Digital Commons Network^™

External Support Structures In Fused Deposition Modeling 3d Printing, Adam Mystkowski

Undergraduate Honors Theses

3D Printing, sometimes also referred to as Additive Manufacturing, is a technology that has garnered a lot of attention in the past several years. While the technology has attracted a significant community of hobbyists, the benefits of the technology have also been recognized in manufacturing. While there are many different types of 3D Printing techniques, the most common type is Fused Deposition Modeling (FDM), mainly due to its relatively low cost compared to other types. However, the technique also present a significant limitation: it tends to struggle with models that have overhanging parts. When a layer is extruded by an …

Algorithmic Bias: Causes And Effects On Marginalized Communities, Katrina M. Baha

Undergraduate Honors Theses

Individuals from marginalized backgrounds face different healthcare outcomes due to algorithmic bias in the technological healthcare industry. Algorithmic biases, which are the biases that arise from the set of steps used to solve or analyze a problem, are evident when people from marginalized communities use healthcare technology. For example, many pulse oximeters, which are the medical devices used to measure oxygen saturation in the blood, are not able to accurately read people who have darker skin tones. Thus, people with darker skin tones are not able to receive proper health care due to their pulse oximetry data being inaccurate. This …

Procedural Level Generation For A Top-Down Roguelike Game, Kieran Ahn, Tyler Edmiston

Honors Thesis

In this file, I present a sequence of algorithms that handle procedural level generation for the game Fragment, a game designed for CMSI 4071 and CMSI 4071 in collaboration with students from the LMU Animation department. I use algorithms inspired by graph theory and implementing best practices to the best of my ability. The full level generation sequence is comprised of four algorithms: the terrain generation, boss room placement, player spawn point selection, and enemy population. The terrain generation algorithm takes advantage of tree traversal methods to create a connected graph of walkable tiles. The boss room placement algorithm randomly …

Algorithmic Bias Automation: The Effects Of Proxy On Machine-Learned Systems, Emely J. Galeano

Senior Projects Spring 2023

Senior Project submitted to The Division of Science, Mathematics and Computing of Bard College.

An Empirical Analysis Of Algorithms For Simple Stochastic Games, Cody William Klingler

Graduate Theses, Dissertations, and Problem Reports

This thesis presents the findings of a computational study on algorithms for Simple Stochastic Games (SSG). Simple Stochastic Games are a restriction of the Shapley stochastic model motivated by their applications in AI planning, logic synthesis, and theoretical computer science. This thesis seeks to empirically assess the performance of these algorithms to compensate for their lack of strong complexity results. Where applicable, we include both variations of algorithms where stable strategies are computed by a linear-programming and naive approach. These algorithms are evaluated on random inputs, in addition to specific difficult cases that were identified experimentally. We are interested in …

Comparative Analysis Of Fullstack Development Technologies: Frontend, Backend And Database, Qozeem Odeniran

Electronic Theses and Dissertations

Accessing websites with various devices has brought changes in the field of application development. The choice of cross-platform, reusable frameworks is very crucial in this era. This thesis embarks in the evaluation of front-end, back-end, and database technologies to address the status quo. Study-a explores front-end development, focusing on angular.js and react.js. Using these frameworks, comparative web applications were created and evaluated locally. Important insights were obtained through benchmark tests, lighthouse metrics, and architectural evaluations. React.js proves to be a performance leader in spite of the possible influence of a virtual machine, opening the door for additional research. Study b …

Wordmuse, John M. Nelson

Computer Science and Software Engineering

Wordmuse is an application that allows users to enter a song and a list of keywords to create a new song. Built on Spotify's API, this project showcases the fusion of music composition and artificial intelligence. This paper also discusses the motivation, design, and creation of Wordmuse.

Constructions And Analyses Of Efficient Symmetric-Key Primitives For Authentication And Encryption., Sebati Ghosh Dr.

Doctoral Theses

In symmetric key cryptography there are two fundamental objectives, viz. 1. confidentiality or secrecy of message from unexpected party and 2. authentication of message which includes authenticating the source of the message as well as integrity of the message against any unwanted modification. Let us first concentrate on confidentiality. In classical symmetric key cryptography two parties, say Alice and Bob, first secretly exchange a key-pair (e, d). Later, if Alice wishes to send a secret message m ∈ M to Bob, she computes c = Ee(m) and transmits c to Bob. Upon receiving c, Bob computes Dd(c) = m and …

Computing Well-Structured Subgraphs In Geometric Intersection Graphs., Satyabrata Jana Dr.

