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Purpose The purpose of this study is to analyze the CEO compensation sensitivity to firm performance, termed as the pay-for-performance sensitivity (PPS) in the Tunisian context and to test the robustness of this relationship when corporate governance (CG) mechanisms are considered. Design/methodology/approach The consideration of past executive pay as one of the explanatory variables makes this estimation model a dynamic one. Furthermore, to avoid the problem of endogeneity, this study uses the system-GMM estimator developed by Blundell and Bond (1998). For robustness check, this study aims to use a simultaneous equation approach (three-stage least squares [3SLS]) to estimate the link between performance and CEO pay with a set of CG mechanisms to control for possible simultaneous interdependencies. Findings Using a sample of 336 firm-years from Tunisia over the 2009–2015 periods, this study finds strong evidence that the pay-performance relationship is insignificant and negative, and it becomes more negative or remains insignificant after introducing CG mechanisms consistently with the managerial power approach. The findings are robust to the use of alternative performance measures. This study provides new empirical evidence that CEOs of Tunisian firms abuse extracting rents independently of firm performance. Originality/value This study contributes to the unexamined research on PPS in a frontier market. This study also shows the ineffectiveness of the Tunisian CG structure and thus recommends for the legislator to impose a mandatory CG guide.

The COVID-19 disease is a multisystem disease due in part to the vascular endothelium injury. Lasting effects and long-term sequelae could persist after the infection and may be due to persistent endothelial dysfunction. Our study focused on the evaluation of endothelial quality index (EQI) by finger thermal monitoring with E4 diagnosis Polymath in a large cohort of long COVID-19 patients to determine whether long-covid 19 symptoms are associated with endothelial dysfunction. This is a cross-sectional multicenter observational study with prospective recruitment of patients. A total of 798 patients were included in this study. A total of 618 patients (77.4%) had long COVID-19 symptoms. The mean EQI was 2.02 ± 0.99 IC95% [1.95–2.08]. A total of 397 (49.7%) patients had impaired EQI. Fatigue, chest pain, and neuro-cognitive difficulties were significantly associated with endothelium dysfunction with an EQI

Background Cystic echinococcosis (CE) has a worldwide distribution and is especially prevalent in North African countries. With a mean annual surgical incidence (ASI) of CE of 12.7 per 100,000 inhabitants, Tunisia is one of the most CE endemic countries in the Mediterranean area. Tataouine governorate is considered to be the most CE hypoendemic region in Tunisia (ASI = 0.92) despite favourable socioeconomic conditions that enable maintenance of the Echinococcus granulosussensu lato (s.l.) life-cycle and a significant environmental contamination with E. granulosuss.l. eggs. The aim of this study was to assess human CE seroprevalence, prevalence of CE in food animals and environmental contamination by E. granulosus s.l. eggs in different districts of Tataouine governorate. Methods This study was conducted from January to December 2018. A total of 374 human sera samples were tested for the presence of immunoglobulin G antibodies against E. granulosus using a commercial ELISA kit. Specimens were also collected from animals slaughtered at the Tataouine abattoir (n = 8609) and examined for the presence of hydatid cysts; 111 hydatid cysts were genotyped. Eggs of E. granulosuss.l. were identified by PCR and DNA sequencing from dog faecal samples (n = 288). Results Serological tests showed that 8.5% of the sera samples tested were positive for E. granulosus-specific antibodies. The average prevalence of hydatidosis in livestock was 1.6%, and CE infection was more prevalent in cattle than in sheep, goats and dromedaries. The contamination rate of dog faeces by E. granulosus sensu stricto eggs varied significantly from 0 to 23.5% depending on the collection area. Molecular analyses only revealed the presence of the G1 genotype for cysts and eggs. Conclusions Based on our findings, CE is likely to be more endemic in the Tataouine governorate than previously described. Thus, to implement an effective control programme against CE, a national survey should be carried out to determine human CE prevalence in the different Tunisian governorates. Graphical Abstract

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.

