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Mobility-Based Models For Advancing Diagnostic/Predictive Healthcare, Elham Rastegari 2019 University of Nebraska at Omaha

Mobility-Based Models For Advancing Diagnostic/Predictive Healthcare, Elham Rastegari

Student Research and Creative Activity Fair

Functional ability has been always considered as one of the important determining factors of individuals’ health and quality of life. Traditional movement analysis systems require expensive facilities and frequent visits for patients to specialized laboratories. Portability and affordability of wearable sensors along with their improved accuracy and capability of monitoring movement during daily activities make them a potential alternative for analyzing mobility patterns for clinical and health assessment purposes. Wearable-based movement data, when combined with other relevant clinical or laboratory data, could enhance evidence-based healthcare and data-driven Clinical Decision Support Systems (CDSS). Utilizing the data from wearable devices, many researchers ...


A Shared-Memory Algorithm For Updating Single-Source Shortest Paths In Large Weighted Dynamic Networks, Sriram Srinivasan 2019 University of Nebraska at Omaha

A Shared-Memory Algorithm For Updating Single-Source Shortest Paths In Large Weighted Dynamic Networks, Sriram Srinivasan

Student Research and Creative Activity Fair

In the last decade growth of social media, increased the interest of network algorithms for analyzing large-scale complex systems. The networks are highly unstructured and exhibit poor locality, which has been a challenge for developing scalable parallel algorithms. The state-of-the-art network algorithms such as Prim's algorithm for Minimum Spanning Tree, Dijkstra's algorithm for Single Source Shortest Path and ISPAN algorithm for detecting strongly connected components are designed and optimized for static networks. The networks which change with time i.e. the dynamic networks such as social networks, the above-mentioned approaches can only be utilized if they are recomputed ...


Finding Truth In Fake News: Reverse Plagiarism And Other Models Of Classification, Matthew Przybyla, David Tran, Amber Whelpley, Daniel W. Engels 2019 Southern Methodist University

Finding Truth In Fake News: Reverse Plagiarism And Other Models Of Classification, Matthew Przybyla, David Tran, Amber Whelpley, Daniel W. Engels

SMU Data Science Review

As the digital age creates new ways of spreading news, fake stories are propagated to widen audiences. A majority of people obtain both fake and truthful news without knowing which is which. There is not currently a reliable and efficient method to identify “fake news”. Several ways of detecting fake news have been produced, but the various algorithms have low accuracy of detection and the definition of what makes a news item ‘fake’ remains unclear. In this paper, we propose a new method of detecting on of fake news through comparison to other news items on the same topic, as ...


Comparative Study Of Sentiment Analysis With Product Reviews Using Machine Learning And Lexicon-Based Approaches, Heidi Nguyen, Aravind Veluchamy, Mamadou Diop, Rashed Iqbal 2019 Southern Methodist University

Comparative Study Of Sentiment Analysis With Product Reviews Using Machine Learning And Lexicon-Based Approaches, Heidi Nguyen, Aravind Veluchamy, Mamadou Diop, Rashed Iqbal

SMU Data Science Review

In this paper, we present a comparative study of text sentiment classification models using term frequency inverse document frequency vectorization in both supervised machine learning and lexicon-based techniques. There have been multiple promising machine learning and lexicon-based techniques, but the relative goodness of each approach on specific types of problems is not well understood. In order to offer researchers comprehensive insights, we compare a total of six algorithms to each other. The three machine learning algorithms are: Logistic Regression (LR), Support Vector Machine (SVM), and Gradient Boosting. The three lexicon-based algorithms are: Valence Aware Dictionary and Sentiment Reasoner (VADER), Pattern ...


The St. Chad Gospels: Diachronic Manuscript Registration And Visualization, Stephen Parsons, C. Seth Parker, W. Brent Seales 2019 University of Kentucky

The St. Chad Gospels: Diachronic Manuscript Registration And Visualization, Stephen Parsons, C. Seth Parker, W. Brent Seales

Manuscript Studies

This paper presents a software framework for the registration and visualization of layered image sets. To demonstrate the utility of these tools, we apply them to the St. Chad Gospels manuscript, relying on images of each page of the document as it appeared over time. An automated pipeline is used to perform non-rigid registration on each series of images. To visualize the differences between copies of the same page, a registered image viewer is constructed that enables direct comparisons of registered images. The registration pipeline and viewer for the resulting aligned images are generalized for use with other data sets.


Towards A Fault-Tolerant, Scheduling Methodology For Safety-Critical Certified Information Systems, Jian Lin 2019 University of Houston-Clear Lake

Towards A Fault-Tolerant, Scheduling Methodology For Safety-Critical Certified Information Systems, Jian Lin

Journal of International Technology and Information Management

Today, many critical information systems have safety-critical and non-safety-critical functions executed on the same platform in order to reduce design and implementation costs. The set of safety-critical functionality is subject to certification requirements and the rest of the functionality does not need to be certified, or is certified to a lower level. The resulting mixed-criticality systems bring challenges in designing such systems, especially when the critical tasks are required to complete with a timing constraint. This paper studies a problem of scheduling a mixed-criticality system with fault tolerance. A fault-recovery technique called checkpointing is used where a program can go ...


