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 study investigates the treatment of used lubricating oils from AL-Mussaib Gas Power Station Company-Iraq, which was treated with different extractive solvents (heptane and 2-propanol). The performance activity of these solvents in the extraction process was examined and evaluated experimentally. Operating parameters were solvent to oil ratios of (1:2, 1:4, 1:6, and 1:8), mixing time (20, 35, 50, and 65 min), temperatures (30, 40, 50, and 60 ºC), and mixing speed (500 rpm). These parameters were studied and analyzed. The quality is determined by the measuring and assessment of important characteristics specially viscosity, viscosity index, specific gravity, pour point, flash point, and ash content. The results confirm that the
... Show MoreThe aim of this essay is to use a single-index model in developing and adjusting Fama-MacBeth. Penalized smoothing spline regression technique (SIMPLS) foresaw this adjustment. Two generalized cross-validation techniques, Generalized Cross Validation Grid (GGCV) and Generalized Cross Validation Fast (FGCV), anticipated the regular value of smoothing covered under this technique. Due to the two-steps nature of the Fama-MacBeth model, this estimation generated four estimates: SIMPLS(FGCV) - SIMPLS(FGCV), SIMPLS(FGCV) - SIM PLS(GGCV), SIMPLS(GGCV) - SIMPLS(FGCV), SIM PLS(GGCV) - SIM PLS(GGCV). Three-factor Fama-French model—market risk premium, size factor, value factor, and their implication for excess stock returns and portfolio return
... Show MoreResearchers employ behavior based malware detection models that depend on API tracking and analyzing features to identify suspected PE applications. Those malware behavior models become more efficient than the signature based malware detection systems for detecting unknown malwares. This is because a simple polymorphic or metamorphic malware can defeat signature based detection systems easily. The growing number of computer malwares and the detection of malware have been the concern for security researchers for a large period of time. The use of logic formulae to model the malware behaviors is one of the most encouraging recent developments in malware research, which provides alternatives to classic virus detection methods. To address the l
... Show MoreIn modern technology, the ownership of electronic data is the key to securing their privacy and identity from any trace or interference. Therefore, a new identity management system called Digital Identity Management, implemented throughout recent years, acts as a holder of the identity data to maintain the holder’s privacy and prevent identity theft. Therefore, an overwhelming number of users have two major problems, users who own data and third-party applications will handle it, and users who have no ownership of their data. Maintaining these identities will be a challenge these days. This paper proposes a system that solves the problem using blockchain technology for Digital Identity Management systems. Blockchain is a powerful techniqu
... Show MoreThe steganography (text in image hiding) methods still considered important issues to the researchers at the present time. The steganography methods were varied in its hiding styles from a simple to complex techniques that are resistant to potential attacks. In current research the attack on the host's secret text problem didn’t considered, but an improved text hiding within the image have highly confidential was proposed and implemented companied with a strong password method, so as to ensure no change will be made in the pixel values of the host image after text hiding. The phrase “highly confidential” denoted to the low suspicious it has been performed may be found in the covered image. The Experimental results show that the covere
... Show MoreThe refractive index sensors based on tapered optical fiber are attractive for many industries due to sensing capability in a variety of application. In this paper, we proposed a refractive index sensor based on multicore fiber (MCF) sandwiched between two standard single mode fibers (SMF). The sensor consisting of three sections, SMF- MCF-SMF is structurally simple and can be easily produced by joining these parts. The MFC contains seven cores and these cores are surrounded by a single cladding. The sensing region is obtained by tapering the MCF section where the evanescent field is generated. The single mode propagating along the SMF is stimulated at the first joint and is coupled to the cladding modes. These modes interfere with the core
... Show MoreAPDBN Rashid, International Journal of Humanities and Social Sciences/ RIMAK, 2023