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Feasible Form Parameter Design Of Complex Ship Hull Form Geometry, Thomas L. Mcculloch
Feasible Form Parameter Design Of Complex Ship Hull Form Geometry, Thomas L. Mcculloch
University of New Orleans Theses and Dissertations
This thesis introduces a new methodology for robust form parameter design of complex hull form geometry via constraint programming, automatic differentiation, interval arithmetic, and truncated hierarchical B- splines. To date, there has been no clearly stated methodology for assuring consistency of general (equality and inequality) constraints across an entire geometric form parameter ship hull design space. In contrast, the method to be given here can be used to produce guaranteed narrowing of the design space, such that infeasible portions are eliminated. Furthermore, we can guarantee that any set of form parameters generated by our method will be self consistent. It …
Bots, Bias And Big Data: Artificial Intelligence, Algorithmic Bias And Disparate Impact Liability In Hiring Practices, Mckenzie Raub
Bots, Bias And Big Data: Artificial Intelligence, Algorithmic Bias And Disparate Impact Liability In Hiring Practices, Mckenzie Raub
Arkansas Law Review
No abstract provided.
On The Exactitude Of Big Data: La Bêtise And Artificial Intelligence, Noel Fitzpatrick, John D. Kelleher
On The Exactitude Of Big Data: La Bêtise And Artificial Intelligence, Noel Fitzpatrick, John D. Kelleher
Articles
This article revisits the question of ‘la bêtise’ or stupidity in the era of Artificial Intelligence driven by Big Data, it extends on the questions posed by Gille Deleuze and more recently by Bernard Stiegler. However, the framework for revisiting the question of la bêtise will be through the lens of contemporary computer science, in particular the development of data science as a mode of analysis, sometimes, misinterpreted as a mode of intelligence. In particular, this article will argue that with the advent of forms of hype (sometimes referred to as the hype cycle) in relation to big data and …
A Model-Based Ai-Driven Test Generation System, Dionny Santiago
A Model-Based Ai-Driven Test Generation System, Dionny Santiago
FIU Electronic Theses and Dissertations
Achieving high software quality today involves manual analysis, test planning, documentation of testing strategy and test cases, and development of automated test scripts to support regression testing. This thesis is motivated by the opportunity to bridge the gap between current test automation and true test automation by investigating learning-based solutions to software testing. We present an approach that combines a trainable web component classifier, a test case description language, and a trainable test generation and execution system that can learn to generate new test cases. Training data was collected and hand-labeled across 7 systems, 95 web pages, and 17,360 elements. …
A Mathematical Framework On Machine Learning: Theory And Application, Bin Shi
A Mathematical Framework On Machine Learning: Theory And Application, Bin Shi
FIU Electronic Theses and Dissertations
The dissertation addresses the research topics of machine learning outlined below. We developed the theory about traditional first-order algorithms from convex opti- mization and provide new insights in nonconvex objective functions from machine learning. Based on the theory analysis, we designed and developed new algorithms to overcome the difficulty of nonconvex objective and to accelerate the speed to obtain the desired result. In this thesis, we answer the two questions: (1) How to design a step size for gradient descent with random initialization? (2) Can we accelerate the current convex optimization algorithms and improve them into nonconvex objective? For application, …
Csc 480 Artificial Intelligence, Ernest Battifarano, Nyc Tech-In-Residence Corps
Csc 480 Artificial Intelligence, Ernest Battifarano, Nyc Tech-In-Residence Corps
Open Educational Resources
No abstract provided.
Machine Learning For Ecosystem Services, Simon Willcock, Javier Martínez-López, Danny A.P. Hooftman, Kenneth J. Bagstad, Stefano Balbi, Alessia Marzo, Carlo Prato, Saverio Sciandrello, Giovanni Signorello
Machine Learning For Ecosystem Services, Simon Willcock, Javier Martínez-López, Danny A.P. Hooftman, Kenneth J. Bagstad, Stefano Balbi, Alessia Marzo, Carlo Prato, Saverio Sciandrello, Giovanni Signorello
Rubenstein School of Environment and Natural Resources Faculty Publications
Recent developments in machine learning have expanded data-driven modelling (DDM) capabilities, allowing artificial intelligence to infer the behaviour of a system by computing and exploiting correlations between observed variables within it. Machine learning algorithms may enable the use of increasingly available ‘big data’ and assist applying ecosystem service models across scales, analysing and predicting the flows of these services to disaggregated beneficiaries. We use the Weka and ARIES software to produce two examples of DDM: firewood use in South Africa and biodiversity value in Sicily, respectively. Our South African example demonstrates that DDM (64–91% accuracy) can identify the areas where …
Evaluating Prose Style Transfer With The Bible, Keith Carlson, Allen Riddell, Daniel Rockmore
Evaluating Prose Style Transfer With The Bible, Keith Carlson, Allen Riddell, Daniel Rockmore
Dartmouth Scholarship
In the prose style transfer task a system, provided with text input and a target prose style, produces output which preserves the meaning of the input text but alters the style. These systems require parallel data for evaluation of results and usually make use of parallel data for training. Currently, there are few publicly available corpora for this task. In this work, we identify a high-quality source of aligned, stylistically distinct text in different versions of the Bible. We provide a standardized split, into training, development and testing data, of the public domain versions in our corpus. This corpus is …
Writing A Moral Code: Algorithms For Ethical Reasoning By Humans And Machines, James F. Mcgrath, Ankur Gupta
Writing A Moral Code: Algorithms For Ethical Reasoning By Humans And Machines, James F. Mcgrath, Ankur Gupta
Scholarship and Professional Work - LAS
The moral and ethical challenges of living in community pertain not only to the intersection of human beings one with another, but also our interactions with our machine creations. This article explores the philosophical and theological framework for reasoning and decision-making through the lens of science fiction, religion, and artificial intelligence (both real and imagined). In comparing the programming of autonomous machines with human ethical deliberation, we discover that both depend on a concrete ordering of priorities derived from a clearly defined value system.
