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Full-Text Articles in Physical Sciences and Mathematics

Widget Detection-Based Testing For Industrial Mobile Games, Xiongfei Wu, Jiaming Ye, Ke Chen, Xiaofei Xie, Ruochen Huang, Lei Ma, Jianjun Zhao May 2023

Widget Detection-Based Testing For Industrial Mobile Games, Xiongfei Wu, Jiaming Ye, Ke Chen, Xiaofei Xie, Ruochen Huang, Lei Ma, Jianjun Zhao

Research Collection School Of Computing and Information Systems

The fast advances in mobile hardware and widespread smartphone usage have fueled the growth of global mobile gaming in the past decade. As a result, the need for quality assurance of mobile gaming has become increasingly pressing. While general-purpose testing methods have been developed for mobile applications, they become struggling when being applied to mobile games due to the unique characteristics of mobile games, such as dynamic loading and stunning visual effects. There comes a growing industrial demand for automated testing techniques with high compatibility (compatible with various resolutions, and platforms) and non-intrusive characteristics (without packaging external modules into the …

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Automating Arduino Programming: From Hardware Setups To Sample Source Code Generation, Imam Nur Bani Yusuf, Diyanah Binte Abdul Jamal, Lingxiao Jiang May 2023

Automating Arduino Programming: From Hardware Setups To Sample Source Code Generation, Imam Nur Bani Yusuf, Diyanah Binte Abdul Jamal, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

An embedded system is a system consisting of software code, controller hardware, and I/O (Input/Output) hardware that performs a specific task. Developing an embedded system presents several challenges. First, the development often involves configuring hardware that requires domain-specific knowledge. Second, the library for the hardware may have API usage patterns that must be followed. To overcome such challenges, we propose a framework called ArduinoProg towards the automatic generation of Arduino applications. ArduinoProg takes a natural language query as input and outputs the configuration and API usage pattern for the hardware described in the query. Motivated by our findings on the …

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Multi-Lingual Multi-Partite Product Title Matching, Huan Lin Tay, Wei Jie Tay, Hady Wirawan Lauw May 2023

Multi-Lingual Multi-Partite Product Title Matching, Huan Lin Tay, Wei Jie Tay, Hady Wirawan Lauw

Research Collection School Of Computing and Information Systems

In a globalized marketplace, one could access products or services from almost anywhere. However, resolving which product in one language corresponds to another product in a different language remains an under-explored problem. We explore this from two perspectives. First, given two products of different languages, how to assess their similarity that could signal a potential match. Second, given products from various languages, how to arrive at a multi-partite clustering that respects cardinality constraints efficiently. We describe algorithms for each perspective and integrate them into a promising solution validated on real-world datasets.

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On-Device Deep Multi-Task Inference Via Multi-Task Zipping, Xiaoxi He, Xu Wang, Zimu Zhou, Jiahang Wu, Zheng Yang, Lothar Thiele May 2023

On-Device Deep Multi-Task Inference Via Multi-Task Zipping, Xiaoxi He, Xu Wang, Zimu Zhou, Jiahang Wu, Zheng Yang, Lothar Thiele

Research Collection School Of Computing and Information Systems

Future mobile devices are anticipated to perceive, understand and react to the world on their own by running multiple correlated deep neural networks locally on-device. Yet the complexity of these deep models needs to be trimmed down both within-model and cross-model to fit in mobile storage and memory. Previous studies squeeze the redundancy within a single model. In this work, we aim to reduce the redundancy across multiple models. We propose Multi-Task Zipping (MTZ), a framework to automatically merge correlated, pre-trained deep neural networks for cross-model compression. Central in MTZ is a layer-wise neuron sharing and incoming weight updating scheme …

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Re-Evaluating Natural Intelligence In The Face Of Chatgpt, Elvin T. Lim, Tze K Koh May 2023

Re-Evaluating Natural Intelligence In The Face Of Chatgpt, Elvin T. Lim, Tze K Koh

Research Collection College of Integrative Studies

How will new technologies impact the nature of higher education? Before ChatGPT, the world witnessed major shifts led by innovations in information storage and transmission. Papyrus in ancient Egypt, the Gutenberg press in 15th-century Europe, and the internet in the 20th century were all milestones in the mass dissemination of knowledge.

