Data Science Commons^™

Sentiment Analysis For Airline Services On Twitter Using Deep Learning With Word Embedding, Nour El Daim El Khalifa Mawada Mohamed

Student Works (2020-2029)

The use of social media platform in the airline industries have increased rapidly to allow analysis introduce the quality and performance of the services. The role of Sentiment Analysis (SA) is to classify people's opinions into different categories, such as positive and negative from text, using existing algorithms. However, existing approaches such as the Bag of Words (BOW) model is frequently used for text classification, where a document is mapped to a feature vector before the construction of the actual model, using machine learning techniques, like Logistical Regression and Support Vector algorithms. This problem has led to low accuracy in …

A Novel Item-Allocation Procedure For The Three-Form Planned Missing Data Design, Kyle M. Lang, E. Whitney G. Moore, Elizabeth M. Grandfield

Kinesiology, Health and Sport Studies

We propose a new method of constructing questionnaire forms in the three-form planned missing data design (PMDD). The random item allocation (RIA) procedure that we propose promises to dramatically simplify the process of implementing three-form PMDDs without compromising statistical performance. Our method is a stochastic approximation to the currently recommended approach of deterministically spreading a scale's items across the X-, A-, B-, and C-blocks when allocating the items in a three-form design. Direct empirical support for the performance of our method is only available for scales containing at least 12 items, so we also propose a modified approach for use …

Finding Common Ground For Citizen Empowerment In The Smart City, John D. Kelleher, Aphra Kerr

Articles

Corporate smart city initiatives are just one example of the contemporary culture of surveillance. They rely on extensive information gathering systems and Big Data analysis to predict citizen behaviour and optimise city services. In this paper we argue that many smart city and social media technologies result in a paradox whereby digital inclusion for the purposes of service provision also results in marginalisation and disempowerment of citizens. Drawing upon insights garnered from a digital inclusion workshop conducted in the Galapagos islands, we propose that critically and creatively unpacking the computational techniques embedded in data services is needed as a first …

A Systematic Literature Survey Of Unmanned Aerial Vehicle Based Structural Health Monitoring, Sreehari Sreenath

Theses, Dissertations and Capstones

Unmanned Aerial Vehicles (UAVs) are being employed in a multitude of civil applications owing to their ease of use, low maintenance, affordability, high-mobility, and ability to hover. UAVs are being utilized for real-time monitoring of road traffic, providing wireless coverage, remote sensing, search and rescue operations, delivery of goods, security and surveillance, precision agriculture, and civil infrastructure inspection. They are the next big revolution in technology and civil infrastructure, and it is expected to dominate more than $45 billion market value. The thesis surveys the UAV assisted Structural Health Monitoring or SHM literature over the last decade and categorize UAVs …

Critical Media, Information, And Digital Literacy: Increasing Understanding Of Machine Learning Through An Interdisciplinary Undergraduate Course, Barbara R. Burke, Elena Machkasova

Communication, Media, and Rhetoric Publications

Widespread use of Artificial Intelligence in all areas of today’s society creates a unique problem: algorithms used in decision-making are generally not understandable to those without a background in data science. Thus, those who use out-of-the-box Machine Learning (ML) approaches in their work and those affected by these approaches are often not in a position to analyse their outcomes and applicability. Our paper describes and evaluates our undergraduate course at the University of Minnesota Morris, which fosters understanding of the main ideas behind ML. With Communication, Media & Rhetoric and Computer Science faculty expertise, students from a variety of majors, …

Tufts Analytics Without Borders 2020 Conference Conference Summary Report, Tufts University

Analytics Without Borders

This conference provided a single venue for interdisciplinary research, collaboration, and communication on applied data analytics in the fields of business, public health, nutrition, and the environment. We advanced a shared agenda to harness the power of data sciences to discuss the complexities of health and nutrition problems through the lens of data sciences. The conference showcased numerous opportunities for students including hands-on workshops on topics related to data sciences, panel discussions on topics ranging from business to health, and both oral and poster presentations for sharing research.

