semiconductor material (iron phthalocyanine) was deposited on n-type silicon wafer (Si) substrates at different thicknesses (100, 200 and 300) nm. FePc organic photoconductive detector has been improved by two methods: the first is to manufacture the detector on PSi substrates, and the second is by coating the detector with polyamide–nylon polymer to enhance the photoconductivity of the FePc detector. The current–voltage (I–V) characteristics, responsivity, photocurrent gain, response time and the quantum efficiency of the fabricated photoconduc

A rapid and sensitive method for analysis of amino acid hydrolysates of nigella sativa L seed has been developed using O-phthaldialehyde(OPA ) as a pre-column derivatizing agent. OPA reagents in the presence of mercaptoethanol react rapidly with primary amino acids ( less than 60 sec.) to form isindole derivatives which easily separated with good selectivity on ODS column. Resolution of amino acid derivatives is carried out with a methanol gradient in 0.01 maqueous sodium acetate. pH 7.1 . The quantitation of amino acid derivatives is reproducible within an average relative deviation of + 1.4% the linearity for most amino acids were more than 0.9993 with detection limit of 0.2 ppm. 15 amino acid were detected in the analysis of