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The Inescapable Detriments Of Neonicotinoids: An Exploration Of The Harmful Pesticide's Effects On Humans And Insects, Fay Levin May 2023

The Inescapable Detriments Of Neonicotinoids: An Exploration Of The Harmful Pesticide's Effects On Humans And Insects, Fay Levin

The Synapse: Intercollegiate science magazine

No abstract provided.

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Generative Stresnet For Crime Prediction, Ba Phong Tran, Hoong Chuin Lau May 2023

Generative Stresnet For Crime Prediction, Ba Phong Tran, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

In this work, we combine STResnet (Zhang et al., 2017) with VAE Kingma & Welling (2013) to generate crime distribution. The outputs can be used for downstream tasks such as patrol deployment planning Chase et al. (2021).

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Chronos: Time-Aware Zero-Shot Identification Of Libraries From Vulnerability Reports, Yunbo Lyu, Thanh Le Cong, Hong Jin Kang, Ratnadira Widyasari, Zhipeng Zhao, Xuan-Bach Dinh Le, Ming Li, David Lo May 2023

Chronos: Time-Aware Zero-Shot Identification Of Libraries From Vulnerability Reports, Yunbo Lyu, Thanh Le Cong, Hong Jin Kang, Ratnadira Widyasari, Zhipeng Zhao, Xuan-Bach Dinh Le, Ming Li, David Lo

Research Collection School Of Computing and Information Systems

Tools that alert developers about library vulnerabilities depend on accurate, up-to-date vulnerability databases which are maintained by security researchers. These databases record the libraries related to each vulnerability. However, the vulnerability reports may not explicitly list every library and human analysis is required to determine all the relevant libraries. Human analysis may be slow and expensive, which motivates the need for automated approaches. Researchers and practitioners have proposed to automatically identify libraries from vulnerability reports using extreme multi-label learning (XML). While state-of-the-art XML techniques showed promising performance, their experimental settings do not practically fit what happens in reality. Previous studies …

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Generation-Based Code Review Automation: How Far Are We?, Xin Zhou, Kisub Kim, Bowen Xu, Donggyun Han, Junda He, David Lo May 2023

Generation-Based Code Review Automation: How Far Are We?, Xin Zhou, Kisub Kim, Bowen Xu, Donggyun Han, Junda He, David Lo

Research Collection School Of Computing and Information Systems

Code review is an effective software quality assurance activity; however, it is labor-intensive and time-consuming. Thus, a number of generation-based automatic code review (ACR) approaches have been proposed recently, which leverage deep learning techniques to automate various activities in the code review process (e.g., code revision generation and review comment generation).We find the previous works carry three main limitations. First, the ACR approaches have been shown to be beneficial in each work, but those methods are not comprehensively compared with each other to show their superiority over their peer ACR approaches. Second, general-purpose pre-trained models such as CodeT5 are proven …

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Exploring A Gradient-Based Explainable Ai Technique For Time-Series Data: A Case Study Of Assessing Stroke Rehabilitation Exercises, Min Hun Lee, Yi Jing Choy May 2023

Exploring A Gradient-Based Explainable Ai Technique For Time-Series Data: A Case Study Of Assessing Stroke Rehabilitation Exercises, Min Hun Lee, Yi Jing Choy

Research Collection School Of Computing and Information Systems

Explainable artificial intelligence (AI) techniques are increasingly being explored to provide insights into why AI and machine learning (ML) models provide a certain outcome in various applications. However, there has been limited exploration of explainable AI techniques on time-series data, especially in the healthcare context. In this paper, we describe a threshold-based method that utilizes a weakly supervised model and a gradient-based explainable AI technique (i.e. saliency map) and explore its feasibility to identify salient frames of time-series data. Using the dataset from 15 post-stroke survivors performing three upper-limb exercises and labels on whether a compensatory motion is observed or …

