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Articles 2521 - 2550 of 195942

Full-Text Articles in Engineering

Process-Structure-Property Relationships Of Nanofibers For Biomedical Applications, Dipasree Bhowmick Dec 2023

Process-Structure-Property Relationships Of Nanofibers For Biomedical Applications, Dipasree Bhowmick

Theses and Dissertations

This thesis explores the fabrication, characterization, and applications of nanofiber membranes utilizing Forcespinning® technology. Two distinct nanofiber systems were developed and evaluated, one focusing on pH-responsive Eudragit-baicalin loaded nanofibrous membranes for wound healing and the second one on thermo-responsive nanofiber-hydrogel (PNIPAAm) systems for biosensing applications, specifically dopamine detection. In the first project, nanofiber membranes loaded with Eudragit and baicalin demonstrated superior antibacterial properties against both gram-negative (E. coli) and gram-positive (B. meg) bacteria. Additionally, these membranes exhibited antioxidant properties and enhanced cell proliferation of 3TT cells, making them promising candidates for wound healing dressings. In the second project, a …

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Electromagnetic Field Analysis, Materials Characterization, And Advanced Modeling Of Modern Guitar Pickups, Luis Alonso Villarreal Dec 2023

Electromagnetic Field Analysis, Materials Characterization, And Advanced Modeling Of Modern Guitar Pickups, Luis Alonso Villarreal

Theses and Dissertations

This Thesis establishes the foundations of modern guitar pickup theory, enhancing current pickup design by an increase in voltage output, reduction of DC resistance, and a reduction of production costs. This research investigates factors that have received insufficient attention, such as the performance of different magnetic materials, magnet geometry, bobbin geometry, metal effects, etc. An equation to calculate the output of guitar pickups is developed. Additionally, this work constructs a modern pickup using the techniques developed in this thesis incorporating theory and advanced modeling techniques to simulate changes in performance and interactions with different magnetic materials and geometries. The new …

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Robust Uncertainty Estimation Framework In Deep Reinforcement Learning For Active Slam, Bryan Joseph Pedraza Dec 2023

Robust Uncertainty Estimation Framework In Deep Reinforcement Learning For Active Slam, Bryan Joseph Pedraza

Theses and Dissertations

Autonomous mobile robots are essential in various domains such as industry, manufacturing and healthcare. Navigating autonomously and avoiding obstacles are crucial tasks that involve localizing the robot to explore and map unknown environments without prior knowledge. Simultaneous localization and mapping (SLAM) present significant challenges. In this study, we introduce a new approach to address robust navigation and mapping of robot actions using Bayesian Actor-Critic (A2C) reinforcement learning. The A2C framework combines policy-based and value-based learning by dividing the model into two components: (1) the policy model (Actor) determines the actions based on the state, and (2) the value model (Critic) …

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Effects Of The Build Orientation And Support Patterns On The Geometric Accuracy In Printing Parts With Overhang Structure: An Experimental Study, Bala Murali Krishna Mohan Dec 2023

Effects Of The Build Orientation And Support Patterns On The Geometric Accuracy In Printing Parts With Overhang Structure: An Experimental Study, Bala Murali Krishna Mohan

Theses and Dissertations

Additive manufacturing is becoming increasingly popular in industries such as manufacturing due to its ability to use raw materials more efficiently and require less machining than traditional methods(Calignano et al., 2017). However, constructing overhanging structures in additive manufacturing can be challenging, potentially affecting the overall geometric quality of the printed components. The objective of this study was to identify the most effective printing orientation for overhanging designs in Fused Deposition Modeling (FDM) using two different support structures. To achieve this, the researchers used a laser scanner to collect point cloud data and conducted a comparative study to determine the …

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Using Statistical Clustering Of Trajectory Data To Support Analysis Of Subject Movement In A Virtual Environment, Martín Alejandro Galicia Avila Dec 2023

Using Statistical Clustering Of Trajectory Data To Support Analysis Of Subject Movement In A Virtual Environment, Martín Alejandro Galicia Avila

Theses and Dissertations

The rising use of virtual reality software requires new methods of spatiotemporal analysis to enhance the user experience. This investigation is focused on forming clusters from spatiotemporal trajectories within a virtual environment and analyzing them in search of human immersion and behavior insights. The cluster centroids are plotted and analyzed to identify associations with the trajectories and user demographics.

