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Full-Text Articles in Physical Sciences and Mathematics

Algorithm For Premature Ventricular Contraction Detection From A Subcutaneous Electrocardiogram Signal, Iris Lynn Shelly Dec 2016

Algorithm For Premature Ventricular Contraction Detection From A Subcutaneous Electrocardiogram Signal, Iris Lynn Shelly

Dissertations and Theses

Cardiac arrhythmias occur when the normal pattern of electrical signals in the heart breaks down. A premature ventricular contraction (PVC) is a common type of arrhythmia that occurs when a heartbeat originates from an ectopic focus within the ventricles rather than from the sinus node in the right atrium. This and other arrhythmias are often diagnosed with the help of an electrocardiogram, or ECG, which records the electrical activity of the heart using electrodes placed on the skin. In an ECG signal, a PVC is characterized by both timing and morphological differences from a normal sinus beat.

An implantable cardiac …


Massively Parallel Algorithm For Solving The Eikonal Equation On Multiple Accelerator Platforms, Anup Shrestha Dec 2016

Massively Parallel Algorithm For Solving The Eikonal Equation On Multiple Accelerator Platforms, Anup Shrestha

Boise State University Theses and Dissertations

The research presented in this thesis investigates parallel implementations of the Fast Sweeping Method (FSM) for Graphics Processing Unit (GPU)-based computational plat forms and proposes a new parallel algorithm for distributed computing platforms with accelerators. Hardware accelerators such as GPUs and co-processors have emerged as general- purpose processors in today’s high performance computing (HPC) platforms, thereby increasing platforms’ performance capabilities. This trend has allowed greater parallelism and substantial acceleration of scientific simulation software. In order to leverage the power of new HPC platforms, scientific applications must be written in specific lower-level programming languages, which used to be platform specific. Newer …


A Survey On Wireless Indoor Localization From The Device Perspective, Jiang Xiao, Zimu Zhou, Youwen Yi, Lionel M. Ni Nov 2016

A Survey On Wireless Indoor Localization From The Device Perspective, Jiang Xiao, Zimu Zhou, Youwen Yi, Lionel M. Ni

Research Collection School Of Computing and Information Systems

With the marvelous development of wireless techniques and ubiquitous deployment of wireless systems indoors, myriad indoor location-based services (ILBSs) have permeated into numerous aspects of modern life. The most fundamental functionality is to pinpoint the location of the target via wireless devices. According to how wireless devices interact with the target, wireless indoor localization schemes roughly fall into two categories: device based and device free. In device-based localization, a wireless device (e.g., a smartphone) is attached to the target and computes its location through cooperation with other deployed wireless devices. In device-free localization, the target carries no wireless devices, while …


Algorithms For Glycan Structure Identification With Tandem Mass Spectrometry, Weiping Sun Sep 2016

Algorithms For Glycan Structure Identification With Tandem Mass Spectrometry, Weiping Sun

Electronic Thesis and Dissertation Repository

Glycosylation is a frequently observed post-translational modification (PTM) of proteins. It has been estimated over half of eukaryotic proteins in nature are glycoproteins. Glycoprotein analysis plays a vital role in drug preparation. Thus, characterization of glycans that are linked to proteins has become necessary in glycoproteomics. Mass spectrometry has become an effective analytical technique for glycoproteomics analysis because of its high throughput and sensitivity. The large amount of spectral data collected in a mass spectrometry experiment makes manual interpretation impossible and requires effective computational approaches for automated analysis. Different algorithmic solutions have been proposed to address the challenges in glycoproteomics …


Privacy-Aware Relevant Data Access With Semantically Enriched Search Queries For Untrusted Cloud Storage Services, Zeeshan Pervez, Mahmood Ahmad, Asad Masood Khattak, Sungyoung Lee, Tae Choong Chung Aug 2016

Privacy-Aware Relevant Data Access With Semantically Enriched Search Queries For Untrusted Cloud Storage Services, Zeeshan Pervez, Mahmood Ahmad, Asad Masood Khattak, Sungyoung Lee, Tae Choong Chung

All Works

© 2016 Pervez et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Privacy-aware search of outsourced data ensures relevant data access in the untrusted domain of a public cloud service provider. Subscriber of a public cloud storage service can determine the presence or absence of a particular keyword by submitting search query in the form of a trapdoor. However, these trapdoor-based search queries are limited in functionality and cannot be used to identify …


