Digital Commons Network^™

Causal Discovery With Latent Confounders Based On Higher-Order Cumulants, Ruichu Cai, Zhiyi Huang, Wei Chen, Zhifeng Hao, Kun Zhang

Machine Learning Faculty Publications

Causal discovery with latent confounders is an important but challenging task in many scientific areas. Despite the success of some overcomplete independent component analysis (OICA) based methods in certain domains, they are computationally expensive and can easily get stuck into local optima. We notice that interestingly, by making use of higher-order cumulants, there exists a closed-form solution to OICA in specific cases, e.g., when the mixing procedure follows the One-Latent-Component structure. In light of the power of the closed-form solution to OICA corresponding to the One-Latent-Component structure, we formulate a way to estimate the mixing matrix using the higher-order cumulants, …

Team Thesyllogist At Semeval-2023 Task 3: Language-Agnostic Framing Detection In Multi-Lingual Online News: A Zero-Shot Transfer Approach, Osama Mohammed Afzal, Preslav Nakov

Natural Language Processing Faculty Publications

We describe our system for SemEval-2022 Task 3 subtask 2 which on detecting the frames used in a news article in a multi-lingual setup. We propose a multi-lingual approach based on machine translation of the input, followed by an English prediction model. Our system demonstrated good zero-shot transfer capability, achieving micro-F1 scores of 53% for Greek (4th on the leaderboard) and 56.1% for Georgian (3rd on the leaderboard), without any prior training on translated data for these languages. Moreover, our system achieved comparable performance on seven other languages, including German, English, French, Russian, Italian, Polish, and Spanish. Our results demonstrate …

Semeval-2023 Task 3: Detecting The Category, The Framing, And The Persuasion Techniques In Online News In A Multi-Lingual Setup, Jakub Piskorski, Nicolas Stefanovitch, Giovanni Da San Martino, Preslav Nakov

Natural Language Processing Faculty Publications

We describe SemEval-2023 task 3 on Detecting the Category, the Framing, and the Persuasion Techniques in Online News in a Multilingual Setup: the dataset, the task organization process, the evaluation setup, the results, and the participating systems. The task focused on news articles in nine languages (six known to the participants upfront: English, French, German, Italian, Polish, and Russian), and three additional ones revealed to the participants at the testing phase: Spanish, Greek, and Georgian). The task featured three subtasks: (1) determining the genre of the article (opinion, reporting, or satire), (2) identifying one or more frames used in an …

Multilingual Multifaceted Understanding Of Online News In Terms Of Genre, Framing And Persuasion Techniques, Jakub Piskorski, Nicolas Stefanovitch, Nikolaos Nikolaidis, Giovanni Da San Martino, Preslav Nakov

Natural Language Processing Faculty Publications

We present a new multilingual multifacet dataset of news articles, each annotated for genre (objective news reporting vs. opinion vs. satire), framing (what key aspects are highlighted), and persuasion techniques (logical fallacies, emotional appeals, ad hominem attacks, etc.). The persuasion techniques are annotated at the span level, using a taxonomy of 23 fine-grained techniques grouped into 6 coarse categories. The dataset contains 1,612 news articles covering recent news on current topics of public interest in six European languages (English, French, German, Italian, Polish, and Russian), with more than 37k annotated spans of persuasion techniques. We describe the dataset and the …

Model Transferability With Responsive Decision Subjects, Yatong Chen, Zeyu Tang, Kun Zhang, Yang Liu

Machine Learning Faculty Publications

Given an algorithmic predictor that is accurate on some source population consisting of strategic human decision subjects, will it remain accurate if the population respond to it? In our setting, an agent or a user corresponds to a sample (X, Y ) drawn from a distribution D and will face a model h and its classification result h(X). Agents can modify X to adapt to h, which will incur a distribution shift on (X, Y ). Our formulation is motivated by applications where the deployed machine learning models are subjected to human agents, and will ultimately face responsive and interactive …

Detecting Out-Of-Distribution Data Through In-Distribution Class Prior, Xue Jiang, Feng Liu, Zhen Fang, Hong Chen, Tongliang Liu, Feng Zheng, Bo Han

Machine Learning Faculty Publications

Given a pre-trained in-distribution (ID) model, the inference-time out-of-distribution (OOD) detection aims to recognize OOD data during the inference stage. However, some representative methods share an unproven assumption that the probability that OOD data belong to every ID class should be the same, i.e., these OOD-to-ID probabilities actually form a uniform distribution. In this paper, we show that this assumption makes the above methods incapable when the ID model is trained with class-imbalanced data. Fortunately, by analyzing the causal relations between ID/OOD classes and features, we identify several common scenarios where the OOD-to-ID probabilities should be the ID-class-prior distribution and …

Orgsp Quarterly: An Orgsp Newsletter From Lincoln Memorial University, Vol 8.2, Lincoln Memorial University, Office Of Research Grants And Sponsored Projects

ORGSP Quarterly

This quarter's issue focuses on summer research. Learn about the excellent work of LMU's faculty, staff, and students.

