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Articles 1891 - 1920 of 68800
Full-Text Articles in Entire DC Network
Learning-Enabled Methods For Optimal, Constrained, And Fault-Tolerant Robot Motion Planning, Charles L. Clark
Learning-Enabled Methods For Optimal, Constrained, And Fault-Tolerant Robot Motion Planning, Charles L. Clark
Theses and Dissertations--Electrical and Computer Engineering
Safe and efficient motion planning is a core requirement for robots operating in complex real-world environments, yet traditional model-based approaches struggle to simultaneously achieve computational efficiency, solution optimality, and the ability to handle complex constraints and potential hardware failures. This dissertation investigates how neural networks, as general purpose function approximators, can be leveraged in both traditional and novel ways to overcome these limitations and advance beyond what purely model-based methods can offer. Three distinct contributions are presented. First, a new motion planner is developed that uses ReLU neural networks to decompose the configuration space into linear cost regions, enabling existing …
Advancing Edge Intelligence: Strategies For Improving Machine Learning On Embedded Devices, Prakash Dhungana
Advancing Edge Intelligence: Strategies For Improving Machine Learning On Embedded Devices, Prakash Dhungana
Theses and Dissertations--Electrical and Computer Engineering
Artificial intelligence (AI) has demonstrated tremendous success in handling complex tasks across multiple domains, a leap largely attributed to complex deep neural network (DNN) architectures. However, the increasing demand for real-time processing, low latency, limited connectivity, and enhanced privacy necessitates edge intelligence, where computation is performed directly on resource-constrained embedded devices rather than relying on cloud infrastructures. While optimized TinyML techniques such as pruning, quantization, and neural architecture search (NAS) have made edge deployment feasible by significantly reducing computation and memory demands, achievable performance remains severely limited by hardware constraints. Furthermore, models deployed in highly dynamic real-world environments suffer from …
Cognitive Load Classification Using Functional Near-Infrared Spectroscopy, Pratham Shah
Cognitive Load Classification Using Functional Near-Infrared Spectroscopy, Pratham Shah
Theses and Dissertations (Comprehensive)
This thesis investigates the classification of cognitive load using functional near-infrared spectroscopy (fNIRS) signals recorded during an N-back working memory task. The study introduces a novel short-channel correction layer designed to suppress superficial physiological noise adaptively, addressing limitations of traditional General Linear Model (GLM) based regression. A single participant dataset comprising 69 validated sessions was analyzed using both conventional machine learning and deep learning approaches. Traditional classifiers: Linear Discriminant Analysis (LDA), Support Vector Machines (SVM), Random Forests, and Gradient Boosting were first evaluated using statistical features (mean, variance, peak, and slope). Among these, Gradient Boosting achieved the highest accuracy (55.6%), …
Taylorkan-Vit: Parameter-Efficient Vision Transformers For Medical Image Classification, Kaniz Fatema, Dr. Emad Mohammed, Dr. Sukhjit Singh Sehra
Taylorkan-Vit: Parameter-Efficient Vision Transformers For Medical Image Classification, Kaniz Fatema, Dr. Emad Mohammed, Dr. Sukhjit Singh Sehra
Theses and Dissertations (Comprehensive)
Effective and interpretable classification of medical images remains a critical challenge in computer-aided diagnosis, particularly in data-scarce and resource-constrained clinical settings where traditional deep learning models prove impractical. This study addresses the fundamental barrier to Vision Transformer adoption in medical imaging—massive parameter counts and data requirements—through a systematic two-phase methodology. Phase 1 evaluates three spline-based Kolmogorov–Arnold Network (KAN) variants to identify the optimal nonlinear approximation function for parameter-efficient medical image classification: SBTAYLOR-KAN (B-splines with Taylor series), SBRBF-KAN (B-splines with Radial Basis Functions), and SBWAVELET-KAN (B-splines with Morlet wavelets). Comprehensive experiments across brain MRI, chest X-rays, and tuberculosis datasets—without any image …
