Computer Sciences Commons^™

Proposing An Optimized Algorithm For Consolidating Electric-Powered Shared Scooters Into Hubs For Efficiently Managing Their Charging And Maintenance Operations, Ojen Goshtasb

Master's Projects

The use of vehicles other than ones containing combustion engines have been adopted significantly over the past few years and the direction it’s taking seems to be the future of urban transportation. The hottest vehicle of choice currently is the electric scooter. They are small and portable, fast, and less costly compared to getting in a cab from Lyft or Uber to get around town. The goal of this paper is to make a proposal to drive the creation of a safe, efficient system for these scooters’ management. This must be beneficial to all parties involved; the rider, non-riders, and …

Management And Security Of Iot Systems Using Microservices, Tharun Theja Kammara

Master's Projects

Devices that assist the user with some task or help them to make an informed decision are called smart devices. A network of such devices connected to internet are collectively called as Internet of Things (IoT). The applications of IoT are expanding exponentially and are becoming a part of our day to day lives. The rise of IoT led to new security and management issues. In this project, we propose a solution for some major problems faced by the IoT devices, including the problem of complexity due to heterogeneous platforms and the lack of IoT device monitoring for security and …

Table Of Contents

Journal of Digital Forensics, Security and Law

No abstract provided.

Virtual Robot Climbing Using Reinforcement Learning, Ujjawal Garg

Master's Projects

Reinforcement Learning (RL) is a field of Artificial Intelligence that has gained a lot of attention in recent years. In this project, RL research was used to design and train an agent to climb and navigate through an environment with slopes. We compared and evaluated the performance of two state-of-the-art reinforcement learning algorithms for locomotion related tasks, Deep Deterministic Policy Gradients (DDPG) and Trust Region Policy Optimisation (TRPO). We observed that, on an average, training with TRPO was three times faster than DDPG, and also much more stable for the locomotion control tasks that we experimented. We conducted experiments and …

Deep Visual Recommendation System, Raksha Sunil

Master's Projects

Recommendation system is a filtering system that predicts ratings or preferences that a user might have. Recommendation system is an evolved form of our trivial information retrieval systems. In this paper, we present a technique to solve new item cold start problem. New item cold start problem occurs when a new item is added to a shopping website like Amazon.com. There is no metadata for this item, no ratings and no reviews because it’s a new item in the system. Absence of data results in no recommendation or bad recommendations. Our approach to solve new item cold start problem requires …

Pasnet: Pathway-Associated Sparse Deepneural Network For Prognosis Prediction From High-Throughput Data, Jie Hao, Youngsoon Kim, Tae-Kyung Kim, Mingon Kang

Faculty Articles

Background: Predicting prognosis in patients from large-scale genomic data is a fundamentally challenging problem in genomic medicine. However, the prognosis still remains poor in many diseases. The poor prognosis maybe caused by high complexity of biological systems, where multiple biological components and their hierarchical relationships are involved. Moreover, it is challenging to develop robust computational solutions with high-dimension, low-sample size data. Results: In this study, we propose a Pathway-Associated Sparse Deep Neural Network (PASNet) that not only predicts patients’ prognoses but also describes complex biological processes regarding biological pathways for prognosis. PASNet models a multilayered, hierarchical biological system of genes …

Pantry: A Macro Library For Python, Derek Pang

Master's Projects

Python lacks a simple way to create custom syntax and constructs that goes outside of its own syntax rules. A paradigm that allows for these possibilities to exist within languages is macros. Macros allow for a shorter set of syntax to expand into a longer set of instructions at compile-time. This gives the capability to evolve the language to fit personal needs.

