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International audience; This paper focuses on the problem of the hierarchical multi‐label classification of research papers, which is the task of assigning the set of relevant labels for a paper from a hierarchy, using reduced amounts of labelled training data. Specifically, we study leveraging unlabelled data, which are usually plentiful and easy to collect, in addition to the few available labelled ones in a semi‐supervised learning framework for achieving better performance results. Thus, in this paper, we propose a semi‐supervised approach for the hierarchical multi‐label classification task of research papers based on the well‐known Co‐training algorithm, which exploit content and bibliographic coupling information as two distinct papers' views. In our approach, two hierarchical multi‐label classifiers, are learnt on different views of the labelled data, and iteratively select their most confident unlabelled samples, which are further added to the labelled set. The success of our suggested Co‐training‐based approach lies in two main components. The first is the use of two suggested selection criteria (i.e., Maximum Agreement and Labels Cardinality Consistency) that enforce selecting confident unlabelled samples. The second is the appliance of an oversampling method that rebalances the labels distribution of the initial labelled set, which reduces the reinforcement of the label imbalance issue during the Co‐training learning. The proposed approach is evaluated using a collection of scientific papers extracted from the ACM digital library. Performed experiments show the effectiveness of our approach with regards to several baseline methods.

Swarms of autonomous aircraft systems (SAAS) are used to accomplish missions that deal with sensitive and critical data. As such, these systems are subject to attacks among which clone attacks. Several clone attacks detection approaches either in stationary or mobile wireless sensor networks have been proposed. Unfortunately, the existing approaches are not suitable for swarms of autonomous aircraft systems because either they do not guarantee a fast enough detection (while most SAAS missions are real time missions, e.g. surveillance), or they depend on strong assumptions that are hard to achieve in practice (e.g. absence of nodes collusion, impossibility for an attacker to track a genuine node). In this paper, we present a novel clone attack detection approach specific to SAAS that solves several unaddressed issues and that makes it possible to improve the security and the privacy of the assets of the SAAS.

International audience; Advanced internet and multimedia set-top boxes are today massively based on 4*4 MIMO systems, with multi-sub-bands standards (Wifi bands, LTE, Bluetooth,…). Multiple antennas spatially distributed on the plastic casing become therefore a great challenge for cost and performances motivations, thus promoting flexible technology and substrate, for assembling subsystems , under compactness considerations, as well as electrical performances improvement. In this paper, we discuss about the characterisation of Multi-band antennas designed on an ultra-low cost material (a cellulosic substrate, i.e. a paper) with design challenges in terms of radiation efficiency maximization and wideband properties under compactness constraints. Simulation and measurements are proposed to validate the designs.

International audience; With the increasing development of handheld devices, Location Based Services (LBSs) became very popular in facilitating users' daily life with a broad range of applications (e.g. traffic monitoring, geo-located search, geo-gaming). However , several studies have shown that the collected mobility data may reveal sensitive information about end-users such as their home and workplaces, their gender, political, religious or sexual preferences. To overcome these threats, many Location Privacy Protection Mechanisms (LPPMs) were proposed in the literature. While the existing LPPMs try to protect most of the users in mobility datasets, there is usually a subset of users who are not protected by any of the existing LPPMs. By analogy to medical research, there are orphan diseases, for which the medical community is still looking for a remedy. In this paper, we present MooD, a fine-grained multi-LPPM user-centric solution whose main objective is to find a treatment to mobile users' orphan disease by protecting them from re-identification attacks. Our experiments are conducted on four real world datasets. The results show that MooD outperforms its competitors, and the amount of user mobility data it is able to protect is in the range between 97.5% to 100% on the various datasets. CCS Concepts • Security and privacy → Pseudonymity, anonymity and untraceability.

International audience; In this article, we present the design and results of an electronically re-writable chipless RFID tag on paper substrate. This tag consists of two resonators build around a modified shorted dipole, integrated with a non-volatile Metal-Insulator-Metal (MIM) switch, which tunes the electrical length of each resonator to resonate at two different frequencies, depending on state of the switch. One can electronically reconfigure the tag using low power DC pulses to change its RF signature. The integrated MIM switch has a layer architecture of Silver-Nafion-Aluminum, formed exclusively using an in-house process in ambient laboratory conditions, notably without the use of any 'clean room' facilities. Operating mechanism of the tag is validated with the help of developed electrical equivalent model. This study proves the concept of realizing 'electronically reconfigurable' chipless tags on flexible and low cost substrates, with a fabrication process compatible with mass production.

One important feature required by autonomous vehicles is the ability to perform a localization task in order to navigate in both known (urban, suburban, and highways) and unknown environments. Instead of relying on LIDAR technology, we propose to leverage a bio-inspired algorithm relying on more conventional cameras and a large neural network (NN) [2]. Yet, this approach must be able to scale. We propose to investigate the development of an FPGA-based solution. Due to the size of NN, dynamic partial reconfiguration will be required, and an efficient (software-based) scheduler must place the hardware tasks on multiple FPGA chip. We intend to implement this algorithm using a unique custom board, Wizarde, which embeds a 3 × 3 matrix of Zynq SoCs with high-end FPGAs to prototype a possible solution.

