This paper presents a hybrid approach for solving null values problem; it hybridizes rough set theory with intelligent swarm algorithm. The proposed approach is a supervised learning model. A large set of complete data called learning data is used to find the decision rule sets that then have been used in solving the incomplete data problem. The intelligent swarm algorithm is used for feature selection which represents bees algorithm as heuristic search algorithm combined with rough set theory as evaluation function. Also another feature selection algorithm called ID3 is presented, it works as statistical algorithm instead of intelligent algorithm. A comparison between those two approaches is made in their performance for null values estima

Comparative taxonomic study has been compeleted for the species of the. genus Centaurium Hill. of Iraq. So the morphological characters were studied comparatively for the first time form Iraqi materials. Stems, leaves ,infloresences and reproductive organs characters were a good taxonomic importance. Geographical distrtribution has been done for the species of the genus in addition to the environment information. The results were presented with schedules, tables, maps and micrographs. Taxonomic key for the species separation was also presented.

<span>One of the main difficulties facing the certified documents documentary archiving system is checking the stamps system, but, that stamps may be contains complex background and surrounded by unwanted data. Therefore, the main objective of this paper is to isolate background and to remove noise that may be surrounded stamp. Our proposed method comprises of four phases, firstly, we apply k-means algorithm for clustering stamp image into a number of clusters and merged them using ISODATA algorithm. Secondly, we compute mean and standard deviation for each remaining cluster to isolate background cluster from stamp cluster. Thirdly, a region growing algorithm is applied to segment the image and then choosing the connected regi

Carbonized nonwoven nanofibers composite were fabricated using the electrospinning method of a polymeric solution composite followed by heat treatment including stabilization and calcination steps. The spun polymeric solution was a binary polymer mixture/organic solvent. In this study, two types of polymers (Polymethylmethacrylate (PMMA) and Polyethylene glycol (PEG)) were used separately as a copolymer with the base polymer (Polyacrylonitrile (PAN)) to prepare a binary polymer mixture in a mixing ratio of 50:50. The prepared precursor solutions were used to prepare the precursor nanofibers composite (PAN: PMMA) and (PAN: PEG).  The fabricated precursors nonwoven fibers composite were stabilized and carbonized to produce carbon nonw

Poly(L-lactic acid) (PLLA)/poly(caprolactone) (PCL) and two types of organoclay (OMMT) including a fatty amide and ocatdecylamine montmorillonite (FA-MMT and ODA-MMT) were employed to produce polymer nanocomposites by melt blending. Materials were characterized using X-ray diffraction (XRD), Fourier transform infrared (FTIR) spectroscopy, thermogravimetric analysis (TGA), elemental analysis, scanning electron microscopy (SEM) and transmission electron microscopy (TEM). Mechanical properties were also investigated for these nanocomposites. The nanocomposites showed increasing mechanical properties and thermal stability. XRD results indicated that the materials formed nanocomposites. SEM morphology showed that increasing content of OMMT reduc

         Rotating blades are the important parts in gas turbines. Hence, an accurate mathematical estimation (F.E.M) of the stresses and deformations characteristics was required in the design applications to avoid failure. In recent year’s there are researchers interest in the effect of temperature on solid bodies has greatly increased, The main of this study investigated the thermal and rotational effects.  So, the thermal stresses due to high pressure and temperature are studies, also determine the steady state stresses and deformations of rotating blades due to mechanical effect. Many parameters such as thickness and centre of rotating are investigated in this paper. The

Objective: The present study aims at identifying the dimensions behind juvenile delinquency, and to identify their
socio-demographic characteristics of gender, age, and type of delinquency.
Methodology: A descriptive study was conducted in correctional schools in Baghdad City to identify the
behavioral, psychological, and social dimensions contributed to juvenile delinquency. The study sample consisted
of (50) juvenile delinquents, of them, 27 males, and 23 females whose ages range from (12 - 20) years. Those
delinquents live in males’ correctional school in Al-Shalichia, and females’ correctional school in Al-Karradah, in
Baghdad City. The study sample was selected in purposively. The study questionnaire was design

The focus of this work is on systematically understanding the effects of packing density of the sand grains on both the internal and bulk mechanical properties for strip footing interacting with granular soil. The studies are based on particle image velocimetry (PIV) method, coupled with a high resolution imaging camera. This provides valuable new insights on the evolution of slip planes at grain-scale under different fractions of the ultimate load. Furthermore, the PIV based results are compared with finite element method simulations in which the experimentally characterised parameters and constitutive behaviour are fed as an input, and a good level of agreements are obtained. The reported results would serve to the practicing engineers, r

This quasi-experimental study investigated generative AI (GenAI) tools—Copilot for chemistry and GitHub Copilot for mathematics—on academic achievement and sustainable professional development among 160 undergraduates (40 experimental/control per department) at the University of Baghdad’s Ibn Al-Haitham College of Education for Pure Sciences (2024–2025). Non-random assignment controlled for covariates. Pre/post validated tests (α ≥ .85; 15 MCQ + 5 essay items) measured outcomes. ANOVA revealed significant gains for experimental groups (p < .001, η2 = .41, Cohen’s d = 0.72 [95% CI: 0.45–0.98]). Chemistry excelled in affective domains; mathematics in cognitive/skills. Findings affirm GenAI’s domain-specific efficacy, prov