Search

National audience; The recent multiplication of autonomous visiting devices in cities of art and history calls for a conceptual framework that makes it possible to reverse design these devices, to identify the visiting strategies to which they respond, to map the strategies that are widely instrumented and those that are more neglected, and thus to open up avenues for the design of complementary devices. Integrating the results of the literature on the diversity of visiting strategies, our conceptual framework is built around five functionalities that are combined to respond to these strategies: (1) discovering an item of interest, (2) accessing the related information, (3) receiving what is transmitted, (4) engaging, (5) reasoning. Each functionality is then broken down into “Form”, then “Conceptual approach” and finally “Implementation”. The use of this framework in reverse design and design is illustrated by the autonomous visit devices of the city of Troyes and its stained glass.; La multiplication récente des dispositifs de visite autonome dans les villes d'art et d'histoire nécessite un cadre conceptuel permettant de rétro-concevoir ces dispositifs, d'identifier à quelles stratégies de visite elles répondent, de cartographier les stratégies qui sont largement instrumentées et celles qui ont été plus délaissées, et ainsi d'ouvrir des pistes pour la conception de dispositifs complémentaires. Intégrant les résultats de la littérature sur la diversité des stratégies de visite, notre cadre conceptuel est construit autour de cinq fonctionnalités à combiner pour répondre à ces stratégies : (1) découvrir un élément d‘intérêt, (2) accéder à l’information associée, (3) accueillir ce qui est transmis, (4) s'engager, (5) raisonner. Chaque fonctionnalité se décline en « Forme », puis en « Approche conceptuelle », et enfin en « Implémentation ». L'usage de ce cadre en rétro-conception et en conception est illustré sur les dispositifs de visite autonome de la ville de Troyes et de ses vitraux.

International audience; Following the trend towards open data, various cultural organisations offer information about their collections. However, these knowledge bases are not used to accompany a visit to historical monuments. We think that a possible explanation for this observation lies in the distinction between availability and accessibility of the knowledge offered: although these knowledge bases make this knowledge available, it is difficult for non-experts to make use of it and make it their own. Rather than a semantic approach to visiting based on description, we advocate an active and semiotic approach based on comparison. We have identi- fied four challenges in applying this approach to church stained-glass windows. The first two challenges are to link the physical space of the building and the stained glass with the documentary space so that visitors can move between the two. Visitors also need to understand and use 'reading keys' to match a represen- tation with its subject. Visitors should afterward finally be able to use their knowledge and skills on other visits. Through interviews and observations, we have iteratively designed paper and digital prototypes to meet these challenges.

International audience; The progress of science and technology has considerably increased the quality of life - especially the material standard of living - (e.g. disappearance of famines, increase in life expectancy) On the other hand, climate change, reduction of biodiversity, decrease of natural resources, and increase of environmental risks are some of the consequences of this human activities. Addressing these new challenges will require holistic comprehension and actionable approaches. The mitigation of these consequences requires effective responses in terms of transition. In this context, engineering and design students need time but also adapted curricula focused on sustainability and eco design concepts to support evolution of their skills, their knowledge and their culture. This article discusses the integration of a strong sustainability knowledge within the ideation process through a pedagogical experience, in order to develop new knowledge-based approaches, methodologies and tools

International audience; The Reverse JPEG Compatibility Attack can be used for steganalysis of JPEG images compressed with Quality Factor 100 by detecting increased variance of decompression rounding errors. In this work, we point out the dangers associated with this attack by showing that in an uncontrolled environment, the variance can be elevated simply by using a different JPEG compressor. If not careful, the steganalyst can wrongly misclassify cover images. In order to deal with the diversity associated to the devices or softwares generating JPEGs, we propose in this paper to build a deep learning detector trained on a huge dataset of downloaded images. Experimental evaluation shows that such a detector can provide operational false alarms as small as 10^{−4} , while still correctly classifying 90% of stego images. Furthermore, it is shown that this performance is directly applicable to other image datasets. As a side product, we indicate that the attack is not applicable to images developed with a specific JPEG compressor based on the trunc quantization function.

COVID’19 crisis management revealed several relationships problems due to missed collaboration between healthcare actors and socio-economic organizations. In fact, these actors didn’t work usually together indeed their interdependencies tasks. The government Healthcare authority asks to identify these types of problems. In this paper, first results of interviews with these actors are presented.This experience feedback formalization is focused on the influence of relationships between these actors and the consequences on the large sanitary crisis management as COVID’19 one.

International audience

International audience; We are interested in how issues relating to privacy and confidentiality are incorporated when using interactive services. Two smart home services based on the use of data from "smart" electricity meters have been evaluated to establish the guarantees and forms of interaction necessary for their appropriation. We show that, given the contextual, dynamic and social nature of privacy, normative responses such as those promoted by the regulator (predefinition of sensitive data, prior to use consent, privacy as the default setting) are insufficient. As mentioned in previous works, the design choices must promote as components of the systems the user control of data throughout the interaction, as well as transparency of the data, processing and actors. However, our results highlight an important dimension not previously addressed: the need to adopt a temporal and diachronic vision of privacy and to broaden the question of interaction beyond use by considering the life cycle of the service and of the relationship with its suppliers.; Nous nous intéressons à la façon dont les questions de vie privée et de sa préservation s'instancient dans l'utilisation de services interactifs. Deux services relatifs à l'habitat et basés sur l'exploitation de données issues de compteurs électriques « intelligents » ont été évalués pour établir les garanties et formes d'interactions nécessaires à leur appropriation. Nous montrons que, compte tenu de la nature contextuelle, dynamique et sociale de la privacy, les réponses normatives telles que celles promues par le législateur (prédéfinition des données sensibles, consentement a priori, privacy intégrée seulement au stade de la conception du système) sont insuffisantes. Comme cela a pu être évoqué dans des travaux antérieurs, les choix de conception doivent favoriser la maîtrise des données dans l'interaction en proposant des moyens d'actions et une transparence des données, traitements et acteurs, en tant que composantes des systèmes. Toutefois, nos résultats mettent en exergue une dimension importante non traitée jusqu'alors : la nécessité d'adopter une vision temporelle et diachronique de la privacy, pour élargir la question de l'interaction au-delà de l'utilisation en considérant la durée de vie du service et de la relation avec ses fournisseurs.