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Trustworthy And Synergistic Artificial Intelligence For Software Engineering: Vision And Roadmaps, David Lo May 2023

Trustworthy And Synergistic Artificial Intelligence For Software Engineering: Vision And Roadmaps, David Lo

Research Collection School Of Computing and Information Systems

For decades, much software engineering research has been dedicated to devising automated solutions aimed at enhancing developer productivity and elevating software quality. The past two decades have witnessed an unparalleled surge in the development of intelligent solutions tailored for software engineering tasks. This momentum established the Artificial Intelligence for Software Engineering (AI4SE) area, which has swiftly become one of the most active and popular areas within the software engiueering field. This Future of Software Engineering (FoSE) paper navigates through several focal points. It commences with a succinct introduction and history of AI4SE. Thereafter, it underscores the core challenges inherent to …

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Ncq: Code Reuse Support For Node.Js Developers, Brittany Reid, Marcelo D'Amorim, Markus Wagner, Christoph Treude May 2023

Ncq: Code Reuse Support For Node.Js Developers, Brittany Reid, Marcelo D'Amorim, Markus Wagner, Christoph Treude

Research Collection School Of Computing and Information Systems

Code reuse is an important part of software development. The adoption of code reuse practices is especially common among Node.js developers. The Node.js package manager, NPM, indexes over 1 Million packages and developers often seek out packages to solve programming tasks. Due to the vast number of packages, selecting the right package is difficult and time consuming. With the goal of improving productivity of developers that heavily reuse code through third-party packages, we present Node Code Query (NCQ), a Read-Eval-Print-Loop environment that allows developers to 1) search for NPM packages using natural language queries, 2) search for code snippets related …

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She Elicits Requirements And He Tests: Software Engineering Gender Bias In Large Language Models, Christoph Treude, Hideaki Hata May 2023

She Elicits Requirements And He Tests: Software Engineering Gender Bias In Large Language Models, Christoph Treude, Hideaki Hata

Research Collection School Of Computing and Information Systems

Implicit gender bias in software development is a well-documented issue, such as the association of technical roles with men. To address this bias, it is important to understand it in more detail. This study uses data mining techniques to investigate the extent to which 56 tasks related to software development, such as assigning GitHub issues and testing, are affected by implicit gender bias embedded in large language models. We systematically translated each task from English into a genderless language and back, and investigated the pronouns associated with each task. Based on translating each task 100 times in different permutations, we …

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Towards Understanding The Open Source Interest In Gender-Related Github Projects, Rita Garcia, Christoph Treude, Wendy La May 2023

Towards Understanding The Open Source Interest In Gender-Related Github Projects, Rita Garcia, Christoph Treude, Wendy La

Research Collection School Of Computing and Information Systems

The open-source community uses the GitHub platform to exchange and share software applications and services of interest. This paper aims to identify the open-source community’s interest in gender-related projects on GitHub. Our findings create research opportunities and identify resources by the open-source community that promote diversity, equity, and inclusion. We use data mining to identify GitHub projects that focus on gender-related topics. We apply quantitative and qualitative methodologies to examine the projects’ attributes and to classify them within a gender social structure and a gender bias taxonomy. We aim to understand the open-source community’s efforts and interests in gender topics …

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Stop Words For Processing Software Engineering Documents: Do They Matter, Yaohou Fan, Chetan Arora, Christoph Treude May 2023

Stop Words For Processing Software Engineering Documents: Do They Matter, Yaohou Fan, Chetan Arora, Christoph Treude