Ensuring that an active path is provided at all times in a Wireless Sensor Network (WSN) is fundamental for securing the timely delivery of critical data and maintaining the quality of service required to effectively support delay-sensitive applications. In duty cycling mode, ensuring such a path becomes a real challenge as the activity scheduling of different nodes should be regulated and adjusted to provide a pipe-lined node activity from source to sink. Furthermore, some transmission delays may be incurred in waiting for a next-hop node to be awakened. The data transfer time is mainly influenced by the performance of both MAC and routing protocols; an inter-layer design allowing efficient coordination between the MAC and routing is then necessary to make the appropriate decisions relating to the selection of the next hop and the adjustment of the duty cycle. In this article, we provide a cross-layer multi-path routing approach designed to support the transfer of critical data over duty-cycled WSN networks. This approach establishes multi-node disjoint paths with complementary duty-cycling schedules to ensure the availability of an active path capable of transmitting critical data at all times. It relies on a tight cooperation between the routing and MAC layers in order to appropriately adjust and regulate the wake-up schedules of involved nodes in the forwarding phase. We analytically proved the correctness of the proposed scheduling adjustment rules. We conducted extensive simulations to show the ability of the CL-NDRECT to provide a viable trade-off between energy conservation and real time responsiveness. Simulation results show that CL-NDRECT provides around 65% cumulative energy saving during route establishment and data transfer compared to the always-on multipath approach at the cost of around 10% increase in response time.

Abnormal event detection has attracted great research attention in video surveillance. In this paper, the authors presented a robust method of trajectories clustering for abnormal event detection. This method is based on two layers and benefits from two well-known clustering algorithms: the agglomerative hierarchical clustering and the k-means clustering. Facing to the challenges related to the trajectories, e.g., different sizes, the authors introduce a preprocessing step to unify their sizes and reduce their dimensionality. The experimental results show the performance and accuracy of their proposed method.

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.

Zoonotic cutaneous leishmaniasis (ZCL) is endemic in central Tunisia and is more prevalent in rural agricultural areas. The aim of this work was to determine ZCL prevalence among farmers and to test their availability to take ownership of the problem and participate actively to fight and address the disease.A sample of farmers from Sidi Bouzid, central Tunisia, was selected randomly. Farmers were interviewed using a standardized questionnaire about ZCL lesion occurrence, its date of onset among family members, and the farmers' availability to contribute to fighting this disease.ZCL occurred in at least one of the family members of 38.5% interviewed farmers. The disease was endemic with recurrent epidemics every 4 or 5 years. ZCL among farmers was associated with irrigation management. With regard to ZCL preventive measures, the majority of farmers agreed and expressed willingness to collaborate (93.1%), to follow health care facilities instructions (73.1%), and to join the nongovernmental organization (NGO) (56.9%). However, they did not agree to reduce irrigation activities mainly at night, to live far from their irrigated fields, or to sleep out of their houses at night.ZCL is more prevalent in farmers engaged in irrigation activities. Farmers are not agreeable to reducing their activity to avoid exposure to the sand fly bites. Thus, population involvement and commitment is required to implement effective control measures to fight and address ZCL.

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.

With growing water shortages, agriculture faces the challenge of increasing water productivity (WP). In this work, WP of two main crops, peach and olive, is evaluated for different cultivars and deficit irrigation practices. WP in peach was estimated over 4-7 years for three cultivars (early, mid-season and late-maturing), two rootstocks and two deficit irrigation strategies. In terms of yield/total water supply, the late maturing cultivar subjected to mild deficit irrigation, gave the highest WP (4.1 kg m-3), compared to the mid-season (3.0 kg m-3) and early cultivar (1.9 kg m-3). Full irrigation reduced slightly the performance of the most productive cultivar (3.7 kg m-3). Performances of early and mid-season cultivars were affected by rootstock. Interaction between mild deficit irrigation and vigorous rootstock induced better WP. Experimental work in olives targeted WP under contrasted environments. In northern Tunisia (450 mm annual rainfall), average yield for three cultivars ('Picholine', 'Chetoui' and 'Mansanille') planted at 6×6 m spacing on a clay soil, varied between 3.9-4.7 and 4.7-6.1 t ha-1, respectively when irrigation was increased from 100 to 200 mm. Under these restrictive conditions, the highest WP values were obtained for 'Picholine', respectively 0.77 and 0.86 kg m-3. However, in southern Tunisia (200 mm rainfall), the 'Chemlali' cultivar, conducted under intensive planting (4×4 m) on sandy soils, showed a drastic increase in production. With irrigation water supply of 200-400 mm, average yield reached 10-12 t ha-1, and WP 2.1 kg m-3. Adaptation to water scarcity is discussed on the basis of the obtained results.

