Institut Mines-Télécom
Recent publications
The rapid growth of technology has given rise to a form of communication unknown to the business world i.e. “electronic word of mouth” (e-WOM), which is considered to be an ideal and the most effective way of communicating. However, as e-WOM progresses online, the factors contributing may differ from those of traditional WOM. The current study attempts to analyze the effect of e-WOM on consumer's purchase intention towards private label brands (PLB) offered by the e-tailers in India. A self-executed questionnaire was the tool to survey and extract data from 437 respondents on platforms of social media. The study brings forth a new framework integrating the models- ELM (Elaborative Likelihood Model) and IAM (Information Adoption Model) along with store image to assess the consumer's PLB purchase intention. The data was analyzed with the help of Structural Equation modeling (SEM). The outcome of the research will help the managers, marketers, e-tailers on the significance of e-WOM in making appropriate strategies to attract more and more e-shoppers. Theoretical and practical implications as well as the limitations of the study are further discussed.
Wireless networks are nowadays indispensable components of telecommunication infrastructures. They offer flexibility, mobility and rapid expansion of telecommunication infrastructures. In wireless networks, transmissions are unisolated and most commonly emitted using omnidirectional antennas. This makes wireless networks more vulnerable to some specific attacks as compared to wired networks. For instance, attacks such as fake access points, intentional jamming and deauthentication can be easily perpetrated against IEEE 802.11 networks using freely accessible software and cheap hardware. Intentional jamming and deauthentication attacks are standalone attacks, but they can be combined with the fake access point attack to increase the latter’s effectiveness. In our research, we work on methods to detect the three different attacks when they are perpetrated independently (one at a time) or concurrently (several at the same time). In this contribution, we present a model that can detect the three attacks, when perpetrated independently, by analysing a set of features (frame interval, Received Signal Strength Indicator, sequence number gap and management frame subtype) extracted from IEEE 802.11 management frame and radiotap headers. We have implemented the model using several supervised learning algorithms. The model with Random Forest and the K-Nearest Neighbour predictors have best detection precision (over 96 %) for fake access point and deauthentication attacks and perfectible detection precision for the intentional jamming attack (over 81%).
This paper presents the chemical and mineralogical characterizations of a cementitious material and its behaviour to temperature increase in conditions close to those of radioactive waste storage. The formulation, based on a CEM III/C, silica fume, bentonite and hydrotalcite makes a low-pH cementitious grout with a low viscosity. Results show that the mineralogical composition of this material evolves during setting. Two years after setting, it is a macro porous geomaterial, composed of few C-(A)-S-H with a low C/S ratio (<0.4) formed from the blast furnace slags. It also contains well-crystallized ettringite, hydrotalcite, calcite and still non hydrated C2S. In contact with air, a substantial enrichment in calcite and gypsum is observed. The heating up to 90 °C leads to the transformation of the Na-rich smectite of the bentonite into a Ca and/or Mg-rich one and the formation of opal-CT, vaterite and aragonite. Hydrotalcite is stable whereas gypsum and anhydrite disappear.
Model predictive control (MPC) has been widely employed to control a large variety of water systems, such as dams, irrigation canals, inland waterways, drinking water networks and wastewater treatment plants. Its predictive capabilities and the possibility to incorporate constraints make MPC well suited to address several, and sometimes opposite, management objectives linked to water systems. The design of MPC for water systems is usually performed via dedicated software (e.g., Matlab) and tested in simulation using dedicated hydraulic software. However, the implementation of MPC strategies in real systems requires additional development to allow for its embedding within the information systems that are used by system managers. A possible solution is to create a tool based on Python that can be easily integrated with the information systems of managers, and within which existing Matlab solutions can be incorporated. In this paper, the development a ready-to-use Python tool using a hierarchical MPC approach designed for the management of the Calais Canal is presented.