Artificial Intelligence For Cognitive Behavior Assessment In Children, Srujana Gattupalli
Artificial Intelligence For Cognitive Behavior Assessment In Children, Srujana Gattupalli
Computer Science and Engineering Dissertations
Cognitive impairments in early childhood can lead to poor academic performance and require proper remedial intervention at the appropriate time. ADHD a?ects about 6-7% of children and is a psychiatric neurodevelopmental disorder that is very hard to diagnose or tell apart from other disorders. Cognitive insu?ciencies hinder the development of working memory and can a?ect school success and even have long term e?ects that can result in low self-esteem and self-acceptance. The main aim of this research is to investigate development of an automated and non-intrusive system for assessing physical exercises related to the treatment and diagnosis of Attention De?cit …
Feeling Ai
SIGNED: The Magazine of The Hong Kong Design Institute
We all develop emotional connections to the devices we use; the smartphone that is a constant companion or the office printer that is a constant source of frustration. Soon, these machines might be able to respond in kind
The Effect Of Endgame Tablebases On Modern Chess Engines, Christopher D. Peterson
The Effect Of Endgame Tablebases On Modern Chess Engines, Christopher D. Peterson
Computer Engineering
Modern chess engines have the ability to augment their evaluation by using massive tables containing billions of positions and their memorized solutions. This report examines the importance of these tables to better understand the circumstances under which they should be used. The analysis conducted in this paper empirically examines differences in size and speed of memorized positions and their impacts on engine strength. Using this technique, situations where memorized tables improve play (and situations where they do not) are discovered.
Ai-Human Collaboration Via Eeg, Adam Noack
Ai-Human Collaboration Via Eeg, Adam Noack
All College Thesis Program, 2016-2019
As AI becomes ever more competent and integrated into our lives, the issue of AI-human goal misalignment looms larger. This is partially because there is often a rift between what humans explicitly command and what they actually mean. Most contemporary AI systems cannot bridge this gap. In this study we attempted to reconcile the goals of human and machine by using EEG signals from a human to help a simulated agent complete a task.
Will Artificial Intelligence Have Free-Will?, Guadalupe Rodriguez
Will Artificial Intelligence Have Free-Will?, Guadalupe Rodriguez
Frankenstein @ 200: Student Posters
Will Artificial Intelligence have free will the way the Creature did?
Evaluating Sequence Discovery Systems In An Abstraction-Aware Manner, Eoin Rogers, Robert J. Ross, John D. Kelleher
Evaluating Sequence Discovery Systems In An Abstraction-Aware Manner, Eoin Rogers, Robert J. Ross, John D. Kelleher
Conference papers
Activity discovery is a challenging machine learning problem where we seek to uncover new or altered behavioural patterns in sensor data. In this paper we motivate and introduce a novel approach to evaluating activity discovery systems. Pre-annotated ground truths, often used to evaluate the performance of such systems on existing datasets, may exist at different levels of abstraction to the output of the output produced by the system. We propose a method for detecting and dealing with this situation, allowing for useful ground truth comparisons. This work has applications for activity discovery, and also for related fields. For example, it …
Ai: Augmentation, More So Than Automation, Steven M. Miller
Ai: Augmentation, More So Than Automation, Steven M. Miller
Asian Management Insights
The take-up of Artificial Intelligence (AI)-enabled systems in organisations is expanding rapidly. Integrating AI-enabled automation with people into workplace processes and societal systems is a complex and evolving challenge. The articles takes a managerial perspective on how firms can effectively deploy human minds and intelligent machines in the workplace.
