Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Engineering (10)
- Computer Sciences (8)
- Environmental Sciences (4)
- Physics (4)
- Applied Mathematics (3)
-
- Electrical and Computer Engineering (3)
- Graphics and Human Computer Interfaces (3)
- Life Sciences (3)
- Numerical Analysis and Computation (3)
- Bioresource and Agricultural Engineering (2)
- Chemistry (2)
- Computational Engineering (2)
- Condensed Matter Physics (2)
- Environmental Monitoring (2)
- Fluid Dynamics (2)
- Medicine and Health Sciences (2)
- Nanoscience and Nanotechnology (2)
- Numerical Analysis and Scientific Computing (2)
- Oceanography and Atmospheric Sciences and Meteorology (2)
- Social and Behavioral Sciences (2)
- Software Engineering (2)
- Statistics and Probability (2)
- Agribusiness (1)
- Agriculture (1)
- Amino Acids, Peptides, and Proteins (1)
- Applied Statistics (1)
- Artificial Intelligence and Robotics (1)
- Astrophysics and Astronomy (1)
- Atomic, Molecular and Optical Physics (1)
- Keyword
-
- Actuators (1)
- Algorithm (1)
- Amorphous (1)
- Bayesian global optimization (1)
- Biosolids-based fertilizers (1)
-
- Bottom Boundary Layer (1)
- Computational electrodynamics (1)
- Concentration Boundary Layer (1)
- Correlated materials (1)
- Data (1)
- Data Science (1)
- Data Visualization (1)
- Degradation (1)
- Eddy covariance (1)
- Emerging contaminants (1)
- Entomology (1)
- Environmental shock (1)
- Expected improvement (1)
- Expected improvement over the dominated hyper-volume (1)
- External gear pump (1)
- Fluid power system (1)
- Fluorescent Imaging (1)
- Forensics (1)
- GDD (1)
- Gaussian process (1)
- Gaussian process regression (1)
- Gene therapy (1)
- Generic structures (1)
- Greenhouse gases (1)
- Haptics (1)
Articles 1 - 20 of 20
Full-Text Articles in Physical Sciences and Mathematics
Multi-Objective Optimization Under Uncertainty Using The Hyper-Volume Expected Improvement, Martin Figura, Piyush Pandita, Rohit K. Tripathy, Ilias Bilionis
Multi-Objective Optimization Under Uncertainty Using The Hyper-Volume Expected Improvement, Martin Figura, Piyush Pandita, Rohit K. Tripathy, Ilias Bilionis
The Summer Undergraduate Research Fellowship (SURF) Symposium
The design of real engineering systems requires the optimization of multiple quantities of interest. In the electric motor design, one wants to maximize the average torque and minimize the torque variation. A study has shown that these attributes vary for different geometries of the rotor teeth. However, simulations of a large number of designs cannot be performed due to their high cost. In many problems, design optimization of multi-objective functions is a very challenging task due to the difficulty to evaluate the expectation of the objectives. Current multi-objective optimization (MOO) techniques, e.g., evolutionary algorithms cannot solve such problems because they …
Persistence Of Trace Organic Contaminants From A Commercial Biosolids-Based Fertilizer In Aerobic Soils, Travis A. Banet, Jihyun R. Kim, Michael L. Mashtare
Persistence Of Trace Organic Contaminants From A Commercial Biosolids-Based Fertilizer In Aerobic Soils, Travis A. Banet, Jihyun R. Kim, Michael L. Mashtare
The Summer Undergraduate Research Fellowship (SURF) Symposium
Municipal biosolids are recycled as agricultural fertilizers. Recent studies have raised concerns due to the presence of emerging contaminants in municipal biosolids. Previous research suggests that these contaminants have the potential to reside in biosolids-based fertilizers that are commercially distributed. Use of these products in urban/suburban areas may provide a pathway for these contaminants to enter ecosystems and impact human and environmental health. Soils from Purdue University’s community garden and MiracleGro Potting Mix were chosen to represent commonly used urban/suburban growth media. Triclosan, triclocarban, and methyl parabens were selected as compounds of interest for this study. A heat treated commercial …
Experimental Testing And Validation Of P-Band Bi-Static Remote Sensing Of Soil Moisture In 137-138mhz Range, Xiangyu Qu, Yao-Cheng Lin, James L. Garrison
Experimental Testing And Validation Of P-Band Bi-Static Remote Sensing Of Soil Moisture In 137-138mhz Range, Xiangyu Qu, Yao-Cheng Lin, James L. Garrison
The Summer Undergraduate Research Fellowship (SURF) Symposium
Remote sensing using readily available communication signal transmitted by ORBCOMM satellites at very high frequency (VHF) range (137-138MHz) is a promising method for detecting the root zone soil moisture content. The radio wave reflectivity of soil is strongly correlated to soil moisture content. Therefore, if we were able to measure the reflectivity, we might be able to estimate the soil moisture content. In this preliminary study, we analyze direct signal data from the satellites to investigate and verify communication channels in frequency range of interest and their characteristics (bandwidth, pattern, etc.). The analysis of direct signal data is also used …
