Computer Sciences Commons^™

Computing The Rectilinear Crossing Number Of K, Soundarya Revoori

USF Tampa Graduate Theses and Dissertations

Rectilinear crossing number of a graph is the number of crossing edges in a drawing with all straight line edges. The problem of drawing an n-vertex complete graph such that its rectilinear crossing number is minimum is known to be an NP-Hard problem. In this thesis, we present a heuristic that attempts to achieve the theoretical lower bound value of the rectilinear crossing number of a n+1 vertex complete graph from that of n vertices. Our algorithm accepts an optimal or near-optimal rectilinear drawing of K_n graph as input and tries to place a new node such that …

Game Specific Approaches To Monte Carlo Tree Search For Dots And Boxes, Jared Prince

Mahurin Honors College Capstone Experience/Thesis Projects

In this project, a Monte Carlo tree search player was designed and implemented for the child’s game dots and boxes, the computational burden of which has left traditional artificial intelligence approaches like minimax ineffective. Two potential improvements to this player were implemented using game-specific information about dots and boxes: the lack of information for decision-making provided by the net score and the inherent symmetry in many states. The results of these two approaches are presented, along with details about the design of the Monte Carlo tree search player. The first improvement, removing net score from the state information, was proven …

Marketing The Mountain State: A Large N Study Of User Engagement On Twitter, Kirk Richardson

Capstone Projects – Politics and Government

Much of the evolving research on the use of social media in destination marketing emphasizes how information diffusion influences the reputational image of place. The present study uses Twitter data to focus on the relative differences in user engagement across discrete account types. Specifically, this is done to examine how the official destination marketing organization of Montana—the Montana Office of Tourism (MTOT)—performs relative to other account types. Several regression analyses conducted on Twitter data associated with an ongoing MTOT place branding campaign reveal that tweets sent from ‘official’ accounts are more likely to be retweeted, and are estimated to receive …

Pedagogical Resources For Industrial Control Systems Security: Design, Implementation, Conveyance, And Evaluation, Guillermo A. Francia Iii, Greg Randall, Jay Snellen

Journal of Cybersecurity Education, Research and Practice

Industrial Control Systems (ICS), which are pervasive in our nation’s critical infrastructures, are becoming increasingly at risk and vulnerable to internal and external threats. It is imperative that the future workforce be educated and trained on the security of such systems. However, it is equally important that careful and deliberate considerations must be exercised in designing and implementing the educational and training activities that pertain to ICS. To that end, we designed and implemented pedagogical materials and tools to facilitate the teaching and learning processes in the area of ICS security. In this paper, we describe those resources, the professional …

Cyber Security For Everyone: An Introductory Course For Non-Technical Majors, Marc J. Dupuis

Journal of Cybersecurity Education, Research and Practice

In this paper, we describe the need for and development of an introductory cyber security course. The course was designed for non-technical majors with the goal of increasing cyber security hygiene for an important segment of the population—college undergraduates. While the need for degree programs that focus on educating and training individuals for occupations in the ever-growing cyber security field is critically important, the need for improved cyber security hygiene from the average everyday person is of equal importance. This paper discusses the approach used, curriculum developed, results from two runs of the course, and frames the overall structure of …

How Much Should We Teach The Enigma Machine?, Jeffrey A. Livermore

Journal of Cybersecurity Education, Research and Practice

Developing courses and programs in Information Assurance can feel like trying to force ten pounds of flour into a five pound sack. We want to pack more into our courses than we have time to teach. As new technologies develop, we often find it necessary to drop old technologies out of the curriculum and our students miss out on the historical impacts the old technologies had. The discipline is so broad and deep that we have to carefully choose what concepts and technologies we study in depth, what we mention in passing, and what we leave out. Leaving out important …

From The Editors, Carole L. Hollingsworth, Michael E. Whitman, Herbert J. Mattord

Journal of Cybersecurity Education, Research and Practice

Welcome to the third issue of the Journal of Cybersecurity Education, Research and Practice (JCERP).

