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Articles 4291 - 4320 of 21795

Full-Text Articles in Engineering

Notes On The Economics Of Residential Hybrid Energy System, Mahelet G. Fikru, Gregory M. Gelles, Ana M. Ichim, Joseph D. Smith Jul 2019

Notes On The Economics Of Residential Hybrid Energy System, Mahelet G. Fikru, Gregory M. Gelles, Ana M. Ichim, Joseph D. Smith

Economics Faculty Research & Creative Works

Despite advances in small-scale hybrid renewable energy technologies, there are limited economic frameworks that model the different decisions made by a residential hybrid system owner. We present a comprehensive review of studies that examine the techno-economic feasibility of small-scale hybrid energy systems, and we find that the most common approach is to compare the annualized life-time costs to the expected energy output and choose the system with the lowest cost per output. While practical, this type of benefit—cost analysis misses out on other production and consumption decisions that are simultaneously made when adopting a hybrid energy system. In this paper, …

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Bioprinting With Human Stem Cell-Laden Alginate-Gelatin Bioink And Bioactive Glass For Tissue Engineering, Krishna C. R. Kolan, Julie A. Semon, Bradley Bromet, D. E. Day, Ming-Chuan Leu Jul 2019

Bioprinting With Human Stem Cell-Laden Alginate-Gelatin Bioink And Bioactive Glass For Tissue Engineering, Krishna C. R. Kolan, Julie A. Semon, Bradley Bromet, D. E. Day, Ming-Chuan Leu

Biological Sciences Faculty Research & Creative Works

Three-dimensional (3D) bioprinting technologies have shown great potential in the fabrication of 3D models for different human tissues. Stem cells are an attractive cell source in tissue engineering as they can be directed by material and environmental cues to differentiate into multiple cell types for tissue repair and regeneration. In this study, we investigate the viability of human adipose-derived mesenchymal stem cells (ASCs) in alginate-gelatin (Alg-Gel) hydrogel bioprinted with or without bioactive glass. Highly angiogenic borate bioactive glass (13-93B3) in 50 wt% is added to polycaprolactone (PCL) to fabricate scaffolds using a solvent-based extrusion 3D bioprinting technique. The fabricated scaffolds …

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Spatially Continuous Strain Monitoring Using Distributed Fiber Optic Sensors Embedded In Carbon Fiber Composites, Sasi Jothibasu, Yang Du, Sudharshan Anandan, Gurjot S. Dhaliwal, Rex E. Gerald Ii, Steve Eugene Watkins, K. Chandrashekhara, Jie Huang Jul 2019

Spatially Continuous Strain Monitoring Using Distributed Fiber Optic Sensors Embedded In Carbon Fiber Composites, Sasi Jothibasu, Yang Du, Sudharshan Anandan, Gurjot S. Dhaliwal, Rex E. Gerald Ii, Steve Eugene Watkins, K. Chandrashekhara, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

A distributed fiber optic strain sensor based on Rayleigh backscattering, embedded in a fiber-reinforced polymer composite, has been demonstrated. The optical frequency domain reflectometry technique is used to analyze the backscattered signal. The shift in the Rayleigh backscattered spectrum is observed to be linearly related to the change in strain of the composite material. The sensor (standard single-mode fiber) is embedded between the layers of the composite laminate. A series of tensile loads is applied to the laminate using an Instron testing machine, and the corresponding strain distribution of the laminate is measured. The results show a linear response indicating …

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Comparative Analysis Of Feature Selection Methods To Identify Biomarkers In A Stroke-Related Dataset, Thomas Clifford, Justin Bruce, Tayo Obafemi-Ajayi, John Matta Jul 2019

Comparative Analysis Of Feature Selection Methods To Identify Biomarkers In A Stroke-Related Dataset, Thomas Clifford, Justin Bruce, Tayo Obafemi-Ajayi, John Matta

