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Marim: Mobile Augmented Reality For Interactive Manuals, Tam Nguyen, Dorothy Tan, Bilal Mirza, Jose Sepulveda 2016 University of Dayton

Marim: Mobile Augmented Reality For Interactive Manuals, Tam Nguyen, Dorothy Tan, Bilal Mirza, Jose Sepulveda

Tam Nguyen

In this work, we present a practical system which uses mobile devices for interactive manuals. In particular, there are two modes provided in the system, namely, expert/trainer and trainee modes. Given the expert/trainer editor, experts design the step-by-step interactive manuals. For each step, the experts capture the images by using phones/tablets and provide visual instructions such as interest regions, text, and action animations. In the trainee mode, the system utilizes the existing object detection and tracking algorithms to identify the step scene and retrieve the respective instruction to be displayed on the mobile device. The trainee then ...


A Framework For Hybrid Intrusion Detection Systems, Robert N. Bronte 2016 Kennesaw State University

A Framework For Hybrid Intrusion Detection Systems, Robert N. Bronte

Master of Science in Information Technology Theses

Web application security is a definite threat to the world’s information technology infrastructure. The Open Web Application Security Project (OWASP), generally defines web application security violations as unauthorized or unintentional exposure, disclosure, or loss of personal information. These breaches occur without the company’s knowledge and it often takes a while before the web application attack is revealed to the public, specifically because the security violations are fixed. Due to the need to protect their reputation, organizations have begun researching solutions to these problems. The most widely accepted solution is the use of an Intrusion Detection System (IDS). Such ...


Constraint Cnf: A Sat And Csp Language Under One Roof, Broes De Cat, Yuliya Lierler 2016 KU Leuven

Constraint Cnf: A Sat And Csp Language Under One Roof, Broes De Cat, Yuliya Lierler

Yuliya Lierler

A new language, called constraint CNF, is proposed. It integrates propositional logic with constraints stemming from constraint programming (CP). A family of algorithms is designed to solve problems expressed in constraint CNF. These algorithms build on techniques from both propositional satisfiability (SAT) and CP. The result is a uniform language and an algorithmic framework, which allow us to gain a deeper understanding of the relation between the solving techniques used in SAT and in CP and apply them together.


Marim: Mobile Augmented Reality For Interactive Manuals, Tam Nguyen, Dorothy Tan, Bilal Mirza, Jose Sepulveda 2016 University of Dayton

Marim: Mobile Augmented Reality For Interactive Manuals, Tam Nguyen, Dorothy Tan, Bilal Mirza, Jose Sepulveda

Computer Science Faculty Publications

In this work, we present a practical system which uses mobile devices for interactive manuals. In particular, there are two modes provided in the system, namely, expert/trainer and trainee modes. Given the expert/trainer editor, experts design the step-by-step interactive manuals. For each step, the experts capture the images by using phones/tablets and provide visual instructions such as interest regions, text, and action animations. In the trainee mode, the system utilizes the existing object detection and tracking algorithms to identify the step scene and retrieve the respective instruction to be displayed on the mobile device. The trainee then ...


Using Machine Learning And Natural Language Processing Algorithms To Automate The Evaluation Of Clinical Decision Support In Electronic Medical Record Systems, Donald A. Szlosek, Jonathan M. Ferretti 2016 University of Southern Maine

Using Machine Learning And Natural Language Processing Algorithms To Automate The Evaluation Of Clinical Decision Support In Electronic Medical Record Systems, Donald A. Szlosek, Jonathan M. Ferretti

eGEMs (Generating Evidence & Methods to improve patient outcomes)

Introduction: As the number of clinical decision support systems incorporated into electronic medical records increases, so does the need to evaluate their effectiveness. The use of medical record review and similar manual methods for evaluating decision rules is laborious and inefficient. Here we use machine learning and natural language processing (NLP) algorithms to accurately evaluate a clinical decision support rule through an electronic medical record system and compare it against manual evaluation.

Methods: Modeled after the electronic medical record system EPIC at Maine Medical Center, we developed a dummy dataset containing physician notes in free text for 3621 artificial patients ...


Stochastic Multiple Gradient Decent For Inferring Action-Based Network Generators, Qian Wu, Viplove Arora, Mario Ventresca 2016 Purdue University

Stochastic Multiple Gradient Decent For Inferring Action-Based Network Generators, Qian Wu, Viplove Arora, Mario Ventresca

The Summer Undergraduate Research Fellowship (SURF) Symposium

Networked systems, like the internet, social networks etc., have in recent years attracted the attention of researchers, specifically to develop models that can help us understand or predict the behavior of these systems. A way of achieving this is through network generators, which are algorithms that can synthesize networks with statistically similar properties to a given target network. Action-based Network Generators (ABNG)is one of these algorithms that defines actions as strategies for nodes to form connections with other nodes, hence generating networks. ABNG is parametrized using an action matrix that assigns an empirical probability distribution to vertices for choosing ...


