Engineering Commons^™

Exploring The Impact Of Competition And Incentives On Game Jam Participation And Behaviour, John Healy, Niamh Germaine

Conference papers

Competitive elements are a common feature of many game jams. However, there has been little research to date on the impact of competition on participants and their behaviours. To better understand how incentives and competition may affect the motivations and behaviour of game jam participants, we surveyed 47 game jam participants and analysed data from 4,564 online game jams. We found that incentives and competition were neither strong deterrents nor significant motivators for game jam participation. However, a significant percentage of the participants surveyed indicated that incentives and competition would affect their behaviour during a game jam. Our findings suggest …

Graph-Based Mutations For Music Generation, Maziar Kanani, Sean O'Leary, James Mcdermott

Conference papers

Our study aims to compare the effects of direct mutation and graphbased mutation on representations of music domain. We focus on short tunes from the Irish folk tradition, represented as integer sequences, and use a graph-based representation based on Pathway Assembly (a directed acyclic graph) and the Sequitur algorithm. We define multiple mutation operators to work directly on the sequences or on the graphs, hypothesizing that graph-based mutations will tend to preserve the pattern used per tune, while direct mutation of sequences will tend to destroy patterns, resulting in new generated tunes that are more complex. We perform experiments on …

Synthetic Heart Sound Dataset, Davoud Shariat Panah, Andrew Hines, Susan Mckeever

Datasets

The repository contains synthetic heart sound recordings. The publication related to this dataset is "Exploring the impact of noise and degradations on heart sound classification models", Biomedical Signal Processing and Control journal.

Hdd Dataset: Optimising Retrofitted Insulation For Irish Residential Building Walls, Rakshit D. Muddu, Aimee Byrne, Anthony James Robinson

Datasets

In this study, a thermal-economic analysis was conducted to determine the optimum insulation thickness of retrofitted insulation walls in different regions in Ireland. This was based on the Heating Degree Day method (HDD). This dataset contains optimum insulation thickness, payback period, cost savings and carbon emission for all 25 counties in the Republic of Ireland

Co-Design Of An Interactive Wellness Park: Exploring Design Requirements For A Multimodal Outdoor Physical Web Installation With Older Adults, Fatima Badmos

Academic Posters Collection

The global demographic landscape is experiencing a notable shift, characterised by a growing proportion of adults over 60. According to projections, the proportion of individuals aged 60 and above is expected to reach one-sixth of the global population by 2030. Furthermore, by 2050, this demographic is projected to exceed a staggering two billion people. Amidst this shift, there is an urgent need to develop interactive and innovative solutions to address older adults' unique challenges, particularly in outdoor physical activity.

A co-design methodology involving older adults’ participation from the idea generation to the application development process will be adopted to address …

Remote Sensing Approach For Terramechanics Applications Utilizing Machine And Deep Learning, Jordan J. Ewing

Dissertations, Master's Theses and Master's Reports

Terrain traversability is critical for developing Go/No Go maps, significantly impacting a mission's success. To predict the mobility of a vehicle over a terrain, one must understand the soil characteristics. In situ measurements performed by soldiers in the field are the current method of collecting this information, which is time-consuming, are only point measurements, and can put soldiers in harm's way. Therefore, this study investigates using remote sensing as an alternative approach to characterize terrain properties.

This approach will explore the relationships between electromagnetic radiation and soil types with varying properties. Optical, thermal, and hyperspectral sensors will be used to …

Dynamic Mode Decomposition Approach For Estimating The Shape Of A Cable, Yash Manik Chavan

Dissertations, Master's Theses and Master's Reports

This study investigates the dynamic behavior of a flexible cable with heterogeneous stiffness using a data-driven approach. The study aims to develop accurate models describing intricate structures with rigid or flexible components. To achieve this, reflective markers were attached to the cable at equal spacing, and the motion was manually excited and captured using an 8-camera setup and OptiTrack's Motive software.

