Computer Sciences Commons^™

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 …

Nf-Κb Inhibitors Attenuate Mcao Induced Neurodegeneration And Oxidative Stress—A Reprofiling Approach, Awais Ali, Fawad Ali Shah, Alam Zeb, Imran Malik, Arooj Mohsin Alvi, Lina Tariq Alkury, Sajid Rashid, Ishtiaq Hussain, Najeeb Ullah, Arif Ullah Khan, Phil Ok Koh, Shupeng Li

All Works

© Copyright © 2020 Ali, Shah, Zeb, Malik, Alvi, Alkury, Rashid, Hussain, Ullah, Ullah Khan, Koh and Li. Stroke is the leading cause of morbidity and mortality worldwide. About 87% of stroke cases are ischemic, which disrupt the physiological activity of the brain, thus leading to a series of complex pathophysiological events. Despite decades of research on neuroprotectants to probe for suitable therapies against ischemic stroke, no successful results have been obtained, and new alternative approaches are urgently required in order to combat this pathological torment. To address these problems, drug repositioning/reprofiling is explored extensively. Drug repurposing aims to identify …

Extensible Performance-Aware Runtime Integrity Measurement, Brian G. Delgado

Dissertations and Theses

Today's interconnected world consists of a broad set of online activities including banking, shopping, managing health records, and social media while relying heavily on servers to manage extensive sets of data. However, stealthy rootkit attacks on this infrastructure have placed these servers at risk. Security researchers have proposed using an existing x86 CPU mode called System Management Mode (SMM) to search for rootkits from a hardware-protected, isolated, and privileged location. SMM has broad visibility into operating system resources including memory regions and CPU registers. However, the use of SMM for runtime integrity measurement mechanisms (SMM-RIMMs) would significantly expand the amount …

A 12-Lead Ecg Database To Identify Origins Of Idiopathic Ventricular Arrhythmia Containing 334 Patients, Jianwei Zhang, Guohua Fu, Kyle Anderson, Huimin Chu, Cyril Rakovski

Mathematics, Physics, and Computer Science Faculty Articles and Research

Cardiac catheter ablation has shown the effectiveness of treating the idiopathic premature ventricular complex and ventricular tachycardia. As the most important prerequisite for successful therapy, criteria based on analysis of 12-lead ECGs are employed to reliably speculate the locations of idiopathic ventricular arrhythmia before a subsequent catheter ablation procedure. Among these possible locations, right ventricular outflow tract and left outflow tract are the major ones. We created a new 12-lead ECG database under the auspices of Chapman University and Ningbo First Hospital of Zhejiang University that aims to provide high quality data enabling detection of the distinctions between idiopathic ventricular …

Evaluating It Governance Structure Implementation In The Gulf Cooperation Council Region, Mathew Nicho, Suadad Muamaar

All Works

© 2020 IOP Publishing Ltd. All rights reserved. IT governance (ITG) implementations in organizations started to gain momentum during the turn of the twenty first century mainly due to (but not limited to) the need for IT business alignment, better return of investment, effective utilization of IT and for a strategic direction of IT. This initially mandates to establish and implement a set of ITG structures in the organization to initiate, adopt, and implement relevant ITG frameworks to set in the motion of successful ITG implementation. While researchers have stated twelve relevant ITG structures that needs to be set in …

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: …

Maximizing Accuracy Through Stereo Vision Camera Positioning For Automated Aerial Refueling, Kirill A. Sarantsev

Theses and Dissertations

Aerial refueling is a key component of the U.S. Air Force strategic arsenal. When two aircraft interact in an aerial refueling operation, the accuracy of relative navigation estimates are critical for the safety, accuracy and success of the mission. Automated Aerial Refueling (AAR) looks to improve the refueling process by creating a more effective system and allowing for Unmanned Aerial Vehicle(s) (UAV) support. This paper considers a cooperative aerial refueling scenario where stereo cameras are used on the tanker to direct a \boom" (a large, long structure through which the fuel will ow) into a port on the receiver aircraft. …

Application Of Digital Particle Image Velocimetry To Insect Motion: Measurement Of Incoming, Outgoing, And Lateral Honeybee Traffic, Sarbajit Mukherjee, Vladimir Kulyukin

