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Detection Of Sensor Attacks In Uncertain Stochastic Linear Systems, Chandreyee Bhowmick, S. Jagannathan Aug 2019

Detection Of Sensor Attacks In Uncertain Stochastic Linear Systems, Chandreyee Bhowmick, S. Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

A novel attack detection scheme is developed for linear discrete-time systems with unknown dynamics that are subject to the additive process and output measurements noise. A novel stochastic adaptive observer is proposed to estimate the state vector in the presence of noisy sensor measurements and uncertain dynamics, and also to generate the innovation signal to detect attacks using a modified $\chi2} $ detector. It has been shown that the innovation signal, which is defined as the difference between the measured and the estimated output from the observer, has a Gaussian distribution with non-zero mean. The modified $\chi^ {2} $ detector …

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A Framework Of Integrating Manufacturing Plants In Smart Grid Operation: Manufacturing Flexible Load Identification, Md. Monirul Islam, Zeyi Sun, Wenqing Hu, Cihan H. Dagli Aug 2019

A Framework Of Integrating Manufacturing Plants In Smart Grid Operation: Manufacturing Flexible Load Identification, Md. Monirul Islam, Zeyi Sun, Wenqing Hu, Cihan H. Dagli

Engineering Management and Systems Engineering Faculty Research & Creative Works

In the deregulated electricity markets run by Independent System Operator (ISO), a two-settlement (day-ahead and real-time) process is typically used to determine the electricity price to the end-use customers at different buses. In the day-ahead settlement, the demand is predicted at each bus based on the previous consumption behavior of the consumers and thus, Locational Marginal Price (LMP) can be determined and shared to the consumers. A significant gap is usually observed between the planned and real-time demands due to the uncertainties of the weather (temperature, wind-speed etc.), the intensity of business, and everyday activities. Therefore, a large price variation …

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Ultrafast Imaging Of The Renner-Teller Effect In A Field-Dressed Molecule, K. Amini, T. Steinle, M. Sclafani, M. Shaikh, A. Sanchez, X. Liu, Anh-Thu Le, For Full List Of Authors, See Publisher's Website. Jul 2019

Ultrafast Imaging Of The Renner-Teller Effect In A Field-Dressed Molecule, K. Amini, T. Steinle, M. Sclafani, M. Shaikh, A. Sanchez, X. Liu, Anh-Thu Le, For Full List Of Authors, See Publisher's Website.

Physics Faculty Research & Creative Works

We present experimental results of linear-to-bent transition of field-dressed molecules, mediated by Renner-Teller effect. Using the state-of-the-art laser-induced electron diffraction (LIED) technique, we image a bent and symmetrically stretched carbon disulfide (CS2) molecule populating an excited electronic state under the influence of strong laser field. Our findings are well-supported by ab initio quantum mechanical calculations.

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Imaging An Isolated Water Molecule With An Attosecond Electron Wave Packet, X. Liu, K. Amini, Anh-Thu Le, Ulrich D. Jentschura, For Full List Of Authors, See Publisher's Website. Jul 2019

Imaging An Isolated Water Molecule With An Attosecond Electron Wave Packet, X. Liu, K. Amini, Anh-Thu Le, Ulrich D. Jentschura, For Full List Of Authors, See Publisher's Website.

Physics Faculty Research & Creative Works

We use laser-induced electron diffraction (LIED) to self-image the molecular structure of an isolated water molecular ion using its own retuning attosecond electron wave packet (EWP). Using LIED's subfemtosecond and picometre spatio-temporal resolution imaging capabilities, we observe the symmetric stretching of the O-H and H-H internuclear distances with increasing laser field strength.