The cable displacement data at the marker locations were used as initial conditions for various Dynamic Mode Decomposition (DMD) models. The performance of the data- driven cable model is compared against the performance of the DMD modeling approach, fitting …

Study Of Nanocomposite Materials Using Molecular Dynamics, Prashik Sunil Gaikwad

Dissertations, Master's Theses and Master's Reports

There is an increase in demand for new lightweight structural materials in the aerospace industry for more efficient and affordable human space travel. Polymer matrix composites (PMCs) with reinforcement material as carbon nanotubes (CNTs) have shown exceptional increase in the mechanical properties. Flattened carbon nanotubes (flCNTs) are a primary component of many carbon nanotube (CNT) yarn and sheet materials, which are promising reinforcements for the next generation of ultra-strong composites for aerospace applications. These flCNT/polymer materials are subjected to extreme pressure and temperature during curing process. Therefore there is a need to investigate the evolution of properties during the curing …

Treating Contaminated Water: Predicting Reactivities Of Aqueous Organic Contaminants With Hydrated Electrons, And Development Of A Biogarden To Manage Greywater Discharge In Monteverde, Costa Rica, Rose C. Daily

Dissertations, Master's Theses and Master's Reports

Advanced reduction processes (ARPs) that generate highly reactive solvated electrons (e^-_aq) are a promising method for the destruction of conventional and emerging aqueous organic contaminants. While there is a large database of contaminant reactivity with e^-_aq in the literature, there is little information on the detailed elementary mechanisms for reduction of multifunctional group compounds and the impact of those functional groups on reactivity. As it is difficult to determine specific mechanisms through experiments and time consuming to measure reactivity, the development of computational approaches to elucidate mechanisms and predict reactivity is becoming increasingly important. In …

Machine Learning And Deep Learning Approaches For Gene Regulatory Network Inference In Plant Species, Sai Teja Mummadi

Dissertations, Master's Theses and Master's Reports

The construction of gene regulatory networks (GRNs) is vital for understanding the regulation of metabolic pathways, biological processes, and complex traits during plant growth and responses to environmental cues and stresses. The increasing availability of public databases has facilitated the development of numerous methods for inferring gene regulatory relationships between transcription factors and their targets. However, there is limited research on supervised learning techniques that utilize available regulatory relationships of plant species in public databases.

This study investigates the potential of machine learning (ML), deep learning (DL), and hybrid approaches for constructing GRNs in plant species, specifically Arabidopsis thaliana, …

Collagen V Promotes Fibroblast Contractility, And Adhesion Formation, And Stability, Shaina P. Royer-Weeden

Dissertations, Master's Theses and Master's Reports

Ehlers-Danlos syndrome, classical type, (cEDS) is a hereditary connective tissue disorder causing excessive elasticity and fragility of the connective tissue and problems with wound healing. Most cases of cEDS are caused by haploinsufficiency for collagen V. Collagen V regulates collagen fibril diameter. In cEDS fibroblast migration is impaired and integrin expression is altered.

The effects of collagen V on collagen gel ultrastructure and how it alters its mechanical properties were measured using scanning electron microscopy (SEM) and rheology respectively. Fibroblast contractility and adhesion dynamics were investigated to better understand the role of fibroblast disfunction in wound healing in cEDS. To …

Wavelet-Based Real-Time Harmonic Phasor Estimation In Complex Signals With Inter-Harmonics And Transient Events, M A Aziz Jahan

Dissertations, Master's Theses and Master's Reports

Addressing the evolving challenges in modern power systems induced by the integration of Inverter Based Resources (IBRs), such as solar inverters, wind turbine converters, electric vehicle charging stations etc is the main goal of this research. The study focuses on the critical task of harmonic phasor estimation in the presence of sub-harmonics, inter-harmonics, time-varying harmonics, DC offset, transient events, and other power quality disturbances. A novel wavelet-based harmonic phasor estimation method is proposed to enhance accuracy, particularly during transient events, ensuring a nuanced understanding of phase angle variations. The research emphasizes the versatility of wavelet analysis for both steady-state and …

Advancing Vehicular Communication Systems: An Evolution From Dsrc To 5g Nr C-V2x Technology For Enhanced Safety, Reliability, And Efficiency In Intelligent Transportation Systems, Mehnaz Tabassum

