Digital Commons Network^™

Application Of Artificial Intelligence To Lithium-Ion Battery Research And Development, Zhen-Wei Zhu, Jing-Yi Qiu, Li Wang, Gao-Ping Cao, Xiang-Ming He, Jing Wang, Hao Zhang

Journal of Electrochemistry

Lithium-ion batteries (LIBs) have become one of the best solutions to the energy storage issue in modern society. However, the battery materials and device development are both complex, and involve multivariable problems. Traditional trial-and-error approach, which relies on researchers to conduct experiments, has encountered bottlenecks in the improvement of the battery performance. Artificial intelligence (AI) is the most potential technology to deal with this issue due to its powerful high-speed and capabilities of processing massive data. In particular, the capability of machine learning (ML) algorithms in assessing multidimensional data variables and discovering patterns in the sets are expected to assist …

Emulating Future Neurotechnology Using Magic, Jay A. Olson, Mariève Cyr, Despina Z. Artenie, Thomas Strandberg, Lars Hall, Matthew L. Tompkins, Amir Raz, Petter Johansson

Psychology Faculty Articles and Research

Recent developments in neuroscience and artificial intelligence have allowed machines to decode mental processes with growing accuracy. Neuroethicists have speculated that perfecting these technologies may result in reactions ranging from an invasion of privacy to an increase in self-understanding. Yet, evaluating these predictions is difficult given that people are poor at forecasting their reactions. To address this, we developed a paradigm using elements of performance magic to emulate future neurotechnologies. We led 59 participants to believe that a (sham) neurotechnological machine could infer their preferences, detect their errors, and reveal their deep-seated attitudes. The machine gave participants randomly assigned positive …

Managing Artificial Intelligence Projects: Key Insights From An Ai Consulting Firm, Gregory Vial, Ann-Frances Cameron, Tanya Giannelia, Jinglu Jiang

Management and Accounting Faculty Scholarship

While organisations are increasingly interested in artificial intelligence (AI), many AI projects encounter significant issues or even fail. To gain a deeper understanding of the issues that arise during these projects and the practices that contribute to addressing them, we study the case of Consult, a North American AI consulting firm that helps organisations leverage the power of AI by providing custom solutions. The management of AI projects at Consult is a multi-method approach that draws on elements from traditional project management, agile practices, and AI workflow practices. While the combination of these elements enables Consult to be effective in …

Strategic Perspective Of Leveraging New Generation Information Technology To Enable Modernization Of Emergency Management, Haibo Zhang, Xinyu Dai, Depei Qian, Jian Lyu

Bulletin of Chinese Academy of Sciences (Chinese Version)

The application and development of the new generation information technology is a vital support to realize the modernization of emergency management. At present, the new generation information technology such as big data and artificial intelligence has been widely used in natural disasters, safe production, and other fields. It has improved the monitoring and early warning, regulation and law enforcement, command and decision support, rescue, and social mobilization capabilities of governments, promoted the level of intrinsic safety of enterprises, provided important support for the precise prevention and control of the COVID-19, and increased the efficiency of China’s emergency management and sense …

Reflecting On The Advancements Of Hfref Therapies Over The Last Two Decades And Predicting What Is Yet To Come, Iliana L. Piña, Gregory T. Gibson, Shelley Zieroth, Rachna Kataria

Division of Cardiology Faculty Papers

What was once considered a topic best avoided, managing heart failure with reduced ejection fraction (HFrEF) has become the focus of many drug and device therapies. While the four pillars of guideline-directed medical therapies have successfully reduced heart failure hospitalizations, and some have even impacted cardiovascular mortality in randomized controlled trials (RCTs), patient-reported outcomes have emerged as important endpoints that merit greater emphasis in future studies. The prospect of an oral inotrope seems more probable now as targets for drug therapies have moved from neurohormonal modulation to intracellular mechanisms and direct cardiac myosin stimulation. While we have come a long …

On-Board Artificial Intelligence For Failure Detection And Safe Trajectory Generation, Eduardo Morillo

Doctoral Dissertations and Master's Theses

The use of autonomous flight vehicles has recently increased due to their versatility and capability of carrying out different type of missions in a wide range of flight conditions. Adequate commanded trajectory generation and modification, as well as high-performance trajectory tracking control laws have been an essential focus of researchers given that integration into the National Air Space (NAS) is becoming a primary need. However, the operational safety of these systems can be easily affected if abnormal flight conditions are present, thereby compromising the nominal bounds of design of the system's flight envelop and trajectory following. This thesis focuses on …

Algorithmic Solutions To Combat Online Fake News, Xinyi Zhou

Dissertations - ALL

The unprecedented growth of new information producing, distributing, and consuming every moment on the Web has fostered the rise of ``fake news.'' Because of its detrimental effect on democracy, global economies, and public health, effectively combating online fake news has become an essential and urgent task.

