Digital Commons Network^™

Tensor Z -Transform, Shih Yu Chang, Hsiao Chun Wu

Faculty Research, Scholarly, and Creative Activity

The multi-input multioutput (MIMO) systems involving multirelational signals generated from distributed sources have been emerging as the most generalized model in practice. The existing work for characterizing such a MIMO system is to build a corresponding transform tensor, each of whose entries turns out to be the individual z-transform of a discrete-time impulse response sequence. However, when a MIMO system has a global feedback mechanism, which also involves multirelational signals, the aforementioned individual z-transforms of the overall transfer tensor are quite difficult to formulate. Therefore, a new mathematical framework to govern both feedforward and feedback MIMO systems is in crucial …

Fpdclustering: A Comprehensive R Package For Probabilistic Distance Clustering Based Methods, Cristina Tortora, Francesco Palumbo

Faculty Research, Scholarly, and Creative Activity

Data clustering has a long history and refers to a vast range of models and methods that exploit the ever-more-performing numerical optimization algorithms and are designed to find homogeneous groups of observations in data. In this framework, the probability distance clustering (PDC) family methods offer a numerically effective alternative to model-based clustering methods and a more flexible opportunity in the framework of geometric data clustering. Given nJ-dimensional data vectors arranged in a data matrix and the number K of clusters, PDC maximizes the joint density function that is defined as the sum of the products between the distance and the …

A Comparative Multivariate Analysis Of Var And Deep Learning-Based Models For Forecasting Volatile Time Series Data, Saroj Gopali, Sima Siami-Namini, Faranak Abri, Akbar Siami Namin

Faculty Research, Scholarly, and Creative Activity

The existing literature on forecasting time series data is primarily based on univariate analysis and techniques such as Univariate Autoregressive (UAR), Univariate Moving Average (UMA), Simple Exponential Smoothing (SES), deep learning models, and, most notably, univariate Long Short-Term Memory (LSTM) built based on univariate variable where the next lag of time series is leveraged for forecasting the next cycle of data. This paper takes this line of research to the next level by focusing on forecasting time series data based on “multivariate” modeling and analysis. To have a better insight of the performance of various deep learning-based models when multivariate …

Anti-Trafficking And Humanitarian Operations: Transferring Learnings For A Better World, Kezban Yagci Sokat, Maria Besiou

Faculty Research, Scholarly, and Creative Activity

Purpose: The purpose of this study is twofold: first, to draw insights from the rich literature on humanitarian operations efforts to combat human trafficking; second, to inspire humanitarian operations researchers to work more on human anti-trafficking. Design/methodology/approach: This is a conceptual paper inspired by recent relevant reports, the academic literature and the authors’ years of involvement in both humanitarian operations and anti-trafficking. Findings: Humanitarian supply chains and human trafficking supply chains very often operate in the same environments and hence face similar challenges. The paper highlights the overlaps between the two domains and demonstrates how two decades of learnings from …

Assessment Of Digital Collaboration Skills, Esperanza Huerta, Ana Lidia Franzoni Velázquez, Scott Jensen

Faculty Research, Scholarly, and Creative Activity

This exploratory study proposes a methodology for assessing digital collaboration skills based on the students' actual behavior. Students' comments using a digital collaboration tool during a one-month long project were manually coded. This methodology is not context specific and can be used across different domains. This assessment contrasts with self-reported measures in which students rate themselves as already possessing collaboration skills. Finally, the study explores the use of generative AI to automatically code student's comments to alleviate the labor-intensive process that coding requires and to enable scalability in coding data.

Correction To: A Fresh Take: Seasonal Changes In Terrestrial Freshwater Inputs Impact Salt Marsh Hydrology And Vegetation Dynamics (Estuaries And Coasts, (2024), 10.1007/S12237-024-01392-1), Maya S. Montalvo, Emilio Grande, Anna E. Braswell, Ate Visser, Bhavna Arora, Erin C. Seybold, Corianne Tatariw, John C. Haskins, Charlie A. Endris, Fuller Gerbl, Mong Han Huang, Darya Morozov, Margaret A. Zimmer

Faculty Research, Scholarly, and Creative Activity

In the original online version of the article the following information was missing from the Funding section: Department of Energy, Small Business Innovation Research Award Number DE-SC0021480. In addition, the following was missing from the Acknowledgements: The authors would like to thank Elkhorn Slough Foundation for providing and facilitating the opportunity to conduct this work at the Cowell Ranch site. Also, the study site noted in the Background section was incorrect. The study was conducted at the Elkhorn Slough on the property of the Elkhorn Slough Foundation. The original article was corrected.

