Computer Sciences Commons^™

Conditional Dilated Attention Tracking Model - C-Datm, Tyler Clayton Highlander

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Current commercial tracking systems do not process images fast enough to perform target-tracking in real- time. State-of-the-art methods use entire scenes to locate objects frame-by-frame and are commonly computationally expensive because they use image convolutions. Alternatively, attention mechanisms track more efficiently by mimicking human optical cognitive interaction to only process small portions of an image. Thus, in this work we use an attention-based approach to create a model called C-DATM (Conditional Dilated Attention tracking Model) that learns to compare target features in a sequence of image-frames using dilated convolutions. The C-DATM is tested using the Modified National Institute of Standards …

Leveraging Schema Information For Improved Knowledge Graph Navigation, Rama Someswar Chittella

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Over the years, the semantic web has emerged as a new generation of the world wide web featuring advanced technologies and research contributions. It has revolutionized the usage of information by allowing users to capture and publish machine-understandable data and expedite methods such as ontologies to perform the same. These ontologies help in the formal representation of a specified domain and foster comprehensive machine understanding. Although, the engineering of ontologies and usage of logic have been an integral part of the web semantics, new areas of research such as the semantic web search, linking and usage of open data on …

Anticipation In Dynamic Environments: Deciding What To Monitor, Zohreh A. Dannenhauer

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In dynamic environments, external changes may occur that may affect planning decisions and goal choices. We claim that an intelligent agent should actively watch for what can go wrong and anticipate changes in the environment that allows the changing of its plan or changing of a given goal. In this thesis, we focus on the relationship between perception, act, interpretation, and planning. We claim that these components are not independent and need to interact with each other to help the agent succeed in achieving its goals and plans. If newly encountered world information affects the plan, the agent adapts to …

Software Implementations And Applications Of Elliptic Curve Cryptography, Kirill Kultinov

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Elliptic Curve Cryptography (ECC) is a public-key cryptography system. Elliptic Curve Cryptography (ECC) can achieve the same level of security as the public-key cryptography system, RSA, with a much smaller key size. It is a promising public key cryptography system with regard to time efficiency and resource utilization. This thesis focuses on the software implementations of ECC over finite field GF(p) with two distinct implementations of the Big Integer classes using character arrays, and bit sets in C++ programming language. Our implementation works on the ECC curves of the form y^2 = x^3 + ax + b (mod p). The …

Rules With Right Hand Existential Or Disjunction With Rowltab, Sri Jitendra Satpathy

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One hotly debated research topic is, “What is the best approach for modeling ontologies?”. In the earlier stages of modeling ontologies, researchers have favored the usage of description logic to capture knowledge. One such choice is the Web Ontology Language (OWL) that is based on description logic. Many tools were designed around this principle and are still widely being used to model and explore ontologies. However, not all users find description logic to be intuitive, at least not without an extensive background in formal logics. Due to this, researchers have tried to explore other ways that will enable such users …

Recognition Of Incomplete Objects Based On Synthesis Of Views Using A Geometric Based Local-Global Graphs, Michael Christopher Robbeloth

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The recognition of single objects is an old research field with many techniques and robust results. The probabilistic recognition of incomplete objects, however, remains an active field with challenging issues associated to shadows, illumination and other visual characteristics. With object incompleteness, we mean missing parts of a known object and not low-resolution images of that object. The employment of various single machine-learning methodologies for accurate classification of the incomplete objects did not provide a robust answer to the challenging problem. In this dissertation, we present a suite of high-level, model-based computer vision techniques encompassing both geometric and machine learning approaches …

Leveraging Blockchain To Mitigate The Risk Of Counterfeit Microelectronics In Its Supply Chain, Aman Ali Pogaku

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System on Chip (SoC) is the backbone component of the electronics industry nowadays. ASIC and FPGA-based SoCs are the two most popular methods of manufacturing SoCs. However, both ASIC and FPGA industries are plagued with risks of counterfeits due to the limitations in Security, Accountability, Complexity, and Governance of their supply chain management. As a result, the current practices of these microelectronics supply chain suffer from performance and efficiency bottlenecks. In this research, we are incorporating blockchain technology into the FPGA and ASIC microelectronic supply chain to help mitigate the risk of counterfeit microelectronics through a secure and decentralized solution …

Design And Development Of An Immersive Simulation For Social Determinants Of Health Training, Lahari Surapaneni