International audience; A growing fraction of the papers published by CCR and at SIGCOMM-sponsored conferences include artifacts such as software or datasets. Besides CCR, these artifacts were rarely evaluated. During the last months of 2018, we organised two different Artifacts Evaluation Committees to which authors could submit the artifacts of their papers for evaluation. The first one evaluated the papers accepted by Conext’18 shortly after the TPC decision. It assigned ACM reproducibility badges to 12 different papers. The second one evaluated papers accepted by CCR and any SIGCOMM-sponsored conference. 28 papers received ACM reproducibility badges. We report on the results of a short survey among artifacts authors and reviewers and provide some suggestions for future artifacts evaluations.

International audience

International audience; This book constitutes the thoroughly refereed proceedings of the First International Conference on Machine Learning for Networking, MLN 2018, held in Paris, France, in November 2018. The 22 revised full papers included in the volume were carefully reviewed and selected from 48 submissions. They present new trends in the following topics: Deep and reinforcement learning; Pattern recognition and classification for networks; Machine learning for network slicing optimization, 5G system, user behavior prediction, multimedia, IoT, security and protection; Optimization and new innovative machine learning methods; Performance analysis of machine learning algorithms; Experimental evaluations of machine learning; Data mining in heterogeneous networks; Distributed and decentralized machine learning algorithms; Intelligent cloud-support communications, resource allocation, energy-aware/green communications, software defined networks, cooperative networks, positioning and navigation systems, wireless communications, wireless sensor networks, underwater sensor networks.

International audience; IntroductionIn January 2015, Rouen University Hospital’s information system experienced serious issues. It was necessary to rapidly switch from the computerized provider order entry (CPOE) system towards a paper-based order entry (PBOE) system. This was an opportunity to evaluate prescriber opinion on the two provider order entry (POE) systems.MethodsAll residents were asked to fill an augmented version of the POE satisfaction and usage survey for both POE systems. The results were compared to identify the strengths and weaknesses of each system.ResultsFifty-one respondents had used the CPOE system and the PBOE system. Overall, satisfaction was higher with PBOE than CPOE (odds ratio (OR) = 3.74; p < 0.001). Usability (OR = 4.00; p < 0.001), reliability (OR = 8.54; p < 0.001), time consumption (OR = 0.50; p < 0.05 – survey statement was formulated negatively), and communication with nurses (OR = 14.27; p < 0.0001) reached statistically better agreement. The more experience with CPOE the more residents were disillusioned with the reliability (OR = 6.55; p < 0.01), the usability (OR = 5.68; p < 0.01) and the patient safety (OR = 0.27; p < 0.05 – survey statement was formulated negatively) of CPOE. Although safety issues were reported for both systems, the causes were different; PBOE imposed frequent rewriting of the order while CPOE lack of usability might be unsafe. Another important issue with both POE systems was time consumption.ConclusionResidents did not report any increase in safety issues with the rapid switch from CPOE to PBOE. They even seemed more satisfied with the rollback to paper, which remains a possible degraded mode in case of health information technology collapse.

International audience; Prototyping interactive objects with personal fabrication tools like 3D printers requires the maker to create subsequent design artifacts from scratch which produces unnecessary waste and does not allow to reuse functional components. We present Interactive Tangrami, paper-folded and reusable building blocks (Tangramis) that can contain various sensor input and visual output capabilities. We propose a digital design toolkit that lets the user plan the shape and functionality of a design piece. The software manages the communication to the physical artifact and streams the interaction data via the Open Sound protocol (OSC) to an application prototyping system (e.g. MaxMSP). The building blocks are fabricated digitally with a rapid and inexpensive ink-jet printing method. Our systems allows to prototype physical user interfaces within minutes and without knowledge of the underlying technologies. We demo its usefulness with two application examples.

International audience; The task of tagging papers with semantic metadata in order to analyze their relatedness represents a good foundation for a paper recommender system. The analysis from this paper extends from previous research in order to create a graph of papers from a specific domain with the purpose of determining each article's importance within the considered corpus of papers. Moreover, as non-latent representations are powerful when used in conjunction with latent ones, our system retrieves semantically close words, not present in the paper, in order to improve the retrieval of papers. Our previous analyses used the semantic representation of papers in different semantic models with the purpose of creating visual graphs based on the semantic relatedness links between the abstracts. The current analysis takes a step forward by proposing a model that can suggest which papers are of the highest relevance, share similar concepts, and are semantically related with the initial query. Our study is performed using paper abstracts in the field of information technology extracted from the Web of Science citation index. The research includes a use case and its corresponding results by using interactive and exploratory network graph representations.

