Shade in house gardens is one of the problems that hinder the growth of lawn and its distribution in the soil, where the types of lawns differ in their durability and adaptation to shade. The research aims to know the resistance of some species of lawn plants to shade and to know the appropriate fertilization procedures that can be followed to reduce the negative effects. The study was conducted in the Amiriya district of Baghdad in a house garden. Three varieties of lawn plants Bermuda, Gazon, and Trifoglio were planted. Five fertilization treatments (contained N and P elements) and the control were used. The sunlight density with the temperature of the study field locations were estimated using the AMT-300 and the vegetation coverage perc

Background: The incorporation of rubber has not been entirely successful because it can have detrimental effects on the transverse Strength and hence the rigidity of the denture base. Materials and methods: Zirconium oxide nanoparticales were coated with a layer of trimethoxysilylpropylmethacrylate (TMSPM) before sonication in monomer (MMA) with the percentages 3% by weight then mixed with powder using conventional procedure.(100) samples were prepared and divided into five groups according to the test performed ,Each group consisted of 20 specimens and these were subdivided into 2 groupsGroup (A): control group (10 specimens of high impact acrylic resin without zirconium oxide) and Group (B):zirconium oxide group(10 specimens of high impac

This work is the first study of the Curculionoidea fauna from Kurdistan region of Iraq, based on the intensive survey in different localities of Kurdistan from March 2016 to November 2017. In total, 41 species belonging to 28 genera, 21 tribes and 3 families were collected and identified, including 25 species newly recorded for the Iraqi fauna.

General distribution, collecting localities and methods, with plant association data for each species are given.

Total dissolved solids are at the top of the parameters list of water quality that requires investigations for planning and management, especially for irrigation and drinking purposes. If the quality of water is sufficiently predictable, then appropriate management is possible. In the current study, Multiple Linear Regression (MLR) and Artificial Neural Network (ANN) models were used as indicators of water quality and for the prediction of Total Dissolved Solids (TDS) along the Tigris River, in Baghdad city. To build these models five water parameters were selected from the intakes of four water treatment plants on the Tigris River, for the period between 2013 and 2017. The selected water parameters were Total Dissolved Solids (TDS

The deterioration of buried sewers during their lifetime can be affected by several factors leading to bad performance and can damage the infrastructure similar to other engineering structures. The Hydraulic deterioration of the buried sewers caused by sewer blockages while the structural deterioration caused by sewer collapses due to sewer specifications and the surrounding soil characteristics and the groundwater level. The main objective of this research is to develop deterioration models, which are used to predict changes in sewer condition that can provide assessment tools for determining the serviceability of sewer networks in Baghdad city. Two deterioration models were developed and tested using statistical software SPSS, the

The background subtraction is a leading technique adopted for detecting the moving objects in video surveillance systems. Various background subtraction models have been applied to tackle different challenges in many surveillance environments. In this paper, we propose a model of pixel-based color-histogram and Fuzzy C-means (FCM) to obtain the background model using cosine similarity (CS) to measure the closeness between the current pixel and the background model and eventually determine the background and foreground pixel according to a tuned threshold. The performance of this model is benchmarked on CDnet2014 dynamic scenes dataset using statistical metrics. The results show a better performance against the state-of the art