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Articles 4171 - 4200 of 75049
Full-Text Articles in Engineering
Mems 411: A Diving Surface Breaker The Jetcycle, Amanda Mclaughlin, Nicholas Harris, Alice Hu, Steven Xiao
Mems 411: A Diving Surface Breaker The Jetcycle, Amanda Mclaughlin, Nicholas Harris, Alice Hu, Steven Xiao
Mechanical Engineering Design Project Class
Create a diving surface breaker for the WashU swimming and Diving team.
Mems 411: Timed Mosquito Egg Container, Daniel Nordquist, Preston Gee, Stephanos Mavrommatis
Mems 411: Timed Mosquito Egg Container, Daniel Nordquist, Preston Gee, Stephanos Mavrommatis
Mechanical Engineering Design Project Class
To aid in the war against mosquitoes, PHD candidate Lauren Johnson tasked this groups with developing a device to help study egg laying patterns. The goal is to create a device that can cut off access to tea water (an attractive breeding site) at specified time intervals in order to observe the effects of daylight and temperatures on mosquito egg laying behavior.
Mems 411: The Ez-Push Fsae E-Assisted Pushbar, Ian Snider, Hunter Tate, Erik Lillegard, Maxwell Wrasman
Mems 411: The Ez-Push Fsae E-Assisted Pushbar, Ian Snider, Hunter Tate, Erik Lillegard, Maxwell Wrasman
Mechanical Engineering Design Project Class
WashU Racing needs a device that will help them transport their Formula SAE car to and from their garage/paddock during events and testing when the car is unable to move under its own power. Pushing the car is very exhausting and requires at least 2 pairs of people, rotating in and out, to push the car. An electronically assisted push bar would only require two people to push the car and wouldn't experience exhaustion due to pushing the car. This device will function similarly to a shopping cart tug while also functioning as a rear jack for the vehicle that …
Mems 411: Dbf Wind Tunnel, Jeremy Choh, Stefan Hester, David Howard, Yang Yang
Mems 411: Dbf Wind Tunnel, Jeremy Choh, Stefan Hester, David Howard, Yang Yang
Mechanical Engineering Design Project Class
Design, Build, Fly (DBF) is a student-run engineering team at Washington University in St. Louis (WUSTL) that designs aircraft for flight competitions. Before assembling the final product, DBF runs numerous simulations on prototypes to understand the effects of drag and lift on the designed shape. The lift and drag parameters are important to aircraft design, as DBF hopes to optimize flight performance during competitions. However, simulations require computational power, are theoretical at best, and may inaccurately represent real-life situations. Preferably, DBF can use physical testing that captures prototype performance with more qualitative details.
Senior Design Group Z approaches DBF's needs …
Information Management Plan – Delivery Team, Robert Moore
Information Management Plan – Delivery Team, Robert Moore
Tools
Information Management Plan – Delivery Team is a support in a spreadsheet format that contains a number of delivery team (tenderers) templates that ISO 19650 recommend the delivery team (tenderers) should consider when responding to a tender to deliver a project for an Asset.
Build Digital has created Industry templates to allow organisations work in accordance with ISO 19650. These templates start to address the information requirements in the ISO 19650 series of standards. The templates are also in accordance with CEN-TR17654-2021” Guideline for the implementation of Exchange Information Requirements (EIR) and BIM Execution Plans (BEP) on European level based …
Harnessing Extrinsic Dissipation To Enhance The Toughness Of Composites And Composite Joints: A State-Of-The-Art Review Of Recent Advances, Gilles Lubineau, Marco Alfano, Ran Tao, Ahmed Wagih, Arief Yudhanto, Xiaole Li, Khaled Almuhammadi, Mjed Hashem, Ping Hu, Hassan A. Mahmoud, Fatih Oz
Harnessing Extrinsic Dissipation To Enhance The Toughness Of Composites And Composite Joints: A State-Of-The-Art Review Of Recent Advances, Gilles Lubineau, Marco Alfano, Ran Tao, Ahmed Wagih, Arief Yudhanto, Xiaole Li, Khaled Almuhammadi, Mjed Hashem, Ping Hu, Hassan A. Mahmoud, Fatih Oz
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Interfaces play a critical role in modern structures, where integrating multiple materials and components is essential to achieve specific functions. Enhancing the mechanical performance of these interfaces, particularly their resistance to delamination, is essential to enable extremely lightweight designs and improve energy efficiency. Improving toughness (or increasing energy dissipation during delamination) has traditionally involved modifying materials to navigate the well-known strength-toughness trade-off. However, a more effective strategy involves promoting non-local or extrinsic energy dissipation. This approach encompasses complex degradation phenomena that extend beyond the crack tip, such as long-range bridging, crack fragmentation, and ligament formation. This work explores this innovative …
The Coalition Development Of Allied Close Air Support Doctrine During World War Ii, David S. Stieghan
The Coalition Development Of Allied Close Air Support Doctrine During World War Ii, David S. Stieghan
Doctoral Dissertations and Projects
This research aims to discover how the American and British air forces worked collaboratively to provide ground support to their armies in Europe during World War II. While the official histories and scholars of the two countries concentrate on their unique national efforts, they analyze little of their cooperative efforts. By examining primary and secondary research sources to discover the experiments, doctrine development, and combat experience of both air forces, an understanding emerges that both nations combined their efforts in World War II in separate directions until beginning to work together on planning for the D-Day invasion.
