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International audience; Reconfigurable Intelligent Meta-surfaces (RIMs) are particular devices able to control and manipulate radio frequency wireless signals. This promising technology allows to improve the reliability of wireless networks, thanks to the capacity of reflecting the desired signals through appropriate phase shifts. The joint use of RIMs and Computer Vision (CV) technology is the main objective of this paper. This synergistic approach is used to correctly identify the specific configuration of a radiation pattern, to be used as input for computing optimal coding sequences of the RIM. Indeed, by the means of a CV algorithm it is possible to infer a connectivity graph related to a real scenario, where people is moving. The information about network nodes such as their distance, the relative position, etc. is used for feeding an intelligent logic, able to compute the optimal configuration for redirecting the signals towards a given receiver target node. Numerical results show the huge potentiality of this combined approach in terms of interference reduction. It has been observed that for high traffic load, it is possible to reduce the average interference in the network of 40%. Furthermore, an analysis including the positioning estimation error of the CV algorithm has been addressed, in order to consider how it affects the interference reduction. Results show that, even though there is an increasing effect of interference, when the error is accounted, the interference reduction impact is still important.

We investigate the largest number of nonzero weights of quasi-cyclic codes. In particular, we focus on the function $\Gamma _{Q}(n,\ell,k,q)$ , that is defined to be the largest number of nonzero weights a quasi-cyclic code of index $\gcd (\ell,n)$ , length $n$ and dimension $k$ over $\mathbb F_{q}$ can have, and connect it to similar functions related to linear and cyclic codes. We provide several upper and lower bounds on this function, using different techniques and studying its asymptotic behavior. Moreover, we determine the smallest index for which a $q$ -ary Reed-Muller code is quasi-cyclic, a result of independent interest.

Upper and lower bounds on the largest number of weights in a cyclic code of given length, dimension and alphabet are given. An application to irreducible cyclic codes is considered. Sharper upper bounds are given for the special cyclic codes (called here strongly cyclic), {whose nonzero codewords have period equal to the length of the code}. Asymptotics are derived on the function $\Gamma(k,q),$ {that is defined as} the largest number of nonzero weights a cyclic code of dimension $k$ over $\F_q$ can have, and an algorithm to compute it is sketched. The nonzero weights in some infinite families of Reed-Muller codes, either binary or $q$-ary, as well as in the $q$-ary Hamming code are determined, two difficult results of independent interest., Comment: submitted on 21 June, 2018

International audience; Huge interest in controlling and manipulating electromagnetic waves is recently and strongly evolving, mainly due to the growing demand of reliable technologies in several application fields, such as communications, healthcare, military and safety. Despite the plethora of technologies existing nowadays, limitations are still present, such as limited speed, low response control, narrow band-width, and large dimensions of electronic devices. In this scenario, new engineered materials with unprecedented electromagnetic properties (i.e., MetaSurfaces) can represent a very suitable technology solution. In this paper, a MetaSurface structure is modelled, designed, manufactured and experimentally tested, to be used in several applications. Specifically, results are presented for (i) advanced medical diagnostics, (ii) enhance communication signals along curvilinear paths (i.e., bend optical fibers) and (iii) cloaking applications. Experimental results reveal that the MetaSurface can fully manipulate and process electromagnetic waves at will. The proposed structure appears to be highly versatile and scalable, with great potential to be used for many other practical applications.

Development and performance evaluation of efficient methods for coding, transmission, and quality assessment of 3D visual content require rich datasets of a suitable test material. The use of these databases allows a fair comparison of systems under test. Moreover, publicly available and widely used datasets are crucial for experimentation leading to reproducible research. This chapter presents an overview of 3D visual content datasets relevant to research in the field of coding, transmission, and quality assessment. Description of regular stereoscopic or multiview image and video datasets is presented. Databases created using emerging technologies, including light-field imaging, are also addressed. Moreover, there are databases of multimedia content annotated with ratings from the subjective experiment, which are a necessary resource for understanding the complex problem of quality of experience while consuming the 3D visual content.

International audience; Recently, a huge interest has been raised in controlling and manipulating electromagnetic waves by means of MetaSurfaces. This type of material makes possible the control of phase and amplitude of electromagnetic waves paving the way of different applications, like cloaking and communications in THz band. In this paper, we propose a novel approach for designing metasurface-based structures that are independent from the geometry and the frequency. As a proof of concept, we realize a 3D curvilinear metasurface and we show this approach can be effectively applied in different applications. In particular, for the THz-based system, we consider a transmitting antenna emitting a signal that impinges on the metasurface. Our analysis focuses on the evaluation of the attenuation of the incident signal on the metasurface in respect of characteristic design parameters, the length of the medium and the frequency.