Intelligent Audio‑To‑Indian Sign‑Language And Sign‑To‑Audio Translation System Using Mediapipe, Tensorflow, Whisper And Google Tts, N. Pothanna, T. Kusuma, S. Haindavi, T. Sreeja, Shaik Shaheem Taj
Intelligent Audio‑To‑Indian Sign‑Language And Sign‑To‑Audio Translation System Using Mediapipe, Tensorflow, Whisper And Google Tts, N. Pothanna, T. Kusuma, S. Haindavi, T. Sreeja, Shaik Shaheem Taj
Mansoura Engineering Journal
Communication barriers between the Deaf community and the general public remain a persistent challenge, particularly in multilingual settings where Indian Sign Language (ISL) is the primary mode of interaction. We propose a real-time bidirectional translation framework integrating MediaPipe for hand landmark extraction, a Convolutional Neural Network (CNN) classifier built with TensorFlow/Keras for gesture recognition, OpenAI Whisper for robust multilingual speech-to-text transcription, and Google TTS for naturalistic speech synthesis. The system achieves 93% classification accuracy across 35 ISL classes (alphabets A–Z and numerals 1–9) on a dataset of 42,700 images, with macro and weighted F1-scores of 0.93. Deployed as a Flask …
Enhancing Underwater Imagery And Organism Detection Using Reinforcement Learning, K. Arul Deepa, P. Ramya, Karpaga Vinodha, Dharmaraja C
Enhancing Underwater Imagery And Organism Detection Using Reinforcement Learning, K. Arul Deepa, P. Ramya, Karpaga Vinodha, Dharmaraja C
Journal of Marine Science and Technology–Taiwan
Underwater environments pose significant challenges in assessing image quality and organism detection due to light scattering and absorption, which limits visibility and color fidelity. Existing solutions often fail to effectively address these challenges, resulting in suboptimal image quality and hindering organism identification. This paper examines the problem through a dual-focused approach: enhancing underwater images and detecting organisms using the Underwater Image Enhancement Benchmark (UIEB) dataset. The first step introduces a state-of-the-art method for image enhancement by applying reinforcement learning (RL) principles. By formulating the enhancement process as a Markov Decision Process (MDP)—where states are represented by image features and actions …
Climate Change Impacts On Hydrology In The Upper James Watershed, Imiya Mudiyanselage Chathuranika, Dalya Ismael
Climate Change Impacts On Hydrology In The Upper James Watershed, Imiya Mudiyanselage Chathuranika, Dalya Ismael
Engineering Technology Faculty Publications
Hydrological modeling of the Upper James Watershed (UJW), Virginia, is critical for predicting water availability, flood management, agriculture, ecosystem protection, and hydropower production under increasing climate change. The Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) is applied to evaluate climate change impacts on key hydrological components within the watershed. Future climate conditions were assessed for the near (NF: 2026-2050), mid (MF: 2051-2075), and far (FF: 2076-2100) periods using three Global Climate Models (GCMs) under Shared Socioeconomic Pathways SSP 2-4.5 and SSP 5-8.5. Climate data were bias-corrected using the Linear Scaling Method (LSM) and used to drive the HEC-HMS model. Results project …
Investigation Of Fine-Grain Cu And Cu Alloys For Low-Temperature Hybrid Bonding Applications, Sarabjot Singh
Investigation Of Fine-Grain Cu And Cu Alloys For Low-Temperature Hybrid Bonding Applications, Sarabjot Singh
Electronic Theses & Dissertations (2024 - present)
Hybrid bonding has emerged as a key enabler for next-generation three-dimensional (3D) integration, offering fine-pitch interconnects and improved electrical performance. However, conventional Cu–Cu hybrid bonding typically requires elevated temperatures to achieve sufficient diffusion and interface quality, posing challenges for temperature-sensitive device integration and process compatibility. This work investigates materials engineering approaches to enable low-temperature Cu–Cu bonding through both microstructure design and alloying strategies.
