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Full-Text Articles in Physical Sciences and Mathematics

Spatiotemporal Subspace Feature Tracking By Mining Discriminatory Characteristics, Richard D. Appiah Oct 2017

Spatiotemporal Subspace Feature Tracking By Mining Discriminatory Characteristics, Richard D. Appiah

Doctoral Dissertations

Recent advancements in data collection technologies have made it possible to collect heterogeneous data at complex levels of abstraction, and at an alarming pace and volume. Data mining, and most recently data science seek to discover hidden patterns and insights from these data by employing a variety of knowledge discovery techniques. At the core of these techniques is the selection and use of features, variables or properties upon which the data were acquired to facilitate effective data modeling. Selecting relevant features in data modeling is critical to ensure an overall model accuracy and optimal predictive performance of future effects. The …


Understanding The Surface Fouling Mechanism Of Ultrananocrystalline Diamond Microelectrodes Using Microfluidics For Neurochemical Detection, An-Yi Chang Jul 2017

Understanding The Surface Fouling Mechanism Of Ultrananocrystalline Diamond Microelectrodes Using Microfluidics For Neurochemical Detection, An-Yi Chang

Doctoral Dissertations

Electrochemical methods are widely used for chronic neurochemical sensing, but thus far, the organic solution redox reactions fouled the electrodes' surface. It caused the reduction of sensitivity and the electrodes' lifetime.

Here, we present the boron-doped nanocrystalline diamond microelectrodes (BDUNCD) as the next generation electrode material for neurochemical sensor development. To aid in long-term chronic monitoring of neurochemicals, they have a wide window of electrochemical potential, extremely low background current, and excellent chemical inertness. The main research goal is to reduce the rate of electrode fouling due to the reaction by-products, and significantly extend their useful lifetime.

We systematically characterize …


Electrochemical Behavior Of Dense Electrodes For Impedancemetric Nox Sensors, Nabamita Pal Jul 2017

Electrochemical Behavior Of Dense Electrodes For Impedancemetric Nox Sensors, Nabamita Pal

Doctoral Dissertations

NOx (NO and NO2) exhaust gas sensors for diesel powered vehicles have traditionally consisted of porous platinum (Pt) electrodes along with a dense ZrO2 based electrolyte. Advancement in diesel engine technology results in lower NOx emissions. Although Pt is chemically and mechanically tolerant to the extreme exhaust gas environment, it is also a strong catalyst for oxygen reduction, which can interfere with the detection of NOx at concentrations below 100 ppm. Countering this behavior can add to the complexity and cost of the conventional NO x sensor design. Recent studies have shown that dense electrodes are less prone to heterogeneous …


Full Simulation For The Qweak Experiment At 1.16 And 0.877 Gev And Their Impact On Extracting The Pv Asymmetry In The N→Δ A Transition, Hend Abdullah Nuhait Jul 2017

Full Simulation For The Qweak Experiment At 1.16 And 0.877 Gev And Their Impact On Extracting The Pv Asymmetry In The N→Δ A Transition, Hend Abdullah Nuhait

Doctoral Dissertations

The Qweak project is seeking to find new physics beyond the Standard Model. It is aimed to measure the weak charge of the proton, which has never been measured, at 4% precision at low momentum transfer. The experiment is performed by scattering electrons from protons and exploiting parity violation in the weak interaction at low four-momentum transfer.

In this experiment, two measurements were considered: which are elastic and inelastic. The elastic is to measure the proton's weak charge. In addition, the inelastic asymmetry measurement, which will extract the low energy constant dΔ. That measurement works in the neutral current …


Motion-Capture-Based Hand Gesture Recognition For Computing And Control, Andrew Gardner Jul 2017

Motion-Capture-Based Hand Gesture Recognition For Computing And Control, Andrew Gardner

Doctoral Dissertations

This dissertation focuses on the study and development of algorithms that enable the analysis and recognition of hand gestures in a motion capture environment. Central to this work is the study of unlabeled point sets in a more abstract sense. Evaluations of proposed methods focus on examining their generalization to users not encountered during system training.