Pantry, implements a hygienic text-substitution macro system for Python. Pantry achieves this through the introduction of an additional preparsing step that utilizes parsing and lexing of the source code. Pantry proposes a way to simply declare a pattern …

Self-Stabilizing Token Distribution With Constant-Space For Trees, Yuichi Sudo, Ajoy K. Datta, Lawrence L. Larmore, Toshimitsu Masuzawa

Computer Science Faculty Research

Self-stabilizing and silent distributed algorithms for token distribution in rooted tree networks are given. Initially, each process of a graph holds at most l tokens. Our goal is to distribute the tokens in the whole network so that every process holds exactly k tokens. In the initial configuration, the total number of tokens in the network may not be equal to nk where n is the number of processes in the network. The root process is given the ability to create a new token or remove a token from the network. We aim to minimize the convergence time, the number …

Loosely-Stabilizing Leader Election With Polylogarithmic Convergence Time, Yuichi Sudo, Fukuhito Ooshita, Hirotsugu Kukugawa, Toshimitsu Masuzawa, Ajoy K. Datta, Lawrence L. Larmore

Computer Science Faculty Research

A loosely-stabilizing leader election protocol with polylogarithmic convergence time in the population protocol model is presented in this paper. In the population protocol model, which is a common abstract model of mobile sensor networks, it is known to be impossible to design a self-stabilizing leader election protocol. Thus, in our prior work, we introduced the concept of loose-stabilization, which is weaker than self-stabilization but has similar advantage as self-stabilization in practice. Following this work, several loosely-stabilizing leader election protocols are presented. The loosely-stabilizing leader election guarantees that, starting from an arbitrary configuration, the system reaches a safe configuration with a …

A Snowball's Chance: Debt Snowball Vs. Debt Avalanche, Evan Mcallister

Senior Honors Projects, 2010-2019

Traditional mathematical analysis states that the most efficient way to pay off interest-bearing consumer debt is to pay the individual debts in order from largest to smallest interest rate. In doing this, the debtor will eliminate the largest sources of interest first, thus shortening the overall time-to-pay. This method is known as the “Debt Avalanche.” The “Debt Snowball” method, popularized in large part by investor-author David Ramsey, recommends that consumers pay debts in order from smallest to largest, regardless of interest rate. In this paper, I conduct an empirical analysis of the Federal Reserve’s Survey of Consumer Finance (SCF), calculating …

The Evolution Of Computational Propaganda: Trends, Threats, And Implications Now And In The Future, Holly Schnader

Senior Honors Projects, 2010-2019

Computational propaganda involves the use of selected narratives, social networks, and complex algorithms in order to develop and conduct influence operations (Woolley and Howard, 2017). In recent years the use of computational propaganda as an arm of cyberwarfare has increased in frequency. I aim to explore this topic to further understand the underlying forces behind the implementation of this tactic and then conduct a futures analysis to best determine how this topic will change over time. Additionally, I hope to gain insights on the implications of the current and potential future trends that computational propaganda has.

My preliminary assessment shows …

Efficient And Practical Composition Of Lock-Free Data Structures, Neha Bajracharya

UNLV Theses, Dissertations, Professional Papers, and Capstones

A concurrent data object is lock-free if it guarantees that at least one, among all concurrent operations, finishes after a finite number of steps. In other words, a lock free technique guarantees that some thread always makes progress. Lock-free data objects offer several advantages over their blocking counterparts, such as being immune to deadlocks and priority inversion, and typically provide high scalability and performance, especially in shared memory multiprocessor architectures.

Composition of data structures is a powerful approach to combine simple data structures to create more complex ones. It works as a building block for many advanced useful data structures. …

Combinatorial Ant Optimization And The Flowshop Problem, Tasmin Chowdhury

UNLV Theses, Dissertations, Professional Papers, and Capstones

Researchers have developed efficient techniques, meta-heuristics to solve many Combinatorial Optimization (CO) problems, e.g., Flow shop Scheduling Problem, Travelling Salesman Problem (TSP) since the early 60s of the last century. Ant Colony Optimization (ACO) and its variants were introduced by Dorigo et al. [DBS06] in the early 1990s which is a technique to solve CO problems. In this thesis, we used the ACO technique to find solutions to the classic Flow shop Scheduling Problem and proposed a novel method for solution improvement. Our solution is composed of two phases; in the first phase, we solved TSP using ACO technique which …

Uas-Based Object Tracking Via Deep Learning, Marc Dinh

UNLV Theses, Dissertations, Professional Papers, and Capstones

Tracking is the task of identifying an object of interest and detect its position over time, and has numerous applications like surveillance, security and traffic control. In present times, unmanned aerial vehicles (UAV) have been more and more common which provides us with a new and less explored domain, with an ideal vantage point for surveillance and monitoring applications.. Aerial tracking is a particularly challenging task as it introduces new environmental variables such as rapid motion in 3D space. We propose a new deep learned tracker architecture catered to aerial tracking.

