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.
The computer vision branch of the artificial intelligence field is concerned with developing algorithms for analyzing video image content. Extracting edge information, which is the essential process in most pictorial pattern recognition problems. A new method of edge detection technique has been introduces in this research, for detecting boundaries.
Selection of typical lossy techniques for encoding edge video images are also discussed in this research. The concentration is devoted to discuss the Block-Truncation coding technique and Discrete Cosine Transform (DCT) coding technique. In order to reduce the volume of pictorial data which one may need to store or transmit,
... Show MoreAfter the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings
... Show MorePavement crack and pothole identification are important tasks in transportation maintenance and road safety. This study offers a novel technique for automatic asphalt pavement crack and pothole detection which is based on image processing. Different types of cracks (transverse, longitudinal, alligator-type, and potholes) can be identified with such techniques. The goal of this research is to evaluate road surface damage by extracting cracks and potholes, categorizing them from images and videos, and comparing the manual and the automated methods. The proposed method was tested on 50 images. The results obtained from image processing showed that the proposed method can detect cracks and potholes and identify their severity levels wit
... Show MoreThis study was designed to evaluate the role of single session autologous facial fat grafting in correcting facial asymmetries after mixing it with platelet-rich fibrin (PRF) and injecting them into rich vascular facial muscular plane.
Fifteen patients (12 females and 3 males) with age ranging from 18 years to 40 years were included in this study and followed up during 6 months, all the patients were treated in the Al-Shaheed Ghazi Al-Hariri for specialized surgeries hospital (Medical City, Baghdad, Iraq).
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Designing machines and equipment for post-harvest operations of agricultural products requires information about their physical properties. The aim of the work was to evaluate the possibility of introducing a new approach to predict the moisture content in bean and corn seeds based on measuring their dimensions using image analysis using artificial neural networks (ANN). Experimental tests were carried out at three levels of wet basis moisture content of seeds: 9, 13 and 17%. The analysis of the results showed a direct relationship between the wet basis moisture content and the main dimensions of the seeds. Based on the statistical analysis of the seed material, it was shown that the characteristics
This work was carried to study the capability of activated alumina from bauxite compared with activated carbon adsorption capability to reduce the color content from Al-Hilla Textile Company wastewater. Six dyes were studied from two types(reactive and dispersed) namely (blue, red, yellow) from wastewater and aqueous solutions.
Forty eight experiments were carried out to study the effect of various initial conditions (bed height, flow rate, initial concentration, pH value, temperature, and competitive adsorption) on adsorption process.
The results showed that the adsorption process using activated carbon insured a good degree of color reduction reaching (99.7%) and was better than activated bauxite which reached (95%).
In this work, γ-Al2O3NPs were successfully biosynthesized, mediated aluminum nitrate nona hydrate Al(NO3)3.9H2O, sodium hydroxide, and aqueous clove extract in alkali media. The γ-Al2O3NPs were characterized by different techniques like Fourier transform infrared spectroscopy (FT-IR), UV-Vis spectroscopy, X-ray diffraction (XRD), scanning electron microscopy (SEM), energy–dispersive x-ray spectroscopy, transmission electron microscope (TEM), Energy-dispersive X-ray spectroscopy (EDX), and atomic force microscopy (AFM). The final results indicated the γ-Al2O3NPs nanoparticle size, bonds nature, element phase, crystallinity, morphology, surface image, particle analysis – threshold detection, and the topography parameter. The id
... Show MoreThis study was conducted to explore the effects of using ionized water on the productive and physiological performance of Japanese quails (Coturnix japonica). Our study was conducted at a private farm from 20th April, 2016 to 13th July, 2016 (84 d). One hundred 42-day-old Japanese quail chicks were used, divided randomly into 5 groups with 4 replicates. Treatments consisted in a control group (T1 - normal water:), alkaline (T2 - pH 8 and T3 - pH 9), and acidic water (T4 - pH 6 and T5 - pH 5). All birds were fed a balanced diet of energy and protein. The egg production ratio, egg weight, cumulative number of eggs, egg mass, feed conversion ratio, productivity per hen per week, and effects on plasma lipids, uric acid, glucose, calcium, and ph
... Show MoreIn this paper, we study and investigate the quark anti-quark interaction mechanism through the annihilation process. The production of photons in association with interaction quark and gluon in the annihilation process. We investigate the effect of critical temperature, strength coupling and photons energy in terms of the quantum chromodynamics model theory framework. We find that the use of large critical temperature Tc =134 allows us to dramatically increase the strength coupling of quarks interaction. Its sensitivity to decreasing in photons rate with respect to strength coupling estimates. We also discuss the effect of photons energy on the rate of the photon , such as energies in range (1.5 to 5 GeV).The photons rate increases
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