Numerical Analysis and Scientific Computing Commons^™

Exploring Mathematical Strategies For Finding Hidden Features In Multi-Dimensional Big Datasets, Tri Duong, Fang Ren, Apurva Mehta

STAR Program Research Presentations

With advances in technology in brighter sources and larger and faster detectors, the amount of data generated at national user facilities such as SLAC is increasing exponentially. Humans have a superb ability to recognize patterns in complex and noisy data and therefore, data is still curated and analyzed by humans. However, a human brain is unable to keep up with the accelerated pace of data generation, and as a consequence, the rate of new discoveries hasn't kept pace with the rate of data creation. Therefore, new procedures to quickly assess and analyze the data are needed. Machine learning approaches are …

The Web Based Monitoring Project At The Cms Experiment, Juan Antonio Lopez-Perez, Kaori Maeshima, William Badgett, Ulf Behrens, Irakli Chakaberia, Youngkwon Jo, Sho Maruyama, James Patrick, Valdas Rapsevicius, Aron Soha, Mantas Stankevicius, Balys Sulmanas, Sachiko Toda, Zongru Wan

Physics Faculty Research

The Compact Muon Solenoid is a large a complex general purpose experiment at the CERN Large Hadron Collider (LHC), built and maintained by many collaborators from around the world. Efficient operation of the detector requires widespread and timely access to a broad range of monitoring and status information. To the end the Web Based Monitoring (WBM) system was developed to present data to users located anywhere from many underlying heterogeneous sources, from real time messaging systems to relational databases. This system provides the power to combine and correlate data in both graphical and tabular formats of interest to the experimenters, …

Computational Fluid Dynamics Study Of Molten Steel Flow Patterns And Particle-Wall Interactions Inside A Slide-Gate Nozzle By A Hybrid Turbulent Model, Mahdi Mohammadi-Ghaleni, Mohsen Asle Zaeem, Jeffrey D. Smith, Ronald J. O'Malley

Materials Science and Engineering Faculty Research & Creative Works

Melt flow patterns and turbulence inside a slide-gate throttled submerged entry nozzle (SEN) were studied using Detached–Eddy Simulation (DES) model, which is a combination of Reynolds–Averaged Navier–Stokes (RANS) and Large–Eddy Simulation (LES) models. The DES switching criterion between RANS and LES was investigated to closely reproduce the flow structures of low and high turbulence regions similar to RANS and LES simulations, respectively. The melt flow patterns inside the nozzle were determined by k–ε (a RANS model), LES, and DES turbulent models, and convergence studies were performed to ensure reliability of the results. Results showed that the DES model has significant …

A Dual-Porosity-Stokes Model And Finite Element Method For Coupling Dual-Porosity Flow And Free Flow, Jiangyong Hou, Meilan Qiu, Xiaoming He, Chaohua Guo, Mingzhen Wei, Baojun Bai

Mathematics and Statistics Faculty Research & Creative Works

In this paper, we propose and numerically solve a new model considering confined flow in dual-porosity media coupled with free flow in embedded macrofractures and conduits. Such situation arises, for example, for fluid flows in hydraulic fractured tight/shale oil/gas reservoirs. The flow in dual-porosity media, which consists of both matrix and microfractures, is described by a dual-porosity model. And the flow in the macrofractures and conduits is governed by the Stokes equation. Then the two models are coupled through four physically valid interface conditions on the interface between dual-porosity media and macrofractures/conduits, which play a key role in a physically …

Quantum Critical Behavior Of The Superfluid-Mott Glass Transition, Thomas Vojta, Jack Crewse, Martin Puschmann, Daniel Arovas, Yury Kiselev

Physics Faculty Research & Creative Works

We investigate the zero-temperature superfluid to insulator transitions in a diluted two-dimensional quantum rotor model with particle-hole symmetry. We map the Hamiltonian onto a classical (2+1)-dimensional XY model with columnar disorder which we analyze by means of large-scale Monte Carlo simulations. For dilutions below the lattice percolation threshold, the system undergoes a generic superfluid-Mott glass transition. In contrast to other quantum phase transitions in disordered systems, its critical behavior is of conventional power-law type with universal (dilution-independent) critical exponents z=1.52(3), ν =1.16(5), ß/ν =0.48(2), γ/ν=2.52(4), and η = -0.52(4). These values agree with and improve upon earlier Monte Carlo results …

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

Research Collection School Of Computing and 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. …

Inverse Laplace Transform And Post Inversion Formula, Qinmao Zhang

Mathematical Sciences Technical Reports (MSTR)

This paper is dedicated to a general numerical approach to inverse Laplace transforms based on the Post Inversion Formula, which is a theoretical equivalent to the inverse Laplace transform. Though most approaches are too computationally intensive to be of practical use, we introduce an efficient algorithm to compute it based on the Parker-Sochacki method (PSM). This paper also contains some example MATLAB code and algorithm analysis.

