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Articles 151 - 180 of 283
Full-Text Articles in Physical Sciences and Mathematics
Approaching Hanabi With Q-Learning And Evolutionary Algorithm, Joseph Palmersten
Approaching Hanabi With Q-Learning And Evolutionary Algorithm, Joseph Palmersten
Culminating Projects in Computer Science and Information Technology
Hanabi is a cooperative card game with hidden information that requires cooperation and communication between the players. For a machine learning agent to be successful at the Hanabi, it will have to learn how to communicate and infer information from the communication of other players. To approach the problem of Hanabi the machine learning methods of Q-learning and Evolutionary algorithm are proposed as potential solutions. The agents that were created using the method are shown to not achieve human levels of communication.
Attentional Parsing Networks, Marcus Karr
Attentional Parsing Networks, Marcus Karr
Master's Theses
Convolutional neural networks (CNNs) have dominated the computer vision field since the early 2010s, when deep learning largely replaced previous approaches like hand-crafted feature engineering and hierarchical image parsing. Meanwhile transformer architectures have attained preeminence in natural language processing, and have even begun to supplant CNNs as the state of the art for some computer vision tasks.
This study proposes a novel transformer-based architecture, the attentional parsing network, that reconciles the deep learning and hierarchical image parsing approaches to computer vision. We recast unsupervised image representation as a sequence-to-sequence translation problem where image patches are mapped to successive layers …
Communicating Uncertain Information From Deep Learning Models In Human Machine Teams, Harishankar V. Subramanian, Casey I. Canfield, Daniel Burton Shank, Luke Andrews, Cihan H. Dagli
Communicating Uncertain Information From Deep Learning Models In Human Machine Teams, Harishankar V. Subramanian, Casey I. Canfield, Daniel Burton Shank, Luke Andrews, Cihan H. Dagli
Engineering Management and Systems Engineering Faculty Research & Creative Works
The role of human-machine teams in society is increasing, as big data and computing power explode. One popular approach to AI is deep learning, which is useful for classification, feature identification, and predictive modeling. However, deep learning models often suffer from inadequate transparency and poor explainability. One aspect of human systems integration is the design of interfaces that support human decision-making. AI models have multiple types of uncertainty embedded, which may be difficult for users to understand. Humans that use these tools need to understand how much they should trust the AI. This study evaluates one simple approach for communicating …
Tag: Automated Image Captioning, Nathan Funckes
Tag: Automated Image Captioning, Nathan Funckes
McNair Scholars Manuscripts
Many websites remain non-ADA compliant, containing images which lack accompanying textual descriptions. This leaves sight-impaired individuals unable to fully enjoy the rich wonders of the web. To address this inequity, our research aims to create an autonomous system capable of generating semantically accurate descriptions of images. This problem involves two tasks: recognizing an image and linguistically describing it. Our solution uses state-of-the-art deep learning: employing a convolutional neural network that "learns" to understand images and extracts their salient features, and a recurrent neural network that learns to generate structured, coherent sentences. These two networks are merged to create a single …
Rethinking Mistake In The Age Of Algorithms: Quoine Pte Ltd V B2c2 Ltd, Vincent Ooi, Kian Peng Soh
Rethinking Mistake In The Age Of Algorithms: Quoine Pte Ltd V B2c2 Ltd, Vincent Ooi, Kian Peng Soh
Research Collection Yong Pung How School Of Law
Good traders remove emotion from the decision-making process. Automated trading algorithms have enabled this, allowing one to trade round the clock, and without the constant need to monitor one’s investments. But software has gremlins. Given the vast amounts of money involved in such trades, it was only a matter of time before disputes involving automated trading software came before the courts. The decision in Quoine v B2C2 (“Quoine”) represents the first time an apex court in the Commonwealth has ruled on the applicability of contractual principles to situations involving automated trading software.