An Algorithm For The Machine Calculation Of Minimal Paths, Robert Whitinger 2016 East Tennessee State University

An Algorithm For The Machine Calculation Of Minimal Paths, Robert Whitinger

Electronic Theses and Dissertations

Problems involving the minimization of functionals date back to antiquity. The mathematics of the calculus of variations has provided a framework for the analytical solution of a limited class of such problems. This paper describes a numerical approximation technique for obtaining machine solutions to minimal path problems. It is shown that this technique is applicable not only to the common case of finding geodesics on parameterized surfaces in R3, but also to the general case of finding minimal functionals on hypersurfaces in Rn associated with an arbitrary metric.


Lattice Boltzmann Methods For Wind Energy Analysis, Stephen Lloyd Wood 2016 University of Tennessee, Knoxville

Lattice Boltzmann Methods For Wind Energy Analysis, Stephen Lloyd Wood

Doctoral Dissertations

An estimate of the United States wind potential conducted in 2011 found that the energy available at an altitude of 80 meters is approximately triple the wind energy available 50 meters above ground. In 2012, 43% of all new electricity generation installed in the U.S. (13.1 GW) came from wind power. The majority of this power, 79%, comes from large utility scale turbines that are being manufactured at unprecedented sizes. Existing wind plants operate with a capacity factor of only approximately 30%. Measurements have shown that the turbulent wake of a turbine persists for many rotor diameters, inducing ...


Feature Extraction To Improve Nowcasting Using Social Media Event Detection On Cloud Computing And Sentiment Analysis, David L. Kimmey 2016 Indiana University - Purdue University Fort Wayne

Feature Extraction To Improve Nowcasting Using Social Media Event Detection On Cloud Computing And Sentiment Analysis, David L. Kimmey

Masters' Theses

Nowcasting is defined as the prediction of the present, the very near future, and the very recent past using real-time data. Nowcasting with social media creates challenges because of the HACE characteristics of big data (i.e., heterogeneous, autonomous, complex, and evolving associations). Thus, this thesis proposes a feature extraction method to improve nowcasting with social media. The proposed social media event detection algorithm utilizes K-SPRE methodology and the results are processed with sentiment analysis. In addition, we develop a parallel algorithm of the methodology on a cloud environment, and we adapt an artificial neural network to build a predictive ...


Latent Semantic Indexing In The Discovery Of Cyber-Bullying In Online Text, Jacob L. Bigelow 2016 Ursinus College

Latent Semantic Indexing In The Discovery Of Cyber-Bullying In Online Text, Jacob L. Bigelow

Computer Science Summer Fellows

The rise in the use of social media and particularly the rise of adolescent use has led to a new means of bullying. Cyber-bullying has proven consequential to youth internet users causing a need for a response. In order to effectively stop this problem we need a verified method of detecting cyber-bullying in online text; we aim to find that method. For this project we look at thirteen thousand labeled posts from Formspring and create a bank of words used in the posts. First the posts are cleaned up by taking out punctuation, normalizing emoticons, and removing high and low ...


Detection Of Cyberbullying In Sms Messaging, Bryan W. Bradley 2016 Ursinus College

Detection Of Cyberbullying In Sms Messaging, Bryan W. Bradley

Computer Science Summer Fellows

Cyberbullying is a type of bullying that uses technology such as cell phones to harass or malign another person. To detect acts of cyberbullying, we are developing an algorithm that will detect cyberbullying in SMS (text) messages. Over 80,000 text messages have been collected by software installed on cell phones carried by participants in our study. This paper describes the development of the algorithm to detect cyberbullying messages, using the cell phone data collected previously. The algorithm works by first separating the messages into conversations in an automated way. The algorithm then analyzes the conversations and scores the severity ...


Formalization Of The Ad Hominem Argumentation Scheme, Douglas Walton 2016 University of Windsor

Formalization Of The Ad Hominem Argumentation Scheme, Douglas Walton

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 ...


Climbing Up Cloud Nine: Performance Enhancement Techniques For Cloud Computing Environments, Mohamed Abusharkh 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 ...


