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Future warming predicted for Tunisia may reduce winter chill and affect the production of tree fruits and nuts, one of the key sectors of the country’s economy. To assess past and future chill availability, we used weather records from 1973 to 2019 to simulate historic and future chill for 20 weather stations (16 from Tunisia, 3 from Algeria and 1 from Libya) by generating 6 past scenarios and 72 future scenarios for 2041–2070 and for 2071–2100, for two Representative Concentration Pathways (RCP4.5 and RCP8.5). We selected three future scenarios representing optimistic, intermediate, and pessimistic outlooks. Safe Winter Chill (SWC; in Chill Portions) was calculated using the Dynamic Model based on data for 100 winter seasons produced with a weather generator. SWC was then mapped for the whole country. Chilling requirements for typical Mediterranean fruit species (almond, pistachio, and peach cultivars) were compared with future SWC to select the best adapted fruit species, and cultivars within species, for each region. Our findings revealed severe SWC decline in the recent past. This decline will continue in the course of the twenty-first century. At the end of the century, we expect few of the studied species and cultivars to be able to fulfill their chilling requirements. By that time, only almonds may remain viable, whereas pistachios and peaches may experience alarming chill shortfalls. While our findings paint a grim picture for Tunisia’s orchards, they also allow insights for many other important fruit-growing regions with Mediterranean climate.

Despite the numerous studies on geomaterials in Tunisia, quite a few clay varieties are not yet well defined. In fact no detailed geological, mineralogical, or geochemical characterizations of Tunisian palygorskite deposits have been carried out to date. The purpose of the present work was to study the continental Eocene clay deposit at the southern end of the Tunisian North axis, between Jebel Rheouis and Jebel Boudinar, to determine its potential as a clay reserve. Nine samples were collected from the Cherahil formation representing the lower, middle, and upper levels. The analytical results obtained using several techniques (chemical analysis, X-ray diffraction, specific surface area measurements, Fourier-Transform infrared spectroscopy, scanning electron microscopy) revealed that palygorskite is the dominant clay mineral. Dolomite and quartz are present as associated minerals. Chemical analysis of sample AR9 showed a smaller potassium content compared to other samples. Sample AR9 consists essentially of dolomite associated with palygorskite and quartz. Other samples (AR5, AR6, and AR7) collected from the same Cherahil formation contained palygorskite as the main phyllosilicate mineral (80%). The important reserve of palygorskite was found in the middle of the Cherahil formation. Dolomite and quartz associated with palygorskite reduced the length and crystallinity of the fibrous clay morphology. Analysis by scanning electron microscopy proved that the crystallinity of palygorskite was less in the lower and upper parts of the Cherahil formation. The central palygorskite deposit may be of interest for pharmaceutical (adsorbent drug) and other applications. The two other levels of Cherahil formation are mineralogically heterogeneous and considered economically less important than the middle level, which is rich in palygorskite.

Effects of drought and salinity on water status, growth and physiological activity of olive can be temporary or permanent and may impact olive production sustainability, especially in southern Mediterranean areas. Tunisia has a Mediterranean climate with high temperatures and low summer rainfall. Thus water stress problems are likely to be more severe for cultivated olive trees. In addition, the reduction in the availability of good quality irrigation water will increase the use of saline water. Olive trees are able to tolerate low soil water availability and quality and develop physiological adaptations to cope with water and salt stress. However, these adaptation strategies are limited and permanent damages can be observed. The permanent effects caused to olive leaves due to drought, and the capacity of irrigation with saline water to avoid these impacts is not well known. The aim of this work was to compare olive leaves performance after a severe drought with, and without, irrigation and to assess recovering capacities after a rainy period. Moreover, irrigation water quality effects were also evaluated. The results showed that, photosynthetic rate was very low for rainfed plants, during drought, as compared to irrigated ones. After re-watering, rainfed trees photosynthetic rate was only 55% of that of trees irrigated with fresh water. Irrigation with saline water (EC = 7.5 dS m−1) reduced drought impact by increasing photosynthesis by 55% but remained lower than that of fresh water by 23%. Thus olive leaves were unable to recover their whole photosynthetic capacity after being exposed to severe water or salt stress. Furthermore, young leaves had the same photosynthetic capacity at the beginning. This indicated that olive leaves lost permanently half of their photosynthetic activity during to drought without irrigation. The use of saline water reduced this gap to 23% as compared to fresh water.

