Alzheimer’s Disease (AD) is the most prevailing type of dementia. The prevalence of AD is estimated to be around 5% after 65 years old and is staggering 30% for more than 85 years old in developed countries. AD destroys brain cells causing people to lose their memory, mental functions and ability to continue daily activities. The findings of this study are likely to aid specialists in their decision-making process by using patients’ Magnetic Resonance Imaging (MRI) to distinguish patients with AD from Normal Control (NC). Performance evolution was applied to 346 Magnetic Resonance images from the Alzheimer's Neuroimaging Initiative (ADNI) collection. The Deep Belief Network (DBN) classifier was used to fulfill classification function. Weights were used to test the proposed method's recognition capacity, and the network was trained with a sample training set. As a result, this study offeres a new method for identifying Alzheimer's disease utilizing automated categorization. In tests, it performed admirably With 98.46% accuracy achieved for AD and NC studied classes when combining Gray Level Co-occurrence Matrix (GLCM) features with a DBN.
In this paper, we prove that our proposed localization algorithm named Improved
Accuracy Distribution localization for wireless sensor networks (IADLoc) [1] is the
best when it is compared with the other localization algorithms by introducing many
cases of studies. The IADLoc is used to minimize the error rate of localization
without any additional cost and minimum energy consumption and also
decentralized implementation. The IADLoc is a range free and also range based
localization algorithm that uses both type of antenna (directional and omnidirectional)
it allows sensors to determine their location based on the region of
intersection (ROI) when the beacon nodes send the information to the sink node and
the la
In this paper, we prove that our proposed localization algorithm named Improved
Accuracy Distribution localization for wireless sensor networks (IADLoc) [1] is the
best when it is compared with the other localization algorithms by introducing many
cases of studies. The IADLoc is used to minimize the error rate of localization
without any additional cost and minimum energy consumption and also
decentralized implementation. The IADLoc is a range free and also range based
localization algorithm that uses both type of antenna (directional and omnidirectional)
it allows sensors to determine their location based on the region of
intersection (ROI) when the beacon nodes send the information to the sink node and
the la
Deepfake is a type of artificial intelligence used to create convincing images, audio, and video hoaxes and it concerns celebrities and everyone because they are easy to manufacture. Deepfake are hard to recognize by people and current approaches, especially high-quality ones. As a defense against Deepfake techniques, various methods to detect Deepfake in images have been suggested. Most of them had limitations, like only working with one face in an image. The face has to be facing forward, with both eyes and the mouth open, depending on what part of the face they worked on. Other than that, a few focus on the impact of pre-processing steps on the detection accuracy of the models. This paper introduces a framework design focused on this asp
... Show MoreBroyden update is one of the one-rank updates which solves the unconstrained optimization problem but this update does not guarantee the positive definite and the symmetric property of Hessian matrix.
In this paper the guarantee of positive definite and symmetric property for the Hessian matrix will be established by updating the vector which represents the difference between the next gradient and the current gradient of the objective function assumed to be twice continuous and differentiable .Numerical results are reported to compare the proposed method with the Broyden method under standard problems.
The concept of sustainability is one of the modern concepts that influenced the quality of the urban plans for the cities, through the interest in the environmental and social aspects as well as the economic aspect and the need to balance to achieve sustainable development.
The research aims to identify the most prominent methods of sustainable urban land use planning and the strategies developed within these approaches to achieve sustainable development. The research started from the problem of a knowledge gap in adopting sustainable approaches and strategies when planning urban land uses for the holy city of Karbala.
In the theoretical aspect, the concepts of sustainable development, sustainable planning methodologies a
... Show MoreA study has been done to find the optimum separators pressures of separation stations. Stage separation of oil and gas is accomplished with a series of separators operating at sequentially reduced pressures. Liquid discharged from a higher pressure separator into the lower pressure separator. The set of working separators pressures which yield maximum recovery of liquid hydrocarbon from the well fluid is the optimum set of pressures which is the target of this work.
Computer model is used to find the optimum separators pressures. The model employs the Peng-Robinson equation of state for volatile oil. Application of this model shows good improvement of al
. Surface Plasmon Resonance (SPR) technology has been adapted to produce a sensitive optical sensor and Biosensor applications. Simulation analysis ( in Matlab) has been made for SPR for gold (Au) layer with thickness (40 nm) and Polyvinyl Alcohol (PVA) polymer with various thickness (10, 20, 30, 40, 50, 60, 70 and 80 nm) deposited on glass prism type D-ZLAF50_Dense lanthanum flint. The sensitive layer was air (n=1). The analysis was taken for different wavelengths from Ultra-Violet wavelength 100 nm to Near Infra- Red wavelength 1000 nm. The properties of θSPR have been calculated from plotted reflectance against incident angle θincid.. The SPR sensitivity (S) was calculated. The results give efficient detection in chan
... Show MoreAbstract
Characterized by the Ordinary Least Squares (OLS) on Maximum Likelihood for the greatest possible way that the exact moments are known , which means that it can be found, while the other method they are unknown, but approximations to their biases correct to 0(n-1) can be obtained by standard methods. In our research expressions for approximations to the biases of the ML estimators (the regression coefficients and scale parameter) for linear (type 1) Extreme Value Regression Model for Largest Values are presented by using the advanced approach depends on finding the first derivative, second and third.
In this work, we first construct Hermite wavelets on the interval [0,1) with it’s product, Operational matrix of integration 2^k M×2^k M is derived, and used it for solving nonlinear Variational problems with reduced it to a system of algebric equations and aid of direct method. Finally, some examples are given to illustrate the efficiency and performance of presented method.
The shell model calculations with Cohen-Kurath (C-K) interaction were carried out to investigate form factors of elastic transverse electron scattering, and magnetic dipole-moments of odd 7,9,11Be isotopes. The effect of the exact value of center of mass correction was adopted to generate the magnetic form factors in Born approximation picture. The contribution of the higher 2p-shell configuration was included to reproduce the experimental data. A significant improvement was obtained in the present results with core-polarization (CP) effect through the effective g-factors. The occupancies percentage with respect to the valence nucleons was also calculated.