Ten Simple Rules For Responsible Big Data Research,
2017
University of Kentucky
Ten Simple Rules For Responsible Big Data Research, Matthew Zook, Solon Barocas, Danah Boyd, Kate Crawford, Emily Keller, Seeta Peña Gangadharan, Alyssa Goodman, Rachelle Hollander, Barbara A. Koenig, Jacob Metcalf, Arvind Narayanan, Alondra Nelson, Frank Pasquale
Geography Faculty Publications
No abstract provided.
Designing Novel Nanostructured Permanent Magnets,
2017
University of Nebraska at Omaha
Designing Novel Nanostructured Permanent Magnets, Ali Al Kadhim
UNO Student Research and Creative Activity Fair
Rare earth element based alloys have been the source of high performance magnetic alloys, and have played a paramount role in the development of various technologies, including: memory devices (such as credit cards, random-access memory), sensors, and various biomedical applications. However, there is a tremendous need to replace rare earth metals with material with powerful magnetic properties. Our group recently found CrTe-based materials that show very promising magnetic properties in nanostructured form. The magnetic modeling of such material in nanostructured form prior to their fabrication demonstrates their magnetic properties in bulk form. In this project, we investigate the behavior of …
Optimizing Campus Mobility With A Focus On Sustainability: A Graph Theory Approach To Intra-Campus Transportation Networks,
2017
Quinn Nelson
Optimizing Campus Mobility With A Focus On Sustainability: A Graph Theory Approach To Intra-Campus Transportation Networks, Quinn M. Nelson
UNO Student Research and Creative Activity Fair
The idea of public transportation is supported by most in theory but often heavily criticized by users when put into application. There are common tensions that are related to public transportation, as described by frequent users: unreliable, too crowded, and slow. The University of Nebraska-Omaha (UNO) is a growing metropolitan institution that uses a shuttle system to transport students among their three campuses daily. As of 2015, the current total student enrollment is approximately 16,000; UNO plans to enroll 20,000 students by 2020. The expected student growth is also reflected by the current construction of new buildings and expansion of …
Inferring User Consumption Preferences From Social Media,
2017
Harbin Institute of Technology
Inferring User Consumption Preferences From Social Media, Yang Li, Jing Jiang, Ting Liu
Research Collection School Of Computing and Information Systems
Social Media has already become a new arena of our lives and involved different aspects of our social presence. Users' personal information and activities on social media presumably reveal their personal interests, which offer great opportunities for many e-commerce applications. In this paper, we propose a principled latent variable model to infer user consumption preferences at the category level (e.g. inferring what categories of products a user would like to buy). Our model naturally links users' published content and following relations on microblogs with their consumption behaviors on e-commerce websites. Experimental results show our model outperforms the state-of-the-art methods significantly …
Recurrent Neural Networks With Auxiliary Labels For Cross-Domain Opinion Target Extraction,
2017
Singapore Management University
Recurrent Neural Networks With Auxiliary Labels For Cross-Domain Opinion Target Extraction, Ying Ding, Jianfei Yu, Jing Jiang
Research Collection School Of Computing and Information Systems
Opinion target extraction is a fundamental task in opinion mining. In recent years, neural network based supervised learning methods have achieved competitive performance on this task. However, as with any supervised learning method, neural network based methods for this task cannot work well when the training data comes from a different domain than the test data. On the other hand, some rule-based unsupervised methods have shown to be robust when applied to different domains. In this work, we use rule-based unsupervised methods to create auxiliary labels and use neural network models to learn a hidden representation that works well for …
Discovering Burst Patterns Of Burst Topic In Twitter,
2017
Harbin Engineering University
Discovering Burst Patterns Of Burst Topic In Twitter, Guozhong Dong, Wu Yang, Feida Zhu, Wei Wang
Research Collection School Of Computing and Information Systems
Twitter has become one of largest social networks for users to broadcast burst topics. There have been many studies on how to detect burst topics. However, mining burst patterns in burst topics has not been solved by the existing works. In this paper, we investigate the problem of mining burst patterns of burst topic in Twitter. A burst topic user graph model is proposed, which can represent the topology structure of burst topic propagation across a large number of Twitter users. Based on the model, hierarchical clustering is applied to cluster burst topics and reveal burst patterns from the macro …
Seapot-Rl: Selective Exploration Algorithm For Policy Transfer In Rl,
2017
National University of Singapore
Seapot-Rl: Selective Exploration Algorithm For Policy Transfer In Rl, Akshay Narayan, Zhuoru Li, Tze-Yun Leong
Research Collection School Of Computing and Information Systems
We propose a new method for transferring a policy from a source task to a target task in model-based reinforcement learning. Our work is motivated by scenarios where a robotic agent operates in similar but challenging environments, such as hospital wards, differentiated by structural arrangements or obstacles, such as furniture. We address problems that require fast responses adapted from incomplete, prior knowledge of the agent in new scenarios. We present an efficient selective exploration strategy that maximally reuses the source task policy. Reuse efficiency is effected through identifying sub-spaces that are different in the target environment, thus limiting the exploration …
