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.
In this research work, a new type of concrete based on sulfur-melamine modification was introduced, and its various properties were studied. This new type of concrete was prepared based on the sulfur-melamine modification and various ingredients. The new sulfur-melamine modifier was fabricated, and its fabrication was confirmed by IR spectroscopy and TG analysis. The surface morphology resulted from this modifier was studied by SEM and EDS analysis. The components ratios in concrete, chemical and physical characteristics resulted from sulfur-melamine modifier, chemical and corrosion resistance of concrete, stability of concrete against water adsorption, stability of concrete against freezing, physical and mechanical properties and durabi
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In this study, we introduce new a nanocomposite of functionalize graphene oxide FGO and functionalize multi wall carbon nanotube (F-MWCNT-FGO).The formation of nanocomposite was confirmed by FT-IR ,XRD and SEM. The magnitude of the dielectric permittivity of the (F-MWCNT-FGO) nanocomposite appears to be very high in the low frequency range and show a unique negative permittivity at frequencies range from 400 Hz to 4000Hz. The ac conductivity of nanocomposite reaches 23.8 S.m-1 at 100Hz.
This research includes a detaile description of new species Rhyncomya irakensis sp. nov.
from Iraq.
Localities distribution, host plants and data of collection were recorded.
The present study reports Morchella conica Pers.1818, which belongs to the family, Morchellaceae as a new record of Iraqi macromycota based on the morphological and molecular methods. During their short and often sporadic fruiting season, this fungal species was found in mixed forest unburned areas in Branan ranges (Suliamaniya Province, Northeast Iraq). Currently, M. conica is the second Morchella species reported from Iraq. The current study aimed to introduce this new record, which is poorly studied in the Middle East. M. conica is morphologically described and phylogenetically confirmed. The relationship between this species and other species within the genus was studied using the nrDNA ITS sequences from different species and divers
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يعد هذا النص أحد النصوص المسمارية المصادرة التي بحوزة المتحف العراقي، ويحمل الرقم المتحفي (235869)، قياساته )12،7x 6x 2،5سم). يتضمن مدخولات كميات من الشعير،أرخ النص الى عصر أور الثالثة (2012-2004 ق.م) و يعود الى السنة الثالثة من حكم الملك أبي-سين (2028-2004 ق.م)،أن الشخصية الرئيسة في هذا النص هو)با-اَ-كا مسمن الماشية( من مدينة أري-ساكرك، ومقارنته مع النصوص المسمارية المنشورة التي تعود الى أرشيفه يبلغ عددها (196) نصاً تضمنت نشاطاته م
... Show MoreThis study includes a detailed morphological description of Cosmina baghdadensis sp. nov.
from Iraq.
Many characters are used in identification especially chaetotaxy and male genetalia.
Locality, host plant, and data of collection were given.
Traditional accounting takes only one dimension (economic) in calculating the value added of the company, and all other aspects (including environmental and social) are neglected, and despite the emergence of Sustainability Accounting and the interest of companies in preparing sustainability reports, these reports are suffering from many problems, including multiple metrics used in measuring companies (cash, quantity and lavish). In addition, these reports may reach dozens of pages in some companies and this causes the problem (information overload) which affects the qualitative properties of accounting information such as appropriate and relative, which requires the need to find a tool that can measure the Sustainability Unit of
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Cybersecurity refers to the actions that are used by people and companies to protect themselves and their information from cyber threats. Different security methods have been proposed for detecting network abnormal behavior, but some effective attacks are still a major concern in the computer community. Many security gaps, like Denial of Service, spam, phishing, and other types of attacks, are reported daily, and the attack numbers are growing. Intrusion detection is a security protection method that is used to detect and report any abnormal traffic automatically that may affect network security, such as internal attacks, external attacks, and maloperations. This paper proposed an anomaly intrusion detection system method based on a
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Cybersecurity refers to the actions that are used by people and companies to protect themselves and their information from cyber threats. Different security methods have been proposed for detecting network abnormal behavior, but some effective attacks are still a major concern in the computer community. Many security gaps, like Denial of Service, spam, phishing, and other types of attacks, are reported daily, and the attack numbers are growing. Intrusion detection is a security protection method that is used to detect and report any abnormal traffic automatically that may affect network security, such as internal attacks, external attacks, and maloperations. This paper proposed an anomaly intrusion detection system method based on a
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