1,295 research outputs found
Deep Over-sampling Framework for Classifying Imbalanced Data
Class imbalance is a challenging issue in practical classification problems
for deep learning models as well as traditional models. Traditionally
successful countermeasures such as synthetic over-sampling have had limited
success with complex, structured data handled by deep learning models. In this
paper, we propose Deep Over-sampling (DOS), a framework for extending the
synthetic over-sampling method to exploit the deep feature space acquired by a
convolutional neural network (CNN). Its key feature is an explicit, supervised
representation learning, for which the training data presents each raw input
sample with a synthetic embedding target in the deep feature space, which is
sampled from the linear subspace of in-class neighbors. We implement an
iterative process of training the CNN and updating the targets, which induces
smaller in-class variance among the embeddings, to increase the discriminative
power of the deep representation. We present an empirical study using public
benchmarks, which shows that the DOS framework not only counteracts class
imbalance better than the existing method, but also improves the performance of
the CNN in the standard, balanced settings
ThumbNet: One Thumbnail Image Contains All You Need for Recognition
Although deep convolutional neural networks (CNNs) have achieved great
success in computer vision tasks, its real-world application is still impeded
by its voracious demand of computational resources. Current works mostly seek
to compress the network by reducing its parameters or parameter-incurred
computation, neglecting the influence of the input image on the system
complexity. Based on the fact that input images of a CNN contain substantial
redundancy, in this paper, we propose a unified framework, dubbed as ThumbNet,
to simultaneously accelerate and compress CNN models by enabling them to infer
on one thumbnail image. We provide three effective strategies to train
ThumbNet. In doing so, ThumbNet learns an inference network that performs
equally well on small images as the original-input network on large images.
With ThumbNet, not only do we obtain the thumbnail-input inference network that
can drastically reduce computation and memory requirements, but also we obtain
an image downscaler that can generate thumbnail images for generic
classification tasks. Extensive experiments show the effectiveness of ThumbNet,
and demonstrate that the thumbnail-input inference network learned by ThumbNet
can adequately retain the accuracy of the original-input network even when the
input images are downscaled 16 times
Interference coloration as an anti-predator defence
Interference coloration, in which the perceived colour varies predictably with the angle of illumination or observation, is extremely widespread across animal groups. However, despite considerable advances in our understanding of the mechanistic basis of interference coloration in animals, we still have a poor understanding of its function. Here, I show, using avian predators hunting dynamic virtual prey, that the presence of interference coloration can significantly reduce a predator's attack success. Predators required more pecks to successfully catch interference-coloured prey compared with otherwise identical prey items that lacked interference coloration, and attacks against prey with interference colours were less accurate, suggesting that changes in colour or brightness caused by prey movement hindered a predator's ability to pinpoint their exact location. The pronounced antipredator benefits of interference coloration may explain why it has evolved independently so many times. © 2015 The Author(s) Published by the Royal Society. All rights reserved
Sex-biased parental care and sexual size dimorphism in a provisioning arthropod
The diverse selection pressures driving the evolution of sexual size dimorphism (SSD) have long been debated. While the balance between fecundity selection and sexual selection has received much attention, explanations based on sex-specific ecology have proven harder to test. In ectotherms, females are typically larger than males, and this is frequently thought to be because size constrains female fecundity more than it constrains male mating success. However, SSD could additionally reflect maternal care strategies. Under this hypothesis, females are relatively larger where reproduction requires greater maximum maternal effort – for example where mothers transport heavy provisions to nests.
To test this hypothesis we focussed on digger wasps (Hymenoptera: Ammophilini), a relatively homogeneous group in which only females provision offspring. In some species, a single large prey item, up to 10 times the mother’s weight, must be carried to each burrow on foot; other species provide many small prey, each flown individually to the nest.
We found more pronounced female-biased SSD in species where females carry single, heavy prey. More generally, SSD was negatively correlated with numbers of prey provided per offspring. Females provisioning multiple small items had longer wings and thoraxes, probably because smaller prey are carried in flight.
