Physical Sciences and Mathematics Commons^™

The Disciple: A Talking Platformer, Benjamin Sernau

Senior Projects Spring 2017

Working in Unity to create a two-dimensional platformer with a Natural Language Generation system, I have considered a new way in which Artificial Intelligence may affect gameplay. The resulting project, The Disciple, takes input from the environment of the game and offers successfully a sentence relevant to what occurs within the game's world. The sentences this system generates are diverse enough so that, while the Natural Language Generation system may restate what it has said, already, it does not utter the same sentence twice in a row. Often, the Natural Language Generation system selects a phrase I have written from …

Designing 2d Interfaces For 3d Gesture Retrieval Utilizing Deep Learning, Spencer Southard

UNF Graduate Theses and Dissertations

Gesture retrieval can be defined as the process of retrieving the correct meaning of the hand movement from a pre-assembled gesture dataset. The purpose of the research discussed here is to design and implement a gesture interface system that facilitates retrieval for an American Sign Language gesture set using a mobile device. The principal challenge discussed here will be the normalization of 2D gestures generated from the mobile device interface and the 3D gestures captured from video samples into a common data structure that can be utilized by deep learning networks. This thesis covers convolutional neural networks and auto encoders …

A New Reinforcement Learning Algorithm With Fixed Exploration For Semi-Markov Decision Processes, Angelo Michael Encapera

Masters Theses

"Artificial intelligence or machine learning techniques are currently being widely applied for solving problems within the field of data analytics. This work presents and demonstrates the use of a new machine learning algorithm for solving semi-Markov decision processes (SMDPs). SMDPs are encountered in the domain of Reinforcement Learning to solve control problems in discrete-event systems. The new algorithm developed here is called iSMART, an acronym for imaging Semi-Markov Average Reward Technique. The algorithm uses a constant exploration rate, unlike its precursor R-SMART, which required exploration decay. The major difference between R-SMART and iSMART is that the latter uses, in addition …

Artificial Intelligence And Its Potential Adverse Impacts On The Philippine Economy, Krista Danielle Yu, Caesar Cororaton, Joel P. Ilao, Charibeth K. Cheng, Kathleen Aviso, Christina D. Cayamanda, Michael Angelo B. Promentilla, Ringgold P. Atienza, Roman Julio B. Infante, Raymond R. Tan

Angelo King Institute for Economic and Business Studies (AKI)

Recent developments in artificial intelligence (AI) and deep learning techniques are expected to reshape the nature of the working environment in many economic sectors through the automation of many white collar jobs. This technological breakthrough poses threats of job obsolescence in several industries, particularly for a labor abundant country such as the Philippines. With human capital as one of its largest resources, the services sector is a major contributor to the country’s economy, contributing around 60% of the total gross domestic product and employing about 22.8 million workers (Philippine Statistics Authority, 2017).

Rationality, Parapsychology, And Artificial Intelligence In Military And Intelligence Research By The United States Government In The Cold War, Guy M. Lomeo

Theses and Dissertations

A study analyzing the roles of rationality, parapsychology, and artificial intelligence in military and intelligence research by the United States Government in the Cold War. An examination of the methodology behind the decisions to pursue research in two fields that were initially considered irrational.

Ai Education: Birds Of A Feather, Todd W. Neller

Computer Science Faculty Publications

Games are beautifully crafted microworlds that invite players to explore complex terrains that spring into existence from even simple rules. As AI educators, games can offer fun ways of teaching important concepts and techniques. Just as Martin Gardner employed games and puzzles to engage both amateurs and professionals in the pursuit of Mathematics, a well-chosen game or puzzle can provide a catalyst for AI learning and research. [excerpt]

Applications Of Computational Geometry And Computer Vision, Joseph Lemley

All Master's Theses

Recent advances in machine learning research promise to bring us closer to the original goals of artificial intelligence. Spurred by recent innovations in low-cost, specialized hardware and incremental refinements in machine learning algorithms, machine learning is revolutionizing entire industries. Perhaps the biggest beneficiary of this progress has been the field of computer vision. Within the domains of computational geometry and computer vision are two problems: Finding large, interesting holes in high dimensional data, and locating and automatically classifying facial features from images. State of the art methods for facial feature classification are compared and new methods for finding empty hyper-rectangles …

Automatically Defined Templates For Improved Prediction Of Non-Stationary, Nonlinear Time Series In Genetic Programming, David Moskowitz

CCE Theses and Dissertations

Soft methods of artificial intelligence are often used in the prediction of non-deterministic time series that cannot be modeled using standard econometric methods. These series, such as occur in finance, often undergo changes to their underlying data generation process resulting in inaccurate approximations or requiring additional human judgment and input in the process, hindering the potential for automated solutions.