International audience; Internet of Robotic Things (IoRT) is a new concept introduced for the first time by ABI Research. Unlike the Internet of Things (IoT), IoRT provides an active sensorization and is considered as the new evolution of IoT. In this context, we propose a Neuro-Dominating Set algorithm (NDS) to efficiently deploy a team of mobile wireless robots in an IoRT scenario, in order to reach a desired inter-robot distance, while maintaining global connectivity in the whole network. We use the term Neuro-Dominating Set to describe our approach, since it is inspired by both neural network and dominating set principles. With NDS algorithm, a robot adopts different behaviors according whether it is a dominating or a dominated robot. Our main goal is to show and demonstrate the beneficial effect of using different behaviors in the IoRT concept. The obtained results show that the proposed method outperforms an existing related technique (i.e., the Virtual Angular Force approach) and the neural network based approach presented in our previous work. As an objective, we aim to decrease the overall traveled distance and keep a low energy consumption level, while maintaining network connectivity and an acceptable convergence time.

International audience; The Internet-of-Vehicles (IoV) allows vehicles to share information for common services, such as traffic status or safety alerts, not only among themselves but also with neighboring devices and users. Vehicular Social Networks (VSNs) appear when IoVs is combined with social features like chat, sharing achievements, wish-listings, etc. In this work, we demonstrate that VSNs require specific data dissemination techniques. To this aim, we consider the Barabási model and we study the impact of its use for data dissemination in VSNs. Moreover, the use of a probabilistic data dissemination protocol based on social features [1] proves that the time-evolving dynamics of the vehicular social network graph presents a small-world structure, where nodes tend to connect through clusters whose average distance is low on average. This result highlights how VSNs are a specific class of vehicular ad hoc networks with peculiar features that distinguish them from classical online social networks.

International audience; Upper and lower bounds on the largest number of weights in a cyclic code of given length, dimension and alphabet are given. An application to irreducible cyclic codes is considered. Sharper upper bounds are given for the special cyclic codes (called here strongly cyclic), whose nonzero codewords have period equal to the length of the code. Asymptotics are derived on the function Γ(k, q), that is defined as the largest number of nonzero weights a cyclic code of dimension k over F q can have, and an algorithm to compute it is sketched. The nonzero weights in some infinite families of Reed-Muller codes, either binary or q-ary, as well as in the q-ary Hamming code are determined, two difficult results of independent interest.

International audience; Quantum communications are gaining more and more interest in the research community thanks to the recent advancements in nanotechnology. Indeed, quantum phenomena represent a natural direction for developing nanotechnology. The exploitation of quantum nature of information offers new potential solutions in the field of computing and networking, and extends the communication potentiality to levels that cannot be imagined in classical communication systems. Quantum communications can be realized in different ways. In this paper, we focus on the exploitation of quantum particles and quantum channels, in order to realize a data transmission system by means of phonons. First, we introduce the channel model of a phonon-based quantum system, and then derive the analysis of the error probability associated to such quantum channel. The application scenario is a biological environment, where phonons are exploited as information carriers. We have dealt a numerical evaluation in order to assess the performance of the quantum communication system. In particular, we have derived numerical results in terms of the error probability and the activity time, which represent how effective are phonons for communication purpose. We observe the frequency dependence of both error probability and activity time, thus allowing to tune the frequency for performance optimization.

International audience; Intelligent inter-vehicle communication is a key research field in the context of vehicular networks that applies in real-life applications (e.g., management of accidents, intelligent fuel consumption, smart traffic jams, etc.). Considering different roles of nodes based on their " social aptitude " to relay information could provide a social component in the vehicular structure that can be useful in getting a clear prediction of the topological evolution in time and space proving to be very effective in managing intelligent data forwarding. In this work we characterize a vehicular network as a graph using the link layer connectivity level and we classify nodes on the basis of specific attributes characterizing their " social aptitude " to forward data. Two forwarding approaches are presented, based on different socialites that allow to (i) select the most social node (i.e., a social hub) or (ii) choose among various social nodes.