Artificial Intelligence: An Analysis Of Alan Turing’S Role In The Conception And Development Of Intelligent Machinery, Erika L. Furtado
Artificial Intelligence: An Analysis Of Alan Turing’S Role In The Conception And Development Of Intelligent Machinery, Erika L. Furtado
Selected Honors Theses
The purpose of this thesis is to follow the thread of Alan Turing’s ideas throughout his decades of research and analyze how his predictions have come to fruition over the years. Turing’s Computing Machinery and Intelligence is the paper in which the Turing Test is described as an alternative way to answer the question “can machines think?” (Turing 433). Since the development of Turing’s original paper, there has been a tremendous amount of advancement in the field of artificial intelligence. The field has made its way into art classification as well as the medical industry. The main concept researched in …
Using Latent Variable Models To Improve Causal Estimation, Huseyin Oktay
Using Latent Variable Models To Improve Causal Estimation, Huseyin Oktay
Doctoral Dissertations
Estimating the causal effect of a treatment from data has been a key goal for a large number of studies in many domains. Traditionally, researchers use carefully designed randomized experiments for causal inference. However, such experiments can not only be costly in terms of time and money but also infeasible for some causal questions. To overcome these challenges, causal estimation methods from observational data have been developed by researchers from diverse disciplines and increasingly studies using such methods account for a large share in empirical work. Such growing interest has also brought together two arguably separate fields: machine learning and …
Sosiel: A Cognitive, Multi-Agent, And Knowledge-Based Platform For Modeling Boundedly-Rational Decision-Making, Garry Sotnik
Sosiel: A Cognitive, Multi-Agent, And Knowledge-Based Platform For Modeling Boundedly-Rational Decision-Making, Garry Sotnik
Dissertations and Theses
Decision-related activities, such as bottom-up and top-down policy development, analysis, and planning, stand to benefit from the development and application of computer-based models that are capable of representing spatiotemporal social human behavior in local contexts. This is especially the case with our efforts to understand and search for ways to mitigate the context-specific effects of climate change, in which case such models need to include interacting social and ecological components. The development and application of such models has been significantly hindered by the challenges in designing artificial agents whose behavior is grounded in both empirical evidence and theory and in …
Resistance Is Futile: Embracing The Era Of The Augmented Worker, Nathaniel Barr, Kelly Peters
Resistance Is Futile: Embracing The Era Of The Augmented Worker, Nathaniel Barr, Kelly Peters
Publications and Scholarship
The prospect of A.I.-augmented workers is both promising and unsettling: How can employees and firms ensure that they get the benefits of A.I. without erasing uniquely human strengths?
Measuring Goal Similarity Using Concept, Context And Task Features, Vahid Eyorokon
Measuring Goal Similarity Using Concept, Context And Task Features, Vahid Eyorokon
Browse all Theses and Dissertations
Goals can be described as the user's desired state of the agent and the world and are satisfied when the agent and the world are altered in such a way that the present state matches the desired state. For physical agents, they must act in the world to alter it in a series of individual atomic actions. Traditionally, agents use planning to create a chain of actions each of which altering the current world state and yielding a new one until the final action yields the desired goal state. Once this goal state has been achieved, the goal is said …
Ai Education Matters: Teaching Hidden Markov Models, Todd W. Neller
Ai Education Matters: Teaching Hidden Markov Models, Todd W. Neller
Computer Science Faculty Publications
In this column, we share resources for learning about and teaching Hidden Markov Models (HMMs). HMMs find many important applications in temporal pattern recognition tasks such as speech/handwriting/gesture recognition and robot localization. In such domains, we may have a finite state machine model with known state transition probabilities, state output probabilities, and state outputs, but lack knowledge of the states generating such outputs. HMMs are useful in framing problems where external sequential evidence is used to derive underlying state information (e.g. intended words and gestures). [excerpt]
Ai Education Matters: Lessons From A Kaggle Click-Through Rate Prediction Competition, Todd W. Neller
Ai Education Matters: Lessons From A Kaggle Click-Through Rate Prediction Competition, Todd W. Neller
Computer Science Faculty Publications
In this column, we will look at a particular Kaggle.com click-through rate (CTR) prediction competition, observe what the winning entries teach about this part of the machine learning landscape, and then discuss the valuable opportunities and resources this commends to AI educators and their students. [excerpt]
Artificial Intelligence And It Professionals, Sunil Mithas, Thomas Kude, Jonathan W. Whitaker
Artificial Intelligence And It Professionals, Sunil Mithas, Thomas Kude, Jonathan W. Whitaker
Management Faculty Publications
How will continuing developments in artificial intelligence (AI) and machine learning influence IT professionals? This article approaches this question by identifying the factors that influence the demand for software developers and IT professionals, describing how these factors relate to AI, and articulating the likely impact on IT professionals.