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Gaze Tracking Embedded Collaborative Robots For Automated Metrology And Reverse Engineering, Sachithra H. Karunathilake Dec 2023

Gaze Tracking Embedded Collaborative Robots For Automated Metrology And Reverse Engineering, Sachithra H. Karunathilake

Theses and Dissertations

Conventional geometric metrology, or three-dimensional (3D) scanning, and reverse engineering heavily rely on the experience of the operators. With an increasing need for automation, robot arms have been adopted for this task. However, due to the large variety of parts and designs, automated path planning could provide a scanning solution that may overlook the critical area, which could potentially deteriorate the scan results. This study explores the integration of collaborative robotics (cobots) with eye tracking technology to improve the autonomous 3D scanning process. The primary objective of this study is to enhance the accuracy and efficiency of cobots in …

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Human-Centric Smart Cities: A Digital Twin-Oriented Design Of Interactive Autonomous Vehicles, Oscar G. De Leon-Vazquez Dec 2023

Human-Centric Smart Cities: A Digital Twin-Oriented Design Of Interactive Autonomous Vehicles, Oscar G. De Leon-Vazquez

Theses and Dissertations

Autonomous vehicle (AV) technology is introduced as a solution to improve transportation safety by eliminating traffic accidents caused by human error, which is the leading cause of 90% of accidents. One key feature of AVs is sensing and perceiving their surrounding environment through processing observations collected from the environment. The perception system is essential for an AV to make informed decisions and safely navigate the environment. This study presents an image semantic segmentation algorithm developed in the area of computer vision to improve AV perception. The U-Net-based algorithm is trained and validated using a synthetically generated dataset in a simulation …

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Enhancing Peanut Harvesting: Evaluating Factors That Influence Yield And Developing A Web-Based Field Drying Forecast Tool, Charles Burkett Dec 2023

Enhancing Peanut Harvesting: Evaluating Factors That Influence Yield And Developing A Web-Based Field Drying Forecast Tool, Charles Burkett

All Theses

Peanuts have one of the largest economic impacts of agronomic crops in the State of South Carolina. Peanut harvest operations involve several steps (digging, curing, combining) using equipment unique to peanut production, including peanut digger/shaker/inverters. This thesis evaluates several aspects of peanut harvest operations, including how precision agriculture technologies can enhance decision-making and enhance production. Several studies were conducted to analyze how various aspects of peanut harvesting operations contribute to decrease losses in yield and revenue. The first study evaluated the influence of operator experience on mean absolute guidance line deviation during peanut digging operations and the associated effects on …

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Temperature Gradient Effect On Solid-Liqid Interface Properties Of Al-Cu Alloy: A Molecular Dynamics Study, Prashant Kumar Jha Dec 2023

Temperature Gradient Effect On Solid-Liqid Interface Properties Of Al-Cu Alloy: A Molecular Dynamics Study, Prashant Kumar Jha

All Theses

Aluminum-copper (Al-Cu) alloys are widely used in the aerospace industry due to their favorable strength-to-weight ratio, good fatigue resistance, and corrosion resistance. These properties make Al-Cu alloys an excellent choice for aircraft structural components that require high strength and low weight. Additive manufacturing (AM), also known as 3D printing, has emerged as a promising processing method for Al-Cu alloys in aerospace manufacturing. AM enables the production of lightweight optimized geometries difficult to manufacture through conventional subtractive methods. AM also reduces material waste by only depositing material where needed in the part geometry. The rapid solidification conditions in AM processes motivate …

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Creation And Validation Of A Novel Bayesian Calibration Method With Griddy Gibbs Sampling, Hannah Stewart Dec 2023