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This thesis research project focuses on design and development of an immersion simulation-based training tool that help raise the social determinants of health (SDOH) awareness among the health care providers. Compared to existing classroom lecture and/or role-play based SDOH education approach, our immersion-simulation based approach provides an easy access and highly realistic experience to such training curriculum at anytime and anywhere with an Internet connection. Such an interactive and immersive exposure is critical to raise SDOH awareness and maintain long-lasting empathy towards actual patients in practice, and thus help providers to be better prepared when encountering with those patients. Particularly, …

Data-Driven And Knowledge-Based Strategies For Realizing Crowd Wisdom On Social Media, Shreyansh Bhatt

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The wisdom of the crowd is a well-known example of collective intelligence wherein an aggregated judgment of a group of individuals is superior to that of an individual. The aggregated judgment is surprisingly accurate for predicting the outcome of a range of tasks from geopolitical forecasting to the stock price prediction. Recent research has shown that participants' previous performance data contributes to the identification of a subset of participants that can collectively predict an accurate outcome. In the absence of such performance data, researchers have explored the role of human-perceived diversity, i.e., whether a human considers a crowd as a …

A Hott Approach To Computational Effects, Phillip A. Wells

Senior Independent Study Theses

A computational effect is any mutation of real-world state that occurs as the result of a computation. We develop a model for describing computational effects within homotopy type theory, a branch of mathematics separate from other foundations such as set theory. Such a model allows us to describe programs as total functions over values while preserving information about the effects those programs induce.

The D&D Sorting Hat: Predicting Dungeons And Dragons Characters From Textual Backstories, Joseph C. Macinnes

Senior Independent Study Theses

Dungeons and Dragons is a tabletop roleplaying game which focuses heavily on character interaction and creating narratives. The current state of the game's character creation process often bogs down new players in decisions related to game mechanics, not a character's identity and personality. This independent study investigates the use of machine learning and natural language processing to make these decisions for a player based on their character's backstory - the textual biography or description of a character. The study presents a collection of existing characters and uses these examples to create a family of models capable of predicting a character's …

Ieee Access Special Section Editorial: Wirelessly Powered Networks, And Technologies, Theofanis P. Raptis, Nuno B. Carvalho, Diego Masotti, Lei Shu, Cong Wang, Yuanyuan Yang

Computer Science Faculty Publications

Wireless Power Transfer (WPT) is, by definition, a process that occurs in any system where electrical energy is transmitted from a power source to a load without the connection of electrical conductors. WPT is the driving technology that will enable the next stage in the current consumer electronics revolution, including battery-less sensors, passive RF identification (RFID), passive wireless sensors, the Internet of Things and 5G, and machine-to-machine solutions. WPT-enabled devices can be powered by harvesting energy from the surroundings, including electromagnetic (EM) energy, leading to a new communication networks paradigm, the Wirelessly Powered Networks.

Assessment Of Two Pedagogical Tools For Cybersecurity Education, Pranita Deshpande

LSU New Orleans Theses and Dissertations

Cybersecurity is an important strategic areas of computer science, and a difficult discipline to teach effectively. To enhance and provide effective teaching and meaningful learning, we develop and assess two pedagogical tools: Peer instruction, and Concept Maps. Peer instruction teaching methodology has shown promising results in core computer science courses by reducing failure rates and improving student retention in computer science major. Concept maps are well-known technique for improving student-learning experience in class. This thesis document presents the results of implementing and evaluating the peer instruction in a semester-long cybersecurity course, i.e., introduction to computer security. Development and evaluation of …

Black Networks In Smart Cities, Shaibal Chakrabarty

Computer Science and Engineering Theses and Dissertations

In this dissertation, we present the Black Networks solution to protect both the data and the metadata for mobile ad-hoc Internet of Things (IoT) networks in Smart Cities. IoT networks are gaining popularity with billions of deployed nodes, and increasingly carrying mission-critical data, whose compromise can lead to catastrophic consequences. IoT nodes are resource-constrained and often exist within insecure environments, making them vulnerable to a broad range of active and passive attacks. Black IoT networks are designed to mitigate multiple communication-based attacks by encrypting the data and the metadata, within a communication frame or packet, while remaining compatible with the …

Historical Effects Of Electronic Interfaces, G James Mitchell

Publications and Research

Electronic interfaces are a primary tool for most professional and personal communication currently happening. Electronics, like the human mind, are limited by the understanding of executing will, or commands. This can be characterized as “interface limitations” of digital technology. Identifying this bottleneck in technological development has been critical in historical changes to both hardware and software technology. Recent medical research examines a novel user interface to reduce task load. I hypothesize, interface developments that take cues from nonverbal human communication enhance and sustain the significance of those technologies in society. By examining pivotal moments of historical technology we can identify …

