3,640 research outputs found
Detection of Alzheimer's Disease using MRI scans based on Inertia Tensor and Machine Learning
Alzheimer's Disease is a devastating neurological disorder that is
increasingly affecting the elderly population. Early and accurate detection of
Alzheimer's is crucial for providing effective treatment and support for
patients and their families. In this study, we present a novel approach for
detecting four different stages of Alzheimer's disease from MRI scan images
based on inertia tensor analysis and machine learning. From each available MRI
scan image for different classes of Dementia, we first compute a very simple 2
x 2 matrix, using the techniques of forming a moment of inertia tensor, which
is largely used in different physical problems. Using the properties of the
obtained inertia tensor and their eigenvalues, along with some other machine
learning techniques, we were able to significantly classify the different types
of Dementia. This process provides a new and unique approach to identifying and
classifying different types of images using machine learning, with a
classification accuracy of (90%) achieved. Our proposed method not only has the
potential to be more cost-effective than current methods but also provides a
new physical insight into the disease by reducing the dimension of the image
matrix. The results of our study highlight the potential of this approach for
advancing the field of Alzheimer's disease detection and improving patient
outcomes
Modeling the Field Emission Current Fluctuation in Carbon Nanotube Thin Films
Owing to their distinct properties, carbon nanotubes (CNTs) have emerged as
promising candidate for field emission devices. It has been found
experimentally that the results related to the field emission performance show
variability. The design of an efficient field emitting device requires the
analysis of the variabilities with a systematic and multiphysics based modeling
approach. In this paper, we develop a model of randomly oriented CNTs in a thin
film by coupling the field emission phenomena, the electron-phonon transport
and the mechanics of single isolated CNT. A computational scheme is developed
by which the states of CNTs are updated in time incremental manner. The device
current is calculated by using Fowler-Nordheim equation for field emission to
study the performance at the device scale.Comment: 4 pages, 5 figure
Texture Segmentation Using Gabor Filters and Wavelets
The present work deals with image segmentation which results in the subdivision of an image into its constituent regions or objects. The result of image segmentation is a set of segments that collectively cover the entire image or a set of contours extracted from the image. Each of the pixels in a region are similar with respect to some characteristic or computed property, such as color, intensity or texture. Specifically this project deals with texture segmentation of an image to find out the different types of textures present in the image.
In this project different type of procedures have been followed to carry out texture segmentation. Procedures starting from fundamental filter transforms till multi-resolution technique using wavelet transform have been considered. Many texture-segmentation schemes are based on a filter-bank model, where the filters called Gabor filters are derived from Gabor elementary functions. Both linear and circular Gabor filters are studied and analyzed in this aspect and how these filters are better in comparison to linear filters is also analyzed. Different types of wavelet transform techniques like Haar transform, S transform, etc. are followed and their performance regarding texture segmentation is being studied
HyBIS: Windows Guest Protection through Advanced Memory Introspection
Effectively protecting the Windows OS is a challenging task, since most
implementation details are not publicly known. Windows has always been the main
target of malwares that have exploited numerous bugs and vulnerabilities.
Recent trusted boot and additional integrity checks have rendered the Windows
OS less vulnerable to kernel-level rootkits. Nevertheless, guest Windows
Virtual Machines are becoming an increasingly interesting attack target. In
this work we introduce and analyze a novel Hypervisor-Based Introspection
System (HyBIS) we developed for protecting Windows OSes from malware and
rootkits. The HyBIS architecture is motivated and detailed, while targeted
experimental results show its effectiveness. Comparison with related work
highlights main HyBIS advantages such as: effective semantic introspection,
support for 64-bit architectures and for latest Windows (8.x and 10), advanced
malware disabling capabilities. We believe the research effort reported here
will pave the way to further advances in the security of Windows OSes
Dynamical Symmetry Breaking by SU(2) Gauge Bosons
This work explores the possibility of obtaining a mass gap in Yang-Mills
theories via the intrinsic gauge bosons, without invoking a separate Higgs
boson or fermion-antifermion pairs. Instead, pairs of gauge bosons in the spin
and isospin singlet state form a pair of composite Higgs bosons which can be
viewed as the simplest possible glueball of Yang-Mills gauge theories.
Quadratic and quartic gauge boson self-interactions form a potential that leads
to a finite expectation value of the gauge boson amplitude. Transverse
polarization ensures Lorentz invariance of the vacuum after averaging over all
possible polarization vectors. But the scalar pair products exhibit a finite
vacuum expectation value which breaks the gauge symmetry dynamically.
Compatibility with the standard Higgs potential determines the quadratic and
quartic coupling constants.Comment: 17 pages, 2 figures. Versions 2,3: added Ref. [15], augmented
Appendix B, clarified the text. Versions 4,5: added Eq. (35) + text (formula
for g), generalized Eq. (B17) + tex
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