Search results for " Computer Science"
showing 10 items of 3983 documents
Run-time scalable NoC for FPGA based virtualized IPs
2017
The integration of virtualized FPGA-based hardware accelerators in a cloud computing is progressing from time to time. As the FPGA has limited resources, the dynamic partial reconfiguration capability of the FPGA is considered to share resources among different virtualized IPs during runtime. On the other hand, the NoC is a promising solution for communication among virtualized FPGA-based IPs. However, not all the virtualized regions of the FPGA will be active all the time. When there is no demand for virtualized IPs, the virtualized regions are loaded with blank bitstreams to save power. However, keeping active the idle components of the NoC connecting with the idle virtualized regions is …
Evaluation of the Colorimetric Performance of Single-Sensor Image Acquisition Systems Employing Colour and Multispectral Filter Array
2015
International audience; Single-sensor colour imaging systems mostly employ a colour filter array (CFA). This enables the acquisition of a colour image by a single sensor at one exposure at the cost of reduced spatial resolution. The idea of CFA fit itself well with multispectral purposes by incorporating more than three types of filters into the array which results in multispectral filter array (MSFA). In comparison with a CFA, an MSFA trades spatial resolution for spectral resolution. A simulation was performed to evaluate the colorimetric performance of such CFA/MSFA imaging systems and investigate the trade-off between spatial resolution and spectral resolution by comparing CFA and MSFA …
SAR Image Classification Combining Structural and Statistical Methods
2011
The main objective of this paper is to develop a new technique of SAR image classification. This technique combines structural parameters, including the Sill, the slope, the fractal dimension and the range, with statistical methods in a supervised image classification. Thanks to the range parameter, we define the suitable size of the image window used in the proposed approach of supervised image classification. This approach is based on a new way of characterising different classes identified on the image. The first step consists in determining relevant area of interest. The second step consists in characterising each area identified, by a matrix. The last step consists in automating the pr…
Spectral alignment of multi-temporal cross-sensor images with automated kernel canonical correlation analysis
2015
In this paper we present an approach to perform relative spectral alignment between optical cross-sensor acquisitions. The proposed method aims at projecting the images from two different and possibly disjoint input spaces into a common latent space, in which standard change detection algorithms can be applied. The system relies on the regularized kernel canonical correlation analysis transformation (kCCA), which can accommodate nonlinear dependencies between pixels by means of kernel functions. To learn the projections, the method employs a subset of samples belonging to the unchanged areas or to uninteresting radiometric differences. Since the availability of ground truth information to p…
« On-the-go » multispectral imaging system to characterize the development of vineyard foliage
2015
International audience; In Precision Viticulture, multispectral imaging systems are currently used in remote sensing for vineyard vigor characterization but few are employed in proximal sensing. This work presents the potential of a proximal multispectral imaging system mounted on a track-laying tractor equipped with a Greenseeker RT-100 to provide an NDVI index. The camera acquired visible and near-infrared images which were calibrated in reflectance. Vegetation indices were computed and compared to Greenseeker data. From two of the resulting datasets, a spatio-temporal study of foliage description through both optical systems is presented. This first study assessed the proximal imagery re…
X!TandemPipeline: a tool to manage sequence redundancy for protein inference and phosphosite identification
2017
X!TandemPipeline is a software designed to perform protein inference and to manage redundancy in the results of phosphosite identification by database search. It provides the minimal list of proteins or phosphosites that are present in a set of samples using grouping algorithms based on the principle of parsimony. Regarding proteins, a two-level classification is performed, where groups gather proteins sharing at least one peptide and subgroups gather proteins that are not distinguishable according to the identified peptides. Regarding phosphosites, an innovative approach based on the concept of phosphoisland is used to gather overlapping phosphopeptides. The graphical interface of X!Tandem…
Simple learning rules to cope with changing environments
2008
10 pages; International audience; We consider an agent that must choose repeatedly among several actions. Each action has a certain probability of giving the agent an energy reward, and costs may be associated with switching between actions. The agent does not know which action has the highest reward probability, and the probabilities change randomly over time. We study two learning rules that have been widely used to model decision-making processes in animals-one deterministic and the other stochastic. In particular, we examine the influence of the rules' 'learning rate' on the agent's energy gain. We compare the performance of each rule with the best performance attainable when the agent …
Coupling agent-based with equation-based models to study spatially explicit megapopulation dynamics
2018
International audience; The incorporation of the spatial heterogeneity of real landscapes into population dynamics remains extremely difficult. We propose combining equation-based modelling (EBM) and agent-based modelling (ABM) to overcome the difficulties classically encountered. ABM facilitates the description of entities that act according to specific rules evolving on various scales. However, a large number of entities may lead to computational difficulties (e.g., for populations of small mammals, such as voles, that can exceed millions of individuals). Here, EBM handles age-structured population growth, and ABM represents the spreading of voles on large scales. Simulations applied to t…
Dynamical model identification of population of oysters for water quality monitoring
2014
International audience; The measurements of valve activity in a population of bivalves under natural environmental conditions (16 oysters in the Bay of Arcachon, France) are used for a physiological model identification. A nonlinear auto-regressive exogenous (NARX) model is designed and tested. The model takes into account the influence of environmental conditions using measurements of the sunlight intensity, the moonlight and tide levels. A possible influence of the internal circadian/circatidal clocks is also analyzed. Through this application, it is demonstrated that the developed dynamical model can be used for estimation of the normal physiological rhythms of permanently immersed oyste…
Null models for animal social network analysis and data collected via focal sampling: Pre‐network or node network permutation?
2020
In social networks analysis, two different approaches have predominated in creating null models for hypothesis testing, namely pre‐network and node network permutation approaches. Although the pre‐network permutation approach appears more advantageous, its use has mainly been restricted to data on associations and sampling methods such as ‘group follows’. The pre‐network permutation approach has recently been adapted to data on interactions and the focal sampling method, but its performance in different scenarios has not been thoroughly explored. Here, we assessed the performance of the pre‐network and node network permutation approach in several simulated scenarios based on proneness to fa…