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...

Lavandula aspic L. is a strongly aromatic shrub plant of the Lamiaceae family and traditionally used in herbal medicine for the treatment of several skin disorders, including wounds, burns, and ulcers. The present study aimed to investigate the composition and in vitro antioxidant activity of lavender essential oil. In addition, it aimed to evaluate the excision wound healing activity and antioxidant property of a Lavandula aspic L. essential oil formulated in ointment using a rat model. The rats were divided into five groups of six animals each. The test groups were topically treated with the vehicle, lavender ointment (4%) and a reference drug, while the control group was left untreated. Wound healing efficiency was determined by monitoring morphological and biochemical parameters and skin histological analysis. Wound contraction and protein synthesis were also determined. Antioxidant activity was assessed by the determination of MDA rates and antioxidant enzymes (GPx, catalase and superoxide dismutase). The treatment with lavender ointment was noted to significantly enhance wound contraction rate (98%) and protein synthesis. Overall, the results provided strong support for the effective wound healing activity of lavender ointment, making it a promising candidate for future application as a therapeutic agent in tissue repairing processes associated with skin injuries.

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.

Background Infective endocarditis (IE) is a life threatening complication in patients with congenital heart disease (CHD). Purpose We aimed to determine the incidence, clinical features and outcomes of IE in patients with CHD. Methods A retrospective single centre review of patients who presented IE (defined by modified Duke criteria) admitted on the cardiology B department of Fattouma Bourguiba University Hospital between January 1998 and march 2015. Results Among the 235 patients included, 10.2% (24 patients) had CHD. The most frequent CHD was ventricular septal defect (30%). Patients with CHD had lower mean age (24 ± 10 years vs. 38 ± 17 years, P Conclusion IE in patients with CHD occurs at young age. It implicates most commonly right heart and aortic valve. Its prognosis is not different from IE in the general population but has higher recurrence rate.

Operating under duty-cycle mode allows wireless sensor networks to prolong their lifetime. However, this working pattern, with the temporary unavailability of nodes, brings challenges to the network design, mainly for a fundamental service like flooding. The challenging task is to authorize sensors to adopt a duty-cycle mode without inflicting any negative impact on the network performances. Context-awareness offers to sensors the ability to adapt their functional behavior according to many contexts in order to cope with network dynamics. In this context, the authors propose an Enhanced-Efficient Context-Aware Multi-hop Broadcast (E-ECAB) protocol, which relies on multi contextual information to optimize resources usage and satisfy the application requirements in a duty-cycled environment. The authors proved that only one transmission is required to achieve the broadcast operation in almost all situations. Simulation results show that E-ECAB achieves a significant improvement compared to previous work in terms of throughput and end-to-end delay without sacrificing energy efficiency.

Productivity of peach cultivars with different ripening seasons was studied under the growers’ conventional conditions of Tunisia. Experiments were performed in northern Tunisia (36° 41ʹ N, 10° 15ʹ E). Performances of Flordastar, Royal Glory, and Carnival as respectively early, mid-season, and late ripening cultivars were evaluated under the grower’s conventional irrigation programs. Fruit growth, yield, water supply, and water productivity were determined through four years. For the three cultivars, Flordastar, Royal Glory, and Carnival, fruit maturity was achieved at 650, 1100, and 2200 GDD, respectively. Average yields were 17.4, 29.8, and 41.1 t ha–1 and mean values of water productivity were 1.9, 3.1, and 3.6 kg fresh yield m–3 for early, mid-season, and late cultivars, respectively. Results of agronomic performances evaluation at the farm scale provided a reference on the behavior of early, mid-season, and late cultivars of peach in irrigated orchards in semi-arid conditions.

