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Numerical Analysis and Scientific Computing Commons™

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2016

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Articles 151 - 180 of 206

Full-Text Articles in Numerical Analysis and Scientific Computing

Nanoscale Frictional Properties Of Nickel With One-Dimensional And Two-Dimensional Materials, Timothy K. Schlenger May 2016

Nanoscale Frictional Properties Of Nickel With One-Dimensional And Two-Dimensional Materials, Timothy K. Schlenger

Mechanical Engineering Undergraduate Honors Theses

When looking at the nanoscale, material interface interactions have been observed to exhibit particularly interesting properties. Our research looks into various combinations of carbyne and graphene atop a nickel block to look into the interface friction properties between them. Both the carbyne and graphene are tested using steered molecular dynamics (SMD) in sheering and peeling directions along the surface of the nickel block. These tests are then analyzed by comparing the magnitude of the acting force versus the displacement of the carbon allotrope sample across the nickel block. It is found that as the width of a carbon allotrope sample …

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Teaching Numerical Methods In The Context Of Galaxy Mergers, Maria Kourjanskaia May 2016

Teaching Numerical Methods In The Context Of Galaxy Mergers, Maria Kourjanskaia

Physics

Methods of teaching numerical methods to solve ordinary differential equations in the context of galaxy mergers were explored. The research published in a paper by Toomre and Toomre in 1972 describing the formation of galactic tails and bridges from close tidal interactions was adapted into a project targeting undergraduate physics students. Typically undergraduate physics students only take one Computational Physics class in which various techniques and algorithms are taught. Although it is important to study computational physics techniques, it is just as important to apply this knowledge to a problem that is representative of what computational physics researchers are investigating …

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Joint Search By Social And Spatial Proximity [Extended Abstract], Kyriakos Mouratidis, Jing Li, Yu Tang, Nikos Mamoulis May 2016

Joint Search By Social And Spatial Proximity [Extended Abstract], Kyriakos Mouratidis, Jing Li, Yu Tang, Nikos Mamoulis

Research Collection School Of Computing and Information Systems

The diffusion of social networks introduces new challengesand opportunities for advanced services, especially so with their ongoingaddition of location-based features. We show how applications like company andfriend recommendation could significantly benefit from incorporating social andspatial proximity, and study a query type that captures these twofold semantics.We develop highly scalable algorithms for its processing, and use real socialnetwork data to empirically verify their efficiency and efficacy.

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Euclidean Co-Embedding Of Ordinal Data For Multi-Type Visualization, Dung D. Le, Hady W. Lauw May 2016

Euclidean Co-Embedding Of Ordinal Data For Multi-Type Visualization, Dung D. Le, Hady W. Lauw

Research Collection School Of Computing and Information Systems

Embedding deals with reducing the high-dimensional representation of data into a low-dimensional representation. Previous work mostly focuses on preserving similarities among objects. Here, not only do we explicitly recognize multiple types of objects, but we also focus on the ordinal relationships across types. Collaborative Ordinal Embedding or COE is based on generative modelling of ordinal triples. Experiments show that COE outperforms the baselines on objective metrics, revealing its capacity for information preservation for ordinal data.

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Context-Aware Advertisement Recommendation For High-Speed Social News Feeding, Yuchen Li, Dongxiang Zhang, Ziquan Lan, Kian-Lee Tan May 2016

Context-Aware Advertisement Recommendation For High-Speed Social News Feeding, Yuchen Li, Dongxiang Zhang, Ziquan Lan, Kian-Lee Tan

Research Collection School Of Computing and Information Systems

Social media advertising is a multi-billion dollar market and has become the major revenue source for Facebook and Twitter. To deliver ads to potentially interested users, these social network platforms learn a prediction model for each user based on their personal interests. However, as user interests often evolve slowly, the user may end up receiving repetitive ads. In this paper, we propose a context-aware advertising framework that takes into account the relatively static personal interests as well as the dynamic news feed from friends to drive growth in the ad click-through rate. To meet the real-time requirement, we first propose …

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Semantic Proximity Search On Graphs With Metagraph-Based Learning, Yuan Fang, Wenqing Lin, Vincent W. Zheng, Min Wu, Kevin Chen-Chuan Chang, Xiao-Li Li May 2016

