With the continuous downscaling of semiconductor processes, the growing power density and thermal issues in multicore processors become more and more challenging, thus reliable dynamic thermal management (DTM) is required to prevent severe challenges in system performance. The accuracy of the thermal profile, delivered to the DTM manager, plays a critical role in the efficiency and reliability of DTM, different sources of noise and variations in deep submicron (DSM) technologies severely affecting the thermal data that can lead to significant degradation of DTM performance. In this article, we propose a novel fault-tolerance scheme exploiting approximate computing to mitigate the DSM effects on DTM efficiency. Approximate computing in hardw

In this study, the results of x-ray diffraction methods were used to determine the Crystallite size and Lattice strain of Cu2O nanoparticles then to compare the results obtained by using variance analysis method, Scherrer method and Williamson-Hall method. The results of these methods of the same powder which is cuprous oxide, using equations during the determination the crystallite size and lattice strain, It was found that the results obtained the values of the crystallite size (28.302nm) and the lattice strain (0.03541) of the variance analysis method respectively and for the Williamson-Hall method were the results of the crystallite size (21.678nm) and lattice strain (0.00317) respectively, and Scherrer method which gives the value of c

ABSTRACT

The research aims to know the reality of a two examined variables at the organization studied identifying the relationship between managerial processes reengineering and organizational citizenship behavior. The research applied on the Electronic Manufacturing Company encompassing a sample of managers and employees consisted of (100) individuals. A questionnaire is the main instrument for data gathering, which has been included (45) questions as well as personal interviews to support the questionnaire's questions and to achieve greater realism for collecting information.

Answers were analyzed to reach the final results through the use of a number of statistical methods via

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

Abstract  

Magnetic abrasive finishing (MAF) process is one of non-traditional or advanced finishing methods which is suitable for different materials and produces high quality level of surface finish where it uses magnetic force as a machining pressure. A set of experimental tests was planned according to Taguchi orthogonal array (OA) L27 (3⁶) with three levels and six input parameters. Experimental estimation and optimization of input parameters for MAF process for stainless steel type 316 plate work piece, six input parameters including amplitude of tooth pole, and number of cycle between teeth, current, cutting speed, working gap, and finishing time, were performed by design of experiment

This work presents a computer studying to simulate the charging process of a dust grain immersed in plasma with negative ions. The study based on the discrete charging model. The model was developed to take into account the effect of negative ions on charging process of dust grain.
The model was translated to a numerical calculation by using computer programs. The program of model has been written with FORTRAN programming language to calculate the charging process for a dust particle in plasma with negative ion, the time distribution of a dust charge, number charge equilibrium and charging time for different value of ηe (ratio of number density of electron to number density of positive ion).

At atmospheric pressure and at a frequency of 9.1 kHz, a constructed magnetically stabilized tornado gliding arc discharge (MSGAD) system was utilized in this study to generate a non-thermal plasma with an alternating voltage source from 2,4,6,8 to 10 kV. Argon gas was used to generate the arc plasma with an adjustable flow rate using a flow meter regulator to stabilize the gas flow rate to 2 L/min. A gliding plasma discharge is achieved by a magnetic field for the purpose of a planned investigation. The influence of the magnetically stabilized tornado gliding arc discharge parameters such as magnetic field and applied voltage on microscopic tornado plasma parameters was studied. The electron temperature1was measured using a Boltzmann plot

   This study aimed to evaluate the reservoir petrophysical properties (porosity, water saturation, and permeability) for optimal flow unit assessment within the Sadi Formation. Utilizing open hole logging data from five wells, the Sadi formation was divided into two rock units. The upper unit (A) is 45-50 meters thick, mainly consisting of limestone, mainly consisting of shaly limestone at the lower part. The lower unit (B) has a thickness of approximately 75-80 meters and is primarily composed of limestone, further subdivided into three subunits (B1, B2, B3). The average water resistivity is 0.04 ohm-m, and the average mud filtrate resistivity is 0.06 ohm-m. The Pickett plot was utilized to determine Archie parameters (tortuosit