International audience; Actuellement, l'Internet des Objets (IdO) est en train de prendre une place importante dans notre vie quotidienne. Il a obtenu un grand succès dans plusieurs domaines d'application. Toutefois, malgré ce succès, l'un des plus grand défis à relever est l'énorme quantité de données générées par les dispositifs de capteur. Cela peut affecter la consommation d'énergie et peut également causer des problèmes de congestion du réseau. Pour résoudre ce problème, nous présentons dans cet article une Approche d'Inférence Bayésienne (BIA) permettant d'éviter la transmission des données fortement corrélées. BIA est basé sur une architecture hiérarchique composée de simple capteur, de passerelles intelligentes et de centres de données. L’Algorithme de Belief Propagation est utilisé pour reconstituer les données manquantes. BIA est évalué sur la base des données collectées sur les capteurs M3 déployés dans la plateforme FIT IoT-LAB. Sur les divers scénarios étudiés, les résultats montrent que notre approche réduit considérablement le nombre de données transmises et la consommation d’énergie tout en maintenant une qualité d’information acceptable

International audience; Nowadays, Internet of Things (IoT) coupled with cloud computing begins to take an important place in economic systems and in society daily life. It has got a large success in several application areas, ranging from smart city applications to smart grids. Despite the apparent success, one major challenge that should be addressed is the huge amount of data generated by the sensing devices. The transmission of these huge amount of data to the network may affect the energy consumption of sensing devices, and can also cause network congestion issues. To face this challenge, we present a Bayesian Inference Approach (BIA), which allows avoiding the transmission of high spatio-temporal correlated data. In this paper, BIA is based on a hierarchical architecture with smart nodes, smart gateways and data centers. Belief Propagation algorithm has been chosen for performing an approximate inference on our model in order to reconstruct the missing sensing data. BIA is evaluated based on the data collected from the M3 sensors deployed in the FIT IoT-LAB platform and according to different scenarios. The results show that our proposed approach reduces drastically the number of transmitted data and the energy consumption, while maintaining an acceptable level of data prediction accuracy.

International audience; The Internet-of-Vehicles allows the coexistence of traditional Inter-net applications with the Internet-of-Things, so that vehicles can communicate not only among them but also to neighboring devices and humans as well. In this context, the human social behavior is a fundamental aspect that needs to be taken into account specially for message dissemination in Vehicular Social Networks. In this paper, we present a probabilistic broadcast protocol that exploits the " social degree " of a vehicle to be selected as next-hop forwarder. The social degree of a vehicle depends on its social activity inside a vehicular social network, so that a vehicle that uses to access and post often in a given vehicular social network is more likely to be " socially trusted ". Selecting a trusted vehicle as next-hop forwarder allows a secure and faster message dissemination with respect to an " asocial " vehicle. Simulation results show that a socially trusted vehicle improves network performance, expressed in terms of overall throughput.

International audience; To meet the food demand of the future, farmers are turning to the Internet of Things (IoT) for advanced analytics. In this case, data generated by sensor nodes and collected by farmers on the field provide a wealth of information about soil, seeds, crops, plant diseases, etc. Therefore, the use of high tech farming techniques and IoT technology offer insights on how to optimize and increase yield. However, one major challenge that should be addressed is the huge amount of data generated by the sensing devices, which make the control of sending useless data very important.To face this challenge, we present a Bayesian Inference Approach (BIA), which allows avoiding the transmission of high spatio-temporal correlateddata. In this paper, BIA is based on the PEACH project, which aims to predict frost events in peach orchards by means of dense monitoringusing low-power wireless mesh networking technology. Belief Propagation algorithm has been chosen for performing an approximate inferenceon our model in order to reconstruct the missing sensing data. According to different scenarios, BIA is evaluated based on the data collected from real sensors deployed on the peach orchard. The results show that our proposed approach reduces drastically the number of transmitted data and the energy consumption, while maintaining an acceptable level of data prediction accuracy.

International audience; L'Internet des Objets (IdO) a obtenu un grand succès dans divers domaines d'application. Toutefois, malgré ce succès, l'un des plus grands défis à relever est la grande quantité de données générées par les dispositifs de capteur. Cela peut affecter la consommation d'énergie et causer la congestion du réseau. Pour resoudre ce probleme, nous proposons dans cet article une Approche d'Inférence Bayésienne (AIB) permettant d'éviter la transmission des données fortement corrélées. AIB est basé sur une architecture hiérarchique composée de simple capteurs, de passerelles intelligentes et de centre de données. L'Algorithme Belief Propagation est utilisé pour reconstituer les données manquantes. La solution proposée est évalué sur la base des données recueillies sur des capteurs réels. Sur les divers scénarios étudiés, les résultats montrent que notre approche réduit considerablement le nombre de données transmises et la consommation d'énergie tout en maintenant une qualité d'information acceptable.