Electrical and Computer Engineering Faculty Research & Creative Works

This paper applies machine learning feature selection techniques to the REGARDS stroke-related dataset to identify health-related biomarkers. A data-driven methodological framework is presented to evaluate multiple feature selection methods. In applying the framework, three classifiers are chosen in conjunction with two wrappers, and their performance with diverse classification targets such as Current Smoker, Current Alcohol Use, and Deceased is evaluated. The performance across logistic regression, random forest and naïve Bayes classifier methods, as quantified by the ROC Area Under Curve metric and selected features, was similar. However, significant differences were observed in running time. Performance of the selected features was …

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Switching Dynamics And Conductance Quantization Of Aloe Polysaccharides-Based Device, Z. X. Lim, I. A. Tayeb, Z. A.A. Hamid, M. F. Ain, A. M. Hashim, J. M. Abdullah, F. Zhao, K. Y. Cheong Jul 2019

Switching Dynamics And Conductance Quantization Of Aloe Polysaccharides-Based Device, Z. X. Lim, I. A. Tayeb, Z. A.A. Hamid, M. F. Ain, A. M. Hashim, J. M. Abdullah, F. Zhao, K. Y. Cheong

Electrical and Computer Engineering Faculty Research & Creative Works

The switching behaviors of polysaccharides-based resistive random-access memories change substantially depending on the electrical inputs. Here, the switching dynamics of the device are presented by varying the applied current compliance (CC) and voltage sweeping rate (ν). The results show that the device resistance in the low-resistance state (RLRS) can be modulated over five orders of magnitude by varying (CC) and ν in the typical current-voltage measurements. The (RLRS) modulation is attributed to the variable tunneling gap between the filament tip and the top electrode (TE). Conductance quantization is observed once a single-atomic contact with resistance ≤12.9kΩ is formed. Depending on …

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Physico-Chemical Characteristics Of Ethanol–Diesel Blend Fuel, Tarek M. Aboul-Fotouh, Eslam Alaa, M. A. Sadek, Hany A. Elazab Jul 2019

Physico-Chemical Characteristics Of Ethanol–Diesel Blend Fuel, Tarek M. Aboul-Fotouh, Eslam Alaa, M. A. Sadek, Hany A. Elazab

Chemical and Biochemical Engineering Faculty Research & Creative Works

In this research we are discussing the physicochemical characteristics of sweet diesel after desulphurization alone and also these characteristics are tested with the adding of high purity HPLC ethanol (99.9%). Those fuel properties of ethanol blended with diesel were experimentally determined to find their stability and to increase their properties and efficiency in the diesel engines. First, we made 4 blends of diesel with ethanol and the fifth sample was pure diesel. The samples were 0% ethanol and 100 % diesel, the second sample was 5% ethanol and 95 % diesel, the third sample was 10 % ethanol and 90% …

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High Octane Number Gasoline-Ether Blend, Tarek M. Aboul-Fotouh, Sherif K. Ibrahim, M. A. Sadek, Hany A. Elazab Jul 2019

High Octane Number Gasoline-Ether Blend, Tarek M. Aboul-Fotouh, Sherif K. Ibrahim, M. A. Sadek, Hany A. Elazab

Chemical and Biochemical Engineering Faculty Research & Creative Works

Gasoline produced in Egypt is a low-grade gasoline that contains high concentration of harmful components that are having a toll on our environment. In addition, those pollutants cause countless diseases and deaths annually to the Egyptian population. This paper targets two main sectors in the production of commercial gasoline. The improvement engine efficiency through the upgrading of octane number is first experimented by using a blend stock that ranges from gasoline fractions and Isomerates. An optimum was then chosen depending on the results obtained from different tests. Through those experiments, it was determined which samples obeyed the EU regulation for …

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Study On Safety Control Of Composite Roof In Deep Roadway Based On Energy Balance Theory, Zhengzheng Xie, Nong Zhang, Yuxin Yuan, Guang Xu, Qun Wei Jul 2019

Study On Safety Control Of Composite Roof In Deep Roadway Based On Energy Balance Theory, Zhengzheng Xie, Nong Zhang, Yuxin Yuan, Guang Xu, Qun Wei