Machine Learning Applications For Drug Repurposing, Hansaim Lim
Machine Learning Applications For Drug Repurposing, Hansaim Lim
Dissertations, Theses, and Capstone Projects
The cost of bringing a drug to market is astounding and the failure rate is intimidating. Drug discovery has been of limited success under the conventional reductionist model of one-drug-one-gene-one-disease paradigm, where a single disease-associated gene is identified and a molecular binder to the specific target is subsequently designed. Under the simplistic paradigm of drug discovery, a drug molecule is assumed to interact only with the intended on-target. However, small molecular drugs often interact with multiple targets, and those off-target interactions are not considered under the conventional paradigm. As a result, drug-induced side effects and adverse reactions are often neglected …
Machine Learning Enhanced Free-Space And Underwater Oam Optical Communications, Patrick L. Neary
Machine Learning Enhanced Free-Space And Underwater Oam Optical Communications, Patrick L. Neary
All Graduate Theses and Dissertations, Spring 1920 to Summer 2023
Communications, bandwidth, security, and hardware simplicity are principles of interest to society at large. Recent advances in optics and in understanding properties of light, such as orbital angular momentum (OAM), have provided new potential mediums for communication.
Machine learning has wound its way into a broad range of fascinating areas. An emerging field of research is the use of a unique property of lasers called orbital angular momentum (OAM). With the proper hardware, a laser can go from a Gaussian shaped distribution to a doughnut shaped pattern, where the radius can be changed. Multiple OAM patterns, or modes, can be …
Information Retrieval-Based Optimization Approaches For Requirement Traceability Recovery, Danissa Victoria Rodriguez Caraballo
Information Retrieval-Based Optimization Approaches For Requirement Traceability Recovery, Danissa Victoria Rodriguez Caraballo
LSU Doctoral Dissertations
Requirements traceability provides support for important software engineering activities. Requirements traceability recovery (RTR) is becoming increasingly important due to the numerous benefits to the overall quality of software. Improving the RTR problem has become an active topic of research for software engineers; researchers have proposed a number of approaches for improving and automating RTR across the requirements and the source code of the system. Textual analysis and Information Retrieval (IR) techniques have been applied to the RTR problem for many years; however, most of the existing IR-based methodologies applied to the RTR problem are semiautomatic or time-consuming, even though many …
Subsurface Analytics: Contribution Of Artificial Intelligence And Machine Learning To Reservoir Engineering, Reservoir Modeling, And Reservoir Management, Shahab D. Mohaghegh
Subsurface Analytics: Contribution Of Artificial Intelligence And Machine Learning To Reservoir Engineering, Reservoir Modeling, And Reservoir Management, Shahab D. Mohaghegh
Faculty & Staff Scholarship
Subsurface Analytics is a new technology that changes the way reservoir simulation and modeling is performed. Instead of starting with the construction of mathematical equations to model the physics of the fluid flow through porous media and then modification of the geological models in order to achieve history match, Subsurface Analytics that is a completely AI-based reservoir simulation and modeling technology takes a completely different approach. In AI-based reservoir modeling, field measurements form the foundation of the reservoir model. Using data-driven, pattern recognition technologies; the physics of the fluid flow through porous media is modeled through discovering the best, most …
Artificial Intelligence Towards The Wireless Channel Modeling Communications In 5g, Saud Mobark Aldossari
Artificial Intelligence Towards The Wireless Channel Modeling Communications In 5g, Saud Mobark Aldossari
USF Tampa Graduate Theses and Dissertations
Channel prediction is a mathematical predicting of the natural propagation of the signal that helps the receiver to approximate the affected signal, which plays an important role in highly mobile or dynamic channels. The standard wireless communication channel modeling can be facilitated by either deterministic or stochastic channel methodologies. The deterministic approach is based on the electromagnetic theories and every single object in that environment has to be known in that propagation space and an example of this method is ray tracing. While the stochastic modeling method is based on measurements that involve statistical distributions of the channel parameters and …
Keeping Ai Under Observation: Anticipated Impacts On Physicians' Standard Of Care, Iria Giuffrida, Taylor Treece
Keeping Ai Under Observation: Anticipated Impacts On Physicians' Standard Of Care, Iria Giuffrida, Taylor Treece
Faculty Publications
As Artificial Intelligence (AI) tools become increasingly present across industries, concerns have started to emerge as to their impact on professional liability. Specifically, for the medical industry--in many ways an inherently "risky" business--hospitals and physicians have begun evaluating the impact of Al tools on their professional malpractice risk. This Essay seeks to address that question, zooming in on how AI may affect physicians' standard of care for medical malpractice claims.