Genetic programming (GP) is a class of nature-inspired algorithms that aims to evolve a population of computer programs to solve a target problem. GP has been applied to time series prediction in finance and other domains. However, most GP-based approaches to …

Evaluation Of Supervised Machine Learning For Classifying Video Traffic, Farrell R. Taylor

CCE Theses and Dissertations

Operational deployment of machine learning based classifiers in real-world networks has become an important area of research to support automated real-time quality of service decisions by Internet service providers (ISPs) and more generally, network administrators. As the Internet has evolved, multimedia applications, such as voice over Internet protocol (VoIP), gaming, and video streaming, have become commonplace. These traffic types are sensitive to network perturbations, e.g. jitter and delay. Automated quality of service (QoS) capabilities offer a degree of relief by prioritizing network traffic without human intervention; however, they rely on the integration of real-time traffic classification to identify applications. Accordingly, …

Enabling Machine Science Through Distributed Human Computing, Mark David Wagy

Graduate College Dissertations and Theses

Distributed human computing techniques have been shown to be effective ways of accessing the problem-solving capabilities of a large group of anonymous individuals over the World Wide Web. They have been successfully applied to such diverse domains as computer security, biology and astronomy. The success of distributed human computing in various domains suggests that it can be utilized for complex collaborative problem solving. Thus it could be used for "machine science": utilizing machines to facilitate the vetting of disparate human hypotheses for solving scientific and engineering problems.

In this thesis, we show that machine science is possible through distributed human …

Email Similarity Matching And Automatic Reply Generation Using Statistical Topic Modeling And Machine Learning, Zachery L. Schiller

Electronic Theses and Dissertations

Responding to email is a time-consuming task that is a requirement for most professions. Many people find themselves answering the same questions over and over, repeatedly replying with answers they have written previously either in whole or in part. In this thesis, the Automatic Mail Reply (AMR) system is implemented to help with repeated email response creation. The system uses past email interactions and, through unsupervised statistical learning, attempts to recover relevant information to give to the user to assist in writing their reply.

Three statistical learning models, term frequency-inverse document frequency (tf-idf), Latent Semantic Analysis (LSA), and Latent Dirichlet …

Artificial Intelligence Animal Recognition System, Bohan Zhang, Xu Cao, Jeremy Straub, Eunjin Kim

Jeremy Straub

Artificial Intelligence Animal recognition system can be widely used for chil-dren education, zoology database implement. It is known that existing animal classification system can be used to distinguish an animal fairly fast. For example mammals, reptiles, amphibians. Our goal is to implement an AI system which could eliminate the possibility by half or more for which animal the user is thinking by means of asking the player "the best" question for an animal property.

Unsupervised Learning Trojan, Arturo Geigel

CCE Theses and Dissertations

This work presents a proof of concept of an Unsupervised Learning Trojan. The Unsupervised Learning Trojan presents new challenges over previous work on the Neural network Trojan, since the attacker does not control most of the environment. The current work will presented an analysis of how the attack can be successful by proposing new assumptions under which the attack can become a viable one. A general analysis of how the compromise can be theoretically supported is presented, providing enough background for practical implementation development. The analysis was carried out using 3 selected algorithms that can cover a wide variety of …

Element Detection In Japanese Comic Book Panels, Toshihiro Kuboi

Master's Theses

Comic books are a unique and increasingly popular form of entertainment combining visual and textual elements of communication. This work pertains to making comic books more accessible. Specifically, this paper explains how we detect elements such as speech bubbles present in Japanese comic book panels. Some applications of the work presented in this paper are automatic detection of text and its transformation into audio or into other languages. Automatic detection of elements can also allow reasoning and analysis at a deeper semantic level than what’s possible today. Our approach uses an expert system and a machine learning system. The expert …

Faults Identification In Three-Phase Induction Motors Using Support Vector Machines, Rama Hammo

Master of Technology Management Plan II Graduate Projects

Induction motor is one of the most important motors used in industrial applications. The operating conditions may sometime lead the machine into different fault situations. The main types of external faults experienced by these motors are over loading, single phasing, unbalanced supply voltage, locked rotor, phase reversal, ground fault, under voltage and over voltage. The machine should be shut down when a fault is experienced to avoid damage and for the safety of the workers. Computer based relays monitor the machine and disconnect it during the faults. The relay logic used to identify these faults requires sophisticated signal processing techniques …

