The availability of different processing levels for satellite images makes it important to measure their suitability for classification tasks. This study investigates the impact of the Landsat data processing level on the accuracy of land cover classification using a support vector machine (SVM) classifier. The classification accuracy values of Landsat 8 (LS8) and Landsat 9 (LS9) data at different processing levels vary notably. For LS9, Collection 2 Level 2 (C2L2) achieved the highest accuracy of (86.55%) with the polynomial kernel of the SVM classifier, surpassing the Fast Line-of-Sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) at (85.31%) and Collection 2 Level 1 (C2L1) at (84.93%). The LS8 data exhibits similar behavior. Conv

Migraine affects more than one billion individuals each year across the world, and is one of the most common neurologic disorders, with a high prevalence and morbidity, especially among young adults and females. Migraine is associated with a wide range of comorbidities, which range from stress and sleep disturbances to suicide. The complex and largely unclear mechanisms of migraine development have resulted in the proposal of various social and biological risk factors, such as hormonal imbalances, genetic and epigenetic influences, as well as cardiovascular, neurological, and autoimmune diseases. Experimental findings suggest an involvement of neuroinflammatory mechanisms in the pathophysiology of migraine. Specifically, preclinical

Chronic myeloid leukemia (CML) is a myeloproliferative disorders characterized by formation of Philadelphia chromosome. After disease development, several events may associate with the reduction of anti-tumor immunity. The present study was designed to investigate the immunological profile of innate and adaptive immune response in Iraqi patients with CML. Patients were grouped into untreated (UT), treated (T) with chemotherapy, while another apparently healthy individuals were recruited to represent the control (C) group. Methods: ELISA technique was used to estimate serum levels of GM-CSF, IL-1a, IL-8, IL2, INF-?, IL-4, and IL-10 while SRID was used to estimate serum levels of C4, IgM, IgA, and IgG. Results: Regarding to innate immune resp

This study discussed a biased estimator of the Negative Binomial Regression model known as (Liu Estimator), This estimate was used to reduce variance and overcome the problem Multicollinearity between explanatory variables, Some estimates were used such as Ridge Regression and Maximum Likelihood Estimators, This research aims at the theoretical comparisons between the new estimator (Liu Estimator) and the estimators

Objectives: The aim of the study was, to assess the nurse's role regarding cardiovascular drug
administration in Erbil city.
Methodology: A descriptive survey was conducted in Hawler teaching and Rizgari teaching Hospitals. The
number of samples is 50 nurses; the period of the study was started from 15th of November 2008 up to
the end of March 2009. A questionnaire was developed by investigators based on extensive review of
available studies and literatures. Data were collected through application of observational check list
consist of two part, part one was demographic sheet and part two about nurse’s responsibility regarding
medication administration which include (before, during, after drug administration). Data

 In this paper, we propose a method using continuous wavelets to study the multivariate fractional Brownian motion through the deviations of the transformed random process to find an efficient estimate of Hurst exponent using eigenvalue regression of the covariance matrix. The results of simulations experiments shown that the performance of the proposed estimator was efficient in bias but the variance get increase as signal change from short to long memory the MASE increase relatively. The estimation process was made by calculating the eigenvalues for the variance-covariance matrix of Meyer’s continuous wavelet details coefficients.