3d Printed Microfluidic Fabrication Methodology, Characterization, Mechanical Design, And Applications In Electrostatic Artificial Muscles And Benthic Microbial Fuel Cells, Terak B. Hornik
Master's Theses
The fabrication of microfluidic devices often requires specialized methods. The development of these methods requires careful characterization and understanding of the processes involved. Using primarily PolyJet 3D printing technology, microfluidics offers a wide scope of applications such as microfluidic benthic microbial fuel cells (MBMFCs) and electrostatic artificial muscles. MBMFCs benefit from the confinement of the microbes resulting in close proximity between the electrode and the organisms. Using a modular design called the Sponge, assembly and upscaling is possible. Electrostatic artificial muscles benefit from a microfluidic approach due to the non-linearity of electrostatic attraction creating disproportionate benefits when miniaturized. When designed …
Joint Modeling Of Degradation Signals And Time-To-Event Data For The Prediction Of Remaining Useful Life,
2024
Georgia Institute of Technology
Joint Modeling Of Degradation Signals And Time-To-Event Data For The Prediction Of Remaining Useful Life, Sebastian Brumm, Erik Linstead, Junde Chen, Narayanaswamy Balakrishnan, Yuxin Wen
Engineering Faculty Articles and Research
Accurate prediction of remaining useful life (RUL) for in-service systems plays an important role in ensuring efficient operation of industrial equipment and in preventing unexpected equipment failures. In this paper, we present a prognostic framework for real-time RUL prediction based on joint modeling of both degradation signals and time-to-event data. The proposed model employs a change point-based general path model to capture signal non-linearity and Neural network (NN) based Cox model to link the time-to-event data with the estimated degradation trend. An empirical two-step scheme for hyperparameter estimation is proposed to enhance prognostic accuracy. Furthermore, an efficient Bayesian model updating …
Long-Distance Photon-Mediated And Short-Distance Entangling Gates In Three-Qubit Quantum Dot Spin Systems,
2024
Chapman University
Long-Distance Photon-Mediated And Short-Distance Entangling Gates In Three-Qubit Quantum Dot Spin Systems, Nooshin M. Estakhri, Ada Warren, Sophia E. Economou, Edwin Barnes
Engineering Faculty Articles and Research
Superconducting resonator couplers will likely become an essential component in modular semiconductor quantum dot (QD) spin qubit processors, as they help alleviate crosstalk and wiring issues as the number of qubits increases. Here, we focus on a three-qubit system composed of two modules: a two-electron triple QD resonator coupled to a single-electron double QD. Using a combination of analytical techniques and numerical results, we derive an effective Hamiltonian that describes the three-qubit logical subspace and show that it accurately captures the dynamics of the system. We examine the performance of short-range and long-range entangling gates, revealing the effect of a …
M3t-Lm: A Multi-Modal Multi-Task Learning Model For Jointly Predicting Patient Length Of Stay And Mortality,
2024
Chapman University
M3t-Lm: A Multi-Modal Multi-Task Learning Model For Jointly Predicting Patient Length Of Stay And Mortality, Junde Chen, Qing Li, Feng Liu, Yuxin Wen
Engineering Faculty Articles and Research
Ensuring accurate predictions of inpatient length of stay (LoS) and mortality rates is essential for enhancing hospital service efficiency, particularly in light of the constraints posed by limited healthcare resources. Integrative analysis of heterogeneous clinic record data from different sources can hold great promise for improving the prognosis and diagnosis level of LoS and mortality. Currently, most existing studies solely focus on single data modality or tend to single-task learning, i.e., training LoS and mortality tasks separately. This limits the utilization of available multi-modal data and prevents the sharing of feature representations that could capture correlations between different tasks, ultimately …
Predictive Residual Neural Networks For Optical Trapping Of Small Particles,
2024
Chapman University
Predictive Residual Neural Networks For Optical Trapping Of Small Particles, Nasim Mohammadi Estrakhri, Ponthea Zahraii, Saman Kashanchi, Nooshin M. Estakhri
Engineering Faculty Articles and Research
Optical tweezers provide a non-contact method to trap, move, and manipulate micro- and nano-sized objects. Using properly designed dielectric and plasmonic nanostructure configurations, optical tweezers have been tailored to create stable and precise trapping for nanoscale objects. Recent advances in numerical optimization techniques allow further enhancement in nanoscale optical traps through inverse optimization of such configurations. One of the main challenges in such optimization approaches is the time-consuming nature of full-wave simulation of nanostructures and postprocessing steps to extract optical forces. To address this challenge, we introduce a surrogate solver based on residual neural networks that can accurately predict the …
