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Real-Time Stealth Intervention For Motor Learning Using Player Flow-State, Ramin Tadayon, Ashish Amresh, Troy McDaniel, Sethuraman Panchanathan 2019 Arizona State University

Real-Time Stealth Intervention For Motor Learning Using Player Flow-State, Ramin Tadayon, Ashish Amresh, Troy Mcdaniel, Sethuraman Panchanathan

Ashish Amresh

We present a novel approach to real-time adaptation in serious games for at-home motor learning. Our approach assesses and responds to the “flow-state” of players by tracking and classifying facial emotions in real-time using the Kinect camera. Three different approaches for stealth assessment and adaptation using performance and flow-state data are defined, along with a case-study evaluation of these approaches based on their effectiveness at maintaining positive affective interaction in a subject.


Real-Time Rfi Mitigation In Radio Astronomy, Emily Ramey, Nick Joslyn, Richard Prestage, Michael Lam, Luke Hawkins, Tim Blattner, Mark Whitehead 2019 Washington University in St. Louis

Real-Time Rfi Mitigation In Radio Astronomy, Emily Ramey, Nick Joslyn, Richard Prestage, Michael Lam, Luke Hawkins, Tim Blattner, Mark Whitehead

Senior Honors Papers / Undergraduate Theses

As the use of wireless technology has increased around the world, Radio Frequency Interference (RFI) has become more and more of a problem for radio astronomers. Preventative measures exist to limit the presence of RFI, and programs exist to remove it from saved data, but the use of algorithms to detect and remove RFI as an observation is occurring is much less common. Such a method would be incredibly useful for observations in which the data must undergo several rounds of processing before being saved, as in pulsar timing studies. Strategies for real-time mitigation have been discussed and tested with ...


Generative Linguistics And Neural Networks At 60: Foundation, Friction, And Fusion, Joe Pater 2019 Selected Works

Generative Linguistics And Neural Networks At 60: Foundation, Friction, And Fusion, Joe Pater

Joe Pater

The birthdate of both generative linguistics and neural networks can be taken as 1957, the year of the publication of foundational work by both Noam Chomsky and Frank Rosenblatt. This paper traces the development of these two approaches to cognitive science, from their largely autonomous early development in their first thirty years, through their collision in the 1980s around the past tense debate (Rumelhart and McClelland 1986, Pinker and Prince 1988), and their integration in much subsequent work up to the present. Although this integration has produced a considerable body of results, the continued general gulf between these two lines ...


When Human Cognitive Modeling Meets Pins: User-Independent Inter-Keystroke Timing Attacks, Ximing LIU, Yingjiu LI, Robert H. DENG, Bing CHANG, Shujun LI 2019 Singapore Management University

When Human Cognitive Modeling Meets Pins: User-Independent Inter-Keystroke Timing Attacks, Ximing Liu, Yingjiu Li, Robert H. Deng, Bing Chang, Shujun Li

Research Collection School Of Information Systems

This paper proposes the first user-independent inter-keystroke timing attacks on PINs. Our attack method is based on an inter-keystroke timing dictionary built from a human cognitive model whose parameters can be determined by a small amount of training data on any users (not necessarily the target victims). Our attacks can thus be potentially launched on a large scale in real-world settings. We investigate inter-keystroke timing attacks in different online attack settings and evaluate their performance on PINs at different strength levels. Our experimental results show that the proposed attack performs significantly better than random guessing attacks. We further demonstrate that ...


Call For Abstracts - Resrb 2019, July 8-9, Wrocław, Poland, Wojciech M. Budzianowski 2018 Wojciech Budzianowski Consulting Services

Call For Abstracts - Resrb 2019, July 8-9, Wrocław, Poland, Wojciech M. Budzianowski

Wojciech Budzianowski

No abstract provided.


Strong Equivalence And Program's Structure In Arguing Essential Equivalence Between First-Order Logic Programs, Yuliya Lierler 2018 Department of Compter Science

Strong Equivalence And Program's Structure In Arguing Essential Equivalence Between First-Order Logic Programs, Yuliya Lierler

Yuliya Lierler

Answer set programming  is a prominent declarative programming paradigm used in formulating combinatorial search problems and implementing distinct knowledge representation formalisms. It is common that several related and yet substantially different answer set programs exist for a given problem. Sometimes these encodings may display significantly different performance. Uncovering precise formal links between these programs is often important and yet far from trivial. This paper claims the correctness   of a number of interesting program rewritings. Notably, they  assume  programs with variables and  such important language features as choice, disjunction, and aggregates. We showcase the utility of some considered rewritings  by using ...