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Projectile Coherence Effects In Simple Atomic Systems, Michael Schulz, A. Hasan, B. Lamichhane, T. Arthanayaka, M. Dhital, S. Bastola, L. Nagy, S. Borbely, F. Jarai-Szabo Jul 2019

Projectile Coherence Effects In Simple Atomic Systems, Michael Schulz, A. Hasan, B. Lamichhane, T. Arthanayaka, M. Dhital, S. Bastola, L. Nagy, S. Borbely, F. Jarai-Szabo

Physics Faculty Research & Creative Works

Recent studies of projectile coherence effects in ion-atom collisions are presented. For intermediate-energy proton collisions an extensive literature provides strong support for the importance of such effects. In this regime coherence effects are now used as a tool to study the few-body dynamics very sensitively. In contrast, for high-energy ion impact the literature is much sparser and here an important role of coherence effects cannot be regarded as being established. In this context, a recent claim that in COLTRIMS experiments the coherence properties are determined only by the target beam is rebutted.

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Controlled Generation Of Dark-Bright Soliton Complexes In Two-Component And Spinor Bose-Einstein Condensates, A. Romero-Ros, Garyfallia C. Katsimiga, P. G. Kevrekidis, P. Schmelcher Jul 2019

Controlled Generation Of Dark-Bright Soliton Complexes In Two-Component And Spinor Bose-Einstein Condensates, A. Romero-Ros, Garyfallia C. Katsimiga, P. G. Kevrekidis, P. Schmelcher

Physics Faculty Research & Creative Works

We report on the controlled creation of multiple soliton complexes of the dark-bright type in one-dimensional two-component, three-component, and spinor Bose-Einstein condensates. The formation of solitonic entities of the dark-bright type is based on the so-called matter-wave interference of spatially separated condensates. In all three cases, a systematic numerical study is carried out upon considering different variations of each system's parameters both in the absence and in the presence of a harmonic trap. It is found that manipulating the initial separation or the chemical potential of the participating components allows us to tailor the number of nucleated dark-bright states. Particularly, …

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Effective Approach To Impurity Dynamics In One-Dimensional Trapped Bose Gases, Simeon I. Mistakidis, A. G. Volosniev, N. T. Zinner, P. Schmelcher Jul 2019

Effective Approach To Impurity Dynamics In One-Dimensional Trapped Bose Gases, Simeon I. Mistakidis, A. G. Volosniev, N. T. Zinner, P. Schmelcher

Physics Faculty Research & Creative Works

We Investigate A Temporal Evolution Of An Impurity Atom In A One-Dimensional Trapped Bose Gas Following A Sudden Change Of The Boson-Impurity Interaction Strength. Our Focus Is On The Effects Of Inhomogeneity Due To The Harmonic Confinement. These Effects Can Be Described By An Effective One-Body Model Where Both The Mass And The Spring Constant Are Renormalized. This Is In Contrast To The Classic Renormalization, Which Addresses Only The Mass. We Propose An Effective Single-Particle Hamiltonian And Apply The Multilayer Multiconfiguration Time-Dependent Hartree Method For Bosons To Explore Its Validity. Numerical Results Suggest That The Effective Mass Is Smaller Than …

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Automated Design Of Random Dynamic Graph Models, Aaron Scott Pope, Daniel R. Tauritz, Chris Rawlings Jul 2019

Automated Design Of Random Dynamic Graph Models, Aaron Scott Pope, Daniel R. Tauritz, Chris Rawlings

Computer Science Faculty Research & Creative Works

Dynamic graphs are an essential tool for representing a wide variety of concepts that change over time. Examples include modeling the evolution of relationships and communities in a social network or tracking the activity of users within an enterprise computer network. In the case of static graph representations, random graph models are often useful for analyzing and predicting the characteristics of a given network. Even though random dynamic graph models are a trending research topic, the field is still relatively unexplored. The selection of available models is limited and manually developing a model for a new application can be difficult …

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All-Sky Search For Continuous Gravitational Waves From Isolated Neutron Stars Using Advanced Ligo O2 Data, B. P. Abbott, R. Abbott, Marco Cavaglia, For Full List Of Authors, See Publisher's Website. Jul 2019

All-Sky Search For Continuous Gravitational Waves From Isolated Neutron Stars Using Advanced Ligo O2 Data, B. P. Abbott, R. Abbott, Marco Cavaglia, For Full List Of Authors, See Publisher's Website.