Creation And Validation Of A Novel Bayesian Calibration Method With Griddy Gibbs Sampling, Hannah Stewart

All Theses

Computer models of physical systems are widely used in lieu of, or in tandem with, experimental testing. It is critical to verify the accuracy of computer models through the process of calibration. Typical calibration methods are often computationally expensive and therefore cannot be performed in real time. This thesis presents a novel Bayesian calibration method using a Griddy Gibbs sampling algorithm to improve calibration speeds. This method was verified in two applications: a location-dependent dataset in the heat transfer analysis of an engine piston, and time-dependent tire forces in a drum test. The proposed method was directly compared to a …

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Cyber-Threat Detection Strategies Governed By An Observer And A Neural-Network For An Autonomous Electric Vehicle, Douglas Scruggs Dec 2023

Cyber-Threat Detection Strategies Governed By An Observer And A Neural-Network For An Autonomous Electric Vehicle, Douglas Scruggs

All Theses

A pathway to prevalence for autonomous electrified transportation is reliant upon accurate and reliable information in the vehicle’s sensor data. This thesis provides insight as to the effective cyber-attack placements on an autonomous electric vehicle’s lateral stability control system (LSCS). Here, Data Integrity Attacks, Replay Attacks, and Denial-of-Service attacks are placed on the sensor data describing the vehicle’s actual yaw-rate and sideslip angle. In this study, there are three different forms of detection methods. These detection methods utilize a residual metric that incorporate sensor data, a state-space observer, and a Neural-Network. The vehicle at hand is a four-motor drive autonomous …

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Effect Of Latex Modified Concrete Overlays With Reduced Surface Preparation On The Load Distribution And Flexural Strength Of Channel Girders, Samuel Dodd Dec 2023

Effect Of Latex Modified Concrete Overlays With Reduced Surface Preparation On The Load Distribution And Flexural Strength Of Channel Girders, Samuel Dodd

All Theses

This thesis investigates the use of a Latex Modified Concrete (LMC) overlay to increase the strength of prestressed channel girders and enhance their ability to distribute load. The research conducted in this thesis involved material testing of several different LMC mixes and flexural testing of an LMC overlay and girder system. The material testing was used to determine a reasonable LMC mix design and surface preparation method to be used for the overlay. Based on material testing it was concluded that a rapid-set mix and pressure washing of the girder surfaces were a reasonable mix design and surface preparation for …

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Development Of A User-Friendly Shelf-Life Model To Evaluate The Suitability Of Sustainable Materials In Roasted And Ground Coffee Fractional Packs, Matthew Baxley Dec 2023

Development Of A User-Friendly Shelf-Life Model To Evaluate The Suitability Of Sustainable Materials In Roasted And Ground Coffee Fractional Packs, Matthew Baxley

All Theses

Roasted and ground coffee is a shelf stable product yet quite sensitive to oxidative staling. A consumer acceptance-based shelf-life modeling system was proposed with intent for the rapid determination of suitable coffee packages. This model requires as input the oxygen consumption rate (OCR) of the coffee, barrier values of packages, and the size of the packaging. Within the time period tested, it was shown that this model accurately predicted the oxygen uptake of coffee over time. Four bio-based packaging systems with barrier layers including mPLA, mPE, mcellophane, and paper were compared against a control (mPET). These materials displayed a range …

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Safe Navigation Of Quadruped Robots Using Density Functions, Andrew Zheng Dec 2023

Safe Navigation Of Quadruped Robots Using Density Functions, Andrew Zheng

All Theses

Safe navigation of mission-critical systems is of utmost importance in many modern autonomous applications. Over the past decades, the approach to the problem has consisted of using probabilistic methods, such as sample-based planners, to generate feasible, safe solutions to the navigation problem. However, these methods use iterative safety checks to guarantee the safety of the system, which can become quite complex. The navigation problem can also be solved in feedback form using potential field methods. Navigation function, a class of potential field methods, is an analytical control design to give almost everywhere convergence properties, but under certain topological constraints and …