National audience

IHM'23 - 34e Conférence Internationale Francophone sur l'Interaction Humain-MachineAFIHM, Université de Technologie de Troyes; The attempt to link digital and ecological transitions is becoming increasingly present in scientific papers. Since the early 2000s, several new fields of research have developed, covering a very broad spectrum of domains, ranging from environmental computing to the sustainability of human-machine interactions. The diversity of research in these domains has allowed to explore different ways of understanding computing in relation to the ecological transition: at the technical level, at the interaction level, at the impact on social structures, and so on. This article aims at describing to what extent Sustainable HCI (SHCI) needs to deal with alignments between HCI and stakeholders’ values in the sustainable transition of socio-technical systems.; La tentative de lier les transitions numériques et écologiques est de plus en plus présente dans les articles scientifiques. Depuis le début des années 2000, plusieurs nouveaux champs de recherche se sont développés, couvrant un très large spectre de domaines, allant de l'informatique environnementale à la soutenabilité des interactions humain-machine. La diversité des recherches dans ces domaines a permis d'explorer différentes manières de comprendre l'informatique en relation avec la transition écologique : au niveau technique, au niveau des interactions, au niveau de l'impact sur les structures sociales, etc. Cet article vise à décrire dans quelle mesure l’interaction humain-machine soutenable (IHMS) doit traiter des alignements entre l'informatique et les valeurs des parties prenantes dans la transition soutenable des systèmes socio-techniques.

Effective capture of polar volatile organic compounds under environmental conditions is a challenge owing to the adsorption competition between polar volatile organic compounds and water.

International audience; The automated conveyor system, as the core component in the modern manufacturing world, has gained lots of attention from researchers. To optimize the operation of the conveyor system, range-inspection control (RIC) has been considered an efficient strategy to bring this conventional technology to an intelligent level. Various algorithms have been put into use to achieve optimal control. However, the current methodologies are only focusing on control optimization, not scaled into the smart manufacturing framework. The schema of alignment and corporation between the physical and virtual spaces for the system remains an important problem. Therefore, the work in this article aims for an effective framework of implementation between the physical and virtual stations in an automated conveyor system. Since increasingly more application scenarios rely on the digital twin (DT) technology to realize the integration of physical and virtual systems, we proposed the DT automated conveyor system (DT-ACS) that constructs the road map to implement the RIC-based conveyor system under the background of a smart factory. Besides, profit-sharing-based deep Q-networks (PDQNs) have been proposed to cope with the RIC optimization problem. The robustness and efficiency of the proposed PDQN were evaluated via sets of experiments. The discussion and conclusion are presented at last accordingly.

National audience; Jusqu'à présent, la recherche sur la soutenabilité s’est centrée principalement au niveau macro sur les acteurs institutionnels et les efforts de changement systémique. Au niveau micro, les chercheurs ont étudié le choix des produits par les consommateurs et leur élimination après usage [1].Le projet D-TechnoSS, financé par l'Agence nationale de la recherche (ANR) (ANR-20-CE10-0006), vise à développer une meilleure compréhension des mécanismes de prise de conscience et de changements des comportements associés à l’adoption de démarches de conception participatives dans une posture de soutenabilité forte.Le projet D-TechnoSS vise à explorer la proposition d’une intégration forte entre société et système de production. Dans le cadre du projet, il sera question de favoriser la prise de conscience des défis sociétaux, de faciliter le changement de comportements peu soutenables et d’accompagner le système productif dans on retour au seuil des limites planétaires. La méthode de recherche est basée sur une approche expérimentale, pour proposer un modèle d’évaluation de la soutenabilité dans une posture de soutenabilité forte.Le projet D-TechnoSS a donc pour ambition de mieux comprendre et accompagner les transitions sociales ainsi que l’adaptation nécessaire du système de production et des méthodes de conception.

International audience; Objectives: Convolutional neural networks (CNNs) have established state-of-the-art performance in computer vision tasks such as object detection and segmentation. One of the major remaining challenges concerns their ability to capture consistent spatial and anatomically plausible attributes in medical image segmentation. To address this issue, many works advocate to integrate prior information at the level of the loss function. However, prior-based losses often suffer from local solutions and training instability. The CoordConv layers are extensions of convolutional neural network wherein convolution is conditioned on spatial coordinates. The objective of this paper is to investigate CoordConv as a proficient substitute to convolutional layers for medical image segmentation tasks when trained under prior-based losses.Methods: This work introduces CoordConv-Unet which is a novel structure that can be used to accommodate training under anatomical prior losses. The proposed architecture demonstrates a dual role relative to prior constrained CNN learning: it either demonstrates a regularizing role that stabilizes learning while maintaining system performance, or improves system performance by allowing the learning to be more stable and to evade local minima.Results: To validate the performance of the proposed model, experiments are conducted on two well-known public datasets from the Decathlon challenge: a mono-modal MRI dataset dedicated to segmentation of the left atrium, and a CT image dataset whose objective is to segment the spleen, an organ characterized with varying size and mild convexity issues.Conclusion: Results show that, despite the inadequacy of CoordConv when trained with the regular dice baseline loss, the proposed CoordConv-Unet structure can improve significantly model performance when trained under anatomically constrained prior losses.