By discovering the …
Balancing Sustainability Goals And Treatment Efficacy For Pfas Removal From Water, Md Moshiur Rahman Tushar, Zaki Alam Pushan, Nirupam Aich, Stetson Rowles
Balancing Sustainability Goals And Treatment Efficacy For Pfas Removal From Water, Md Moshiur Rahman Tushar, Zaki Alam Pushan, Nirupam Aich, Stetson Rowles
Civil Engineering & Construction: Faculty Publications
Per- and polyfluoroalkyl substances (PFAS) are emerging water contaminants with significant environmental and health impacts, posing challenges in water treatment due to their high stability and persistence. With increasing regulations, a critical need remains in understanding the sustainability of PFAS treatment technologies. Our review examines the environmental, economic, and social impacts of current PFAS treatment technologies across different water types and contexts. Additionally, we propose a framework for future sustainability studies to enable more holistic technology evaluations under specific conditions.
Pyrophosphate-Free Glycolysis In Clostridium Thermocellum Increases Both Thermodynamic Driving Force And Ethanol Titers, Bishal Dev Sharma, Shuen Hon, Eashant Thusoo, David M. Stevenson, Daniel Amador-Noguez, Adam M. Guss, Lee R. Lynd, Daniel G. Olson
Pyrophosphate-Free Glycolysis In Clostridium Thermocellum Increases Both Thermodynamic Driving Force And Ethanol Titers, Bishal Dev Sharma, Shuen Hon, Eashant Thusoo, David M. Stevenson, Daniel Amador-Noguez, Adam M. Guss, Lee R. Lynd, Daniel G. Olson
Dartmouth Scholarship
Background
Clostridium thermocellum is a promising candidate for production of cellulosic biofuels, however, its final product titer is too low for commercial application, and this may be due to thermodynamic limitations in glycolysis. Previous studies in this organism have revealed a metabolic bottleneck at the phosphofructokinase (PFK) reaction in glycolysis. In the wild-type organism, this reaction uses pyrophosphate (PPi) as an energy cofactor, which is thermodynamically less favorable compared to reactions that use ATP as a cofactor. Previously we showed that replacing the PPi-linked PFK reaction with an ATP-linked reaction increased the thermodynamic driving force of glycolysis, but only had …
Beyond The Surface: Understanding Temperature Polarisation In Dcmd Membranes Through Varied Operational Parameters, Hiras Ahamed Hijaz, Masoumeh Zargar, Abdellah Shafieian, Amir Razmjou, Mehdi Khiadani
Beyond The Surface: Understanding Temperature Polarisation In Dcmd Membranes Through Varied Operational Parameters, Hiras Ahamed Hijaz, Masoumeh Zargar, Abdellah Shafieian, Amir Razmjou, Mehdi Khiadani
Research outputs 2022 to 2026
Conventionally, a single Temperature Polarisation Coefficient (TPC) value is calculated to quantify Temperature Polarisation (TP). In this research, the extent of polarisation is investigated by capturing temperature profiles at specific points along a MD membrane using miniature thermocouples, eliminating the need for TPC calculations. The extent of polarisation at a point is affected by two contributory factors, namely the proximity of flow inlets and the difference in vapour pressure across the membrane at that point. Under this direction, this work examined the influence of permeate temperature, feed salinity, and flow direction on the development of the temperature profiles. Our analysis …
The Boris Experience: Evaluating Omnichannel Returns And Repurchase Intention, Jianliang Hao, Robert G. Richey Jr., Tyler R. Morgan, Ian M. Slazinik
The Boris Experience: Evaluating Omnichannel Returns And Repurchase Intention, Jianliang Hao, Robert G. Richey Jr., Tyler R. Morgan, Ian M. Slazinik
Faculty Publications
Researchers have examined the influence of the factors on reducing return rates in retailing over the years. However, the returns experience is often an overlooked way to drive customer engagement and repeat sales in the now ubiquitous omnichannel setting. The focus on returns prevention in existing research overshadows management’s need to understand better the comprehensive mechanics linking the customer in-store return experience with their repurchase actions. Recognizing the need to bridge different stages of the returns management process, this research aims to explore the facilitators and barriers of in-store return activities.