In an initial exploratory study, we compare various classification algorithms based upon multiple interpretations and feature transformations of point sets, including those based upon aggregate features (e.g. mean) and a pseudo-rasterization of the capture space. We find aggregate feature classifiers to be balanced across …


Synthesis, Characterization, And Activity Of Co/Fe Alumina/Silica Supported Ft Catalysts And The Study Of Promoter Effect Of Ruthenium, Sunday Azubike Esumike Jan 2017

Synthesis, Characterization, And Activity Of Co/Fe Alumina/Silica Supported Ft Catalysts And The Study Of Promoter Effect Of Ruthenium, Sunday Azubike Esumike

Doctoral Dissertations

The alumina and hybrid alumina-silica FT catalyst were prepared by one-step solgel/oil-drop methods using metal-nitrate-solutions (method-I), and nanoparticle-metaloxides (method-2). The nanoparticle-metal-oxides did not participate in solubility equilibria in contrast to metal nitrate in method-1 causing no metal ion seepage; therefore, method-2 yields higher XRF metal loading efficiency than method-1. The thermal analysis confirmed that the metal loading by method-1 and method-2 involved two different pathways. Method-1 involves solubility equilibria in the conversion of metal-nitrate to metal- hydroxide and finally to metal-oxide, while in method-2 nanoparticle-metal-oxide remained intact during sol-gel-oil-drop and calcination steps.

The alumina supported catalysts were dominated by γ-alumina …


A Study Of Mathematics Achievement, Placement, And Graduation Of Engineering Students, Sara Hahler Blazek Jan 2017

A Study Of Mathematics Achievement, Placement, And Graduation Of Engineering Students, Sara Hahler Blazek

Doctoral Dissertations

The purpose of this study was to determine how background knowledge impacts freshmen engineering students' success at Louisiana Tech University in terms of grades in two different freshman classes and graduation. To determine what factors impact students, three different studies were implemented. The first study used linear regression to analyze which demographic and academic variables significantly impacted freshman math and engineering courses. Using regression discontinuity, the second study determined if the university's placement requirement for Pre-Calculus was appropriate. The final study analyzed factors that impact graduation for engineering students as well as other disciplines to determine which significant variables were …


Anxiolytic Effects Of Propranolol And Diphenoxylate On Mice And Automated Stretch-Attend Posture Analysis, Kevin Scott Holly Oct 2016

Anxiolytic Effects Of Propranolol And Diphenoxylate On Mice And Automated Stretch-Attend Posture Analysis, Kevin Scott Holly

Doctoral Dissertations

The prevention of social anxiety, performance anxiety, and social phobia via the combination of two generic drugs, diphenoxylate HC1 (opioid) plus atropine sulfate (anticholinergic) and propranolol HCl (beta blocker) was evaluated in mice through behavioral studies. A patent published on a September 8, 2011 by Benjamin D. Holly, US 2011/0218215 Al, prompted the research. The drug combination of diphenoxylate and atropine plus propranolol could be an immediate treatment for patients suffering from acute phobic and social anxiety disorders. Demonstrating the anxiolytic effects of the treatment on mice would validate a mouse model for neuroscientist to be used to detect the …


Generalized Partial Directed Coherence And Centrality Measures In Brain Networks For Epileptogenic Focus Localization, Joshua Aaron Adkinson Oct 2016

Generalized Partial Directed Coherence And Centrality Measures In Brain Networks For Epileptogenic Focus Localization, Joshua Aaron Adkinson

Doctoral Dissertations

Accurate epileptogenic focus localization is required prior to surgical resection of brain tissue for treatment of patients with intractable temporal lobe epilepsy, a clinical need that is partially fulfilled to date through a subjective, and at times inconclusive, evaluation of the recorded electroencephalogram (EEG). Using brain connectivity analysis, patterns of causal interactions between brain regions were derived from multichannel EEG of 127 seizures in nine patients with focal, temporal lobe epilepsy (TLE). The statistically significant directed interactions in the reconstructed brain networks were estimated from three second intracranial multi-electrode EEG segments using the Generalized Partial Directed Coherence (GPDC) and validated …


Thermal Analysis In A Triple-Layered Skin Structure With Embedded Vasculature, Tumor, And Gold Nanoshells, Casey O. Orndorff Jul 2016

Thermal Analysis In A Triple-Layered Skin Structure With Embedded Vasculature, Tumor, And Gold Nanoshells, Casey O. Orndorff

Doctoral Dissertations

In hyperthermia skin cancer treatment, the objective is to control laser heating of the tumor (target temperatures of 42-46 °C) so that the temperatures of the normal tissue surrounding the tumor remains low enough not to damage the normal tissue. However, obtaining accurate temperature distributions in living tissue related to hyperthermia skin cancer treatment without using an intruding sensor is a challenge. The objective of this dissertation research is to develop a mathematical model that can accurately predict the temperature distribution in the tumor region and surrounding normal tissue induced by laser irradiation. The model is based on a modified …