Modeling And Vibration Suppression Of Rotating Machines Using The Sparse Identification Of Nonlinear Dynamics And Terminal Sliding Mode Control, Sina Piramoon, Mohammad Ayoubi, Saeid Bashash

Faculty Research, Scholarly, and Creative Activity

This paper presents a novel physics-based data-driven approach for reconstructing the nonlinear governing equations and suppressing vibrations in vertical-shaft rotary machines during transient motion. We first identify the key nonlinear terms using a physics-based methodology. Subsequently, a data-driven approach, known as the Sparse Identification of Nonlinear Dynamical Systems (SINDy), is employed to reconstruct the nonlinear governing equations of a typical rotary machine. After validating the model, a robust nonlinear controller is designed using the terminal sliding mode control (TSMC) technique to reduce lateral vibrations in the machine’s shaft. Extensive experimental tests on a laboratory-scale rotary system confirm the stability and …

Computer Vision Intelligence Test Modeling And Generation: A Case Study On Smart Ocr, Jing Shu, Bing Jiun Miu, Eugene Chang, Jerry Gao, Jun Liu

Faculty Research, Scholarly, and Creative Activity

AI-based systems possess distinctive characteristics and introduce challenges in quality evaluation at the same time. Consequently, ensuring and validating AI software quality is of critical importance. In this paper, we present an effective AI software functional testing model to address this challenge. Specifically, we first present a comprehensive literature review of previous work, covering key facets of AI software testing processes. We then introduce a 3D classification model to systematically evaluate the image-based text extraction AI function, as well as test coverage criteria and complexity. To evaluate the performance of our proposed AI software quality test, we propose four evaluation …

Predictive Modeling In Healthcare, Ibrahim Essa Abdulla Ali Alattar

Theses

Predictive modelling, especially the use of horizontal lines, has become an important tool in clinical practice to help make informed decisions and accurate predictions. This study focuses on the use of horizontal regression in clinical practice, evaluating its effectiveness in revealing patterns and improving the accuracy of predictions. This study introduces the process of developing a linear model, emphasizing the importance of preliminary data analysis, feature selection, and model evaluation. To make sure your model's predictions are accurate, consider key assumptions such as sampling, independence, and homoscedasticity. The main goal is to provide doctors with the knowledge and skills needed …

Boxes And Tangled Tetrahedra, Hidefumi Katsuura

Faculty Research, Scholarly, and Creative Activity

The twin tetrahedron of a given tetrahedron is obtained by circumscribing it by a parallelepiped. However, in general, it is not easy to construct a box that circumscribes a tetrahedron. Actually, constructing a box is equivalent of finding two tangled tetrahedra. We first establish a theorem to construct tangled tetrahedra circumscribed in a box with concurrent diagonals. This generalizes the idea of twin tetrahedra circumscribed in a parallelepiped. And we show that two tetrahedra are twins if and only if they are tangled with concurrent diagonals at the centroid of one of the tetrahedra. We establish a theorem in order …

Glacial Deposits, Vol. 48, 2024, Department Of Geography, Geology, And The Environment

Glacial Deposits

Newsletter of the Department of Geography, Geology, and the Environment

Participation In Collaborative Fisheries Research Improves The Perceptions Of Recreational Anglers Towards Marine Protected Areas, Erin M. Johnston, Grant T. Waltz, Rosamaria Kosaka, Ellie M. Brauer, Shelby L. Ziegler, Erica T. Jarvis Mason, Hunter S. Glanz, Lauren Zaragoza, Allison N. Kellum, Rachel O. Brooks, Brice X. Semmens, Christopher J. Honeyman, Jennifer E. Caselle, Lyall F. Bellquist, Sadie L. Small, Steven G. Morgan, Timothy J. Mulligan, Connor L. Coscino, Jay M. Staton

Faculty Research, Scholarly, and Creative Activity

Collaborative fisheries research programs engage stakeholders in data collection efforts, often with the benefit of increasing transparency about the status and management of natural resources. These programs are particularly important in marine systems, where management of recreational and commercial fisheries have historically been contentious. One such program is the California Collaborative Fisheries Research Program (CCFRP), which was designed in 2006 to engage recreational anglers in the scientific process and evaluate the efficacy of California’s network of marine protected areas. CCFRP began on the Central Coast of California and expanded statewide in 2017 to include six partner institutions in three regions: …

