Other Computer Sciences Commons^™

A High-Precision Machine Learning Algorithm To Classify Left And Right Outflow Tract Ventricular Tachycardia, Jianwei Zhang, Guohua Fu, Islam Abudayyeh, Magdi Yacoub, Anthony Chang, William Feaster, Louis Ehwerhemuepha, Hesham El-Askary, Xianfeng Du, Bin He, Mingjun Feng, Yibo Yu, Binhao Wang, Jing Liu, Hai Yao, Hulmin Chu, Cyril Rakovski

Mathematics, Physics, and Computer Science Faculty Articles and Research

Introduction: Multiple algorithms based on 12-lead ECG measurements have been proposed to identify the right ventricular outflow tract (RVOT) and left ventricular outflow tract (LVOT) locations from which ventricular tachycardia (VT) and frequent premature ventricular complex (PVC) originate. However, a clinical-grade machine learning algorithm that automatically analyzes characteristics of 12-lead ECGs and predicts RVOT or LVOT origins of VT and PVC is not currently available. The effective ablation sites of RVOT and LVOT, confirmed by a successful ablation procedure, provide evidence to create RVOT and LVOT labels for the machine learning model.

Methods: We randomly sampled training, validation, and testing …

Exploring The Efficiency Of Self-Organizing Software Teams With Game Theory, Clay Stevens, Jared Soundy, Hau Chan

School of Computing: Conference and Workshop Papers

Over the last two decades, software development has moved away from centralized, plan-based management toward agile methodologies such as Scrum. Agile methodologies are founded on a shared set of core principles, including self-organizing software development teams. Such teams are promoted as a way to increase both developer productivity and team morale, which is echoed by academic research. However, recent works on agile neglect to consider strategic behavior among developers, particularly during task assignment–one of the primary functions of a self-organizing team. This paper argues that self-organizing software teams could be readily modeled using game theory, providing insight into how agile …

Olympic Games Event Recognition Via Transfer Learning With Photobombing Guided Data Augmentation, Yousef I. Mohamad, Samah S. Baraheem, Tam Van Nguyen

Computer Science Faculty Publications

Automatic event recognition in sports photos is both an interesting and valuable research topic in the field of computer vision and deep learning. With the rapid increase and the explosive spread of data, which is being captured momentarily, the need for fast and precise access to the right information has become a challenging task with considerable importance for multiple practical applications, i.e., sports image and video search, sport data analysis, healthcare monitoring applications, monitoring and surveillance systems for indoor and outdoor activities, and video captioning. In this paper, we evaluate different deep learning models in recognizing and interpreting the sport …

Landlords Of The Digital World: How Territoriality And Social Identity Predict Playing Intensity In Location-Based Games, Samuli Laato, Bastian Kordyaka, A.K.M. Najmul Islam, Konstantinos Papangelis

Presentations and other scholarship

Popular location-based games (LBGs) such as Pokemon GO have been downloaded hundreds of millions of times and have been shown to have a positive impact on mild exercise and social well-being of their players. Several currently popular LBGs introduce a gamified implementation of territorial conflict, where players are divided into teams that battle for the ownership of geographically distributed points of interest. We investigate how social factors and territoriality influence playing intensity in the context of Pok´emon GO. Using reasoning from social identity theory, we propose a structural model connecting territoriality, sociality and playing intensity. To test the model, we …

Collaborative Behavior, Performance And Engagement With Visual Analytics Tasks Using Mobile Devices, Lei Chen, Hai-Ning Liang, Feiyu Lu, Konstantinos Papangelis, Ka Lok Man, Yong Yue

Articles

Interactive visualizations are external tools that can support users’ exploratory activities. Collaboration can bring benefits to the exploration of visual representations or visu‐ alizations. This research investigates the use of co‐located collaborative visualizations in mobile devices, how users working with two different modes of interaction and view (Shared or Non‐Shared) and how being placed at various position arrangements (Corner‐to‐Corner, Face‐to‐Face, and Side‐by‐Side) affect their knowledge acquisition, engagement level, and learning efficiency. A user study is conducted with 60 partici‐ pants divided into 6 groups (2 modes×3 positions) using a tool that we developed to support the exploration of 3D visual …