This dissertation starts with making typological, theoretical, and empirical efforts to promote the public's comprehension of fake news and lay the foundation for algorithmically combating fake news. As there has been no universal definition of fake news, this dissertation discusses the definition of fake news from three dimensions: veracity, intention, and news, comparing it …

Predicting The Outcomes Of Internet-Based Cognitive Behavioral Therapy For Tinnitus: Applications Of Artificial Neural Network And Support Vector Machine, Hansapani Rodrigo, Eldré W. Beukes, Gerhard Andersson, Vinaya Manchaiah

School of Mathematical and Statistical Sciences Faculty Publications and Presentations

Purpose:

Internet-based cognitive behavioral therapy (ICBT) has been found to be effective for tinnitus management, although there is limited understanding about who will benefit the most from ICBT. Traditional statistical models have largely failed to identify the nonlinear associations and hence find strong predictors of success with ICBT. This study aimed at examining the use of an artificial neural network (ANN) and support vector machine (SVM) to identify variables associated with treatment success in ICBT for tinnitus.

Method:

The study involved a secondary analysis of data from 228 individuals who had completed ICBT in previous intervention studies. A 13-point reduction …

Data-Driven Deep Learning-Based Analysis On Thz Imaging, Haoyan Liu

Graduate Theses and Dissertations

Breast cancer affects about 12.5% of women population in the United States. Surgical operations are often needed post diagnosis. Breast conserving surgery can help remove malignant tumors while maximizing the remaining healthy tissues. Due to lacking effective real-time tumor analysis tools and a unified operation standard, re-excision rate could be higher than 30% among breast conserving surgery patients. This results in significant physical, physiological, and financial burdens to those patients. This work designs deep learning-based segmentation algorithms that detect tissue type in excised tissues using pulsed THz technology. This work evaluates the algorithms for tissue type classification task among freshly …

Automated Government For Vulnerable Citizens: Intermediating Rights, Sofia Ranchordás, Luisa Scarcella

William & Mary Bill of Rights Journal

Filing tax returns or applying for unemployment benefits are some of the most common government transactions. Yet interacting with tax and social security authorities is for many a source of government anxiety. Bureaucracy, regulatory delays, and the complexity of the administrative legal system have been regarded for decades as the key reasons for this problem. Digital government promised a solution in the shape of simplified forms, electronic filing, and better communication with citizens. In the United States, privately developed software systems such as TurboTax and MiDAS emerged as intermediaries between citizens and digital government, selling convenience and efficiency. These systems …

Automated License Plate Recognition Systems, Nicholas Noboa

Master's Theses and Capstones

Automated license plate recognition systems make use of machines learning coupled with traditional algorithmic programming to create software capable of identifying and transcribing vehicles’ license plates. From this point, automated license plate recognition systems can be capable of performing a variety of functions, including billing an account or querying the plate number against a database to identify vehicles of concern. These capabilities allow for an efficient method of autonomous vehicle identification, although the unmanned nature of these systems raises concerns over the possibility of their use for surveillance, be it against an individual or group. This thesis will explore the …

Divide-And-Conquer Distributed Learning: Privacy-Preserving Offloading Of Neural Network Computations, Lewis C.L. Brown

Graduate Theses and Dissertations

Machine learning has become a highly utilized technology to perform decision making on high dimensional data. As dataset sizes have become increasingly large so too have the neural networks to learn the complex patterns hidden within. This expansion has continued to the degree that it may be infeasible to train a model from a singular device due to computational or memory limitations of underlying hardware. Purpose built computing clusters for training large models are commonplace while access to networks of heterogeneous devices is still typically more accessible. In addition, with the rise of 5G networks, computation at the edge becoming …

