Digital Commons Network^™

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.

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 …

Building Services Engineering September/October 2024

Building Services Engineering

No abstract provided.

A Systematic Unified Approach For Addressing Temporal Instability In Road Safety Analysis, Kazi Redwan Shabab, Tanmoy Bhowmik, Mohamed H. Zaki, Naveen Eluru

Civil and Environmental Engineering Faculty Publications and Presentations

Multivariate models are widely employed for crash frequency analysis in traffic safety literature. In the context of analyzing data for multiple instances (such as years), it becomes essential to evaluate the stability of parameters over time. The current research proposes a novel approach, labelled the mixed spline indicator pooled model, that offers significant enhancement relative to current approaches employed for capturing temporal instability. The proposed approach entails carefully creating independent variables that allow us to measure parameter slope changes over time and can be easily integrated into existing methodological frameworks. The current research effort compares four multivariate model systems: year …

Automated Concrete Bridge Deck Inspection Using Unmanned Aerial System (Uas)-Collected Data: A Machine Learning (Ml) Approach, Rojal Pokhrel, Reihaneh Samsami, Saida Elmi, Colin Brooks

Michigan Tech Publications

Bridges are crucial components of infrastructure networks that facilitate national connectivity and development. According to the National Bridge Inventory (NBI) and the Federal Highway Administration (FHWA), the cost to repair U.S. bridges was recently estimated at approximately USD 164 billion. Traditionally, bridge inspections are performed manually, which poses several challenges in terms of safety, efficiency, and accessibility. To address these issues, this research study introduces a method using Unmanned Aerial Systems (UASs) to help automate the inspection process. This methodology employs UASs to capture visual images of a concrete bridge deck, which are then analyzed using advanced machine learning techniques …

Enhancing Multi-Agent System Testing With Diversity-Guided Exploration And Adaptive Critical State Exploitation, Xuyan Ma, Yawen Wang, Junjie Wang, Xiaofei Xie

Research Collection School Of Computing and Information Systems

Multi-agent systems (MASs) have achieved remarkable success in multi-robot control, intelligent transportation, and multiplayer games, etc. Thorough testing for MAS is urgently needed to ensure its robustness in the face of constantly changing and unexpected scenarios. Existing methods mainly focus on single-agent system testing and cannot be directly applied to MAS testing due to the complexity of MAS. To our best knowledge, there are fewer studies on MAS testing. While several studies have focused on adversarial attacks on MASs, they primarily target failure detection from an attack perspective, i.e., discovering failure scenarios, while ignoring the diversity of scenarios. In this …

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 …

Two-Dimensional Quantum Material Identification Via Self-Attention And Soft-Labeling In Deep Learning, Xuan Bac Nguyen, Apoorva Bisht, Benjamin Thompson, Hugh O.H. Churchill, Khoa Luu, Samee U. Khan

Electrical Engineering and Computer Science Faculty Publications and Presentations

Detecting two-dimensional (2D) materials in silicon chips presents a significant challenge in the field of quantum machines due to the difficulty of data collection. Specifically, among thousands of flakes, not all flakes are useful or well-annotated, resulting in noisy and hard samples within the dataset, which challenges the deep neural network (DNN) to learn. To address this problem, we propose a novel method for identifying quantum 2D flakes even when there is a high rate of missing annotations in the input images. In particular, we first propose a new mechanism for automatically detecting false negative flakes that are missing annotations. …

Integrating Blockchain Technology Into The Software Development Life Cycle To Satisfy The Software Bill Of Materials Requirement For Government Software Systems, Walter T. Scott Ii

Theses and Dissertations

This thesis explores the integration of Blockchain Technology (BT) into the Software Development Life Cycle (SDLC) to satisfy the Software Bill of Materials (SBOM) requirement for government software systems. This study begins by synthesizing a standard SDLC definition from various government and industry references, which may provide the foundation for future efforts to standardize software development practices across the government software development community. This study proceeds to define working definitions for the software supply chain (SSC) and software supply chain management (SCM) before introducing and detailing the SBOM requirement as well as providing an overview of prior research regarding SBOMs …

Validation Of Mobile Devices In Arbitrary Locations Against Force Plate Standard For Balance Assessment, German J. Ellsworth

Master's Theses

With balance assessment being essential to the prediction of fall risk and detection and assessment of motor disorders, increasing clinical accessibility to objective balance metrics is essential. Work has been done validating center of mass (COM) acceleration metrics against well regarded force plate center of pressure (COP) position standards for mobile device data acquisition systems, but most research is restricted to devices being close to the COM or strapped in a harness configuration. Through the use of rigid body kinematics and the inverted pendulum model, this study develops novel methodology for calculating COM acceleration using mobile devices in arbitrary positions, …

A Data-Driven Framework For Analyzing And Predicting Social Media Engagement During Rumor Propagation, Joseph E. Faza

Master's Theses

The spread of rumors on social media has become a significant concern, as platforms like X (formerly known as Twitter) enable rapid dissemination of unverified information. These rumors can shape public perception and behavior, making it crucial to understand the dynamics of their spread. The main objective of this study is to explore how users interact with rumor-related tweets and identify key factors that predict tweet engagement. By analyzing tweets from seven different rumor events, this research aims to uncover patterns in user engagement and provide insights into the spread of misinformation. The study utilized a dataset of tweets from …

The Role Of The Metaverse In Transforming The Management Skill Set Of Construction Practitioners, Ali M. Saad, Islam H. El-Adaway

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

No abstract provided.

