Many of the signs that the global energy system indicate the start of a period of transition from total dependence on fossil energy sources, especially oil, into a new era in which alternative energy sources play an important role in meeting the growing needs of energy demand, so sought many of the developed countries through research the studies carried out to try to bring renewable energy sources and non-renewable (shale oil, oil sands, solar energy, wind energy .... etc) replace traditional fossil energy sources (oil, gas, coal) and despite the recent availability dramatically and spread throughout the the world, but they are going to dry up in the foreseeable future. So many countries, especially the developed sought to find

Big data analysis is essential for modern applications in areas such as healthcare, assistive technology, intelligent transportation, environment and climate monitoring. Traditional algorithms in data mining and machine learning do not scale well with data size. Mining and learning from big data need time and memory efficient techniques, albeit the cost of possible loss in accuracy. We have developed a data aggregation structure to summarize data with large number of instances and data generated from multiple data sources. Data are aggregated at multiple resolutions and resolution provides a trade-off between efficiency and accuracy. The structure is built once, updated incrementally, and serves as a common data input for multiple mining an

Big data of different types, such as texts and images, are rapidly generated from the internet and other applications. Dealing with this data using traditional methods is not practical since it is available in various sizes, types, and processing speed requirements. Therefore, data analytics has become an important tool because only meaningful information is analyzed and extracted, which makes it essential for big data applications to analyze and extract useful information. This paper presents several innovative methods that use data analytics techniques to improve the analysis process and data management. Furthermore, this paper discusses how the revolution of data analytics based on artificial intelligence algorithms might provide

      Three monogeneans: Dactylogyrus folkmanovae from gills of Chondrostoma regium, D. reinii from gills of Mesopotamichthys sharpeyi and D. robustus from gills of Leuciscus vorax were collected from Diyala River in Diyala Province. The description, measurements and illustrations of these parasites were given.

Background: Generally, genetic disorders are a leading cause of spontaneous abortion, neonatal death, increased morbidity and mortality in children and adults as well. They a significant health care and psychosocial burden for the patient, the family, the healthcare system and the community as a whole. Chromosomal abnormalities occur much more frequently than is generally appreciated. It is estimated that approximately 1 of 200 newborn infants had some form of chromosomal abnormality. The figure is much higher in fetuses that do not survive to term. It is estimated that in 50% of first trimester abortions, the fetus has a chromosomal abnormality. Aim of the study: This study aims to shed some light on the results of chromosomal studies per

The research discusses the need to find the innovative structures and methodologies for developing Human Capital (HC) in Iraqi Universities. One of the most important of these structures is Communities of Practice (CoPs) which contributes to develop HC by using learning, teaching and training through the conversion speed of knowledge and creativity into practice. This research has been used the comparative approach through employing the methodology of Data Envelopment Analysis (DEA) by using (Excel 2010 - Solver) as a field evidence to prove the role of CoPs in developing HC. In light of the given information, a researcher adopted on an archived preliminary data about (23) colleges at Mosul University as a deliberate sample for t

Today, problems of spatial data integration have been further complicated by the rapid development in communication technologies and the increasing amount of available data sources on the World Wide Web. Thus, web-based geospatial data sources can be managed by different communities and the data themselves can vary in respect to quality, coverage, and purpose. Integrating such multiple geospatial datasets remains a challenge for geospatial data consumers. This paper concentrates on the integration of geometric and classification schemes for official data, such as Ordnance Survey (OS) national mapping data, with volunteered geographic information (VGI) data, such as the data derived from the OpenStreetMap (OSM) project. Useful descriptions o

In this research the specific activity of natural radionuclides 226Ra, 232Th and 40K were determined by sodium iodide enhanced by thallium NaI(TI) detector and assessed the annual effective dose in Dielac 1 and 2 and Nactalia 1 and 2 for children of less than 1 year which are available in Baghdad markets. The specific activity of 40K has the greater value in all the types which is in the range of allowed levels globally that suggested by UNSCEAR. The mean value of annual effective doses were 2.92, 4.005 and 1.6325 mSv/y for 226Ra, 232Th and 40K respectively.

     The objective of the study is to demonstrate the predictive ability is better between the logistic regression model and Linear Discriminant function using the original data first and then the Home vehicles to reduce the dimensions of the variables for data and socio-economic survey of the family to the province of Baghdad in 2012 and included a sample of 615 observation with 13 variable, 12 of them is an explanatory variable and the depended variable is number of workers and the unemployed.

     Was conducted to compare the two methods above and it became clear by comparing the  logistic regression model best of a Linear Discriminant  function written