Mining Engineering Faculty Research & Creative Works

Improving the safety and stability of composite roof in deep roadway is the strong guarantee for safe mining and sustainable development of coal mines. With three roadways of different composite roofs in Hulusu Coal Mine and Menkeqing Coal Mine as the research background, this paper explores the mechanical properties and energy dissipation law of coal-rock structures with different height ratios from the perspective of energy release and dissipation through lab experiments. The results indicate that the key to the stability of coal-rock structures lies in maintaining relatively low dissipation energy. Based on experimental results and the energy balance theory, two …

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Stochastic Resonance Enables Bpp/Log∗ Complexity And Universal Approximation In Analog Recurrent Neural Networks, Emmett Redd, A. Steven Younger, Tayo Obafemi-Ajayi Jul 2019

Stochastic Resonance Enables Bpp/Log∗ Complexity And Universal Approximation In Analog Recurrent Neural Networks, Emmett Redd, A. Steven Younger, Tayo Obafemi-Ajayi

Electrical and Computer Engineering Faculty Research & Creative Works

Stochastic resonance (SR) is a natural process that without limit increases the precision of signal measurements in biological and physical sciences. Most artificial neural networks (NNs) are implemented on digital computers of fixed precision. A NN accessing universal approximation and a computational complexity class more powerful that of a Turing machine needs analog signals utilizing SR's limitless precision increase. This paper links an analog recurrent (AR) NN theorem, SR, BPP/log∗ (a physically realizable, super-Turing computation class), and universal approximation so NNs following them can be made computationally more powerful. An optical neural network mimicking chaos indicates super-Turing computation has been …

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Recurrent Network And Multi-Arm Bandit Methods For Multi-Task Learning Without Task Specification, Thy Nguyen, Tayo Obafemi-Ajayi Jul 2019

Recurrent Network And Multi-Arm Bandit Methods For Multi-Task Learning Without Task Specification, Thy Nguyen, Tayo Obafemi-Ajayi

Electrical and Computer Engineering Faculty Research & Creative Works

This paper addresses the problem of multi-task learning (MTL) in settings where the task assignment is not known. We propose two mechanisms for the problem of inference of task's parameter without task specification: parameter adaptation and parameter selection methods. In parameter adaptation, the model's parameter is iteratively updated using a recurrent neural network (RNN) learner as the mechanism to adapt to different tasks. For the parameter selection model, a parameter matrix is learned beforehand with the task known apriori. During testing, a bandit algorithm is utilized to determine the appropriate parameter vector for the model on the fly. We explored …

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Genotype Combinations Linked To Phenotype Subgroups In Autism Spectrum Disorders, Junya Zhao, Thy Nguyen, Jonathan Kopel, Perry B. Koob, Donald A. Adieroh, Tayo Obafemi-Ajayi Jul 2019

Genotype Combinations Linked To Phenotype Subgroups In Autism Spectrum Disorders, Junya Zhao, Thy Nguyen, Jonathan Kopel, Perry B. Koob, Donald A. Adieroh, Tayo Obafemi-Ajayi

Electrical and Computer Engineering Faculty Research & Creative Works

This paper investigates a computational model that allows for systematic comparison of phenotype data with genotype (Single Nucleotide Polymorphisms (SNPs)) data based on machine learning techniques to identify discriminant genotype markers associated with the phenotypic subgroups. The proposed discriminant SNP identifier model is empirically evaluated using Autism Spectrum Disorder (ASD) simplex sample. Six phenotype markers were selected to cluster the sample in a hexagonal lattice format yielding five multidimensional subgroups based on extremities of the phenotype markers. The SNP selection model includes random subspace selection of SNPs in conjunction with feature selection algorithms to determine which set of SNPs were …

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Analysis Of Sea Clutter Using Dynamic Mode Decomposition, Yanming Zhang, Lijun Jiang, Hong Tat Ewe Jul 2019

Analysis Of Sea Clutter Using Dynamic Mode Decomposition, Yanming Zhang, Lijun Jiang, Hong Tat Ewe

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, a novel method based on a dynamic mode decomposition (DMD) for sea clutter analysis is proposed. It extracts the temporal patterns and corresponding dynamic modes from the sea clutter simultaneously. Moreover, the temporal patterns display similar properties with traditional analysis using Doppler spectrum. The corresponding dynamic modes represent the cardinal feature within the sea clutter. To demonstrate the effectiveness of the proposed method, the measured sea clutter data collected by IPIX radar is analyzed. It is shown that DMD spectrum has the same frequency-shift and similar amplitude with the Doppler Spectrum. In addition, the Probability Density Function …

