Data Science Commons^™

Toward A Manifold Encoding Neural Responses, Luciano Dyballa, Andra M. Rudzite, Mahmood S. Hoseini, Mishek Thapa, Michael P. Stryker, Greg D. Field, Steven W. Zucker

MODVIS Workshop

Understanding circuit properties from physiological data presents two challenges: (i) recordings do not reveal connectivity, and (ii) stimuli only exercise circuits to a limited extent. We address these challenges for the mouse visual system with a novel neural manifold obtained using unsupervised algorithms. Each point in our manifold is a neuron; nearby neurons respond similarly in time to similar parts of a stimulus ensemble. This ensemble includes drifting gratings and flows, i.e., patterns resembling what a mouse would “see” running through fields.

Regarding (i), our manifold differs from the standard practice in computational neuroscience: embedding trials in neural coordinates. Topology …

Ptmtorrent: A Dataset For Mining Open-Source Pre-Trained Model Packages, Wenxin Jiang, Nicholas Synovic, Purvish Jajal, Taylor R. Schorlemmer, Arav Tewari, Bhavesh Pareek, George K. Thiruvathukal, James C. Davis

Computer Science: Faculty Publications and Other Works

Due to the cost of developing and training deep learning models from scratch, machine learning engineers have begun to reuse pre-trained models (PTMs) and fine-tune them for downstream tasks. PTM registries known as “model hubs” support engineers in distributing and reusing deep learning models. PTM packages include pre-trained weights, documentation, model architectures, datasets, and metadata. Mining the information in PTM packages will enable the discovery of engineering phenomena and tools to support software engineers. However, accessing this information is difficult — there are many PTM registries, and both the registries and the individual packages may have rate limiting for accessing …

Pruning Ghsom To Create An Explainable Intrusion Detection System, Thomas Michael Kirby

Theses and Dissertations

Intrusion Detection Systems (IDS) that provide high detection rates but are black boxes lead
to models that make predictions a security analyst cannot understand. Self-Organizing Maps
(SOMs) have been used to predict intrusion to a network, while also explaining predictions through
visualization and identifying significant features. However, they have not been able to compete with
the detection rates of black box models. Growing Hierarchical Self-Organizing Maps (GHSOMs)
have been used to obtain high detection rates on the NSL-KDD and CIC-IDS-2017 network traffic
datasets, but they neglect creating explanations or visualizations, which results in another black
box model.
This paper offers …

An Analysis Of Text-Based Machine Learning Models For Vulnerability Detection, Kollin Ryne Napier

Theses and Dissertations

With an increase in complexity of software, developers rely more on reuse and dependencies in their source code via code snippets. As a result, it is becoming harder to identify and mitigate vulnerabilities. Although traditional analysis tools are still utilized, machine learning models are being adopted to expand efforts and combat such threats. Given the possibilities towards usage of such models, research in this area has introduced various approaches which vary in usability and prediction. In generalizing models to a more natural language approach, researchers have opted to train models on source code to identify existing and potential vulnerabilities. Exploratory …

Locomotion And Life History In A Leaping Primate: Mechanics And Energetics Of Movement Throughout The Propithecus Lifespan, Nicholas Heslep

Masters Theses, 2020-current

Arboreal primates are typically altricial, exhibit long juvenile periods, and use dynamic locomotor behaviors that can be challenging and risky. Sifaka (Propithecus verreauxi) have particularly slow life histories for their size, with long juvenile periods, protracted reproductive careers, and long life spans. Slow somatic growth poses potential mechanical challenges for juvenile sifaka who use thigh-powered vertical clinging and leaping to follow group members during travel. I examined mechanical and energetic costs of movement in developing sifaka. I instrumented 8 wild sifaka (3 yearlings, 3 subadults, 2 adults) in 4 social groups with inertial sensors measuring tri-axial acceleration for …

Big Ideas In Sports Analytics And Statistical Tools For Their Investigation, Benjamin S. Baumer, Gregory J. Matthews, Quang Nguyen

Statistical and Data Sciences: Faculty Publications

Sports analytics—broadly defined as the pursuit of improvement in athletic performance through the analysis of data—has expanded its footprint both in the professional sports industry and in academia over the past 30 years. In this article, we connect four big ideas that are common across multiple sports: the expected value of a game state, win probability, measures of team strength, and the use of sports betting market data. For each, we explore both the shared similarities and individual idiosyncracies of analytical approaches in each sport. While our focus is on the concepts underlying each type of analysis, any implementation necessarily …

A Recommender System For Movie Ratings With Matrix Factorization Algorithm, Amir Alipour Yengejeh