Semantic Proximity Search On Graphs With Metagraph-Based Learning, Yuan Fang, Wenqing Lin, Vincent W. Zheng, Min Wu, Kevin Chen-Chuan Chang, Xiao-Li Li

Research Collection School Of Computing and Information Systems

Given ubiquitous graph data such as the Web and social networks, proximity search on graphs has been an active research topic. The task boils down to measuring the proximity between two nodes on a graph. Although most earlier studies deal with homogeneous or bipartite graphs only, many real-world graphs are heterogeneous with objects of various types, giving rise to different semantic classes of proximity. For instance, on a social network two users can be close for different reasons, such as being classmates or family members, which represent two distinct classes of proximity. Thus, it becomes inadequate to only measure a …

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Temporal Kernel Descriptors For Learning With Time-Sensitive Patterns, Doyen Sahoo, Abhishek Sharma, Hoi, Steven C. H., Peilin Zhao May 2016

Temporal Kernel Descriptors For Learning With Time-Sensitive Patterns, Doyen Sahoo, Abhishek Sharma, Hoi, Steven C. H., Peilin Zhao

Research Collection School Of Computing and Information Systems

Detecting temporal patterns is one of the most prevalent challenges while mining data. Often, timestamps or information about when certain instances or events occurred can provide us with critical information to recognize temporal patterns. Unfortunately, most existing techniques are not able to fully extract useful temporal information based on the time (especially at different resolutions of time). They miss out on 3 crucial factors: (i) they do not distinguish between timestamp features (which have cyclical or periodic properties) and ordinary features; (ii) they are not able to detect patterns exhibited at different resolutions of time (e.g. different patterns at the …

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A Core Task Abstraction Approach To Hierarchical Reinforcement Learning [Extended Abstract], Zhuoru Li, Akshay Narayan, Tze-Yun Leong May 2016

A Core Task Abstraction Approach To Hierarchical Reinforcement Learning [Extended Abstract], Zhuoru Li, Akshay Narayan, Tze-Yun Leong

Research Collection School Of Computing and Information Systems

We propose a new, core task abstraction (CTA) approach to learning the relevant transition functions in model-based hierarchical reinforcement learning. CTA exploits contextual independences of the state variables conditional on the task-specific actions; its promising performance is demonstrated through a set of benchmark problems.

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Mining And Clustering Mobility Evolution Patterns From Social Media For Urban Informatics, Chien-Cheng Chen, Meng-Fen Chiang, Wen-Chih Peng May 2016

Mining And Clustering Mobility Evolution Patterns From Social Media For Urban Informatics, Chien-Cheng Chen, Meng-Fen Chiang, Wen-Chih Peng

Research Collection School Of Computing and Information Systems

In this paper, given a set of check-in data, we aim at discovering representative daily movement behavior of users in a city. For example, daily movement behavior on a weekday may show users moving from one to another spatial region associated with time information. Since check-in data contain both spatial and temporal information, we propose a mobility evolution pattern to capture the daily movement behavior of users in a city. Furthermore, given a set of daily mobility evolution patterns, we formulate their similarity distances and then discover representative mobility evolution patterns via the clustering process. Representative mobility evolution patterns are …

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#Greysanatomy Vs. #Yankees: Demographics And Hashtag Use On Twitter, Jisun An, Ingmar Weber May 2016

#Greysanatomy Vs. #Yankees: Demographics And Hashtag Use On Twitter, Jisun An, Ingmar Weber

Research Collection School Of Computing and Information Systems

Demographics, in particular, gender, age, and race, are a key predictor of human behavior. Despite the significant effect that demographics plays, most scientific studies using online social media do not consider this factor, mainly due to the lack of such information. In this work, we use state-of-the-art face analysis software to infer gender, age, and race from profile images of 350K Twitter users from New York. For the period from November 1, 2014 to October 31, 2015, we study which hashtags are used by different demographic groups. Though we find considerable overlap for the most popular hashtags, there are also …

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Method For Determining Time-Resolved Heat Transfer Coefficient And Adiabatic Effectiveness Waveforms With Unsteady Film Cooling, James L. Rutledge, Jonathan F. Mccall Apr 2016

Method For Determining Time-Resolved Heat Transfer Coefficient And Adiabatic Effectiveness Waveforms With Unsteady Film Cooling, James L. Rutledge, Jonathan F. Mccall

AFIT Patents

A new method for determining heat transfer coefficient (h) and adiabatic effectiveness (η) waveforms h(t) and η(t) from a single test uses a novel inverse heat transfer methodology to use surface temperature histories obtained using prior art approaches to approximate the h(t) and η(t) waveforms. The method best curve fits the data to a pair of truncated Fourier series.