This work begins by examining grain refinement in Cu as a pathway to enhance diffusion through increased grain boundary density, providing efficient atomic transport without introducing additional elements. Three Cu-based systems Cu–Co, Cu–Ag, and Cu–Al were systematically …
Scalable Single-Erbium Telecom Qudits With Record Room-Temperature Quantum Coherence In Silicon-Based Nanostructures, Alexander Kaloyeros
Scalable Single-Erbium Telecom Qudits With Record Room-Temperature Quantum Coherence In Silicon-Based Nanostructures, Alexander Kaloyeros
Electronic Theses & Dissertations (2024 - present)
Advancing quantum information science demands solid-state quantum systems that maintain long quantum coherence at elevated temperatures while supporting scalable, CMOS-compatible fabrication and telecom C-band operation. No existing platform has simultaneously achieved these requirements, as state-of-the-art demonstrations of coherent control of erbium ions, with an intrinsic telecom-band optical transition, have been confined to cryogenic temperatures below < 10 K under controlled vacuum conditions. This thesis introduces a new paradigm in which materials science and engineering provides the enabling pathway to quantum coherence.
A foundry-compatible nanofabrication approach, paired with targeted materials engineering, is developed to realize a new class of CMOS-scalable quantum system: arrays of spatially isolated single-erbium-ion qudits (five-level systems) embedded in silicon-based (e.g., silicon carbide (SiC) and SiCxOy) hollow nanopillars (HNPs). Non-lithographically …
Development And Analysis Of An Embedded Hardware Platform For Low-Power Rram–Based In-Memory Computing And Neural Network Applications, Jeelka Solanki
Development And Analysis Of An Embedded Hardware Platform For Low-Power Rram–Based In-Memory Computing And Neural Network Applications, Jeelka Solanki
Electronic Theses & Dissertations (2024 - present)
Conventional computing architectures are based on repeated data transfer between memory and the compute unit; however, artificial neural network applications rely on data-intensive vector-matrix multiplication as a mathematical operation, where data movement from memory to compute processor results in increased power consumption and reduced performance. Possible solutions to this problem include in-memory computing, which addresses the data transfer bottleneck by computing directly within the memory. To demonstrate the potential of this approach, our research group fabricated hafnium oxide-based resistive random-access memory (RRAM) arrays using a 65nm CMOS technology for in-memory compute operations. This work demonstrates the design and development of …
Molecular Diffusion In Chemically Amplified Resists For Euv Lithography, Eshan Dilina Thilakarathna
Molecular Diffusion In Chemically Amplified Resists For Euv Lithography, Eshan Dilina Thilakarathna
Electronic Theses & Dissertations (2024 - present)
Photolithography is a critical manufacturing step in high-volume manufacturing (HVM) of semiconductor devices, where a photoresist layer is used to transfer nanoscale patterns onto the underlying stack materials. As the microelectronics industry continues to move toward smaller node sizes, driven by Moore's Law. As a result, the tolerances for photoresist performance have become increasingly demanding, which necessitates simultaneous improvements in resolution, defectivity, and roughness. At advanced nodes, these performance limitations are governed by the fundamental stochastic nature of the photochemical processes occurring within the resist film itself, rather than the optical or tool-level constraints. Photon shot noise, the statistical distribution …
De Novo Protein Binding To Zinc Oxide Through Biomineralization Pathways, Jean-Mark A. Francis
De Novo Protein Binding To Zinc Oxide Through Biomineralization Pathways, Jean-Mark A. Francis
Theses and Dissertations