Computer Science Faculty and Staff Publications

The well-being of a honeybee (Apis mellifera) colony depends on forager traffic. Consistent discrepancies in forager traffic indicate that the hive may not be healthy and require human intervention. Honeybee traffic in the vicinity of a hive can be divided into three types: incoming, outgoing, and lateral. These types constitute directional traffic, and are juxtaposed with omnidirectional traffic where bee motions are considered regardless of direction. Accurate measurement of directional honeybee traffic is fundamental to electronic beehive monitoring systems that continuously monitor honeybee colonies to detect deviations from the norm. An algorithm based on digital particle image velocimetry is proposed …

Predictive Text Encourages Predictable Writing, Kenneth C. Arnold, Krysta Chauncey, Krysztof Z. Gajos

University Faculty Publications and Creative Works

Intelligent text entry systems, including the now-ubiquitous predictive keyboard, can make text entry more efficient, but little is known about how these systems affect the content that people write. To study how predictive text systems affect content, we compared image captions written with different kinds of predictive text suggestions. Our key findings were that captions written with suggestions were shorter and that they included fewer words that that the system did not predict. Suggestions also boosted text entry speed, but with diminishing benefit for faster typists. Our findings imply that text entry systems should be evaluated not just by speed …

Efficient Model-Data Integration For Flexible Modeling, Parameter Analysis & Visualization, And Data Management, Angela Gregory, Chao Chen, Rui Wi, Sarah Miller, Sajjad Ahmad, John W. Anderson, Hays Berrett, Karl Benedict, Dan Cadol, Sergiu M. Dascalu, Donna Delparte, Lynn Fenstermaker, Sarah Godsey, Frederick C. Harris Jr., James P. Mcnamara, Scott W. Tyler, John Savickas, Luke Sheneman, Mark Stone, Matthew A. Turner

Civil and Environmental Engineering and Construction Faculty Research

Due to the complexity and heterogeneity inherent to the hydrologic cycle, the modeling of physical water processes has historically and inevitably been characterized by a broad spectrum of disciplines including data management, visualization, and statistical analyses. This is further complicated by the sub-disciplines within the water science community, where specific aspects of water processes are modeled independently with simplification and model boundary integration receiving little attention. This can hinder current and future research efforts to understand, explore, and advance water science. We developed the Virtual Watershed Platform to improve understanding of hydrologic processes and more generally streamline model-data integration and …

Automated Extraction Of Network Activity From Memory Resident Code, Austin Nicholas Sellers

LSU Master's Theses

Advancements in malware development, including the use of file-less and memory-only payloads, have led to a significant interest in the use of volatile memory analysis by digital forensics practitioners. Memory analysis can uncover a wealth of information not available via traditional analysis, such as the discovery of injected code, hooked APIs, and more. Unfortunately, the process of analyzing such malicious code is largely left to analysts who must manually reverse engineer the code to discover its intent. This task is not only slow and error-prone, but is also generally left only to senior-level analysts to perform, given that significant reverse …

Any-Shot Object Detection, Shafin Rahman, Salman Khan, Nick Barnes, Fahad Shahbaz Khan

Computer Vision Faculty Publications

Previous work on novel object detection considers zero or few-shot settings where none or few examples of each category are available for training. In real world scenarios, it is less practical to expect that ‘all’ the novel classes are either unseen or have few-examples. Here, we propose a more realistic setting termed ‘Any-shot detection’, where totally unseen and few-shot categories can simultaneously co-occur during inference. Any-shot detection offers unique challenges compared to conventional novel object detection such as, a high imbalance between unseen, few-shot and seen object classes, susceptibility to forget base-training while learning novel classes and distinguishing novel classes …

Toward Culturally Relevant Emotion Detection Using Physiological Signals, Khadija Zanna

USF Tampa Graduate Theses and Dissertations

Research shows that emotional distress has a statistically significant impact on a student’s grade point average and intent to drop out of college. Because students of different races have varying college experiences, it is important to understand the emotional experiences of different racial groups to better support students’ needs and academic success. In this work, we explore several physiological responses to ten different emotional stimuli captured from 140 students. We employ unsupervised learning via the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm and supervised learning via Random Forests and Support Vector machines to analyze clustering partitions and classification …

Estimating Error And Bias In Offline Evaluation Results, Mucun Tian, Michael D. Ekstrand

Computer Science Faculty Publications and Presentations

Offline evaluations of recommender systems attempt to estimate users’ satisfaction with recommendations using static data from prior user interactions. These evaluations provide researchers and developers with first approximations of the likely performance of a new system and help weed out bad ideas before presenting them to users. However, offline evaluation cannot accurately assess novel, relevant recommendations, because the most novel items were previously unknown to the user, so they are missing from the historical data and cannot be judged as relevant.