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Assessing Blockchain’S Potential To Ensure Data Integrity And Security For Ai And Machine Learning Applications, Aiasha Siddika Dec 2023

Assessing Blockchain’S Potential To Ensure Data Integrity And Security For Ai And Machine Learning Applications, Aiasha Siddika

Master of Science in Information Technology Theses

The increasing use of data-centric approaches in the fields of Machine Learning and Artificial Intelligence (ML/AI) has raised substantial issues over the security, integrity, and trustworthiness of data. In response to this challenge, Blockchain technology offered a promising and practical solution, as its inherent characteristics as a decentralized distributed ledger, coupled with cryptographic processes, offer an unprecedented level of data confidentiality and immutability. This study examines the mutually beneficial connection between Blockchain technology and ML/AI, using Blockchain's inherent capacity to protect against unauthorized alterations of data during the training phase of ML models. The method involves building valid blocks of …

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A Poisson-Based Distribution Learning Framework For Short-Term Prediction Of Food Delivery Demand Ranges, Jian Liang, Jintao Ke, Hai Wang, Hongbo Ye, Jinjun Tang Dec 2023

A Poisson-Based Distribution Learning Framework For Short-Term Prediction Of Food Delivery Demand Ranges, Jian Liang, Jintao Ke, Hai Wang, Hongbo Ye, Jinjun Tang

Research Collection School Of Computing and Information Systems

The COVID-19 pandemic has caused a dramatic change in the demand composition of restaurants and, at the same time, catalyzed on-demand food delivery (OFD) services—such as DoorDash, Grubhub, and Uber Eats—to a large extent. With massive amounts of data on customers, drivers, and merchants, OFD platforms can achieve higher efficiency with better strategic and operational decisions; these include dynamic pricing, order bundling and dispatching, and driver relocation. Some of these decisions, and especially proactive decisions in real time, rely on accurate and reliable short-term predictions of demand ranges or distributions. In this paper, we develop a Poisson-based distribution prediction (PDP) …

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Neural Airport Ground Handling, Yaoxin Wu, Jianan Zhou, Yunwen Xia, Xianli Zhang, Zhiguang Cao, Jie Zhang Dec 2023

Neural Airport Ground Handling, Yaoxin Wu, Jianan Zhou, Yunwen Xia, Xianli Zhang, Zhiguang Cao, Jie Zhang

Research Collection School Of Computing and Information Systems

Airport ground handling (AGH) offers necessary operations to flights during their turnarounds and is of great importance to the efficiency of airport management and the economics of aviation. Such a problem involves the interplay among the operations that leads to NP-hard problems with complex constraints. Hence, existing methods for AGH are usually designed with massive domain knowledge but still fail to yield high-quality solutions efficiently. In this paper, we aim to enhance the solution quality and computation efficiency for solving AGH. Particularly, we first model AGH as a multiple-fleet vehicle routing problem (VRP) with miscellaneous constraints including precedence, time windows, …

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Directional Microwave Emission From Femtosecond-Laser Illuminated Linear Arrays Of Superconducting Rings, Thomas J. Bullard, Kyle Frische, Charlie Ebbing, Stephen J. Hageman, John Morrison, John Bulmer, Enam A. Chowdury, Michael L. Dexter, Timothy J. Haugan, Anil K. Patniak Dec 2023

Directional Microwave Emission From Femtosecond-Laser Illuminated Linear Arrays Of Superconducting Rings, Thomas J. Bullard, Kyle Frische, Charlie Ebbing, Stephen J. Hageman, John Morrison, John Bulmer, Enam A. Chowdury, Michael L. Dexter, Timothy J. Haugan, Anil K. Patniak

Faculty Publications

We examine the electromagnetic emission from two photo-illuminated linear arrays composed of inductively charged superconducting ring elements. The arrays are illuminated by an ultrafast infrared laser that triggers microwave broadband emission detected in the 1–26 GHz range. Based on constructive interference from the arrays a narrowing of the forward radiation lobe is observed with increasing element count and frequency demonstrating directed GHz emission. Results suggest that higher frequencies and a larger number of elements are achievable leading to a unique pulsed array emitter concept that can span frequencies from the microwave to the terahertz (THz) regime.

