Engineering Commons^™

Evaluation Of Standard And Semantically-Augmented Distance Metrics For Neurology Patients, Daniel B. Hier, Jonathan Kopel, Steven U. Brint, Donald C. Wunsch, Gayla R. Olbricht, Sima Azizi, Blaine Allen

Electrical and Computer Engineering Faculty Research & Creative Works

Background: Patient distances can be calculated based on signs and symptoms derived from an ontological hierarchy. There is controversy as to whether patient distance metrics that consider the semantic similarity between concepts can outperform standard patient distance metrics that are agnostic to concept similarity. The choice of distance metric can dominate the performance of classification or clustering algorithms. Our objective was to determine if semantically augmented distance metrics would outperform standard metrics on machine learning tasks.

Methods: We converted the neurological findings from 382 published neurology cases into sets of concepts with corresponding machine-readable codes. We calculated patient distances by …

Action Recognition In Manufacturing Assembly Using Multimodal Sensor Fusion, Md. Al-Amin, Wenjin Tao, David Doell, Ravon Lingard, Zhaozheng Yin, Ming-Chuan Leu, Ruwen Qin

Computer Science Faculty Research & Creative Works

Production innovations are occurring faster than ever. Manufacturing workers thus need to frequently learn new methods and skills. In fast changing, largely uncertain production systems, manufacturers with the ability to comprehend workers' behavior and assess their operation performance in near real-time will achieve better performance than peers. Action recognition can serve this purpose. Despite that human action recognition has been an active field of study in machine learning, limited work has been done for recognizing worker actions in performing manufacturing tasks that involve complex, intricate operations. Using data captured by one sensor or a single type of sensor to recognize …

Multicellular Models Bridging Intracellular Signaling And Gene Transcription To Population Dynamics, Mohammad Aminul Islam, Satyaki Roy, Sajal K. Das, Dipak Barua

Computer Science Faculty Research & Creative Works

Cell signaling and gene transcription occur at faster time scales compared to cellular death, division, and evolution. Bridging these multiscale events in a model is computationally challenging. We introduce a framework for the systematic development of multiscale cell population models. Using message passing interface (MPI) parallelism, the framework creates a population model from a single-cell biochemical network model. It launches parallel simulations on a single-cell model and treats each stand-alone parallel process as a cell object. MPI mediates cell-to-cell and cell-to-environment communications in a server-client fashion. In the framework, model-specific higher level rules link the intracellular molecular events to cellular …

Early Detection Of Disease Using Electronic Health Records And Fisher's Wishart Discriminant Analysis, Sijia Yang, Jian Bian, Zeyi Sun, Licheng Wang, Haojin Zhu, Haoyi Xiong, Yu Li

Engineering Management and Systems Engineering Faculty Research & Creative Works

Linear Discriminant Analysis (LDA) is a simple and effective technique for pattern classification, while it is also widely-used for early detection of diseases using Electronic Health Records (EHR) data. However, the performance of LDA for EHR data classification is frequently affected by two main factors: ill-posed estimation of LDA parameters (e.g., covariance matrix), and "linear inseparability" of the EHR data for classification. To handle these two issues, in this paper, we propose a novel classifier FWDA -- Fisher's Wishart Discriminant Analysis, which is developed as a faster and robust nonlinear classifier. Specifically, FWDA first surrogates the distribution of "potential" inverse …

Worker Activity Recognition In Smart Manufacturing Using Imu And Semg Signals With Convolutional Neural Networks, Wenjin Tao, Ze-Hao Lai, Ming-Chuan Leu, Zhaozheng Yin

Mechanical and Aerospace Engineering Faculty Research & Creative Works

In a smart manufacturing system involving workers, recognition of the worker's activity can be used for quantification and evaluation of the worker's performance, as well as to provide onsite instructions with augmented reality. In this paper, we propose a method for activity recognition using Inertial Measurement Unit (IMU) and surface electromyography (sEMG) signals obtained from a Myo armband. The raw 10-channel IMU signals are stacked to form a signal image. This image is transformed into an activity image by applying Discrete Fourier Transformation (DFT) and then fed into a Convolutional Neural Network (CNN) for feature extraction, resulting in a high-level …

Modeling Of Cloud-Based Digital Twins For Smart Manufacturing With Mt Connect, Liwen Hu, Ngoc-Tu Nguyen, Wenjin Tao, Ming-Chuan Leu, Xiaoqing Frank Liu, Rakib Shahriar, S M Nahian Al Sunny