From Cellular To Holistic: Development Of Algorithms To Study Human Health And Diseases, Casey Anne Cole
From Cellular To Holistic: Development Of Algorithms To Study Human Health And Diseases, Casey Anne Cole
Theses and Dissertations
The development of theoretical computational methods and their application has become widespread in the world today. In this dissertation, I present my work in the creation of models to detect and describe complex biological and health related problems. The first major part of my work centers around the creation and enhancement of methods to calculate protein structure and dynamics. To this end, substantial enhancement has been made to the software package REDCRAFT to better facilitate its usage in protein structure calculation. The enhancements have led to an overall increase in its ability to characterize proteins under difficult conditions such as …
Autonomous Trading Strategies For Dynamic Energy Markets, Moinul Morshed Porag Chowdhury
Autonomous Trading Strategies For Dynamic Energy Markets, Moinul Morshed Porag Chowdhury
Open Access Theses & Dissertations
With increasing energy demand and an intermittent supply of renewable energy sources, our current energy grid needs a transformation towards a more robust, reliable energy trading architecture. The smart grid promises this architecture as the future of the present energy market, where traders will use digital technologies to automate the management of power delivery. It will improve many issues of the current energy grid such as sustainable, clean, renewable, reliable and secure energy supply, customer participation in markets, distributed generation, and transparency in energy trading. Using autonomous trading agents, we can bridge several dynamic energy markets and ensure an efficient …
Customer And Employee Social Media Comments/Feedback And Stock Purchasing Decisions Enhanced By Sentiment Analysis, Drew Mikel Hall
Customer And Employee Social Media Comments/Feedback And Stock Purchasing Decisions Enhanced By Sentiment Analysis, Drew Mikel Hall
Walden Dissertations and Doctoral Studies
The U.S. Securities and Exchange Commission (SEC) warns professional investors that sentiment analysis tools may lead to impulsive investment decision-making. This warning comes despite evidence showing that aided social sentiment investment decision tools can increase accurate investment decision-making by 18%. Using Fama's theory of efficient market hypothesis, the purpose of this quantitative correlational study was to examine whether customer Twitter comments and employee Glassdoor feedback sentiment predicted successful investing decisions measured by business stock prices. Two thousand records from 3 archival U.S. public NASDAQ 100 datasets from March 28, 2016, to June 15, 2016 (79 days) of 53 companies with …
Potential Impacts Of Artificial Intelligence On Spine Imaging Interpretation And Diagnosis, David Howard Durrant
Potential Impacts Of Artificial Intelligence On Spine Imaging Interpretation And Diagnosis, David Howard Durrant
Walden Dissertations and Doctoral Studies
Spine and related disorders represent one of the most common causes of pain and disability in the United States. Imaging represents an important diagnostic procedure in spine care. Imaging studies contain actionable data and insights undetectable through routine visual analysis. Convergent advances in imaging, artificial intelligence (AI), and radiomic methods has revealed the potential of multiscale in vivo interrogation to improve the assessment and monitoring of pathology. AI offers various types of decision support through the analysis of structured and unstructured data. The primary purpose of this qualitative exploratory case study was to identify the potential impacts of AI solutions …
A Mathematical Analysis Of The Game Of Santorini, Carson Clyde Geissler
A Mathematical Analysis Of The Game Of Santorini, Carson Clyde Geissler
Senior Independent Study Theses
Santorini is a two player combinatorial board game. Santorini bears resemblance to the graph theory game of Geography, a game of moving and deleting vertices on a graph. We explore Santorini with game theory, complexity theory, and artificial intelligence. We present David Lichtenstein’s proof that Geography is PSPACE-hard and adapt the proof for generalized forms of Santorini. Last, we discuss the development of an AI built for a software implementation of Santorini and present a number of improvements to that AI.
Perceptions, Potholes, And Possibilities Of Using Digital Voice Assistants To Differentiate Instructions, Adrian A. Weir
Perceptions, Potholes, And Possibilities Of Using Digital Voice Assistants To Differentiate Instructions, Adrian A. Weir
Walden Dissertations and Doctoral Studies
Access to technologies and understanding the potential uses of technology to differentiate instruction have been a concern for the teachers and students in a local school district located in the southeastern United States. Despite the emergence of digital voice assistants (DVAs) as tools for instructions, teachers lack knowledge and strategies for using DVAs to differentiate instruction in their classrooms. The purpose of this qualitative study was to identify teacher knowledge and strategies employed among special education (SPED) teachers using DVAs to differentiate instruction in their classrooms. The concepts of Carol Tomlinson’s differentiation theory and Mishra and Koehler’s TPACK framework served …
Incorporating Cardiac Substructures Into Radiation Therapy For Improved Cardiac Sparing, Eric Daniel Morris
Incorporating Cardiac Substructures Into Radiation Therapy For Improved Cardiac Sparing, Eric Daniel Morris
Wayne State University Dissertations
Growing evidence suggests that radiation therapy (RT) doses to the heart and cardiac substructures (CS) are strongly linked to cardiac toxicities, though only the heart is considered clinically. This work aimed to utilize the superior soft-tissue contrast of magnetic resonance (MR) to segment CS, quantify uncertainties in their position, assess their effect on treatment planning and an MR-guided environment.