The Good, The Bad, And The Ugly Of Us Antitrust, Maurice E. Stucke

Scholarly Works

This article examines the bad and ugly as the US federal agencies seek to rejuvenate competition. The bad is legislative hiatus to update the antitrust laws for the digital economy. The ugly is when courts push their own economic beliefs, without regard for the congressional intent and aims of the antitrust laws. Regardless of who wins, the rule of law (and those most dependent on the antitrust law) suffer. To correct America’s market power problem, the article proposes restoring the constitutional balance, where the courts adjudicate, the legislature legislates, and enforcers enforce.

Fuzzy Mathematics Under Non-Minimal "And"-Operations (T-Norms): Equivalence Leads To Metric, Order Leads To Kinematic Metric, Topology Leads To Area Or Volume, Purbita Jana, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

Most formulas analyzed in fuzzy mathematics assume -- explicitly or implicitly -- that the corresponding "and"-operation (t-norm) is the simplest minimum operation. In this paper, we analyze what happens if instead, we use other "and"-operations. It turns out that for such operations, a fuzzification of a mathematical theory naturally leads to a more complex mathematical setting: fuzzification of equivalence relation leads to metric, fuzzification of order leads to kinematic metric, and fuzzification of topology leads to area or volume.

Why Resilient Modulus Is Proportional To The Square Root Of Unconfined Compressive Strength (Ucs): A Qualitative Explanation, Edgar Daniel Rodriguez Velasquez, Vladik Kreinovich

Departmental Technical Reports (CS)

The strength of the pavement is determine by its resilient modulus, i.e., by its ability to withstand (practically) instantaneous stresses caused by the passing traffic. However, the resilient modulus is not easy to measure: its measurement requires a special expensive equipment that many labs do not have. So, instead of measuring it, practitioners often measure easier-to-measure Unconfined Compressive Strength (UCS) -- that describes the effect of a continuously applied force -- and estimate the resilient modulus based on the result of this measurement. An empirical formula shows that the resilient modulus is proportional to the square root of the Unconfined …

How To Estimate Unknown Unknowns: From Cosmic Light To Election Polls, Talha Azfar, Vignesh Ponraj, Vladik Kreinovich, Nguyen Hoang Phuong

Departmental Technical Reports (CS)

In two different areas of research -- in the study of space light and in the study of voting -- the observed value of the quantity of interest is twice larger than what we would expect. That the observed value is larger makes perfect sense: there are phenomena that we do not take into account in our estimations. However, the fact that the observed value is exactly twice larger deserves explanation. In this paper, we show that Laplace Indeterminacy Principle leads to such an explanation.

Three’S A Crowd: Conflicts Of Interest In Third- Party Preparation Of Environmental Impact Statements And Evolving Agency Responsibility Under Nepa, Colleen Mcgrath

UC Law Environmental Journal

Although the National Environmental Policy Act (NEPA) is designed to promote accountability and transparency about the environmental impacts of large-scale government projects, the lack of oversight over the production of Environmental Impact Statements (EIS) can result in incomplete or biased reports, especially when the EIS is prepared by a third party that has financial or organizational ties to the project. As such, this paper investigates the inherent conflicts of interest that arise when third parties prepare EIS and how that lack of impartiality can undermine the credibility of environmental assessments, erode public trust, and diminish the effectiveness of NEPA as …

Improved Burned Area Mapping Using Monotemporal Landsat-9 Imagery And Convolutional Shift-Transformer, Seyd Teymoor Seydi, Mojtaba Sadegh

Civil Engineering Faculty Publications and Presentations

Satellite imagery, specifically Landsat, have been widely used for mapping and monitoring wildfire burned areas. The new Landsat-9 satellite – with higher radiometric resolution compared to its predecessors, and improved temporal resolution when combined with Landsat-8 (∼8 days) – enables a wide range of applications, particularly burned area mapping (BAM). We propose a novel deep learning BAM model that leverages the strengths of the convolutional layers for deep feature generation from Landsat-9 imagery and shift-transformer block for burned area classification. The performance of the model is evaluated in five large fire case studies across the globe. BAM results are also …

Improving Catheter-Associated Urinary Tract Infections In The Intensive Care Unit: Implementation Of A Rounding Tool To Enhance Communication And Collaboration., Bethany Carol Risen

Doctor of Nursing Practice Papers

Background/Significance: Catheter-associated urinary tract infections (CAUTIs) are avoidable and costly healthcare-associated infections (HAIs) and are associated with high morbidity and mortality. A rise in CAUTIs at the project site, and the need for a standardized CAUTI prevention communication process, prompted this quality improvement project.

