SRI International

About: SRI International is a nonprofit organization based out in Menlo Park, California, United States. It is known for research contribution in the topics: Ionosphere & Laser. The organization has 7222 authors who have published 13102 publications receiving 660724 citations. The organization is also known as: Stanford Research Institute & SRI.

Atomic and Molecular Polarizabilities-A Review of Recent Advances

Abstract: Publisher Summary This chapter focuses on the recent developments in the experimental and theoretical determination of the polarizabilities of simple atoms and molecules. Polarizability values (related to the “quadratic Stark effect”) are accurately known for the noble gas atoms and for hydrogen, in theory, but the remainder of the periodic table has proven much more difficult to deal with, both theoretically and experimentally. The static electric dipole polarizability of the ground-state hydrogen atom is almost exactly 4.5a30, where a0 is the Bohr radius. Across rows of the periodic table, polarizabilities range from hundreds (of a30 units) for the alkali metal atoms generally monotonically down to a few for noble gas atoms. Excited atoms have much larger polarizabilities; recent polarizability measurements for atoms in Rydberg orbits have yielded values on the order of 1010a30. Further research on molecular polarizabilities can help in the determination of polarizability anisotropies whether through state selection or with beams of different temperatures. Supersonic molecular beams are found to have low internal energies, and the internal energy can be controlled somewhat in “seeded” beams.

High-Strain Actuator Materials Based on Dielectric Elastomers

Abstract: Dielectric elastomers are a new class of actuator materials that exhibit excellent performance. The principle of operation, as well as methods to fabricate and test these elastomers, is summarized here. The Figure is a sketch of an elastomer film (light gray) stretched on a frame (black) and patterned with an electrode (mid-gray). Upon applying a voltage, the active portion of the elastomer expands and the strain can easily be measured optically.

Self-Calibration of a Moving Camera from PointCorrespondences and Fundamental Matrices

Abstract: We address the problem of estimating three-dimensional motion, and structure from motion with an uncalibrated moving camera We show that point correspondences between three images, and the fundamental matrices computed from these point correspondences, are sufficient to recover the internal orientation of the camera (its calibration), the motion parameters, and to compute coherent perspective projection matrices which enable us to reconstruct 3-D structure up to a similarity In contrast with other methods, no calibration object with a known 3-D shape is needed, and no limitations are put upon the unknown motions to be performed or the parameters to be recovered, as long as they define a projective camera The theory of the method, which is based on the constraint that the observed points are part of a static scene, thus allowing us to link the intrinsic parameters and the fundamental matrix via the absolute conic, is first detailed Several algorithms are then presented, and their performances compared by means of extensive simulations and illustrated by several experiments with real images

Neurocube: a programmable digital neuromorphic architecture with high-density 3D memory

Abstract: This paper presents a programmable and scalable digital neuromorphic architecture based on 3D high-density memory integrated with logic tier for efficient neural computing. The proposed architecture consists of clusters of processing engines, connected by 2D mesh network as a processing tier, which is integrated in 3D with multiple tiers of DRAM. The PE clusters access multiple memory channels (vaults) in parallel. The operating principle, referred to as the memory centric computing, embeds specialized state-machines within the vault controllers of HMC to drive data into the PE clusters. The paper presents the basic architecture of the Neurocube and an analysis of the logic tier synthesized in 28nm and 15nm process technologies. The performance of the Neurocube is evaluated and illustrated through the mapping of a Convolutional Neural Network and estimating the subsequent power and performance for both training and inference.