Physical Sciences and Mathematics Commons^™

A Hybrid Gaze Pointer With Voice Control, Indhuja Ravi

Master's Projects

Accessibility in technology has been a challenge since the beginning of the 1800s. Starting with building typewriters for the blind by Pellegrino Turri to the on-screen keyboard built by Microsoft, there have been several advancements towards assistive technologies. The basic tools necessary for anyone to operate a computer are to be able to navigate the device, input information, and perceive the output. All these three categories have been undergoing tremendous advancements over the years. Especially, with the internet boom, it has now become a necessity to point onto a computer screen. This has somewhat attracted research into this particular area. …

Automating Text Encapsulation Using Deep Learning, Anket Sah

Master's Projects

Data is an important aspect in any form be it communication, reviews, news articles, social media data, machine or real-time data. With the emergence of Covid-19, a pandemic seen like no other in recent times, information is being poured in from all directions on the internet. At times it is overwhelming to determine which data to read and follow. Another crucial aspect is separating factual data from distorted data that is being circulated widely. The title or short description of this data can play a key role. Many times, these descriptions can deceive a user with unwanted information. The user …

American Sign Language Assistant, Charulata Lodha

Master's Projects

Our implementation of a prototype computer vision system to help the deaf and mute
communicate in a shopping setting. Our system uses live video feeds to recognize American Sign Language (ASL) gestures and notify shop clerks of deaf and mute patrons’ intents. It generates a video dataset in the Unity Game Engine of 3D humanoid models in a shop setting performing ASL signs. Our system uses OpenPose to detect and recognize the bone points of the human body
from the live feed. The system then represents the motion sequences as high dimensional skeleton joint point trajectories followed by a time-warping …

Machine Learning Using Serverless Computing, Vidish Naik

Master's Projects

Machine learning has been trending in the domain of computer science for quite some time. Newer and newer models and techniques are being developed every day. The adoption of cloud computing has only expedited the process of training machine learning. With its variety of services, cloud computing provides many options for training machine learning models. Leveraging these services is up to the user. Serverless computing is an important service offered by cloud service providers. It is useful for short tasks that are event-driven or periodic. Machine learning training can be divided into short tasks or batches to take advantage of …

Visual And Lingual Emotion Recognition Using Deep Learning Techniques, Akshay Kajale

Master's Projects

Emotion recognition has been an integral part of many applications like video games, cognitive computing, and human computer interaction. Emotion can be recognized by many sources including speech, facial expressions, hand gestures and textual attributes. We have developed a prototype emotion recognition system using computer vision and natural language processing techniques. Our goal hybrid system uses mobile camera frames and features abstracted from speech named Mel Frequency Cepstral Coefficient (MFCC) to recognize the emotion of a person. To acknowledge the emotions based on facial expressions, we have developed a Convolutional Neural Network (CNN) model, which has an accuracy of 68%. …

Defending Vehicles Against Cyberthreats: Challenges And A Detection-Based Solution, Qilin Liu

Master's Projects

The lack of concern with security when vehicular network protocols were designed some thirty years ago is about to take its toll as vehicles become more connected and smart. Today as demands for more functionality and connectivity on vehicles continue to grow, a plethora of Electronic Control Units (ECUs) that are able to communicate to external networks are added to the automobile networks. The proliferation of ECU and the increasing autonomy level give drivers more control over their vehicles and make driving easier, but at the same time they expand the attack surface, bringing more vulnerabilities to vehicles that might …

Grazing Intensity And Frequency Effects On Herbage Accumulation And Nutritive Value Of Tifton 85 Bermudagrass (Cynodon Sp.), Kesi Liu, Lynn E. Sollenberger, U. Renée White, Y. C. Newman, Joao M. B. Vendramini

IGC Proceedings (1993-2023)

No abstract provided.

Fatty Acid Analysis Of Six Important Forage, Zhiqiang Li, J. G. Han

IGC Proceedings (1993-2023)

No abstract provided.