International audience; Internet of Robotic Things (IoRT) is a new concept introduced for the first time by ABI Research. Unlike the Internet of Things (IoT), IoRT provides adynamic actuation and is considered as the new evolution of IoT. This new concept will bring new opportunities and challenges, while providing newbusiness ideas for IoT and robotics’ entrepreneurs. In this work, we will focus particularly on two issues: (i) connectivity maintenance among multiple IoRT robots, and (ii) their collective coverage. We will propose (i) IoT-based, and (ii) a neural network control scheme to efficiently maintain the global connectivity among multiple mobile robots to a desired quality-of-service (QoS) level. The proposed approaches will try to find a trade-off between collective coverage and communication quality. The IoT-based approach is based on the computation of the algebraic connectivity and the use of virtual force algorithm. The neural network controller, in turn, is completely distributed and mimics perfectly the IoT-based approach. Results show that our approaches are efficient, in terms of convergence time, connectivity, and energy consumption.

International audience; Nowadays, Internet of Things (IoT) coupled with cloud computing begins to take an important place in economic systems and in society daily life. It has got a large success in several application areas, ranging from smart city applications to smart grids. One major challenge that should be addressed is the huge amount of data generated by the sensing devices, which make the control of sending useless data very important.To face this challenge, we present a Bayesian Inference Approach (BIA), which allows avoiding the transmission of high spatio-temporal correlated data. In this paper, BIA is based on a hierarchical architecture with simple nodes, smart gateways and data centers. Belief Propagation algorithm has been chosen for performing an approximate inference on our model in order to reconstruct the missing sensing data. BIA is evaluated based on the data collected from real sensors and according to different scenarios. The results show that our proposed approach reduces drastically the number of transmitted data and the energy consumption, while maintaining an acceptable level of data prediction accuracy.

Light field technology may have a positive impact on several multimedia applications thanks to novel ways to explore the captured scenes, such as changing the parallax (horizontally and vertically) and refocusing the content. These innovative use cases require new considerations that affect the whole processing chain, from content acquisition to visualization, as well as the methodologies for quality evaluation. In particular, capturing and selecting the appropriate content is crucial for a successful development and evaluation of audiovisual technologies. Thus, this paper presents a framework addressing the reconsideration of the space of attributes for an adequate characterization of light field data. Firstly, an exhaustive characterization of light field content is described, based on various particular features, including depth and refocusing properties to traditional spatial, temporal, and color indicators. Then, based on this characterization, specific techniques are proposed for an effective selection of light field content for perceptual quality assessment.

Vehicular communication networks are a type of network in which vehicles and roadside units are the communicating nodes, providing each other with information such as safety warnings and traffic information. As a cooperative approach, vehicular communications can be more effective in avoiding accidents and traffic congestion, rather than each vehicle trying to solve these problems individually. Therefore, intelligent transportation systems (ITS) have been developed to address the challenges of the safety, security, and efficacy of the current transportation systems. The field of inter vehicular communications (IVC) includes both vehicle-to-vehicle (V2V) and vehicle-to infrastructures (V2I) communication and is also known as the vehicular ad hoc network (VANET). The VANET is recognized as an important component of ITS in various national plans [1]. Direct communication between vehicles may be set up by means of mobile ad hoc networks (MANETs), which do not depend on the altered foundation. Research on MANETs covers the application prerequisites and correspondence conventions for everything from sensor systems to handheld PCs and vehicular frameworks [2].

International audience; Terahertz frequency band is an emerging research area related to nano-scale communications. In this frequency range, specific features can provide the possibility to overcome the issues related to the spectrum scarcity and capacity limitation. Apart high molecular absorption, and very high reflection loss that represent main phenomena in THz band, we can derive the characteristics of the channel affected by chirality effects occurring in the propagation medium, specifically , in the case where a Giant Optical Activity is present. This effect is typical of the so-called chiral-metamaterials in (4–10) THz band, and is of stimulating interest particularly for millimeter wireless communications. In this paper, we analyze the behavior of specific parameters of a chiral-metamaterial, like the relative electrical permit-tivity, magnetic permeability and chirality coefficients, and from that we derive the channel behavior both for Line-of-Sight and No Line-of-Sight propagations. We notice the presence of spectral windows, due to peaks of resonance of chiral parameter. Finally, performances of the chirality-affected channel have been assessed in terms of (i) channel capacity, (ii) propagation delay, and (iii) coherence band-width, for different distances.