Converting Lignocellulosic Biomass Into Valuable End Products For Decentralized Energy Solutions: A Comprehensive Overview, Ahmed Aboulmagd Dr., Ahmad Mustafa, Shah Faisal, Jaswinder Singh, Boutaina Rezki, Karan Kumar, Vijayanand Moholkar, Ozben Kutlu, Hamdy Thabet, Zeinhom El-Bahy, Oguzhan Der, Cassamo Mussagy, Luigi Di Bitonto, Mushtaq Ahmad, Carlo Pastore
Converting Lignocellulosic Biomass Into Valuable End Products For Decentralized Energy Solutions: A Comprehensive Overview, Ahmed Aboulmagd Dr., Ahmad Mustafa, Shah Faisal, Jaswinder Singh, Boutaina Rezki, Karan Kumar, Vijayanand Moholkar, Ozben Kutlu, Hamdy Thabet, Zeinhom El-Bahy, Oguzhan Der, Cassamo Mussagy, Luigi Di Bitonto, Mushtaq Ahmad, Carlo Pastore
Renewable Mechanical Energy
This review manuscript delves into lignocellulosic biomass (LCB) as a sustainable energy source, addressing the global demand for renewable alternatives amidst increasing oil and gas consumption and solid waste production. LCB, consisting of lignin, cellulose, and hemicellulose, is versatile for biochemical and thermochemical conversions like anaerobic digestion, fermentation, gasification, and pyrolysis. Recent advancements have led to a 25 % increase in bioethanol yields through alkali pre-treatment and optimized fermentation, a 20 % enhancement in microbial delignification efficiency, and a 35 % improvement in enzyme efficiency via nanobiotechnology. These innovations enhance biofuel production sustainability and cost-effectiveness. Decentralized energy systems utilizing locally …
Zeolite 13x Particles With Porous Tio2 Coating And Ag2o Nanoparticles As Multi-Functional Filler Materials For Face Masks, Wei Su, Kaiying Wang, Han Yu, Fateme Fayyazbakhsh, Jeremy Watts, Yue-Wern Huang, Jee-Ching Wang, Xinhua Liang
Zeolite 13x Particles With Porous Tio2 Coating And Ag2o Nanoparticles As Multi-Functional Filler Materials For Face Masks, Wei Su, Kaiying Wang, Han Yu, Fateme Fayyazbakhsh, Jeremy Watts, Yue-Wern Huang, Jee-Ching Wang, Xinhua Liang
Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works
Adsorbent components in face masks are crucial for protecting individuals exposed to dangerous situations. In this study, one porous TiO2 layer was deposited on zeolite 13X particles by coating hybrid organic/inorganic titanium alkoxide film via molecular layer deposition (MLD), followed by heat treatment to remove organic components in the MLD film. Various concentrations of Ag2O nanoparticles were impregnated on the TiO2-coated 13X particles, offering a wide range of antibacterial, antifungal, and antiviral characteristics. The obtained composite particles were characterized using X-ray photoelectron spectroscopy and thermal gravimetric analysis to study the composition and mass loading of …
Acoustofluidics-Based Intracellular Nanoparticle Delivery, Zhishang Li, Zhenhua Tian, Jason N. Belling, Joseph Rich, Haodong Zhu, Zhehan Ma, Hunter Bachman, Liang Shen, Yaosi Liang, Xiolin Qi, Liv K. Heidenreich, Yao Gong, Shujie Yang, Wenfen Zhang, Peiran Zhang, Yingchun Fu, Yibin Ying, Steven J. Jonas, Yanbin Li, Paul S. Weiss, Tony J. Huang
Acoustofluidics-Based Intracellular Nanoparticle Delivery, Zhishang Li, Zhenhua Tian, Jason N. Belling, Joseph Rich, Haodong Zhu, Zhehan Ma, Hunter Bachman, Liang Shen, Yaosi Liang, Xiolin Qi, Liv K. Heidenreich, Yao Gong, Shujie Yang, Wenfen Zhang, Peiran Zhang, Yingchun Fu, Yibin Ying, Steven J. Jonas, Yanbin Li, Paul S. Weiss, Tony J. Huang
Faculty Publications
Controlled intracellular delivery of biomolecular cargo is critical for developing targeted therapeutics and cell reprogramming. Conventional delivery approaches (e.g., endocytosis of nano-vectors, microinjection, and electroporation) usually require time-consuming uptake processes, labor-intensive operations, and/or costly specialized equipment. Here, we present an acoustofluidics-based intracellular delivery approach capable of effectively delivering various functional nanomaterials to multiple cell types (e.g., adherent and suspension cancer cells). By tuning the standing acoustic waves in a glass capillary, our approach can push cells in flow to the capillary wall and enhance membrane permeability by increasing membrane stress to deform cells via acoustic radiation forces. Moreover, by coating …
