Engineering Commons^™

Personalized Digital Phenotype Score, Healthcare Management And Intervention Strategies Using Knowledge Enabled Digital Health Framework For Pediatric Asthma, Utkarshani Jaimini, Amit Sheth

Publications

Asthma is a personalized, and multi-trigger respiratory condition which requires continuous monitoring and management of symptoms and medication adherence. We developed kHealth: Knowledge-enabled Digital Healthcare Framework to monitor and manage the asthma symptoms, medication adherence, lung function, daily activity, sleep quality, indoor, and outdoor environmental triggers of pediatric asthma patients. The kHealth framework collects up to 1852 data points per patient per day. It is practically impossible for the clinicians, parents, and the patient to analyze this vast amount of multimodal data collected from the kHealth framework. In this chapter, we describe the personalized scores, clinically relevant asthma categorization using …

Fourth-Order Comprehensive Adjoint Sensitivity Analysis (4th-Casam) Of Response-Coupled Linear Forward/Adjoint Systems: I. Theoretical Framework, Dan Gabriel Cacuci

Faculty Publications

The most general quantities of interest (called “responses”) produced by the computational model of a linear physical system can depend on both the forward and adjoint state functions that describe the respective system. This work presents the Fourth-Order Comprehensive Adjoint Sensitivity Analysis Methodology (4th-CASAM) for linear systems, which enables the efficient computation of the exact expressions of the 1st-, 2nd-, 3rd-and 4th-order sensitivities of a generic system response, which can depend on both the forward and adjoint state functions, with respect to all of the parameters underlying the respective forward/adjoint systems. Among the best known such system responses are various …

Illustrating Important Effects Of Second-Order Sensitivities On Response Uncertainties In Reactor Physics, Dan Gabriel Cacuci

Faculty Publications

This paper illustrates the relative importance of the largest first- and second-order sensitivities of the leakage response of an OECD/NEA reactor physics benchmark (a polyethylene-reflected plutonium sphere) to the benchmark’s underlying total cross sections. It will be shown that numerous 2nd-order sensitivities of the leakage response with respect to the total cross sections are significantly larger than the largest corresponding 1st-order sensitivities. In particular, the contributions of the 2nd-order sensitivities cause the mean (expected) value of the response to differ appreciably from its computed value and also cause the response distribution to be skewed towards positive values relative to the …

Cyber Social Threats 2021: Ai, Covid-19 Vaccine, Detection And Countering Strategies, Ugur Kursuncu, Jeremy Blackburn, Yelena Mejova, Megan Squire, Amit Sheth

Publications

In recent years, online platforms have been utilized for promoting harmful content and behavior such as extremism, harassment, mis/disinformation, human trafficking, genderbased violence among others affecting our society, often leading to real-world events. Such content and behaviors are inherently complex, making the recognition of these narratives challenging for researchers as well as social media companies. The Cyber Social Threats (CySoc) Workshop 2021 aimed to facilitate a rich forum for researchers and practitioners from both academia and industry in the areas of computing and social science, to discuss novel avenues for research on interdisciplinary aspects of harmful communications on social media, …

Characterization Of Time-Variant And Time-Invariant Assessment Of Suicidality On Reddit Using C-Ssrs, Manas Gaur, Vamsi Aribandi, Amanuel Alambo, Ugur Kursuncu, Krishnaprasad Thirunarayan, Jonathan Beich, Jyotishman Pathak, Amit Sheth

Publications

Suicide is the 10th leading cause of death in the U.S (1999-2019). However, predicting when someone will attempt suicide has been nearly impossible. In the modern world, many individuals suffering from mental illness seek emotional support and advice on well-known and easily-accessible social media platforms such as Reddit. While prior artificial intelligence research has demonstrated the ability to extract valuable information from social media on suicidal thoughts and behaviors, these efforts have not considered both severity and temporality of risk. The insights made possible by access to such data have enormous clinical potential - most dramatically envisioned as a trigger …

Uniform Strain-Dependent Thermal Conductivity Of Pentagonal And Hexagonal Silicene, Huake Liu, Guangzhao Qin, Ming Hu

