Engineering Commons^™

An Open Source Cyberinfrastructure For Collecting, Processing, Storing And Accessing High Temporal Resolution Residential Water Use Data, Camilo J. Bastidas Pacheco, Joseph C. Brewer, Jeffery S. Horsburgh, Juan Caraballo

Publications

Collecting and managing high temporal resolution residential water use data is challenging due to cost and technical requirements associated with the volume and velocity of data collected. We developed an open-source, modular, generalized architecture called Cyberinfrastructure for Intelligent Water Supply (CIWS) to automate the process from data collection to analysis and presentation of high temporal residential water use data. A prototype implementation was built using existing open-source technologies, including smart meters, databases, and services. Two case studies were selected to test functionalities of CIWS, including push and pull data models within single family and multi-unit residential contexts, respectively. CIWS was …

Augmented Human Machine Intelligence For Distributed Inference, Baocheng Geng

Dissertations - ALL

With the advent of the internet of things (IoT) era and the extensive deployment of smart devices and wireless sensor networks (WSNs), interactions of humans and machine data are everywhere. In numerous applications, humans are essential parts in the decision making process, where they may either serve as information sources or act as the final decision makers. For various tasks including detection and classification of targets, detection of outliers, generation of surveillance patterns and interactions between entities, seamless integration of the human and the machine expertise is required where they simultaneously work within the same modeling environment to understand and …

Development Of Computational Antibiotic Screening Platform Across Bacterial Outer Membrane Proteins, Yinghui Dai

Dissertations - ALL

Antibiotics are medicines used to treat bacterial infections by either killing bacteria or stopping them from reproducing. Throughout the use of antibiotics, bacteria has developed a variety of defense mechanisms against antibiotics and thus diminishing their effectiveness. Antibiotic resistance is a growing threat and becomes a global crisis as it is able to constantly evolve and rapidly spread. In the face of increasing bacterial resistance to all known antibiotics, there is an urgent need to accelerate the antibiotic discovery pipeline and discover new classes of antibiotics. A major bottleneck in the discovery of novel antibiotics is the limited permeability of …

Thermal And Mechanical Analysis Of Bombyx Mori Silk Nanofibers, Justin Busnot

Department of Mechanical and Materials Engineering: Dissertations, Theses, and Student Research

This thesis presents a study on the thermomechanical properties of Bombyx Mori silk nanofibers. These nanofibers were obtained from silkworm cocoons which were degummed to separate the fibroin and the sericin, the two proteins that make up silk. The fibroin was then centrifuged to remove insoluble particles and stored and 4°C before the electrospinning process. A parametric study of the electrospinning process was carried out in order to identify the factors allowing to obtain optimal mechanical properties. The current as well as the flow rate applied, the diameter of the syringe, the distance separating the syringe from collector or even …

Modeling Cyanotoxin Production, Fate And Transport In Surface Waterbodies, Bernadel Rose Hintz Garstecki

Dissertations and Theses

Cyanobacteria exist throughout the world and are frequently associated with forming toxic blooms. The toxins produced by cyanobacteria, cyanotoxins, are harmful to both humans and animals. Rising temperatures due to global climate change, increased nutrient loading, and other anthropogenic impacts on waterbodies are expected to increase the prevalence of cyanobacteria. It is vital that we protect our drinking water supplies and natural water resources. Modeling the production and movement of these toxins is an important step in limiting exposure to them and evaluating management strategies to mitigate their impact. Cyanotoxins are diverse and the conditions under which they are formed …

Compact Sealed Spark Gaps, Seth Miller

Electrical and Computer Engineering ETDs

Spark gaps have always been a good solution for high power switching. They are simple, cheap, handle a large amount of Coulomb transfer, and are more forgiving to work with compared to solid-state alternatives. Even with solid-state switching advancing a long way since the 20th century, spark gaps outperform them in terms of peak power handling capabilities, Coulomb transfer, and make them attractive for higher power systems. Most lab settings use spark gaps because the cost is low, and they can be repaired if they break or wear out as opposed to a semiconductor alternative. While this technology is great …

Lyapunov Function-Based Stabilizing Control Scheme For Wireless Power Transfer Systems With Lcc Compensation Network, Abu Shahir Md Khalid Hasan