Distributed Multi-Robot Localization And Coordination Framework For Mobile Robots,
2024
California Polytechnic State University, San Luis Obispo
Distributed Multi-Robot Localization And Coordination Framework For Mobile Robots, Dmitri Dobrynin, Indigo T. Garcia
College of Engineering Summer Undergraduate Research Program
This project aims to develop an experimental framework for multiple mobile robots, both in simulation and real-world hardware, using ROS 2 as the primary operating system. Utilizing TurtleBot 3 platforms, the team will establish a robust setup that enables tasks such as distributed localization, autonomous navigation, path planning, and formation control for mobile robots. Leveraging simulation environments like Gazebo, the project will replicate real-world setups in a simulated environment for testing and development. All tasks, communication, and sensor integration will be implemented using ROS 2, ensuring seamless coordination and interoperability among the robots. The project involves integrating various sensors and …
Review Of Hardware Implementation For The Two-Wheeled Self-Balancing Robot,
2024
College of Computer Science and Information Technology, Kerbala University, Kerbala, Iraq
Review Of Hardware Implementation For The Two-Wheeled Self-Balancing Robot, Ghaidaa Hadi Salih Elias
Al-Bahir
The working principle of a self-balancing robot is similar to that of an inverted pendulum, with the mobile robot's controller playing a crucial part in both self-balancing and stabilization. It is the kind that constantly modifies itself to keep balance when it rides on two wheels. This review will center on the basic construction of the suggested robot, summarize the recent studies relative to control methods and the building of the two-wheeled self-balancing robot, and discuss the outcomes of control experiments conducted on hardware systems. It will assist researchers in building and designing two-wheeled mobile robots in the future.
Multimodal Mixing Convolutional Neural Network And Transformer For Alzheimer’S Disease Recognition,
2024
Chapman University
Multimodal Mixing Convolutional Neural Network And Transformer For Alzheimer’S Disease Recognition, Junde Chen, Yun Wang, Adnan Zeb, M. D. Suzauddola, Yuxin Wen
Engineering Faculty Articles and Research
Early recognition of Alzheimer’s disease (AD) and its precursor state, mild cognitive impairment (MCI), is pivotal in interrupting the progression of the disease and providing suitable treatment. Recent development in deep learning techniques has drawn great research attention for improving the efficacy of AD recognition. However, numerous current methods solely utilize data from a single auxiliary domain, limiting their ability to harness valuable intrinsic insights from multiple domains. To cope with the challenge, this paper is devoted to establishing an innovative multimodal medical data fusion model, termed as MMDF, to perform Alzheimer’s disease recognition. Multimodal data including clinical records and …
Fpca-Setcn: A Novel Deep Learning Framework For Remaining Useful Life Prediction,
2024
Chapman University
Fpca-Setcn: A Novel Deep Learning Framework For Remaining Useful Life Prediction, Junde Chen, Yuxin Wen, Xuxue Sun, Adnan Zeb, Mohammad Saleh Meiabadi, Sasan Sattarpanah Karganroudi
Engineering Faculty Articles and Research
The accurate prediction of remaining useful life (RUL) can serve as a reliable foundation for equipment maintenance, thereby effectively reducing the incidence of failure and maintenance costs. In this study, a novel deep learning (DL) framework that incorporates functional principal component analysis (FPCA) and enhanced temporal convolutional network (TCN) is proposed for RUL prediction. Precisely, FPCA is employed to capture the changing patterns in multistream degradation trajectories. Subsequently, the reconstructed signals from FPCA are fed into a convolutional block for extracting deep-level features. An enhanced squeeze-and-excitation (ESE) block is then incorporated into the network for adaptive feature recalibration, enhancing the …
Engineering Ecological Analysis Of Rise Of Huawei’S Harmonyos And Its Implications,
2024
School of Humanities, University of Chinese Academy of Sciences, Beijing 100049, China; China State Railway Group Co. Ltd., Beijing 100080, China
Engineering Ecological Analysis Of Rise Of Huawei’S Harmonyos And Its Implications, Dazhou Wang, Yishi Lyu, Zhihuan Fu
Bulletin of Chinese Academy of Sciences (Chinese Version)