De novo proteins are structurally distinct from proteins found in nature and thus capable of having their amino acid sequence modified to accomplish tasks such as increasing protein-nanoparticle binding without unfolding or decomposing. Zinc Oxide nanoparticles are functionally distinct from their bulk counterparts and are widely used as semiconductors in a variety of fields such as medicine and agriculture. With demand for these nanoparticles increasing, environmentally sustainable methods of Zinc Oxide nanoparticle synthesis are being investigated as an eco-friendly alternative to currently utilized but environmentally hazardous chemical and physical techniques. This research investigates the binding characteristics between Zinc Oxide nanoparticles …
Regulation Of Tgf-Β1–Induced Epithelial–Mesenchymal Transition By Integrin Inhibition, Wesam Elhawabri
Regulation Of Tgf-Β1–Induced Epithelial–Mesenchymal Transition By Integrin Inhibition, Wesam Elhawabri
Theses and Dissertations
Epithelial–mesenchymal transition (EMT) is a critical process underlying cancer progression, fibrosis, and tissue remodeling, characterized by coordinated changes in cell morphology, nuclear structure, and extracellular matrix (ECM) organization. Transforming growth factor beta 1 (TGF-β1) is a primary inducer of EMT; however, the extent to which integrin-mediated signaling and ECM remodeling regulate these structural changes remains incompletely understood. In this study, we quantitatively investigated EMT-associated remodeling in A549 lung carcinoma cells and MCF10A epithelial cells following TGF-β1 stimulation. Cells were cultured on ECM-coated substrates and treated with TGF-β1 in the presence or absence of integrin-targeting inhibitors (ATN-161, 28-G11, and STX-100). Im …
Proof Of Recovery: A Model To Enhance Data Integrity In Data Management Systems, Gustaf Barkstrom
Proof Of Recovery: A Model To Enhance Data Integrity In Data Management Systems, Gustaf Barkstrom
Theses and Dissertations
Businesses lose millions of dollars every year when they can’t restore data from backups. Research shows that Disaster Recovery Plan (DRP) testing is not conducted frequently enough, nor are records maintained that demonstrate full data recovery from backups. This work introduces a design science artifact called PRTOK that aims to increase DRP testing. The design science artifact is a software solution that integrates with Data Management Systems (DMS)
such as iRODS and DSpace, and can work with formats such as HDF5 and BagIt. Proof-of- recovery records, or tokens, are recorded in a replicated, resilient, and indelible proof-of- authority blockchain data …
Nanomagnet Based Straintronic Devices For Unconventional Computing: Simulation And Performance Analysis, Rahnuma Rahman
Nanomagnet Based Straintronic Devices For Unconventional Computing: Simulation And Performance Analysis, Rahnuma Rahman
Theses and Dissertations
Nanomagnetic devices are of great interest in digital hardware because of their non-volatility and dynamic ability to change magnetization but suffer from high switching error rates and temperature sensitivity. Magnetostrictive nanomagnets that utilize strain to switch between stable magnetization states encoding bit information are of interest since they are extremely energy efficient as piezoelectric layers can be used to rotate magnetization that have switching energies in the range of attojoules. Their stochasticity can also be useful in probabilistic, analog, neuromorphic, and collective computing systems, where occasional switching errors are not devastating. The dissertation extends spintronics beyond conventional computing schemes by …
Ontological Runtime Monitoring For Mission Engineering, Alexander R. Will
Ontological Runtime Monitoring For Mission Engineering, Alexander R. Will
Theses and Dissertations
The advent of the Urban Air Mobility (UAM) concept will bring low-altitude aviation to civilians through passenger and cargo transport. However, the prospective vehicles in UAM studies are predominantly autonomous, raising questions about their efficacy and stability in densely populated urban areas. At the same time, extensive work has been performed to define a new branch of systems engineering that focuses on runtime behavior, synchronization, communication, and task allocation.This field is known as "mission engineering". Mission engineering has been deployed in military scenarios to model human-autonomy cooperation. By applying the concepts from this field to UAM, full systems-of-systems can be …