Computerized Classification Of Surface Spikes In Three-Dimensional Electron Microscopic Reconstructions Of Viruses, Younes Benkarroum

Dissertations, Theses, and Capstone Projects

The purpose of this research is to develop computer techniques for improved three-dimensional (3D) reconstruction of viruses from electron microscopic images of them and for the subsequent improved classification of the surface spikes in the resulting reconstruction. The broader impact of such work is the following.

Influenza is an infectious disease caused by rapidly-changing viruses that appear seasonally in the human population. New strains of influenza viruses appear every year, with the potential to cause a serious global pandemic. Two kinds of spikes – hemagglutinin (HA) and neuraminidase (NA) – decorate the surface of the virus particles and these proteins …

High-Frequency Instabilities Of Stationary Crossflow Vortices In A Hypersonic Boundary Layer, Fei Li, Meelan Choudhari, Pedro Paredes-Gonzalez, Lian Duan

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Hypersonic boundary layer flows over a circular cone at moderate incidence angle can support strong crossflow instability in between the windward and leeward rays on the plane of symmetry. Due to more efficient excitation of stationary crossflow vortices by surface roughness, such boundary layer flows may transition to turbulence via rapid amplification of the high-frequency secondary instabilities of finite-amplitude stationary crossflow vortices. The amplification characteristics of these secondary instabilities are investigated for crossflow vortices generated by an azimuthally periodic array of roughness elements over a 7° half-angle circular cone in a Mach 6 free stream. The analysis is based on …

Tasker: Behavioral Insights Via Campus-Based Experimental Mobile Crowd-Sourcing, Thivya Kandappu, Nikita Jaiman, Randy Tandriansyah Daratan, Archan Misra, Shih-Fen Cheng, Cen Chen, Hoong Chuin Lau, Deepthi Chander, Koustuv Dasgupta

Research Collection School Of Computing and Information Systems

While mobile crowd-sourcing has become a game-changer for many urban operations, such as last mile logistics and municipal monitoring, we believe that the design of such crowdsourcing strategies must better accommodate the real-world behavioral preferences and characteristics of users. To provide a real-world testbed to study the impact of novel mobile crowd-sourcing strategies, we have designed, developed and experimented with a real-world mobile crowd-tasking platform on the SMU campus, called TA$Ker. We enhanced the TA$Ker platform to support several new features (e.g., task bundling, differential pricing and cheating analytics) and experimentally investigated these features via a two-month deployment of TA$Ker, …

A Reinforcement Learning Framework For Trajectory Prediction Under Uncertainty And Budget Constraint, Truc Viet Le, Siyuan Liu, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

We consider the problem of trajectory prediction, where a trajectory is an ordered sequence of location visits and corresponding timestamps. The problem arises when an agent makes sequential decisions to visit a set of spatial locations of interest. Each location bears a stochastic utility and the agent has a limited budget to spend. Given the agent's observed partial trajectory, our goal is to predict the agent's remaining trajectory. We propose a solution framework to the problem that incorporates both the stochastic utility of each location and the budget constraint. We first cluster the agents into groups of homogeneous behaviors called …

On The Geodesic Centers Of Polygonal Domains, Haitao Wang

Computer Science Faculty and Staff Publications

In this paper, we study the problem of computing Euclidean geodesic centers of a polygonal domain P of n vertices. We give a necessary condition for a point being a geodesic center. We show that there is at most one geodesic center among all points of P that have topologically-equivalent shortest path maps. This implies that the total number of geodesic centers is bounded by the size of the shortest path map equivalence decomposition of P, which is known to be O(n^{10}). One key observation is a pi-range property on shortest path lengths when points are moving. With these observations, …

Bayesian Networks To Assess The Newborn Stool Microbiome, William E. Bennett Jr.