Automatic substructure segmentation of 12 CS was completed using a novel hybrid MR/computed tomography (CT) atlas method and was improved upon using a 3-dimensional neural network (U-Net) from deep learning. Intra-fraction motion due to respiration was then quantified. The inter-fraction setup …
Development Of A Modeling Algorithm To Predict Lean Implementation Success, Richard Charles Barclay
Development Of A Modeling Algorithm To Predict Lean Implementation Success, Richard Charles Barclay
Doctoral Dissertations
”Lean has become a common term and goal in organizations throughout the world. The approach of eliminating waste and continuous improvement may seem simple on the surface but can be more complex when it comes to implementation. Some firms implement lean with great success, getting complete organizational buy-in and realizing the efficiencies foundational to lean. Other organizations struggle to implement lean. Never able to get the buy-in or traction needed to really institute the sort of cultural change that is often needed to implement change. It would be beneficial to have a tool that organizations could use to assess their …
Artificial Neural Network Models For Pattern Discovery From Ecg Time Series, Mehakpreet Kaur
Artificial Neural Network Models For Pattern Discovery From Ecg Time Series, Mehakpreet Kaur
Electronic Theses and Dissertations
Artificial Neural Network (ANN) models have recently become de facto models for deep learning with a wide range of applications spanning from scientific fields such as computer vision, physics, biology, medicine to social life (suggesting preferred movies, shopping lists, etc.). Due to advancements in computer technology and the increased practice of Artificial Intelligence (AI) in medicine and biological research, ANNs have been extensively applied not only to provide quick information about diseases, but also to make diagnostics accurate and cost-effective. We propose an ANN-based model to analyze a patient's electrocardiogram (ECG) data and produce accurate diagnostics regarding possible heart diseases …
Human Path Prediction Using Auto Encoder Lstms And Single Temporal Encoders, Hayden Hudgins
Human Path Prediction Using Auto Encoder Lstms And Single Temporal Encoders, Hayden Hudgins
Master's Theses
Due to automation, the world is changing at a rapid pace. Autonomous agents have become more common over the last several years and, as a result, have created a need for improved software to back them up. The most important aspect of this greater software is path prediction, as robots need to be able to decide where to move in the future. In order to accomplish this, a robot must know how to avoid humans, putting frame prediction at the core of many modern day solutions. A popular way to solve this complex problem of frame prediction is Auto Encoder …
You Might Be A Robot, Bryan Casey, Mark A. Lemley
You Might Be A Robot, Bryan Casey, Mark A. Lemley
Cornell Law Review
As robots and artificial intelligence (Al) increase their influence over society, policymakers are increasingly regulating them. But to regulate these technologies, we first need to know what they are. And here we come to a problem. No one has been able to offer a decent definition of robots arid AI-not even experts. What's more, technological advances make it harder and harder each day to tell people from robots and robots from "dumb" machines. We have already seen disastrous legal definitions written with one target in mind inadvertently affecting others. In fact, if you are reading this you are (probably) not …
Landing Throttleable Hybrid Rockets With Hierarchical Reinforcement Learning In A Simulated Environment, Francesco Alessandro Stefano Mikulis-Borsoi
Landing Throttleable Hybrid Rockets With Hierarchical Reinforcement Learning In A Simulated Environment, Francesco Alessandro Stefano Mikulis-Borsoi
Honors Theses and Capstones
In this paper, I develop a hierarchical Markov Decision Process (MDP) structure for completing the task of vertical rocket landing. I start by covering the background of this problem, and formally defining its constraints. In order to reduce mistakes while formulating different MDPs, I define and develop the criteria for a standardized MDP definition format. I then decompose the problem into several sub-problems of vertical landing, namely velocity control and vertical stability control. By exploiting MDP coupling and symmetrical properties, I am able to significantly reduce the size of the state space compared to a unified MDP formulation. This paper …
Multi-Agent Narrative Experience Management As Story Graph Pruning, Edward T. Garcia
Multi-Agent Narrative Experience Management As Story Graph Pruning, Edward T. Garcia
University of New Orleans Theses and Dissertations
In this thesis I describe a method where an experience manager chooses actions for non-player characters (NPCs) in intelligent interactive narratives through story graph representation and pruning. The space of all stories can be represented as a story graph where nodes are states and edges are actions. By shaping the domain as a story graph, experience manager decisions can be made by pruning edges. Starting with a full graph, I apply a set of pruning strategies that will allow the narrative to be finishable, NPCs to act believably, and the player to be responsible for how the story unfolds. By …
Liability For Ai Decision-Making: Some Legal And Ethical Considerations, Iria Giuffrida
Liability For Ai Decision-Making: Some Legal And Ethical Considerations, Iria Giuffrida
Faculty Publications
No abstract provided.
