Computer Sciences Commons^™

Hierarchical Representation Learning With Connectionist Models, De Wang

Computer Science and Engineering Dissertations - Archive

To unleash the power of big data, efficient algorithms which are scalable to millions of data are desired. Deep learning is one area that benefits from big data enormously. Deep learning uses neural networks to mimic human brains, this approach is termed connectionist in AI community. In this dissertation, we propose several novel learning strategies to improve the performance of connectionist models. Evaluation of a large neural network during inference phase requires a lot of GPU memory and computation, which will degrade user experience due to response latency. Model distillation is one way to distill the knowledge contained in one …

Efficient And Expressive Keyword Search Over Encrypted Data In The Cloud, Hui Cui, Zhiguo Wan, Deng, Robert H., Guilin Wang, Yingjiu Li

Research Collection School Of Computing and Information Systems

Searchable encryption allows a cloud server to conduct keyword search over encrypted data on behalf of the data users without learning the underlying plaintexts. However, most existing searchable encryption schemes only support single or conjunctive keyword search, while a few other schemes that are able to perform expressive keyword search are computationally inefficient since they are built from bilinear pairings over the composite-order groups. In this paper, we propose an expressive public-key searchable encryption scheme in the prime-order groups, which allows keyword search policies (i.e., predicates, access structures) to be expressed in conjunctive, disjunctive or any monotonic Boolean formulas and …

Geometric Algorithms For Intervals And Related Problems, Shimin Li

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

In this dissertation, we study several problems related to intervals and develop efficient algorithms for them. Interval problems have many applications in reality because many objects, values, and ranges are intervals in nature, such as time intervals, distances, line segments, probabilities, etc. Problems on intervals are gaining attention also because intervals are among the most basic geometric objects, and for the same reason, computational geometry techniques find useful for attacking these problems. Specifically, the problems we study in this dissertation includes the following: balanced splitting on weighted intervals, minimizing the movements of spreading points, dispersing points on intervals, multiple barrier …

A Multiple Radar Approach For Automatic Target Recognition Of Aircraft Using Inverse Synthetic Aperture Radar, Carlos Pena-Caballero, Elifaleth Cantu, Jesus Rodriguez, Adolfo Gonzales, Osvaldo Castellanos, Angel Cantu, Megan K. Strait, Jae Son, Dong-Chul Kim

Computer Science Faculty Publications

Following the recent advancements in radar technologies, research on automatic target recognition using Inverse Synthetic Aperture Radar (ISAR) has correspondingly seen more attention and activity. ISAR automatic target recognition researchers aim to fully automate recognition and classification of military vehicles, but because radar images often do not present a clear image of what they detect, it is considered a challenging process to do this. Here we present a novel approach to fully automate a system with Convolutional Neural Networks (CNNs) that results in better target recognition and requires less training time. Specifically, we developed a simulator to generate images with …

Improving The Efficacy Of Context-Aware Applications, Jon C. Hammer

Graduate Theses and Dissertations

In this dissertation, we explore methods for enhancing the context-awareness capabilities of modern computers, including mobile devices, tablets, wearables, and traditional computers. Advancements include proposed methods for fusing information from multiple logical sensors, localizing nearby objects using depth sensors, and building models to better understand the content of 2D images.

First, we propose a system called Unagi, designed to incorporate multiple logical sensors into a single framework that allows context-aware application developers to easily test new ideas and create novel experiences. Unagi is responsible for collecting data, extracting features, and building personalized models for each individual user. We demonstrate the …

Development Of A ‘Smart’ Resistance Exercise Band To Assess Strength, Emily V. Wechsler, John A. Batsis, David F. Kotz, Ryan J. Halter

Wetterhahn Science Symposium Posters 2018

No abstract provided.

Assessing The Quality And Stability Of Recommender Systems, David Shriver

School of Computing: Dissertations, Theses, and Student Research

Recommender systems help users to find products they may like when lacking personal experience or facing an overwhelmingly large set of items. However, assessing the quality and stability of recommender systems can present challenges for developers. First, traditional accuracy metrics, such as precision and recall, for validating the quality of recommendations, offer only a coarse, one-dimensional view of the system performance. Second, assessing the stability of a recommender systems requires generating new data and retraining a system, which is expensive. In this work, we present two new approaches for assessing the quality and stability of recommender systems to address these …

Performance Evaluation Of V-Enodeb Using Virtualized Radio Resource Management, Sai Keerti Teja Boddepalli

School of Computing: Dissertations, Theses, and Student Research

With the demand upsurge for high bandwidth services, continuous increase in the number of cellular subscriptions, adoption of Internet of Things (IoT), and marked growth in Machine-to-Machine (M2M) traffic, there is great stress exerted on cellular network infrastructure. The present wireline and wireless networking technologies are rigid in nature and heavily hardware-dependent, as a result of which the process of infrastructure upgrade to keep up with future demand is cumbersome and expensive.