International audience

Retailers with short lifetime products in stock always face a problem of whether new products should be ordered when on-hand products partially decay and how to deal with the old products if a new batch is ordered. In this article, we consider the sales of a perishable product with a fixed short lifetime in two shelves, where new items of the product in a regular shelf are sold in a preset normal price, and old items in a markdown (discount) shelf are sold in a discounted price. We study the problem of the joint ordering of new items and pricing of old items and propose a joint ordering and markdown policy when the demand of the product depends on its price, and freshness as well as unsatisfied demand is lost. First, we formulate a one-period model, in which the present shelf ages of items in the two shelves are considered and use the Karush–Kuhn–Tucker condition to analytically obtain the optimal solution of the joint ordering and markdown problem. Second, numerical experiments are conducted to evaluate the performance of the two-shelf policy when the optimal solution of the one-period model is applied to the multiperiod problem in the form of a myopic policy. The results show that the proposed two-shelf joint ordering and markdown policy for perishable products performs better than the traditional one-shelf policy. Note to Practitioners —In this article, we develop a joint ordering and markdown policy for perishable products deployed on two shelves: a regular shelf for fresh products and a markdown shelf for less fresh products. Although the closed-form policy is obtained for the one-period situation with deterministic demand, it is not difficult to extend it to the multiperiod case with random demand. This article not only reveals the underlying reason of employing both regular shelf and markdown shelf in the practice of retailing management for perishable products but also proposes an easy-to-implement ordering and markdown policy, which will bring higher profit than the traditional one-shelf policy and will improve the performance of managing a perishable products retailing system.

This study reports research on Nickel etch mask used for deep plasma etching of silicon carbide (SiC) substrates, aiming to fabricate power integrated devices. Ni masks with significant thicknesses are requested when performing deep etches of SiC, which are less compatible with classic thin film physical vapor deposition (PVD) methods. Uniform and smooth plasma etched surfaces of SiC were obtained without micromasking phenomena upon using Ni masks deposed by electroplating. Detailed here is this Ni masks based technology we developed beyond its limitation, in order to obtain a high-etched thickness of silicon carbide substrates.

The objective of this paper is to discuss the problem of maintenance modelling and optimisation for a deteriorating Photo- voltaic panel system. In this paper, we model the dust accumulation process as PV panels’ as the main degradation cause considering the wind conditions as covariates. The dust accumulation process is mod- eled by a non-homogeneous compound Poisson process (NHCPP). The covariates process is assumed to be a time-homogenous Markov chain with finite state space. A model similar to the proportional hazards model is used to show the influence of covariates on the degradation process. In the framework of the system under consideration, an appropriate maintenance policy which minimises the long run average maintenance cost and maximises the long run average profits is derived. Numerical implementations are presented to illustrate the performance of the proposed model.

International audience; Value Analysis (VA) is a collaborative method that could be used to make a decision in the early phase of complex projects. In this framework, Stakeholders are involved into the process of decision-making and project success is facilitated. Systeme Architechting (SA) is a set of processes used for the conceptual phase of the design of complex systems while System Engineering (SE) is the set of processes used for the design phase of the system. The difference resides in the information on which the decision-making is based: it is very abstract in the architecting phase while it is materialized in the engineering phase. In complex projects, Stakeholders are multiple and carry specific technical, social and environmental expectations that define their perceived Value of the project. The aim of this paper is to demonstrate that VA and SA are two complementary approaches to collect and analyse Stakeholder needs in a complex project. The article presents an analysis of the literature review on VA and SA / SE, which shows the complementarity of these approaches to involve Stakeholders in the upstream phases of the design of complex systems. Based on this analysis, an illustration case is proposed to show how to integrate VA into SA to understand the needs of Stakeholders. The article concludes that the two methods VA and SA can be combined to analyze and would allow following several dimensions of Value (economic, social and environmental) within a complex project.

International audience; In this paper, we propose a novel zoning-based tracking technique that combines the sensors' mobility with a WiFi-based observation model in the belief functions framework to track the sensors in real time. The next possible destinations of the sensors are predicted, leading to a mobility model. The belief functions framework is used to propagate the previous step evidence till the current one. The mobility of the sensors, along with information from the network, are used to obtain an accurate estimation of their position. The contributions of this paper are two-fold. Firstly, it proposes new mobility models based on the transition between zones and hidden Markov models, to generate evidence on the zones of the sensors without the use of inertial measurement units. Secondly, it explores the fusion of evidence generated by the mobility models on one hand, and the observation model on the other hand. The efficiency of the proposed method is demonstrated through experiments conducted on real data in two experimental scenarios.

Implant-related follow up complications resulting from poor implant integration, delamination, chipping, mechanical instability, inflammation or graft-vs-host reaction may lead to low patient tolerance, prolonged care and sometimes leading to a second surgery. Hence, there is an urgent need for developing biomaterials which will help to overcome the above compatibility problems. Ti based alloys have been widely used for biomedical applications, due to their excellent properties, such as low modulus, high biocompatibility and high corrosion resistance. In order to further improve the physical, mechanical and tribological properties of these alloys, microstructural modification is often required. Hence, this study aims to develop and evaluate the structural and tribological behavior of Hot Isostatic Pressed (HIPed) and sintered Ti-6Al-7Nb samples containing niobium, which is less toxic and less expensive as compared to the usual alloying element, vanadium (Ti-6Al-4 V). The Ti-6Al-7Nb alloys were fabricated by using nanoparticle powders milled for different durations (2, 6, 12 and 18 h) to evaluate the effect of milling time on the morphological and structural properties. Friction and wear tests were carried out on the (HIPed) and finally sintered Ti-6Al-7Nb alloy samples, to evaluate their tribological properties under different applied loads (2, 8 and 16 N), with an alumina α-Al2O3 ball as a counter face using an oscillating tribometer. The physical characterization of the nanopowders formed using different milling times indicated that the particle and crystallite size continually decreased with increasing milling time, while the microstrain increased. It is observed that the friction coefficient and wear rate for the samples prepared by powders milled for 18 h and tested under 2 N were lowest with values of 0.25 and 1.51 × 10−2 μm3∙N-1 μm-1, respectively compared to other milled samples. This improvement in tribological properties is attributed to the grain refinement at high milling times. The antibacterial evaluation of the fabricated alloys showed an improvement in antibacterial performance of the samples milled at 18 h compared to the other milling times.