The Design, Development, And Determination Of A Virtual Reality Classroom, Victoria Alexxis Reddington

Electronic Theses and Dissertations

The COVID-19 pandemic has radically changed the way students learn and engage with their peers and instructors. Likewise, instructors have had to quickly transform their course materials to suit the online classroom format. Results from a survey of students and instructors at the University of Denver revealed that perceived levels of learning and collaboration were lessened with the transition to online learning. Moreover, the sense of presence in an educational atmosphere with other individuals was reported to be significantly stronger in a real physical classroom, as compared to an online classroom. This thesis therefore seeks to provide a new, alternative …

Text Classification Using Novel Term Weighting Scheme-Based Improved Tf-Idf For Internet Media Reports, Zhiying Jiang Phd, Bo Gao, Yanlin He, Yongming Han, Paul Doyle, Qunxiong Zhu

Other

With the rapid development of the internet technology, a large amount of internet text data can be obtained. The text classification (TC) technology plays a very important role in processing massive text data, but the accuracy of classification is directly affected by the performance of term weighting in TC. Due to the original design of information retrieval (IR), term frequency-inverse document frequency (TF-IDF) is not effective enough for TC, especially for processing text data with unbalanced distributions in internet media reports. Therefore, the variance between the DF value of a particular term and the average of all DFs , namely, …

Quantifying Shape Of Star-Like Objects Using Shape Curves And A New Compactness Measure, Gopal K. Mulukutla, Emese Hadnagy, Matthew Fearon, Edward Garboczi

All Materials

Shape is an important indicator of the physical and chemical behavior of natural and engineered particulate materials (e.g., sediment, sand, rock, volcanic ash). It directly or indirectly affects numerous microscopic and macroscopic geologic, environmental and engineering processes. Due to the complex, highly irregular shapes found in particulate materials, there is a perennial need for quantitative shape descriptions. We developed a new characterization method (shape curve analysis) and a new quantitative measure (compactness, not the topological mathematical definition) by applying a fundamental principle that the geometric anisotropy of an object is a unique signature of its internal spatial distribution …

A Customizable Speech Practice Application For People Who Stutter, Eric Grimm, Nikola Vuckovic

Honors Program Theses

Stuttering is a speech impediment that often requires speech therapy to curb the symptoms. In speech therapy, people who stutter (PWS) learn techniques that they can use to improve their fluency. PWS often practice their techniques extensively in order to maintain fluent speech. Many listen to audio recordings to practice where a single word or sentence is played on the recording and then there is a pause, giving the user a chance to say the word(s) to practice. This style of practice is not customizable and is repetitive since the contents do not change. Thus, we have developed an application …

R2u3d: Recurrent Residual 3d U-Net For Lung Segmentation, Dhaval D. Kadia, Md Zahangir Alom, Ranga Burada, Tam Nguyen, Vijayan K. Asari

Computer Science Faculty Publications

3D Lung segmentation is essential since it processes the volumetric information of the lungs, removes the unnecessary areas of the scan, and segments the actual area of the lungs in a 3D volume. Recently, the deep learning model, such as U-Net outperforms other network architectures for biomedical image segmentation. In this paper, we propose a novel model, namely, Recurrent Residual 3D U-Net (R(2)U3D), for the 3D lung segmentation task. In particular, the proposed model integrates 3D convolution into the Recurrent Residual Neural Network based on U-Net. It helps learn spatial dependencies in 3D and increases the propagation of 3D volumetric …

A Hybrid Decision Tree - Neural Network (Dt-Nn) Model For Predictive Maintenance Applications In Aircraft, Jarrod Carson

Honors Theses

As the Age of Information has evolved over the last several decades, the demand for technology which stores, analyzes, and utilizes data has increased substantially. For countless industries such as the medical, retail, and aircraft industries, such technology is crucial to their operation. This project proposes a hybrid machine learning model consisting of Decision Trees and Neural Networks which is able to classify data of varying volume and variety effectively and efficiently. The model’s structure consists of a decision tree with each node of the tree containing a neural network trained to classify a specific category of the output using …

Automatic Hierarchy Expansion For Improved Structure And Chord Evaluation, Katherine M. Kinnaird, Brian Mcfee

Statistical and Data Sciences: Faculty Publications

No abstract provided.