Despite much theorising, few empirical studies have tested how sex-biased parental care can affect SSD. Our study reveals that such costs can be associated with the evolution of dimorphism, and this should be investigated in other clades where parental care costs differ between sexes and species
A Late Maoist Industrial Revolution? Economic Growth in Jiangsu Province, 1966-1978
According to the conventional wisdom, the promise of the Chinese revolution of 1949 went unfulfilled in the Maoist era. Instead of taking-off, the economy grew slowly and widespread rural poverty persisted. The economic turning point was instead the famous political climacteric of 1976-78. But this metric of aggregates is the wrong criterion by which to judge China’s economic record because industrial revolutions have regional beginnings. They invariably take place against a backcloth of slow aggregate growth and stagnant material living standards. Accordingly, we should dwell neither on China’s slow overall growth nor its widespread poverty before 1978, but look instead for evidence of an emerging regional growth pole. This article argues that Jiangsu was such a growth pole in the late Maoist era, and that its record bears comparison with that of Lancashire and Yorkshire during the early years of Britain's industrial revolution. This holds out the intriguing possibility that a Chinese economic take-off, diffusing out of the Yangzi delta, would have occurred even without post-1978 policy changes
Evolutionary connectionism: algorithmic principles underlying the evolution of biological organisation in evo-devo, evo-eco and evolutionary transitions
The mechanisms of variation, selection and inheritance, on which evolution by natural selection depends, are not fixed over evolutionary time. Current evolutionary biology is increasingly focussed on understanding how the evolution of developmental organisations modifies the distribution of phenotypic variation, the evolution of ecological relationships modifies the selective environment, and the evolution of reproductive relationships modifies the heritability of the evolutionary unit. The major transitions in evolution, in particular, involve radical changes in developmental, ecological and reproductive organisations that instantiate variation, selection and inheritance at a higher level of biological organisation. However, current evolutionary theory is poorly equipped to describe how these organisations change over evolutionary time and especially how that results in adaptive complexes at successive scales of organisation (the key problem is that evolution is self-referential, i.e. the products of evolution change the parameters of the evolutionary process). Here we first reinterpret the central open questions in these domains from a perspective that emphasises the common underlying themes. We then synthesise the findings from a developing body of work that is building a new theoretical approach to these questions by converting well-understood theory and results from models of cognitive learning. Specifically, connectionist models of memory and learning demonstrate how simple incremental mechanisms, adjusting the relationships between individually-simple components, can produce organisations that exhibit complex system-level behaviours and improve the adaptive capabilities of the system. We use the term “evolutionary connectionism” to recognise that, by functionally equivalent processes, natural selection acting on the relationships within and between evolutionary entities can result in organisations that produce complex system-level behaviours in evolutionary systems and modify the adaptive capabilities of natural selection over time. We review the evidence supporting the functional equivalences between the domains of learning and of evolution, and discuss the potential for this to resolve conceptual problems in our understanding of the evolution of developmental, ecological and reproductive organisations and, in particular, the major evolutionary transitions
An Updated Search of Steady TeV Ray Point Sources in Northern Hemisphere Using the Tibet Air Shower Array
Using the data taken from Tibet II High Density (HD) Array (1997
February-1999 September) and Tibet-III array (1999 November-2005 November), our
previous northern sky survey for TeV ray point sources has now been
updated by a factor of 2.8 improved statistics. From to
in declination (Dec) range, no new TeV ray point
sources with sufficiently high significance were identified while the
well-known Crab Nebula and Mrk421 remain to be the brightest TeV ray
sources within the field of view of the Tibet air shower array. Based on the
currently available data and at the 90% confidence level (C.L.), the flux upper
limits for different power law index assumption are re-derived, which are
approximately improved by 1.7 times as compared with our previous reported
limits.Comment: This paper has been accepted by hepn
3D reactive inkjet printing of polydimethylsiloxane
Material jetting is a process whereby liquid material can be deposited onto a substrate to solidify. Through a process of progressive additional layers, this deposition can then be used to produce 3D structures. However, the current material jetting catalogue is limited owing to the constraints on the viscosity of inks that can be deposited. Most inks currently being used are either solvent or photocuring based, with the latter becoming increasingly popular due to increased throughput. Full Reactive Inkjet Printing (FRIJP) is an alternative processing method currently being investigated as a route to widen the material catalogue. FRIJP is the combination, on the substrate, of two reactive components which then react together in contact on the substrate. In this work a two-part polydimethylsiloxane (PDMS) ink has been developed, printed individually, and cured. The successful printing of PDMS has been used to fabricate complex 3D geometry for the first time using FRIJP. Through the use of a prepared substrate feature resolutions up to 48 ± 2 μm (X, Y) were possible. Curing analysis has been conducted. It was found that not only does the reaction occur to a similar degree to conventional processes, but that there is no variation in the cured sample when printed at elevated substrate temperatures
Estimating the age of Calliphora vicina eggs (Diptera: Calliphoridae): determination of embryonic morphological landmarks and preservation of egg samples
ORCID No. 0000-0002-8917-9646© The Author(s) 2016. Open Access. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The attached file is the published version of the article
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