LSU Master's Theses

A stabilizing control scheme based on a Lyapunov function is proposed for wireless power transfer (or WPT) systems. A state-space model of the WPT system is developed and the Lyapunov function is formulated based on an energy equation of the system involving state variables. The internal resistance of a battery varies during charge and discharge. Therefore, if a WPT system is used to charge a battery, its output load will vary. Furthermore, the coupling coefficient between the transmitter (primary) and receiver (secondary) coils decreases when they are misaligned. Comparative case studies are conducted to verify the efficacy of the proposed …

Enhanced Oil Recovery In Tight Rocks Using The “Slot-Drill” Completion, Hassan Amer

LSU Master's Theses

Enhanced oil recovery (EOR) is essential in shale/tight formations because primary recovery typically produces less than 10% of the original hydrocarbon in-place (OHIP). This work presents a novel “slot-drill” EOR technology, which involves injecting gas through a horizontal fracture that is cut into the formation near the top of the reservoir (using a tensioned abrasive cutting cable mounted to the drillstring) and producing oil from a second slot-drilled horizontal fracture near the bottom of the reservoir.

The dusty-gas diffusion model was implemented in a compositional simulator to account for the diffusion mechanism expected during the injection of gases in this …

An Economical Method For Securely Disintegrating Solid-State Drives Using Blenders, Brandon J. Hopkins Phd, Kevin A. Riggle

Journal of Digital Forensics, Security and Law

Pulverizing solid-state drives (SSDs) down to particles no larger than 2 mm is required by the United States National Security Agency (NSA) to ensure the highest level of data security, but commercial disintegrators that achieve this standard are large, heavy, costly, and often difficult to access globally. Here, we present a portable, inexpensive, and accessible method of pulverizing SSDs using a household blender and other readily available materials. We verify this approach by pulverizing SSDs with a variety of household blenders for fixed periods of time and sieve the resulting powder to ensure appropriate particle size. Among the 6 household …

Load Flow Solution Of Distribution Systems - A Bibliometric Survey, K. V. S. Ramachandra Murthy, Vijay Kumar D, Lakshmi Kambhampati, Rayudu Srinivas, Rayudu Srinivas

Library Philosophy and Practice (e-journal)

In this paper, Bibliometric Survey has been carried out on ‘Load Flow Solution of Distribution Systems’ from 2012 to 2021. Scopus database has been used for the analysis. There were total 1711 documents found on this topic. The statistical analysis is carried out source wise, year wise, area wise, Country wise, University wise, author wise, and based on funding agency. Network analysis is also carried out based on Co-authorship, Co-occurrence. Results are presented. During 2020 and 2018, there were 263 documents published which is the highest. ‘IEEE Transactions on Power Systems’ has published 90 documents during the period of study …

High-Throughput Design Of High-Performance Lightweight High-Entropy Alloys, Rui Feng, Chuan Zhang, Michael C. Gao, Zongrui Pei, Fan Zhang, Yan Chen, Dong Ma, Ke An, Jonathan D. Poplawsky, Lizhi Ouyang, Yang Ren, Jeffrey A. Hawk, Michael Widom, Peter K. Liaw

Mathematical Sciences Faculty Research

Developing affordable and light high-temperature materials alternative to Ni-base superalloys has significantly increased the efforts in designing advanced ferritic superalloys. However, currently developed ferritic superalloys still exhibit low high-temperature strengths, which limits their usage. Here we use a CALPHAD-based high-throughput computational method to design light, strong, and low-cost high-entropy alloys for elevated-temperature applications. Through the high-throughput screening, precipitation-strengthened lightweight high-entropy alloys are discovered from thousands of initial compositions, which exhibit enhanced strengths compared to other counterparts at room and elevated temperatures. The experimental and theoretical understanding of both successful and failed cases in their strengthening mechanisms and order-disorder transitions further …

Investigation And Statistical Modeling Of The Mechanical Properties Of Additively Manufactured Lattices, Derek G. Spear, Anthony N. Palazotto

Faculty Publications

This paper describes the background, test methodology, and experimental results associated with the testing and analysis of quasi-static compression testing of additively manufactured open-cell lattice structures. The study aims to examine the effect of lattice topology, cell size, cell density, and surface thickness on the mechanical properties of lattice structures. Three lattice designs were chosen, the Diamond, I-WP, and Primitive Triply Periodic Minimal Surfaces (TPMSs). Uniaxial compression tests were conducted for every combination of the three lattice designs, three cell sizes, three cell densities, and three surface thicknesses. In order to perform an efficient experiment and gain the most information …

Adaptive Mobile Eeg Noise Cancellation Using 2d Convolutional Autoencoders For Bci Authentication, Tyree Lewis