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A Novel Data-Driven Analysis Method For Nonlinear Electromagnetic Radiations Based On Dynamic Mode Decomposition, Yanming Zhang, Lijun Jiang Jul 2019

A Novel Data-Driven Analysis Method For Nonlinear Electromagnetic Radiations Based On Dynamic Mode Decomposition, Yanming Zhang, Lijun Jiang

Electrical and Computer Engineering Faculty Research & Creative Works

Nonlinear effects generated in complex electronic systems such as cell phones and computers cause broadband electromagnetic radiations. They are very difficult to model but could be key contributors to the radiated spurious emission (RSE) and radio frequency interference (RFI). In this paper, a novel data-driven characterization method is proposed to analyze the transient responses of the nonlinear circuits and their nonlinear electromagnetic radiations. It employs the dynamic mode decomposition (DMD) to simultaneously extract the temporal patterns and their corresponding dynamic modes. The temporal patterns show high order harmonics generated by the nonlinearity. Then these temporal spatial coherent patterns could provide …

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Distributed State Estimation By Using Active-Passive Sensor Networks, Akhilesh Raj, S. Jagannathan, Tansel Yucelen Jul 2019

Distributed State Estimation By Using Active-Passive Sensor Networks, Akhilesh Raj, S. Jagannathan, Tansel Yucelen

Electrical and Computer Engineering Faculty Research & Creative Works

This paper proposes a novel adaptive observer for heterogeneous sensor networks (HSNs) to estimate state vector of an unknown target or process by using the sensed output when the input to the target/process is also not known. In an HSN, nodes are considered either active or passive depending upon their ability to sense the target output. The local information exchange among the nodes is dictated by a connected graph. By using the criterion of collective observability, a novel distributed adaptive estimation is introduced where the nodes are allowed to have different sensor modalities. Stability analysis shows uniform ultimate boundedness of …

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Distributed Fiber-Optic Pressure Sensor Based On Bourdon Tubes Metered By Optical Frequency-Domain Reflectometry, Chen Zhu, Yiyang Zhuang, Yizhen Chen, Rex E. Gerald Ii, Jie Huang Jul 2019

Distributed Fiber-Optic Pressure Sensor Based On Bourdon Tubes Metered By Optical Frequency-Domain Reflectometry, Chen Zhu, Yiyang Zhuang, Yizhen Chen, Rex E. Gerald Ii, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

We report a distributed fiber-optic pressure sensor based on Bourdon tubes using Rayleigh backscattering metered by optical frequency-domain reflectometry (OFDR). In the proposed sensor, a piece of single-mode fiber (SMF) is attached to the concave surfaces of Bourdon tubes using a thin layer of epoxy. The strain profiles along the concave surface of the Bourdon tube vary with applied pressure, and the strain variations are transferred to the attached SMF through the epoxy layer, resulting in spectral shifts in the local Rayleigh backscattering signals. By monitoring the local spectral shifts of the OFDR system, the pressure applied to the Bourdon …

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Active-Passive Dynamic Consensus Filters For Linear Time-Invariant Multiagent Systems, J. Daniel Peterson, Tansel Yucelen, S. Jagannathan Jul 2019

Active-Passive Dynamic Consensus Filters For Linear Time-Invariant Multiagent Systems, J. Daniel Peterson, Tansel Yucelen, S. Jagannathan

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Active-passive dynamic consensus filters consist of a group of agents, where a subset of these agents is able to observe a quantity of interest (i.e. active agents) and the rest are subject to no observations (i.e. passive agents). Specifically, the objective of these filters is that the states of all agents are required to converge to the weighted average of the set of observations sensed by the active agents. Existing active-passive dynamic consensus filters in the classical sense assume that all agents can be modeled as having single integrator dynamics, which may not always hold in practice. Motivating from this …

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Stabilization Of Homoclinic Orbits Of Two Degree-Of-Freedom Underactuated Systems, Nilay Kant, Ranjan Mukherjee, Hassan K. Khalil Jul 2019

