Computer Sciences Commons^™

Retrospective On A Decade Of Research In Visualization For Cybersecurity, R. Jordan Crouser, Erina Fukuda, Subashini Sridhar

Computer Science: Faculty Publications

Over the past decade, the visualization for cybersecurity (VizSec) research community has adapted many information visualization techniques to support the critical work of cyber analysts. While these efforts have yielded many specialized tools and platforms, the community lacks a unified approach to the design and implementation of these systems. In this work, we provide a retrospective analysis of the past decade of VizSec publications, with an eye toward developing a more cohesive understanding of the emerging patterns of design at work in our community. We identify common thematic groupings among existing work, as well as several interesting pat- terns of …

Relation Algebras, Idempotent Semirings And Generalized Bunched Implication Algebras, Peter Jipsen

Mathematics, Physics, and Computer Science Faculty Articles and Research

This paper investigates connections between algebraic structures that are common in theoretical computer science and algebraic logic. Idempotent semirings are the basis of Kleene algebras, relation algebras, residuated lattices and bunched implication algebras. Extending a result of Chajda and Länger, we show that involutive residuated lattices are determined by a pair of dually isomorphic idempotent semirings on the same set, and this result also applies to relation algebras. Generalized bunched implication algebras (GBI-algebras for short) are residuated lattices expanded with a Heyting implication. We construct bounded cyclic involutive GBI-algebras from so-called weakening relations, and prove that the class of weakening …

A Deep Learning Framework For Automated Vesicle Fusion Detection, Haohan Li, Zhaozheng Yin, Yingke Xu

Computer Science Faculty Research & Creative Works

Quantitative analysis of vesicle-plasma membrane fusion events in the fluorescence microscopy, has been proven to be important in the vesicle exocytosis study. In this paper, we present a framework to automatically detect fusion events. First, an iterative searching algorithm is developed to extract image patch sequences containing potential events. Then, we propose an event image to integrate the critical image patches of a candidate event into a single-image joint representation as the input to Convolutional Neural Networks (CNNs). According to the duration of candidate events, we design three CNN architectures to automatically learn features for the fusion event classification. Compared …

Experiences With Scala Across The College-Level Curriculum, Konstantin Läufer, George K. Thiruvathukal, Mark C. Lewis

Emerging Technologies Laboratory

Various hybrid-functional languages, designed to balance compile-time error detection, conciseness, and performance, have emerged. Scala, e.g., is interoperable with Java and has become an early leader in adoption, especially in the start-up and open-source spaces.

As educators, we have recognized Scala’s value as a teaching language across the CS curriculum. In CS1, the read-eval-print loop and simple, uniform syntax aid programming in the small. In CS2, higher-order methods allow concise, efficient manipulation of collections. In a programming languages course, advanced constructs facilitate the separation of concerns, program representation and interpretation, and concurrent programming. In advanced applied courses, language mechanisms and …

A Parallelized Method For Solving Large Scale Integer Linear Optimization Problems Using Cut-And-Solve With Applications To Cgwas, John Brandenburg

Theses

The commercial solver CPLEX has been one of the top solvers of mixed-integer and purely integer linear problems for some time. Its method of solving, Branch-and-Cut, has been shown to be highly effective, but has its limits in terms of input sizes which are tractable, and cannot be effectively parallelized beyond a small number. Here we present a different method of solution, Cut-and-Solve, which utilizes the power of CPLEX to effectively parallelize any mixed-integer or integer linear problem. We have utilized Cut-and-Solve in a novel way to offer optimal solution guarantees more quickly. We will show comparisons of Cut-and-Solve to …

Group Work Versus Informal Collaborations: Student Perspectives, Andrew Danowitz

Computer Science and Software Engineering

A substantial body of research exists showing that, when implemented correctly, the use of group work in a class can improve student learning outcomes. When implemented incorrectly, however, group-based assignments can lead to dysfunction and inter-personal conflicts that can hamper overall student success. This problem can be especially acute in first and second year engineering fundamentals courses where advanced students who learn the concepts faster may end up completing—and reaping the benefits of—a lions-share of the group work. As the course material starts to build on itself, those students who initially underperformed in their group may lack the understanding to …

Network Exploration Of Correlated Multivariate Protein Data For Alzheimer's Disease Association, Matthew J. Lane