Mechanical and Aerospace Engineering Faculty Research & Creative Works

The common modeling of digital twins uses an information model to describe the physical machines. The integration of digital twins into productive cyber-physical cloud manufacturing (CPCM) systems imposes strong demands such as reducing overhead and saving resources. In this paper, we develop and investigate a new method for building cloud-based digital twins (CBDT), which can be adapted to the CPCM platform. Our method helps reduce computing resources in the information processing center for efficient interactions between human users and physical machines. We introduce a knowledge resource center (KRC) built on a cloud server for information intensive applications. An information model …

Design The Capacity Of Onsite Generation System With Renewable Sources For Manufacturing Plant, Xiao Zhong, Md Monirul Islam, Haoyi Xiong, Zeyi Sun

Computer Science Faculty Research & Creative Works

The utilization of onsite generation system with renewable sources in manufacturing plants plays a critical role in improving the resilience, enhancing the sustainability, and bettering the cost effectiveness for manufacturers. When designing the capacity of onsite generation system, the manufacturing energy load needs to be met and the cost for building and operating such onsite system with renewable sources are two critical factors need to be carefully quantified. Due to the randomness of machine failures and the variation of local weather, it is challenging to determine the energy load and onsite generation supply at different time periods. In this paper, …

Learning Curve Analysis Using Intensive Longitudinal And Cluster-Correlated Data, Xiao Zhong, Zeyi Sun, Haoyi Xiong, Neil Heffernan, Md Monirul Islam

Engineering Management and Systems Engineering Faculty Research & Creative Works

Intensive longitudinal and cluster-correlated data (ILCCD) can be generated in any situation where numerical or categorical characteristics of multiple individuals or study units are observed and measured at tens, hundreds, or thousands of occasions. The spacing of measurements in time for each individual can be regular or irregular, fixed or random, and the number of characteristics measured at each occasion may be few or many. Such data can also arise in situations involving continuous-time measurements of recurrent events. Generalized linear models (GLMs) are usually considered for the analysis of correlated non-normal data, while multivariate analysis of variance (MANOVA) is another …

Homogenization Of Plastic Deformation In Heterogeneous Lamella Structures, Rui Yuan, Irene J. Beyerlein, Caizhi Zhou

Materials Science and Engineering Faculty Research & Creative Works

It has been shown that unlike its constituent nanocrystalline (NC) phase, a heterogeneous lamella (HL) composite comprising NC and coarse-grain layers exhibits greatly improved ductility. To understand the origin of this enhancement, we present a 3D discrete dislocation, crystal plasticity finite element model to study the development of strains across this microstructure. Here we show that the HL structure homogenizes the plastic strains in the NC layer, weakening the effect of strain concentrations. These findings can provide valuable insight into the effects of material length scales on material instabilities, which is needed to design heterogeneous structures with superior properties.

Shape Analysis Of Traffic Flow Curves Using A Hybrid Computational Analysis, Wasim Irshad Kayani, Shikhar P. Acharya, Ivan G. Guardiola, Donald C. Wunsch, B. Schumacher, Isaac Wagner-Muns

Engineering Management and Systems Engineering Faculty Research & Creative Works

This paper highlights and validates the use of shape analysis using Mathematical Morphology tools as a means to develop meaningful clustering of historical data. Furthermore, through clustering more appropriate grouping can be accomplished that can result in the better parameterization or estimation of models. This results in more effective prediction model development. Hence, in an effort to highlight this within the research herein, a Back-Propagation Neural Network is used to validate the classification achieved through the employment of MM tools. Specifically, the Granulometric Size Distribution (GSD) is used to achieve clustering of daily traffic flow patterns based solely on their …

Computational Fluid Dynamics Study Of Molten Steel Flow Patterns And Particle-Wall Interactions Inside A Slide-Gate Nozzle By A Hybrid Turbulent Model, Mahdi Mohammadi-Ghaleni, Mohsen Asle Zaeem, Jeffrey D. Smith, Ronald J. O'Malley

Materials Science and Engineering Faculty Research & Creative Works

Melt flow patterns and turbulence inside a slide-gate throttled submerged entry nozzle (SEN) were studied using Detached–Eddy Simulation (DES) model, which is a combination of Reynolds–Averaged Navier–Stokes (RANS) and Large–Eddy Simulation (LES) models. The DES switching criterion between RANS and LES was investigated to closely reproduce the flow structures of low and high turbulence regions similar to RANS and LES simulations, respectively. The melt flow patterns inside the nozzle were determined by k–ε (a RANS model), LES, and DES turbulent models, and convergence studies were performed to ensure reliability of the results. Results showed that the DES model has significant …