Wuji: Automatic Online Combat Game Testing Using Evolutionary Deep Reinforcement Learning, Yan Zheng, Xiaofei Xie, Ting Su, Lei Ma, Jianye Hao, Zhaopeng Meng, Yang Liu, Ruimin Shen, Yingfeng Chen, Changjie Fan
Wuji: Automatic Online Combat Game Testing Using Evolutionary Deep Reinforcement Learning, Yan Zheng, Xiaofei Xie, Ting Su, Lei Ma, Jianye Hao, Zhaopeng Meng, Yang Liu, Ruimin Shen, Yingfeng Chen, Changjie Fan
Research Collection School Of Computing and Information Systems
—Game testing has been long recognized as a notoriously challenging task, which mainly relies on manual playing and scripting based testing in game industry. Even until recently, automated game testing still remains to be largely untouched niche. A key challenge is that game testing often requires to play the game as a sequential decision process. A bug may only be triggered until completing certain difficult intermediate tasks, which requires a certain level of intelligence. The recent success of deep reinforcement learning (DRL) sheds light on advancing automated game testing, without human competitive intelligent support. However, the existing DRLs mostly focus …
Artificial Intelligence And The Challenge For Rural Medicine, James Denvir
Artificial Intelligence And The Challenge For Rural Medicine, James Denvir
Marshall Journal of Medicine
Recent advances in artificial intelligence, machine learning, and deep learning are beginning to have an impact on everyday experiences, from natural language processing used in automated telephone call centers to semi-autonomous vehicles. These techniques have also been applied to medical care. In this editorial we discuss applications of AI to medicine and argue for a proactive approach to include rural medicine in this paradigm shift.
Court Record In The Age Of Artificial Intelligence, Fredric I. Lederer
Court Record In The Age Of Artificial Intelligence, Fredric I. Lederer
Popular Media
No abstract provided.
Designing Women: Essentializing Femininity In Ai Linguistics, Ellianie S. Vega
Designing Women: Essentializing Femininity In Ai Linguistics, Ellianie S. Vega
Student Publications
Since the eighties, feminists have considered technology a force capable of subverting sexism because of technology’s ability to produce unbiased logic. Most famously, Donna Haraway’s “A Cyborg Manifesto” posits that the cyborg has the inherent capability to transcend gender because of its removal from social construct and lack of loyalty to the natural world. But while humanoids and artificial intelligence have been imagined as inherently subversive to gender, current artificial intelligence perpetuates gender divides in labor and language as their programmers imbue them with traits considered “feminine.” A majority of 21st century AI and humanoids are programmed to fit female …
Implementing Facial Recognition Technology In A Municipal Archives Digitization Project, Rebecca Bakker
Implementing Facial Recognition Technology In A Municipal Archives Digitization Project, Rebecca Bakker
Works of the FIU Libraries
This poster at the 2019 annual meeting of the South Florida Archivists highlights a project where the facial recognition technology of Adobe Lightroom CC is used to identify individuals in photographs held by a local municipal archive. The photographs contain hundreds of images showing unnamed commissioners and city workers from the 1970s to the 1990s, with most of the images lacking metadata or information. Various strategies are employed to identify key city officials in the photographs, allowing their names to be added to the metadata of the records hosted in a digital repository. The poster demonstrates the potential and limitations …