Databases and Information Systems Commons^™

Cslc Tutoring Portal, Brian Hodges

Theses/Capstones/Creative Projects

A web portal designed for the Computer Science Learning Center to track students requesting help

Ai: Augmentation, More So Than Automation, Steven M. Miller

Asian Management Insights

The take-up of Artificial Intelligence (AI)-enabled systems in organisations is expanding rapidly. Integrating AI-enabled automation with people into workplace processes and societal systems is a complex and evolving challenge. The articles takes a managerial perspective on how firms can effectively deploy human minds and intelligent machines in the workplace.

Trade-Offs Between Monetary Gain And Risk Taking In Cybersecurity Behavior, X. Zhan, Fiona Fui-Hoon Nah, M. Cheng

Research Collection School Of Computing and Information Systems

Phishers and hackers exploit users’ susceptibility to deception by providing incentives. This research focuses on studying the risk-taking behavior of users in downloading software from the Internet. We proposed an experimental study to assess the degree of risks that people are willing to take for monetary gains when they download software from uncertified sources.

Factors Influencing The Adoption Of Smart Wearable Devices, Apurva Adapa, Fiona Fui-Hoon Nah, Richard H. Hall, Keng Siau

Research Collection School Of Computing and Information Systems

This article examined factors associated with the adoption of smart wearable devices. More specifically, this research explored the contributing and inhibiting factors that influence the adoption of wearable devices through in-depth interviews. The laddering approach was used in the interviews to identify not only the factors but also their relationships to underlying values. The wearable devices examined were a Smart Glass (Google Glass) and a Smart Watch (Sony Smart Watch 3). Two user groups, college students and working professionals, participated in the study. After the participants had the opportunity to try out each of the two devices, the factors that …

Entity Summarization Of Reviews And Micro-Reviews, Thanh Son Nguyen

Dissertations and Theses Collection (Open Access)

Along with the regular review content, there is a new type of user-generated content arising from the prevalence of mobile devices and social media, that is micro-review. Micro-reviews are bite-size reviews (usually under 200 char- acters), commonly posted on social media or check-in services, using a mobile device. They capture the immediate reaction of users, and they are rich in information, concise, and to the point. Both reviews and micro-reviews are useful for users to get to know the entity of interest, thus facilitating users in making their decision of purchasing or dining. However, the abundant number of both reviews …

Recommending Apis For Software Evolution, Ferdian Thung

Dissertations and Theses Collection (Open Access)

Softwares are constantly evolving. This evolution has been made easier through the use of Application Programming Interfaces (APIs). By leveraging APIs, developers reuse previously implemented functionalities and concentrate on writing new codes. These APIs may originate from either third parties or internally from other compo- nents of the software that are currently developed. In the first case, developers need to know how to find and use third party APIs. In the second case, developers need to be aware of internal APIs in their own software. In either case, there is often too much information to digest. For instance, finding the …

Automatic Vulnerability Detection And Repair, Siqi Ma

Dissertations and Theses Collection (Open Access)

Vulnerability becomes a major threat to the security of many systems, including computer systems (e.g., Windows and Linux) and mobile systems (e.g., Android and iOS). Attackers can steal private information and perform harmful actions by exploiting unpatched vulnerabilities. Vulnerabilities often remain undetected for a long time as they may not affect the typical functionalities of systems. Thus, it is important to detect and repair a vulnerability in time. However, it is often difficult for a developer to detect and repair a vulnerability correctly and timely if he/she is not a security expert. Fortunately, automatic repair approaches significantly assist developers to …

Effect Of Probable And Guaranteed Monetary Value Gains And Losses On Cybersecurity Behavior Of Users, S. Ravindran, Fiona Fui-Hoon Nah, M. Cheng

Research Collection School Of Computing and Information Systems

The objective of this research is to examine users’ cybersecurity behavior in monetary gain and loss scenarios. Using Prospect Theory, we hypothesize that users are more likely to engage in risky cybersecurity behavior to avoid monetary losses than to benefit from monetary gains. We also hypothesize that guaranteed gains have a greater effect on a user’s risk-taking behavior than potential gains, and potential losses have a greater effect on a user’s risk-taking behavior than guaranteed losses. An experimental study is proposed to test the research hypotheses.

