Computer Sciences Commons^™

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 …

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 …

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 …

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.

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

Articles

Editorial. No abstract is available.

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 …

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: …

A Nwb-Based Dataset And Processing Pipeline Of Human Single-Neuron Activity During A Declarative Memory Task, N. Chandravadia, D. Liang, A. G. P. Schjetnan, A. Carlson, M. Faraut, J. M. Chung, C. M. Reed, B. Dichter, Uri Maoz, S. K. Kalia, T. A. Valiante, A. N. Mamelak, U. Rutishauser

Psychology Faculty Articles and Research

A challenge for data sharing in systems neuroscience is the multitude of different data formats used. Neurodata Without Borders: Neurophysiology 2.0 (NWB:N) has emerged as a standardized data format for the storage of cellular-level data together with meta-data, stimulus information, and behavior. A key next step to facilitate NWB:N adoption is to provide easy to use processing pipelines to import/export data from/to NWB:N. Here, we present a NWB-formatted dataset of 1863 single neurons recorded from the medial temporal lobes of 59 human subjects undergoing intracranial monitoring while they performed a recognition memory task. We provide code to analyze and export/import …

Identification And Description Of Potentially Influential Social Network Members Using The Strategic Player Approach, Miles Q. Ott, Sara G. Balestrieri, Graham Diguiseppi, Melissa A. Clark, Michael Bernstein, Sarah Helseth, Nancy P. Barnett

Statistical and Data Sciences: Faculty Publications

Background: Diffusion of innovations theory posits that ideas and behaviors can be spread through social network ties. In intervention work, intervening upon certain network members may lead to intervention effects “diffusing” into the network to affect the behavior of network members who did not receive the intervention. The strategic players (SP) method, an extension of Borgatti’s Key Players approach, is used to balance the (sometimes) opposing goals of spreading the intervention to as many members of the target group as possible, while preventing the spread of the intervention to others. Objectives: We sought to test whether members of the SP …

Optimal Multi-Stage Arrhythmia Classification Approach, Jianwei Zhang, Huimin Chu, Daniele Struppa, Jianming Zhang, Sir Magdi Yacoub, Hesham El-Askary, Anthony Chang, Louis Ehwerhemuepha, Islam Abudayyeh, Alexander Barrett, Guohua Fu, Hai Yao, Dongbo Li, Hangyuan Guo, Cyril Rakovski

Mathematics, Physics, and Computer Science Faculty Articles and Research

Arrhythmia constitutes a problem with the rate or rhythm of the heartbeat, and an early diagnosis is essential for the timely inception of successful treatment. We have jointly optimized the entire multi-stage arrhythmia classification scheme based on 12-lead surface ECGs that attains the accuracy performance level of professional cardiologists. The new approach is comprised of a three-step noise reduction stage, a novel feature extraction method and an optimal classification model with finely tuned hyperparameters. We carried out an exhaustive study comparing thousands of competing classification algorithms that were trained on our proprietary, large and expertly labeled dataset consisting of 12-lead …

Taking The *Sigh* Out Of Science, Kathleen Devlin

Q2S Enhancing Pedagogy

This PowerPoint presentation describes a project where I will use social media in an attempt to improve the negative perception of science. Beginning Fall 2020, on the first day of class, I will have the students complete a pre-assessment on their perception of science. I will then ask the students to follow at least one pre-selected science person/group on either Instagram, Twitter, or Youtube. Each week I will have them do a quick think-pair-share on the topic they followed, and then do a short writing assignment. At the end of the semester I will have them complete a post-assessment and …

Evaluation Of Text Mining Techniques Using Twitter Data For Hurricane Disaster Resilience, Joshua Eason, Sathish Kumar

SDSU Data Science Symposium

Data obtained from social media microblogging websites such as Twitter provide the unique ability to collect and analyze conversations of the public in order to gain perspective on the thoughts and feelings of the general public. Sentiment and volume analysis techniques were applied to the dataset in order to gain an understanding of the amount and level of sentiment associated with certain disaster-related tweets, including a topical analysis of specific terms. This study showed that disaster-type events such as a hurricane can cause some strong negative sentiment in the period of time directly preceding the event, but ultimately returns quickly …

Virtual Water Flows Embodied In International And Interprovincial Trade Of Yellow River Basin: A Multiregional Input-Output Analysis, Guilian Tian, Xiaosheng Han, Chen Zhang, Jiaojiao Li, Jinjing Liu

Information Systems and Analytics Department Faculty Journal Articles

With the imminent need of regional environmental protection and sustainable economic development, the concept of virtual water is widely used to solve the problem of regional water shortage. In this paper, nine provinces, namely Qinghai, Sichuan, Gansu, Ningxia, Inner Mongolia, Shaanxi, Shanxi, Henan, and Shandong in the Yellow River Basin (YRB), are taken as the research objects. Through the analysis of input-output tables of 30 provinces in China in 2012, the characteristics of virtual water trade in this region are estimated by using a multi-regional input-output (MRIO) model. The results show that: (1) The YRB had a net inflow of …

Who Owns Bitcoin? Private Law Facing The Blockchain, Matthias Lehmann

Minnesota Journal of Law, Science & Technology

No abstract provided.