Localization Using Convolutional Neural Networks, Shannon D. Fong 2018 California Polytechnic State University, San Luis Obispo

Localization Using Convolutional Neural Networks, Shannon D. Fong

Computer Engineering

With the increased accessibility to powerful GPUs, ability to develop machine learning algorithms has increased significantly. Coupled with open source deep learning frameworks, average users are now able to experiment with convolutional neural networks (CNNs) to solve novel problems. This project sought to train a CNN capable of classifying between various locations within a building. A single continuous video was taken while standing at each desired location so that every class in the neural network was represented by a single video. Each location was given a number to be used for classification and the video was subsequently titled locX. These ...


Exploring Photo Privacy Protection On Smartphones, David Darling 2018 University of Arkansas, Fayetteville

Exploring Photo Privacy Protection On Smartphones, David Darling

Computer Science and Computer Engineering Undergraduate Honors Theses

The proliferation of modern smartphone camera use in the past decade has resulted in unprecedented numbers of personal photos being taken and stored on popular devices. However, it has also caused privacy concerns. These photos sometimes contain potentially harmful information if they were to be leaked such as the personally identifiable information found on ID cards or in legal documents. With current security measures on iOS and Android phones, it is possible for 3rd party apps downloaded from official app stores or other locations to access the photo libraries on these devices without user knowledge or consent. Additionally, the prevalence ...


Automation Of Post-Earthquake Civil Infrastructure Reconnaissance, Jack Bergquist 2018 California Polytechnic State University, San Luis Obispo

Automation Of Post-Earthquake Civil Infrastructure Reconnaissance, Jack Bergquist

Architectural Engineering

Traditionally post-earthquake structural engineering reconnaissance consists of a team of experts who are deployed to the field to record and capture earthquake damage data, which is later uploaded into online repositories. Despite many advances to these data archives in recent years, the entries in online repositories often have limited metadata which make it difficult and time consuming to extract specific damage evidence that can be used for meaningful analysis. This report outlines the author’s contributions to overcoming these challenges via the development of a neural network that automatically filters and classifies post-earthquake civil infrastructure damage data after a seismic ...


A Survey Of Virtual Network Architectures, Lenoy Avidan 2018 California Polytechnic State University, San Luis Obispo

A Survey Of Virtual Network Architectures, Lenoy Avidan

Computer Science

With the storage needs of the world increasing, especially with the growth of cloud computing, data centers are being utilized more than ever. The increasing need of storage has led to more use of virtualization to help intra and inter data center communications. The virtualization of physical networks is used to help achieve this goal, but with the creation of Virtual Networks, systems must be designed to create, manage, and secure them. A Virtual Network Architecture is the system design for creating and maintaining virtual network components and the resulting networks they create. Different companies design different Virtual Network Architectures ...


Modeling And Simulation Methodologies For Spinal Cord Stimulation., Saliya Kumara Kirigeeganage 2018 University of Louisville

Modeling And Simulation Methodologies For Spinal Cord Stimulation., Saliya Kumara Kirigeeganage

Electronic Theses and Dissertations

The use of neural prostheses to improve health of paraplegics has been a prime interest of neuroscientists over the last few decades. Scientists have performed experiments with spinal cord stimulation (SCS) to enable voluntary motor function of paralyzed patients. However, the experimentation on the human spinal cord is not a trivial task. Therefore, modeling and simulation techniques play a significant role in understanding the underlying concepts and mechanics of the spinal cord stimulation. In this work, simulation and modeling techniques related to spinal cord stimulation were investigated. The initial work was intended to visualize the electric field distribution patterns in ...


A Transfer Learning Approach For Sentiment Classification., Omar Abdelwahab 2018 University of Louisville

A Transfer Learning Approach For Sentiment Classification., Omar Abdelwahab

Electronic Theses and Dissertations

The idea of developing machine learning systems or Artificial Intelligence agents that would learn from different tasks and be able to accumulate that knowledge with time so that it functions successfully on a new task that it has not seen before is an idea and a research area that is still being explored. In this work, we will lay out an algorithm that allows a machine learning system or an AI agent to learn from k different domains then uses some or no data from the new task for the system to perform strongly on that new task. In order ...


Social Network For Software Developers, Sanket Prabhakar Jadhav 2018 California State University - San Bernardino

Social Network For Software Developers, Sanket Prabhakar Jadhav

Electronic Theses, Projects, and Dissertations

This project is the design and implementation of a web-based message board for software developers. The purpose of “Social Network for Software Developers” is to connect inexperienced software developers with experienced software developers.


