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Full-Text Articles in Physical Sciences and Mathematics

Machine Learning Prediction Of Hea Properties, Nicholas J. Beaver, Nathaniel Melisso, Travis Murphy Oct 2023

Machine Learning Prediction Of Hea Properties, Nicholas J. Beaver, Nathaniel Melisso, Travis Murphy

College of Engineering Summer Undergraduate Research Program

High-entropy alloys (HEA) are a very new development in the field of metallurgical materials. They are made up of multiple principle atoms unlike traditional alloys, which contributes to their high configurational entropy. The microstructure and properties of HEAs are are not well predicted with the models developed for more common engineering alloys, and there is not enough data available on HEAs to fully represent the complex behavior of these alloys. To that end, we explore how the use of machine learning models can be used to model the complex, high dimensional behavior in the HEA composition space. Based on our …


Integrating Human Expert Knowledge With Openai And Chatgpt: A Secure And Privacy-Enabled Knowledge Acquisition Approach, Ben Phillips Oct 2023

Integrating Human Expert Knowledge With Openai And Chatgpt: A Secure And Privacy-Enabled Knowledge Acquisition Approach, Ben Phillips

College of Engineering Summer Undergraduate Research Program

Advanced Large Language Models (LLMs) struggle to produce accurate results and preserve user privacy for use cases involving domain-specific knowledge. A privacy-preserving approach for leveraging LLM capabilities on domain-specific knowledge could greatly expand the use cases of LLMs in a variety of disciplines and industries. This project explores a method for acquiring domain-specific knowledge for use with GPT3 while protecting sensitive user information with ML-based text-sanitization.


Development Of User Interface And Testing Harness, Jacob Amezquita, William Albertini Oct 2023

Development Of User Interface And Testing Harness, Jacob Amezquita, William Albertini

College of Engineering Summer Undergraduate Research Program

No abstract provided.


Ai For Search And Rescue - Locating A Missing Person, David Hernandez, Sai Rama Balakrishnan, Timmy Chin, Aditya Manikonda, Vasanth Pugalenthi Oct 2023

Ai For Search And Rescue - Locating A Missing Person, David Hernandez, Sai Rama Balakrishnan, Timmy Chin, Aditya Manikonda, Vasanth Pugalenthi

College of Engineering Summer Undergraduate Research Program

Building on the work done initially as a SURP 2021 project and continued through 2021-23, the focus for this summer project will be on the use of computer technology for locating a missing person. Over the last year, we developed the digital equivalents of about 30 paper-based S&R forms and the infrastructure to collect the respective information. In their current use, these paper forms are filled out by search teams, collected in a command post, and reviewed by search coordinators. This process is time-consuming, prone to errors and loss of information, and relies heavily on the experience, skills, and mental …


Ethics And Social Justice For Ai In Data Science, Arya Ramchander, Kylene Nicole Landenberger Oct 2023

Ethics And Social Justice For Ai In Data Science, Arya Ramchander, Kylene Nicole Landenberger

College of Engineering Summer Undergraduate Research Program

The advances of AI raise several critical questions about human values and ethics, highlighting the need for researchers and developers to consider the ethical implications and the risks of neglecting them. In the past few years, student researchers have developed an AI model that allows users to test their surveys for possible breaches of subject confidentiality. This allows the users to gauge the ethicality of their proposal. This summer, we have expanded on this research and launched an interactive model for students and researches to assess their current work for ethical and social justice implications. Using Langchain and Figma, we …


Exploring Approaches To Engage K-12 Students In Learning Computational Thinking Using Collaborative Robots, Zoila Anuri Kanu Oct 2023

Exploring Approaches To Engage K-12 Students In Learning Computational Thinking Using Collaborative Robots, Zoila Anuri Kanu

College of Engineering Summer Undergraduate Research Program

Minority students are largely underrepresented in the STEM field. The goal for this project was to develop a program which promotes the inclusion of computation skills among students and help them work collaboratively with the use of human – robot interaction. Robots are such a strong tool that can be used to enhance computational thinking and engage students towards a technical field. Through workshops and readings about computational thinking we worked on building a block-based program that introduces the uses of robots as teaching tool for computational thinking.


