Physical Sciences and Mathematics Commons^™

Supporting Text And Data Analysis Across Campus From The Academic Library, Amy Kirchhoff, Hejin Shin Phd

Digital Initiatives Symposium

The ability to comprehend and communicate with text-based data is essential to future success in academics and employment, as evidenced in a recent survey from Bloomberg Research Services which shows that nearly 97% of survey respondents now use data analytics in their companies and 58% consider data and text mining a business analytics tool (https://www.sas.com/content/dam/SAS/bp_de/doc/studie/ba-st-the-current-state-of-business-analytics-2317022.pdf). This has fueled a substantial growth in text analysis research (involving the use of technology to analyze un- and semi-structured text data for valuable insights, trends, and patterns) across disciplines and a corresponding demand on academic libraries to support text analysis pedagogy and text analysis …

Sentiment Analysis Of Public Perception Towards Elon Musk On Reddit (2008-2022), Daniel Maya Bonilla, Samuel Iradukunda, Pamela Thomas

The Cardinal Edge

As Elon Musk’s influence in technology and business continues to expand, it becomes crucial to comprehend public sentiment surrounding him in order to gauge the impact of his actions and statements. In this study, we conducted a comprehensive analysis of comments from various subreddits discussing Elon Musk over a 14-year period, from 2008 to 2022. Utilizing advanced sentiment analysis models and natural language processing techniques, we examined patterns and shifts in public sentiment towards Musk, identifying correlations with key events in his life and career. Our findings reveal that public sentiment is shaped by a multitude of factors, including his …

Statistical Methods For Single Cell Sequencing Data Analysis, Fei Qin

Theses and Dissertations

The recent emergence of single cell sequencing (SCS) technology has provided us with single-cell DNA or RNA sequencing (scDNA/RNA-seq) information to investigate cellular evolutionary relationships. Despite many analysis methods have been developed to infer intra-tumor genetic heterogeneity, cluster cellular subclones, detect genetic mutations, and investigate spatially variable (SV) genes, exploring SCS data remains statistically challenging due to its noisy nature.

To identify subclones with scDNA-seq data, many existing studies use an independent statistical model to detect copy number profile in the first step, followed by classical clustering methods for subclone identification in downstream analyses. However, spurious results might be generated …

Digital Dna: The Ethical Implications Of Big Data As The World’S New-Age Commodity, Clark H. Dotson

Honors Theses

In the emerging digital world that we find ourselves in, it becomes apparent that data collection has become a staple of daily life, whether we like it or not. This research discussion aims to bring light to just how much one’s own digital identity is valued in the technologically-infused world of today, with distinct research and local examples to bring awareness to the ethical implications of your online presence. The paper in question examines anecdotal and research evidence of the collection of data, both through true and unjust means, as well as ethical implications of what this information truly represents. …

Use Of Social Media During The Covid-19 Pandemic Of 2020, Aliya Goncalves Almeida

Honors Program Theses and Projects

Nowadays billions of people use social media platforms as a way to keep in touch with family and friends, fill spare time, find content, find inspiration for things to do and buy, share, and discuss opinions with others, and the list goes on. This project focused and investigated on the use of social media during the years, in particular during quarantine/lockdown. Utilizing the public source data, I explored several research questions including how many hours people spent on social media, the popularity of social media apps, as well as what age group uses social media platforms (teenagers, young adults, adults). …

The Effectiveness Of Visualization Techniques For Supporting Decision-Making, Cansu Yalim, Holly A. H. Handley

Modeling, Simulation and Visualization Student Capstone Conference

Although visualization is beneficial for evaluating and communicating data, the efficiency of various visualization approaches for different data types is not always evident. This research aims to address this issue by investigating the usefulness of several visualization techniques for various data kinds, including continuous, categorical, and time-series data. The qualitative appraisal of each technique's strengths, weaknesses, and interpretation of the dataset is investigated. The research questions include: which visualization approaches perform best for different data types, and what factors impact their usefulness? The absence of clear directions for both researchers and practitioners on how to identify the most effective visualization …

Beyond News Values On Twitter: Predicting Factors That Drive User Engagement In News, Zhiyan Zhong

