Engineering Commons^™

Gait And Turning Characteristics From Daily Life Increase Ability To Predict Future Falls In People With Parkinson’S Disease, Vrutangkumar Shah, Adam Jagodinsky, James Mcnames, Multiple Additional Authors

Electrical and Computer Engineering Faculty Publications and Presentations

Objectives: To investigate if digital measures of gait (walking and turning) collected passively over a week of daily activities in people with Parkinson’s disease (PD) increases the discriminative ability to predict future falls compared to fall history alone. Methods: We recruited 34 individuals with PD (17 with history of falls and 17 non-fallers), age: 68 ± 6 years, MDS-UPDRS III ON: 31 ± 9. Participants were classified as fallers (at least one fall) or non-fallers based on self-reported falls in past 6 months. Eighty digital measures of gait were derived from 3 inertial sensors (Opal® V2 System) placed on the …

A Representation For Many Player Generalized Divide The Dollar Games, Garrison Greenwood, Daniel Ashlock

Electrical and Computer Engineering Faculty Publications and Presentations

Divide the dollar is a simplified version of a two player bargaining problem game devised by John Nash. The generalized divide the dollar game has n > 2 players. Evolutionary algorithms can be used to evolve individual players for this generalized game but representation—i.e., a genome plus a move or search operator(s)—must be carefully chosen since it affects the search process. This paper proposes an entirely new representation called a demand matrix. Each individual in the evolving population now represents a collection of n players rather than just an individual player. Players use previous outcomes to decide their choices (bids) in …

Opal Actigraphy (Activity And Sleep) Measures Compared To Actigraph: A Validation Study, Vrutangkumar Shah, Barbara H. Brumbach, Sean Pearson, Paul Vasilyev, James Mcnames, Multiple Additional Authors

Electrical and Computer Engineering Faculty Publications and Presentations

Physical activity and sleep monitoring in daily life provide vital information to track health status and physical fitness. The aim of this study was to establish concurrent validity for the new Opal Actigraphy solution in relation to the widely used ActiGraph GT9X for measuring physical activity from accelerometry epic counts (sedentary to vigorous levels) and sleep periods in daily life. Twenty participants (age 56 + 22 years) wore two wearable devices on each wrist for 7 days and nights, recording 3-D accelerations at 30 Hz. Bland–Altman plots and intraclass correlation coefficients (ICCs) assessed validity (agreement) and test–retest reliability between ActiGraph …

Graphical Models In Reconstructability Analysis And Bayesian Networks, Marcus Andrew Harris

Dissertations and Theses

This research focuses on the investigation of two machine learning methodologies, Reconstructability Analysis (RA) and Bayesian Networks (BN). Both methods are probabilistic graphical modeling (PGM) methodologies. RA was developed in the systems community and has applications including time-series analysis, classification, decomposition, compression, pattern recognition, prediction, control, and decision analysis. BNs have origins in path models and have applications similar to those of RA. BNs are another graphical modeling approach for data modeling that is closely related to RA; where BN overlaps RA the two methods are equivalent, but RA and BN each has distinctive features absent in the other methodology. …

Systems Thinking Activities Used In K-12 For Up To Two Decades, Diana Fisher, Systems Thinking Association

Complex Systems Faculty Publications and Presentations

Infusing systems thinking activities in pre-college education (grades K-12) means updating precollege education so it includes a study of many systemic behavior patterns that are ubiquitous in the real world. Systems thinking tools include those using both paper and pencil and the computer and enhance learning in the classroom making it more student-centered, more active, and allowing students to analyze problems that have been heretofore beyond the scope of K-12 classrooms. Students in primary school have used behavior over time graphs to demonstrate dynamics described in story books, like the Lorax, and created stock-flow diagrams to describe what was needed …

Numerical Modeling Of A Pile-Supported Wharf Subjected To Liquefaction-Induced Lateral Ground Deformations, Milad Souri, Arash Khosravifar, Stephen Dickenson, Nason Mccullough, Scott Schlechter

Civil and Environmental Engineering Faculty Publications and Presentations

Fully-coupled nonlinear dynamic analysis is increasingly used for assessing the seismic performance of pile-supported wharf structures subjected to liquefaction-induced lateral ground deformations. Several numerical challenges exist for analysis of this highly nonlinear soil-structure interaction, which require robust, yet practical, solutions that are validated with experimental data. This study presents a numerical model of a pile-supported wharf and evaluates the applicability of a soil constitutive model, and modeling assumptions and methods by using recorded data from a well-instrumented, large-scale centrifuge test. The objectives of this study include: (a) evaluating the performance of a recently developed pressure-dependent multi-yield surface constitutive soil model …

