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Spatial And Temporal Storm Generation From A Stochastic View, Jiaxiang Ding, Josept D. Revuelta-Acosta, Engel Bernard 2018 Purdue University

Spatial And Temporal Storm Generation From A Stochastic View, Jiaxiang Ding, Josept D. Revuelta-Acosta, Engel Bernard

The Summer Undergraduate Research Fellowship (SURF) Symposium

Precipitation is one of the most important parameters in the study of hydrology and most of the research has been done on daily storm generation. Current weather generation models are used to replicate daily or monthly time resolution, which is not able to show the variability within one day or one month. This project deals with sub-daily storm generation with finer resolution and more accurate estimation, which also requires an independent storm separation method. And the Monte Carlo correlated multivariate simulation is applied to compute the variables. The description is essential for soil erosion and water quality research. Another reason ...


Understanding Suspend/Resume Path Of Linux Device Drivers, Yi Qiao, Xiaozhu Felix Lin 2018 Purdue University

Understanding Suspend/Resume Path Of Linux Device Drivers, Yi Qiao, Xiaozhu Felix Lin

The Summer Undergraduate Research Fellowship (SURF) Symposium

Suspend/Resume (S/R), stands for putting mobile devices into sleep mode and wakes them up. Such a S/R process is heavily used in mobile devices today. While controlling by the operating system (OS), S/R process consumes a dominating portion of energy. In order to minimize the power consumption, we have to understand what happens on the S/R Path of modern device drivers so that further solutions reducing the overhead in that process can be found. In a modern OS, device drivers can make up over 70% of the source code, while still heavily dependent on the ...


New Methods For Understanding And Controlling The Self-Assembly Of Reacting Systems Using Coarse-Grained Molecular Dynamics, Stephen Thomas 2018 Boise State University

New Methods For Understanding And Controlling The Self-Assembly Of Reacting Systems Using Coarse-Grained Molecular Dynamics, Stephen Thomas

Boise State University Theses and Dissertations

This research aims at developing new computational methods to understand the molecular self-assembly of reacting systems whose complex structures depend on the thermodynamics of mixing, reaction kinetics, and diffusion kinetics. The specific reacting system examined in this study is epoxy, cured with linear chain thermoplastic tougheners whose complex microstructure is known from experiments to affect mechanical properties and to be sensitive to processing conditions. Mesoscale simulation techniques have helped to bridge the length and time scales needed to predict the microstructures of cured epoxies, but the prohibitive computational cost of simulating experimentally relevant system sizes has limited their impact. In ...


Single Particle Behavior In Low Reynolds Linear Shear Flow, Nima Fathi, Peter Vorobieff, Seyed Sobhan Aleyasin, Goodarz Ahmadi 2018 University of New Mexico

Single Particle Behavior In Low Reynolds Linear Shear Flow, Nima Fathi, Peter Vorobieff, Seyed Sobhan Aleyasin, Goodarz Ahmadi

Nima Fathi

Horizontal linear shear stress apparatus offers a convenient way to study the rheology of rigid particles suspended in viscous shear flows in the laboratory. The single particle trajectories of a buoyant spherical solid particle in a linear shear flow are investigated. Reynolds numbers less than 0.1 are considered to provide the creeping flow in this investigating. The experimental apparatus provides a linear stress, Stokes, Couette flow where the wall boundary conditions of the set up can change. The two-dimensional CFD analysis is performed to simulate the primary and secondary phases of the domain. Our numerical assessment, discrete phase element ...


Formalizing Schoenberg’S Fundamentals Of Musical Composition Through Petri Nets, A. Baratè, Davide Andrea Mauro, G. Haus, L. A. Ludovico 2018 Marshall University

Formalizing Schoenberg’S Fundamentals Of Musical Composition Through Petri Nets, A. Baratè, Davide Andrea Mauro, G. Haus, L. A. Ludovico

Weisberg Division of Computer Science Faculty Research

The formalization of musical composition rules is a topic

that has been studied for a long time. It can lead to a better

understanding of the underlying processes, and provide a

useful tool for musicologist to aid and speed up the analysis

process. In our attempt we introduce Schoenberg’s

rules from Fundamentals of Musical Composition using a

specialized version of Petri nets, called Music Petri nets.