A Dynamic Run-Profile Energy-Aware Approach For Scheduling Computationally Intensive Bioinformatics Applications, Sachin Pawaskar, Hesham Ali Jul 2016

A Dynamic Run-Profile Energy-Aware Approach For Scheduling Computationally Intensive Bioinformatics Applications, Sachin Pawaskar, Hesham Ali

Computer Science Faculty Proceedings & Presentations

High Performance Computing (HPC) resources are housed in large datacenters, which consume exorbitant amounts of energy and are quickly demanding attention from businesses as they result in high operating costs. On the other hand HPC environments have been very useful to researchers in many emerging areas in life sciences such as Bioinformatics and Medical Informatics. In an earlier work, we introduced a dynamic model for energy aware scheduling (EAS) in a HPC environment; the model is domain agnostic and incorporates both the deadline parameter as well as energy parameters for computationally intensive applications. Our proposed EAS model incorporates 2-phases. In …


Novel Monte Carlo Methods For Large-Scale Linear Algebra Operations, Hao Ji Jul 2016

Novel Monte Carlo Methods For Large-Scale Linear Algebra Operations, Hao Ji

Computer Science Theses & Dissertations

Linear algebra operations play an important role in scientific computing and data analysis. With increasing data volume and complexity in the "Big Data" era, linear algebra operations are important tools to process massive datasets. On one hand, the advent of modern high-performance computing architectures with increasing computing power has greatly enhanced our capability to deal with a large volume of data. One the other hand, many classical, deterministic numerical linear algebra algorithms have difficulty to scale to handle large data sets.

Monte Carlo methods, which are based on statistical sampling, exhibit many attractive properties in dealing with large volume of …


A Horizon Decomposition Approach For The Capacitated Lot-Sizing Problem With Setup Times, Ioannis Fragkos, Zeger Degraeve, Bert De Reyck May 2016

A Horizon Decomposition Approach For The Capacitated Lot-Sizing Problem With Setup Times, Ioannis Fragkos, Zeger Degraeve, Bert De Reyck

Research Collection Lee Kong Chian School Of Business

We introduce horizon decomposition in the context of Dantzig-Wolfe decomposition, and apply it to the capacitated lot-sizing problem with setup times. We partition the problem horizon in contiguous overlapping intervals and create subproblems identical to the original problem, but of smaller size. The user has the flexibility to regulate the size of the master problem and the subproblem via two scalar parameters. We investigate empirically which parameter configurations are efficient, and assess their robustness at different problem classes. Our branch-and-price algorithm outperforms state-of-the-art branch-and-cut solvers when tested to a new data set of challenging instances that we generated. Our methodology …


On Effective Location-Aware Music Recommendation, Zhiyong Cheng, Jialie Shen Apr 2016

On Effective Location-Aware Music Recommendation, Zhiyong Cheng, Jialie Shen

Research Collection School Of Computing and Information Systems

Rapid advances in mobile devices and cloud-based music service now allow consumers to enjoy music any-time and anywhere. Consequently, there has been an increasing demand in studying intelligent techniques to facilitate context-aware music recommendation. However, one important context that is generally overlooked is user's venue, which often includes surrounding atmosphere, correlates with activities, and greatly influences the user's music preferences. In this article, we present a novel venue-aware music recommender system called VenueMusic to effectively identify suitable songs for various types of popular venues in our daily lives. Toward this goal, a Location-aware Topic Model (LTM) is proposed to (i) …


Opinion Question Answering By Sentiment Clip Localization, Lei Pang, Chong-Wah Ngo Mar 2016

Opinion Question Answering By Sentiment Clip Localization, Lei Pang, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

This article considers multimedia question answering beyond factoid and how-to questions. We are interested in searching videos for answering opinion-oriented questions that are controversial and hotly debated. Examples of questions include "Should Edward Snowden be pardoned?" and "Obamacare-unconstitutional or not?". These questions often invoke emotional response, either positively or negatively, hence are likely to be better answered by videos than texts, due to the vivid display of emotional signals visible through facial expression and speaking tone. Nevertheless, a potential answer of duration 60s may be embedded in a video of 10min, resulting in degraded user experience compared to reading the …


A Feature Selection Algorithm To Compute Gene Centric Methylation From Probe Level Methylation Data, Brittany Baur, Serdar Bozdag Feb 2016

A Feature Selection Algorithm To Compute Gene Centric Methylation From Probe Level Methylation Data, Brittany Baur, Serdar Bozdag