First, a study of six state-of-the-art deep learned trackers …

Learning About Large Scale Image Search: Lessons From Global Scale Hotel Recognition To Fight Sex Trafficking, Abby Stylianou

McKelvey School of Engineering Graduate Student Theses & Dissertations

Hotel recognition is a sub-domain of scene recognition that involves determining what hotel is seen in a photograph taken in a hotel. The hotel recognition task is a challenging computer vision task due to the properties of hotel rooms, including low visual similarity between rooms in the same hotel and high visual similarity between rooms in different hotels, particularly those from the same chain. Building accurate approaches for hotel recognition is important to investigations of human trafficking. Images of human trafficking victims are often shared by traffickers among criminal networks and posted in online advertisements. These images are often taken …

Scheduling Two Machines With Dissimilar Costs, Madhurupa Moitra

UNLV Theses, Dissertations, Professional Papers, and Capstones

We consider two devices, which has states ON and OFF. In the ON state, the devices use their full power whereas in the OFF state the devices consume no energy but a constant cost is associated with switching back to ON. Such two devices are configured with different run and power-up costs on which a sequence of jobs must be processed. The object is to minimize the cost. Such systems are widely used to conserve energy, for example, to speed scale CPUs, to control data centers, or to manage renewable energy.

The problems are studied in the framework of online …

Application Of Machine Learning Techniques In Credit Card Fraud Detection, Ronish Shakya

UNLV Theses, Dissertations, Professional Papers, and Capstones

Credit card fraud is an ever-growing problem in today’s financial market. There has been a rapid increase in the rate of fraudulent activities in recent years causing a substantial financial loss to many organizations, companies, and government agencies. The numbers are expected to increase in the future, because of which, many researchers in this field have focused on detecting fraudulent behaviors early using advanced machine learning techniques. However, the credit card fraud detection is not a straightforward task mainly because of two reasons: (i) the fraudulent behaviors usually differ for each attempt and (ii) the dataset is highly imbalanced, i.e., …

Computational Explorations Of Information And Mechanism Design In Markets, Zhuoshu Li

McKelvey School of Engineering Graduate Student Theses & Dissertations

Markets or platforms assemble multiple selfishly-motivated and strategic agents. The outcomes of such agent interactions depend heavily on the rules, regulations, and norms of the platform, as well as the information available to agents. This thesis investigates the design and analysis of mechanisms and information structures through the ``computational lens'' in both static and dynamic settings. It both addresses the outcome of single platforms and fills a gap in the study of the dynamics of multiple platform interactions.

In static market settings, we are particularly interested in the role of information, because mechanisms are harder to change than the information …

Nanopower Analog Frontends For Cyber-Physical Systems, Kenji Aono

McKelvey School of Engineering Graduate Student Theses & Dissertations

In a world that is increasingly dominated by advances made in digital systems, this work will explore the exploiting of naturally occurring physical phenomena to pave the way towards a self-powered sensor for Cyber-Physical Systems (CPS). In general, a sensor frontend can be broken up into a handful of basic stages: transduction, filtering, energy conversion, measurement, and interfacing. One analog artifact that was investigated for filtering was the physical phenomenon of hysteresis induced in current-mode biquads driven near or at their saturation limit. Known as jump resonance, this analog construct facilitates a higher quality factor to be brought about without …

Facial Expression Recognition By De-Expression Residue Learning, Huiyuan Yang, Umur Ciftci, Lijun Yin

Computer Science Faculty Research & Creative Works

A facial expression is a combination of an expressive component and a neutral component of a person. In this paper, we propose to recognize facial expressions by extracting information of the expressive component through a de-expression learning procedure, called De-expression Residue Learning (DeRL). First, a generative model is trained by cGAN. This model generates the corresponding neutral face image for any input face image. We call this procedure de-expression because the expressive information is filtered out by the generative model; however, the expressive information is still recorded in the intermediate layers. Given the neutral face image, unlike previous works using …

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 …

Variations On A Theme: Using Amino Acid Sequences To Generate Music, Aaron Kosmatin

Master's Projects

In this project, we explore using a musical space to represent the properties of amino acids. We consider previous mappings and explore the limitations of these mappings. In this exploration, we will propose a new method of mapping into musical spaces that extends the properties that can be represented. For this work, we will use amino acid sequences as our example mapping. The amino acid properties we will use include mass, charge, structure, and hydrophobicity. Finally, we will show how the different musical properties can be compared for similarity.