Currently, the larviculture of many marine fish species with small-sized larvae depends for a short time after hatching, on the supply of high-quality live zooplankton to ensure high survival and growth rates. During the last few decades, the research community has made great efforts to develop artificial diets, which can completely substitute live prey. However, studies aimed at determining optimal levels of minerals in marine larvae compound feeds and the potential of novel delivery vectors for mineral acquisition has only very recently begun. Recently, the agro-food industry has developed several nano-delivery systems, which could be used for animal feed, too. Delivery through nano-encapsulation of minerals and feed additives would protect the bioactive molecules during feed manufacturing and fish feeding and allow an efficient acquisition of active substances into biological system. The idea is that dietary minerals in the form of nanoparticles may enter cells more easily than their larger counterparts enter and thus speed up their assimilation in fish. Accordingly, we evaluated the efficacy of early weaning diets fortified with organic, inorganic, or nanoparticle forms of trace minerals (Se, Zn, and Mn) in gilthead seabream (Sparus aurata) larvae. We tested four experimental diets: a trace mineral-deficient control diet, and three diets supplemented with different forms of trace minerals. At the end of the feeding trial, larvae growth performance and ossification, and the level of expression of six target genes (SLC11A2β, dmt1, BMP2, OC, SOD, GPX), were evaluated. Our data demonstrated that weaning diets supplemented with Mn, Se, and Zn in amino acid-chelated (organic) or nanoparticle form were more effective than diets supplemented with inorganic form of minerals to promote bone mineralization, and prevent skeletal anomalies in seabream larvae. Furthermore, nanometals markedly improved larval stress resistance in comparison to inorganic minerals and upregulated mRNA copy number of OC gene. The expression of this gene was strongly correlated with mineralization degree, thus confirming its potency as a good marker of bone mineralization in gilthead seabream larvae.

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.

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.

Climate changes are expected to have a great and negative impact on agriculture in Mediterranean region. In this region, olive industry plays a key role at regional and national level as in Tunisia. With expected increasing temperature, the impact of climate change on the phonological behavior of the olive cultivars was evaluated in the main production region in central Tunisia (34°56′08″N, 10°36′54″E) during 2005–2015.The relationships between the budburst and flowering dates and climatic variations were investigated for the main local (Chemlali, Chemchali, Oueslati and Chetoui) and foreign (Koroneiki and Arbequina) olive cultivars to state their adaptability to warm area climate. Chilling was computed as chill portions (CP) from October to budburst using Dynamic Model, whereas heat accumulation was quantified as growing degree hours (GDH) from budburst to the beginning of flowering. As a result, variable budburst and flowering dates of olive cultivars were obtained related to the climatic conditions occurring each year. ‘Chemlali’ and ‘Arbequina’ seemed to be the precocious cultivars with an average budburst date of DOY-71 (March-12), whereas ‘Chemchali’ and ‘Koroneiki’ were the most late with an average budburst dates of DOY-80 and DOY-81 (March21-22). The beginning of flowering occurred from DOY-93 (3-April) to DOY-126 (6-May), where ‘Chemchali’ seemed, also, to be the latest one. Winter chill impacted significantly olive flowering with a positive correlation between flowering date and chill accumulation. A tendency for advancing flowering of local and foreign olive cultivars occurred subsequent a lack of winter chill. Trends for increasing heat accumulation with increasing chilling were observed in exponential manner to achieve flowering of olive cultivars. Moreover, winter temperature, appeared to be one of the most important variables in determining flowering time of olive cultivars mainly when quarterly and monthly mean temperatures were considered. In conclusion, this investigation is the first database concerning olive cultivars originated from different geographical areas and grown in a warm area. It revealed that olive cultivars behaved differently with contrasting chilling and heat accumulations and in years with extreme climatic conditions. It will be more interesting to consider the important genetic diversity of olive tree to mitigate the harmful effect of increasing temperature in the future.