USF Tampa Graduate Theses and Dissertations

Electroencephalography (EEG) signals can be used for many purposes and has the potential to be adapted to various systems. When EEG is recorded from users, these studies are performed primarily in an indoor environment, while the user is stationary. This is due to the levels of noise that are experienced when recording EEG data, to minimize errors in the data. This thesis aims to adapt tasks that are performed indoors to an external environment by removing both noise and artefacts in EEG, using a 2D Convolutional Autoencoder (CAE). The data is recorded from subjects is passed into the 2D CAE …

Monitoring Damage Occurrence, Post-Peak Crack Propagation And Air Permeability In Concrete Using The Brazilian Indirect Tension Test, Angel M. Padilla

Civil Engineering ETDs

This research aims to investigate the relationship between stress, damage, crack propagation, and permeability evolution in concrete. A novel experimental test method is presented that enables monitoring post-peak cracking behavior of concrete using the Brazilian tension test by slowing crack propagation while concurrently measuring permeability and monitoring damage propagation using acoustic emission techniques. The modified Brazilian test method utilizes spring supports in parallel to the test specimen to off-load the test specimen incrementally to slow down the post-peak crack propagation. A vacuum flow system is attached to the rear side of the concrete during loading to measure apparent air permeability …

Early-Stage Gas Identification Using Convolutional Long Short-Term Neural Network With Sensor Array Time Series Data, Kai Zhou, Yixin Liu

Michigan Tech Publications, Part 1

Gas identification/classification through pattern recognition techniques based on gas sensor arrays often requires the equilibrium responses or the full traces of time-series data of the sensor array. Leveraging upon the diverse gas sensing kinetics behaviors measured via the sensor array, a computational intelligence-based meta-model is proposed to automatically conduct the feature extraction and subsequent gas identification using time-series data during the transitional phase before reaching equilibrium. The time-series data contains implicit temporal dependency/correlation that is worth being characterized to enhance the gas identification performance and reliability. In this context, a tailored approach so-called convolutional long short-term memory (CLSTM) neural network …

Performance Evaluation Of A Prestressed Belitic Calcium Sulfoaluminate Cement (Bcsa) Concrete Bridge Girder, Nick Markosian, Raed Tawadrous, Mohammad Mastali, Robert J. Thomas, Marc Maguire

Durham School of Architectural Engineering and Construction: Faculty Publications

Belitic calcium sulfoaluminate (BCSA) cement is a sustainable alternative to Portland cement that offers rapid setting characteristics that could accelerate throughput in precast concrete operations. BCSA cements have lower carbon footprint, embodied energy, and natural resource consumption than Portland cement. However, these benefits are not often utilized in structural members due to lack of specifications and perceived logistical challenges. This paper evaluates the performance of a full-scale precast, prestressed voided deck slab bridge girder made with BCSA cement concrete. The rapid-set properties of BCSA cement allowed the initial concrete compressive strength to reach the required 4300 psi release strength at …

Premium-Cnn: Propagating Uncertainty Towards Robust Convolutional Neural Networks, Dimah Dera, Nidhal Carla Bouaynaya, Ghulam Rasool, Roman Shterenberg, Hassan M. Fathallah-Shaykh

Electrical and Computer Engineering Faculty Publications

Deep neural networks (DNNs) have surpassed human-level accuracy in various learning tasks. However, unlike humans who have a natural cognitive intuition for probabilities, DNNs cannot express their uncertainty in the output decisions. This limits the deployment of DNNs in mission-critical domains, such as warfighter decision-making or medical diagnosis. Bayesian inference provides a principled approach to reason about model's uncertainty by estimating the posterior distribution of the unknown parameters. The challenge in DNNs remains the multi-layer stages of non-linearities, which make the propagation of high-dimensional distributions mathematically intractable. This paper establishes the theoretical and algorithmic foundations of uncertainty or belief propagation …

Impact Of Personality Traits And Team Criteria On Construction Team Performance, Arlys Silva Payne

LSU Doctoral Dissertations

This dissertation investigated how personality traits and team criteria influence team performance in real construction projects. Though personality influence on team performance has been significantly investigated in other business sectors, the literature revealed that the construction industry lacks investigations regarding personality influencing team performance. The existing literature revealed that the Big Five Factors (BFF) was the most popular assessment tool for personality. Thus, this dissertation adopted the 50-Item Personality questionnaire developed by Goldberg, which consited of extraversion, aggreeableness, conscientiousness, neuroticism, and openness to experience. The literature also revealed several common team criteria to evaluate team performance: team member satisfaction, shared …