Stabilization Of Homoclinic Orbits Of Two Degree-Of-Freedom Underactuated Systems, Nilay Kant, Ranjan Mukherjee, Hassan K. Khalil

Mechanical and Aerospace Engineering Faculty Research & Creative Works

A hybrid controller for stabilization of homoclinic orbits of two degree-of-freedom (DOF) underactuated systems is proposed. The controller is comprised of continuous-time inputs, impulsive brakings, and virtual impulsive inputs for resetting of the passive coordinate. Impulsive brakings of the active coordinate result in instantaneous negative changes in the mechanical energy of the system. An impulsive dynamical system framework is adopted for modeling the hybrid dynamics and a Lyapunov function is defined for stabilization of the orbit. Sufficient conditions for stabilization are presented such that the Lyapunov function decreases monotonically under the action of the continuous inputs and undergoes negative jumps …

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Impedance Mismatch Effects In Microstrip And Stripline Ebg Common-Mode Filters, Marina Y. Koledintseva, Sergiu Radu, Joe Nuebel Jul 2019

Impedance Mismatch Effects In Microstrip And Stripline Ebg Common-Mode Filters, Marina Y. Koledintseva, Sergiu Radu, Joe Nuebel

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, impedance mismatch effects on the characteristics of common-mode (CM) electromagnetic bandgap (EBG) filters are studied using 3D full-wave numerical simulations. Herein, the terminations are fixed at 50 Ohms, and the effect of the differential line impedance variations are studied. Two types of CM EBG filters are considered in this work, both are designed using standard printed circuit board technology. The first group contains microstrip (MS) differential pairs running above the EBG plane, and the second group contains strip line (SL) differential pairs running on one of the layers next to the EBG plane. It is shown that …

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Advanced Measurement Techniques For Enabling Multiphase Reactors And Flow Systems For Sustainable And Cleaner Processes, Muthanna H. Al-Dahhan Jul 2019

Advanced Measurement Techniques For Enabling Multiphase Reactors And Flow Systems For Sustainable And Cleaner Processes, Muthanna H. Al-Dahhan

Chemical and Biochemical Engineering Faculty Research & Creative Works

No abstract provided.

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Local Receptive Fields Based Extreme Learning Machine With Hybrid Filter Kernels For Image Classification, Bo He, Yan Song, Yuemei Zhu, Qixin Sha, Yue Shen, Tianhong Yan, Rui Nian, Amaury Lendasse Jul 2019

Local Receptive Fields Based Extreme Learning Machine With Hybrid Filter Kernels For Image Classification, Bo He, Yan Song, Yuemei Zhu, Qixin Sha, Yue Shen, Tianhong Yan, Rui Nian, Amaury Lendasse

Engineering Management and Systems Engineering Faculty Research & Creative Works

In This Paper, an Innovative Method Called Extreme Learning Machine with Hybrid Local Receptive Fields (Elm-Hlrf) is Presented for Image Classification. in This Method, Filters Generated by Gabor Functions and the Randomly Generated Convolution Filters Are Incorporated into the Convolution Filter Kernels of Local Receptive Fields based Extreme Learning Machine (Elm-Lrf). Extreme Learning Machine (Elm) is Derived from Single Hidden Layer Feed-Forward Neural Networks, and the Parameters of its Hidden Layer Can Be Generated Randomly. as Locally Connected Elm, Elm-Lrf Directly Processes Information with Strong Correlations Such as Images and Speech. in This Paper, Two Main Contributions Are Proposed to …

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A Set-Theoretic Model Reference Adaptive Control Architecture With Dead-Zone Effect, Ehsan Arabi, Tansel Yucelen Jul 2019

A Set-Theoretic Model Reference Adaptive Control Architecture With Dead-Zone Effect, Ehsan Arabi, Tansel Yucelen