How Will Ai Impact Knowledge Sharing Within Construction Clustering? Bringing Back The Conversation On Social Contagion Within Construction Clusters, Oluwasegun O. Seriki, Mark Mulville, Ruairi Hayden
How Will Ai Impact Knowledge Sharing Within Construction Clustering? Bringing Back The Conversation On Social Contagion Within Construction Clusters, Oluwasegun O. Seriki, Mark Mulville, Ruairi Hayden
Conference Papers
Construction clusters and innovation systems play a crucial role in enhancing competitiveness and fostering sustainable development in the construction sector. These clusters facilitate knowledge sharing, interactive learning, and collaborative innovation among firms, institutions, and other stakeholders. The success of construction clusters depends on numerous factors, including firm size, economic climate, and attitudes towards innovation. While some clusters transform into innovation systems by becoming tacit-knowledge intensive, there is not much data or investigation into how they may adapt to changing demands spurred by advances in artificial intelligence (AI). There is some preliminary research highlighting the lack of dispersed innovation networks within …
Identifying Opportunities For Nature-Based Solutions With Geospatialized Life Cycle Assessments And Fine-Scale Socioecological Data, Gabriela Shirkey, Annick Anctil, Ranjeet John, Venkatesh Kolluru, Leah Mungai, Herve Kashongwe, Lauren T. Cooper, Ilke Celik, Joshua B. Fisher, Jiquan Chen
Identifying Opportunities For Nature-Based Solutions With Geospatialized Life Cycle Assessments And Fine-Scale Socioecological Data, Gabriela Shirkey, Annick Anctil, Ranjeet John, Venkatesh Kolluru, Leah Mungai, Herve Kashongwe, Lauren T. Cooper, Ilke Celik, Joshua B. Fisher, Jiquan Chen
Civil and Environmental Engineering Faculty Publications and Presentations
As we increasingly understand the impact that land management intensification has on local and global climate, the call for nature-based solutions (NbS) in agroecosystems has expanded. Moreover, the pressing need to determine when and where NbS should be used raises challenges to socioecological data integration as we overcome spatiotemporal resolutions. Natural and working lands is an effort promoting NbS, particularly emissions reduction and carbon stock maintenance in forests. To overcome the spatiotemporal limitation, we integrated life cycle assessments (LCA), an ecological carbon stock model, and a land cover land use change model to synthesize rates of global warming potential (GWP) …
Optimized Fabrication Of Dendritic Mesoporous Silica Nanoparticles As Efficient Delivery System For Cancer Immunotherapy, Varsha Godakhindi, Mostafa Yazdimamaghani, Sudip Kumar Dam, Farzana Ferdous, Andrew Z. Wang, Mubin Tarannum, Jonathan Serody, Juan L. Vivero-Escoto
Optimized Fabrication Of Dendritic Mesoporous Silica Nanoparticles As Efficient Delivery System For Cancer Immunotherapy, Varsha Godakhindi, Mostafa Yazdimamaghani, Sudip Kumar Dam, Farzana Ferdous, Andrew Z. Wang, Mubin Tarannum, Jonathan Serody, Juan L. Vivero-Escoto
Chemical and Biochemical Engineering Faculty Research & Creative Works
In the past decade, cancer immunotherapy has revolutionized the field of oncology. Major immunotherapy approaches such as immune checkpoint inhibitors, cancer vaccines, adoptive cell therapy, cytokines, and immunomodulators have shown great promise in preclinical and clinical settings. Among them, immunomodulatory agents including cancer vaccines are particularly appealing; however, they face limitations, notably the absence of efficient and precise targeted delivery of immune-modulatory agents to specific immune cells and the potential for off-target toxicity. Nanomaterials can play a pivotal role in addressing targeting and other challenges in cancer immunotherapy. Dendritic mesoporous silica nanoparticles (DMSNs) can enhance the efficacy of cancer vaccines …
Leveraging Machine Learning For Defect Detection In Irrigation Concrete Canal Lining In Egypt: Advancing Construction Quality And Efficiency, Mohamed Nabawy
Leveraging Machine Learning For Defect Detection In Irrigation Concrete Canal Lining In Egypt: Advancing Construction Quality And Efficiency, Mohamed Nabawy
