Physical Sciences and Mathematics Commons^™

Binary Classifiers For Noisy Datasets: A Comparative Study Of Existing Quantum Machine Learning Frameworks And Some New Approaches, Nikolaos Schetakis, Davit Aghamalyan, Paul Robert Griffin, Michael Boguslavsky

Research Collection School Of Computing and Information Systems

This technology offer is a quantum machine learning algorithm applied to binary classification models for noisy datasets which are prevalent in financial and other datasets. By combining hybrid-neural networks, quantum parametric circuits, and data re-uploading we have improved the classification of non-convex 2-dimensional figures by understanding learning stability as noise increases in the dataset. The metric we use for assessing the performance of our quantum classifiers is the area under the receiver operator curve (ROC AUC). We are interested to collaborate with partners with use cases for binary classification of noisy data. Also, as quantum technology is still insufficient for …

The Ratio Method: Addressing Complex Tort Liability In The Fourth Industrial Revolution, Harrison C. Margolin, Grant H. Frazier

St. Mary's Law Journal

Emerging technologies of the Fourth Industrial Revolution show fundamental promise for improving productivity and quality of life, though their misuse may also cause significant social disruption. For example, while artificial intelligence will be used to accelerate society’s processes, it may also displace millions of workers and arm cybercriminals with increasingly powerful hacking capabilities. Similarly, human gene editing shows promise for curing numerous diseases, but also raises significant concerns about adverse health consequences related to the corruption of human and pathogenic genomes.

In most instances, only specialists understand the growing intricacies of these novel technologies. As the complexity and speed of …

Umaine Artificial Intelligence Webinar: Ai For Space And Aerospace Promotional Flyer, University Of Maine Artificial Intelligence, Institute Of Electrical And Electronics Engineers Maine Com/Cs Chapter, Vice President For Research And Dean Of The Graduate School

General University of Maine Publications

Promotional flyer for the first webinar in the UMaine Artificial Intelligence 2021-2022 webinar series.

The University of Maine Artificial Intelligence Initiative (UMaine AI) is a unique Maine-based venture that brings together university, industry, government, and community collaborators from Maine and beyond to advance the field of artificial intelligence, and through development of innovative technologies and applications find transformative solutions to enhance human life and societal well-being in Maine and beyond.

Deep Fakes: The Algorithms That Create And Detect Them And The National Security Risks They Pose, Nick Dunard

James Madison Undergraduate Research Journal (JMURJ)

The dissemination of deep fakes for nefarious purposes poses significant national security risks to the United States, requiring an urgent development of technologies to detect their use and strategies to mitigate their effects. Deep fakes are images and videos created by or with the assistance of AI algorithms in which a person’s likeness, actions, or words have been replaced by someone else’s to deceive an audience. Often created with the help of generative adversarial networks, deep fakes can be used to blackmail, harass, exploit, and intimidate individuals and businesses; in large-scale disinformation campaigns, they can incite political tensions around the …

Research On The Issues Of Next Generation Wargame System Model Engine, Yubo Tang, Bilong Shen, Shi Lei, Yi Xing

Journal of System Simulation

Abstract: Aiming at the more and more complex war systems, widely used artificial intelligence technology is needed to make up the human deficiencies in future wargame deduction, which is necessary for the next generation wargame system model engine. To address these challenges, a framework prototype of the next generation wargame model engine based on the experience of the long-term development and application is proposed. The decoupling method for the complexity of structure and computation is researched. The human-computer integration architecture on digital twinning technology is studied. Some new modeling techniques which the threshold of model development is reduced and the …

The Role Of Trust In Advice Acceptance From Non-Human Actors, Rahul Banerjee

Dissertations and Theses Collection (Open Access)

Advancements in technology are now allowing non-human actors in the form of robot-advisors, driverless cars, medical assistants to perform increasingly complex tasks. While technological change is as old as civilization, these non-human actors can do novel tasks. One such task is that they provide advice which is a credence service (Dulleck, & Kerschbamer, 2006). Using a financial services context this thesis studies the role trust plays in advice acceptance.