Fusion-Net: Integration Of Dimension Reduction And Deep Learning Neural Network For Image Classification, Mohammad Masum, Philippe Laval

Published and Grey Literature from PhD Candidates

Building a deep network using original digital images requires learning many parameters which may reduce the accuracy rates. The images can be compressed by using dimension reduction methods and extracted reduced features can be feeding into a deep network for classification. Hence, in the training phase of the network, the number of parameters will be decreased. Principal Component Analysis is a well-known dimension reduction technique that leverage orthogonal linear transformation of the original data. In this paper, we propose a neural network-based framework, named Fusion-Net, which implements PCA on an image dataset (CIFAR-10) and then a neural network applies on …

Data Rescue & Curation Best Practices Guide, Ocul Data Community (Odc) Data Rescue Group

Western Libraries Publications

he aim of the Data Rescue & Curation Best Practices Guide is to provide an accessible and hands-on approach to handling data rescue and digital curation of at-risk data for use in secondary research. We provide a set of examples and workflows for addressing common challenges with social science survey data that can be applied to other social and behavioural research data. The goal of this guide and set of workflows presented is to improve librarians’ and data curators’ skills in providing access to high-quality, well-documented, and reusable research data. The aspects of data curation that are addressed throughout this …

Edge-Cloud Computing For Iot Data Analytics: Embedding Intelligence In The Edge With Deep Learning, Ananda Mohon M. Ghosh, Katarina Grolinger

Electrical and Computer Engineering Publications

Rapid growth in numbers of connected devices including sensors, mobile, wearable, and other Internet of Things (IoT) devices, is creating an explosion of data that are moving across the network. To carry out machine learning (ML), IoT data are typically transferred to the cloud or another centralized system for storage and processing; however, this causes latencies and increases network traffic. Edge computing has the potential to remedy those issues by moving computation closer to the network edge and data sources. On the other hand, edge computing is limited in terms of computational power and thus is not well suited for …

Deep Learning For Load Forecasting With Smart Meter Data: Online Adaptive Recurrent Neural Network, Mohammad Navid Fekri, Harsh Patel, Katarina Grolinger, Vinay Sharma

Electrical and Computer Engineering Publications

No abstract provided.

The Mathematics, Computer Science, And Data Science Student Research Showcase, Seton Hall University

Petersheim Academic Exposition

No abstract provided.

Interview With Deborah Winslow Of The National Science Foundation, Jerome W. Crowder, Mike Fortun, Rachel Besara, Lindsay Poirier

Statistical and Data Sciences: Faculty Books

Chapter Abstract:

In this chapter the editors interview Dr. Deborah Winslow about her work at the National Science Foundation (NSF) and the evolution of data management plans (DMPs) in Anthropology and the Social, Behavioral and Economic Sciences (SBE). She outlines what the NSF expects to see in a DMP and what not to include. The conversation moves into how anthropologists collaborate with “adjacent disciplines” and how the ideas and terms for data, and the expectations of data change. She emphasizes thinking about the kind of data you will collect and what you plan to do with those data later, in …

Supp & Mapp: Adaptable Structure-Based Representations For Mir Tasks, Claire Savard, Erin H. Bugbee, Melissa R, Mcguirl, Katherine M. Kinnaird

Statistical and Data Sciences: Faculty Publications

Accurate and flexible representations of music data are paramount to addressing MIR tasks, yet many of the existing approaches are difficult to interpret or rigid in nature. This work introduces two new song representations for structure-based retrieval methods: Surface Pattern Preservation (SuPP), a continuous song representation, and Matrix Pattern Preservation (MaPP), SuPP’s discrete counterpart. These representations come equipped with several user-defined parameters so that they are adaptable for a range of MIR tasks. Experimental results show MaPP as successful in addressing the cover song task on a set of Mazurka scores, with a mean precision of 0.965 and recall of …

Building Something With The Raspberry Pi, Richard Kordel

Harrisburg University Presidential Research Grants

In 2017 Ryan Korn and I submitted a grant proposal in the annual Harrisburg University President’s Grant process. Our proposal was to partner with a local high school to install a classroom of 20 Raspberry Pi’s, along with the requisite peripherals. In that classroom students would be challenged to design something that combined programming with physical computing. In our presentation to the school we suggested that this project would give students the opportunity to be “amazing.”

