Fast intra mode decision algorithm for H.263 to H.264/AVC transcoding

2007-2008 > Academic research: refereed > Refereed conference paperVersion of RecordPublishe

Role of deposit-feeding sea cucumbers in integrated multitrophic aquaculture: progress, problems, potential and future challenges

There is significant commercial and research interest in the application of sea cucumbers as nutrient recyclers and processors of particulate waste in polyculture or integrated multitrophic aquaculture (IMTA) systems. The following article reviews examples of existing IMTA systems operating with sea cucumbers, and details the role and effect of several sea cucumber species in experimental and pilot IMTA systems worldwide. Historical observations and quantification of impacts of sea cucumber deposit-feeding and locomotion are examined, as is the development and testing of concepts for the application of sea cucumbers in sediment remediation and site recovery. The extension of applied IMTA systems is reported, from basic piloting through to economically viable farming systems operating at commercial scales. The near-global recognition of the ecological and economic value of deposit-feeding sea cucumbers in IMTA applications within existing and developing aquaculture industries is discussed. Predictions and recommendations are offered for optimal development of sea cucumber IMTA globally. Future directions within the industry are indicated, and key areas of ecological, biological and commercial concern are highlighted to be kept in mind and addressed in a precautionary manner as the industry develops

Dynamic concept composition for zero-example event detection

© Copyright 2016, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved. In this paper, we focus on automatically detecting events in unconstrained videos without the use of any visual training exemplars. In principle, zero-shot learning makes it possible to train an event detection model based on the assumption that events (e.g. birthday party) can be described by multiple mid-level semantic concepts (e.g. "blowing candle", "birthday cake"). Towards this goal, we first pre-Train a bundle of concept classifiers using data from other sources. Then we evaluate the semantic correlation of each concept w.r.t. the event of interest and pick up the relevant concept classifiers, which are applied on all test videos to get multiple prediction score vectors. While most existing systems combine the predictions of the concept classifiers with fixed weights, we propose to learn the optimal weights of the concept classifiers for each testing video by exploring a set of online available videos with freeform text descriptions of their content. To validate the effectiveness of the proposed approach, we have conducted extensive experiments on the latest TRECVID MEDTest 2014, MEDTest 2013 and CCV dataset. The experimental results confirm the superiority of the proposed approach

Multi-scale simulation of the nano-metric cutting process

Molecular dynamics (MD) simulation and the finite element (FE) method are two popular numerical techniques for the simulation of machining processes. The two methods have their own strengths and limitations. MD simulation can cover the phenomena occurring at nano-metric scale but is limited by the computational cost and capacity, whilst the FE method is suitable for modelling meso- to macro-scale machining and for simulating macro-parameters, such as the temperature in a cutting zone, the stress/strain distribution and cutting forces, etc. With the successful application of multi-scale simulations in many research fields, the application of simulation to the machining processes is emerging, particularly in relation to machined surface generation and integrity formation, i.e. the machined surface roughness, residual stress, micro-hardness, microstructure and fatigue. Based on the quasi-continuum (QC) method, the multi-scale simulation of nano-metric cutting has been proposed. Cutting simulations are performed on single-crystal aluminium to investigate the chip formation, generation and propagation of the material dislocation during the cutting process. In addition, the effect of the tool rake angle on the cutting force and internal stress under the workpiece surface is investigated: The cutting force and internal stress in the workpiece material decrease with the increase of the rake angle. Finally, to ease multi-scale modelling and its simulation steps and to increase their speed, a computationally efficient MATLAB-based programme has been developed, which facilitates the geometrical modelling of cutting, the simulation conditions, the implementation of simulation and the analysis of results within a unified integrated virtual-simulation environment

Gravitational radiation in quantum gravity

The effective field theory of quantum gravity generically predicts non-locality to be present in the effective action, which results from the low-energy propagation of gravitons and massless matter. Working to second order in gravitational curvature, we reconsider the effects of quantum gravity on the gravitational radiation emitted from a binary system. In particular, we calculate for the first time the leading order quantum gravitational correction to the classical quadrupole radiation formula which appears at second order in Newton’s constant

