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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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On The Instabilities And Transitions Of The Western Boundary Current, Daozhi Han, Marco Hernandez, Quan Wang Jul 2019

On The Instabilities And Transitions Of The Western Boundary Current, Daozhi Han, Marco Hernandez, Quan Wang

Mathematics and Statistics Faculty Research & Creative Works

We study the stability and dynamic transitions of the western boundary currents in a rectangular closed basin. By reducing the infinite dynamical system to a finite dimensional one via center manifold reduction, we derive a non-dimensional transition number that determines the types of dynamical transition. We show by careful numerical evaluation of the transition number that both continuous transitions (supercritical Hopf bifurcation) and catastrophic transitions (subcritical Hopf bifurcation) can happen at the critical Reynolds number, depending on the aspect ratio and stratification. The regions separating the continuous and catastrophic transitions are delineated on the parameter plane.

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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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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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The Ideal And Real Gas Heat Capacity Of Cesium Atoms At High Temperatures, Louis Biolsi, Michael Biolsi Jul 2019

The Ideal And Real Gas Heat Capacity Of Cesium Atoms At High Temperatures, Louis Biolsi, Michael Biolsi

Chemistry Faculty Research & Creative Works

The Ideal Gas Heat Capacity, Cp, of Cesium Atoms is Calculated to High Temperatures using Statistical Mechanics. There Are a Large Number of Electronic States in the State Sum that Determines the Partition Function: 174 Known Levels for Cesium Atoms Below the First Ionization Potential. Thus, at High Temperatures, Cp Becomes Very Large Unless the Number of Contributing States is Constrained. Two Arguments Are Used to Do This. First, at High Temperatures, the Increased Size of the Atoms Constrains the Sum (Bethe Method). Second, the Existence of Interacting Charged Species at Higher Temperatures, Which Lowers the Ionization …

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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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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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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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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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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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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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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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Multicenter Distorted-Wave Approach For Electron-Impact Ionization Of Molecules, Esam Ali, Don H. Madison Jul 2019

Multicenter Distorted-Wave Approach For Electron-Impact Ionization Of Molecules, Esam Ali, Don H. Madison

Physics Faculty Research & Creative Works

We have previously used the molecular three-body distorted-wave model to examine electron-impact single ionization of molecules. One of the possible weaknesses of this approach lies in the fact that the continuum electron wave functions do not depend on the orientation of the molecule. Here we introduce a model called the multicenter molecular three-body distorted-wave (MCM3DW) approach, for which the continuum electron wave functions depend on the orientation of the molecule at the time of ionization. The MCM3DW results are compared with experimental data taken from work by Dorn and colleagues [Ren, Phys. Rev. A 91, 032707 (2015)10.1103/PhysRevA.91.032707; Phys. Rev. A …

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Scholars' Mine Quick Facts June 2019, Nancy S. Krost Jun 2019

Scholars' Mine Quick Facts June 2019, Nancy S. Krost

Scholars’ Mine Statistics

Scholars' Mine Quick Facts are monthly reports of downloads, page hits, and other information about works in the institutional repository of Missouri S&T. A map with downloads by region is also included.

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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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Additive-Free Palladium-Catalyzed Decarboxylative Cross-Coupling Of Aryl Chlorides, Ryan A. Daley, En Chih Liu, Joseph J. Topczewski Jun 2019

Additive-Free Palladium-Catalyzed Decarboxylative Cross-Coupling Of Aryl Chlorides, Ryan A. Daley, En Chih Liu, Joseph J. Topczewski

Chemistry Faculty Research & Creative Works

The cross-coupling of sodium (hetero)aryl carboxylates with (hetero)aryl chlorides proceed with 1 mol % palladium catalyst and does not require inorganic base, silver salts, or copper salts. This coupling uses two low energy partners, and the only stoichiometric byproducts are carbon dioxide and sodium chloride. The substrate scope includes less activated aryl chlorides and carboxylates (>25 examples). The palladium loading could be reduced to 0.1 mol %, and Buchwald-style precatalysts could be used.

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Data-Driven Privacy-Preserving Communication, Ye Wang, Prakash Ishwar, Ardhendu S. Tripathy Jun 2019

Data-Driven Privacy-Preserving Communication, Ye Wang, Prakash Ishwar, Ardhendu S. Tripathy

Computer Science Faculty Research & Creative Works

A communication system including a receiver to receive training data. An input interface to receive input data coupled to a hardware processor and a memory. The hardware processor is configured to initialize the privacy module using the training data. Generate a trained privacy module, by iteratively optimizing an objective function. Wherein for each iteration the objective function is computed by a combination of a distortion of the useful attributes in the transformed data and of a mutual information between the sensitive attributes and the transformed data. Such that the mutual information is estimated by the auxiliary module that maximizes a …

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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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Deepsz: A Novel Framework To Compress Deep Neural Networks By Using Error-Bounded Lossy Compression, Sian Jin, Sheng Di, Xin Liang, Jiannan Tian, Dingwen Tao, Franck Cappello Jun 2019

Deepsz: A Novel Framework To Compress Deep Neural Networks By Using Error-Bounded Lossy Compression, Sian Jin, Sheng Di, Xin Liang, Jiannan Tian, Dingwen Tao, Franck Cappello

Computer Science Faculty Research & Creative Works

Today's deep neural networks (DNNs) are becoming deeper and wider because of increasing demand on the analysis quality and more and more complex applications to resolve. The wide and deep DNNs, however, require large amounts of resources (such as memory, storage, and I/O), significantly restricting their utilization on resource-constrained platforms. Although some DNN simplification methods (such as weight quantization) have been proposed to address this issue, they suffer from either low compression ratios or high compression errors, which may introduce an expensive fine-tuning overhead (i.e., a costly retraining process for the target inference accuracy). In this paper, we propose DeepSZ: …

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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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