Digital Commons Network^™

Exploring Social Networks: An Analysis Of Intra-Organizational Networks, Ximeng Chen, Yiding Cao, Jiachen Liu, Danushka Bandara, Hiroki Sayama

Northeast Journal of Complex Systems (NEJCS)

This research investigates intra-organizational social networks by employing network science methods, aiming to provide actionable insights for both managers and employees. Using datasets from the Colorado Index of Complex Networks (ICON), this study examines four intra-organizational networks from a consulting firm and a research team, focusing on advice requests and skill awareness. The analysis includes network topology, degree distribution, community detection, correlation between communities and node attributes, maximal clique detection, and multilayer network analysis. The findings reveal that intra-organizational networks are intricate and significantly impact organizational efficiency and individual career development. Key insights include the importance of mid-level employees in …

Nanofiber-Hydrogel Composite Scaffold Fabrication Methods For Peripheral Nerve Regeneration, Jacob Lee Carter

Theses and Dissertations

Nerve graft conduits (NGCs) are a rapidly advancing field for treating peripheral nerve injuries that aim to guide the growth of regenerating axons across damaged gaps. A more effective NGC can be manufactured by combining the use of nanofibers to act as guidewires within a 3-D hydrogel that imitates the extracellular matrix of nerve tissue. Several methods have been developed to embed aligned nanofibers in an ordered architecture within a hydrogel matrix. The first method involves layer-by-layer additive manufacturing to create NGCs with rows of polycaprolactone (PCL) nanofibers surrounded by a gelatin methacrylate (GelMe) hydrogel in a 3-D structure. A …

A Multimodal Residual Spatial-Temporal Fusion Model Based On Automatic Sleep Classification, Yecai Guo, Shuang Tong

Journal of System Simulation

Abstract: Highly accurate sleep staging plays a crucial role in correctly assessing sleep conditions. Aiming at the problem that the existing convolutional network cannot obtain the topological characteristics of physiological signals, a sleep staging algorithm based on multi-modal residual spatio-temporal fusion is proposed. Time-frequency images and spatio-temporal images are obtained using short-time Fourier transform and adaptive map convolution, which are converted into high-dimensional feature vectors; lightweight interaction of feature information flow is realized through time-frequency feature and spatiotemporal feature extraction modules; the feature enhancement fusion module fuses feature information to outputs sleep staging results. The results show that the model …

Fine-Tuning Cesium Lead Chloride Perovskite Field-Effect Transistors For Sensing Applications: Bridging Numerical Modeling And Experimental Validation, Gehad Ali, Reem Mahmoud, Mohamed Wafeek, Motaz Yousef, Sameh O. Abdellatif

Electrical Engineering

No abstract provided.

Evolution Of Physical, Thermal, And Mechanical Properties Of Poly(Methyl Methacrylate)-Based Elium Thermoplastic Polymer During Polymerization, Swapnil S. Bamane, Prathamesh Deshpande, Sagar Patil, Marianna Maiaru, Gregory Odegard

Michigan Tech Publications

Elium-based thermoplastic composites are a key material for future use in the marine, wind energy, and automotive industries because of their recyclability and ease of manufacture. To optimize the processing of the Elium composites to yield optimal structural properties, computational process modeling can be used to relate processing parameters to residual stresses and material durability. The key ingredient for reliable and accurate process modeling is the evolution of physical, thermal, and mechanical properties during polymerization. The objective of this study is to use molecular dynamics to predict the mass density, bulk modulus, shear modulus, Young’s modulus, Poisson’s ratio, glass transition …

Integrated Environmental Vulnerability Assessment And Adaptation Strategies For Coastal Areas Under Sustainable Development, Lien-Kwei Chien, Yu-Chi Li, Chia-Feng Hsu

Journal of Marine Science and Technology–Taiwan

This research focuses on the holistic management and environmental vulnerability of coastal areas in Taiwan within the framework of sustainable development. With economic and social growth gravitating towards coastal regions, the strain on the natural environment is increasing. Therefore, discovering a balance between economic progress and environmental conservation is paramount. To decipher the vulnerability of Taiwan's coastal zones, this study first defines ‘Integrated Environmental Vulnerability of Coastal Areas.’Key vulnerability factors were identified across environmental, social, and economic dimensions. Seven core determinants were determined using the Fuzzy Delphi method: biodiversity, coastal erosion, water pollution, population density, population aging, land utilization, and …

Evalution Of The Ability To Infer Tilt Angle And Size Distributions Of Fish Using A Broadband Scientific Echosounder Based On Simulation, Jing Liu