Factors Influencing The Adoption Of Smart Wearable Devices, Apurva Adapa, Fiona Fui-Hoon Nah, Richard H. Hall, Keng Siau, Samuel Smith

Research Collection School Of Computing and Information Systems

This article examined factors associated with the adoption of smart wearable devices. More specifically, this research explored the contributing and inhibiting factors that influence the adoption of wearable devices through in-depth interviews. The laddering approach was used in the interviews to identify not only the factors but also their relationships to underlying values. The wearable devices examined were a Smart Glass (Google Glass) and a Smart Watch (Sony Smart Watch 3). Two user groups, college students and working professionals, participated in the study. After the participants had the opportunity to try out each of the two devices, the factors that …

Evidence Aggregation For Answer Re-Ranking In Open-Domain Question Answering, Shuohang Wang, Mo Yu, Jing Jiang, Wei Zhang, Xiaoxiao Guo, Shiyu Chang, Zhiguo Wang, Tim Klinger, Gerald Tesauro, Murray Campbell

Research Collection School Of Computing and Information Systems

A popular recent approach to answering open-domain questions is to first search for question-related passages and then apply reading comprehension models to extract answers. Existing methods usually extract answers from single passages independently. But some questions require a combination of evidence from across different sources to answer correctly. In this paper, we propose two models which make use of multiple passages to generate their answers. Both use an answer-reranking approach which reorders the answer candidates generated by an existing state-of-the-art QA model. We propose two methods, namely, strength-based re-ranking and coverage-based re-ranking, to make use of the aggregated evidence from …

Big Data For Climate Change Actions And The Paradox Of Citizen Informedness, Kustini Lim-Wavde, Robert J. Kauffman

Research Collection School Of Computing and Information Systems

Advanced sensor technology, social media, and other information technologies have provided us with “big data” on climate change. Due to the World Meteorological Organization’s Global Climate Observing System, climate observations and records, as well as discussions on climate-related concerns such as measurement of air temperature, are widely available now. The United Nations’ Global Pulse visualises public engagement on climate change globally, with data such as the volume of climate-related tweets. Big data, data analytics, and the sharing of scientific results in the popular press have created, as a result, an unprecedented level of citizen informedness—the degree to which citizens have …

Understanding The Effects Of Taxi Ride-Sharing: A Case Study Of Singapore, Yazhe Wang, Baihua Zheng, Ee Peng Lim

Research Collection School Of Computing and Information Systems

This paper studies the effects of ride-sharing among those calling on taxis in Singapore for similar origin and destination pairs at nearly the same time of day. It proposes a simple yet practical framework for taxi ride-sharing and scheduling, to reduce waiting times and travel times during peak demand periods. The solution method helps taxi users save money while helping taxi drivers serve multiple requests per day, thus increasing their earnings. A comprehensive simulation study is conducted, based on real taxi booking data for the city of Singapore, to evaluate the effect of various factors of the ride-sharing practice, e.g., …

Discovering Hidden Topical Hubs And Authorities In Online Social Networks, Roy Ka-Wei Lee, Tuan-Anh Hoang, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Finding influential users in online social networks is an important problem with many possible useful applications. HITS and other link analysis methods, in particular, have been often used to identify hub and authority users in web graphs and online social networks. These works, however, have not considered topical aspect of links in their analysis. A straightforward approach to overcome this limitation is to first apply topic models to learn the user topics before applying the HITS algorithm. In this paper, we instead propose a novel topic model known as Hub and Authority Topic (HAT) model to combines the two process …

Analysis Of 2016-17 Major League Soccer Season Data Using Poisson Regression With R, Ian D. Campbell

Undergraduate Theses and Capstone Projects

To the outside observer, soccer is chaotic with no given pattern or scheme to follow, a random conglomeration of passes and shots that go on for 90 minutes. Yet, what if there was a pattern to the chaos, or a way to describe the events that occur in the game quantifiably. Sports statistics is a critical part of baseball and a variety of other of today’s sports, but we see very little statistics and data analysis done on soccer. Of this research, there has been looks into the effect of possession time on the outcome of a game, the difference …

