California Polytechnic State University - San Luis Obispo
University of Arkansas, Fayetteville
Marquette University
Michigan Technological University
University of Kentucky
Stability Analysis Of A More General Class Of Systems With Delay-Dependent Coefficients,
2019
Laboratoire des Signaux et Syst`emes (L2S) CentraleSup´elec-CNRS-Universit´e Paris Sud, 3 rue Joliot- Curie 91192 Gif-sur-Yvette cedex, France.
Stability Analysis Of A More General Class Of Systems With Delay-Dependent Coefficients, Chi Jin, Keqin Gu, Islam Boussaada, Silviu-Iulian Niculescu
SIUE Faculty Research, Scholarship, and Creative Activity
This paper presents a systematic method to analyse the stability of systems with single delay in which the coefficient polynomials of the characteristic equation depend on the delay. Such systems often arise in, for example, life science and engineering systems. A method to analyze such systems was presented by Beretta and Kuang in a 2002 paper, but with some very restrictive assumptions. This work extends their results to the general case with the exception of some degenerate cases. It is found that a much richer behavior is possible when the restrictive assumptions are removed. The interval of interest for the ...
Validating The Opa Cascading Blackout Model On A 19402 Bus Transmission Network With Both Mesh And Tree Structures,
2019
BACV Solutions, Inc.
Validating The Opa Cascading Blackout Model On A 19402 Bus Transmission Network With Both Mesh And Tree Structures, Benjamin A. Carreras, Jose M. Reynolds-Barredo, Ian Dobson, David E. Newman
Electrical and Computer Engineering Conference Papers, Posters and Presentations
The OPA model calculates the long-term risk of cascading blackouts by simulating cascading outages and the slow process of network upgrade in response to blackouts. We validate OPA on a detailed 19402 bus network model of the Western Electricity Coordinating Council (WECC) interconnection with publicly available data. To do this, we examine scalings on a series of WECC interconnection models with increasing detail. The most detailed, 19402 bus network has more tree structures at the edges of the main mesh structure, and we extend the OPA model to account for this. The higher-risk cascading outages are the large cascades that ...
Thin-Film Sensor For Fatigue Crack Sensing And Monitoring In Steel Bridges Under Varying Crack Propagation Rates And Random Traffic Loads,
2019
University of Kansas
Thin-Film Sensor For Fatigue Crack Sensing And Monitoring In Steel Bridges Under Varying Crack Propagation Rates And Random Traffic Loads, Xiangxiong Kong, Jian Li, Caroline Bennett, William Collins, Simon Laflamme, Hongki Jo
Civil, Construction and Environmental Engineering Publications
Fatigue cracks are critical structural concerns for steel highway bridges, and fatigue initiation and propagation activity continues undetected between physical bridge inspections. Monitoring fatigue crack activity between physical inspections can provide far greater reliability in structural performance and can be used to prevent excessive damage and repair costs. In this paper, a thin-film strain sensor, called a soft elastomeric capacitor (SEC) sensor, is evaluated for sensing and monitoring fatigue cracks in steel bridges. The SEC is a flexible and mechanically robust strain sensor, capable of monitoring strain over large structural surfaces. By deploying multiple SECs in the form of dense ...
Csar 62 Spin Curve,
2018
Singh Center for Nanotechnology
Csar 62 Spin Curve, Mohsen Azadi, Georgia Griggs, Glen De Villafranca, Gerald Lopez
Protocols and Reports
No abstract provided.
Electrically-Conductive Asphalt Mastic: Temperature Dependence And Heating Efficiency,
2018
Iowa State University
Electrically-Conductive Asphalt Mastic: Temperature Dependence And Heating Efficiency, Ali Arabzadeh, Halil Ceylan, Sunghwan Kim, Alireza Sassani, Kasthurirangan Gopalakrishnan, Mani Mina
Civil, Construction and Environmental Engineering Publications
Asphalt mastic, a pitch-matrix composite, consists of bitumen and mineral fillers (very fine aggregates), that fills the voids created by coarser aggregates in asphalt concrete. In this study, asphalt mastic was modified with carbon fiber (CF) and graphite powder (GP) to produce single-phase (containing only CF) and two-phase (containing both CF and GP) electrically-conductive asphalt mastic (ECAM) for anti-icing and deicing applications. Volume resistivities of ECAMs were measured at two different temperatures and the influence of temperature on electrical conductivity was evaluated, revealing that reduction in temperature enhances the ECAM's electrical conductivity. After analyzing the volume resistivity data for ...
Study Of Physical Layer Security And Teaching Methods In Wireless Communications,
2018
NC A&T State Unversity
Study Of Physical Layer Security And Teaching Methods In Wireless Communications, Zhijian Xie, Christopher Horne
KSU Proceedings on Cybersecurity Education, Research and Practice
In most wireless channels, the signals propagate in all directions. For the communication between Alice and Bob, an Eavesdropper can receive the signals from both Alice and Bob as far as the Eavesdropper is in the range determined by the transmitting power. Through phased array antenna with beam tracking circuits or cooperative iteration, the signals are confined near the straight line connecting the positions of Alice and Bob, so it will largely reduce the valid placement of an Eavesdropper. Sometimes, this reduction can be prohibitive for Eavesdropper to wiretap the channel since the reduced space can be readily protected. Two ...