Data Science and Data Mining

Nowadays, a Recommender System is a technology
that aims to predict preferences based on the user’s selections.
These systems are applied in numerous fields, such as movies,
music, news, books, research articles, search queries, social tags,
and various products. In this study, we use this potential tool to
predict the ratings of users’ preferences in MovieLens datasets. To
do so, we applied the matrix factorization algorithm and calculate
the RMSE as our evaluation metric. The results represent that
RMSE estimated for the train and test set are 0.83 and 0.93 that
are very close one another. This results indicates that …

Genome-Wide Association Study Of The Maize Crop By The Lasso Regression Analysis, Amir Alipour Yengejeh

Data Science and Data Mining

The accurate estimation of the male flowering period in Maize crops is key for the prediction crop fertility. The recent scientific investigations has shown that the genetic single nucleotic polymorphism (SNP) can contribute in this regard. The genomewide association study (GWAS) is employed to generate these attributes (SNP). But it caused a high-dimensional data in which 4,981 observations with 7,389 SNP attributes. Hence, in this study, we used the penalized regression approach with the least absolute shrinkage and selection operator (Lasso) to reduce the dataset. In this regard, we set the regularization parameter to 0.21. It resulted in a set …

Analysis Of Credit Approval By Decision Tree, Amir Alipour Yengejeh

Data Science and Data Mining

Nowadays, machine learning algorithms are com-
monly used by the financial institutions or bankers to evaluate
the applications’ requires for credit card. In this study, we used
the decision tree algorithm to predict credit card approval based
on the other associated features applicants like age, employment
status, Education Level, etc. Our results shows that the applicants’
Prior Default and Debt, and Employed have more contribution
in the credit card approval.

Movie Recommender System Using Matrix Factorization, Roland Fiagbe

Data Science and Data Mining

Recommendation systems are a popular and beneficial field that can help people make informed decisions automatically. This technique assists users in selecting relevant information from an overwhelming amount of available data. When it comes to movie recommendations, two common methods are collaborative filtering, which compares similarities between users, and content-based filtering, which takes a user’s specific preferences into account. However, our study focuses on the collaborative filtering approach, specifically matrix factorization. Various similarity metrics are used to identify user similarities for recommendation purposes. Our project aims to predict movie ratings for unwatched movies using the MovieLens rating dataset. We developed …

Mesoporous Silica Nanoparticles As A Gene Delivery Platform For Cancer Therapy, Nisar Ul Khaliq, Juyeon Lee, Joohyeon Kim, Yejin Kim, Sohyeon Yu, Jisu Kim, Sangwoo Kim, Daekyung Sung, Hyungjun Kim

Faculty, Staff and Student Publications

Cancer remains a major global health challenge. Traditional chemotherapy often results in side effects and drug resistance, necessitating the development of alternative treatment strategies such as gene therapy. Mesoporous silica nanoparticles (MSNs) offer many advantages as a gene delivery carrier, including high loading capacity, controlled drug release, and easy surface functionalization. MSNs are biodegradable and biocompatible, making them promising candidates for drug delivery applications. Recent studies demonstrating the use of MSNs for the delivery of therapeutic nucleic acids to cancer cells have been reviewed, along with their potential as a tool for cancer therapy. The major challenges and future interventions …

Accessible And Functional Visualizations For Exploring And Analyzing The Writing And Programming Process, Shaney Flores

Theses

Background. Developing easily decodable and insightful visuals is a challenge in the field of data visualization. This challenge becomes more pronounced when the data is of a complex nature. Good visualizations clearly convey their data using designs with appropriate encoding, visual attributes (i.e., color, shape, size, etc.), and accessibility features (e.g., distinctive colors for color-blind individu- als). One area where well-designed visualizations can make a significant impact is elucidating the learning process. Users ranging from self-taught individuals to students enrolled in coursework could use such visuals to detect problematic areas in their process of learning skills such as writing …

Do Integrated Circuits Make For An Integrated Supply Chain? A Network Analysis Of Trade Flows, Noah Martens

Electronic Theses and Dissertations

Integrated circuits (colloquially referred to as chips) are an increasingly critical commodity experiencing continuous and substantial rises in demand. These increases in demand recently resulted in shortages. This paper seeks to understand the market for chips and construct a framework by which a network analysis of trade flows can evaluate concentration in the international market for a particular product category. Leveraging this framework and proposing a new model, I evaluate the level and nature of concentration in the chips sector, as well as two key inputs to the manufacturing process, silicon and chip fabricators. I find moderate-to-high levels of concentration …

A Vlp-Based Vaccine Displaying Hbha And Mtp Antigens Of Mycobacterium Tuberculosis Induces Potentially Protective Immune Responses In M Tuberculosis H37ra Infected Mice, Juan Wang, Tao Xie, Inayat Ullah, Youjun Mi, Xiaoping Li, Yang Gong, Pu He, Yuqi Liu, Fei Li, Jixi Li, Zengjun Lu, Bingdong Zhu