International audience; Surface plasmon resonance can be used to manipulate light at the nanoscale. It was used here to trigger photopolymerization of an atom transfer radical polymerization (ATRP) molecular system, leading to a thin polymer shell at the surface of the metal nanostructure. The polymerization can be reactivated from the first polymer shell to covalently graft a second monomer layer with precise control over the thickness at the nanometric scale, depending on the photonic parameters. This route can be applied to different nanoobjects and allows an anisotropic surface modification in agreement with the spatial localization of the enhanced electromagnetic field near the nanostructure. This new route opens the door towards the preparation of multifunctional hybrid metal/polymer nanostructures.

This study aims at evaluating the effects of surface mechanical attrition treatment (SMAT) on mechanical properties and corrosion resistance of NiCrBSi coatings deposited by high-velocity oxygen-fuel (HVOF) spraying. The as-deposited coating has a typical HVOF-sprayed morphology with unmelted and deformed particles, associated with voids and porosities, whereas after SMAT, the affected zone morphology is more compact, without porosity or crack. The thickness of the affected zone varies from about 30 to 100 µm according to the SMAT parameters. The surface roughness is much lower for SMAT-treated coatings (from Ra = 6.8 µm to a Ra ≈ 2.3 µm). Whatever the SMAT parameters used in this work, the treated materials are harder compared to the as-deposited coating (from 6.6 to 7.6 GPa). They exhibit compressive residual stresses around − 360 MPa, while tensile stresses with an average value of 180 MPa were evaluated for the as-deposited coating. In addition, the treated coatings show better wear resistance as well as better corrosion resistance in a 3 wt.% NaCl solution. The better compromise in terms of SMAT parameters corresponds to amplitude of vibration of the SMAT sonotrode of 15 μm and SMAT duration of 810 s.

International audience; This paper considers dynamic systems widely used in industry for which the behavior can be approximated to a second order differential equation. The components of such a system suffer from random faults and failures due to wear, age or usage. These events impact the dynamic behavior which is interpreted as a modification of the initial differential equation with random coefficients. At given times, the system is solicited and its output – the only source of information – is measured to infer the position of equation roots in the complex plane. The Euclidian distance between the current and initial positions of a root is proposed as a new indicator reflecting the gradual deterioration of system performance. Such an indicator presents stochastic trajectories in time according to the random evolution of the root location in complex plane. More especially, these trajectories can be modeled by an univariate non-linear diffusion process if underlying degradation sources are assumed to be homogeneous Gamma processes. Based on this model, the system remaining useful lifetime is assessed. Two predictive maintenance policies are also designed showing the feasibility to easily maintain dynamic systems solely on the system output.

In this paper, an advanced model formulated in the framework of non-associative plasticity is used to accurately predict the springback of advanced high strength steels material. The proposed model strongly couples the isotropic ductile damage to the phenomena a combined nonlinear isotropic and kinematic hardening, initial anisotropic plastic flow and induced anisotropies due to the distortion of the yield function and the plastic potential respectively. For the application, the simulations were conducted for U-draw bending of as-received DP 780 steel sheet proposed by Numisheet’2011 Benchmark. The proposed model was able to capture adequately the Bauschinger effect, transient hardening (distortional) and ductile damage-induced softening. The results have shown that the distortion of yield function affect significantly the stress distribution especially in the sidewall curl during the forming stage thereby explaining observed variations in springback. For full coupling with isotropic ductile damage, the predicted angular springback was found in good agreement with experimental measurements and the sidewall curl was significantly improved in comparison to the simple use of hardening models. This means that isotropic ductile damage and its effect on the other physical phenomena require special attention in order to take benefit when designing newly developed advanced high strength steels (AHSS) parts for automotive and aerospace industries.

International audience; Monolithic reactors play an important role in the integrated approach to environmental protection, especially in air pollution abatement. Mathematical modelling of catalytic reactors has become a key procedure in the design, development and optimisation of many industrial processes. The objective of this study was the modelling and simulation of the catalytic oxidation of volatile organic compounds by a commercial V2O5-WO3/TiO2 honeycomb catalyst, specific for the SCR-DeNOx process in high-dust flue gases from stationary incineration. The mathematical model is developed for the numerical simulation of a tubular plug flow reactor, using mass balance equation to predict results for benzene conversion under isothermal conditions.

International audience; Chemical vapour deposition (CVD) is an important technique that uses volatile precursors to produce thin film deposits on an exposed substrate, having the capability to generate different types of nanostructures (e.g. nanoparticles, nanotubes, nanofibers or nanocomposites) as catalytic materials. The environmental hazard of volatile organic compounds (VOCs) requires efficient methods to reduce their emission into the atmosphere, due to their high potential to cause severe health issues, along with their extended spread in the environment. Catalytic combustion proves to be one of the most effective means for the abatement of VOCs, employing different catalysts, such as noble metals or non-noble metal oxides, to facilitate the oxidation process of the pollutants. These catalysts can be prepared through various methods as multiple steps wet processes or CVD techniques, indicating the superiority of the CVD-prepared catalysts compared to those prepared using the former type of process, due to the ability to achieve high dispersion of the active material, together with enhanced textural and morphological properties. This paper aims to present the various CVD techniques employed in the fabrication of different catalysts with the possibility of generating materials at nano-scale for use in numerous reactions, mostly in combustion process for VOCs decomposition.