International audience; In a context of the end of Moore's law, energy dissipation constitutes a real challenge. Among the new energy efficient paradigms for data processing, bio-inspired computing is very promising, moreover introducing cognitive characteristics. As applications at very high scale are addressed, the size and energy dissipation of both the neuron and synapse cells needs to be minimized. In this context, this paper presents the design of an original artificial neuron, using standard 65nm CMOS technology with optimized energy efficiency and its application in basic neural networks. By recalling brain and neuron features, it is shown why neuron energy efficiency is roughly limited to 1 pJ/spike in biological neuron. Biological and artificial neurons features are carefully compared, highlighting the importance of downscaling. The artificial neuron circuit presented was designed to exhibit wide band spiking frequencies, targeting large scale bio-inspired information processing applications. The most important feature of the fabricated circuits is the neuron energy efficiency in the few fJ/spike range, which improves prior state-of-the-art by two to three orders of magnitude. This performance is achieved by minimizing two key parameters: the supply voltage and the related membrane capacitance. Meanwhile, the obtained standby power at a resting output does not exceed tens of picowatts. The circuit is sized to 35 mu m(2), reaching a spiking output frequency of 26kHz. It is then shown how this artificial technology has already been used for two applications: (i) emulation of bursting mode, important in brain stimulation context or for robotics (locomotion rhythm), (ii) stochastic resonance application, useful to detect an electrical signal buried in noise, phenomena exploited in nature by species. These results already allow envisioning the development of highly integrated neuro-processors (vision application). A variant circuit (biomimetic) could be used for robotics, neuroscience or medical applications.

International audience; Sentiment analysis has grown to become increasingly important for companies to more accurately understand customer/supplier sentiments about their processes/products and services, and predict customer churn. In particular, existing sentiment analysis aims to better understand their customer’s or supplier’s emotions which are essentially the affirmative, negative, and neutral views of users on tangible or intangible entities e.g., products or services. One of the most prevalent sources to analyse these sentiments is Twitter. Unfortunately, however, existing sentiment analysis techniques suffer from three serious shortcomings: (1) they have problems to effectively deal with streaming data as they can merely exploit (Twitter) hashtags, and (2) neglect the context of Tweets. In this paper, we present SANA: a context-aware solution for dealing with streaming (Twitter) data, analysing this data on the fly taking into account context and more comprehensive semantics of Tweets, and dynamically monitoring and visualising trends in sentiments through dashboarding and query facilities.

International audience; Photographic paper texture characterization constitutes a challenging image processing task and an important stake both for manufacturers and art museums. The present contribution shows how the Hyperbolic Wavelet Transform, thanks to its joint multiscale and anisotropie nature, permits to achieve an accurate photographic paper texture analysis and characterization. A cepstral-type distance, constructed on the coefficients of the Hyperbolic Wavelet Transform, is then used to measure similarity between pairs of paper textures. Spectral clustering followed by Ascendant Hierarchical Clustering applied to the similarity matrix enables an unsupervised classification of photographic paper sheets. This methodology is applied to a test dataset made available in the framework of the Historic Photographic Paper Classification Challenge. The relevance of the proposed texture characterization and classification procedure is assessed by comparisons against the database documentation provided by experts.

This paper presents a new design of a low cost passive UHF RFID tag antenna using paper substrate. The design is based on a short dipole loaded at both ends with a pair of triangles and four arms in order to reduce the size of the design. By choosing a proper dimension of the short dipole and the T-matching network, a good and broadband impedance matching can be achieved. The simulation results carried out by ADS from Agilent technologies and CST Microwave Studio electromagnetic solvers, demonstrate that we have good performances in term of return loss, gain, radiation pattern and read range for the desired frequency bands. This antenna has a total area of 80×34 mm2 and mounted on a paper substrate. With a constant dielectric permittivity, equal to 3.3, a thickness of 0.5 mm and a loss tangent of 0.04. The simulated bandwidth at the UHF RFID band is about 56 MHz, which covers the North and South American UHF RFID band (894–950 MHz). The gain obtained into simulation of this antenna is 1.88 dB at 915 MHz and the simulated read range is 5.78 m.

International audience; We present the results of a comprehensive multi-pass analysis of visualization paper keywords supplied by authors for their papers published in the IEEE Visualization conference series (now called IEEE VIS) between 1990–2015. From this analysis we derived a set of visualization topics that we discuss in the context of the current taxonomy that is used to categorize papers and assign reviewers in the IEEE VIS reviewing process. We point out missing and overemphasized topics in the current taxonomy and start a discussion on the importance of establishing common visualization terminology. Our analysis of research topics in visualization can, thus, serve as a starting point to (a) help create a common vocabulary to improve communication among different visualization subgroups , (b) facilitate the process of understanding differences and commonalities of the various research sub-fields in visualization, (c) provide an understanding of emerging new research trends, (d) facilitate the crucial step of finding the right reviewers for research submissions, and (e) it can eventually lead to a comprehensive taxonomy of visualization research. One additional tangible outcome of our work is an online query tool (http://keyvis.org/) that allows visualization researchers to easily browse the 3 952 keywords used for IEEE VIS papers since 1990 to find related work or make informed keyword choices.

International audience; Wove paper, made on a papermaking screen or mold having a surface of smooth tightly woven wires, was the predominant paper type used for printing in the twentieth century. To aid in the study and classification of fine art prints on wove paper, the present work compares the results of five different image processing approaches for characterizing surface texture. Using a collection of popular wove papers, a reference dataset of raking light close-up images was assembled. Five research teams undertook their own processing strategies to detect affinities among the paper samples. Their success in identifying similarity groupings are reported.