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Hpc Made Easy: Using Docker To Distribute And Test Trilinos, Sean J. Deal Apr 2016

Hpc Made Easy: Using Docker To Distribute And Test Trilinos, Sean J. Deal

All College Thesis Program, 2016-2019

Virtualization is an enticing option for computer science research given its ability to provide repeatable, standardized environments, but traditional virtual machines have too much overhead cost to be practical. Docker, a Linux-based tool for operating-system level virtualization, has been quickly gaining popularity throughout the computer science field by touting a virtualization solution that is easily distributable and more lightweight than virtual machines. This thesis aims to explore if Docker is a viable option for conducting virtualized research by evaluating the results of parallel performance tests using the Trilinos project.

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Catching Card Counters, Sarah French Apr 2016

Catching Card Counters, Sarah French

Honors Projects in Mathematics

The casino industry has been researched through a variety of disciplines including psychological gambling habits, technological advances, business strategies, and mathematical simulations. In the vast number of studies that have been conducted, there are few scholarly articles that focus on the specific aspect of card counting. The majority of games in the casino are designed to favor the “house”. This study focuses on the game of blackjack, in which players using a card counting strategy can tip the odds in their favor. A computer simulation was used to model the betting strategy of a card counter who would bet methodically. …

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Performance Portable High Performance Conjugate Gradients Benchmark, Zachary Bookey Apr 2016

Performance Portable High Performance Conjugate Gradients Benchmark, Zachary Bookey

All College Thesis Program, 2016-2019

The High Performance Conjugate Gradient Benchmark (HPCG) is an international project to create a more appropriate benchmark test for the world's most powerful computers. The current LINPACK benchmark, which is the standard for measuring the performance of the top 500 fastest computers in the world, is moving computers in a direction that is no longer beneficial to many important parallel applications. HPCG is designed to exercise computations and data access patterns more commonly found in applications. The reference version of HPCG exploits only some parallelism available on existing supercomputers and the main focus of this work was to create a …

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The Anisotropy Of Hexagonal Close-Packed And Liquid Interface Free Energy Using Molecular Dynamics Simulations Based On Modified Embedded-Atom Method, Ebrahim Asadi, Mohsen Asle Zaeem Apr 2016

The Anisotropy Of Hexagonal Close-Packed And Liquid Interface Free Energy Using Molecular Dynamics Simulations Based On Modified Embedded-Atom Method, Ebrahim Asadi, Mohsen Asle Zaeem

Materials Science and Engineering Faculty Research & Creative Works

This work aims to comprehensively study the anisotropy of the hexagonal close-packed (HCP)-liquid interface free energy using molecular dynamics (MD) simulations based on the modified-embedded atom method (MEAM). As a case study, all the simulations are performed for Magnesium (Mg). The solid-liquid coexisting approach is used to accurately calculate the melting point and melting properties. Then, the capillary fluctuation method (CFM) is used to determine the HCP-liquid interface free energy (γ) and anisotropy parameters. In CFM, a continuous order parameter is employed to accurately locate the HCP-liquid interface location, and the HCP symmetry-adapted spherical harmonics are used to expand γ …

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Alignment For Comprehensive Two-Dimensional Gas Chromatography (Gcxgc) With Global, Low-Order Polynomial Transformations, Davis Rempe, Stephen Reichenbach, Stephen Scott Apr 2016

Alignment For Comprehensive Two-Dimensional Gas Chromatography (Gcxgc) With Global, Low-Order Polynomial Transformations, Davis Rempe, Stephen Reichenbach, Stephen Scott

UCARE: Research Products

As columns age and differ between systems, retention times for GC x GC may vary between runs. In order to properly analyze chromatograms, it is often desirable to align chromatographic features between chromatograms. This alignment can be characterized by a mapping of retention times from one chromatogram to the retention times of another chromatogram. Alignment methods can be classified as global or local, i.e., whether the geometric differences between chromatograms are characterized by a single function for the entire chromatogram or by a combination of many functions for different regions of the chromatogram. Previous work has shown that global, low-degree …