Automating Deep-Sea Video Annotation Using Machine Learning, Hanson Egbert, Lubomir Stanchev, Benjamin Ruttenberg Feb 2020

Automating Deep-Sea Video Annotation Using Machine Learning, Hanson Egbert, Lubomir Stanchev, Benjamin Ruttenberg

Computer Science and Software Engineering

As the world explores opportunities to develop offshore renewable energy capacity, there will be a growing need for pre-construction biological surveys and post-construction monitoring in the challenging marine environment. Underwater video is a powerful tool to facilitate such surveys, but the interpretation of the imagery is costly and time-consuming. Emerging technologies have improved automated analysis of underwater video, but these technologies are not yet accurate or accessible enough for widespread adoption in the scientific community or industries that might benefit from these tools. To address these challenges, we developed a website that allows us to: (1) Quickly play and annotate …


Rplidar A2 Accuracy, Ramiro O. Garcia Sep 2019

Rplidar A2 Accuracy, Ramiro O. Garcia

STAR Program Research Presentations

Traffic is not only a source of frustration but also a leading cause of death for people under 35 years of age. Recent research has focused on how driver assistance technology can be used to mitigate traffic fatalities and create more enjoyable commutes. In addition, self-driving vehicles can reduce fuel consumption the amount by 5% and increases the number of cars on the highway. To achieve this we need to research reliable sensors. This summer I research Rplidar A2 sensor which hopefully will be responsible for recording distance to the preceding car and helping prevent Insider Attacks or Misbehaviors of …


Exploring Delay Dispersal In Us Airport Network, Brandon Sripimonwan, Arun Sathanur Aug 2019

Exploring Delay Dispersal In Us Airport Network, Brandon Sripimonwan, Arun Sathanur

STAR Program Research Presentations

The modeling of delay diffusion in airport networks can potentially help develop strategies to prevent the spread of such delays and disruptions. With this goal, we used the publicly-available historical United States Federal Aviation Administration (FAA) flight data to model the spread of delays in the US airport network. For the major (ASPM-77) airports for January 2017, using a threshold on the volume of flights, we sparsify the network in order to better recognize patterns and cluster structure of the network. We developed a diffusion simulator and greedy optimizer to find the top influential airport nodes that propagate the most …


Combining Parts Of Speech, Term Proximity, And Query Expansion For Document Retrieval, Lubomir Stanchev, Eric Labouve Jan 2019

Combining Parts Of Speech, Term Proximity, And Query Expansion For Document Retrieval, Lubomir Stanchev, Eric Labouve

Computer Science and Software Engineering

Document retrieval systems recover documents from a database and order them according to their perceived relevance to a user's search query. This is a difficult task for machines to accomplish because there exists a semantic gap between the meaning of the terms in a user's literal query and a user's true intentions. The main goal of this study is to modify the Okapi BM25 document retrieval system to improve search results for textual queries and unstructured, textual corpora. This research hypothesizes that Okapi BM25 is not taking full advantage of the structure of text inside documents. This structure holds valuable …


Visualization Of Geospatial Data As An Analytical And Educational Tool, Richard A. Vu Aug 2018

Visualization Of Geospatial Data As An Analytical And Educational Tool, Richard A. Vu

STAR Program Research Presentations

World Wind is an open-source API developed for Java, Android, and browsers that is designed to visualize and interact with geospatial data. The Web World Wind client is composed of four major components: the HTML template, the globe, geospatial features, and application features. The template was implemented using Bootstrap and hosts the globe provided by World Wind. This globe draws its data from multiple imagery sources, including the Open Geospatial Consortium (OGC) Web Map Service and Web Map Tile Service. This enables the application to perform and visualize complex calculations with multiple types of data such as weather and terrain. …


Characterizing Mental Health And Wellness In Students Across Engineering Disciplines, Andrew Danowitz, Kacey Beddoes Apr 2018

Characterizing Mental Health And Wellness In Students Across Engineering Disciplines, Andrew Danowitz, Kacey Beddoes

Computer Science and Software Engineering

Anecdotal evidence has long supported the idea that engineering students have lower levels of mental health and wellness than their peers. It is often posited that the large number of courses, low overall retention, difficult courses, and the abundance of intensive engineering projects lead to an unhealthy work-life balance and eventually lower levels of mental health for this population. To date, however, there has been no comprehensive study on the prevalence and types of mental health conditions that afflict engineering students, or any data on whether certain disciplines within engineering may see a greater prevalence of certain mental health conditions …


Semantic Document Clustering Using Information From Wordnet And Dbpedia, Lubomir Stanchev Jan 2018

Semantic Document Clustering Using Information From Wordnet And Dbpedia, Lubomir Stanchev