Part 1: Long and Short Papers (Continued); International audience; For expert interfaces, it is not obvious whether providing multiple modes of interaction, each tuned to different sub-tasks, leads to a better user experience than providing a more limited set. In this paper, we investigate this question in the context of air traffic control. We present and analyze an augmented flight strip board offering several forms of interaction, including touch, digital pen and physical paper objects. We explore the technical challenges of adding finger detection to such a flight strip board and evaluate how expert air traffic controllers interact with the resulting system. We find that users are able to quickly adapt to the wide range of offered modalities. Users were not overburden by the choice of different modalities, and did not find it difficult to determine the appropriate modality to use for each interaction.

International audience; Languages for embedded systems ensure predictable timing behavior by specifying constraints based on either data streaming or reactive control models of computation. Moreover, various toolsets facilitate the incremental integration of application functionalities and the system design by evolutionary refinement and model-based code generation. Modern embedded systems involve various sources of interference in shared resources (e.g. multicores) and advanced real-time constraints , such as mixed-criticality levels. A sufficiently expressive model-ing approach for complex dependency patterns between real-time tasks is needed along with a formal analysis of models for runtime resource managers with timing constraints. Our approach utilizes a model of computation , called Fixed-Priority Process Networks, which ensures functional determinism by unifying streaming and reactive control within a timed automata framework. The tool flow extends the open source TASTE tool-suite with model transformations to the BIP language and code generation tools. We outline the use of our flow on the design of a spacecraft on-board application running on a quad-core LEON4FT processor.

Conference of 16th International Conference on Embedded Computer Systems: Architectures, Modeling and Simulation, SAMOS 2016 ; Conference Date: 17 July 2016 Through 21 July 2016; Conference Code:126004; International audience; The Modular Microserver DataCentre (M2DC) project investigates, develops and demonstrates a modular, highly-efficient, cost-optimized server architecture composed of heterogeneous micro server computing resources, being able to be tailored to meet requirements from various application domains, including the Internet of Things. M2DC is built on three main pillars: a flexible server architecture that can be easily customised, maintained and updated; advanced management strategies and system efficiency enhancements (SEE); well-defined interfaces to surrounding software data centre ecosystem.

International audience; In this paper, we demonstrate for the first time that a 19-bit chipless tag based on a paper substrate can be realized using the flexography technique, which is an industrial high-speed printing process. The chipless tag is able to operate within the ultra-wide band (UWB) and has a reasonable size ( 7×3 cm 2) compared to state-of-the-art versions. Thus, it is possible to use this design for various identification applications that require a low unit cost of tags. Both the simulation and measurement results are shown, and performance comparisons are provided between several realization processes, such as classical chemical etching, flexography printing, and catalyst inkjet printing.

Computer Vision, Imaging and Computer Graphics - Theory and Applications : International Joint Conference, VISIGRAPP 2015, Berlin, Germany, March 11-14, 2015, Revised Selected Papers

International audience; The need for safety and comfort in vehicular environments has led to a lot of research in vehicular ad-hoc networks (VANET), ranging from vehicle to vehicle (V2V) and vehicle to infrastructure (V2I) communications to security. As regards the latter aspect, mostly the focus has been on resorting to public key infrastructure (PKI) and its related concepts. Moreover, methods used to detect the most feared security attacks are based almost exclusively on the use of physical characteristics as well as PKI concepts or both. However with emerging technologies that enable connecting a vehicle to external resources, VANET is evolving, thus inheriting security threats that are common place in conventional IT systems. Therefore, as it is shown in the paper, VANET security must go beyond cryptographic-centric mechanisms that are commonly used for providing data security in wireless environment

WOS:000373963700037; International audience

International audience; This paper presents S-Notebook, a tool that makes it possible to "extend" mobile devices with augmented paper. Paper is used to overcome the physical limitations of mobile devices by offering ad- ditional space to annotate digital files and to easily create relation- ships between them. S-Notebook allows users to link paper annota- tions or drawings to anchors in digital files without having to learn pre-defined pen gestures. The systems stores meta data such as spa- tial or temporal location of anchors in the document as well as the zoom level of the view. Tapping on notes with the digital pen make appear the corresponding documents as displayed when the notes were taken. A given piece of augmented paper can contain notes as- sociated to several documents, possibliy at several locations. The annotation space can thus serve as a simple way to relate various pieces of one or several digital documents between them. When the user shares his notes, the piece of paper becomes a tangible to- ken that virtually contains digital information.

Part 5: Panel Session – Risk Management of Identity Management; International audience; We motivate and give a brief overview of the Conflicting Incentives Risk Analysis (CIRA) method, explaining key ideas and concepts, offering a small example and give an overview of remaining challenges in relation to the use of CIRA in large scale risk analysis projects.

