Engineering Commons^™

Reduced-Scale Experiments And Numerical Simulations Of Informal Settlement Dwelling Fires, Vigneshwaran Narayanan, Antonio Cicicone, Ayden D. Botha, Richard Shaun Walls

Progress in Scale Modeling, an International Journal

Informal settlement dwellings (ISDs) house approximately one billion people in the developing world and this number is expected to double by the year 2030. Contemporary research on ISD fires has focused on understanding the fire dynamics within individual dwellings (micro-scale) and fire spread in settlements consisting of multiple dwellings (macro-scale). This paper aims to do two primary things: investigate if scaling methods that were derived for compartments with thermally thick boundaries can be applied to ISDs (compartments with thermally thin boundaries), and if they can adequately represent the most important phenomena associated with full-scale ISD fires; and demonstrate Fire Dynamics …

Container Migration In Ad-Hoc Wireless Mesh Networks, Gagan Gupta, Kyle Fenole, Siddharth Venkatesh

Computer Science and Engineering Senior Theses

This project aims to implement container migration on an ad hoc mesh network, which would allow for a mobile fog computing mesh network in areas with no connectivity. This kind of system would allow for a rapidly deployable and mobile compute cluster that could be used in rural scenarios or situations where existing connectivity infrastructures are out of commission i.e. disaster recovery. We use technologies like Docker, CRIU, and batman-adv to create a mesh compute network that is decentralized, flexible, and consistent. Docker with CRIU facilitates container live migration by checkpointing a container in one network node and restoring that …

Kernel Matrix-Based Heuristic Multiple Kernel Learning, Stanton R. Price, Derek T. Anderson, Timothy C. Havens, Steven R. Price

Michigan Tech Publications, Part 1

Kernel theory is a demonstrated tool that has made its way into nearly all areas of machine learning. However, a serious limitation of kernel methods is knowing which kernel is needed in practice. Multiple kernel learning (MKL) is an attempt to learn a new tailored kernel through the aggregation of a set of valid known kernels. There are generally three approaches to MKL: fixed rules, heuristics, and optimization. Optimization is the most popular; however, a shortcoming of most optimization approaches is that they are tightly coupled with the underlying objective function and overfitting occurs. Herein, we take a different approach …

Velachain: A Decentralized Exchange Built For Cross-Chain Communication, Connor Callahan, Bradley Lostak

Computer Science and Engineering Senior Theses

The blockchain industry is one of the fastest growing industries in the world right now. Billions of dollars of venture capital money is being put to work to innovate in this new space. One of the problems that has plagued the blockchain space since its inception is the lack of interoperability between blockchains. A single blockchain is great at dictating its own state but they rarely contain functionality to communicate with other blockchains. Furthermore, users on these blockchains have limited ways to swap cryptocurrencies from one blockchain to another. For this project, we built a cryptocurrency decentralized exchange built on …

On-Line Process Physics Tests Via Lyapunov-Based Economic Model Predictive Control And Simulation-Based Testing Of Image-Based Process Control, Henrique Oyama, A. F. Leonard, Minhazur Rahman, Govanni Gjonaj, Michael Williamson, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

Next-generation manufacturing involves increasing use of automation and data to enhance process efficiency. An important question for the chemical process industries, as new process systems (e.g., intensified processes) and new data modalities (e.g., images) are integrated with traditional plant automation concepts, will be how to best evaluate alternative strategies for data-driven modeling and synthesizing process data. Two methods which could be used to aid in this are those which aid in testing data-based techniques on-line, and those which enable various data-based techniques to be assessed in simulation. In this work, we discuss two techniques in this domain which can be …

Design And Control Of Modular Soft Robotic Actuators With Architected Structures, Nicholas Pagliocca

Theses and Dissertations

Soft robotic systems composed of highly compliant materials offer unparalleled advantages compared to rigid-body systems in applications such as fragile material handling and human-machine interactions. Often, their motions are prescribed by structural anisotropy and reinforcement materials to directionally limit motion. The continuum motion and non-linear material response intrinsic to soft robotics makes their design, modeling, and control a formidable challenge for engineers. Leveraging the deformation driven response of soft robotic actuators, highly versatile compliant architected structures whose local deformations dictate global material response can be integrated into soft robotic actuators for tunable mechanical responses. In this thesis, flexible center-symmetric perforated …

Mpc-Stanet: Alzheimer’S Disease Recognition Method Based On Multiple Phantom Convolution And Spatial Transformation Attention Mechanism, Yujian Liu, Kun Tang, Weiwei Cai, Aibin Chen, Guoxiong Zhou, Liujun Li, Runmin Liu