Organize Events Mobile Application, Thakshak Mani Chandra Reddy Gudimetla 2018 California State University, San Bernardino

Organize Events Mobile Application, Thakshak Mani Chandra Reddy Gudimetla

Electronic Theses, Projects, and Dissertations

In a big organization there are many events organized every day. To know about the events, we typically need to check an events page, rely on flyers or on distributed pamphlets or through word of mouth. To register for an event a user now a days typically does this online which involves inputting user details. At the event, the user either signs a sheet of paper or enters credentials in a web page loaded on a tablet or other electronic device. Typically, this is a time-consuming process with many redundancies like entering user details every time the user wants to ...


Automatic Identification Of Animals In The Wild: A Comparative Study Between C-Capsule Networks And Deep Convolutional Neural Networks., Joel Kamdem Teto, Ying Xie 2018 Kennesaw State University

Automatic Identification Of Animals In The Wild: A Comparative Study Between C-Capsule Networks And Deep Convolutional Neural Networks., Joel Kamdem Teto, Ying Xie

Master of Science in Computer Science Theses

The evolution of machine learning and computer vision in technology has driven a lot of

improvements and innovation into several domains. We see it being applied for credit decisions, insurance quotes, malware detection, fraud detection, email composition, and any other area having enough information to allow the machine to learn patterns. Over the years the number of sensors, cameras, and cognitive pieces of equipment placed in the wilderness has been growing exponentially. However, the resources (human) to leverage these data into something meaningful are not improving at the same rate. For instance, a team of scientist volunteers took 8.4 ...


A Validation Study Of Time Series Data Forecasting Using Neural Networks, Marco Martinez, Jeremy Evert 2018 Southwestern Oklahoma State University

A Validation Study Of Time Series Data Forecasting Using Neural Networks, Marco Martinez, Jeremy Evert

Student Research

Artificial Intelligence(AI) is a growing topic in Computer Science and has many uses in real world applications. One application is using Al, or more specifically Neural Networks to model data and predict outcomes. Neural Networks have been used in the past to predict weather changes, create facial recognition software , and to create self-driving cars. Our project is a validation study of, “Modeling Time Series Data With Deep Fourier Neural Networks” by Gashler and Ashmore, 2016. Here we show that a neural network can be trained to be an effective predictor of weather patterns in Alaska over several years. Our ...


Effective Methods And Tools For Mining App Store Reviews, Nishant Jha 2018 Louisiana State University and Agricultural and Mechanical College

Effective Methods And Tools For Mining App Store Reviews, Nishant Jha

LSU Doctoral Dissertations

Research on mining user reviews in mobile application (app) stores has noticeably advanced in the past few years. The main objective is to extract useful information that app developers can use to build more sustainable apps. In general, existing research on app store mining can be classified into three genres: classification of user feedback into different types of software maintenance requests (e.g., bug reports and feature requests), building practical tools that are readily available for developers to use, and proposing visions for enhanced mobile app stores that integrate multiple sources of user feedback to ensure app survivability. Despite these ...


Introducing Competencies In Organizations, Henk Plessius, Anand Sheombar, Pascal Ravesteyn 2018 HU University of Applied Science

Introducing Competencies In Organizations, Henk Plessius, Anand Sheombar, Pascal Ravesteyn

Communications of the IIMA

In the fast-changing world of IT, relevant competencies are getting more important as these determine how successful you can function in practice. As a consequence, organizations are introducing competency frameworks like the European e-Competence Framework (e-CF, 2014) in their IT departments. However, for many organizations it is unclear what good practices and pitfalls are when introducing such a framework. In this paper this topic is studied by analysing 13 interviews with IT- and HR-managers who are (or recently have been) involved in a transition towards the use of competencies with their IT-staff.


Julia Language Ephemeris And Physical Constants Reader For Solar System Bodies, Julia Mihaylov, Renee Spear 2018 Embry-Riddle Aeronautical University

Julia Language Ephemeris And Physical Constants Reader For Solar System Bodies, Julia Mihaylov, Renee Spear

Undergraduate Research Symposium - Prescott

This presentation was the forerunner a second paper by the authors for the AAS/AIAA conference in January 2019, and is not available for download. For a description of the first presentation, see the authors' Discovery Day 2018 - Presentation.

Publicly released in 2012, the Julia language is a relatively new, open source dynamic language. One major benefit of Julia is its combined capabilities of both dynamic and static coding languages. It nearly matches the computational efficiency of static languages, such as FORTRAN or C, and exceeds that of dynamic languages, such as MATLAB or Python. Additionally, unlike Python, Julia was ...


Developing High Performance Grid Computing Systems On A Budget, Forrest Mobley 2018 Embry-Riddle Aeronautical University

Developing High Performance Grid Computing Systems On A Budget, Forrest Mobley

Undergraduate Research Symposium - Prescott

High performance grid computing systems are essential for today’s engineering and research projects, as they make certain impossibilities possible, and save time and money as well. However, these supercomputers can cost upwards of a hundred million dollars and require large amounts of space and energy to keep, making them all but inaccessible to small engineering firms and universities. As most of these institutions do not require the massive level of computing power offered by these large grid computers, small scale versions are often built, with various setups. The purpose of this project was to set up a new small ...


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