International audience; Interest and need for Wireless Body Area Networks (WBANs) havesignicantly increased recently. WBAN consists of miniaturized sensors de-signed to collect and transmit data through wireless network, enabling medicalspecialists to monitor patients during their normal daily life and providing realtime opinions for medical diagnosis. Many wireless technologies have provedthemselves in WBAN applications, while others are still under investigations.The choice of the technology to adopt may depend on the disease to moni-tor and the performance requirements, i.e. reliability, latency and data rate.In addition, the suitable sensor is essential when seeking to extract the datarelated to a medical measure.This paper aims at surveying the wireless technologies used in WBAN sys-tems. In addition to a detailed survey on the existing technologies, the use ofthe emerging Low Power Wide Area Network (LPWAN) technologies, and thefuture 5G, B5G and 6G is investigated, where the suitability of these technolo-gies to WBAN applications is studied from several perspectives. Furthermore,medical applications of WBAN are discussed by presenting their methodolo-gies, the adopted wireless technologies and the used sensors. Given that eachmedical application requires the appropriate sensor to extract the data, wehighlight a wide range of the sensors used in the market for medical systems.Recent and future challenges in WBAN systems are given related to the powerconsumption, the emergence of the Internet of Things (IoT) technologies inWBAN and others.

International audience; From a European technological and industrial perspective of the 20th century, Knowledge Management (KM) was viewed as the next step towards reaching a smart knowledge-based economy. But today, in the 21th century of big data and fast moving information, we argue that KM is not enough for reaching a qualitative human-based post-industrial society. We need a broader view in order to understand user needs and respond to their personal desires. In this endeavor, Living labs are a good way to reposition creative people at the center of technologies. But we need also methodologies and tools to accompany the transition from a competitive economy to a more sustainable society. We experimented this move at University of Reunion Island in the domain of e-education. We conceived a new paradigm called Sign Management (SM) for enhancing content producers with multimedia tools on a Creativity Platform. A methodology for co-designing educational e-services was applied in both natural (biodiversity) and cultural (music) domains in order that linear knowledge transmission lets place to an iterative know-how sharing approach between teachers and learners. This sign-based methodology serves as a condition for opening the era of Semiotic Web (Web of Signs) over Semantic Web (Web of Things). The objective is to co-create qualitative educational e-services with people based on a more natural/artificial and intelligent approach in the frame of Living labs.

Background In the health care environment, teamwork is paramount, especially when referring to patient safety. We are interested in recent and innovative solutions such as escape games, which is a type of adventure game that may be highly useful as an educational tool, potentially combining good communication skills with successful gamification. They involve teams of 5 to 10 individuals who are “locked” in the same room and must collaborate to solve puzzles while under pressure from a timer. Objective The purpose of this paper was to describe the steps involved in creating and implementing an educational escape game. This tool can then be put into service or further developed by trainers who wish to use it for learning interprofessional collaboration. Therefore, we started with an experience of creating an educational escape game for emergency medicine teams. Methods We chose to develop an educational escape game by using 6 successive steps. First, we built a team. Second, we chose the pedagogical objectives. Third, we gamified (switched from objectives to scenario). Next, we found the human and material resources needed. Thereafter, we designed briefing and debriefing. Lastly, we tested the game. Results By following these 6 steps, we created the first ambulant educational escape game that teaches people, or nurses, doctors, and paramedics, working in emergency medicine to work as a team. Conclusions From a pedagogic point of view, this game may be a good tool for helping people in multidisciplinary fields (medical and paramedical teams) to learn how to work collaboratively and to communicate as a group. Above all, it seems to be an innovative tool that complements medical simulation–based learning and thus consolidates traditional education.

Biodiesel is an eco-friendly, renewable, and potential liquid biofuel mitigating greenhouse gas emissions. Biodiesel has been produced initially from vegetable oils, non-edible oils, and waste oils. However, these feedstocks have several disadvantages such as requirement of land and labor and remain expensive. Similarly, in reference to waste oils, the feedstock content is succinct in supply and unable to meet the demand. Recent studies demonstrated utilization of lignocellulosic substrates for biodiesel production using oleaginous microorganisms. These microbes accumulate higher lipid content under stress conditions, whose lipid composition is similar to vegetable oils. In this paper, feedstocks used for biodiesel production such as vegetable oils, non-edible oils, oleaginous microalgae, fungi, yeast, and bacteria have been illustrated. Thereafter, steps enumerated in biodiesel production from lignocellulosic substrates through pretreatment, saccharification and oleaginous microbe-mediated fermentation, lipid extraction, transesterification, and purification of biodiesel are discussed. Besides, the importance of metabolic engineering in ensuring biofuels and biorefinery and a brief note on integration of liquid biofuels have been included that have significant importance in terms of circular economy aspects. Fil: Chintagunta, Anjani Devi. Vignan’s Foundation for Science, Technology and Research. Department of Biotechnology; India Fil: Zuccaro, Gaetano. Institut National de la Recherche Agronomique; Francia. Università degli Studi di Napoli Federico II; Italia Fil: Kumar, Mahesh. Central Agricultural University; India Fil: Kumar, S. P. Jeevan. Indian Institute of Seed Science; India. Directorate of Floricultural Research; India Fil: Garlapati, Vijay Kumar. Jaypee University of Information Technology; India Fil: Postemsky, Pablo Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Centro de Recursos Naturales Renovables de la Zona Semiárida. Universidad Nacional del Sur. Centro de Recursos Naturales Renovables de la Zona Semiárida; Argentina Fil: Kumar, N. S. Sampath. Vignan’s Foundation for Science, Technology and Research. Department of Biotechnology; India Fil: Chandel, Anuj K.. Universidade de Sao Paulo; Brasil Fil: Simal Gandara, Jesus. Universidad de Vigo; España

Learning how to model a problem described in natural language as a linear program requires students to practice using various and numerous exercises. Moreover, immediate feedback on the validity of their solutions helps a better and faster understanding. In this paper, we present an idea on how students and teachers can automatically evaluate linear programming models. We also describe how this idea was implemented on the learning platform caseine.org and is now used by hundreds of students from various universities.