Computer Science and Software Engineering

Semantic document clustering is a type of unsupervised learning in which documents are grouped together based on their meaning. Unlike traditional approaches that cluster documents based on common keywords, this technique can group documents that share no words in common as long as they are on the same subject. We compute the similarity between two documents as a function of the semantic similarity between the words and phrases in the documents. We model information from WordNet and DBPedia as a probabilistic graph that can be used to compute the similarity between two terms. We experimentally validate our algorithm on the …


Intuition: Role, Biases, Cognitive Basis, And A Hypothetical Synergistic Explanation Of Intuitive Brain Operations, Jens G. Pohl Jul 2017

Intuition: Role, Biases, Cognitive Basis, And A Hypothetical Synergistic Explanation Of Intuitive Brain Operations, Jens G. Pohl

Collaborative Agent Design (CAD) Research Center

This paper explores the characteristics of the intuitive responses that are generated by our brain continuously in an automatic and effortless manner. However, while intuition is a very powerful mechanism, it is also subject to many biasing influences. The author discusses the role of intuition, examines representative examples of biasing influences, compares cognitive theories of intuition advanced by Simon (2002), Klein (2003 and 1999), and Kahneman (2011), and then advances a hypothetical explanation of the neurological operations underlying intuition based on Hebbian rules (Hebb 1949) of plasticity in combination with synergetic principles.


Teaching Systems And Robotics In A Four-Week Summer Short Course, Andrew Danowitz, Bridget Benson, Jeremy Edmonds Jun 2017

Teaching Systems And Robotics In A Four-Week Summer Short Course, Andrew Danowitz, Bridget Benson, Jeremy Edmonds

Computer Science and Software Engineering

This paper describes a four-week summer short-course designed to introduce students with limited hands-on technical experience to the low-level details of embedded systems and robotics. Students start the course using a Raspberry Pi 3 to learn the basics of Linux and programming, and end the course by competing in a capture-the-flag type competition with the web-configurable GPS-guided autonomous robots they designed and tested in the course. Throughout the course, students are introduced to programming languages including Python and PHP, advanced programming concepts such as using sockets for inter-process communication, data interchange formats such as JSON, basic API development, system concepts …


Group Work Versus Informal Collaborations: Student Perspectives, Andrew Danowitz Apr 2017

Group Work Versus Informal Collaborations: Student Perspectives, Andrew Danowitz

Computer Science and Software Engineering

A substantial body of research exists showing that, when implemented correctly, the use of group work in a class can improve student learning outcomes. When implemented incorrectly, however, group-based assignments can lead to dysfunction and inter-personal conflicts that can hamper overall student success. This problem can be especially acute in first and second year engineering fundamentals courses where advanced students who learn the concepts faster may end up completing—and reaping the benefits of—a lions-share of the group work. As the course material starts to build on itself, those students who initially underperformed in their group may lack the understanding to …


Implementing Semantic Document Search Using A Bounded Random Walk In A Probabilistic Graph, Lubomir Stanchev Jan 2017

Implementing Semantic Document Search Using A Bounded Random Walk In A Probabilistic Graph, Lubomir Stanchev

Computer Science and Software Engineering

Given a set of documents and an input query that is expressed using natural language, the problem of document search is retrieving all relevant documents ordered by the degree of relevance. Semantic document search fetches not only documents that contain words from the input query, but also documents that are semantically relevant. For example, the query "friendly pets" will consider documents that contain the words "dog" and "cat", among others. One way to implement semantic search is to use a probabilistic graph in which the input query is connected to the documents through paths that contain semantically similar words and …


Fine-Tuning An Algorithm For Semantic Document Clustering Using A Similarity Graph, Lubomir Stanchev Dec 2016

Fine-Tuning An Algorithm For Semantic Document Clustering Using A Similarity Graph, Lubomir Stanchev

Computer Science and Software Engineering

In this article, we examine an algorithm for document clustering using a similarity graph. The graph stores words and common phrases from the English language as nodes and it can be used to compute the degree of semantic similarity between any two phrases. One application of the similarity graph is semantic document clustering, that is, grouping documents based on the meaning of the words in them. Since our algorithm for semantic document clustering relies on multiple parameters, we examine how fine-tuning these values affects the quality of the result. Specifically, we use the Reuters-21578 benchmark, which contains 11,362 newswire stories …


Leveraging The Final Project To Improve Student Motivation In Introductory Digital Design Courses, Andrew Danowitz Oct 2016

Leveraging The Final Project To Improve Student Motivation In Introductory Digital Design Courses, Andrew Danowitz