Uncovering Object Categories In Infant Views, Naiti S. Bhatt

Scripps Senior Theses

While adults recognize objects in a near-instant, infants must learn how to categorize the objects in their visual environments. Recent work has shown that egocentric head-mounted camera videos contain rich data that illuminate the infant experience (Clerkin et al., 2017; Franchak et al., 2011; Yoshida & Smith, 2008). While past work has focused on the social information in view, in this work, we aim to characterize the objects in infants’ at-home visual environments by modifying modern computer vision models for the infant view. To do so, we collected manual annotations of objects that infants seemed to be interacting within a …

Interactive Visual Self-Service Data Classification Approach To Democratize Machine Learning, Sridevi Narayana Wagle

All Master's Theses

Machine learning algorithms often produce models considered as complex black-box models by both end users and developers. Such algorithms fail to explain the model in terms of the domain they are designed for. The proposed Iterative Visual Logical Classifier (IVLC) is an interpretable machine learning algorithm that allows end users to design a model and classify data with more confidence and without having to compromise on the accuracy. Such technique is especially helpful when dealing with sensitive and crucial data like cancer data in the medical domain with high cost of errors. With the help of the proposed interactive and …

Design Project: Smart Headband, John Michel, Jack Durkin, Noah Lewis

Williams Honors College, Honors Research Projects

Concussion in sports is a prevalent medical issue. It can be difficult for medical professionals to diagnose concussions. With the fast pace nature of many sports, and the damaging effects of concussions, it is important that any concussion risks are assessed immediately. There is a growing trend of wearable technology that collects data such as steps and provides the wearer with in-depth information regarding their performance. The Smart Headband project created a wearable that can record impact data and provide the wearer with a detailed analysis on their risk of sustaining a concussion. The Smart Headband uses accelerometers and gyroscopes …

Interactive Virtual Reality Reading Experience, Nathaniel Shetler

Williams Honors College, Honors Research Projects

The project is an interactive virtual reality reading experience. The user is able to read a book or story in VR. When certain achievements are reached, such as finishing a chapter, the user is given the opportunity to transport to the environment that they are reading about. This gives the user a great opportunity to interact and learn hands-on with the material they are reading about. For example, if the user is reading about World War I, they will be given the opportunity to transport to the battlefields/trenches in Europe.

Optimizing Sparse Tensor Computations Via Orderings And Multilayered Data-Structures, Trevor Garnett

Summer Community of Scholars Posters (RCEU and HCR Combined Programs)

No abstract provided.

Evaluation Of Traceability Management Tools For Student Software Development, Abi Kunkle

Summer Community of Scholars Posters (RCEU and HCR Combined Programs)

No abstract provided.

The Data Science Corps Wrangle-Analyze- Visualize Program: Building Data Acumen For Undergraduate Students, Nicholas J. Horton, Benjamin Baumer, Andrew Zieffler, Valerie Barr

Statistical and Data Sciences: Faculty Publications

We congratulate Kolaczyk, Wright, and Yajima on their innovative statistics practicum that places “practice” at the center of data science education (Kolaczyk et al., 2021, this issue). Their year-long practicum course focuses on the data science life cycle with engagement with external partners and university consulting projects. We agree that training postgraduates in practice needs to be foregrounded in the curriculum in order for students to develop necessary depth in data science practice.

Understanding The Research And Applications Of Quantum Computing, Joshua Foss

Williams Honors College, Honors Research Projects

In-Depth research of current quantum computing understanding and practices. Presentation of possible new and creative applications of quantum computing.