Digital Commons Network^™

The Impact Of Oppression: Transforming Historical Database Instruction Into Contemporary Discussion, Kelleen Maluski

Publications

No abstract provided.

Critical Teaching Behaviors: Defining, Documenting, And Discussing Good Teaching., Lauren Cornejo Barbeau, Claudia Cornejo Happel, Nancy L. Chick

Publications

What does “good” teaching mean, and how can we know it when we see it? Perhaps you have grappled with these questions at some point in your career, either as an instructor wanting to document or grow your teaching effectiveness or as a peer or administrator trying to provide guidance to or assess the teaching of others.This book serves three purposes: a condensed, evidence-based guide to effective teaching; a resource on creating a focused teaching narrative and teaching portfolio; and a toolkit that equips faculty to conduct peer observations, student midterm feedback, and productive conversations related to teaching.

The first …

What Twenty-First-Century Free Speech Law Means For Securities Regulation, Helen Norton

Publications

Securities law has long regulated securities-related speech--and until recently, it did so with little, if any, First Amendment controversy. Yet the antiregulatory turn in the Supreme Court's twenty-first-century Free Speech Clause doctrine has inspired corporate speakers' increasingly successful efforts to resist regulation in a variety of settings, settings that now include securities law. This doctrinal turn empowers courts, if they so choose, to dismantle the securities regulation framework in place since the Great Depression. At stake are not only recent governmental proposals to require companies to disclose accurate information about their vulnerabilities to climate change and other emerging risks, but …

Demo Alleviate: Demonstrating Artificial Intelligence Enabled Virtual Assistance For Telehealth: The Mental Health Case, Kaushik Roy, Vedant Khandelwal, Raxit Goswami, Nathan Dolbir, Jinendra Malekar, Amit Sheth

Publications

After the pandemic, artificial intelligence (AI) powered support for mental health care has become increasingly important. The breadth and complexity of significant challenges required to provide adequate care involve: (a) Personalized patient understanding, (b) Safety-constrained and medically validated chatbot patient interactions, and (c) Support for continued feedback-based refinements in design using chatbot-patient interactions. We propose Alleviate, a chatbot designed to assist patients suffering from mental health challenges with personalized care and assist clinicians with understanding their patients better. Alleviate draws from an array of publicly available clinically valid mental-health texts and databases, allowing Alleviate to make medically sound and informed …

"Sidetreks", The Commercial Appeal's Weekend Living, Issue 3, 1981?

Publications

Booklet, "Sidetreks: Weekend Trips From...The Commercial Appeal's Weekend Living", Issue 3, 1981?

"This third offering, like the others, is designed to provide minivacations for area residents. There are 10 new treks in this book. Each trip can make an easy three-day weekend, with most designed for a Saturday and Sunday getaway. Most call for less than a half-day's driving. The areas recommended are rich in history, scenic beauty and places to have a good time and enjoy recreation and entertainment."

"Sidetreks", The Commercial Appeal's Weekend Living, Issue 4, 1982

Publications

Booklet, "Sidetreks: Weekend Trips From...The Commercial Appeal's Weekend Living", Issue 4, 1982

"Each year for three years, The Commercial Appeal has produced a Sidetreks book - collections of short trips taken from the newspaper's Weekend Living Section. In those years, more than 10,000 copies have been sold. Now, in 1982, comes Sidetreks 4. This offering, like the others, is designed to provide minivacations for area residents. Of the 10 trips included in Sidetreks 4, each provides a leisurely three-day weekend trip. Most are designed for a Saturday and Sunday getaway and average five to six hours driving time."