Civil Engineering
Abstract:
Defects during the construction phase of projects pose significant challenges, particularly in terms of
safety, cost overruns, delays, and labor inefficiencies. In irrigation concrete canal lining construction
with mega investments, early detection of defects is critical to ensuring quality and project success.
This study explores the application of machine learning (ML) for onsite defect detection, focusing
on the development and deployment of an object detection mobile application specifically tailored
for identifying visible defects in concrete canal lining construction. Leveraging the machine learning
capabilities of Microsoft Azure, a custom object detection model was trained and validated to
recognize defects such …
Highly Porous Nanocarriers For Osmolyte Delivery And Drought Mitigation In Wheat And Ryegrass, David Britt
Highly Porous Nanocarriers For Osmolyte Delivery And Drought Mitigation In Wheat And Ryegrass, David Britt
Funded Research Records
No abstract provided.
Etherealbreathing: A Holographic Biofeedback Game To Support Relaxation In Autistic Children, Arturo Morales Téllez, Isabel López Hurtado, Franceli L. Cibrian, Monica Tentori
Etherealbreathing: A Holographic Biofeedback Game To Support Relaxation In Autistic Children, Arturo Morales Téllez, Isabel López Hurtado, Franceli L. Cibrian, Monica Tentori
Engineering Faculty Articles and Research
Biofeedback training for box breathing is becoming increasingly accessible due to advancements in consumer-grade breathing sensors. However, there is limited research on their design and applications for specialized populations. This study evaluates a novel biofeedback holographic game, EtherealBreathing, designed to support autistic children. In EtherealBreathing, children practice box breathing to collect virtual elements to maintain the Earth's balance, using a wearable sensor to measure chest expansion for breath detection. A deployment study with 20 autistic children revealed that EtherealBreathing effectively promotes box breathing, leading to better health-related outcomes, such as lowering participants’ heart and respiratory rates than traditional practices. Biofeedback …
A Novel, Direct Matrix Solver For Supersonic Boundary Element Method Systems, Cory D. Goates, Doug Hunsaker
A Novel, Direct Matrix Solver For Supersonic Boundary Element Method Systems, Cory D. Goates, Doug Hunsaker
Mechanical and Aerospace Engineering Faculty Publications
For problems with very fine surface meshes, typically the most time-consuming step of a boundary element method (BEM, also called a panel method) is solving the final linear system of equations. Many have already studied how to efficiently solve the dense, asymmetric systems which arise in elliptic BEMs. However, this has not been studied for a supersonic aerodynamic BEM, for which the governing PDE is hyperbolic. Due to this hyperbolic character, the matrix equation which arises from a supersonic BEM has a large number of identically zero elements. But the resulting linear system of equations is also not sparse in …
The Role Of Customers In Strategic Information Technology (It) Initiatives, Siddharth Aggarwal
The Role Of Customers In Strategic Information Technology (It) Initiatives, Siddharth Aggarwal
Doctoral Dissertations and Projects
This study focused on a small organization in the United States of America. The organization has IT departments that cater to the IT needs of its internal and external customers through IT products and services. Such organizations run full life cycles of product management and product development and often face off with situations to prioritize the use of their limited resources. Ideally, organizations focus on strategic IT initiatives that might be in the company's and its customers' best interest. However, instances occur when IT-driven initiatives lose that focus and might end up diverting resources toward the latest shiny technology and …
Bilayer Asymmetric-Based Metal-Organic Frameworks Membrane For Blue Energy Conversion, Rockson Kwesi Tonnah, Milton Chai, Mohammad Khedri, Milad Razbin, Reza Maleki, Amir Razmjou, Mohsen Asadnia
Bilayer Asymmetric-Based Metal-Organic Frameworks Membrane For Blue Energy Conversion, Rockson Kwesi Tonnah, Milton Chai, Mohammad Khedri, Milad Razbin, Reza Maleki, Amir Razmjou, Mohsen Asadnia