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Alzheimer's disease (AD) is a progressive neurodegenerative disease with insidious and irreversible onset. The recognition of the disease stage of AD and the administration of effective interventional treatment are important to slow down and control the progression of the disease. However, due to the unbalanced distribution of the acquired data volume, the problem that the features change inconspicuously in different disease stages of AD, and the scattered and narrow areas of the feature areas (hippocampal region, medial temporal lobe, etc.), the effective recognition of AD remains a critical unmet need. Therefore, we first employ class-balancing operation using data expansion and …

Method And System For Automatic Selection Of One Or More Image Processing Algorithm, Tanushyam Chattopadhyay, Ramu Vempada Reddy, Utpal Garain

Patents

Disclosed is a method and system for automatic algorithm selection for image processing. The invention discloses the method and system for automatically selecting the correct algorithm(s) for a varying requirement of the image for processing. The selection of algorithm is completely automatic and guided by a plurality of machine learning approaches. The system here is configured to pre-process plurality of images for creating a training data. Next, the test image is extracted, pre-processed and matched for assessing the best possible match of algorithm for processing.

Progress On Static Structures In Leaky Mode Waveguides, Manusha Korimi

Theses and Dissertations

Virtual reality (VR) head-mounted displays provide a high definition, immersive experi-ence to the viewer. However, most existing technologies have flaws like bulky design and vergence-accommodation conflict that may cause stress in the neck muscles, posture issues, nausea, motion sickness and dizziness. Similarly, augmented reality (AR) displays, which use transparent light modulators, exist, but they possess low field of view and a limited number of discrete depth planes when wide field of view and continuous depth would be ideal. The ultimate goal of my research is use leaky mode waveguide devices to create wide-view angle, transparent near eye holographic displays for …

Modified Q-Learning Method For Automatic Voltage Regulation In Wide-Area Multigeneration Systems, Brook Abegaz, Sina Zarrabian

Engineering Science Faculty Publications

The state-estimation and optimal control of multigeneration systems are challenging for wide-area systems having numerous distributed automatic voltage regulators (AVR). This paper proposes a modified Q-learning method and algorithm that aim to improve the convergence of the approach and enhance the dynamic response and stability of the terminal voltage of multiple generators in the experimental Western System Coordinating Council (WSCC) and large-scale IEEE 39-bus test systems. The large-scale experimental testbed consists of a six-area, 39-bus system having ten generators that are connected to ten AVRs. The implementation shows promising results in providing stable terminal voltage profiles and other system parameters …

Soft-Mask De-Mixing For Anechoic Mixtures, Swarnadeep Bagchi, Ruairí De Fréin

Articles

This paper extends a computationally efficient, soft-mask based source separation (SS) technique called Redress, to anechoic mixing scenarios. SS methods are an integral part of hearing aid research. We call the resulting method D-Redress. In its original form, Redress was intended for instantaneous mixing scenarios. Numerical evaluations demonstrate that soft-mask based techniques reduce the level of artifacts in the separated speech. Monte Carlo trials on 1000 real speech mixtures demonstrate that the D-Redress successfully extends Redress in terms of Overall-Perceptual (OPS), Target-Perceptual (TPS) scores and Human-Ear Intelligibility (HEI).

Measuring Shuttlecock Drag In Free Flight, Achyut Paudel, Lloyd Smith

International Sports Engineering Association – Engineering of Sport

No abstract provided.

Body-Attached Sensor Nodes For Automatic Detection Of Hike Events And Parameters, Giuseppe Sanseverino, Dominik Krumm, Wolfgang Kilian, Stephan Odenwald

International Sports Engineering Association – Engineering of Sport

No abstract provided.

Variability In Rotational Traction Testing Of Artificial Surfaces., Harry Mcgowan, Paul Fleming, Steph Forrester, David James

International Sports Engineering Association – Engineering of Sport

No abstract provided.

Improvement Of The Training Paddle For A Swimmer With Unilateral Transradial Deficiency, Motomu Nakashima, Yohei Chida

International Sports Engineering Association – Engineering of Sport

No abstract provided.

The Effect Of Pressure And Kick Speed In Soccer On Head Injury And Goalkeeper Movement, Praveen Kumar Sharma, Lloyd Smith

International Sports Engineering Association – Engineering of Sport

No abstract provided.

A Novel Framework For Design-Property Decision-Making In Polymer Lattices When Controlling For Printed Mass, Ana Paula Clares, Guha Manogharan, Landon Thomas, David Krzeminski

International Sports Engineering Association – Engineering of Sport

No abstract provided.