High-Frequency Instabilities Of Stationary Crossflow Vortices In A Hypersonic Boundary Layer, Fei Li, Meelan Choudhari, Pedro Paredes-Gonzalez, Lian Duan

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Hypersonic boundary layer flows over a circular cone at moderate incidence angle can support strong crossflow instability in between the windward and leeward rays on the plane of symmetry. Due to more efficient excitation of stationary crossflow vortices by surface roughness, such boundary layer flows may transition to turbulence via rapid amplification of the high-frequency secondary instabilities of finite-amplitude stationary crossflow vortices. The amplification characteristics of these secondary instabilities are investigated for crossflow vortices generated by an azimuthally periodic array of roughness elements over a 7° half-angle circular cone in a Mach 6 free stream. The analysis is based on …

The Anisotropy Of Hexagonal Close-Packed And Liquid Interface Free Energy Using Molecular Dynamics Simulations Based On Modified Embedded-Atom Method, Ebrahim Asadi, Mohsen Asle Zaeem

Materials Science and Engineering Faculty Research & Creative Works

This work aims to comprehensively study the anisotropy of the hexagonal close-packed (HCP)-liquid interface free energy using molecular dynamics (MD) simulations based on the modified-embedded atom method (MEAM). As a case study, all the simulations are performed for Magnesium (Mg). The solid-liquid coexisting approach is used to accurately calculate the melting point and melting properties. Then, the capillary fluctuation method (CFM) is used to determine the HCP-liquid interface free energy (γ) and anisotropy parameters. In CFM, a continuous order parameter is employed to accurately locate the HCP-liquid interface location, and the HCP symmetry-adapted spherical harmonics are used to expand γ …

Geometric Consideration Of Nanostructures For Energy Storage Systems, Jonghyun Park, Jie Li, Wei Lu, Ann Marie Sastry

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Battery performance and its fade are determined by various aspects such as the transport of ions and electrons through heterogeneous internal structures; kinetic reactions at the interfaces; and the corresponding interplay between mechanical, chemical, and thermal responses. The fundamental factor determining this complex multiscale and multiphysical nature of a battery is the geometry of active materials. In this work, we systematically consider the tradeoffs among a selection of limiting geometries of media designed to store ions or other species via a diffusion process. Specifically, we begin the investigation by considering diffusion in spheres, rods, and plates at the particle level, …

Ionic And Electronic Conductivities Of Atomic Layer Deposition Thin Film Coated Lithium Ion Battery Cathode Particles, Rajankumar L. Patel, Jonghyun Park, Xinhua Liang

Mechanical and Aerospace Engineering Faculty Research & Creative Works

It is imperative to ascertain the ionic and electronic components of the total conductivity of an electrochemically active material. A blocking technique, called the “Hebb-Wagner method”, is normally used to explain the two components (ionic and electronic) of a mixed conductor, in combination with the complex ac impedance method and dc polarization measurements. CeO₂ atomic layer deposition (ALD)-coated and uncoated, LiMn₂O₄ (LMO) and LiMn_1.5Ni_0.5O₄ (LMNO) powders were pressed into pellets and then painted with silver to act as a blocking electrode. The electronic conductivities were derived from the currents obtained using …

Silicon-Wall Interfacial Free Energy Via Thermodynamics Integration, Wan Shou, Heng Pan

Mechanical and Aerospace Engineering Faculty Research & Creative Works

We compute the interfacial free energy of a silicon system in contact with flat and structured walls by molecular dynamics simulation. The thermodynamics integration method, previously applied to Lennard-Jones potentials [R. Benjamin and J. Horbach, J. Chem. Phys. 137, 044707 (2012)], has been extended and implemented in Tersoff potentials with two-body and three-body interactions taken into consideration. The thermodynamic integration scheme includes two steps. In the first step, the bulk Tersoff system is reversibly transformed to a state where it interacts with a structureless flat wall, and in a second step, the flat structureless wall is reversibly transformed into an …

Coupled Crystal Orientation-Size Effects On The Strength Of Nano Crystals, Rui Yuan, Irene J. Beyerlein, Caizhi Zhou

Materials Science and Engineering Faculty Research & Creative Works

We study the combined effects of grain size and texture on the strength of nanocrystalline copper (Cu) and nickel (Ni) using a crystal-plasticity based mechanics model. Within the model, slip occurs in discrete slip events exclusively by individual dislocations emitted statistically from the grain boundaries. We show that a Hall-Petch relationship emerges in both initially texture and non-textured materials and our values are in agreement with experimental measurements from numerous studies. We find that the Hall-Petch slope increases with texture strength, indicating that preferred orientations intensify the enhancements in strength that accompany grain size reductions. These findings reveal that texture …

