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Articles 1 - 16 of 16
Full-Text Articles in Theory and Algorithms
Search For Slow-Moving Magnetic Monopoles With An Improved High-Energy Event Removal Algorithm, Reeshi N. Gihosal
Search For Slow-Moving Magnetic Monopoles With An Improved High-Energy Event Removal Algorithm, Reeshi N. Gihosal
Honors Theses
Fermilab’s NOvA (NuMI Off-axis 𝑣𝑒 Appearance) experiment focuses on understanding the behavior of neutrinos and how they affect the cosmos. A sub-focus of the NOvA experiment is the search for magnetic monopoles. These elusive particles have not yet been observed in nature, leaving their behavior to be mysterious. The Far Detector, located in Ash River, MN, is integral in the search for these particles. This project is on simulated magnetic monopoles with speeds thousandths the speed of light, with focus on the role of slicing algorithms in event reconstruction using the NOvA experiment’s reconstruction algorithm. Using sample data, analysis occurred …
Algorithm Performance In The Search For Hamiltonian Cycles, Chance Davis
Algorithm Performance In The Search For Hamiltonian Cycles, Chance Davis
Honors Theses
The Hamiltonian cycle problem is ubiquitous in both computer science and graph theory: Given a connected graph, a solution would either confirm the existence of a cycle which visits each vertex only once or its nonexistence. The importance of this problem, as well as its difficulty, is described in the Clay Mathematics Institute’s Millenium Prize Problems and Karp’s 21 NP-complete problems. Despite its “hardness,” solutions to the Hamiltonian cycle problem are desired in logistics, electronic circuit design, and network routing, among other fields. In this work, we benchmark a promising exhaustive enumeration algorithm on various graphs, including ones derived from …
Optimized Student Grouping For Enhanced Classroom Performance, Kathryn E. Reardon
Optimized Student Grouping For Enhanced Classroom Performance, Kathryn E. Reardon
Honors Theses
Effective grouping methods enhance classroom collaboration and allow for a student-centered teaching approach; however, traditional grouping methods are time-consuming, subjective, and can create inconsistent group dynamics. This project addresses these challenges by employing a data-driven approach to optimize student groups based on academic performance, behavior, attendance, language barriers, and teacher preferences. The minimum viable product is a web application with an algorithm-driven system to group students and a database storage for group results. During the initiation phase, a problem was defined with a proposed solution. During the planning phase, potential design choices and grouping methods were researched and assessed. During …
Comparative Analysis Of Classical And Machine Learning Pathfinding Approaches, Miguel Gapud
Comparative Analysis Of Classical And Machine Learning Pathfinding Approaches, Miguel Gapud
Honors Theses
Pathfinding is an essential task for any autonomous robot. Graph-based classical pathfinding algorithms and machine learning approaches have both been used for this end, but they are often not compared against each other. An implementation of end-to-end (E2E) pathfinding using Proximal Policy Optimization (PPO) and an Alexnet architecture is compared against an implementation of Hybrid A*. A digital twin in Unity3D is used as the testing environment with the Clearpath Dingo as the pathfinding robot. In machine learning, the robot is controlled using PPO through ROS-Noetic with a camera as its sensor. Hybrid A* and its controls are implemented directly …
Development Of An Algorithm To Identify And Calculate The Amount Of File Slack On An Image Of A Given Drive, Nicholas Flynn
Development Of An Algorithm To Identify And Calculate The Amount Of File Slack On An Image Of A Given Drive, Nicholas Flynn
Honors Theses
As society increasingly relies on technology, the rates of cyber crime have been increasing at exponential rates. Cyber criminals are also discovering new ways to hide evidence of their crimes. This study develops a forensic analysis algorithm to evaluate the amount of file slack on an image of a drive. Slack space, leftover drive space on a disk sector after a file has been written, can be exploited to hide data. The algorithm aims to detect and calculate this slack space to help direct forensic investigations. The algorithm was evaluated on a population dataset of 100,000 files with random data …