New Frontiers Of Laser Welding Technology, Kyung-Eun Min, Jae-Won Jang, Cheolhee Kim

Mechanical and Materials Engineering Faculty Publications and Presentations

With the advances in power sources and optic technologies, high-power laser welding has been utilized in many applications such as automotive, battery manufacturing, and electronic industries. The low-heat input of laser power and its precise control enables minimal thermal damage and geometric inaccuracy in the weldment. Recently, laser welding has evolved in combination with machine learning, monitoring and control technology, new materials, and new processes. This Special Issue aims to present the recent advances in the development in innovative laser welding technologies based on new laser power sources, laser optics, systems, and monitoring technologies. A total of six papers are …

Driver And Bicyclist Comprehension Of Blue Light Detection Confirmation Systems, Douglas P. Cobb, Hisham Jashami, Christopher Monsere, Sirisha Kothuri, David S. Hurwitz

Civil and Environmental Engineering Faculty Publications and Presentations

This study analyzed motorist and bicyclist understanding and preference of positive confirmation of detection of a bicycle by the traffic signal infrastructure using a blue light detection confirmation (BLDC). The research analyzed results of an online survey of 1,123 respondents and intercept survey of 337 respondents. The study initially found that participants of the survey did not understand the meaning of the blue light itself, but comprehension of the system rose from 40% to 50% when supplemental signs were used. Respondents overwhelmingly indicated that they preferred the sign option that included symbols, text, and a representation of the blue light, …

Comparing The Performance Of Different Machine Learning Models In The Evaluation Of Solder Joint Fatigue Life Under Thermal Cycling, Jason Scott Ross

Dissertations and Theses

Predicting the reliability of board-level solder joints is a challenging process for the designer because the fatigue life of solder is influenced by a large variety of design parameters and many nonlinear, coupled phenomena. Machine learning has shown promise as a way of predicting the fatigue life of board-level solder joints. In the present work, the performance of various machine learning models to predict the fatigue life of board-level solder joints is discussed. Experimental data from many different solder joint thermal fatigue tests are used to train the different machine learning models. A web-based database for storing, sharing, and uploading …

Coriolis Forces On Wind Turbine Wakes Within A Wind Farm, Natalie Violetta Frank

Dissertations and Theses

As wind plant footprints and turbine scales grow larger, understanding the interactions between mesoscale physical phenomena, such as Earth's rotation, and large-scale farm wakes become increasingly important. Current field research notes spatial and temporal influences on the global farm wakes caused by Coriolis forces. However, using field experiments to study this is notoriously difficult as there is additional influence from wind veer in the atmospheric boundary layer caused by many factors ranging from terrain to the diurnal cycles. Experiments are performed on a wind plant under the influence of Coriolis forces. This is achieved by placing the wind plant on …

Dissecting Succulence: Crassulacean Acid Metabolism And Hydraulic Capacitance Are Independent Adaptations In Clusia Leaves, Alistair Leverett, Samantha Hartzell, Klaus Winter, Milton Garcia, Multiple Additional Authors

Civil and Environmental Engineering Faculty Publications and Presentations

Succulence is found across the world as an adaptation to water-limited niches. The fleshy organs of succulent plants develop via enlarged photosynthetic chlorenchyma and/or achlorophyllous water storage hydrenchyma cells. The precise mechanism by which anatomical traits contribute to drought tolerance is unclear, as the effect of succulence is multifaceted. Large cells are believed to provide space for nocturnal storage of malic acid fixed by crassulacean acid metabolism (CAM), whilst also buffering water potentials by elevating hydraulic capacitance (CFT). The effect of CAM and elevated CFT on growth and water conservation have not been compared, despite the assumption that these adaptations …

Damage Detection In Reinforced Concrete Member Using Local Time-Frequency Transform Applied To Vibration Measurements, Ning Liu, Thomas Schumacher, Yan Li, Lina Xu, Bo Wang

Civil and Environmental Engineering Faculty Publications and Presentations

Signal processing and analysis of structural vibration measurements are key components of structural damage detection (SDD) in structural health monitoring (SHM). The goal of signal processing is to extract subtle changes in the measured signals, which can be used to infer changes in structural parameters and damage. Time-frequency analysis is one of the most popular characterization methods for studying non-stationary vibration signals. In this article, the local time-frequency transform (LTFT) is applied and evaluated to calculate the time-domain signals because of its excellent time-frequency energy distribution properties. The LTFT matches the input data by the Fourier basis in an inverse …