International audience; Mobile phone camera-based document video scan- ning is an interesting research problem which has entered into a new era with the emergence of widely used, processing capable and motion sensors equipped smartphones. We present our ongoing research on mobile phone camera-based document image mosaic reconstruction method for video scanning of paper documents. In this work, we have optimized the classic keypoint feature descriptor based image registration method, by employing the accelerometer and gyroscope sensor data. Experimental results are evaluated using optical character recognition (OCR) on the reconstructed mosaic from mobile phone camera-based video scanning of paper documents.

International audience; In this paper, the dual-band retrodirective reflector array using Substrate Integrated Waveguide (SIW) and inkjetprinted technologies on paper, for operability around 3.6 GHz and 5.8 GHz is proposed. It offers the versatility of multi-band retrodirective designs potentially covering numerous RFID interrogation, sensing and communication bands.

International audience; Automation throughout history has caused profound changes in employment dynamics. With the advent of the fourth industrial revolution, a new threat may affect employability, asrobots and AI-based processes can now assume tasks considered exclusive to humans. This position paperaims to motivate the study of the effects of AI and automation on employability, extending it into a collaborative network perspective. The problem is firstly observed from a historical perspective. The collaboration aspects are considered through the analysis of two casestudies. Results suggestthata latent element of collaborative networks, complexity, may have effects in terms of employability.

Background When new technology is integrated into a care pathway, it faces resistance due to the changes it introduces into the existing context. To understand the success or failure of digital health innovations, it is necessary to pay attention to the adjustments that users must perform to make them work, by reshaping the context and sometimes by altering the ways in which they perform activities. This adaptation work, most of which remains invisible, constitutes an important factor in the success of innovations and the ways in which they transform care practices. Objective This work aims to present a sociological framework for studying new health technology uses through a qualitative analysis of the different types of tasks and activities that users, both health professionals and patients, must perform to integrate these technologies and make them work in their daily routine. Methods This paper uses a three-part method to structure a theoretical model to study users’ invisible work. The first part of the method includes a thematic literature review, previously published by one of the coauthors, of major sociological studies conducted on digital health innovations integration into existing care organizations and practices. The second part extends this review to introduce definitions and applications of the users’ invisible work concept. The third part consists of producing a theoretical framework to study the concept according to the different contexts and practices of the users. Results The paper proposes four dimensions (organizational, interactional, practical, and experiential), each composed of a set of criteria that allow a comparative analysis of different users’ work according to different health technologies. Conclusions This framework can be applied both as an analytical tool in a research protocol and as an agenda to identify less visible adoption criteria for digital health technologies.

Conference of 7th International Conference on Tests and Proofs, TAP 2013 ; Conference Date: 16 June 2013 Through 20 June 2013; Conference Code:99450; International audience; To help formal verification tools to make their way into industry, they ought to be more widely used in software engineering classes. This tutorial paper serves this purpose and provides a lesson on formal specification and proof of programs with Frama-C, an open-source platform dedicated to analysis of C programs, and acsl, a specification language for C.

Background In the recent decades, the number of apps promoting health behaviors and health-related strategies and interventions has increased alongside the number of smartphone users. Nevertheless, the validity process for measuring and reporting app quality remains unsatisfactory for health professionals and end users and represents a public health concern. The Mobile Application Rating Scale (MARS) is a tool validated and widely used in the scientific literature to evaluate and compare mHealth app functionalities. However, MARS is not adapted to the French culture nor to the language. Objective This study aims to translate, adapt, and validate the equivalent French version of MARS (ie, MARS-F). Methods The original MARS was first translated to French by two independent bilingual scientists, and their common version was blind back-translated twice by two native English speakers, culminating in a final well-established MARS-F. Its comprehensibility was then evaluated by 6 individuals (3 researchers and 3 nonacademics), and the final MARS-F version was created. Two bilingual raters independently completed the evaluation of 63 apps using MARS and MARS-F. Interrater reliability was assessed using intraclass correlation coefficients. In addition, internal consistency and validity of both scales were assessed. Mokken scale analysis was used to investigate the scalability of both MARS and MARS-F. Results MARS-F had a good alignment with the original MARS, with properties comparable between the two scales. The correlation coefficients (r) between the corresponding dimensions of MARS and MARS-F ranged from 0.97 to 0.99. The internal consistencies of the MARS-F dimensions engagement (ω=0.79), functionality (ω=0.79), esthetics (ω=0.78), and information quality (ω=0.61) were acceptable and that for the overall MARS score (ω=0.86) was good. Mokken scale analysis revealed a strong scalability for MARS (Loevinger H=0.37) and a good scalability for MARS-F (H=0.35). Conclusions MARS-F is a valid tool, and it would serve as a crucial aid for researchers, health care professionals, public health authorities, and interested third parties, to assess the quality of mHealth apps in French-speaking countries.