Transcription Through The Eye Of A Needle: Daily And Annual Cyclic Gene Expression Variation In Douglas-Fir Needles,
2017
University of Minnesota - Morris
Transcription Through The Eye Of A Needle: Daily And Annual Cyclic Gene Expression Variation In Douglas-Fir Needles, Peter Dolan
Computer Science Publications
Background: Perennial growth in plants is the product of interdependent cycles of daily and annual stimuli that induce cycles of growth and dormancy. In conifers, needles are the key perennial organ that integrates daily and seasonal signals from light, temperature, and water availability. To understand the relationship between seasonal cycles and seasonal gene expression responses in conifers, we examined diurnal and circannual needle mRNA accumulation in Douglas-fir (Pseudotsuga menziesii) needles at diurnal and circannual scales. Using mRNA sequencing, we sampled 6.1 × 109 reads from 19 trees and constructed a de novo pan-transcriptome reference that includes 173,882 tree-derived transcripts. Using …
A Robust Framework For Mining Youtube Data,
2017
Marshall University
A Robust Framework For Mining Youtube Data, Zifeng Tian
Theses, Dissertations and Capstones
YouTube is currently the most popular and successful video sharing website. As YouTube has broad and profound social impact, YouTube analytics has become a hot research area. The videos on YouTube have become a treasure of data. However, getting access to the immense and massive YouTube data is a challenge. Previous research, studies, and analysis so far, are only conducted on very small volumes of YouTube video data. To date, there exists no mechanism to systematically and continuously collect, process and store the rich set of YouTube data. This thesis presents a methodology to systematically and continuously mine and store …
High Performance Techniques Applied In Partial Differential Equations Library,
2017
College of Saint Benedict/Saint John's University
High Performance Techniques Applied In Partial Differential Equations Library, Shilei Lin
All College Thesis Program, 2016-2019
This thesis explores various Trilinos packages to determine a method for updating the deal.ii library, which specializes in solving partial differential equations by finite element methods. It begins with introducing related concepts and general goals, followed by exploring computational and mathematical methods which are analytical solutions of one-dimensional Boussinesq equations and developing newer prototypes for solvers in deal.ii based on Trilinos packages. After demonstrating the methods, it indicates the reducing solving time in newer prototypes. Based on results from the prototype, similar methods are applied to update the deal.ii library. In the end, a testing program is exploited to demonstrate …
Comparison Of Two-Pass Algorithms For Dynamic Topic Modelling Based On Matrix Decompositions,
2017
Technological University Dublin
Comparison Of Two-Pass Algorithms For Dynamic Topic Modelling Based On Matrix Decompositions, John Cardiff, Gabriella Skitalinskaya, Mikhail Alexandrov
Conference Papers
In this paper we present a two-pass algorithm based on different matrix decompositions, such as LSI, PCA, ICA and NMF, which allows tracking of the evolution of topics over time. The proposed dynamic topic models as output give an easily interpreted overview of topics found in a sequentially organized set of documents that does not require further processing. Each topic is presented by a user-specified number of top-terms. Such an approach to topic modeling if applied to, for example, a news article data set, can be convenient and useful for economists, sociologists, political scientists. The proposed approach allows to achieve …
WMU
An Out-Of-Core Gpu Based Dimensionality Reduction Algorithm For Big Mass Spectrometry Data And Its Application In Bottom-Up Proteomics, Muaaz Awan, Fahad Saeed
Parallel Computing and Data Science Lab Technical Reports
Modern high resolution Mass Spectrometry instruments can generate millions of spectra in a single systems biology experiment. Each spectrum consists of thousands of peaks but only a small number of peaks actively contribute to deduction of peptides. Therefore, pre-processing of MS data to detect noisy and non-useful peaks are an active area of research. Most of the sequential noise reducing algorithms are impractical to use as a pre-processing step due to high time-complexity. In this paper, we present a GPU based dimensionality-reduction algorithm, called G-MSR, for MS2 spectra. Our proposed algorithm uses novel data structures which optimize the memory and …
Discovery And Characterization Of Small Molecule Rac1 Inhibitors,
2017
University of Nebraska Medical Center
Discovery And Characterization Of Small Molecule Rac1 Inhibitors, Jamie L. Arnst, Ashley L. Hein, Margaret A. Taylor, Nick Y. Palermo, Jacob I. Contreras, Yogesh A. Sonawane, Andrw O. Wahl, Michel M. Ouellette, Amarnath Natarajan, Ying Yan
Holland Computing Center: Faculty Publications
Aberrant activation of Rho GTPase Rac1 has been observed in various tumor types, including pancreatic cancer. Rac1 activates multiple signaling pathways that lead to uncontrolled proliferation, invasion and metastasis. Thus, inhibition of Rac1 activity is a viable therapeutic strategy for proliferative disorders such as cancer. Here we identified small molecule inhibitors that target the nucleotide-binding site of Rac1 through in silico screening. Follow up in vitro studies demonstrated that two compounds blocked active Rac1 from binding to its effector PAK1. Fluorescence polarization studies indicate that these compounds target the nucleotide-binding site of Rac1. In cells, both compounds blocked Rac1 binding …