International audience; The integration of upgrading strategies (UPS) as part of the livelihood strategies of small farmers is vital for enhancing their food systems. The success of the UPS implementation largely relies on the interactions among key actors. Understanding the complex social realities of farmers is essential for adapting strategies to the local context. Therefore, the objective of this study is to determine the impact of UPS on the livelihood of participants in two case study areas in Tanzania. We used a mixed-method approach to understand the relations between, roles, and motivations of relevant actors in the participatory implementation of their UPS using the Net-Map tool for social network analysis and focus group discussions. Our results reveal why the implementation of UPS improved people´s livelihoods and allowed us to derive some success factors. Motivations for participating in a UPS group differed to some extent among all UPS groups and all types of actors. Based on our results, we found that UPS allow participants to enhance their social networks within their communities and develop skills that improve their livelihood strategies , resulting in more diverse livelihood outcomes. This research provides a knowledge base for UPS considerations and other participatory actions with local subsistence stakeholders. ARTICLE HISTORY

International audience; Homeotropic alignment of liquid crystals (LCs) is one of the key modes used in commercial liquid crystal displays (LCDs) due to its advantages, such as high contrast ratios and fast response speed. Here, we report stable homeotropic LC alignment with a small pretilt angle in a nematic, negative LC host doped with additives including self-aligning agents, photoresponsive azo dyes, and reactive mesogen via an in situ self-assembled, dual-wavelength photoalignment approach. The underlying mechanism of stable, pretilted homeotropic LC alignment was further analyzed in detail. The achieved pretilted homeotropic LC cells are very stable against heat and UV light exposure and demonstrate excellent electro-optical characteristics. The experimental results show that such a noncontact, simple homeotropic alignment technique has big potential in many applications, such as high-quality LCDs, spatial light modulators, and other optoelectronic devices.

International audience; Whichever the application field, every material forming process generates residual stresses on the surface. While they are likely to enhance the aimed properties of the final mechanical part, these stresses may also drastically reduce them and result in early failures. Therefore, understanding the residual stress state remains a major challenge when coating complex parts, especially as most characterization methods at the microscopic scale involve specific sample preparation procedures which may affect the residual stresses field. This work investigates the residual stress state that exists in chromium oxide coatings deposited via Atmospheric Plasma Spray (APS), using two pioneering techniques featuring high spatial resolution: Scanning Microwave Microscopy and Raman Micro-Spectroscopy. The first technique combines the measurement of microwave electromagnetic capacities of a Vector Network Analyzer with the subnanometric resolution of an Atomic Force Microscope: it thus enables performing depth investigations at very accurately defined positions of the probe on the surface. The second technique relies on the principle of photons inelastic scattering and involves a laser beam aiming at the material sample: it allows a fine characterization of the microstructure as well as defects and stresses detection via molecular vibratory signatures. The investigation scale is limited here to a few cubic micrometers. Due to the highly localized scales of our investigations, which also depend on the device, the objective of our procedure required that the comparison should be made not on individual points but on definite mapped areas, every spot being analyzed and post-treated one after another, with optimum measuring parameters. Results have been correlated with XRD measurements to cross-check the average amount of stress observed over a wider area.

International audience; With the development of monitoring equipment, research on condition-based maintenance (CBM) is rapidly growing. CBM optimization aims to find an optimal CBM policy which minimizes the average cost of the system over a specified duration of time. This paper proposes a dynamic auto-adaptive predictive maintenance policy for single-unit systems whose gradual deterioration is governed by an increasing stochastic process. The parameters of the degradation process are assumed to be unknown and Bayes' theorem is used to update the prior information. The time interval between two successive inspections is scheduled based on the remaining useful life (RUL) of the system and is updated along with the degradation parameters. A procedure is proposed to dynamically adapt the maintenance decision variables accordingly. Finally, different possible maintenance policies are considered and compared to illustrate their performance.

Objectives According to the material flow analysis, the domestic flow of trichloroethylene with the highest emission among carcinogens in group 1 was determined. The purpose of this study is to provide basic data for efficient chemical management and establish measures to reduce emissions. Methods In this study, the material flow analysis of trichloroethylene was analyzed in Korea in 2014. The material flow chart was presented using STAN 2.6 software. The flow of trichloroethylene by region and industry was analyzed to identify the characteristics of each flow, and the emission reduction method was presented. Results and Discussion Trichloroethylene was used up to 79.8% in the Seoul metropolitan area, 45.6% in the manufacturing of other machinery and equipment, and 29.4% in the manufacturing of fabricated metal products except machinery and furniture. Trichloroethylene was emitted 42.0% in the manufacturing of rubber and plastics products and 26.8% in the manufacturing of primary metals. The analysis of emissions by company size resulted in 3.9% of total emissions from large companies, 61.6% from mid-sized companies, and 34.5% from small-sized companies. Trichloroethylene was used in various industries and regions, with higher emissions compared to its use.mplement duties in the emission reduction plan, and consider emission reduction incentives. Conclusions Trichloroethylene has been emitted in large quantities relative to its usage. The study found that the management of chemicals in small businesses was insufficient. This result of the material flow analysis is used as basic data to reduce emissions of chemicals. The result of the study helps to recognize the risk of chemicals and suggest alternative materials, introduce inter-company information and expert exchange system, introduce a total amount of carcinogens emission system, implement duties in the emission reduction plan, and consider emission reduction incentives. In addition, measures to improve risk are proposed to establish risk-based database.

International audience; Our paper aims to provide elements of reflection on the spatial and territorial dimensions in circular economy processes and to question their contribution to a sustainable territorial development. We start by examining the territorial roots of the major circular economy strategies defined by the French public authorities and devote a special place to industrial and territorial ecology, which shows a stronger interest in the spatial dimensions of circular processes. In the second part, we question the circular economy’s actual capacity to contribute to the sustainable development of society as a whole and to its implementation at the local level: after proposing a definition of sustainable territorial development, we assess the various existing strategies based on the principles thus defined.; L’objectif de cet article est de fournir des éléments de réflexion sur la place de l’espace et la dimension territoriale dans les processus d’économie circulaire ainsi que d’interroger leur contribution au développement durable des territoires. Nous commençons par examiner les racines territoriales des grandes stratégies d’économie circulaire définies par les pouvoirs publics français en faisant une place particulière à l’écologie industrielle et territoriale, qui manifeste un intérêt plus fort pour les dimensions spatiales des processus circulaires. Dans une seconde partie, nous interrogeons la capacité réelle de l’économie circulaire à contribuer au développement durable de la société dans son ensemble et à sa mise en action au niveau local : après avoir proposé une définition du développement territorial durable, nous procédons à un examen des différentes stratégies en cours fondées sur les principes ainsi définis.