Dissertations, Master's Theses and Master's Reports

This work focuses on the evolution of connected vehicles communication technologies and performance evaluation of vehicular communication systems, specifically in the context of Cellular Vehicle-to-Everything (C-V2X) technology and the Third Generation Partnership Project (3GPP) specifications. The dissertation also discusses the evolution of vehicle communication systems from Dedicated Short-Range Communication (DSRC) through 5G technologies. It examines the motivation for this shift, which are the growing demand for transportation safety, low latency, high data rate, low energy use, and seamless inter connectivity. The research delves into the greater capabilities and improved performance that 5G offers for direct V2V communications by analyzing the …

Development And Verification Of Automated Fixtures For Functional Testing Of Space Grade Printed Circuit Board Assemblies, Nicholas A. Wylie

Dissertations, Master's Theses and Master's Reports

Orbion Space Technology is a developer and manufacturer of electric propulsion systems for military and commercial spacecraft. Orbion’s products include a Power Processing Unit (PPU) which is utilized for power and control of the satellite propulsion system. These PPUs are complex electro-mechanical assemblies that include multiple Printed Circuit Board Assemblies (PCBA) and are built to IPC standards. To ensure smooth fabrication and to reduce the risk of complications from in-process rework of PCBAs, comprehensive electrical functional testing at the board-level is required before higher- level assembly. Electrical functional testing provides verification of quality, workmanship, and manufacturing defects of the PCBAs. …

On The Gaussian-Core Vortex Lattice Model For The Analysis Of Wind Farm Flow Dynamics, Apurva Baruah

Dissertations, Master's Theses and Master's Reports

Wind power science has seen tremendous development and growth over the last 40 years. Advancements in design, manufacturing, installation, and operation of wind turbines have enabled the commercial deployment of wind power generation systems. These have been due, in a large part, to the expertise in the simulation and modeling of individual wind turbines. The new generation of wind energy systems calls for a need to accurately predict and model the entire wind farm, and not just individual turbines. The commercial deployment of these wind farms depends on model's ability to accurately capture the different physics involved, each at its …

Nanomaterials For Cardiovascular Engineering, Roya Bagheri

Dissertations, Master's Theses and Master's Reports

Cardiovascular diseases and disorders (i.e., those related to heart and blood vessels) are the main reasons for mortality worldwide. Nanomaterials, with their unique morphologies and properties, have a great potential for advancing cardiovascular engineering to treat diseases and disorders. In this dissertation, several cardiovascular applications of conductive nanomaterials were investigated. First, a conductive nanomaterial was explored to fabricate biohybrid nanomaterial-cardiomyocyte (CM – heart muscle cell) systems. Using Carbon Nanotube (CNT) forest as a 3D porous and conductive scaffold was investigated. The influence of the CNT forest on the viability, attachment, and spreading of CMs and their genetic information was …

Fabrication And Optical Properties Of Two-Dimensional Transition Metal Dichalcogenides, Manpreet Boora

Dissertations, Master's Theses and Master's Reports

Two-dimensional layered materials such as graphene and transition metal dichalcogenides have gained a lot of attention because of their distinctive chemical, optical, and electronic properties. Transition metal dichalcogenides can have a tunable bandgap in the range of 1 − 3 eV (visible), which enables their applications in ultrathin field effect transistors, photovoltaics, sensors, and optoelectronic devices. They exhibit an indirect-to-direct band gap transition when thinned down from bulk to a single layer. They show strong photoluminescence, electron–photon interaction, valley pseudospin, nonlinear optical response, and lack of dangling bonds. Many exotic phenomena appear when materials are thinned to nanoscale size because …

Development And Testing Of A Low Mass Vibratory Lunar Compactor, Charles Carey

Dissertations, Master's Theses and Master's Reports

NASA and other agencies are working to return to the moon, with the Artemis Program [1]. As a part of this new effort, an emphasis is being placed on having a sustained presence, building lunar bases and other permanent structures. The development of such infrastructure will require the development of civil engineering structures, and site preparation becomes a necessity. The Planetary Surface Technology Development Laboratory is developing a low mass lunar compactor as part of an autonomous site preparation vehicle in partnership with Colorado School of Mines, funded by NASA’s 2021 Lunar Surface Technology Research grant. The low mass lunar …

Novel Bayesian Neural Networks And Uncertainty Quantification Of Computational Mechanics Models, Ponkrshnan Thiagarajan