Journal of Marine Science and Technology–Taiwan

The biological information, such as species, size, and tilt angle, is crucial for converting the echo data into biomass information in acoustic surveys. Typically, the information can be obtained through trawl net sampling or underwater camera observations. However, both methods have some limitations. To overcome these limitations, scientists have utilized inversion methods with multi-frequency and broadband echosounders to derive biological information about fish, plankton, and krill. However, evaluating the reliability and accuracy of these inversion methods has been challenging due to the difficulty in obtaining accurate biological information. In this study, a numerical simulation method was used to generate fish …

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 …

A Marine Knowledge System For Ocean Affairs: Integrating Data, Evaluating Usage, And Enabling Sustainable Marine Management, Yu-Jen Pan

Journal of Marine Science and Technology–Taiwan

This study presents the evolution and assessment of the Marine Knowledge Education System (MKES), designed to improve user acceptance among students in professional marine science courses in Taiwan. The MKES leverages real-world maritime cases from the General Coast Guard Administration and is built upon existing technologies like cloud services, social networks, and data analysis tools. The technology acceptance model (TAM) provides the theoretical underpinning for the assessment of user confidence. Data was collected from 190 participants through purposive sampling. Path analysis confirmed all hypothesized relationships within the TAM with statistical significance (p < 0.001). Additionally, paired-sample t-tests revealed a significant increase in student acceptance of the MKES after integrating it into the marine science curriculum. These findings underscore the capacity of the MKES as a digital learning tool to enrich course pedagogy and improve student learning outcomes, thereby offering valuable support in advancing the education of professional marine managers.

Experimental Study Of Drag Characteristics And Dust Removal Performance Of A Hybrid Wet-Filter Precipitator, Hang Yi, Zifeng Yang, Deqiang Chang, Xinjiao Tian, Jingxian Liu

Mechanical and Materials Engineering Faculty Publications

With their advantages of high dust removal efficiency and low drag characteristics, hybrid wet-filter precipitators have great potential for dust control in coal mines, but the underlying mechanisms are not well understood. In this study, to help fill this knowledge gap, a hybrid wet-filter precipitator consisting of a 40-layer metal filter and a defogger device is designed and a prototype is constructed. Experiments are conducted to investigate its drag characteristics under wind velocities from 0.85 to 5.68 m/s and its dust removal performance under wind velocities of 2 and 4 m/s. On the basis of results with the initial design, …

256-Level Honey Memristor-Based In-Memory Neuromorphic System, Harshvardhan Uppaluru, Zoe Templin, Mohammed Rafeeq Khan, Md Omar Faruque, Feng Zhao, Jinhui Wang

Electrical and Computer Engineering Faculty Research & Creative Works

Promising synaptic behavior has been exhibited by memristors based on natural organic materials. Such memristor-based neuromorphic systems offer notable benefits, including environmental sustainability, low production and disposal costs, non-volatile storage capability, and bio/Complementary Metal-Oxide-Semiconductor (CMOS) compatibility. Here, a 256-level honey memristor-based neuromorphic system is experimentally evaluated for image recognition. In detail, first, 256-level honey memristors are manufactured and tested based on in-house technology; next, the non-linear characteristics and inherent variation of honey memristor devices, which lead to imprecise weight updates and limit the inference accuracy, are investigated. Experimental results indicate that the inference accuracy of the 256-level honey memristor-based neuromorphic …

Dynamic Maze Puzzle Navigation Using Deep Reinforcement Learning, Luisa Shu Yi Chiu

Master's Theses

The implementation of deep reinforcement learning in mobile robotics offers a great solution for the development of autonomous mobile robots to efficiently complete tasks and transport objects. Reinforcement learning continues to show impressive potential in robotics applications through self-learning and biological plausibility. Despite its advancements, challenges remain in applying these machine learning techniques in dynamic environments. This thesis explores the performance of Deep Q-Networks (DQN), using images as an input, for mobile robot navigation in dynamic maze puzzles and aims to contribute to advancements in deep reinforcement learning applications for simulated and real-life robotic systems. This project is a step …

Dual Base Sige Is-Hbt For Use In Biosensing Applications, Liam Stephen Hayes

Master's Theses

The proposed research is for a novel SiGe-based Ion-Sensitive Dual Hetero-junction Bipolar Transistor (IS-HBT) to be used in both trans-dermal biological sensing as well as Lab-on-Chip (LOC) applications. The end goals for the device designed are two: For one, the research done for this work will be used to substantiate the claims made by Zafar et al. [1] that an HBT-style structure is better suited for biosensing application rather than a conventional Field Effect Transistor (FET) based geometries. Secondly, it provides the final element to be integrated along with a selectivity membrane, as well as with a reverse-iontophoresis system to …

