Two unsupervised classifiers for optimum multithreshold are presented; fast Otsu and k-means. The unparametric methods produce an efficient procedure to separate the regions (classes) by select optimum levels, either on the gray levels of image histogram (as Otsu classifier), or on the gray levels of image intensities(as k-mean classifier), which are represent threshold values of the classes. In order to compare between the experimental results of these classifiers, the computation time is recorded and the needed iterations for k-means classifier to converge with optimum classes centers. The variation in the recorded computation time for k-means classifier is discussed.

Optimizing system performance in dynamic and heterogeneous environments and the efficient management of computational tasks are crucial. This paper therefore looks at task scheduling and resource allocation algorithms in some depth. The work evaluates five algorithms: Genetic Algorithms (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), Firefly Algorithm (FA) and Simulated Annealing (SA) across various workloads achieved by varying the task-to-node ratio. The paper identifies Finish Time and Deadline as two key performance metrics for gauging the efficacy of an algorithm, and a comprehensive investigation of the behaviors of these algorithms across different workloads was carried out. Results from the experiment

Change detection is a technology ascertaining the changes of
specific features within a certain time Interval. The use of remotely
sensed image to detect changes in land use and land cover is widely
preferred over other conventional survey techniques because this
method is very efficient for assessing the change or degrading trends
of a region. In this research two remotely sensed image of Baghdad
city gathered by landsat -7and landsat -8 ETM+ for two time period
2000 and 2014 have been used to detect the most important changes.
Registration and rectification the two original images are the first
preprocessing steps was applied in this paper. Change detection using
NDVI subtractive has been computed, subtrac

CuO nanoparticles were synthesized in two different ways, firstly by precipitation method using copper acetate monohydrate Cu(CO₂CH₁₃)₂·H2O, glacial acetic acid (CH3COOH) and sodium hydroxide(NaOH), and secondly by sol-gel method using copper chloride(CuCl₂), sodium  hydroxide (NaOH) and ethanol (C₂H₆O). Results of scanning electron microscopy (SEM) showed that different CuO nanostructures (spherical and Reef) can be formed using precipitation and sol- gel process, respectively, at which the particle size was found to be less than 2 µm. X-ray diffraction (XRD)manifested that the pure synthesized powder has no inclusions that may exist during preparations. XRD result

Background: Diabetes and hypertension are related to cardiovascular risk factors and are possible to detect development of atherosclerosis in cardiovascular system, were can predict their effect and measurement by ultrasound and Doppler study. These risk factors included increased intima-media thickness, resistive index (RI) and pulsatility index (PI) of the right common carotid arteries. Method: We studied 20 patients with diabetes and hypertension, and 20 patients with diabetes only, were examine right carotid arteries for these two groups. In this sample we studied the Lumen diameter of the Rt. carotid arteries, Intima – media thickness (IMT), peak systolic velocity, end diastolic velocity, and Pulsatility index, Resistance index were

Abstract: Mixed ligand Mn(II), Co(II), Ni(II), Cu (II), Zn(II), and Cd(II) complexes with (TMAP) Schiff base ligand and (8HQ) have been composition and analyzed. Diagnosis by, melting point, solubility, Electronic, mass and IR-spectroscopic studies, conductivity elemental, thermoanalytical analysis displayed the forming of mononuclear complexes. Spectral studies results suggest an octahedral system or the metal (II) mixed complexes. The detainments of molar conductance of the mixed complexes in DMF coincide to electrolytic nature of the mixed complexes, consequently, these complexes could be subedited as [M(TMAP)(8Q)(H2O)]nX.yH2O (M=Co(II) and Cu(II) complexes(where n = 1, y = 0 ); [M(TMAP)(8Q)(H2O)]nX.yH2O (M = (where n = 1, y = 1 for Ni(

       In recent years, the attention of researchers has increased of semi-parametric regression models, because it is possible to integrate the parametric and non-parametric regression models in one and then form a regression model has the potential to deal with the cruse of dimensionality in non-parametric models that occurs through the increasing of explanatory variables. Involved in the analysis and then decreasing the accuracy of the estimation. As well as the privilege of this type of model with flexibility in the application field compared to the parametric models which comply with certain conditions such as knowledge of the distribution of errors or the parametric models may

Reservoir quality assessment is important for detecting hydrocarbon-bearing zones and guiding future enhancement strategies. This study presents a detailed petrophysical evaluation of the Mishrif Formation in the Buzurgan Oilfield, which was selected due to its strategic value through its significant remaining reserves which making it an ideal candidate for advanced evaluation techniques. This study aims for shale content, porosity, permeability, water saturation, net to gross, and lithology determination. Well log and core data were used together to establish accurate property estimations. Permeability prediction through conventional methods, like core permeability-porosity correlations, was highly dispersive due to the heterogenei