The Evolution Of Ai On The Commercial Flight Deck: Finding Balance Between Efficiency And Safety While Maintaining The Integrity Of Operator Trust, Mark Miller, Sam Holley, Leila Halawi

Publications

As artificial intelligence (AI) seeks to improve modern society, the commercial aviation industry offers a significant opportunity. Although many parts of commercial aviation including maintenance, the ramp, and air traffic control show promise to integrate AI, the highly computerized digital flight deck (DFD) could be challenging. The researchers seek to understand what role AI could provide going forward by assessing AI evolution on the commercial flight deck over the past 50 years. A modified SHELL diagram is used to complete a Human Factors (HF) analysis of the early use for AI on the commercial flight deck through introduction of the …

Quantifying Geogrid Reinforcement Mechanism In Roadway Performance Using Cyclic Plate Load (Cpl) Test, G.S. Ellithy, A. Crippa

Publications

For decades, geogrids have been used successfully to improve performance in both paved and unpaved roadway construction. Even though the current state of practice differentiates between the design methodology incorporating geogrids in paved and unpaved roadways, the true improvement contribution of geogrids is to the base layer, or to the layer that is placed directly on top of it. It has been established that the three reinforcement mechanisms by which geogrids enhance roadway performance are: lateral restraint, bearing capacity increase and membrane tension support. In order to quantify these mechanisms and their contribution to the roadway performance improvement, two Cyclic …

Use Of Digital Technologies For Public Health Surveillance During The Covid-19 Pandemic: A Scoping Review, Lorie Donelle Phd, Rn, Fcan, Leigha Comer, Brad Hiebert, Jodi Hall, Jacob J. Shelley, Maxwell J. Smith, Anita Kothari, Jacquelyn Burkell, Saverio Stranges, Tommy Cooke, James M. Shelley, Jason Gilliland, Marionette Ngole, Danica Facca

Publications

Throughout the COVID-19 pandemic, a variety of digital technologies have been leveraged for public health surveillance worldwide. However, concerns remain around the rapid development and deployment of digital technologies, how these technologies have been used, and their efficacy in supporting public health goals. Following the five-stage scoping review framework, we conducted a scoping review of the peer-reviewed and grey literature to identify the types and nature of digital technologies used for surveillance during the COVID-19 pandemic and the success of these measures. We conducted a search of the peer-reviewed and grey literature published between 1 December 2019 and 31 December …

Successes And Barriers Of Health Information Exchange Participation Across Hospitals In South Carolina From 2014 To 2020: Longitudinal Observational Study, Kausik Lakkaraju, Aniket Gupta, Biplav Srivastava, Marco Valtorta, Dezhi Wu

Publications

Sentiment Analysis Systems (SASs) are data-driven Artificial Intelligence (AI) systems that output polarity and emotional intensity when given a piece of text as input. Like other AIs, SASs are also known to have unstable behavior when subjected to changes in data which can make them problematic to trust out of concerns like bias when AI works with humans and data has protected attributes like gender, race, and age. Recently, an approach was introduced to assess SASs in a blackbox setting without training data or code, and rating them for bias using synthetic English data. We augment it by introducing two …

A Snapshot Of Postgraduate Research At Mtu 2023, Stephen Cassidy

Publications

As our postgraduate research students live and work in an increasingly digital and information-driven age, the ability to write and communicate in a variety of styles appropriate to a range of audiences becomes increasingly important. The Graduate Studies Office working with the MTU Library Service and others, supports research students to develop their writing skills not just for academic publication but also for communicating to the general public. As part of this initiative, we organized the second annual MTU Postgraduate Research Writing Competition. Its aim was to provide postgraduate research students from all disciplines across the University with an opportunity …

Regulating The Risks Of Ai, Margot E. Kaminski

Publications

Companies and governments now use Artificial Intelligence (“AI”) in a wide range of settings. But using AI leads to well-known risks that arguably present challenges for a traditional liability model. It is thus unsurprising that lawmakers in both the United States and the European Union (“EU”) have turned to the tools of risk regulation in governing AI systems.

This Article describes the growing convergence around risk regulation in AI governance. It then addresses the question: what does it mean to use risk regulation to govern AI systems? The primary contribution of this Article is to offer an analytic framework for …

Preface: New Directions In Prosecutorial Reform, Miriam Aroni Krinsky, Justin Murray, Maybell Romero

Publications

This Preface, which introduces the American Criminal Law Review’s Symposium Issue on Reform-Minded Prosecution, begins by describing the power that prosecutors hold in the criminal legal system, which has historically gone unchecked and unquestioned. As mass incarceration, police violence, and wrongful convictions began to permeate the public consciousness, many communities focused their attention on the critical role of their local elected prosecutor and elected leaders who promised to do the job differently. Reform-minded prosecutors have enjoyed remarkable electoral successes over the past decade such that close to twenty percent of the U.S. population now resides in a jurisdiction with a …