We present a simulation study to estimate the error that such missing data causes in commonly-used evaluation metrics in …

Treatment Effects Of Modafinil For Cocaine Use Disorders: A Retrospective Analysis Of Aggregated Clinical Trial Data From Three Cocaine Treatment Studies, Daniel Ruskin

Honors Scholar Theses

Approximately 913,000 individuals in the United States meet the diagnostic criteria for cocaine use disorder (CUD). The widespread usage of cocaine, along with the negative cardiac and neurological effects associated with the drug, has made cocaine one of the top three drugs associated with overdose deaths in the United States. This epidemic has brought cocaine dependency into the public spotlight and has prompted extensive research into treatment strategies. However, at the time of writing, no drugs have been approved by the United States Food and Drug Administration (FDA) for use in treating CUD. The purpose of this study is to …

Graph Classification With Kernels, Embeddings And Convolutional Neural Networks, Monica Golahalli Seenappa, Katerina Potika, Petros Potikas

Faculty Publications, Computer Science

In the graph classification problem, given is a family of graphs and a group of different categories, and we aim to classify all the graphs (of the family) into the given categories. Earlier approaches, such as graph kernels and graph embedding techniques have focused on extracting certain features by processing the entire graph. However, real world graphs are complex and noisy and these traditional approaches are computationally intensive. With the introduction of the deep learning framework, there have been numerous attempts to create more efficient classification approaches. We modify a kernel graph convolutional neural network approach, that extracts subgraphs (patches) …

All You Need To Know About Cybersecurity Ever! In 45 Minutes, Joe Beckman

Purdue Road School

This session will cover the information every local government official needs to know to keep their data safe from hackers.

Using Logical Specifications For Multi-Objective Reinforcement Learning, Kolby Nottingham

Undergraduate Honors Theses

In the multi-objective reinforcement learning (MORL) paradigm, the relative importance of environment objectives is often unknown prior to training, so agents must learn to specialize their behavior to optimize different combinations of environment objectives that are specified post-training. These are typically linear combinations, so the agent is effectively parameterized by a weight vector that describes how to balance competing environment objectives. However, we show that behaviors can be successfully specified and learned by much more expressive non-linear logical specifications. We test our agent in several environments with various objectives and show that it can generalize to many never-before-seen specifications.

Data Mining Of Chinese Social Networks: Factors That Indicate Post Deletion, Meisam Navaki Arefi

Computer Science ETDs

Widespread Chinese social media applications such as Sina Weibo (Chinese Twitter), the most popular social network in China, are widely known for monitoring and deleting posts to conform to Chinese government requirements. Censorship of Chinese social media is a complex process that involves many factors. There are multiple stakeholders and many different interests: economic, political, legal, personal, etc., which means that there is not a single strategy dictated by a single government authority. Moreover, sometimes Chinese social media do not follow the directives of government, out of concern that they are more strictly censoring than their competitors.

One crucial question …

The Water Is Always Running: Vaporwave, Fluxus, And The Role Of Defamiliarization In Music-Led Virtual Realities, Zachary William Buckley

Theses and Dissertations

This thesis examines how a Fluxus approach to participatory music can leverage environmental metaphors and affordances, heighten user awareness of their interactions through a making-strange approach to musical interaction, and balance functional and creative user experiences in a meaningful and participatory musical interaction. This research has been conducted using the virtual reality experience The Water Is Always Running. This work presents an unusual music-making environment, a 3D kitchen with dishwashing simulation, to explore how a making-strange approach to musical interaction and participation can heighten the awareness of process for the user. To create this work, ideas have been leveraged from …

Finding Music In Chaos: Designing And Composing With Virtual Instruments Inspired By Chaotic Equations, Landon P. Viator