Petri nets are a formal tool for studying systems that are

concurrent, asynchronous, distributed, parallel, nondeterministic,

and/or stochastic. We present some examples

highlighting how multiple approaches to the analysis task

can find ...


Computer Design Of Microfluidic Mixers For Protein/Rna Folding Studies, Venkatesh Inguva, Sagar V. Kathuria, Osman Bilsel, Blair James Perot 2018 University of Massachusetts Amherst

Computer Design Of Microfluidic Mixers For Protein/Rna Folding Studies, Venkatesh Inguva, Sagar V. Kathuria, Osman Bilsel, Blair James Perot

Open Access Articles

Kinetic studies of biological macromolecules increasingly use microfluidic mixers to initiate and monitor reaction progress. A motivation for using microfluidic mixers is to reduce sample consumption and decrease mixing time to microseconds. Some applications, such as small-angle x-ray scattering, also require large ( > 10 micron) sampling areas to ensure high signal-to-noise ratios and to minimize parasitic scattering. Chaotic to marginally turbulent mixers are well suited for these applications because this class of mixers provides a good middle ground between existing laminar and turbulent mixers. In this study, we model various chaotic to marginally turbulent mixing concepts such as flow turning, flow ...


Effect Of Material Viscoelasticity On Frequency Tuning Of Dielectric Elastomer Membrane Resonators, Liyang Tian 2018 The University of Western Ontario

Effect Of Material Viscoelasticity On Frequency Tuning Of Dielectric Elastomer Membrane Resonators, Liyang Tian

Electronic Thesis and Dissertation Repository

Dielectric elastomers (DEs) capable of large voltage-induced deformation show promise for applications such as resonators and oscillators. However, the dynamic performance of such vibrational devices is not only strongly affected by the nonlinear electromechanical coupling and material hyperelasticity, but also significantly by the material viscoelasticity. The material viscoelasticity of DEs originates from the highly mobile polymer chains that constitute the polymer networks of the DE. Moreover, due to the multiple viscous polymer subnetworks, DEs possess multiple relaxation processes. Therefore, in order to predict the dynamic performance of DE-based devices, a theoretical model that accounts for the multiple relaxation processes is ...


Roborodentia Robot: Treadbot, Stephen C. Schmidt 2018 California Polytechnic State University, San Luis Obispo

Roborodentia Robot: Treadbot, Stephen C. Schmidt

Computer Science

This document is a summary of my contest entry to the 2018 Cal Poly Roborodentia competition. It is meant to be a process overview and design outline of the mechanical, electrical, and software components of my robot.


Jasmint: Language To User-Friendly Ast With Emphasis On Translation, John E. Bradbury 2018 California Polytechnic State University, San Luis Obispo

Jasmint: Language To User-Friendly Ast With Emphasis On Translation, John E. Bradbury

Computer Science

The goal of this project was to create a language (JASMINT) which would be easily transformable into other languages. With this, a library could be built which provides a rich set of functions, including typechecking, interpreting, and serialization, in order to make user modules easy to write. These modules are able to translate this AST into other languages and through the translation blocks can add new functionalities to JASMINT. The final state of the project at submission includes a library which handles all features except dynamic memory, transpilers (JasmintCxxTranspiler and JasmintPythonTranspiler) which handle most features except classes and dynamic memory ...


Artificial Neural Network-Based Robotic Control, Justin Ng 2018 California Polytechnic State University, San Luis Obispo

Artificial Neural Network-Based Robotic Control, Justin Ng

Master's Theses and Project Reports

Artificial neural networks (ANNs) are highly-capable alternatives to traditional problem solving schemes due to their ability to solve non-linear systems with a nonalgorithmic approach. The applications of ANNs range from process control to pattern recognition and, with increasing importance, robotics. This paper demonstrates continuous control of a robot using the deep deterministic policy gradients (DDPG) algorithm, an actor-critic reinforcement learning strategy, originally conceived by Google DeepMind. After training, the robot performs controlled locomotion within an enclosed area. The paper also details the robot design process and explores the challenges of implementation in a real-time system.