Panoramas From Photons, Sacha Jungerman, Atul Ingle, Mohit Gupta

Computer Science Faculty Publications and Presentations

Scene reconstruction in the presence of high-speed motion and low illumination is important in many applications such as augmented and virtual reality, drone navigation, and autonomous robotics. Traditional motion estimation techniques fail in such conditions, suffering from too much blur in the presence of high-speed motion and strong noise in low-light conditions. Single-photon cameras have recently emerged as a promising technology capable of capturing hundreds of thousands of photon frames per second thanks to their high speed and extreme sensitivity. Unfortunately, traditional computer vision techniques are not well suited for dealing with the binary-valued photon data captured by these cameras …

Eugenol, Menthol And Other Flavour Chemicals In Kreteks And ‘White’ Cigarettes Purchased In Indonesia, Joanna Cohen, Beladenta Amalia, Wentai Luo, Kevin J. Mcwhirter, James F. Pankow

Civil and Environmental Engineering Faculty Publications and Presentations

Background Flavoured tobacco products are not restricted in Indonesia, a country with about 68 million adults who smoke. Most use clove-mixed tobacco cigarettes (‘kreteks’); non-clove (‘white’) cigarettes are also available. Although the use of flavour chemicals has been identified by WHO as promoting tobacco use, little has been reported for Indonesia about the levels of flavourants in either kreteks or ‘white cigarettes’.

Methods 22 kretek brand variants and nine ‘white’ cigarette brand variants were purchased in Indonesia during 2021/2022; one of the kretek packs contained three colour-coded variants, giving a total sample number of 24 for the kreteks. Chemical analyses …

Multicopter Drone Mass Distribution Impacts On Viability, Performance, And Sustainability, Miguel Figliozzi

Civil and Environmental Engineering Faculty Publications and Presentations

This short communication highlights the value of drone mass and its distribution, a topic that despite its importance has received scant attention in the rapidly growing drone literature. In particular, the focus is on the impact of mass distribution on drone viability, performance, and sustainability.

Implementing Super-Resolution Of Non-Stationary Tides With Wavelets: An Introduction To Cwt_Multi, Matthew Lobo, David A. Jay, Silvia Innocenti, Stefan A. Talke, Steven Dykstra, Pascal Matte

Civil and Environmental Engineering Faculty Publications and Presentations

Tides are often non-stationary due to non-astronomical influences. Investigating variable tidal properties implies a tradeoff between separating adjacent frequencies (using long analysis windows) and resolving their time variations (short windows). Previous continuous wavelet transform (CWT) tidal methods resolved tidal species. Here, we present CWT_Multi, a Matlab code that: a) uses CWT linearity (via the “Response Coefficient Method”) to implement super-resolution (Munk and Hasselman 1964); b) provides a Munk-Hasselman constituent-selection criterion; and c) introduces an objective, time-variable form of inference (“dynamic inference”) based on time-varying data properties. CWT_Multi resolves tidal species on time-scales of days and multiple constituents per species with …

Exploratory Analysis Of Factors Affecting Home Delivery Returns, Michael Bronson, Miguel Figliozzi, Ali Riahi Samani, Sabya Mishra

Civil and Environmental Engineering Faculty Publications and Presentations

E-commerce and house deliveries have experienced a rapid growth in the last two decades. The return of online shopping products is an undesirable side effect of online shopping that has not been properly studied in the transportation literature. Utilizing binary logit models, this research answers two novel research questions focusing on the online shopping channel: (i) What household characteristics are associated with a higher or lower propensity to return online purchases? and (ii) What type of products contribute to positive return delivery rates? To answer these questions models are developed using data collected from a household online survey of e-commerce …

Learned Compressive Representations For Single-Photon 3d Imaging, Felipe Gutierrez-Barragan, Fangzhou Mu, Andrei Ardelean, Atul Ingle, Claudio Bruschini, Edoardo Charbon, Yin Li, Mohit Gupta, Andreas Velten

Computer Science Faculty Publications and Presentations

Single-photon 3D cameras can record the time-of-arrival of billions of photons per second with picosecond accuracy. One common approach to summarize the photon data stream is to build a per-pixel timestamp histogram, resulting in a 3D histogram tensor that encodes distances along the time axis. As the spatio-temporal resolution of the histogram tensor increases, the in-pixel memory requirements and output data rates can quickly become impractical. To overcome this limitation, we propose a family of linear compressive representations of histogram tensors that can be computed efficiently, in an online fashion, as a matrix operation. We design practical lightweight compressive representations …

Machine Learning Predictions Of Electricity Capacity, Marcus Harris, Elizabeth Kirby, Ameeta Agrawal, Rhitabrat Pokharel, Francis Puyleart, Martin Zwick