Robo-advisors are rapidly replacing human financial advisors as the agent-provider for portfolio investment services. For centuries, it was the banker (human financial advisor) who was responsible for providing his investors with …

Application Of Artificial Intelligence And Machine Learning In Libraries: A Systematic Review, Rajesh Kumar Das, Mohammad Sharif Ul Islam

Library Philosophy and Practice (e-journal)

As the concept and implementation of cutting-edge technologies like artificial intelligence and machine learning has become relevant, academics, researchers and information professionals involve research in this area. The objective of this systematic literature review is to provide a synthesis of empirical studies exploring application of artificial intelligence and machine learning in libraries. To achieve the objectives of the study, a systematic literature review was conducted based on the original guidelines proposed by Kitchenham et al. (2009). Data was collected from Web of Science, Scopus, LISA and LISTA databases. Following the rigorous/ established selection process, a total of thirty-two articles were …

Interpretability Of Ai In Computer Systems And Public Policy, Farzana Beente Yusuf

FIU Electronic Theses and Dissertations

Advances in Artificial Intelligence (AI) have led to spectacular innovations and sophisticated systems for tasks that were thought to be capable only by humans. Examples include playing chess and Go, face and voice recognition, driving vehicles, and more. In recent years, the impact of AI has moved beyond offering mere predictive models into building interpretable models that appeal to human logic and intuition because they ensure transparency and simplicity and can be used to make meaningful decisions in real-world applications. A second trend in AI is characterized by important advancements in the realm of causal reasoning. Identifying causal relationships is …

Machine Learning In Stock Price Prediction Using Long Short-Term Memory Networks And Gradient Boosted Decision Trees, Carl Samuel Cederborg

Honors Projects

Quantitative analysis has been a staple of the financial world and investing for many years. Recently, machine learning has been applied to this field with varying levels of success. In this paper, two different methods of machine learning (ML) are applied to predicting stock prices. The first utilizes deep learning and Long Short-Term Memory networks (LSTMs), and the second uses ensemble learning in the form of gradient tree boosting. Using closing price as the training data and Root Mean Squared Error (RMSE) as the error metric, experimental results suggest the gradient boosting approach is more viable.

Honors Symposium: ML is …

The Future Of Artificial Intelligence In The Healthcare Industry, Erika Bonnist

Honors Theses

Technology has played an immense role in the evolution of healthcare delivery for the United States and on an international scale. Today, perhaps no innovation offers more potential than artificial intelligence. Utilizing machine intelligence as opposed to human intelligence for the purposes of planning, offering solutions, and providing insights, AI has the ability to alter traditional dynamics between doctors, patients, and administrators; this reality is now producing both elation at artificial intelligence's medical promise and uncertainty regarding its capacity in current systems. Nevertheless, current trends reveal that interest in AI among healthcare stakeholders is continuously increasing, and with the current …

Recommender App Development For Essential Health Products : Covid And Beyond, Jessica Lourenco

Theses, Dissertations and Culminating Projects

The COVID-19 pandemic has affected all of our lives in many ways and as a result people have become more health conscious. Now more than ever it is critical to take cautious steps to prevent being infected and spreading the virus. It is important to be supplied with the right products that maintain us all safe and healthy. Although many stores have health related products, sometimes it is a hassle to find them and even to pick out the best ones. With that, the Health Essentials app was developed to facilitate the findings of health products. The app is solely …

The Power Of The "Internet Of Things" To Mislead And Manipulate Consumers: A Regulatory Challenge, Kate Tokeley

Notre Dame Journal on Emerging Technologies

The “Internet of Things” revolution is on its way, and with it comes an unprecedented risk of unregulated misleading marketing and a dramatic increase in the power of personalized manipulative marketing. IoT is a term that refers to a growing network of internet-connected physical “smart” objects accumulating in our homes and cities. These include “smart” versions of traditional objects such as refrigerators, thermostats, watches, toys, light bulbs, cars, and Alexa-style digital assistants. The corporations who develop IoT are able to utilize a far greater depth of data than is possible from merely tracking our web browsing in regular online environments. …

Datascope: Predictive Diagnosis In Iiot-Enabled Smart Manufacturing, Adam Geltz, Reilly Sollenberger, Peilong Li