Faculty Publications

Two-dimensional (2D) pentagonal monolayer structures have shown promising characteristics and fascinating physical and chemical properties. The disparate strain-dependent thermal conductivity of two-dimensional penta-structures was reported, but the difference between the silicon-based pentagonal and hexagonal structures is barely researched. In this work, based on first-principles calculations, we studied the strain-modulated phonon transport behavior of two 2D pentagonal (penta-SiH and bilayer penta-Si) and one hexagonal silicene structures (H-silicene), of which the penta-SiH and H-silicene mean the structures are hydrogenated for the purpose of thermodynamical stability. We found that the silicon-based pentagonal structure also presented a different strain-dependent thermal conductivity from other pentagonal …

Resolving Anodic Current And Temperature Distributions In A Polymer Electrolyte Membrane Water Electrolysis Cell Using A Pseudo-Two-Phase Computational Fluid Dynamics Model, J. Lopata, Z. Kang, J. Young, G. Bender, J. W. Weidner, H-S. Cho, Sirivatch Shimpalee

Faculty Publications

Expanding upon our prior experimental work, we constructed a three-dimensional model of a polymer electrolyte membrane water electrolyzer using computational fluid dynamics. We applied the assumption of pseudo-two-phase flow, the flow of two phases with equal velocity. Experimental data were used to obtain parameters and to determine the conditions under which this model was valid. Anodic distributions of current density, temperature, liquid saturation, and relative humidity were obtained at various flow rates. The overall current density and temperature difference from inlet to outlet at the anode agreed strongly with experimental measurements under most circumstances. This verification allowed us to further …

Real-Time Motion Tracking Of Cognitive Baxter Robot Based On Differential Inverse Kinematics, Shaobo Li, Xingxing Zhang, Jing Yang, Qiang Bai, Jianjun Hu, Qisong Song, Zhiang Li

Faculty Publications

The tracking motion of the robot is realized based on a specific robot or relying on an expensive movement acquisition system. It has the problems of complex control procedures, lack of real-time performance, and difficulty in achieving secondary development. We propose a robot real-time tracking control method based on the control principle of differential inverse kinematics, which fuses the position and joint angle information of the robot’s actuators to realize the real-time estimation of the user’s movement during the tracking process. The motion coordinates of each joint of the robot are calculated and the coordinate conversion between man and machine …

Demo Abstract: Porting And Execution Of Anomalies Detection Models On Embedded Systems In Iot, Bharath Sudharsan, Pankesh Patel, Abdul Wahid, Muhammad Yahya, John G. Breslin, Muhammad Intizar Ali

Publications

In the Industry 4.0 era, Microcontrollers (MCUs) based tiny embedded sensor systems have become the sensing paradigm to interact with the physical world. In 2020, 25.6 billion MCUs were shipped, and over 250 billion MCUs are already operating in the wild. Such low-power, low-cost MCUs are being used as the brain to control diverse applications and soon will become the global digital nervous system. In an Industrial IoT setup, such tiny MCU-based embedded systems are equipped with anomaly detection models and mounted on production plant machines for monitoring the machine’s health/condition. These models process the machine’s health data (from temperature, …

A Critical Review On The Development Of Ionic Liquids-Based Nanofluids As Heat Transfer Fluids For Solar Thermal Energy, Titan C. Paul, Amitav Tikadar, Rajib Mahamud, Azzam S. Salman, A.K.M. Monjur Morshed, Jamil A. Khan

Faculty Publications

In recent years, solar thermal energy (STE) has attracted energy researchers because of its higher efficacy compared to the photovoltaic solar cell. STE is one of the forms of solar energy whereby heat is transferred via a secondary medium called heat transfer fluids (HTFs). Therefore, the overall performance of STE depends on the thermophysical properties and thermal performance of the HTFs. Traditional HTFs suffer from low decomposition temperature, high melting point, and higher vapor pressure. To overcome these limitations, researchers have recently begun working on new HTFs for STE. Ionic liquids (ILs) are considered as a potential candidate for the …

