Pagi World: A Physically Realistic, General-Purpose Simulation Environment For Developmental Ai Systems, 2016 Indiana University - Purdue University Fort Wayne
Pagi World: A Physically Realistic, General-Purpose Simulation Environment For Developmental Ai Systems, John Licato, Selmer Bringsjord
Computer Science Faculty Presentations
There has long been a need for a simulation environment rich enough to support the development of an AI system sufficiently knowledgeable about physical causality to pass certain tests of Psychometric Artificial Intelligence (PAI) and Psychometric Artificial General Intelligence (PAGI). In this article, we present a simulation environment, PAGI World, which is: cross-platform (as it can be run on all major operating systems); open-source (and thus completely free of charge to use); able to work with AI systems written in almost any programming language; as agnostic as possible regarding which AI approach is used; and easy to set up and ...
Toward Autonomous Multi-Rotor Indoor Aerial Vehicles, 2016 Western Kentucky University
Toward Autonomous Multi-Rotor Indoor Aerial Vehicles, Connor Brooks
Honors College Capstone Experience/Thesis Projects
In this project, we worked to create an indoor autonomous micro aerial vehicle (MAV) using a multi-layer architecture with modular hardware and software components. We required that all computing was done onboard the vehicle during time of flight so that no remote connection of any kind was necessary for successful control of the vehicle, even when flying autonomously. We utilized environmental sensors including ultrasonic sensors, light detection and ranging modules, and inertial measurement units to acquire necessary environment information for autonomous flight. We used a three-layered system that combined a modular control architecture with distributed on-board computing to allow for ...
V3nlp Framework: Tools To Build Applications For Extracting Concepts From Clinical Text, 2016 VA Salt Lake City Health Care System and University of Utah School of Medicine
V3nlp Framework: Tools To Build Applications For Extracting Concepts From Clinical Text, Guy Divita, Marjorie Carter Ms, Le-Thuy Tran Phd, Doug Redd Ms, Qing T. Zeng Phd, Scott Duvall Phd, Matthew H. Samore Md, Phd, Adi V. Gundlapalli Md, Phd, Ms
eGEMs (Generating Evidence & Methods to improve patient outcomes)
Introduction: Substantial amounts of clinically significant information are contained only within the narrative of the clinical notes in electronic medical records. v3NLP Framework is a set of best of breed functionalities developed to transform this information into structured data for use in quality improvement, research, population health surveillance, and decision support.
Background: MetaMap, cTAKES and similar well known NLP tools do not have sufficient scalability out of the box. v3NLP Framework evolved out of the necessity to scale these tools up and provide a framework to customize and tune techniques to fit a variety of tasks, including document classification, tuned ...
Paper-Android-Based Health Care Management System, 2016 Gomal University, Dera Ismail Khan
Paper-Android-Based Health Care Management System, Fazal Masud Kundi, Anam Habib, Ammara Habib, Dr. Muhammad Zubair Asghar
Dr. Muhammad Zubair Asghar
A Genetic Algorithmic Approach To Automated Auction Mechanism Design, 2016 CUNY Guttman Community College
A Genetic Algorithmic Approach To Automated Auction Mechanism Design, Jinzhong Niu, Simon Parsons
Publications and Research
In this paper, we present a genetic algorithmic approach to automated auction mechanism design in the context of \cat games. This is a follow-up to one piece of our prior work in the domain, the reinforcement learning-based grey-box approach. Our experiments show that given the same search space the grey-box approach is able to produce better auction mechanisms than the genetic algorithmic approach. The comparison can also shed light on the design and evaluation of similar search solutions to other domain problems.
Formalization Of The Ad Hominem Argumentation Scheme, 2016 University of Windsor
Formalization Of The Ad Hominem Argumentation Scheme, Douglas Walton
In this paper, several examples from the literature, and one central new one, are used as case studies of texts of discourse containing an argumentation scheme that has now been widely investigated in literature on argumentation. Argumentation schemes represent common patterns of reasoning used in everyday conversational discourse. The most typical ones represent defeasible arguments based on nonmonotonic reasoning. Each scheme has a matching set of critical questions used to evaluate a particular argument fitting that scheme. The project is to study how to build a formal computational model of this scheme for the circumstantial ad hominem argument using argumentation ...
