A band rationing method is applied to calculate the salinity index (SI) and Normalized Multi-Band Drought Index (NMDI) as pre-processing to take Agriculture decision in these areas is presented. To separate the land from other features that exist in the scene, the classical classification method (Maximum likelihood classification) is used by classified the study area to multi classes (Healthy vegetation (HV), Grasslands (GL), Water (W), Urban (U), Bare Soil (BS)). A Landsat 8 satellite image of an area in the south of Iraq are used, where the land cover is classified according to indicator ranges for each (SI) and (NMDI).

The aim of this study is interpretation well logs to determine Petrophysical properties of tertiary reservoir in Khabaz oil field using IP software (V.3.5). The study consisted of seven wells which distributed in Khabaz oilfield. Tertiary reservoir composed from mainly several reservoir units. These units are : Jeribe, Unit (A), Unit (A'), Unit (B), Unit (BE), Unit (E),the Unit (B) considers best reservoir unit because it has good Petrophysical properties (low water saturation and high porous media ) with high existence of hydrocarbon in this unit. Several well logging tools such as Neutron, Density, and Sonic log were used to identify total porosity, secondary porosity, and effective porosity in tertiary reservoir. For

    Ten species of whiteflies (Hemiptera, Aleyrodidae) representing six genera were studied from a collection from different localities in the middle of Iraq. These species are Acaudaleyrodes rachipora (Singh, 1931); Bemisia afer  (Priesner and Hosny,1934); Bemisia tabaci (Gennadius, 1889); Dialeurodes citri (Ashmead,1885); Dialeurodes kirkaldy (Kotinsky, 1907); Neomaskellia andropogonis Corbett, 1926;  Siphoninus phillyreae (Haliday, 1835); Trialeurodes ricini (Misra, 1924); Trialeurodes vapovariorum (Westwood,1856) and Trialeurodes irakeensis (Al-Malo and Abdul-Rassoul, 2000). Notes are given on their localities, date of c

Background: The incidence of oral cancers is increasing all over the world. Early detection ofthis important public health matter makes them more amenable to treatment and allows the greatest chance of cure.The aim of this study was to investigate the awareness and knowledge on oral cancer among final -year dental students in Iraq. Materials and methods: Questionnaires were delivered to 160 final–year dental students in the College of Dentistry in Baghdad. The questionnaire focused on the awareness/knowledge of oral cancer, earlyand common clinical signs and symptoms andassociated risk factors. Results: It was found that 87% of students were aware of oral cancer. The followings were recognized as signs and symptoms of oral cancer: persis

Trials were carried out in the middle of Iraq ( 3 different sites ) during 2009 to detecation and determined the seasonal occurrence of Agriotes lineatus L. Three YATOR funnel traps were used in each of these sites which baited with the specific pheromone of A. lineatus from the first of March to the end of October in the College of Agriculture - Abu- Ghraib / Provenance of Baghdad and AL-Nile / Provenance of Babylon , while in AL-Radhwania was used through May- June. Pheromone dispenser were changed every 6 weeks in each of these traps . Males of A. lineatus were found in all of the three sites , and the total number capture were 208 , 897 and 57 male / 3 traps / season in College of Agriculture , AL-Nile and AL-Radhwania respectiv

Various theories have been proposed since in last century to predict the first sighting of a new crescent moon. None of them uses the concept of machine and deep learning to process, interpret and simulate patterns hidden in databases. Many of these theories use interpolation and extrapolation techniques to identify sighting regions through such data. In this study, a pattern recognizer artificial neural network was trained to distinguish between visibility regions. Essential parameters of crescent moon sighting were collected from moon sight datasets and used to build an intelligent system of pattern recognition to predict the crescent sight conditions. The proposed ANN learned the datasets with an accuracy of more than 72% in comp