This study aims to explore the rise of the Harmony operating system from the perspective of engineering ecology. In the face of increasingly fierce global technological competition, Huawei, as a leading Chinese information technology enterprise, launched its self-developed HarmonyOS and has progressively built the Harmony ecosystem, providing foundational support for the development of all sectors. The development path of HarmonyOS can be divided into three main phases based on its strategic goals, technological and product characteristics, and ecological construction: the initial phase, the acceleration phase, and the transformation phase. It is revealed that, throughout this development, various construction strategies for …
Esd-Robust 4h-Sic Low-Voltage Cmos Technology Development For High Temperature,
2024
University of Arkansas, Fayetteville
Esd-Robust 4h-Sic Low-Voltage Cmos Technology Development For High Temperature, Hui Wang
Graduate Theses and Dissertations
This dissertation explores the development and optimization of electrostatic discharge (ESD)-robust, low-voltage CMOS technology using 4H-silicon carbide (SiC) tailored for high-temperature applications, addressing the critical need for reliable semiconductor devices in harsh environmental conditions. The advent of SiC as a semiconductor material offers significant advantages over traditional silicon (Si) in harsh environments, including higher thermal conductivity, greater electron mobility, and improved electrical characteristics at elevated temperatures. This research explores the integration of 4H-SiC into CMOS technology to enhance device reliability and performance in extreme conditions such as those found in aerospace, automotive, and energy sectors. The study begins with a …
Convex Approach To Data-Driven Optimal Control With Safety Constraints Using Linear Transfer Operator,
2024
Clemson University
Convex Approach To Data-Driven Optimal Control With Safety Constraints Using Linear Transfer Operator, Joseph Raphel Moyalan
All Dissertations
This thesis is concerned with the data-driven solution to the optimal control problem with safety constraints for a class of control-affine nonlinear systems. Designing optimal control satisfying safety constraints is a problem of interest in various applications, including robotics, power systems, transportation networks, and manufacturing. This problem is known to be non-convex. One of this thesis's main contributions is providing a convex formulation to this non-convex problem. The second main contribution is providing a data-driven framework for solving the control problem with safety constraints. The linear operator theoretic framework involving Perron-Frobenius and Koopman operators provides the convex formulation and associated …
Reinforcement Learning Assisted Communication Resources Optimization In Advanced Air Mobility.,
2024
University of Louisville
Reinforcement Learning Assisted Communication Resources Optimization In Advanced Air Mobility., Ruixuan Han
Electronic Theses and Dissertations
Advanced air mobility (AAM), which envisages a safe and efficient aviation transportation system, has drawn significant attention to support the increasing mobility demand in metropolitan areas. Communication services for AAM aerial vehicles (AVs) are crucial for ensuring flight safety. This dissertation explores three research topics on communication resource allocation problems in AAM applications. The first topic, addressed in Chapter II, investigates the joint velocity selection and spectrum allocation problem for AAM applications to enhance spectrum utilization efficiency (SUE). In the AAM scenario, multiple AVs travel along predefined paths for passenger and cargo deliveries. Given that AAM aims to provide fast …
Heat And Mass Transfer Characteristics During Vacuum Drying Of Wood,
2024
Mechanical engineering,Mansoura University
Heat And Mass Transfer Characteristics During Vacuum Drying Of Wood, Mohamed Salah Elmetwaly, Lotfy Hassan Rabie Saker, Mohamed Sameh Salem
Journal of Engineering Research
The properties affecting the characteristics of heat and mass transfer during vacuum drying of wood are studied in this paper. The experimental work is carried out in 0.0365 m3 test rig vacuum dryer. The drying chamber dimensions are 0.5 m long and 0.305 m diameter carbon steel cylinder. This drying chamber is internally coated with epoxy paint, also this chamber is detachable closing caps at both ends meaning welded at one end and bolted at the other end to facilitate loading and unloading of the specimen. Two stainless steel heat exchanger plates with dimensions 0.3 m length, 0.15 m …
Balloon Borne Gps-Enabled Radiosondes That Enable Simultaneous Multi-Point Atmospheric Sensing With A Single Ground Station,
2024
Embry-Riddle Aeronautical University
Balloon Borne Gps-Enabled Radiosondes That Enable Simultaneous Multi-Point Atmospheric Sensing With A Single Ground Station, Peter A. Ribbens
Doctoral Dissertations and Master's Theses