Software-defined networks (SDN) hold the promise to decrease network rigidity by providing central control and flow abstraction, which in current network setups are hardware-based. The embrace of SDN …

Computer Science Minor Marketing Plan, Shannon Oryniak

Senior Honors Projects

Computer Science is one of the fastest growing industries with the highest job demand. It has allowed us to do things we’d never dream capable, and bring to life creations and projects in every field.

While it may not seem like it, computer science involves a great deal of creativity. There are thousands of different ways to code a program and billions of different uses for them. While not everyone may want to code programs for a living, I do believe having an understanding of computer science can be beneficial for any major or any career. Entrepreneurs can learn to …

Improving Asynchronous Advantage Actor Critic With A More Intelligent Exploration Strategy, James B. Holliday

Graduate Theses and Dissertations

We propose a simple and efficient modification to the Asynchronous Advantage Actor Critic (A3C)

algorithm that improves training. In 2016 Google’s DeepMind set a new standard for state-of-theart

reinforcement learning performance with the introduction of the A3C algorithm. The goal of

this research is to show that A3C can be improved by the use of a new novel exploration strategy we

call “Follow then Forage Exploration” (FFE). FFE forces the agents to follow the best known path

at the beginning of a training episode and then later in the episode the agent is forced to “forage”

and explores randomly. In …

A Proposed Approach To Hybrid Software-Hardware Application Design For Enhanced Application Performance, Alex Shipman

Graduate Theses and Dissertations

One important aspect of many commercial computer systems is their performance; therefore, system designers seek to improve the performance next-generation systems with respect to previous generations. This could mean improved computational performance, reduced power consumption leading to better battery life in mobile devices, smaller form factors, or improvements in many areas. In terms of increased system speed and computation performance, processor manufacturers have been able to increase the clock frequency of processors up to a point, but now it is more common to seek performance gains through increased parallelism (such as a processor having more processor cores on a single …

A Home Security System Based On Smartphone Sensors, Michael Mahler

Graduate Theses and Dissertations

Several new smartphones are released every year. Many people upgrade to new phones, and their old phones are not put to any further use. In this paper, we explore the feasibility of using such retired smartphones and their on-board sensors to build a home security system. We observe that door-related events such as opening and closing have unique vibration signatures when compared to many types of environmental vibrational noise. These events can be captured by the accelerometer of a smartphone when the phone is mounted on a wall near a door. The rotation of a door can also be captured …

Computer Vision Evidence Supporting Craniometric Alignment Of Rat Brain Atlases To Streamline Expert-Guided, First-Order Migration Of Hypothalamic Spatial Datasets Related To Behavioral Control, Khan, Jose Perez, Claire Wells, Olac Fuentes

Departmental Papers (Biology)

The rat has arguably the most widely studied brain among all animals, with numerous reference atlases for rat brain having been published since 1946. For example, many neuroscientists have used the atlases of Paxinos and Watson (PW, first published in 1982) or Swanson (S, first published in 1992) as guides to probe or map specific rat brain structures and their connections. Despite nearly three decades of contemporaneous publication, no independent attempt has been made to establish a basic framework that allows data mapped in PW to be placed in register with S, or vice versa. …

Blockchain: The Backbone Of Supply Chains In Omni-Channels, Yejin Lee

Renée Crown University Honors Thesis Projects - All

From the financial industry to the healthcare industry, many use cases for blockchain have been explored and adopted. However, unlike most industries, the retail industry has yet to fully explore blockchain’s capabilities, for the industry’s priority is in improving its practices first. One of its practices in the works is omni-channels, which face struggles of its own, that oftentimes result from supply chain inefficiencies. This paper will utilize already explored blockchain potentials as a guide to explore and introduce new potentials in blockchain for supply chain in omni-channels.