The question of frame-indifference of the thermomechanical models has to be addressed to deal correctly with the behavior of matter undergoing finite transformations. In this work, we propose to test a spacetime formalism to investigate the benefits of the covariance principle for application to covariant modeling and numerical simulations for finite transformations. Several models especially for heat conduction are proposed following this framework and next compared to existing models. This article also investigates numerical simulations using the heat equation with two different thermal dissipative models for heat conduction, without thermomechanical couplings. The numerical comparison between the spacetime thermal models derived in this work and the corresponding Newtonian thermal models, which adds the time as a discretized variable, is also performed through an example to investigate their advantages and drawbacks.

International audience; In this work, two copper metal matrix composites (MMCs) reinforced with 20 wt.% of Ti(C,N) or Ti2AlN particles were studied. The reinforcement particles were synthesized by flash sintering under 2 bar nitrogen atmosphere causing an SHS reaction ignited by electrical current. This reaction led to produce TiC0.7N0.3 solid solution for the MMC1 reinforcement and Ti2AlN, TiN, and Ti3Al titanium aluminide for the MMC2 reinforcement. Both MMCs were densified by liquid phase sintering. The structural characterization was performed by XRD analysis while the morphology and chemical element distribution of both MMCs were analyzed by SEM and EDS. The structure of the two MMCs was relatively dense and showed good wettability. The mechanical and tribological behavior of MMCs evaluated by nanoindentation and wear testing reveals that the addition of 20 wt.% of reinforcement considerably improves the properties of copper matrix. Indeed, the MMC1 proved to be 3 times harder and 10 times more wear-resistant than the MMC2 composite.

The wind energy market is in continuous development since the last decade. This market accounts more than 600 GW of installed wind turbines in 2018, with 14 GW of onshore wind turbines installed in France. With the new Act of 17 August 2015 on energy transition for green growth, France committed fully to energy transformation, with an objective of national renewable energy share of 35% in 2030. Thus, incentives and many provisions were applied to enhance public and private investments in mature renewable energy sources. Within these energy sources, the wind energy market gets a new twist in pricing policies and new actors have emerged. The purpose of this paper is to describe the current state of art of pricing policies and describe the role of the industry’s recent actors (wind farm managers and manufacturers, aggregators, CRE…). These policies are then discussed to outline their opportunities and challenges in the French wind energy market. Keywords: Aggregator, France, Power purchase agreement, Pricing policy, Wind energy

Objective : In this study, we proposed the concept of the particulate matter footprint (PM Footprint) and assessed the PM Footprint in transportation modes (road, rail, and water transportation). In addition, we assessed the contribution of secondary particulate matter formation gas emissions, which contribute to particulate matter formation.Method : To calculate the PM Footprint in the transportation sector, the ReCiPe life cycle impact assessment method in life cycle assessment (LCA) was used. For the PM Footprint of each transportation mode, the life cycle inventory data were multiplied by the characterization factors of PM10, PM2.5 and secondary particulate matter formation emissions such as NOx, SOx, NH3. The PM Footprint values were shown in kg PM2.5 eqv. value.Results and Discussion : The road transportation (trucks) had a much higher PM Footprint value than rail and water transportation in tkm unit based. In the road transportation mode, small size truck such as 3.5 tons (1.37E-03 kg PM2.5 eqv./tkm), 3.51~5 tons (9.65E-04 kg PM2.5 eqv./tkm), 1.25 tons (8.38E-04 kg PM2.5 eqv./tkm), and 1 ton (7.83E-04 kg PM2.5 eqv./tkm) had higher PM Footprint value than big size trucks. In the rail transportation mode, the diesel rail transportation had the highest PM Footprint value, followed by electric + diesel rail transportation and electric rail transportation. In the water transportation mode, the tanker LNG_100 dwt had the highest PM Footprint value, followed by ro-ro ship coastal, and tanker coastal 500~20,000 dwt. The secondary particulate matter formation emissions (NOx, SOx, NH3) contributed to PM Footprint value with 59% in road transportation, 80% in rail transportation, and 61% in water transportation. Conclusions : The PM Footprint values, which shown in this study and the results of the directed polluted PM and secondary gas emissions should be considered for national PM reduction policy and planning. Finally, a certification system using the PM Footprint in this study should be developed and settled down for national PM reduction.

International audience; The problem addressed in this paper was motivated by a real optimization problem of supply chain of the hospital center of Troyes (HCT). The HCT is currently seeking to review and improve its logistics processes. The implementation of techniques and methods of operational research must provide solutions to improve the efficiency of logistics activities. In this work, the studied problem focuses on the catering component of the hospital logistics. A novel mathematical model for the production scheduling of multi-products and multi-stages food processes in hospital catering is proposed. This mathematical model has been implemented in commercial solver CPLEX and it has been tested on real instances of HCT and from the literature. The implementation results of the mathematical model proposed have proved its efficiency for the scheduling of the food production process.

International audience; Mesoporous TiO2 films with enhanced photocatalytic activity in both UV and visible wavelength ranges were developed through a non-conventional atomic layer deposition (ALD) process at room temperature. Deposition at such a low temperature promotes the accumulation of by-products in the amorphous TiO2 films, caused by the incomplete hydrolysis of the TiCl4 precursor. The additional thermal annealing induces the fast recrystallisation of amorphous films, as well as an in situ acidic treatment of TiO2. The interplay between the deposition parameters, such as purge time, the amount of structural defects introduced and the enhancement of the photocatalytic properties from different mesoporous films clearly shows that our easily upscalable non-conventional ALD process is of great industrial interest for environmental remediation and other photocatalytic applications, such as hydrogen production.

