Wide-band RF photonic second order vector sum phase-shifter

A novel technique to extend the phasing range of the vector sum phase shifter by exploiting its second order response is proposed and implemented. A continuously variable phase shift is demonstrated between 8 and 16 GHz with phasing range exceeding 450° measured at 16 GHz. Good agreement between the predictions and measurements has been obtained

Wide-band photonically phased array antenna using vector sum phase shifting approach

In this paper, a wide-band photonically phased array antenna is demonstrated. The array configuration consists of a 4 x 1 Vivaldi single-polarization antenna array and an independent photonic phasing system for each element. The phasing network of this array is implemented using two novel photonic phase shifters based on the vector summation approach. A vector sum phase shifter (VSPS), which exhibits a frequency-linear characteristic from dc to 15 GHz and can be continuously tuned from 0 to 100 degrees, is presented. A second-order VSPS (SO-VSPS), a modification of the VSPS that is capable of 0-430 degrees phasing range, is also demonstrated. This paper presents the operation and characterization of each component of the array, including the radiating elements and the various photonic phase shifters; and, finally, a demonstration of the combined system. A discussion on the practicality of this system for airborne applications is presented, along with suggestions for simplification and improvement

Silent MST approximation for tiny memory

In network distributed computing, minimum spanning tree (MST) is one of the key problems, and silent self-stabilization one of the most demanding fault-tolerance properties. For this problem and this model, a polynomial-time algorithm with $O(\log^2\!n)$ memory is known for the state model. This is memory optimal for weights in the classic $[1,\text{poly}(n)]$ range (where $n$ is the size of the network). In this paper, we go below this $O(\log^2\!n)$ memory, using approximation and parametrized complexity. More specifically, our contributions are two-fold. We introduce a second parameter~$s$, which is the space needed to encode a weight, and we design a silent polynomial-time self-stabilizing algorithm, with space $O(\log n \cdot s)$. In turn, this allows us to get an approximation algorithm for the problem, with a trade-off between the approximation ratio of the solution and the space used. For polynomial weights, this trade-off goes smoothly from memory $O(\log n)$ for an $n$-approximation, to memory $O(\log^2\!n)$ for exact solutions, with for example memory $O(\log n\log\log n)$ for a 2-approximation

Effects of Static and Dynamic Hamstring Stretching on Anaerobic Exercise Performance

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Statistical Basis for Predicting Technological Progress

Forecasting technological progress is of great interest to engineers, policy makers, and private investors. Several models have been proposed for predicting technological improvement, but how well do these models perform? An early hypothesis made by Theodore Wright in 1936 is that cost decreases as a power law of cumulative production. An alternative hypothesis is Moore's law, which can be generalized to say that technologies improve exponentially with time. Other alternatives were proposed by Goddard, Sinclair et al., and Nordhaus. These hypotheses have not previously been rigorously tested. Using a new database on the cost and production of 62 different technologies, which is the most expansive of its kind, we test the ability of six different postulated laws to predict future costs. Our approach involves hindcasting and developing a statistical model to rank the performance of the postulated laws. Wright's law produces the best forecasts, but Moore's law is not far behind. We discover a previously unobserved regularity that production tends to increase exponentially. A combination of an exponential decrease in cost and an exponential increase in production would make Moore's law and Wright's law indistinguishable, as originally pointed out by Sahal. We show for the first time that these regularities are observed in data to such a degree that the performance of these two laws is nearly tied. Our results show that technological progress is forecastable, with the square root of the logarithmic error growing linearly with the forecasting horizon at a typical rate of 2.5% per year. These results have implications for theories of technological change, and assessments of candidate technologies and policies for climate change mitigation

Comparison of some Reduced Representation Approximations

In the field of numerical approximation, specialists considering highly complex problems have recently proposed various ways to simplify their underlying problems. In this field, depending on the problem they were tackling and the community that are at work, different approaches have been developed with some success and have even gained some maturity, the applications can now be applied to information analysis or for numerical simulation of PDE's. At this point, a crossed analysis and effort for understanding the similarities and the differences between these approaches that found their starting points in different backgrounds is of interest. It is the purpose of this paper to contribute to this effort by comparing some constructive reduced representations of complex functions. We present here in full details the Adaptive Cross Approximation (ACA) and the Empirical Interpolation Method (EIM) together with other approaches that enter in the same category

A redistribution of water due to pileus cloud formation near the tropopause

International audienceThin stratiform clouds called pileus can form in the earth's atmosphere when humid air is lifted above rising convection. In the lower troposphere pileus lifetimes are short, so they have been considered little more than an attractive curiosity. This paper describes pileus cloud forming near the tropopause at low-latitudes, and discusses how they may be associated with a redistribution of water vapor and ice at cold temperatures