Automatic Program Rewriting In Non-Ground Answer Set Programs, Nicholas Hippen, Yuliya Lierler 2018 University of Nebraska at Omaha

Automatic Program Rewriting In Non-Ground Answer Set Programs, Nicholas Hippen, Yuliya Lierler

Yuliya Lierler

Answer set programming is a popular constraint programming paradigm that has seen wide use across various industry applications. However, logic programs under answer set semantics often require careful design and nontrivial expertise from a programmer to obtain satisfactory solving times. In order to reduce this burden on a software engineer we propose an automated rewriting technique for non-ground logic programs that we implement in a system Projector. We conduct rigorous experimental analysis, which shows that applying system Projector to a logic program can improve its performance, even after significant human-performed optimizations.


Project Renew Worcester, Danni Yue, Amy Zhang, Jing Han, Omid Ashrafi, Yiming Xu 2018 Clark University

Project Renew Worcester, Danni Yue, Amy Zhang, Jing Han, Omid Ashrafi, Yiming Xu

School of Professional Studies

n The client for this capstone project is RENEW Worcester which is a fledgling solar power project whose main goals are to bring renewable energy in the form of solar power into local, primarily low-income communities and are committed to the mission of making the transition off of fossil fuels to clean, renewable power. Based in Worcester, Massachusetts, they are a local chapter of Co-op Power which is a consumer-owned sustainable energy cooperative (co-op) made up of numerous different local chapters all over the New England area as well as the state of New York. The problem that we will ...


Calculating The Cohomology Of A Lie Algebra Using Maple And The Serre Hochschild Spectral Sequence, Jacob Kullberg 2018 Utah State University

Calculating The Cohomology Of A Lie Algebra Using Maple And The Serre Hochschild Spectral Sequence, Jacob Kullberg

All Graduate Plan B and other Reports

Lie algebra cohomology is an important tool in many branches of mathematics. It is used in the Topology of homogeneous spaces, Deformation theory, and Extension theory. There exists extensive theory for calculating the cohomology of semi simple Lie algebras, but more tools are needed for calculating the cohomology of general Lie algebras. To calculate the cohomology of general Lie algebras, I used the symbolic software program called Maple. I wrote software to calculate the cohomology in several different ways. I wrote several programs to calculate the cohomology directly. This proved to be computationally expensive as the number of differential forms ...


The Role Of Information Communication Technologies (Icts) In Shaping Identity Threats And Responses, Mary Macharia 2018 University of Arkansas, Fayetteville

The Role Of Information Communication Technologies (Icts) In Shaping Identity Threats And Responses, Mary Macharia

Theses and Dissertations

With the rising use of social media, people are increasingly experiencing, and responding to, identity threats online. This sometimes leads to online backlash via “cybermobs” or the creation of online social movements that traverse offline. Prior information systems (IS) research on identity threats and responses largely focuses on information communication technology (ICT) implementations within organizations in an offline context. Therefore, we lack understanding of ICT-mediated identity threats and responses and ways to promote healthier and productive interactions online. This two-essay dissertation seeks to fill this gap. Essay 1 combines a review of ICT-mediated identity threats with a qualitative study (based ...


Phr: Patient Health Record, Quinn Nelson 2018 University of Nebraska at Omaha

Phr: Patient Health Record, Quinn Nelson

Theses/Capstones/Creative Projects

The rapid development of information technology systems has expanded into multiple disciplines and results in systems that are limited by initial design and implementation: the Healthcare Information Technology (HIT) space is no different. The introduction of the Electronic Health Record (EHR) system has changed the way healthcare operates. Initial designs of these systems were focused on serving the needs of insurance companies and healthcare billing departments. Research shows that the design of EHR systems negatively impact provider-patient interactions and the care they receive. This capstone project capitalizes on the collaboration efforts between UNO and UNMC – by joining a research group ...


Improving Accuracy Of The Edgebox Approach, Kamna Yadav 2018 Utah State University

Improving Accuracy Of The Edgebox Approach, Kamna Yadav

All Graduate Theses and Dissertations

Object region detection plays a vital role in many domains ranging from self-driving cars to lane detection, which heavily involves the task of object detection. Improving the performance of object region detection approaches is of great importance and therefore is an active ongoing research in Computer Vision. Traditional sliding window paradigm has been widely used to identify hundreds of thousands of windows (covering different scales, angles, and aspect ratios for objects) before the classification step. However, it is not only computationally expensive but also produces relatively low accuracy in terms of the classifier output by providing many negative samples. Object ...


Review Of: The World Of Scary Video Games: A Study In Videoludic Horror, Approaches To Digital Game Studies, Matthew Murray 2018 University of Nevada, Las Vegas

Review Of: The World Of Scary Video Games: A Study In Videoludic Horror, Approaches To Digital Game Studies, Matthew Murray

Library Faculty Publications

No abstract provided.