Complex Systems Faculty Publications and Presentations

This research applies machine learning methods to build predictive models of Net Load Imbalance for the Resource Sufficiency Flexible Ramping Requirement in the Western Energy Imbalance Market. Several methods are used in this research, including Reconstructability Analysis, developed in the systems community, and more well-known methods such as Bayesian Networks, Support Vector Regression, and Neural Networks. The aims of the research are to identify predictive variables and obtain a new stand-alone model that improves prediction accuracy and reduces the INC (ability to increase generation) and DEC (ability to decrease generation) Resource Sufficiency Requirements for Western Energy Imbalance Market participants. This …

Rasterizing Co2 Emissions And Characterizing Their Trends Via An Enhanced Population-Light Index At Multiple Scales In China During 2013–2019, Bin Guo, Tingting Xie, Wencai Zhang, Haojie Wu, Dingming Zhang, Xiaowei Zhu, Xuying Ma, Min Wu, Pingping Luo

Mechanical and Materials Engineering Faculty Publications and Presentations

Climate change caused by CO2 emissions (CE) has received widespread global concerns. Obtaining precision CE data is necessary for achieving carbon peak and carbon neutrality. Significant deficiencies of existing CE datasets such as coarse spatial resolution and low precision can hardly meet the actual requirements. An enhanced population-light index (RPNTL) was developed in this study, which integrates the Nighttime Light Digital Number (DN) Value from the National Polar-orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) and population density to improve CE estimation accuracy. The CE from the Carbon Emission Accounts & Datasets (CEADS) was divided into three sectors, …

Implications Of Physical Fault Injections On Single Chip Motes, Sara Faour, Mališa Vučinić, Filip Maksimovic, David Burnett, Paul Muhlethaler, Thomas Watteyne, Kristofer Pister

Electrical and Computer Engineering Faculty Publications and Presentations

Single-chip motes are wireless sensor nodes that integrate computation, communication, power and sensing on a single chip. We consider the security threats these novel devices are subject to when employed in safety-critical applications. Fault injection attacks are a prominent form of physical attacks that pose a threat to the normal and secure functioning of targeted devices, potentially compromising their intended behavior. These attacks have been studied mainly on commercial off-the-shelf devices which rely on external components such as crystal oscillators and passives. Such external components are absent from single-chip motes, resulting in a uniquely different attack surface compared to commercial …

Highly Power Dense Dc To Three-Phase Ac Modular Converters With Tiny Module Capacitors, Wiwin Hartini Lew

Dissertations and Theses

A Modular Multilevel Converter (MMC) is an attractive candidate in high power conversion due to its modularity and scalability. The energy storage element, namely the module capacitance in the MMC submodule circuit, is typically large and when scaled to convert high power, requires very bulky module capacitors. In addition to deteriorating the power density, the design necessitates the use of electrolytic capacitors, which further affects the overall converter efficiency and reliability. This research presents an MMC submodule topology and the accompanying modulation approach that reduces the submodule capacitance requirements significantly compared to conventional MMC topology (few micro-farads versus several milli-farads). …

Hydraulic Redistribution Under Saline Conditions, Josh Gottlieb

Civil and Environmental Engineering Undergraduate Honors Theses

Water scarcity and soil salinity are dual stressors for plants in arid, salt-affected ecosystems. Hydraulic redistribution, a hydraulic adaptation which moves water through plant roots into dry or saline soil regions along potential gradients, aids plant survival in stressful environments. Recent theory regarding hydraulic redistribution proposes limitations on the process within saline soils. This study applies a minimalist resistor-capacitor model of the soil-plant-atmosphere system to the experimental conditions of a 2010 study investigating hydraulic redistribution in a salt affected area. The effectiveness of the model is evaluated, and a sensitivity analysis is conducted to identify key dynamics affecting the moisture …

Biomechanical And Sensory Feedback Regularize The Behavior Of Different Locomotor Central Pattern Generators, Kaiyu Deng, Alexander J. Hunt, Nicholas Szczecinski, Matthew Tresch, Hillel J. Chiel, Charles Heckman, Roger Quinn

Mechanical and Materials Engineering Faculty Publications and Presentations

This work presents an in-depth numerical investigation into a hypothesized two-layer central pattern generator (CPG) that controls mammalian walking and how different parameter choices might affect the stepping of a simulated neuromechanical model. Particular attention is paid to the functional role of features that have not received a great deal of attention in previous work: the weak cross-excitatory connectivity within the rhythm generator and the synapse strength between the two layers. Sensitivity evaluations of deafferented CPG models and the combined neuromechanical model are performed. Locomotion frequency is increased in two different ways for both models to investigate whether the model’s …

Sensor Formed From Conductive Nanoparticles And A Porous Non-Conductive Substrate, Erik T. Thostenson, Thomas Schumacher

Civil and Environmental Engineering Faculty Publications and Presentations

In various aspects, the sensors include a substrate that is porous and non-conductive with nanoparticles deposited onto the substrate within pores of the substrate by an electrophoretic process to form a sensor element. The nanoparticles are electrically conductive. The sensor includes a detector in communication with the sensor element to measure a change in an electrical property of the sensor element. The change in the electrical property may result from alterations in quantum tunneling between nanoparticles within the sensor element, in various aspects.