As part of the grant, the top three students would be given scholarships to HU and the top five finalists would all be permitted …

Sediment Dynamics In The Magdalena River Basin, Colombia: Implications For Understanding Tropical River Processes And Hydropower Development, Luke H. Fisher

Graduate Student Theses, Dissertations, & Professional Papers

The Magdalena River Basin of Colombia has a globally relevant sediment flux, however, studies of the sediment regime in the basin are limited in scope. This knowledge gap limits application of understanding of sediment dynamics to hydropower decision making. To close this gap, we implemented a sediment budget framework to quantify the impacts of hydropower development in a 118,000 km² portion of the Magdalena River basin. We informed this framework with analysis of background erosion rates derived from ¹⁰Be cosmogenic nuclides and modern sediment fluxes derived from monitoring and optical remote sensing. We standardized these data to spatially …

Modeling Twitter Sentiment As A Function Of Particulate Matter 2.5 For Communities Impacted By Wildfire Across Montana And Idaho, Matthew Kelly

Graduate Student Theses, Dissertations, & Professional Papers

Fine particulate matter (PM2.5) is a known pollutant with clinically detrimental physiological and behavioral effects. We consider Twitter sentiment as a potential indicator for well-being in communities impacted by wildfire-associated PM2.5 across Montana and Idaho spanning 5 years (2014-2018). From these geospatial air quality data and geo-tagged tweets, we trained county level models to examine the power of Twitter sentiment as a function of PM2.5. For all 24 counties sampled, we found between 1 and 8 affective dimensions where a positive �� 2 was detected with a significant F-statistic (�� < 0.05). Specifically, we show that sentiment for anticipation in the wildfire-prone county of Missoula, MT yielded respective training/test set �� 2 of 0.0958 and 0.0686 with a p-value for the F-statistic of 3.09E-07. These analyses support social media sentiment as a potential public health metric by showing one of the first observations of a relationship between PM2.5 and Twitter sentiment.

Completing The Cycle: Creating A Data Management Services Program, Scott Bacon, Eric Resnis, Ariana Baker

Library Faculty Presentations

The implementation of Coastal Carolina University’s Data Management Services program is explored in this presentation. Our library continued to see growth in data management support requests from researchers, so we felt the need to programmatically develop data management services to serve those needs. We assembled a Data Management Services Working Group to examine what types of services were being offered at other M1 institutions. A research data management life cycle was then developed to serve as a standard framework. The services we currently offer were then integrated with those we knew our faculty wanted. We also explored services apart from …

An Analytical Examination On The Effects Of Vegetarian And Omnivorous Diets On C-Reactive Protein, Aletha Kleis

Undergraduate Honors Theses

There is a lack of research regarding how following a vegetarian or omnivores diet effects C-Reactive Protein (CRP) levels of people as seen through results from an analysis of data gathered from the National Health and Nutrition Examination Survey (NHANES). The level of CRP is a reflection of how much inflammation there is in one’s body and is a popular indicator of risk for heart disease. Thus, in this research, I use the NHANES data to look at the relationship of CRP levels of people who identified themselves as vegetarian or not, while also considering the general healthiness of each …

Evolution Of Integration, Build, Test, And Release Engineering Into Devops And To Devsecops, Vishnu Pendyala

Faculty Research, Scholarly, and Creative Activity

Software engineering operations in large organizations are primarily comprised of integrating code from multiple branches, building, testing the build, and releasing it. Agile and related methodologies accelerated the software development activities. Realizing the importance of the development and operations teams working closely with each other, the set of practices that automated the engineering processes of software development evolved into DevOps, signifying the close collaboration of both development and operations teams. With the advent of cloud computing and the opening up of firewalls, the security aspects of software started moving into the applications leading to DevSecOps. This chapter traces the journey …

Continuous Deployment Transitions At Scale, Laurie Williams, Kent Beck, Jeffrey Creasey, Andrew Glover, James Holman, Jez Humble, David Mclaughlin, John Thomas Micco, Brendan Murphy, Jason A. Cox, Vishnu Pendyala, Steven Place, Zachary T. Pritchard, Chuck Rossi, Tony Savor, Michael Stumm, Chris Parnin

Faculty Research, Scholarly, and Creative Activity

Predictable, rapid, and data-driven feature rollout; lightning-fast; and automated fix deployment are some of the benefits most large software organizations worldwide are striving for. In the process, they are transitioning toward the use of continuous deployment practices. Continuous deployment enables companies to make hundreds or thousands of software changes to live computing infrastructure every day while maintaining service to millions of customers. Such ultra-fast changes create a new reality in software development. Over the past four years, the Continuous Deployment Summit, hosted at Facebook, Netflix, Google, and Twitter has been held. Representatives from companies like Cisco, Facebook, Google, IBM, Microsoft, …