Doctoral Theses

For a set of geometric objects, the associative geometric intersection graph is the graph with a vertex for each object and an edge between two vertices if and only if the corresponding objects intersect. Geometric intersection graphs are very important due to their theoretical properties and applicability. Based on the different geometric objects, several types of geometric intersection graphs are defined. Given a graph G, an induced (either vertex or edge) subgraph H ⊆ G is said to be an well-structured subgraph if H satisfies certain properties among the vertices in H. This thesis studies some well-structured subgraphs finding problems …

Data Ethics: An Investigation Of Data, Algorithms, And Practice, Gabrialla S. Cockerell

Honors Projects

This paper encompasses an examination of defective data collection, algorithms, and practices that continue to be cycled through society under the illusion that all information is processed uniformly, and technological innovation consistently parallels societal betterment. However, vulnerable communities, typically the impoverished and racially discriminated, get ensnared in these harmful cycles due to their disadvantages. Their hindrances are reflected in their information due to the interconnectedness of data, such as race being highly correlated to wealth, education, and location. However, their information continues to be analyzed with the same measures as populations who are not significantly affected by racial bias. Not …

Data And Algorithmic Modeling Approaches To Count Data, Andraya Hack

Honors College Theses

Various techniques are used to create predictions based on count data. This type of data takes the form of a non-negative integers such as the number of claims an insurance policy holder may make. These predictions can allow people to prepare for likely outcomes. Thus, it is important to know how accurate the predictions are. Traditional statistical approaches for predicting count data include Poisson regression as well as negative binomial regression. Both methods also have a zero-inflated version that can be used when the data has an overabundance of zeros. Another procedure is to use computer algorithms, also known as …

Stubbornly Merging Discrete Vector Fields, Douglas W. Lenseth

Legacy Theses & Dissertations (2009 - 2024)

We address the basic question in discrete Morse theory of combining discrete gradientfields that are partially defined on subsets of the given complex. This is a well-posed question when the discrete gradient field V is generated using a fixed algorithm which has a local nature. One example is ProcessLowerStars, a widely used algorithm for computing persistent homology associated to a grayscale image in 2D or 3D. While the algorithm for V may be inherently local, being computed within stars of vertices and so embarrassingly parallelizable, in practical use it is natural to want to distribute the computation over patches Pi, …

I'M Special But A.I. Doesn't Get It, Huei Huei Laurel Teo

Dissertations and Theses Collection (Open Access)

A growing body of management research on artificial intelligence (AI) has consistently shown that people innately distrust decisions made by AI and find such decision processes simply less fair compared to decisions made by humans. My dissertation adopts a different perspective to propose that aside from fairness concerns, AI decision methods trigger perceptions in people that their individual uniqueness has not be adequately considered and this has negative consequences for their psychological or subjective well-being.

By combining theories of uniqueness, individuality, power, and well-being, I develop five studies to provide empirical evidence that aversion to AI-mediated decisions also operates through …

Efficient Handover Mechanisms For Heterogeneous Networks., Shankar Kumar Ghosh Dr.

Doctoral Theses

In this thesis, some analytical frameworks have been developed to analyze the effect of different system parameters on handover performances in heterogeneous network (HetNet) and based on such frameworks, some efficient handover algorithms have been proposed. The study starts with an analytical framework to investigate the effect of resource allocation mechanisms, upper layer mobility management protocols (MMPs) and handover decision metrics on user perceived throughput. This analysis reveals that among other factors, handover decision metric plays a crucial role in determining user perceived throughput in HetNet. Subsequently, we develop two handover decision metrics for ultra dense networks (UDN) and unlicensed …

Practical Considerations And Applications For Autonomous Robot Swarms, Rory Alan Hector

LSU Doctoral Dissertations

In recent years, the study of autonomous entities such as unmanned vehicles has begun to revolutionize both military and civilian devices. One important research focus of autonomous entities has been coordination problems for autonomous robot swarms. Traditionally, robot models are used for algorithms that account for the minimum specifications needed to operate the swarm. However, these theoretical models also gloss over important practical details. Some of these details, such as time, have been considered before (as epochs of execution). In this dissertation, we examine these details in the context of several problems and introduce new performance measures to capture practical …

Zero-Knowledge Proof, Deniability And Their Applications In Blockchain, E-Voting And Deniable Secret Handshake Protocols., Somnath Panja Dr.

