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Articles 1 - 4 of 4
Full-Text Articles in Physical Sciences and Mathematics
Self-Assembled Composite Nano-/Micronecklaces With Sio2 Beads In Boron Strings, Hai Ni, Xiaodong Li
Self-Assembled Composite Nano-/Micronecklaces With Sio2 Beads In Boron Strings, Hai Ni, Xiaodong Li
Faculty Publications
Nano-/micronecklaces with SiO2 beads in boron strings were synthesized by simply sublimating the desired powders in a sealed quartz tube at high temperature. The boron strings have a rectangular cross section with width varying from 80to1000nm while the SiO2 beads bear either spindle or spherical shape with a size ranging from 100nmto5μm. The spacing between the SiO2 beads is uniform in each boron string. Both the boron strings and the SiO2 beads are amorphous and free of defects. The supersaturated vapors of silicon and oxygen induced the SiO2 bead formation.
Multiple Masks-Based Pixel Comparison Steganalysis Method For Mobile Imaging, Sos S. Agaian, Gilbert L. Peterson, Benjamin M. Rodriguez
Multiple Masks-Based Pixel Comparison Steganalysis Method For Mobile Imaging, Sos S. Agaian, Gilbert L. Peterson, Benjamin M. Rodriguez
Faculty Publications
No abstract provided.
Erratum: “Terahertz Studies Of The Dielectric Response And Second-Order Phonons In A Gase Crystal” [Appl. Phys. Lett.87, 182104 (2005)], B. L. Yu, F. Zeng, V. Kartazayev, R. R. Alfano, K. C. Mandal
Erratum: “Terahertz Studies Of The Dielectric Response And Second-Order Phonons In A Gase Crystal” [Appl. Phys. Lett.87, 182104 (2005)], B. L. Yu, F. Zeng, V. Kartazayev, R. R. Alfano, K. C. Mandal
Faculty Publications
No abstract provided.
Learning Real-Time A* Path Planner For Unmanned Air Vehicle Target Sensing, Jason K. Howlett, Timothy W. Mclain, Michael A. Goodrich
Learning Real-Time A* Path Planner For Unmanned Air Vehicle Target Sensing, Jason K. Howlett, Timothy W. Mclain, Michael A. Goodrich
Faculty Publications
This paper presents a path planner for sensing closely-spaced targets from a fixed-wing unmanned air vehicle (UAV) having a specified sensor footprint. The planner is based on the learning real-time A* (LRTA*) search algorithm and produces dynamically feasible paths that accomplish the sensing objectives in the shortest possible distance. A tree of candidate paths that span the area of interest is created by assembling primitive turn and straight sections of a specified step size in a sequential fashion from the starting position of the UAV. An LRTA* search of the tree produces feasible paths any time during its execution and …