Development Of A Disc Blade Cutting System For Sesame Harvesting: Determination Of Operating Criteria And Energy Requirements, Selcuk Ugurluay, Gamze Genc

The Philippine Agricultural Scientist

This study aimed to explore the use of rotary disc blades in cutting, since the mowing units used in sesame harvesting contain many parts, require frequent lubrication, and have vibration problems. An experimental setup with a disc blade working on a cut-mowing system based from harvesting methods of sesame plants was designed and fabricated. The most suitable cutting criteria which are blade edge types (30°-30°, 30°-Flat, 45°-45°, 45°-Flat) and disc blade diameters (150, 180, and 210 mm) were determined for shearing and disc cutting action. The lowest cutting energy was consumed by the disc blade with a 30°-wedge angle at …

Enhancing Ammonium And Bicarbonate Tolerance In Chlorella Sorokiniana Through Ems-Induced Mutagenesis, Wentao Yang

McKelvey School of Engineering Graduate Student Theses & Dissertations

This study explores the enhancement of ammonium and bicarbonate tolerance in Chlorella sorokiniana via EMS-induced mutagenesis, aimed at improving the microalgae's resilience and growth under high-stress conditions of elevated NH4+ and HCO3 concentrations. By mutating C. sorokiniana using EMS, we developed mutant strains capable of thriving in conditions that are inhibitory to the wild type strain. The successful adaptation of these strains demonstrates a significant increase in biomass production and tolerance to environmental stressors, highlighting the potential of EMS mutagenesis in industrial algal applications for sustainable biofuel production and environmental remediation.

First-Principles Simulation Of The Interaction Between Dna Nucleotides And One-Dimensional Carbon Chain In Electrical Based Sequencing, Zeina Salman, Jin-Woo Kim, Steve Tung

Biological and Agricultural Engineering Faculty Publications and Presentations

Electrical DNA sequencing has attracted significant attention in recent years due to its simplified sequencing protocol, compact sequencing system, and relatively low sequencing cost. In the design and fabrication of the sequencing device, carbon-based nanomaterials such as graphene have been explored as a promising sensing material that provides an excellent combination of spatial resolution and base specificity. Using first-principles simulation, we determined the effect on the electrical conductivity of a one-dimensional carbon chain due to the presence of four DNA bases. The simulation results indicate that the interaction between the carbon chain and different DNA bases leads to different levels …

2024 Summer Proceedings Teuscher Lab, Teuscher Group, Christof Teuscher, Chelsea Ogbede, Lauren Sanday, Sofia Vargas, Artem Arefev

altREU Projects

How will computation evolve in the coming years? What problems can be tackled using artificial intelligence, in a world increasingly driven by data? And how can that data be used to better inform our decisions as a society? In this unique collection of research projects, each chapter represents a distinct work undertaken by a single individual or a group of students as part of the altREU program led by Christof Teuscher. The projects, rooted in applications of artificial intelligence and innovative computation techniques, examine impactful solutions to numerous pressing challenges affecting communities around the world.

Reducing Attack Opportunities Through Decentralized Event-Triggered Control, Paul Griffioen, Raffaele Romagnoli, Bruce H. Krogh, Bruno Sinopoli

Faculty Work Comprehensive List

Cyber-physical systems are prevalent in many critical infrastructures and are vulnerable to a variety of attacks from the network. Decentralized control systems are particularly vulnerable since they rely heavily on network communication to achieve their goals. To address network vulnerabilities, we present an event-triggered network connection and communication protocol that minimizes the amount of time agents are connected to the network, reducing the window of opportunity for attacks. This mechanism is a function of only local information and ensures stability for the overall system in attack-free scenarios. Our approach distinguishes itself from current decentralized event-triggered control strategies by considering an …

Resting-State Eeg Microstate Features For Major Depressive Disorder Classification, George M. V. Quinn

Dissertations, Theses, and Capstone Projects

Neuroimaging studies have revealed consistent abnormalities in functional connectivity within specific neural networks that may serve as biomarkers for major depressive disorder (MDD). It is important to find inexpensive, non-invasive techniques that target these biomarkers to make diagnosis easier and more objective. EEG microstates are quasi-stable potential topographies that are thought to reflect the quasi-stable network activity of the underlying neural generators. MDD has been shown to alter features of the four canonical EEG microstates (A, B, C, D) with some conflicting results. The most consistent network abnormalities in MDD are found in the anterior default mode network, and this …

Altered Cortical Activity During A Finger Tap In People With Stroke, Priya Balasubramanian, Roxanne P. Deleon, Dylan B. Snyder, Scott A. Beardsley, Allison S. Hyngstrom, Brian D. Schmit

