This study investigates the influence of asymmetric involute teeth profiles for helical gears on the bending stress. Theoretically, bending stress has been estimated in spur involute gears which have symmetric teeth profile by based on the Lewis, 1892 equation. Later, this equation is developed by, Abdullah, 2012. to determine the effect of an asymmetric tooth profile for the spur gear on the bending stress. And then these equations are applied with stress concentration factor once for symmetric and once other for asymmetric teeth profile. In this paper, the bending stresses for various types of helical gear with various types of asymmetric teeth profile are calculated numerically for defined the stress concentration fac

     Magnesium oxide nanoparticles (MgO NPs) were synthesized by a green method using the peels of Persimmon extract as the reducing agent , magnesium nitrate, and NaOH. This method is eco-friendly and non-toxic. In this study, an ultrasound device was used to reduce the particle size, with the impact on the energy gap was set at the beginning at 5.39 eV and then turned to 4.10 eV. The morphological analysis using atomic force microscopy (AFM)  showed that the grain size for MgO NPs was 67.70 nm which became 42.33 nm after the use of the ultrasound. The shape of the particles was almost spherical and became cylindrical.  In addition the Field-Emission Scanning Electron Microscopy (FESEM) analysis sh

A morphotectonic analysis is conducted on Shatt Al-Arab drainage basin. This study aims to analysis of the river patterns of Shatt Al-Arab channel and their relationship with the development of subsurface geological structures and the neotectonic activity, as well as an attempt to determine the relative amount to this activity.
Transverse river profile analysis is derived quantifiable and comparable parameters such as neotectonic index (Eh*Ln), Eh, Ch, and Bs. These parameters are useful to detect the morphotectonic indicators of Shatt Al-Arab basin. The analysis showed the role of the subsurface structures that affecting the river cross sections shape, through channel incision, as in (Dair and NuhrUmr) cross sections, while in the ot

 Monthly variations in Physio-chemical parameters of Al-Garraf water in Waist province, one of the main tributaries of the Tigris River to investigate the water quality of the river from August 2014 to January 2015. The study location situated in the southeastern sector of Iraq and surrounded by wide and fertile agricultural lands. Three stations were selected for collecting  samples monthly, samples were taken each month. Station one is located at 500 m of  the AL - KUT Dam. The second is situated at distance of 15 Km away from the former (Kut- Muwafaqiya) and the latter station is located at 18 Km apart from the second one upon entering the river hand Muwafaqiya.  In the present study fourteen physical and chemical

Image compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye

In the latest years there has been a profound evolution in computer science and technology, which incorporated several fields. Under this evolution, Content Base Image Retrieval (CBIR) is among the image processing field. There are several image retrieval methods that can easily extract feature as a result of the image retrieval methods’ progresses. To the researchers, finding resourceful image retrieval devices has therefore become an extensive area of concern. Image retrieval technique refers to a system used to search and retrieve images from digital images’ huge database. In this paper, the author focuses on recommendation of a fresh method for retrieving image. For multi presentation of image in Convolutional Neural Network (CNN),

 Abstract

Basra province is known for its logistic location for trading activity and oil industry. By geological point of view, Basra areas are believed to consist mainly of alternation of (clay, silty clay, clayey silt, silt and sand) type of soil. Any development of industry in this area should be affected by the occurrence of the clay soil. That is why the investigation to the soil is more than necessary. In this case, a vast testing program was carried out by the author to evaluate the various formations constituting the of some Basra soils. An attempt to characterize and discuss the nature, minerals, engineering behavior and field properties of soil samples extracted from more than one thousand and one

This research discusses application Artificial Neural Network (ANN) and Geographical InformationSystem (GIS) models on water quality of Diyala River using Water Quality Index (WQI). Fourteen water parameterswere used for estimating WQI: pH, Temperature, Dissolved Oxygen, Orthophosphate, Nitrate, Calcium, Magnesium,Total Hardness, Sodium, Sulphate, Chloride, Total Dissolved Solids, Electrical Conductivity and Total Alkalinity.These parameters were provided from the Water Resources Ministryfrom seven stations along the river for the period2011 to 2016. The results of WQI analysis revealed that Diyala River is good to poor at the north of Diyala provincewhile it is poor to very polluted at the south of Baghdad City. The selected parameters wer

In the present study, an attempt has been to develop a new water quality index (WQI) method that depends on the Iraqi specifications for drinking water (IQS 417, 2009) to assess the validity of the Euphrates River for drinking by classifying the quality of the river water at different stations along its entire reach inside the Iraqi lands. The proposed classifications by this method are: Excellent, Good, Acceptable, Poor, and Very poor. Eight water quality parameters have been selected to represent the quality of the river water these are: Ion Hydrogen Concentration (pH), Calcium (Ca), Magnesium (Mg), Sodium (Na), Chloride (Cl), Sulphate (SO_4), Nitrate (NO_3), and Total Dissolved Solids (TDS). The variation of the water quality parameters