In the last years, new non-invasively laser methods were used to detect breast tumors for pre- and postmenopausal females. The methods based on using laser radiation are safer than the other daily used methods for breast tumor detection like X-ray mammography, CT-scanner, and nuclear medicine.  

      One of these new methods is called FDPM (Frequency Domain Photon Migration). It is based on the modulation of laser beam by variable frequency sinusoidal waves. The modulated laser radiations illuminate the breast tissue and received from opposite side.

      In this paper the amplitude and the phase shift of the received signal were calculated according to the orig

Recently The problem of desertification and vegetation cover degradation become an environmental global challenge. This problem could be summarized as as the land cover changes. In this paper, the area of Al- Muthana in the south of Iraq will be consider as one of Semi-arid lands. For this purpose, the Ladsat-8 images can be used with 15 m in spatial resolution. In order to over Achieve the work, many important ground truth data must be collected such as, rain precipitation, temperature distribution over the seasons, the DEM of the region, and the soil texture characteristics. The extracted data from this project are tables, 2-D figures, and GIS maps represent the distributions of vegetation areas, evaporation / precipitation, river levels

Machine Learning (ML) algorithms are increasingly being utilized in the medical field to manage and diagnose diseases, leading to improved patient treatment and disease management. Several recent studies have found that Covid-19 patients have a higher incidence of blood clots, and understanding the pathological pathways that lead to blood clot formation (thrombogenesis) is critical. Current methods of reporting thrombogenesis-related fluid dynamic metrics for patient-specific anatomies are based on computational fluid dynamics (CFD) analysis, which can take weeks to months for a single patient. In this paper, we propose a ML-based method for rapid thrombogenesis prediction in the carotid artery of Covid-19 patients. Our proposed system aims

       Vegetation monitoring is considered an important application in remote sensing task due to variation of vegetation types and their distribution. The vegetation concentration around the Earth is increase in 5% in 2000 according to NASA monitoring. This increase is due to the Indian vegetable programs. In this research, the vegetation monitoring in Baghdad city was done using Normalized Difference Vegetation Index (NDVI) for temporal Landsat satellite images (Landsat 5 TM& Landsat 8 OIL). These images had been used and utilize in different times during the period from 2000, 2010, 2015 & 2017. The outcomes of the study demonstrate that a change in the vegetation Cover (VC) in Baghdad city. (NDVI) generally shows a

The need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2, 0, 0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlat

The need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2,0,0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlation coefficien

Abstract

     This research deals with Building A probabilistic Linear programming model  representing, the operation of production in the Middle Refinery Company (Dura, Semawa, Najaif) Considering the demand of each product (Gasoline, Kerosene,Gas Oil, Fuel Oil ).are random variables ,follows certain probability distribution, which are testing by using Statistical programme (Easy fit), thes distribution are found to be Cauchy distribution ,Erlang distribution ,Pareto distribution ,Normal distribution ,and General Extreme value distribution .              &

The reserve estimation process is continuous during the life of the field due to risk and inaccuracy that are considered an endemic problem thereby must be studied. Furthermore, the truth and properly defined hydrocarbon content can be identified just only at the field depletion. As a result, reserve estimation challenge is a function of time and available data. Reserve estimation can be divided into five types: analogy, volumetric, decline curve analysis, material balance and reservoir simulation, each of them differs from another to the kind of data required. The choice of the suitable and appropriate method relies on reservoir maturity, heterogeneity in the reservoir and data acquisition required. In this research, three types of rese