The Shared Ethical Framework To Allocate Scarce Medical Resources: A Lesson From Covid-19, Govind Persad, Govind C. Persad

Publications

The COVID-19 pandemic has helped to clarify the fair and equitable allocation of scarce medical resources, both within and among countries. The ethical allocation of such resources entails a three-step process: (1) elucidating the fundamental ethical values for allocation, (2) using these values to delineate priority tiers for scarce resources, and (3) implementing the prioritisation to faithfully realise the fundamental values. Myriad reports and assessments have elucidated five core substantive values for ethical allocation: maximising benefits and minimising harms, mitigating unfair disadvantage, equal moral concern, reciprocity, and instrumental value. These values are universal. None of the values are sufficient alone, …

Dynamic Function Learning Through Control Of Ensemble Systems, Wei Zhang, Vignesh Narayanan, Jr-Shin Li

Publications

Learning tasks involving function approximation are preva- lent in numerous domains of science and engineering. The underlying idea is to design a learning algorithm that gener- ates a sequence of functions converging to the desired target function with arbitrary accuracy by using the available data samples. In this paper, we present a novel interpretation of iterative function learning through the lens of ensemble dy- namical systems, with an emphasis on establishing the equiv- alence between convergence of function learning algorithms and asymptotic behavior of ensemble systems. In particular, given a set of observation data in a function learning task, we …

Cooperative Deep Q -Learning Framework For Environments Providing Image Feedback, Krishnan Raghavan, Vignesh Narayanan, Sarangapani Jagannathan

Publications

In this article, we address two key challenges in deep reinforcement learning (DRL) setting, sample inefficiency, and slow learning, with a dual-neural network (NN)-driven learning approach. In the proposed approach, we use two deep NNs with independent initialization to robustly approximate the action-value function in the presence of image inputs. In particular, we develop a temporal difference (TD) error-driven learning (EDL) approach, where we introduce a set of linear transformations of the TD error to directly update the parameters of each layer in the deep NN. We demonstrate theoretically that the cost minimized by the EDL regime is an approximation …

Knowledge Graph Guided Semantic Evaluation Of Language Models For User Trust, Kaushik Roy, Tarun Garg, Vedant Palit, Yuxin Zi, Vignesh Narayanan, Amit Sheth

Publications

A fundamental question in natural language processing is - what kind of language structure and semantics is the language model capturing? Graph formats such as knowledge graphs are easy to evaluate as they explicitly express language semantics and structure. This study evaluates the semantics encoded in the self-attention transformers by leveraging explicit knowledge graph structures. We propose novel metrics to measure the reconstruction error when providing graph path sequences from a knowledge graph and trying to reproduce/reconstruct the same from the outputs of the self-attention transformer models. The opacity of language models has an immense bearing on societal issues of …

Moment-Based Reinforcement Learning For Ensemble Control, Yao-Chi Yu, Vignesh Narayanan, Jr-Shin Li

Publications

Problems involving controlling the collective behavior of a population of structurally similar dynamical systems, the so-called ensemble control, arise in diverse emerging applications and pose a grand challenge in systems science and control engineering. Owing to the severely under-actuated nature and the difficulty of placing large-scale sensor networks, ensemble systems are limited to being actuated and monitored at the population level. Moreover, mathematical models describing the dynamics of ensemble systems are often elusive. Therefore, it is essential to design broadcast controls that excite the entire population in such a way that the heterogeneity in system dynamics are robustly compensated. In …

Cook-Gen: Robust Generative Modeling Of Cooking Actions From Recipes, Revathy Venkataramanan, Kaushik Roy, Kanak Ray, Renjith Prasad, Yuxin Zi, Vignesh Narayanan, Amit Sheth

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As people become more aware of their food choices, food computation models have become increasingly popular in assisting people in maintaining healthy eating habits. For example, food recommendation systems analyze recipe instructions to assess nutritional contents and provide recipe recommendations. The recent and remarkable successes of generative AI methods, such as auto-regressive large language models, can lead to robust methods for a more comprehensive understanding of recipes for healthy food recommendations beyond surface-level nutrition content assessments. In this study, we explore the use of generative AI methods to extend current food computation models, primarily involving the analysis of nutrition and …