Gene Set Enrichment And Projection: A Computational Tool For Knowledge Discovery In Transcriptomes, Karl Douglas Stamm 2016 Marquette University

Gene Set Enrichment And Projection: A Computational Tool For Knowledge Discovery In Transcriptomes, Karl Douglas Stamm

Dissertations (2009 -)

Explaining the mechanism behind a genetic disease involves two phases, collecting and analyzing data associated to the disease, then interpreting those data in the context of biological systems. The objective of this dissertation was to develop a method of integrating complementary datasets surrounding any single biological process, with the goal of presenting the response to a signal in terms of a set of downstream biological effects. This dissertation specifically tests the hypothesis that computational projection methods overlaid with domain expertise can direct research towards relevant systems-level signals underlying complex genetic disease. To this end, I developed a software algorithm named ...


Optimizing Main Memory Usage In Modern Computing Systems To Improve Overall System Performance, Daniel Jose Campello 2016 Florida International University

Optimizing Main Memory Usage In Modern Computing Systems To Improve Overall System Performance, Daniel Jose Campello

FIU Electronic Theses and Dissertations

Operating Systems use fast, CPU-addressable main memory to maintain an application’s temporary data as anonymous data and to cache copies of persistent data stored in slower block-based storage devices. However, the use of this faster memory comes at a high cost. Therefore, several techniques have been implemented to use main memory more efficiently in the literature. In this dissertation we introduce three distinct approaches to improve overall system performance by optimizing main memory usage.

First, DRAM and host-side caching of file system data are used for speeding up virtual machine performance in today’s virtualized data centers. The clustering ...


Optimizing The Mix Of Games And Their Locations On The Casino Floor, Jason D. Fiege, Anastasia D. Baran 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 ...


Signal Processing Based On Stable Radix-2 Dct I-Iv Algorithms Having Orthogonal Factors, Sirani K. M. Perera 2016 Embry-Riddle Aeronautical University - Daytona Beach

Signal Processing Based On Stable Radix-2 Dct I-Iv Algorithms Having Orthogonal Factors, Sirani K. M. Perera

Electronic Journal of Linear Algebra

This paper presents stable, radix-2, completely recursive discrete cosine transform algorithms DCT-I and DCT-III solely based on DCT-I, DCT-II, DCT-III, and DCT-IV having sparse and orthogonal factors. Error bounds for computing the completely recursive DCT-I, DCT-II, DCT-III, and DCT-IV algorithms having sparse and orthogonal factors are addressed. Signal flow graphs are demonstrated based on the completely recursive DCT-I, DCT-II, DCT-III, and DCT-IV algorithms having orthogonal factors. Finally image compression results are presented based on the recursive 2D DCT-II and DCT-IV algorithms for image size 512 by 512 pixels with transfer block sizes 8 by 8, 16 by 16, and 32 ...


Stationary And Time-Dependent Optimization Of The Casino Floor Slot Machine Mix, Anastasia D. Baran, Jason D. Fiege 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 ...


Robust Partial Order Schedules For Rcpsp/Max With Durational Uncertainty, Na FU, Pradeep VARAKANTHAM, Pradeep VARAKANTHAM 2016 Singapore Management University

Robust Partial Order Schedules For Rcpsp/Max With Durational Uncertainty, Na Fu, Pradeep Varakantham, Pradeep Varakantham

Research Collection School Of Information Systems

In this work, we consider RCPSP/max with durational uncertainty. We focus on computing robust Partial Order Schedules (or, in short POS) which can be executed with risk controlled feasibility and optimality, i.e., there is stochastic posteriori quality guarantee that the derived POS can be executed with all constraints honored and completion before robust makespan. To address this problem, we propose BACCHUS: a solution method on Benders Accelerated Cut Creation for Handling Uncertainty in Scheduling. In our proposed approach, we first give an MILP formulation for the deterministic RCPSP/max and partition the model into POS generation process and ...


Designing And Comparing Multiple Portfolios Of Parameter Configurations For Online Algorithm Selection, Aldy GUNAWAN, Hoong Chuin LAU, Mustafa MISIR 2016 Singapore Management University

Designing And Comparing Multiple Portfolios Of Parameter Configurations For Online Algorithm Selection, Aldy Gunawan, Hoong Chuin Lau, Mustafa Misir

Research Collection School Of Information Systems

Algorithm portfolios seek to determine an effective set of algorithms that can be used within an algorithm selection framework to solve problems. A limited number of these portfolio studies focus on generating different versions of a target algorithm using different parameter configurations. In this paper, we employ a Design of Experiments (DOE) approach to determine a promising range of values for each parameter of an algorithm. These ranges are further processed to determine a portfolio of parameter configurations, which would be used within two online Algorithm Selection approaches for solving different instances of a given combinatorial optimization problem effectively. We ...


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