Activated carbon (AC) is being developed as a treatment for decontaminating polluted water. In this study, the activated carbon prepared by physical activation of Pinus halepensis cone wastes was applied for iron removal from groundwater. The adsorption process was performed in two steps: batch and fixed-bed column adsorption. The minimum time to reach the adsorption equilibrium was 60 min with maximum of Fe2+ removal equal to 7.35 mg/g. The isotherm models were used to fit the experimental data and the results showed good correlations, with the Langmuir isotherm with good linear correlation coefficients. The effective retention volume of the fixed-bed column is 360 BV for AC. The prepared AC showed promising results, which makes it convenient to serve an effective adsorbent for the removal of heavy metal ions from wastewater.

Pinus halepensis cone waste (PHCW) was collected from local seeds—Pinus halepensis processing industry. This study investigated the PHCW use as an adsorbent for wastewater treatment. The synthesis of activated carbon from PHCW was performed as a function of temperature under CO2 and N2 flow. The characterization was performed by adsorption–desorption N2 isotherms, FTIR, the point of zero charge, and SEM. Functional acid or basic groups were detected on the surface of activated carbon. For both physical activation and pyrolysis, the maximum value of surface area was obtained at 800 °C. The adsorption–desorption N2 isotherms of activated carbon under CO2 and N2 flow showed very similar trend characteristics of a mesoporous framework. The present results suggest that PHCW is a potential source for the synthesis of carbon materials with potential novel applications.

The present paper reports an automated approach for the characterization and analysis of the behavioral of sand flies; the method used is based on Gaussian mixture model and Kalman filter for the detection and tracking of sand flies, and then the extraction of an optimized set of features from the trajectory of flight is performed for the classification process. So, we propose here two optimized sets of features; the first one is used to identify sand flies among other insects, and the second is employed for the characterization of the behavioral change in the sand flies in the presence of a repulsive odor. These features are tested on three different classifiers; artificial neural network, support vector machine and K-nearest neighbor (KNN), and the results show an important improvement in the classification accuracy and confirm the effectiveness of our approach; the accuracy rate of the proposed method reached 88.6% for the identification of sand flies and 93.4% for the detection of their behavior change. Instead of the excessive use of pesticides over wide areas, the presented investigation is a key pillar of the development of an ecological way for a statistical information gathering about sand flies in order to fight against disease carried by those insects especially leishmaniosis and pappataci fever.

Linear supra-molecular liquid crystals, 4-(octyloxy) benzoic acid (8OBA) and 4-(octyloxy)-3-fluoro benzoic acid (8OBAF), have been synthesized. The structure of these compounds was investigated by NMR and FTIR. The thermal and phase behavior of these compounds were studied by polarized optical microscopy (POM), differential scanning calorimetry (DSC) and dielectric spectroscopy. The influence of fluorine atom in benzene ring core compounds and on electro-optical and optical properties has been studied as well. The binary mixtures of these compounds are well-established and the phase diagram (temperature-concentration) is plotted in heating as well as in cooling mode. The substituted mesogen exhibits rich phase variance compared to the 80BA. From the experimental observations, smectic-G phase appeared in the complexes.

As the energy efficiency remains a key issue in wireless sensor networks, duty-cycled mechanisms acquired much interest due to their ability to reduce energy consumption by allowing sensor nodes to switch to the sleeping state whenever possible. The challenging task is to authorize a sensor node to adopt a duty-cycle mode without inflicting any negative impact on the performance of the network. A context-aware paradigm allows sensors to adapt their functional behavior according to the context in order to enhance network performances. In this context, the authors propose an enhanced version the Efficient Context-Aware Multi-hop Broadcasting (E-ECAB) protocol, which combines the advantages of context awareness by considering a multi criteria and duty-cycle technique in order to optimize resources usage and satisfy the application requirements. Simulation results show that E-ECAB achieves a significant improvement in term of throughput and end-to-end delay without sacrificing energy efficiency.