Finding All Nearest Neighbors With A Single Graph Traversal, Yixin Xu, Qi Jianzhong, Borovica‐Gajic Renata, Kulik Lars

Research Collection School Of Computing and Information Systems

Finding the nearest neighbor is a key operation in data analysis and mining. An important variant of nearest neighbor query is the all nearest neighbor (ANN) query, which reports all nearest neighbors for a given set of query objects. Existing studies on ANN queries have focused on Euclidean space. Given the widespread occurrence of spatial networks in urban environments, we study the ANN query in spatial network settings. An example of an ANN query on spatial networks is finding the nearest car parks for all cars currently on the road. We propose VIVET, an index-based algorithm to efficiently process ANN …

Anflo: Detecting Anomalous Sensitive Information Flows In Android Apps, Biniam Fisseha Demissie, Mariano Ceccato, Lwin Khin Shar

Research Collection School Of Computing and Information Systems

Smartphone apps usually have access to sensitive user data such as contacts, geo-location, and account credentials and they might share such data to external entities through the Internet or with other apps. Confidentiality of user data could be breached if there are anomalies in the way sensitive data is handled by an app which is vulnerable or malicious. Existing approaches that detect anomalous sensitive data flows have limitations in terms of accuracy because the definition of anomalous flows may differ for different apps with different functionalities; it is normal for “Health” apps to share heart rate information through the Internet …

Assessing Classical And Expressive Aesthetics Of Web Pages Using Machine Learning, Ang Chen, Fiona Fui-Hoon Nah, Langtao Chen

Research Collection School Of Computing and Information Systems

Aesthetics plays a key role in web design. However, most websites are developed based on designers’ "inspirations" or "educated guesses" (Liu, 2003). While perceptions of aesthetics are intuitive abilities of humankind, the underlying principles for assessing aesthetics are not well understood. In this research, we propose using machine learning techniques to explore and more fully understand the patterns and underlying principles of aesthetics. We propose using machine learning techniques to develop predictive models for two aesthetic dimensions – classical aesthetics and expressive aesthetics – as well as for overall aesthetics of web pages in order to evaluate the aesthetic quality …

Evaluating Sequence Discovery Systems In An Abstraction-Aware Manner, Eoin Rogers, Robert J. Ross, John D. Kelleher

Conference papers

Activity discovery is a challenging machine learning problem where we seek to uncover new or altered behavioural patterns in sensor data. In this paper we motivate and introduce a novel approach to evaluating activity discovery systems. Pre-annotated ground truths, often used to evaluate the performance of such systems on existing datasets, may exist at different levels of abstraction to the output of the output produced by the system. We propose a method for detecting and dealing with this situation, allowing for useful ground truth comparisons. This work has applications for activity discovery, and also for related fields. For example, it …

Creating A Reproducible Metadata Transformation Pipeline Using Technology Best Practices, Cara Key, Mike Waugh

Digital Initiatives Symposium

Over the course of two years, a team of librarians and programmers from LSU Libraries migrated the 186 collections of the Louisiana Digital Library from OCLC's CONTENTdm platform over to the open-source Islandora platform.

Early in the process, the team understood the value of creating a reproducible metadata transformation pipeline, because there were so many unknowns at the beginning of the process along with the certainty that mistakes would be made. This presentation will describe how the team used innovative and collaborative tools, such as Trello, Ansible, Vagrant, VirtualBox, git and GitHub to accomplish the task.

Small Web-Based Denormalized Database Effectiveness Threshold, Min Young Lee

Undergraduate Research Celebration 2018

No abstract provided.

Blockchain: Technical Review, Evan D. Poff

Marriott Student Review

This review of blockchain technology accompanies the article "Strategic Implications of Blockchain."

