Computer Sciences Commons^™

Processing Narratives By Means Of Action Languages, Craig Olson

Computer Science Theses, Dissertations, and Student Creative Activity

In this work we design a narrative understanding system Text2ALM that can be used in Question Answering domains. System Text2ALM utilizes an action language 𝒜ℒℳ to perform inferences on complex interactions of events described in narratives. The methodology that Text2ALM follows in its implementation was originally outlined by Yuliya Lierler, Daniela Inclezan, and Michael Gelfond in 2017 via a manual process, and this work serves as a proof of concept in a large-scale environment. Our system automates the conversion of a narrative to an 𝒜ℒℳ model containing facts about the narrative. We make use of the VerbNet lexicon that we …

Grant Anon Minigames Extension, Justin Robbins

Theses/Capstones/Creative Projects

The Grant Anon system was designed to be a casualized version of the real-time strategy genre, a genre usually known for its difficulty and competitiveness because of Starcraft II, the most popular game in the genre. Grant Anon was designed as part of a capstone project, and this report details the extension that was created to add an additional element designed to make it easier for any player to enjoy Grant Anon: minigames. These minigames serve to reduce the skill needed to participate effectively in Grant Anon. This is accomplished by providing an alternative means of gaining an advantage over …

A Communication Architecture For Crowd Management In Emergency And Disruptive Scenarios, Alfredo J. Perez, Sherali Zeadally

Computer Science Faculty Publications

Crowd management aims to develop support infrastructures that can effectively manage crowds at any time. In emergency and disruptive scenarios this concept can minimize the risk to human life and to the infrastructure. We propose the Communication Architecture for Crowd Management (CACROM), which can support crowd management under emergency and disruptive scenarios. We identify, describe, and discuss the various components of the proposed architecture, and we briefly discuss open challenges in the design of crowd management systems for emergency and disruptive scenarios.

A Formal Approach To Circle Formation In Multi-Agent Systems, Rui Yang

Computer Science Graduate Research Workshop

No abstract provided.

Conflict Resolution Using Α-Shapes For Distributed Robotic Sampling Of Ambient Phenomena In Initially Unknown Environments, Brad Woosley

Computer Science Graduate Research Workshop

No abstract provided.

Dynamic Lazy Grounding In Answer Set Programming, Brian Hodges

Computer Science Graduate Research Workshop

No abstract provided.

Automatic Program Rewriting For Non-Ground Answer Set Programs, Nicholas Hippen

Computer Science Graduate Research Workshop

No abstract provided.

Automated Tool Support For Security Bug Repair In Mobile Applications, Larry Singleton

Computer Science Graduate Research Workshop

No abstract provided.

Tool Support For Recurring Code Change Inspection With Deep Learning, Krishna Teja Ayinala

Computer Science Graduate Research Workshop

No abstract provided.

Analysis Of Subgoal Data In Computer Science Principles - Data Cleaning, Hari Ramilison

Computer Science Graduate Research Workshop

No abstract provided.

Co-Designing An Academic Focus Mobile Application, Mohammad Farhad Afzali

Computer Science Graduate Research Workshop

No abstract provided.

Processing Narratives By Means Of Action Languages, Craig Olson

Computer Science Graduate Research Workshop

No abstract provided.

Intelligent And Human-Aware Decision Making For Semi-Autonomous Human Rehabilitation Assistance Using Modular Robots, Anoop Mishra

Computer Science Graduate Research Workshop

No abstract provided.

Machine Learning Techniques For Predicting Mobility-Related Perception Errors In Astronauts, Steven Belcher

Computer Science Graduate Research Workshop

No abstract provided.

A Technique For Improving Classification Accuracy Of Highly Imbalanced And Sparse Datasets, Sindhura Bonthu

Computer Science Graduate Research Workshop

No abstract provided.

Learning From Imbalanced Datasets: Evaluating The Predictive Accuracy Of Minority Classes, Adithi Deborah Chakravarthy

Computer Science Graduate Research Workshop

No abstract provided.