As the energy efficiency remains a key issue in wireless sensor networks, duty-cycled mechanisms acquired much interest due to their ability to reduce energy consumption by allowing sensor nodes to switch to the sleeping state whenever possible. The challenging task is to authorize a sensor node to adopt a duty-cycle mode without inflicting any negative impact on the performance of the network. A context-aware paradigm allows sensors to adapt their functional behavior according to the context in order to enhance network performances. In this context, the authors propose an enhanced version the Efficient Context-Aware Multi-hop Broadcasting (E-ECAB) protocol, which combines the advantages of context awareness by considering a multi criteria and duty-cycle technique in order to optimize resources usage and satisfy the application requirements. Simulation results show that E-ECAB achieves a significant improvement in term of throughput and end-to-end delay without sacrificing energy efficiency.

Graphs are a fundamental structure that provides an intuitive abstraction for modeling and analyzing complex and highly interconnected data. Given the potential complexity of such data, some approaches proposed extending decision-support systems with multidimensional analysis capabilities over graphs. In this paper, we introduce TopoGraph, an end-to-end framwork for building and analyzing graph cubes. TopoGraph extends the existing graph cube models by defining new types of dimensions and measures and organizing them within a multidimensional space that guarantees multidimensional integrity constraints. This results in defining three new types of graph cubes: property graph cubes, topological graph cubes, and graph-structured cubes. Afterwards, we define the algebraic OLAP operations for such novel cubes. We implement and experimentally validate TopoGraph with different types of real-world datasets.

In this paper, we design a new robust Observer-based Discrete-Time Sliding Mode Control for an uncertain linear discrete-time delay system. The considered system is subject to time-varying states delay, unmatched Unknown and norm-Bounded UBB parametric uncertainties, external disturbances and nonlinearities which are assumed to satisfy a Holder condition. A new delay-dependent sufficient conditions guaranteeing the robust asymptotic stability of the closed-loop system is derived in terms of Linear Matrix Inequalities. With respect to these conditions, a new discrete-time sliding mode control law is designed based on a novel observer structure and a new sliding surface. A numerical example is presented to illustrate the efficiency of our proposed approach.

Sales and operations planning (S&OP) is a midterm planning practice that is widely used in industries with relatively volatile demand and limited capacities to align demand and supply. Several research studies, as well as practical guides, have been developed to examine the design and implementation of S&OP processes. Most of these studies are general and have no reference to the industry behind them. However, regarding planning, each industry has its properties. Taking a "one size fits all" approach is not profitable for extreme cases, such as for an automotive industry known for the very large product portfolios. Our contribution intends to examine this issue in detail by performing a literature review on the effectiveness of S&OP and its impacts on supply chain performance. We try to reveal why actual S&OP practices are not fit for highly diversified mass production systems, and we deduce that there is a need to redefine the S&OP process for such industries.

Bone charcoal (BC) is being developed as a treatment for decontamination of polluted water. In this study, bone charcoal was obtained by pyrolysis of cow bones and tested for the elimination of copper from aqueous solutions. The minimum time to reach the removal equilibrium by adsorption was 10 min with a maximum of copper removal equal to 9615 mg/g. Different kinetics models were applied to fit the experimental data: the pseudo second-order model correlated the results with a linear correlation coefficient equal to 1.

This paper proposes a Core Ontology of Know-How and Knowing-That (COOK). Know-How and Knowing-That are two types of knowledge according to the epistemological point of view. COOK is founded on work analysis in epistemology, philosophy of capacity/disposition and philosophy of action. This work allows to establish a conceptual analysis of Know-How and Knowing-That. Know-How is defined as the disposition to perform a type of action, whereas Knowing-That is defined as a belief state and concerns a description which can be factual or prescriptive. Taking into account the whole amount of data for an organisation, COOK enhances knowledge identification, decision-making and knowledge sharing among organisation or between different organisations geographically dispersed. Furthermore, COOK is used for the semantic refinement of knowledge evaluation criteria family. These criteria can be related to (i) functional point of view which aims to calculate the contribution degree of Know-How/Knowing-That to the o...