Examination Dialogue: An Argumentation Framework For Critically Questioning An Expert Opinion, 2016 University of Windsor
Examination Dialogue: An Argumentation Framework For Critically Questioning An Expert Opinion, Douglas Walton
Recent work in argumentation theory (Walton and Krabbe, 1995; Walton, 2005) and artificial intelligence (Bench-Capon, 1992, 2003; Cawsey, 1992; McBurney and Parsons, 2002; Bench-Capon and Prakken, 2005) uses types of dialogue as contexts of argument use. This paper provides an analysis of a special type called examination dialogue, in which one party questions another party, sometimes critically or even antagonistically, to try to find out what that party knows about something. This type of dialogue is most prominent in law and in both legal and non-legal arguments based on expert opinion. It is also central to dialogue systems for questioning ...
Critical Questions In Computational Models Of Legal Argument, 2016 University of Windsor
Critical Questions In Computational Models Of Legal Argument, Douglas Walton, Thomas F. Gordon
Two recent computational models of legal argumentation, by Verheij and Gordon respectively, have interpreted critical questions as premises of arguments that can be defeated using Pollock’s concepts of undercutters and rebuttals. Using the scheme for arguments from expert opinion as an example, this paper evaluates and compares these two models of critical questions from the perspective of argumentation theory and competing legal theories about proof standardsfor defeating presumptions. The applicable proof standard is found to be a legal issue subject to argument. Verheij’smodel is shown to have problems because the proof stan-dards it applies to different kinds of ...
Climbing Up Cloud Nine: Performance Enhancement Techniques For Cloud Computing Environments, 2016 The University of Western Ontario
Climbing Up Cloud Nine: Performance Enhancement Techniques For Cloud Computing Environments, Mohamed Abusharkh
Electronic Thesis and Dissertation Repository
With the transformation of cloud computing technologies from an attractive trend to a business reality, the need is more pressing than ever for efficient cloud service management tools and techniques. As cloud technologies continue to mature, the service model, resource allocation methodologies, energy efficiency models and general service management schemes are not yet saturated. The burden of making this all tick perfectly falls on cloud providers. Surely, economy of scale revenues and leveraging existing infrastructure and giant workforce are there as positives, but it is far from straightforward operation from that point. Performance and service delivery will still depend on ...
Energy Consumption Prediction With Big Data: Balancing Prediction Accuracy And Computational Resources, Katarina Grolinger, Miriam Am Capretz, Luke Seewald
Electrical and Computer Engineering Publications
In recent years, advances in sensor technologies and expansion of smart meters have resulted in massive growth of energy data sets. These Big Data have created new opportunities for energy prediction, but at the same time, they impose new challenges for traditional technologies. On the other hand, new approaches for handling and processing these Big Data have emerged, such as MapReduce, Spark, Storm, and Oxdata H2O. This paper explores how findings from machine learning with Big Data can benefit energy consumption prediction. An approach based on local learning with support vector regression (SVR) is presented. Although local learning itself is ...
Analysis On Alergia Algorithm: Pattern Recognition By Automata Theory, 2016 San Jose State University
Analysis On Alergia Algorithm: Pattern Recognition By Automata Theory, Xuanyi Qi
Based on Kolmogorov Complexity, a finite set x of strings has a pattern if the set x can be output by a Turing machine of length that is less than minimum of all |x|; this Turing machine, that may not be unique, is called a pattern of the finite set of string. In order to find a pattern of a given finite set of strings (assuming such a pattern exists), the ALERGIA algorithm is used to approximate such a pattern (Turing machine) in terms of finite automata. Note that each finite automaton defines a partition on formal language Σ*, ALERGIA ...
Dna Analysis Using Grammatical Inference, 2016 San Jose State University
Dna Analysis Using Grammatical Inference, Cory Cook
An accurate language definition capable of distinguishing between coding and non-coding DNA has important applications and analytical significance to the field of computational biology. The method proposed here uses positive sample grammatical inference and statistical information to infer languages for coding DNA.
An algorithm is proposed for the searching of an optimal subset of input sequences for the inference of regular grammars by optimizing a relevant accuracy metric. The algorithm does not guarantee the finding of the optimal subset; however, testing shows improvement in accuracy and performance over the basis algorithm.
Testing shows that the accuracy of inferred languages for ...
Analyze Large Multidimensional Datasets Using Algebraic Topology, 2016 San Jose State University
Analyze Large Multidimensional Datasets Using Algebraic Topology, David Le
This paper presents an efficient algorithm to extract knowledge from high-dimensionality, high- complexity datasets using algebraic topology, namely simplicial complexes. Based on concept of isomorphism of relations, our method turn a relational table into a geometric object (a simplicial complex is a polyhedron). So, conceptually association rule searching is turned into a geometric traversal problem. By leveraging on the core concepts behind Simplicial Complex, we use a new technique (in computer science) that improves the performance over existing methods and uses far less memory. It was designed and developed with a strong emphasis on scalability, reliability, and extensibility. This paper ...
