Carnegie Mellon University
Liberty University
Singapore Management University
Fractal Analysis Of Dna Sequences,
2016
Universidad del Valle - Colombia - Georgia Institute of Technology
Fractal Analysis Of Dna Sequences, Christian G. Arias, Pedro Antonio Moreno Phd, Carlos Tellez
Annual Symposium on Biomathematics and Ecology: Education and Research
No abstract provided.
An Environmental Impact Evaluation Model Generated By Compound Probability Distributions,
2016
University of Illinois Urbana-Champaign
An Environmental Impact Evaluation Model Generated By Compound Probability Distributions, Devin Akman, Olcay Akman
Annual Symposium on Biomathematics and Ecology: Education and Research
No abstract provided.
Teaching Systems Biology Of The Circadian Clock With Journal Articles And Matlab,
2016
Colby College
Teaching Systems Biology Of The Circadian Clock With Journal Articles And Matlab, Stephanie R. Taylor
Annual Symposium on Biomathematics and Ecology: Education and Research
No abstract provided.
Neural Networks: Using Biomarkers To Inform Diagnosis, Classification Of Disease And Approach To Therapy,
2016
Shenandoah University
Neural Networks: Using Biomarkers To Inform Diagnosis, Classification Of Disease And Approach To Therapy, Paula Grajdeanu
Annual Symposium on Biomathematics and Ecology: Education and Research
No abstract provided.
Computerized Classification Of Surface Spikes In Three-Dimensional Electron Microscopic Reconstructions Of Viruses,
2016
The Graduate Center, City University of New York
Computerized Classification Of Surface Spikes In Three-Dimensional Electron Microscopic Reconstructions Of Viruses, Younes Benkarroum
All Graduate Works by Year: 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 are primarily ...
Bayesian Networks To Assess The Newborn Stool Microbiome,
2016
Washington University in St. Louis
Bayesian Networks To Assess The Newborn Stool Microbiome, William E. Bennett Jr.
Engineering and Applied Science 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,
2016
Trevecca Nazarene University
High Altitude Cosmic Ray Detection, Jordan D. Van Nest
2016 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 ...
Creating Art Patterns With Math And Code,
2016
CUNY New York City College of Technology
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,
2016
Purdue University
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,
2016
Purdue University
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 ...
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.
Density Functional Theory Based Electrolyte Design Formulation For Lithium-Sulfur Batteries,
2016
Richland School District 400
Density Functional Theory Based Electrolyte Design Formulation For Lithium-Sulfur Batteries, Cynthia Ly, Carolyn Sturges, Vijay Murugesan
STAR (STEM Teacher and Researcher) Program Posters
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 ...
Spica: Stereographic Projection For Interactive Crystallographic Analysis,
2016
University of Nebraska-Lincoln
Spica: Stereographic Projection For Interactive Crystallographic Analysis, X. Z. (Xingzhong) Li
Faculty Publications from Nebraska Center for Materials and Nanoscience
In numerous research fields, especially the applications of electron and X-ray diffraction, stereographic projection represents a powerful tool for researchers. SPICA is a new computer program for stereographic projection in interactive crystallographic analysis, which inherits features from the previous JECP/SP and includes more functions for extensive crystallographic analysis. SPICA provides fully interactive options for users to plot stereograms of crystal directions and crystal planes, traces, and Kikuchi maps for an arbitrary crystal structure; it can be used to explore the orientation relationships between two crystalline phases with a composite stereogram; it is also used to predict the tilt angles ...
Energy Consumption Prediction With Big Data: Balancing Prediction Accuracy And Computational Resources,
2016
Western University
Energy Consumption Prediction With Big Data: Balancing Prediction Accuracy And Computational Resources, Katarina Grolinger, Miriam Am Capretz, Luke Seewald
Electrical and Computer Engineering Publications
In recent years, advances in sensor technologies and expansion of smart meters have resulted in massive growth of energy data sets. These Big Data have created new opportunities for energy prediction, but at the same time, they impose new challenges for traditional technologies. On the other hand, new approaches for handling and processing these Big Data have emerged, such as MapReduce, Spark, Storm, and Oxdata H2O. This paper explores how findings from machine learning with Big Data can benefit energy consumption prediction. An approach based on local learning with support vector regression (SVR) is presented. Although local learning itself is ...
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 ...
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 ...
Experimental Building Demonstration Model With Viscous Fluid Dampers,
2016
California Polytechnic State University, San Luis Obispo
Experimental Building Demonstration Model With Viscous Fluid Dampers, Blake Thomas Reeve, Brianna Jean Kufa, Aden Malek Stepanians, Sophie Carmion Ratkovich
Architectural Engineering
The Architectural Engineering major places a heavy emphasis on structural dynamics and the role of wind and seismic loading in building analysis and design. Buildings of high importance that are critical to community function, such as hospitals, often utilize supplemental damping devices like supplemental viscous fluid dampers or base isolators to reduce the overall demands on the structural system. The design and analysis of these dampers are typically not taught at the undergraduate level, and is frequently performed by mechanical engineers, in lieu of structural engineers.
To better understand and research building behavior with supplemental damping devices, our multi-disciplinary team ...
Contributing To Astropy: A Community Python Library For Astronomers,
2016
Macalester College
Contributing To Astropy: A Community Python Library For Astronomers, Asra Nizami
Macalester Journal of Physics and Astronomy
This paper discusses the author’s contributions to two packages affiliated with Astropy, a community Python library for astronomers. The packages the author contributed to were modeling, a sub-package within the core Astropy package, and WCSAxes, an Astropy affiliated package, outside the core package.
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 ...
Hill's Diagrammatic Method And Reduced Graph Powers,
2016
The College of William & Mary
Hill's Diagrammatic Method And Reduced Graph Powers, Gregory D. Smith, Richard Hammack
Biology and Medicine Through Mathematics Conference
No abstract provided.
