International Professional University of Technology in Nagoya Repository
Not a member yet
15131 research outputs found
Sort by
Parallel Light Speed Labeling: an efficient connected component algorithm for labeling and analysis on multi-core processors
No full textInternational audienceIn the last decade, many papers have been published to present sequential connected component labeling (CCL) algorithms. As modern processors are multi-core and tend to many cores, designing a CCL algorithm should address parallelism and multithreading. After a review of sequential CCL algorithms and a study of their variations, this paper presents the parallel version of the Light Speed Labeling for Connected Component Analysis (CCA) and compares it to our parallelized implementations of State-of-the-Art sequential algorithms. We provide some benchmarks that help to figure out the intrinsic differences between these parallel algorithms. We show that thanks to its run-based processing, the LSL is intrinsically more efficient and faster than all pixel-based algorithms. We show also, that all the pixel-based are memory-bound on multi-socket machines and so are inefficient and do not scale, whereas LSL, thanks to its RLE compression can scale on such high-end machines. On a 4×15-core machine, and for 8192×8192 images, LSL outperforms its best competitor by a factor ×10.8 and achieves a throughput of 42.4 gigapixel labeled per second
Sorting methods and convergence rates for Array-RQMC: some empirical comparisons
No full textInternational audienc
Non-linear filtering and optimal investment under partial information for stochastic volatility models
No full textInternational audienceThis paper studies the question of filtering and maximizing terminal wealth from expected utility in a partially information stochastic volatility models. The special features is that the only information available to the investor is the one generated by the asset prices, and the unobservable processes will be modeled by a stochastic differential equations. Using the change of measure techniques, the partial observation context can be transformed into a full information context such that coefficients depend only on past history of observed prices (filter processes). Adapting the stochastic non-linear filtering, we show that under some assumptions on the model coefficients, the estimation of the filters depend on a priorimodels for the trend and the stochastic volatility. Moreover, these filters satisfy a stochastic partial differential equations named "Kushner-Stratonovich equations". Using the martingale duality approach in this partially observed incomplete model, we can characterize the value function and the optimal portfolio. The main result here is that the dual value function associated to the martingale approach can be expressed, via the dynamic programming approach, in terms of the solution to a semilinear partial differential equation which depends also on the filters estimate and the volatility. We illustrate our results with some examples of stochastic volatility models popular in the financial literature
Stabilization of Nonlinear Time-Varying Systems through a New Prediction Based Approach
No full textInternational audience—We propose a prediction based stabilization approach for a general class of nonlinear time-varying systems with pointwise delay in the input. It is based on a recent new prediction strategy, which makes it possible to circumvent the problem of constructing and estimating distributed terms in the expression for the stabilizing control laws. Our result applies in cases where other recent results do not
EEG-based Classification of Epileptic and Non-epileptic Events using Multi-array Decomposition
No full textInternational audienc
Distributed Spectrum Management in TV White Space Networks
No full textInternational audienceIn this paper, we investigate the spectrum management problem in TV White Space (TVWS) Cognitive Radio Networks using a game theoretical approach, accounting for adjacent-channel interference. TV Bands Devices (TVBDs) compete to access available TV channels and choose idle blocks that optimize some objective function. Specifically, the goal of each TVBD is to minimize the price paid to the Database operator and a cost function that depends on the interference between unlicensed devices. We show that the proposed TVWS management game admits a potential function under general conditions. Accordingly, we use a Best Response algorithm to converge in few iterations to the Nash Equilibrium (NE) points. We evaluate the performance of the proposed game, considering both static and dynamic TVWS scenarios and taking into account users' mobility. Our results show that at the NE, the game provides an interesting tradeoff between efficient TV spectrum use and reduction of interference between TVBDs
Evaluating Multi-User Selection for Exploring Graph Topology on Wall-Displays
No full textInternational audienceWall-displays allow multiple users to simultaneously view and analyze large amounts of information, such as the increasingly complex graphs present in domains like biology or social network analysis. We focus on how pairs explore graphs on a touch enabled wall-display using two techniques, both adapted for collaboration: a basic localized selection, and a propagation selection technique that uses the idea of diffusion/transmission from an origin node. We assess in a controlled experiment the impact of selection technique on a shortest path identification task. Pairs consistently divided space even if the task is not spatially divisible, and for the basic selection technique that has a localized visual effect, it led to parallel work that negatively impacted accuracy. The large visual footprint of the propagation technique led to close coordination, improving speed and accuracy for complex graphs only. We then observed the use of propagation on additional graph topology tasks, confirming pair strategies on spatial division and coordination
InfraPhenoGrid: A scientific workflow infrastructure for Plant Phenomics on the Grid
No full textInternational audiencePlant phenotyping consists in the observation of physical and biochemical traits of plant genotypes in response to environmental conditions. Challenges , in particular in context of climate change and food security, are numerous. High-throughput platforms have been introduced to observe the dynamic growth of a large number of plants in different environmental conditions. Instead of considering a few genotypes at a time (as it is the case when phenomic traits are measured manually), such platforms make it possible to use completely new kinds of approaches. However, the data sets produced by such widely instrumented platforms are huge, constantly augmenting and produced by increasingly complex experiments, reaching a point where distributed computation is mandatory to extract knowledge from data. In this paper, we introduce InfraPhenoGrid, the infrastructure we designed and deploy to efficiently manage data sets produced by the PhenoArch plant phenomics platform in the context of the French Phenome Project. Our solution consists in deploying scientific workflows on a Grid using a middle-ware to pilot workflow executions. Our approach is user-friendly in the sense that despite the intrinsic complexity of the infrastructure, running scientific workflows and understanding results obtained (using provenance information) is kept as simple as possible for end-users
Validation of Formal Specifications through Transformation and Animation
No full textInternational audienceA significant impediment to the uptake of formal refinement-based methods among practitioners is the challenge of validating that the formal specifications of these methods capture the desired intents. Animation of specifications is widely recognized as an effective way of addressing such validation. However, animation tools are unable to directly execute (and thus animate) the typical uses of several of the specification constructs often found in ideal formal specifications. To address this problem we have developed transformation heuristics that, starting with an ideal formal specification, guide its conversion into an animatable form. We show several of these heuristics, and address the need to prove that the application of these transformations preserves the relevant behavior of the original specification. Portions of several case studies illustrate this approac
A Pattern Mining Approach to Study Strategy Balance in RTS Games
No full textInternational audienceWhereas purest strategic games such as Go and Chess seem timeless, the lifetime of a video game is short, influenced by popular culture, trends, boredom and technological innovations. Even the important budget and de- velopments allocated by editors cannot guarantee a timeless success. Instead, novelties and corrections are proposed to extend an inevitably bounded lifetime. Novelties can unexpectedly break the balance of a game, as players can discover unbalanced strategies that developers did not take into account. In the new context of electronic sports, an important challenge is to be able to detect game balance issues. In this article, we consider real time strategy games (RTS) and present an efficient pattern mining algorithm as a basic tool for game balance designers that enables one to search for unbalanced strategies in historical data through a Knowledge Discovery in Databases process (KDD). We experiment with our algorithm on StarCraft II historical data, played professionally as an electronic sport