Physics Faculty Research & Creative Works

We present results of an all-sky search for continuous gravitational waves (CWs), which can be produced by fast spinning neutron stars with an asymmetry around their rotation axis, using data from the second observing run of the Advanced LIGO detectors. Three different semicoherent methods are used to search in a gravitational-wave frequency band from 20 to 1922 Hz and a first frequency derivative from -1 × 10-8 to 2 × 10-9 Hz/s. None of these searches has found clear evidence for a CW signal, so upper limits on the gravitational-wave strain amplitude are calculated, which for this broad …

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Adhesion Of Two-Dimensional Titanium Carbides (Mxenes) And Graphene To Silicon, Yanxiao Li, Shuohan Huang, Congjie Wei, Chenglin Wu, Vadym Mochalin Jul 2019

Adhesion Of Two-Dimensional Titanium Carbides (Mxenes) And Graphene To Silicon, Yanxiao Li, Shuohan Huang, Congjie Wei, Chenglin Wu, Vadym Mochalin

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Two-dimensional transition metal carbides (MXenes) have attracted a great interest of the research community as a relatively recently discovered large class of materials with unique electronic and optical properties. Understanding of adhesion between MXenes and various substrates is critically important for MXene device fabrication and performance. We report results of direct atomic force microscopy (AFM) measurements of adhesion of two MXenes (Ti3C2Tx and Ti2CTx) with a SiO2 coated Si spherical tip. The Maugis-Dugdale theory was applied to convert the AFM measured adhesion force to adhesion energy, while taking into account …

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Cafe Grants Go To Four Projects, Missouri University Of Science And Technology Jul 2019

Cafe Grants Go To Four Projects, Missouri University Of Science And Technology

CAFE Announcements

No abstract provided.

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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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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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Message From Program Chairs, Bruce M. Mcmillin, David Lo Jul 2019

Message From Program Chairs, Bruce M. Mcmillin, David Lo

Computer Science Faculty Research & Creative Works

No abstract provided.

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Imaging An Isolated Water Molecule Using A Single Electron Wave Packet, Xinyao Liu, Kasra Amini, Tobias Steinle, Anh-Thu Le, For Full List Of Authors, See Publisher's Website. Jul 2019

Imaging An Isolated Water Molecule Using A Single Electron Wave Packet, Xinyao Liu, Kasra Amini, Tobias Steinle, Anh-Thu Le, For Full List Of Authors, See Publisher's Website.

Physics Faculty Research & Creative Works

Observing changes in molecular structure requires atomic-scale Ångstrom and femtosecond spatio-temporal resolution. We use the Fourier transform (FT) variant of laser-induced electron diffraction (LIED), FT-LIED, to directly retrieve the molecular structure of H2O+ with picometer and femtosecond resolution without a priori knowledge of the molecular structure nor the use of retrieval algorithms or ab initio calculations. We identify a symmetrically stretched H2O+ field-dressed structure that is most likely in the ground electronic state. We subsequently study the nuclear response of an isolated water molecule to an external laser field at four different field strengths. …

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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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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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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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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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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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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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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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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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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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Charge Deposition, Redistribution, And Decay Properties Of Insulating Surfaces Obtained From Guiding Of Low-Energy Ions Through Capillaries, Robert D. Dubois, K. Tokési, E. Giglio Jun 2019

Charge Deposition, Redistribution, And Decay Properties Of Insulating Surfaces Obtained From Guiding Of Low-Energy Ions Through Capillaries, Robert D. Dubois, K. Tokési, E. Giglio

Physics Faculty Research & Creative Works

We present a combined experimental and theoretical study of the transmission of single charged 1-keV Ar ions through a cylindrical glass capillary of macroscopic dimensions. From quantitative measurements of the incoming and transmitted ion currents, combined with a detailed analysis, the amount of beam entering the capillary was determined. This, combined with the measured transmitted currents, was used to determine the amount of charge deposited on the inner wall of the capillary which produces the guiding electric field. We show experimental results for fully, and partially, discharged conditions of the time evolution of the guided beam intensity following a wide …

