A delayed SIR epidemic model with a general incidence rate

A delayed SIR epidemic model with a generalized incidence rate is studied. The time delay represents the incubation period. The threshold parameter, $R_0(\tau)$ is obtained which determines whether the disease is extinct or not. Throughout the paper, we mainly use the technique of Lyapunov functional to establish the global stability of both the disease-free and endemic equilibrium

Sensitive attribute prediction for social networks users

International audienceSocial networks are popular means of data sharing but they are vulnerable to privacy breaches. For instance, relating users with similar profiles an entity can predict personal data with high probability. We present SONSAI a tool to help Facebook users to protect their private information from these inferences. The system samples a subnetwork centered on the user, cleanses the collected public data and predicts user sensitive attribute values by leveraging machine learning techniques. Since SONSAI displays the most relevant attributes exploited by each inference, the user can modify them to prevent undesirable inferences. The tool is designed to perform reasonably with the limited resources of a personal computer, by collecting and processing a relatively small relevant part of network data

Pyocele du cornet moyen : a propos d’un cas

Introduction : Les mucocèles sont des formations kystiques bénignes mais expansives, tapissées par un épithélium respiratoire, sans connexion avec les cavités sinusiennes ou nasales. Elles se développent le plus souvent dans le complexe ethmoïdofrontal. Le terme pyocèle correspond à une mucocèle dont le contenu est infecté. La localisation turbinale moyenne est exceptionnelle.Observation : Nous rapportons l’observation d’un patient âgé de 75 ans qui se plaignait d’une obstruction nasale chronique gauche. L’examen clinique montrait un cornet moyen élargi obstruant la totalité de la fosse nasale gauche. L’Imagerie (TDM et IRM) a révélée une formation ovalaire d’allure kystique expansive développée aux dépens du cornet moyen, associée à un polype postérieur. Le diagnostic de mucocèle sur concha bullosa a été porté. Le patient a été opéré par voie endonasale avec marsupialisation et polypectomie. Les suites opératoires étaient simples avec amélioration des signes cliniques.Conclusion : Les pyocèles du cornet moyen sont des lésions rares bénignes, toutefois destructrices. Un bilan radiologique est indispensable pour guider le choix du traitement chirurgical. La voie endonasale reste le traitement de référence pour cette pathologie.Mots clés : Concha bullosa, Pyocèle, Obstruction nasaleIntroduction : A mucocele is an epithelium-lined cavity that contains mucus that fills the sinus and is capable of expansion. The majority of mucoceles are situated in the frontal and/or ethmoid sinuses. A pyocele occurs when a mucocele becomes infected. Concha bullosa mucopyocele is a rare entity that presents with persistent nasal symptoms.Case report : This paper presents patient aged 75 who were admitted with persistent nasal complaints. Anterior rhinoscopy showed enlarged middle turbinates obstructing the nasal cavities. MRI and CT Scann revealed expansif cystic lesion in the middle turbinate with a nasal polyp. With the diagnosis of concha bullosa mucocele, lateral part of the affected middle turbinate and the polyp were resected with an endoscopic approach. There were no intraoperative or postoperative complications. Nasal obstruction vanished postoperatively.Conclusion: Mucopyocele of middle turbinate are rare benign lesions. Radiological assessment is essential to guide the choice of surgical treatment. Endonasal approach is the standard treatment for this disease.Key words : Concha bullosa, Pyocele, Nasal obstructio

An Ambulance Service evaluation of Quality Control Measures based on patients‘ perception in Qatar

Background: The lack of healthcare quality management poses significant legal and financial implications 1,2 . A proactive approach to systems improvement seems warranted and reasonable. It is not clear if current quality control measures are perceived by patients. The study aims to understand if any correlation exists in this respect in the context of patients using the Hamad Medical Corporation Ambulance Service in Qatar. Methods: A survey was distributed to adult patients transported by the Ambulance Service's emergency division to the Hamad General Hospital's See and Treat unit in Doha (n = 255). The patients had to be free from serious injury/illness, fully conscious, and with re-collection of the service received. The original SERVQUAL model 3 consisting of 5 dimensions (Reliability/Assurance/Tangibility/Empathy/Responsiveness) was modified and a 6th dimension (Quality Control) was added. The Spearman's rank correlation was used to test the strength between quality control (QC) and service quality responses. Results: The mean age was 33.46 years ( ± 9.62). Patients’ continent of origin distribution is presented in Table 1. The QC dimension was correlated with that of the SERVQUAL dimensions presented in Table 2. Most of the SERQUAL dimensions had strong correlations with QC. Interestingly, there was a weak correlation between Assurance/QC and a moderate correlation between Tangibility/QC. The results seem to be driven by providing service within promised timeframes, access to care, and patients’ perception of ambulance staff's willingness to help. Conclusion: An awareness of the variables with strong correlations is indicative of the significant impact QC measures have and the associated perception of importance held by patients. This study sheds light on the importance of evaluating quality processes and limiting internal costs. The number of patients by continent of origin did not enable valid statistical tests based on that variable. The Ambulance Service's QC measures appear to maintain favorable patients’ perceptions of services received

