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Articles 1 - 12 of 12
Full-Text Articles in Engineering
Capillary-Tube Package Devices For The Quantitative Performance Evaluation Of Nuclear Magnetic Resonance Spectrometers And Pulse Sequences, Lingyu Chi, Ming Huang, Annalise R. Pfaff, Jie Huang, Rex E. Gerald Ii, Klaus Woelk
Capillary-Tube Package Devices For The Quantitative Performance Evaluation Of Nuclear Magnetic Resonance Spectrometers And Pulse Sequences, Lingyu Chi, Ming Huang, Annalise R. Pfaff, Jie Huang, Rex E. Gerald Ii, Klaus Woelk
Electrical and Computer Engineering Faculty Research & Creative Works
With the increased sensitivity of modern nuclear magnetic resonance (NMR) spectrometers, the minimum amount needed for chemical-shift referencing of NMR spectra has decreased to a point where a few microliters can be sufficient to observe a reference signal. The reduction in the amount of required reference material is the basis for the NMR Capillary-tube Package (CapPack) platform that utilizes capillary tubes with inner diameters smaller than 150 µm as NMR-tube inserts for external reference standards. It is shown how commercially available electrophoresis capillary tubes with outer diameters of 360 µm are filled with reference liquids or solutions and then permanently …
Multicellular Models Bridging Intracellular Signaling And Gene Transcription To Population Dynamics, Mohammad Aminul Islam, Satyaki Roy, Sajal K. Das, Dipak Barua
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
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 …
Explosive Dust Test Vessel Comparison Using Pulverized Pittsburgh Coal, Jacob Miller, Jay Schafler, Phillip R. Mulligan, Robert Eades, Kyle A. Perry, Catherine E. Johnson
Explosive Dust Test Vessel Comparison Using Pulverized Pittsburgh Coal, Jacob Miller, Jay Schafler, Phillip R. Mulligan, Robert Eades, Kyle A. Perry, Catherine E. Johnson
Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works
Explosions of coal dust are a major safety concern within the coal mining industry. The explosion and subsequent fires caused by coal dust can result in significant property damage, loss of life in underground coal mines and damage to coal processing facilities. The United States Bureau of Mines conducted research on coal dust explosions until 1996 when it was dissolved. In the following years, the American Society for Testing and Materials (ASTM) developed a test standard, ASTM E1226, to provide a standard test method characterizing the “explosibility” of particulate solids of combustible materials suspended in air. The research presented herein …
Detonation Synthesis Of Alpha-Variant Silicon Carbide, Martin Langenderfer, Catherine E. Johnson, William Fahrenholtz, Vadym Mochalin
Detonation Synthesis Of Alpha-Variant Silicon Carbide, Martin Langenderfer, Catherine E. Johnson, William Fahrenholtz, Vadym Mochalin
Mining Engineering Faculty Research & Creative Works
A recent research study has been undertaken to develop facilities for conducting detonation synthesis of nanomaterials. This process involves a familiar technique that has been utilized for the industrial synthesis of nanodiamonds. Developments through this study have allowed for experimentation with the concept of modifying explosive compositions to induce synthesis of new nanomaterials. Initial experimentation has been conducted with the end goal being synthesis of alpha variant silicon carbide (α-SiC) in the nano-scale. The α-SiC that can be produced through detonation synthesis methods is critical to the ceramics industry because of a number of unique properties of the material. Conventional …
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
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 …
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
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 …
Nmr Studies Of Loaded Microspheres, Ming Huang, Sisi Chen, Rex E. Gerald Ii, Jie Huang, Klaus Woelk
Nmr Studies Of Loaded Microspheres, Ming Huang, Sisi Chen, Rex E. Gerald Ii, Jie Huang, Klaus Woelk
Electrical and Computer Engineering Faculty Research & Creative Works