McKelvey School of Engineering Graduate Student Theses & Dissertations

In human stool, a large population of bacterial genes and transcripts from hundreds of genera coexist with host genes and transcripts. Assessments of the metagenome and transcriptome are particularly challenging, since there is a great deal of sequence overlap among related species and related genes. We sequenced the total RNA content from stool samples in a neonate using previously-described methods. We then performed stepwise alignment of different populations of RNA sequence reads to different indices, including ribosomal databases, the human genome, and all sequenced bacterial genomes. Each pool of RNA at each alignment step was subjected to compression to assess …

High Altitude Cosmic Ray Detection, Jordan D. Van Nest

2017 Academic High Altitude Conference

Cosmic rays are high energy atomic nuclei travelling near the speed of light that collide with atoms and molecules in Earth’s upper atmosphere (primarily with nitrogen and oxygen), breaking down into a shower of particles of various energies in the stratosphere. As they travel earthward, these particles continue to break down and lose energy which results in relatively little ionizing radiation reaching the surface. Due to the scattering of cosmic rays, the angle at which the rays enter the atmosphere can affect the number and energies of ionizing particles detected at various altitudes. When using a standard Geiger counter on …

Creating Art Patterns With Math And Code, Boyan Kostadinov

Publications and Research

The goal of this talk is to showcase some visualization projects that we developed for a 3-day Code in R summer program, designed to inspire the creative side of our STEM students by engaging them with computational projects that we developed with the purpose of mixing calculus level math and code to create complex geometric patterns. One of the goals of this program was to attract more minority and female students into applied math and computer science majors.

The projects are designed to be implemented using the high-level, open-source and free computational environment R, a popular software in industry for …

Generalizing The Quantum Dot Lab Towards Arbitrary Shapes And Compositions, Matthew A. Bliss, Prasad Sarangapani, James Fonseca, Gerhard Klimeck

The Summer Undergraduate Research Fellowship (SURF) Symposium

As applications in nanotechnology reach the scale of countable atoms, computer simulation has become a necessity in the understanding of new devices, such as quantum dots. To understand the various optoelectronic properties of these nanoparticles, the Quantum Dot Lab (QDL) has been created and powered by NEMO5 to simulate on multi-scale, multi-physics bases. QDL is easy to use by offering choices of different QD geometries such as shapes and sizes to the users from a predefined menu. The simplicity of use, however, limits the simulation of general QD shapes and compositions. A method to import generic strained crystalline and amorphous …

Analyzing Sports Training Data With Machine Learning Techniques, Rehana Mahfuz, Zeinab Mourad, Aly El Gamal

The Summer Undergraduate Research Fellowship (SURF) Symposium

In the sports industry, there has not been enough effort in analyzing the personalized monitoring data of athletes collected during training sessions. This research is an attempt to find meaningful patterns in the Purdue Women’s Soccer training data that could help the coach design more efficient training sessions. We are specifically interested in studying this problem as an unsupervised learning problem. Our initial attempt is to cluster the players as well as drills into groups using k-means, c-means and spectral clustering algorithms, combined with feature transformation and reduction steps. These basic algorithms serve as a benchmark to measure performance improvements …

Density Functional Theory Based Electrolyte Design Formulation For Lithium-Sulfur Batteries, Cynthia Ly, Carolyn Sturges, Vijay Murugesan

STAR Program Research Presentations

Lithium-ion (Li-ion) batteries are commonly used in portable electronics such as cellphones and laptops. Most Li-ion batteries operate on intercalation principle with typical theoretical specific energy of 400-600 (Wh/Kg). There is great scientific interest in lithium-sulfur (Li-S) batteries as a possible successor of traditional Li-ion batteries because Li-S holds the potential of being a very powerful (1550 Wh/kg theoretical specific energy) yet very cost-efficient battery (due the abundance and inexpensiveness of sulfur). However, one major problem in Li-S battery research is the polysulfide “shuttle phenomenon”, which is the shuttling of polysulfide species due to the dissolution of sulfide from the …

Changes In R, R Core Team

The R Journal

CHANGES IN R 3.3.1 patched

CHANGES IN R 3.3.1

CHANGES IN R 3.3.0

Changes On Cran, Kurt Hornik, Achim Zeileis

The R Journal

In the past 8 months,1322 new packages were added to the CRAN package repository. 43 packages were unarchived,48 archived,1 package had to be removed.The following shows the growth of the number of active packages in the CRAN package repository:

Nonparametric Tests For The Interaction In Two-Way Factorial Designs Using R, Jos Feys

The R Journal

An increasing number of R packages include nonparametric tests for the interaction in two-way factorial designs. This paper briefly describes the different methods of testing and reports the resulting p-values of such tests on datasets for four types of designs: between, within, mixed, and pretest-posttest designs. Potential users are advised only to apply tests they are quite familiar with and not be guided by p-values for selecting packages and tests.