The Analysis Of Cation‐Anion Difference Of Six Important Forage, Zhiqiang Li, J. G. Han

IGC Proceedings (1993-2023)

No abstract provided.

Effect Of Additive On Alfalfa Mixed Silage Quality, X. X. Li, Q. Zh. Sun

IGC Proceedings (1993-2023)

No abstract provided.

Mathematical Modeling Of The Functioning Of A Hydrodynamic System With Distributed Parameters, Olim Suvonov, Elmira Nazirova

Bulletin of TUIT: Management and Communication Technologies

The work examines the process of functioning of the hydrodynamic system "reservoir-well" taking into account the dynamic process of shutting down and starting a group of production wells. A mathematical model for determining system states, an algorithm for solving an applied problem and the results of computational experiments in the form of graphs are given.

Eastward-Propagating Planetary Waves In The Middle Atmosphere During Major Sudden Stratospheric Warming Events, Christian Todd Rhodes

Electronic Theses and Dissertations

No abstract provided.

Experience-Driven Control For Networking And Computing, Zhiyuan Xu

Dissertations - ALL

Modern networking and computing systems have become very complicated and highly dynamic, which makes them hard to model, predict and control. In this thesis, we aim to study system control problems from a whole new perspective by leveraging emerging Deep Reinforcement Learning (DRL), to develop experience-driven model-free approaches, which enable a network or a device to learn the best way to control itself from its own experience (e.g., runtime statistics data) rather than from accurate mathematical models, just as a human learns a new skill (e.g., driving, swimming, etc). To demonstrate the feasibility and superiority of this experience-driven control design …

Computational Algorithms For Predicting Membrane Protein Assembly From Angstrom To Micron Scale, Nandhini Rajagopal

Dissertations - ALL

Biological barriers in the human body are one of the most crucial interfaces perfected through evolution for diverse and unique functions. Of the wide range of barriers, the paracellular protein interfaces of epithelial and endothelial cells called tight junctions with high molecular specificities are vital for homeostasis and to maintain proper health. While the breakdown of these barriers is associated with serious pathological consequences, their intact presence also poses a challenge to effective delivery of therapeutic drugs. Complimenting a rigorous combination of in vitro and in vivo approaches to establishing the fundamental biological construct, in addition to elucidating pathological implications …

N-Bakry Emery Ricci Curvature & N-Quasi Einstein Metrics, Alice Wu Lim

Dissertations - ALL

We begin the thesis by giving an intuitive introduction to calculus on mani- folds for the non-mathematician. We then give a semi-intuitive description on Ricci curvature for the non-geometer. We give a description of the N-Bakry- Émery Ricci curvature and the N-quasi Einstein metric. The main results in this thesis are related to the N-Bakry-Émery Ricci curvature and the N-quasi Einstein metric.

Our first set of main results are as follows. We generalize topological results known for noncompact manifolds with nonnegative Ricci curvature to spaces with nonnegative N-Bakry Émery Ricci curvature. We study the Splitting Theorem and a property called …

Effects Of Air Pollution, Temperature And Moisture Content On Copper And Silver Corrosions And The Reliability Of Data Center Equipment, Rui Zhang

Dissertations - ALL

The effects of moisture content, temperature, and pollutant mixture on atmospheric corrosion of copper and silver were investigated by exposing test specimens to different environmental conditions, followed by surface characterization using the coulometric reduction, Scanning Electron Microscopy, and Energy Dispersive Spectrometry (SEM/EDS). Printed circuit board test cards (PCBs) with bare copper were also used to investigate the effects of voltage bias on the PCBs on the corrosion rate. The test specimens were exposed to mixed flowing gases (MFG) environment with eight different combinations of the following five pollutants at the fixed concentration levels: 60 ppb O3, 80 ppb NO2, 40 …