Dissertations, Master's Theses and Master's Reports

Computational and data-driven models suffer from a wide range of uncertainties that impact the reliability of such models. Given the exponential proliferation of machine learning models in real-world systems, establishing a degree of confidence in their predictions becomes paramount. Reliability in predictions takes on utmost significance in domains such as autonomous driving, medical image analysis, etc., where human lives are involved, and inaccuracies in predictions could lead to disastrous outcomes. For these reasons, comprehending and quantifying uncertainties in computational and data-driven models is of utmost importance. A number of techniques have been developed to quantify uncertainties in machine learning models. …

Molecular Dynamics Modeling Of Polymers For Aerospace Composites, Swapnil Sambhaji Bamane

Dissertations, Master's Theses and Master's Reports

Polymer matrix composite materials are widely used as structural materials in aerospace and aeronautical vehicles. Resin/reinforcement wetting and the effect of polymerization on the thermo-mechanical properties of the resin are key parameters in the manufacturing of aerospace composite materials. Determining the contact angle between combinations of liquid resin and reinforcement surfaces is a common method for quantifying wettability. It is challenging to determine contact angle values experimentally of high-performance resins on CNT materials such as CNT, graphene, bundles or yarns, and BNNT surfaces. It is also experimentally difficult to determine the effect of polymerization reaction on material properties of a …

Benchmarking Model Predictive Control And Reinforcement Learning For Legged Robot Locomotion, Shivayogi Akki

Dissertations, Master's Theses and Master's Reports

This research delves into the realm of quadrupedal robotics, focusing on the comparative analysis of Model Predictive Control (MPC) and Reinforcement Learning (RL) as predominant control strategies. Through the comprehensive dataset compiled and the insights derived from this analysis, this research aims to serve as a valuable resource for the legged robotics community, guiding researchers and practitioners in the selection and implementation of control strategies. The ultimate goal is to contribute to the advancement of legged robot capabilities and facilitate their successful deployment in real-world applications.

In this study, we employ the Unitree Go1 quadrupedal robot as a testbed, subjecting …

Performance Evaluation Of Using Waste Glass Powder And Fly Ash In Alkali-Activated Slag Binder And Mortar Samples As Partial Precursors, Sunday A. Eniola

Dissertations, Master's Theses and Master's Reports

The increasing environmental burden at landfills due to the disposal of waste glass has motivated the scientific community to find an alternative for its utilization. One of these promising routes is to use glass powder (GP) as precursor and waste glass sands as sand replacement in alkali-activated slag (AAS) mortar to reduce the setting time, shrinkage, and efflorescence characteristics for the field applications by comparing with class F fly ash (FFA). This study first experimentally investigates the setting behavior, shrinkage behavior and compressive strength, and efflorescence characteristics of AAS binder prepared with partially replaced glass powder and fly ash. The …

Hydro Cyclonic Separation Of Polyester Microfibers From Washing Machine Wastewater, Joe Kulkarni

Dissertations, Master's Theses and Master's Reports

Clothing made from synthetic materials shed fibers in washing machines, and these fibers find their way into the effluent water. These fibers can absorb toxic materials in wastewater treatment plants and can then carry these toxins into other aquatic environments.

It’s believed that a hydro cyclone could be scaled down enough to fit into a washing machine and could be used to filter out up to 80% of the microparticles from the effluent water. It’s proposed to investigate if a hydro cyclone can be used for this application. The overall goal was for the hydro cyclone to concentrate the micro …

Predicting The Reactivities And Reaction Mechanisms Of Photochemically Produced Reactive Intermediates, Benjamin Barrios Cerda

Dissertations, Master's Theses and Master's Reports

Photochemically produced reactive intermediates (PPRIs) such as the hydroxyl radical, carbonate radical (CO₃^•-) singlet oxygen (¹O₂) and triplet state of chromophoric dissolved organic matter (³CDOM^*) are formed in sunlit natural waters upon photoexcitation of chromophoric dissolved organic matter (CDOM). PPRIs react with the organic compounds involved in key environmental processes, resulting in transformation products of smaller molecular weight than their parent compounds. Photochemical transformation of these key water constituents due to their reactions with PPRIs may pose potential effects on human and aquatic ecosystems. Consequently, there is a need …

To The Moon: Strategic Competition In The Cislunar Region, Shawn M. Willis

Faculty Publications

China’s advancing space capabilities, particularly in the cislunar region, call for increased cislunar space domain awareness on the part of the United States. US military and civilian decisionmakers must take into account the full scope of China’s cislunar plans and capabilities as the military builds space strategies and future force designs. The United States must also increase near-term investments that support more robust cislunar space domain awareness.