This paper proposes a discrete-time sliding mode control (DT-SMC) algorithm for uncertain linear systems with time-varying delay on the state. The parameter uncertainties and the external disturbances are assumed to be unknown but norm-bounded. The sliding mode existence depends on that of the stable linear sliding surface, which is ensured by a sufficient condition that depends on the delay bounds and is derived using LMI. A numerical example as well as an application to the Two-Area Four-Machine power system has been presented to illustrate and confirm the usefulness and the effectiveness of the proposed control strategy.

Multimedia transport over Wireless Sensor Networks (WSN) has been a challenging task due to the limited available resources of such networks. The capability of Multipath routing to balance and distribute the load of a given flow on different disjoint non correlated paths is a viable solution to ensure the required high throughput. Moreover, operating the WSN under a duty-cycle mode reinforces the challenge as nodes become subject to frequent alternation between the active and inactive states in the quest to prolong the network life and minimize the energy consumption. In this context, we propose a cross-layer multi-path routing approach taking into account diverse contextual information in order to establish non-correlated and node-disjoint paths able to concurrently transport multimedia content from sources to the sink. The approach relies on a tight cooperation between the routing and MAC layers in order to appropriately adjust and regulate the wake-up scheduling of involved nodes in the forwarding phase. It incorporates a continuous observation of local contextual data to improve the routing process. Independently of the initial duty-cycle scheduling, the conducted mathematical analysis proves that our adjustment rules provide a maximal overlapping interval between the activity periods of the involved nodes. We compare our approach against the single path option and FMRP, a multipath routing protocol designed for always-on WSNs using non-correlated paths. Simulation results showed significant improvements in terms of latency and throughput. The proposed approach attains 27% energy conservation, and it enhances the delay and goodput by 50% over the single path option and up to 90% over the FMRP.

The ability of Tunisian smectite, collected from Aleg Formation (Jebel Romena), in the adsorption of nickel (Ni(II) and chromium (Cr(III)) cations from aqueous solutions has been studied through a bath adsorption mechanism with respect to different optimal parameters including the amount of adsorption, pH, and contact time. The characterization of a smectite sample was performed using XRD, XRF, FT-IR, SEM, BET-specific surface area techniques, thermo-gravimetric analyses, and CEC. The process of adsorption kinetics was examined using the pseudo-first-order, the pseudo-second-order, and the intraparticle diffusion models. The results revealed that the adsorption of Ni(II) and Cr(III) cations was according to the pseudo-second-order model. The changes of the thermodynamic parameters such us the Gibbs free energy (ΔG), the enthalpy (ΔH), and entropy (ΔS) attested, spontaneous and endothermic between 10 and 40 °C.

The study aims to combine between the valorization of the adsorption ability of the clay mineral and essential oil with insecticidal effect for synthesis of a powder formulation investigated as natural insecticide. The insecticidal formulation created by the adsorption of the terpenes from Eucalyptus globulus essential oil onto the Tunisian clay classed beidellite (Bd). Furthermore, modified beidellite was investigated for increasing the amount of terpenes adsorbed. Organoclays (OC) were prepared by hexadecyltrimethyl ammonium (HDTMA) and didodecyldimethyl ammonium bromide (DDDMA) intercalation in the interlayer space of Bd. The OC was characterized by X-ray diffraction (XRD), Fourier transformed infrared (FTIR) analysis and Textural analysis by nitrogen adsorption desorption (BET method) in order to confirm the success of organic modification. After adsorption studies, the kinetic models are examined. Results show the adsorption of terpenes onto Bd and modified Bd flows the pseudo-second-order model. Moreover, the adsorption ability of terpenes from Eucalyptus globulus oil is enhanced after organic modification, especially HDTMA.

