702 research outputs found
Multi-resolution texture classification based on local image orientation
The aim of this paper is to evaluate quantitatively the discriminative power of the image orientation in the texture classification process. In this regard, we have evaluated the performance of two texture classification schemes where the image orientation is extracted using the partial derivatives of the Gaussian function. Since the texture descriptors are dependent on the observation scale, in this study the main emphasis is placed on the implementation of multi-resolution texture analysis schemes. The experimental results were obtained when the analysed texture descriptors were applied to standard texture databases
Decision Problems for Nash Equilibria in Stochastic Games
We analyse the computational complexity of finding Nash equilibria in
stochastic multiplayer games with -regular objectives. While the
existence of an equilibrium whose payoff falls into a certain interval may be
undecidable, we single out several decidable restrictions of the problem.
First, restricting the search space to stationary, or pure stationary,
equilibria results in problems that are typically contained in PSPACE and NP,
respectively. Second, we show that the existence of an equilibrium with a
binary payoff (i.e. an equilibrium where each player either wins or loses with
probability 1) is decidable. We also establish that the existence of a Nash
equilibrium with a certain binary payoff entails the existence of an
equilibrium with the same payoff in pure, finite-state strategies.Comment: 22 pages, revised versio
A distributed collaborative platform for personal health profiles in patient-driven health social network
Health social networks (HSNs) have become an integral part of healthcare to augment the ability of people to communicate, collaborate, and share information in the healthcare domain despite obstacles of geography and time. Doctors disseminate relevant medical updates in these platforms and patients take into account opinions of strangers when making medical decisions. This paper introduces our efforts to develop a core platform called Distributed Platform for Health Profiles (DPHP) that enables individuals or groups to control their personal health profiles. DPHP stores user's personal health profiles in a non-proprietary manner which will enable healthcare providers and pharmaceutical companies to reuse these profiles in parallel in order to maximize the effort where users benefit from each usage for their personal health profiles. DPHP also facilitates the selection of appropriate data aggregators and assessing their offered datasets in an autonomous way. Experimental results were described to demonstrate the proposed search model in DPHP. Multiple advantages might arise when healthcare providers utilize DPHP to collect data for various data analysis techniques in order to improve the clinical diagnosis and the efficiency measurement for some medications in treating certain diseases
Labour supply and skills demands in fashion retailing
If, as Adam Smith once famously suggested, Britain was a nation of shopkeepers then it is now a nation of shopworkers. Retail is now a significant part of the UK economy, accounting for ÂŁ256 billion in sales and one-third of all consumer spending (Skillsmart, 2007). It is the largest private sector employer in the UK, employing 3m workers, or 1 in 10 of the working population. For future job creation in the UK economy retail is also similarly prominent and the sector is expected to create a further 250,000 jobs to 2014 (Skillsmart, 2007). The centrality of retail to economic success and job creation is apparent in other advanced economies. For example, within the US, retail sales is the occupation with the largest projected job growth in the period 2004-2014 (Gatta et al., 2009) and in Australia retail accounts for 1 in 6 workers (Buchanan et al., 2003). Within the UK these workers are employed in approximately 290,000 businesses, encompassing large and small organizations and also a number of sub-sectors. This variance suggests that retail should not be regarded as homogenous in its labour demands. Hart et al. (2007) note how skill requirements and the types of workers employed may differ across the sector. This chapter further opens up this point, providing an analysis of the labour supply and skills demands for the sub-sectors of clothing, footwear and leather goods, which are described by Skillsmart (2007: 48) as being 'significant categories in UK retailing'
Le projet DYLAN ou les enjeux politiques, cognitifs et stratégiques du plurilinguisme
Composed of 19 universities from 12 countries, the Dylan Project is an integrated project (IP) of the 6th Framework Programme of the European Union, under Priority 7 « Citizenship and governance in a knowledge-based society ».The project addresses the core issue underlying topic 3.3.1: establish whether and how a European knowledge based society designed to ensure economic competitiveness and social cohesion can be created within a European Union that is linguistically more diverse than ever. The overarching objectives are to show that, in this respect, the linguistic diversity prevalent in Europe is potentially an asset rather than an obstacle and to identify the conditions under which individual and societal multilingualism can be turned to advantage.It will show in what ways the usage of multilingual repertoires can promote the creation and the transfer of knowledge (cognitive asset) and have an impact on communication control, problem solving and decision making (strategic asset), in the diversity of economic, political and educational contexts
Sampling-based Algorithms for Optimal Motion Planning
During the last decade, sampling-based path planning algorithms, such as
Probabilistic RoadMaps (PRM) and Rapidly-exploring Random Trees (RRT), have
been shown to work well in practice and possess theoretical guarantees such as
probabilistic completeness. However, little effort has been devoted to the
formal analysis of the quality of the solution returned by such algorithms,
e.g., as a function of the number of samples. The purpose of this paper is to
fill this gap, by rigorously analyzing the asymptotic behavior of the cost of
the solution returned by stochastic sampling-based algorithms as the number of
samples increases. A number of negative results are provided, characterizing
existing algorithms, e.g., showing that, under mild technical conditions, the
cost of the solution returned by broadly used sampling-based algorithms
converges almost surely to a non-optimal value. The main contribution of the
paper is the introduction of new algorithms, namely, PRM* and RRT*, which are
provably asymptotically optimal, i.e., such that the cost of the returned
solution converges almost surely to the optimum. Moreover, it is shown that the
computational complexity of the new algorithms is within a constant factor of
that of their probabilistically complete (but not asymptotically optimal)
counterparts. The analysis in this paper hinges on novel connections between
stochastic sampling-based path planning algorithms and the theory of random
geometric graphs.Comment: 76 pages, 26 figures, to appear in International Journal of Robotics
Researc
Parental transfer of the antimicrobial protein LBP/BPI protects Biomphalaria glabrata eggs against oomycete infections
Copyright: © 2013 Baron et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: This work was funded by ANR (ANR-07-BLAN-0214 and ANR-12-EMMA-00O7-01), CNRS and INRA. PvW was financially supported by the BBSRC. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Peer reviewedPublisher PD
Recommended from our members
Automated Segmentation of HeLa Nuclear Envelope from Electron Microscopy Images
This paper describes an image-processing pipeline for the automatic segmentation of the nuclear envelope of HeLcells observed through Electron Microscopy. The pipeline was applied to a 3D stack of 300 images. The intermediate results of neighbouring slices are further combined to improve the final results. Comparison with a handsegmented ground truth reported Jaccard similarity values between 94-98% on the central slices with a decrease towards the edges of the cell where the structure was considerably more complex. The processing is unsupervised and each 2D slice is processed in about 5-10 seconds running on a MacBook Pro. No systematic attempt to make the code faster was made. These encouraging results could be further used to provide data for more complex segmentation techniques like Deep Learning, which require a considerable amount of data to train architectures like Convolutional Neural Networks. The code is freely available from https://github.com/reyesaldasoro/HeLa-Cell-Segmentatio
- âŠ