Environmental Engineering 3.0: Faced With Planetary Problems, Solutions Must Scale-Up Caring, Daniel B. Oerther, Sarah Oerther, Linda A. Mccauley

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Forum papers are thought-provoking opinion pieces or essays founded in fact, sometimes containing speculation, on a civil engineering topic of general interest and relevance to the readership of the journal. The views expressed in this Forum article do not necessarily reflect the views of ASCE or the Editorial Board of the journal.

Price Escalation In Construction Projects: Examining National And International Contracts, Bahaa Chammout, Islam H. El-Adaway, Mohammad Abdul Nabi, Rayan H. Assaad

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

The construction industry has witnessed unprecedented disruptions in the supply chain (SC) over the past four years due to the consecutive impacts of the 2018 steel and aluminum tariffs, the COVID-19 pandemic, and the Russian-Ukrainian war. SC disruptions have been linked to price escalations, the management of which varies across different construction contracts. Thus, there is a timely need to understand the contractual implications of price escalation clauses. This article fulfills this research requirement by following an interdependent research methodology. First, the authors analyzed and compared price escalation provisions under various US-based, international, and UK-based standard design-bid-build contracts. Second, the …

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, …

Climate Change Prediction Model Using Mcdm Technique Based On Neutrosophic Soft Functions With Aggregate Operators, Kainat Muniba, Muhammad Naveed Jafar, Asma Riffat, Jawaria Mukhtar, Adeel Saleem

Neutrosophic Systems with Applications

The increasing impact of climate change necessitates innovative approaches in modeling and prediction to mitigate its adverse effects. This paper introduces a novel methodology integrating Neutrosophic Soft Functions (NSFs) into climate change prediction frameworks. NSFs, a hybrid of Neutrosophic Set Theory and Soft Set Theory, provide a flexible framework for handling uncertain and imprecise information inherent in climate data. This study explores the application of NSFs in capturing the complex interplay of various climatic variables, including temperature, precipitation, humidity, and atmospheric pressure, thereby enhancing the accuracy and reliability of climate change predictions. By incorporating NSFs into existing predictive models, such …

Value Of Electrical Heavy Civil Machinery In The American Construction Industry, Kaston Wong

Construction Management

Every day the construction industry is releasing an unhealthy amount of greenhouse gases into the atmosphere. The consequences may seem trivial at first because the planet is slowly deteriorating, and it is not easily discernable on a day-to-day basis; however, similar to constantly taking care of one’s home, one must take care of the planet. On the other hand, the difference between degradation of a home and planet is that the pollution released into the world is irreversible; therefore, we need to be even more conscientious of the environment. As the construction industry continues to grow, the need for heavy …

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.

Improving Military Medical Evacuation System Performance Via Stochastic Optimization, Virbon B. Frial

Theses and Dissertations

This research highlights the importance of improving the performance of military medical evacuation systems to reduce the risk of permanent disability or death among service members in deployed environments. We employ a range of stochastic optimization techniques relating to integer programming, Markov decision process, approximate dynamic programming, and machine learning, as appropriate, to gain insights into factors that contribute to improving system performance.

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 …

Investigating The Neurovascular Correlates Of Cognitive Function In Individuals With Spinal Cord Injury Using Functional Near-Infrared Spectroscopy, Donna Yali Chen

Dissertations

Individuals with spinal cord injury (SCI) have a 13 times greater risk of cognitive impairment than able-bodied individuals and commonly report symptoms of depression and anxiety. The reports of cognitive impairment in individuals with SCI are independent of concomitant brain injury. Although the direct cause of cognitive impairment in individuals with SCI is unknown, key contributors may include comorbid depression, chronic pain, anxiety, fatigue, brain injury, or cardiovascular dysfunction. Previous studies have focused on SCI at the level of the spinal cord but have under-investigated the supraspinal levels. Due to the lack of neuroimaging studies on SCI rehabilitation, it is …

Federated Learning Systems For Mobile Sensing Data, Xiaopeng Jiang

Dissertations

Federated Learning (FL) has emerged as a new distributed Deep Learning (DL) paradigm that enables privacy-aware training and inference on mobile devices with help from the cloud. This dissertation presents a comprehensive exploration of FL with mobile sensing data, covering systems, applications, and optimizations.