Computational Micro-Flow With Spectral Element Method And High Reynolds Number Flow With Discontinuous Galerkin Finite Element Method, Haibo Zhang Jul 2016

Computational Micro-Flow With Spectral Element Method And High Reynolds Number Flow With Discontinuous Galerkin Finite Element Method, Haibo Zhang

Doctoral Dissertations

In this dissertation, two numerical methods with high order accuracy, Spectral Element Method (SEM) and Discontinuous Galerkin Finite Element Method (DG-FEM), are chosen to solve problems in Computational Fluid Dynamics (CFD). The merits of these two methods will be discussed and utilized in different kinds of CFD problems. The simulations of the micro-flow systems with complex geometries and physical applications will be presented by SEM. Moreover, the numerical solutions for the Hyperbolic Flow will be obtained by DG-FEM. By solving problems with these two methods, the differences between them will be discussed as well.

Compressible Navier-Stokes equations with Electro-osmosis body …


Experimental Investigation And Numerical Simulation Of A Copper Micro-Channel Heat Exchanger With Hfe-7200 Working Fluid, Eric Borquist Jul 2016

Experimental Investigation And Numerical Simulation Of A Copper Micro-Channel Heat Exchanger With Hfe-7200 Working Fluid, Eric Borquist

Doctoral Dissertations

Ever increasing cost and consumption of global energy resources has inspired the development of energy harvesting techniques which increase system efficiency, sustainability, and environmental impact by using waste energy otherwise lost to the surroundings. As part of a larger effort to produce a multi-energy source prototype, this study focused on the fabrication and testing of a waste heat recovery micro-channel heat exchanger. Reducing cost and facility requirements were a priority for potential industry and commercial adoption of such energy harvesting devices. During development of the micro-channel heat exchanger, a new fabrication process using mature technologies was created that reduced cost, …


Mutlifunctional Platforms For Gene And Drug Delivery For Cancer Therapy, Jeffery J. Ambrose Jr. Apr 2016

Mutlifunctional Platforms For Gene And Drug Delivery For Cancer Therapy, Jeffery J. Ambrose Jr.

Doctoral Dissertations

The National Cancer Institute and the American Cancer Society estimate that 1.6 million new cancer incidences and over half a million cancer related deaths occur annually [1][2]. Cancer the second most common cause of death in the United States [1], [2]. Although the causes of cancer can vary depending on cell type, all or almost all instances of cancer arise from a mutation or from an abnormal activation of the cellular genes that control cell growth and mitosis [3].

Treatment of a given cancer type depends on the subtype, stage and progression of the cancer. Varieties of cancer therapy include …


Tunable Controlled Release Of Molecular Species From Halloysite Nanotubes, Divya Narayan Elumalai Apr 2016

Tunable Controlled Release Of Molecular Species From Halloysite Nanotubes, Divya Narayan Elumalai

Doctoral Dissertations

Encouraged by potential applications in rust coatings, self-healing composites, selective delivery of drugs, and catalysis, the transport of molecular species through Halloysite nanotubes (HNTs), specifically the storage and controlled release of these molecules, has attracted strong interest in recent years. HNTs are a naturally occurring biocompatible nanomaterial that are abundantly and readily available. They are alumosilicate based tubular clay nanotubes with an inner lumen of 15 nm and a length of 600-900 nm. The size of the inner lumen of HNTs may be adjusted by etching. The lumen can be loaded with functional agents like antioxidants, anticorrosion agents, flame-retardant agents, …


Sensitivity Of Mixed Models To Computational Algorithms Of Time Series Data, Gunaime Nevine Apr 2015

Sensitivity Of Mixed Models To Computational Algorithms Of Time Series Data, Gunaime Nevine

Doctoral Dissertations

Statistical analysis is influenced by implementation of the algorithms used to execute the computations associated with various statistical techniques. Over many years; very important criteria for model comparison has been studied and examined, and two algorithms on a single dataset have been performed numerous times. The goal of this research is not comparing two or more models on one dataset, but comparing models with numerical algorithms that have been used to solve them on the same dataset.