Computer Science and Software Engineering

Student retention rates in engineering, especially among traditionally underrepresented groups, remain an obstacle to training a large, diverse engineering workforce. The NSF's Science and Engineering Indicators 2016 indicate that of students entering college with an intent to major in engineering, only 63% graduate with an engineering degree [1]. With research suggesting that misperceptions or a lack of knowledge about what work in a certain field is like can deter students from studying that discipline [2], [3], it is possible that providing a meaningful project experience at the introductory level could provide a strong positive impact on retention rates. This could …


Exploring Mathematical Strategies For Finding Hidden Features In Multi-Dimensional Big Datasets, Tri Duong, Fang Ren, Apurva Mehta Oct 2016

Exploring Mathematical Strategies For Finding Hidden Features In Multi-Dimensional Big Datasets, Tri Duong, Fang Ren, Apurva Mehta

STAR Program Research Presentations

With advances in technology in brighter sources and larger and faster detectors, the amount of data generated at national user facilities such as SLAC is increasing exponentially. Humans have a superb ability to recognize patterns in complex and noisy data and therefore, data is still curated and analyzed by humans. However, a human brain is unable to keep up with the accelerated pace of data generation, and as a consequence, the rate of new discoveries hasn't kept pace with the rate of data creation. Therefore, new procedures to quickly assess and analyze the data are needed. Machine learning approaches are …


Creating A Probabilistic Model For Wordnet, Lubomir Stanchev Sep 2016

Creating A Probabilistic Model For Wordnet, Lubomir Stanchev

Computer Science and Software Engineering

We present a probabilistic model for extracting and storing information from WordNet and the British National Corpus. We map the data into a directed probabilistic graph that can be used to compute the conditional probability between a pair of words from the English language. For example, the graph can be used to deduce that there is a 10% probability that someone who is interested in dogs is also interested in the word “canine”. We propose three ways for computing this probability, where the best results are achieved when performing multiple random walks in the graph. Unlike existing approaches that only …


Optimization And Coding Of A Lcls Control Program, Tanner M. Worden Sep 2016

Optimization And Coding Of A Lcls Control Program, Tanner M. Worden

STAR Program Research Presentations

SLAS’s, Linac Coherent Light Source (LCLS) also known as X-ray free-electron laser (XFEL) is the first X-ray laser of its kind. It gave Scientist from around the world the unique ability to observe the world at a subatomic level. Allowing for major advancements in the field of biological chemistry, drug science, material science and many more. Since the LCLS is a fairly unique scientific instrument, the demand for its use by the scientific community has always been high since it turned on back in 2009. This means that any and all time that the laser is not being used for …


Density Functional Theory Based Electrolyte Design Formulation For Lithium-Sulfur Batteries, Cynthia Ly, Carolyn Sturges, Vijay Murugesan Aug 2016

Density Functional Theory Based Electrolyte Design Formulation For Lithium-Sulfur Batteries, Cynthia Ly, Carolyn Sturges, Vijay Murugesan

STAR Program Research Presentations

Lithium-ion (Li-ion) batteries are commonly used in portable electronics such as cellphones and laptops. Most Li-ion batteries operate on intercalation principle with typical theoretical specific energy of 400-600 (Wh/Kg). There is great scientific interest in lithium-sulfur (Li-S) batteries as a possible successor of traditional Li-ion batteries because Li-S holds the potential of being a very powerful (1550 Wh/kg theoretical specific energy) yet very cost-efficient battery (due the abundance and inexpensiveness of sulfur). However, one major problem in Li-S battery research is the polysulfide “shuttle phenomenon”, which is the shuttling of polysulfide species due to the dissolution of sulfide from the …


Citizen Science Sensor Development - Smap | Soil Moisture Active Passive, Hagop Hovhannesian Aug 2016

Citizen Science Sensor Development - Smap | Soil Moisture Active Passive, Hagop Hovhannesian

STAR Program Research Presentations

“Detailed monitoring of soil moisture provides a view of how our whole Earth system works.”