Exploring Self-Organisation In Crowd Teams, Ioanna Lykourentzou, Antonios Liapis, Costas Papastathis, Konstantinos Papangelis, Costas Vassilakis

Presentations and other scholarship

Online crowds have the potential to do more complex work in teams, rather than as individuals. Team formation algorithms typically maximize some notion of global utility of team output by allocating people to teams or tasks. However, decisions made by these algorithms do not consider the decisions or preferences of the people themselves. This paper explores a complementary strategy, which relies on the crowd itself to self-organize into effective teams. Our preliminary results show that users perceive the ability to choose their teammate extremely useful in a crowdsourcing setting. We also find that self-organisation makes users feel more productive, creative …

In Their Shoes: A Structured Analysis Of Job Demands, Resources, Work Experiences, And Platform Commitment Of Crowdworkers In China, Yihong Wang, Konstantinos Papangelis, Ioanna Lykourentzou, Hai-Ning Liang, Irwyn Sadien, Evangelia Demerouti, Vassilis-Javed Khan

Articles

Despite the growing interest in crowdsourcing, this new labor model has recently received severe criticism. The most important point of this criticism is that crowdworkers are often underpaid and overworked. This severely affects job satisfaction and productivity. Although there is a growing body of evidence exploring the work experiences of crowdworkers in various countries, there have been a very limited number of studies to the best of our knowledge exploring the work experiences of Chinese crowdworkers. In this paper we aim to address this gap. Based on a framework of well-established approaches, namely the Job Demands-Resources model, the Work Design …

Exploring The Employment Landscape For Individuals With Autism Spectrum Disorders Using Supervised And Unsupervised Machine Learning, Kayleigh Hyde

Computational and Data Sciences (PhD) Dissertations

Autism Spectrum Disorders (ASD) are a class of neurodevelopmental disorders which usually present with difficulties in social interactions, verbal and nonverbal forms of communication, repetitive behaviors, and restricted interests. Employment rates of young adults with ASD is a national concern, and research suggests that young adults with “high functioning” ASD experience significant difficulty in transitioning to work. One of the goals of this study was to identify the barriers associated with these individuals’ transition into the world of work. A classification tree analysis was used with a sample of 236 caregivers of individuals with ASD or the individuals themselves, who …

Digital Age Of Consent And Age Verification: Can They Protect Children?, Liliana Pasquale, Paola Zippo, Cliona Curley, Brian O'Neill, Marina Mongiello

Articles

Children are increasingly accessing social media content through mobile devices. Existing data protection regulations have focused on defining the digital age of consent, in order to limit collection of children’s personal data by organizations. However, children can easily bypass the mechanisms adopted by apps to verify their age, and thereby be exposed to privacy and safety threats. We conducted a study to identify how the top 10 social and communication apps among underage users apply age limits in their Terms of Use. We also assess the robustness of the mechanisms these apps put in place to verify the age of …

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 …

Deep Siamese Neural Networks For Facial Expression Recognition In The Wild, Wassan Hayale

Electronic Theses and Dissertations

The variation of facial images in the wild conditions due to head pose, face illumination, and occlusion can significantly affect the Facial Expression Recognition (FER) performance. Moreover, between subject variation introduced by age, gender, ethnic backgrounds, and identity can also influence the FER performance. This Ph.D. dissertation presents a novel algorithm for end-to-end facial expression recognition, valence and arousal estimation, and visual object matching based on deep Siamese Neural Networks to handle the extreme variation that exists in a facial dataset. In our main Siamese Neural Networks for facial expression recognition, the first network represents the classification framework, where we …

Certification-Driven Testing Of Safety-Critical Systems, Aiman S. Gannous

Electronic Theses and Dissertations

Safety-critical systems are those systems that when they fail they could cause loss of life or significant physical damages. Since software now is an essential component of these types of systems, failures caused by software faults could come from flaws in the software development life-cycle. As a result, challenges unfold in two directions. First, in verifying that the software will not put the system in an unsafe state, and identifying external failures and mitigate them properly. Second, in providing sufficient evidence for an efficient safety certification process. In this study, we propose an approach for testing safety-critical systems called Model-Combinatorial …

The Oceans Above Us: An Augmented Reality Experience, Chris Nalani Dimeo

Mahurin Honors College Capstone Experience/Thesis Projects

Augmented reality holds the potential to be the new fabric of our everyday lives.

Also known as AR, augmented reality is any technology that superimposes graphical information over a real-world environment, whether it be through a smartphone screen or visually projected onto the environment. Though it has existed in various forms for decades, augmented reality development is still widely considered the work of experts in technology-related fields.

In November 2019, however, Adobe unveiled a new augmented reality development platform, Project Aero, along with boasts that the app’s intuitive design and integration with other Adobe programs would place AR creation into …

An Analysis Of The Success Of Farmers Markets In Kentucky Using Logistic Regression And Support Vector Machines, Jeron Russell

Mahurin Honors College Capstone Experience/Thesis Projects

The purpose of this research is to look at the relationship that market-specific, economic, and demographic variables have with the success of farmers markets in Kentucky. It additionally seeks to build a tool for predicting farmers market success that could be used by policy makers to aid in decision-making processes concerning farmers markets. Logistic regression and Support Vector Machines (SVMs) are used on data acquired from the Kentucky Department of Agriculture and the American Community Survey in order to analyze the data in a traditional statistical approach as well as a machine learning approach. The results included an SVM model …

A Description Of A Humans Knowledge Using Artificial Intelligence, Dj Price

Mahurin Honors College Capstone Experience/Thesis Projects

There currently does not exist a way to easily view the relationships between a collection of written items (e.g. sports articles, diary entries, research papers). In recent years, novel machine learning methods have been developed which are very good at extracting semantic relationships from large numbers of documents. One of them is the (unsupervised) machine learning model Doc2Vec which constructs vectors for documents. The research project detailed in this paper uses this and other already existing algorithms to analyze the relationship between pieces of text. We set forth a broader ambition for this project before discussing the use and need …