Empirical Dynamical Modeling Of Cortico-Hippocampal Information Transfer During Memory Encoding, Sam Y. Cole
Empirical Dynamical Modeling Of Cortico-Hippocampal Information Transfer During Memory Encoding, Sam Y. Cole
Theses and Dissertations
Understanding how brain dynamics support successful memory formation remains a central challenge in neuroscience. This dissertation applies tools from empirical dynamical systems theory to investigate the neural mechanisms underlying episodic encoding, with a focus on cortico-hippocampal interactions. Using stereoelectroencephalography (sEEG) data recorded during a delayed free recall of word lists task, this work reveals nonlinear, state-dependent shifts in directed information flow between cortex and hippocampus that distinguish successful from unsuccessful encoding. To further characterize these dynamics, state-space trajectories are reconstructed using time-delay embedding and recurrence-based methods, and features derived from these trajectories are used to classify memory outcomes. By integrating …
Modeling Of Laser-Produced Plasma Plumes: Expansion, Chemistry, And Thin-Film Deposition, Edmund Tsiri Semaha, Edmund Tsiri Semaha
Modeling Of Laser-Produced Plasma Plumes: Expansion, Chemistry, And Thin-Film Deposition, Edmund Tsiri Semaha, Edmund Tsiri Semaha
Theses and Dissertations
Abstract
Laser-assisted material processing involves coupled plasma expansion, chemical reactions, and particle transport that govern the quality of thin-film deposition. This dissertation presents a comprehensive computational investigation of these processes using the OpenFOAM framework. First, the performance of the twoPhaseEulerFoam (tPEF), rhoCentralFoam (rCF), and sonicFoam (sF) solvers is evaluated for modeling laser-produced plasma plume expansion under atmospheric conditions, demonstrating that tPEF accurately captures shock-wave propagation, hydrodynamic behavior, and multispecies interactions. Building on this validation, the reactingFoam (rF) solver is employed to investigate the chemistry of aluminum plasma expanding into an air environment (Al–N₂–O₂). The model incorporates appropriate thermodynamic, transport, and …
Effect Of Ionic Strength On Gelation Time And Strength Of Amps-Based Polymer Gels, Maryam Sharifi Paroushi, Xuyang Tian, Baojun Bai, Thomas P. Schuman, Yin Zhang, Mingzhen Wei
Effect Of Ionic Strength On Gelation Time And Strength Of Amps-Based Polymer Gels, Maryam Sharifi Paroushi, Xuyang Tian, Baojun Bai, Thomas P. Schuman, Yin Zhang, Mingzhen Wei
Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works
Polymer gel treatment has been widely applied for improving sweep efficiency and controlling excessive water and gas production. Their performance depends on gelation time and final gel strength. In most studies, brine salinity is used to describe the effect of formation water on gel behavior. However, changing salinity also changes ionic strength and ion composition at the same time. Because of this coupling, it is difficult to identify the mechanisms controlling gelation, which has led to inconsistent trends in the literature. Increasing salinity has been reported to either slow or accelerate gelation and to weaken or strengthen gels depending on …
Investigation Of Succinylated Zwitterionic Polyethylenimine/Dna Complexes: Performance In Serum, Internalization, And Intracellular Fate, Levi Lampe
Theses and Dissertations--Chemical and Materials Engineering
Gene therapy has promised to revolutionize medicine since the earliest clinical trials, but a lack of delivery methods that are both safe and efficient has hampered progress. Gene therapy with viral vectors is effective at delivering nucleic acids to cells, but is associated with dangerous immunogenic responses and cancer-causing insertions into the genome. Viral vectors are also among the most prohibitively costly therapeutics in medicine. Polymeric vectors avoid these dangers and are made from inexpensive, off-the- shelf materials, but have been hindered by poor efficiency compared to viral vectors.