Machines And The Moral Community, Erica L. Neely

Philosophy and Religion Faculty Scholarship

A key distinction in ethics is between members and nonmembers of the moral community. Over time, our notion of this community has expanded as we have moved from a rationality criterion to a sentience criterion for membership. I argue that a sentience criterion is insufficient to accommodate all members of the moral community; the true underlying criterion can be understood in terms of whether a being has interests. This may be extended to conscious, self-aware machines, as well as to any autonomous intelligent machines. Such machines exhibit an ability to formulate desires for the course of their own existence; this …

Iterative Statistical Verification Of Probabilistic Plans, Colin M. Potts

Lawrence University Honors Projects

Artificial intelligence seeks to create intelligent agents. An agent can be anything: an autopilot, a self-driving car, a robot, a person, or even an anti-virus system. While the current state-of-the-art may not achieve intelligence (a rather dubious thing to quantify) it certainly achieves a sense of autonomy. A key aspect of an autonomous system is its ability to maintain and guarantee safety—defined as avoiding some set of undesired outcomes. The piece of software responsible for this is called a planner, which is essentially an automated problem solver. An advantage computer planners have over humans is their ability to consider and …

Practical Tractability Of Csps By Higher Level Consistency And Tree Decomposition, Shant Karakashian

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Constraint Satisfaction is a flexible paradigm for modeling many decision problems in Engineering, Computer Science, and Management. Constraint Satisfaction Problems (CSPs) are in general NP-complete and are usually solved with search. Research has identified various islands of tractability, which enable solving certain CSPs with backtrack-free search. For example, one sufficient condition for tractability relates the consistency level of a CSP to treewidth of the CSP's constraint network. However, enforcing higher levels of consistency on a CSP may require the addition of constraints, thus altering the topology of the constraint network and increasing its treewidth. This thesis addresses the following question: …

Coupling Numerical Simulation And Pattern Recognition To Model Production And Evaluate Carbon Dioxide Injection In Shale Gas Reservoir, Amirmasoud Kalantari-Dahaghi

Graduate Theses, Dissertations, and Problem Reports

Massive multi-cluster, multi-stage hydraulic fractures have significantly increased the complexity of the flow behavior in shale. This has translated into multiple challenges in the modeling of production from shale wells.

Most commonly used numerical techniques for modeling production from shale wells are Explicit Hydraulic Fracture (EHF) and Stimulated Reservoir Volume (SRV). Model setup for the EHF technique is long and laborious and its implementation is computationally expensive, such that it becomes impractical to model beyond a single pad. On the other hand, identifying the extent and conductivity of SRV is a challenging proposition. SRV technique is commonly used to simplify …

Toward Large-Scale Agent Guidance In An Urban Taxi Service, Agussurja Lucas, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Empty taxi cruising represents a wastage of resources in the context of urban taxi services. In this work, we seek to minimize such wastage. An analysis of a large trace of taxi operations reveals that the services’ inefficiency is caused by drivers’ greedy cruising behavior. We model the existing system as a continuous time Markov chain. To address the problem, we propose that each taxi be equipped with an intelligent agent that will guide the driver when cruising for passengers. Then, drawing from AI literature on multiagent planning, we explore two possible ways to compute such guidance. The first formulation …

Bringing To Life An Ancient Urban Center At Monte Albán, Mexico: Exploiting The Synergy Between The Micro, Meso, And Macro Levels In A Complex System, Thaer W. Jayyousi

Wayne State University Dissertations

In this dissertation, agent-based models of emergent ancient urban centers were constructed through the use of techniques from computational intelligence, agent-based modeling, complex systems, and data-mining of existing archaeological data from the prehistoric urban center, Monte Albán. This real world application was selected because of its importance in understanding the emergence of modern economic and political systems. Specifically, Cultural Algorithms was used to evolve models of early Monte Alban, models that can then be compared with existing models of ancient and modern urban centers.

