Other Computer Sciences Commons^™

A Vertical Cooperation Model To Manage Digital Collections And Institutional Resources, Jack M. Maness, Kim Pham, Fernando Reyes, Jeff Rynhart

University Libraries: Faculty Scholarship

The technology space of the University of Denver Libraries to manage digital collections and institutional resources isn’t relegated to one department on campus – rather, it distributed across a network of collaborators with the skills and expertise to provide that support. The infrastructure, which is comprised of an archival metadata management system (Archivespace), a digital repository (Node.js + ElasticSearch), preservation storage (ArchivesDirect), and a streaming server (Kaltura) is independently but cooperatively managed across IT, library departments and vendors. The coordinated eort of digital curation activities still allows each group to focus on the service they have the most vested interest …

Completing A Crowdsourcing Task Instead Of An Assignment; What Do University Students Think?, Javed-Vassilis Khan, Konstantinos Papangelis, Panos Markopoulos

Presentations and other scholarship

University educators actively seek realistic projects to include in their educational activities. However, finding an actually realistic project is not trivial. The rise of crowdsourcing platforms, in which a variety of tasks are offered in the form of an open call, might be an alternative source to help educators scaleup project-based learning. But how do university students feel about executing crowdsourcing tasks instead of their typical assignments? In a study with 24 industrial design students, we investigate students' attitudes on introducing crowdsourcing tasks as assignments. Based on our study we offer four suggestions to universities that consider integrating crowdsourcing tasks …

Smart Cities At Play: Lived Experiences, Emerging Forms Of Playfulness, And Problems Of Participation, Konstantinos Papangelis, Jin-Ha Lee, Michael Saker, Catherine Jones

Presentations and other scholarship

In recent years, the notion of smart cities has become the focus of a growing body of research. To date, much of this attention has revolved around the technical aspect, with related concerns including the creation and implementation of suitable smart city technologies. What is notably missing from these discussions, however, is a consideration of the lived experience of supposedly 'smart spaces' and the extent to which physical and digital environments are currently producing new forms of play and playfulness that can be contextualized within this field. With this in mind, the purpose of our workshop is as follows. First, …

Quantum Computing And Quantum Algorithms, Daniel Serban

Senior Honors Theses

The field of quantum computing and quantum algorithms is studied from the ground up. Qubits and their quantum-mechanical properties are discussed, followed by how they are transformed by quantum gates. From there, quantum algorithms are explored as well as the use of high-level quantum programming languages to implement them. One quantum algorithm is selected to be implemented in the Qiskit quantum programming language. The validity and success of the resulting computation is proven with matrix multiplication of the qubits and quantum gates involved.

Philosophical Perspectives, Jochen Albrecht

Publications and Research

This entry follows in the footsteps of Anselin’s famous 1989 NCGIA working paper entitled “What is special about spatial?” (a report that is very timely again in an age when non-spatial data scientists are ignorant of the special characteristics of spatial data), where he outlines three unrelated but fundamental characteristics of spatial data. In a similar vein, I am going to discuss some philosophical perspectives that are internally unrelated to each other and could warrant individual entries in this Body of Knowledge. The first one is the notions of space and time and how they have evolved in …

Fast Clustering Using A Grid-Based Underlying Density Function Approximation, Daniel Brown

Master of Science in Computer Science Theses

Clustering is an unsupervised machine learning task that seeks to partition a set of data into smaller groupings, referred to as “clusters”, where items within the same cluster are somehow alike, while differing from those in other clusters. There are many different algorithms for clustering, but many of them are overly complex and scale poorly with larger data sets. In this paper, a new algorithm for clustering is proposed to solve some of these issues. Density-based clustering algorithms use a concept called the “underlying density function”, which is a conceptual higher-dimension function that describes the possible results from the continuous …

Storage Management Strategy In Mobile Phones For Photo Crowdsensing, En Wang, Zhengdao Qu, Xinyao Liang, Xiangyu Meng, Yongjian Yang, Dawei Li, Weibin Meng

Department of Computer Science Faculty Scholarship and Creative Works

In mobile crowdsensing, some users jointly finish a sensing task through the sensors equipped in their intelligent terminals. In particular, the photo crowdsensing based on Mobile Edge Computing (MEC) collects pictures for some specific targets or events and uploads them to nearby edge servers, which leads to richer data content and more efficient data storage compared with the common mobile crowdsensing; hence, it has attracted an important amount of attention recently. However, the mobile users prefer uploading the photos through Wifi APs (PoIs) rather than cellular networks. Therefore, photos stored in mobile phones are exchanged among users, in order to …