The Soil Moisture Active Passive (SMAP) satellite mission was launched in January 2015; its main purpose is to acquire global measurements of soil moisture. SMAP partnered with the GLOBE program (Global Learning and Observations to Benefit the Environment), which is an international program where students collect environmental variables in a scientifically methodical way. SMAP readings and maps have various uses in various fields, which include monitoring drought, predicting floods, assisting in crop productivity, and linking water, energy and carbon cycles. The goal of this project …


Reverse-Engineering The Brain: The Parts Are As Complex As The Whole., Jens G. Pohl Aug 2016

Reverse-Engineering The Brain: The Parts Are As Complex As The Whole., Jens G. Pohl

Collaborative Agent Design (CAD) Research Center

The purpose of this paper is to review the current state of neuroscience research with a focus on what has been achieved to date in unraveling the mysteries of brain operations, major research initiatives, fundamental challenges, and potentially realizable objectives. General research approaches aimed at constructing a wiring diagram of the brain (i.e., connectome), determining how the brain encodes and computes information, and whole brain simulation attempts are reviewed in terms of strategies employed and difficulties encountered. While promising advances have been made during the past 50 years due to electron microscopy, the development of new experimental methods, and the …


Automated Detection Of Deep-Sea Animals, Dallas J. Hollis, Duane Edgington, Danelle Cline Jul 2016

Automated Detection Of Deep-Sea Animals, Dallas J. Hollis, Duane Edgington, Danelle Cline

STAR Program Research Presentations

The Monterey Bay Aquarium Research Institute routinely deploys remotely operated underwater vehicles equipped with high definition cameras for use in scientific studies. Utilizing a video collection of over 22,000 hours and the Video Annotation and Reference System, we have set out to automate the detection and classification of deep-sea animals. This paper serves to explore the pitfalls of automation and suggest possible solutions to automated detection in diverse ecosystems with varying field conditions. Detection was tested using a saliency-based neuromorphic selective attention algorithm. The animals that were not detected were then used to tune saliency parameters. Once objects are detected, …


Leveraging New Platforms To Provide Students With A Realistic Soc Design Experience, Andrew Danowitz, Antonio M. Leija Jun 2016

Leveraging New Platforms To Provide Students With A Realistic Soc Design Experience, Andrew Danowitz, Antonio M. Leija

Computer Science and Software Engineering

Recently there have been a slew of digital design products released that promise to simplify the task of giving students a real-world System-on-Chip (SoC) design experience. These “programmable SoCs” from companies such as Xilinx, Cypress, and Altera combine modern multi-core ARM processors connected to an FPGA through a widely used SoC interconnect standard. This paper discusses a Real Time Embedded System Course I designed that uses the Xilinx Zynq platform to give students first-hand experience with modern System-on-Chip design methodologies and the challenges that designers face in both hardware and software bring-up for a modern IP-based design.

The first portion …


Creating A Probabilistic Graph For Wordnet Using Markov Logic Network, Lubomir Stanchev Jun 2016

Creating A Probabilistic Graph For Wordnet Using Markov Logic Network, Lubomir Stanchev

Computer Science and Software Engineering

The paper shows how to create a probabilistic graph for WordNet. A node is created for every word and phrase in WordNet. An edge between two nodes is labeled with the probability that a user that is interested in the source concept will also be interested in the destination concept. For example, an edge with weight 0.3 between “canine” and “dog” indicates that there is a 30% probability that a user who searches for “canine” will be interested in results that contain the word “dog”. We refer to the graph as probabilistic because we enforce the constraint that the sum …


Semantic Document Clustering Using A Similarity Graph, Lubomir Stanchev Feb 2016

Semantic Document Clustering Using A Similarity Graph, Lubomir Stanchev

Computer Science and Software Engineering

Document clustering addresses the problem of identifying groups of similar documents without human supervision. Unlike most existing solutions that perform document clustering based on keywords matching, we propose an algorithm that considers the meaning of the terms in the documents. For example, a document that contains the words "dog" and "cat" multiple times may be placed in the same category as a document that contains the word "pet" even if the two documents share only noise words in common. Our semantic clustering algorithm is based on a similarity graph that stores the degree of semantic relationship between terms (extracted from …


Using Data Visualization Software To Aid In The Analysis Of Geographical Data, Matthew R. Evers, Inzamam Rahaman Aug 2015

Using Data Visualization Software To Aid In The Analysis Of Geographical Data, Matthew R. Evers, Inzamam Rahaman

STAR Program Research Presentations

NASA Web World Wind (Web WW) is designed to visualize and manage geographical data. As a first implementation of visualization and analysis, we designed an application to map earthquake data onto the globe. Portions of this code were merged with application monitoring magnetic field anomalies possibly associated with earthquake precursor activity. Web WW enabled the visualization of the directional vectors from this data to point to the source location of the earthquake. We also developed a prototype urban management application which utilizes OpenStreetMaps to provide simple features such as route navigation, geographical and services information in an area of interest. …