On Multi-Step Sensor Scheduling via Convex Optimization

Effective sensor scheduling requires the consideration of long-term effects and thus optimization over long time horizons. Determining the optimal sensor schedule, however, is equivalent to solving a binary integer program, which is computationally demanding for long time horizons and many sensors. For linear Gaussian systems, two efficient multi-step sensor scheduling approaches are proposed in this paper. The first approach determines approximate but close to optimal sensor schedules via convex optimization. The second approach combines convex optimization with a \BB search for efficiently determining the optimal sensor schedule.Comment: 6 pages, appeared in the proceedings of the 2nd International Workshop on Cognitive Information Processing (CIP), Elba, Italy, June 201

Experimental research on the development of Ceratium hirundinella O.F.Muller [Translation from: Z.Bot. 14, 337-371, 1922]

The most important aim of this study lay in filling in the great gap in our knowledge of the processes of germination in the Ceratium cyst and the early developmental stages in the standing stock of Ceratium hirundinella. contained rich cysts, we now succeeded extraordinarily well in pursuing the consistent development of Ceratium from the cyst to the completed cell. A series of experiments were carried out on the cysts and the juvenile stages of Ceratium, which showed very interesting results. The author presents in a general descriptive part the normal processes of germination in Ceratium cysts and the development of the juvenile stages in order to show in an experimental part the changes in form of C. hirundinella under the influence of temperature, light and varying salinities

Enhancing Decision Tree based Interpretation of Deep Neural Networks through L1-Orthogonal Regularization

One obstacle that so far prevents the introduction of machine learning models primarily in critical areas is the lack of explainability. In this work, a practicable approach of gaining explainability of deep artificial neural networks (NN) using an interpretable surrogate model based on decision trees is presented. Simply fitting a decision tree to a trained NN usually leads to unsatisfactory results in terms of accuracy and fidelity. Using L1-orthogonal regularization during training, however, preserves the accuracy of the NN, while it can be closely approximated by small decision trees. Tests with different data sets confirm that L1-orthogonal regularization yields models of lower complexity and at the same time higher fidelity compared to other regularizers.Comment: 8 pages, 18th IEEE International Conference on Machine Learning and Applications (ICMLA) 201

Compensating linkage for main rotor control

A compensating linkage for the rotor control system on rotary wing aircraft is described. The main rotor and transmission are isolated from the airframe structure by clastic suspension. The compensating linkage prevents unwanted signal inputs to the rotor control system caused by relative motion of the airframe structure and the main rotor and transmission

Fe 1, Cr 1 and Cr 2 gf-values from shock-tube measurements

Fe and Cr oscillator strength and statistical population factors measured by absorption technique from shock heated ga

FE I, CR I and CR II GF values from shock tube measurements

Absorption spectra determination of iron and chromium Fermi-Dirac values by shock heated argon tub

Photoelectron spectroscopy of NpPd3 and PuPd3

We present the results of x-ray and ultraviolet photoelectron spectroscopy of NpPd3 and PuPd3. The spectra indicate that for both compounds, the 5f electrons are well localized on the actinide sites. Comparison with bulk measurements indicates that for NpPd3 the electrons have a valence of Np3+ and thus a ground state 5f4 with a Hund's rules 5I4 configuration. Similarly for PuPd3, we find a Pu3+ valence, 5f5 ground state and a Hund's rules 6H5/2 configuration

Discovery of the secondary eclipse of HAT-P-11 b

We report the detection of the secondary eclipse of HAT-P-11 b, a Neptune-sized planet orbiting an active K4 dwarf. Using all available short-cadence data of the Kepler mission, we derive refined planetary ephemeris increasing their precision by more than an order of magnitude. Our simultaneous primary and secondary transit modeling results in improved transit and orbital parameters. In particular, the precise timing of the secondary eclipse allows to pin down the orbital eccentricity to $0.26459_{-0.00048}^{+0.00069}$. The secondary eclipse depth of $6.09_{-1.11}^{+1.12}$ ppm corresponds to a $5.5\sigma$ detection and results in a geometric albedo of $0.39\pm0.07$ for HAT-P-11 b, close to Neptune's value, which may indicate further resemblances between these two bodies. Due to the substantial orbital eccentricity, the planetary equilibrium temperature is expected to change significantly with orbital position and ought to vary between $630^\circ$ K and $950^\circ$ K, depending on the details of heat redistribution in the atmosphere of HAT-P-11 b.Comment: Accepted by A&A, 27/10/201