International audience; Quantum phenomena represent a natural direction for developing nanotechnology, since it has to be considered as a new scale where new phenomena can occur and can be exploited for information purpose. Specific quantum particles are phonons, the quanta of mechanical vibrations (i.e., acoustic excitations), that can be analyzed as potential information carriers in a body network context. In this paper we derive the theoretical expression of the channel capacity of a phonon-based quantum network. By irradiating a sample of biological human tissue with an electromagnetic field, we obtain the generation of phonons from photon-phonon interaction, and can observe the information capacity in the frequency range [10ˆ3 10ˆ12 ] Hz.

International audience; Technology in the THz frequency band has progressed rapidly in the last a fewyears. The THz frequency band offers greater communication bandwidth than atmicrowaves frequencies, and is imposing for nano-scale communications. Indeed,what makes THz waves interesting, is their possible applications because of theirspecific features. Traditional channel models for lower frequencies do not takeinto consideration specific properties as the very high molecular absorption or thevery high reflection loss. In a propagation medium exhibiting a Giant Optical Activity,it is also important to derive the characteristics of the channel affected bychirality effects. This phenomenon occurs in particular material so-called chiralmetamaterialsin (4–10) THz band.The main contribution of this paper consist in the analysis of specific parametersof a chiral-metamaterial, such as the relative electrical permittivity, magnetic permeabilityand chirality coefficients. These parameters will be considered for thechannel model derivation both in Line-of-Sight and No Line-of-Sight propagation. The chiral effect affects the channel through the presence of spectral windows,due to peaks of resonance of chiral parameter. Performance analysis of thechirality-affected channel has been assessed in terms of (i) channel capacity, (ii)propagation delay, (iii) coherence bandwidth, and (iv) symbol rates, for differentdistances and propagation modes.

International audience; —Cloud computing and Internet of Things (IoT) represent two different technologies that are massively being adopted in our daily life, playing a fundamental role in the future Internet. One important challenge that need to be handled is the enormous amount of data generated by sensing devices, that make the control of sending useless data very important. In order to face with this challenge, there is a increasing interest about predictive approaches to avoid to send high spatio-temporal correlated data. Belief Propagation (BP) algorithm is a method of performing approximate inference on arbitrary graphical models that is becoming increasingly popular in the context of IoT. By exploiting BP, we can derive effective methods to drastically reduce the number of transmitted messages, while keeping high the data throughput in the global information system. In this paper, we propose a BP approach in a hierarchical architecture with simple nodes, gateways and data centers. We evaluate the error bounding and propose a corrective mechanism to keep a certain quality of the global information in the architecture considered.

International audience; Internet of Robotic Things (IoRT) is a new concept introduced for the first time by ABI Research. Unlike the Internet of Things (IoT), IoRT provides an active sensorization and is considered as the new evolution of IoT. This new concept will bring new opportunities and challenges, while providing new business ideas for IoT and robotics’ entrepreneurs. In this paper, we will focus particularly on two issues: (i) connectivity maintenance among multiple IoRT robots, and (ii) their collective coverage. We will propose (i) IoRT-based, and (ii) a neural network control scheme to efficiently maintain the global connectivity among multiple mobile robots to a desired quality-of-service (QoS) level. The proposed approaches will try to find a trade-off between collective coverage and communication quality. The IoT-based approach is based on the computation of the algebraic connectivity and the use of virtual force algorithm. The neural network controller, in turn, is completely distributed and mimics perfectly the IoT-based approach. Results show that our approaches are efficient, in terms of convergence, connectivity, and energy consumption.

International audience; In this work, we investigate the interaction of a nanoparticulate system for nanomedicine applications with the biological environment, i.e., the human body. Following the molecular communication paradigm, we assess how our nanoparticulate system model is suitable for coexistence in a biological environment. Specifically, we assume the presence of the human immune system that can affect the optimal behavior of nanoparticles, aiming to locally deliver drug inside the human body. When a flow of nanoparticles is injected into the blood, the interference due to the immune system can provide a strong decrease of the nanoparticle concentration, by means of “humoral immunity”, the phagocytosis process, etc. As a consequence, the correct drug delivery will occur with a lower probability. Since the mechanism behind the biological immune system is very complicated, in this paper, we start from a simplistic nanoparticulate model, where the nanoparticles and the cells of the immune system are subject to the diffusion laws. Finally, we derive the end-to-end physical model of our nanoparticulate nanomedicine system with the presence of the human immune system cells. The error analysis is then investigated in terms of how these errors can affect the performance of the system, i.e., nanoparticle survival probability.

