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. Conversely, when using the maximum-likelihood classifier, the highest accuracy (83.06%) was achieved with FLAASH. The results demonstrate significant variations in accuracies for different land cover classes, which emphasizes the importance of per-class accuracy. The results highlight the critical role of preprocessing techniques and classifier selection in optimizing the classification processes and land cover mapping accuracy for remote sensing geospatial applications. Finally, the actual differences in classification accuracy between processing levels are larger than those given by the confusion matrix. So, the consideration of alternative evaluation methods with the absence of reference images is critical.
Background: Coated archwires have been introduced to improve esthetics during orthodontic treatment. Theaim of the present study was to evaluate and compare the load–deflection characteristics and force levels of six brands of coated nickel titanium orthodontic archwires using palatal and gingival deflection. Materials and methods: Ten round wires (0.016 inch) and ten rectangular wires (0.019x0.025 inch) were obtained from each of six brands (G&H, Opal, Ortho Technology, Dany, Hubit and Astar Companies). The load-deflection properties of these archwires were evaluated by the modified bending test usinga readymade dental arch model in both palatal and gingival directions at 37°C temperature using a universal material testing machi
... Show MoreIn this study the prevalence of acute, sub-acute and chronic toxoplasmosis were monitored in a group of Iraqi pregnant women according to the anti-T.gondii antibodies (IgG and IgM), as well as the levels of both progesterone and estrogen hormones were measured using mini-VIDAS®technique. This study demonstrated that there was high prevalence of chronic toxoplasmosis (31.70%) when it compared with acute and sub-acute type, results also showed that the acute toxoplasmosis always related with low concentration of both progesterone and estrogen which were (5.35 ± 7.15 ng/ml) and (70.66 ± 51.08 pg/ml) respectively
Obesity is an escalating health problem in developing countries. One to ten children worldwide are overweight in a report showed by the International Obesity Task Force. Ghrelin, orexigenic peptide, has 28 amino acids, it is considered the greatest remarkable promotion in the last two decades for understanding the physiological changes of action regulating food intake and hunger. Obestatin is a 23-amino acid peptide nearly connected to ghrelin that secures from substitutio
... Show MoreFibromyalgia (FM) is a common, debilitating, and chronic pain syndrome. The women are more likely to have more tender points on examination than are their male counterparts. Iraqi study showed that FM occur in 1.5% among adolescents of Iraqi population. In compare to normal healthy women, present study was revealed that Iraqi women with FM have significant elevation of calcium (p = 0.003) with significant reduction of magnesium (p = 0.001), whereas the inorganic phosphorous was not differs (p = 0.31). In conclusion, magnesium and calcium would play a crucial role in etiopathogenesis of fibromyalgia.
Key words: calcium, magnesium, phosphorous, Fibromyalgia.
Background: There is plenty of evidence
suggesting that involvement of several groups of
viruses in the development and / or acceleration of
Type 1 Diabetes Mellitus (T1DM).
Objective: To analyze the T- cell proliferation in
the presence of Coxsackie virus B5 (CVB5), Polio
and Adenovirus antigens in addition to assessment
of Interferon- gamma (IFN-γ), Interleukins (IL-10
and IL-6).
Methods: In 60 Iraqi T1DM children with recent
onset of T1DM, Lymphocyte proliferation was
analyzed using Methylthiazol tetrazolium (MTT)
assay by culturing Peripheral Blood Lymphocytes
(PBLs) with Coxsackie Virus B5 (CVB5),
Adenovirus, and Polio vaccine. Serum Interferon-γ,
IL-10 and IL-6 were quantified by sandw
The researcher highlighted the general budget in Iraq for the period (2003-2018) facing the challenges of administrative and financial corruption, in addition to the fluctuations in oil prices, the repercussions and many problems suffered and will suffer the Iraqi government in the process of preparing the general budget of the state and weak contribution of the agricultural and industrial sectors and other economic sectors and neglect altogether, oil has become the main supplier in funding Iraq's budget after 2003, and the impact on the unemployment rates in Iraq, which recorded fluctuating rates and then increased during the period (2012-2018) to achieve this, an inductive method was adopted, using theoretical and descriptive a
... Show MoreCrime is considered as an unlawful activity of all kinds and it is punished by law. Crimes have an impact on a society's quality of life and economic development. With a large rise in crime globally, there is a necessity to analyze crime data to bring down the rate of crime. This encourages the police and people to occupy the required measures and more effectively restricting the crimes. The purpose of this research is to develop predictive models that can aid in crime pattern analysis and thus support the Boston department's crime prevention efforts. The geographical location factor has been adopted in our model, and this is due to its being an influential factor in several situations, whether it is traveling to a specific area or livin
... Show More<span lang="EN-US">Diabetes is one of the deadliest diseases in the world that can lead to stroke, blindness, organ failure, and amputation of lower limbs. Researches state that diabetes can be controlled if it is detected at an early stage. Scientists are becoming more interested in classification algorithms in diagnosing diseases. In this study, we have analyzed the performance of five classification algorithms namely naïve Bayes, support vector machine, multi layer perceptron artificial neural network, decision tree, and random forest using diabetes dataset that contains the information of 2000 female patients. Various metrics were applied in evaluating the performance of the classifiers such as precision, area under the c
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