Research Collection School Of Computing and Information Systems

Stop words, which are considered non-predictive, are often eliminated in natural language processing tasks. However, the definition of uninformative vocabulary is vague, so most algorithms use general knowledge-based stop lists to remove stop words. There is an ongoing debate among academics about the usefulness of stop word elimination, especially in domainspecific settings. In this work, we investigate the usefulness of stop word removal in a software engineering context. To do this, we replicate and experiment with three software engineering research tools from related work. Additionally, we construct a corpus of software engineering domain-related text from 10,000 Stack Overflow questions and …

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Lpt: Long-Tailed Prompt Tuning For Image Classification, Bowen Dong, Pan Zhou, Shuicheng Yan, Wangmeng Zuo May 2023

Lpt: Long-Tailed Prompt Tuning For Image Classification, Bowen Dong, Pan Zhou, Shuicheng Yan, Wangmeng Zuo

Research Collection School Of Computing and Information Systems

For long-tailed classification tasks, most works often pretrain a big model on a large-scale (unlabeled) dataset, and then fine-tune the whole pretrained model for adapting to long-tailed data. Though promising, fine-tuning the whole pretrained model tends to suffer from high cost in computation and deployment of different models for different tasks, as well as weakened generalization capability for overfitting to certain features of long-tailed data. To alleviate these issues, we propose an effective Long-tailed Prompt Tuning (LPT) method for long-tailed classification tasks. LPT introduces several trainable prompts into a frozen pretrained model to adapt it to long-tailed data. For better …

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Towards Understanding Why Mask Reconstruction Pretraining Helps In Downstream Tasks, Jiachun Pan, Pan Zhou, Shuicheng Yan May 2023

Towards Understanding Why Mask Reconstruction Pretraining Helps In Downstream Tasks, Jiachun Pan, Pan Zhou, Shuicheng Yan

Research Collection School Of Computing and Information Systems

For unsupervised pretraining, mask-reconstruction pretraining (MRP) approaches, e.g. MAE (He et al., 2021) and data2vec (Baevski et al., 2022), randomly mask input patches and then reconstruct the pixels or semantic features of these masked patches via an auto-encoder. Then for a downstream task, supervised fine-tuning the pretrained encoder remarkably surpasses the conventional “supervised learning" (SL) trained from scratch. However, it is still unclear 1) how MRP performs semantic feature learning in the pretraining phase and 2) why it helps in downstream tasks. To solve these problems, we first theoretically show that on an auto-encoder of a two/one-layered convolution encoder/decoder, MRP …

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Synthesis, Radiolabeling And Evaluation Of A Suite Of Tracers With 44Sc For Detecting Extracellular Dna, Zhiyao Li May 2023

Synthesis, Radiolabeling And Evaluation Of A Suite Of Tracers With 44Sc For Detecting Extracellular Dna, Zhiyao Li

McKelvey School of Engineering Theses & Dissertations

Neutrophil extracellular traps involve the rapid translocation of DNA to the outside of the cell under certain stimuli. This structure forms a fibrous network that is able to limit the spread of pathogens and to kill microorganisms. It has also been shown to be present in various pathological processes such as inflammation, autoimmune diseases, and cancer metastasis. Currently, the formation process of NETs in vivo is being extensively studied. However noninvasive detection and quantitation has yet to be achieved. A class of PET tracers are described here that consists of a DNA dye as the backbone that is labeled with …

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Sim-To-Real Reinforcement Learning Framework For Autonomous Aerial Leaf Sampling, Ashraful Islam May 2023

Sim-To-Real Reinforcement Learning Framework For Autonomous Aerial Leaf Sampling, Ashraful Islam

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Using unmanned aerial systems (UAS) for leaf sampling is contributing to a better understanding of the influence of climate change on plant species, and the dynamics of forest ecology by studying hard-to-reach tree canopies. Currently, multiple skilled operators are required for UAS maneuvering and using the leaf sampling tool. This often limits sampling to only the canopy top or periphery. Sim-to-real reinforcement learning (RL) can be leveraged to tackle challenges in the autonomous operation of aerial leaf sampling in the changing environment of a tree canopy. However, trans- ferring an RL controller that is learned in simulation to real UAS …