This paper proposes a combined control and state estimation strategy for inland waterways, aiming at simultaneously attaining the optimal water level management and maximizing hydroelectricity generation. The latter can be realized by turbines installed in canal locks that harness the energy generated during lock filling and draining operations. These two objectives are of opposed nature, as maximization of energy generation can be achieved by maximizing the number of lock operations, which in turn leads to unbalanced water levels upstream and downstream of the lock. To address this issue, the multi-objective optimization problem is formulated . Then, model predictive control (MPC) and moving horizon estimation (MHE) are designed to maintain navigation conditions in the canals while maximizing energy production. Finally, the proposed strategy is applied to a realistic case study based on part of the inland waterways in the north of France.
Vehicular communications are an important focus of studies for 5G applications and beyond. However, in a scenario with doubly-selective and highly variable channel characteristics, tracking the wireless channel to ensure communication reliability is one of the main goals to provide communication efficiency. Moreover, multicarrier modulation schemes usually employed in these scenarios are susceptible to nonlinear distortions caused by high power amplifiers (HPA) at the transmitter, impairing the channel estimation and detection capability of the receivers. In view of these requirements and challenges, in the present work we propose a low complexity estimator based on the long short-term memory (LSTM) network, followed by a neural network (NN) in order to improve the data-pilot aided (DPA) estimation. In addition, we propose a new technique to exploit the characteristics of the vehicular channel, by sampling the subcarriers used at the input of the LSTM. Thus, besides tracking the variations of the wireless channel, the LSTM network is also used to interpolate the channel estimates for all subcarriers. The simulation results show the superiority of the proposed scheme in comparison with other state-of-the-art schemes, especially in high signal-to-noise ratio (SNR) regimes. Furthermore, the proposed scheme significantly reduces the computational complexity due to the subcarrier sampling procedure.
Ti-Nb alloys are high-profile candidates for the biomedical applications. However, because of poor surface integrity (i.e. residual stress and surface roughness), Ti-Nb implantable medical devices need to be machined in order to obtain functional surfaces finish. In this work, experimentaland numerical investigations are conducted to study the micro-cutting response of Ti42Nb titanium alloy produced by laser-based powder bed fusion. Experimental micro-cutting tests are carried out using precision turning lathe. Trials are performed with two cutting velocities of 60 m/min and 120 m/min and different feed rates, varying from 5 to 40μm/rev. For the numerical study, a porous crystal plasticity-based model is proposed to address the impact of anisotropy and microstructure heterogeneities of the polycrystalline material. The crystal plasticity-basedmodel is identified using strain–stress curves obtained from compression tests performed under two strain rates and a wide range of temperatures. Numerical micro-cutting simulations are performed in order to gain insight into the impact of microstructural features (i.e. crystallographic orientation and grain size) on the machinability of the alloy.According to the results, the effect of the strain rates and the temperature on the thermomechanical behavior of the Ti42Nb titanium alloy produced by laser-based powder bed fusion is correctly depicted. The model captured the strain localization on adiabatic shear band during compression tests. According to the micro-cutting simulations, the local variables such as temperature, damage and plastic deformation are strongly impacted by the crystallographic orientations and the grain size.In addition, depending on the crystallographic orientations, the chip morphology changes form continues, slightly segmented to largely segmented.
Pyroglutamide derivatives have emerged as promising inhibitors of human farnesyltransferase (FTIs), an important target in oncology and also in rare diseases such as Hutchinson-Gilford progeria syndrome (HGPS). This report describes the chemical efforts to enrich the pyroglutamide series using greener and recyclable catalysts. The central reaction studied was an amidation between methyl pyroglutamates or vinylogues and amines. Ten catalysts have been tested in this amidation reaction: two classical Lewis acids (ZnCl2, ZrCl4), four impregnated montmorillonite K10 with ZnCl2 namely Cat1, Cat2, Cat3 and Cat4 (not activated, activated at 120 °C, 280 °C and 500 °C, respectively) and four montmorillonites K10 (commercial montmorillonite K10 not activated, activated at 120 °C, 280 °C and 500 °C). The most efficient catalyst was Cat4. The recyclability of Cat4 over five synthesis runs has been successfully tested. Twenty-six amides were synthesized and screened for their potential to inhibit human farnesyltransferase. Four points of chemical modulation around the pyrrolidine-2-one ring have been realized allowing to complete structure-activity relationships in these series. The study revealed several potent inhibitors targeting human farnesyltransferase in vitro with IC50 values in the submicromolar range and down to 30 nM. The docking of compounds in the active site of FTase highlighted that the S-isomers of pyroglutamides had good affinity. This study propels pyroglutamide derivatives as promising candidates for future functionality assays and in vivo evaluation.