Innovative diagnostic approaches and therapies are more and more based on the use of injections or oral delivery of nanoparticle sized substances. For a better understanding of the overall phenomena, aiming to facilitate a safe application at large scale, the development of accurate models and analysis techniques are required. These techniques take into consideration different aspects of the overall process: accurate numerical modeling of the different phases of the nanoparticles in the body, and knowledge of the local environment, that can be varying very fast within a short-range in the body itself. Such aspects should be taken into account to correctly predict the amount of drug and its timely release for the specific disease. Deep and accurate analysis of the interaction between the nanoparticles and the biological fluid where the nanoparticles are immersed is mandatory for an efficient correlation of all these aspects. Because of their biocompatibility, in this paper, we focus our attention on systems of Titanium (Ti), and its oxide (e.g., ${\rm TiO}_{2}$ ), given their specific features in terms of density, lack of cytotoxic effects, etc. Specifically, we present the study and design of an in-body system by characterizing each of the emission, diffusion, and reception processes with a proper realistic model. The theoretical investigation is further supported by experimental study of the morphology and other important characteristics (e.g., the pH of the particles, and thermal stability) of ${\rm TiO}_{2}$ systems when immersed in a Ringer solution, in order to derive important information related to their potential toxicity inside the human body.

International audience; Nanotechnology is gaining more and more consensus in several application fields, comprised in-body applications. Innovative therapies and diagnostic approaches are based on the use of injections or oral delivery of nanoparticles. The acceleration of this type of development makes very urgent a deeply and accurate analysis of the interaction between the nanoparticles and the biological fluid where the nanoparti-cles are immersed. In this paper, we focus on Titanium (T i and its alloy (e.g., T iO2) systems, given their specific features in terms of density, lack of cytotoxic effects, etc.. Specifically, we design and study an in-body system by characterizing the emission and diffusion processes. Further, we propose an experimental study of the morphology and other important characteristics (e.g. the pH of the particles, and the dielectric constant of the solution) of nano-T iO2 systems when immersed in a Ringer solution, in order to derive important information related to their potential toxicity inside the human body.

International audience; This article surveys recent literature on Vehicular Social Networks that are a particular class of vehicular ad hoc networks, characterized by social aspects and features. Starting from this pillar, we investigate perspectives of next generation vehicles under the assumption of social networking for vehicular applications (i.e., safety and entertainment applications). This paper plays a role as a starting point about socially-inspired vehicles, and main related applications, as well as communication techniques. Vehicular communications can be considered as the “first social network for automobiles”, since each driver can share data with other neighbors. As an instance, heavy traffic is a common occurrence in some areas on the roads (e.g., at intersections, taxi loading/unloading areas, and so on); as a consequence, roads become a popular social place for vehicles to connect to each other. Human factors are then involved in vehicular ad hoc networks, not only due to the safety related applications, but also forentertainment purpose. Social characteristics and human behavior largely impact on vehicular ad hoc networks, and this arises to the vehicular social networks, which are formed when vehicles (individuals) “socialize” and share common interests. In this paper, we provide a survey on main features of vehicular social networks, from novel emerging technologies to social aspects used for mobile applications, as well as main issues and challenges. Vehicular social networks are described as decentralized opportunistic communication networks formed among vehicles. They exploit mobility aspects, and basics of traditional social networks, in order to create novel approaches of message exchange through the detection of dynamic social structures. An overview of the main state-of-the-art on safety and entertainment applications relying on social networking solutionsis also provided.

In this contribution, we present a communication paradigm among nanodevices, based on acoustic vibrations for medical applications. We consider a swarm of nanorobots able to communicate in a distributed and decentralized fashion, propelled in a biological environment (i.e., the human brain). Each nanorobot is intended to i) recognize a cancer cell, ii) destroy it, and then iii) forward information about the presence of cancer formation to other nanorobots, through acoustic signals. The choice of acoustic waves as communication mean is related to the application context, where it is not advisable either to use indiscriminate chemical substances or electromagnetic waves. The effectiveness of the proposed approach is assessed in terms of achievement of the objective (i.e., to destroy the majority of tumor cells), and the velocity of detection and destruction of cancer cells, through a comparison with other related techniques.