In this paper, we study the estimation of olive tree biophysical properties driven by Sentinel-2 (S2) image inversion. The latter is based on the forward/backward radiative transfer model (RTM). The forward step is done simulating the DART model on a realistic olive tree mock-up, whereas the backward is done based on a coupling between the Look UP Table (LUT) and the Markov Chain Monte Carlo (MCMC). The parameters Leaf area index (LAI), chlorophyll (Cab) water (Cw) contents and mesophyll structure (N) are therefore derived. Soil reflectance is pre-calculated based on an upscaling of the S2 resolution to 3m using Planet images. Moreover to obtain a significant representation of the local heterogeneity, S2 are upscaled to the 80m resolution. The estimation results are promising.

It is approved that the essential oil of Eucalyptus globulus has an important insecticidal activity against pests grain stock. This study is interested in ensuring the terpenic compounds with the insecticidal activity on a Tunisian clay support. The aim of this study has developed an insecticide formulation without any negative impact on the environment.

In this paper, we presented an approach to automatically detect abnormal high-level events in a parking lot. A high-level event or a scenario is a combination of simple events with spatial, temporal and logical relations. We proposed to define the simple events through a spatio-temporal analysis of features extracted from a low-level processing. The low level processing involves detecting, tracking and classifying moving objects. To naturally model the relations between simpler events, a Petri Nets model was used. The experimental results based on recorded parking video data sets and public data sets illustrate the performance of our approach.

In an increasingly competitive market, making well-informed decisions requires the analysis of a wide range of heterogeneous, large and complex data. This paper focuses on the emerging field of graph warehousing. Graphs are widespread structures that yield a great expressive power. They are used for modeling highly complex and interconnected domains, and efficiently solving emerging big data application. This paper presents the current status and open challenges of graph BI and analytics, and motivates the need for new warehousing frameworks aware of the topological nature of graphs. We survey the topics of graph modeling, management, processing and analysis in graph warehouses. Then we conclude by discussing future research directions and positioning them within a unified architecture of a graph BI and analytics framework.

International audience; The present research work is an in vivo study that aimed to evaluate the potential role of bioglass-chitosan (BG-CS) and bioglass-chitosan-20%ciprofloxacin (BG-CS-20Cip) in antioxidant profile and osteointegration. These scaffolds were implanted in the defect bone of femoral condyles in ovariectomized rats. The treatment with BG-CS-20Cip has shown a significantly higher stress proteins concentration in comparison with that implanted with BG-CS group. The thiol and vitamin C in BG-CS-20Cip group were significantly enhanced when compared with those in BG-CS group. The histological and physicochemical analyses highlight the BG-CS implications in the bone construction. This property was found to decrease with the presence of ciprofloxacin that caused the delay of this phenomenon. ICP-OES has revealed that the introduction of this antibiotic to the composite led to decrease bone mineralization by evaluating Ca/P ratio. The SEM results have confirmed a progressive degradation of BG-CS and BG-CS-20Cip. However, such bioresorbability and bioactivity of BG-CS was proven to be faster than those of BG-CS-20Cip. Therefore, the incorporation of ciprofloxacin in BG-CS was characterized by a delaying effect of composite dissolution and the formation of apatitic phase. The development of BG-CS as a therapeutic biomaterial protector against oxidative stress is likely to make an effective choice for the application in tissue engineering.

Due to the increasing importance and volume of highly interconnected data, such as in social or information networks, a plethora of graph mining techniques have been designed to enable the analysis of such data. In this work, we focus on the mining of associations between entity features in networks. We model each entity feature as a dimension to be analyzed. Consequently we build our approach on top of the existing graph cube framework which is an extension of the concept of the data cube to networks. Our task is particularly challenging because it requires the analysis of both the initial multidimensional network and all its subsequent aggregate forms. As soon as we deal with a big data situation it is impossible for an analyst to consider manually all the possible views of the network data. The aim of this work is to design an algorithm for the discovery of interesting patterns in large graph cubes. Thus, instead of examining all the possible aggregations manually, the proposed technique leads the analyst to the interesting associations or patterns in the multidimensional network. Furthermore, we study the application of existing algorithms from the frequent itemset mining literature on graph data and propose a mapping between the two settings.