Data From: Machine Learning Predictions Of Electricity Capacity, Marcus Harris, Elizabeth Kirby, Ameeta Agrawal, Rhitabrat Pokharel, Francis Puyleart, Martin Zwick

Complex Systems Faculty Datasets

This research applies machine learning methods to build predictive models of Net Load Imbalance for the Resource Sufficiency Flexible Ramping Requirement in the Western Energy Imbalance Market. Several methods are used in this research, including Reconstructability Analysis, developed in the systems community, and more well-known methods such as Bayesian Networks, Support Vector Regression, and Neural Networks. The aims of the research are to identify predictive variables and obtain a new stand-alone model that improves prediction accuracy and reduces the INC (ability to increase generation) and DEC (ability to decrease generation) Resource Sufficiency Requirements for Western Energy Imbalance Market participants. This …

Feasibility Of Tracking Human Kinematics With Simultaneous Localization And Mapping (Slam), Sepehr Laal, Paul Vasilyev, Sean Pearson, Mateo Aboy, James Mcnames

Electrical and Computer Engineering Faculty Publications and Presentations

We evaluated a new wearable technology that fuses inertial sensors and cameras for tracking human kinematics. These devices use on-board simultaneous localization and mapping (SLAM) algorithms to localize the camera within the environment. Significance of this technology is in its potential to overcome many of the limitations of the other dominant technologies. Our results demonstrate this system often attains an estimated orientation error of less than 1^o and a position error of less than 4 cm as compared to a robotic arm. This demonstrates that SLAM’s accuracy is adequate for many practical applications for tracking human kinematics.

Sequential Frame-Interpolation And Dct-Based Video Compression Framework, Yeganeh Jalalpour, Wu-Chi Feng, Feng Liu

Computer Science Faculty Publications and Presentations

Video data is ubiquitous; capturing, transferring, and storing even compressed video data is challenging because it requires substantial resources. With the large amount of video traffic being transmitted on the internet, any improvement in compressing such data, even small, can drastically impact resource consumption. In this paper, we present a hybrid video compression framework that unites the advantages of both DCT-based and interpolation-based video compression methods in a single framework. We show that our work can deliver the same visual quality or, in some cases, improve visual quality while reducing the bandwidth by 10--20%.

Study On The Spatiotemporal Dynamic Of Ground-Level Ozone Concentrations On Multiple Scales Across China During The Blue Sky Protection Campaign, Haoji Wu, Lin Pei, Xiaowei Zhu, Bin Guo, Dingming Zhang, Multiple Additional Authors

Mechanical and Materials Engineering Faculty Publications and Presentations

Surface ozone (O3), one of the harmful air pollutants, generated significantly negative effects on human health and plants. Existing O3 datasets with coarse spatiotemporal resolution and limited coverage, and the uncertainties of O3 influential factors seriously restrain related epidemiology and air pollution studies. To tackle above issues, we proposed a novel scheme to estimate daily O3 concentrations on a fine grid scale (1 km × 1 km) from 2018 to 2020 across China based on machine learning methods using hourly observed ground-level pollutant concentrations data, meteorological data, satellite data, and auxiliary data including digital elevation model (DEM), land use …

Evaluation Of Metaverse Integration Of Freight Fluidity Measurement Alternatives Using Fuzzy Dombi Edas Model, Muhammet Deveci, Ilgin Gokasar, Oscar Castillo, Tugrul Daim

Engineering and Technology Management Faculty Publications and Presentations

Developments in transportation systems, changes in consumerism trends, and conditions such as COVID-19 have increased both the demand and the load on freight transportation. Since various companies are transporting goods all over the world to evaluate the sustainability, speed, and resiliency of freight transportation systems, data and freight fluidity measurement systems are needed. In this study, an integrated decision-making model is proposed to advantage prioritize the freight fluidity measurement alternatives. The proposed model is composed of two main stages. In the first stage, the Dombi norms based Logarithmic Methodology of Additive Weights (LMAW) is used to find the weights of …