Tin oxide was deposited by using vacuum thermal method on silicon wafer engraved by Computer Numerical Controlled (CNC) Machine. The inscription was engraved by diamond-made brine. Deep 0.05 mm in the form of concentric squares. Electrical results in the dark were shown high value of forward current and the high value of the detection factor from 6.42 before engraving to 10.41 after engraving. (I-V) characters in illumination with powers (50, 100, 150, 200, 250) mW/cm2 show Improved properties of the detector, Especially at power (150, 200, 250) mW/cm2. Response improved in rise time from 2.4 μs to 0.72 μs and time of inactivity improved 515.2 μs to 44.2 μs. Sensitivity angle increased at zone from 40o to 65o.

Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d

In this research, the electrical characteristics of glow discharge plasma were studied. Glow discharge plasma generated in a home-made DC magnetron sputtering system, and a DC-power supply of high voltage as input to the discharge electrodes were both utilized. The distance between two electrodes is 4cm. The gas used to produce plasma is argon gas which flows inside the chamber at a rate of 40 sccm. The influence of work function for different target materials (gold, copper, and silver), - 5cm in diameter and around 1mm thickness - different working pressures, and different applied voltages on electrical characteristics (discharge current, discharge potential, and Paschen’s curve) were studied. The results showed that the discharge cur

This work is concerned with a two stages four beds adsorption chiller utilizing activated carbon-methanol adsorption pair that operates on six separated processes. The four beds that act as thermal compressors are powered by a low grade thermal energy in the form of hot water at a temperature range of 65 to 83 °C.  As well as, the water pumps and control cycle consume insignificant electrical power. This adsorption chiller consists of three water cycles. The first water cycle is the driven hot water cycle. The second cycle is the cold water cycle to cool the carbon, which adsorbs the methanol. Finally, the chilled water cycle that is used to overcome the building load. The theoretical results showed that average cycle cooling power

Time series analysis is the statistical approach used to analyze a series of data. Time series is the most popular statistical method for forecasting, which is widely used in several statistical and economic applications. The wavelet transform is a powerful mathematical technique that converts an analyzed signal into a time-frequency representation. The wavelet transform method provides signal information in both the time domain and frequency domain. The aims of this study are to propose a wavelet function by derivation of a quotient from two different Fibonacci coefficient polynomials, as well as a comparison between ARIMA and wavelet-ARIMA. The time series data for daily wind speed is used for this study. From the obtained results, the

This review is concluded of 8-Hydroxyquinline (8HQ) compound and derivatives which has a very significant interests with a strong fluorescence , furthermore the relationship between divalent metal ions and characteristic of chelating . In the same way coordinated features have increase of its organic action and inorganic behavior by giving many samples of compounds which are a good chelating agents ligands with more capable of forming very stable complexes.Therefore, the role of (8HQ) is not limited on complexes only but its applications in different fields so this review will focus on demonstration preparation methods and properties of (8HQ) derivatives with their complexes and applications, hopefully that we will cover a part of scientifi

In this work, a new development of predictive voltage-tracking control algorithm for Proton Exchange Membrane Fuel Cell (PEMFCs) model, using a neural network technique based on-line auto-tuning intelligent algorithm was proposed. The aim of proposed robust feedback nonlinear neural predictive voltage controller is to find precisely and quickly the optimal hydrogen partial pressure action to control the stack terminal voltage of the (PEMFC) model for N-step ahead prediction. The Chaotic Particle Swarm Optimization (CPSO) implemented as a stable and robust on-line auto-tune algorithm to find the optimal weights for the proposed predictive neural network controller to improve system performance in terms of fast-tracking de

As the reservoir conditions are in continuous changing during its life, well production rateand its performance will change and it needs to re-model according to the current situationsand to keep the production rate as high as possible.Well productivity is affected by changing in reservoir pressure, water cut, tubing size andwellhead pressure. For electrical submersible pump (ESP), it will also affected by numberof stages and operating frequency.In general, the production rate increases when reservoir pressure increases and/or water cutdecreases. Also the flow rate increase when tubing size increases and/or wellhead pressuredecreases. For ESP well, production rate increases when number of stages is increasedand/or pump frequency is