The Subject Librarian Newsletter, Engineering And Computer Science, Spring 2018,
2018
University of Central Florida
The Subject Librarian Newsletter, Engineering And Computer Science, Spring 2018, Buenaventura "Ven" Basco
Buenaventura "Ven" Basco
No abstract provided.
The Subject Librarian Newsletter, Engineering And Computer Science, Fall 2017,
2018
University of Central Florida
The Subject Librarian Newsletter, Engineering And Computer Science, Fall 2017, Buenaventura "Ven" Basco
Buenaventura "Ven" Basco
No abstract provided.
Transactive Energy Design For Integrated Transmission And Distribution Systems,
2018
Iowa State University
Transactive Energy Design For Integrated Transmission And Distribution Systems, Hieu Trung Nguyen, Swathi Battula, Rohit Reddy Takkala, Zhaoyu Wang, Leigh Tesfatsion
Economics Working Papers
The increasing deployment of distributed energy resources (DERs) is disrupting every aspect of power system operations, from retail distribution to wholesale production and transmission. This paper reports on the development of an agentbased test system enabling the study of new transactive energy system (TES) designs to ensure the reliable efficient operation of integrated transmission and distribution (ITD) systems with growing DER penetration. This ITD test system is used to explore the ability of a non-profit Distribution System Operator (DSO), participating within an ITD system, to use an innovative TES design to manage the power usage of DER devices in accordance ...
Vibration Analysis Via Neural Network Inverse Models To Determine Aircraft Engine Unbalance Condition,
2018
Missouri University of Science and Technology
Vibration Analysis Via Neural Network Inverse Models To Determine Aircraft Engine Unbalance Condition, Xiao Hu, J. L. Vian, Donald C. Wunsch, J. R. Slepski
Donald C. Wunsch
This paper describes the use of artificial neural networks (ANNs) with the vibration data from real flight tests for detecting engine health condition - mass imbalance herein. Order-tracking data, calculated from time series is used as the input to the neural networks to determine the amount and location of mass imbalance on aircraft engines. Several neural network methods, including multilayer perceptron (MLP), extended Kalman filter (EKF) and support vector machines (SVMs) are used in the neural network inverse model for the performance comparison. The promising performances are presented at the end.
Using Neural Networks To Estimate Wind Turbine Power Generation,
2018
Missouri University of Science and Technology
Using Neural Networks To Estimate Wind Turbine Power Generation, Shuhui Li, Donald C. Wunsch, Edgar O'Hair, Michael G. Giesselmann
Donald C. Wunsch
This paper uses data collected at Central and South West Services Fort Davis wind farm to develop a neural network based prediction of power produced by each turbine. The power generated by electric wind turbines changes rapidly because of the continuous fluctuation of wind speed and direction. It is important for the power industry to have the capability to perform this prediction for diagnostic purposes—lower-than-expected wind power may be an early indicator of a need for maintenance. In this paper, characteristics of wind power generation are first evaluated in order to establish the relative importance for the neural network ...
Two Neural Network Based Decentralized Controller Designs For Large Scale Power Systems,
2018
Missouri University of Science and Technology
Two Neural Network Based Decentralized Controller Designs For Large Scale Power Systems, Wenxin Liu, Jagannathan Sarangapani, Ganesh K. Venayagamoorthy, Donald C. Wunsch, Mariesa Crow, David A. Cartes
Donald C. Wunsch
This paper presents two neural network (NN) based decentralized controller designs for large scale power systems' generators, one is for the excitation control and the other is for the steam valve control. Though the control signals are calculated using local signals only, the transient and overall system stabilities can be guaranteed. NNs are used to approximate the unknown and/or imprecise dynamics of the local power system and the interconnection terms, thus the requirements for exact system parameters are released. Simulation studies with a three machine power system demonstrate the effectiveness of the proposed controller designs.
Training Winner-Take-All Simultaneous Recurrent Neural Networks,
2018
Missouri University of Science and Technology
Training Winner-Take-All Simultaneous Recurrent Neural Networks, Xindi Cai, Danil V. Prokhorov, Donald C. Wunsch
Donald C. Wunsch
The winner-take-all (WTA) network is useful in database management, very large scale integration (VLSI) design, and digital processing. The synthesis procedure of WTA on single-layer fully connected architecture with sigmoid transfer function is still not fully explored. We discuss the use of simultaneous recurrent networks (SRNs) trained by Kalman filter algorithms for the task of finding the maximum among N numbers. The simulation demonstrates the effectiveness of our training approach under conditions of a shared-weight SRN architecture. A more general SRN also succeeds in solving a real classification application on car engine data.