Tutorial - Shodhguru Labs: Optimization And Hyperparameter Tuning For Neural Networks, Kaushik Roy

Publications

Neural networks have emerged as a powerful and versatile class of machine learning models, revolutionizing various fields with their ability to learn complex patterns and make accurate predictions. The performance of neural networks depends significantly on the appropriate choice of hyperparameters, which are critical factors governing their architecture, regularization, and optimization techniques. As the demand for high-performance neural networks grows across diverse applications, the need for efficient optimization and hyperparameter tuning methods becomes paramount. This paper presents a comprehensive exploration of optimization strategies and hyperparameter tuning techniques for neural networks. Neural networks have emerged as a powerful and versatile class …

Flying Blind: Exploring The Visual Cues Used By Helicopter Pilots In Degraded Visual Environments, Brandon Dreslin, Molly C. Mersinger, Shivani Patel, Alex Chaparro

Publications

Helicopter pilots rely on visual cues from the environment and instrument displays during critical phases of flight – particularly final approach and landing – to safely land. However, the specific visual cues pilots rely on and how they integrate those cues to make anticipatory inceptor inputs or corrections are not well understood. Importantly, those cues may be degraded under nighttime and brownout/whiteout conditions where the downwash of a helicopter’s rotors cause loose dirt/snow to be projected into the air, resulting in the obfuscation of the pilot’s vision outside the aircraft. The lack of visual cues in these conditions means that …

Proknow: Process Knowledge For Safety Constrained And Explainable Question Generation For Mental Health Diagnostic Assistance, Kaushik Roy, Manas Gaur, Misagh Soltani, Vipula Rawte, Ashwin Kalyan, Amit Sheth

Publications

Current Virtual Mental Health Assistants (VMHAs) provide counseling and suggestive care. They refrain from patient diagnostic assistance because of a lack of training on safety-constrained and specialized clinical process knowledge (Pro-Know). In this work, we define ProKnow as an ordered set of information that maps to evidence-based guidelines or categories of conceptual understanding to experts in a domain. We also introduce a new dataset of diagnostic conversations guided by safety constraints and ProKnow that healthcare professionals use (ProKnow-data). We develop a method for natural language question generation (NLG) that collects diagnostic information from the patient interactively (ProKnow-algo). We demonstrate the …

Ierl: Interpretable Ensemble Representation Learning - Combining Crowdsourced Knowledge And Distributed Semantic Representations, Yuxin Zi, Kaushik Roy, Vignesh Narayanan, Manas Gaur, Amit Sheth

Publications

Large Language Models (LLMs) encode meanings of words in the form of distributed semantics. Distributed semantics capture common statistical patterns among language tokens (words, phrases, and sentences) from large amounts of data. LLMs perform exceedingly well across General Language Understanding Evaluation (GLUE) tasks designed to test a model’s understanding of the meanings of the input tokens. However, recent studies have shown that LLMs tend to generate unintended, inconsistent, or wrong texts as outputs when processing inputs that were seen rarely during training, or inputs that are associated with diverse contexts (e.g., well-known hallucination phenomenon in language generation tasks). Crowdsourced and …

A Semantic Web Approach To Fault Tolerant Autonomous Manufacturing, Fadi El Kalach, Ruwan Wickramarachchi, Ramy Harik, Amit Sheth

Publications

The next phase of manufacturing is centered on making the switch from traditional automated to autonomous systems. Future factories are required to be agile, allowing for more customized production, and resistance to disturbances. Such production lines would be able to reallocate resources as needed and minimize downtime while keeping up with market demands. These systems must be capable of complex decision-making based on parameters such as machine status, sensory/IoT data, and inspection results. Current manufacturing lines lack this complex capability and instead focus on low-level decision-making on the machine level without utilizing the generated data to its full extent. This …

Acm Web Conference 2023, Usha Lokala, Kaushik Roy, Utkarshani Jaimini, Amit Sheth