Dartmouth College Master’s Theses

When deciding on what news stories to cover, traditional journalism determines news values by following several elements of newsworthiness, such as impact, timeliness, and prominence. However, these guidelines do not always seem to correspond with the success of content on social media. As people are increasingly turning to social media for news, our research aims to understand and predict factors that drive user engagement for news on social media. In this study, we analyze news content published on Twitter, and examine a diverse set of characteristics like metrics retrieved from the Twitter API and semantics by natural language processing, including …

Contemporary Velocity Field For Turkey Inferred From Combination Of A Dense Network Of Long Term Gnss Observations, Ali̇ İhsan Kurt, Ali̇ Değer Özbakir, Ayhan Ci̇ngöz, Semi̇h Ergi̇ntav, Uğur Doğan, Seda Özarpaci

Turkish Journal of Earth Sciences

The Anatolia?Aegean domain represents a broad plate boundary zone, with the deformation accommodated by major faults bounding quasi-low deforming units. First-order features of this deformation were obtained in the form of a GNSS-derived velocity field. During the last decade, the accuracy of velocity solutions was improved, and the expansion of continuous networks increased spatial resolution. Nonetheless, an accurate representation of the deformation field requires interstation distances much lower than the locking depth of nearby faults, which has not yet been satisfied. The basis for creating a precise and accurate velocity field is uniform processing of the time series recorded both …

Exclusive 𝝅⁻ Electroproduction Off The Neutron In Deuterium In The Resonance Region, Y. Tian, R. W. Gothe, V. I. Mokeev, G. Hollis, M. J. Amaryan, W. R. Armstrong, H. Atac, H. Avakian, L. Barion, M. Battaglieri, I. Bedlinskiy, B. Benkel, F. Benmokhtar, A. Bianconi, L. Biondo, A. Biselli, F. Bossù, S. Boiarinov, M. Bondì, J. Zhang, Et Al., The Clas Collaboration

Physics Faculty Publications

New results for the exclusive and quasifree cross sections off neutrons bound in deuterium 𝛾_vn(p) → pπ− (p) are presented over a wide final state hadron angle range with a kinematic coverage of the invariant mass (W) up to 1.825 GeV and the four-momentum transfer squared (Q²) from 0.4 to 1.0 GeV². The exclusive structure functions were extracted and their Legendre moments were obtained. Final-state-interaction contributions have been kinematically separated from the extracted quasifree cross sections off bound neutrons solely based on the analysis of the experimental data. These new results will serve as …

Tenvr: Matlab-Based Toolbox For Environmental Research, Aleksandar I. Goranov, Rachel L. Sleighter, Dobromir A. Yordanov, Patrick G. Hatcher

Chemistry & Biochemistry Faculty Publications

With the advancements in science and technology, datasets become larger and more multivariate, which warrants the need for programming tools for fast data processing and multivariate statistical analysis. Here, the MATLAB-based Toolbox for Environmental Research "TEnvR" (pronounced "ten-ver") is introduced. This novel toolbox includes 44 open-source codes for automated data analysis from a multitude of techniques, such as ultraviolet-visible, fluorescence, and nuclear magnetic resonance spectroscopies, as well as from ultrahigh resolution mass spectrometry. Provided are codes for processing data (e.g., spectral corrections, formula assignment), visualization of figures, calculation of metrics, multivariate statistics, and automated work-up of large datasets. TEnvR allows …

Complete Study Of An Original Power-Exponential Transformation Approach For Generalizing Probability Distributions, Mustafa S. Shama, Farid El Ktaibi, Jamal N. Al Abbasi, Christophe Chesneau, Ahmed Z. Afify

All Works

In this paper, we propose a flexible and general family of distributions based on an original power-exponential transformation approach. We call it the modified generalized-G (MGG) family. The elegance and significance of this family lie in the ability to modify the standard distributions by changing their functional forms without adding new parameters, by compounding two distributions, or by adding one or two shape parameters. The aim of this modification is to provide flexible shapes for the corresponding probability functions. In particular, the distributions of the MGG family can possess increasing, constant, decreasing, “unimodal”, or “bathtub-shaped“ hazard rate functions, which are …

