In this research study the synodic month for the moon and their
relationship with the mean anomaly for the moon orbit and date A.D
and for long periods of time (100 years), we was design a computer
program that calculates the period of synodic months, and the
coordinates of the moon at the moment of the new moon with high
accuracy. During the 100 year, there are 1236 period of synodic
months.
We found that the when New Moon occurs near perigee (mean
anomaly = 0°), the length of the synodic month at a minimum.
Similarly, when New Moon occurs near apogee (mean anomaly =
180°), the length of the synodic month reaches a maximum. The
shortest synodic month on 2053 /1/ 16 and lasted (29.27436) days.
The lo

In this research study the synodic month for the moon and theirrelationship with the mean anomaly for the moon orbit and date A.Dand for long periods of time (100 years), we was design a computerprogram that calculates the period of synodic months, and thecoordinates of the moon at the moment of the new moon with highaccuracy. During the 100 year, there are 1236 period of synodicmonths.We found that the when New Moon occurs near perigee (meananomaly = 0°), the length of the synodic month at a minimum.Similarly, when New Moon occurs near apogee (mean anomaly =180°), the length of the synodic month reaches a maximum. Theshortest synodic month on 2053 /1/ 16 and lasted (29.27436) days.The longest synodic month began on 2008 /11/ 27 a

The business process re-engineering is one of the popular concepts at this time because its provide a radical solution for the problems that companies faces. This method appeared because the changes of competition and costumers 'desires at the two last decades. The markets become wider because of the globalization so the companies must change its way to stay a life.

        The research aim is to concentrate on the  BPR  because it's a  philosophy aims to re-organize the company's business process to achieve the competitive advantage, the research also aims to a plicate  the BPR using cost management technique  in the State Company of Vegetable Oils Industry.

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A simple physical technique was used in this study to create stable and cost-effective copper oxide (CuO) nanoparticles from pure copper metal using the pulsed laser ablation technique. The synthesis of crystalline CuO nanoparticles was confirmed by various analytical techniques such as particle concentration measurement using atomic absorption spectrometry (AAS), field emission scanning electron microscopy (FE-SEM), the energy dispersive X-ray (EDX), and X-ray diffraction (XRD) to determine the crystal size and identify of the crystal structure of the prepared particles. The main characteristic diffraction peaks of the three samples were consistent. The corresponding 2θ is also consistent, and the cytotoxicity of the nanoparticles was

In this paper, some commonly used hierarchical cluster techniques have been compared. A comparison was made between the agglomerative hierarchical clustering technique and the k-means technique, which includes the k-mean technique, the variant K-means technique, and the bisecting K-means, although the hierarchical cluster technique is considered to be one of the best clustering methods. It has a limited usage due to the time complexity. The results, which are calculated based on the analysis of the characteristics of the cluster algorithms and the nature of the data, showed that the bisecting K-means technique is the best compared to the rest of the other methods used.

In light of today's business world, who faces challenges and intense competition as a result of the rapid evolution of technical and informational, organizations had to respond to variables through the adoption of modern management techniques that reduce the effects of risks and activating the role of the internal control system in order to contribute to the early detection of risks and reduce the negative results expected .The research is to address the problem faced by organizations which still follow the traditional methods in the control activities, and the lack of knowledge of the management and their staff of the importance of the existence of risk management and internal control system takes into account these risks, and the limit

Abstract

            Sovereign wealth funds are an important tool for achieving economic stability and avoiding the local economy from external shocks, including the shocks of international oil prices. The spread of these funds is the result of large current account surpluses in many Asian and oil-exporting economies. These surpluses are due to higher commodity prices Has led to a rapid accumulation of foreign assets in central banks. Many countries with rent economies face the problem of their dependence on non-renewable natural resources, especially the oil countries, including Iraq. Oil revenues are more than 97% of oil exports, so they suffer from structural imbal

This study focuses on the biodegradation of oxymatrine insecticide by some soil fungi isolated from four agriculture stations. The results showed that the highest degradation rate 94.66% was recorded by Ulocladium sp. at 10 days and A. niger recorded the lowest degradation rate 45.86%, while at 20 days Ulocladium sp. also showed the highest degradation rate 94.98% and the lowest degradation rate reached to 82.49% with A.niger. The mix (Exerohilum sp.+Ulocladium sp.) recorded the highest degradation rate of oxymatrine insecticide 90.22%, 88.51%, 85.34%  at 4, 8 and 12 ppm.The use of mixed isolates enhanced the biodegradation process. There is no study of oxymatrine biodegradation

Precise forecasting of pore pressures is crucial for efficiently planning and drilling oil and gas wells. It reduces expenses and saves time while preventing drilling complications. Since direct measurement of pore pressure in wellbores is costly and time-intensive, the ability to estimate it using empirical or machine learning models is beneficial. The present study aims to predict pore pressure using artificial neural network. The building and testing of artificial neural network are based on the data from five oil fields and several formations. The artificial neural network model is built using a measured dataset consisting of 77 data points of Pore pressure obtained from the modular formation dynamics tester. The input variables