Publications

Improving the performance and explanations of ML algorithms is a priority for adoption by humans in the real world. In critical domains such as healthcare, such technology has significant potential to reduce the burden on humans and considerably reduce manual assessments by providing quality assistance at scale. In today’s data-driven world, artificial intelligence (AI) systems are still experiencing issues with bias, explainability, and human-like reasoning and interpretability. Causal AI is the technique that can reason and make human-like choices making it possible to go beyond narrow Machine learning-based techniques and can be integrated into human decision-making. It also offers intrinsic …

Tutorial - Shodhguru Labs: Knowledge-Infused Artificial Intelligence For Mental Healthcare, Kaushik Roy

Publications

Artificial Intelligence (AI) systems for mental healthcare (MHCare) have been ever-growing after realizing the importance of early interventions for patients with chronic mental health (MH) conditions. Social media (SocMedia) emerged as the go-to platform for supporting patients seeking MHCare. The creation of peer-support groups without social stigma has resulted in patients transitioning from clinical settings to SocMedia supported interactions for quick help. Researchers started exploring SocMedia content in search of cues that showcase correlation or causation between different MH conditions to design better interventional strategies. User-level Classification-based AI systems were designed to leverage diverse SocMedia data from various MH conditions, …

L3 Ensembles: Lifelong Learning Approach For Ensemble Of Foundational Language Models*, Aidin Shiri, Kaushik Roy, Amit Sheth, Manas Gaur

Publications

Fine-tuning pre-trained foundational language models (FLM) for specific tasks is often impractical, especially for resource-constrained devices. This necessitates the development of a Lifelong Learning (L3) framework that continuously adapts to a stream of Natural Language Processing (NLP) tasks efficiently. We propose an approach that focuses on extracting meaningful representations from unseen data, constructing a structured knowledge base, and improving task performance incrementally. We conducted experiments on various NLP tasks to validate its effectiveness, including benchmarks like GLUE and SuperGLUE. We measured good performance across the accuracy, training efficiency, and knowledge transfer metrics. Initial experimental results show that the proposed L3 …

The Troubling Emergence Of Hallucination In Large Language Models--An Extensive Definition, Quantification, And Prescriptive Remediations, Vipula Rawte, Swagata Chakraborty, Agnibh Pathak, Anubhav Sarkar, S.M Towhidul Islam Tonmoy, Aman Chadha, Amit Sheth, Amitava Das

Publications

The recent advancements in Large Language Models (LLMs) have garnered widespread acclaim for their remarkable emerging capabilities. However, the issue of hallucination has parallelly emerged as a by-product, posing significant concerns. While some recent endeavors have been made to identify and mitigate different types of hallucination, there has been a limited emphasis on the nuanced categorization of hallucination and associated mitigation methods. To address this gap, we offer a finegrained discourse on profiling hallucination based on its degree, orientation, and category, along with offering strategies for alleviation. As such, we define two overarching orientations of hallucination: (i) factual mirage (FM) …

Science Communication As A Collective Intelligence Endeavour: A Manifesto And Examples For Implementation, Maria Petrescu

Publications

Effective science communication is challenging when scientific messages are informed by a continually updating evidence base and must often compete against misinformation. We argue for the need for a new programme of science communication as collective intelligence—a collaborative approach, supported by technology. This would have four key advantages over the typical model where scientists communicate as individuals: scientific messages would be informed by (1) a wider base of aggregated knowledge, (2) contributions from a diverse scientific community, (3) participatory input from stakeholders, and (4) better responsiveness to ongoing changes in the state of knowledge.

Cognitive Processing Disruptions Affecting Flight Deck Performance: Implications For Cognitive Resilience, Sam J. Holley, Mark D. Miller

Publications

The flight deck of a commercial aircraft has become progressively digitized and operates in multiple modes with displays and indicators that require increasing levels of comprehension. Examining several aspects of cognitive processing is important to understand how threats to safety might occur and what actions might be taken to reduce severity or to eliminate the threat altogether. This paper presents the elements of cognition to consider, relevant characteristics of working memory and cognitive processing speed, types of disruptions and how they are addressed, results from overload or confusion, and the need for effective cognitive resilience to recover and repair the …