Clustering Data Of Mixed Categorical And Numerical Type With Unsupervised Feature Learning, Dao Lam, Mingzhen Wei, Donald C. Wunsch

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Mixed-type categorical and numerical data are a challenge in many applications. This general area of mixed-type data is among the frontier areas, where computational intelligence approaches are often brittle compared with the capabilities of living creatures. In this paper, unsupervised feature learning (UFL) is applied to the mixed-type data to achieve a sparse representation, which makes it easier for clustering algorithms to separate the data. Unlike other UFL methods that work with homogeneous data, such as image and video data, the presented UFL works with the mixed-type data using fuzzy adaptive resonance theory (ART). UFL with fuzzy ART (UFLA) obtains …

System And Process For Upgrading Hydrocarbons, Dennis N. Bingham, Kerry M. Klingler, Joseph D. Smith, Terry D. Turner, Bruce M. Wilding

Chemical and Biochemical Engineering Faculty Research & Creative Works

In one embodiment, a system for upgrading a hydrocarbon material may include a black wax upgrade subsystem and a molten salt gasification (MSG) subsystem. The black wax upgrade subsystem and the MSG subsystem may be located within a common pressure boundary, such as within a pressure vessel. Gaseous materials produced by the MSG subsystem may be used in the process carried out within the black wax upgrade subsystem. For example, hydrogen may pass through a gaseous transfer interface to interact with black wax feed material to hydrogenate such material during a cracking process. In one embodiment, the gaseous transfer interface …

Real Time Mission Planning, Emad William Saad, Stefan Richard Bieniawski, Paul Edward Riley Pigg, John Lyle Vian, Paul Michael Robinette, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

The different advantageous embodiments provide a system comprising a number of computers, a graphical user interface, first program code stored on the computer, and second program code stored on the computer. The graphical user interface is executed by a computer in the number of computers. The computer is configured to run the first program code to define a mission using a number of mission elements. The computer is configured to run the second program code to generate instructions for a number of assets to execute the mission and monitor the number of assets during execution of the mission.

Preface, Gennady Fridman, Jeremy Levesley, Ivan Tyukin, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

In August 2014 a conference on “Model reduction across disciplines” was held in Leicester, UK. As a scientific field, model reduction is an important part of mathematical modelling and data analysis with very wide areas of applications. The main scientific goal of the conference was to facilitate interdisciplinary discussion of model reduction and coarse-graining methodologies in order to reveal their general mathematical nature. This time, however, the conference had an additional personal and more profound mission – it was dedicated to the 60th birthday of Professor Alexander Gorban (albeit with some delay) whose fantastic achievements in applying model reduction techniques …

Methods And Systems For Biclustering Algorithm, Donald C. Wunsch, Rui Xu, Sejun Kim

Electrical and Computer Engineering Faculty Research & Creative Works

Methods and systems for improved unsupervised learning are described. The unsupervised learning can consist of biclustering a data set, e.g., by biclustering subsets of the entire data set. In an example, the biclustering does not include feeding know and proven results into the biclustering methodology or system. A hierarchical approach can be used that feeds proven clusters back into the biclustering methodology or system as the input. Data that does not cluster may be discarded. Thus, a very large unknown data set can be acted on to learn about the data. The system is also amenable to parallelization.

Systems, Methods And Devices For Vector Control Of Permanent Magnet Synchronous Machines Using Artificial Neural Networks, Shuhui Li, Michael Fairbank, Xingang Fu, Donald C. Wunsch, Eduardo Alonso

Electrical and Computer Engineering Faculty Research & Creative Works

An example method for controlling an AC electrical machine can include providing a PWM converter operably connected between an electrical power source and the AC electrical machine and providing a neural network vector control system operably connected to the PWM converter. The control system can include a current-loop neural network configured to receive a plurality of inputs. The current-loop neural network can be configured to optimize the compensating dq-control voltage. The inputs can be d- and q-axis currents, d- and q-axis error signals, predicted d- and q-axis current signals, and a feedback compensating dq-control voltage. The d- and q-axis error …

Producing High Strength Aluminum Alloy By Combination Of Equal Channel Angular Pressing And Bake Hardening, Hamid Alihosseini, Mohsen Asle Zaeem, Kamran Dehghani, Ghader Faraji

Materials Science and Engineering Faculty Research & Creative Works

A combination of severe plastic deformation by equal channel angular pressing (ECAP) and bake hardening (BH) was used to produce high strength ultrafine-grained AA6061 aluminum alloy. 2, 4 and 8 passes of ECAP were performed, and the bake hardenability of samples was tested by 6% pre-straining followed by baking at 200 °C for 20 min. The microstructures obtained for various passes of ECAP were characterized by XRD, EBSD, and TEM techniques. The microstructures were refined from an average grain size of 20 µm to 212 nm after 8 passes of ECAP. Maximum bake hardenability of 110 MPa, and final yield …