Theoretical Spectroscopic Predictions Of Electronically Excited States, Noah R. Garrett
Theoretical Spectroscopic Predictions Of Electronically Excited States, Noah R. Garrett
Honors Theses
The quest for faster computation of anharmonic vibrational frequencies of both ground and excited electronic states has led to combining coupled cluster theory harmonic force constants with density functional theory (DFT) cubic and quartic force constants for defining a quartic force field (QFF) utilized in conjunction with vibrational perturbation theory at second order (VPT2). This work shows that explicitly correlated coupled cluster theory at the singles, doubles, and perturbative triples level [CCSD(T)-F12] provides accurate anharmonic vibrational frequencies and rotational constants when conjoined with any of B3LYP, CAM-B3LYP, BHandHLYP, PBE0, and ωB97XD for roughly one-quarter of the computational time of the …
Exploration Of Feature Selection Techniques In Machine Learning Models On Hptlc Images For Rule Extraction, Bozidar-Brannan Kovachev
Exploration Of Feature Selection Techniques In Machine Learning Models On Hptlc Images For Rule Extraction, Bozidar-Brannan Kovachev
Honors Theses
Research related to Biology often utilizes machine learning models that are ultimately uninterpretable by the researcher. It would be helpful if researchers could leverage the same computing power but instead gain specific insight into decision-making to gain a deeper understanding of their domain knowledge. This paper seeks to select features and derive rules from a machine learning classification problem in biochemistry. The specific point of interest is five species of Glycyrrhiza, or Licorice, and the ability to classify them using High-Performance Thin Layer Chromatography (HPTLC) images. These images were taken using HPTLC methods under varying conditions to provide eight …
Improving Adjacency List Storage Methods For Polypeptide Similarity Analysis, Arianna Swensen
Improving Adjacency List Storage Methods For Polypeptide Similarity Analysis, Arianna Swensen
Honors Theses
Protein design is a complex biomolecular and computational problem. Working on increasingly large protein folding problems requires an improvement in current analysis methods available. This work first discusses various methods of protein design, including de novo protein design, which is the primary focus of this thesis. Then, a new approach utilizing a B+ tree to effectively store and query a graph of keys and vertices is proposed in order to store the number of times two polypeptides are considered to be similar. This approach is found to have a reduction in time complexity from current mapping methods and thus provides …
Decoding Cyclic Codes Via Gröbner Bases, Eduardo Sosa
Decoding Cyclic Codes Via Gröbner Bases, Eduardo Sosa
Honors Theses
In this paper, we analyze the decoding of cyclic codes. First, we introduce linear and cyclic codes, standard decoding processes, and some standard theorems in coding theory. Then, we will introduce Gr¨obner Bases, and describe their connection to the decoding of cyclic codes. Finally, we go in-depth into how we decode cyclic codes using the key equation, and how a breakthrough by A. Brinton Cooper on decoding BCH codes using Gr¨obner Bases gave rise to the search for a polynomial-time algorithm that could someday decode any cyclic code. We discuss the different approaches taken toward developing such an algorithm and …
Dijkstra’S Pathfinder, Taylor F. Malamut
Dijkstra’S Pathfinder, Taylor F. Malamut
Honors Theses
Dijkstra’s algorithm has been widely studied and applied since it was first published in 1959. This research shows that Dijkstra’s algorithm can be used to find the shortest path between two stations on the Washington D.C. Metro. After exploring different types of research and applying Dijkstra’s algorithm, it was found that the algorithm will always yield the shortest path, even if visually a shorter path was initially expected.