Flexible And Feasible Support Measures For Mining Frequent Patterns In Large Labeled Graphs, Jinghan Meng

USF Tampa Graduate Theses and Dissertations

In recent years, the popularity of graph databases has grown rapidly. This paper focuses on single-graph as an effective model to represent information and its related graph mining techniques. In frequent pattern mining in a single-graph setting, there are two main problems: support measure and search scheme. In this paper, we propose a novel framework for constructing support measures that brings together existing minimum-image-based and overlap-graph-based support measures. Our framework is built on the concept of occurrence / instance hypergraphs. Based on that, we present two new support measures: minimum instance (MI) measure and minimum vertex cover (MVC) measure, that …

A Knowledge Graph Framework For Detecting Traffic Events Using Stationary Cameras, Roopteja Muppalla, Sarasi Lalithsena, Tanvi Banerjee, Amit Sheth

Kno.e.sis Publications

With the rapid increase in urban development, it is critical to utilize dynamic sensor streams for traffic understanding, especially in larger cities where route planning or infrastructure planning is more critical. This creates a strong need to understand traffic patterns using ubiquitous sensors to allow city officials to be better informed when planning urban construction and to provide an understanding of the traffic dynamics in the city. In this study, we propose our framework ITSKG (Imagery-based Traffic Sensing Knowledge Graph) which utilizes the stationary traffic camera information as sensors to understand the traffic patterns. The proposed system extracts image-based features …

Teaching Systems And Robotics In A Four-Week Summer Short Course, Andrew Danowitz, Bridget Benson, Jeremy Edmonds

Computer Science and Software Engineering

This paper describes a four-week summer short-course designed to introduce students with limited hands-on technical experience to the low-level details of embedded systems and robotics. Students start the course using a Raspberry Pi 3 to learn the basics of Linux and programming, and end the course by competing in a capture-the-flag type competition with the web-configurable GPS-guided autonomous robots they designed and tested in the course. Throughout the course, students are introduced to programming languages including Python and PHP, advanced programming concepts such as using sockets for inter-process communication, data interchange formats such as JSON, basic API development, system concepts …

The Necst Program - Networking And Engaging In Computer Science And Information Technology Program, Jerry Alan Fails

Computer Science Faculty Publications and Presentations

In this paper, we describe the NECST Program and its innovative mentorship structure for transitioning graduate students in computer science whose undergraduate experiences may be in other disciplines. NECST employs several activities that provide the additional scaffolding to support students as they make this transition. While we believe these activities may be suited for other situations, the program helps address the unique challenges northern New Jersey faces with relation to graduate studies in computing fields.

Question Type Recognition Using Natural Language Input, Aishwarya Soni

Master's Projects

Recently, numerous specialists are concentrating on the utilization of Natural Language Processing (NLP) systems in various domains, for example, data extraction and content mining. One of the difficulties with these innovations is building up a precise Question and Answering (QA) System. Question type recognition is the most significant task in a QA system, for example, chat bots. Organization such as National Institute of Standards (NIST) hosts a conference series called as Text REtrieval Conference (TREC) series which keeps a competition every year to encourage and improve the technique of information retrieval from a large corpus of text. When a user …

Calculating Music Similarity With Mobile Device Playlists, Jacob O'Bryant, Dennis Ng

Journal of Undergraduate Research

Music recommendation systems, such as Pandora and Spotify, help listeners to discover new music. The similarity of different songs is an important measure used in music recommendation. We have studied manually-created playlists on mobile devices to see if they can be used to accurately calculate song similarity. We collected playlists from 41 research subjects and used a co-occurrence model to calculate similarity between songs in the collection.

(Dis)Enchanted: (Re)Constructing Love And Creating Community In The, Shannon A. Suddeth

USF Tampa Graduate Theses and Dissertations

This thesis examines a queer fan community for the television show Once Upon a Time (OUAT) that utilizes the social networking site Tumblr as their primary base of fan activity. The Swan Queen fan community is comprised of individuals that collectively support and celebrate a non-canon romantic relationship between two of the female lead characters of the show rather than the canonic, heterocentric relationships that occur between the two women and their respective male love interests. I answer two research questions in this study: First, how are members of the Swan Queen fan community developing counter narratives of …

Estimation Of Human Poses Categories And Physical Object Properties From Motion Trajectories, Mona Fathollahi Ghezelghieh

USF Tampa Graduate Theses and Dissertations

Despite the impressive advancements in people detection and tracking, safety is still a key barrier to the deployment of autonomous vehicles in urban environments [1]. For example, in non-autonomous technology, there is an implicit communication between the people crossing the street and the driver to make sure they have communicated their intent to the driver. Therefore, it is crucial for the autonomous car to infer the future intent of the pedestrian quickly. We believe that human body orientation with respect to the camera can help the intelligent unit of the car to anticipate the future movement of the pedestrians. To …

Active Cleaning Of Label Noise Using Support Vector Machines, Rajmadhan Ekambaram

