Physical Sciences and Mathematics Commons^™

Teaching Applications And Implications Of Blockchain Via Project-Based Learning: A Case Study, Kevin Mentzer, Mark Frydenberg, David J. Yates

Information Systems and Analytics Department Faculty Journal Articles

This paper presents student projects analyzing or using blockchain technologies, created by students enrolled in courses dedicated to teaching blockchain, at two different universities during the 2018-2019 academic year. Students explored perceptions related to storing private healthcare information on a blockchain, managing the security of Internet of Things devices, maintaining public governmental records, and creating smart contracts. The course designs, which were centered around project-based learning, include self-regulated learning and peer feedback as ways to improve student learning. Students either wrote a research paper or worked in teams on a programming project to build and deploy a blockchain-based application using …

Chicago Alliance For Equity In Computer Science, Steven Mcgee, Lucia Dettori, Ronald I. Greenberg, Andrew M. Rasmussen, Dale F. Reed, Don Yanek

Computer Science: Faculty Publications and Other Works

In 2016, CPS enacted a high school computer science graduation requirement as a means to broaden participation in computer science. ECS is the primary course that supports enactment of this policy. With limited numbers of certified computer science teachers, CPS relied on teachers from a variety of disciplines to teach ECS. The ECS professional development program is designed to prepare teachers from all backgrounds to support student success in ECS. This study examines how the profile of ECS teachers changed and the impact of that change on teachers' experiences with ECS professional development.

New Methods For Deep Learning Based Real-Valued Inter-Residue Distance Prediction, Jacob Barger

Theses

Background: Much of the recent success in protein structure prediction has been a result of accurate protein contact prediction--a binary classification problem. Dozens of methods, built from various types of machine learning and deep learning algorithms, have been published over the last two decades for predicting contacts. Recently, many groups, including Google DeepMind, have demonstrated that reformulating the problem as a multi-class classification problem is a more promising direction to pursue. As an alternative approach, we recently proposed real-valued distance predictions, formulating the problem as a regression problem. The nuances of protein 3D structures make this formulation appropriate, allowing predictions …

Analyzing Yankees And Red Sox Sentiment Over The Course Of A Season, Connor Koch

Honors Projects in Data Science

This paper investigates data collected on twitter which references the Yankees or Red Sox during the 2020 Major League Baseball (MLB) season. The objective is to analyze the sentiment of tweets referencing the Yankees and Red Sox over the course of the season. In addition, an investigation of the networks within the data and the topics that were prevalent will be conducted. The 2020 MLB season was started late because of the COVID-19 pandemic and was a season like no other. The expectation of a dataset revolving around baseball is that the topics discussed would be about baseball. The findings …

Asymptotically-Optimal Topological Nearest-Neighbor Filtering, Read Sandström, Jory Denny, Nancy M. Amato

Department of Math & Statistics Faculty Publications

Nearest-neighbor finding is a major bottleneck for sampling-based motion planning algorithms. The cost of finding nearest neighbors grows with the size of the roadmap, leading to a significant computational bottleneck for problems which require many configurations to find a solution. In this work, we develop a method of mapping configurations of a jointed robot to neighborhoods in the workspace that supports fast search for configurations in nearby neighborhoods. This expedites nearest-neighbor search by locating a small set of the most likely candidates for connecting to the query with a local plan. We show that this filtering technique can preserve asymptotically-optimal …

Computer Science Teacher Survey, Josh B. Mcgee, Sarah C. Mckenzie

Arkansas Education Reports

In April/May of 2020, the University of Arkansas’ Office for Education Policy (OEP), in partnership with Arkansas Governor Asa Hutchinson's Computer Science and Cyber Security Task Force, fielded a survey with the 400+ Arkansas educators who at that time held a computer science endorsement (528), computer science approval code (5016), or computer science technical permit (5014) on their educator’s license. The survey received 153 responses, a nearly 40 percent response rate.