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Late Holocene Slip History Of The Central Garlock Fault, Mojave Desert, California, James Eric Burns May 2023

Late Holocene Slip History Of The Central Garlock Fault, Mojave Desert, California, James Eric Burns

Electronic Theses, Projects, and Dissertations

This study investigates the late Holocene slip history of the central Garlock Fault, using measurements of left-lateral offsets of alluvial features from airborne and hand-held LiDAR imagery, drone photogrammetry, and field measurements. IRSL dating of the offset late Holocene alluvial deposits was compared to published paleoseismic records to estimate the number of earthquakes that contributed to the offsets. Focus was given to geomorphic features offset in the past 1-4 earthquakes. Results indicate the average slip per earthquake was about 5.75 m (range: 4.75 to 6.25 m) in the past four events in the El Paso Mountains (EPM) and was 4.3-7.3 …

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Heart Disease Prediction Using Binary Classification, Virendra Sunil Devare May 2023

Heart Disease Prediction Using Binary Classification, Virendra Sunil Devare

Electronic Theses, Projects, and Dissertations

In this project, I built a neural network model to predict heard disease with binary classification technique using patient information dataset from UCI Machine Learning repository. This dataset was preprocessed to remove missing elements and performed feature extraction. Our result shows that the model that I built has the best performance accuracy in heart disease classification if compared to other models and algorithms. The model achieved 94.98% accuracy after hyperparameter tuning and 0.947 area under the curve in ROC curve analysis. In addition, to identify the most important factors in heart disease prediction, I also performed feature importance analysis. Our …

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Minions Fitness Tracker, Mohammad Hasibur Rahman May 2023

Minions Fitness Tracker, Mohammad Hasibur Rahman

2023 MathWorks Fitness Tracker Challenge

I made a fitness tracker that counts the steps of user using their mobile device. I made this tracker using MATLAB sensor and added the sensor path with the mobile device, the tracker would count the number of steps taken by finding peaks in acceleration data.

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Long-Term Spatial And Temporal Assessment Of Criteria Air Pollutants Concentration Trends In The Lower Rio Grande Valley Region Of Texas, Usa, Md Salahuddin Majumder May 2023

Long-Term Spatial And Temporal Assessment Of Criteria Air Pollutants Concentration Trends In The Lower Rio Grande Valley Region Of Texas, Usa, Md Salahuddin Majumder

Theses and Dissertations

Air pollution is a substantial environmental challenge all over the world. This study investigated the long-term air pollution levels in the Lower Rio Grande Valley region, by utilizing data collected from five continuous ambient monitoring stations in two counties over 23 years, from January 2000 to December 2022, to analyze daily, monthly, and seasonal variations of different pollutants, including ground-level ozone, particulate matter, and carbon monoxide. This study also identified distinct daily and seasonal patterns for O3, PM2.5, PM10, and CO at each monitoring site, influenced by factors such as traffic emissions, temperature, solar radiation, indoor heating, and weather conditions. …

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The Use Of Fluorescence Resonance Energy Transfer And Bent Dna To Study Dna And Ion Interactions, Kaitlin Bullard May 2023

The Use Of Fluorescence Resonance Energy Transfer And Bent Dna To Study Dna And Ion Interactions, Kaitlin Bullard

Physics Undergraduate Honors Theses

Studying DNA interactions is advantageous to developments in the medical field since DNA and its interactions affect our health greatly. In addition, it is important to understand how the bendability of DNA depends on metal ions, which are essential for various fundamental processes in cells. In this work, we investigate the use of FRET and self-assembled bent DNA molecules to quantify DNA interactions with magnesium ions. We measured that the FRET efficiency increased at higher concentrations of magnesium ions. We also ran simulations to further understand the mechanisms. These observations show that magnesium ions increase the stability and flexibility of …

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Analysis On High Mass X-Ray Binary Spectral Shape Dependence On Luminosity For Ngc3310, Izabela Pavel May 2023