Features of a complex system were used to help interpret the archaeological data. The analysis went …

Cross-Talk: A Shared Parameter Space For Gesturally Extended Human/Machine Improvisation, William Brent, Adam James Wilson

Publications and Research

This paper describes Cross-talk, a piece of music and performance system for two instruments augmented with infrared motion-tracking capability, and an artificial software improviser. Cross-talk was commissioned by the Ammerman Center for Arts and Technology at Connecticut College, for the 13th Biennial Symposium on Arts and Technology. The work is part of an ongoing collaboration focused on developing integrated hardware and software performance systems to extend the timbral and expressive capabilities of traditional musical instruments and to generate musical structure in response to information retrieved from human performers in real-time. Artistic motivations and prior related work are presented here, along …

Diagnosis Of Skin Diseases Using Online Expert System, Dr. Muhammad Zubair Asghar, Muhammad Junaid Asghar

Dr. Muhammad Zubair Asghar

This paper describes Expert System (ES) for diagnosis and management of skin diseases. More than 13 types of skin diseases can be diagnosed and treated by our system. It is rule based web-supported expert system, assisting skin specialists, medical students doing specialization in dermatology, researchers as well as skin patients having computer know-how. System was developed with Java Technology. The expert rules were developed on the symptoms of each type of skin disease, and they were presented using tree-graph and inferred using forward-chaining with depth-first search method. User interaction with system is enhanced with efficient user interfaces. The web based …

Optimization Of Railway System Through The Application Of Advanced Technologies, Praveen Jha Dr

Praveen Jha Dr

Railway System can be made truly automated, modern, safe, profitable and timely by providing an integrated solution to the loads of problems in the Railway System in most scientific, effective and inexpensive manner through the application of state-of-art geo-spatial programs - Railways Automatic Tracking Program (RATP) and Program for Optimization and Automation of Railway System (POARS) - developed by the author for addressing the pertinent issues of safety and optimization of railway operations. This could put in place the Optimized Railway System (ORS) that could automatically control all the systems of railways. Real time tracking of trains could be done …

Expert System For Online Diagnosis Of Red-Eye Diseases, Dr. Muhammad Zubair Asghar, Muhammad Junaid Asghar

Dr. Muhammad Zubair Asghar

This paper describes Expert System (ES) for online diagnosis and prescription of red-eye diseases. The types of eye diseases that can be diagnosed with this system are called Red-eye diseases i.e. disease in which red-eye is the common symptom. It is rule based web-supported expert system, assisting ophthalmologists, medical students doing specialization in ophthalmology, researchers as well as eye patients having computer know-how. System was designed and programmed with Java Technology. The expert rules were developed on the symptoms of each type of Red-eye disease, and they were presented using tree-graph and inferred using forward-chaining with depth-first search method. User …

The Development Of Hierarchical Knowledge In Robot Systems, Stephen W. Hart

Open Access Dissertations

This dissertation investigates two complementary ideas in the literature on machine learning and robotics--those of embodiment and intrinsic motivation--to address a unified framework for skill learning and knowledge acquisition. "Embodied" systems make use of structure derived directly from sensory and motor configurations for learning behavior. Intrinsically motivated systems learn by searching for native, hedonic value through interaction with the world. Psychological theories of intrinsic motivation suggest that there exist internal drives favoring open-ended cognitive development and exploration. I argue that intrinsically motivated, embodied systems can learn generalizable skills, acquire control knowledge, and form an epistemological understanding of the world …

Computer Assisted Diagnoses For Red Eye (Cadre), Dr. Muhammad Zubair Asghar

Dr. Muhammad Zubair Asghar

This paper introduces an expert System (ES) named as “CADRE-Computer Assisted Diagnoses for Red Eye. Mostly the remote areas of the population are deprived of the facilities of having experts in eye disease. So it is the need of the day to store the expertise of Eye specialists in computers through using ES technology. This ES is a rule-based Expert System that assists in red-eye diagnosis and treatment. The knowledge acquired from literature review and human experts of the specific domain was used as a base for analysis, diagnosis and recommendations. CADRE evaluates the risk factors of 20 eye diseases …

Proceedings Of The 18th Irish Conference On Artificial Intelligence And Cognitive Science, Sarah Jane Delany, Michael Madden

Books/Book Chapters

These proceedings contain the papers that were accepted for publication at AICS-2007, the 18th Annual Conference on Artificial Intelligence and Cognitive Science, which was held in the Technological University Dublin; Dublin, Ireland; on the 29th to the 31st August 2007. AICS is the annual conference of the Artificial Intelligence Association of Ireland (AIAI).

A Context-Dependent Model Of Proximity In Physically Situated Environments, John D. Kelleher, Geert-Jan M. Kruijff

Conference papers

The paper presents a computational model for a context-dependent analysis of a physical environment in terms of spatial proximity. The model provides a basis for grounding linguistic analyses of spatial expressions in visual perception. The model uses potential fields to model spatial proximity. It has been implemented, and when combined with a handcrafted grammar, is used to enable a conversational robot to carry out a situated dialogue with a human. The key concept in our approach is defining the region that is proximal to a landmark based on the spatial configuration of other objects in the scene. The model extends …