Buzzwords, Evan D. Poff

Marriott Student Review

This feature will explain the following buzzwords:

• Blockchain
• Cryptocurrency
• Work-Life Integration
• Passive Equities
• Risk-Adjusted Returns

Efficient Reduced Bias Genetic Algorithm For Generic Community Detection Objectives, Aditya Karnam Gururaj Rao

Theses

The problem of community structure identification has been an extensively investigated area for biology, physics, social sciences, and computer science in recent years for studying the properties of networks representing complex relationships. Most traditional methods, such as K-means and hierarchical clustering, are based on the assumption that communities have spherical configurations. Lately, Genetic Algorithms (GA) are being utilized for efficient community detection without imposing sphericity. GAs are machine learning methods which mimic natural selection and scale with the complexity of the network. However, traditional GA approaches employ a representation method that dramatically increases the solution space to be searched by …

Modular Scheduling System For Westside School District, Tyler Bienhoff

Honors Program: Senior Projects (Public)

Westside School district offers a modular scheduling system for their high school that is more similar to a college schedule than the typical high school system. Due to the complexity of their master schedule each semester, there are no commercially available products that can assist in creating a schedule. Hence, this thesis discusses a scheduling algorithm and management system that was built specifically for Westside High School with the potential to be expanded for use by other interested schools. The first part of the paper is focused on gathering input from students and faculty for which courses and how many …

Supporting User Evaluation Of Messaging Interactions With Potential Romantic Partners Discovered Online, Douglas Zytko

Dissertations

Online dating systems have transformed the way people pursue romance. To arrive at a decision to meet for a face-to-face date, users gather information about each other online pertinent to romantic attraction. Yet sometimes they discover on the date that they made the wrong choice. One aspect of online dating system-use that may be a contributing factor, but is largely overlooked in the literature, is interaction through text-based messaging interfaces. This dissertation explores how messaging interactions inform face-to-face meeting decisions through two qualitative studies, and explores through a mixed methods field study how innovative messaging interfaces that embody theory from …

Cross-Platform Openhds Web Application, Nick Littlefield

Thinking Matters Symposium Archive

A proof of concept cross platform data collection application for Demographic and Health studies has been developed. This application allows for the collection of information about locations, individuals, births, and deaths within a region. This application can be run on both mobile devices, laptops, and desktops.

Surveying Digital Collections Stewardship In Nebraska [Original Survey Form], Jennifer L. Thoegersen, Blake Graham

University of Nebraska-Lincoln Data Repository

No abstract provided.

Feature Detection In Medical Images Using Deep Learning, Anthony Pasquarelli

Honors Projects in Information Systems and Analytics

This project explores the use of deep learning to predict age based on pediatric hand X-Rays. Data from the Radiological Society of North America’s pediatric bone age challenge were used to train and evaluate a convolutional neural network. The project used InceptionV3, a CNN developed by Google, that was pre-trained on ImageNet, a popular online image dataset. Our fine-tuned version of InceptionV3 yielded an average error of less than 10 months between predicted and actual age. This project shows the effectiveness of deep learning in analyzing medical images and the potential for even greater improvements in the future. In addition …

Environmental Restoration Database, Joao Nascimento

Graduate Theses & Non-Theses

Environmental restoration projects face many challenges. Public awareness, funding constraints, unpredictable weather, unknown biological/chemical factors and the uncertainty about how the targeted ecosystem will develop work against the planned and ideal restoration.

One way the projects’ efficiency can be improved is by using software tools for data and quality management systems, in order to share information, make field practice follow rules, keep track of maintenance tasks, measure results and, therefore, increase the rate of success by the amount of resources invested.

Since the conception of every project, all resources involved need to be focused and coherent to the final restoration …

Foundations Of Health Information Technology (Undergraduate) Course Materials, Chi Zhang

Computer Science and Information Technology Ancillary Materials

This is a collection of all materials used in Health Information Technology by Dr. Chi Zhang at Kennesaw State University, including lecture slides, assignments, and assessments, including a question bank.

Topics covered include:

• Clinical Financial Records
• Evidence-Based Medicine
• e-Prescribing
• Patient Bedside Systems
• Telemedicine
• Health Information Networks
• Cryptography
• Accreditation
• HIPAA Privacy and Security