Progress of analog-hybrid computation

Review of fast analog/hybrid computer systems, integrated operational amplifiers, electronic mode-control switches, digital attenuators, and packaging technique

A quantitative narrative on movement, disease and patch exploitation in nesting agent groups

Abstract Animal relocation data has recently become considerably more ubiquitous, finely structured (collection frequencies measured in minutes) and co-variate rich (physiology of individuals, environmental and landscape information, and accelerometer data). To better understand the impacts of ecological interactions, individual movement and disease on global change ecology, including wildlife management and conservation, it is important to have simulators that will provide demographic, movement, and epidemiology null models against which to compare patterns observed in empirical systems. Such models may then be used to develop quantitative narratives that enhance our intuition and understanding of the relationship between population structure and generative processes: in essence, along with empirical and experimental narratives, quantitative narratives are used to advance ecological epistemology. Here we describe a simulator that accounts for the influence of consumer-resource interactions, existence of social groups anchored around a central location, territoriality, group-switching behavior, and disease dynamics on population size. We use this simulator to develop new and reinforce existing quantitative narratives and point out areas for future study. Author summary The health and viability of species are of considerable concern to all nature lovers. Population models are central to our efforts to assess the numerical and ecological status of species and threats posed by climate change. Models, however, are crude caricatures of complex ecological systems. So how do we construct reliable assessment models able to capture processes essential to predicating the impacts of global change on population viability without getting tied up in their vast complexities? We broach this question and demonstrate how models focusing at the level of the individual (i.e., agent-based models) are tools for developing robust, narratives to augment narratives arising purely from empirical data sources and experimental outcomes. We do this in the context of nesting social groups, foraging for food, while exhibiting territoriality and group-switching behavior; and, we evaluate the impact of disease on the viability of such populations

Generalised MBER-based vector precoding design for multiuser transmission

We propose a generalized vector precoding (VP) design based on the minimum bit error rate (MBER) criterion for multiuser transmission in the downlink of a multiuser system, where the base station (BS) equipped with multiple transmitting antennas communicates with single-receiving-antenna mobile station (MS) receivers each having a modulo device. Given the knowledge of the channel state information and the current information symbol vector to be transmitted, our scheme directly generates the effective symbol vector based on the MBER criterion using the particle swarm optimization (PSO) algorithm. The proposed PSO-aided generalized MBER VP scheme is shown to outperform the powerful minimum mean-square-error (MMSE) VP and improved MMSE-VP benchmarks, particularly for rank-deficient systems, where the number of BS transmitting antennas is lower than the number of MSs supported

Protection of Works of Art From Atmospheric Ozone

Assesses the colorfastness of organic colorants and watercolor pigments tested in atmospheric ozone. A summary of a full report of the Environmental Quality Laboratory, California Institute of Technology, Pasadena

The extrapolation of laboratory and aircraft radar sea return data to spacecraft altitudes

Laboratory measurements show that the spectra of capillary waves grow with wind speed over six orders of magnitude. The scatter in the data can be partially understood and predicted from a combination of turbulence theory, radar theory, and the small sample theory of statistical inference. When these results are applied to a prediction of the sea return values to be obtained by S193 on Skylab, it can be shown that the size of the illuminated patch effectively averages out the horizontal scales of gustiness, so that the measurement will correspond to the synoptic scale wind

Using Hierarchical Data Mining to Characterize Performance of Wireless System Configurations

This paper presents a statistical framework for assessing wireless systems performance using hierarchical data mining techniques. We consider WCDMA (wideband code division multiple access) systems with two-branch STTD (space time transmit diversity) and 1/2 rate convolutional coding (forward error correction codes). Monte Carlo simulation estimates the bit error probability (BEP) of the system across a wide range of signal-to-noise ratios (SNRs). A performance database of simulation runs is collected over a targeted space of system configurations. This database is then mined to obtain regions of the configuration space that exhibit acceptable average performance. The shape of the mined regions illustrates the joint influence of configuration parameters on system performance. The role of data mining in this application is to provide explainable and statistically valid design conclusions. The research issue is to define statistically meaningful aggregation of data in a manner that permits efficient and effective data mining algorithms. We achieve a good compromise between these goals and help establish the applicability of data mining for characterizing wireless systems performance

Engineering Art Galleries

The Art Gallery Problem is one of the most well-known problems in Computational Geometry, with a rich history in the study of algorithms, complexity, and variants. Recently there has been a surge in experimental work on the problem. In this survey, we describe this work, show the chronology of developments, and compare current algorithms, including two unpublished versions, in an exhaustive experiment. Furthermore, we show what core algorithmic ingredients have led to recent successes