Theses

Alzheimer Disease (AD) is difficult to diagnose by using genetic testing or other traditional methods. Unlike diseases with simple genetic risk components, there exists no single marker determining as to whether someone will develop AD. Furthermore, AD is highly heterogeneous and different subgroups of individuals develop the disease due to differing factors. Traditional diagnostic methods using perceivable cognitive deficiencies are often too little too late due to the brain having suffered damage from decades of disease progression. In order to observe AD at early stages prior to the observation of cognitive deficiencies, biomarkers with greater accuracy are required. By using …

The Creation Of A Building Map Application For A University Setting, William T. Whitesell

Senior Honors Theses

The use of navigational technology in mobile and web devices has sharply increased in recent years. With the capability to create interactive maps now available, navigating in real time between locations has become possible. This is especially essential in areas and organizations experiencing rapid expansion like Liberty University (LU). Therefore, the author proposes a project to create an interactive map application (IMA) for LU’s academic buildings that is scalable and usable through both the university’s website and with a mobile application. There are several considerations that must be taken into account when creating the LU map application, such as development …

Mapping Community Space And Place In Mto Wa Mbu, Tanzania Through Surveys And Gis, Jessica Craigg

Georgia College Student Research Events

Cities throughout the African continent have been developing at an unprecedented pace, many of them due to the influence of the tourism industry. This is particularly true in Tanzania, a country famous for its national parks and their draw to tourists who help provide money for development. However, the only way to get the whole story on how to spend this money is through the experiences and needs of the people themselves. This study focuses on a small town in northeastern Tanzania, Mto wa Mbu, situated near Lake Manyara National Park, and its people’s perceptions of the park and community. …

2017 Petersheim Academic Exposition Schedule Of Events, Seton Hall University

Petersheim Academic Exposition

2017 Petersheim Academic Exposition

Monitoring The Dark Web And Securing Onion Services, John Schriner

Publications and Research

This paper focuses on how researchers monitor the Dark Web. After defining what onion services and Tor are, we discuss tools for monitoring and securing onion services. As Tor Project itself is research-driven, we find that the development and use of these tools help us to project where use of the Dark Web is headed.

An Appromximation Algorithm For Motif Finding In Dna Sequences, Hasnaa Imad Al-Shaikhli

Research and Creative Activities Poster Day

• Motif finding is a significant problem in biology and computer science fields.

• Search for similar (not exact) motifs in multiple DNA sequences is non -trivial, and is a time trivial, and is a time -consuming problem.

• IDEA: design an algorithm that reduces the search space to decrease the run -time based on a d-neighbors set analysis.

• The d -neighbors set is a list of all instances for subsequence x of length I with maximum allowed mutations ≤ d.

• Analyzing these sets to make use of the distance frequencies between neighbors without generating them would help …

Enhance A Deep Neural Network Model For Twitter Sentiment Analysis By Incorporating A User-Level Information, Ahmed Sulaiman M Alharbi

Research and Creative Activities Poster Day

Most existing sentiment classification methods for social media focus on document-level classification. They utilize local text information and ignore the crucial characteristic information of users. These methods usually suffer from high model complexity and only exhibit word-level preference.

Therefore, motivated by the successful utilization of deep neural networks in computer vision, speech recognition and natural language processing and their ability of learning in multi-prospective ways, a neural network based sentiment analysis model is proposed to incorporate user-level information into sentiment classification.

By user-level information we mean information extracted or inferred from the user that helps the proposed model to engage …

Design And Implementation Of An Rfid-Based Customer Shopping Behavior Mining System, Zimu Zhou, Longfei Shangguan, Xiaolong Zheng, Lei Yang, Yunhao Liu

Research Collection School Of Computing and Information Systems

Shopping behavior data is of great importance in understanding the effectiveness of marketing and merchandising campaigns. Online clothing stores are capable of capturing customer shopping behavior by analyzing the click streams and customer shopping carts. Retailers with physical clothing stores, however, still lack effective methods to comprehensively identify shopping behaviors. In this paper, we show that backscatter signals of passive RFID tags can be exploited to detect and record how customers browse stores, which garments they pay attention to, and which garments they usually pair up. The intuition is that the phase readings of tags attached to items will demonstrate …

Machine Learning Csc 461, Amanda Izenstark

Library Impact Statements

No abstract provided.

