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Full-Text Articles in Physical Sciences and Mathematics

Demonstration Of Visible And Near Infrared Raman Spectrometers And Improved Matched Filter Model For Analysis Of Combined Raman Signals, Alexander Matthew Atkinson Oct 2019

Demonstration Of Visible And Near Infrared Raman Spectrometers And Improved Matched Filter Model For Analysis Of Combined Raman Signals, Alexander Matthew Atkinson

Electrical & Computer Engineering Theses & Dissertations

Raman spectroscopy is a powerful analysis technique that has found applications in fields such as analytical chemistry, planetary sciences, and medical diagnostics. Recent studies have shown that analysis of Raman spectral profiles can be greatly assisted by use of computational models with achievements including high accuracy pure sample classification with imbalanced data sets and detection of ideal sample deviations for pharmaceutical quality control. The adoption of automated methods is a necessary step in streamlining the analysis process as Raman hardware becomes more advanced. Due to limits in the architectures of current machine learning based Raman classification models, transfer from pure …


Computational Analysis Of Antipode Algorithms For The Output Feedback Hopf Algebra, Lance Berlin Oct 2019

Computational Analysis Of Antipode Algorithms For The Output Feedback Hopf Algebra, Lance Berlin

Electrical & Computer Engineering Theses & Dissertations

The feedback interconnection of two systems written in terms of Chen-Fliess series can be described explicitly in terms of the antipode of the output feedback Hopf algebra. At present, there are three known computational approaches to calculating this antipode: the left coproduct method, the right coproduct method, and the derivation method. Each of these algorithms is defined recursively, and thus becomes computationally expensive quite quickly. This motivates the need for a more complete understanding of the algorithmic complexity of these methods, as well as the development of new approaches for determining the Hopf algebra antipode. The main goals of this …


Laser-Spark Multicharged Ion Implantation System ‒ Application In Ion Implantation And Neural Deposition Of Carbon In Nickel (111), Oguzhan Balki Oct 2019

Laser-Spark Multicharged Ion Implantation System ‒ Application In Ion Implantation And Neural Deposition Of Carbon In Nickel (111), Oguzhan Balki

Electrical & Computer Engineering Theses & Dissertations

Carbon ions generated by ablation of a carbon target using an Nd:YAG laser pulse (wavelength λ = 1064 nm, pulse width τ = 7 ns, and laser fluence of 10-110 J/cm2) are characterized. Time-of-flight analyzer, a three-mesh retarding field analyzer, and an electrostatic ion energy analyzer are used to study the charge and energy of carbon ions generated by laser ablation. The dependencies of the ion signal on the laser fluence, laser focal point position relative to target surface, and the acceleration voltage are described. Up to C4+ are observed. When no acceleration voltage is applied between …


Pulse Power Effects On Transient Plasma Ignition For Combustion, David Wayne Alderman Ii Oct 2019

Pulse Power Effects On Transient Plasma Ignition For Combustion, David Wayne Alderman Ii

Electrical & Computer Engineering Theses & Dissertations

Transient plasma ignition (TPI) uses highly non-equilibrium plasmas, driven by less than 100 nanosecond, high-voltage pulses, to initiate combustion. The effects of pulse repetition frequency (PRF) and ultrashort nanosecond rise times on TPI are investigated in this work using lean, stoichiometric, and rich air-fuel mixtures at atmospheric pressure. Experimental data show the transient plasmas driven by ultrashort rise time, high voltage pulses at high PRF’s enhance the combustion of lean or stoichiometric air-methane mixtures in a static chamber. In particular, increasing PRF enhances the combustion performance by means of reduced delay times independent of the equivalence ratio of the air-fuel …


Using Feature Extraction From Deep Convolutional Neural Networks For Pathological Image Analysis And Its Visual Interpretability, Wei-Wen Hsu Jul 2019

Using Feature Extraction From Deep Convolutional Neural Networks For Pathological Image Analysis And Its Visual Interpretability, Wei-Wen Hsu

Electrical & Computer Engineering Theses & Dissertations

This dissertation presents a computer-aided diagnosis (CAD) system using deep learning approaches for lesion detection and classification on whole-slide images (WSIs) with breast cancer. The deep features being distinguishing in classification from the convolutional neural networks (CNN) are demonstrated in this study to provide comprehensive interpretability for the proposed CAD system using the domain knowledge in pathology. In the experiment, a total of 186 slides of WSIs were collected and classified into three categories: Non-Carcinoma, Ductal Carcinoma in Situ (DCIS), and Invasive Ductal Carcinoma (IDC). Instead of conducting pixel-wise classification (segmentation) into three classes directly, a hierarchical framework with the …


Cyber Security- A New Secured Password Generation Algorithm With Graphical Authentication And Alphanumeric Passwords Along With Encryption, Akash Rao Apr 2019

Cyber Security- A New Secured Password Generation Algorithm With Graphical Authentication And Alphanumeric Passwords Along With Encryption, Akash Rao

Electrical & Computer Engineering Theses & Dissertations

Graphical passwords are always considered as an alternative of alphanumeric passwords for their better memorability and usability [1]. Alphanumeric passwords provide an adequate amount of satisfaction, but they do not offer better memorability compared to graphical passwords [1].

On the other hand, graphical passwords are considered less secured and provide better memorability [1]. Therefore many researchers have researched on graphical passwords to overcome the vulnerability. One of the most significant weaknesses of the graphical passwords is "Shoulder Surfing Attack," which means, sneaking into a victim's computer to learn the whole password or part of password or some confidential information. Such …


On Analytic Nonlinear Input-Output Systems: Expanded Global Convergence And System Interconnections, Irina M. Winter Arboleda Apr 2019

On Analytic Nonlinear Input-Output Systems: Expanded Global Convergence And System Interconnections, Irina M. Winter Arboleda

Electrical & Computer Engineering Theses & Dissertations

Functional series representations of nonlinear systems first appeared in engineering in the early 1950’s. One common representation of a nonlinear input-output system are Chen-Fliess series or Fliess operators. Such operators are described by functional series indexed by words over a noncommutative alphabet. They can be viewed as a noncommutative generalization of a Taylor series. A Fliess operator is said to be globally convergent when its radius of convergence is infinite, in other words, when there is no a priori upper bound on both the L1-norm of an admissible input and the length of time over which the corresponding output is …