Exploring Population Change Detection By Monitoring Effective Number Of Breeders,
2017
University of Montana
Exploring Population Change Detection By Monitoring Effective Number Of Breeders, Brian Trethewey
Graduate Student Theses, Dissertations, & Professional Papers
Detecting if a population is in decline is an important objective for biologists and conservationists who are monitoring threatened populations. As genetic methods improve effective population size (Ne) and effective number of breeders (Nb) continue to gain popularity as a way to monitor species. Using simulated populations and linkage disequilibrium, we explored detecting population decline through Nb in age structured populations. Through comparisons of sensitivity (1 – false negatives) and specificity (1- false positives) over 1000 replicates, we explored how factors such as starting Nb, number of SNPs, number of individuals …
K-Mer Analysis Pipeline For Classification Of Dna Sequences From Metagenomic Samples,
2017
University of Montana
K-Mer Analysis Pipeline For Classification Of Dna Sequences From Metagenomic Samples, Russell Kaehler
Graduate Student Theses, Dissertations, & Professional Papers
Biological sequence datasets are increasing at a prodigious rate. The volume of data in these datasets surpasses what is observed in many other fields of science. New developments wherein metagenomic DNA from complex bacterial communities is recovered and sequenced are producing a new kind of data known as metagenomic data, which is comprised of DNA fragments from many genomes. Developing a utility to analyze such metagenomic data and predict the sample class from which it originated has many possible implications for ecological and medical applications. Within this document is a description of a series of analytical techniques used to process …
Xic Clustering By Baseyian Network,
2017
Computer Sciences
Xic Clustering By Baseyian Network, Kyle J. Handy
Graduate Student Theses, Dissertations, & Professional Papers
No abstract provided.
Data Mining By Grid Computing In The Search For Extrasolar Planets,
2017
Dublin Institute for Advanced Studies
Data Mining By Grid Computing In The Search For Extrasolar Planets, Oisin Creaner [Thesis]
Doctoral
A system is presented here to provide improved precision in ensemble differential photometry. This is achieved by using the power of grid computing to analyse astronomical catalogues. This produces new catalogues of optimised pointings for each star, which maximise the number and quality of reference stars available. Astronomical phenomena such as exoplanet transits and small-scale structure within quasars may be observed by means of millimagnitude photometric variability on the timescale of minutes to hours. Because of atmospheric distortion, ground-based observations of these phenomena require the use of differential photometry whereby the target is compared with one or more reference stars. …
Rationalizing The Band Gap Tunability Of Semiconductors Via Electronic Structure Calculations,
2017
Duquesne University
Rationalizing The Band Gap Tunability Of Semiconductors Via Electronic Structure Calculations, Matthew N. Srnec
Electronic Theses and Dissertations
The polymorphs of titanium dioxide and various diamond-like semiconductor materials are promising candidates in photovoltaic solar cell applications. Several of these polymorphs have been studied with experimental and computational methods, which often aim at tuning the electronic structure, particularly the band gap value of the crystalline solid. Prior studies report that the addition of a substituent into the structure of titanium dioxide decreases its band gap value, but the reasons for this are unknown. Possible explanations for the change in band gap involve the substituent atom's crystal radius, electronegativity, and ionization energy. Understanding the cause of these changes will provide …
Anomaly Detection In Rfid Networks,
2017
University of North Florida
Anomaly Detection In Rfid Networks, Alaa Alkadi
UNF Graduate Theses and Dissertations
Available security standards for RFID networks (e.g. ISO/IEC 29167) are designed to secure individual tag-reader sessions and do not protect against active attacks that could also compromise the system as a whole (e.g. tag cloning or replay attacks). Proper traffic characterization models of the communication within an RFID network can lead to better understanding of operation under “normal” system state conditions and can consequently help identify security breaches not addressed by current standards. This study of RFID traffic characterization considers two piecewise-constant data smoothing techniques, namely Bayesian blocks and Knuth’s algorithms, over time-tagged events and compares them in the context …
A Physics-Based Approach To Modeling Wildland Fire Spread Through Porous Fuel Beds,
2017
University of Kentucky
A Physics-Based Approach To Modeling Wildland Fire Spread Through Porous Fuel Beds, Tingting Tang
Theses and Dissertations--Mechanical and Aerospace Engineering
Wildfires are becoming increasingly erratic nowadays at least in part because of climate change. CFD (computational fluid dynamics)-based models with the potential of simulating extreme behaviors are gaining increasing attention as a means to predict such behavior in order to aid firefighting efforts. This dissertation describes a wildfire model based on the current understanding of wildfire physics. The model includes physics of turbulence, inhomogeneous porous fuel beds, heat release, ignition, and firebrands. A discrete dynamical system for flow in porous media is derived and incorporated into the subgrid-scale model for synthetic-velocity large-eddy simulation (LES), and a general porosity-permeability model is …