Biomedical Engineering Faculty Research and Publications

This study describes electroencephalography (EEG) measurements during a simple finger movement in people with stroke to understand how temporal patterns of cortical activation and network connectivity align with prolonged muscle contraction at the end of a task. We investigated changes in the EEG temporal patterns in the beta band (13–26 Hz) of people with chronic stroke (N = 10, 7 F/3 M) and controls (N = 10, 7 F/3 M), during and after a cued movement of the index finger. We quantified the change in beta band EEG power relative to baseline as activation at each electrode and …

Nasogastric Tube Insertion Aid, Lauren S. Ark, Angela D. Biezins, Zachary B. Crum, Claire E. Nodine, Morgan N. Pope, Natsumi L. Shudo

Biomedical Engineering

The Nasogastric Tube Insertion Aid project, developed under the sponsorship of the BiCEP Program at California Polytechnic State University, aims to enhance the accuracy and efficiency of nasogastric (NG) tube placement. This initiative was inspired by challenges observed during the BiCEP summer program, where difficulties in NG tube insertions led to multiple attempts, increased patient discomfort, and serious medical risks, including lung punctures and brain trauma. The project's goal was to design an insertion aid that improves placement accuracy while being cost-effective and user-friendly for medical professionals. The device features an external tensioning mechanism that allows controlled deflection of the …

Analysis Of The Thermal Aging Kinetics Of Tallow, Chicken Oil, Lard, And Sheep Oil, Yun-Chuan Hsieh, Hao Ouyang, Yulin Zhang, Donyau Chiang, Fuqian Yang, Hsin-Lung Chen, Sanboh Lee

Chemical and Materials Engineering Faculty Publications

Understanding the thermal aging kinetics of animal oils is of vital importance in the storage and applications of animal oils. In this work, we use four different techniques, including UV-Vis spectrometry, viscometry, impedance spectroscopy, and acid–base titration, to study the thermal aging kinetics of tallow, chicken oil, lard, and sheep oil in the temperature range from 120 ◦C to 180 ◦C. The evolutions of the UV-Vis absorbance, dynamic viscosity, electric impedance, and acid titration are discussed with the defect kinetics. The evolutions of the color centers, defects for dynamic viscosity, and electric dipoles follow second-order, first-order, and zero-order kinetics, respectively. …

Antibiotic-Loaded Dendrimer Hydrogels In Periodontal Bone Regeneration: An In Vitro Release Feasibility Study, Nicholas Yesbeck, Da Huang, Caroline Carrico, Parthasarathy Madurantakam, Hu Yang

Chemical and Biochemical Engineering Faculty Research & Creative Works

The prescription of a course of oral antibiotics following bone grafting procedures is a common practice in clinical periodontics to reduce surgical site infections. The goal of this study is to characterize the release profile of antibiotics via local delivery using dendrimer hydrogels (DH) and to analyze the effect of two different particulate bone allografts on the release of the antibiotics in vitro. DH were synthesized from Poly amidoamine (PAMAM) dendrimer G5 and polyethylene glycol diacrylate, and cefazolin was chosen as the antibiotic. The antibiotic-loaded samples were bathed in PBS and incubated at 37 °C; aliquots were taken (1 h, …

Paper-Recorded Ecg Digitization Method With Automatic Reference Voltage Selection For Telemonitoring And Diagnosis, Liang Hung Wang, Chao Xin Xie, Tao Yang, Hong Xin Tan, Ming Hui Fan, I. Chun Kuo, Zne Jung Lee, Tsung Yi Chen, Pao Cheng Huang, Shih Lun Chen, Patricia Angela R. Abu

Department of Information Systems & Computer Science Faculty Publications

In electrocardiograms (ECGs), multiple forms of encryption and preservation formats create difficulties for data sharing and retrospective disease analysis. Additionally, photography and storage using mobile devices are convenient, but the images acquired contain different noise interferences. To address this problem, a suite of novel methodologies was proposed for converting paper-recorded ECGs into digital data. Firstly, this study ingeniously removed gridlines by utilizing the Hue Saturation Value (HSV) spatial properties of ECGs. Moreover, this study introduced an innovative adaptive local thresholding method with high robustness for foreground–background separation. Subsequently, an algorithm for the automatic recognition of calibration square waves was proposed …

Enhanced Perfluorooctanoic Acid (Pfoa) Degradation By Electrochemical Activation Of Peroxydisulfate (Pds) During Electrooxidation For Water Treatment, Melvin S. Samuel, Kadarkarai Govindan, Donald R. Ryan, Sean T. Mcbeath, Brooke K. Mayer, Patrick J. Mcnamara