Automated Pruning Of Greenhouse Indeterminate Tomato Plants, Joey M. Angeja, Joey M. Angeja 2018 California Polytechnic State University, San Luis Obispo

Automated Pruning Of Greenhouse Indeterminate Tomato Plants, Joey M. Angeja, Joey M. Angeja

Master's Theses and Project Reports

Pruning of indeterminate tomato plants is vital for a profitable yield and it still remains a manual process. There has been research in automated pruning of grapevines, trees, and other plants, but tomato plants have yet to be explored. Wage increases are contributing to the depleting profits of greenhouse tomato farmers. Rises in population are the driving force behind the need for efficient growing techniques. The major contribution of this thesis is a computer vision algorithm for detecting greenhouse tomato pruning points without the use of depth sensors. Given an up-close 2-D image of a tomato stem with the background ...


Vehicle Pseudonym Association Attack Model, Pierson Yieh, Pierson Yieh 2018 California Polytechnic State University, San Luis Obispo

Vehicle Pseudonym Association Attack Model, Pierson Yieh, Pierson Yieh

Master's Theses and Project Reports

With recent advances in technology, Vehicular Ad-hoc Networks (VANETs) have grown in application. One of these areas of application is Vehicle Safety Communication (VSC) technology. VSC technology allows for vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications that enhance vehicle safety and driving experience. However, these newly developing technologies bring with them a concern for the vehicular privacy of drivers. Vehicles already employ the use of pseudonyms, unique identifiers used with signal messages for a limited period of time, to prevent long term tracking. But can attackers still attack vehicular privacy even when vehicles employ a pseudonym change strategy? The major contribution ...


Resource Brokering In Grid Computing, Adrian T. Bienkowski 2018 The University of Western Ontario

Resource Brokering In Grid Computing, Adrian T. Bienkowski

Electronic Thesis and Dissertation Repository

Grid Computing has emerged in the academia and evolved towards the bases of what is currently known as Cloud Computing and Internet of Things (IoT). The vast collection of resources that provide the nature for Grid Computing environment is very complex; multiple administrative domains control access and set policies to the shared computing resources. It is a decentralized environment with geographically distributed computing and storage resources, where each computing resource can be modeled as an autonomous computing entity, yet collectively can work together. This is a class of Cooperative Distributed Systems (CDS). We extend this by applying characteristic of open ...


Modeling Of Swimming Cells From Nano-Scale To Micro-Scale, Yicheng Zhao 2018 Washinton University in St. Louis

Modeling Of Swimming Cells From Nano-Scale To Micro-Scale, Yicheng Zhao

Engineering and Applied Science Theses & Dissertations

Certain human genetic diseases -- primary ciliary dyskinesia, infertility, and hydrocephalus -- are characterized by changes in beat frequency and waveform of cilia and flagella. Chlamydomonas reinhardtii, which is a single-cell green alga about ten micrometers in diameter that swims with two flagella, serves as an excellent biological model because its flagella share the same structure and genetic background as mammalian cilia and flagella. This study uses the finite element method to investigate the behavior of C. reinhardtii swimming from nano-scale to micro-scale. At the device-level, micro-scale modeling indicates that well-designed acoustic microfluidic devices can be used to trap groups of C ...


Why Latent Representations In Convolutional Neural Networks Fall Outside Visual Space, Katerina Malakhova 2018 Pavlov Institute of Physiology of the Russian Academy of Sciences

Why Latent Representations In Convolutional Neural Networks Fall Outside Visual Space, Katerina Malakhova

MODVIS Workshop

It is common to compare properties of visual information processing by artificial neural networks and the primate visual system.

Some remarkable similarities were observed in the responses of neurons in IT cortex and units in higher layers of CNNs. Here I show that latent representations formed by weights in convolutional layers do not necessarily reflect visual domain. Instead they are strongly dependent on a choice of training set and cost function.

The most striking example is when an individual unit, which is highly selective to some members of a category is, nevertheless, inhibited by visually similar objects of the same ...