Essential oils from aromatic plants are currently mentioned as suitable tools for excellent protection of stored grains from insect pest attacks. The present work aimed to study the processes of the synthesis insecticidal formulation with clay. The active terpenic compounds of essential oil of Eucalyptus globulus (Eg) were fixed in the palygorskite by adsorption process. Two sample types of palygorskites were used: raw and organo-palygorskite. The palygorskite clays were characterized by different physicochemical techniques including X-ray diffraction (XRD), Fourier transform infrared (FTIR) analyses, thermogravimetric analysis (TG), differential thermal analysis (DTA), Brunauer-Emmet-Teller (BET), and scanning electron microscope (SEM). Results reveal that the raw clay has a fibrous structure with impurities essential calcite. These structures and physicochemical properties of raw palygorskite and organo-palygorskite give it the potential of material adsorbent. Results show that the adsorption capacity strongly depends on affinity between terpenic compounds and organic cations rather than on interlayer distance of organo-palygorskite. The highest adsorption capacity of terpenic compounds is acquired with palygorskite interlaced by didodecyldimethylammonium bromide (DDDMA). These results validated the potential utility of the Paly-DDDMA as adsorbent fibrous clay for the retention of terpenic compounds in application of environmental preservation.

Delivering multimedia content, requiring high throughput and reduced end-to-end delay, is a hard task in Wireless Sensor Networks, due to the limited bandwidth and energy. Multipath routing is an attractive alternative to remedy to these constraints by allowing bandwidth aggregation to achieve high throughput and load balancing to reduce latency and energy consumption. However, inter-path correlation can throttle concurrent data transfer through different paths. Besides, operating under duty-cycle mode, adopted by many long-term applications, incurs additional challenges due to the intermittent unavailability of nodes. In this context, we propose CFMPR-M, a Correlation-Free MultiPath Routing protocol for multimedia traffic in duty-cycled networks, providing simple mechanisms to construct non-correlated routes towards the sink. It relies on a cross-layer interaction between MAC and routing levels, useful to avoid the drawbacks inherent to duty-cycle mode. Simulation results show the good performance of our protocol in terms of energy consumption, establishment time and control overhead.

In this paper, the authors propose a multi-criteria methodology for identifying “Crucial Know-How/Knowing-That”. Know-How and Knowing-That are two kinds of knowledge. Know-How is a disposition to perform a type of action whereas Knowing-That is a belief state and concerns a description which can be factual or propositional. The category of “crucial Know-How/Knowing-That” represents the subset of Know-How/Knowing-That sufficient for Know-How/Knowing-That capitalization. The authors are interested in special Know-How/Knowing-that called “Likely Crucial Know-How/Knowing-That” which represent the set of Know-How/Knowing-That under validation and experimentation and can be crucial in the short or medium term. For thus, a new decision class is attributed to this category of Know-How/Knowing-That. The methodology is composed of three phases: (i) the construction of the preference model of decision maker, (ii) the evaluation of “crucial Know-How/Knowing-That” and (iii) the sorting of this set of Know-How/Knowing-That. The methodology is experimented in the ASHMS organization and validated in the medical field.

ITIL is a large collection of best practices, tools and methods used in the management and handling of IT services. It's composed of five books related to the most important IT management fields. In this paper, we will place the emphasis on the Service Operation field in ITIL and more precisely, on the incident management process used for managing the life cycle of IT incidents. The main idea is to find a solution for an automated optimal planning of interventions in the incident management process. Indeed, despite the number of software solutions for incident management process, intervention planning is still a manual task due to the high complexity of its automation. In this paper, we propose two solutions for automated optimal planning of interventions in the incident management. The first is inspired by the vehicle routing problems and the second is inspired by the constraint-based problems. Eventually, we will compare between the results of these two solution.