During the examination of a collection made by the authors in 2009 in San Pedro de Atacama (Antofagasta Region, Chile) one specimen was identified as Bryum incacorralis Herzog, a moss not previously known from Chile (Müller, 2009) and easily confused with some species of Philonotis Brid. (Ochi, 1980). Comparison with the type material confirmed its identity (Holotype: Bolivia, Cochabamba: an Felsen der "Estradillas" bei Incacorral, 3000 m, Herzog s.n., JE! no. 04003475). Bryum incacorralis was first described by Herzog (1909) based on material collected in Cochabamba (Bolivia), and later recorded by Griffin (1977) and O'Shea (2010) from Venezuela. It is placed in the so-called sect. "Alpiniformia" within the genus Bryum which is characterized by the presence of ovate to ovate-lanceolate leaf shape, the costa ceasing just below the leaf apex, the very dense areolation of the leaf, and long, more or less clavate capsules (Ochi, 1980). This note constitute the first record of Bryum incacorralis from Chile, where the species was found in the highlands of the north part of the country, in San Pedro de Atacama, an arid high plateau placed at the east of Antofagasta, growing on soil between Laretia, at ca. 4000 m. Bryum incacorralis is a distinctive species characterized by small to medium sized plants, scarcely lustrous, with ovate-lanceolate leaves, not or hardily bordered, equally spaced through the stem, with an acuminate apex and an abruptly narrowed base; laminal cells hexagonal to short-rectangular, and a costa ceasing just below the apex. Chilean specimen is synoicous, with antheridia and archegonia mixed at the same gametoecium, with abundant filiform paraphyses longer than the sexual structures. In comparison with the type specimen, the Chilean sample is more robust, its leaves margin are little revolute, and the apex vary from mild to markedly abruptly acuminate, sometimes ending in a small mucro. Fil: Jimenez, Maria Soledad. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Botanica del Nordeste. Universidad Nacional del Nordeste. Facultad de Ciencias Agrarias. Instituto de Botanica del Nordeste; Argentina Fil: Suarez, Guillermo Martin. Fundación Miguel Lillo; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Ellis, L. T.. Natural History Museum; Reino Unido Fil: Asthana, A. K.. National Botanical Research Institute; India Fil: Srivastava, A.. National Botanical Research Institute; India Fil: Bakalin, V. A.. Botanical Garden Institute; Rusia. Institute of Biology and Soil Science; Rusia Fil: Bednarek Ochyra, H.. Polish Academy of Sciences; Polonia Fil: Cano, M. J.. Universidad de Murcia; España Fil: Jiménez, J. A.. Universidad de Murcia; España Fil: Alonso, M.. Universidad de Murcia; España Fil: Deme, J.. University of Pécs; Hungría Fil: Csiky, J.. University of Pécs; Hungría Fil: Dia, M. G.. Universitá di Palermo; Italia Fil: Campisi, P.. Universitá di Palermo; Italia Fil: Erzberger, P.. Fil: Garilleti, R.. Universidad de Valencia; España Fil: Gorobets, K. V.. Far-Eastern Federal University; Rusia Fil: Gremmen, N. J. M.. Fil: Jukoniene, I.. Institute of Botany; Lituania Fil: Kiebacher, T.. Swiss Federal Research Institute WSL; Suiza Fil: Kirmaci, M.. Adnan Menderes Üniversitesi; Turquía Fil: Koczur, A.. Polish Academy of Sciences; Polonia Fil: Kürschner, H.. Freie Universität Berlin; Alemania Fil: Lara, F.. Universidad Autónoma de Madrid; España Fil: Mazimpaka, V.. Universidad Autónoma de Madrid; España Fil: Larraín, J.. The Field Museum; Estados Unidos Fil: Lebouvier, M.. Universite de Rennes I; Francia Fil: Medina, R.. University Of Connecticut; Estados Unidos Fil: Natcheva, R.. Bulgarian Academy of Sciences; Bulgaria Fil: Newsham, K. K.. NERC British Antarctic Survey; Reino Unido. The University Centre in Svalbard; Noruega

