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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.


Safe Automated Refactoring For Intelligent Parallelization Of Java 8 Streams, Raffi T. Khatchadourian, Yiming Tang, Mehdi Bagherzadeh, Syed Ahmed 2019 CUNY Hunter College

Safe Automated Refactoring For Intelligent Parallelization Of Java 8 Streams, Raffi T. Khatchadourian, Yiming Tang, Mehdi Bagherzadeh, Syed Ahmed

Publications and Research

Streaming APIs are becoming more pervasive in mainstream Object-Oriented programming languages. For example, the Stream API introduced in Java 8 allows for functional-like, MapReduce-style operations in processing both finite and infinite data structures. However, using this API efficiently involves subtle considerations like determining when it is best for stream operations to run in parallel, when running operations in parallel can be less efficient, and when it is safe to run in parallel due to possible lambda expression side-effects. In this paper, we present an automated refactoring approach that assists developers in writing efficient stream code in a semantics-preserving fashion. The ...


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 ...


2019 Petersheim Academic Exposition Schedule Of Events, Seton Hall University 2019 Seton Hall University

2019 Petersheim Academic Exposition Schedule Of Events, Seton Hall University

Petersheim Academic Exposition

2019 Petersheim Academic Exposition


Software Acquisition And Project Management (Ksu), Rebecca Rutherfoord, Dawn Tatum, Susan VandeVen, Richard Halstead-Nussloch, James Rutherfoord, Zhigang Li 2019 Kennesaw State University

Software Acquisition And Project Management (Ksu), Rebecca Rutherfoord, Dawn Tatum, Susan Vandeven, Richard Halstead-Nussloch, James Rutherfoord, Zhigang Li

Computer Science and Information Technology Grants Collections

This Grants Collection for Software Acquisition and Project Management was created under a Round Eleven ALG Textbook Transformation Grant.

Affordable Learning Georgia Grants Collections are intended to provide faculty with the frameworks to quickly implement or revise the same materials as a Textbook Transformation Grants team, along with the aims and lessons learned from project teams during the implementation process.

Documents are in .pdf format, with a separate .docx (Word) version available for download. Each collection contains the following materials:

  • Linked Syllabus
  • Initial Proposal
  • Final Report


Csci 380-04 Selected Topics In Computer Science: Mobile Application And Product Development, Bhargava Chinthirla, Eric Spector, NYC Tech-in-Residence Corps 2019 CUNY John Jay College

Csci 380-04 Selected Topics In Computer Science: Mobile Application And Product Development, Bhargava Chinthirla, Eric Spector, Nyc Tech-In-Residence Corps

Open Educational Resources

No abstract provided.


Csci 381/780 Data Analytics, Kumar Ramansenthil, NYC Tech-in-Residence Corps 2019 CUNY Queens College

Csci 381/780 Data Analytics, Kumar Ramansenthil, Nyc Tech-In-Residence Corps

Open Educational Resources

No abstract provided.


Cis 356 Digital Trends And Transformations, Douglas Ng, NYC Tech-in-Residence Corps 2019 CUNY Lehman College

Cis 356 Digital Trends And Transformations, Douglas Ng, Nyc Tech-In-Residence Corps

Open Educational Resources

No abstract provided.


Google Trends Data As A Proxy For Interest In Leadership, Finley W. Walker 2019 Southeastern University - Lakeland

Google Trends Data As A Proxy For Interest In Leadership, Finley W. Walker

College of Education

The purpose of this quantitative study was to investigate the observable patterns of online search behavior in the topic of leadership using Google Trends data. Institutions have had a historically difficult time predicting good leadership candidates. Better predictions can be made by using the big data offered by groups such as Google to learn who, where, and when people are interested in leadership. The study utilized descriptive, comparative, and correlative methodologies to study Google users’ interest in leadership from 2004 to 2017. Society has placed great value into leadership throughout history, and though overall interest remains strong, it appears that ...


Csc 21700 Probability And Statistics For Computer Science, Evan Agovino, NYC Tech-in-Residence Corps 2019 CUNY City College

Csc 21700 Probability And Statistics For Computer Science, Evan Agovino, Nyc Tech-In-Residence Corps

Open Educational Resources

No abstract provided.