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Semantic Visualization With Neighborhood Graph Regularization, Tuan Minh Van Le, Hady W. Lauw Apr 2016

Semantic Visualization With Neighborhood Graph Regularization, Tuan Minh Van Le, Hady W. Lauw

Research Collection School Of Computing and Information Systems

Visualization of high-dimensional data, such as text documents, is useful to map out the similarities among various data points. In the high-dimensional space, documents are commonly represented as bags of words, with dimensionality equal to the vocabulary size. Classical approaches to document visualization directly reduce this into visualizable two or three dimensions. Recent approaches consider an intermediate representation in topic space, between word space and visualization space, which preserves the semantics by topic modeling. While aiming for a good fit between the model parameters and the observed data, previous approaches have not considered the local consistency among data instances. We …

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Policy Analytics, Household Informedness And The Collection Of Household Hazardous Waste, Kustini Lim-Wavde, Robert J. Kauffman, Greg Dawson Apr 2016

Policy Analytics, Household Informedness And The Collection Of Household Hazardous Waste, Kustini Lim-Wavde, Robert J. Kauffman, Greg Dawson

Research Collection School Of Computing and Information Systems

Proper collection of Household Hazardous Waste (HHW) is an important action to support environmental sustainability. We investigate the role of household informedness, the degree to which households have the necessary information to make utility-maximizing decisions, as they relate to participation in HHW collection programs. We find two factors that influence household informedness: the provision of public education about HHW and environmental quality information. We conducted an empirical study on HHW collection in California to obtain statistical evidence on the effect of these factors on the amount of HHW collected. The findings of this policy analytics study improve our understanding of …

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Ontology-Aided Feature Correlation For Multi-Modal Urban Sensing, Archan Misra, Zaman Lantra, Kasthuri Jayarajah Apr 2016

Ontology-Aided Feature Correlation For Multi-Modal Urban Sensing, Archan Misra, Zaman Lantra, Kasthuri Jayarajah

Research Collection School Of Computing and Information Systems

The paper explores the use of correlation across features extracted from different sensing channels to help in urban situational understanding. We use real-world datasets to show how such correlation can improve the accuracy of detection of city-wide events by combining metadata analysis with image analysis of Instagram content. We demonstrate this through a case study on the Singapore Haze. We show that simple ontological relationships and reasoning can significantly help in automating such correlation-based understanding of transient urban events.

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Mercury Isotopes Of Atmospheric Particle Bound Mercury For Source Apportionment Study In Urban Kolkata, India, Reshmi Das, Xianfeng Wang, Bahareh Khezri, Richard D. Webster, Pradip Kumar Sikdar, Subhajit Datta Apr 2016

Mercury Isotopes Of Atmospheric Particle Bound Mercury For Source Apportionment Study In Urban Kolkata, India, Reshmi Das, Xianfeng Wang, Bahareh Khezri, Richard D. Webster, Pradip Kumar Sikdar, Subhajit Datta

Research Collection School Of Computing and Information Systems

The particle bound mercury (PBM) in urban-industrial areas is mainly of anthropogenic origin, and is derived from two principal sources: Hg bound to particulate matter directly emitted by industries and power generation plants, and adsorption of gaseous elemental mercury (GEM) and gaseous oxidized mercury (GOM) on air particulates from gas or aqueous phases. Here, we measured the Hg isotope composition of PBM in PM10 samples collected from three locations, a traffic junction, a waste incineration site and an industrial site in Kolkata, the largest metropolis in Eastern India. Sampling was carried out in winter and monsoon seasons between 2013–2015. …

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Spatio-Temporal Generalization Of The Harris Criterion And Its Application To Diffusive Disorder, Thomas Vojta, Ronald Dickman Mar 2016

Spatio-Temporal Generalization Of The Harris Criterion And Its Application To Diffusive Disorder, Thomas Vojta, Ronald Dickman

