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Analysis Of 3d Cone-Beam Ct Image Reconstruction Performance On A Fpga, Devin Held 2016 The University of Western Ontario

Analysis Of 3d Cone-Beam Ct Image Reconstruction Performance On A Fpga, Devin Held

Electronic Thesis and Dissertation Repository

Efficient and accurate tomographic image reconstruction has been an intensive topic of research due to the increasing everyday usage in areas such as radiology, biology, and materials science. Computed tomography (CT) scans are used to analyze internal structures through capture of x-ray images. Cone-beam CT scans project a cone-shaped x-ray to capture 2D image data from a single focal point, rotating around the object. CT scans are prone to multiple artifacts, including motion blur, streaks, and pixel irregularities, therefore must be run through image reconstruction software to reduce visual artifacts. The most common algorithm used is the Feldkamp, Davis, and ...


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 ...


Plackett-Luce Regression Mixture Model For Heterogeneous Rankings, MAKSIM TKACHENKO, Hady Wirawan LAUW 2016 Singapore Management University

Plackett-Luce Regression Mixture Model For Heterogeneous Rankings, Maksim Tkachenko, Hady Wirawan Lauw

Research Collection School Of Information Systems

Learning to rank is an important problem in many scenarios, such as information retrieval, natural language processing, recommender systems, etc. The objective is to learn a function that ranks a number of instances based on their features. In the vast majority of the learning to rank literature, there is an implicit assumption that the population of ranking instances are homogeneous, and thus can be modeled by a single central ranking function. In this work, we are concerned with learning to rank for a heterogeneous population, which may consist of a number of sub-populations, each of which may rank objects dierently ...


Is Only One Gps Point Position Sufficient To Locate You To The Road Network Accurately?, Hao WU, Weiwei SUN, Baihua ZHENG 2016 Singapore Management University

Is Only One Gps Point Position Sufficient To Locate You To The Road Network Accurately?, Hao Wu, Weiwei Sun, Baihua Zheng

Research Collection School Of Information Systems

Locating only one GPS position to a road segment accurately is crucial to many location-based services such as mobile taxi-hailing service, geo-tagging, POI check-in, etc. This problem is challenging because of errors including the GPS errors and the digital map errors (misalignment and the same representation of bidirectional roads) and a lack of context information. To the best of our knowledge, no existing work studies this problem directly and the work to reduce GPS signal errors by considering hardware aspect is the most relevant. Consequently, this work is the first attempt to solve the problem of locating one GPS position ...


Probabilistic Models For Contextual Agreement In Preferences, DO HA LOC, Hady Wirawan LAUW 2016 Singapore Management University

Probabilistic Models For Contextual Agreement In Preferences, Do Ha Loc, Hady Wirawan Lauw

Research Collection School Of Information Systems

The long-tail theory for consumer demand implies the need for more accurate personalization technologies to target items to the users who most desire them. A key tenet of personalization is the capacity to model user preferences. Most of the previous work on recommendation and personalization has focused primarily on individual preferences. While some focus on shared preferences between pairs of users, they assume that the same similarity value applies to all items. Here we investigate the notion of "context," hypothesizing that while two users may agree on their preferences on some items, they may also disagree on other items. To ...


Representation Learning For Homophilic Preferences, NGUYEN. Trong T., Hady Wirawan LAUW 2016 Singapore Management University

Representation Learning For Homophilic Preferences, Nguyen. Trong T., Hady Wirawan Lauw

Research Collection School Of Information Systems

Users express their personal preferences through ratings, adoptions, and other consumption behaviors. We seek tolearn latent representations for user preferences from such behavioral data. One representation learning model that has been shown to be effective for large preference datasets is Restricted Boltzmann Machine (RBM). While homophily, or the tendency of friends to share their preferences at some level, is an established notion in sociology, thus far it has not yet been clearly demonstrated on RBM-based preference models. The question lies in how to appropriately incorporate social network into the architecture of RBM-based models for learning representations of preferences. In this ...


Modeling Sequential Preferences With Dynamic User And Context Factors, LE DUC TRONG, Yuan FANG, Hady Wirawan LAUW 2016 Singapore Management University

Modeling Sequential Preferences With Dynamic User And Context Factors, Le Duc Trong, Yuan Fang, Hady Wirawan Lauw

Research Collection School Of Information Systems

Users express their preferences for items in diverse forms, through their liking for items, as well as through the sequence in which they consume items. The latter, referred to as “sequential preference”, manifests itself in scenarios such as song or video playlists, topics one reads or writes about in social media, etc. The current approach to modeling sequential preferences relies primarily on the sequence information, i.e., which item follows another item. However, there are other important factors, due to either the user or the context, which may dynamically affect the way a sequence unfolds. In this work, we develop ...


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 ...


Efficient And Expressive Keyword Search Over Encrypted Data In The Cloud, Hui CUI, Zhiguo WAN, DENG, Robert H., Guilin WANG, Yingjiu LI 2016 Singapore Management University

Efficient And Expressive Keyword Search Over Encrypted Data In The Cloud, Hui Cui, Zhiguo Wan, Deng, Robert H., Guilin Wang, Yingjiu Li

Research Collection School Of Information Systems

Searchable encryption allows a cloud server to conduct keyword search over encrypted data on behalf of the data users without learning the underlying plaintexts. However, most existing searchable encryption schemes only support single or conjunctive keyword search, while a few other schemes that are able to perform expressive keyword search are computationally inefficient since they are built from bilinear pairings over the composite-order groups. In this paper, we propose an expressive public-key searchable encryption scheme in the prime-order groups, which allows keyword search policies (i.e., predicates, access structures) to be expressed in conjunctive, disjunctive or any monotonic Boolean formulas ...


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 ...


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