Summer Scholarship, Creative Arts and Research Projects (SCARP)

This a collaborative project between Elizabethtown College and CPNet, LLC that is looking to help apply predictive modeling with CPNet’s domain knowledge to one of CPNet’s clients' IIoT manufacturing problems. CPNet has provided us with datasets taken from one of their clients in the hope that we can build a model that will be able to predict when a part within the machines they are looking at will fail and subsequently shut the machine down. We are trying to take their data and turn it into information that the company can take preemptive action on and save them downtime during …

Law Library Blog (January 2021): Legal Beagle's Blog Archive, Roger Williams University School Of Law

Law Library Newsletters/Blog

No abstract provided.

Interpretable, Not Black-Box, Artificial Intelligence Should Be Used For Embryo Selection, Michael Anis Mihdi Afnan, Yanhe Liu, Vincent Conitzer, Cynthia Rudin, Abhishek Mishra, Julian Savulescu, Masoud Afnan

Research outputs 2014 to 2021

Artificial intelligence (AI) techniques are starting to be used in IVF, in particular for selecting which embryos to transfer to the woman. AI has the potential to process complex data sets, to be better at identifying subtle but important patterns, and to be more objective than humans when evaluating embryos. However, a current review of the literature shows much work is still needed before AI can be ethically implemented for this purpose. No randomized controlled trials (RCTs) have been published, and the efficacy studies which exist demonstrate that algorithms can broadly differentiate well between ‘good-’ and ‘poor-’ quality embryos but …

Administrative Law In The Automated State, Cary Coglianese

All Faculty Scholarship

In the future, administrative agencies will rely increasingly on digital automation powered by machine learning algorithms. Can U.S. administrative law accommodate such a future? Not only might a highly automated state readily meet longstanding administrative law principles, but the responsible use of machine learning algorithms might perform even better than the status quo in terms of fulfilling administrative law’s core values of expert decision-making and democratic accountability. Algorithmic governance clearly promises more accurate, data-driven decisions. Moreover, due to their mathematical properties, algorithms might well prove to be more faithful agents of democratic institutions. Yet even if an automated state were …

Human-Ai Teaming For Dynamic Interpersonal Skill Training, Xavian Alexander Ogletree

Browse all Theses and Dissertations

In almost every field, there is a need for strong interpersonal skills. This is especially true in fields such as medicine, psychology, and education. For instance, healthcare providers need to show understanding and compassion for LGBTQ+ and BIPOC (Black, Indigenous, and People of Color), or individuals with unique developmental or mental health needs. Improving interpersonal skills often requires first-person experience with expert evaluation and guidance to achieve proficiency. However, due to limited availability of assessment capabilities, professional standardized patients and instructional experts, students and professionals currently have inadequate opportunities for expert-guided training sessions. Therefore, this research aims to demonstrate leveraging …

Playing Pong Using Q-Learning, Akash Kumar

West Chester University Master’s Theses

This thesis involves the use of a reinforcement learning algorithm (RL) called Q-learning to train a Q-agent to play a game of Pong against a near-perfect opponent. Compared to previously related work which trained Pong RL agents by combining Q-learning with deep learning in an algorithm known as Deep Q-Networks, the work presented in this paper takes advantage of known environment constraints of the custom-made Pong environment to train the agent using one-step Q-learning alone. In addition, the thesis explores ways of making the Q-learning more efficient by converting Markov Decision Processes (MDPs) to Partially Observable Markov Decision Processes (POMDPs), …

Technology And The (Re)Construction Of Law, Christian Sundquist

Articles

Innovative advancements in technology and artificial intelligence have created a unique opportunity to re-envision both legal education and the practice of law. The COVID-19 pandemic has accelerated the technological disruption of both legal education and practice, as remote work, “Zoom” client meetings, virtual teaching, and online dispute resolution have become increasingly normalized. This essay explores how technological innovations in the coronavirus era are facilitating radical changes to our traditional adversarial system, the practice of law, and the very meaning of “legal knowledge.” It concludes with suggestions on how to reform legal education to better prepare our students for the emerging …