A Study On Global Reef Deterioration: Exploring Coral Bleaching, Emily Fernandez

CMC Senior Theses

This thesis is a study on coral bleaching and coral mortality, studying the relationship between variables such as depth, exposure, distance to shore, and temperature for percent bleaching. All of the analyses were made using two different data sets, that contain information about bleaching events in specific regions, and dates, and provide information factors such as depth, temperature, and exposure. Models were created for different relationships of variables for eco-regions, recent data, and countries. I attempted to find relationships between variables such as depth, temperature, exposure, and distance to shore, and how they affect coral bleaching. Unfortunately, I did not …

Distinctive Features Of Nonverbal Behavior And Mimicry In Application Interviews Through Data Analysis And Machine Learning, Sanne Rogiers, Elias Corneillie, Filip Lievens, Frederik Anseel, Peter Veelaert, Wilfried Philips

Research Collection Lee Kong Chian School Of Business

This paper reveals the characteristics and effects of nonverbal behavior and human mimicry in the context of application interviews. It discloses a novel analyzation method for psychological research by utilizing machine learning. In comparison to traditional manual data analysis, machine learning proves to be able to analyze the data more deeply and to discover connections in the data invisible to the human eye. The paper describes an experiment to measure and analyze the reactions of evaluators to job applicants who adopt specific behaviors: mimicry, suppress, immediacy and natural behavior. First, evaluation of the applicant qualifications by the interviewer reveals …

Financial Literacy: Self-Evaluation And Reality, Yangsijia Wang

Undergraduate Student Research Internships Conference

This study is on the topic of financial literacy, with the data source containing information on clients' demographic information and self-evaluation, change in account value, and trade record, three major problems were investigated: first, whether a client's demographic traits are related to his/her self-evaluation of financial knowledge level; second, does the trading behaviour differ for clients who self-identified as in different financial knowledge groups; and third, do people who self-identified as financially knowledgeable have better investment result. Data manipulation was done using SQL and R. Exploratory analysis including multiple types of plots and proportion tables was used to derive the …

Estimating The Health Effects Of Adding Bicycle And Pedestrian Paths At The Census Tract Level: Multiple Model Comparison, Ross J. Gore, Christopher Lynch, Craig Jordan, Andrew Collins, R. Michael Robinson, Gabrielle Fuller, Pearson Ames, Prateek Keerthi, Yash Kandukuri

VMASC Publications

Background: Adding additional bicycle and pedestrian paths to an area can lead to improved health outcomes for residents over time. However, quantitatively determining which areas benefit more from bicycle and pedestrian paths, how many miles of bicycle and pedestrian paths are needed, and the health outcomes that may be most improved remain open questions.

Objective: Our work provides and evaluates a methodology that offers actionable insight for city-level planners, public health officials, and decision makers tasked with the question “To what extent will adding specified bicycle and pedestrian path mileage to a census tract improve residents’ health outcomes over time?” …

Automatic Data Aggregation To Assist In The Systematic Classification Of Small Lunar Craters, Liam Powers

Physics and Astronomy Summer Fellows

Crater counting has been one of the dominant methods of characterizing surfaces of planetary bodies in the absence of material samples. Unfortunately, counts often rely on the subjective expertise of the counter, which limits the volume of reliable data that is accessible to researchers. Our work seeks to develop a quantifiable method of classifying individual craters within a count population to better determine a given crater’s age and origin. Recommendations are then generated in order to increase the accuracy of human counters, and improve the efficiency of the counting process. Preliminary work on the Moon uses LRO LOLA elevation data, …

Heat Flow In Terrestrial-Type Bodies From High P,T Electrical Resistivity Measurements Of Au, Fe-Si And Fe-Ni-Si Solid And Liquid Alloys, Meryem Berrada

Electronic Thesis and Dissertation Repository

The source of the fluid stirring mechanism that powers the dynamo of terrestrial-type bodies during their active magnetic field era is debated. Prior to the formation of a solid inner core, thermal convection may cause enough mechanical stirring of the core fluid to generate a magnetic field through dynamo action. After inner core formation, compositional convection in the liquid outer core becomes the main source of fluid stirring mechanism to power a dynamo. Constraints on the likelihood and duration of these convection mechanisms may be obtained by the experimental determination of the thermal properties of core materials. These cores consist …

A Bayesian Programming Approach To Car-Following Model Calibration And Validation Using Limited Data, Franklin Abodo

