In the current digitalized world, cloud computing becomes a feasible solution for the virtualization of cloud computing resources.  Though cloud computing has many advantages to outsourcing an organization’s information, but the strong security is the main aspect of cloud computing. Identity authentication theft becomes a vital part of the protection of cloud computing data. In this process, the intruders violate the security protocols and perform attacks on the organizations or user’s data. The situation of cloud data disclosure leads to the cloud user feeling insecure while using the cloud platform. The different traditional cryptographic techniques are not able to stop such kinds of attacks. BB84 protocol is the first quantum cry

      The production of fission products during reactor operation has a very important effect on  reactor reactivity .Results of neutron cross section evaluations are presented for the main product nuclides considered as being the most important  for reactor calculation and burn-up consideration . Data from the main international libraries considered as containing the most up-to-date nuclear data   and the latest experimental measurements are considered in the evaluation processes, we describe the evaluated cross sections of the fission product nuclides by making inter comparison of the data and point out the discrepancies among libraries.

ANN modeling is used here to predict missing monthly precipitation data in one station of the eight weather stations network in Sulaimani Governorate. Eight models were developed, one for each station as for prediction. The accuracy of prediction obtain is excellent with correlation coefficients between the predicted and the measured values of monthly precipitation ranged from (90% to 97.2%). The eight ANN models are found after many trials for each station and those with the highest correlation coefficient were selected. All the ANN models are found to have a hyperbolic tangent and identity activation functions for the hidden and output layers respectively, with learning rate of (0.4) and momentum term of (0.9), but with different data

In recent years, social media has been increasing widely and obviously as a media for users expressing their emotions and feelings through thousands of posts and comments related to tourism companies. As a consequence, it became difficult for tourists to read all the comments to determine whether these opinions are positive or negative to assess the success of a tourism company. In this paper, a modest model is proposed to assess e-tourism companies using Iraqi dialect reviews collected from Facebook. The reviews are analyzed using text mining techniques for sentiment classification. The generated sentiment words are classified into positive, negative and neutral comments by utilizing Rough Set Theory, Naïve Bayes and K-Nearest Neighbor

      Cloud computing has gained considerable attention in academia and industry in recent years. The cloud facilitates data sharing and enables cost efficiency, thus playing a vital role today as well as for the foreseeable future. In this paper, a brief discussion the application of multi-tenant and load-balancing technologies to cloud-based digital resource sharing suitable for academic and digital libraries is presented. As a new paradigm for digital resource sharing, a proposal of improving the current user service model with private cloud storage for other sectors, including the medical and financial fields is offered. This paper gives a summary of cloud computing and its possible applications, combined with digital data optim

Evaluation study was conducted for seismic interpretation using two-dimensional seismic data for Subba oil field, which is located in the southern Iraq. The Subba oil field was discovered in 1973 through the results of the seismic surveys and the digging of the first exploratory well SU-1 in 1975 to the south of the Subba oil field. The entire length of the field is 35 km and its width is about 10 km. The Subba oil field contains 15 wells most of them distributed in the central of the field.

     This study is dealing with the field data and how to process it for the purpose of interpretation; the processes included conversion of field data format, compensation of lost data and noise disposal, as well as the a

     Machine learning-based techniques are used widely for the classification of images into various categories. The advancement of Convolutional Neural Network (CNN) affects the field of computer vision on a large scale. It has been applied to classify and localize objects in images. Among the fields of applications of CNN, it has been applied to understand huge unstructured astronomical data being collected every second. Galaxies have diverse and complex shapes and their morphology carries fundamental information about the whole universe. Studying these galaxies has been a tremendous task for the researchers around the world. Researchers have already applied some basic CNN models to predict the morphological classes

      COVID-19 is a disease caused by a coronavirus spread globally, including in Iraq; infections have appeared on all Iraq lands in varying proportions. Iraq is among the higher infected world countries. Forty-six infections were simulated on 23 March 2020. Injuries on the eastern side of Baghdad city and to the right side of the Tigris River, which divides the city into two parts, are a natural barrier in quarantine and easily control the movement of people from both sides.

In this study, a model was considered a scientific and practical method by following the steps of identifying infected people using the best scientific approach for the spatial process to prevent the virus from spreading. Remote sensing techniques were

Accurate predictive tools for VLE calculation are always needed. A new method is introduced for VLE calculation which is very simple to apply with very good results compared with previously used methods. It does not need any physical property except each binary system need tow constants only. Also, this method can be applied to calculate VLE data for any binary system at any polarity or from any group family. But the system binary should not confirm an azeotrope. This new method is expanding in application to cover a range of temperature. This expansion does not need anything except the application of the new proposed form with the system of two constants. This method with its development is applied to 56 binary mixtures with 1120 equili

In this paper, we used the maximum likelihood estimation method to find the estimation values ​​for survival and hazard rate functions of the Exponential Rayleigh distribution based on a sample of the real data for lung cancer and stomach cancer obtained from the Iraqi Ministry of Health and Environment, Department of Medical City, Tumor Teaching Hospital, depending on patients' diagnosis records and number of days the patient remains in the hospital until his death.