Exploring Regional And Telecoupled Land Use Change Impacts From Environmental Shocks, Kevin Hill, Liz Wachs, Brady Hardiman, David Yu, Shweta Singh
Exploring Regional And Telecoupled Land Use Change Impacts From Environmental Shocks, Kevin Hill, Liz Wachs, Brady Hardiman, David Yu, Shweta Singh
The Summer Undergraduate Research Fellowship (SURF) Symposium
Natural disasters or environmental shocks have the potential to disrupt local agricultural systems as well as distant agricultural systems through cascading effects. In this work we selected two distinct environmental shocks and traced their cascading effects on land use change. Quantifying cascading effects is a salient issue because climate change forecasts indicate an increase in frequency and intensity of global environmental shocks. This study incorporated the concept of telecoupled systems involving interrelating ecological, economic and political/social components. A telecoupled framework involving cascading effects was implemented using three approaches. The first approach involved using bilateral agricultural trade matrix data to analyze …
Ifly: Code Development For An App To Support Automating Entomological Data Collection, Michael P. Cosentino, Trevor Stamper
Ifly: Code Development For An App To Support Automating Entomological Data Collection, Michael P. Cosentino, Trevor Stamper
The Summer Undergraduate Research Fellowship (SURF) Symposium
We are developing a prototype entomological data-collection application called "iFly," which runs on a field-capable iPad device. In this phase, we tackled refining screens and introducing a database manager to streamline operations as info is entered, stored, retrieved and delivered. We used SQLite3 database in Apple's Xcode Integrated Development Environment (IDE). Xcode gives mixed programming results. Apple's iOS environment ensures functional and fairly error-free apps can be built. But the sophisticated Xcode IDE requires specialist developers and valuable project time is spent as new programmers learn key techniques. The iFly prototype was advanced with improved database integration; however, more work …
Particle Swarm Transport In Porous Media, Alison R. Hoe, Laura J Pyrak-Nolte
Particle Swarm Transport In Porous Media, Alison R. Hoe, Laura J Pyrak-Nolte
The Summer Undergraduate Research Fellowship (SURF) Symposium
In recent years, interest in particulate transport in the subsurface has increased with the increased use of micro-particulates in consumer products. In this research, we study particulate swarm transport through porous media that depends on the complexity of the flow paths, on the size and shape of the particles and on the physical interactions among the particles, fluids, and matrix. Specifically, we investigate the effect of pore geometry and grain wettability on swarm evolution under gravity. Swarms were composed of 3 micron polystyrene beads in either water or water with KCL (%). Two types of grains are used to simulate …
Photonicstd-2d: Modeling Light Scattering In Periodic Multilayer Photonic Structures, Alexey Bondarev, Shaimaa Azzam, Zhaxylyk Kudyshev, Alexander V. Kildishev
Photonicstd-2d: Modeling Light Scattering In Periodic Multilayer Photonic Structures, Alexey Bondarev, Shaimaa Azzam, Zhaxylyk Kudyshev, Alexander V. Kildishev
The Summer Undergraduate Research Fellowship (SURF) Symposium
Efficient modeling of electromagnetic processes in optical and plasmonic metamaterials is important for enabling new and exciting ways to manipulate light for advanced applications. In this work, we put together a tool for numerical simulation of propagation of normally incident light through a nanostructured multilayer composite material. The user builds a unit cell of a given material layer-by-layer starting from a substrate up to a superstrate, splitting each layer further into segments. The segments are defined by width and material -- dielectric, metal or active medium. Simulations are performed with the finite difference time domain (FDTD) method. A database of …
Design Optimization Of A Stochastic Multi-Objective Problem: Gaussian Process Regressions For Objective Surrogates, Juan Sebastian Martinez, Piyush Pandita, Rohit K. Tripathy, Ilias Bilionis
Design Optimization Of A Stochastic Multi-Objective Problem: Gaussian Process Regressions For Objective Surrogates, Juan Sebastian Martinez, Piyush Pandita, Rohit K. Tripathy, Ilias Bilionis
The Summer Undergraduate Research Fellowship (SURF) Symposium
Multi-objective optimization (MOO) problems arise frequently in science and engineering situations. In an optimization problem, we want to find the set of input parameters that generate the set of optimal outputs, mathematically known as the Pareto frontier (PF). Solving the MOO problem is a challenge since expensive experiments can be performed only a constrained number of times and there is a limited set of data to work with, e.g. a roll-to-roll microwave plasma chemical vapor deposition (MPCVD) reactor for manufacturing high quality graphene. State-of-the-art techniques, e.g. evolutionary algorithms; particle swarm optimization, require a large amount of observations and do not …