Angular Rate Effect On Stiffness And Damping Characteristics Of Different Head/Neck Assemblies During Cyclic Tests, Marco Rango, Giuseppe Zullo, Leonardo Marin, Andrey Koptyug, Nicola Petrone

International Sports Engineering Association – Engineering of Sport

No abstract provided.

Vibrational Analysis Of A Flexible Bicycle Stem During Indoor In-Vivo Cycling On A Two Rollers Servohydraulic Test Bench, Mattia Scapinello, Enrico Girlanda, Nicola Petrone

International Sports Engineering Association – Engineering of Sport

No abstract provided.

Cycling And Sustainability: Development Of A Recycled Carbon Fiber (Rcf) Crankset Demonstrator, Morgan Chamberlain, Justin Miller, Diana Heflin, Teal Dowd, Jung Soo Rhim, Ilke Akturk, Jacob Coffing, Jan-Anders Mansson

International Sports Engineering Association – Engineering of Sport

No abstract provided.

Homologation And Certification Approach For Smart Bike Trainers, Diana Heflin, Justin Miller, Teal Dowd, Michael Rogers, Jan-Anders Mansson

International Sports Engineering Association – Engineering of Sport

No abstract provided.

Smart Trainer Homologation System, Teal Dowd, Justin Miller, Diana Heflin, Wim Sweldens, Andrei Krasilnikau, Jan-Anders Mansson

International Sports Engineering Association – Engineering of Sport

No abstract provided.

Automatic Summarization Of Cyclocross Races, Jelle De Bock, Steven Verstockt

International Sports Engineering Association – Engineering of Sport

No abstract provided.

Aerodynamical Benefits By Optimizing Cycling Posture, Silas Koehn, Luca Oggiano, Kai Schaffarczyk, Alois Peter Schaffarczyk

International Sports Engineering Association – Engineering of Sport

No abstract provided.

Parameter-Space Mining Of 2018-2020 Tours De France To Model 2021 Tour De France, Noah Baumgartner, John Goff

International Sports Engineering Association – Engineering of Sport

No abstract provided.

Data-Driven Evaluation Of Road Cycling Courses, Steven Verstockt, Jelle De Bock

International Sports Engineering Association – Engineering of Sport

No abstract provided.

Brilliance Bias In Gpt-3, Ashley Troske, Edith Gonzalez, Nicole Lawson

Computer Science and Engineering Senior Theses

Language has a profound impact on how we perceive the world. With GPT- 3’s rise in popularity, present in 300 applications averaging 4.5 billion words per day, it is critical for us as programmers to identify and correct biases in its generations. A variety of biases have been identified in generative language models, spanning biases based on gender, race, and religion. Our project pioneers the study of the Brilliance Bias for generative models. This implicit, yet powerful bias imposes the idea of “brilliance” being a male trait and in turn, sets back women’s achievements starting as young as 5-7 years. …

Database Of Non-Government Organizations On The Global Scale, Jeremy Mekker

Computer Science and Engineering Senior Theses

Currently in the world, there are about 10 million non-profit/non-governmental organizations. In order to find these organizations, one must diligently scour the Internet for hours on end. Most research into helping refugees or those in need results in only finding larger organizations that cover many different tasks in the targeted area. This is an active problem. While larger organizations tend to help a wider audience of people, often the help that one would like to give does not get delivered as urgently as the donor would hope. In order to combat this, the primary objective would be to optimize the …

Neural Network Interpretability For Autonomous Driving Neural Networks, Raghav Kapoor, Casey Nguyen

Computer Science and Engineering Senior Theses

In the field of neural networks, there has been a long-standing problem that needs to be addressed: gaining insight into how neural networks make decisions. Neural Networks are still considered black boxes and are often difficult to understand. This lack of understanding becomes an ethical dilemma especially in the domain of self-driving cars. Given the limited number of works geared towards unravelling neural network logic for autonomous driving vehicles, our team seeks to create a novel neural network interpretability method to influence the neural network during its training process.

Deep Neural Networks have demonstrated impressive performance in complex tasks, such …

Improving Diversity In Journalistic Sources With Computer Vision, Austin Johnson, Carlos Mercado, Sabiq Khan

Computer Science and Engineering Senior Theses

News is a constant part of our lives, and has a significant impact on how we see the world. Simply put, journalistic sources are not diverse enough, and typically are only those in the majority. Newsrooms have made passionate declarations about wanting more diversity in their news sources. Our project aims to help with that. Building on top of the DEI toolkit, we aim to help newsrooms increase the diversity of their sources by analyzing their sources using a google search to pick an image and facial recognition software to determine the gender and race of the image.