International audience; The optical properties of a monolayer of nanocomposite film (PMMA/gold nanocubes) were provided by fitting a proposed theoretical model to spectroscopic ellipsometry (SE) measurements. For such a thin film, these features cannot be successfully determined by means of experimental and conventional effective medium theory such as Maxwell-Garnett or Bruggeman. To make it possible, we developed a model of two classical Lorentz oscillators; one for a PMMA layer and the other for GNCs, revealing one homogeneous layer and rapid analysis without the need for large computational resources. Additionally, we tailored both the size and number of GNCs in the PMMA layer by tuning the synthesis parameters as seen in scanning electron microscopy (SEM) images. In parallel, SE measurements clearly highlighted the change in the optical properties of GNCs as a function of their density on the substrate and dimensions. Our findings demonstrate that SE is an alternative method to characterize layered GNCs on opaque substrates efficiently, which has potential implications for designing other morphologies in the future.

International audience; Additive manufacturing (AM) is a promising way to produce complex structures by adding layers. AM arises great interest both in industrial and academic sectors to develop new advanced structured materials. To benefit from its advantages, it is important to accurately characterize the mechanical properties of the obtained structures in order to ensure their integrity during operation. It becomes important to characterize these structures at the local scale (micron and/or the nanometer scale). In the specific case of polymeric materials produced by Fused Deposition Modeling (FDM), the comprehension of the mechanical behavior between adjacent layers during deformation can help to improve mechanical properties. However, few studies in the literature have focused on implementing approaches to characterize local strains at the surface of these materials. In this study, an original approach based on the use of a speckle pattern with particles average size of 20 microns in diameter was coupled to digital image correlation (DIC). It has been applied to the case of a SENT structure with a notch made by FDM. The successive images recorded by a digital microscope allow a qualitative analysis of the evolutions of the local strains. The kinematic fields are obtained by DIC. The strain evolutions at the notch’s tip are highlighted. The deformation mechanisms at the local scale are confronted with the macroscopic behavior of the structure.

Due to social, environmental and technical evolutions, complex technical projects (numerous stakeholders and several/high level expertises) need to evolve in their management practices. Many management and design methodologies exist to limit costs and resources used in a project. The proposed paper aims at identifying the challenges encountered in complex projects’ management and determining how one of them, the Value Management, should be evolved. The research methodology combines a bibliographical analysis (on engineering methodologies for complex projects’ management) and a demonstration of Value Management interest on a case study to address sustainable stakes.

International audience; In less than truckload transportation, shippers collaborate to reduce their logistics costs by consolidating their transportation requests in the procurement of transportation services from a carrier for serving the requests. In this paper, we study shipper collaboration in forward and reverse logistics, in which multiple shippers with forward or/and reverse logistics operations consolidate their transportation requests. In the forward and reverse logistics, manufacturers deliver new products to their customers and used products are collected from customers and transported to remanufacturers for repair or reproduction. This gives rise to a new vehicle routing problem with pickup and delivery requests and three different types of depots (product depots, vehicle depots and recycle depots). A hybrid approach combining greedy randomized adaptive search procedure (GRASP) and iterated local search (ILS) is proposed to find a near optimal solution of the problem. Numerical experiments on a large set of randomly generated instances with different problem sizes demonstrate that shipper collaboration in forward and reverse logistics can realize significant cost savings compared with the isolated operation of each shipper without cooperation, and the proposed approach is effective in the sense that it can find a high quality solution in a reasonable computation time.

International audience; Disassembly lot sizing problem is one of the important operational problems in disassembly systems. It can be defined as the problem of determining the disassembly quantity and timing of the used-products to fulfill the demand of their parts over a finite planning horizon. This paper considers the case of multiple product types with parts commonality and the objective is to minimize the sum of setup, disassembly operation, and inventory holding costs. High inventory holding cost can be generated: because of disparity between independent and unbalanced demands, and the disassembly of one unit of used-product generates all the parts with different ratios. Aggregate formulation (AGG) can be used to model this problem by considering disposal decisions. Linear-Programming (LP) relaxation of this model doesn’t give very good lower bound, especially for the large-sized instances. We aim to improve lower bound of the problem. Facility Location-based formulation (FAL) is developed which can obtain optimal or near optimal solution by using LP relaxation approach. A two-phase heuristic is proposed which constructs an initial solution by using LP relaxation approach, and then improves by a dynamic programming based heuristic. Computational experiments are conducted on randomly generated test problems which show that the models and methods can give optimal or near-optimal solutions in very short computational times.

Background In France, the number of emergency department (ED) admissions doubled between 1996 and 2016. To cope with the resulting crowding situation, redirecting patients to new healthcare services was considered a viable solution which would spread demand more evenly across available healthcare delivery points and render care more efficient. The objective of this study was to analyze the impact of opening new on-demand care services based on variations in patient flow at a large hospital emergency department. Methods We performed a before-and-after study investigating the use of unscheduled care services in the Aube region in eastern France, that focused on ED attendance at Troyes Hospital. A hierarchical clustering based on co-occurrence of diagnoses was applied which divided the population into different multimorbidity profiles. Temporal trends of the resultant clusters were also studied empirically and using regression models. A multivariate logistic regression model was constructed to adjust the periodic effect for appropriate confounders and therefore confirm its presence. Results In total, 120,722 visits to the ED were recorded over a 24-month period (2018–2019) and 16 clusters were identified, accounting for 94.76% of all visits. There was a decrease of 56.77 visits per week in seven specific clusters and an increase of use of unscheduled health care services by 328.12 visits per week. Conclusions Using an innovative and reliable methodology to evaluate changes in patient flow through the ED, these findings may help inform public health policy experts on the implementation of unscheduled care services to ease pressure on hospital EDs.