Using Decipher V2.0 To Analyze Big Biological Sequence Data In R, Erik S. Wright

The R Journal

In recent years, the cost of DNA sequencing has decreased at a rate that has outpaced improvements in memory capacity. It is now common to collect or have access to many gigabytes of biological sequences. This has created an urgent need for approaches that analyze sequences in subsets without requiring all of the sequences to be loaded into memory at one time. It has also opened opportunities to improve the organization and accessibility of information acquired in sequencing projects. The DECIPHER package offers solutions to these problems by assisting in the curation of large sets of biological sequences stored in …

Scmamp: Statistical Comparison Of Multiple Algorithms In Multiple Problems, Borja Calvo, Guzmán Santafé

The R Journal

Comparing the results obtained by two or more algorithms in a set of problems is a central task in areas such as machine learning or optimization. Drawing conclusions from these comparisons may require the use of statistical tools such as hypothesis testing. There are some interesting papers that cover this topic. In this manuscript we present scmamp, an R package aimed at being a tool that simplifies the whole process of analyzing the results obtained when comparing algorithms, from loading the data to the production of plots and tables.

Comparing the performance of different algorithms is an essential step …

Swmpr: An R Package For Retrieving, Organizing, And Analyzing Environmental Data For Estuaries, Marcus W. Beck

The R Journal

The System-Wide Monitoring Program (SWMP)was implemented in 1995 by the US National Estuarine Research Reserve System. This program has provided two decades of continuous monitoring data at over 140 fixed stations in 28 estuaries. However, the increasing quantity of data provided by the monitoring network has complicated broad-scale comparisons between systems and, in some cases, prevented simple trend analysis of water quality parameters at individual sites. This article describes the SWMPr package that provides several functions that facilitate data retrieval, organization, and analysis of time series data in the reserve estuaries. Previously unavailable functions for estuaries are also provided to …

Spatio-Temporal Interpolation Using Gstat, Benedikt Gräler, Edzer Pebesma, Gerard Heuvelink

The R Journal

We present new spatio-temporal geostatistical modelling and interpolation capabilities of the R package gstat. Various spatio-temporal covariance models have been implemented, such as the separable, product-sum, metric and sum-metric models. Inareal-world application we comparespatio temporal interpolations using these models with a purely spatial kriging approach. The target variable of the application is the daily mean PM10 concentration measured at rural air quality monitoring stations across Germany in 2005. R code for variogram fitting and interpolation is presented in this paper to illustrate the workflow of spatio-temporal interpolation using gstat. We conclude that the system works properly and that the …

Model Builder For Item Factor Analysis With Openmx, Joshua N. Pritikin, Karen M. Schmidt

The R Journal

We introduce a shiny web application to facilitate the construction of Item Factor Analysis (a.k.a. Item Response Theory) models using the OpenMx package. The web application assists with importing data, outcome recoding, and model specification. However, the app does not conduct any analysis but, rather, generates an analysis script. Generated Rmarkdown output serves dual purposes: to analyze a data set and demonstrate good programming practices. The app can be used as a teaching tool or as a starting point for custom analysis scripts.

Quickpsy: An R Package To Fit Psychometric Functions For Multiple Groups, Daniel Linares, Joan López-Moliner

The R Journal

quickpsy is a package to parametrically fit psychometric functions. In comparison with previous R packages, quickpsy was built to easily fit and plot data for multiple groups. Here, we describe the standard parametric model used to fit psychometric functions and the standard estimation of its parameters using maximum likelihood. We also provide examples of usage of quickpsy, including how allowing the lapse rate to vary can sometimes eliminate the bias in parameter estimation, but not in general. Finally, we describe some implementation details, such as how to avoid the problems associated to round-off errors in the maximisation of the …

Variable Clustering In High-Dimensional Linear Regression: The R Package Clere, Loïc Yengo, Julien Jacques, Christophe Biernacki, Mickael Canouil

The R Journal

Dimension reduction is one of the biggest challenges in high-dimensional regression models. We recently introduced a new methodology based on variable clustering as a means to reduce dimensionality. We present here the R package clere that implements some refinements of this methodology. An overview of the package functionalities as well as examples to run an analysis are described. Numerical experiments on real data were performed to illustrate the good predictive performance of our parsimonious method compared to standard dimension reduction approaches.

Maps, Coordinate Reference Systems And Visualising Geographic Data With Mapmisc, Patrick E. Brown

The R Journal

The mapmisc package provides functions for visualising geospatial data, including fetching background map layers, producing colour scales and legends, and adding scale bars and orientation arrows to plots. Background maps are returned in the coordinate reference system of the dataset supplied, and inset maps and direction arrows reflect the map projection being plotted. This is a “light weight” package having an emphasis on simplicity and ease of use

Editorial, Michael Lawrence

The R Journal

On behalf of the editorial board, I am pleased to publish Volume 8, Issue 1 of the R Journal. This issue contains 27 contributed research articles. Each of them either presents an R package, a specific extension of an R package or applications using R packages available from the Comprehensive R Archive Network (CRAN, http:://CRAN.R-project.org). It thus provides a small but current cross-section of the burgeoning R ecosystem.