Search results for " Method."
showing 10 items of 10241 documents
Fruit body based inventories in wood-inhabiting fungi: Should we replicate in space or time?
2016
We assessed the effect of survey design on the results when conducting fruit body surveys of wood-inhabiting fungi. Our results demonstrate that the optimal design depends on the ecological question to be addressed, as well as the group of fungal species under research. If the aim is to record the total species richness in a dead wood unit or to estimate the population size of a species, repeating the survey over time is generally necessary. However, if the aim is to estimate the total species richness in the forest or to assess how environmental covariates influence species richness or community composition, it is generally more efficient to increase the number of dead wood units than to r…
Ecosystem carbon response of an Arctic peatland to simulated permafrost thaw
2019
Permafrost peatlands are biogeochemical hot spots in the Arctic as they store vast amounts of carbon. Permafrost thaw could release part of these long-term immobile carbon stocks as the greenhouse gases (GHGs) carbon dioxide (CO 2 ) and methane (CH 4 ) to the atmosphere, but how much, at which time-span and as which gaseous carbon species is still highly uncertain. Here we assess the effect of permafrost thaw on GHG dynamics under different moisture and vegetation scenarios in a permafrost peatland. A novel experimental approach using intact plant–soil systems (mesocosms) allowed us to simulate permafrost thaw under near-natural conditions. We monitored GHG flux dynamics via high-resolution…
la prospection systématique d’un fond de rivière : l’exemple du Doubs
2020
La présentation des méthodes mises en œuvre et des résultats obtenus à l’occasion d’une opération de prospection subaquatique systématique menée sur la rivière Doubs, en amont de Verdun-sur-le-Doubs (Saône-et-Loire), illustre en grandeur réelle l’intérêt de la démarche adoptée, fondée sur des principes simples, dans la perspective d’un inventaire systématique du patrimoine fluvial immergé. La diversité des vestiges découverts et leur répartition sur la longue durée en soulignent la pertinence mais également, s’il en était encore besoin, la réalité du formidable potentiel archéologique que recèlent les cours d’eau. The presentation of the methods used and results obtained during a systematic…
Wine Fermentation
2019
Currently wineries are facing new challenges due to actual market demands for creation of products exhibiting more individual flavors[...]
Two-Dimensional Numerical Modelling of a Moored Floating Body under Sloping Seabed Conditions
2020
A coupled floating body-mooring line model is developed by combining a boundary element model for a two-dimensional floating body and a catenary mooring line model. The boundary element model is formulated in the time domain by a continuous Rankine source, and a reflection potential is introduced to account for the wave reflection due to sloping seabed. This newly developed model is validated by comparisons against available data. Then, dynamic response analyses are performed for the moored body in various seabed conditions. Compared with a flat seabed, a sloping seabed causes unsymmetrical mooring line configuration and generates noticeable effects in the motion responses of the floating b…
Massively Parallel ANS Decoding on GPUs
2019
In recent years, graphics processors have enabled significant advances in the fields of big data and streamed deep learning. In order to keep control of rapidly growing amounts of data and to achieve sufficient throughput rates, compression features are a key part of many applications including popular deep learning pipelines. However, as most of the respective APIs rely on CPU-based preprocessing for decoding, data decompression frequently becomes a bottleneck in accelerated compute systems. This establishes the need for efficient GPU-based solutions for decompression. Asymmetric numeral systems (ANS) represent a modern approach to entropy coding, combining superior compression results wit…
Nvidia CUDA parallel processing of large FDTD meshes in a desktop computer
2020
The Finite Difference in Time Domain numerical (FDTD) method is a well know and mature technique in computational electrodynamics. Usually FDTD is used in the analysis of electromagnetic structures, and antennas. However still there is a high computational burden, which is a limitation for use in combination with optimization algorithms. The parallelization of FDTD to calculate in GPU is possible using Matlab and CUDA tools. For instance, the simulation of a planar array, with a three dimensional FDTD mesh 790x276x588, for 6200 time steps, takes one day -elapsed time- using the CPU of an Intel Core i3 at 2.4GHz in a personal computer, 8Gb RAM. This time is reduced 120 times when the calcula…
Combining congested-flow isolation and injection throttling in HPC interconnection networks
2011
Existing congestion control mechanisms in interconnects can be divided into two general approaches. One is to throttle traffic injection at the sources that contribute to congestion, and the other is to isolate the congested traffic in specially designated resources. These two approaches have different, but non-overlapping weaknesses. In this paper we present in detail a method that combines injection throttling and congested-flow isolation. Through simulation studies we first demonstrate the respective flaws of the injection throttling and of flow isolation. Thereafter we show that our combined method extracts the best of both approaches in the sense that it gives fast reaction to congesti…
FeatherCNN: Fast Inference Computation with TensorGEMM on ARM Architectures
2020
Deep Learning is ubiquitous in a wide field of applications ranging from research to industry. In comparison to time-consuming iterative training of convolutional neural networks (CNNs), inference is a relatively lightweight operation making it amenable to execution on mobile devices. Nevertheless, lower latency and higher computation efficiency are crucial to allow for complex models and prolonged battery life. Addressing the aforementioned challenges, we propose FeatherCNN – a fast inference library for ARM CPUs – targeting the performance ceiling of mobile devices. FeatherCNN employs three key techniques: 1) A highly efficient TensorGEMM (generalized matrix multiplication) routine is app…
Hpdm : A Hybrid Pseudonym Distribution Method for Vehicular Ad-Hoc Networks
2016
Abstract Protecting the location privacy of drivers is still one of the main challenges in Vehicular Ad-hoc Networks (VANETs). The changing of pseudonym is commonly accepted as a solution to this problem. The pseudonyms represent fake vehicle identifiers. Roadside Units (RSUs) play a central role in the existing pseudonyms distribution solutions. Indeed, the VANET area should totally be covered by RSUs in order to satisfy the demand of vehicles in terms of pseudonyms. However, the total coverage is costly and hard to be achieved, especially in the first phase of VANETs deployment. In addition, RSUs could be overloaded due to the large number of pseudonyms requests that could be received fro…