Book Genre Classification By Its Cover Using A Multi-View Learning Approach, Chandra Shakhar Kundu

Masters Theses & Specialist Projects

An interesting topic in the visual analysis is to determine the genre of a book by its cover. The book cover is the very first communication to the reader which shapes the reader’s expectation about the type of the book. Each book cover is carefully designed by the cover designers and typographers to convey the visual representation of its content. In this study, we explore several different deep learning approaches for predicting the genre from the cover image alone, such as MobileNet V1, MobileNet V2, ResNet50, Inception V2. Moreover, we add an extra modality by extracting text from the cover …

Smart Cities At Play: Technology And Emerging Forms Of Playfulness, Konstantinos Papangelis, Michael Saker, Catherine Jones

Articles

Editorial. No abstract is available.

Digital Forensic Readiness: An Examination Of Law Enforcement Agencies In The State Of Maryland, James B. Mcnicholas Iii

Masters Theses & Doctoral Dissertations

Digital forensic readiness within the law enforcement community, especially at the local level, has gone mostly unexplored. As a result, a current lack of data exists that examines the digital forensic readiness of individual agencies, the possibility of proximity relationships, and correlations between readiness and backlogs. This quantitative, crosssectional research study sought to explore these issues by focusing on the state of Maryland. The study resulted in the creation of a digital forensic readiness scoring model that was then used to assign digital forensic readiness scores to thirty (30) of the one-hundred-forty-one (141) law enforcement agencies throughout Maryland. It was …

An Examination Of The Work Practices Of Crowdfarms, Yihong Wang, Konstantinos Papangelis, Michael Saker, Ioanna Lykourentzou, Vassilis-Javed Khan, Alan Chamberlain, Jonathan Grudin

Presentations and other scholarship

Crowdsourcing is a new value creation business model. Annual revenue of the Chinese market alone is hundreds of millions of dollars, yet few studies have focused on the practices of the Chinese crowdsourcing workforce, and those that do mainly focus on solo crowdworkers. We have extended our study of solo crowdworker practices to include crowdfarms, a relatively new entry to the gig economy: small companies that carry out crowdwork as a key part of their business. We report here on interviews of people who work in53 crowdfarms. We describe how crowdfarms procure jobs, carry out macrotasks and microtasks, manage their …

The Influence Of Peer And Parental Norms On First-Generation College Students’ Binge Drinking Trajectories, Graham T. Diguiseppi, Jordan P. Davis, Matthew K. Meisel, Melissa A. Clark, Mya L. Roberson, Miles Q. Ott, Nancy P. Barnett

Statistical and Data Sciences: Faculty Publications

Introduction: First-generation college students are those whose parents have not completed a four-year college degree. The current study addressed the lack of research on first-generation college students’ alcohol use by comparing the binge drinking trajectories of first-generation and continuing-generation students over their first three semesters. The dynamic influence of peer and parental social norms on students’ binge drinking frequencies were also examined. Methods: 1342 college students (n = 225 first-generation) at one private University completed online surveys. Group differences were examined at Time 1, and latent growth-curve models tested the association between first-generation status and social norms (peer descriptive, peer …

Multi-Label Model For Toxicity Prediction, Xiu Huan Yap, Michael L. Raymer

Celebration of Undergraduate & Graduate Research, Scholarship, and Creative Activities Materials

Most computational predictive models are specifically trained for a single toxicity endpoint. Since more than 1300 toxicity assays have been reported in the TOXCAST dashboard, achieving high coverage over this growing number of toxicity endpoints remains challenging. Furthermore, single-endpoint models lack the ability to learn dependencies between endpoints, such as those targeting similar biological pathways, which may be used to boost model performance. In this study, we characterize the performance of 3 multi-label classification (MLC) models, namely Classifier Chains (CC), Label Powersets (LP) and Stacking (SBR), on Tox21 challenge data. These MLC models employ the Problem Transformation approach, which is …

Explainable Deep Learning For Medical Image Analysis, Brennan Rhoadarmer

UCARE: Research Products

Explainable Deep Learning for Medical Image Analysis is a project focused on improving the ability for deep learning models to explain the reasoning behind their classification in order to improve their viability in the medical field, where explanations of decisions is critical for the care of patients. In order to explore this topic, we work to implement GradCAM, which is a new method of determining the cause classification in models by tracing back through the model layers to the input.

