The research aims to build a list of digital citizenship axes and standards and indicators emanating from them, which should be included in the content of the computer textbook scheduled for second grade intermediate students in Iraq, and the analysis of the above mentioned book according to the same list using the descriptive analytical method ((method of content analysis)). The research community and its sample consisted of the content of the computer textbook scheduled for the second year intermediate students for the academic year 2018-2019, and the research tool was built in its initial form after reference to a set of specialized literature and previous studies that dealt with topics related to digital citizenship, and the authenticit

irrigation use at many stations along the Euphrates River inside the Iraqi lands and to try to correlate the results with the satellite image analyses for the purpose of making a colored model for the Euphrates that can be used to predict the quality classifications of the river for irrigation use at any point along the river. The Bhargava method was used to calculate the water quality index for irrigation use at sixteen stations along the river from its entrance to the Iraqi land at Al-Qaim in Anbar governorate to its union with the Tigris River at Qurna in Basrah governorate. Coordinates of the sixteen stations of the Euphrates River were projected at the mosaic of Iraq satellite image which was taken from LANDSAT satellite for bands 1, 2

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This  article  co;nsiders a shrunken  estimator  Â·Of  Al-Hermyari·   and

AI Gobuii (.1) to estimate  the mean (8) of a normal clistributicm N (8 cr4)  with  known variance  (cr+),  when  <:I    guess value (So) av11il ble about the mean (B) as· an initial estrmate. This estimator is shown to be

more efficient tl1an the class-ical estimators  especially when 8 is close to 8•. General expressions .for bias and MSE -of considered  estitnator are gi 'en, witeh  some examples.  Nut.nerical cresdlts, comparisons  and

conclusions ate reported.

Surfaces quality is one of the most specified customer requirements for machine parts. The major indication of surfaces quality on machined parts is surface roughness. The research aim is to study the cutting conditions and their effects on the surface roughness. This paper utilizes regression models to predict surface roughness over the machining time for variety of cutting conditions in turning. In the experimental part for turning, different types of materials (Aluminum alloy, Copper alloy, and Gray cast iron) were considered with different cutting speed ( ) and feed rate ( ). A mathematical Model depending on statistical-mathematical method between surface roughness (Rz ) and cutting condition ( , ) were derived, for the three materials