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

Phenol oxidation by Fenton's reagent (H2O2 + Fe+2) in aqueous solution has been studied for the purpose of learning
more about the reactions involved and the extent of the oxidation process, under various operating conditions. An initial
phenol concentration of 100 mg/L was used as representative of a phenolic industrial wastewater. Working temperature
of 25C was tested, and initial pH was set at 5.6 . The H2O2 and the Fe+2 doses were varied in the range of
(H2O2/Fe+2/phenol = 3/0.25/1 to 5/0.5/1). Keeping the stirring speed of 200 rpm.
The results exhibit that the highest phenol conversion (100%) was obtained under (H2O/Fe+2/phenol ratio of 5/0.5/1)
at about 180 min. The study has indicated that Fenton's oxidation i

Physical adsorption by nitrogen gas was studied on seven commercial platinum reforming catalysts (RG-402, RG-412, RG-432, RG-451, RG 422,RG-482, PS-10), four prepared platinum catalysts (0.1%Pt/alumina, 0.2 %Pt/alumina, 0.45 %Pt/alumina and 0.55% Pt/alumina), and -alumina support. Physical adsorption was carried out by using Accelerated Surface Area and Porosimetry (ASAP 2400 device) at 77 K . The results indicate that the surface area in genaral decreases with increasing platinum percentage, high platinum loaded (0.45% and 0.55%) it was found that the percent increasing in surface area was lower than those obtained for low platinum loaded catalysts , and at very higher platinum loading 0.6 %Pt , some reduction in surface area was

Background: The present study aimed to determine the influence of the different types of mouth wash on discoloration of different orthodontic ceramic, sapphire brackets and adhesives. Materials and methods: The sample composed of 120 ceramic brackets and 120 sapphire brackets, the brackets were divided according to bond material into three groups of 40 brackets include unbounded brackets, chemically cured (no-mix) bonded brackets and Light cured bonded brackets all these groups were further subdivided according to mouth wash type into three groups with 10 brackets each which include; Listerine, cetrimide, chlorhexidine 0.2%, and one control group which immersed in artificial saliva; then Staining measurements were performed with UV-Visibl

The MTX was converted to MTX  nanoparticles  by the modified method based on changing the pH gradually . For the first time MTX NPs+Meropenem complex were prepared and evaluated as a potential tool to overcome antimicrobial resistance and to improve pharmacokinetics of the drug, the results showed that the antibacterial activity of complex (MTX NPs plus MEM) has increased (from 1( µg/ml) to >0.5( µg/ml) for p1 , from 2( µg/ml) to 1( µg/ml) for p10 and from 8( µg/ml) to 4( µg/ml) for p48).

in this work the polymides were prepared as rthemally stable polymers by diffrent ways