Editors’ Choice-Examining Performance And Durability Of Anion Exchange Membrane Fuel Cells With Novel Spirocyclic Anion Exchange Membranes, Ami C. Yang-Neyerlin, Samantha Medina, Kelly M. Meek, Derek J. Strasser, Cheng He, Daniel M. Knauss, Mustain E William, Svitlana Pylypenko, Bryan S. Pivovar

Faculty Publications

A series of spirocyclic copolymer membranes with varying ion exchange capacities (IECs) were investigated to probe the impact of polymer properties on in situ fuel cell performance and stability. In-situ electrochemical tests and post-mortem electron microscopy analysis of cross-sectioned membrane electrode assemblies (MEAs) have been combined with voltage loss breakdown analysis to evaluate the performance and degradation of different MEAs, and to probe the catalyst morphology and electrode structure at different stages of operation. Voltage loss breakdown results show that membrane degradation and kinetic losses played only a minor role in observed performance degradation and that performance losses were primarily …

Agent-Based Coordinated Control Of Power Electronic Converters In A Microgrid, Maryam Nasri, Hebert L. Ginn Iii, Mehrdad Moallem

Faculty Publications

This paper presents the implementation of an agent-based architecture suitable for the coordination of power electronic converters in stand-alone microgrids. To this end, a publish-subscribe agent architecture was utilized as a distributed microgrid control platform. Over a distributed hash table (DHT) searching overlay, the publish-subscribe architecture was identified based on a numerical analysis as a scalable agent-based technology for the distributed real-time coordination of power converters in microgrids. The developed framework was set up to deploy power-sharing distributed optimization algorithms while keeping a deterministic time period of a few tens of milliseconds for a system with tens of converters and …

Owsnet: Towards Real-Time Offensive Words Spotting Network For Consumer Iot Devices, Bharath Sudharsan, Sweta Malik, Peter Corcoran, Pankesh Patel, John G. Breslin, Muhammad Intizar Ali

Publications

Every modern household owns at least a dozen of IoT devices like smart speakers, video doorbells, smartwatches, where most of them are equipped with a Keyword spotting(KWS) system-based digital voice assistant like Alexa. The state-of-the-art KWS systems require a large number of operations, higher computation, memory resources to show top performance. In this paper, in contrast to existing resource-demanding KWS systems, we propose a light-weight temporal convolution based KWS system named OWSNet, that can comfortably execute on a variety of IoT devices around us and can accurately spot multiple keywords in real-time without disturbing the device's routine functionalities.

When OWSNet …

Mlatticeabc: Generic Lattice Constant Prediction Of Crystal Materials Using Machine Learning, Yuxin Li, Wenhui Yang, Rongzhi Dong, Jianjun Hu

Faculty Publications

Lattice constants such as unit cell edge lengths and plane angles are important parameters of the periodic structures of crystal materials. Predicting crystal lattice constants has wide applications in crystal structure prediction and materials property prediction. Previous work has used machine learning models such as neural networks and support vector machines combined with composition features for lattice constant prediction and has achieved a maximum performance for cubic structures with an average coefficient of determination (R2) of 0.82. Other models tailored for special materials family of a fixed form such as ABX3 perovskites can achieve much higher performance due …

Cognitive Digital Twins For Smart Manufacturing, Muhammad Intizar Ali, Pankesh Patel, John G. Breslin, Ramy Harik, Amit Sheth

Publications

Smart manufacturing or Industry 4.0, a trend initiated a decade ago, aims to revolutionize traditional manufacturing using technology-driven approaches. Modern digital technologies such as the Industrial Internet of Things (IIoT), Big Data Analytics, Augmented/Virtual Reality, and Artificial Intelligence (AI) are the key enablers of new smart manufacturing approaches. The digital twin is an emerging concept whereby a digital replica can be built of any physical object. Digital twins are becoming mainstream; many organizations have started to rely on digital twins to monitor, analyze, and simulate physical assets and processes. The current use of digital twins for smart manufacturing is largely …