LSU Doctoral Dissertations

Using chaos theory to design novel audio synthesis engines has been explored little in computer music. This could be because of the difficulty of obtaining harmonic tones or the likelihood of chaos-based synthesis engines to explode, which then requires re-instantiating of the engine to proceed with sound production. This process is not desirable when composing because of the time wasted fixing the synthesis engine instead of the composer being able to focus completely on the creative aspects of composition. One way to remedy these issues is to connect chaotic equations to individual parts of the synthesis engine instead of relying …

Machine Learning For The Preliminary Diagnosis Of Dementia, Fubao Zhu, Xiaonan Li, Haipeng Tang, Zhuo He, Chaoyang Zhang, Guang-Uei Hung, Pai-Yi Chiu, Weihua Zhou

Michigan Tech Publications, Part 1

Objective. The reliable diagnosis remains a challenging issue in the early stages of dementia. We aimed to develop and validate a new method based on machine learning to help the preliminary diagnosis of normal, mild cognitive impairment (MCI), very mild dementia (VMD), and dementia using an informant-based questionnaire. Methods. We enrolled 5,272 individuals who filled out a 37-item questionnaire. In order to select the most important features, three different techniques of feature selection were tested. Then, the top features combined with six classification algorithms were used to develop the diagnostic models. Results. Information Gain was the most …

Encryption Decrypted, Alex Ramsey

UNO Student Research and Creative Activity Fair

Encryption is a complex and bewildering process, yet it is absolutely foundational for secure and safe activities on the internet. Encryption, in its many forms, ultimately enables identity verification, password protection, secure conversation, cryptocurrency trade, and other online activities. Despite this widespread use, encryption is not a process easily explained to the layperson due to its complexity. Thus, the object of this research is to demystify the process of encryption and provide an understanding of one of the most common forms of modern encryption - RSA Encryption. This will be accomplished through the information provided on my poster as well …

Automated Tool Support - Repairing Security Bugs In Mobile Applications, Larry Singleton

UNO Student Research and Creative Activity Fair

Cryptography is often a critical component in secure software systems. Cryptographic primitive misuses often cause several vulnerability issues. To secure data and communications in applications, developers often rely on cryptographic algorithms and APIs which provide confidentiality, integrity, and authentication based on solid mathematical foundations. While many advanced crypto algorithms are available to developers, the correct usage of these APIs is challenging. Turning mathematical equations in crypto algorithms into an application is a difficult task. A mistake in cryptographic implementations can subvert the security of the entire system. In this research, we present an automated approach for Finding and Repairing Bugs …

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, …

Simultaneous Localization And Mapping Analysis, Jacob Miller, Kurtis Clark, Jeremy Evert

Student Research

Objectives

• Simulate virtual robot for test and analysis
• Analyze SLAM solutions using ROS
• Assemble a functional Turtlebot
• Emphasize projects related to current research trajectories for NASA, and general robotics applications

Robot Simulation Analysis, Kurtis Clark, Jacob Miller, Jeremy Evert

Student Research

Objectives

• Build a tutorial targeted to Middle School and High School Students to get ROS running on a Virtual Machine
• Make ROS and it's simulations approachable to middle school and high school students.

Machine Learning For Effective Parkinson's Disease Diagnosis, Brennon Brimhall

Undergraduate Honors Theses

Parkinson’s Disease is a degenerative neurological condition that affects approximately 10 million people globally. Because there is currently no cure, there is a strong motivation for research into improved and automated diagnostic procedures. Using Random Forests, a computer can effectively learn to diagnose Parkinson’s disease in a patient with high accuracy (94%), precision (95%), and recall (91%) across the data of over 2800 patients. Using similar techniques, I further determine that the most predictive medical tests relate to tremors observed in patients.

Black Box Analysis Of Android Malware Detectors, Guruswamy Nellaivadivelu, Fabio Di Troia, Mark Stamp

Faculty Publications, Computer Science

If a malware detector relies heavily on a feature that is obfuscated in a given malware sample, then the detector will likely fail to correctly classify the malware. In this research, we obfuscate selected features of known Android malware samples and determine whether these obfuscated samples can still be reliably detected. Using this approach, we discover which features are most significant for various sets of Android malware detectors, in effect, performing a black box analysis of these detectors. We find that there is a surprisingly high degree of variability among the key features used by popular malware detectors.