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Articles 1 - 12 of 12
Full-Text Articles in Physical Sciences and Mathematics
Using Particle Swarm Optimization To Generate Optimal Experimental Designs With Replication Structures, Thomsen Bolton
Using Particle Swarm Optimization To Generate Optimal Experimental Designs With Replication Structures, Thomsen Bolton
Student Research Symposium
The modern dominant approach to planning experiments in industrial engineering and manufacturing is optimal design. This is a popular design paradigm because it 1) requires specification of an optimality criterion which incorporates practical objectives as definition of a design with high quality and 2) yields a design via high-dimensional optimization that gives the researcher ‘the most bang for the buck’ for a fixed sample/experimental run size. We aim to adapt the state-of-the-art meta-heuristic optimization algorithm, the Particle Swarm Optimization (PSO), to generating optimal designs with user-specified replication structure. Recently, PSO has been demonstrated to be highly effective at generating candidate …
Generating Optimal Space-Filling Designs With Particle Swarm Optimization, Rebekah Scott
Generating Optimal Space-Filling Designs With Particle Swarm Optimization, Rebekah Scott
Student Research Symposium
In 1935, Ronald Fisher published The Design of Experiments, establishing classical designs for various types of experiments. With the rise of computing power came optimal design, where statisticians can better customize designs according to the needs of the researchers running the experiment. This research focuses on generating optimal MaxMin space-filling designs with particle swarm optimization using various distance metrics (Manhattan, Euclidean, etc). Interestingly, changing the distance metric in the objective function had a minimal effect on the design, except for Aitchison geometry on the simplex. Space-filling designs are optimal for supporting high-order models with only a small sacrifice in prediction …
Fast Computation Of Friction Stir Welding Process With Model Order Reduction And Machine Learning, Joshua Kay
Fast Computation Of Friction Stir Welding Process With Model Order Reduction And Machine Learning, Joshua Kay
Student Research Symposium
Joining aluminum alloys and other metal workpieces is a typical manufacturing process, which can be accomplished by various welding techniques. Friction stir welding (FSW), a relatively new technology patented in 1991, has many advantages over conventional welding processes. For the FSW process, it is desirable to determine an optimal set of parameters to avoid product defects in the joints. Modeling and simulating the FSW process is computationally expensive which creates a bottleneck in searching for optimal operating parameters. Reduced order modeling techniques will be used to significantly reduce computation time for FSW models while maintaining accuracy. In addition, machine learning …
Manifold Alignment With Inter-Domain Diffusion, Andres Duque
Manifold Alignment With Inter-Domain Diffusion, Andres Duque
Student Research Symposium
The integration of multimodal data presents a challenge in cases when the study of a given phenomena by different instruments or conditions generates distinct but related domains. In this paper, we propose Diffusion Transport Alignment (DTA) a semi-supervised manifold alignment method that exploits prior correspondence knowledge between distinct data views. DTA finds a bijection between two domains, which by assumption, share a similar geometrical structure coming from the same underlying data generating process. We empirically demonstrate the effectiveness of our method to integrate multimodal data, as well as how it can improve the performance of machine learning tasks, otherwise less …
Analyzing Suicidal Text Using Natural Language Processing, Cassandra Barton
Analyzing Suicidal Text Using Natural Language Processing, Cassandra Barton
Student Research Symposium
Using Natural Language Processing (NLP), we are able to analyze text from suicidal individuals. This can be done using a variety of methods. I analyzed a dataset of a girl named Victoria that died by suicide. I used a machine learning method to train a different dataset and tested it on her diary entries to classify her text into two categories: suicidal vs non-suicidal. I used topic modeling to find out unique topics in each subset. I also found a pattern in her diary entries. NLP allows us to help individuals that are suicidal and their family members and close …
Modeling The Spread Of Curly Top Disease In Tomato Crops, Rachel Frantz
Modeling The Spread Of Curly Top Disease In Tomato Crops, Rachel Frantz
Student Research Symposium
Curly Top disease (CT), caused by a family of curtoviruses, infects a wide variety of agricultural crops. Historically, CT has caused extensive damage in tomato crops resulting in substantial economic loss for the tomato industry. Control methods for CT are scarce, and methods for predicting and assessing the scope of CT outbreaks are limited. In this paper, we formulate two theoretical models, a deterministic model and a stochastic model, for the spread of CT in a heterogeneous environment consisting of beets (preferred host) and tomatoes. The models are composed of two susceptible classes and two infected classes (infectious beets and …