Dynamic Phases, Pinning, And Pattern Formation For Driven Dislocation Assemblies, Caizhi Zhou, Charles Reichhardt, Cynthia Olson Reichhardt, Irene J. Beyerlein

Materials Science and Engineering Faculty Research & Creative Works

We examine driven dislocation assemblies and show that they can exhibit a set of dynamical phases remarkably similar to those of driven systems with quenched disorder such as vortices in superconductors, magnetic domain walls, and charge density wave materials. These phases include pinned-jammed, fluctuating, and dynamically ordered states, and each produces distinct dislocation patterns as well as specific features in the noise fluctuations and transport properties. Our work suggests that many of the results established for systems with quenched disorder undergoing plastic depinning transitions can be applied to dislocation systems, providing a new approach for understanding pattern formation and dynamics …

Quantitative Modeling Of The Equilibration Of Two-Phase Solid-Liquid Fe By Atomistic Simulations On Diffusive Time Scales, Ebrahim Asadi, Mohsen Asle Zaeem, Sasan Nouranian, Michael I. Baskes

Materials Science and Engineering Faculty Research & Creative Works

In this paper, molecular dynamics (MD) simulations based on the modified-embedded atom method (MEAM) and a phase-field crystal (PFC) model are utilized to quantitatively investigate the solid-liquid properties of Fe. A set of second nearest-neighbor MEAM parameters for higherature applications are developed for Fe, and the solid-liquid coexisting approach is utilized in MD simulations to accurately calculate the melting point, expansion in melting, latent heat, and solid-liquid interface free energy, and surface anisotropy. The required input properties to determine the PFC model parameters, such as liquid structure factor and fluctuations of atoms in the solid, are also calculated from MD …

Big Data -- A 21st Century Science Maginot Line? No-Boundary Thinking: Shifting From The Big Data Paradigm, Xiuzhen Huang, Steven F. Jennings, Barry Bruce, Alison Buchan, Liming Cai, Pengyin Chen, Carole Cramer, Weihua Guan, Uwe Kk Hilgert, Hongmei Jiang, Zenglu Li, Gail Mcclure, Donald F. Mcmullen, Bindu Nanduri, Andy Perkins, Bhanu Rekepalli, Saeed Salem, Jennifer Specker, Karl Walker, Donald C. Wunsch, Donghai Xiong, Shuzhong Zhang, Yu Zhang, Zhongming Zhao, Jason H. Moore

Electrical and Computer Engineering Faculty Research & Creative Works

Whether your interests lie in scientific arenas, the corporate world, or in government, you have certainly heard the praises of big data: Big data will give you new insights, allow you to become more efficient, and/or will solve your problems. While big data has had some outstanding successes, many are now beginning to see that it is not the Silver Bullet that it has been touted to be. Here our main concern is the overall impact of big data; the current manifestation of big data is constructing a Maginot Line in science in the 21st century. Big data is not …

Vehicle Base Station, Emad William Saad, John L. Vian, Matthew A. Vavrina, Jared A. Nisbett, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

A system to load and unload material from a vehicle comprises a vehicle base station and an assembly to autonomously load and unload material from the vehicle.

Nonlinear Development And Secondary Instability Of Traveling Crossflow Vortices, Fei Li, Meelan M. Choudhari, Lian Duan, Chau-Lyan Chang

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Building upon the prior research targeting the laminar breakdown mechanisms associated with stationary crossflow instability over a swept-wing configuration, this paper investigates the secondary instability of traveling crossflow modes as an alternate scenario for transition. For the parameter range investigated herein, this alternate scenario is shown to be viable unless the initial amplitudes of the traveling crossflow instability are lower than those of the stationary modes by considerably more than one order of magnitude. The linear growth predictions based on the secondary instability theory are found to agree well with both parabolized stability equations and direct numerical simulation, and the …

Adaptive Resonance Theory And Diffusion Maps For Clustering Applications In Pattern Analysis, Donald C. Wunsch, David J. Morris, Rui Xu

Electrical and Computer Engineering Faculty Research & Creative Works

Adaptive Resonance is primarily a theory that learning is regulated by resonance phenomena in neural circuits. Diffusion maps are a class of kernel methods on edge-weighted graphs. While either of these approaches have demonstrated success in image analysis, their combination is particularly effective. These techniques are reviewed and some example applications are given.