International audience; In recent decades and to deal with the scarcity of fossil fuels, many studies have been developed in order to set up a sustainable biofuel production sector. This new sector must be efficient (high productivity), economically profitable (low production costs and therefore acceptable fuel prices), and ethical (low carbon balance, no competition with food resources). The production of bioethanol is based on the fermentation of reserve sugars, accumulated in the form of starch in microalgae and glycogen in cyanobacteria. The advantage of this bioenergy production route lies in the fact that the post-crop fermentation process is at the industrial stage since it has already been tested for many years for the production of bioethanol from agricultural resources. One of the most cultivated cyanobacteria is Arthrospira (“Spirulina”) and its production is also already at industrial scale. Depending on the cultivation conditions, this cyanobacteria is able to accumulate up to 65% DW (dry weight) of glycogen, making it a feasible feedstock for bioethanol production. The aim of this review is to provide a clear overview of these operating conditions for glycogen accumulation.

International audience; Standard physical pen-and-paper creation and computer graphics tools tend to evolve in separate tracks. In this paper, we propose a new interface, PapARt, that bridges the gap between these two worlds. We developed a system that allow users to visualize, ma- nipulate and edit a 3D scene projected onto a paper sheet. Using multitouch and tangible interfaces, users can directly interact with the 3D scene to prepare their drawings. Then, thanks to the pro- jection of the 3D scene directly on the final surface medium, they can draw using standard tools while relying on the underlying 3D scene. Hence, users benefit from both the power of interactive 3D graphics and fast and easy interaction metaphors, while keeping a direct link with the physical material. PapARt has been tested dur- ing a large scale exhibition for general public. Such an interface, which combines computer-assisted drawing and free form user ex- pressiveness on a standard sheet of paper, opens new perspectives for enhancing user creation.

Background During the COVID-19 pandemic, numerous countries, including China and France, have implemented lockdown measures that have been effective in controlling the epidemic. However, little is known about the impact of these measures on the population as expressed on social media from different cultural contexts. Objective This study aims to assess and compare the evolution of the topics discussed on Chinese and French social media during the COVID-19 lockdown. Methods We extracted posts containing COVID-19–related or lockdown-related keywords in the most commonly used microblogging social media platforms (ie, Weibo in China and Twitter in France) from 1 week before lockdown to the lifting of the lockdown. A topic model was applied independently for three periods (prelockdown, early lockdown, and mid to late lockdown) to assess the evolution of the topics discussed on Chinese and French social media. Results A total of 6395; 23,422; and 141,643 Chinese Weibo messages, and 34,327; 119,919; and 282,965 French tweets were extracted in the prelockdown, early lockdown, and mid to late lockdown periods, respectively, in China and France. Four categories of topics were discussed in a continuously evolving way in all three periods: epidemic news and everyday life, scientific information, public measures, and solidarity and encouragement. The most represented category over all periods in both countries was epidemic news and everyday life. Scientific information was far more discussed on Weibo than in French tweets. Misinformation circulated through social media in both countries; however, it was more concerned with the virus and epidemic in China, whereas it was more concerned with the lockdown measures in France. Regarding public measures, more criticisms were identified in French tweets than on Weibo. Advantages and data privacy concerns regarding tracing apps were also addressed in French tweets. All these differences were explained by the different uses of social media, the different timelines of the epidemic, and the different cultural contexts in these two countries. Conclusions This study is the first to compare the social media content in eastern and western countries during the unprecedented COVID-19 lockdown. Using general COVID-19–related social media data, our results describe common and different public reactions, behaviors, and concerns in China and France, even covering the topics identified in prior studies focusing on specific interests. We believe our study can help characterize country-specific public needs and appropriately address them during an outbreak.

International audience; This study evaluated the properties of bio-coal briquettes made by blending coal with beniseed (sesame seed) stalks in order to determine the optimum composition. The briquettes were produced using a hydraulic compression machine at 5, 10 and 15 bar applied to coal:biomass compositions of 100:0, 80:20, 60:40, 40:60, 20:80 and 0:100% by weight of mixture and particle sizes of 212, 300 and 600 µm. The physical, ultimate and proximate properties of the briquettes were then measured and analyzed. The results indicated that the optimum composition for producing the briquettes lies between 60:40% and 40:60%. These ranges of composition of briquettes had the lowest ignition time of 57.6s, highest percentage volatile matter of 42.7% and low percentage sulphur content of 0.38%. Furthermore, the 40:60% briquettes had the highest mean calorific value of 26.67 MJ/kg. These indicate good potentials for briquettes using coal and beniseed stalks as an alternative energy source while contributing to a friendly environment and wealth generation.