Non-destructive testing (NDT) techniques are usually used for the characterisation of defects arising in polymer composites during manufacturing or in-service use. However, each of these NDT techniques cannot always allow a full diagnosis of the material’s or component’s structural health. Thus, several techniques have to be combined in order to improve the diagnosis of the damaged state of composite structures and their evolution during the part’s life span. This opinion paper proposes a critical overview of the use and applicability of these NDT techniques for the detection and characterisation of damage to structural composite materials in view of in-service performance assessment and residual durability prognosis. It also addresses some current trends of structural health monitoring (SHM) of these materials, such as sensor–actuator embedding and NDT data fusion, and draws future perspectives on how composite SHM could evolve in the digital era, taking advantage of artificial intelligence, Internet of Things and big data to implement digital twins.
Purpose/Objective(s) In patients treated with radiotherapy for a locally advanced lung cancer, respect of dose constraints to organs at risks (OARs) insufficiently protects patients from acute pulmonary toxicity (APT), such toxicities being associated with a potential impact on treatment's completion and the patients’ quality of life. Dosimetric planning doesn't take into account regional lung functionality. An APT prediction model combining usual dosimetry features with the mean dose (DMeanPmap) received by a voxel-based volume (Pmap) localized in the posterior right lung has been previously developed. A DMeanPmap ≥ 30.3Gy was associated with a higher risk of APT. In the present study, the authors aim to demonstrate the possibility of decreasing the DMeanPmap via a volumetric arc therapy (VMAT)-based adapted planning and evaluate the impact on the risk of APT. Materials/Methods Among the 207 patients included in the initial study, only patients who presented with an APT ≥ grade 2 and with a probability of APT (ProbAPT) ≥ 8% based on the prediction model were included. Dosimetry planning was optimized with a new constraint (DMeanPmap < 30.3Gy) added to the usual constraints. Initial and optimized treatment plans were compared using the T-test for independent variables and the non-parametric Mann-Whitney U test otherwise, regarding both doses to OARs and PTV (Planning Target Volume) coverage. Conformity and heterogeneity indexes were also compared. Risk of APT was recalculated using the new dosimetric features and the APT prediction model. Results Dosimetric optimization was considered successful for 27 out of the 44 included patients (61.4%), meaning the dosimetric constraint on the Pmap region was achieved without compromising the PTV coverage (p = 0.61). Optimization significantly decreased median DMeanPmap from 28.8Gy (IC95% 24.2-33.4) to 22.1Gy (IC95% 18.3-26.0). When recomputing the risk of APT using the new dosimetric features, optimization significantly reduced the risk of APT (p < 0.0001) by reclassifying 43.2% (19/44) of the patients. Conclusion Our approach appears as both easily implementable on a daily basis and efficient at reducing the risk of APT. Regional radiosensitivity should be considered in usual lung dose constraints, opening the possibility of an easily implementable adaptive dosimetry planning.
Calcium sulfoaluminate cement is a relatively new type of cement with environmental advantages linked to its low carbon emission. However, there is a lack of knowledge on its use with supplementary cementitious materials. This article aims to study the effect of utilizing the activated flash-calcined sediment from Noyelles-sous-Lens (SC) as a supplementary cementitious material in calcium sulfoaluminate mortar. Therefore, four mixes are prepared by replacing calcium sulfoaluminate cement with 5%, 10%, and 20% of flash-calcined sediment. The reactivity of the cement pastes with and without the sediment is studied by isothermal calorimetry and by measuring the setting time. Then, the mechanical performance is tested at 1, 7, and 28 days. The results show that adding the flash-calcined sediment has an accelerator effect on cement hydration and decreases the induction period. The cumulative heat release and the compressive strength at 28 days are almost the same up to 10% of sediment substitution.