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Convolution And Autoencoders Applied To Nonlinear Differential Equations, Noah Borquaye Dec 2023

Convolution And Autoencoders Applied To Nonlinear Differential Equations, Noah Borquaye

Electronic Theses and Dissertations

Autoencoders, a type of artificial neural network, have gained recognition by researchers in various fields, especially machine learning due to their vast applications in data representations from inputs. Recently researchers have explored the possibility to extend the application of autoencoders to solve nonlinear differential equations. Algorithms and methods employed in an autoencoder framework include sparse identification of nonlinear dynamics (SINDy), dynamic mode decomposition (DMD), Koopman operator theory and singular value decomposition (SVD). These approaches use matrix multiplication to represent linear transformation. However, machine learning algorithms often use convolution to represent linear transformations. In our work, we modify these approaches to …

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Impact Of Weather Factors On Airport Arrival Rates: Application Of Machine Learning In Air Transportation, Robert W. Maxson, Dothang Truong, Woojin Choi Dec 2023

Impact Of Weather Factors On Airport Arrival Rates: Application Of Machine Learning In Air Transportation, Robert W. Maxson, Dothang Truong, Woojin Choi

Publications

Weather is responsible for approximately 70% of air transportation delays in the National Airspace System, and delays resulting from convective weather alone cost airlines and passengers millions of dollars each year due to delays that could be avoided. This research sought to establish relationships between environmental variables and airport efficiency estimates by data mining archived weather and airport performance data at ten geographically and climatologically different airports. Several meaningful relationships were discovered from six out of ten airports using various machine learning methods within an overarching data mining protocol, and the developed models were tested using historical data.

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Thermal Atomization On Superhydrophobic Surfaces Of Varying Temperature Jump Length, Eric D. Lee, Daniel Maynes, Julie Crockett, Brian D. Iverson Dec 2023

Thermal Atomization On Superhydrophobic Surfaces Of Varying Temperature Jump Length, Eric D. Lee, Daniel Maynes, Julie Crockett, Brian D. Iverson

Faculty Publications

This paper presents an experimental study of drop impingement and thermal atomization on hydrophobic and superhydrophobic (SH) surfaces. Superhydrophobic surfaces having both microscale and nanoscale geometry are considered. Microscale SH surfaces are coated with a hydrophobic coating and exhibit micropillars and cavities which are classified using the surface solid fraction and center to center pitch. The solid fraction and pitch values explored in this study range from 0.05-1.0 and 8-60 μm respectively. Nanoscale textured surfaces are created by applying a blanket layer of carbon nanotubes. Both types of surfaces are further classified by a temperature jump length (λ …

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Residual Trapping Of Co2, N2, And A Co2-N2 Mixture In Indiana Limestone Using Robust Nmr Coreflooding: Implications For Co2 Geological Storage, Amer Alanazi, Auby Baban, Muhammad Ali, Alireza Keshavarz, Stefan Iglauer, Hussein Hoteit Dec 2023

Residual Trapping Of Co2, N2, And A Co2-N2 Mixture In Indiana Limestone Using Robust Nmr Coreflooding: Implications For Co2 Geological Storage, Amer Alanazi, Auby Baban, Muhammad Ali, Alireza Keshavarz, Stefan Iglauer, Hussein Hoteit

Research outputs 2022 to 2026

Carbon capture and sequestration (CCS) in geological formations is a prominent solution for reducing anthropogenic carbon emissions and mitigating climate change. The capillary trapping of CO2 is a primary trapping mechanism governed by the pressure difference between the wetting and nonwetting phases in a porous rock, making the latter a key input parameter for dynamic simulation models. During the CCS operational process, however, the CO2 is prone to contamination by impurities from various sources such as surfaces (e.g., pipelines and tanks) and the subsurface (e.g., existing natural gas). Such contamination can strongly influence the overall CO2 wettability, storage capacity, and …