IF=5.578; International audience; Currently, India imports 84% of its total oil needs and aims to bring that down to 67% by 2022. To aim for this, the hunt for sustainable production of non-toxic, renewable, and low-cost alternative fuel sources is the need of the hour. Azolla microphylla plant which grows on the water surfaces can be a potential feedstock for the production of biodiesel. The oil was extracted from the azolla plant by the solvent extraction method. The biodiesel was produced from the azolla oil through the transesterification process. The azolla biodiesel was blended with the diesel in the ratio of 25:75, 50:50, and 75:25 by volume and tested in a diesel engine at the part and maximum load conditions. The engine characteristics of the azolla biodiesel blends, neat azolla biodiesel, and sole diesel were compared. The result showed that brake thermal efficiency (BTE) was highest for the B25 (25% azolla biodiesel, 75% diesel) blend with a value of 25.9% which was less than sole diesel, whose BTE value was 26.8% at maximum load. The high viscous nature of biodiesel blends results in inferior evaporation and improper air–fuel mixing process. Due to this, the B25 blend gave the least CO, HC, and smoke emissions among the test blends, but slightly higher than that of neat diesel. The NO emission for diesel was 852 ppm, 882 ppm, and it is 806 ppm, 824 ppm for B25 at the part and maximum load respectively. The peak cylinder pressure for diesel and B25 blend was 50.8 bar and 49.4 bar respectively at maximum load.

To develop quality software and systems, both functional and non-functional requirements need to be taken into account at the highest level of abstraction. However the issue of relationships between non-functional requirements and functional requirements has been rarely addressed. In this article, we outline an extension of the SysML requirements meta-model with relevant concepts of commonly used goal-oriented requirements engineering approaches. The main contribution of our approach is to analyse and describe the impact of non-functional requirements on functional requirements.

We deal with the 3D reconstruction of deformed paperlike surfaces given a template and a single perspective image, for which the internal camera parameters are known. The general problem is ill-posed. We show that when the surface rulings are parallel the problem is well-posed. Given a procedure to recover the rulings direction, this particular problem is equivalent to the reconstruction of a 2D curve seen from a set of ID camera pairs given a ID template. Paper can be physically modeled by exploiting local properties. This allows us to formulate the reconstruction problem by non linear variational optimization. We provide experimental results which validate our approach on simulated and real data.

International audience; Two kinds of bibliographic tools are used to retrieve scientific publications and make them available online. For one kind, access is free as they store information made publicly available online. For the other kind, access fees are required as they are compiled on information provided by the major publishers of scientific literature. The former can easily be interfered with, but it is generally assumed that the latter guarantee the integrity of the data they sell. Unfortunately, duplicate and fake publications are appearing in scientific conferences and, as a result, in the bibliographic services. We demonstrate a software method of detecting these duplicate and fake publications. Both the free services (such as Google Scholar and DBLP) and the charged-for services (such as IEEE Xplore) accept and index these publications.

In our research, we study the case of a pulp and paper producer who decides to establish a partnership with one buyer. Using two different types of relationship, namely a traditional system without any collaboration scheme and Collaborative Planning, Forecasting and Replenishment, we develop decision models describing the producer and the buyer planning processes. We also identify which approach is more profitable for each actor as well as for the network, based on real costs and parameters obtained from the industrial case. We then test how different incentives can improve the traditional system and provide higher gains for each partner. Our results show that using incentives increases the system's profit by up to 4% if parameters are well defined.

International audience; A proper situation management system is one of the keys to success on the battlefield. It strongly relies on data collection, fusion and interpretation. Unmanned Aerial Vehicles (UAVs) are becoming a major collection platform, but there is almost no collaborative intelligence in these systems. We claim that a swarm of small UAVs connected together that could make cooperative decisions in an autonomous way (without requiring any intervention from the ground) would be a major contributor to the information superiority. In this paper we present our vision of this approach and the research project that we are running to achieve an operational system. It deals with levels 1, 2 and 4 of the DoD JDL definition of information fusion. This is a position paper describing a work in progress.

International audience; The COVID-19 crisis has turned the world upside-down and many aspects of our social and daily lives need to be adapted. In this position paper, we argue that data management techniques for mobile computing scenarios also have to be extended for them to be useful and suited to the new situation. In particular, the concept of social distancing, which has been shown to be one of the most effective measures to cope with the virus expansion, should be incorporated as a natural component of many information services and applications for mobile users. We illustrate this idea with two example use cases: mobile recommender systems and information services for drivers. We outline current challenges and some ideas for future work.

Summarizing video content is an important task in many applications. This task can be defined as the computation of the ordered list of actions present in a video. Such a list could be extracted using action detection algorithms. However, it is not necessary to determine the temporal boundaries of actions to know their existence. Moreover, localizing precise boundaries usually requires dense video analysis to be effective. In this work, we propose to directly compute this ordered list by sparsely browsing the video and selecting one frame per action instance, task known as action spotting in literature. To do this, we propose ActionSpotter, a spotting algorithm that takes advantage of Deep Reinforcement Learning to efficiently spot actions while adapting its video browsing speed, without additional supervision. Experiments performed on datasets THUMOS14 and ActivityNet show that our framework outperforms state of the art detection methods. In particular, the spotting mean Average Precision on THUMOS14 is significantly improved from 59.7% to 65.6% while skipping 23% of video.