First, a mobile-cloud FL system, FLSys, is designed to balance model performance with resource consumption, tolerate communication failures, and achieve scalability. In FLSys, different DL models with different FL aggregation methods can be trained and accessed concurrently by different apps. In addition, FLSys provides advanced privacy-preserving mechanisms and a common API for third-party app developers to …

Data Driven Decision Making For Sustainable Planning And Operations Of Large Scale Networks, Bahareh Kargar

Dissertations

This dissertation explores data-driven decision-making networks, focusing on sustainable planning and operations for large-scale systems such as healthcare supply chains and power systems. One significant application in healthcare is the optimization of vaccine supply chains. An agent-based simulation-optimization modeling framework is developed to enhance the efficiency and sustainability of vaccine distribution. First, an agent-based epidemiological model of COVID-19 is extended to capture disease transmission dynamics and forecast the number of susceptible individuals and infections. Then, a sustainable vaccine supply chain considering the impacts of greenhouse gases is developed and integrated with the simulation model to minimize total costs and environmental …

Electrified Membrane For Water Treatment And Resource Recovery: Advancing Multiscale Strategies In Gas-Involving Reactions, Jianan Gao

Dissertations

Multifunctional, modular, and scalable water treatment technologies that operate without chemical additives are crucial for addressing global water pollution challenges. While traditional membrane-based separation processes are crucial for ensuring clean water supplies, they primarily focus on pollutant removal rather than on the upcycling of pollutants into valuable resources. Electrified membrane filtration presents a robust alternative, utilizing minimal or no chemical additives and harnessing electrical power to directly reduce contaminants or produce reactive oxidants or reductants on-site.

This dissertation is dedicated to the development of innovative electrochemically reactive membranes designed to address three major challenges: (1) the engineering of electrocatalysts with …

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 …

Estimation Of Spo2 Levels And Heart Rate From Ppg Signals In The Presence Of Motion Artifacts, Chizhong Wang

Dissertations

In the rapidly advancing world of health technology, wearable devices are at the forefront, fundamentally changing how individuals monitor their health. The key to this transformation is photoplethysmography (PPG), a non-invasive optical method that measures blood flow variations through the skin by detecting changes in light absorption with each heartbeat. This capability makes PPG essential for monitoring vital signs such as heart rate and blood oxygen saturation(SpO₂). Furthermore, the utility of PPG signals has been extended beyond traditional health metrics to include human activity classification, offering a holistic perspective on an individual's physical health and activity levels, in …

Investigations On Structure-Related Properties Of Organic Inorganic Hybrid Materials For Multifunction, Anu Ranjani E Ms

Theses and Dissertations

Two-dimensional (2D) hybrid halide perovskites have become a versatile material in diverse applications like optoelectronics, lighting and display, magnetism, etc. These materials are often termed as layered hybrid halide perovskites (LHHPs) due to their unique structure with alternate organic and inorganic layers. The presence of insulating organic layers separates the inorganic perovskite slabs, creating a quantum-confined architectural configuration. This unique configuration endows these materials with a spectrum of distinctive functionalities, encompassing photovoltaics, lighting and displays, second harmonic generation, optical limiting, ferroelectricity, and ferromagnetism. The exceptional attribute is that a single LHHP can respond autonomously to external stimuli, such as changes …

Enhancing Security And Privacy For Smarter Environment Through A Robust Cyber-Physical System Framework, Ramya S

Theses and Dissertations

As digital computing paradigm and practices have emerged in disciplines, devices with processors and sensors were rudimentary, performing independent tasks with limited power. The first computer processors were slow, bulky and consuming high energy, as sensors in thermometers and pressure gauges provide original, independent measurements without effective communication, 1999. It often required powerful, energy-efficient processors and advanced sensors to enable seamless communication and sophisticated data processing.

These devices, since smart home systems to industrial automation tools, which continuously collect, analyse and share data via the internet, facilitating if real-time management, predictive maintenance, and improved seamless experience are used, transforming everyday …

Deep Learning Technique For The Classification Of Stress Among The Students Using Physiological Biomarkers With A Hybrid Feature Approach, Rajendran Vg

Theses and Dissertations

Adolescence is a crucial part in life, and the presence of stress, anxiety, depression, and health issues during this stage is a great concern. This research aims to analyze and predict the cognitive stress in students during the examination period using EEG biomarkers. In this study, raw EEG data is acquired under two different experimental conditions, before and after examination, from 14 subjects with an eight-channel Enobio device. After preprocessing of the EEG signal, the brain rhythms such as theta, alpha, and beta sub-band energies and EEG band ratios such as neural activity, heart rate, arousal index, vigilance index and …

Ai In Healthcare: Early Diagnosis Of Skin Cancer Using Medical Image Processing And Deep Neural Networks, Nirmala V

Theses and Dissertations

Several cancer types are commonly prevalent, and skin cancer is one among them, becoming even more widespread worldwide in the last few decades. To diagnose skin cancer at an early stage and obtain appropriate therapy to treat it, there is a demand to know more about the disease’s characteristics or severity. Skin cancer is caused mainly by various reasons, including damage of the sun or tanning beds by ultraviolet light exposure.

Failing to treat skin cancer might substantially impair an individual’s quality of life as the victim. They likely to experience physical issues linked with the deformities caused by psychological …