X-Means Clustering Implementing The Gap Statistic For Multiple Positron Emission Particle Tracking, Matthew Herald 2018 University of Tennessee, Knoxville

X-Means Clustering Implementing The Gap Statistic For Multiple Positron Emission Particle Tracking, Matthew Herald

EURēCA: Exhibition of Undergraduate Research and Creative Achievement

The most efficient and accurate method for clustering Coincidence Lines (CL) for Positron Emission Particle Tracking (PEPT) is undetermined. A number of methods have been created to perform this task. A novel clustering method featuring x-means is presented using an automated k-value estimator for k-means clustering. Gap statistic is used to select the best k-value. Geant4 Application for Tomographic Emission is used to simulate particles of 50 µCi and the detection and electronic chain associated with the Siemens Inveon Pre-Clinical Scanner. The simulation produces an array of coincident lines (CL) in a format consistent with scanner output. The CL are ...


Design Of A Distributed Real-Time E-Health Cyber Ecosystem With Collective Actions: Diagnosis, Dynamic Queueing, And Decision Making, Yanlin Zhou 2018 University of Nebraska - Lincoln

Design Of A Distributed Real-Time E-Health Cyber Ecosystem With Collective Actions: Diagnosis, Dynamic Queueing, And Decision Making, Yanlin Zhou

Theses, Dissertations, and Student Research from Electrical & Computer Engineering

In this thesis, we develop a framework for E-health Cyber Ecosystems, and look into different involved actors. The three interested parties in the ecosystem including patients, doctors, and healthcare providers are discussed in 3 different phases. In Phase 1, machine-learning based modeling and simulation analysis is performed to remotely predict a patient's risk level of having heart diseases in real time. In Phase 2, an online dynamic queueing model is devised to pair doctors with patients having high risk levels (diagnosed in Phase 1) to confirm the risk, and provide help. In Phase 3, a decision making paradigm is ...


Re-Evaluating Performance Measurement: New Mathematical Methods To Address Common Performance Measurement Challenges, Jordan David Benis 2018 Duquesne University

Re-Evaluating Performance Measurement: New Mathematical Methods To Address Common Performance Measurement Challenges, Jordan David Benis

Electronic Theses and Dissertations

Performance Measurement is an essential discipline for any business. Robust and reliable performance metrics for people, processes, and technologies enable a business to identify and address deficiencies to improve performance and profitability. The complexity of modern operating environments presents real challenges to developing equitable and accurate performance metrics. This thesis explores and develops two new methods to address common challenges encountered in businesses across the world. The first method addresses the challenge of estimating the relative complexity of various tasks by utilizing the Pearson Correlation Coefficient to identify potentially over weighted and under weighted tasks. The second method addresses the ...


The 3d Abstract Tile Assembly Model Is Intrinsically Universal, Aaron Koch, Daniel Hader, Matthew J. Patitz 2018 Iowa State University

The 3d Abstract Tile Assembly Model Is Intrinsically Universal, Aaron Koch, Daniel Hader, Matthew J. Patitz

Computer Science and Computer Engineering Undergraduate Honors Theses

In this paper, we prove that the three-dimensional abstract Tile Assembly Model (3DaTAM) is intrinsically universal. This means that there is a universal tile set in the 3DaTAM which can be used to simulate any 3DaTAM system. This result adds to a body of work on the intrinsic universality of models of self-assembly, and is specifically motivated by a result in FOCS 2016 showing that any intrinsically universal tile set for the 2DaTAM requires nondeterminism (i.e. undirectedness) even when simulating directed systems. To prove our result we have not only designed, but also fully implemented what we believe to ...


Multi Self-Adapting Particle Swarm Optimization Algorithm (Msapso)., Gerhard Koch 2018 University of Louisville

Multi Self-Adapting Particle Swarm Optimization Algorithm (Msapso)., Gerhard Koch

Electronic Theses and Dissertations

The performance and stability of the Particle Swarm Optimization algorithm depends on parameters that are typically tuned manually or adapted based on knowledge from empirical parameter studies. Such parameter selection is ineffectual when faced with a broad range of problem types, which often hinders the adoption of PSO to real world problems. This dissertation develops a dynamic self-optimization approach for the respective parameters (inertia weight, social and cognition). The effects of self-adaption for the optimal balance between superior performance (convergence) and the robustness (divergence) of the algorithm with regard to both simple and complex benchmark functions is investigated. This work ...


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