Digital Commons Network^™

Statistical Approaches For Signal Processing With Application To Automatic Singer Identification, Shiteng Yang

Theses

In the music world, the oldest instrument is known as the singing voice that plays an important role in musical recordings. The singer's identity serves as a primary aid for people to organize, browse, and retrieve music recordings. In this thesis, we focus on the problem of singer identification based on the acoustic features of singing voice. An automatic singer identification system is constructed and has achieved a very high identification accuracy. This system consists of three crucial parts: singing voice detection, background music removal and pattern recognition. These parts are introduced and explored in great details in this thesis. …

Energy Dispersion Model Using Tight Binding Theory, Divya S. Vajpey

Theses

2-D Semiconductors are novel materials in the field of nano-electronics. Their unusual transport properties have led to an extensive research attention towards similar materials. Graphene has carriers that exhibit an effective "speed of light" (106 m/s) in the low energy range of

This research proposes to achieve a common energy dispersion model for different hybridized structures, using tight binding theory. The goal is to achieve a suitable starting point to obtain practical electronic transport calculations for complex atomic structures. We begin with analyzing the electronic properties by obtaining the analytic solution of the wave function, from the Schrödinger equation. We …

A New Wifi Based Covert Channel Using 802.11 Physical Layer Properties, Vikrant D. Waghmode

Theses

In this project we designed and implemented a covert channel that uses wireless signal strength to leak information. This covert channel encodes information by fluctuating wireless signal strength. This can be achieved by applying different levels of transmission power to the transmission source. We have also provided some quantitative analysis of this channel by analyzing the wireless signal strength fluctuations in different environmental conditions to support this theory. Further, we discuss a scenario about how this can be implemented along with some limitations and challenges involved in the implementation of this covert channel. Finally, we devise a working demo to …

Performance And Degradation Analysis Of Operating Pv Systems, Felipe Da Silva Freire

Theses

The environmental concerns together with the decrease in technology cost lead the solar market to growth rapidly along the last decade. The photovoltaic (PV) systems are one of the solar energy alternatives and the silicon solar cells are currently the most widespread technology. Photovoltaic (PV) modules are considered the most reliable component of a photovoltaic system. The reliability and lifetime depends on the modules energy conversion performance and degradation modes. The analysis of monitoring data give insights about the PV system performance along its service time. The comparison between this data and mathematical models configure a way to predict the …

Propagation Of Sensor Noise In Navigation Equations And High Accuracy Dynamic Calibration Of Sensors, Timothy A. Nichols

Theses

Accurate navigation in GPS denied locations is extremely hard to achieve. Inertial Navigation Systems (INS) are currently the only reasonable onboard alternative to GPS but INS has error terms that grow very quickly. Even current high-end INSs have an error exceeding one km after only ten minutes of use. A high-accuracy INS would be very useful in underwater applications, spacecraft and extraterrestrial rovers, and military applications. This thesis seeks to enable such Inertial Navigation Systems.

Cyclotomic Polynomials In Ring-Lwe Homomorphic Encryption Schemes, Tamalika Mukherjee

Theses

Homomorphic Encryption has been considered the 'Holy Grail of Cryptography' since the discovery of secure public key cryptography in the 1970s. In 2009, a long-standing question about whether fully homomorphic encryption is theoretically plausible was affirmatively answered by Craig Gentry and his bootstrapping construction. Gentry's breakthrough has initiated a surge of new research in this area, one of the most promising ideas being the Learning With Errors (LWE) problem posed by Oded Regev's. Although this problem has proved to be versatile as a basis for homomorphic encryption schemes, the large key sizes result in a quadratic overhead making this inefficient …

Prediction Of The Frictional Characteristics Of Halogen-Free Ionic Liquids In Elastohydrodynamic Point Contacts., Karthik Janardhanan

Theses

Ionic Liquids have emerged as effective lubricants and additives to lubricants, in the last decade. Halogen-free ionic liquids have recently started to be considered as more environmentally stable than their halogenated counterparts, which tend to form highly toxic and corrosive acids when exposed to moisture. Most of the studies using ionic liquids as lubricants or additives of lubricants have been done experimentally. Due to the complex nature of the lubrication mechanism of these ordered fluids, the development of a theoretical model that predicts the ionic liquid lubrication ability is currently incomplete. In this study, a suitable and existing friction model …