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Small Scale Desalination Technologies: A Comprehensive Review, Hamed Kariman, Abdellah Shafieian, Mehdi Khiadani Dec 2023

Small Scale Desalination Technologies: A Comprehensive Review, Hamed Kariman, Abdellah Shafieian, Mehdi Khiadani

Research outputs 2022 to 2026

In recent decades, problems related to fresh water has become a very important issue for humans. Small-scale desalination (SSD) systems, besides large-scale desalination (LSD) systems, fulfil an important role in meeting freshwater demand by eliminating the cost of transmission and have the advantage of treating water on-site. In this study, for the first time, a comprehensive review of previous studies has been carried out on SSD systems (less than 25 m3/d water production). These systems are powered using renewable, non-renewable or hybrid sources of energy, incorporating different treatment technologies such as: reverse osmosis (RO); electro dialysis (ED); capacitive deionization (CDI); …

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Thermo-Hydraulic Performance Evaluation Of A Naca 63-015 Heat Exchanger With Shark Denticles As Surface Textures, Aakash S. Hurry, Kevin Hayward, Ferdinando Guzzomi, Kanishk Rauthan, Ana Vafadar Dec 2023

Thermo-Hydraulic Performance Evaluation Of A Naca 63-015 Heat Exchanger With Shark Denticles As Surface Textures, Aakash S. Hurry, Kevin Hayward, Ferdinando Guzzomi, Kanishk Rauthan, Ana Vafadar

Research outputs 2022 to 2026

In this study, the effect of using bio-inspired surface texturing as a technique to further enhance the efficiency of a single Plate Fin Heat Exchanger (PFHX) was investigated experimentally. By using biomimicry across disciplines, the denticle, which is a body adaptation from shark skin for enhanced hydrodynamics, was identified as a surface texture to be used on the fin of a PFHX. A smooth NACA 63-015 PFHX (HX0) was used as baseline for thermo-hydraulic performance comparisons. Initially, three PFHXs (HX1, HX2 and HX3), consisting of arrays of denticles upscaled to different scale factors, were designed and printed in ABS plastic …

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Understanding The Impact Of Trade Policy Effect Uncertainty On Firm-Level Innovation Investment: A Deep Learning Approach, Daniel Chang, Nan Hu, Peng Liang, Morgan Swink Dec 2023

Understanding The Impact Of Trade Policy Effect Uncertainty On Firm-Level Innovation Investment: A Deep Learning Approach, Daniel Chang, Nan Hu, Peng Liang, Morgan Swink

Research Collection School Of Computing and Information Systems

Integrating the real options perspective and resource dependence theory, this study examines how firms adjust their innovation investments to trade policy effect uncertainty (TPEU), a less studied type of firm specific, perceived environmental uncertainty in which managers have difficulty predicting how potential policy changes will affect business operations. To develop a text-based, context-dependent, time-varying measure of firm-level perceived TPEU, we apply Bidirectional Encoder Representations from Transformers (BERT), a state-of-the-art deep learning approach. We apply BERT to analyze the texts of mandatory Management Discussion and Analysis (MD&A) sections of annual reports for a sample of 22,669 firm-year observations from 3,181 unique …

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Optimal Route Planning Using Computer Simulation In The Context Of Distributor-To-Consumer Supply Network, Miriam Aguilera Nava Dec 2023

Optimal Route Planning Using Computer Simulation In The Context Of Distributor-To-Consumer Supply Network, Miriam Aguilera Nava

Open Access Theses & Dissertations

Effective route planning for distribution centers is a multifaceted challenge crucial tobusiness success, as it directly impacts time and cost savings while enhancing overall delivery efficiency. Oversight of proper planning can lead to problems and inefficiencies in the distribution process. Hence, this work undertakes a comparative experiment of two delivery strategies in a distributor-to-consumer supply network. While the first strategy investigates the delivery process by zip area, the second strategy considers the clustering of the areas for more streamlined delivery fulfillment. The effectiveness of the delivery process is gauged based on a set of metrics, including total distance traveled, average …