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Kinetic Resolution Of Cyclic Secondary Azides, Using An Enantioselective Copper-Catalyzed Azide-Alkyne Cycloaddition, Juliana R. Alexander, Amy A. Ott, En Chih Liu, Joseph J. Topczewski Jun 2019

Kinetic Resolution Of Cyclic Secondary Azides, Using An Enantioselective Copper-Catalyzed Azide-Alkyne Cycloaddition, Juliana R. Alexander, Amy A. Ott, En Chih Liu, Joseph J. Topczewski

Chemistry Faculty Research & Creative Works

An enantioselective copper-catalyzed azide-alkyne cycloaddition (E-CuAAC) is reported by kinetic resolution. Chiral triazoles were isolated in high yield with limiting alkyne (up to 97:3 enantiomeric ratio (er)). A range of substrates were tolerated (>30 examples), and the reaction was scaled to >1 g. The er of a triazole product could be enhanced by recrystallization and the recovered scalemic azide could be racemized and recycled. Recycling the azide allows efficient use of the undesired azide enantiomer.

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Spiking Networks For Improved Cognitive Abilities Of Edge Computing Devices, Anton Akusok, Yoan Miche, Kaj Mikael Björk, Renjie Hu, Leonardo Espinosa Leal, Amaury Lendasse Jun 2019

Spiking Networks For Improved Cognitive Abilities Of Edge Computing Devices, Anton Akusok, Yoan Miche, Kaj Mikael Björk, Renjie Hu, Leonardo Espinosa Leal, Amaury Lendasse

Engineering Management and Systems Engineering Faculty Research & Creative Works

This Concept Paper Highlights a Recently Opened Opportunity for Large Scale Analytical Algorithms to Be Trained Directly on Edge Devices. Such Approach is a Response to the Arising Need of Processing Data Generated by Natural Person (A Human Being), Also Known as Personal Data. Spiking Neural Networks Are the Core Method Behind It: Suitable for a Low Latency Energy-Constrained Hardware, Enabling Local Training or Re-Training, While Not Taking Advantage of Scalability Available in the Cloud.

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Positivity-Preserving, Energy Stable Numerical Schemes For The Cahn-Hilliard Equation With Logarithmic Potential, Wenbin Chen, Cheng Wang, Xiaoming Wang, Steven M. Wise Jun 2019

Positivity-Preserving, Energy Stable Numerical Schemes For The Cahn-Hilliard Equation With Logarithmic Potential, Wenbin Chen, Cheng Wang, Xiaoming Wang, Steven M. Wise

Mathematics and Statistics Faculty Research & Creative Works

In this paper we present and analyze finite difference numerical schemes for the Cahn-Hilliard equation with a logarithmic Flory Huggins energy potential. Both first and second order accurate temporal algorithms are considered. in the first order scheme, we treat the nonlinear logarithmic terms and the surface diffusion term implicitly and update the linear expansive term and the mobility explicitly. We provide a theoretical justification that this numerical algorithm has a unique solution, such that the positivity is always preserved for the logarithmic arguments, i.e., the phase variable is always between −1 and 1, at a point-wise level. in particular, our …

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Source Reconstruction Method Based On Machine Learning Algorithms, He Ming Yao, Lijun Jiang, Wei E.I. Sha Jun 2019

Source Reconstruction Method Based On Machine Learning Algorithms, He Ming Yao, Lijun Jiang, Wei E.I. Sha

Electrical and Computer Engineering Faculty Research & Creative Works

This paper proposes a new source reconstruction method (SRM) based on deep learning. The conventional SRM usually requires oversampled measurements data to ensure higher accuracy. Thus, conventional SRM numerical system is usually highly singular. A deep convolutional neural network (ConvNet) is proposed to reconstruct the equivalent sources of the target to overcome difficulty. The deep ConvNet allows us to employ less data samples. Besides, the ill-conditioned numerical system can be effectively avoided. Numerical examples are presented to demonstrate the feasibility and accuracy of the proposed method. Its performance is also compared with the traditional neural network and interpolation method. Moreover, …

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