Research outputs 2022 to 2026
The conversion of Gibbs free energy at the interface of solutions with salinity gradients into electrical energy is essentially a means of mitigating environmental pollution and bolstering the availability of new energy sources to enhance the renewable energy portfolio. However, a three-dimensional (3D) sub-nanofluidic membrane with high ion conductivity and selectivity for a reverse electrodialysis (RED) based osmotic energy conversion in both aqueous and organic solutions remains largely unexplored. Herein, we engineered a bilayer metal organic frameworks (MOFs) membrane with polystyrene sulfonated angstrom-size channels in UiO-66-NH2 base layer and isoreticular MIL-88B membrane as the top layer to enhance permselectivity and …
An Evaluation Of Features Extracted From Facial Images In The Context Of Accurate Age Estimation⋆, Malik Awais Khan, Aurelia Power, Peter Corcoran, Christina Thorpe
An Evaluation Of Features Extracted From Facial Images In The Context Of Accurate Age Estimation⋆, Malik Awais Khan, Aurelia Power, Peter Corcoran, Christina Thorpe
Conference papers
Age estimation by face image recognition can be used in numerous ways with regression models to manage access control, improve security, and guarantee the protection of children online. The approaches used for predicting age—including data selection, cleaning techniques, feature extraction, algorithm choice, and hyperparameter tuning—often struggles with generalization. Furthermore, a lot of methods neglect to specifically address how extracted face features might be used for prediction. To address the lack of racial diversity we acquired a dataset consisting of different races from literature. We also examined the ability of local, global and hybrid facial features to predict ages. Two variants …
Enhanced Wind Velocity Imputation Near Building Structures Using Advanced Machine Learning Techniques, Istiak Ahammed, Sujeen Song, Gang Hu, Jinwoo An, Bubryur Kim
Enhanced Wind Velocity Imputation Near Building Structures Using Advanced Machine Learning Techniques, Istiak Ahammed, Sujeen Song, Gang Hu, Jinwoo An, Bubryur Kim
Civil Engineering Faculty Publications
The evaluation of instantaneous wind flow patterns nearest to building architecture is crucial to ensuring structural stability, architectural integrity, and pedestrian safety. Particle image velocimetry (PIV), a technique for studying fluid flow by tracing particles, provides accurate predictions of instantaneous wind velocities (IWV). However, PIV encounters challenges in specific regions due to laser light-based experimentation, leading to missing data. Consequently, investigating the wind circulation pattern around buildings becomes more challenging. Numerous ML techniques have been employed to impute missing wind velocities at random building locations with minimal structural impact. This paper focuses on addressing this concern by utilizing a machine …
Identifying Subject Bias In Wifi-Based Human Activity Recognition Evaluation Methods, Amany Elkelany, Robert J. Ross, Susan Mckeever
Identifying Subject Bias In Wifi-Based Human Activity Recognition Evaluation Methods, Amany Elkelany, Robert J. Ross, Susan Mckeever
Conference papers
WiFi-based Human Activity Recognition (HAR) has emerged as a promising approach for monitoring and analysing human activities in a non-intrusive manner, leveraging WiFi signals for activity classification. Despite advancements, existing WiFi-based HAR research lacks consideration of subject (human) bias. This results in learning models performing well on individuals used in the training samples but failing to generalise to new/unseen subjects, in contrast to known good practices in machine learning. In this paper, we address this oversight directly by systematically examining the evaluation methodology for the WiFi-based HAR context. Specifically, we investigate the impact of Leave-One-Subject-Out Cross-Validation (LOSOCV) in a hybrid …
Towards Rare Event And Anomaly Prediction In Manufacturing: Bridging Methodological Gaps In Industrial Applications, Chathurangi Shyalika, Renjith Prasad, Ruwan Wickramarachchi, Amit Sheth