Mathematics, Statistics and Computer Science Faculty Research and Publications

DNA methylation is an important epigenetic event that effects gene expression during development and various diseases such as cancer. Understanding the mechanism of action of DNA methylation is important for downstream analysis. In the Illumina Infinium HumanMethylation 450K array, there are tens of probes associated with each gene. Given methylation intensities of all these probes, it is necessary to compute which of these probes are most representative of the gene centric methylation level. In this study, we developed a feature selection algorithm based on sequential forward selection that utilized different classification methods to compute gene centric DNA methylation using probe …


Negative Factor: Improving Regular-Expression Matching In Strings, Xiaochun Yang, Tao Qiu, Bin Wang, Baihua Zheng, Yaoshu Wang, Chen Li Feb 2016

Negative Factor: Improving Regular-Expression Matching In Strings, Xiaochun Yang, Tao Qiu, Bin Wang, Baihua Zheng, Yaoshu Wang, Chen Li

Research Collection School Of Computing and Information Systems

The problem of finding matches of a regular expression (RE) on a string exists in many applications such as text editing, biosequence search, and shell commands. Existing techniques first identify candidates using substrings in the RE, then verify each of them using an automaton. These techniques become inefficient when there are many candidate occurrences that need to be verified. In this paper we propose a novel technique that prunes false negatives by utilizing negative factors, which are substrings that cannot appear in an answer. A main advantage of the technique is that it can be integrated with many existing algorithms …


Evaluating And Improving The Efficiency Of Software And Algorithms For Sequence Data Analysis, Hugh L. Eaves Jan 2016

Evaluating And Improving The Efficiency Of Software And Algorithms For Sequence Data Analysis, Hugh L. Eaves

Theses and Dissertations

With the ever-growing size of sequence data sets, data processing and analysis are an increasingly large portion of the time and money spent on nucleic acid sequencing projects. Correspondingly, the performance of the software and algorithms used to perform that analysis has a direct effect on the time and expense involved. Although the analytical methods are widely varied, certain types of software and algorithms are applicable to a number of areas. Targeting improvements to these common elements has the potential for wide reaching rewards. This dissertation research consisted of several projects to characterize and improve upon the efficiency of several …


Efficient Execution Of Top-K Closeness Centrality Queries, Paul W. Olsen Jan 2016

Efficient Execution Of Top-K Closeness Centrality Queries, Paul W. Olsen

Legacy Theses & Dissertations (2009 - 2024)

Many of today's applications can benefit from the discovery of the most central entities in real-world networks.


Improving Patient Safety, Health Data Accuracy, And Remote Self-Management Of Health Through The Establishment Of A Biometric-Based Global Uhid, Guy Hembroff Jan 2016

Improving Patient Safety, Health Data Accuracy, And Remote Self-Management Of Health Through The Establishment Of A Biometric-Based Global Uhid, Guy Hembroff

Michigan Tech Publications

Healthcare systems globally continue to face challenges surrounding patient identification. Consequences of misidentification include incomplete and inaccurate electronic patient health records potentially jeopardizing patients' safety, a significant amount of cases of medical fraud because of inadequate identification mechanisms, and difficulties affiliated with the value of remote health self-management application data being aggregated accurately into the user's Electronic Health Record (EHR). We introduce a new technique of user identification in healthcare capable of establishing a global identifier. Our research has developed algorithms capable of establishing a Unique Health Identifier (UHID) based on the user's fingerprint biometric, with the utilization of facial-recognition …


Algorithms Leveraging Smartphone Sensing For Analyzing Explosion Events, Srinivas Chakravarthi Thandu Jan 2016

Algorithms Leveraging Smartphone Sensing For Analyzing Explosion Events, Srinivas Chakravarthi Thandu

Doctoral Dissertations

"The increasing frequency of explosive disasters throughout the world in recent years have created a clear need for the systems to monitor for them continuously to improve the post-disaster emergency events such as rescue and recovery operations. Disasters both man-made and natural are unfortunate and not preferred, however monitoring them may be a lifesaving phenomenon in emergency scenarios. Dedicated sensors deployed in the public places and their associated networks to monitor such events may be inadequate and must be complemented for making the monitoring more pervasive and effective. In the recent past, modern smartphones with significant processing, networking and storage …


Applications Of Computational Geometry And Computer Vision, Joseph Lemley Jan 2016

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 …