USF Tampa Graduate Theses and Dissertations

Large scale datasets collected using non-expert labelers are prone to labeling errors. Errors in the given labels or label noise affect the classifier performance, classifier complexity, class proportions, etc. It may be that a relatively small, but important class needs to have all its examples identified. Typical solutions to the label noise problem involve creating classifiers that are robust or tolerant to errors in the labels, or removing the suspected examples using machine learning algorithms. Finding the label noise examples through a manual review process is largely unexplored due to the cost and time factors involved. Nevertheless, we believe it …

Lost In The Crowd: Are Large Social Graphs Inherently Indistinguishable?, Subramanian Viswanathan Vadamalai

USF Tampa Graduate Theses and Dissertations

Real social graphs datasets are fundamental to understanding a variety of phenomena, such as epidemics, crowd management and political uprisings, yet releasing digital recordings of such datasets exposes the participants to privacy violations. A safer approach to making real social network topologies available is to anonymize them by modifying the graph structure enough as to decouple the node identity from its social ties, yet preserving the graph characteristics in aggregate. At scale, this approach comes with a significant challenge in computational complexity.

This thesis questions the need to structurally anonymize very large graphs. Intuitively, the larger the graph, the easier …

Insights Into The Binding Mode Of Mek Type-Iii Inhibitors. A Step Towards Discovering And Designing Allosteric Kinase Inhibitors Across The Human Kinome, Zheng Zhao, Lei Xie, Philip E. Bourne

Publications and Research

Protein kinases are critical drug targets for treating a large variety of human diseases. Type- III kinase inhibitors have attracted increasing attention as highly selective therapeutics. Thus, understanding the binding mechanism of existing type-III kinase inhibitors provides useful insights into designing new type-III kinase inhibitors. In this work, we have systematically studied the binding mode of MEK-targeted type-III inhibitors using structural systems pharmacology and molecular dynamics simulation. Our studies provide detailed sequence, structure, interaction-fingerprint, pharmacophore and binding-site information on the binding characteristics of MEK type-III kinase inhibitors. We hypothesize that the helix-folding activation loop is a hallmark allosteric binding site …

Toward Accurate And Efficient Feature Selection For Speaker Recognition On Wearables, Rui Liu, Reza Rawassizadeh, David Kotz

Dartmouth Scholarship

Due to the user-interface limitations of wearable devices, voice-based interfaces are becoming more common; speaker recognition may then address the authentication requirements of wearable applications. Wearable devices have small form factor, limited energy budget and limited computational capacity. In this paper, we examine the challenge of computing speaker recognition on small wearable platforms, and specifically, reducing resource use (energy use, response time) by trimming the input through careful feature selections. For our experiments, we analyze four different feature-selection algorithms and three different feature sets for speaker identification and speaker verification. Our results show that Principal Component Analysis (PCA) with frequency-domain …

Privacy Issues And Solutions For Consumer Wearables, Alfredo J. Perez, Sherali Zeadally

Computer Science Faculty Publications

Consumer wearables have emerged as disrupting devices that benefit citizens in areas such as mobile health, fitness, security, and entertainment. The mass adoption of these devices not only generates high revenues but also exposes important privacy issues. The authors identify some of the major privacy issues associated with consumer wearables and explore possible solutions to address privacy concerns.

Improving Text Classification With Word Embedding, Lihao Ge

Master's Projects

One challenge in text classification is that it is hard to make feature reduction basing upon the meaning of the features. An improper feature reduction may even worsen the classification accuracy. Word2Vec, a word embedding method, has recently been gaining popularity due to its high precision rate of analyzing the semantic similarity between words at relatively low computational cost. However, there are only a limited number of researchers focusing on feature reduction using Word2Vec. In this project, we developed a Word2Vec based method to reduce the feature size while increasing the classification accuracy. The feature reduction is achieved by loosely …

An Ensemble Multilabel Classification For Disease Risk Prediction, Runzhi Li, Wei Liu, Yusong Lin, Hongling Zhao, Chaoyang Zhang

Faculty Publications

It is important to identify and prevent disease risk as early as possible through regular physical examinations. We formulate the disease risk prediction into a multilabel classification problem. A novel Ensemble Label Power-set Pruned datasets Joint Decomposition (ELPPJD) method is proposed in this work. First, we transform the multilabel classification into a multiclass classification. Then, we propose the pruned datasets and joint decomposition methods to deal with the imbalance learning problem. Two strategies size balanced (SB) and label similarity (LS) are designed to decompose the training dataset. In the experiments, the dataset is from the real physical examination records. We …

Stay Safe Online!, Jenny Blaine

Innovate! Teaching with Technology Conference

Inform audience of potential online threats to their online security and reasons for that; empower audience to employ best practices to protect themselves during online activities.