Fuzzy Similarity Analysis Of Effective Training Samples To Improve Machine Learning Estimations Of Water Quality Parameters Using Sentinel-2 Remote Sensing Data, Alireza Taheri Dehkordi, Mohammad Javad Valadan Zoej, Ali Mehran, Mohsen Jafari, Amir Masoud Chegoonian

Faculty Research, Scholarly, and Creative Activity

Continuous monitoring of water quality parameters (WQPs) is crucial due to the global degradation of water quality, primarily caused by climate change and population growth. Typically, machine learning (ML) models are employed to retrieve WQPs, but they require a large amount of training samples to accurately capture the data relationships. Even with sufficient training data, discrepancies still exist between values of predicted and in-situ WQPs. This study proposes a fuzzy similarity analysis (FSA) technique to enhance ML estimates of WQPs by using the prediction errors in effective training samples. The method was successfully applied to retrieve turbidity (Turb) and specific …

Characterization Of Curing Kinetics Of An Anisotropic Conductive Adhesive Using Rheology And Differential Scanning Calorimetry, Connor Kirkpatrick

Theses

A kinetic study performed to further the understanding of a novel magnetically aligned anisotropic conductive adhesive (ACA) was performed using differential scanning calorimetry (DSC) and a rheometer, under both isothermal and non-isothermal conditions. Isothermal data was collected at 70, 80, and 90°C, whereas non-isothermal data was collected at 5, 10, 20, and 30°C/min, with results interpreted through the use of an autocatalytic model. For isothermal experiments, the rate of conversion was found to increase with increasing isothermal curing temperature, and this was reflected in the kinetic rate constant. Moreover, the rate constant determined by DSC was found to range from …

The Evolving Role Of Libraries In The Fourth Industrial Revolution: Navigating Digital Transformation, Abdullahi Olayinka Isiaka, Abdulfatai Soliu, Biliamin Abiola Aremu, Benjamin Adebisi Bamidele, Saidu Saba-Jibril, Adelani Rotimi Ibitoye

Library Philosophy and Practice (e-journal)

Abstract

This article explores the transformative impact of the Fourth Industrial Revolution (4IR) on libraries and their pivotal role in navigating the challenges and opportunities brought forth by rapid technological advancements. Libraries, traditionally perceived as repositories of books and information, are undergoing a profound metamorphosis in the digital age. The 4IR, characterized by breakthroughs in Artificial Intelligence, the Internet of Things, and Data Analytics, demands a redefinition of the library’s purpose and services. The first section introduces the concept of the 4IR and its key technological advancements. Emphasis is placed on understanding the dynamic landscape of the 4IR and the …

Predictability And Adaptation In Law And Other Markets (Chapter In A Coming Book: Research Handbook On Law And Time), Saul Levmore

Coase-Sandor Institute for Law & Economics Research Paper Series

People and enterprises that are subject to the law find it useful to know what the law is at present, but then also to anticipate future rules. If laws are stable this is easily done. Stability is more common where the judicial branch is concerned, because precedents are often valued, and for good reason. They are more often followed by judges than by those involved in other methods of lawmaking. But in all of lawmaking, and even in the private sphere, there is value to consistency and certainty. And yet, surprises can be attractive if they are not confronted on …

Integration Of Blockchain And Cryptographic Techniques For Location Based Services, Rashed Al Shamali

Theses

As digital systems continue to evolve in complexity, protecting user identities and ensuring the secure transmission of data has become paramount. Conventional techniques such as passwords and digital signatures are often insufficient to address modern security threats unless paired with more sophisticated technologies. This thesis proposes a framework that integrates Blockchain Technology with Elliptic Curve Cryptography (ECC) to fortify identity verification protocols and enhance location-obscuring methods. Blockchain’s inherent features of decentralization, immutability, and non-repudiation makes it an ideal platform for secure data exchange. When combined with ECC, which provides robust encryption with smaller key sizes, the system achieves a heightened …

The Statewide Standard, 2024, College Of Education

The Statewide Standard

No abstract provided.

Maximizing The Number Of H-Colorings Of Graphs With A Fixed Minimum Degree, John Engbers

Mathematical and Statistical Science Faculty Research and Publications

For graphs G and H, an H-coloring of G is an adjacency-preserving map from the vertex set of G to the vertex set of H.