Sheaf Theory As A Foundation For Heterogeneous Data Fusion, Seyed M-H Mansourbeigi 2018 Utah State University

Sheaf Theory As A Foundation For Heterogeneous Data Fusion, Seyed M-H Mansourbeigi

All Graduate Theses and Dissertations

A major impediment to scientific progress in many fields is the inability to make sense of the huge amounts of data that have been collected via experiment or computer simulation. This dissertation provides tools to visualize, represent, and analyze the collection of sensors and data all at once in a single combinatorial geometric object. Encoding and translating heterogeneous data into common language are modeled by supporting objects. In this methodology, the behavior of the system based on the detection of noise in the system, possible failure in data exchange and recognition of the redundant or complimentary sensors are studied via ...


Worker Activity Recognition In Smart Manufacturing Using Imu And Semg Signals With Convolutional Neural Networks, Wenjin Tao, Ze-Hao Lai, Ming-Chuan Leu, Zhaozheng Yin 2018 Missouri University of Science and Technology

Worker Activity Recognition In Smart Manufacturing Using Imu And Semg Signals With Convolutional Neural Networks, Wenjin Tao, Ze-Hao Lai, Ming-Chuan Leu, Zhaozheng Yin

Zhaozheng Yin

In a smart manufacturing system involving workers, recognition of the worker's activity can be used for quantification and evaluation of the worker's performance, as well as to provide onsite instructions with augmented reality. In this paper, we propose a method for activity recognition using Inertial Measurement Unit (IMU) and surface electromyography (sEMG) signals obtained from a Myo armband. The raw 10-channel IMU signals are stacked to form a signal image. This image is transformed into an activity image by applying Discrete Fourier Transformation (DFT) and then fed into a Convolutional Neural Network (CNN) for feature extraction, resulting in ...


Enabling The Social Internet Of Things, Ahmed E. Khaled, Sumi Helal 2018 Northeastern Illinois University

Enabling The Social Internet Of Things, Ahmed E. Khaled, Sumi Helal

Faculty Research and Creative Activities Symposium

No abstract provided.


A Study Of Text Simplification On Breast Cancer Information Targeting A Low-Health Literacy Population, Francisco D. Iacobelli, Xiwei Wang 2018 Northeastern Illinois University

A Study Of Text Simplification On Breast Cancer Information Targeting A Low-Health Literacy Population, Francisco D. Iacobelli, Xiwei Wang

Faculty Research and Creative Activities Symposium

No abstract provided.


Virtual Reality And Visualization In Research And Cultural Preservation, Kari Noe 2018 University of Hawaiʻi at Mānoa

Virtual Reality And Visualization In Research And Cultural Preservation, Kari Noe

Mānoa Horizons

Visualization as a field can be defined as the process of turning data into interactive images to provide insight or knowledge to a user. New innovations in virtual reality hardware open up new opportunities in the field of visualization, rather than merely for entertainment. My research portfolio and poster highlight two visualization projects that I have created that utilize current virtual reality hardware, the HTC Vive and the University of Hawaiʻi at Mānoa’s Laboratory of Advanced Visualization and Applications (LAVA) Destiny-class CyberCANOE. The At-Risk Artifact Visualization System will allow users to view and study 3D models of archaeological artifacts ...


The Automated Design Of Probabilistic Selection Methods For Evolutionary Algorithms, Samuel N. Richter, Daniel R. Tauritz 2018 Missouri University of Science and Technology

The Automated Design Of Probabilistic Selection Methods For Evolutionary Algorithms, Samuel N. Richter, Daniel R. Tauritz

Daniel R. Tauritz

Selection functions enable Evolutionary Algorithms (EAs) to apply selection pressure to a population of individuals, by regulating the probability that an individual's genes survive, typically based on fitness. Various conventional fitness based selection methods exist, each providing a unique relationship between the fitnesses of individuals in a population and their chances of selection. However, the full space of selection algorithms is only limited by max algorithm size, and each possible selection algorithm is optimal for some EA configuration applied to a particular problem class. Therefore, improved performance may be expected by tuning an EA's selection algorithm to the ...


Automated Design Of Network Security Metrics, Aaron Scott Pope, Daniel R. Tauritz, Robert Morning, Alexander D. Kent 2018 Missouri University of Science and Technology

Automated Design Of Network Security Metrics, Aaron Scott Pope, Daniel R. Tauritz, Robert Morning, Alexander D. Kent

Daniel R. Tauritz

Many abstract security measurements are based on characteristics of a graph that represents the network. These are typically simple and quick to compute but are often of little practical use in making real-world predictions. Practical network security is often measured using simulation or real-world exercises. These approaches better represent realistic outcomes but can be costly and time-consuming. This work aims to combine the strengths of these two approaches, developing efficient heuristics that accurately predict attack success. Hyper-heuristic machine learning techniques, trained on network attack simulation training data, are used to produce novel graph-based security metrics. These low-cost metrics serve as ...


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