Early Detection Of Diseases Using Electronic Health Records Data And Covariance-Regularized Linear Discriminant Analysis, Jiang Bian, Laura E. Barnes, Guanling Chen, Haoyi Xiong

Computer Science Faculty Research & Creative Works

The availability of Electronic Health Records (EHR) in health care settings provides terrific opportunities for early detection of patients' potential diseases. While many data mining tools have been adopted for EHR-based disease early detection, Linear Discriminant Analysis (LDA) is one of the most widely used statistical prediction methods. To improve the performance of LDA for early detection of diseases, we proposed to leverage CRDA - Covariance-Regularized LDA classifiers on top of diagnosis-frequency vector data representation. Specifically, CRDA employs a sparse precision matrix estimator derived based on graphical lasso to boost the accuracy of LDA classifiers. Algorithm analysis demonstrates that the …

Bayesian Statistics I Sta 415, Amanda Izenstark

Library Impact Statements

No abstract provided.

Information Fusion Based Techniques For Hevc, D. G. Fernández, A. A. Del Barrio, Guillermo Botella, Uwe Meyer-Baese, Anke Meyer-Baese, Christos Grecos

All Faculty Scholarship for the College of the Sciences

Aiming at the conflict circumstances of multi-parameter H.265/HEVC encoder system, the present paper introduces the analysis of many optimizations' set in order to improve the trade-off between quality, performance and power consumption for different reliable and accurate applications. This method is based on the Pareto optimization and has been tested with different resolutions on real-time encoders.

Pre-Processing Techniques To Improve Hevc Subjective Quality, D. G. Fernández, A. A. Del Barrio, Guillermo Botella, Uwe Meyer-Baese, Anke Meyer-Baese, Christos Grecos

All Faculty Scholarship for the College of the Sciences

Nowadays, HEVC is the cutting edge encoding standard being the most efficient solution for transmission of video content. In this paper a subjective quality improvement based on pre-processing algorithms for homogeneous and chaotic regions detection is proposed and evaluated for low bit-rate applications at high resolutions. This goal is achieved by means of a texture classification applied to the input frames. Furthermore, these calculations help also reduce the complexity of the HEVC encoder. Therefore both the subjective quality and the HEVC performance are improved.

Granting Personhood For Sentient Non-Human Animals And Sentient Artificial Intelligences: A Demonstrative Argument, Jeremiah Meadows

Virginias Collegiate Honors Council Conference

While the subject of personhood has been exhaustively debated regarding the unborn, personhood for sentient animals and artificial intelligences is a concept that is rarely deliberated. Humanity has learned that there are multiple animal species which are very similar to humans in their self-awareness, emotional capacity, and free will. These traits have been partially developed for artificial intelligences as well, and those characteristics will evolve alongside human and technological development. As stratified societies emerged, there have been multiple occurrences where individuals were deemed lesser but then later acquired equal standing. Dr. Daniel Wilson, roboticist, wrote in his novel Robopocalypse, “It …

2-(51, 6, 1) Block Designs, Wenting Zhao, Mark Liffiton. Faculty Advisor

John Wesley Powell Student Research Conference

No abstract provided.

Semantic Description Of Activities In Videos, Fillipe Dias Moreira De Souza

USF Tampa Graduate Theses and Dissertations

Description of human activities in videos results not only in detection of actions and objects but also in identification of their active semantic relationships in the scene. Towards this broader goal, we present a combinatorial approach that assumes availability of algorithms for detecting and labeling objects and actions, albeit with some errors. Given these uncertain labels and detected objects, we link them into interpretative structures using domain knowledge encoded with concepts of Grenander’s general pattern theory. Here a semantic video description is built using basic units, termed generators, that represent labels of objects or actions. These generators have multiple out-bonds, …

The Chess Puzzle Lock Screen, Ryan J. Hayes

Student Scholar Showcase

The Chess Puzzle Lock Screen

Many times each day, owners of cellphones use their phone’s lock screen in order to access their device. The goal of this project has been to take advantage of the action of unlocking one’s device by incorporating an element of self-help into the process. Every time a user who is interested in learning a new field attempts to access their device, that user is faced with a problem pertaining to a subject they are interested in learning more about. After many repetitions of this scenario, the user will have increased their understanding of this field. …