The wide proliferation of wireless sensor networks in various domains has lead to the emergence of numerous applications with different requirements to satisfy for the well functioning. It is imperative to develop different approaches and communication protocols to meet these diverse and specific requirements while considering the most critical constraint, network lifetime. Adopting duty cycling is an efficient way to conserve energy, by allowing nodes to turn off their radio whenever possible. With these intermittent sleeping periods, it is hard to meet short delay delivery for real time traffic in duty cycled networks, since involved nodes in forwarding are not always awake. For delay intolerant applications, providing an always-on path without scarifying energy can be an effective solution. In this context, we propose a node-disjoint multipath routing algorithm, operating under duty cycled environment, to construct n complementary paths from the source towards the sink. To support urgent data transfer from sources of critical traffic, our protocol aims to offer always at least one available path while others are down. Simulation results show good performances in term of energy consumption and the number of exchanged packets control with a relative small increase in paths establishment time.

International audience; This paper presents a method for detecting and tracking phlebotominaes that are vectors for many important diseases. A method based on the Gaussian mixture model is used for Foreground/Background classification. Then, the mathematical morphology operations are used to refine theclassification results and eliminate areas that do not represent phlebotominaes. Thereafter, the Kalman filter is used for the prediction and stimation of their positions, thus the Hungarian algorithm is used for the assignment of the detected positions to tracks. The results can help us study the behavior of these insects, and to improve traps and solutions that limit their spread in case of infection. The proposed method is tested on a real phlebotominaes video sequences recorded at Pasteur institute of Tunisia, and the experimental results show the efficiency of the proposed algorithm to accurately detect the position and track phlebotominaes.

Context-awareness has gained an increasing popularity in ubiquitous computing environments as it allows automatic adaptation of protocols behavior according to context changes. Nowadays, wireless sensor networks (WSNs), deployed as a main appliance to gather contextual information, can benefit from their own context data. In such scarce resource networks, the concept of context-awareness can be exploited either to optimize resource usage or to enhance the functional behavior of operating protocols. In this paper, we investigate the benefits brought by the concept of context-awareness when exploited in duty-cycled networks, since WSNs rely mainly on power saving mode in order to prolong the lifetime of sensor nodes. We focus mainly on the broadcast operation required for data collection and routing task. To quantify these improvements, we propose a comparative study relying on our ECAB protocol, using context-awareness jointly with a duty cycle mechanism to assure an efficient multi-hop broadcasting. To this end, we compare ECAB against protocols operating without context-awareness. Results show the effectiveness of this concept to improve network performances related to energy consumption, latency and packet delivery.

Trajectories of moving objects provide crucial clues for video event analysis especially in surveillance applications. In this paper, we proposed a novel approach for detecting abnormal events in video surveillance. Our approach is based on trajectory analysis involving two phases. In the first phase, we extracted clusters of normal events through an agglomerative hierarchical clustering of saved trajectories that were of different lengths, of different local time shifts and containing noise. Then, for each cluster a model was established. In the second phase, we aimed to classify a new event as normal or abnormal one. To achieve this objective, a comparison was performed with the extracted clusters' models thereby reducing the complexity and accelerating the classification process. Experiments were conducted to demonstrate the efficacy and the performance of our approach.

The detection of abnormal events is a major challenge in video surveillance systems. In most of the cases, it is based on the analysis of the trajectories of moving objects in a controlled scene. The existing works rely on two phases. Firstly, they extract normal/abnormal clusters from saved trajectories through an unsupervised clustering algorithm. In the second phase, they consider a new detected trajectory and classify it as either normal or abnormal. In both phases, they need to compute similarity between trajectories. Thus, measuring such a similarity is a critical step while analyzing trajectories since it affects the quality of further applications such as clustering and classification. Despite the differences of the measured distances, authors claim the performance of the adopted distance. In this paper, we present a comparative experimental study on the efficiency of four distances widely used as trajectories’ similarity measure. Particularly, we examine the impact of the use of these distances on the quality of trajectory clustering. The experimental results demonstrate that the Longest Common SubSequence (LCSS) distance is the most accurate and efficient for the clustering task even in the case of different sampling rates and noise.