Intra-Exchange Cryptocurrency Arbitrage Bot, Eric Han

Master's Projects

Cryptocurrencies are defined as a digital currency in which encryption techniques are utilized to regulate generation of units of currency and verify the transfer of funds, independent of a central governing body such as a bank. Due to the large number of cryptocurrencies currently available, there inherently exists many price discrepancies due to market inefficiencies. Market inefficiencies occur when the price of assets do not reflect their true value. In fact, these types of pricing discrepancies exist in other financial markets, including fiat currency exchanges and stock exchanges. However, these discrepancies are more significant in the cryptocurrency domain due to …

Gradubique: An Academic Transcript Database Using Blockchain Architecture, Thinh Nguyen

Master's Projects

Blockchain has been widely adopted in the last few years even though it is in its infancy. The first well-known application built on blockchain technology was Bitcoin, which is a decentralized and distributed ledger to record crypto-currency transactions. All of the transactions in Bitcoin are anonymously transferred and validated by participants in the network. Bitcoin protocol and its operations are so reliable that technologists have been inspired to enhance blockchain technologies and deploy it outside of the crypto-currency world. The demand for private and non-crypto-currency solutions have surged among consortiums because of the security and fault tolerant features of blockchain. …

Feasibility Of Peltier Chips As Thermoelectric Generators On Heatsinks, Matthew Choquette, Dillon Ranstrom

Augsburg Honors Review

As the demand of computer processing grows, the burden placed on CPUs will increase as well. Computing systems produce heat, which is attracted to a metal heatsink where it is dissipated out of the system by a fan. Liquid cooling can be more effective, but is more expensive and increases the risk of damaging leaks. Peltier chips, electronic components which transfer heat into electricity, can be used in an effort to reclaim and reuse some of this waste heat. This experiment tested twelve heatsinks of various designs to maximize the effect of the Peltier chip. Variations in designs of the …

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 …

2018 December 11 - Computation And Research In Data Science (Cards) Minutes, Computation And Research In Data Science, East Tennessee State University

Computation and Research in Data Science (CaRDS) Board Meeting Minutes

No abstract provided.

Evaluating An Educational Cybersecurity Playable Case Study, Tanner West Johnson

Theses and Dissertations

The realities of cyberattacks have become more and more prevalent in the world today. Due to the growing number of these attacks, the need for highly trained individuals has also increased. Because of a shortage of qualified candidates for these positions, there is an increasing need for cybersecurity education within high schools and universities. In this thesis, I discuss the development and evaluation of Cybermatics, an educational simulation, or playable case study, designed to help students learn and develop skills within the cybersecurity discipline.

This playable case study was designed to allow students to gain an understanding of the field …

Open Source Foundations For Spatial Decision Support Systems, Jochen Albrecht

Publications and Research

Spatial Decision Support Systems (SDSS) were a hot topic in the 1990s, when researchers tried to imbue GIS with additional decision support features. Successful practical developments such as HAZUS or CommunityViz have since been built, based on commercial desktop software and without much heed for theory other than what underlies their process models. Others, like UrbanSim, have been completely overhauled twice but without much external scrutiny. Both the practical and the theoretical foundations of decision support systems have developed considerably over the past 20 years. This article presents an overview of these developments and then looks at what corresponding tools …

Designing Cybersecurity Competitions In The Cloud: A Framework And Feasibility Study, Chandler Ryan Newby

Theses and Dissertations

Cybersecurity is an ever-expanding field. In order to stay current, training, development, and constant learning are necessary. One of these training methods has historically been competitions. Cybersecurity competitions provide a method for competitors to experience firsthand cybersecurity concepts and situations. These experiences can help build interest in, and improve skills in, cybersecurity.

While there are diverse types of cybersecurity competitions, most are run with on-premise hardware, often centralized at a specific location, and are usually limited in scope by available hardware. This research focuses on the possibility of running cybersecurity competitions, specifically CCDC style competitions, in a public cloud environment. …