Sentiment Classification Bias In User Generated Content, Alpana Deshpande

Theses - ALL

Interactive websites generate terabytes of data on a daily basis. This data canbe used in multiple analytical applications to teach computers more about human behavior. Text classification is such an application. Multiple freely available user-generated text data can be used to teach computers to identify the sentiments behind a user's on-screen interactions without the need of any human intervention. Sentiment analysis is an interesting problem, solving which would theoretically get a computer closer to passing the Turing test. Through this thesis, we test the ability of a classifier to accurately identify user sentiments. However, we do not focus on standard …

Enhancing Usability Of Malware Analysis Pipelines With Reverse Engineering, Jeffrey Ching

Theses - ALL

Lots of work has been done on analyzing software distributed in binary form. This is a challenging problem because of the relatively unstructured nature of binaries. To recover high-level structure, various attempts have included static and dynamic analysis. However, human inspection is often required, as high-level structure is compiled away. Recent success in this area includes work on variable-name recovery, vulnerability discovery, class recovery for object-oriented languages. We are interested in building a pipeline for user to analyze malware. In this thesis we tackle two problems central to malware analysis pipelines. The first is D3RE, an interactive querying tool that …

Torsion Subgroups Of Rational Elliptic Curves Over Odd Degree Galois Fields, Caleb Mcwhorter

Dissertations - ALL

The Mordell-Weil Theorem states that if K is a number field and E/K is an elliptic curve that the group of K-rational points E(K) is a finitely generated abelian group, i.e. E(K) = Z^{r_K} ⊕ E(K)_tors, where r_K is the rank of E and E(K)_tors is the subgroup of torsion points on E. Unfortunately, very little is known about the rank r_K. Even in the case of K = Q, it is not known which ranks are possible or if the ranks are bounded. However, there have been great strides in determining the sets E(K)_tors. Progress began in 1977 with …

Inferring Degree Of Localization Of Twitter Persons And Topics Through Time, Language, And Location Features, Aleksey Valeriy Panasyuk

Dissertations - ALL

Identifying authoritative influencers related to a geographic area (geo-influencers) can aid content recommendation systems and local expert finding. This thesis addresses this important problem using Twitter data.

A geo-influencer is identified via the locations of its followers. On Twitter, due to privacy reasons, the location reported by followers is limited to profile via a textual string or messages with coordinates. However, this textual string is often not possible to geocode and less than 1\% of message traffic provides coordinates. First, the error rates associated with Google's geocoder are studied and a classifier is built that gives a warning for self-reported …

Year-Independent Prediction Of Food Insecurity Using Classical & Neural Network Machine Learning Methods, Caleb Christiansen, Torrey J. Wagner, Brent Langhals

Faculty Publications

Current food crisis predictions are developed by the Famine Early Warning System Network, but they fail to classify the majority of food crisis outbreaks with model metrics of recall (0.23), precision (0.42), and f1 (0.30). In this work, using a World Bank dataset, classical and neural network (NN) machine learning algorithms were developed to predict food crises in 21 countries. The best classical logistic regression algorithm achieved a high level of significance (p < 0.001) and precision (0.75) but was deficient in recall (0.20) and f1 (0.32). Of particular interest, the classical algorithm indicated that the vegetation index and the food price index were both positively correlated with food crises. A novel method for performing an iterative multidimensional hyperparameter search is presented, which resulted in significantly improved performance when applied to this dataset. Four iterations were conducted, which resulted in excellent 0.96 for metrics of precision, recall, and f1. Due to this strong performance, the food crisis year was removed from the dataset to prevent immediate extrapolation when used on future data, and the modeling process was repeated. The best “no year” model metrics remained strong, achieving ≥0.92 for recall, precision, and f1 while meeting a 10% f1 overfitting threshold on the test (0.84) and holdout (0.83) datasets. The year-agnostic neural network model represents a novel approach to classify food crises and outperforms current food crisis prediction efforts.

Ambient Obstruction Solitons And Homogeneous Gradient Bach Solitons, Erin Renee Griffin

Dissertations - ALL

Differential geometry is a diverse field which applies principles from calculus to a more general set of objects. Endowing a smooth manifold with a Riemannian metric allows us to measure length and angle in a way such that length is positive. This enables us to examine measures of curvature on a manifold. The study of manifolds with such metrics is called Riemannian geometry. Using geometric flows associated with tensors, we are able to analyze the relationship between metrics and curvature. Examining solitons, specifically gradient solitons, is one way we investigate this relationship.