Optimizing The Mix Of Games And Their Locations On The Casino Floor, 2016 nQube Technical Computing Corp.
Optimizing The Mix Of Games And Their Locations On The Casino Floor, Jason D. Fiege, Anastasia D. Baran
International Conference on Gambling and Risk Taking
We present a mathematical framework and computational approach that aims to optimize the mix and locations of slot machine types and denominations, plus other games to maximize the overall performance of the gaming floor. This problem belongs to a larger class of spatial resource optimization problems, concerned with optimizing the allocation and spatial distribution of finite resources, subject to various constraints. We introduce a powerful multi-objective evolutionary optimization and data-modelling platform, developed by the presenter since 2002, and show how this software can be used for casino floor optimization. We begin by extending a linear formulation of the casino floor ...
Stationary And Time-Dependent Optimization Of The Casino Floor Slot Machine Mix, 2016 nQube Technical Computing Corp.
Stationary And Time-Dependent Optimization Of The Casino Floor Slot Machine Mix, Anastasia D. Baran, Jason D. Fiege
International Conference on Gambling and Risk Taking
Modeling and optimizing the performance of a mix of slot machines on a gaming floor can be addressed at various levels of coarseness, and may or may not consider time-dependent trends. For example, a model might consider only time-averaged, aggregate data for all machines of a given type; time-dependent aggregate data; time-averaged data for individual machines; or fully time dependent data for individual machines. Fine-grained, time-dependent data for individual machines offers the most potential for detailed analysis and improvements to the casino floor performance, but also suffers the greatest amount of statistical noise. We present a theoretical analysis of single ...
Machine Learning On The Cloud For Pattern Recognition, 2016 San Jose State University
Machine Learning On The Cloud For Pattern Recognition, Tien Nguyen
Pattern recognition is a field of machine learning with applications to areas such as text recognition and computer vision. Machine learning algorithms, such as convolutional neural networks, may be trained to classify images. However, such tasks may be computationally intensive for a commercial computer for larger volumes or larger sizes of images. Cloud computing allows one to overcome the processing and memory constraints of average commercial computers, allowing computations on larger amounts of data. In this project, we developed a system for detection and tracking of moving human and vehicle objects in videos in real time or near real time ...
Multi Faceted Text Classification Using Supervised Machine Learning Models, 2016 San Jose State University
Multi Faceted Text Classification Using Supervised Machine Learning Models, Abhiteja Gajjala
In recent year’s document management tasks (known as information retrieval) increased a lot due to availability of digital documents everywhere. The need of automatic methods for extracting document information became a prominent method for organizing information and knowledge discovery. Text Classification is one such solution, where in the natural language text is assigned to one or more predefined categories based on the content. In my research classification of text is mainly focused on sentiment label classification. The idea proposed for sentiment analysis is multi-class classification of online movie reviews. Many research papers discussed the classification of sentiment either positive ...
Supervised Learning For Multi-Domain Text Classification, 2016 San Jose State University
Supervised Learning For Multi-Domain Text Classification, Siva Charan Reddy Gangireddy
Digital information available on the Internet is increasing day by day. As a result of this, the demand for tools that help people in finding and analyzing all these resources are also growing in number. Text Classification, in particular, has been very useful in managing the information. Text Classification is the process of assigning natural language text to one or more categories based on the content. It has many important applications in the real world. For example, finding the sentiment of the reviews, posted by people on restaurants, movies and other such things are all applications of Text classification. In ...
Concatenative Synthesis For Novel Timbral Creation, 2016 California Polytechnic State University, San Luis Obispo
Concatenative Synthesis For Novel Timbral Creation, James Eric Bilous
Master's Theses and Project Reports
Modern day musicians rely on a variety of instruments for musical expression. Tones produced from electronic instruments have become almost as commonplace as those produced by traditional ones as evidenced by the plethora of artists who can be found composing and performing with nothing more than a personal computer. This desire to embrace technical innovation as a means to augment performance art has created a budding field in computer science that explores the creation and manipulation of sound for artistic purposes. One facet of this new frontier concerns timbral creation, or the development of new sounds with unique characteristics that ...
Movie Script Shot Lister, 2016 San Jose State University
Movie Script Shot Lister, David Robert Smith
The making of a motion picture almost always starts with the script, the written version of a story envisioned within the mind of its creator. The script is then broken down into shots. Each individual shot is filmed and then they are edited together to create the motion picture. The goal of the Movie Script Shot Lister thesis project is to be able to read in a script for a movie or television show, and automatically generate a shot list. While a script is text, a shot list is the blue print for how to visualize that script, so the ...