Find Me If You Can: Aligning Users In Different Social Networks, Priyanka Kasbekar, Katerina Potika, Chris Pollett

Faculty Publications, Computer Science

Online Social Networks allow users to share experiences with friends and relatives, make announcements, find news and jobs, and more. Several have user bases that number in the hundred of millions and even billions. Very often many users belong to multiple social networks at the same time under possibly different user names. Identifying a user from one social network on another social network gives information about a user's behavior on each platform, which in turn can help companies perform graph mining tasks, such as community detection and link prediction. The process of identifying or aligning users in multiple networks is …

An Analysis Of Syntax Exercises On The Performance Of Cs1 Students, Shelsey B. Sullivan

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Students in introductory programming classes (CS1) generally have a difficult time learning the rules of programming. Although the general concepts of programming are relatively easy to learn, it can be difficult to learn what exactly can be typed in what order, which is known as syntax. To attempt to help students overcome this barrier, a study was conducted that introduced exercises into a CS1 class which taught the programming syntax in simple steps. The results of this study were obtained by analyzing the keys the students pressed, the errors of their code, their midterm exam scores, and their responses to …

Improving Convolutional Neural Network Robustness To Adversarial Images Through Image Filtering, Natalie E. Bogda

Masters Theses

The field of computer vision and deep learning is known for its ability to recognize images with extremely high accuracy. Convolutional neural networks exist that can correctly classify 96\% of 1.2 million images of complex scenes. However, with just a few carefully positioned imperceptible changes to the pixels of an input image, an otherwise accurate network will misclassify this almost identical image with high confidence. These perturbed images are known as \textit{adversarial examples} and expose that convolutional neural networks do not necessarily "see" the world in the way that humans do. This work focuses on increasing the robustness of classifiers …

A Computer Science Academic Vocabulary List, David Roesler

Dissertations and Theses

This thesis documents the development of the Computer Science Academic Vocabulary List (CSAVL), a pedagogical tool intended for use by English-for-specific-purpose educators and material developers. A 3.5-million-word corpus of academic computer science textbooks and journal articles was developed in order to produce the CSAVL. This study draws on the improved methodologies used in the creation of recent lemma-based word lists such as the Academic Vocabulary List (AVL) and the Medical Academic Vocabulary List (MAVL), which take into account the discipline-specific meanings of academic vocabulary. The CSAVL provides specific information for each entry, including part of speech and CS-specific meanings in …

Being Human In Stem Csc 213x, Harrison Dekker

Library Impact Statements

No abstract provided.

Exploring Covid-19 Data Csc 292, Harrison Dekker

Library Impact Statements

No abstract provided.

Engagement And Computational Thinking Through Creative Coding, Dana Hoppe

Honors Theses

Rising enrollments in Computer Science pose an opportunity to engage students from diverse backgrounds and interests; and a challenge to deliver on positive learning outcomes. While student engagement is the driving factor for increased learning performance and retention, it has been declining to new lows for Computer Science students in recent years. In order to further explore the potential of contextualized computing as a tool for increasing engagement in computing and developing Computational Thinking aptitude in students, we have developed an introductory computing course contextualized with Art and Design with modules centered around guiding pedagogical principles and aimed at middle …

Devops: Architecting Your Infrastructure (Syllabus), Jeremy Andrews, Nyc Tech-In-Residence Corps

Open Educational Resources

Syllabus for the "DevOps" course delivered at the City College of New York in Spring 2020 by Jeremy Andrews as part of the Tech-in-Residence Corps program.

Devops: Lecture 1 - "Overview", Jeremy Andrews, Nyc Tech-In-Residence Corps

Open Educational Resources

Overview lecture for the "DevOps" course delivered at the City College of New York in Spring 2020 by Jeremy Andrews as part of the Tech-in-Residence Corps program.