Civil and Environmental Engineering Faculty Research and Publications

Improved treatment of per- and polyfluoroalkyl substances (PFAS) in water is critically important in light of the proposed United States Environmental Protection Agency (USEPA) drinking water regulations at ng L−1 levels. The addition of peroxymonosulfate (PMS) during electrooxidation (EO) can remove and destroy PFAS, but ng L−1 levels have not been tested, and PMS itself can be toxic. The objective of this research was to test peroxydisulfate (PDS, an alternative to PMS) activation by boron-doped diamond (BDD) electrodes for perfluorooctanoic acid (PFOA) degradation. The influence of PDS concentration, temperature, and environmental water matrix effects, and PFOA concentration on PDS-EO …

Optimal Placement Of Artificial Hair-Cell Airflow Sensors For Bioinspired Flight-By-Feel, Alex C. Hollenbeck

Theses and Dissertations

The Sparse Sensor Placement Optimization for Prediction (SSPOP) algorithm reduces highdimensional airflow data to a low-dimensional sparse approximation to identify an optimal placement for any number of sensors on airfoil or wing models of arbitrary shape and size, and outperforms conventional optimization techniques in accuracy and speed. For 2D flow this algorithm found a sensor placement solution (design point, or DP) which predicts AoA to within 0.10 degrees and ranks within the top 1 percent of the design space. On 3D wing models SSPOP found four-sensor DPs ranked well within the top 0.10 percent. Experimental validation with velocity and pressure …

Seal Counting On Our Plages (S.C.O.O.P.), Kaanan Kharwa

Master's Theses

The Vertebrate Integrative Physiology (VIP) lab monitors the population of northern elephant seals at the largest mainland breeding colony, located at Piedras Blancas (San Simeon, CA). As the population expands, more human-seal interactions and conflicts over land use occur. The VIP lab's work informs California State Parks and helps with the management of the rookery. Currently, members of the VIP lab fly a drone over the beaches, capture multiple images, and manually count the seals, which takes around 14 to 21 hours of analysis per survey. Machine learning methods such as Convolutional Neural Networks (CNN) and Region-based Convolutional Neural Networks …

Behind Armor Blunt Trauma: Liver Injuries Using A Live Animal Model, Narayan Yoganandan, Alok Shah, Brian D. Stemper, Lewis Somber, Valeta Carol Chancey, Joseph Mcentire

Biomedical Engineering Faculty Research and Publications

Introduction

While the 44-mm clay penetration criterion was developed in the 1970s for soft body armor applications, and the researchers acknowledged the need to conduct additional tests, the same behind the armor blunt trauma displacement limit is used for both soft and hard body armor evaluations and design considerations. Because the human thoraco-abdominal contents are heterogeneous, have different skeletal coverage, and have different functional requirements, the same level of penetration limit does not imply the same level of protection. It is important to determine the regional responses of different thoraco-abdominal organs to better describe human tolerance and improve the current …

Development Of Tissue-Engineered Model Of Fibrotic Scarring After Spinal Cord Injury To Study Astrocyte Activation And Neurite Outgrowth In Vitro, Nikolas Ala-Kokko, Inha Baek, Younghye Song

Biomedical Engineering Faculty Publications and Presentations

Traumatic spinal cord injuries (SCI) are debilitating injuries affecting twenty-seven million people worldwide and cause functional impairments. Despite decades of research and medical advancements, current treatment options for SCI remain limited, in part due to the complex pathophysiology of spinal cord lesions including cellular transformation and extracellular matrix (ECM) remodeling. Recent studies have increased focus on fibrotic scarring after SCI, and yet much remains unclear about the impact of fibrotic scarring on SCI lesion progression. Here, using collagen and decellularized spinal cord-based composite hydrogels, a three-dimensional (3D) cell culture model mimicking the fibrous core of spinal cord lesions was implemented …

Microwave Catalysis-Enabled Membrane Processes For Microbial Inactivation, Fangzhou Liu

Dissertations

The COVID-19 pandemic has highlighted the urgent need for advanced technologies to combat virus transmission. Traditional membrane filtration technologies primarily serve as physical barriers, capturing pollutants but failing to inactivate microbial agents such as bacteria and viruses. These membranes typically target larger particles but are ineffective against sub-micrometer viral particles. Thus, there's a critical demand for membrane filtration processes that combine robust filtration with antifouling and reaction -enabled functions for efficient pathogen disinfection. This research explores a novel microwave-assisted membrane filtration process incorporating catalytic reactions to enhance microbial disinfection and prevent membrane fouling, offering a groundbreaking solution to global challenges …