Metasurface polarizers are essential optical components in modern integrated optics and play a vital role in many optical applications including Quantum Key Distribution systems in quantum cryptography. However, inverse design of metasurface polarizers with high efficiency depends on the proper prediction of structural dimensions based on required optical response. Deep learning neural networks can efficiently help in the inverse design process, minimizing both time and simulation resources requirements, while better results can be achieved compared to traditional optimization methods. Hereby, utilizing the COMSOL Multiphysics Surrogate model and deep neural networks to design a metasurface grating structure with high extinction ration of »60000 at visible spectral wavelength of 632 nm, could be achieved.
Using the Neural network as a type of associative memory will be introduced in this paper through the problem of mobile position estimation where mobile estimate its location depending on the signal strength reach to it from several around base stations where the neural network can be implemented inside the mobile. Traditional methods of time of arrival (TOA) and received signal strength (RSS) are used and compared with two analytical methods, optimal positioning method and average positioning method. The data that are used for training are ideal since they can be obtained based on geometry of CDMA cell topology. The test of the two methods TOA and RSS take many cases through a nonlinear path that MS can move through that region. The result
... Show MoreThe method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par
... Show MoreThis research is a continued efforts for a project on the fire tube boiler control for Al Rasheed edible oil factory. The aim is to enhance the control system with new integral control one. A functional blocks diagram (FBD) was built and simulated. With Schneider smart relays, FBD differs than ladder logic programming in which the PID option is active. An extensive work was done to understand the operation sequence, emergency shutdown, and faults causing the trips. A control program was designed to control logical sequence of operation. Furthermore temperature is controlled via cascade control with fuel and air controllers. The temperature controller output is send as remote set point to the fuel controller in a serial cascade manner. The f
... Show MoreThe consumption of dried bananas has increased because they contain essential nutrients. In order to preserve bananas for a longer period, a drying process is carried out, which makes them a light snack that does not spoil quickly. On the other hand, machine learning algorithms can be used to predict the sweetness of dried bananas. The article aimed to study the effect of different drying times (6, 8, and 10 hours) using an air dryer on some physical and chemical characteristics of bananas, including CIE-L*a*b, water content, carbohydrates, and sweetness. Also predicting the sweetness of dried bananas based on the CIE-L*a*b ratios using machine learn- ing algorithms RF, SVM, LDA, KNN, and CART. The results showed that increasing the drying
... Show MoreCorrosion Resistance Enhancement for low carbon steel is very important to extend its life service, the coating process is one of the methods which can using to achieve this, and it's the most important in surface treatments to improve the properties of metals and alloys surfaces such as corrosion resistance. In this work, low carbon steel was nitrided and coated with nano zinc using gas phase coating technical, to enhance the resistance of corrosion. The process included adding two layers. The first, a nitride layer, was added by precipitating nitrogen (N) gas, and the second, a zinc (Zn) layer, was added by precipitating Zn. The process of precipitating was carried out at different periods (5, 10, and 15 minutes). Scan electron mi
... Show MoreThis paper examined accounting information systems (AIS) as a mediator between small and medium-sized enterprises (SMEs) strategies, including (finance source, administrative innovation, organizational culture, developing capabilities levels of SMEs, information source, development of business managers, and technological innovation) and organizational performance. In this quantitative study, 450 self-administered questionnaires were distributed to the managers and owners of SMEs using purposive sampling. Data were analyzed using the structural equation modeling (SEM) method via SmartPLS3 Software. The study offers empirical findings on the importance of AIS as a mediator, considers various factors, a
Hydrochloric acid (HCl) is a substance that is frequently utilized in industrial operations for important tasks such as chemical cleaning and pickling metallic surfaces.Therefore, the corrosion inhibition ability of three newly synthesized quinazoline derivatives namely, 3-allyl-2-(propylthio) quinazolin-4(3H)-one) (APQ), (3-allyl-2-(allylthio) quinazolin-4(3H)-one) (AAQ), (3-allyl- 2-( Prop -2-yn -1-ylthio) Quinazolin - 4 (3H) - one) (AYQ) were theoretically determined and these compounds were characterized using Fourier Transform Infra-Red (FTIR) and 1H and 13C Nuclear Magnetic Resonance (NMR) spectroscopic. A series of quantum chemical properties of these derivatives: EHOMO, ELUMO, energy gap (ΔE),dipole moment (μ), hardness (η), soft
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