Cloud Service Reliability And Usability Measurement, Abdullah Bokhary

Computer Science and Engineering Theses and Dissertations

Cloud computing has become a major resource for fulfilling people's computational and storage needs. Investing in these services requires measuring and assuring its quality in general, and reliability and usability are primary concerns. However, using traditional reliability models can be challenging because of the environmental constraints and limited data availability due to the heterogeneous environment and diverse stakeholders. Also, the quality of cloud service Application Programming Interfaces (APIs) has a direct impact on the usability and reliability of the service.

We developed a framework to measure reliability with alternative available information that most cloud providers offer in three stages: 1) …

Improving The Accuracy Of Mobile Touchscreen Qwerty Keyboards, Amanda Kirk

Electronic Theses and Dissertations

In this thesis we explore alternative keyboard layouts in hopes of finding one that increases the accuracy of text input on mobile touchscreen devices. In particular, we investigate if a single swap of 2 keys can significantly improve accuracy on mobile touchscreen QWERTY keyboards. We do so by carefully considering the placement of keys, exploiting a specific vulnerability that occurs within a keyboard layout, namely, that the placement of particular keys next to others may be increasing errors when typing. We simulate the act of typing on a mobile touchscreen QWERTY keyboard, beginning with modeling the typographical errors that can …

A Bi-Encoder Lstm Model For Learning Unstructured Dialogs, Diwanshu Shekhar

Electronic Theses and Dissertations

Creating a data-driven model that is trained on a large dataset of unstructured dialogs is a crucial step in developing a Retrieval-based Chatbot systems. This thesis presents a Long Short Term Memory (LSTM) based Recurrent Neural Network architecture that learns unstructured multi-turn dialogs and provides implementation results on the task of selecting the best response from a collection of given responses. Ubuntu Dialog Corpus Version 2 (UDCv2) was used as the corpus for training. Ryan et al. (2015) explored learning models such as TF-IDF (Term Frequency-Inverse Document Frequency), Recurrent Neural Network (RNN) and a Dual Encoder (DE) based on Long …

Using Eeg-Validated Music Emotion Recognition Techniques To Classify Multi-Genre Popular Music For Therapeutic Purposes, Dejoy Shastikk Kumaran

The International Student Science Fair 2018

Music is observed to possess significant beneficial effects to human mental health, especially for patients undergoing therapy and older adults. Prior research focusing on machine recognition of the emotion music induces by classifying low-level music features has utilized subjective annotation to label data for classification. We validate this approach by using an electroencephalography-based approach to cross-check the predictions of music emotion made with the predictions from low-level music feature data as well as collected subjective annotation data. Collecting 8-channel EEG data from 10 participants listening to segments of 40 songs from 5 different genres, we obtain a subject-independent classification accuracy …

Using Eeg-Validated Music Emotion Recognition Techniques To Classify Multi-Genre Popular Music For Therapeutic Purposes, Dejoy Shastikk Kumaran

The International Student Science Fair 2018

Music is observed to possess significant beneficial effects to human mental health, especially for patients undergoing therapy and older adults. Prior research focusing on machine recognition of the emotion music induces by classifying low-level music features has utilized subjective annotation to label data for classification. We validate this approach by using an electroencephalography-based approach to cross-check the predictions of music emotion made with the predictions from low-level music feature data as well as collected subjective annotation data. Collecting 8-channel EEG data from 10 participants listening to segments of 40 songs from 5 different genres, we obtain a subject-independent classification accuracy …

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

Undergraduate Research Celebration 2018

No abstract provided.

An Investigation Of Scenic Visualization Using Virtual Reality During Rehearsal, Cyrus Jian Bonyadi

Computer Science

In this paper, we discuss the use of virtual reality as a tool for actors during the rehearsal process and assess methods to implement and continue this research in future works. During the rehearsal process, the scenic design is normally introduced to actors close to the end of rehearsals. In introducing a virtual reality environment to train actors, we hoped to help them develop a better understanding of the design at an earlier point in the process. Our investigative pilot study involves two productions in a university theatre, where we render the scenic design of the production for which our …

Survey Of Techniques For Producing Blended Images: A Case Study Using Rollins College Archives, Hannah Holman