Towards Rare Event And Anomaly Prediction In Manufacturing: Bridging Methodological Gaps In Industrial Applications, Chathurangi Shyalika, Renjith Prasad, Ruwan Wickramarachchi, Amit Sheth
Publications
Rare event prediction is critical in industrial applications, including real-world Industry 4.0 applications. These events, defined by their low occurrence frequency, are often difficult to predict due to the skewed data distribution, which complicates modeling and evaluation. In our research, we provide a comprehensive review of current approaches to rare event prediction across four key dimensions: rare event data, data processing techniques, algorithmic approaches, and evaluation methodologies [1]. By analyzing diverse datasets with multiple modalities, including numerical, image, text, and audio, we categorize the primary challenges and present the gaps in current research. Specifically, we present three novel research contributions …
Predicting Chaotic Systems With Quantum Echo-State Networks, Erik Connerty, Ethan N. Evans, Gerasimos Angelatos, Vignesh Narayanan
Predicting Chaotic Systems With Quantum Echo-State Networks, Erik Connerty, Ethan N. Evans, Gerasimos Angelatos, Vignesh Narayanan
Publications
Recent advancements in artificial neural networks have enabled impressive tasks on classical computers, but they demand significant computational resources. While quantum computing offers potential beyond classical systems, the advantages of quantum neural networks (QNNs) remain largely unexplored. In this work, we present and examine a quantum circuit (QC) that implements and aims to improve upon the classical echo-state network (ESN), a type of reservoir-based recurrent neural networks (RNNs), using quantum computers. Typically, ESNs consist of an extremely large reservoir that learns high-dimensional embeddings, enabling prediction of complex system trajectories. Quantum echo-state networks (QESNs) aim to reduce this need for prohibitively …
Understanding Confusion: A Case Study Of Training A Machine Model To Predict And Interpret Consensus From Volunteer Labels, Ramanakumar Sankar, Kameswara Mantha, Cooper Nesmith, Lucy Fortson, Shawn R. Brueshaber, Candice Hansen-Koharcheck, Glenn Orton
Understanding Confusion: A Case Study Of Training A Machine Model To Predict And Interpret Consensus From Volunteer Labels, Ramanakumar Sankar, Kameswara Mantha, Cooper Nesmith, Lucy Fortson, Shawn R. Brueshaber, Candice Hansen-Koharcheck, Glenn Orton
Michigan Tech Publications
Citizen science has become a valuable and reliable method for interpreting and processing big datasets, and is vital in the era of ever-growing data volumes. However, there are inherent difficulties in the generating labels from citizen scientists, due to the inherent variability between the members of the crowd, leading to variability in the results. Sometimes, this is useful — such as with serendipitous discoveries, which corresponds to rare/unknown classes in the data — but it might also be due to ambiguity between classes. The primary issue is then to distinguish between the intrinsic variability in the dataset and the uncertainty …
Microstructured Microstructure: Effects Of Concentration Variations On Shock Initiation Of Hmx-Based Plastic Explosives, Dana D. Dlott, Lawrence Salvati, Siva Kumar Valluri
Microstructured Microstructure: Effects Of Concentration Variations On Shock Initiation Of Hmx-Based Plastic Explosives, Dana D. Dlott, Lawrence Salvati, Siva Kumar Valluri
Mechanical and Aerospace Engineering Faculty Research & Creative Works
We studied shock-compressed plastic-bonded explosives (PBX) consisting of HMX (cyclotetramethylene-tetranitramine) with PDMS (poly-dimethylsiloxane) binder, where we varied the HMX weight percent (wt%) up to a maximum of 60 wt%. In this lower-concentration regime, HMX particle clustering causes the PBX structure to consist of HMX clusters and PDMS islands. Structural analysis by optical microscopy allowed us to compute a radial correlation function that gives the mean distance from an average HMX particle to the nearest polymer island. Short-duration 20 GPa shocks (4 ns) created hot spots, and time-resolved thermal emission was used to obtain the growth rate of the subsequent deflagration. …