Radiosondes are balloon borne atmospheric instruments that are a critical tool for understanding dynamics in the lower layers of the atmosphere. The low-cost radiosondes developed in the Space and Atmospheric Instrumentation Lab have been further developed to improve the system's use as a science-quality atmospheric instrument that is unique in its ability to simultaneously track multiple sondes with a single ground station. Sensors to measure temperature and pressure were added to improve measurements of the atmospheric state. A printed circuit board shield and 3D-printed shell were designed to make mass manufacturing possible. A thermistor-based temperature sensor was developed and tested …
Creative Insights Into Motion: Enhancing Human Activity Understanding With 3d Data Visualization And Annotation,
2024
Chapman University
Creative Insights Into Motion: Enhancing Human Activity Understanding With 3d Data Visualization And Annotation, Isaac Browen, Hector M. Camarillo-Abad, Franceli L. Cibrian, Trudi Di Qi
Engineering Faculty Articles and Research
This paper presents a novel 3D system for human motion analysis - Motion Data Visualization and Annotation (MoViAn). Designed to provide a comprehensive visual representation of 3D human motion data, MoViAn incorporates detailed visualization of gaze direction, hand movements, and object interactions, alongside an interactive interface for efficient data annotation. A user study involving eight participants indicates that MoViAn enables users to thoroughly explore and annotate human motion data, with System Usability Scale (SUS) results demonstrating a satisfactory usability level. The contribution of this paper lies in the development of an interactive and usable data analytics tool aimed at deepening …
Evaluating Visual Dependence In Postural Stability Using Smartphone And Stroboscopic Glasses,
2024
Chapman University
Evaluating Visual Dependence In Postural Stability Using Smartphone And Stroboscopic Glasses, Brent A. Harper, Michael Shiraishi, Rahul Soangra
Physical Therapy Faculty Articles and Research
This study explores the efficacy of integrating stroboscopic glasses with smartphone-based applications to evaluate postural control, offering a cost-effective alternative to traditional forceplate technology. Athletes, particularly those with visual and visuo-oculomotor enhancements due to sports, often suffer from injuries that necessitate reliance on visual inputs for balance—conditions that can be simulated and studied using visual perturbation methods such as stroboscopic glasses. These glasses intermittently occlude vision, mimicking visual impairments that are crucial in assessing dependency on visual information for postural stability. Participants performed these tasks under three visual conditions: full vision, partial vision occlusion via stroboscopic glasses, and no vision …
Autonomous Apple Harvester Robot,
2024
California Polytechnic State University, San Luis Obispo
Autonomous Apple Harvester Robot, Jack Ryan Cline, Tyus Green, Devon Woolston
Electrical Engineering
As agricultural demands rise and manual labor costs increase, there has become a dire need to automate apple harvesting. However, the precision and speed necessary for cost-efficient apple harvesting pose a significant challenge for robotic automation. To maintain cost-effective production, a harvester must be able to operate fast enough and long enough to compete with human labor. It must also be able to navigate and traverse apple orchards autonomously and pick apples without damaging the fruit or tree. This project presents an apple harvesting robot that uses a Mask R-CNN vision system with an RGB-D camera to detect the location …
Cal Poly Gen 2 Battlebot Electrical System,
2024
California Polytechnic State University, San Luis Obispo
Cal Poly Gen 2 Battlebot Electrical System, Kelvin C. Villago
Electrical Engineering
BattleBots is a popular robot combat sport where engineers from all over the world design and construct a robot with the aim to disable or impair the opposing robot. The Cal Poly Gen 2 BattleBot aims to complete a robot from scratch with hopes to compete in the official competition. This report focuses on the electronic design behind the robot, specifically the printed circuit board (PCB) and component selection. The design process of this project involved choosing specific motors and microcontrollers based on cost, efficiency, and benefits with the end goal of a complete printed circuit board (PCB). Brushed motors …
Machine Learning For Graph Algorithms And Representations,
2024
Dartmouth College
Machine Learning For Graph Algorithms And Representations, Allison Gunby-Mann
Dartmouth College Ph.D Dissertations
This thesis explores a variety of common graph theoretic problems from a machine learning perspective. The topics covered include fundamental network problems such as distance approximation, distance sensitivity, community detection, cross-network alignment, and graph embedding dimension reduction. These projects are unified by the theme of machine learning on graphs, graph embeddings, and representations of graphs.