Extensions Of The Morse-Hedlund Theorem, Eben Blaisdell
Extensions Of The Morse-Hedlund Theorem, Eben Blaisdell
Honors Theses
Bi-infinite words are sequences of characters that are infinite forwards and backwards; for example "...ababababab...". The Morse-Hedlund theorem says that a bi-infinite word f repeats itself, in at most n letters, if and only if the number of distinct subwords of length n is at most n. Using the example, "...ababababab...", there are 2 subwords of length 3, namely "aba" and "bab". Since 2 is less than 3, we must have that "...ababababab..." repeats itself after at most 3 letters. In fact it does repeat itself every two letters. …
Mechanism Design, Matching Theory And The Stable Roommates Problem, Yashaswi Mohanty
Mechanism Design, Matching Theory And The Stable Roommates Problem, Yashaswi Mohanty
Honors Theses
This thesis consists of two independent albeit related chapters. The first chapter introduces concepts from mechanism design and matching theory, and discusses potential applications of this theory, particularly in relation to dorm allocations in colleges. The second chapter investigates a subset of the dorm allocation problem, namely that of matching roommates. In particular, the paper looks at the probability of solvability of random instances of the stable roommates game under the condition that preferences are not completely random and exogenous but endogenously determined through a dependence on room choice. These probabilities are estimated using Monte-Carlo simulations and then compared with …
Normal Surfaces And 3-Manifold Algorithms, Josh D. Hews
Normal Surfaces And 3-Manifold Algorithms, Josh D. Hews
Honors Theses
This survey will develop the theory of normal surfaces as they apply to the S3 recognition algorithm. Sections 2 and 3 provide necessary background on manifold theory. Section 4 presents the theory of normal surfaces in triangulations of 3-manifolds. Section 6 discusses issues related to implementing algorithms based on normal surfaces, as well as an overview of the Regina, a program that implements many 3-manifold algorithms. Finally section 7 presents the proof of the 3-sphere recognition algorithm and discusses how Regina implements the algorithm.
Using Genetic Algorithms To Evolve Artificial Neural Networks, William T. Kearney
Using Genetic Algorithms To Evolve Artificial Neural Networks, William T. Kearney
Honors Theses
This paper demonstrates that neuroevolution is an effective method to determine an optimal neural network topology. I provide an overview of the NeuroEvolution of Augmenting Topologies (NEAT) algorithm, and describe how unique characteristics of this algorithm solve various problem inherent to neuroevolution (namely the competing conventions problem and the challenges associated with protecting topological innovation). Parallelization is shown to greatly speed up efficiency, further reinforcing neuroevolution as a potential alternative to traditional backpropagation. I also demonstrate that appropriate parameter selection is critical in order to efficiently converge to an optimal topology. Lastly, I produce an example solution to a medical …
An Analysis Of Peer-To-Peer Distributed Hash Algorithms In Improving Fault Tolerance In The Hadoop Running Environment, Benjamin R. Knaus
An Analysis Of Peer-To-Peer Distributed Hash Algorithms In Improving Fault Tolerance In The Hadoop Running Environment, Benjamin R. Knaus
Honors Theses
Cloud computing is a “new frontier” in the world of computing. One of the cloud architectures widely used is the Hadoop running environment. Hadoop consists of many parts—including MapReduce, TaskTrackers, and JobTrackers. Right now, there is no fault-tolerance for JobTrackers in Hadoop. This paper analyzes four different distributed hash algorithms (Pastry, Tapestry, CAN, and Chord) that could be implemented inside Hadoop to improve JobTracker fault-tolerance. We recommend Chord as the best suited for integration and improvement of Hadoop.
Utilization Of Probabilistic Models In Short Read Assembly From Second-Generation Sequencing, Matthew W. Segar
Utilization Of Probabilistic Models In Short Read Assembly From Second-Generation Sequencing, Matthew W. Segar
Honors Theses
With the advent of cheaper and faster DNA sequencing technologies, assembly methods have greatly changed. Instead of outputting reads that are thousands of base pairs long, new sequencers parallelize the task by producing read lengths between 35 and 400 base pairs. Reconstructing an organism’s genome from these millions of reads is a computationally expensive task. Our algorithm solves this problem by organizing and indexing the reads using n-grams, which are short, fixed-length DNA sequences of length n. These n-grams are used to efficiently locate putative read joins, thereby eliminating the need to perform an exhaustive search over all possible read …