In this research, different models have been broadly applied in modeling and their contrasting which are affected by the numerical algorithms in different …


Performance Modeling And Optimization Techniques For Heterogeneous Computing, Supada Laosooksathit Jan 2014

Performance Modeling And Optimization Techniques For Heterogeneous Computing, Supada Laosooksathit

Doctoral Dissertations

Since Graphics Processing Units (CPUs) have increasingly gained popularity amoung non-graphic and computational applications, known as General-Purpose computation on GPU (GPGPU), CPUs have been deployed in many clusters, including the world's fastest supercomputer. However, to make the most efficiency from a GPU system, one should consider both performance and reliability of the system.

This dissertation makes four major contributions. First, the two-level checkpoint/restart protocol that aims to reduce the checkpoint and recovery costs with a latency hiding strategy in a system between a CPU (Central Processing Unit) and a GPU is proposed. The experimental results and analysis reveals some benefits, …


Vulnerability Analysis Of Cyber-Behavioral Biometric Authentication, Abdul Serwadda Jan 2014

Vulnerability Analysis Of Cyber-Behavioral Biometric Authentication, Abdul Serwadda

Doctoral Dissertations

Research on cyber-behavioral biometric authentication has traditionally assumed naïve (or zero-effort) impostors who make no attempt to generate sophisticated forgeries of biometric samples. Given the plethora of adversarial technologies on the Internet, it is questionable as to whether the zero-effort threat model provides a realistic estimate of how these authentication systems would perform in the wake of adversity. To better evaluate the efficiency of these authentication systems, there is need for research on algorithmic attacks which simulate the state-of-the-art threats.

To tackle this problem, we took the case of keystroke and touch-based authentication and developed a new family of algorithmic …


Modeling And Control Of Nanoparticle Bloodstream Concentration For Cancer Therapies, Scarlett S. Bracey Oct 2013

Modeling And Control Of Nanoparticle Bloodstream Concentration For Cancer Therapies, Scarlett S. Bracey

Doctoral Dissertations

Currently, the most commonly used treatments for cancerous tumors (chemotherapy, radiation, etc.) have almost no method of monitoring the administration of the treatment for adverse effects in real time. Without any real time feedback or control, treatment becomes a "guess and check" method with no way of predicting the effects of the drugs based on the actual bioavailability to the patient's body. One particular drug may be effective for one patient, yet provide no benefit to another. Doctors and scientists do not routinely attempt to quantifiably explain this discrepancy. In this work, mathematical modeling and analysis techniques are joined together …


A Mathematical Model And Numerical Method For Thermoelectric Dna Sequencing, Liwei Shi Jul 2013

A Mathematical Model And Numerical Method For Thermoelectric Dna Sequencing, Liwei Shi

Doctoral Dissertations

DNA sequencing is the process of determining the precise order of nucleotide bases, adenine, guanine, cytosine, and thymine within a DNA molecule. It includes any method or technology that is used to determine the order of the four bases in a strand of DNA. The advent of rapid DNA sequencing methods has greatly accelerated biological and medical research and discovery. Thermoelectric DNA sequencing is a novel method to sequence DNA by measuring the heat that is released when DNA polymerase inserts a deoxyribonucleoside triphosphate into a growing DNA strand. The thermoelectric device for this project is composed of four parts: …


A Novel Microfluidic Enrichment Technique For Carbonylated Proteins, Bryant C. Hollins Oct 2012

A Novel Microfluidic Enrichment Technique For Carbonylated Proteins, Bryant C. Hollins

Doctoral Dissertations

Proteins are the building blocks of cells in living organisms, and are composed of amino acids. The expression of proteins is regulated by the processes of transcription and translation. Proteins undergo post-translational modifications in order to dictate their role physiologically within a cell.

Not all post-translational modifications are beneficial for the protein or the cell. One type of post-translational modification, called carbonylation, irreversibly places a carbonyl group onto an amino acid residue, most commonly proline, lysine, arginine, and threonine. This modification can have severe consequences physiologically, including loss of solubility, loss of function, and protein aggregation.

Carbonylated proteins have commonly …


Machine Learning Approaches For Determining Effective Seeds For K -Means Algorithm, Kaveephong Lertwachara Apr 2003

Machine Learning Approaches For Determining Effective Seeds For K -Means Algorithm, Kaveephong Lertwachara

Doctoral Dissertations

In this study, I investigate and conduct an experiment on two-stage clustering procedures, hybrid models in simulated environments where conditions such as collinearity problems and cluster structures are controlled, and in real-life problems where conditions are not controlled. The first hybrid model (NK) is an integration between a neural network (NN) and the k-means algorithm (KM) where NN screens seeds and passes them to KM. The second hybrid (GK) uses a genetic algorithm (GA) instead of the neural network. Both NN and GA used in this study are in their simplest-possible forms.