The Turning-Off Of Supernova Remnants: The Transition Into The Radiative Phase, Ryan A. Lazur, Rodolfo Barniol Duran, Dimitrios Giannios
The Turning-Off Of Supernova Remnants: The Transition Into The Radiative Phase, Ryan A. Lazur, Rodolfo Barniol Duran, Dimitrios Giannios
The Summer Undergraduate Research Fellowship (SURF) Symposium
Supernovae are amongst the most energetic events in the Universe. Understanding the different stages of the life of a supernova is currently one of the main objectives in astrophysics. During a supernova explosion, material with mass several times that of the Sun is ejected with a speed about 1/10 that of light. In current models, the transition from the Sedov-Taylor to the radiative phase is assumed to be almost instantaneous, which is not entirely accurate. Here the physics of the transition to the radiative phase will be revisited. Observations indicate that the supernova ejecta remains bright in the radio band …
Passive Visual Analytics Of Social Media Data For Detection Of Unusual Events, Kush Rustagi, Junghoon Chae
Passive Visual Analytics Of Social Media Data For Detection Of Unusual Events, Kush Rustagi, Junghoon Chae
The Summer Undergraduate Research Fellowship (SURF) Symposium
Now that social media sites have gained substantial traction, huge amounts of un-analyzed valuable data are being generated. Posts containing images and text have spatiotemporal data attached as well, having immense value for increasing situational awareness of local events, providing insights for investigations and understanding the extent of incidents, their severity, and consequences, as well as their time-evolving nature. However, the large volume of unstructured social media data hinders exploration and examination. To analyze such social media data, the S.M.A.R.T system provides the analyst with an interactive visual spatiotemporal analysis and spatial decision support environment that assists in evacuation planning …
Classifying Pattern Formation In Materials Via Machine Learning, Lukasz Burzawa, Shuo Liu, Erica W. Carlson
Classifying Pattern Formation In Materials Via Machine Learning, Lukasz Burzawa, Shuo Liu, Erica W. Carlson
The Summer Undergraduate Research Fellowship (SURF) Symposium
Scanning probe experiments such as scanning tunneling microscopy (STM) and atomic force microscopy (AFM) on strongly correlated materials often reveal complex pattern formation that occurs on multiple length scales. We have shown in two disparate correlated materials that the pattern formation is driven by proximity to a disorder-driven critical point. We developed new analysis concepts and techniques that relate the observed pattern formation to critical exponents by analyzing the geometry and statistics of clusters observed in these experiments and converting that information into critical exponents. Machine learning algorithms can be helpful correlating data from scanning probe experiments to theoretical models …
Haptic Foot Feedback For Kicking Training In Virtual Reality, Hank Huang, Hong Tan
Haptic Foot Feedback For Kicking Training In Virtual Reality, Hank Huang, Hong Tan
The Summer Undergraduate Research Fellowship (SURF) Symposium
As means to further supplement athletic performances increases, virtual reality is becoming helpful to sports in terms of cognitive training such as reaction, mentality, and game strategies. With the aid of haptic feedback, interaction with virtual objects increases by another dimension, in addition to the presence of visual and auditory feedback. This research presents an integrated system of a virtual reality environment, motion tracking system, and a haptic unit designed for the dorsal foot. The prototype simulates a scenario of virtual kicking and returns haptic response upon collision between the user’s foot and virtual object. The overall system was evaluated …
Analyzing Sports Training Data With Machine Learning Techniques, Rehana Mahfuz, Zeinab Mourad, Aly El Gamal
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 …
Assembly Of Nucleic Acid-Based Nanoparticles By Gas-Liquid Segmented Flow Microfluidics, Matthew L. Capek, Ross Verheul, David H. Thompson
Assembly Of Nucleic Acid-Based Nanoparticles By Gas-Liquid Segmented Flow Microfluidics, Matthew L. Capek, Ross Verheul, David H. Thompson
The Summer Undergraduate Research Fellowship (SURF) Symposium
The development of novel and efficient mixing methods is important for optimizing the efficiency of many biological and chemical processes. Tuning the physical and performance properties of nucleic acid-based nanoparticles is one such example known to be strongly affected by mixing efficiency. The characteristics of DNA nanoparticles (such as size, polydispersity, ζ-potential, and gel shift) are important to ensure their therapeutic potency, and new methods to optimize these characteristics are of significant importance to achieve the highest efficacy. In the present study, a simple segmented flow microfluidics system has been developed to augment mixing of pDNA/bPEI nanoparticles. This DNA and …