Doctoral Theses

In this thesis, we propose a cryptographic technique for an authenticated, end-to-end verifiable and secret ballot election. Currently, almost all verifiable e-voting systems require trusted authorities to perform the tallying process except for the DRE-i and DRE-ip systems. We have shown a weaknesses in the DRE-ip system and proposed a solution. We have modified the DRE-ip system so that no adversary can create and post a valid ballot on the public bulletin board without detection. We provide security proofs to prove the security properties of the proposed scheme. We propose two methods to store these ballots using blockchain and cloud …

On Class Imbalanced Learning:Design Of Non-Parametricclassifiers, Performance Indices, And Deep Oversampling Strategies., Sankha Mullick Dr.

Doctoral Theses

The relevance of classification is almost endless in the everyday application of machine learning. However, the performance of a classifier is only limited to the fulfillment of the inherent assumptions it makes about the training examples. For example, to facilitate unbiased learning a classifier is expected to be trained with an equal number of labeled data instances from all of the classes. However, in a large number of practical applications such as anomaly detection, semantic segmentation, disease prediction, etc. it may not be possible to gather an equal number of diverse training points for all the classes. This results in …

Rankings Of Mma Fighters, Michael Schaefer

All Graduate Theses, Dissertations, and Other Capstone Projects

Ranking is an essential process that allows sporting authorities to determine the relative performance of athletes. While ranking is straightforward in some sports, it is more complicated in MMA (mixed martial arts), where competition is often fragmented. This paper describes the mathematics behind four existing ranking algorithms: Elo’s System, Massey’s Method, Colley’s Method, and Google’s PageRank, and shows how to adapt them to rank MMA fighters in the UFC (Ultimate Fighting Championship). We also provide a performance analysis for each ranking method.

A Validity-Based Approach For Feature Selection In Intrusion Detection Systems, Eljilani Hmouda

CCE Theses and Dissertations

Intrusion detection systems are tools that detect and remedy the presence of malicious activities. Intrusion detection systems face many challenges in terms of accurate analysis and evaluation. One such challenge is the involvement of many features during analysis, which leads to high data volume and ultimately excessive computational overhead. This research surrounds the development of a new intrusion detection system by employing an entropy-based measure called v-measure to select significant features and reduce dimensionality. After the development of the intrusion detection system, this feature reduction technique was tested on public datasets by applying machine learning classifiers such as Decision Tree, …

Secret Sharing And Its Variants, Matroids,Combinatorics., Shion Samadder Chaudhury Dr.

Doctoral Theses

The main focus of this thesis is secret sharing. Secret Sharing is a very basic and fundamental cryptographic primitive. It is a method to share a secret by a dealer among different parties in such a way that only certain predetermined subsets of parties can together reconstruct the secret while some of the remaining subsets of parties can have no information about the secret. Secret sharing was introduced independently by Shamir [139] and Blakely [20]. What they introduced is called a threshold secret sharing scheme. In such a secret sharing scheme the subsets of parties that can reconstruct a secret …

Fair And Diverse Group Formation Based On Multidimensional Features, Mohammed Saad A Alqahtani

Graduate Theses and Dissertations

The goal of group formation is to build a team to accomplish a specific task. Algorithms are being developed to improve the team's effectiveness so formed and the efficiency of the group selection process. However, there is concern that team formation algorithms could be biased against minorities due to the algorithms themselves or the data on which they are trained. Hence, it is essential to build fair team formation systems that incorporate demographic information into the process of building the group. Although there has been extensive work on modeling individuals’ expertise for expert recommendation and/or team formation, there has been …

Algorithm Performance On The Estimation Of Cdom And Doc In The North Slopes Of Alaska, Monica Weisenbach

Masters Theses

Use of satellite imagery makes environmental monitoring easy and convenient with little of the logistics involved in planning sampling campaigns. Colored dissolved organic matter (CDOM) is an important component to track as a proxy for the large pool of dissolved organic carbon (DOC). In a world contending with the looming issue of global climate change, the ability to investigate the carbon cycle of inland to coastal environments allows for examination of the magnitude of carbon flowing through the system and potential changes over years. The Arctic region is a critical area for climate change impacts but is a difficult landscape …

Automated Code Engine For Tensor Hypercontraction: Derivation, Optimization And Implementation Of Rank-Reduced Coupled Cluster Theories, Yao Zhao

Dissertations, Theses, and Capstone Projects

The ultimate goal of electronic structure theory is solving the electronic Schr¨odinger Equation. However, even accurate approximations of solving Schr¨odinger Equation, such as high order coupled cluster theories, require computational efforts that are too demanding to be applied on large chemical systems. This thesis tackles the problem of curse of dimensionality: how to reduce the time complexity of high-accuracy coupled cluster methods in order to accelerate computations of molecular energy. On one hand, we believe that low-rank approximation (i.e. Tensor HyperContraction) of high-order tensors appearing in coupled cluster theory is a promising way to achieve rank-reduced coupled cluster theory. On …