Mechanical and Aerospace Engineering Faculty Research & Creative Works

By introducing a system error dependent learning rate, the recently proposed set-theoretic model reference adaptive control architecture provides user-defined worst-case performance guarantees on the system error between an uncertain dynamical system of interest and a given reference model. In this architecture, the adaptation process is always active. However, it is of practical interest to stop the adaptation process when it is not needed (i.e., in the presence of small system errors). Motivated from this standpoint, we present a new set-theoretic model reference adaptive control architecture with dead-zone effect. The key feature of our framework utilizes a modified and continuous generalized …

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Multi-Objective Optimization Approach To Find Biclusters In Gene Expression Data, Jeffrey Dale, Junya Zhao, Tayo Obafemi-Ajayi Jul 2019

Multi-Objective Optimization Approach To Find Biclusters In Gene Expression Data, Jeffrey Dale, Junya Zhao, Tayo Obafemi-Ajayi

Electrical and Computer Engineering Faculty Research & Creative Works

Gene expression levels of organisms are measured by DNA microarrays. Finding biclusters in gene expression matrices provides invaluable information about effects of disease at the genetic level. These biclusters could identify which genes are up-regulated/down-regulated under certain conditions. This paper investigates a methodology for evolutionary-based biclustering using the NSGA-II algorithm. It also presents an improvement to the recovery and relevance external validation metrics as well as a new method for synthetic data generation for biclustering. Results obtained demonstrate its effectiveness in discovering useful biclusters on varied synthetic data when applied with the average Spearman's rho measure as the fitness function.

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Event-Triggered Adaptive Distributed State Estimation By Using Active-Passive Sensor Networks, Akhilesh Raj, S. Jagannathan, Tansel Yucelen Jul 2019

Event-Triggered Adaptive Distributed State Estimation By Using Active-Passive Sensor Networks, Akhilesh Raj, S. Jagannathan, Tansel Yucelen

Electrical and Computer Engineering Faculty Research & Creative Works

This paper proposes a novel event-triggered adaptive observer for each node in the heterogeneous sensor networks (HSNs) in order to estimate state vector of an unknown target or process by using the sensed output when the input to the target/ process is unknown. A subset of nodes in the HSN referred to as active nodes, can sense the target periodically, estimate the target state vector by using their adaptive observer and can communicate the estimated state vector of the target with the neighboring nodes including passive nodes only at event triggered instants. The adaptive observer parameters of active nodes are …

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Fully Adaptive Cloud Profiling Radar Simulation, J. Delong, M. A. Shattal, A. O'Brien, C. D. Ball, J. T. Johnson, G. E. Smith Jul 2019

Fully Adaptive Cloud Profiling Radar Simulation, J. Delong, M. A. Shattal, A. O'Brien, C. D. Ball, J. T. Johnson, G. E. Smith

Electrical and Computer Engineering Faculty Research & Creative Works

This paper demonstrates how the fully adaptive radar framework can be applied to cloud profiling radars. A simulation based on the GEOS5 nature run dataset is introduced in which the cloud profiling radar continuously adapts its pulse repetition frequency (PRF) such that the unambiguous range is 1.2 times the cloud column height. This process maximizes the (PRF) which would in turn maximize the unambiguous velocity estimate.

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Real‐Time Overhead Power Line Sag Monitoring, Jie Huang, Rui Bo Jun 2019

Real‐Time Overhead Power Line Sag Monitoring, Jie Huang, Rui Bo

Electrical and Computer Engineering Faculty Research & Creative Works

System and method for determining real-time sag and shape information of an electrical power line based on strain distribution along a length of an optical fiber associated with the power line. An embedded fiber coupled to an overhead transmission line measures strain using the backscatter of an optical signal, the optical signal is then interrogated using an interferometer.

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Method Of Forming Microparticles For Use In Cell Seeding, Sutapa Barua, Chase Herman Jun 2019

Method Of Forming Microparticles For Use In Cell Seeding, Sutapa Barua, Chase Herman

Chemical and Biochemical Engineering Faculty Research & Creative Works

The present invention is directed to methods for forming microparticles useful for cell seeding and for conjugating protein to the surface of the microparticles. The method comprises co-injecting an organic solution of PLGA or other polymer with an aqueous solution into a flow focusing tube.