Dagstuhl-Workshop MBEES:

modellbasierte automobile Steuergeräteentwicklun

A Recurrent Neural Network Survival Model: Predicting Web User Return Time

The size of a website's active user base directly affects its value. Thus, it is important to monitor and influence a user's likelihood to return to a site. Essential to this is predicting when a user will return. Current state of the art approaches to solve this problem come in two flavors: (1) Recurrent Neural Network (RNN) based solutions and (2) survival analysis methods. We observe that both techniques are severely limited when applied to this problem. Survival models can only incorporate aggregate representations of users instead of automatically learning a representation directly from a raw time series of user actions. RNNs can automatically learn features, but can not be directly trained with examples of non-returning users who have no target value for their return time. We develop a novel RNN survival model that removes the limitations of the state of the art methods. We demonstrate that this model can successfully be applied to return time prediction on a large e-commerce dataset with a superior ability to discriminate between returning and non-returning users than either method applied in isolation.Comment: Accepted into ECML PKDD 2018; 8 figures and 1 tabl

DRENCH: A Semi-Distributed Resource Management Framework for NFV based Service Function Chaining

As networks grow in scale and complexity, the use of Network Function Virtualization (NFV) and the ability to dynamically instantiate network function instances (NFls) allow us to scale out the network's capabilities in response to demand. At the same time, an increasing number of computing resources, deployed closer to users, as well as network equipment are now capable of performing general-purpose computation for NFV. However, NFV management in the presence of Service Function Chaining (SFC) for arbitrary topologies is a challenging task. In this work we argue for the necessity of an algorithmic resource managementframework that captures the involved tradeoffs of NFls minimum workload, load balancing, and flow path stretch. We introduce DRENCH as a low complexity NFV and flow steering management framework. In DRENCH an NFV market is considered where a centralised SDN controller acts as market orchestrator of NFV nodes. Through competition, NFV nodes make flow steering and NFl instantiation/consolidation decisions. DRENCH design enables third party NFV nodes participation while it can coexist with other NFV management solutions. DRENCH orchestrator parameterisation strikes the right balance between path stretch and NFl load balancing, resulting in significantly lower Flow Completion Times, up to 1Ox less, in some cases

Searching (the) FIRST radio arcs near ACO clusters

Gravitational lensing (GL) of distant radio sources by galaxy clusters should produce radio arc(let)s. We extracted radio sources from the FIRST survey near Abell cluster cores and found their radio position angles to be uniformly distributed with respect to the cluster centres. This result holds even when we restrict the sample to the richest or most centrally condensed clusters, and to sources with high S/N and large axial ratio. Our failure to detect GL with statistical methods may be due to poor cluster centre positions. We did not find convincing candidates for arcs either. Our result agrees with theoretical estimates predicting that surveys much deeper than FIRST are required to detect the effect. This is in apparent conflict with the detection of such an effect claimed by Bagchi & Kapahi (1995).Comment: 6 pages; 8 figures and 1 style file are included; to appear in Proc. "Observational Cosmology with the New Radio Surveys", eds. M. Bremer, N. Jackson & I. Perez-Fournon, Kluwer Acad. Pres

Abrupt Onset of Second Energy Gap at Superconducting Transition of Underdoped Bi2212

The superconducting gap - an energy scale tied to the superconducting phenomena-opens on the Fermi surface at the superconducting transition temperature (TC) in conventional BCS superconductors. Quite differently, in underdoped high-TC superconducting cuprates, a pseudogap, whose relation to the superconducting gap remains a mystery, develops well above TC. Whether the pseudogap is a distinct phenomenon or the incoherent continuation of the superconducting gap above TC is one of the central questions in high-TC research. While some experimental evidence suggests they are distinct, this issue is still under intense debate. A crucial piece of evidence to firmly establish this two-gap picture is still missing: a direct and unambiguous observation of a single-particle gap tied to the superconducting transition as function of temperature. Here we report the discovery of such an energy gap in underdoped Bi2212 in the momentum space region overlooked in previous measurements. Near the diagonal of Cu-O bond direction (nodal direction), we found a gap which opens at TC and exhibits a canonical (BCS-like) temperature dependence accompanied by the appearance of the so-called Bogoliubov quasiparticles, a classical signature of superconductivity. This is in sharp contrast to the pseudogap near the Cu-O bond direction (antinodal region) measured in earlier experiments. The emerging two-gap phenomenon points to a picture of richer quantum configurations in high temperature superconductors.Comment: 16 pages, 4 figures, authors' version Corrected typos in the abstrac