Some Advice For Psychologists Who Want To Work With Computer Scientists On Big Data, Cornelius J. König, Andrew M. Demetriou, Philipp Glock, Annemarie M. F. Hiemstra, Dragos Iliescu, Camelia Ionescu, Markus Langer, Cynthia C. S. Liem, Anja Linnenbürger, Rudolf Siegel, Ilias Vartholomaios

Personnel Assessment and Decisions

This article is based on conversations from the project “Big Data in Psychological Assessment” (BDPA) funded by the European Union, which was initiated because of the advances in data science and artificial intelligence that offer tremendous opportunities for personnel assessment practice in handling and interpreting this kind of data. We argue that psychologists and computer scientists can benefit from interdisciplinary collaboration. This article aims to inform psychologists who are interested in working with computer scientists about the potentials of interdisciplinary collaboration, as well as the challenges such as differing terminologies, foci of interest, data quality standards, approaches to data analyses, …

A Multi-Branch Separable Convolution Neural Network For Pedestrian Attribute Recognition, Imran N. Junejo, Naveed Ahmed

All Works

© 2020 The Authors Computer science; Computer Vision; Image processing; Deep learning; Pedestrian attribute recognition

Experiential Learning In The Technology Disciplines February 2020, Patricia Sendall, Christopher S. Stuetzle, Zachary A. Kissel, Tahir Hameed

Computer Science Faculty Publications

Learning-by-doing has long been a tradition in the technology disciplines. It is the "hands-on" work, combined with student reflection, feedback and assessment, that reinforces theory into practice. Over the past 40 years, experiential learning (EL) in higher education has grown beyond in-class assignments to include internships, cooperative education, team-based learning, project-based learning, community engagement, service learning, international and study-away experiences, capstone projects and research opportunities. This paper provides an overview of experiential education theory and practice in the undergraduate technology disciplines, and presents examples of how experiential learning practices have evolved over time at a medium-sized institution in the Northeast …

Ms In Quantum Computing, Joanna M. Burkhardt

Library Impact Statements

No abstract provided.

Using Natural Language Processing To Categorize Fictional Literature In An Unsupervised Manner, Dalton J. Crutchfield

Electronic Theses and Dissertations

When following a plot in a story, categorization is something that humans do without even thinking; whether this is simple classification like “This is science fiction” or more complex trope recognition like recognizing a Chekhov's gun or a rags to riches storyline, humans group stories with other similar stories. Research has been done to categorize basic plots and acknowledge common story tropes on the literary side, however, there is not a formula or set way to determine these plots in a story line automatically. This paper explores multiple natural language processing techniques in an attempt to automatically compare and cluster …

Prediction Of Sudden Cardiac Death Using Ensemble Classifiers, Ayman Momtaz El-Geneidy

CCE Theses and Dissertations

Sudden Cardiac Death (SCD) is a medical problem that is responsible for over 300,000 deaths per year in the United States and millions worldwide. SCD is defined as death occurring from within one hour of the onset of acute symptoms, an unwitnessed death in the absence of pre-existing progressive circulatory failures or other causes of deaths, or death during attempted resuscitation. Sudden death due to cardiac reasons is a leading cause of death among Congestive Heart Failure (CHF) patients. The use of Electronic Medical Records (EMR) systems has made a wealth of medical data available for research and analysis. Supervised …

A Pcnn Framework For Blood Cell Image Segmentation, Carol D. Lenihan

CCE Theses and Dissertations

This research presents novel methods for segmenting digital blood cell images under a Pulse Coupled Neural Network (PCNN) framework. A blood cell image contains different types of blood cells found in the peripheral blood stream such as red blood cells (RBCs), white blood cells (WBCs), and platelets. WBCs can be classified into five normal types – neutrophil, monocyte, lymphocyte, eosinophil, and basophil – as well as abnormal types such as lymphoblasts and others. The focus of this research is on identifying and counting RBCs, normal types of WBCs, and lymphoblasts. The total number of RBCs and WBCs, along with classification …

The Perceptions And Lived Experiences Of Female Students In A Computer Science Program At A Community College, Terry Voldase