This thesis focuses on the geometric flows associated …

Carbonate Paleothermometry In Fayetteville Green Lake, New York, Micah Wiesner

Theses - ALL

Lacustrine carbonates are important paleoclimate archives, but unknowns in the seasonal timing and depth of precipitation obscure the interpretation of temperatures associated with them. The clumped isotope paleothermometer records the formation temperature T(D47) of carbonates. This study examines a set of lacustrine carbonates formed in the water column, in addition to carbonate from a sediment core, to better understand the depth and seasonality of carbonate formation in a lacustrine setting. We test that, regardless of season and formation temperature, lacustrine carbonates form in isotopic equilibrium with respect to D47 and d18O fractionation. Further, we account for the effect of our …

Internet Of Medical Things (Iomt): Overview, Emerging Technologies, And Case Studies, Sahshanu Razdan, Sachin Sharma

Articles

No abstract provided.

Mesoproterozoic Basement From The Central And Southern Appalachians Reveal High-Temperature Magmatic Conditions And Non-Laurentian Origin Of Earth's Most Zircon Fertile Magmas, Kyle Makovsky

Dissertations - ALL

The Mesoproterozoic (1.4-0.9 Ga) Grenville Orogeny led to the formation of the supercontinent Rodinia. One unique characteristic of the Grenville Orogeny is that it produced a volumetrically significant amount of zirconium- (Zr) enriched granitoids, evidently more than any period both prior to and after the Grenville. To investigate this further, Mesoproterozoic basement rocks were sampled along the axis of the current Appalachian Mountains from western North Carolina north to southern New York, as well as from the northern Andes in southern Colombia. Zircon was extracted from these rocks to exploit its propensity to incorporate several isotopic tracers useful in determining …

Beyond The Standard Models Of Particle Physics And Cosmology, Gabriele Rigo

Dissertations - ALL

Despite their numerous successes both from the theoretical and experimental point of view, conceptual and observational evidence suggests the Standard Models of Particle Physics and Cosmology should be considered incomplete theories, reliable only within their well-defined regime of validity. This dissertation covers various possible extensions of those models from the theoretical, phenomenological and model-building perspective. The topics analyzed range from extra-dimensional approaches to the hierarchy problem, to the AdS/CFT description of perturbative anomaly inflow, and new probes of vacuum energy in neutron stars and gravitational waves.

Hochschild Cohomology Of Short Gorenstein Rings, Mkrtich Ohanyan

Dissertations - ALL

Let k be a field of characteristic 0. In this thesis, we show that the Hochschild cohomology of the family of short Gorenstein k-algebras

sGor(N) =k[X_0,...,X_N](X_iX_j, X_i^2−X_j^2 | i,j= 0,...,N, i different from j), N≥2,

exhibits exponential growth. The proof uses Gröbner-Shirshov basis theory and along the way we describe an explicit monomial basis for the Koszul dual of sGor(N) for N≥2.

The Impact Of Direct Sowing Into Sward Of Permanent Grassland On Forage Production, P. Komárek, A. Kohoutek, P. Nerušil, V. Odstrčilová

IGC Proceedings (1993-2023)

No abstract provided.

Comparison On The Newly Developed Silage Inoculant (Lactobacillus Plantarum Nlri 401) For Whole Crop Rice Silage, Jong-Geun Kim, Eui-Soo Chung, Jun-Sang Ham, Sei-Hyung Yoon, Meing-Joong Kim, Sung Seo

IGC Proceedings (1993-2023)

No abstract provided.

Assessment Of Mineral Elements Of Some Range Species In Contrast Of Livestock Requirements, S. H. Kaboli, Hossein Arzani, L. Fazel

IGC Proceedings (1993-2023)

No abstract provided.