Learning Equations for Extrapolation and Control

We present an approach to identify concise equations from data using a shallow neural network approach. In contrast to ordinary black-box regression, this approach allows understanding functional relations and generalizing them from observed data to unseen parts of the parameter space. We show how to extend the class of learnable equations for a recently proposed equation learning network to include divisions, and we improve the learning and model selection strategy to be useful for challenging real-world data. For systems governed by analytical expressions, our method can in many cases identify the true underlying equation and extrapolate to unseen domains. We demonstrate its effectiveness by experiments on a cart-pendulum system, where only 2 random rollouts are required to learn the forward dynamics and successfully achieve the swing-up task.Comment: 9 pages, 9 figures, ICML 201

Resistive switching in ultra-thin La0.7Sr0.3MnO3 / SrRuO3 superlattices

Superlattices may play an important role in next generation electronic and spintronic devices if the key-challenge of the reading and writing data can be solved. This challenge emerges from the coupling of low dimensional individual layers with macroscopic world. Here we report the study of the resistive switching characteristics of a of hybrid structure made out of a superlattice with ultrathin layers of two ferromagnetic metallic oxides, La0.7Sr0.3MnO3 (LSMO) and SrRuO3 (SRO). Bipolar resistive switching memory effects are measured on these LSMO/SRO superlattices, and the observed switching is explainable by ohmic and space charge-limited conduction laws. It is evident from the endurance characteristics that the on/off memory window of the cell is greater than 14, which indicates that this cell can reliably distinguish the stored information between high and low resistance states. The findings may pave a way to the construction of devices based on nonvolatile resistive memory effects

Tort Law: What Defenses Are There to a Products Liability Action in Ohio?

Bowling v. Heil Co., 31 Ohio St. 3d 277, 511 N.E.2d 373 (1987); Onderko v. Richmond Mfg. Co., 31 Ohio St. 3d 296, 511 N.E.2d 388 (1987)

Negative capacitance in organic semiconductor devices: bipolar injection and charge recombination mechanism

We report negative capacitance at low frequencies in organic semiconductor based diodes and show that it appears only under bipolar injection conditions. We account quantitatively for this phenomenon by the recombination current due to electron-hole annihilation. Simple addition of the recombination current to the well established model of space charge limited current in the presence of traps, yields excellent fits to the experimentally measured admittance data. The dependence of the extracted characteristic recombination time on the bias voltage is indicative of a recombination process which is mediated by localized traps.Comment: 3 pages, 3 figures, accepted for publication in Applied Physics Letter

Combining Appearance and Motion for Human Action Classification in Videos

We study the question of activity classification in videos and present a novel approach for recognizing human action categories in videos by combining information from appearance and motion of human body parts. Our approach uses a tracking step which involves Particle Filtering and a local non - parametric clustering step. The motion information is provided by the trajectory of the cluster modes of a local set of particles. The statistical information about the particles of that cluster over a number of frames provides the appearance information. Later we use a “Bag ofWords” model to build one histogram per video sequence from the set of these robust appearance and motion descriptors. These histograms provide us characteristic information which helps us to discriminate among various human actions and thus classify them correctly. We tested our approach on the standard KTH and Weizmann human action datasets and the results were comparable to the state of the art. Additionally our approach is able to distinguish between activities that involve the motion of complete body from those in which only certain body parts move. In other words, our method discriminates well between activities with “gross motion” like running, jogging etc. and “local motion” like waving, boxing etc

Polyfluorene as a model system for space-charge-limited conduction

Ethyl-hexyl substituted polyfluorene (PF) with its high level of molecular disorder can be described very well by one-carrier space-charge-limited conduction for a discrete set of trap levels with energy $\sim$ 0.5 eV above the valence band edge. Sweeping the bias above the trap-filling limit in the as-is polymer generates a new set of exponential traps, which is clearly seen in the density of states calculations. The trapped charges in the new set of traps have very long lifetimes and can be detrapped by photoexcitation. Thermal cycling the PF film to a crystalline phase prevents creation of additional traps at higher voltages.Comment: 13 pages, 4 figures. Physical Review B (accepted, 2007

MIDAS, prototype Multivariate Interactive Digital Analysis System for large area earth resources surveys. Volume 1: System description

A third-generation, fast, low cost, multispectral recognition system (MIDAS) able to keep pace with the large quantity and high rates of data acquisition from large regions with present and projected sensots is described. The program can process a complete ERTS frame in forty seconds and provide a color map of sixteen constituent categories in a few minutes. A principle objective of the MIDAS program is to provide a system well interfaced with the human operator and thus to obtain large overall reductions in turn-around time and significant gains in throughput. The hardware and software generated in the overall program is described. The system contains a midi-computer to control the various high speed processing elements in the data path, a preprocessor to condition data, and a classifier which implements an all digital prototype multivariate Gaussian maximum likelihood or a Bayesian decision algorithm. Sufficient software was developed to perform signature extraction, control the preprocessor, compute classifier coefficients, control the classifier operation, operate the color display and printer, and diagnose operation