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 ...
Feature Extraction To Improve Nowcasting Using Social Media Event Detection On Cloud Computing And Sentiment Analysis, 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
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 ...
An Algorithm For The Machine Calculation Of Minimal Paths, 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.
Latent Semantic Indexing In The Discovery Of Cyber-Bullying In Online Text, 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, 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, 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 ...
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 ...
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 ...
Signal Processing Based On Stable Radix-2 Dct I-Iv Algorithms Having Orthogonal Factors, 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, 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 ...
Packet Filter Approach To Detect Denial Of Service Attacks, 2016 California State University, San Bernardino
Packet Filter Approach To Detect Denial Of Service Attacks, Essa Yahya M Muharish
Electronic Theses, Projects, and Dissertations
Denial of service attacks (DoS) are a common threat to many online services. These attacks aim to overcome the availability of an online service with massive traffic from multiple sources. By spoofing legitimate users, an attacker floods a target system with a high quantity of packets or connections to crash its network resources, bandwidth, equipment, or servers. Packet filtering methods are the most known way to prevent these attacks via identifying and blocking the spoofed attack from reaching its target. In this project, the extent of the DoS attacks problem and attempts to prevent it are explored. The attacks categories ...
The Contributions Of Anatol Rapoport To Game Theory, 2016 Western University
The Contributions Of Anatol Rapoport To Game Theory, Erika Simpson
Political Science Publications
Game theory is used to rationally and dispassionately examine the strategic behaviour of nations, especially superpower behaviour. This article explains how basic game theory - at its simplest level - was used by Anatol Rapoport to generate ideas about how to enhance world peace. Rapoport was at the forefront of the game theoreticians who sought to conceptualize strategies that could promote international cooperation. Accordingly, the basic logic of game theory is explained using the game models of ‘Chicken’ and ‘Prisoner’s Dilemma’. These models were used by Rapoport in his books and lectures in simple and complex ways. Then Rapoport’s revolutionary ...
Whiteboard Scanning Using Super-Resolution, 2016 Dickinson College
Whiteboard Scanning Using Super-Resolution, Wode Ni
Honors Theses By Year
In this project, we investigated the effectiveness of the Super-Resolution algorithm on a distant whiteboard scenario. Imagine a person taking a video or an image sequence of a whiteboard from a distance. Due to the limitation of camera resolution and the distance, the words in the whiteboard images are sometimes illegible. Though there exist applications to enhance the image quality, the resolution limit caused by the distance is difficult to overcome. Super-resolution, a class of techniques in the field of Computer Vision, enables us to enhance the quality of the images by utilizing the information of multiple low quality images ...
Pain Management: Formal Verification Of An Android Application Using Eventb2sql, 2016 Dickinson College
Pain Management: Formal Verification Of An Android Application Using Eventb2sql, Graham Peter Williams
Honors Theses By Year
This project is a case study on formal verification of an Android application used for pain management. When it comes to healthcare applications, the consistency of the application is crucial, as it may affect the wellbeing of the user. The application will check for trends in the user reports of pain, stress, etc. and notify the user accordingly. The model that specifies these trends is defined in Event-B using an Eclipse-based IDE called Rodin. We used the automated and interactive theorem provers built into Rodin to verify that the model always gives the user consistent information. The Event-B model is ...
Applying Novelty Search To The Construction Of Ensemble Systems, 2016 Dickinson College
Applying Novelty Search To The Construction Of Ensemble Systems, Hieu Kinh Le
Honors Theses By Year
Ensemble methods are widely applied in classification problems. Ensemble methods combine results from multiple classifiers to overcome the possible deficiency of any single classifier. One important question is how to construct an ensemble system so that it can utilize all individuals most efficiently to improve classification results. An ensemble system thus needs some level of diversity in terms of error among individuals to avoid group mistakes. Novelty Search is a recently published approach in evolutionary computation in which individuals evolve based on a novelty metric, which evaluates how different their behavior is in addition to an objective metric that shows ...
Identifying Relationships Between Scientific Datasets, 2016 Portland State University
Identifying Relationships Between Scientific Datasets, Abdussalam Alawini
Dissertations and Theses
Scientific datasets associated with a research project can proliferate over time as a result of activities such as sharing datasets among collaborators, extending existing datasets with new measurements, and extracting subsets of data for analysis. As such datasets begin to accumulate, it becomes increasingly difficult for a scientist to keep track of their derivation history, which complicates data sharing, provenance tracking, and scientific reproducibility. Understanding what relationships exist between datasets can help scientists recall their original derivation history. For instance, if dataset A is contained in dataset B, then the connection between A and B could be that A was ...
Sparse Feature Learning For Image Analysis In Segmentation, Classification, And Disease Diagnosis., 2016 University of Louisville
Sparse Feature Learning For Image Analysis In Segmentation, Classification, And Disease Diagnosis., Ehsan Hosseini-Asl
Electronic Theses and Dissertations
The success of machine learning algorithms generally depends on intermediate data representation, called features that disentangle the hidden factors of variation in data. Moreover, machine learning models are required to be generalized, in order to reduce the specificity or bias toward the training dataset. Unsupervised feature learning is useful in taking advantage of large amount of unlabeled data, which is available to capture these variations. However, learned features are required to capture variational patterns in data space. In this dissertation, unsupervised feature learning with sparsity is investigated for sparse and local feature extraction with application to lung segmentation, interpretable deep ...
Ant Colony Optimization For Continuous Spaces, 2016 University of Arkansas, Fayetteville
Ant Colony Optimization For Continuous Spaces, Rachel Findley
Computer Science and Computer Engineering Undergraduate Honors Theses
Ant Colony Optimization (ACO) is an optimization algorithm designed to find semi-optimal solutions to Combinatorial Optimization Problems. The challenge of modifying this algorithm to effectively optimize over a continuous domain is one that has been tackled by several researchers. In this paper, ACO has been modified to use several variations of the algorithm for continuous spaces. An aspect of ACO which is crucial to its success when optimizing over a continuous space is choosing the appropriate object (solution component) out of an infinite set to add to the ant's path. This step is highly important in shaping good solutions ...
User Interface Design, 2016 University of Dayton
User Interface Design, Moritz Stefaner, Sebastien Ferre, Saverio Perugini, Jonathan Koren, Yi Zhang
As detailed in Chap. 1, system implementations for dynamic taxonomies and faceted search allow a wide range of query possibilities on the data. Only when these are made accessible by appropriate user interfaces, the resulting applications can support a variety of search, browsing and analysis tasks. User interface design in this area is confronted with specific challenges. This chapter presents an overview of both established and novel principles and solutions.
Program Transformations For Information Personalization, 2016 University of Dayton
Program Transformations For Information Personalization, Saverio Perugini, Naren Ramakrishnan
Personalization constitutes the mechanisms necessary to automatically customize information content, structure, and presentation to the end user to reduce information overload. Unlike traditional approaches to personalization, the central theme of our approach is to model a website as a program and conduct website transformation for personalization by program transformation (e.g., partial evaluation, program slicing). The goal of this paper is study personalization through a program transformation lens and develop a formal model, based on program transformations, for personalized interaction with hierarchical hypermedia. The specific research issues addressed involve identifying and developing program representations and transformations suitable for classes of ...