High In-Plane Thermal Conductivity Of Aluminum Nitride Thin Films, Md Shafkat Bin Hoque, Yee Rui Koh, Jeffrey L. Braun, Abdullah Mamun, Zeyu Liu, Kenny Huynh, Micheal E. Liao, Kamal Hussain, Zhe Cheng, Eric R. Hoglund, David H. Olson, John A. Tomko, Kiumars Aryana, Roisul Galib, John T. Gaskins, Mirza Mohammad Mahbube Elahi, Zayd C. Leseman, James M. Howe, Tengfei Luo, Samuel Graham, Mark S. Goorsky, Asif Khan, Patrick E. Hopkins

Faculty Publications

High thermal conductivity materials show promise for thermal mitigation and heat removal in devices. However, shrinking the length scales of these materials often leads to significant reductions in thermal conductivities, thus invalidating their applicability to functional devices. In this work, we report on high in-plane thermal conductivities of 3.05, 3.75, and 6 μm thick aluminum nitride (AlN) films measured via steady-state thermoreflectance. At room temperature, the AlN films possess an in-plane thermal conductivity of ∼260 ± 40 W m–1 K–1, one of the highest reported to date for any thin film material of equivalent thickness. At low temperatures, the in-plane …

Unified Multi-Objective Genetic Algorithm For Energy Efficient Job Shop Scheduling, Hongjong Wei, Shaobo Li, Huageng Quan, Dacheng Liu, Shu Rao, Chuanjiang Li, Jianjun Hu

Faculty Publications

In recent years, people have paid more and more attention to traditional manufacturing’s environmental impact, especially in terms of energy consumption and related emissions of carbon dioxide. Except for adopting new equipment, production scheduling could play an important role in reducing the total energy consumption of a manufacturing plant. Machine tools waste a considerable amount of energy because of their underutilization. Consequently, energy saving can be achieved by switching machines to standby or off when they lay idle for a comparatively long period. Herein, we first introduce the objectives of minimizing non-processing energy consumption, total weighted tardiness and earliness, and …

Hybrid Lattice Boltzmann Agglomeration Method For Modeling Transport Phenomena In Polymer Electrolyte Membrane Fuel Cells, P. Satjaritanun, F. C. Cetinbas, S. Hirano, I. V. Zenyuk, R. K. Ahluwalia, Sirivatch Shimpalee

Faculty Publications

The Hybrid Lattice Boltzmann Agglomeration Method (HLBAM) was employed to model transport phenomena and electrochemical kinetics in the catalyst layer of a polymer electrolyte membrane fuel cell (PEMFC). This work showed the advantages of using a direct modeling-based HLBAM approach, which incorporates the detailed structure of catalyst layers from X-ray computed tomography as well as local transport variables related characteristics and effective properties from the hybrid catalyst microstructure. The local transport variables and effective properties from the hybrid catalyst model were used to simulate the electrochemical kinetics inside the detailed structure of the catalyst layer. HLBAM can predict the distribution …

Machine Learning Meets Internet Of Things: From Theory To Practice, Bharath Sudharsan, Pankesh Patel

Publications

Standalone execution of problem-solving Artificial Intelligence (AI) on IoT devices produces a higher level of autonomy and privacy. This is because the sensitive user data collected by the devices need not be transmitted to the cloud for inference. The chipsets used to design IoT devices are resource-constrained due to their limited memory footprint, fewer computation cores, and low clock speeds. These limitations constrain one from deploying and executing complex problem-solving AI (usually an ML model) on IoT devices. Since there is a high potential for building intelligent IoT devices, in this tutorial, we teach researchers and developers; (i) How to …

Covid-19: Insights Into Virus-Receptor Interactions, Azadeh Sepahvandi, Maryann Ghaffari, Amir Hossein Bahmanpour, Fathollah Moztarzadeh, Payam Zarrintaj, Hasan Uludağ, Masoud Mozafari

