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Talence, France

Gavoille C.,iversity of Bordeaux | Glacet C.,French Institute for Research in Computer Science and Automation | Hanusse N.,French National Center for Scientific Research | Ilcinkas D.,French National Center for Scientific Research
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

We present a distributed asynchronous algorithm that, for every undirected weighted n-node graph G, constructs name-independent routing tables for G. The size of each table is Õ(√n), whereas the length of any route is stretched by a factor of at most 7 w.r.t. the shortest path. At any step, the memory space of each node is Õ(√n). The algorithm terminates in time O (D), where D is the hop-diameter of G. In synchronous scenarios and with uniform weights, it consumes Õ(m √n + n3/2 min {D, √n}) messages, where m is the number of edges of G. In the realistic case of sparse networks of poly-logarithmic diameter, the communication complexity of our scheme, that is Õ(n3/2), improves by a factor of √n the communication complexity of any shortest-path routing scheme on the same family of networks. This factor is provable thanks to a new lower bound of independent interest. © Springer-Verlag 2013. Source

Bhandari S.,Malaviya National Institute of Technology, Jaipur | Gupta R.,Malaviya National Institute of Technology, Jaipur | Laxmi V.,Malaviya National Institute of Technology, Jaipur | Gaur M.S.,Malaviya National Institute of Technology, Jaipur | And 2 more authors.
ACM International Conference Proceeding Series

Android being the most popular open source mobile operating system, attracts a plethora of app developers. Millions of applications are developed for Android platform with a great extent of behavioral diversities and are available on Play Store as well as on many third party app stores. Due to its open nature, in the past Android Platform has been targeted by many malware writers. The conventional way of signature-based detection methods for detecting malware on a device are no longer promising due to an exponential in-crease in the number of variants of the same application with different signatures. Moreover, they lack in dynamic analysis too. In this paper, we propose DRACO, which employs a two-phase detection technique that blends the synergy of both static and dynamic analysis. It has two modules, client module that is in the form an Android app and gets installed on mobile devices and a server module that runs on a server. DRACO also explains user about the features contributing to the maliciousness of analyzed app and generates scoring for that maliciousness. It does not require any root or super-user privileges. In an evaluation of 18,000 benign applications and 10,000 malware samples, DRACO performs better than several related existing approaches and detects 98.4% of the malware with few false alerts. On ten popular smartphones, the method requires an average of 6 seconds for on device analysis and 90 seconds on server analysis. © 2015 ACM. Source

Karaman S.,iversity of Bordeaux | Benois-Pineau J.,iversity of Bordeaux | Dovgalecs V.,University Of Bordeaux | Megret R.,University Of Bordeaux | And 4 more authors.
Multimedia Tools and Applications

This paper presents a method for indexing activities of daily living in videos acquired from wearable cameras. It addresses the problematic of analyzing the complex multimedia data acquired from wearable devices, which has been recently a growing concern due to the increasing amount of this kind of multimedia data. In the context of dementia diagnosis by doctors, patient activities are recorded in the environment of their home using a lightweight wearable device, to be later visualized by the medical practitioners. The recording mode poses great challenges since the video data consists in a single sequence shot where strong motion and sharp lighting changes often appear. Because of the length of the recordings, tools for an efficient navigation in terms of activities of interest are crucial. Our work introduces a video structuring approach that combines automatic motion based segmentation of the video and activity recognition by a hierarchical two-level Hidden Markov Model. We define a multi-modal description space over visual and audio features, including mid-level features such as motion, location, speech and noise detections. We show their complementarities globally as well as for specific activities. Experiments on real data obtained from the recording of several patients at home show the difficulty of the task and the promising results of the proposed approach. © 2012 Springer Science+Business Media, LLC. Source

Karaman S.,iversity of Bordeaux | Benois-Pineau J.,iversity of Bordeaux | Megret R.,University Of Bordeaux | Bugeau A.,iversity of Bordeaux
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

In this paper, we propose a new multi-layer structural approach for the task of object based image retrieval. In our work we tackle the problem of structural organization of local features. The structural features we propose are nested multi-layered local graphs built upon sets of SURF feature points with Delaunay triangulation. A Bag-of-Visual-Words (BoVW) framework is applied on these graphs, giving birth to a Bag-of-Graph-Words representation. The multi-layer nature of the descriptors consists in scaling from trivial Delaunay graphs - isolated feature points - by increasing the number of nodes layer by layer up to graphs with maximal number of nodes. For each layer of graphs its own visual dictionary is built. The experiments conducted on the SIVAL and Caltech-101 data sets reveal that the graph features at different layers exhibit complementary performances on the same content. The combination of all layers, yields significant improvement of the object recognition performance. © 2012 Springer-Verlag. Source

Jallageas J.,AST Innovations | Cherif M.,iversity of Bordeaux | K'nevez J.-Y.,iversity of Bordeaux | Cahuc O.,iversity of Bordeaux
SAE International Journal of Materials and Manufacturing

To reduce the weight of aero structures, composite materials are combined with metallic parts. These multilayer materials are one-shot drilled during the assembly process. During drilling, interactions appear between the different layers creating new quality issues. To improve machining efficiency, the portable semi-automated drilling units commonly used for such operations need to be upgraded. For this purpose, vibration systems have been recently introduced into drilling units. This article first considers the effect of the reciprocating axial movement on the quality of the machined surface, then focuses on the effect of the oscillation parameters (frequency, magnitude) on the cutting process (cutting forces, thermal load, etc.). Experimental and numerical results are used to find the method that produces the optimal vibration setting. This method is then applied to the case of drilling composite-metallic stack. We conclude that specific vibration parameters need to be set up according to the type of material drilled (composite, metallic). A new vibration system concept has therefore been specifically developed to adapt the oscillation magnitudes to each kind of material. The entire mechanism of the system is shown and analytically modeled. In conclusion, the article describes briefly the auto-adaptive drilling technique for an understanding of the benefit of the new vibration system when associated with this technique. © 2013 SAE International. Source

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