Two-Sided Matching For Mentor-Mentee Allocations—Algorithms And Manipulation Strategies, Christian Haas, Margeret Hall

Information Systems and Quantitative Analysis Faculty Publications

In scenarios where allocations are determined by participant’s preferences, Two-Sided Matching is a well-established approach with applications in College Admissions, School Choice, and Mentor-Mentee matching problems. In such a context, participants in the matching have preferences with whom they want to be matched with. This article studies two important concepts in Two-Sided Matching: multiple objectives when finding a solution, and manipulation of preferences by participants. We use real data sets from a Mentor-Mentee program for the evaluation to provide insight on realistic effects and implications of the two concepts. In the first part of the article, we consider the quality …

Role Of Gender Differences On Individuals' Responses To Electronic Word-Of-Mouth In Social Interactions, Jonghak Sun, Seokwoo Song, Deanna House, Mintaek Kwon

Information Systems and Quantitative Analysis Faculty Publications

Considering the significant effects of electronic Word-of-Mouth (eWOM), this research explores how individuals respond to eWOM and whether gender differences exist in their perceptions. To do so, by employing the perspective of social interactions, we examine the proposed relationships are different between genders. We collected data using a survey and tested the hypotheses via path analysis. The results indicate that, gender differences were found specific to search effort, product involvement, and information credibility. Women with strong online ties had a tendency to be more involved in the product information and to find the information more credible. In addition, when women …

Design For Safety: Decreasing First Responder Health Risks Through Real-Time Bio-Sensor Alerts, Suzy Fendrick

UNO Student Research and Creative Activity Fair

The focus of this research project is using the Design Thinking process to create an informative dashboard for first responders. Design Thinking involves empathizing with the user, defining the problems to be solved, ideation, creating prototypes, and testing. This iterate process focuses on the user, resulting in the most effective product possible. The dashboard will display real-time biosensor data from sensors in the first responders’ uniforms. This project is part of a larger project with the goal of vastly improving the safety of first responders during emergency hazardous material incidents.

Evaluating An Electronic Protocol In A Pediatric Intensive Care Unit, Jeanette Rose

UNO Student Research and Creative Activity Fair

A team of clinicians at Children’s Hospital and Medical Center (CHMC) developed a standardized protocol in 2018 for the care of patients needing sedation. This protocol is ordered through the EPIC electronic health record system for patients in the pediatric intensive care unit (PICU). When used, electronic protocols reduce the variation in clinical decision making which can ultimately improve patient outcomes. The goal of this project is to evaluate this technology, how the protocol is being used, and how it may be improved. Actual users of the EPIC sedation protocol were the subjects of this study, including PICU physicians, physician …

Forensics Analysis For Bone Pair Matching Using Bipartite Graphs In Commingled Remains, Ryan Ernst

UNO Student Research and Creative Activity Fair

Identification of missing prisoners of war is a complex and time consuming task. There are many missing soldiers whose remains have yet to be returned to their families and loved ones. This nation has a solemn obligation to its soldiers and their families who have made the ultimate sacrifice for their country. There are currently over 82,000 unidentified prisoners of war which are identified at a rate of 100+ per year. At this rate it would take 300+ years to complete the identification process. Previously, anthropologists used excel spreadsheets to sort through skeletal data. This project aims to streamline the …

Use Of Exploratory Data Analysis And Visualization In Identification Of Commingled Human Remains, Vivek Bhat Hosmat

UNO Student Research and Creative Activity Fair

The field of Exploratory data analysis and Visualization is revolutionizing the way we perceive things. At times, Visualization is seen as a subset of Exploratory data analysis and then there are branches in Visualization, types, technologies, tools which makes one feel that Visualization is a standalone pillar. Either way, they both work well together to extract meaningful information from almost any kind of data. These fields can very well be the stepping stone for in-depth or conclusive research. They can direct research based on facts and observations rather than one’s intuition or even a brute force technique. This project was …

Data Analytics Pipeline For Rna Structure Analysis Via Shape, Quinn Nelson

UNO Student Research and Creative Activity Fair

Coxsackievirus B3 (CVB3) is a cardiovirulent enterovirus from the family Picornaviridae. The RNA genome houses an internal ribosome entry site (IRES) in the 5’ untranslated region (5’UTR) that enables cap-independent translation. Ample evidence suggests that the structure of the 5’UTR is a critical element for virulence. We probe RNA structure in solution using base-specific modifying agents such as dimethyl sulfate as well as backbone targeting agents such as N-methylisatoic anhydride used in Selective 2’-Hydroxyl Acylation Analyzed by Primer Extension (SHAPE). We have developed a pipeline that merges and evaluates base-specific and SHAPE data together with statistical analyses that provides confidence …

Exploratory Factor Analysis Of Graphical Features For Link Prediction In Social Networks, Lale Madahali, Lotfi Najjar, Margeret Hall

