Search results for "Computer science"

Including the Past: Performance Modeling Using a Preload Concept by Means of the Fitness-Fatigue Model

2019

Abstract In mathematical modeling by means of performance models, the Fitness-Fatigue Model (FF-Model) is a common approach in sport and exercise science to study the training performance relationship. The FF-Model uses an initial basic level of performance and two antagonistic terms (for fitness and fatigue). By model calibration, parameters are adapted to the subject’s individual physical response to training load. Although the simulation of the recorded training data in most cases shows useful results when the model is calibrated and all parameters are adjusted, this method has two major difficulties. First, a fitted value as basic performance will usually be too high. Second, without mo…

Graph Rewriting Based Search for Molecular Structures: Definitions, Algorithms, Hardness

2018

We define a graph rewriting system that is easily understandable by humans, but rich enough to allow very general queries to molecule databases. It is based on the substitution of a single node in a node- and edge-labeled graph by an arbitrary graph, explicitly assigning new endpoints to the edges incident to the replaced node. For these graph rewriting systems, we are interested in the subgraph-matching problem. We show that the problem is NP-complete, even on graphs that are stars. As a positive result, we give an algorithm which is polynomial if both rules and query graph have bounded degree and bounded cut size. We demonstrate that molecular graphs of practically relevant molecules in d…

A time-varying observer for linear systems with asynchronous discrete-time measurements

2017

International audience; In this paper we propose a time-varying observer for a linear continuous-time plant with asynchronous discrete-time measurements. The proposed observer is contextualized in the hybrid systems framework providing an elegant setting for the proposed solution. In particular some theoretical tools are provided, in terms of LMIs, certifying asymptotic stability of a certain compact set where the estimation error is zero. Moreover the case of asynchronous measurements is considered, i.e. when the measurements are not provided in well defined time instants, but they occur at an arbitrary time in a certain time interval. A design procedure based on the numerical solution of …

Intelligence artificielle : quel avenir en anatomie pathologique ?

2019

Resume Les techniques d’intelligence artificielle et en particulier les reseaux de neurones profonds (Deep Learning) sont en pleine emergence dans le domaine biomedical. Les reseaux de neurones s’inspirent du modele biologique, ils sont interconnectes entre eux et suivent des modeles mathematiques. Lors de l’utilisation des reseaux de neurones artificiels, deux phases sont necessaires : une phase d’apprentissage et une phase d’exploitation. Les deux principales applications sont la classification et la regression. Des outils informatiques comme les processeurs graphiques accelerateurs de calcul ou des bibliotheques de developpement specifiques ont donne un nouveau souffle a ces techniques. …

Deduplication Potential of HPC Applications’ Checkpoints

2016

HPC systems contain an increasing number of components, decreasing the mean time between failures. Checkpoint mechanisms help to overcome such failures for long-running applications. A viable solution to remove the resulting pressure from the I/O backends is to deduplicate the checkpoints. However, there is little knowledge about the potential to save I/Os for HPC applications by using deduplication within the checkpointing process. In this paper, we perform a broad study about the deduplication behavior of HPC application checkpointing and its impact on system design.

Analysis of Activity States of Local Neuronal Microcircuits in Mouse Brain

2018

Time series of neuronal activity corresponding to different activity states in mouse brain are analyzed in the time domain and the time-frequency domain. The signals are associated with either a slow wave brain state or a persistent brain state. For both states, characteristic spectral features are identified and a simple detector is proposed that is able to identify the brain state with low latency and high accuracy. In practice, being able to monitor the brain state online and in real time is crucial for improved in vivoexperiments and, ultimately, for a causal understanding of brain dynamics.

A Fast Multiresolution Approach Useful for Retinal Image Segmentation

2018

Retinal diseases such as retinopathy of prematurity (ROP), diabetic and hypertensive retinopathy present several deformities of fundus oculi which can be analyzed both during screening and monitoring such as the increase of tortuosity, lesions of tissues, exudates and hemorrhages. In particular, one of the first morphological changes of vessel structures is the increase of tortuosity. The aim of this work is the enhancement and the detection of the principal characteristics in retinal image by exploiting a non-supervised and automated methodology. With respect to the well-known image analysis through Gabor or Gaussian filters, our approach uses a filter bank that resembles the “à trous” wav…

Combining GPU and FPGA technology for efficient exhaustive interaction analysis in GWAS

2016

Interaction between genes has become a major topic in quantitative genetics. It is believed that these interactions play a significant role in genetic variations causing complex diseases. Due to the number of tests required for an exhaustive search in genome-wide association studies (GWAS), a large amount of computational power is required. In this paper, we present a hybrid architecture consisting of tightly interconnected CPUs, GPUs and FPGAs and a fine-tuned software suite to outperform other implementations in pairwise interaction analysis while consuming less than 300Watts and fitting into a standard desktop computer case.

WITHDRAWN: Nouvelles stratégies innovantes en immunothérapie

2018

SPECTR

2018

Modern high throughput sequencing platforms can produce large amounts of short read DNA data at low cost. Error correction is an important but time-consuming initial step when processing this data in order to improve the quality of downstream analyses. In this paper, we present a Scalable Parallel Error CorrecToR designed to improve the throughput of DNA error correction for Illumina reads on various parallel platforms. Our design is based on a k-spectrum approach where a Bloom filter is frequently probed as a key operation and is optimized towards AVX-512-based multi-core CPUs, Xeon Phi many-cores (both KNC and KNL), and heterogeneous compute clusters. A number of architecture-specific opt…