Parallel projected variable metric algorithms for unconstrained optimization

The parallel variable metric optimization algorithms of Straeter (1973) and van Laarhoven (1985) are reviewed, and the possible drawbacks of the algorithms are noted. By including Davidon (1975) projections in the variable metric updating, researchers can generalize Straeter's algorithm to a family of parallel projected variable metric algorithms which do not suffer the above drawbacks and which retain quadratic termination. Finally researchers consider the numerical performance of one member of the family on several standard example problems and illustrate how the choice of the displacement vectors affects the performance of the algorithm

Evidence of Early Enrichment of the Galactic Disk by Large-Scale Winds

Large-scale homogeneous surveys of Galactic stars may indicate that the elemental abundance gradient evolves with cosmic time, a phenomenon that was not foreseen in existing models of Galactic chemical evolution (GCE). If the phenomenon is confirmed in future studies, we show that this effect, at least in part, is due to large-scale winds that once enriched the disk. These set up the steep abundance gradient in the inner disk (R <14 kpc). At the close of the wind phase, chemical enrichment through accretion of metal-poor material from the halo onto the disk gradually reduced the metallicity of the inner region, whereas a slow increase in the metallicity proceeded beyond the solar circle. Our "wind+infall" model accounts for flattening of the abundance gradient in the inner disk, in good agreement with observations. Accordingly, we propose that enrichment by large-scale winds is a crucial factor for chemical evolution in the disk. We anticipate that rapid flattening of the abundance gradient is the hallmarks of disk galaxies with significant central bulges.Comment: 9 pages including 5 figures, accepted for publication in PAS

Sequential License Buyback Auctions: An Experimental Analysis

Fisheries managers use licenses as a method of capping the size of a fishing industry, but as management goals change and the size of fishery stocks fluctuate, managers may be faced with the decision to buy back licenses. The vast majority of economic literature on license buyback programs focuses on the changes to economic efficiency of the fleet, often citing changes to the composition of fleet size. However, managers have little guidance in deciding how to structure a buyback auction, despite the fact that the auction structure plays a key role in determining which licenses are retired and in the composition of the remaining fleet. With the Texas Park and Wildlife Department’s Inshore Shrimp License Buyback Program as a basis for auction design, this research uses three experimental treatments to analyze how individuals respond to various reverse auction structures. In terms of the quickest license expiration, our experiments suggest that fisheries managers should select a binding auction with no sequential quality. However, we find that managers would see higher average bids from fishers in comparison to the two sequential auctions. The results are also relevant to other environmental programs in which environmental services are purchased over time in a sequential reverse auction.Fisheries management, license buyback, reverse auction, Institutional and Behavioral Economics, Research and Development/Tech Change/Emerging Technologies, Research Methods/ Statistical Methods, Q22, Q28, C9,

The mechanical properties of inconel 718 sheet alloy at 800 deg, 1000 deg, and 1200 deg f

Mechanical properties of Inconel sheet superalloy at very high temperatures for supersonic transpor

Multivariable Repetitive-predictive Controllers using Frequency Decomposition

Repetitive control is a methodology for the tracking of a periodic reference signal. This paper develops a new approach to repetitive control systems design using receding horizon control with frequency decomposition of the reference signal. Moreover, design and implementation issues for this form of repetitive predictive control are investigated from the perspectives of controller complexity and the effects of measurement noise. The analysis is supported by a simulation study on a multi-input multi-output robot arm where the model has been constructed from measured frequency response data, and experimental results from application to an industrial AC motor

Film advance indicator

A film advancement indicator which includes an optical sensor that detects the rotational movement of a disc that rotates only when the film advance is described. When the film does not advance, an indicator light is activated. A counter is included in the electronic circuit to determine the number of film frames advanced

Applications Technology Satellite /ATS-1/ Suprathermal Ion Detector experiment /SID/ data reduction and analysis Final report, 6 Dec. 1966 - 30 Mar. 1970

Data analysis on ATS-1 Suprathermal Ion Detector /SID/ measurements of low energy plasma flow in magnetopause boundar

Visual Dynamics: Probabilistic Future Frame Synthesis via Cross Convolutional Networks

We study the problem of synthesizing a number of likely future frames from a single input image. In contrast to traditional methods, which have tackled this problem in a deterministic or non-parametric way, we propose a novel approach that models future frames in a probabilistic manner. Our probabilistic model makes it possible for us to sample and synthesize many possible future frames from a single input image. Future frame synthesis is challenging, as it involves low- and high-level image and motion understanding. We propose a novel network structure, namely a Cross Convolutional Network to aid in synthesizing future frames; this network structure encodes image and motion information as feature maps and convolutional kernels, respectively. In experiments, our model performs well on synthetic data, such as 2D shapes and animated game sprites, as well as on real-wold videos. We also show that our model can be applied to tasks such as visual analogy-making, and present an analysis of the learned network representations.Comment: The first two authors contributed equally to this wor