Physics Faculty Research & Creative Works

We investigate how a clean continuous phase transition is affected by spatiotemporal disorder, i.e., by an external perturbation that fluctuates in both space and time. We derive a generalization of the Harris criterion for the stability of the clean critical behavior in terms of the space-time correlation function of the external perturbation. As an application, we consider diffusive disorder, i.e., an external perturbation governed by diffusive dynamics, and its effects on a variety of equilibrium and nonequilibrium critical points. We also discuss the relation between diffusive disorder and diffusive dynamical degrees of freedom in the example of model C of …

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A Uniform Database Of Teleseismic Shear-Wave Splitting Measurements For The Western And Central United States: December 2014 Update, Bin B. Yang, Kelly H. Liu, Haider H. Dahm, Stephen S. Gao Mar 2016

A Uniform Database Of Teleseismic Shear-Wave Splitting Measurements For The Western And Central United States: December 2014 Update, Bin B. Yang, Kelly H. Liu, Haider H. Dahm, Stephen S. Gao

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

We present a new version of a shear-wave splitting (SWS) database for the western and central United States (WCUS) using broadband seismic data recorded up to the end of 2014 to update a previous version that used data recorded prior to the end of 2012, when the USArray Transportable Array stations were still recording in the easternmost region of theWCUS. A total of 7452 pairs of additional measurements recorded by 1202 digital broadband seismic stations are obtained, and all the measurements in the previous database are rechecked. The resulting uniform SWS database contains a total of 23,448 pairs of well-defined …

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The Mantle Transition Zone Beneath The Afar Depression And Adjacent Regions: Implications For Mantle Plumes And Hydration, Cory A. Reed, Stephen S. Gao, Kelly H. Liu, Y. Yu Mar 2016

The Mantle Transition Zone Beneath The Afar Depression And Adjacent Regions: Implications For Mantle Plumes And Hydration, Cory A. Reed, Stephen S. Gao, Kelly H. Liu, Y. Yu

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

The Afar Depression and its adjacent areas are underlain by an upper mantle marked by some of the world's largest negative velocity anomalies, which are frequently attributed to the thermal influences of a lower-mantle plume. In spite of numerous studies, however, the existence of a plume beneath the area remains enigmatic, partially due to inadequate quantities of broad-band seismic data and the limited vertical resolution at the mantle transition zone (MTZ) depth of the techniques employed by previous investigations. In this study, we use an unprecedented quantity (over 14 500) of P-to-S receiver functions (RFs) recorded by 139 stations from …

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Feature Knowledge Based Fault Detection Of Induction Motors Through The Analysis Of Stator Current Data, Ting Yang, Haibo Pen, Zhaoxia Wang, Che Sau Chang Mar 2016

Feature Knowledge Based Fault Detection Of Induction Motors Through The Analysis Of Stator Current Data, Ting Yang, Haibo Pen, Zhaoxia Wang, Che Sau Chang

Research Collection School Of Computing and Information Systems

The fault detection of electrical or mechanical anomalies in induction motors has been a challenging problem for researchers over decades to ensure the safety and economic operations of industrial processes. To address this issue, this paper studies the stator current data obtained from inverter-fed laboratory induction motors and investigates the unique signatures of the healthy and faulty motors with the aim of developing knowledge based fault detection method for performing online detection of motor fault problems, such as broken-rotor-bar and bearing faults. Stator current data collected from induction motors were analyzed by leveraging fast Fourier transform (FFT), and the FFT …

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Harmonic Analysis In Integrated Energy System Based On Compressed Sensing, Ting Yang, Haibo Pen, Dan Wang, Zhaoxia Wang Mar 2016

Harmonic Analysis In Integrated Energy System Based On Compressed Sensing, Ting Yang, Haibo Pen, Dan Wang, Zhaoxia Wang

Research Collection School Of Computing and Information Systems

The advent of Integrated Energy Systems enabled various distributed energy to access the system through different power electronic devices. The development of this has made the harmonic environment more complex. It needs low complexity and high precision of harmonic detection and analysis methods to improve power quality. To solve the shortages of large data storage capacities and high complexity of compression in sampling under the Nyquist sampling framework, this research paper presents a harmonic analysis scheme based on compressed sensing theory. The proposed scheme enables the performance of the functions of compressive sampling, signal reconstruction and harmonic detection simultaneously. In …

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Calculated Vibrational States Of Ozone Up To Dissociation, Steve Alexandre Ndengué, Richard Dawes, Xiaogang Wang, Tucker Carrington Jr., Zhigang Sun, Hua Guo Feb 2016