The accurate modeling of solar heat gains is an important factor to evaluate precisely both thermal comfort and energy consumption in a building. This paper aims at introducing a methodology to calculate the distribution of incoming solar energy on the internal surfaces of closed spaces with multiple openings. The numerical model is evaluated by comparing the obtained results with published data. In order to justify and prove its functionality, it has been linked to the building simulation software ZAER, which assumes that all the sunspot projection through a glazed window is located on the floor. The coupled simulation tool is indeed a useful tool, having a physical basis with relatively little extra computational effort. By linking this tool with a thermal comfort model, we study the influence of a glazed wall belonging to a south oriented room upon the winter thermal comfort of an unconditioned Tunisian building.

Increasing water scarcity has changed the primary objective of farmers from seeking maximum yields to preservation of the agricultural system. Deficit irrigation may be used to reduce water use; however, the adoption of this technique requires precise knowledge of tree water status and the implementation of specific irrigation skills to reduce the impact of stress. The present work investigates the water status of peach in relation to water supply under high evaporative demand with the objective of developing practical methods for deficit irrigation scheduling. A field experiment was carried out in 2006 and 2008 at the research station of INAT-Mornag in northern Tunisia. Drip-irrigated mid-season cultivar Royal Glory grafted on GF677 was used. Total water applied during the dry season was in the range 50–100 mm in 2006 and 200–300 mm in 2008. Predawn ( Ψ PD ), midday ( Ψ m ), and stem ( Ψ stem ) water potentials, weather factors, irrigation and soil moisture were monitored. Results show that ET c was 524 and 603 mm for 2006 and 2008, respectively, under ET o of 1171 and 1180 mm. With highly variable quantity and distribution of precipitation, the contribution of soil reservoir water is essential to regulate evapotranspiration of trees. In 2006, applied water covered 0.35–0.50 ET c during the initial-mid season period and 0.60–0.65 ET c in postharvest. Irrigation was adjusted in 2008 to cover 0.55–0.75 ET c during vegetative and fruit growth and 0.50–0.65 ET c during postharvest. Water supply indices were defined as ratios between cumulated water supply ( I + P ) and ET o over different periods of time. Seasonal ( K s ), 30-days ( K 30 ), 15-days ( K 15 ), and 7-days ( K 7 ) were calculated over the cropping season starting in October. Tree water status and fraction of available water (FAW) was relatively high early in the season but declined to extremely low values during the high evaporative demand period and during the periods without irrigation. Extreme low values of −1.28, −2.13 and −2.51 MPa, respectively for Ψ PD , Ψ m and Ψ stem were observed during the high evaporative demand period. Relationships were significant between Ψ stem and Ψ PD and Ψ m . A good correlation was also observed between FAW and Ψ PD , Ψ m and Ψ stem . Analysis of the relationships between water supply indices ( K 7 , K 15 , K 30 and K s ) and tree water potential shows a high correlation between Ψ stem and K s . Upper and lower limits of 0.8 and 0.5 could be adopted for K s in order to maintain water status of peach trees within acceptable level corresponding to moderate and severe water deficit.

Long-term effects of deficit irrigation on yield and water productivity of peach trees (Prunus persica L., cv. Carnival) grown in a semi-arid climate in northern Tunisia (36°41'N, 10°15'E) were investigated. Continuous deficit irrigation (Di I-II-III) was compared with the grower's irrigation programme (Control). The effects of Di I-II-III on yield and fruit quality were analysed. The benefit of deficit irrigation strategy in terms of water saving and agricultural water productivity (Wp) were estimated. Different relationships were investigated between yield, fruit quality, and Wp, and irrigation and total water supply. In reference to the high water needs of late cultivar Carnival for irrigation, Di I-II-III led to an important water saving (33%) with a yield reduction of 14%. Yield and fruit quality seemed to be related to watering regimes. Fruit dry matter (DM) decreased linearly with irrigation water supply for both Control and Di I-II-III. Unlike yield, Di I-II-III improved the dry weight of fruit. C...

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.