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Upcyclying Of Polyethylene Terephtalate By Addition Of Thermoplastic Elastomer, Diego Francisco Bermudez Dec 2023

Upcyclying Of Polyethylene Terephtalate By Addition Of Thermoplastic Elastomer, Diego Francisco Bermudez

Open Access Theses & Dissertations

Continual overconsumption of single-use plastics has generated challenges of solid waste management across the United States. Common plastic waste management solutions, such as landfill, have caused the migration of contaminants into the environment consequently affecting not only the health of wildlife, but also that of human beings. Alternative strategies for the handling of single-use plastic such as polyethylene terephthalate (PET), used in the food packaging industry, can ultimately help mitigate the noxious consequences of single-use plastics affecting entire ecosystems. This study demonstrates a potential avenue of materials upcycling by studying the effects of coupling PET with the thermoplastic elastomer styrene-ethylene-butylene-styrene …

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Bitcoin's Technical Foundation And Its Potential For A Decentralized And Environmentally Friendly Future, Iqtiar Md Siddique Dec 2023

Bitcoin's Technical Foundation And Its Potential For A Decentralized And Environmentally Friendly Future, Iqtiar Md Siddique

Open Access Theses & Dissertations

This research examines a systematic analysis of Bitcoin, employing a Coefficient of Variation (CV) approach to gauge its degree of decentralization. Bitcoin, an innovative decentralized digital currency, has received much attention for its potential to revolutionize traditional financial systems. This study employs the Coefficient of Variation (CV) to acquire insights into the wealth distribution and concentration among Bitcoin users. This research demonstrates how decentralized the network of Bitcoin is. The methodology uses real data on Bitcoin addresses and their holdings to compute the Coefficient of Variation (CV). This approach provides valuable insights into the ongoing discourse surrounding Bitcoin's decentralization, offering …

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Characterization Of Fcc Al-Cu-Ni-Mn-Ag High Entropy Alloy, Gina Zavala Alvarado Dec 2023

Characterization Of Fcc Al-Cu-Ni-Mn-Ag High Entropy Alloy, Gina Zavala Alvarado

Open Access Theses & Dissertations

The effect of Ag on the microstructure developed in Al-Cu-Ni-Mn alloy has been determined. The modified Al-Cu-Ni-Mn alloy by Ag addition shows the presence of three microconstituents consisting of phases rich in (1) Cu, (2) Ni, and (3) Ag. The foregoing alloys heated for 24 hours from 600 to 1000 °C show excellent oxidation resistance. Oxide formation and microstructural changes of the alloy have been characterized by elemental mapping and X-ray diffraction (XRD). Results show that the elements of Al and Mn preferentially oxidize while Cu and Ni provide oxidation resistance to the alloy. Hardness was taken on the alloy …

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Aicropcam: Deploying Classification, Segmentation, Detection, And Counting Deep-Learning Models For Crop Monitoring On The Edge, Nipuna Chamara, Geng (Frank) Bai, Yufeng Ge Dec 2023

Aicropcam: Deploying Classification, Segmentation, Detection, And Counting Deep-Learning Models For Crop Monitoring On The Edge, Nipuna Chamara, Geng (Frank) Bai, Yufeng Ge

Department of Biological Systems Engineering: Papers and Publications

Precision Agriculture (PA) promises to meet the future demands for food, feed, fiber, and fuel while keeping their production sustainable and environmentally friendly. PA relies heavily on sensing technologies to inform site-specific decision supports for planting, irrigation, fertilization, spraying, and harvesting. Traditional point-based sensors enjoy small data sizes but are limited in their capacity to measure plant and canopy parameters. On the other hand, imaging sensors can be powerful in measuring a wide range of these parameters, especially when coupled with Artificial Intelligence. The challenge, however, is the lack of computing, electric power, and connectivity infrastructure in agricultural fields, preventing …

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