Cslc Tutoring Portal, Brian Hodges

Theses/Capstones/Creative Projects

A web portal designed for the Computer Science Learning Center to track students requesting help

An Industry-Based Study On The Efficiency Benefits Of Utilising Public Cloud Infrastructure And Infrastructure As Code Tools In The It Environment Creation Process, Shane Callanan

Masters

The traditional approaches to IT infrastructure management typically involve the procuring, housing and running of company-owned and maintained physical servers. In recent years, alternative solutions to IT infrastructure management based on public cloud technologies have emerged. Infrastructure as a Service (IaaS), also known as public cloud infrastructure, allows for the on-demand provisioning of IT infrastructure resources via the Internet. Cloud Service Providers (CSP) such as Amazon Web Services (AWS) offer integration of their cloud-based infrastructure with Infrastructure as Code (IaC) tools. These tools allow for the entire configuration of public cloud based infrastructure to be scripted out and defined as …

Customizing Indoor Wireless Coverage Via 3d-Fabricated Reflectors, Xi Xiong

Dartmouth College Master’s Theses

Judicious control of indoor wireless coverage is crucial in built environments. It enhances signal reception, reduces harmful interference, and raises the barrier for malicious attackers. Existing methods are either costly, vulnerable to attacks, or hard to configure. We present a low-cost, secure, and easy-to-configure approach that uses an easily-accessible, 3D-fabricated reflector to customize wireless coverage. With input on coarse-grained environment setting and preferred coverage (e.g., areas with signals to be strengthened or weakened), the system computes an optimized reflector shape tailored to the given environment. The user simply 3D prints the reflector and places it around a Wi-Fi access point …

Parameterizing And Aggregating Activation Functions In Deep Neural Networks, Luke Benjamin Godfrey

Graduate Theses and Dissertations

The nonlinear activation functions applied by each neuron in a neural network are essential for making neural networks powerful representational models. If these are omitted, even deep neural networks reduce to simple linear regression due to the fact that a linear combination of linear combinations is still a linear combination. In much of the existing literature on neural networks, just one or two activation functions are selected for the entire network, even though the use of heterogenous activation functions has been shown to produce superior results in some cases. Even less often employed are activation functions that can adapt their …

File Fragment Classification Using Neural Networks With Lossless Representations, Luke Hiester

Undergraduate Honors Theses

This study explores the use of neural networks as universal models for classifying file fragments. This approach differs from previous work in its lossless feature representation, with fragments’ bits as direct input, and its use of feedforward, recurrent, and convolutional networks as classifiers, whereas previous work has only tested feedforward networks. Due to the study’s exploratory nature, the models were not directly evaluated in a practical setting; rather, easily reproducible experiments were performed to attempt to answer the initial question of whether this approach is worthwhile to pursue further, especially due to its high computational cost. The experiments tested classification …

Ai: Augmentation, More So Than Automation, Steven M. Miller

Asian Management Insights

The take-up of Artificial Intelligence (AI)-enabled systems in organisations is expanding rapidly. Integrating AI-enabled automation with people into workplace processes and societal systems is a complex and evolving challenge. The articles takes a managerial perspective on how firms can effectively deploy human minds and intelligent machines in the workplace.

Self-Reconfiguration Planning In Modular Reconfigurable Robots, Keaton Griffith

Honors Theses

MSRs are highly versatile robots that work together to form into different configurations. However, to take advantage of this ability to transform, the MSR must utilize an SRP algorithm to determine what actions to perform to shape itself to reach its goal configuration. An SRP algorithm can be boiled down to a search method through an unexplored graph which we approach with four basic search algorithms to see which algorithm is best when designing an SRP algorithm. To do this we create a general MSR model known as stickbots and use different search algorithms on a variety of SRP problems …

Proverbial Machine Translation: Translating Proverbs Between Spanish And English Using Phrased Based Statistical Machine Translation With The Grammatical Category Based Approach, Teneala Spencer

Honors Theses

The focus of the research presented in the paper is translating the non-literal interpretation of proverbs from Spanish to English without changing their intended meaning. Proverbs have limited variation in comparison to slang, poetry, and metaphors which tend to differ significantly within the context that they are used. Although there are many other approaches for machine translation (MT), the one most suitable for the research project is Phrased Based Statistical Machine translation used in conjunction with the Grammatical Category- Based approach.

Consensus Ensemble Approaches Improve De Novo Transcriptome Assemblies, Adam Voshall

School of Computing: Dissertations, Theses, and Student Research

Accurate and comprehensive transcriptome assemblies lay the foundation for a range of analyses, such as differential gene expression analysis, metabolic pathway reconstruction, novel gene discovery, or metabolic flux analysis. With the arrival of next-generation sequencing technologies it has become possible to acquire the whole transcriptome data rapidly even from non-model organisms. However, the problem of accurately assembling the transcriptome for any given sample remains extremely challenging, especially in species with a high prevalence of recent gene or genome duplications, those with alternative splicing of transcripts, or those whose genomes are not well studied. This thesis provides a detailed overview of …