Spanish And English Phoneme Recognition By Training On Simulated Classroom Audio Recordings Of Collaborative Learning Environments, Mario J. Esparza Perez

Electrical and Computer Engineering ETDs

Audio recordings of collaborative learning environments contain a constant presence of cross-talk and background noise. Dynamic speech recognition between Spanish and English is required in these environments. To eliminate the standard requirement of large-scale ground truth, the thesis develops a simulated dataset by transforming audio transcriptions into phonemes and using 3D speaker geometry and data augmentation to generate an acoustic simulation of Spanish and English speech. The thesis develops a low-complexity neural network for recognizing Spanish and English phonemes (available at github.com/muelitas/keywordRec). When trained on 41 English phonemes, 0.099 PER is achieved on Speech Commands. When trained on 36 Spanish …

Lessons To Be Learned In Adoption Of Autonomous Equipment For Field Crops, James Lowenberg-Deboer, Karl Behrendt, Melf-Hinrich Ehlers, Carl R. Dillon, Andreas Gabriel, Iona Yuelu Huang, Ian Kumwenda, Tyler Mark, Andreas Meyer-Aurich, Gabor Milics, Kehinde Oluseyi Olagunju, Søren Marcus Pedersen, Jordan M. Shockley, David Rose

Agricultural Economics Faculty Publications

Autonomous equipment for crop production is on the verge of technical and economic feasibility, but government regulation may slow its adoption. Key regulatory issues include requirements for on-site human supervision, liability for autonomous machine error, and intellectual property in robotic learning. As an example of the impact of regulation on the economic benefits of autonomous crop equipment, analysis from the United Kingdom suggests that requiring 100% on-site human supervision almost wipes out the economic benefits of autonomous crop equipment for small and medium farms and increases the economies-of-scale advantage of larger farms.

Riyadh Neighborhood Residents’ Use And Satisfaction With Urban Green Spaces, Tahar Ledraa, Majed Hallawani, Awad Al-Qahtani

Emirates Journal for Engineering Research

Neighborhood urban green spaces are indispensable elements for residents’ rest and recreation. They are also of paramount importance to enhance quality of life within neighborhoods. However, these urban green spaces did not receive much research interest, particularly in cities of the developing world. Larger city parks seem to have been the focus of studies. The present study is undertaken under the contention that dissatisfaction with a service is the difference between what is expected from that service and what is really experienced out of it. The gap between expectancy and what is experienced in reality would lead to how satisfied …

The Development Of An Instrument To Measure Transdermal Hydrogen Sulfide As A Way To Evaluate Microvascular Health In Humans, Benjamin Thomas Matheson

Biomedical Engineering ETDs

Hydrogen sulfide (H₂S) is a gasotransmitter critical in maintaining microcirculation homeostasis. Impaired microcirculation occurs in multiple disease states such as peripheral vascular disease, diabetes mellitus (DM), and hypertension. Early detection and identification of patients with DM who are at risk for heart attack, stroke and amputation due to microvascular disease is crucial. Human skin is an accessible vascular bed that provides an opportunity to non-invasively measure H₂S, which could be used as a biomarker to evaluate microvascular health.

In this work, a novel H₂S gas sensor, called the transdermal arterial gasotransmitter sensor (TAGS^{TM …}

Final 2021 Residential Metals Abatement Program (Rmap) School Soil Sampling Field Sampling Plan (Fsp) Submittal #2 (Covering Highland View Christian School, Hillcrest Elementary, Kennedy Elementary, Silver Bow Montessori, & West Elementary), Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Extracting Microplastic From Anhydrous Beach Sediment Utilizing Relative Terminal Velocities, Grace Robertson, Jackson Schuler

Student Works

The primary intent of this research was to investigate and develop a method to extract microplastics from anhydrous beach sediment. Microplastic is found abundantly in coastal sea environments, including aqueous bottom sediment, and beach sediment (Sagawa, Kawaai, & Hinata, 2018). The scope of the microplastic extraction method in this case is limited to strictly the anhydrous beach sediment. The Venturi Effect and Burnoulli’s Principle have been utilized in the design of a nozzle with airflow that has been injected with a sediment and microplastic heterogenous mixture. A nozzle was designed to operate at the specific terminal velocity of sediment such …