Faculty, Staff and Student Publications

Heparin-binding hemagglutinin (HBHA) and M. tuberculosis pili (MTP) are important antigens on the surface of Mycobacterium tuberculosis. To display these antigens effectively, the fusion protein HBHA-MTP with a molecular weight of 20 kD (L20) was inserted into the receptor-binding hemagglutinin (HA) fragment of influenza virus and was expressed along with matrix protein M1 in Sf9 insect cells to generate influenza virus-like particles (LV20 in short). The results showed that the insertion of L20 into the envelope of the influenza virus did not affect the self-assembly and morphology of LV20 VLPs. The expression of L20 was successfully verified by transmission …

A Probabilistic Exploration Of Food Supplementation And Assistance, Logan Mattingly

Honors College Theses

Food insecurity is a stark threat that grips our country and affects households throughout our country. Dietary insufficiency manifests itself in ways that affect health and public safety. According to researchers, individuals who suffer from food insecurity have a higher risk of aggression, anxiety, suicide ideation and depression. These problems tend to occur unequally distributed among those households with lower income. In this work, an exploratory analysis within these data sets will be performed to examine the socio-economic, biographical, nutritional, and geographical principal components of food insecurity among survey participants and how the US Supplemental Nutrition Assistance Program (SNAP) effects …

Dense & Attention Convolutional Neural Networks For Toe Walking Recognition, Junde Chen, Rahul Soangra, Marybeth Grant-Beuttler, Y. A. Nanehkaran, Yuxin Wen

Physical Therapy Faculty Articles and Research

Idiopathic toe walking (ITW) is a gait disorder where children’s initial contacts show limited or no heel touch during the gait cycle. Toe walking can lead to poor balance, increased risk of falling or tripping, leg pain, and stunted growth in children. Early detection and identification can facilitate targeted interventions for children diagnosed with ITW. This study proposes a new one-dimensional (1D) Dense & Attention convolutional network architecture, which is termed as the DANet, to detect idiopathic toe walking. The dense block is integrated into the network to maximize information transfer and avoid missed features. Further, the attention modules are …

Hawk Mountain Raptor Migration Phenology’S Relation To Weather, Eric Burgos

Computer Science and Information Technology Faculty

We have been studying year-round raptor migration phenology across the United States and North America for multiple decades now. Hawk Mountain Sanctuary’s Autumn migration hawk count began in 1934 and is the longest running raptor migration count in the world. A decline in total raptor counts passing through Hawk Mountain’s North Lookout is well documented and much research has already been done in what could be the main causes for this decrease in counts year-over-year. We know that cold front passages have long been associated with autumnal migration in northeastern North America. Using updated analysis techniques, we examined 60 years’ …

Integration Of Computer Algebra Systems And Machine Learning In The Authoring Of The Sanyms Intelligent Tutoring System, Sam Ford

Computational and Data Sciences (PhD) Dissertations

Computer-based feedback is an increasingly common tool in mathematics education. The feedback that such programs provide can range from indicating whether an answer was correct, to giving an answer or worked out solution or suggesting a similar practice problem. One type of computer-based feedback, the Intelligent Tutoring Systems (ITS), is able to provide feedback not just once per problem, but at multiple points during the process of solving a problem. Creating an ITS that gives feedback for even a narrow topic is often a time-intensive process, and machine learning is only recently being integrated into the ITS authoring process.

We …

Consumers' Perceptions Of Digital Privacy In The United States And Japan, Destiny Randle

Whittier Scholars Program

The purpose of my study is to explore the contours of contemporary consumer privacy protections derived from legislation, regulations and publicly available company policies as a way to get a better understanding of how consumer data is protected. A few examples ranging from company-based consumer protection in the United States to data breaches in Japan will be explored and examined. Finally, this paper includes a comparative survey of consumer perceptions and concerns related to personal data privacy in the U.S. and Japan. As a way to assess the degree to which digital privacy and personal data breaches have adversely influenced …

Brif: A Novel And Efficient Implementation Of Random Forests Based On Bit Packing And Parallel Computing, Yanchao Liu

Industrial and Systems Engineering Faculty Research Publications

Random forests are powerful and popular machine learning methods. While general principles of tree induction are straightforward and well-understood, the numerous algorithmic treatments implemented in software tools, as well as their impacts on performance, are less familiar to most users. This paper introduces a new random forest toolkit (the ‘brif’ package in R and Python) along with its key algorithmic design features, and demonstrates the effects of the forest’s hyper-parameters such as the split search method, tree depth and the voting mechanism, on the classification performance. Summaries of benchmarking experiments are also presented. Results show that ‘brif’ stands out among …