This paper aims to study the chemical degradation of Brilliant Green in water via photo-Fenton (H2O2/Fe2+/UV) and Fenton (H2O2/Fe2+) reaction. Fe- B nano particles are applied as incrustation in the inner wall surface of reactor. The data form X- Ray diffraction (XRD) analysis that Fe- B nanocomposite catalyst consist mainly of SiO2 (quartz) and Fe2O3 (hematite) crystallites. B.G dye degradation is estimated to discover the catalytic action of Fe- B synthesized surface in the presence of UVC light and hydrogen peroxide. B.G dye solution with 10 ppm primary concentration is reduced by 99.9% under the later parameter 2ml H2O2, pH= 7, temperature =25°C within 10 min. It is clear that pH of the solution affects the photo- catalytic degradation

The aims of the research is to know the role of Organisational learning in building talent management strategies in the Ministry of Science and Technology , where we see the challenges facing organizations today dictate now and in the future activation of scientific expertise to meet these challenges and the dissemination of these concepts within the priorities and data organizational culture of these organizations despite having a lot of the importance of organizational knowledge and learning applications .Despite learning and adopting some of the organizations have to enhance their competitiveness, we find a lot of organizations, including (The ministry researched) still do not realize the importance of the role of organization

Research on the automated extraction of essential data from an electrocardiography (ECG) recording has been a significant topic for a long time. The main focus of digital processing processes is to measure fiducial points that determine the beginning and end of the P, QRS, and T waves based on their waveform properties. The presence of unavoidable noise during ECG data collection and inherent physiological differences among individuals make it challenging to accurately identify these reference points, resulting in suboptimal performance. This is done through several primary stages that rely on the idea of preliminary processing of the ECG electrical signal through a set of steps (preparing raw data and converting them into files tha

The research deals with Environmental Management and how to develop its programs with the use of Knowledge Management, the environmental programs that integrate with processes can add strategic value to business through improving rates of resource utilization , efficiencies , reduce waste, use risk management, cut costs, avoid fines and reduce insurance. All these activities and processes can improve it through knowledge management, the optimal usage for all organizations information , employ it in high value and share it among all organizations members who involves in modify its strategy . Choosing suitable environmental management information system, develop it and modify it with organization processes, can greatly serve the en

         The issue of penalized regression model has received considerable critical attention to variable selection. It plays an essential role in dealing with high dimensional data. Arctangent denoted by the Atan penalty has been used in both estimation and variable selection as an efficient method recently. However, the Atan penalty is very sensitive to outliers in response to variables or heavy-tailed error distribution. While the least absolute deviation is a good method to get robustness in regression estimation. The specific objective of this research is to propose a robust Atan estimator from combining these two ideas at once. Simulation experiments and real data applications show that the p

         The issue of penalized regression model has received considerable critical attention to variable selection. It plays an essential role in dealing with high dimensional data. Arctangent denoted by the Atan penalty has been used in both estimation and variable selection as an efficient method recently. However, the Atan penalty is very sensitive to outliers in response to variables or heavy-tailed error distribution. While the least absolute deviation is a good method to get robustness in regression estimation. The specific objective of this research is to propose a robust Atan estimator from combining these two ideas at once. Simulation experiments and real data applications show that the proposed LAD-Atan estimator

In this study, we made a comparison between LASSO & SCAD methods, which are two special methods for dealing with models in partial quantile regression. (Nadaraya & Watson Kernel) was used to estimate the non-parametric part ;in addition, the rule of thumb method was used to estimate the smoothing bandwidth (h). Penalty methods proved to be efficient in estimating the regression coefficients, but the SCAD method according to the mean squared error criterion (MSE) was the best after estimating the missing data using the mean imputation method

Permeability data has major importance work that should be handled in all reservoir simulation studies. The importance of permeability data increases in mature oil and gas fields due to its sensitivity for the requirements of some specific improved recoveries. However, the industry has a huge source of data of air permeability measurements against little number of liquid permeability values. This is due to the relatively high cost of special core analysis.
The current study suggests a correlation to convert air permeability data that are conventionally measured during laboratory core analysis into liquid permeability. This correlation introduces a feasible estimation in cases of data loose and poorly consolidated formations, or in cas