International audience; This article addresses a new version of the biomedical sample transportation problem, as a vehicle routing problem with precedence constraints arising in the context of healthcare logistics, and proposes an iterated local search algorithm to solve it. This new version is more realistic and complex since it considers the collection centres’ opening hours and the moment at which they are visited as decision variables, granting additional flexibility to elaborate more efficient routes. Indeed, this problem is harder to model and to solve than its previous version because the constraint on the short samples’ lifetime leads to interdependency between successive pickups at each collection center. A metaheuristic is thus proposed to solve real-life instances. Numerical experiments confirm (1) the value of simultaneously planning routes, opening hours, and visit hours (which is new in the literature) and (2) the efficiency of the proposed algorithm to solve this problem.

Background: Next generation sequencing instruments are providing new opportunities for comprehensive analyses of cancer genomes. The increasing availability of tumor data allows to research the complexity of cancer disease with machine learning methods. The large available repositories of high dimensional tumor samples characterised with germline and somatic mutation data requires advance computational modelling for data interpretation. In this work, we propose to analyze this complex data with neural network learning, a methodology that made impressive advances in image and natural language processing. Results: Here we present a tumor mutation profile analysis pipeline based on an autoencoder model, which is used to discover better representations of lower dimensionality from large somatic mutation data of 40 different tumor types and subtypes. Kernel learning with hierarchical cluster analysis are used to assess the quality of the learned somatic mutation embedding, on which support vector machine models are used to accurately classify tumor subtypes. Conclusions: The learned latent space maps the original samples in a much lower dimension while keeping the biological signals from the original tumor samples. This pipeline and the resulting embedding allows an easier exploration of the heterogeneity within and across tumor types and to perform an accurate classification of tumor samples in the pan-cancer somatic mutation landscape. Fil: Palazzo, Martin. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigación en Biomedicina de Buenos Aires - Instituto Partner de la Sociedad Max Planck; Argentina. Universidad Tecnológica Nacional; Argentina Fil: Beauseroy, Pierre. Université de Technologie de Troyes; Francia Fil: Yankilevich, Patricio. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigación en Biomedicina de Buenos Aires - Instituto Partner de la Sociedad Max Planck; Argentina

In an increasingly competitive economic environment, innovation has become an invaluable asset to the organization and for effective knowledge management (KM). Nowadays, organizations are knowledge based and their success and survival depend on creativity, diversity, and innovation. A knowledge map is a vital tool for better KM and innovation. To this effect, the innovation processes on KMin education system through knowledge transfer activities will facilitate the shift from teaching as knowledge transmission to teaching as learning facilitation. In this context, we present a new approach based on, the one hand, the critical knowledge mapping being based on an extraction work of the expert knowledge and on the other hand, the description of the conceptual framework design which allows one to exploit and integrate knowledge capitalized and external knowledge by the open innovation process. In addition, this practice makes it possible to examine how KM, in particular, the knowledge mapping, can be used to establish the flow of the internal and external information in order to increase the efficiency of creativity and invention.

International audience; Most condition-based imperfect maintenance models developed over the last few decades are memoryless in the sense that maintenance efficiency is completely [Formula: see text]-independent of previous interventions. However, many maintenance activities exhibit their past dependency in engineering practice, and this significant property should not be ignored in maintenance modeling. In this spirit, our aim is to develop a condition-based maintenance model for continuously deteriorating systems subject to a special kind of past-dependent imperfect repairs. Such a repair can put the system back to a deterioration level better than the one at just before the current repair, but worse than the one reached at the last repair. Besides, inspection and replacement are memoryless actions available for the system. They result in different effects on the system deterioration and incur different costs. To achieve high economic performances in the long term, these actions are coordinated into a control-limit deterioration-based maintenance policy. Its long-run maintenance cost rate is analytically evaluated using the semi-regenerative process theory. Numerous sensitivity studies to maintenance costs and to system characteristics give a thorough understanding about the policy behavior. Furthermore, comparisons with more classical policies justify the importance of incorporating the past dependency in maintenance modeling.

International audience; Despite the climate emergency, there is still no consensus on renewable energies, which have to confront forms of social opposition that may well affect the success of any project (especially wind energy and biogas). We propose an original analytical framework to go beyond the nimbyist approach, combining the proximity theory and the exit-voice model. This enables us to examine the thinking adopted by biogas production stakeholders and the ensuing associations in order to identify and understand the obstacles to the development of joint biogas production projects. Taking further other theories that highlight the importance of place attachment and place identity, we show that the challenges linked to a project's territorial governance can explain conflicts that may lead the project initiators to abandon a biogas plant's construction. We show that considering the local residents' interests and including them in the participative procedures are not the only factors that count, but also, more generally, coordination between all of the stakeholders. Our paper also highlights the need for an intermediary actor to play the role of facilitator in organising different types of proximity.

The plasmon resonances (modes) of a metal nanostructure can be defined as a dipole, a quadrupole, or high-order modes depending on the surface charge distribution induced by the incident field. In a non-symmetrical environment or clusters, the modes can hybridize and exhibit different behavior and properties. In this work, we study experimentally and numerically the substrate-induced hybridization of plasmonic modes of a silver nanocylinder. The applications of plasmonic nanoparticles such as refractive index sensing and enhanced spectroscopies often rely on the sustained mode spectral position and specific spatial near-field distribution. However, we show that the implementation of such plasmonic nanoparticles in a sensing system can result in a change of the modes nature, its hybridization or dehybridization. These changes are not clearly pronounced in the far-field spectra and then may result in unexpected modifications of the sensor behavior. We show that the hybridization between the dipolar and quadrupolar modes of the plasmonic nanoparticle on the substrate results from quadrupolar mode excitation due to the superposition of the reflected and incoming light and, then, depends on the reflection of the substrate. The existence of the hybridized modes strongly depends on the surrounding environment of nanoparticles, and after the deposition of the nanometric polymer layer on top of the nanoparticle the hybridized modes vanish and are replaced by uncoupled multipolar resonances., 18 pages, 6 figures