Virtual Reality: Google Cardboard And Unity, Emma Elliott

Student Scholar Showcase

Virtual Reality is currently the hottest way for people to play video games because it provides an immersive and interactive world to explore. It uses computer software to create sounds, realistic images, and other effects to simulate a virtual setting. The current craze started on the Oculus Rift headset and has incited other companies to make their own, but most are expensive or require another system to play. Instead of buying an expensive headset, anyone with a smartphone can play in Virtual Reality with Google’s cheap alternative, the Google Cardboard. The goal of this project is to complete a prototype …

Identifying The Brain Mechanisms Encoding Trust Behaviors, Gokce Hazaroglu

Theses and Dissertations

Early life trauma may disrupt the family dynamic by altering trust. The purpose of this dissertation is to understand the brain mechanisms that encode trust. University of Arkansas for Medical Sciences (UAMS) researchers are currently conducting a triadic cooperative experiment (TCE) while participants’ brain activity is concurrently being recorded via a functional magnetic resonance imaging (fMRI) scanner. The TCE is a socioeconomic task in which two caregivers and an adolescent take turns transferring wealth to each other which is multiplied by a constant factor. The task encourages cooperation between participants by first, randomly assigning who must give wealth on any …

Satellite Detection And Ranging System, A S M Sarwar Zahan

Theses and Dissertations

The thrust on Nano-satellite technologies is increasing day by day. Research is going on to detect satellites in austere environment. However, the technology of tracking the satellite in both in-formation and out of formation is yet to discover. I propose a novel algorithm to detect satellites in regular orbit and even in different close operations, i.e. docking, inspection and rendezvous. I aim to modify two existing and promising image processing algorithms and apply towards my own satellite detection problem. Various image processing algorithms have incorporated to enable tracking of the Target Flight Unit (T-FU) from the Chase Flight Unit (C-FU). …

Identifying Temporal Structure In Fmri Bold Signal, Onder Hazaroglu

Theses and Dissertations

To better understand the brain’s structure and function, we need to be able to measure the brain’s activity. The field of measuring the brain is neuroimaging. Neuroimaging methodology predominantly relies on the functional magnetic resonance imaging (fMRI) blood oxygen level dependent (BOLD) contrast signal. Although the BOLD signal is a valid measure, it is an indirect measure of neural activity. Rather, two interacting latent components comprise BOLD: 1) neural events, which encode cognitive processes, and 2) physiological responses to neural events, which are well-modeled by the Hemodynamic Response Function (HRF). In this dissertation, we explore models of these components via …

Stream Data Quality Assessment Based On Distributed Computing Platforms, Wei Dai

Theses and Dissertations

In this era of big data, data quality will be increasingly important because people need high quality data to make decisions, analyze patterns, and discover knowledge. So, measuring data quality is a vital mission. In this thesis, Chapter 1 is the introduction, Chapter 2 is a literature review, Chapter 3 illustrates how to discover potentially important data based on a reference algorithm, a frequency algorithm, and an entropy algorithm, in Chapter 4, the author offers a concise five-layer data quality framework to measure stream data quality scorecards, in Chapter 5, the author shows how to visualize data quality scorecards through …

Blocking Strategies For Performing Entity Resolution In A Distributed Computing Environment, Pei Wang

Theses and Dissertations

Entity resolution (ER) is an O(n2) problem where n is the number of records to be processed. The pair-wise nature of ER makes it impractical to perform on large datasets without the use of a technique called blocking. In blocking the records are separated into groups (called blocks) in such a way the records most likely to match are within the same block. The ER system only compares pairs of records within the same block, thus reducing the total number of pairs to match. Traditionally, blocking algorithms build inverted indices in memory to quickly locate potential matches. With the advent …

Quantitative Criticism Of Literary Relationships, Joseph P. Dexter, Theodore Katz, Nilesh Tripuraneni, Tathagata Dasgupta, Ajay Kannan, James Brofos, Jorge A. Bonilla Lopez, Lea Schroeder

Dartmouth Scholarship

Authors often convey meaning by referring to or imitating prior works of literature, a process that creates complex networks of literary relationships (“intertextuality”) and contributes to cultural evolution. In this paper, we use techniques from stylometry and machine learning to address subjective literary critical questions about Latin literature, a corpus marked by an extraordinary concentration of intertextuality. Our work, which we term “quantitative criticism,” focuses on case studies involving two influential Roman authors, the playwright Seneca and the historian Livy. We find that four plays related to but distinct from Seneca’s main writings are differentiated from the rest of the …