The Outdoor Fashion Industry Is Not Sustainable, Joshua Hillam
The Outdoor Fashion Industry Is Not Sustainable, Joshua Hillam
Student Research Symposium
Outdoor fashion companies are responsible for a large amount of waste and pollution worldwide. I believe they are ethically bound to make changes in their manufacturing process to decrease their footprint because their products are used in outdoor environments that are impacted negatively by waste and pollution. The fashion industry as a whole is responsible for 10% of the carbon emissions worldwide. Research was conducted by first understanding what being sustainable means from the EPA, from individuals who work in the fashion industry, and from companies that advocate for more sustainable clothing. I then investigated what materials are the most …
Finding Higher Order Interactions Using Local Corex, Thomas Kerby
Finding Higher Order Interactions Using Local Corex, Thomas Kerby
Student Research Symposium
In applications such as financial markets, social networks, and gene expression data, the variables often interact in complex ways. Yet accurately characterizing pairwise variable interactions can be a difficult task, let alone efficiently characterizing complex higher-order interactions, which is an unsolved problem. This difficulty is exacerbated when variable interactions change across the data. For example, gene interactions in single-cell RNA-sequencing (scRNA-seq) data will typically differ from one cell type to another. To solve these problems, we propose a new method called Local Correlation Explanation (CorEx). Local CorEx captures higher-order variable interactions at a local scale by first clustering data points …
Modeling The Extended Low And Sudden High Periods Of Activity In Infectious Diseases, Dana Strong
Modeling The Extended Low And Sudden High Periods Of Activity In Infectious Diseases, Dana Strong
Student Research Symposium
This research explores how the aggregation of individuals during disease spread may, in conjunction with noise, explain how some diseases’ trajectories spend some time at low numbers after which there is a sudden outbreak.
Ensemble Kernel Density Estimation, Ethan Ancell
Ensemble Kernel Density Estimation, Ethan Ancell
Student Research Symposium
The problem of estimating a probability density function from data has many applications in machine learning and data science. Nonparametric estimators are useful in this context as they require relatively few assumptions on the densities. Unfortunately, standard nonparametric methods such as kernel density estimationtend to converge slowly to the true value in high dimensions as a function of the data sample size. Recent work has shown that optimally weighted ensembles of nonparametric estimators can be used to achieve a fast convergence rate when estimating information theoretic functionals such as information divergence. We explore the extension of this theory to density …
Development Of Particle Image Velocimetry Learning Tool: Learnpiv.Org, Kevin Roberts
Development Of Particle Image Velocimetry Learning Tool: Learnpiv.Org, Kevin Roberts
Student Research Symposium
Particle Image Velocimetry (PIV) is an experimental measurement technique used for quantitative and visual analysis of the velocity distribution in a flow field. Researchers conduct PIV by using lasers to illuminate particles in a flow field of interest, digital cameras to record images of these illuminated particles, and PIV software to analyze the recorded images, producing a velocity vector field. Applying proper techniques to gather useful images and identifying PIV processing algorithm parameters to the collected images is a challenging task for novice PIV users who are unaware of the inner workings of PIV algorithms. Recognizing this problem, we created …
Role And Responsibilities Of State Cooperative Extension Services For Wildlife Damage Control, James L. Byford
Role And Responsibilities Of State Cooperative Extension Services For Wildlife Damage Control, James L. Byford
Wildlife Damage Management Conference
The Cooperative Extension Service was established by the Smith-Lever Act in 1914. It was designed to improve the lives of people, through education in: agriculture, natural resources, home economics and community development. Its audiences include both adult and youth. 4-H is the primary youth audience. The Cooperative Extension Service is an "extension" of the Land employees include university faculty (specialists) and professional agents in every county, in every state in the country. Extension's primary mission is to conduct an educational program, using research-based information. Research results are condensed into a form that the average person can understand. The role of …