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A New Method for Detecting Cerebral Tissues Abnormality in Magnetic Resonance Images
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We propose a new method for detecting the abnormality in cerebral tissues present within Magnetic Resonance Images (MRI). Present classifier is comprised of cerebral tissue extraction, image division into angular and distance span vectors, acquirement of four features for each portion and classification to ascertain the abnormality location. The threshold value and region of interest are discerned using operator input and Otsu algorithm. Novel brain slices image division is introduced via angular and distance span vectors of sizes 24˚ with 15 pixels. Rotation invariance of the angular span vector is determined. An automatic image categorization into normal and abnormal brain tissues is performed using Support Vector Machine (SVM). Standard Deviation, Mean, Energy and Entropy are extorted using the histogram approach for each merger space. These features are found to be higher in occurrence in the tumor region than the non-tumor one. MRI scans of the five brains with 60 slices from each are utilized for testing the proposed method’s authenticity. These brain images (230 slices as normal and 70 abnormal) are accessed from the Internet Brain Segmentation Repository (IBSR) dataset. 60% images for training and 40% for testing phase are used. Average classification accuracy as much as 98.02% (training) and 98.19% (testing) are achieved.

Publication Date
Tue Nov 01 2016
Journal Name
Iosr Journal Of Computer Engineering
Implementation of new Secure Mechanism for Data Deduplication in Hybrid Cloud
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Cloud computing provides huge amount of area for storage of the data, but with an increase of number of users and size of their data, cloud storage environment faces earnest problem such as saving storage space, managing this large data, security and privacy of data. To save space in cloud storage one of the important methods is data deduplication, it is one of the compression technique that allows only one copy of the data to be saved and eliminate the extra copies. To offer security and privacy of the sensitive data while supporting the deduplication, In this work attacks that exploit the hybrid cloud deduplication have been identified, allowing an attacker to gain access to the files of other users based on very small hash signatures of

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Publication Date
Sun Sep 30 2001
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
New Development in the Process for the Production of Polybutadiene Rubber
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Publication Date
Mon Mar 09 2015
Journal Name
Monthly Notices Of The Royal Astronomical Society
A reliable iterative method for solving Volterra integro-differential equations and some applications for the Lane–Emden equations of the first kind
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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
A new approach for the topical treatment of acne vulgaris by clindamycin HCL supported on kalion
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Has been studied both processes Almetzaz and extortion of a substance Alklanda Maysan different amounts of Alcaúlan Guy 70% alcohol solution using the method when the wavelength

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Publication Date
Sun Oct 31 2021
Journal Name
International Journal Of Sustainable Development And Planning
The Crossing as a New Approach for the Urban Transformation of Traditional Cities Towards the Sustainability
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The topic of urban transformations has attracted the attention of researchers as it is one of the basic issues through which cities can be transformed towards sustainability. A specific level of transformation levels according to a philosophical concept known as a crossing. This article has relied on a specific methodology that aims to find a new approach for urban transformation based on the crossing concept. This concept derives from philosophical entrances based on the concepts of (being, process, becoming, and integration). Four levels have been for the crossing are (normal, ascending, leap, and descending). Each of these levels includes specific characteristics that distinguish it. The results showed that there is no descending

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Publication Date
Tue Feb 01 2011
Journal Name
Iop Conference Series: Materials Science And Engineering
Contour extraction of echocardiographic images based on pre-processing
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In this work we present a technique to extract the heart contours from noisy echocardiograph images. Our technique is based on improving the image before applying contours detection to reduce heavy noise and get better image quality. To perform that, we combine many pre-processing techniques (filtering, morphological operations, and contrast adjustment) to avoid unclear edges and enhance low contrast of echocardiograph images, after implementing these techniques we can get legible detection for heart boundaries and valves movement by traditional edge detection methods.

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Publication Date
Mon Feb 22 2021
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
MRI images series segmentation using the geodesic deformable model
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Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
Clouds Height Classification Using Texture Analysis of Meteosat Images
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In the present work, pattern recognition is carried out by the contrast and relative variance of clouds. The K-mean clustering process is then applied to classify the cloud type; also, texture analysis being adopted to extract the textural features and using them in cloud classification process. The test image used in the classification process is the Meteosat-7 image for the D3 region.The K-mean method is adopted as an unsupervised classification. This method depends on the initial chosen seeds of cluster. Since, the initial seeds are chosen randomly, the user supply a set of means, or cluster centers in the n-dimensional space.The K-mean cluster has been applied on two bands (IR2 band) and (water vapour band).The textural analysis is used

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Publication Date
Fri Apr 01 2022
Journal Name
Neuroquantology
Optical Distinguish of Malignancy Cases of Skin Tumors Images
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The aim of the study is to detect the malignant conditions of the skin tumors through the features of optical images. This research included some of image processing techniques to detect skin cancer as a strong threat to human beings' lives. Using image processing and analysis methods to improves the ability of pathologists to detect this disease leading to more specified diagnosis and better treatment of them. One hundred images were collected from Benign and Malignant tumors and some appropriate image features were calculated, like Maximum Probability, Entropy, Coefficient of Variation, Homogeneity and Contrast, and using Minimum Distance method to separate these images. These features with Minimum Distance as a proposed making decision a

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Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Classification of Optical Images of Cervical Lymph Node Cells
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Abstract<p>the study considers the optical classification of cervical nodal lymph cells and is based on research into the development of a Computer Aid Diagnosis (CAD) to detect the malignancy cases of diseases. We consider 2 sets of features one of them is the statistical features; included Mode, Median, Mean, Standard Deviation and Maximum Probability Density and the second set are the features that consist of Euclidian geometrical features like the Object Perimeter, Area and Infill Coefficient. The segmentation method is based on following up the cell and its background regions as ranges in the minimum-maximum of pixel values. The decision making approach is based on applying of Minimum Dista</p> ... Show More
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