Information from 54 Magnetic Resonance Imaging (MRI) brain tumor images (27 benign and 27 malignant) were collected and subjected to multilayer perceptron artificial neural network available on the well know software of IBM SPSS 17 (Statistical Package for the Social Sciences). After many attempts, automatic architecture was decided to be adopted in this research work. Thirteen shape and statistical characteristics of images were considered. The neural network revealed an 89.1 % of correct classification for the training sample and 100 % of correct classification for the test sample. The normalized importance of the considered characteristics showed that kurtosis accounted for 100 % which means that this variable has a substantial effect on how the network perform when predicting cases of brain tumor, contrast accounted for 64.3 %, correlation accounted for 56.7 %, and entropy accounted for 54.8 %. All remaining characteristics accounted for 21.3-46.8 % of normalized importance. The output of the neural networks showed that sensitivity and specificity were scored remarkably high level of probability as it approached % 96.
Background: Debonding and fracture of artificial teeth from denture bases are common clinical problem, bonding of artificial teeth to heat cure acrylic and high impact heat cure acrylic denture base materials with autoclave processing method is not well known. The aim of this study was to evaluate the effect of autoclave processing method on shear bond of artificial teeth to heat cure denture base material and high impact heat cure denture base material. Materials and methods: Heat polymerized (Vertex) and high impact acrylic (Vertex) acrylic resins were used. Teeth were processed to each of the denture base materials after the application of different surface treatments. The sample (which consist of artificial tooth attached to the dentur
... Show MoreAbstract Objectives: This research seeks to highlight one of the important topics artificial intelligence and its impact on education and media. This issue has received considerable attention from international institutions and organizations in order to keep pace with the world's current progress. The study provided an overview of the concept of artificial intelligence, its definitions, its importance and characteristics and its impact on education in general and on the student and teacher in particular, as well as linking the subject of education to the media because social media that is one of the media has a great impact on the academic community. Methods: This study relied on the analytical descriptive curriculum where one of the curr
... Show MoreThis study investigated the efficacy of nasal injection of rhodamine B nanospanlastic (RBN) for magnetic vesicle imaging of specific brain locations. Effective delivery of RBN, which functions as fluorescence agents, to specific brain regions is necessary to achieve fluorescence particle imaging (FPI). There has been interest in nasal administration as a means of administering drugs directly to the brain, thereby circumventing the blood-brain barrier. We offered experimental nasal fluorescence agent administration by in vivo research. Fluorescent tests confirmed that, upon nasal delivery, the intended nanospanlastic migrated into the brain. Furthermore, using fluorescent microscopy, we demonstrated how these nanospanla
... Show MoreMixing this strategy with a qualitative research design and an idea known as AI-supported journalism, the paper is going to approach the requirements of how AI technologies may transform journalism content and culture in a way beyond what one anticipates; therefore, enabling more of it to reach an audience. The current research used descriptive research design to investigate the potential applications of the AI tools that mediate civilizational conversation and a structured questionnaire to media professionals. AI-driven journalism can promote peaceful cohabitation and mutual respect and thus act as a bridge between cultures, the research said. The piece even goes on to mention the need for media establishments and civil soc
... Show MoreBackground:The demand for esthetic orthodontic appliances is increasing so that the esthetic orthodontic archwires were introduced. This in vitro study was designed to evaluate the surface roughness offiber-reinforced polymer composite (FRPC) archwires compared to coated nickel-titanium (NiTi) archwires immersed in artificial saliva. Materials and Methods:Three types of esthetic orthodontic archwires were used: FRPC (Dentaurum), Teflon coated NiTi (Dentaurum) and epoxy coated NiTi (Orthotechnology). They were round (0.018 inch) in cross section and cut into pieces of 15 mm in length.Forty pieces from each type were divided into four groups; one group was left at a dry condition and the other three groups were immersed in artificial saliva (
... Show MoreThe research aims to shed light on the role of artificial intelligence in achieving Ambidexterity performance, as banks work to take advantage of modern technologies, artificial intelligence is an innovation that is expected to have a long-term impact, as well as banks can improve the quality of their services and analyze data to ensure that customers' future needs are understood. . The Bank of Baghdad and the Middle East Bank were chosen as a community for the study because they had a role in the economic development of the country as well as their active role in the banking market. A sample of department managers was highlighted in collecting data and extracting results based on the checklist, which is the main tool for the stu
... Show MoreThe 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
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