Purpose: The purpose of this quality improvement project was to decrease CAUTIs through improved communication and collaboration amongst the critical care team.

Methods: Twelve nurses completed the Collaboration and Satisfaction about Care Decisions (CSACD) questionnaire pre- and post- intervention which, evaluated communication and collaboration. Nurses also assessed IUC indication and removal during interdisciplinary rounds.

Intervention: This …

Arcadia: A Student Journal For Faith And Culture

Arcadia: A Student Journal for Faith and Culture

No abstract provided.

Longwood Magazine 2023 Summer, Longwood University

Alumni Newsletters & Bulletins

No abstract provided.

Olli Fall 2023 Catalog, Toniann Leavitt

Osher Lifelong Learning Institute

No abstract provided.

In Their Words: Student Reflections On Information-Seeking Behaviors, Sarah P.C. Dahlen, Kathlene Hanson

Library Faculty Publications and Presentations

Academic librarians try to facilitate student information seeking by providing classroom instruction, creating tutorials and guides, and selecting and modifying search tools to best meet student needs and preferences. These efforts are often informed by interactions with students, and can be even better informed through analysis of student descriptions of their searching practices. In this case study, 50 upper-division students from the Social and Behavioral Sciences major completed searching tasks in a few library search tools and were then interviewed about their search behaviors, both in the experimental setting and in general. Their responses illuminate some of their tendencies, including …

The Art Of A Slugslayer: An Exploration Of The Process Of Extracting Radulae From Lehmannia Valentiana For The Purpose Of Viewing In The Scanning Electron Microscope, Elizabeth Gannon

Mahurin Honors College Capstone Experience/Thesis Projects

A radula is an anatomical structure found exclusively in mollusks that acts as both tongue and teeth in feeding. Its structure has been studied for more than a century, yet published methods for identifying, dissecting, and cleaning radulae for microscopy are almost unintelligible to anyone not already familiar with molluscan anatomy. The purpose of this project was to identify the best method of garden slug radula isolation and present it in a manner that anyone could understand and successfully use.

After identifying the location of the radula in the slug, the easiest means of removal proved to be simply regurgitating …

Ua64/2 The Challenge: Magazine For The Center For Gifted Studies (No. 54, Summer 2023), Elizabeth Joyce Editor, Western Kentucky University

Gifted Studies Publications

Magazine created by and about the WKU Center for Gifted Studies.

Developing A Quality Control System For Biotechnological Device Inspection Improvement, Harsimran Hothi, Fatemeh Davoudi Kakhki

General Engineering

Incoming quality control (IQC) is integral to quality management system of manufacturing industries. IQC plays a significant role in ensuring delivery of high standard products to the target customers and, in turn, affects the company’s reputation and their competitiveness in the industry. Presenting a case from a biotechnology company, the purpose of this research is to develop a quality control system for inspection improvement of a biotechnological device. During the COVID-19 pandemic, the IQC Department encountered inconsistencies with output rate when providing inspected parts to the Manufacturing Department: an issue that could be mitigated with a documented process that addresses …

Empirical Study Of Machine Learning For Intelligent Bearing Fault Diagnosis, Armin Moghadam, Fatemeh Davoudi Kakhki

General Engineering

Bearing failure highly impacts performance and production of manufacturing systems, causes safety incidents, and results in casualties and property loss. According to the current literature, bearing faults cause 30-40% of all failures in induction motors. Therefore, identification of bearing faults, at early stages, is crucial to ensure seamless and reliable operation of induction motors in industrial and manufacturing operations. Faults occur in four components of bearing: inner race, outer race, ball, and cage. Regardless of the component in which fault occurs, it causes changes in vibration signals. Therefore, comparing normal signals with faulty ones is helpful in detecting localized faults …

Ensemble Of Handcrafted Features Of Environment Sound Classification Using A Deep Convolutional Neural Network To Enhance Accuracy And Reduce Computational Complexity, Ibrahim Abdulrahman Aljubayri

Theses and Dissertations

Environmental sound classification (ESC) is an area of active research in signal and image processing that has made significant strides over the past several years. The goal of ESC is to classify environmental sounds by extracting and analyzing handcrafted and deep features from various acoustic events. The task is complex because environmental sounds are typically unstructured, nonstationary, and overlapping. Multiple deep learning (DL) approaches have successfully tackled the ESC problem and outperformed conventional classifiers like k-nearest neighbors (kNN) or support vector machine (SVM). However, most DL approaches have high computational costs, making them unsuitable for use in embedded systems applications. …

Tuning Oxo Formation Energies Using Spectator Ligands In The Mil-100 Metal Organic Framework, Victoria E. Lee, Stephen P. Vicchio, Rachel B. Getman

Chemistry Summer Research Program

No abstract provided.

