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Full-Text Articles in Engineering
The Electronic Structure And Secondary Pyroelectric Properties Of Lithium Tetraborate, Volodymyr T. Adamiv, Yaroslav V. Burak, David J. Wooten, John W. Mcclory, James C. Petrosky, Ihor Ketsman, Ya B. Losovyj, Peter A. Dowben, Jie Xiao
The Electronic Structure And Secondary Pyroelectric Properties Of Lithium Tetraborate, Volodymyr T. Adamiv, Yaroslav V. Burak, David J. Wooten, John W. Mcclory, James C. Petrosky, Ihor Ketsman, Ya B. Losovyj, Peter A. Dowben, Jie Xiao
Faculty Publications
We review the pyroelectric properties and electronic structure of Li2B4O7(110) and Li2B4O7(100) surfaces. There is evidence for a pyroelectric current along the [110] direction of stoichiometric Li2B4O7 so that the pyroelectric coefficient is nonzero but roughly 103 smaller than along the [001] direction of spontaneous polarization. Abrupt decreases in the pyroelectric coefficient along the [110] direction can be correlated with anomalies in the elastic stiffness contributing to the concept that the pyroelectric coefficient is not simply a vector but has qualities of …
Stochastic Feature Selection With Distributed Feature Spacing For Hyperspectral Data, Jeffrey D. Clark, Michael J. Mendenhall, Gilbert L. Peterson
Stochastic Feature Selection With Distributed Feature Spacing For Hyperspectral Data, Jeffrey D. Clark, Michael J. Mendenhall, Gilbert L. Peterson
Faculty Publications
Feature subset selection is a well studied problem in machine learning. One short-coming of many methods is the selection of highly correlated features; a characteristic of hyperspectral data. A novel stochastic feature selection method with three major components is presented. First, we present an optimized feature selection method that maximizes a heuristic using a simulated annealing search which increases the chance of avoiding locally optimum solutions. Second, we exploit local cross correlation pair-wise amongst classes of interest to select suitable features for class discrimination. Third, we adopt the concept of distributed spacing from the multi-objective optimization community to distribute features …
Wireless Sensor Network Radio Power Management And Simulation Models, Michael I. Brownfield, Theresa Nelson, Scott Midkiff, Nathaniel J. Davis Iv
Wireless Sensor Network Radio Power Management And Simulation Models, Michael I. Brownfield, Theresa Nelson, Scott Midkiff, Nathaniel J. Davis Iv
Faculty Publications
Wireless sensor networks (WSNs) create a new frontier in collecting and processing data from remote locations. The IEEE 802.15.4 wireless personal area network-low rate (WPAN-LR) WSNs rely on hardware simplicity to make sensor field deployments both affordable and long-lasting without maintenance support. WSN designers strive to extend network lifetimes while meeting application-specific throughput and latency requirements. Effective power management places sensor nodes (or motes) into one of the available energy-saving modes based upon the sleep period duration and the current state of the radio. The newest generation of WPAN-LR-based sensor platform radios operates at a 250 kbps data rate and …