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.
This work presents a novel technique for the detection of oil aging in electrical transformers using a single mode optical fiber sensor based on surface plasmon resonance (SPR). The aging of insulating oil is a critical issue in the maintenance and performance of electrical transformers, as it can lead to reduce insulation properties, increase risk of electrical breakdown, and decrease operational lifespan. Many parameters are calculated in this study in order to examine the efficiency of this sensor like sensitivity (S), signal to noise ratio (SNR), resolution (refractive index unit) and figure of merit (FOM) and the values are for figure of merit is 11.05, the signal to noise ratio is 20.3, the sensitivity is 6.63, and the resolution is 3
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* Khalifa E. Sharquie1, Hayder Al-Hamamy2, Adil A. Noaimi1, Mohammed A. Al-Marsomy3, Husam Ali Salman4, American Journal of Dermatology and Venereology, 2014 - Cited by 2
This article showcases the development and utilization of a side-polished fiber optic sensor that can identify altered refractive index levels within a glucose solution through the investigation of the surface Plasmon resonance (SPR) effect. The aim was to enhance efficiency by means of the placement of a 50 nm-thick layer of gold at the D-shape fiber sensing area. The detector was fabricated by utilizing a silica optical fiber (SOF), which underwent a cladding stripping process that resulted in three distinct lengths, followed by a polishing method to remove a portion of the fiber diameter and produce a cross-sectional D-shape. During experimentation with glucose solution, the side-polished fiber optic sensor revealed an adept detection
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Social Networking has dominated the whole world by providing a platform of information dissemination. Usually people share information without knowing its truthfulness. Nowadays Social Networks are used for gaining influence in many fields like in elections, advertisements etc. It is not surprising that social media has become a weapon for manipulating sentiments by spreading disinformation. Propaganda is one of the systematic and deliberate attempts used for influencing people for the political, religious gains. In this research paper, efforts were made to classify Propagandist text from Non-Propagandist text using supervised machine learning algorithms. Data was collected from the news sources from July 2018-August 2018. After annota
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The current research aims to detect the level of suicidal tendencies among secondary school students in terms of gender and educational stage (intermediate school students and high school students). The researcher adopted Al Hafeez's (2017) scale for suicidal tendencies, it consists of (57) items including six domains, namely: suicidal ideation, social motives for suicide, tendency to self-harm, desire for death, indifference and pessimism about life, willingness to commit suicide. The scale was modified to be (42) items after it was exposed to a group of experts. The scale was applied to a sample of (200) male and female students from secondary schools in Baghdad Governorate (Karkh - Rusafa) for the academic year 2021-2022. The results
... Show MoreIn cognitive radio networks, there are two important probabilities; the first probability is important to primary users called probability of detection as it indicates their protection level from secondary users, and the second probability is important to the secondary users called probability of false alarm which is used for determining their using of unoccupied channel. Cooperation sensing can improve the probabilities of detection and false alarm. A new approach of determine optimal value for these probabilities, is supposed and considered to face multi secondary users through discovering an optimal threshold value for each unique detection curve then jointly find the optimal thresholds. To get the aggregated throughput over transmission
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Background Over the past decade there has been a growing awareness of, and interest in, the trace element concentration differences between normal and diseased tissues. Significant changes in tissue concentrations of Zinc (Zn) and Copper (Cu) have been previously reported in inflammation and cancer of certain human tissues.
Aim:(1)To correlate between Zn and Cu concentrations and the histological picture of normal and certain inflamed human tissues, namely the gall bladder (GB) the vermiform appendix (VA), visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT). (2) to detect whether there is a difference in the above-mentioned parameters between VAT and SAT. (3) to obtain recordings for trace element levels in human tissu