In this paper, the Monte-Carlo simulation method was used to compare the robust circular S estimator with the circular Least squares method in the case of no outlier data and in the case of the presence of an outlier in the data through two trends, the first is contaminant with high inflection points that represents contaminant in the circular independent variable, and the second the contaminant in the vertical variable that represents the circular dependent variable using three comparison criteria, the median standard error (Median SE), the median of the mean squares of error (Median MSE), and the median of the mean cosines of the circular residuals (Median A(k)). It was concluded that the method of least squares is better than the

The semiempirical (PM3) and DFT quantum mechanical methods were used to investigate the theoretical degradation of Indigo dye. The chemical reactivity of the Indigo dye was evaluated by comparing the potential energy stability of the mean bonds. Seven transition states were suggested and studied to estimate the actually starting step of the degradation reaction. The bond length and bond angle calculations indicate that the best active site in the Indigo dye molecule is at C10=C11.  The most possible transition states are examined for all suggested paths of Indigo dye degradation predicated on zero-point energy and imaginary frequency. The first starting step of the reaction mechanism is proposed. The change in enthalpy, Gibbs free energ

In this paper, a Modified Weighted Low Energy Adaptive Clustering Hierarchy (MW-LEACH) protocol is implemented to improve the Quality of Service (QoS) in Wireless Sensor Network (WSN) with mobile sink node. The Quality of Service is measured in terms of Throughput Ratio (TR), Packet Loss Ratio (PLR) and Energy Consumption (EC). The protocol is implemented based on Python simulation. Simulation Results showed that the proposed protocol provides better Quality of Service in comparison with Weighted Low Energy Cluster Hierarchy (W-LEACH) protocol by 63%.

Survival analysis is widely applied in data describing for the life time of item until the occurrence of an event of interest such as death or another event of understudy . The purpose of this paper is to use the dynamic approach in the deep learning neural network method, where in this method a dynamic neural network that suits the nature of discrete survival data and time varying effect. This neural network is based on the Levenberg-Marquardt (L-M) algorithm in training, and the method is called Proposed Dynamic Artificial Neural Network (PDANN). Then a comparison was made with another method that depends entirely on the Bayes methodology is called Maximum A Posterior (MAP) method. This method was carried out using numerical algorithms re

Energy crisis and the requirements of health and feel good, all this renewed attention to the importance of natural lighting in all kinds of factories.
    Research problem was how to achieve the plant's own natural outlets visual comfort and satisfaction of workers in Companies, the industries of cotton and general al-fedaa.

     The research compuns address the impact of daylight to provide visual comfort in the factory. Indeed, the light must be treated very carefully, and natural lighting should be thinking from the perspective of the occupants of the plant and not wishing to view from the outsid

Background: Non-alcoholic fatty liver disease (NAFLD) is the most common liver disorder globally. The prevalence is 25% worldwide, distributed widely in different populations and regions. The highest rates are reported for the Middle East (32%). Due to modern lifestyles and diet, there has been a persistent increase in the number of NAFLD patients. This increase occurred at the same time  where there were also increases in the number of people considered being obese all over the world. By analyzing fatty liver risk factors, studies found that body mass index, one of the most classical epidemiological indexes assessing obesity, was associated with the risk of fatty liver.

Objectives: To assess age, sex, and body

The numerical analysis was conducted to studying the influence of length to diameter ratio (L/D) on the behavior of the soil treated with sand columns treated with 8% sodium silicate for both floating and end bearing type by using finite element method (Plaxis 3D Foundation ) for isolated foundation of real dimensions. The analysis’s study indicate that in the floating type the best improvement ratio was achieved at (L/D=8) when using columns with a diameter of (0.5, 0.7), but when using columns with a diameter of 0.3 m, it was noticed that the bearing improvement ratio increases with increasing (L/d). While the results of the analysis for end bearing type show that the higher improvement ratio was achieved at (L/D=4) when using columns w

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

ءأرﻘﻟا ةﺎﯾﺣﺑ ًﺎﻘﯾﺛو ًﻻﺎﺻﺗا لﺻﺗﺗ. نﻣ ﮫﺑﺗﺎﮐﻟﻟ ﻲﺻﺧﺷﻟا ﻊﺑﺎطﻟا ﻲﻔﺣﺻﻟا دوﻣﻌﻟا لﻣﺣﯾ ا فﻟﺗﺧﻣﻟ ﮫﻟوﺎﻧﺗ لﻼﺧ وا ﮫﺋارا وا هرظﻧ ﺔﮭﺟو لﻣﺣﺗ ﻲﺗﻟا ﺔﯾﻣوﯾﻟا ثادﺣﻻاو ﺎﯾﺎﺿﻘﻟ ﺢﺿﻔﺑ موﻘﯾو ثادﺣﻻاو ﺔﯾﺑﻟﺳﻟا رھاوظﻟﻟ ىدﺻﺗﯾ وا، ءيرﺎﻘﻟا ﯽﻟا ﮫﺑرﺎﺟﺗ وا هرﺎﮐﻓا ءﺎطﺧﻻا دﺻرﯾ بﯾﻗرﺑ ﮫﺑﺷا وھو، ءيرﺟﻟا دﻘﻧﻟا نﻋ مﻧﯾ بوﻟﺳﺎﺑ ﺔﺋطﺎﺧﻟا تﺎﺳرﺎﻣﻣﻟا ﺎﮭﺣدﻣﯾو تﺎﯾﺑﺎﺟﯾﻻا ﯽﻟﻋ

Digital image is widely used in computer applications. This paper introduces a proposed method of image zooming based upon inverse slantlet transform and image scaling. Slantlet transform (SLT) is based on the principle of designing different filters for different scales.

      First we apply SLT on color image, the idea of transform color image into slant, where large coefficients are mainly the   signal and smaller one represent the noise. By suitably modifying these coefficients , using scaling up image by  box and Bartlett filters so that the image scales up to 2X2 and then inverse slantlet transform from modifying coefficients using to the reconstructed image .

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