Faculty Publications

The recent outbreak of Coronavirus Disease 2019 (COVID-19) calls for rapid mobilization of scientists to probe and explore solutions to this deadly disease. A limited understanding of the high transmissibility of SARS-CoV-2 (Severe acute respiratory syndrome coronavirus 2) relative to other coronavirus strains guides a deeper investigation into the virus/receptor interactions. The cutting-edge studies in thermodynamic and kinetic properties of interactions such as protein-protein interplays have been reviewed in many modeling and analysis studies. Highlighting the thermodynamic assessments of biological interactions and emphasizing the boosted transmissibility of SARS-CoV-2 despite its high similarity in structure and sequence with other coronavirus strains …

Effect Of Defects Part Ii: Multiscale Effect Of Microvoids, Orientation Of Rivet Holes On The Damage Propagation, And Ultimate Failure Strength Of Composites, Vahid Tavaf, Mohammadsadegh Saadatzi, Sourav Banerjee

Faculty Publications

Material properties at the vicinity of the cut-outs in composites are not entirely defect-free. The nteraction of multiple cutouts like rivet holes, the repercussion of their configuration on crack propagation, and ultimate strength were predicted using Peridynamic method and the results are reported in this article. The effect of microscale defects at the vicinity of the cutouts on macroscale damage propagation were shown to have quantifiable manifestation. This study focused on two to four holes in unidirectional composite plates with 0°, 45°, and 90° fiber directions, while the vicinity of a hole was considered degraded. Numerical results were validated using …

Identification Of Active Surface Species In Molten Carbonates Using In Situ Raman Spectroscopy, Peng Zhang, Tao Wu, Kevin Huang

Faculty Publications

Here we report the results of a study on active surface species of a pristine and modified (Li-Na)₂CO₃ eutectic using in situ Raman spectroscopy technique. The effects of gas compositions, temperature, time, and alkaline earth have been systematically studied. The species of CO₄^2–, HCO₄^–, and C₂O₅^2– are identified as the three major active species on the surface of (Li-Na)₂CO₃ eutectic by a combined Raman spectroscopy and theoretical density functional theory calculations. The results further reveal that CO₄^2–, HCO₄^–, …

Multi-Robot Coordination With Environmental Disturbances, Adem Coskun

Theses and Dissertations

Multi-robot systems are increasingly deployed in environments where they interact with humans. From the perspective of a robot, such interaction could be considered a disturbance that causes a well-planned trajectory to fail. This dissertation addresses the problem of multi-robot coordination in scenarios where the robots may experience unexpected delays in their movements.

Prior work by Čáp, Gregoire, and Frazzoli introduced a control law, called RMTRACK, which enables robots in such scenarios to execute pre-planned paths in spite of disturbances that affect the execution speed of each robot while guaranteeing that each robot can reach its goal without collisions and without …

Hydrothermal Synthesis And Structural Investigation Of A Crystalline Uranyl Borosilicate, Kristen A. Pace, Vladislav V. Klepov, Mark D. Smith, Travis Williams, Gregory Morrison, Jochen A. Lauterbach, Scott T. Misture, Hans Conrad Zur Loye

Faculty Publications

The relevance of multidimensional and porous crystalline materials to nuclear waste reme-diation and storage applications has motivated exploratory research focused on materials discovery of compounds, such as actinide mixed-oxoanion phases, which exhibit rich structural chemistry. The novel phase K1.8 Na1.2 [(UO2)BSi4 O12 ] has been synthesized using hydrothermal methods, rep-resenting the first example of a uranyl borosilicate. The three-dimensional structure crystallizes in the orthorhombic space group Cmce with lattice parameters a = 15.5471(19) Å, b = 14.3403(17) Å, c = 11.7315(15) Å, and V = 2615.5(6) Å3, and is composed of UO6 octahedra linked by [BSi4 O12 ]5− chains to …

High-Order Wave-Damage Interaction Coefficients (Wdic) Extracted Through Modal Decomposition, Hanfei Mei, Victor Giurgiutiu