Bioaccumulation Of Polychlorinated Biphenyl Compounds And Mercury In A Mining Impacted Aquatic Ecosystem, Michelle Bollini

Dissertations, Master's Theses and Master's Reports

The Keweenaw area continues to be influenced by the century of copper mining that ended nearly 50 years ago. This project is focused on Torch Lake, an aquatic ecosystem that has been heavily impacted by mining waste disposal. The watershed has been impaired by mine discharge and tailings, smelter and smokestack plumes, and poor waste disposal practices. The lake is listed as a Great Lakes Area of Concern with beneficial use impairments of restrictions on fish consumption and a degraded benthic community. Polychlorinated biphenyl compounds (PCBs) and methylmercury (MeHg) are persistent, bioaccumulative, and toxic substances (PBTs). These contaminants pose threats …

Microscopic And Laboratory Scale Characterization Methods To Evaluate Biomass Deconstruction, Meenaa Chandrasekar

Dissertations, Master's Theses and Master's Reports

Renewable fuels from lignocellulosic biomass are an appealing option because they can seamlessly integrate into the existing fuel distribution infrastructure. Lignocellulosic biomass constitutes nonedible plant material obtained from plant cell walls. The natural recalcitrance of lignocellulosic biomass poses a challenge in accessing the cell wall carbohydrates during biochemical conversion. Despite various approaches, enzymatic hydrolysis of lignocellulosic biomass remains economically impractical due to incomplete knowledge about biomass recalcitrance and the influence of environmental factors on biomass quality.

The first goal of this dissertation was to construct a microfluidic imaging reactor to better understand the tissue-specific deconstruction of plant materials. Confocal laser …

Investigating The Effects Of Network Dynamics On Quality Of Delivery Prediction And Monitoring For Video Delivery Networks, Obinna C. Izima

Doctoral

Video streaming over the Internet requires an optimized delivery system given the advances in network architecture, for example, Software Defined Networks. Machine Learning (ML) models have been deployed in an attempt to predict the quality of the video streams. Some of these efforts have considered the prediction of Quality of Delivery (QoD) metrics of the video stream in an effort to measure the quality of the video stream from the network perspective. In most cases, these models have either treated the ML algorithms as black-boxes or failed to capture the network dynamics of the associated video streams.

This PhD investigates …

An Adaptive Image Restoration Algorithm Based On Hybrid Total Variation Regularization, Cong Thang Pham, Thi Thu Thao Tran, Hung Vi Dang, Hoai Phuong Dang

Turkish Journal of Electrical Engineering and Computer Sciences

In imaging systems, the mixed Poisson-Gaussian noise (MPGN) model can accurately describe the noise present. Total variation (TV) regularization-based methods have been widely utilized for Poisson-Gaussian removal with edge-preserving. However, TV regularization sometimes causes staircase artifacts with piecewise constants. To overcome this issue, we propose a new model in which the regularization term is represented by a combination of total variation and high-order total variation. We study the existence and uniqueness of the minimizer for the considered model. Numerically, the minimization problem can be efficiently solved by the alternating minimization method. Furthermore, we give rigorous convergence analyses of our algorithm. …

Deep Learning-Based Classification Of Chaotic Systems Over Phase Portraits, Sezgi̇n Kaçar, Süleyman Uzun, Burak Aricioğlu

Turkish Journal of Electrical Engineering and Computer Sciences

This study performed a deep learning-based classification of chaotic systems over their phase portraits. To the best of the authors' knowledge, such classification studies over phase portraits have not been conducted in the literature. To that end, a dataset consisting of the phase portraits of the most known two chaotic systems, namely Lorenz and Chen, is generated for different values of the parameters, initial conditions, step size, and time length. Then, a classification with high accuracy is carried out employing transfer learning methods. The transfer learning methods used in the study are SqueezeNet, VGG-19, AlexNet, ResNet50, ResNet101, DenseNet201, ShuffleNet, and …