A Model For Community-Driven Development Of Best Practices: The Ocean Observatories Initiative Biogeochemical Sensors Data Best Practices And User Guide, Hilary I. Palevsky, Sophie Clayton, Heather Benway, Mairead Maheigan, Dariia Atamanchuk, Roman Battisi, Jennifer Batryn, Annie Bourbonnais, Ellen M. Briggs, Filipa Carvalho, Alison P. Chase, Rachel Eveleth, Rob Fatland, Kristen E. Fogaren, Jonathan Peter Fram, Susan E. Hartman, Isabela Le Bras, Cara C. M. Manning, Joseph A. Needoba, Merrie Beth Neely, Hilde Oliver, Andrew C. Reed, Jennie E. Rheuban, Christina Schallenberg, Ian Walsh, Christopher Wingard, Kohen Bauer, Baoshen Chen, Jose Cuevas, Susana Flecha, Micah Horwith, Melissa Melendez, Tyler Menz, Sara Rivero-Calle, Nicholas P. Roden, Tobias Steinhoff, Paulo Nicolás Trucco-Pignata, Michael F. Vardaro, Meg Yoder

OES Faculty Publications

The field of oceanography is transitioning from data-poor to data-rich, thanks in part to increased deployment of in-situ platforms and sensors, such as those that instrument the US-funded Ocean Observatories Initiative (OOI). However, generating science-ready data products from these sensors, particularly those making biogeochemical measurements, often requires extensive end-user calibration and validation procedures, which can present a significant barrier. Openly available community-developed and -vetted Best Practices contribute to overcoming such barriers, but collaboratively developing user-friendly Best Practices can be challenging. Here we describe the process undertaken by the NSF-funded OOI Biogeochemical Sensor Data Working Group to develop Best Practices for …

Interpreting An Archaean Paleoenvironment Through 3d Imagery Of Microbialites, Cecilia M. Howard, Nathan D. Sheldon, Selena Y. Smith, Nora Noffke

OES Faculty Publications

While stromatolites, and to a lesser extent thrombolites, have been extensively studied in order to unravel Precambrian (>539 Ma) biological evolution, studies of clastic-dominated microbially induced sedimentary structures (MISS) are relatively scarce. The lack of a consolidated record of clastic microbialites creates questions about how much (and what) information on depositional and taphonomic settings can be gleaned from these fossils. We used μCT scanning, a non-destructive X-ray-based 3D imaging method, to reconstruct morphologies of ancient MISS and mat textures in two previously described coastal Archaean samples from the ~3.48 Ga Dresser Formation, Pilbara, Western Australia. The aim of this …

Revisiting Rockafellar’S Theorem On Relative Interiors Of Convex Graphs With Applications To Convex Generalized Differentiation, Boris S. Mordukhovich, Nguyen Mau Nam, Dang Van Cuong, G. Sandine

Mathematics and Statistics Faculty Publications and Presentations

In this paper we revisit a theorem by Rockafellar on representing the relative interior of the graph of a convex set-valued mapping in terms of the relative interior of its domain and function values. Then we apply this theorem to provide a simple way to prove many calculus rules of generalized differentiation for set-valued mappings and nonsmooth functions in finite dimensions. Using this important theorem by Rockafellar allows us to improve some results on generalized differentiation of set-valued mappings in [13] by replacing the relative interior qualifications on graphs with qualifications on domains and/or ranges.

Proof Of The Kresch-Tamvakis Conjecture, John Caughman, Taiyo S. Terada

Mathematics and Statistics Faculty Publications and Presentations

In this paper we resolve a conjecture of Kresch and Tamvakis.

Is Now A(Nother) Teachable Moment Honoring The Memory Of Dr. William S. Spriggs, Francine J. Lipman

Scholarly Works

No abstract provided.

Deep Adaptive Graph Clustering Via Von Mises-Fisher Distributions, Pengfei Wang, Daqing Wu, Chong Chen, Kunpeng Liu, Yanjie Fu, Jianqiang Huang, Yuanchun Zhou, Jianfeng Zhan, Xiansheng Hua

Computer Science Faculty Publications and Presentations

Graph clustering has been a hot research topic and is widely used in many fields, such as community detection in social networks. Lots of works combining auto-encoder and graph neural networks have been applied to clustering tasks by utilizing node attributes and graph structure. These works usually assumed the inherent parameters (i.e., size and variance) of different clusters in the latent embedding space are homogeneous, and hence the assigned probability is monotonous over the Euclidean distance between node embeddings and centroids. Unfortunately, this assumption usually does not hold since the size and concentration of different clusters can be quite different, …

Optical Coherence Elastography Measures The Biomechanical Properties Of The Ex Vivo Porcine Cornea After Lasik, Achuth Nair, Fernando Zvietcovich, Manmohan Singh, Mitchell P Weikert, Salavat R Aglyamov, Kirill V Larin

Faculty, Staff and Students Publications

SIGNIFICANCE: The biomechanical impact of refractive surgery has long been an area of investigation. Changes to the cornea structure cause alterations to its mechanical integrity, but few studies have examined its specific mechanical impact.