Data Analytics With Mapreduce In Apache Spark And Hadoop Systems, Zongxuan Du

Theses

MapReduce comes from a traditional problem solving method: separating a big problem and solving each small parts. With the target of computing larger dataset in more efficient and cheaper way, this is implement into a programming mode to deal with massive quantity of data. The users get a map function and use it to abstract dataset into key / value logical pair and then use a reduce function to group all value with the same key. With this mode, task can be automatic spread the job into clusters grouped by lots of normal computers. MapReduce program can be easily implemented …

Gene Network Understanding And Analysis, Maria E. Somoza

Theses

Gene regulatory network (GRN) is a collection of regulators that interact with each other in the cell to govern the gene expression levels of mRNA and proteins. These regulators can either be DNA, RNA, protein and their complex. Transcriptional gene regulation is an important mechanisms in which an in-depth study can lead to various practical applications, and a greater understanding of how organisms control their cellular behavior. One of the most widely studied organisms in gene regulatory networks are the Mycobacterium tuberculosis and Corynebacterium glutamicum ATCC 13032.

Gene co-expression networks are of biological interests due to co-expressed genes which are …

Simulation Of A Low Voltage Customer Microgrid Using Petri Nets, Joshua Mark

Theses

With renewable energy coming to the forefront of how power is generated and delivered to the modern consumer, Microgrids are emerging as an optimal and efficient method for implementing renewables and changing the infrastructure of the dated transmission and distribution grid. This thesis work presents mathematical models of Petri Nets for the simulation of a low voltage customer Microgrid. Using previous work created in this specific field, a Hybrid Petri Net is modified such that it consists of multiple distributed generators, storage, and the utility which is referred to as the main distribution grid in this thesis. A Discrete Petri …

Semi Supervised Weighted Maximum Variance Dimensionality Reduction, Pranitha Surya Andalam

Theses

In the recent years, we have huge amounts of data which we want to classify with minimal human intervention. Only few features from the data that is available might be useful in some scenarios. In those scenarios, the dimensionality reduction methods play a major role for extracting useful features. The two parameter weighted maximum variance (2P-WMV) is a generalized dimensionality reduction method of which principal component analysis (PCA) and maximum margin criterion (MMC) are special cases.. In this paper, we have extended the 2P-WMV approach from our previous work to a semi-supervised version. The objective of this work is specially …

Multisensory Integration In Weakly Electric Fish, Andrea Roeser

Theses

Animals integrate information from across sensory systems, such as vision and hearing, to improve perception. To understand how neural circuits in the central nervous system integrate information from different senses, the responses of midbrain neurons to two categories of electrosensory stimuli in Eigenmannia virescens were studied. The first category of stimulus is electrical signals with frequencies below 50 Hz that are encoded in the activity of ampullary receptors. The second category is amplitude modulations of the electric organ discharge, which are encoded by p-type tuberous receptors. Six multisensory neurons were found that responded to both categories of stimuli. However, when …

A Computational Model For Transdermal Diffusion Of Lidocaine And Tetracaine Topical Patches, Qian Dong

Theses

In recent years, transdermal drug delivery patches (TDDP) have developed rapidly. This is because the TDD system has more advantages than traditional drug delivery systems such as oral medicine and intravenous injection. In order to reach the circulatory system of the human body, drug molecules have to pass through the epidermis (outer layer) of the skin. The barrier properties of epidermis originate from low permeability of stratum corneum (SC) which is the outermost layer of the human skin. The objective of this thesis is to build a Finite Element (FE) model, utilizing commercial FE software (ANSYS), that can be implemented …

Koh Etching Of Silicon, Ying Wang

Theses

In this research, a series of comparative etching experiments on silicon wafers have been carried out using potassium hydroxide (KOH) for different experimental etching conditions for concentration, temperature and time on (100) orientation p-type silicon wafers. Besides the basic etching conditions, the position of the immersed wafer also has unpredictable effect on the etching process. This may be attributed to the relative contact position between the surface of the immersed wafer and the flow patterns of the stirred etching solution.