Porous-wall hollow glass microspheres (PWHGMs) are a novel form of glass materials that consist of 1-μm-thick porous silica shells, 20-100 μm in diameter, with a hollow cavity in the center. Utilizing the central cavity for material storage and the porous walls for controlled release is a unique combination that renders PWHGMs a superior vehicle for targeted drug delivery. In this study, NMR spectroscopy was used to characterize PWHGMs for the first time. A vacuum-based loading system was developed to load PWHGMs with various compounds followed by a washing procedure that uses solvents immiscible with the target material. Immiscible binary model …
Spectral Analysis Of Surface Waves To Detect Subsurface Voids, Payman Hajiani, Neil Lennart Anderson, J. David Rogers
Spectral Analysis Of Surface Waves To Detect Subsurface Voids, Payman Hajiani, Neil Lennart Anderson, J. David Rogers
Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works
Systems and methods for detecting a subsurface cavity. A source applies a force to ground under inspection and a plurality of sensors coupled to the ground detect resulting surface waves. A processor is configured to extract phase and frequency components of the acquired seismic data, identify a phase shift in surface waves in the ground under inspection based on the extracted phase and frequency components, and determine one or more physical characteristics of a subsurface cavity based on the identified phase shift
A Multi-Step Nonlinear Dimension-Reduction Approach With Applications To Bigdata, R. Krishnan, V. A. Samaranayake, Jagannathan Sarangapani
A Multi-Step Nonlinear Dimension-Reduction Approach With Applications To Bigdata, R. Krishnan, V. A. Samaranayake, Jagannathan Sarangapani
Mathematics and Statistics Faculty Research & Creative Works
In this paper, a multi-step dimension-reduction approach is proposed for addressing nonlinear relationships within attributes. In this work, the attributes in the data are first organized into groups. In each group, the dimensions are reduced via a parametric mapping that takes into account nonlinear relationships. Mapping parameters are estimated using a low rank singular value decomposition (SVD) of distance covariance. Subsequently, the attributes are reorganized into groups based on the magnitude of their respective singular values. The group-wise organization and the subsequent reduction process is performed for multiple steps until a singular value-based user-defined criterion is satisfied. Simulation analysis is …
Direct Error Driven Learning For Deep Neural Networks With Applications To Bigdata, R. Krishnan, Jagannathan Sarangapani, V. A. Samaranayake
Direct Error Driven Learning For Deep Neural Networks With Applications To Bigdata, R. Krishnan, Jagannathan Sarangapani, V. A. Samaranayake
Electrical and Computer Engineering Faculty Research & Creative Works
In this paper, generalization error for traditional learning regimes-based classification is demonstrated to increase in the presence of bigdata challenges such as noise and heterogeneity. To reduce this error while mitigating vanishing gradients, a deep neural network (NN)-based framework with a direct error-driven learning scheme is proposed. To reduce the impact of heterogeneity, an overall cost comprised of the learning error and approximate generalization error is defined where two NNs are utilized to estimate the costs respectively. To mitigate the issue of vanishing gradients, a direct error-driven learning regime is proposed where the error is directly utilized for learning. It …
Phytoforensics: Trees As Bioindicators Of Potential Indoor Exposure Via Vapor Intrusion, Jordan L. Wilson, V. A. Samaranayake, Matt A. Limmer, Joel Gerard Burken
Phytoforensics: Trees As Bioindicators Of Potential Indoor Exposure Via Vapor Intrusion, Jordan L. Wilson, V. A. Samaranayake, Matt A. Limmer, Joel Gerard Burken
Mathematics and Statistics Faculty Research & Creative Works
Human exposure to volatile organic compounds (VOCs) via vapor intrusion (VI) is an emerging public health concern with notable detrimental impacts on public health. Phytoforensics, plant sampling to semi-quantitatively delineate subsurface contamination, provides a potential non-invasive screening approach to detect VI potential, and plant sampling is effective and also time- and cost-efficient. Existing VI assessment methods are time- and resource-intensive, invasive, and require access into residential and commercial buildings to drill holes through basement slabs to install sampling ports or require substantial equipment to install groundwater or soil vapor sampling outside the home. Tree-core samples collected in 2 days at …