Acceptability And Feasibility Of A Low-Cost Device For Gestational Age Assessment In A Low-Resource Setting: Qualitative Study, Angela Koech, Peris Muoga Musitia, Grace Mwashigadi, Mai-Lei Woo Kinshella, Marianne Vidler, Marleen Temmerman, Rachel Craik, J. Alison Noble, Peter Dadelszen Von Dadelszen, Aris T . Papageorghiou

Obstetrics and Gynaecology, East Africa

Background: Ultrasound for gestational age (GA) assessment is not routinely available in resource-constrained settings, particularly in rural and remote locations. The TraCer device combines a handheld wireless ultrasound probe and a tablet with artificial intelligence (AI)-enabled software that obtains GA from videos of the fetal head by automated measurements of the fetal transcerebellar diameter and head circumference.

Objective: The aim of this study was to assess the perceptions of pregnant women, their families, and health care workers regarding the feasibility and acceptability of the TraCer device in an appropriate setting.

Methods: A descriptive study using qualitative methods was conducted in …

Novel Technologies And Their Effect On The Customer Journey: Customers' Sentiment With Tesla App, Andrew Jaymes

Electronic Theses, Projects, and Dissertations

This culminating experience project explores how novel technologies, such as artificial intelligence (AI), the Internet of Things (IoT), and virtual and augmented reality (VR/AR), impact customer experience. The customer journey framework was used to analyze customers' responses to interactions with novel Technologies integrated into Tesla electric vehicles. After gathering customer response data from the Tesla Motors subreddit page, we were able to score customer experiences with the Tesla app, over-the-air software updates, and full self-driving features, using the NRC sentiment lexicon. Our results showed customers tended to express more positive sentiments than negative sentiments when describing their experiences with these …

Supporting Inclusive Learning Using Chatbots? A Chatbot-Led Interview Study, Sambhav Gupta, Yu Chen

Faculty Research, Scholarly, and Creative Activity

Supporting student academic success has been one of the major goals for higher education. However, low teacher-to-student ratio makes it difficult for students to receive sufficient and personalized support that they might want to. The advancement of artificial intelligence (AI) and conversational agents, such as chatbots, has provided opportunities for assisting learning for different types of students. This research aims at investigating the opportunities and requirements of chatbots as an intelligent helper to facilitate equity in learning. We developed a chatbot as an experimental platform to investigate the design opportunities of using chatbots to support inclusive learning. Through a chatbot-led …

Hard-Real-Time Computing Performance In A Cloud Environment, Alvin Cornelius Murphy

Engineering Management & Systems Engineering Theses & Dissertations

The United States Department of Defense (DoD) is rapidly working with DoD Services to move from multi-year (e.g., 7-10) traditional acquisition programs to a commercial industrybased approach for software development. While commercial technologies and approaches provide an opportunity for rapid fielding of mission capabilities to pace threats, the suitability of commercial technologies to meet hard-real-time requirements within a surface combat system is unclear. This research establishes technical data to validate the effectiveness and suitability of current commercial technologies to meet the hard-real-time demands of a DoD combat management system. (Moreland Jr., 2013) conducted similar research; however, microservices, containers, and container …

Protectbot: A Chatbot To Protect Children On Gaming Platforms, Anum Faraz

Theses

Online gaming no longer has limited access, as it has become available to a high percentage of children in recent years. Consequently, children are exposed to multifaceted threats, such as cyberbullying, grooming, and sexting. The online gaming industry is taking concerted measures to create a safe environment for children to play and interact with, such efforts remain inadequate and fragmented. Different approaches utilizing machine learning (ML) techniques to detect child predatory behavior have been designed to provide potential detection and protection in this context. After analyzing the available AI tools and solutions it was observed that the available solutions are …

Predicting Credit Ratings Using Deep Learning Models – An Analysis Of The Indian It Industry, Shweta Pol, Manoj Hudnurkar, Suhas Suresh Ambekar

Australasian Accounting, Business and Finance Journal

Due to the complexity of transactions and the availability of Big Data, many banks and financial institutions are reviewing their business models. Various tasks get involved in determining the credit worthiness like working with spreadsheets, manually gathering data from customers and corporations, etc. In this research paper, we aim to automate and analyze the credit ratings of the Information and technology industry in India. Various Deep-Learning models are incorporated to predict the credit rankings from highest to lowest separately for each company to find the best fit model. Factors like Share Capital, Depreciation & Amortisation, Intangible Assets, Operating Margin, inventory …

