Skull image separation is one of the initial procedures used to detect brain abnormalities. In an MRI image of the brain, this process involves distinguishing the tissue that makes up the brain from the tissue that does not make up the brain. Even for experienced radiologists, separating the brain from the skull is a difficult task, and the accuracy of the results can vary quite a little from one individual to the next. Therefore, skull stripping in brain magnetic resonance volume has become increasingly popular due to the requirement for a dependable, accurate, and thorough method for processing brain datasets. Furthermore, skull stripping must be performed accurately for neuroimaging diagnostic systems since neither non-brain tissues nor the removal of brain sections can be addressed in the subsequent steps, resulting in an unfixed mistake during further analysis. Therefore, accurate skull stripping is necessary for neuroimaging diagnostic systems. This paper proposes a system based on deep learning and Image processing, an innovative method for converting a pre-trained model into another type of pre-trainer using pre-processing operations and the CLAHE filter as a critical phase. The global IBSR data set was used as a test and training set. For the system's efficacy, work was performed based on the principle of three dimensions and three sections of MR images and two-dimensional images, and the results were 99.9% accurate.
Nigella sativa seeds (NSS) are reputed traditionally and scientifically as a potent agent that promote milk secretion (galactagogue), but their mechanism of action is studied trivially. One suggestion was that these seeds are bio-transformed to sex hormones within the ovaries. Therefore, this investigation was designated to throw light on the action of these seeds in the absence of ovaries i.e. in male rats. Thirty Norway male albino rats were used in this investigation. They were divided into experimental (n=20,fed NSS 2g/ Kg body weight /day for 14 days) and control (n=10, fed placebo for 14 days). After sacrifice mammary gland and blood samples were obtained. Experimental rats revealed a significant increase (p (0.01>in
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The research aims to investigate the possibility of joint auditing in improving the market value of Iraqi companies listed on the Iraq Stock Exchange. The sample was represented by 10 Iraqi companies listed in the Iraq market for the period from 2014-2017 (2 years before implementation and 2 years after implementation) and the research was based on the idea that joint auditing enhances investor confidence and raises their level of security as a result of providing quality and reliable reports, and thus This indicates good news in the market that reflects on the performance of stocks and the market value of companies that adopt joint auditing. The results of the analysis indicate an improvement in the market value, but this improv
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The topic of the research revolves around constructivist theory, which is one of the most important theories that added weight to the theoretical and epistemological field of international relations. The constructivist theory studies international relations from a completely different side of theories by focusing on the social aspects of international relations, and by looking at international relations as social constructs. Ideas, cultures, norms, standards and language play a major role in their formation. The study also examines the state of the war on terrorism as it represents one of the most international cases in which its composition and composition coincide with constructive ideas and a
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The study aimes to analyze the discourse of Arab tweeters regarding the normalization of Arab-Israeli relations on the social media site (Twitter).
Study Methodology: The study relay on the survey method, using the comprehensive survey method, and this research is one of the descriptive types that aim to describe the phenomenon in a qualitative way, and discuss it through the method of in-depth analysis, in addition to using the tools of (discourse analysis).
Study sample: A sample of (8686) tweets for (7425) tweeters, which was posted on Twitter during the period from 15/9 to 30/9/2020, on the issue of normalizing Arab-Israeli relations.
Study tools: The data study was collected using the data mining tool from social networks (
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the films of cdse pure and doped with copper ratio glass substrate effect od cucomcentration technique thikness doped with copper is an anonmg and the density of state increases
Face recognition is a crucial biometric technology used in various security and identification applications. Ensuring accuracy and reliability in facial recognition systems requires robust feature extraction and secure processing methods. This study presents an accurate facial recognition model using a feature extraction approach within a cloud environment. First, the facial images undergo preprocessing, including grayscale conversion, histogram equalization, Viola-Jones face detection, and resizing. Then, features are extracted using a hybrid approach that combines Linear Discriminant Analysis (LDA) and Gray-Level Co-occurrence Matrix (GLCM). The extracted features are encrypted using the Data Encryption Standard (DES) for security
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Products’ quality inspection is an important stage in every production route, in which the quality of the produced goods is estimated and compared with the desired specifications. With traditional inspection, the process rely on manual methods that generates various costs and large time consumption. On the contrary, today’s inspection systems that use modern techniques like computer vision, are more accurate and efficient. However, the amount of work needed to build a computer vision system based on classic techniques is relatively large, due to the issue of manually selecting and extracting features from digital images, which also produces labor costs for the system engineers. In this research, we pr
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Ground-based active optical sensors (GBAOS) have been successfully used in agriculture to predict crop yield potential (YP) early in the season and to improvise N rates for optimal crop yield. However, the models were found weak or inconsistent due to environmental variation especially rainfall. The objectives of the study were to evaluate if GBAOS could predict YP across multiple locations, soil types, cultivation systems, and rainfall differences. This study was carried from 2011 to 2013 on corn (Zea mays L.) in North Dakota, and in 2017 in potatoes in Maine. Six N rates were used on 50 sites in North Dakota and 12 N rates on two sites, one dryland and one irrigated, in Maine. Two active GBAOS used for this study were GreenSeeker and Holl
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