The surface morphology analysis indicates that the specific position of the wafer, with respect to the flow of the etchant, …

Effect Of Temperature On The Fracture Behavior Of Lead-Free Solder Joints, Patrick Thompson

Theses

The objective of the present study is to examine the effect of temperature on the fracture behavior of Cu-SAC305-Cu joints. To this end, double cantilever beam (DCB) specimens, consisting of a thin layer of Sn96.5Ag3.0Cu0.5 (SAC305) solder sandwiched between two copper bars, fabricated under standard surface mount (SMT) processing conditions are fractured under various temperatures with a MTS machine equipped with an environment chamber. The load-displacement behavior corresponding to crack initiation and the subsequent toughening before ultimate failure and the displacements near crack tip are recorded and used to calculate the fracture energy release rates. The fracture surfaces and the …

Radiative Properties Of Silicon Related Materials, Scott Sanowitz

Theses

The objective of this thesis is to study the optical properties of silicon, as a function of temperature, in the infrared range of wavelengths. The wavelength range, considered in this study, is between 1 micron and 20 microns. The temperature range observed is from 50 degrees Celsius to 1000 degrees Celsius. Varying wafer thickness and doping are taken into account. The thickness of the native oxide, silicon dioxide, must be taken into account as well as its orientation (front side versus back side). The effect of layering wafers one onto another is investigated. It is shown that all these parameters …

Effect Of Melt Method On Thoracolumbar Connective Tissue, Faria Sanjana

Theses

Approximately, 31 million adults in the United States suffer from low back pain (LBP). Altered connective tissue structure has been identified in adults with chronic LBP. Numerous novel treatments are being developed targeting the connective tissue and nervous system to relieve people from LBP. One such self-care treatment is the MELT method. The objective of this study was to determine whether thickness of thoracolumbar connective tissue and other biomechanical and viscoelastic properties of myofascial tissue in the low back region change in subjects with chronic LBP as a result of MELT.

Using ultrasound imaging and an algorithm developed in MATLAB, …

Uusing The Kdj As A Trading Strategy On Biotech Companies, Shijie Zha

Theses

Mean Reversion is the most commonly used model in quantitative trading. This model is associated with several factors, like ma5 and ma10 line. These factors are the most significant in stock markets. However, the disadvantages of this model are lag and inaccuracy.

In this research, we get the historical and current stock data by web crawler, analyze the quantitative data and build a new model involved with the KDJ. Taking biotech companies marketed in the United States and B-share marketed in China as the research subjects, the result shows increased profits compared with the Mean Reversion model. It also shows …

Rectangle Visibility Numbers Of Graphs, Eric Peterson

Theses

Very-Large Scale Integration (VLSI) is the problem of arranging components on the surface of a circuit board and developing the wired network between components. One methodology in VLSI is to treat the entire network as a graph, where the components correspond to vertices and the wired connections correspond to edges. We say that a graph G has a rectangle visibility representation if we can assign each vertex of G to a unique axis-aligned rectangle in the plane such that two vertices u and v are adjacent if and only if there exists an unobstructed horizontal or vertical channel of finite …

Colored Saturation Parameters For Bipartite Graphs, Christine Van Oostendorp

Theses

Let F and H be fixed graphs and let G be a spanning subgraph of H. G is an F-free subgraph of H if F is not a subgraph of G. We say that G is an F-saturated subgraph of H if G is F-free and for any edge e in E(H)-E(G), F is a subgraph of G+e. The saturation number of F in K_{n,n}, denoted sat(K_{n,n}, F), is the minimum size of an F-saturated subgraph of K_{n,n}. A t-edge-coloring of a graph G is a labeling f: E(G) to [t], where [t] denotes the set { 1, 2, ..., …

Developing A Prototype System For Syndromic Surveillance And Visualization Using Social Media Data., Anup Aryal

Theses

Syndromic surveillance of emerging diseases is crucial for timely planning and execution of epidemic response from both local and global authorities. Traditional sources of information employed by surveillance systems are not only slow but also impractical for developing countries. Internet and social media provide a free source of a large amount of data which can be utilized for Syndromic surveillance.

We propose developing a prototype system for gathering, storing, filtering and presenting data collected from Twitter (a popular social media platform). Since social media data is inherently noisy we describe ways to preprocess the gathered data and utilize SVM (Support …

Effects Of Using Ipad On First Grade Students' Achievements In Arabic Language Classes In Saudi Arabia, Jawaher Alsulami

Theses

Although the iPad device has become a new trend as a teaching and learning tool in schools, using it in Saudi schools is still relatively new. So, the purpose of the study was to investigate whether the iPad enhances the teaching and learning styles in Arabic language classes for first grade in Albushra primary school. It also examined how this new educational tool affects students' skills and achievements, how teachers and students use it in their Arabic language classes, and what are advantages and disadvantages of using it in a class and at home. The study data was collected by …

Kernelized Cost-Sensitive Listwise Ranking, Gabriela Guimaraes Olinto

Theses

This thesis research aims to conduct a study on a cost-sensitive listwise approach to learning to rank.