Computer Science

The Rollins College Archives are a treasure trove of historic resources relating to the college’s history, and they are often underutilized or overlooked by both the student body and the surrounding community. In particular, historic resources are all too often excluded from work in computer science and related fields. This project aims to bridge that gap by bringing the two areas together. To that end, the goal of this project is to merge past and present by blending historic photos with input of a present day scene in order to reveal changes and juxtapositions of the same scene across eras. …

Understanding Natural Keyboard Typing Using Convolutional Neural Networks On Mobile Sensor Data, Travis Siems

Computer Science and Engineering Theses and Dissertations

Mobile phones and other devices with embedded sensors are becoming increasingly ubiquitous. Audio and motion sensor data may be able to detect information that we did not think possible. Some researchers have created models that can predict computer keyboard typing from a nearby mobile device; however, certain limitations to their experiment setup and methods compelled us to be skeptical of the models’ realistic prediction capability. We investigate the possibility of understanding natural keyboard typing from mobile phones by performing a well-designed data collection experiment that encourages natural typing and interactions. This data collection helps capture realistic vulnerabilities of the security …

Multi-Scale And Multi-Modal Streaming Data Aggregation And Processing For Decision Support During Natural Disasters, Shruti Kar

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With the surge in digital information systems, there is a data deluge from various sources that can be analyzed and integrated to produce relevant, reliable and actionable information, for better decision making. We employ multi-modal data (i.e., unstructured text, gazetteers, and imagery) for an aggregate level analysis and location-centric demand/request matching in the context of disaster relief. After classifying the Need expressed in a tweet (the WHAT), we leverage OpenStreetMap to geolocate that Need on a computationally accessible map of the local terrain (the WHERE) populated with location features such as hospitals and housing. Further, our novel use of flood …

Developing An Affect-Aware Rear-Projected Robotic Agent, Ali Mollahosseini

Electronic Theses and Dissertations

Social (or Sociable) robots are designed to interact with people in a natural and interpersonal manner. They are becoming an integrated part of our daily lives and have achieved positive outcomes in several applications such as education, health care, quality of life, entertainment, etc. Despite significant progress towards the development of realistic social robotic agents, a number of problems remain to be solved. First, current social robots either lack enough ability to have deep social interaction with human, or they are very expensive to build and maintain. Second, current social robots have yet to reach the full emotional and social …

Algorithmic Music Generation For Pedagogy Of Sight Reading, Ryan Stephen Davis

Electronic Theses and Dissertations

Autodeus is the name of the program that has been developed and was designed to aid guitar students in the attainment and betterment of musical notation sight reading skills. Its primary goal is to provide a very flexible tool that has the ability to generate virtually endless types of sight reading exercises at many various skill levels.

A complimentary 2 year-long comprehensive guitar sight-reading course syllabus can be implemented via Autodeus as it is capable of generating all the necessary exercises. It is able to generate these exercises quickly and efficiently through the use of a back tracking algorithm that …

Rnn-Based Generation Of Polyphonic Music And Jazz Improvisation, Andrew Hannum

Electronic Theses and Dissertations

This paper presents techniques developed for algorithmic composition of both polyphonic music, and of simulated jazz improvisation, using multiple novel data sources and the character-based recurrent neural network architecture char-rnn. In addition, techniques and tooling are presented aimed at using the results of the algorithmic composition to create exercises for musical pedagogy.

Motivations, Team Dynamics, Development Practices And How They Impact The Success Of Open Source Software: A Study Of Projects Of Code For America Brigades, Le Chang

Electronic Theses and Dissertations

Open data movement has nurtured the growth of civic open source software (OSS) in the recent decade. This emerging phenomenon has demonstrated a way that a community can collectively utilize technology to solve its problems.

This study is based on software projects in brigades of Code for America, which is a network of organizations that group volunteers to create digital solutions to community problems. In this study, we analyze the software engineering practices of current civic open source software development, participants' motivations and perceptions of the projects, and provide insights on the antecedents of success of the application development.

A …

The Software Development Life Cycle And Its Application, Gillian Lemke

Senior Honors Theses and Projects

The Software Development Life Cycle (SLDC) is a concept that is incredibly important to have a deep understanding of as a software engineer. With this project, my goal was to learn the complexities of each step conceptually and apply my skills to an actual application. The SDLC includes the following phases: planning and requirement analysis, design and development, implementation, testing, integration, and maintenance. In order to apply these concepts, I created a web application for users to schedule messages to be sent at a future time and date. The API is written in Ruby on Rails and the front end …