Tissue Classification Through Analysis Of Gene Expression Data Using A New Family Of Art Architectures,
2018
Missouri University of Science and Technology
Tissue Classification Through Analysis Of Gene Expression Data Using A New Family Of Art Architectures, Rui Xu, Georgios C. Anagnostopoulos, Donald C. Wunsch
Donald C. Wunsch
Correct classification is crucial to cancer diagnosis and treatment. We demonstrate that a new family of neural network architectures-Ellipsoid ART and ARTMAP (EA/EAM)-can cluster and classify tissues successfully through analysis of gene expression data generated by DNA microarray experiments
Time Series Prediction With A Weighted Bidirectional Multi-Stream Extended Kalman Filter,
2018
Missouri University of Science and Technology
Time Series Prediction With A Weighted Bidirectional Multi-Stream Extended Kalman Filter, Donald C. Wunsch, Xiao Hu
Donald C. Wunsch
This paper describes the use of a multi-stream extended Kalman filter (EKF) to tackle the IJCNN 2004 challenge problem - time series prediction on CATS benchmark. A weighted bidirectional approach was adopted in the experiments to incorporate the forward and backward predictions of the time series. EKF is a practical, general approach to neural networks training. It consists of the following: 1) gradient calculation by backpropagation through time (BPTT); 2) weight updates based on the extended Kalman filter; and 3) data presentation using multi-stream mechanics.
Time Series Prediction With Recurrent Neural Networks Using A Hybrid Pso-Ea Algorithm,
2018
Missouri University of Science and Technology
Time Series Prediction With Recurrent Neural Networks Using A Hybrid Pso-Ea Algorithm, Nian Zhang, Ganesh K. Venayagamoorthy, Donald C. Wunsch, Xindi Cai
Donald C. Wunsch
To predict the 100 missing values from the time series consisting of 5000 data given for the IJCNN 2004 time series prediction competition, we applied an architecture which automates the design of recurrent neural networks using a new evolutionary learning algorithm. This new evolutionary learning algorithm is based on a hybrid of particle swarm optimization (PSO) and evolutionary algorithm (EA). By combining the searching abilities of these two global optimization methods, the evolution of individuals is no longer restricted to be in the same generation, and better performed individuals may produce offspring to replace those with poor performance. The novel ...
The Subcircuit Extraction Problem,
2018
Missouri University of Science and Technology
The Subcircuit Extraction Problem, Nian Zhang, Donald C. Wunsch, Frank Harary
Donald C. Wunsch
The steady down scaling of CMOS device dimensions has been the main stimulus to the growth of microelectronics and computer aided very large scale integration (VLSI) design. But the more an integrated circuit (IC) is scaled, the higher its packing density becomes. The increasing size of chips, measured in either area or number of transistors, and the waste of the large capital investment involved in fabricating and testing circuits that do not work, make layout analysis and verification an important part of physical design automation. The most efficient way to overcome these difficulties is to identify a related collection of ...
The General Approximation Theorem,
2018
Missouri University of Science and Technology
The General Approximation Theorem, Donald C. Wunsch, Alexander N. Gorban
Donald C. Wunsch
A general approximation theorem is proved. It uniformly envelopes both the classical Stone theorem and approximation of functions of several variables by means of superpositions and linear combinations of functions of one variable. This theorem is interpreted as a statement on universal approximating possibilities ("approximating omnipotence") of arbitrary nonlinearity. For the neural networks, our result states that the function of neuron activation must be nonlinear, and nothing else
Survey Of Clustering Algorithms,
2018
Missouri University of Science and Technology
Survey Of Clustering Algorithms, Rui Xu, Donald C. Wunsch
Donald C. Wunsch
Data analysis plays an indispensable role for understanding various phenomena. Cluster analysis, primitive exploration with little or no prior knowledge, consists of research developed across a wide variety of communities. The diversity, on one hand, equips us with many tools. On the other hand, the profusion of options causes confusion. We survey clustering algorithms for data sets appearing in statistics, computer science, and machine learning, and illustrate their applications in some benchmark data sets, the traveling salesman problem, and bioinformatics, a new field attracting intensive efforts. Several tightly related topics, proximity measure, and cluster validation, are also discussed.
Speeding Up Vlsi Layout Verification Using Fuzzy Attributed Graphs Approach,
2018
Missouri University of Science and Technology
Speeding Up Vlsi Layout Verification Using Fuzzy Attributed Graphs Approach, Nian Zhang, Donald C. Wunsch
Donald C. Wunsch
Technical and economic factors have caused the field of physical design automation to receive increasing attention and commercialization. The steady down-scaling of complementary metal oxide semiconductor (CMOS) device dimensions has been the main stimulus to the growth of microelectronics and computer-aided very large scale integration (VLSI) design. The more an Integrated Circuit (IC) is scaled, the higher its packing density becomes. For example, in 2006 Intel's 65-nm process technology for high performance microprocessor has a reduced gate length of 35 nanometers. In their 70-Mbit SRAM chip, there are up to 0.5 billion transistors in a 110 mm2 chip ...