Big Data Affirmative Action, Peter N. Salib

Northwestern University Law Review

As a vast and ever-growing body of social-scientific research shows, discrimination remains pervasive in the United States. In education, work, consumer markets, healthcare, criminal justice, and more, Black people fare worse than whites, women worse than men, and so on. Moreover, the evidence now convincingly demonstrates that this inequality is driven by discrimination. Yet solutions are scarce. The best empirical studies find that popular interventions—like diversity seminars and antibias trainings—have little or no effect. And more muscular solutions—like hiring quotas or school busing—are now regularly struck down as illegal. Indeed, in the last thirty years, the Supreme Court has invalidated …

Predictive Modelling For Topic Handling Of Natural Language Dialogue With Virtual Agents, Lareina Milambiling

Electronic Thesis and Dissertation Repository

In this thesis, we aim to contribute to ongoing research in the field of human- computer dialogue and help move closer to the goal of having more realistic human-computer dialogue. We address the current challenge of topic handling in human-computer conversation by proposing a Topic Handler model that is designed in such a way that is flexible and compatible with third party dialogue systems. This model builds off of previously proposed dialogue grammars and systems and is based on speech act theory and conversation analysis. By employing feature engineering of existing dialogue act corpora and using this data in machine …

An Empirical Study Of Artifacts And Security Risks In The Pre-Trained Model Supply Chain, Wenxin Jiang, Nicholas Synovic, Rohan Sethi, Aryan Indarapu, Matt Hyattt, Taylor R. Schorlemmer, George K. Thiruvathukal, James C. Davis

Computer Science: Faculty Publications and Other Works

Deep neural networks achieve state-of-the-art performance on many tasks, but require increasingly complex architectures and costly training procedures. Engineers can reduce costs by reusing a pre-trained model (PTM) and fine-tuning it for their own tasks. To facilitate software reuse, engineers collaborate around model hubs, collections of PTMs and datasets organized by problem domain. Although model hubs are now comparable in popularity and size to other software ecosystems, the associated PTM supply chain has not yet been examined from a software engineering perspective.

We present an empirical study of artifacts and security features in 8 model hubs. We indicate the potential …

Open-Source Clinical Machine Learning Models: Critical Appraisal Of Feasibility, Advantages, And Challenges, Keerthi B. Harish, W. Nicholson Price Ii, Yindalon Aphinyanaphongs

Articles

Machine learning applications promise to augment clinical capabilities and at least 64 models have already been approved by the US Food and Drug Administration. These tools are developed, shared, and used in an environment in which regulations and market forces remain immature. An important consideration when evaluating this environment is the introduction of open-source solutions in which innovations are freely shared; such solutions have long been a facet of digital culture. We discuss the feasibility and implications of open-source machine learning in a health care infrastructure built upon proprietary information. The decreased cost of development as compared to drugs and …

Diagnostic Accuracy Of Artificial Intelligence For Detecting Gastrointestinal Luminal Pathologies: A Systematic Review And Meta-Analysis, Om Parkash, Asra Tus Saleha Siddiqui, Uswa Jiwani, Fahad Rind, Zahra Ali Padhani, Arjumand Rizvi, Zahra Hoodbhoy, Jai K. Das

Section of Gastroenterology

Background: Artificial Intelligence (AI) holds considerable promise for diagnostics in the field of gastroenterology. This systematic review and meta-analysis aims to assess the diagnostic accuracy of AI models compared with the gold standard of experts and histopathology for the diagnosis of various gastrointestinal (GI) luminal pathologies including polyps, neoplasms, and inflammatory bowel disease.
Methods: We searched PubMed, CINAHL, Wiley Cochrane Library, and Web of Science electronic databases to identify studies assessing the diagnostic performance of AI models for GI luminal pathologies. We extracted binary diagnostic accuracy data and constructed contingency tables to derive the outcomes of interest: sensitivity and specificity. …

A Guided Chatbot Learning Experience In The Science Classroom, Jennifer Davis

Department of Teaching, Learning, and Teacher Education: Dissertations, Theses, and Student Research