Interdisciplinary Informatics Faculty Proceedings & Presentations

Social Networks attract much attention due to their ability to replicate social interactions at scale. Link prediction, or the assessment of which unconnected nodes are likely to connect in the future, is an interesting but non-trivial research area. Three approaches exist to deal with the link prediction problem: feature-based models, Bayesian probabilistic models, probabilistic relational models. In feature-based methods, graphical features are extracted and used for classification. Usually, these features are subdivided into three feature groups based on their formula. Some formulas are extracted based on neighborhood graph traverse. Accordingly, there exists three groups of features, neighborhood features, path-based features, …

Computational Thinking Bins: Outreach And More, Briana B. Morrison, Brian Dorn, Michelle Friend

Computer Science Faculty Publications

Computational Thinking Bins are stand alone, individual boxes, each containing an activity for groups of students that teaches a computing concept. We have a devised a system that has allowed us to create an initial set, test the set, continually improve and add to our set. We currently use these bins in outreach events for middle and high school students. As we have shared this resource with K-12 teachers, many have expressed an interest in acquiring their own set. In this paper we will share our experience throughout the process, introduce the bins, and explain how you can create your …

Marktplatz Zur Koordinierung Und Finanzierung Von Open Source Software, Georg J.P. Link, Malvika Rao, Don Marti, Andy Leak, Rich Bodo

Information Systems and Quantitative Analysis Faculty Publications

Open Source ist ein zunehmend beliebter Kollaborationsmechanismus für die Entwicklung von Software, auch in Unternehmen. Unsere Arbeit schafft die fehlende Verbindung zwischen Open Source Projekten, Unternehmen und Märkten. Ohne diese Verbindung wurden Koordinations- und Finanzierungsprobleme sichtbar, die zu schwerwiegenden Sicherheitslücken führen. In diesem Paper entwickeln wir acht Design Features, die ein Marktplatz für Open Source haben sollte, um diese Probleme zu beseitigen. Wir begründen jedes Design Feature mit den bestehenden Praktiken von Open Source und stellen einen Prototypen vor. Abschließend diskutieren wir, welche Auswirkungen die Einführung eines solchen Marktplatzes haben könnte.

Translation: Marketplace to Coordinate and Finance Open Source Software …

Facepet: Enhancing Bystanders’ Facial Privacy With Smart Wearables/Internet Of Things, Alfredo J. Perez, Sherali Zeadally, Luis Y. Matos Garcia, Jason A. Mouloud, Scott Griffith

Computer Science Faculty Publications

Given the availability of cameras in mobile phones, drones and Internet-connected devices, facial privacy has become an area of major interest in the last few years, especially when photos are captured and can be used to identify bystanders’ faces who may have not given consent for these photos to be taken and be identified. Some solutions to protect facial privacy in photos currently exist. However, many of these solutions do not give a choice to bystanders because they rely on algorithms that de-identify photos or protocols to deactivate devices and systems not controlled by bystanders, thereby being dependent on the …

Phr: Patient Health Record, Quinn Nelson

Theses/Capstones/Creative Projects

The rapid development of information technology systems has expanded into multiple disciplines and results in systems that are limited by initial design and implementation: the Healthcare Information Technology (HIT) space is no different. The introduction of the Electronic Health Record (EHR) system has changed the way healthcare operates. Initial designs of these systems were focused on serving the needs of insurance companies and healthcare billing departments. Research shows that the design of EHR systems negatively impact provider-patient interactions and the care they receive. This capstone project capitalizes on the collaboration efforts between UNO and UNMC – by joining a research …

Multi-Label Classification Using Higher-Order Label Clusters, Dilanga Lakshitha Bandara Abeyrathna Galapita Mudiyanselage

Student Work

Multi-label classification (MLC) is one of the major classification approaches in the context of data mining where each instance in the dataset is annotated with a set of labels. The nature of multiple labels associated with one instance often demands higher computational power compared to conventional single-label classification tasks. A multi-label classification is often simplified by decomposing the task into single-label classification which ignores correlations among labels. Incorporating label correlations into classification task can be hard since correlations may be missing, or may exist among a pair or a large subset of labels. In this study, a novel MLC approach …

Visualization, Feature Selection, Machine Learning: Identifying The Responsible Group For Extreme Acts Of Violence, Mahdi Hashemi, Margeret A. Hall

Interdisciplinary Informatics Faculty Publications

The toll of human casualties and psychological impacts on societies make any study on violent extremism worthwhile, let alone attempting to detect patterns among them. This paper is an effort to predict which violent extremist organization (VEO), among 14 currently active ones throughout the world, is responsible for a violent act based on 14 features, including its human and structural tolls, its target type and value, intelligence, and weapons utilized in the attack. Three main steps in our paper include: 1) the visualization of the violent acts through linear and non-linear dimensionality reduction techniques; 2) sequential forward feature selection based …