Calculated Vibrational States Of Ozone Up To Dissociation, Steve Alexandre Ndengué, Richard Dawes, Xiaogang Wang, Tucker Carrington Jr., Zhigang Sun, Hua Guo

Chemistry Faculty Research & Creative Works

A new accurate global potential energy surface for the ground electronic state of ozone [R. Dawes et al., J. Chem. Phys. 139, 201103 (2013)] was published fairly recently. The topography near dissociation differs significantly from previous surfaces, without spurious submerged reefs and corresponding van der Waals wells. This has enabled significantly improved descriptions of scattering processes, capturing the negative temperature dependence and large kinetic isotope effects in exchange reaction rates. The exchange reactivity was found to depend on the character of near-threshold resonances and their overlap with reactant and product wavefunctions, which in turn are sensitive to the potential. Here …

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Random Field Disorder At An Absorbing State Transition In One And Two Dimensions, Hatem Barghathi, Thomas Vojta Feb 2016

Random Field Disorder At An Absorbing State Transition In One And Two Dimensions, Hatem Barghathi, Thomas Vojta

Physics Faculty Research & Creative Works

We investigate the behavior of nonequilibrium phase transitions under the influence of disorder that locally breaks the symmetry between two symmetrical macroscopic absorbing states. In equilibrium systems such "random-field" disorder destroys the phase transition in low dimensions by preventing spontaneous symmetry breaking. In contrast, we show here that random-field disorder fails to destroy the nonequilibrium phase transition of the one- and two-dimensional generalized contact process. Instead, it modifies the dynamics in the symmetry-broken phase. Specifically, the dynamics in the one-dimensional case is described by a Sinai walk of the domain walls between two different absorbing states. In the two-dimensional case, …

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Hpcnmf: A High-Performance Toolbox For Non-Negative Matrix Factorization, Karthik Devarajan, Guoli Wang Feb 2016

Hpcnmf: A High-Performance Toolbox For Non-Negative Matrix Factorization, Karthik Devarajan, Guoli Wang

COBRA Preprint Series

Non-negative matrix factorization (NMF) is a widely used machine learning algorithm for dimension reduction of large-scale data. It has found successful applications in a variety of fields such as computational biology, neuroscience, natural language processing, information retrieval, image processing and speech recognition. In bioinformatics, for example, it has been used to extract patterns and profiles from genomic and text-mining data as well as in protein sequence and structure analysis. While the scientific performance of NMF is very promising in dealing with high dimensional data sets and complex data structures, its computational cost is high and sometimes could be critical for …

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Signal Flow Graph Approach To Efficient Dst I-Iv Algorithms, Sirani M. Perera Jan 2016

Signal Flow Graph Approach To Efficient Dst I-Iv Algorithms, Sirani M. Perera

Publications

In this paper, fast and efficient discrete sine transformation (DST) algorithms are presented based on the factorization of sparse, scaled orthogonal, rotation, rotation-reflection, and butterfly matrices. These algorithms are completely recursive and solely based on DST I-IV. The presented algorithms have low arithmetic cost compared to the known fast DST algorithms. Furthermore, the language of signal flow graph representation of digital structures is used to describe these efficient and recursive DST algorithms having (n�1) points signal flow graph for DST-I and n points signal flow graphs for DST II-IV.

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Retrival Of Atmospheric Aerosol Size Distributions Using Stochastic Particle Swarm Optimization, Benjamin D. Nault-Maurer Jan 2016

Retrival Of Atmospheric Aerosol Size Distributions Using Stochastic Particle Swarm Optimization, Benjamin D. Nault-Maurer

All College Thesis Program, 2016-2019

A stochastic particle swarm optimization (SPSO) technique’s robustness is studied in regards to atmospheric aerosol size distribution estimations for a bimodal distribution that focuses on Aitken and accumulation mode aerosols. The SPSO method is used to calculate a set of 11 aerosol optical depth (AOD) values based on a size distribution and match them to an inputted set of AOD values. This method is tested using computer generated AOD values with fixed distribution parameters, generated AOD values with varying distribution parameters, two sets of AOD measurements in clear conditions, and one set of AOD values in hazy conditions. The SPSO …

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