Algorithms To Approximate Solutions Of Poisson's Equation In Three Dimensions, Ray Dambrose 2019 University of Mary Washington

Algorithms To Approximate Solutions Of Poisson's Equation In Three Dimensions, Ray Dambrose

Rose-Hulman Undergraduate Mathematics Journal

The focus of this research was to develop numerical algorithms to approximate solutions of Poisson's equation in three dimensional rectangular prism domains. Numerical analysis of partial differential equations is vital to understanding and modeling these complex problems. Poisson's equation can be approximated with a finite difference approximation. A system of equations can be formed that gives solutions at internal points of the domain. A computer program was developed to solve this system with inputs such as boundary conditions and a nonhomogenous source function. Approximate solutions are compared with exact solutions to prove their accuracy. The program is tested ...


Demo: A Low-Cost Fleet Monitoring System, Lotfi ben Othmane, Venecia Alvarez, Kendall Berner, Matthew Fuhrmann, William Fuhrmann, Anthony Guss, Tyler Hartsock 2019 Iowa State University

Demo: A Low-Cost Fleet Monitoring System, Lotfi Ben Othmane, Venecia Alvarez, Kendall Berner, Matthew Fuhrmann, William Fuhrmann, Anthony Guss, Tyler Hartsock

Lotfi ben Othmane

Organizations use fleet monitoring systems for e.g., vehicle tracking, driver behavior analysis, and efficient fleet management. Current systems are designed for commercial use and are of high cost. We present a prototype of a low-cost fleet monitoring system that could be used for non-commercial applications. The system is composed of a device, a service application, and a Web application. The device reads data such as speed and fuel from the internal network of the connected vehicle and the location of the vehicle and sends them to a remote service. The remote service processes and stores the data. The users ...


Poster: Image Disguising For Privacy-Preserving Deep Learning, Sagar Sharma, Keke Chen 2019 Wright State University - Main Campus

Poster: Image Disguising For Privacy-Preserving Deep Learning, Sagar Sharma, Keke Chen

Keke Chen

No abstract provided.


Poster: Privacy-Preserving Boostingwith Random Linear Classifiers, Sagar Sharma, Keke Chen 2019 Wright State University - Main Campus

Poster: Privacy-Preserving Boostingwith Random Linear Classifiers, Sagar Sharma, Keke Chen

Keke Chen

We propose SecureBoost, a privacy-preserving predictive modeling framework, that allows service providers (SPs) to build powerful boosting models over encrypted or randomly masked user submit- ted data. SecureBoost uses random linear classifiers (RLCs) as the base classifiers. A Cryptographic Service Provider (CSP) manages keys and assists the SP’s processing to reduce the complexity of the protocol constructions. The SP learns only the base models (i.e., RLCs) and the CSP learns only the weights of the base models and a limited leakage function. This separated parameter holding avoids any party from abusing the final model or conducting model-based attacks ...


Towards Practical Privacy-Preserving Analytics For Iot And Cloud Based Healthcare Systems, Sagar Sharma, Keke Chen, Amit P. Sheth 2019 Wright State University - Main Campus

Towards Practical Privacy-Preserving Analytics For Iot And Cloud Based Healthcare Systems, Sagar Sharma, Keke Chen, Amit P. Sheth

Keke Chen

Modern healthcare systems now rely on advanced computing methods and technologies, such as IoT devices and clouds, to collect and analyze personal health data at unprecedented scale and depth. Patients, doctors, healthcare providers, and researchers depend on analytical models derived from such data sources to remotely monitor patients, early-diagnose diseases, and find personalized treatments and medications. However, without appropriate privacy protection, conducting data analytics becomes a source of privacy nightmare. In this paper, we present the research challenges in developing practical privacy-preserving analytics in healthcare information systems. The study is based on kHealth - a personalized digital healthcare information system that ...


Augmented Personalized Health: Using Semantically Integrated Multimodal Data For Patient Empowered Health Management Strategies, Amit P. Sheth, Hong Y. Yip, Utkarshani Jaimini, Dipesh Kadariya, Vaikunth Sridharan, R. Venkataramanan, Tanvi Banerjee, Krishnaprasad Thirunarayan, Maninder Kalra 2019 Wright State University - Main Campus

Augmented Personalized Health: Using Semantically Integrated Multimodal Data For Patient Empowered Health Management Strategies, Amit P. Sheth, Hong Y. Yip, Utkarshani Jaimini, Dipesh Kadariya, Vaikunth Sridharan, R. Venkataramanan, Tanvi Banerjee, Krishnaprasad Thirunarayan, Maninder Kalra

Krishnaprasad Thirunarayan

Healthcare as we know it is in the process of going through a massive change from:

1. Episodic to continuous

2. Disease-focused to wellness and quality of life focused

3. Clinic-centric to anywhere a patient is

4. Clinician controlled to patient empowered

5. Being driven by limited data to 360-degree, multimodal personal-public-population physical-cyber-social big data-driven URL: https://mhealth.md2k.org/2018-tech-showcase-home