In the simulated data sets, I investigate two …


Modular Machine Learning Methods For Computer-Aided Diagnosis Of Breast Cancer, Mia Kathleen Markey '94 Jun 2002

Modular Machine Learning Methods For Computer-Aided Diagnosis Of Breast Cancer, Mia Kathleen Markey '94

Doctoral Dissertations

The purpose of this study was to improve breast cancer diagnosis by reducing the number of benign biopsies performed. To this end, we investigated modular and ensemble systems of machine learning methods for computer-aided diagnosis (CAD) of breast cancer. A modular system partitions the input space into smaller domains, each of which is handled by a local model. An ensemble system uses multiple models for the same cases and combines the models' predictions.

Five supervised machine learning techniques (LDA, SVM, BP-ANN, CBR, CART) were trained to predict the biopsy outcome from mammographic findings (BIRADS™) and patient age based on a …


Asp -Pricing: A Black -Scholes Option Pricing Formulation, Chaitanya Singh Apr 2002

Asp -Pricing: A Black -Scholes Option Pricing Formulation, Chaitanya Singh

Doctoral Dissertations

The Applications Service Provider (ASP) arrangement has engendered a revolution in the area of corporate information technology (IT) by transforming software from a packaged off-the-shelf product to an on-line virtual service.

The focus of this study is to establish a sound mathematical foundation for evaluating software rental agreements (embedding exit flexibility) by incorporating a real options framework (based upon the Black-Scholes approach) into the traditional capital budgeting technique. The static discounted cash flow or net present value analysis may not adequately serve as a ‘barometer’ of outsourcing value due to its inherent weaknesses. On the other hand, the options approach …


Fluid Flow In Micro-Channels: A Stochastic Approach, Hilda Marino Black Jul 2000

Fluid Flow In Micro-Channels: A Stochastic Approach, Hilda Marino Black

Doctoral Dissertations

In this study free molecular flow in a micro-channel was modeled using a stochastic approach, namely the Kolmogorov forward equation in three dimensions. Model equations were discretized using Central Difference and Backward Difference methods and solved using the Jacobi method. Parameters were used that reflect the characteristic geometry of experimental work performed at the Louisiana Tech University Institute for Micromanufacturing.

The solution to the model equations provided the probability density function of the distance traveled by a particle in the micro-channel. From this distribution we obtained the distribution of the residence time of a particle in the micro-channel. Knowledge of …


A Hybrid Finite Element-Finite Difference Method For Thermal Analysis In A Double-Layered Thin Film, Teng Zhu Apr 2000

A Hybrid Finite Element-Finite Difference Method For Thermal Analysis In A Double-Layered Thin Film, Teng Zhu

Doctoral Dissertations

Thin film technology is of vital importance in microtechnology applications. For instance, thin films of metals, of dielectrics such as SiO2, or Si semiconductors are important components of microelectronic devices. The reduction of the device size to the microscale has the advantage of enhancing the switching speed of the device. The reduction, on the other hand, increases the rate of heat generation that leads to a high thermal load on the microdevice. Heat transfer at the microscale with an ultrafast pulsed-laser is also a very important process for thin films. Hence, studying the thermal behavior of thin films or of …


Bottom-Up Design Of Artificial Neural Network For Single-Lead Electrocardiogram Beat And Rhythm Classification, Srikanth Thiagarajan Jan 2000

Bottom-Up Design Of Artificial Neural Network For Single-Lead Electrocardiogram Beat And Rhythm Classification, Srikanth Thiagarajan

Doctoral Dissertations

Performance improvement in computerized Electrocardiogram (ECG) classification is vital to improve reliability in this life-saving technology. The non-linearly overlapping nature of the ECG classification task prevents the statistical and the syntactic procedures from reaching the maximum performance. A new approach, a neural network-based classification scheme, has been implemented in clinical ECG problems with much success. The focus, however, has been on narrow clinical problem domains and the implementations lacked engineering precision. An optimal utilization of frequency information was missing. This dissertation attempts to improve the accuracy of neural network-based single-lead (lead-II) ECG beat and rhythm classification. A bottom-up approach defined …