Effectively Enforcing Minimality During Backtrack Search, Daniel J. Geschwender

School of Computing: Dissertations, Theses, and Student Research

Constraint Processing is an expressive and powerful framework for modeling and solving combinatorial decision problems. Enforcing consistency during backtrack search is an effective technique for reducing thrashing in a large search tree. The higher the level of the consistency enforced, the stronger the pruning of inconsistent subtrees. Recently, high-level consistencies (HLC) were shown to be instrumental for solving difficult instances. In particular, minimality, which is guaranteed to prune all inconsistent branches, is advantageous even when enforced locally. In this thesis, we study two algorithms for computing minimality and propose three new mechanisms that significantly improve performance. Then, we integrate the …

Application Of Cosine Similarity In Bioinformatics, Srikanth Maturu

School of Computing: Dissertations, Theses, and Student Research

Finding similar sequences to an input query sequence (DNA or proteins) from a sequence data set is an important problem in bioinformatics. It provides researchers an intuition of what could be related or how the search space can be reduced for further tasks. An exact brute-force nearest-neighbor algorithm used for this task has complexity O(m * n) where n is the database size and m is the query size. Such an algorithm faces time-complexity issues as the database and query sizes increase. Furthermore, the use of alignment-based similarity measures such as minimum edit distance adds an additional complexity to the …

Region Based Gene Expression Via Reanalysis Of Publicly Available Microarray Data Sets., Ernur Saka

Electronic Theses and Dissertations

A DNA microarray is a high-throughput technology used to identify relative gene expression. One of the most widely used platforms is the Affymetrix® GeneChip® technology which detects gene expression levels based on probe sets composed of a set of twenty-five nucleotide probes designed to hybridize with specific gene targets. Given a particular Affymetrix® GeneChip® platform, the design of the probes is fixed. However, the method of analysis is dynamic in nature due to the ability to annotate and group probes into uniquely defined groupings. This is particularly important since publicly available repositories of microarray datasets, such as ArrayExpress and NCBI’s …

Investigation Of Alternatives For Migrating The One-Stop-Shop (Oss) Application To A Single, Web-Based Offering That Is Conducive For Both Desktop And Mobile Use., Sahiti Katragadda

All Graduate Plan B and other Reports, Spring 1920 to Spring 2023

The One-Stop-Shop (OSS) application provides real-time data which is helpful for travelers in the Western United States in planning their travel. Included is traditional information (routing, imagery, weather), as well as points of interest and other route-specific information (elevations, rest areas, etc.). The system displays real-time data streams in a web-based application and in a separate mobile web application, which are presented to end users in a user-friendly format.

OSS web application and OSS mobile web application features have been examined and the best design features for the mobile application have been identified. Along with that, additional design features are …

The Kumaraswamy Marshall-Olkin Log-Logistic Distribution With Application, Selen Cakmakyapan, Gamze Ozel, Yehia Mousa Hussein El Gebaly, Gholamhossein G. Hamedani

Mathematics, Statistics and Computer Science Faculty Research and Publications

In this paper, we define and study a new lifetime model called the Kumaraswamy Marshall-Olkin log-logistic distribution. The new model has the advantage of being capable of modeling various shapes of aging and failure criteria. The new model contains some well-known distributions as special cases such as the Marshall-Olkin log-logistic, log-logistic, lomax, Pareto type II and Burr XII distributions. Some of its mathematical properties including explicit expressions for the quantile and generating functions, ordinary moments, skewness, kurtosis are derived. The maximum likelihood estimators of the unknown parameters are obtained. The importance and flexibility of the new model is proved empirically …

Trade-Offs Between Monetary Gain And Risk Taking In Cybersecurity Behavior, X. Zhan, Fiona Fui-Hoon Nah, M. Cheng

Research Collection School Of Computing and Information Systems

Phishers and hackers exploit users’ susceptibility to deception by providing incentives. This research focuses on studying the risk-taking behavior of users in downloading software from the Internet. We proposed an experimental study to assess the degree of risks that people are willing to take for monetary gains when they download software from uncertified sources.

Applications Of Varying Leadership Structures For Software Engineering Teams, Elliot Sandfort

Honors Program: Senior Projects (Public)

This thesis explores the similarities and differences between applications of managing software engineering teams in Design Studio and the state of the practice. Information about the leadership structure of Design Studio teams was gathered over 3 semesters of Design Studio experiences with two companies: Hudl and TD Ameritrade. Information about leadership concepts in the state of the practice was gathered from experiences and observations with three different companies: Hudl, Garmin, and TD Ameritrade. From these experiences and observations, it can be concluded that the leadership structure of Design Studio is valuable as a student learning experience, and with proper consideration …