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Algal Remediation Of Wastewater Produced From Hydrothermally Treated Septage, Kyle Mcgaughy, Ahmad Abu Hajer, Edward Drabold, David J. Bayless, M. Toufiq Reza Jun 2019

Algal Remediation Of Wastewater Produced From Hydrothermally Treated Septage, Kyle Mcgaughy, Ahmad Abu Hajer, Edward Drabold, David J. Bayless, M. Toufiq Reza

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Hydrothermal carbonization (HTC) is a promising technology to convert wet wastes like septic tank wastes, or septage, to valuable platform chemical, fuels, and materials. However, the byproduct of HTC, process liquid, often contains large amount of nitrogen species (up to 2 g/L of nitrogen), phosphorus, and a variety of organic carbon containing compounds. Therefore, the HTC process liquid is not often treated at wastewater treatment plant. In this study, HTC process liquid was treated with algae as an alternative to commercial wastewater treatment. The HTC process liquid was first diluted and then used to grow Chlorella sp. over a short …

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Novel Coupling Smart Water-Co₂ Flooding For Sandstone Reservoirs; Smart Seawater-Alternating-Co₂ Flooding (Smsw-Agf), Hasan N. Al-Saedi, Ralph E. Flori Jun 2019

Novel Coupling Smart Water-Co₂ Flooding For Sandstone Reservoirs; Smart Seawater-Alternating-Co₂ Flooding (Smsw-Agf), Hasan N. Al-Saedi, Ralph E. Flori

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

CO2 flooding is an environmentally friendly and cost-effective EOR technique that can be used to unlock residual oil from oil reservoirs. Smart water is any water that is engineered by manipulating the ionic composition, regardless of the resulting salinity of the water. One CO2 flooding mechanism is wettability alteration, which meets with the main smart water flooding function. Injecting CO2 alone raise an early breakthrough and gravity override problems, which have already been solved using water alternating gas (WAG) using regular water. WAG is an emerging enhanced oil recovery process designed to enhance sweep efficiency during gas …

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Contractual Guidelines For Contractors Working Under Projects Funded By Southeastern Us Dots, Islam H. El-Adaway, Amr Elsayegh, I. S. Abotaleb, C. Smith, M. Bootwala, S. Eteifa Jun 2019

Contractual Guidelines For Contractors Working Under Projects Funded By Southeastern Us Dots, Islam H. El-Adaway, Amr Elsayegh, I. S. Abotaleb, C. Smith, M. Bootwala, S. Eteifa

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Transportation projects in the infrastructure sector contribute to approximately 42% of the total expenditures on public construction projects in the US. The main source of funding of these projects is the taxpayer's hard-earned money. The ever-growing problem by transportation projects is that the available funds are less than those required to have a stable and well maintained transportation network. Unnecessary costs in these projects are mainly caused by Conflicts, Claims and Disputes (C2D). According to recent reports, C2D in construction is greatly attributed to poor contract administration. The goal of this paper is to provide better understanding and utilization of …

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Post Deposition Annealing Effect On Properties Of Y 2 O 3 /Al 2 O 3 Stacking Gate Dielectric On 4h-Sic, Feng Zhao, Oliver Amnuayphol, Kuan Yew Cheong, Yew Hoong Wong, Jheng Yi Jiang, Chih Fang Huang Jun 2019

Post Deposition Annealing Effect On Properties Of Y 2 O 3 /Al 2 O 3 Stacking Gate Dielectric On 4h-Sic, Feng Zhao, Oliver Amnuayphol, Kuan Yew Cheong, Yew Hoong Wong, Jheng Yi Jiang, Chih Fang Huang

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, the effect of post deposition annealing (PDA) on the chemical, structural, and electrical properties of the high-kY2O3 /Al2O3 stacking dielectric on p-type 4H-SiC were studied. High-k dielectric provides a physically thicker film with equivalent capacitance, therefore better exploits the high breakdown strength of 4H-SiC in its MOSFET devices. The Y2O3 /Al2O3 stacking films were deposited using RF magnetron sputtering, with PDA in Ar ambient at 400 °C, 600 °C, 800 °C and 1000 °C. X-ray diffraction (XRD) and angle resolved X-ray photoelectron spectroscopy (XPS) results …

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