Resume Introduction L’analgesie postoperatoire apres une cesarienne est essentielle. La morphine par voie intrathecale (IT) a faible dose est la technique de reference pour l’analgesie apres cesarienne. Cependant, sa duree d’action est limitee aux 24 premieres heures postoperatoires. L’adjonction de certains adjuvants en IT pourrait ameliorer la duree et la qualite de l’analgesie. Objectif Evaluer l’effet de l’adjonction du sulfate de magnesium a la morphine, administre par voie IT sur la duree de l’analgesie apres une rachianesthesie pour cesarienne. Type d’etude Etude prospective, randomisee, en double insu. Parturientes et methodes Apres l’accord du comite local d’ethique et obtention du consentement eclaire, 105 parturientes, ASA I ou II, proposees pour cesarienne programmee ou semi-urgente, ont ete incluses dans cette etude. Elles ont ete randomisees en trois groupes : (1) groupe Morphine (M) : 10 mg de bupivacaine isobare a 0,5 % (2 ml) + 100 μg morphine (1 ml) + 10 μg fentanyl (0,1 ml) + 1 ml serum physiologique, (2) groupe Magnesium (Mg) : 10 mg de bupivacaine isobare a 0,5 % (2 ml) + 100 mg de MgSO4 (1 ml) + 10 μg fentanyl (0,1 ml) + 1 ml serum physiologique, (3) groupe Morphine + Magnesium (M + Mg) : 10 mg de bupivacaine isobare a 0,5 % (2 ml) + 100 mg de MgSO4 (1 ml) + 100 μg morphine (1 ml) + 10 μg fentanyl (0,1 ml). Le critere de jugement principal etait le delai entre la realisation de la rachianesthesie (T0) et la premiere demande analgesique. Nous avons recueilli egalement les scores de la douleur (echelle visuelle analogique [Eva]) a 0, 1, 2, 4 heures puis toutes les quatre heures jusqu’a la 36e heure postoperatoire, la survenue des effets indesirables (nausees, vomissements, prurit, depression respiratoire) et la satisfaction des parturientes. Resultats Le delai de la premiere demande d’antalgique etait de 28 ± 8 heures dans le groupe MMg contre 19 ± 6 heures dans le groupe M et 7 ± 6 heures dans le groupe Mg (p Conclusion Chez les parturientes operees de cesarienne sous rachianesthesie, l’adjonction de 100 mg de sulfate de magnesium a 100 μg de morphine en IT prolonge significativement la duree de l’analgesie postoperatoire et reduit les scores de la douleur sans augmenter l’incidence des effets indesirables par rapport a la morphine ou au sulfate de magnesium seul.

The assessment of building thermal comfort quality in the Mediterranean context necessitates detailed information concerning local air speed and temperature inside the space. We have extended the three-dimensional zonal model ZAER (Zonal AERial model) to enable predictions of air flow pattern and thermal distributions between and within rooms. Numerical simulations from the new program have been compared with data obtained from measurements on the experimental cell Minibat (CETHIL, INSA Lyon laboratory) and with the prediction of another zonal model as well as a computational fluid dynamics (CFD) tool. The comparison indicates that this new program is an effective model for predicting air flow and temperature distribution in a partitioned building. By coupling ZAER with a thermal comfort model, we study the influence of a passive solar component belonging to a south-oriented room upon the winter thermal comfort of an unconditioned Tunisian dwelling. The obtained results show that this simulation tool has the potential to describe realistically the thermal comfort within a dwelling, and that a Trombe wall can be a useful heating component to improve thermal winter comfort in the Tunisian context, even in another room.

Convective heat and mass transfer through large internal openings play an important role in the aero-thermal behaviour of buildings. These phenomena become even more dominant in the case of naturally ventilated buildings. The three-dimensional zonal model of coupled heat transfer and air flow calculations ZAER (Zonal AERial model) has been extended to enable predictions of variations in temperature distributions and airflows between and within rooms subjected to natural convection. This new model has been validated by comparison with experimental measurements and with results from the zonal model of Wurtz and a computational fluid dynamic (CFD) tool. A sensitivity analysis with respect to physical parameters is also presented. The results indicate that this simulation model is an effective tool for predicting airflow and temperature distribution within a partitioned dwelling in the case of natural convection.