Probabilistic Analysis Of The Active Earth Pressure On Earth Retaining Walls For C‑Φ Soils According To The Mazindrani And Ganjali Method, Julian Osorio, Juan Camilo Viviescas, Juan Pablo Osorio

Articles

The determination of the earth pressure coefficients (K) in geotechnical engineering is one of the most critical procedures in designing earth retaining walls. However, most earth pressure theories are made for either clay or sands, where the c-ϕ soils are the least analysed. In this paper, an analysis of the earth pressure for drained mixed soils based in Mazindrani and Ganjali (J Geotech Geoenviron Eng 123:110–112, 1997) theory was carried out. Earth pressure coefficients are generally used in a deterministic way and can represent designs under an inadmissible risk. Therefore, Reliability-based design arises as an essential tool to deal with …

Use Of Machine Learning For Automated Convergence Of Numerical Iterative Schemes, Leonardo A. Bueno-Benitez

Doctoral Dissertations and Master's Theses

Convergence of a numerical solution scheme occurs when a sequence of increasingly refined iterative solutions approaches a value consistent with the modeled phenomenon. Approximations using iterative schemes need to satisfy convergence criteria, such as reaching a specific error tolerance or number of iterations. The schemes often bypass the criteria or prematurely converge because of oscillations that may be inherent to the solution. Using a Support Vector Machines (SVM) machine learning approach, an algorithm is designed to use the source data to train a model to predict convergence in the solution process and stop unnecessary iterations. The discretization of the Navier …

Fixed Bottom Wind Turbine Wave-Wake Interaction, Ondrej Fercak

Dissertations and Theses

The interest and benefits of offshore wind energy has also brought along legitimate design challenges for engineers. Most notably, the complex interaction between wind and turbine is further complicated by the addition of dynamic ocean waves. This dynamic coupling between wind, wave, and turbine is not fully understood. Even small improvements in wind turbine performance are welcome, so characterizing a fundamental dynamic in offshore energy is necessary to optimize design. Experimentation and simulation have been used to characterize inflow and turbine wakes and separately, wind-wave interactions. But only simulations have just begun to look at the wind, wave, and turbine …

Laboratory And Full-Scale Pavement Sections Testing For Evaluating Frost Action In Cold Regions, Dorin Papuc

Theses and Dissertations

A comprehensive laboratory testing plan was conducted as part of this project to select two frost-susceptible soils for use in constructing three full-scale test strips. A total of 16 soils were obtained from various suppliers in NJ and were evaluated to determine their frost-susceptibility. The evaluation included conducting sieve analysis, hydrometer analysis, and specific gravity. Using these measures, two soils were selected (namely, Soil #2 and Soil #13) for constructing the test strips. The properties (Atterberg Limits, moisture-density relationships, California bearing ratio (CBR), Resilient Modulus among others) were determined through a laboratory testing plan. In addition, this study involved constructing …

Correlating Diffusional Dynamics And Receptor Tyrosine Kinase Function Using Single Quantum Dot Tracking, Irais Ortiz Caraveo

Biomedical Engineering ETDs

Epidermal growth factor receptor (EGFR) signal transduction is initiated via ligand (EGF) binding, followed by dimerization, autophosphorylation of the C-terminal tails, and recruitment of proteins that form a larger signaling complex to propagate the signal. We explored the relationship between receptor mobility and signaling using single-particle tracking (SPT) by examining the diffusional dynamics of EGFR and two truncation mutants to understand whether mobility changes are correlated with signaling. Results revealed that phosphorylation of the C-terminal tail of EGFR is required for maximal reduction in mobility that occurs with EGF stimulation, indicating that receptor mobility is a read-out for receptor signaling. …

Pathcnn: Interpretable Convolutional Neural Networks For Survival Prediction And Pathway Analysis Applied To Glioblastoma, Jung Hun Oh, Wookjin Choi, Euiseong Ko, Mingon Kang, Allen Tannenbaum, Joseph O. Deasy

Computer Science Faculty Research

Motivation: Convolutional neural networks (CNNs) have achieved great success in the areas of image processing and computer vision, handling grid-structured inputs and efficiently capturing local dependencies through multiple levels of abstraction. However, a lack of interpretability remains a key barrier to the adoption of deep neural networks, particularly in predictive modeling of disease outcomes. Moreover, because biological array data are generally represented in a non-grid structured format, CNNs cannot be applied directly. Results: To address these issues, we propose a novel method, called PathCNN, that constructs an interpretable CNN model on integrated multi-omics data using a newly defined pathway image. …