The Adoption Of Cryptocurrency Technology Into The Us Banking Infrastructure, Trevor Melito

Senior Theses

This thesis examines the possibility of using Blockchain technology to permanently change the payment structure of the US banking system. First, I examine the current technology that dominates the banking sector. I introduce the most frequently used payments methods including Automatic Clearing House transfers and wire transfers, both domestically and internationally. In addition, I highlight the major players controlling these transactions. Under the current system, frictions between senders and receivers cause billions of dollars in losses each year.

Next, I examine Blockchain’s roots along with some similar cryptocurrency technology, namely Distributed Ledger Technology and Smart Contracts. The transparency, security, and …

Byod-Insure: A Security Assessment Model For Enterprise Byod, Melva Ratchford

Masters Theses & Doctoral Dissertations

As organizations continue allowing employees to use their personal mobile devices to access the organizations’ networks and the corporate data, a phenomenon called ‘Bring Your Own Device’ or BYOD, proper security controls need to be adopted not only to secure the corporate data but also to protect the organizations against possible litigation problems. Until recently, current literature and research have been focused on specific areas or solutions regarding BYOD. The information associated with BYOD security issues in the areas of Management, IT, Users and Mobile Device Solutions is fragmented. This research is based on a need to provide a holistic …

Learning In The Machine: To Share Or Not To Share?, Jordan Ott, Erik Linstead, Nicholas Lahaye, Pierre Baldi

Engineering Faculty Articles and Research

Weight-sharing is one of the pillars behind Convolutional Neural Networks and their successes. However, in physical neural systems such as the brain, weight-sharing is implausible. This discrepancy raises the fundamental question of whether weight-sharing is necessary. If so, to which degree of precision? If not, what are the alternatives? The goal of this study is to investigate these questions, primarily through simulations where the weight-sharing assumption is relaxed. Taking inspiration from neural circuitry, we explore the use of Free Convolutional Networks and neurons with variable connection patterns. Using Free Convolutional Networks, we show that while weight-sharing is a pragmatic optimization …

De Novo Sequencing And Analysis Of Salvia Hispanica Tissue-Specific Transcriptome And Identification Of Genes Involved In Terpenoid Biosynthesis, James Wimberley, Joseph Cahill, Hagop S. Atamian

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Salvia hispanica (commonly known as chia) is gaining popularity worldwide as a healthy food supplement due to its low saturated fatty acid and high polyunsaturated fatty acid content, in addition to being rich in protein, fiber, and antioxidants. Chia leaves contain plethora of secondary metabolites with medicinal properties. In this study, we sequenced chia leaf and root transcriptomes using the Illumina platform. The short reads were assembled into contigs using the Trinity software and annotated against the Uniprot database. The reads were de novo assembled into 103,367 contigs, which represented 92.8% transcriptome completeness and a diverse set of Gene Ontology …

Capturing The City’S Heritage On-The-Go: Design Requirements For Mobile Crowdsourced Cultural Heritage, Bas Hannewijk, Federica Lucia Vinella, Vassilis-Javed Khan, Ioanna Lykourentzou, Konstantinos Papangelis, Judith Masthoff

Articles

Intangible Cultural Heritage is at a continuous risk of extinction. Where historical artefacts engine the machinery of intercontinental mass-tourism, socio-technical changes are reshaping the anthropomorphic landscapes everywhere on the globe, at an unprecedented rate. There is an increasing urge to tap into the hidden semantics and the anecdotes surrounding people, memories and places. The vast cultural knowledge made of testimony, oral history and traditions constitutes a rich cultural ontology tying together human beings, times, and situations. Altogether, these complex, multidimensional features make the task of data-mapping of intangible cultural heritage a problem of sustainability and preservation. This paper addresses a …

Communicating Computing Limitations Through Kinesthetic Pedagogy, Michael Mason

Honors Program: Senior Projects (Public)

Abstract concepts, such as those in advanced Computer Science and Mathematics, can be extremely difficult to understand fundamentally without an existing background in a similar subject. Recent research has shown that raw visualizations without learner interaction are not particularly effective at communicating complex information because they allow the learner to ignore the example (Lauer 2006, Naps 2002). Forcing somebody to interact with an example ensures that they can grasp the visualization. This paper describes a six step technique to demonstrate the limitations of computing through kinesthetic pedagogy, then offers an example exercise utilizing the method. The six proposed steps are: …