Reading is an interactive process that goes on between the reader and the text, resulting in comprehension. The text presents letters, words, sentences, and paragraphs that encode meaning. The reader uses knowledge, skills, and strategies to determine what that meaning is. Reading comprehension is much more than decoding; it results when the reader knows which skills and strategies are appropriate for the type oftext, and understands how to apply them to accomplish the reading purpose.Reading comprehension is important because without it reading is nothing more than tracking symbols on a page with your eyes and sounding them out leaving the reader with no information. Instead of promoting traditional approaches, reading should be taught in a more interactive and communicative manner. In this light, this study investigates the difficulties faced by engineering students in reading comprehension in a university setting where the medium of instruction and communication is not English, but where students are required to read textbooks in English. The participants are selected from College of Engineering/ University of Al-Mustansiriya to take the test. However, a standardized test is used to show the students‟ difficulties in reading comprehension. Two passages are used in the test, the first one is concerned with their specialization in engineering while the second is concerned with general topics. Data analysis is conducted through using one sample T. test and percentages statistical methods. Results of this study reveal that engineering students have great difficulties in reading comprehension since most of them have not succeeded in the test. Reasons behind such results have been illustrated and certain suggestions have been given to be useful for both teachers and students of scientific fields especially engineering.
Abstract
The method binery logistic regression and linear discrimint function of the most important statistical methods used in the classification and prediction when the data of the kind of binery (0,1) you can not use the normal regression therefore resort to binary logistic regression and linear discriminant function in the case of two group in the case of a Multicollinearity problem between the data (the data containing high correlation) It became not possible to use binary logistic regression and linear discriminant function, to solve this problem, we resort to Partial least square regression.
In this, search th
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In this research , Aprocess ( LICVD) was used for producing silicon nitride powders with chemical compositon Si3N4 ,by using TEA-Co2 Laser to induc reaction in the gas phase, NH3 was used as on additive to SiH4. Reactant gases that were vibrationaly heated by absorbing energy emitted from TEA-Co2 Laser decomposes throug coillsion assisted multiple photon dissociation causing Si3N4 powders. By the dependence of the LICVD process on varios parameters such as Laser intensity , total gas pressure, partial pressures of SiH4 and NH3 were investigated. Dissociation rate as a function of Laser intensity and pressure was investigated. The powders obtained exhibit various colors from brown which is rich in Si to white.This
... Show MoreA simple, precise and accurate spectrophotometric method has been developed for simultaneous estimation of sulfanilamide and furosemide in their mixture by using first and second order derivative method in the ultraviolet region. The method depends on first and second derivative spectrophotometry, with zero-crossing and peak to base line and peak area measurements. The first derivative amplitudes at 214, 238 and 266 nm were selected for the assay of sulfanilamide and 240, 260, 284, 314 and 352 nm for furosemide. Peak area at 201222, 222-251 and 251-281 nm selected for estimation of sulfanilamide and at 229-249, 249270, 270-294, 294-333 and 333-382 nm for furosemide. The second derivative amplitudes at 220, 252 and 274 nm for sulfanilamid
... Show MoreInformation about soil consolidation is essential in geotechnical design. Because of the time and expense involved in performing consolidation tests, equations are required to estimate compression index from soil index properties. Although many empirical equations concerning soil properties have been proposed, such equations may not be appropriate for local situations. The aim of this study is to investigate the consolidation and physical properties of the cohesive soil. Artificial Neural Network (ANN) has been adapted in this investigation to predict the compression index and compression ratio using basic index properties. One hundred and ninety five consolidation results for soils tested at different construction sites
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The present study aimed to try to find natural substances stimulate the production of bacteriocin, as well as "for detection of bacteriocin producing isolates. Two hundred and eighty ( 280) bacterial isolates, gram negative only, were collected from 760 different pathogenic samples, consist: (Urinary tract infection, septicemia, Vaginal inflammation and diarrhea). The isolated bacteria are: Escherichia coli, Klebsiella pneumonia Pseudomonas aeruginosa,, Salmonella typhi, Enterobacter cloacae, Acinetobacter baumannii, Serratia liquefaciens, Citrobacter freundii, Proteus mirabilis and Serrattia odorifera. Cup assay method was used to detect bacteriocin production. Loc
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