Exploratory Search With Archetype-Based Language Models, Brent D. Davis

Electronic Thesis and Dissertation Repository

This dissertation explores how machine learning, natural language processing and information retrieval may assist the exploratory search task. Exploratory search is a search where the ideal outcome of the search is unknown, and thus the ideal language to use in a retrieval query to match it is unavailable. Three algorithms represent the contribution of this work. Archetype-based Modeling and Search provides a way to use previously identified archetypal documents relevant to an archetype to form a notion of similarity and find related documents that match the defined archetype. This is beneficial for exploratory search as it can generalize beyond standard …

Analysis Of Music Genre Clustering Algorithms, Samuel Walter Stern

Theses and Dissertations

Classification and clustering of music genres has become an increasingly prevalent focusin recent years, prompting a push for research into relevant algorithms. The most successful algorithms have typically applied the Naive Bayes or k-Nearest Neighbors algorithms, or used Neural Networks to perform classification. This thesis seeks to investigate the use of unsupervised clustering algorithms such as K-Means or Hierarchical clustering, and establish their usefulness in comparison to or conjunction with established methods.

Dealing With Classification Irregularities In Real-World Scenarios., Payel Sadhukhan Dr.

Doctoral Theses

Data processing by the human sensory system comes naturally. This processing, commonly denoted as pattern recognition and analysis are carried out spontaneously by humans. In day to day life, in most cases, decision making by humans come without any conscious effort. From the middle of the past century, humans have shown interest to render their abstraction capabilities (pattern recognition and analysis) to the machine. The abstraction capability of the machine is ’machine intelligence’ or ’machine learning’ [87].The primary goal of machine learning methods is to extract some meaningful information from the ’data’. Data refers to the information or attributes that …

Algorithms Related To Triangle Groups, Bao The Pham

LSU Doctoral Dissertations

Given a finite index subgroup of $\PSL_2(\Z)$, one can talk about the different properties of this subgroup. These properties have been studied extensively in an attempt to classify these subgroups. Tim Hsu created an algorithm to determine whether a subgroup is a congruence subgroup by using permutations \cite{hsu}. Lang, Lim, and Tan also created an algorithm to determine if a subgroup is a congruence subgroup by using Farey Symbols \cite{llt}. Sebbar classified torsion-free congruence subgroups of genus 0 \cite{sebbar}. Pauli and Cummins computed and tabulated all congruence subgroups of genus less than 24 \cite{ps}. However, there are still some problems …

Counting And Sampling Small Structures In Graph And Hypergraph Data Streams, Themistoklis Haris

Dartmouth College Undergraduate Theses

In this thesis, we explore the problem of approximating the number of elementary substructures called simplices in large k-uniform hypergraphs. The hypergraphs are assumed to be too large to be stored in memory, so we adopt a data stream model, where the hypergraph is defined by a sequence of hyperedges.

First we propose an algorithm that (ε, δ)-estimates the number of simplices using O(m^1+1/k / T) bits of space. In addition, we prove that no constant-pass streaming algorithm can (ε, δ)- approximate the number of simplices using less than O( m ^1+1/k / T ) bits of space. Thus …

Studies On Diagnostic Coverage And X-Sensitivity In Logic Circuits., Manjari Pradhan Dr.

Doctoral Theses

Today’s integrated circuits comprise billions of interconnected transistors assembled on a tiny silicon chip, and testing them to ensure functional and timing correctness continues to be a major challenge to designers and test engineers with further downscaling of transistors. Although substantial progress has been witnessed during the last five decades in the area of algorithmic test generation and fault diagnosis, applications of combinatorial and machinelearning (ML) techniques to solve these problems remain largely unexplored till date. In this thesis, we study three problems in the context of digital logic test and diagnosis. The first problem is that of fault diagnosis …

Essays In Social Choice Theory., Dipjyoti Majumdar Dr.

Doctoral Theses

The purpose of this thesis is to explore some issues in social choice theory and decision theory. Social choice theory provides the theoretical foundations for the field of public choice and welfare economics. It tries to bring together normative aspects like perspective value judgements and positive aspects, like strategic con- siderations. The second feature which is our focus, is closely related to the problem of providing appropriate incentives to agents, an issue of prime importance in eco- nomics.Consider for example, a set of agents who must elect one among a set of can- didates. These candidates may be physical agents …