Personalized Prediction Of Suicide Risk For Web-Based Intervention, Amanuel Alambo, Manas Gaur, Ugur Kursuncu, Krishnaprasad Thirunarayan, Jeremiah Schumm, Jyotishman Pathak, Amit P. Sheth 2019 Wright State University - Main Campus

Personalized Prediction Of Suicide Risk For Web-Based Intervention, Amanuel Alambo, Manas Gaur, Ugur Kursuncu, Krishnaprasad Thirunarayan, Jeremiah Schumm, Jyotishman Pathak, Amit P. Sheth

Krishnaprasad Thirunarayan

Across the United States, suicide is the second leading cause of death for people aged between 15 and 34, and younger people are more prone to mental health problems, suicidal thoughts, and behaviors. For instance, 80% of patients with Borderline Personality Disorder have suicide-related behaviors, and between 4-9% of them commit suicide. Moreover, the social stigma associated with mental health issues and suicide deter patients from sharing their experiences directly with others. In such a situation, social media that provides a free and open forum for voluntary expression can provide insights into suicide ideation and self-destructive behavior.

Reddit is a ...


"What's Ur Type?" Contextualized Classification Of User Types In Marijuana-Related Communications Using Compositional Multiview Embedding, Ugur Kursuncu, Manas Gaur, Usha Lokala, Anurag Illendula, Krishnaprasad Thirunarayan, Raminta Daniulaityte, Amit P. Sheth, Budak Arpinar 2019 Wright State University - Main Campus

"What's Ur Type?" Contextualized Classification Of User Types In Marijuana-Related Communications Using Compositional Multiview Embedding, Ugur Kursuncu, Manas Gaur, Usha Lokala, Anurag Illendula, Krishnaprasad Thirunarayan, Raminta Daniulaityte, Amit P. Sheth, Budak Arpinar

Krishnaprasad Thirunarayan

With 93% of pro-marijuana population in US favoring legalization of medical marijuana, high expectations of a greater return for Marijuana stocks, and public actively sharing information about medical, recreational and business aspects related to marijuana, it is no surprise that marijuana culture is thriving on Twitter. After the legalization of marijuana for recreational and medical purposes in 29 states, there has been a dramatic increase in the volume of drug-related communication on Twitter. Specifically, Twitter accounts have been established for promotional and informational purposes, some prominent among them being American Ganja, Medical Marijuana Exchange, and Cannabis Now. Identification and characterization ...


Question Answering For Suicide Risk Assessment Using Reddit, Amanuel Alambo, Usha Lokala, Ugur Kursuncu, Krishnaprasad Thirunarayan, Amelia Gyrard, Randon S. Welton, Jyotishman Pathak, Amit P. Sheth 2019 Wright State University - Main Campus

Question Answering For Suicide Risk Assessment Using Reddit, Amanuel Alambo, Usha Lokala, Ugur Kursuncu, Krishnaprasad Thirunarayan, Amelia Gyrard, Randon S. Welton, Jyotishman Pathak, Amit P. Sheth

Krishnaprasad Thirunarayan

Mental Health America designed ten questionnaires that are used to determine the risk of mental disorders. They are also commonly used by Mental Health Professionals (MHPs) to assess suicidality. Specifically, the Columbia Suicide Severity Rating Scale (C-SSRS), a widely used suicide assessment questionnaire, helps MHPs determine the severity of suicide risk and offer an appropriate treatment. A major challenge in suicide treatment is the social stigma wherein the patient feels reluctance in discussing his/her conditions with an MHP, which leads to inaccurate assessment and treatment of patients. On the other hand, the same patient is comfortable freely discussing his ...


Identifying Depressive Disorder In The Twitter Population, Goonmeet Bajaj, Amir Hossein Yazdavar, Krishnaprasad Thirunarayan, Amit Sheth 2019 Wright State University - Main Campus

Identifying Depressive Disorder In The Twitter Population, Goonmeet Bajaj, Amir Hossein Yazdavar, Krishnaprasad Thirunarayan, Amit Sheth

Krishnaprasad Thirunarayan

Depression is a highly prevalent public health challenge and a major cause of disability across the globe.

  • Annually 6.7% of Americans (that is, more than 16 million).
  • Traditional approaches to curb depression involve survey·based methods via phone or online questionnaires.
  • Large temporal gaps and cognitive bias.

Social media provides a method for learning users' feelings, emotions, behaviors, and decisions in real-time.


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