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.

While it is possible to check the energy performance of a given building by means of several available methods, the inverse problem of determining the optimum configuration given a desired performance is more difficult to solve. In the Mediterranean region this problem is more complex due to the following two reasons: the air-conditioning load is as important as the heating load, and the energy needs depend on a high number of architectural parameters which have different, even contradictory, effects on summer and winter loads. In this paper we present an optimization algorithm that couples pseudo-random optimization techniques, the genetic algorithms (GA), with a simplified tool for building thermal evaluation (CHEOPS) for the purpose of minimizing the energy consumption of Mediterranean buildings. Since increasing the energy performance usually requires the use of special devices resulting in a high construction cost, we also propose to use GA for the purpose of economical optimization.

Duty-cycling scheme consists in switching between active and sleeping modes. While this technique is widely exploited in WSNs to reduce power consumption, It raises several challenges especially for broadcast communications. In fact, as many neighboring nodes are involved in the communication, keeping them all active during a specific period of time requires a preliminary synchronization process which is a complex task and causes extra overhead. In this context, we propose an Efficient Context-Aware multi-hop Broadcasting (ECAB) over asynchronous duty cycled networks. ECAB exploits both the neighborhood knowledge and the traffic load conditions to regulate node behaviors and dynamically adjust duty-cycling schedules. Our objective is to reduce energy consumption without performances penalties. Simulation results show that ECAB outperforms RI-MAC and greatly improves energy consumption compared to broadcast under always-on networks with small degradation related to end-to-end delay and packet delivery.

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.

A thermal comfort field survey has been conducted in five towns from two climatic zones in Tunisia. Two hundred persons were concerned by this survey. They have been asked in their houses and working places at their normal living conditions once each month during 1 year. The selected sample of buildings has been chosen among free running buildings. Only few office buildings were equipped with heating systems but not with air conditioning systems. The survey results have been processed and correlations between sensations and globe temperatures have been found. The comfort temperatures have been calculated for each location and each month. They have been correlated with the mean outdoor air temperature and with the outdoors running mean temperature. Robust correlations have been found. The description of this survey and the methodology of data analysis are described in details in this paper. The main results are discussed and compared with those of similar surveys conducted in different geographic locations.

This paper presents a method for the accurate detection of the positions of moving phlebotomenae (sand-flies), and the extraction of their complete shape. The proposed method is based on the background subtraction approach, with a statistical background model found using Gaussian mixture model. Furthermore, a method based on the maximization of interclass variance, is used to eliminate wings of the phlebotomenae and then detect accurately its position. Results are further used to study the behaviour of phlebotomenae, and subsequently, improve the traps to fight against many diseases transmitted by these insects, especially leishmaniasis. The experimental results show the efficiency of the proposed algorithm to accurately detect the position and extract the complete shape of moving phlebotomenaes even in case of very blurry ones.

The thermal regulation which is under preparation for Tunisian buildings is based on the thermal comfort level achieved in the building by natural means, since residential buildings are rarely heated or cooled. This paper investigates the appropriate building solutions in order to reach the highest possible comfort level, while keeping the overrun cost of construction at a reduced level.

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.

Graphs are ubiquitous data structures commonly used to represent highly connected data. Many real-world applications, such as social and biological networks, are modeled as graphs. To answer the surge for graph data management, many graph database solutions were developed. These databases are commonly classified as NoSQL graph databases, and they provide better support for graph data management than their relational counterparts. However, each of these databases implement their own operational graph data model, which differ among the products. Further, there is no commonly agreed conceptual model for graph databases. In this paper, we introduce a novel conceptual model for graph databases. The aim of our model is to provide analysts with a set of simple, well-defined, and adaptable conceptual components to perform rich analysis tasks. These components take into account the evolving aspect of the graph. Our model is analytics-oriented, flexible and incremental, enabling analysis over evolving graph data. The proposed model provides a typing mechanism for the underlying graph, and formally defines the minimal set of data structures and operators needed to analyze the graph.