A benchmark polymer for in vitro nucleic acid delivery has been …
Anaerobic Digestion Of Food Waste Components: Modeling Biogas Production, Opeyemi E. Adelegan
Anaerobic Digestion Of Food Waste Components: Modeling Biogas Production, Opeyemi E. Adelegan
Civil Engineering Dissertations
Food waste constitutes the single largest component of municipal solid waste landfilled in the United States — approximately 22% of 292.4 million tons generated in 2018 — and its anaerobic decomposition releases methane, a greenhouse gas with global warming potential approximately 27–30 times that of carbon dioxide over a 100-year horizon (IPCC, 2021). Anaerobic digestion (AD) offers an alternative management pathway that recovers energy and produces nutrient-rich digestate, but AD performance varies by as much as five-fold across food waste streams (130–630 m3 CH4 per Mg VS added), and existing predictive tools either treat food waste as a …
Beyond The Square Pulse: Waveform Shape, Eeg Correlates, And The Pursuit Of Natural Sensation In Tens, Jason Whitson
Beyond The Square Pulse: Waveform Shape, Eeg Correlates, And The Pursuit Of Natural Sensation In Tens, Jason Whitson
Honors Undergraduate Theses
This study investigates the relationship between electrical stimulus characteristics of shape and charge on evoked sensations and electroencephalogram (EEG) data during multi-waveform transcutaneous electrical nerve stimulation (TENS) of the median nerve. Neuromodulation methods have traditionally had little control over the location and quality of their associated evoked sensation (e.g., electric, vibration, touch). This experiment utilized five unique stimulus waveforms during TENS stimulation. EEG data were collected concurrently to provide an introductory objective measure of the neural responses underlying these sensory changes. Eleven participants completed three tasks (thresholding, super-threshold stimulation, two-alternative forced choice) using a two-electrode TENS approach. Stimulus waveforms were …
Timing And Stability Of Uav Operations In Smart City Environments: Experimental Analysis And Design Implications, Rabia Ipek Yasar
Timing And Stability Of Uav Operations In Smart City Environments: Experimental Analysis And Design Implications, Rabia Ipek Yasar
Theses and Dissertations
This thesis investigates the deployment and performance of unmanned aerial vehicles (UAVs) within the Virginia Commonwealth University Open Cyber City (OCC) testbed. The study focuses on evaluating real-time indoor positioning performance using the Crazyflie drone platform. High-precision position measurements are obtained using the Vicon motion capture system, enabling analysis of the latency between the drone’s actual position and the system-reported position. In a closed-loop control system, the time difference between the position measurement and the application of the control command is called the system delay. Both stationary (hovering) and trajectory-following experiments are conducted to evaluate system performance. Communication delays in …
Utilizing Coal For Mesophase Pitch-Based Carbon Fiber Production: Precursors, Processes, And Progress, Christina M. Thompson
Utilizing Coal For Mesophase Pitch-Based Carbon Fiber Production: Precursors, Processes, And Progress, Christina M. Thompson
Theses and Dissertations--Chemistry
Graphitic materials possess unique properties due to the unique combination of layered crystalline structure and carbon’s low atomic weight. High performance carbon fiber is one such example, displaying exceptional strength-to-weight ratios, stiffness, and thermal and chemical resistance. These properties render high performance carbon fiber a critical structural reinforcement material in the manufacture of composites across various industries, such as for automotive and aerospace applications. However, balancing fiber performance with precursor and processing costs remains a challenge. As alternative carbonaceous feedstocks are explored, coal has gained interest for utilization in graphitic products as a relatively abundant and low-cost source of aromatic …
Development And Characterization Of Flat And Flexible Rebco Cables For High-Field Accelerator Magnets, Emily Romancew
Development And Characterization Of Flat And Flexible Rebco Cables For High-Field Accelerator Magnets, Emily Romancew
Graduate Research Theses & Dissertations
High-Temperature Superconducting (HTS) materials are at the forefront of innovation for fundamental particle physics. The next generation of particle accelerators aims to explore higher mass particles and is dependent on the ability to achieve higher fields in the 20–30 T range to keep machine size within a practical footprint. Current magnet technology relies on low-temperature superconductors (LTS) such as NbTi and Nb₃Sn, which are limited to fields of approximately 8–16 T, while high-temperature superconductors (HTS), particularly Rare-Earth Barium Copper Oxide (REBCO), offer a promising pathway toward higher-field magnets due to their ability to carry large currents at elevated magnetic fields. …
An Integrated Pull System Framework For Disassembly Industries: Bridging The Supply-Demand Mismatch In Duck Meat Processing, Hongchao Yu
Graduate Research Theses & Dissertations
Disassembly-based production systems, such as duck meat processing, face inherent operational challenges due to one-to-many production structures, short product shelf life, and volatile customer demand. A single carcass must be processed into multiple products at largely fixed biological ratios, while demand varies across products and over time. This supply-demand mismatch frequently leads to simultaneous surplus and shortage, resulting in unstable shipment schedules, excess inventory, and unavoidable waste. Traditional order-driven pull systems typically respond to orders independently and are limited in their ability to coordinate these interrelated effects.