AIM To quantify how the biomechanical properties of the cornea are altered by laser assisted in situ keratomileusis (LASIK) using optical coherence elastography (OCE) in ex vivo porcine corneas.

APPROACH: Three OCE techniques, wave-based air-coupled ultrasound (ACUS) OCE, heartbeat (Hb) OCE, and compression OCE were used to measure the mechanical properties of paired porcine corneas, where one eye of the pair was left untreated, and the …

Metabolink Is A Novel Algorithm For Unveiling Cell-Specific Metabolic Pathways In Longitudinal Datasets, Jared Lichtarge, Gerarda Cappuccio, Soumya Pati, Alfred Kwabena Dei-Ampeh, Senghong Sing, Lihua Ma, Zhandong Liu, Mirjana Maletic-Savatic

Duncan NRI Faculty and Staff Publications

Introduction: In the rapidly advancing field of 'omics research, there is an increasing demand for sophisticated bioinformatic tools to enable efficient and consistent data analysis. As biological datasets, particularly metabolomics, become larger and more complex, innovative strategies are essential for deciphering the intricate molecular and cellular networks.

Methods: We introduce a pioneering analytical approach that combines Principal Component Analysis (PCA) with Graphical Lasso (GLASSO). This method is designed to reduce the dimensionality of large datasets while preserving significant variance. For the first time, we applied the PCA-GLASSO algorithm (i.e., MetaboLINK) to metabolomics data derived from Nuclear Magnetic Resonance (NMR) spectroscopy …

A Use Case Of Chatgpt: Summary Of An Expert Panel Discussion On Electronic Health Records And Implementation Science, Seppo T Rinne, Julian Brunner, Timothy P Hogan, Jacqueline M Ferguson, Drew A Helmer, Sylvia J Hysong, Grace Mckee, Amanda Midboe, Megan E Shepherd-Banigan, A Rani Elwy

Center for Medical Ethics and Health Policy Staff Publications

Objective: Artificial intelligence (AI) is revolutionizing healthcare, but less is known about how it may facilitate methodological innovations in research settings. In this manuscript, we describe a novel use of AI in summarizing and reporting qualitative data generated from an expert panel discussion about the role of electronic health records (EHRs) in implementation science.

Materials and methods: 15 implementation scientists participated in an hour-long expert panel discussion addressing how EHRs can support implementation strategies, measure implementation outcomes, and influence implementation science. Notes from the discussion were synthesized by ChatGPT (a large language model-LLM) to generate a manuscript summarizing the discussion, …

Twenty Years Of Epithelial-Mesenchymal Transition: A State Of The Field From Temtia X, Pierre Savagner, Thomas Brabletz, Chonghui Cheng, Christine Gilles, Tian Hong, Myriam Polette, Guojun Sheng, Marc P Stemmler, Erik W Thompson

Faculty, Staff and Students Publications

This report summarizes the 10th biennial meeting of The Epithelial Mesenchymal Transition International Association (TEMTIA), that took place in Paris on November 7-10, 2022. It provides a short but comprehensive introduction to the presentations and discussions that took place during the 3-day meeting. Similarly to previous TEMTIA meetings, TEMTIA X reviewed the most recent aspects of the epithelial-mesenchymal transition (EMT), a cellular process involved during distinct stages of development but also during wound healing and fibrosis to some degree. EMT has also been associated at various levels during tumor cell progression and metastasis. The meeting emphasized the intermediate stages of …

Efficacy Of Etripamil Nasal Spray For Acute Conversion Of Supraventricular Tachycardia: A Network Meta-Analysis, Adam Macech, Nicola Luigi Bragazzi, Francesco Chirico, Basar Cander, Michal Pruc, Zubaid Rafique, William Frank Peacock, Arash Ziapour, Lukasz Szarpak, Anna Salak, Milosz J Jaguszewski

Faculty, Staff and Students Publications

No abstract provided.