Analysis On High Mass X-Ray Binary Spectral Shape Dependence On Luminosity For Ngc3310, Izabela Pavel

Physics Undergraduate Honors Theses

In most normal galaxies, the most X-ray luminous sources are high-mass X-ray binaries (HMXBs), which are binary star systems that contain compact objects (black holes or neutron stars) accreting from massive (> 8M⊙) companion stars. These HMXBs are thought to have been important sources of ionizing emission within star-forming galaxies that may have contributed to the heating of the intergalatic medium (gas over large cosmic scales) in the early Universe. When studying how HMXBs contribute to interstellar medium feedback, a single spectral shape of an absorbed power-law is typically assumed to be universal. The goal of this thesis is to …

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Excitation Power Dependence Of Blinking In Copper-Indium-Sulfide Quantum Dots, Nicholas Chambers May 2023

Excitation Power Dependence Of Blinking In Copper-Indium-Sulfide Quantum Dots, Nicholas Chambers

Physics Undergraduate Honors Theses

Under continuous excitation, quantum dots exhibit random transitions between fluorescent ON states and non-fluorescent OFF states --- a phenomenon known as blinking. A physical description of the mechanism responsible for blinking that applies broadly to many types of quantum dots remains under debate. We study the blinking behavior of the non-toxic CuInS2 quantum dot, a system that has seen little investigation at the single-particle level. In particular, the optical properties of CuInS2 quantum are often improved by adding ZnS to the nanoparticles, but this addition leads to complex structural-optical property relationships that are even less understood. To probe the relationship …

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Fabrication Of Black Phosphorus Terahertz Photoconductive Antennas, Nathan Tanner Sawyers May 2023

Fabrication Of Black Phosphorus Terahertz Photoconductive Antennas, Nathan Tanner Sawyers

Physics Undergraduate Honors Theses

Terahertz (THz) photoconductive antennas (PCAs) using 40nm thin-film flakes of black phosphorus (BP) and hexagonal boron nitride (hBN) have been shown computationally to be capable of THz emission comparable to those based on GaAs [2]. In this paper, I briefly describe the scientific and practical interest in THz emissions and explain what warrants research into black phosphorus as a photoconductive semiconductor in THz devices. Furthermore, I outline the basic principle of how these antennas work and mention alternative designs produced by other researchers in the past. Finally, I summarize the fabrication process of these antennas, as well as the measurements …

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Photon Correlation Measurements And Second Harmonic Generation Using Pulsed Lasers, Apoorva Bisht May 2023

Photon Correlation Measurements And Second Harmonic Generation Using Pulsed Lasers, Apoorva Bisht

Physics Undergraduate Honors Theses

Correlation measurements are one of the fundamental ways to understand the photon statistics/distribution for a source of light. It is also an important method to confirm single photon sources by confirming the anitbunching nature. This project developed a correlation measurement system, utilized field programmable gate arrays, and non-linear crystals for processes like second harmonic generation and down conversion.

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Echolocation-Location-Location: Acousics, Mammals, Technology, Mammals, And Military, Anadi Mehal Purewal-Legha May 2023

Echolocation-Location-Location: Acousics, Mammals, Technology, Mammals, And Military, Anadi Mehal Purewal-Legha

The Synapse: Intercollegiate science magazine

No abstract provided.

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Exploring The Structure Of Partial Difference Sets With Denniston Parameters, Nicolas Ferree May 2023

Exploring The Structure Of Partial Difference Sets With Denniston Parameters, Nicolas Ferree

Honors Theses

In this work, we investigate the structure of particular partial difference sets (PDS) of size 70 with Denniston parameters in an elementary abelian group and in a nonelementary abelian group. We will make extensive use of character theory in our investigation and ultimately seek to understand the nature of difference sets with these parameters. To begin, we will cover some basic definitions and examples of difference sets and partial difference sets. We will then move on to some basic theorems about partial difference sets before introducing a group ring formalism and using it to explore several important constructions of partial …

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