This paper describes a recently created image database, TID2013, intended for evaluation of full-reference visual quality assessment metrics. With respect to TID2008, the new database contains a larger number (3000) of test images obtained from 25 reference images, 24 types of distortions for each reference image, and 5 levels for each type of distortion. Motivations for introducing 7 new types of distortions and one additional level of distortions are given; examples of distorted images are presented. Mean opinion scores (MOS) for the new database have been collected by performing 985 subjective experiments with volunteers (observers) from five countries (Finland, France, Italy, Ukraine, and USA). The availability of MOS allows the use of the designed database as a fundamental tool for assessing the effectiveness of visual quality. Furthermore, existing visual quality metrics have been tested with the proposed database and the collected results have been analyzed using rank order correlation coefficients between MOS and considered metrics. These correlation indices have been obtained both considering the full set of distorted images and specific image subsets, for highlighting advantages and drawbacks of existing, state of the art, quality metrics. Approaches to thorough performance analysis for a given metric are presented to detect practical situations or distortion types for which this metric is not adequate enough to human perception. The created image database and the collected MOS values are freely available for downloading and utilization for scientific purposes. We have created a new large database.This database contains larger number of distorted images and distortion types.MOS values for all images are obtained and provided.Analysis of correlation between MOS and a wide set of existing metrics is carried out.Methodology for determining drawbacks of existing visual quality metrics is described.

The use of EEG biometrics, for the purpose of automatic people recognition, has received increasing attention in the recent years. Most of current analysis rely on the extraction of features characterizing the activity of single brain regions, like power-spectrum estimates, thus neglecting possible temporal dependencies between the generated EEG signals. However, important physiological information can be extracted from the way different brain regions are functionally coupled. In this study, we propose a novel approach that fuses spectral coherencebased connectivity between different brain regions as a possibly viable biometric feature. The proposed approach is tested on a large dataset of subjects (N=108) during eyes-closed (EC) and eyes-open (EO) resting state conditions. The obtained recognition performances show that using brain connectivity leads to higher distinctiveness with respect to power-spectrum measurements, in both the experimental conditions. Notably, a 100% recognition accuracy is obtained in EC and EO when integrating functional connectivity between regions in the frontal lobe, while a lower 97.41% is obtained in EC (96.26% in EO) when fusing power spectrum information from centro-parietal regions. Taken together, these results suggest that functional connectivity patterns represent effective features for improving EEG-based biometric systems., Comment: Key words: EEG, Resting state, Biometrics, Spectral coherence, Match score fusion

This paper presents a hybrid watermarking technique which mixes additive and multiplicative watermark embedding with emphasis on its robustness versus the imperceptibility of the watermark. The embedding is performed in six wavelet sub-bands using independently three embedding equations and two parameters to modulate the embedding strength for multiplicative and additive embedding. The watermark strength is independently modulated into distinct image areas. Specifically, when a multiplicative embedding is used, the visibility threshold is first reached near the image edges, whereas using an additive embedding technique the visibility threshold is first reached into the smooth areas. A subjective experiment has been used to provide the optimal watermark strength for three distinct embedding equations. Observers were asked to tune the watermark amplitude and to set the strength at the visibility threshold. The experimental results showed that using an hybrid watermarking technique significantly improves the robustness performance. This work is a preliminary study for the design of an optimal wavelet domain Just Noticeable Difference (JND) mask.

International audience; In this paper we address the problem of crosstalk reduction for autostereoscopic displays. Crosstalk refers to the perception of one or more unwanted views in addition to the desired one. Specifically, the proposed approach consists of three different stages: a crosstalk measurement stage, where the crosstalk is modeled, a filter design stage, based on the results obtained out of the measurements, to mitigate the crosstalk effect, and a validation test carried out by means of subjective measurements performed in a controlled environment as recommended in ITU BT 500-11. Our analysis, synthesis, and subjective experiments are performed on the Alioscopy® display, which is a lenticular multiview display.

In watermarking and data hiding context, it may be very useful to have methods checking the invisibility of the inserted data or at least, checking the objective quality after the mark embedding or after an attack on the watermarked media. Many works exist in the literature dealing with quality assessment mainly focused on compression application. Nevertheless, visual quality assessment should include special requirements that depend on the application context. This chapter presents an extended review of both subjective and objective quality assessment of images and video in the field of watermarking and data hiding applications.

International audience; In the last decade digital watermarking techniques have been devised to answer the ever-growing need to protect the intellectual property of digital still images, video sequences or audio from piracy attacks. Because of the proliferation of watermarking algorithms and their applications some benchmarks have been created in order to help watermarkers comparing their algorithms in terms of robustness against various attacks (i.e. Stirmark, Checkmark). However, no equal attention has been devoted to the proposition of benchmarks tailored to assess the watermark perceptual transparency. In this work, we study several watermarking techniques in terms of the mark invisibility through subjective experiments. Moreover, we test the ability of several objective metrics, used in the literature mainly to evaluate distortions due to the coding process, to be correlated with subjective scores. The conclusions drawn in the paper are supported by extensive experimentations using both several watermarking techniques and objective metrics.