This dissertation develops an integrated pull system framework for perishable disassembly processes, using …
Feasibility Of Corn Stover For Biogas Production In Northwestern Illinois: A Case Study Of Jo Daviess And Carroll Counties, Anthony Amotoe-Bondzie
Feasibility Of Corn Stover For Biogas Production In Northwestern Illinois: A Case Study Of Jo Daviess And Carroll Counties, Anthony Amotoe-Bondzie
Masters Theses
The growing demand for renewable energy and sustainable waste management has intensified interest in agricultural residues such as bioenergy feedstocks. This study evaluated the feasibility of converting corn stover into biogas through anaerobic digestion (AD) in Jo Daviess and Carroll Counties, Illinois, with consideration of the Savanna Industrial Park as a potential centralized processing hub. Although corn stover represents one of the largest biomass resources in the United States, this research identifies a critical gap between theoretical availability and practically recoverable feedstock. Using a mixed-methods framework, the study integrates biomass quantification, methane yield modeling, economic analysis, and policy assessment. Results …
Design And Validation Of A Novel Patterned Microfluidic Culture Platform For Hipsc-Cm Maturation, Anisia Gabriela Țiplea
Design And Validation Of A Novel Patterned Microfluidic Culture Platform For Hipsc-Cm Maturation, Anisia Gabriela Țiplea
Dartmouth College Master’s Theses
Adult cardiomyocytes (CMs) are among the most challenging cells to culture in vitro, given their poor adherence to plastic culture wells and poor maturation outside the native extracellular matrix (Narkar et al., 2022). Human induced pluripotent stem cell-derived CMs (hiPSC-CMs) offer a viable alternative to study heart development and disease progression. While not comparable to adult CMs in their maturity (Narkar et al., 2022), they mimic the clinical phenotypes of heart failure and are more feasible to culture. Nevertheless, hiPSC-CMs require specialized culture conditions that cannot be achieved with 2D static culturing, which fail to replicate native tissue environments (X. …
Lean Service System Optimization In U.S. Automotive Maintenance Centers: A Time Study And Simulation-Based Approach To Reducing Service Cycle Time And Increasing Efficiency, Rakibul Hasan Sarker
Lean Service System Optimization In U.S. Automotive Maintenance Centers: A Time Study And Simulation-Based Approach To Reducing Service Cycle Time And Increasing Efficiency, Rakibul Hasan Sarker
All Graduate Theses, Dissertations, and Other Capstone Projects
The primary objective of this study is to measure the current service time at a U.S. automobile service center, with the aim of reducing waste and optimizing service operations through time study and simulation modeling. Inefficiencies in those service centers increase service time and labor costs, reduce service quality, and reduce workshop productivity, thereby increasing customer waiting time. In this study, real-world shop floor data were collected from a single service center, namely Jiffy Lube. Over the course of ten working days, 205 vehicle data points were acquired. Service time, bay time, and overall process time were computed and examined …
The Crowdfunding Paradox In Crisis: Rising Funder Demand Vs. Declining Entrepreneur Supply, Dan Liu, Guangzhi Shang, Cynthia Fan Yang
The Crowdfunding Paradox In Crisis: Rising Funder Demand Vs. Declining Entrepreneur Supply, Dan Liu, Guangzhi Shang, Cynthia Fan Yang
Journal of International Technology and Information Management
This study investigates how the crowdfunding marketplace responds to major crises, focusing on behavioral shifts among funders and entrepreneurs. Results show a dual impact on platform dynamics. On the demand side, funders become more engaged, with notable increases in the number of backers, average contributions, and total pledge amounts. This heightened activity suggests stronger altruistic motivations, as individuals view crowdfunding as a way to support others during difficult times. On the supply side, however, entrepreneurs act more cautiously, leading to a decline in new project launches. This drop likely reflects increased risk aversion and uncertainty as creators navigate volatile conditions. …