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). St

Addressed the problem of the research is marked: (Performing processors for the time between Impressionism and superrealism) the concept of time and how to submit artwork. The search came in four sections: general framework for research and identified the research problem and the need for him. With an indication of the importance of his presence. Then determine the research objectives of (detection processors performing to the concept of time in works of art in each of Impressionism and superrealism. And a comparison between them to reveal similarities and differences), followed by the establishment of boundaries Find three (objectivity, the temporal and spatial) were then determine the terms related to the title. Then provide the theore

A new modified differential evolution algorithm DE-BEA, is proposed to improve the reliability of the standard DE/current-to-rand/1/bin by implementing a new mutation scheme inspired by the bacterial evolutionary algorithm (BEA). The crossover and the selection schemes of the DE method are also modified to fit the new DE-BEA mechanism. The new scheme diversifies the population by applying to all the individuals a segment based scheme that generates multiple copies (clones) from each individual one-by-one and applies the BEA segment-wise mechanism. These new steps are embedded in the DE/current-to-rand/bin scheme. The performance of the new algorithm has been compared with several DE variants over eighteen benchmark functions including sever

The aim of the present research is to know the following : What are the Science and technology, society and environment issues (S.T.S.E) which included in the content of thechemistry Book second grade intermediate ? And to achieve the objective of search The two researchers has prepares a list of science and technology, society and environment issues (STSE) consisted of (9) key issues namely (Air quality and the atmosphere, sustainable development, water security, health and preventive security, mineral resources investment, pollution of various kinds, energy, food industry, production of weapons technology) and from which (70) sub-issues emerge,Arbitrators competent agreement has been received . Then, thetwo researchers analyzed the con

Alpha shape theory for 3D visualization and volumetric measurement of brain tumor progression using magnetic resonance images

 The researcher was interested in studying a crucial aspect of the systematic world music culture. He highlights the analysis of the harmonic construction in the musical compositions of the artist Khalil Ismail, where harmony is a significant Western musical science, a pillar of the structure of instrumental and vocal music.
It depends on the compositions of vertical sounds performed simultaneously, as tones coincide and are sometimes dissonant to give sound resonance that enriches musical work and attracts recipients. Hence, the researcher has many questions, including: Can the composition of the writings of the artist Khalil Ismail determine in an objective research framework? Is there a study on this subject in some detail? whic

Traffic classification is referred to as the task of categorizing traffic flows into application-aware classes such as chats, streaming, VoIP, etc. Most systems of network traffic identification are based on features. These features may be static signatures, port numbers, statistical characteristics, and so on. Current methods of data flow classification are effective, they still lack new inventive approaches to meet the needs of vital points such as real-time traffic classification, low power consumption, ), Central Processing Unit (CPU) utilization, etc. Our novel Fast Deep Packet Header Inspection (FDPHI) traffic classification proposal employs 1 Dimension Convolution Neural Network (1D-CNN) to automatically learn more representational c

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Background: Odontogenic tumors are a diverse group of lesions with a variety of clinical behavior and histopathologic subtypes, from hamartomatous and benign to malignant. The study aimed to examine the clinical and pathological features of odontogenic tumors in Baghdad over the last 11 years (2011–2021). Materials and Methods: The present retrospective study analyzed all formalin-fixed, paraffin-embedded tissue blocks of patients diagnosed with an odontogenic tumor that were retrieved from archives at a teaching hospital/College of Dentistry in Baghdad University, Iraq, between 2011 and 2021. The diagnosis of each case was confirmed by examining the hematoxylin and eosin stained sections by two expert pathologists. Data from pati