Effects Of Low-Energy X-Rays And Uv Radiation On Fibroblast Cells, Michelle Gorodisky, Congyue Peng, Arianna Csiszer, Delphine Dean

Chemistry Summer Research Program

No abstract provided.

Understanding The Leaders Of Tomorrow: The Need To Study Leadership In Adolescence, Jennifer L. Tackett, Kathleen W. Reardon, Nathanael J. Fast, Lars Johnson

Psychology Faculty Publications

Leadership traits and behaviors are observed early in human development, and although an improved understanding of youth leadership would usefully inform many real-world contexts (e.g., education, parenting, policy), most empirical work on leadership has been limited to adult populations. The purpose of the current article is to add a developmental perspective to leadership research that has so far been absent. Here, we (a) highlight adolescence as a critical developmental period for leadership emergence and development, (b) argue that leadership among youths is poorly understood and critically understudied, (c) provide exemplars of synergy between research on leadership and adolescent development that …

Compact Flexible Heart Rate Monitor Simulations, Jack Ellingson, Dean Arakaki

Electrical Engineering

Cardiovascular disease is a global health concern; heart rate monitors can help assess cardiac health. Sensors must be effective and non-invasive. This project develops and characterizes flexible substrate antennas for heart beat detection through reflection coefficient measurements. Antenna substrate printing and sensor applications are through external collaborations. The project includes curved ground plane and substrate HFSS models to determine reflection coefficient responses to chest expansions.

Design And Analysis Of 3d Cassegrain Antenna Using Hfss, Andrew Wu, Dean Arakaki

Electrical Engineering

Parabolic antennas offer high gain and narrow beamwidth by employing a reflector to collimate radio waves. Dual reflectors reduce antenna system size over single reflectors and increase design optimization options. This paper introduces a detailed HFSS-based Cassegrain dual reflector design procedure for antenna design engineers. A stripline power splitter excites a 4x4 patch feed array. The parameterized model illustrates performance tradeoffs to meet system operating requirements.

The Decentralization Problem Of Low Power Lenses And Treatment Methods, Mundher Sameen Shuker

Al-Nisour Journal for Medical Sciences

In a study where all patients (50) were chosen, the causes of the eccentricity issue with low energy lenses (0.25D to 1.0D) and treatment options were examined. who wore visual techniques teaching clinic at the College of Health and Medical Technologies-Bagdad. For the period from (1-9-2021 up to 1-5-2022). The causes of deviation in the center of the lenses were studied determined the treatment methods, it appeared that they occurred in the process of smoothing and centering. Process of the lenses was determined by using Newton's rings examination kit and the diameter of the lens after centrifuging and edges with …

Kg-Hub-Building And Exchanging Biological Knowledge Graphs., J Harry Caufield, Tim Putman, Kevin Schaper, Deepak R Unni, Harshad Hegde, Tiffany J Callahan, Luca Cappelletti, Sierra A T Moxon, Vida Ravanmehr, Seth Carbon, Lauren E Chan, Katherina Cortes, Kent A Shefchek, Glass Elsarboukh, Jim Balhoff, Tommaso Fontana, Nicolas Matentzoglu, Richard M Bruskiewich, Anne E Thessen, Nomi L Harris, Monica C Munoz-Torres, Melissa A Haendel, Peter N Robinson, Marcin P Joachimiak, Christopher J Mungall, Justin T Reese

Faculty Research 2023

MOTIVATION: Knowledge graphs (KGs) are a powerful approach for integrating heterogeneous data and making inferences in biology and many other domains, but a coherent solution for constructing, exchanging, and facilitating the downstream use of KGs is lacking.

RESULTS: Here we present KG-Hub, a platform that enables standardized construction, exchange, and reuse of KGs. Features include a simple, modular extract-transform-load pattern for producing graphs compliant with Biolink Model (a high-level data model for standardizing biological data), easy integration of any OBO (Open Biological and Biomedical Ontologies) ontology, cached downloads of upstream data sources, versioned and automatically updated builds with stable URLs, …