This dissertation describes a practitioner’s design-based development of a prototype chatbot to guide students in learning biological concepts of genetic mutations and protein synthesis. This chatbot’s architecture provides learning activities, feedback, and support throughout a series of short, connected lessons. The chatbot is designed to scaffold learners through a predict, observe, explain model of inquiry learning. It utilizes real-world phenomena to lead students through biology core ideas, science and engineering practices, and crosscutting concepts. Results of prototype testing include survey results in support of the proof of concept among both students and teachers, as well as accuracy measurements of chatbot …

A Scientometric Review Of Artificial Intelligence In Tourism (2000-2021), Rujun Wang, Yu Mu, Ying Huang

University of South Florida (USF) M3 Publishing

With the increase in the combination of artificial intelligence and the service industry, many applications of artificial intelligence in tourism have been gradually spawned. However, most of the existing research focuses on the algorithms and models of artificial intelligence, and few scholars have systematically reviewed the intersection of tourism and artificial intelligence, this study is based on scientometric, reviewing and sorting out 2689 relevant literature published in 2000-2021, and achieving the three purposes of status carding, hot spot snooping and trend prediction. First, through the participating locations, institutions and authors of collaborative networks, the main sources of AI-related research in …

Deepfake Fight: Ai-Powered Disinformation And Perfidy Under The Geneva Conventions, David Nicholas Allen

Notre Dame Journal on Emerging Technologies

Deception and disinformation are as much a part of the battlefield as bullets and bombs. However, just like with bullets and bombs, if the law does not properly regulate a capability’s use the capability could degrade faith in the law. In this respect, this paper examines deepfake technology, a modern artificial intelligence-based capability that can generate superficially-perfect yet wholly invented media content. The paper looks ahead to its potential future applications in armed conflict, processes the ways in which current law contemplates such deception, and distills recommendations for improving governance where needed.

In Defense Of (Virtuous) Autonomous Weapons, Don Howard

Notre Dame Journal on Emerging Technologies

I will argue, we can construct effective means for norming the use of autonomous weapons short of a total ban by building upon the foundation of existing requirements stipulated in Article 36 of Protocol I to the Geneva Conventions that all new weapons technologies be reviewed for compliance with the International Law of Armed Conflict (ILOAC) and International Humanitarian Law (IHL). I begin with a critical review of several of the most commonly encountered arguments in favor of a ban. That is followed by a discussion of the moral opportunities afforded by enhanced autonomy. I conclude with a concrete policy …

Ethical Ai In American Policing, Elizabeth E. Joh

Notre Dame Journal on Emerging Technologies

We know there are problems in the use of artificial intelligence in policing, but we don’t quite know what to do about them. One can also find many reports and white papers today offering principles for the responsible use of AI systems by the government, civil society organizations, and the private sector. Yet, largely missing from the current debate in the United States is a shared framework for thinking about the ethical and responsible use of AI that is specific to policing. There are many AI policy guidance documents now, but their value to the police is limited. Simply repeating …

Note: Regulating Artificial Intelligence: A Call For A United States Artificial Intelligence Agency, Noah John Kahekili Rosenberg

Notre Dame Journal on Emerging Technologies

this Note draws upon two examples of emerging AI technologies that demonstrate the need for federal regulation: autonomous vehicles (i.e., self-driving cars) and algorithm-based hiring software. Part I illustrates the public safety concerns associated with AI technologies by outlining the inadequacy of existing laws and regulations on autonomous vehicles. Part II addresses the shortcomings of current regulations on algorithm-based hiring software and the issue of discrimination and inherent bias in AI. Part III recommends the creation of a new federal agency to guide AI regulation and enforcement.

Using Artificial Intelligence In The Law Review Submissions Process, Brenda M. Simon

Faculty Scholarship

The use of artificial intelligence to help editors examine law review submissions may provide a way to improve an overburdened system. This Article is the first to explore the promise and pitfalls of using artificial intelligence in the law review submissions process. Technology-assisted review of submissions offers many possible benefits. It can simplify preemption checks, prevent plagiarism, detect failure to comply with formatting requirements, and identify missing citations. These efficiencies may allow editors to address serious flaws in the current selection process, including the use of heuristics that may result in discriminatory outcomes and dependence on lower-ranked journals to conduct …