Missing sensor data is a common problem associated with the Internet of Things (IoT) ecosystems, which affect the accuracy of the associated services such as adequate medical intervention for older adults living at home. This problem is caused by many factors, power down is one of them, communication failure and sensor failure are another two reasons. Multiple missing data imputation methods have been developed to solve this issue. However, irregular temporal missing data locations is challenging to handle, due to lack of knowledge of their occurrence probability and their random temporal location. In this paper, we propose a Bayesian Gaussian Process based imputation technique that accounts for temporal forcing to fill in the missing sensor data. Our approach; Bayesian Gaussian Process (BGaP); can impute missing data efficiently at any missing rate and for any temporal location using prior knowledge gathered on past observations. We illustrated how our approach performs using real data collected from sensors deployed in the residence of 10 older adults over a two-year period. Using our novel approach, we were able to impute all the missing data which allowed us to observe long-term behavior changes that we would not have been able to observe otherwise.
The hop plant (Humulus lupulus L.) has been exploited for a long time for both its brewing and medicinal uses, due in particular to its specific chemical composition. These last years, hop cultivation that was in decline has been experiencing a renewal for several reasons, such as a craze for strongly hopped aromatic beers. In this context, the present work aims at investigating the genetic and chemical diversity of fifty wild hops collected from different locations in Northern France. These wild hops were compared to ten commercial varieties and three heirloom varieties cultivated in the same sampled geographical area. Genetic analysis relying on genome fingerprinting using 11 microsatellite markers showed a high level of diversity. A total of 56 alleles were determined with an average of 10.9 alleles per locus and assessed a significant population structure (mean pairwise FST = 0.29). Phytochemical characterization of hops was based on volatile compound analysis by HS-SPME GC-MS, quantification of the main prenylated phenolic compounds by UHPLC-UV as well as untargeted metabolomics by UHPLC-HRMS and revealed a high level of chemical diversity among the assessed wild accessions. In particular, analysis of volatile compounds revealed the presence of some minor but original compounds, such as aromadendrene, allo-aromadendrene, isoledene, β-guaiene, α-ylangene and β-pinene in some wild accessions; while analysis of phenolic compounds showed high content of β-acids in these wild accessions, up to 2.37% of colupulone. Genetic diversity of wild hops previously observed was hence supported by their chemical diversity. Sample soil analysis was also performed to get a pedological classification of these different collection sites. Results of the multivariate statistical analysis suggest that wild hops constitute a huge pool of chemical and genetic diversity of this species.
The present article is discussing the performance of heat transfer enhancement (HTE) using a trapezoidal vortex generator in a Concentric Tube Heat Exchanger (CTHE) through Computational Fluid Dynamics (CFD) code ANSYS Fluent. Heat transfer and fluid flow analysis are conducted for various Reynolds numbers inside the tube and annular. The effects of Vortex Generators (VGs) are studied as well, and the turbulence flow is simulated using the k-ꞷ model. The analysis was made on four designs, where the VGs are placed in three different locations as follows: (case 0) no VGs, (case 1) VGs inside the tube, (case 2) VGs on the interface between annular and tube, and (case 3) VGs on the outer wall of the annular part. Accordingly, the overall heat transfer, heat transfer ratio, and heat transfer/power of each of the three cases with VGs are normalized to case 0 to study the effect of VGs on the flow and heat transfer enhancement. Results show that VGs are effective in all locations and cases, however, the highest improvement was spotted in case 1 at Reynolds number of 8000 for the cold fluid and Reynolds number of 2000 for the hot water, where the enhancement of heat transfer ratio was 97% for case 1, 92% for case 2 and 56% for case 3, whereas the thermal enhancement factor was 210% for case 1, 180% for case 2 and 142% for case 3.