Generalizing The Quantum Dot Lab Towards Arbitrary Shapes And Compositions, Matthew A. Bliss, Prasad Sarangapani, James Fonseca, Gerhard Klimeck
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 …
Comparing Carbon Dioxide And Water Vapor Fluxes From Tilled And Non-Tilled Maize Canopy Fields, Heather Sussman, Richard Grant
Comparing Carbon Dioxide And Water Vapor Fluxes From Tilled And Non-Tilled Maize Canopy Fields, Heather Sussman, Richard Grant
The Summer Undergraduate Research Fellowship (SURF) Symposium
Agricultural activities account for approximately 25% of worldwide greenhouse gas emissions. Farm management practices, such as tillage and no-tillage, may contribute more to this percentage than others. The two most abundant greenhouse gases responsible for climate change are CO2 and H2O, therefore it is important to determine whether tillage or no-tillage emits less of these gases. Fluxes of CO2 and H2O from two maize canopy fields, one with tillage and one with no-tillage, were measured in Indiana during the 2016 growing season. This study utilized the eddy covariance method, which represents flux as a …
Velocity Profiling, Turbulence, And Chlorophyll Concentrations In The Bottom Boundary Layer Of Lake Michigan Near Muskegon, Michigan, Jonathan M. Benoit, Cary D. Troy, David J. Cannon
Velocity Profiling, Turbulence, And Chlorophyll Concentrations In The Bottom Boundary Layer Of Lake Michigan Near Muskegon, Michigan, Jonathan M. Benoit, Cary D. Troy, David J. Cannon
The Summer Undergraduate Research Fellowship (SURF) Symposium
The characterization of water flow and turbulence near lake beds is important for modelling environmental and ecological effects throughout a lake. In Lake Michigan, where invasive filter-feeding Quagga mussels dominate the lake bed, turbulence plays an important role in determining how much of chlorophyll is mixed down to the Quagga Mussels. Deep in Lake Michigan (44m) near Muskegon, MI, a large tripod was deployed, attached with an Acoustic Doppler Velocimeter, a fluorometer to measure chlorophyll concentrations, and a temperature sensor. Measurements were recorded from late May until early August by sampling velocities every hour in ten-minute bursts at 4 Hz, …
A Fast Model For The Simulation Of External Gear Pumps, Zechao Lu, Xinran Zhao, Andrea Vacca
A Fast Model For The Simulation Of External Gear Pumps, Zechao Lu, Xinran Zhao, Andrea Vacca
The Summer Undergraduate Research Fellowship (SURF) Symposium
External gear pump is an important category of positive displacement fluid machines used to perform the mechanical–hydraulic energy conversions in many fluid power applications. An efficient numerical simulation program is needed to simulate the system in order to provide a direction for design purpose. The model consists of a lumped parameter fluid dynamic model and a model that simulates the radial micro-motions of the gear’s axes of rotation. The system consists of a set of ordinary differential equations related to the conservation on mass of the internal control volumes of the pump, which are given by the tooth space volumes …
Stochastic Multiple Gradient Decent For Inferring Action-Based Network Generators, Qian Wu, Viplove Arora, Mario Ventresca
Stochastic Multiple Gradient Decent For Inferring Action-Based Network Generators, Qian Wu, Viplove Arora, Mario Ventresca
The Summer Undergraduate Research Fellowship (SURF) Symposium
Networked systems, like the internet, social networks etc., have in recent years attracted the attention of researchers, specifically to develop models that can help us understand or predict the behavior of these systems. A way of achieving this is through network generators, which are algorithms that can synthesize networks with statistically similar properties to a given target network. Action-based Network Generators (ABNG)is one of these algorithms that defines actions as strategies for nodes to form connections with other nodes, hence generating networks. ABNG is parametrized using an action matrix that assigns an empirical probability distribution to vertices for choosing specific …
Gdd(Growth Degree Day) Module For Vinsense Visual Analytics System, Pradeep K. Lam, David Ebert , Phd, Jiawei Zhang
Gdd(Growth Degree Day) Module For Vinsense Visual Analytics System, Pradeep K. Lam, David Ebert , Phd, Jiawei Zhang
The Summer Undergraduate Research Fellowship (SURF) Symposium
Limited resources and increasing costs require vineyards to develop optimized methods of planting, growing, and harvesting crops in order to ensure max yield and stay competitive in the marketplace. Data from sensors planted within the soil paired with weather reports and observation data from farmers could help develop competitive farming strategies. While automatic computation models are usually a black box that cannot explain how the input data are transformed into output, the farmers require an approach that allows them to interactively manipulate and supervise the computation process. The VinSense project was developed for this purpose. In this paper, we focus …