Walden Dissertations and Doctoral Studies

America's higher education institutions have aligned computer science curricula with today's modern technology. Despite these efforts, data have shown that there is slow growth among young women majoring in computer science and even slower growth in this area at community colleges. Higher education institutions have also acknowledged a gap between men and women entering the computer science field and a need to explore options for computer science programs to engage women in the industry. The purpose of this phenomenological study was to gain an understanding of the perceptions and lived experiences of female students enrolled in computer classes at New …

Examination Of Practices Used By Ap Computer Science Teachers With Higher Than Average Female Enrollment, Derek J. Miller

Graduate Research Theses & Dissertations

This dissertation examines the practices employed by AP Computer Science A teachers that can help recruit and retain female students in computer science. A survey was sent to teachers to see what practices they used in their classrooms and what practices they thought had the biggest influence on female student recruitment and retention. Of the five practice categories (recruitment, pedagogical, curricular, extracurricular, and mentoring), the survey respondents thought recruitment was the most influential and curricular was the least influential. After the survey, 12 teachers were chosen for interviews because they had a higher enrollment of female students than the rest …

A Tutorial And Future Research For Building A Blockchain-Based Secure Communication Scheme For Internet Of Intelligent Things, Mohammad Wazid, Ashok Kumar Das, Sachin Shetty, Minho Jo

Computational Modeling & Simulation Engineering Faculty Publications

The Internet of Intelligent Things (IoIT) communication environment can be utilized in various types of applications (for example, intelligent battlefields, smart healthcare systems, the industrial internet, home automation, and many more). Communications that happen in such environments can have different types of security and privacy issues, which can be resolved through the utilization of blockchain. In this paper, we propose a tutorial that aims in desiging a generalized blockchain-based secure authentication key management scheme for the IoIT environment. Moreover, some issues with using blockchain for a communication environment are discussed as future research directions. The details of different types of …

Social Media Based Algorithmic Clinical Decision Support Learning From Behavioral Predispositions, Radhika V. Medury

Doctoral Dissertations

Behavioral disorders are disabilities characterized by an individual’s mood, thinking, and social interactions. The commonality of behavioral disorders amongst the United States population has increased in the last few years, with an estimated 50% of all Americans diagnosed with a behavioral disorder at some point in their lifetime. AttentionDeficit/Hyperactivity Disorder is one such behavioral disorder that is a severe public health concern because of its high prevalence, incurable nature, significant impact on domestic life, and peer relationships. Symptomatically, in theory, ADHD is characterized by inattention, hyperactivity, and impulsivity. Access to providers who can offer diagnosis and treat the disorder varies …

An Adversarial Framework For Deep 3d Target Template Generation, Walter E. Waldow

Browse all Theses and Dissertations

This paper presents a framework for the generation of 3D models. This is an important problem for many reasons. For example, 3D models are important for systems that are involved in target recognition. These systems use 3D models to train up accuracy on identifying real world object. Traditional means of gathering 3D models have limitations that the generation of 3D models can help overcome. The framework uses a novel generative adversarial network (GAN) that learns latent representations of two dimensional views of a model to bootstrap the network’s ability to learn to generate three dimensional objects. The novel architecture is …

Ethics, Privacy And Data Collection: A Complex Intersection, Matthew S. Brown

Honors Theses

The technology around us enables incredible abilities such as high-resolution video calls and the ability to stay connected with everyone we care about through social media. This technology also comes with a hidden cost in the form of data collection.

This work explores what privacy means and how users understand what data social media companies collect and monetize. This thesis also proposes a more ethical business model that addresses privacy concerns from an individual perspective.

Identifying Knowledge Gaps Using A Graph-Based Knowledge Representation, Daniel P. Schmidt

Browse all Theses and Dissertations

Knowledge integration and knowledge bases are becoming more and more prevalent in the systems we use every day. When developing these knowledge bases, it is important to ensure the correctness of the information upon entry, as well as allow queries of all sorts; for this, understanding where the gaps in knowledge can arise is critical. This thesis proposes a descriptive taxonomy of knowledge gaps, along with a framework for automated detection and resolution of some of those gaps. Additionally, the effectiveness of this framework is evaluated in terms of successful responses to queries on a knowledge base constructed from a …