Résumé Background Les arthroplasties totales du genou (PTG) sont en augmentation constante depuis plusieurs décennies en Europe et aux USA. Bien qu’en progression dans tous les pays, leur croissance est inégale : faible en Europe du Nord et centrale, en ralentissement aux USA et exponentielle au Royaume-Uni. Pour la France, une croissance de +32,2 % des actes d’arthroplasties unicompartimentales et totales du genou a été recensée entre 2012 et 2018, mais aucune étude n’a focalisé sur l’évolution des actes de PTG et l’évolution du statut des malades qui bénéficient d’une PTG. Aussi, nous avons ainsi mené sur la base des données nationales françaises une étude des actes pour déterminer : 1) l'évolution des tendances de croissance par sexe et par âge, (2) l'observation ou non d'un rajeunissement, (3) l’évolution de l’état de comorbidité des patients lors de l’opération, et (4) la stabilisation future du taux d'incidence ou pas et la prévision pour 2050. Hypothèse Notre hypothèse était qu’en France, il existait une dynamique à la hausse différente pour chaque sexe. Matériel et méthode L’étude a été menée en France sur la période 2009-2019 pour chaque sexe et tranche d’âge. Les données sont issues de la base de données du SNDS (Système National des Données de Santé), qui regroupe toutes les interventions menées en France. En se basant sur le recueil des actes effectués, il a été déduit (1) les taux d’incidence et leur évolution et (2) L’évaluation indirecte de l’état de comorbidité du patient. En utilisant des modèles de projection de types linéaire, Poisson et logistique, les taux d’incidence ont été projetés aux années 2030, 2040 et 2050. Résultats Une augmentation du taux d’incidence plus forte entre 2009 et 2019 est observée pour les hommes, de 71,2 à 122,9 (soit +73 %) par rapport aux femmes de 124,2 à 181 (soit +46 %), qui se constate dans toutes les classes d’âges. Néanmoins, la croissance est plus importante chez les moins de 65 ans, tant chez les hommes de 20,9 à 37,9 (soit +82 %) que les femmes de 33,6 à 51,3 (soit +53 %). Sur la période, la proportion des patients avec des comorbidités peu sévères augmentait (de 40 093 à 67 430 PTG, soit de 53,1 % à 65,7 % du total des actes), à la différence des autres classes. Tous les modèles de projection sont validés. Toutefois, tant chez les hommes que les femmes, une projection logistique de +33 % d’ici 2050 (soit 151 575 PTG), avec l’atteinte d’un plateau vers 2030 est la plus probable. Conclusion Bien que la croissance soit plus forte chez les hommes par rapport aux femmes, les deux sexes suivent une évolution similaire avec une augmentation des actes plus élevée chez les moins de 65 ans et un glissement vers des patients à plus faible comorbidité. A plus long terme, l’évolution du taux d’incidence s’inscrit dans une dynamique de type logistique, avec l’atteinte d’un plateau vers 2030. Face à cette demande croissante, une augmentation de la charge en soins sera à prévoir. Niveau de preuve IV, Étude épidémiologique descriptive.
To better understand the influence of the prepreg parameters such as surface roughness, fibres/matrix distribution (e.g. presence or absence of pure matrix layer on the prepreg surface) and initial matrix crystallinity, two different carbon fibres/Poly-Ether-Ketone-Ketone prepregs are used to fabricate unidirectional laminate by Vacuum-Bag-Only (VBO) process. By an in-situ monitoring set-up, the laminate thickness and the temperature difference along the thickness direction are measured throughout the consolidation cycle. The quality of laminate is assessed in terms of interlaminar shear strength and void content. A finite element model has been developed to describe the intimate contact establishment by the deformation of surface roughness between the glass transition temperature and the melting temperature of the matrix. In particular, the model takes into account the real profilometer data and the variable Young’s modulus of matrix in terms of temperature and crystallinity. Finally, the high influence of the matrix crystallinity degree and the surface roughness on the intimate contact phenomenon is highlighted.
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1,311 members
Luigi Iannone
  • Département d'Informatique et Réseaux
Jean-Marc Le Caillec
  • Département Image et Traitement de l'Information
Zribi Amin
  • Département Signal et Communications
Alexander Pelov
  • Département Réseaux, Sécurité et Multimédia (RSM)
Antoine Beugnard
  • Département Informatique (Bretagne)
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