Learning to Rank is an area of application in machine learning, typically supervised, to build ranking models for Information Retrieval systems. The training data consists of lists of items with some partial order specified induced by an ordinal score or a binary judgment (relevant/not relevant). The model purpose is to produce a permutation of the items in this list in a way which is close to the rankings in the training data. This technique has been

successfully applied to ranking, and several approaches …

Development Of A System Model For An Indirect Passive Solar Dryer With Experimental Validation, Samantha Huselstein

Theses

Solar crop drying is a cheap and effective way to preserve food material, especially in developing countries where fuel and electricity are expensive or unavailable. Some tropical fruits are difficult to transport and store leading to significant spoilage. Without access to fuel and large drying systems, preserving fruits for later use is challenging or not possible for the rural farmer. Developing low-cost, easily assembled locally and low maintenance fruit drying systems would improve access to off-season and distant markets. A mathematical model of an indirect passive solar drying system was developed to design and optimize drying systems for use in …

Evolutionary Weights For Random Subspace Learning, Andre Lobato Ramos

Theses

Ensemble learning is a widely used technique in Data Mining, this method allows us to aggregate models to reduce prediction error. There are many methods on how to perform model aggregation, one of them is known as Random Subspace Learning, which consists of building subspace of the feature space where we want to create our models. The task of selecting good subspaces and in turn produce good models for better prediction can be a daunting one, so we want to propose a new method to accomplish such a task. This proposed method allows for an automated data-driven way to attribute …

On Identification Of Nonlinear Parameters In Pdes, Raphael Kahler

Theses

Inverse problems have been studied in great detail and optimization methods using objective functionals such as output least-squares (OLS) and modified output least-squares (MOLS) are well understood. However, the existing literature has only dealt with identifying parameters that appear linearly in systems of partial differential equations. We investigate the changes that occur in the identification process if the parameter appears nonlinearly. We extend the OLS and MOLS functionals to this nonlinear case and give first and second derivative formulas. We further show that the typical convexity of the MOLS functional can not be guaranteed when identifying nonlinear parameters. To numerically …

A Modification And Application Of Parametric Continuation Method To Variety Of Nonlinear Boundary Value Problems In Applied Mechanics, Akshay Patil

Theses

In the field of engineering, researches often come across strong nonlinear boundary value problems which cannot be solved easily. Numerical convergence for many problems, typically solved by the Newton-Raphson linearization algorithm, is sensitive to the initial approach, relaxation parameters and differential topology. Emphasis in the present work is placed on the alternative approach, the so called parametric imbedding of a particular problem into the family of problems. While this may appear to complicate rather than to simplify the problem, its justification lies in the fact that a relation between infinitesimally close neighboring processes results in a simple Cauchy problem with …

Techniques For Digital Low Dropout Regulator Modeling And Transient Response Enhancement, Paul Martin West

Theses

Low dropout regulators (LDOs) are important components for power management in modern integrated circuits. With the continued scaling down of power supply voltage, digital LDOs have become a more attractive design choice since they avoid the difficulty of designing high-gain amplifiers with low voltage. This thesis investigates techniques for both modeling and enhancement of digital LDO transient response. It discusses the importance of the resistance in the output stage of an LDO, and proposes a simulation model for examining LDO transient response. In addition, the thesis studies circuit techniques to improve LDO transient response. Different LDO circuits are implemented and …

Fusion Of Mini-Deep Nets, Sai Prasad Nooka

Theses

Image classification and object recognition are some of the most prominent problems in computer vision. The difficult nature of finding objects regardless of pose and occlusions requires a large number of compute resources. Recent advancements in technology have made great strides towards solving this problem, and in particular, deep learning has revolutionized this field in the last few years.

The classification of large datasets, such as the popular ImageNet dataset, requires a network with millions of weights. Learning each of these weights using back propagation requires a compute intensive training phase with many training samples. Recent compute technology has proven …

Visualization Of Mind: Visual Exploration Of Brain Activity, Bilegsaikhan Baasanjav

Theses

Since ancient times, philosophical and religious thinkers have made attempts to understand the nature of the mind. Today, new developments in technology enable scientists and researchers to explore the brain’s complex physical activity, revealing a deeper mental reality. Moreover, the emergence of low-cost biometric devices gives nonscientific communities an ability to explore usage of biometric data in variety of ways.

This project explores visualization of human brain activity using electroencephalogram neural interface to create a visually engaging and meaningful user experience. The implementation of the project takes a form of an interactive installation. It projects the visual form, whose visual …