International audience; Graph coloring was exploited in wireless sensor networks to solve many optimization problems, mainly related to channel assignment. In this paper, we propose to use coloring to jointly manage channel access and routing to the sink. We introduce CHRA, a coloring based hierarchical routing approach. Coloring is exploited to avoid interferences and also to schedule nodes transmissions to the sink. We provide an analytical study assessing the performance of CHRA and present an investigation of various coloring heuristics to study their impact on CHRA performances on maintaining the network connectivity and coverage, while reducing the energy consumption.

This paper discusses the issues of classification, evaluation and cartography of organizational knowledge in the medical field. Its aim is to propose an Organizational Know-How/Knowing That Decision Support System (O2K-DSS) which can be applied to practical decision situations. O2K-DSS aims to propose a preference model based on multi-criteria decision support tools which allow the selection, the classification and the sorting of decision objects like know-how/knowing that in our case. Our goal is to propose a new category of decision class for ‘likely crucial know-how’/‘likely crucial knowing that’ which represents the subset of knowledge insufficient for knowledge capitalisation at time t. In fact, we classify know-how/knowing that into three decision classes: (1) the first class Cl1 for ‘non crucial know-how’/‘non crucial knowing that’ which represents the subset of knowledge whose level of validation is sufficient for not capitalising it, (2) the second class Cl2 for ‘likely crucial know-how’/‘likely ...

International audience; Wireless sensor networks (WSN) have received significant attention over the last few years as they afford a growing number of applications in various fields. At the same time, these networks provide numerous challenges due to their constraints, primarily related to energy scarcity. To overcome energy waste caused by collisions and contention based algorithm, the channel assignment mechanisms, like TDMA, seem to be an effective way for scheduling node transmissions. To solve channel assignment problems, graph coloring theory has been exploited in many research works, primarily in order to assure collision-free communications. In this paper, we present a novel distributed coloring algorithm for WSNs taking into account constraints of a real WSN environment. Our collision aware coloring algorithm assures a 2 hop nodes coloring, in a deterministic time execution, without requiring a neighborhood discovering phase. Performance evaluation results have shown the effectivness of our algorithm in terms of exchanged control packets per node as well as the number of colors used.

International audience; Graph coloring was exploited in wireless sensor networks to solve many optimization problems. These problems are related in general to channel assignment. In this paper, we propose to jointly use coloring for routing purposes. We introduce CHRA a coloring based hierarchical routing approach. Coloring is exploited to avoid interferences and also to schedule nodes transmissions to sink. We provide an analytical and experimental study assessing the performance of CHRA in terms of end-to-end delay and energy consumption. In particular, we find that CHRA performs better than LEACH, a well established hierarchical routing protocol.

The assessment of building thermal comfort quality in the Mediterranean context necessitates an accurate knowledge of air temperature and velocity fields inside the space. Also, these thermal and airflow aspects must be considered in combination because of their very strong interdependence. In this particular context, a three-dimensional calculation model of coupled heat transfer and airflow calculation has been developed, which enables the evaluation of temperature field and airflow pattern inside unconditioned buildings under transient conditions, taking into account external conditions. This approach is based on a temperature and pressure driven zonal airflow model, coupled with a thermal model founded on the coupling of reduced-order state models. By combining this with a thermal comfort model it is possible to evaluate the thermal quality of buildings by the prediction of a comfort vote. This paper presents an application of the coupled simulation tool dealing with the influence of a night na...

This paper presents a three-dimensional zonal model, ZAER, for heat transfer and air flow calculations. It is based on an intermediate approach between single-air-node and CFD models. The indoor air volume is divided into macroscopic homogeneous zones. Heat and mass balance equations are written for each zone, while the mass flow rates across the interfaces are calculated by power pressure laws. The simulation tool ZAER allows the determination of temperature fields and air flow distributions inside unconditioned buildings, taking into account external boundary conditions. We also present an experimental validation of the model by comparing its predictions with experimental data obtained from measurements on the experimental cell Minibat (CETHIL, INSA Lyon Laboratory), for different configurations. The results obtained are in good agreement with experimental data, and suggest that the ZAER model is an appropriate tool to assess satisfactorily temperature heterogeneity and air movement within a room.