FIU Electronic Theses and Dissertations

Traffic simulation software is used by transportation researchers and engineers to design and evaluate changes to roadway networks. Underlying these simulators are mathematical models of microscopic driver behavior from which macroscopic measures of flow and congestion can be recovered. Many models are intended to apply to only a subset of possible traffic scenarios and roadway configurations, while others do not have any explicit constraint on their applicability. Work zones on highways are one scenario for which no model invented to date has been shown to accurately reproduce realistic driving behavior. This makes it difficult to optimize for safety and other …

State Prediction Of Poverty Alleviation Objects Based On Hmm And Multidimensional Data, Jun He, Sunyan Hong, Yifang Zhou, Shikai Shen, Muquan Zou

Journal of System Simulation

Abstract: In order to solve the problems of inaccurate prediction of poverty, poverty reduction and poverty returen, and the difficulty in identifying the key factors affecting the state transition, 8 key features and 22 observed states are extracted from the poverty reduction basic data and multi-industry data. The relationship between observed state and implied state is constructed, and the hidden markov model (HMM) of poverty alleviation is established. Data of a deep poverty county for three consecutive years are used as samples for parameter training, test experiment and result verification. The results show that the method has a strong …

How Blockchain Solutions Enable Better Decision Making Through Blockchain Analytics, Sammy Ter Haar

Information Systems Undergraduate Honors Theses

Since the founding of computers, data scientists have been able to engineer devices that increase individuals’ opportunities to communicate with each other. In the 1990s, the internet took over with many people not understanding its utility. Flash forward 30 years, and we cannot live without our connection to the internet. The internet of information is what we called early adopters with individuals posting blogs for others to read, this was known as Web 1.0. As we progress, platforms became social allowing individuals in different areas to communicate and engage with each other, this was known as Web 2.0. As Dr. …

An Exploratory Data Analysis On Covid-19 And Its Effects On Crime In New York City, Lanlie Nguyen

Honors Projects

The purpose of this study was to analyze the effects of the COVID-19 pandemic and how it has affected the crime rates present in New York City over the years of 2019 and 2020. There is limited criminal research that investigate the connection to pandemics, and how it can be used to reduce crime rates in similar situations. The goal of this study is to reduce crime rates and provide possible policy implications.

This project analyzes the crime rate trends present before and during the COVID-19 pandemic, and compares it to the number of COVID-19 cases. Analysis of the statewide …

Topological Data Analysis With Mapper, Gretchen Langenbahn

Honors Projects

This project is an introduction and overview of Mapper. Mapper is a method of high dimensional data visualization. Data visualization is a very important part of data analysis as it allows for further interpretation and exploration of data. Visualization of high dimensional data sets can be challenging as each variable is a new dimension that must be represented on a 2D, or at most 3D, graph. Mapper allows for high dimensional visualization by using Topological methods to study the relationships between points. This project goes over two different data set: the Iris data set, and a high dimensional data set …

Big Data With Cloud Computing: Discussions And Challenges, Amanpreet Kaur Sandhu

Big Data Mining and Analytics

With the recent advancements in computer technologies, the amount of data available is increasing day by day. However, excessive amounts of data create great challenges for users. Meanwhile, cloud computing services provide a powerful environment to store large volumes of data. They eliminate various requirements, such as dedicated space and maintenance of expensive computer hardware and software. Handling big data is a time-consuming task that requires large computational clusters to ensure successful data storage and processing. In this work, the definition, classification, and characteristics of big data are discussed, along with various cloud services, such as Microsoft Azure, Google Cloud, …

Ascp-Iomt: Ai-Enabled Lightweight Secure Communication Protocol For Internet Of Medical Things, Mohammad Wazid, Jaskaran Singh, Ashok Kumar Das, Sachin Shetty, Muhammad Khurram Khan, Joel J.P.C. Rodrigues

VMASC Publications

The Internet of Medical Things (IoMT) is a unification of smart healthcare devices, tools, and software, which connect various patients and other users to the healthcare information system through the networking technology. It further reduces unnecessary hospital visits and the burden on healthcare systems by connecting the patients to their healthcare experts (i.e., doctors) and allows secure transmission of healthcare data over an insecure channel (e.g., the Internet). Since Artificial Intelligence (AI) has a great impact on the performance and usability of an information system, it is important to include its modules in a healthcare information system, which will be …