Multiple Audiences

2d And 3d Pointing Device Based On A Passive Lights Detection Operation Method Using One Camera, Fuhua Cheng

Computer Science Faculty Patents

Systems for surface-free pointing and/or command input include a computing device operably linked to an imaging device. The imaging device can be any suitable video recording device including a conventional webcam. At least one pointing/input device is provided including first, second, and third sets of actuable light sources, wherein at least the first and second sets emit differently colored light. The imaging device captures one or more sequential image frames each including a view of a scene including the activated light sources. One or more computer program products calculate a two-dimensional or three-dimensional position and/or a motion and/or an orientation …

Utilizing The Power Of Graphical Processing For Dna Mapping: A Comparison Of Gnumap And Barracuda, Cole Lyman, Mark Clement

Journal of Undergraduate Research

Recent advances in genome sequencing technologies have resulted in a large increase in the amount of genetic data available. Large Genome Wide Association Studies (GWAS) have the potential to identify the causes of cancer, Alzheimer’s disease, heart failure and many other diseases if the large quantities of data that are becoming available can be analyzed effectively. Next-generation read mapping software, a crucial step in analyzing genetic data, is slow while trying to achieve high mapping accuracy. One approach to speeding up next-generation read mapping focuses on using Graphical Processing Units (GPUs). This project compared the effectiveness of two genome mappers, …

Viral Marketing For Smart Cities: Influencers In Social Network Communities, Madhura Kaple, Ketki Kulkarni, Katerina Potika

Faculty Publications, Computer Science

Social networks are used by cities primarily for announcing local-area events, but also for increasing engagement of citizens in votes and elections. Given the current plethora of heterogeneous social networks, city administrators can benefit from social networks to promote initiatives, which are important to a current smart city as well use them to discover future needs in order to manage resources more efficiently. Our focus in this paper is how we can adapt commercial and viral marketing techniques to smart city systems to influence the behavior, opinion and choices of citizens in order to improve their well being and that …

Intuitive Error Space Exploration Of Medical Image Data In Clinical Daily Routine, Christina Gillmann, Pablo Arbeláez, José Tiberio Hernández Peñaloza, Hans Hagen, Thomas Wischgoll

Computer Science and Engineering Faculty Publications

Medical image data can be affected by several image errors. These errors can lead to uncertain or wrong diagnosis in clinical daily routine. A large variety of image error metrics are available that target different aspects of image quality forming a highdimensional error space, which cannot be reviewed trivially. To solve this problem, this paper presents a novel error space exploration technique that is suitable for clinical daily routine. Therefore, the clinical workflow for reviewing medical data is extended by error space cluster information, that can be explored by user-defined selections. The presented tool was applied to two real-world datasets …

Investigating Security For Ubiquitous Sensor Networks, Alfredo J. Perez, Sherali Zeadally, Nafaa Jabeur

Information Science Faculty Publications

The availability of powerful and sensor-enabled mobile and Internet-connected devices have enabled the advent of the ubiquitous sensor network paradigm which is providing various types of solutions to the community and the individual user in various sectors including environmental monitoring, entertainment, transportation, security, and healthcare. We explore and compare the features of wireless sensor networks and ubiquitous sensor networks and based on the differences between these two types of systems, we classify the security-related challenges of ubiquitous sensor networks. We identify and discuss solutions available to address these challenges. Finally, we briefly discuss open challenges that need to be addressed …

Back To The Future: Logic And Machine Learning, Simon Dobnik, John D. Kelleher

Conference papers

In this paper we argue that since the beginning of the natural language processing or computational linguistics there has been a strong connection between logic and machine learning. First of all, there is something logical about language or linguistic about logic. Secondly, we argue that rather than distinguishing between logic and machine learning, a more useful distinction is between top-down approaches and data-driven approaches. Examining some recent approaches in deep learning we argue that they incorporate both properties and this is the reason for their very successful adoption to solve several problems within language technology.

Reflections On An Experiment, Evaluating The Impact Of Spatialisation On Exploration, Clement Roux, John Mcauley

Conference papers

This paper reports on an experiment designed to evaluate whether visualising a digital library (using a spatialisation technique) can influence exploratory search behaviour. In the experiment we asked participants to complete a set of novel tasks using one of two interfaces - a visualisation interface, ExploViz, and its search-based equivalent, LibSearch. A set of measures were used to capture sensemaking and exploratory behaviour and to analyse cognitive load. As results were non-significant, we reflect upon the design of the experiment, consider possible issues and suggest how these could be addressed in future iterations.