Alzheimer's disease (AD) increasingly affects the elderly and is a major killer of those 65 and over. Different deep-learning methods are used for automatic diagnosis, yet they have some limitations. Deep Learning is one of the modern methods that were used to detect and classify a medical image because of the ability of deep Learning to extract the features of images automatically. However, there are still limitations to using deep learning to accurately classify medical images because extracting the fine edges of medical images is sometimes considered difficult, and some distortion in the images. Therefore, this research aims to develop A Computer-Aided Brain Diagnosis (CABD) system that can tell if a brain scan exhibits indications of Alzheimer's disease. The system employs MRI and feature extraction methods to categorize images. This paper adopts the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset includes functional MRI and Positron-Version Tomography scans for Alzheimer's patient identification, which were produced for people with Alzheimer's as well as typical individuals. The proposed technique uses MRI brain scans to discover and categorize traits utilizing the Histogram Features Extraction (HFE) technique to be combined with the Canny edge to representing the input image of the Convolutional Neural Networks (CNN) classification. This strategy keeps track of their instances of gradient orientation in an image. The experimental result provided an accuracy of 97.7% for classifying ADNI images.
This research is concerned with the re-analysis of optical data (the imaginary part of the dielectric function as a function of photon energy E) of a-Si:H films prepared by Jackson et al. and Ferlauto et al. through using nonlinear regression fitting we estimated the optical energy gap and the deviation from the Tauc model by considering the parameter of energy photon-dependence of the momentum matrix element of the p as a free parameter by assuming that density of states distribution to be a square root function. It is observed for films prepared by Jackson et al. that the value of the parameter p for the photon energy range is is close to the value assumed by the Cody model and the optical gap energy is which is also close to the value
... Show MoreToxoplasmosis is an infection caused by Toxoplasma gondii that leads to abortion or hydrocephalus during pregnancy.One hundered and twenty two aborted women were selected for this study. Serum samples were collected form Al-Kadhmia and Kamal Al-Samari Hospitals,and laboratories around Baghdad, and tested for specific IgG and IgM anti-toxoplasma antibodies to confirm toxoplasmosis in those women by using ELISA test.The result recorded that 51(41.8%) women had antibodies against Toxoplasma gondii, 25(59.5%) women were positive for IgG, and 17(40.5%) women were positive forIgM, while 9(17.6%)women were positive for both.
The diagnoses system of varicose disease has a good level of performance due to the complexity and uniqueness in patterns of vein of the leg. In addition, the patterns of vein are internal of the body, and its features are hard to duplicate, this reason make this method not easy to fake, and thus make it contains of a good features for varicose disease diagnoses. The proposed system used more than one type of algorithms to produce diagnoses system of varicose disease with high accuracy, in addition, this multi-algorithm technique based on veins as a factor to recognize varicose infection. The obtained results indicate that the design of varicose diagnoses system by applying multi- algorithms (Naïve Bayes and Back-Propagation) produced new
... Show MoreOptical burst switching (OBS) network is a new generation optical communication technology. In an OBS network, an edge node first sends a control packet, called burst header packet (BHP) which reserves the necessary resources for the upcoming data burst (DB). Once the reservation is complete, the DB starts travelling to its destination through the reserved path. A notable attack on OBS network is BHP flooding attack where an edge node sends BHPs to reserve resources, but never actually sends the associated DB. As a result the reserved resources are wasted and when this happen in sufficiently large scale, a denial of service (DoS) may take place. In this study, we propose a semi-supervised machine learning approach using k-means algorithm
... Show MoreThe Early – Middle Miocene Ghar and Lower Fars sedimentary succession at the representative oil-well Nu-18 of the Nahr Umr oil field south Iraq; is taken by this study to investigate the sedimentological to reservoir rock facies buildups and related reservoir zonation; as first rock-typing attempt for the both formations. The sedimentological characterization of the Early Miocene Ghar formation is mainly comprised by successive buildups of sands-gravels and sandstones, whereas; the Middle Miocene Lower Fars formation is started by limestone, limestone-marly/marl anhydritic, upgraded into interbedded-series of marl and anhydrite facies, with less-common occurrences of thin-sandstone interlayers, terminated by marl-sandy-secti
... Show MoreThe university course timetable problem (UCTP) is typically a combinatorial optimization problem. Manually achieving a useful timetable requires many days of effort, and the results are still unsatisfactory. unsatisfactory. Various states of art methods (heuristic, meta-heuristic) are used to satisfactorily solve UCTP. However, these approaches typically represent the instance-specific solutions. The hyper-heuristic framework adequately addresses this complex problem. This research proposed Particle Swarm Optimizer-based Hyper Heuristic (HH PSO) to solve UCTP efficiently. PSO is used as a higher-level method that selects low-level heuristics (LLH) sequence which further generates an optimal solution. The proposed a
... Show MoreComplex-valued regular functions that are normalized in the open unit disk are vastly studied. The current study introduces a new fractional integrodifferential (non-linear) operator. Based on the pre-Schwarzian derivative, certain appropriate stipulations on the parameters included in this con-structed operator to be univalent and bounded are investigated and determined.
The present study was conducted to estimate the incidence, clinical findings, cytological and histopathological characteristics of spontaneously occurring skin neoplasms in dogs. A total of 40 grossly suspected cases of cutaneous and subcutaneous tumors were gathered during the period from July 2016 to August 2018 from male and female dogs in Baghdad city. Dogs with skin neoplasia revealed various clinical signs, and their ages were older than 5 years to 15 years. German shepherd 30% followed by Terrier dogs 25% were more influenced than other breeds. Concerning tumor features, the majority of neoplasms had solitary lesion 70%, regular shapes 65% with black color 55%. The tumors frequently occurred on fore-limbs and abdomen, and 80% of them
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