Fundamentals Of Neutrosophic Logic And Sets And Their Role In Artificial Intelligence (Fundamentos De La Lógica Y Los Conjuntos Neutrosóficos Y Su Papel En La Inteligencia Artificial ), Florentin Smarandache, Maykel Leyva-Vazquez
Fundamentals Of Neutrosophic Logic And Sets And Their Role In Artificial Intelligence (Fundamentos De La Lógica Y Los Conjuntos Neutrosóficos Y Su Papel En La Inteligencia Artificial ), Florentin Smarandache, Maykel Leyva-Vazquez
Branch Mathematics and Statistics Faculty and Staff Publications
Neutrosophy is a new branch of philosophy which studies the origin, nature and scope of neutralities. This has formed the basis for a series of mathematical theories that generalize the classical and fuzzy theories such as the neutrosophic sets and the neutrosophic logic. In the paper, the fundamental concepts related to neutrosophy and its antecedents are presented. Additionally, fundamental concepts of artificial intelligence will be defined and how neutrosophy has come to strengthen this discipline.
Development Of A Locomotion And Balancing Strategy For Humanoid Robots, Emile Bahdi
Development Of A Locomotion And Balancing Strategy For Humanoid Robots, Emile Bahdi
Electronic Theses and Dissertations
The locomotion ability and high mobility are the most distinguished features of humanoid robots. Due to the non-linear dynamics of walking, developing and controlling the locomotion of humanoid robots is a challenging task. In this thesis, we study and develop a walking engine for the humanoid robot, NAO, which is the official robotic platform used in the RoboCup Spl. Aldebaran Robotics, the manufacturing company of NAO provides a walking module that has disadvantages, such as being a black box that does not provide control of the gait as well as the robot walk with a bent knee. The latter disadvantage, …
Rnn-Based Generation Of Polyphonic Music And Jazz Improvisation, Andrew Hannum
Rnn-Based Generation Of Polyphonic Music And Jazz Improvisation, Andrew Hannum
Electronic Theses and Dissertations
This paper presents techniques developed for algorithmic composition of both polyphonic music, and of simulated jazz improvisation, using multiple novel data sources and the character-based recurrent neural network architecture char-rnn. In addition, techniques and tooling are presented aimed at using the results of the algorithmic composition to create exercises for musical pedagogy.
Bringing Defensive Artificial Intelligence Capabilities To Mobile Devices, Kevin Chong, Ahmed Ibrahim
Bringing Defensive Artificial Intelligence Capabilities To Mobile Devices, Kevin Chong, Ahmed Ibrahim
Australian Information Security Management Conference
Traditional firewalls are losing their effectiveness against new and evolving threats today. Artificial intelligence (AI) driven firewalls are gaining popularity due to their ability to defend against threats that are not fully known. However, a firewall can only protect devices in the same network it is deployed in, leaving mobile devices unprotected once they leave the network. To comprehensively protect a mobile device, capabilities of an AI-driven firewall can enhance the defensive capabilities of the device. This paper proposes porting AI technologies to mobile devices for defence against today’s ever-evolving threats. A defensive AI technique providing firewall-like capability is being …
Special Issue: Neutrosophic Information Theory And Applications, Florentin Smarandache, Jun Ye
Special Issue: Neutrosophic Information Theory And Applications, Florentin Smarandache, Jun Ye
Branch Mathematics and Statistics Faculty and Staff Publications
Neutrosophiclogic,symboliclogic,set,probability,statistics,etc.,are,respectively,generalizations of fuzzy and intuitionistic fuzzy logic and set, classical and imprecise probability, classical statistics, and so on. Neutrosophic logic, symbol logic, and set are gaining significant attention in solving many real-life problems that involve uncertainty, impreciseness, vagueness, incompleteness, inconsistency, and indeterminacy. A number of new neutrosophic theories have been proposed and have been applied in computational intelligence, multiple-attribute decision making, image processing, medical diagnosis, fault diagnosis, optimization design, etc. This Special Issue gathers original research papers that report on the state of the art, as well as on recent advancements in neutrosophic information theory in soft computing, artificial intelligence, …
Deep Learning Methods For Visual Object Recognition, Zeyad Hailat
Deep Learning Methods For Visual Object Recognition, Zeyad Hailat
Wayne State University Dissertations
Convolutional neural networks (CNNs) attain state-of-the-art performance on various classification tasks assuming a sufficiently large number of labeled training examples. Unfortunately, curating sufficiently large labeled training dataset requires human involvement, which is expensive, time-consuming, and susceptible to noisy labels. Semi-supervised learning methods can alleviate the aforementioned problems by employing one of two techniques. First, utilizing a limited number of labeled data in conjunction with sufficiently large unlabeled data to construct a classification model. Second, exploiting sufficiently large noisy label training data to learn a classification model. In this dissertation, we proposed a few new methods to mitigate the aforementioned problems. …