Faculty Publications

This paper presents a new technique for the extraction of high-order wave-damage interaction coefficients (WDIC) through modal decomposition. The frequency and direction dependent complex-valued WDIC are used to model the scattering and mode conversion phenomena of guided wave interaction with damage. These coefficients are extracted from the harmonic analysis of local finite element model (FEM) mesh with non-reflective boundaries (NRB) and they are capable of describing the amplitude and phase of the scattered waves as a function of frequency and direction. To extract the WDIC of each wave mode, all the possible propagating wave modes are considered to be scattered …

Prediction Of Residual Stress And Distortion In Laser Powder Bed Fusion Additive Manufacturing, Bhanuprakash Sairam Kosaraju

Theses and Dissertations

Additive Manufacturing (AM) has its proven advantages to unlock the design space and manufacturing capabilities for complex geometries with lightweights. Distortion is one of the most common defects that occur in Laser Powder Bed Fusion Additive Manufacturing (LPBFAM), which is caused by the significant residual stress during the printing process. This can lead to numerous process iterations to achieve the requisite form and fit tolerances.

In this study, Finite Element (FE) model that utilizes the element birth approach was developed to predict the residual stress and distortion in the LPBFAM process. The methodology leverages a simplified approach where the detailed …

Anisotropic Wave Behavior In Isotropic Material With Orthogonal Surface Perturbation, Khaleda Akter

Theses and Dissertations

Elastic wave propagation in anisotropic media is of great interest in various branches of engineering and applied sciences. In this study, an anisotropic wave propagation behavior in isotropic material with orthogonal surface perturbation is presented. The conventional method of estimating dispersion equations for isotropic material is to apply Helmholtz decomposition on the potential functions for Rayleigh-Lamb wave and Shear Horizontal (SH) waves. However, the presence of isotropic material with orthogonal surface perturbations in two coordinate directions significantly affect the wave propagation behavior due to its direction dependency, and hence, the Helmholtz decomposition of the potential functions cannot be applied to …

Degradative Processes Of Commercial And Next-Generation Lithium-Ion Battery Materials, Benjamin Ng

Theses and Dissertations

The work embodied in this thesis bridges the gap between modern and next-generation Li-ion batteries (LIBs). First, a detailed study of the complex interfacial interactions (e.g. electrode/electrolyte, particle/particle, particle/solid-electrolyte interphase) in existing LIBs (graphite anode, Li(Ni_0.5Mn_0.3Co_0.2)O_2 cathode) are investigated and then used to develop strategies for safer, more energy-dense, and more durable electrode materials (i.e. tailored hybrid materials). The first portion of this thesis focuses heavily on decoupling the complex thermodynamics, reaction kinetics, and mass transport properties in commercially available LIBs. This thesis includes a detailed investigation into the operating parameter space for LIBs, including temperature (-30^oC to +52^oC), state-of-charge …

Sonodegradation Of Amitriptyline And Ibuprofen In The Presence Of Mxene, Minjung Jeon

Theses and Dissertations

Environmental pollution has intensified and accelerated due to a steady increase in the number of industries, and finding methods to remove hazardous contaminants, which can be typically divided into inorganic and organic compounds, have become inevitable. One of the widely used water treatment technologies is adsorption and various kinds of adsorbents for the removal of inorganic and organic contaminants from water have been discovered. Recently, MXene, as an emerging nanomaterial, has gained rapid attention owing to its unique characteristics and various applicability. Particularly, in the area of adsorptive application, MXene and MXene-based adsorbents have shown great potential in a large …

Preferential Vaporization Potential Of Crude Oils And Its Impact On Flame Flashback Behaviors, Ayuob Al Wahaibi

Theses and Dissertations

As combined cycle gas turbines for power generation operating on light distillate fuels provide a sufficient energy, there is a global trend in using heavy liquids (e.g. HFO, crude oils) for direct-firing in gas turbine. However, using these heavy fuels imposes many challenges due to their wide range of physical/chemical properties, which control near-limit combustion behaviors, such lean blow-out and flashback. In addition, the ignition propensity of these heavy fuels is not reported in crude assays, and utilizing a simple, with small sample, and quick methodology to characterize the ignition propensity is important in determining the fuel quality.

In this …