Post-Quantum Secure Identity-Based Encryption Scheme Using Random Integer Lattices For Iot-Enabled Ai Applications, Dharminder Dharminder, Ashok Kumar Das, Sourav Saha, Basudeb Bera, Athanasios V. Vasilakos

VMASC Publications

Identity-based encryption is an important cryptographic system that is employed to ensure confidentiality of a message in communication. This article presents a provably secure identity based encryption based on post quantum security assumption. The security of the proposed encryption is based on the hard problem, namely Learning with Errors on integer lattices. This construction is anonymous and produces pseudo random ciphers. Both public-key size and ciphertext-size have been reduced in the proposed encryption as compared to those for other relevant schemes without compromising the security. Next, we incorporate the constructed identity based encryption (IBE) for Internet of Things (IoT) applications, …

The State Of The Art Of Information Integration In Space Applications, Zhuming Bi, K. L. Yung, Andrew W.H. Ip., Yuk Ming Tang, Chris W.J. Zhang, Li Da Xu

Information Technology & Decision Sciences Faculty Publications

This paper aims to present a comprehensive survey on information integration (II) in space informatics. With an ever-increasing scale and dynamics of complex space systems, II has become essential in dealing with the complexity, changes, dynamics, and uncertainties of space systems. The applications of space II (SII) require addressing some distinctive functional requirements (FRs) of heterogeneity, networking, communication, security, latency, and resilience; while limited works are available to examine recent advances of SII thoroughly. This survey helps to gain the understanding of the state of the art of SII in sense that (1) technical drivers for SII are discussed and …

A Longitudinal Analysis Of Pathways To Computing Careers: Defining Broadening Participation In Computing (Bpc) Success With A Rearview Lens, Mercy Jaiyeola

Theses and Dissertations

Efforts to increase the participation of groups historically underrepresented in computing studies, and in the computing workforce, are well documented. It is a national effort with funding from a variety of sources being allocated to research in broadening participation in computing (BPC). Many of the BPC efforts are funded by the National Science Foundation (NSF) but as existing literature shows, the growth in representation of traditionally underrepresented minorities and women is not commensurate to the efforts and resources that have been directed toward this aim.

Instead of attempting to tackle the barriers to increasing representation, this dissertation research tackles the …

Data Analysis Of The “2021 Covid, Equity And Social Justice Showcase”, Cristo Leon, James Lipuma

STEM Month

During the “2021 STEM for All Video Showcase” (NSF, 2021) funded by the National Science Foundation, 287 short videos showcasing federally funded projects aimed at improving STEM and CS education were presented.

The videos highlight strategies to engage students during COVID-19 and address educational inequities.

Nnetfix: An Artificial Neural Network-Based Denoising Engine For Gravitational-Wave Signals, Kentaro Mogushi, Ryan Quitzow-James, Marco Cavaglià, Sumeet Kulkarni, Fergus Hayes

Faculty and Student Publications

Instrumental and environmental transient noise bursts in gravitational-wave (GW) detectors, or glitches, may impair astrophysical observations by adversely affecting the sky localization and the parameter estimation of GW signals. Denoising of detector data is especially relevant during low-latency operations because electromagnetic follow-up of candidate detections requires accurate, rapid sky localization and inference of astrophysical sources. NNETFIX is a machine learning, artificial neural network-based algorithm designed to estimate the data containing a transient GW signal with an overlapping glitch as though the glitch was absent. The sky localization calculated from the denoised data may be significantly more accurate than the sky …

Nnetfix: An Artificial Neural Network-Based Denoising Engine For Gravitational-Wave Signals, Kentaro Mogushi, Ryan Quitzow-James, Marco Cavaglia, For Full List Of Authors, See Publisher's Website.

Physics Faculty Research & Creative Works

Instrumental and environmental transient noise bursts in gravitational-wave (GW) detectors, or glitches, may impair astrophysical observations by adversely affecting the sky localization and the parameter estimation of GW signals. Denoising of detector data is especially relevant during low-latency operations because electromagnetic follow-up of candidate detections requires accurate, rapid sky localization and inference of astrophysical sources. NNETFIX is a machine learning, artificial neural network-based algorithm designed to estimate the data containing a transient GW signal with an overlapping glitch as though the glitch was absent. The sky localization calculated from the denoised data may be significantly more accurate than the sky …