Two-phase preference disclosure in attributed social networks

International audienceIn order to demonstrate privacy threats in social networks we show how to infer user preferences by random walks in a multiple graph representing simultaneously attributes and relationships links. For the approach to scale in a rst phase we reduce the space of attribute values by partition in balanced homogeneous clusters. Following the Deepwalk approach, the random walks are considered as sentences. Hence unsu-pervised learning techniques from natural languages processing can be employed in second phase to deduce semantic similarities of some attributes. We conduct initial experiments on real datasets to evaluate our approach

Online link disclosure strategies for social networks

International audienceWhile online social networks have become an important channel for social interactions, they also raise ethical and privacy issues. A well known fact is that social networks leak information, that may be sensitive, about users. However, performing accurate real world online privacy attacks in a reasonable time frame remains a challenging task. In this paper we address the problem of rapidly disclosing many friendship links using only legitimate queries (i.e., queries and tools provided by the targeted social network). Our study sheds new light on the intrinsic relation between communities (usually represented as groups) and friendships between individuals. To develop an efficient attack we analyzed group distributions, densities and visibility parameters from a large sample of a social network. By effectively exploring the target group network, our proposed algorithm is able to perform friendship and mutual-friend attacks along a strategy that minimizes the number of queries. The results of attacks performed on active Facebook profiles show that $5$ different friendship links are disclosed in average for each single legitimate query in the best case

Qatar Ambulance Service staff's perception on the Quality-of-Service delivery to patients

Background: Quality improvement has been well documented in various industries to improve safety and processes. 1 However, limited research has taken place within the pre-hospital sector in this regard. Various factors can be attributed to the delivery of effective services. Studies often investigate customer/patient perception and often sideline the importance of employee perception. 2 This study evaluates Qatar's Hamad Medical Corporation Ambulance Service (HMCAS) staffs’ perception on service delivery to patients they treat and transport. Methods: An online survey was designed and distributed to HMCAS staff working within the emergency section (N = 750). A 5-point Likert scale (1 = strongly disagree to 5 = strongly agree) was used. The SERVQUAL model consisting of 5 dimensions (RATER): Reliability, Assurance, Tangibility, Empathy, and Responsiveness was used. 3 Two variables with the highest perception score were regarded as the drivers of service quality. A negative gap score (perception minus expectation) was used as the basis for the study recommendations. Results: As per the required calculated sample size to achieve a 95% confidence interval, 255 questionnaires were completed. Respondents were 79% Ambulance Paramedics, 18% supervisors, and 3% managers. The weights of each dimension's variables were calculated to obtain perception and expectation scores. Descriptive statistics and gap scores of the survey responses are presented in Table 1 for the two variables of each dimension. None of the gap scores were found to be statistically significant. The proposed recommendations generated from this study are presented in Table 2. Conclusion: A standardized staff quality perception tool can assist in identifying potentially missed quality-related service issue(s). In this study, the SERVQUAL model was easily adapted and applied to the pre-hospital Emergency Medical Service setting in Qatar and proved useful in identifying service delivery proponents needing attention. Overall and reassuringly, the staff believes that they provide quality service to their patients

In-network processing in Wireless Sensor Networks using a content centric approach

National audienceIn this work, we have designed and developed a novel approach for data aggregation in Wireless Sensor Networks using CCNx protocol. The developed solution has been implemented in the Contiki operating system and evaluated using the Cooja simulator. We have compared the performance of our proposed solution with the SPIN protocol in terms of the number of exchanged messages and response times

Analyse automatisée des risques sur la vie privée dans les réseaux sociaux

In this thesis we shed the light on the danger of privacy leakage on social network. We investigate privacy breaches, design attacks, show their feasibility and study their accuracies. This approach helps us to track the origin of threats and is a first step toward designing effective countermeasures. We have first introduced a subject sensitivity measure through a questionnaire survey. Then, we have designed on-line friendship and group membership link disclosure (with certainty) attacks on the largest social network “Facebook”. These attacks successfully uncover the local network of a target using only legitimate queries. We have also designed sampling techniques to rapidly collect useful data around a target. The collected data are represented by social-attribute networks and used to perform attribute inference (with uncertainty) attacks. To increase the accuracy of attacks, we have designed cleansing algorithms. These algorithms quantify the correlation between subjects, select the most relevant ones and combat data sparsity. Finally, we have used a shallow neural network to classify the data and infer the secret values of a sensitive attribute of a given target with high accuracy measured by AUC on real datasets. The proposed algorithms in this work are included in a system called SONSAI that can help end users analyzing their local network to take the hand over their privacyCette thèse vise à comprendre le risque de fuite d’informations personnelles sur un réseau social. Nous étudions les violations potentielles de la vie privée, concevons des attaques, prouvons leur faisabilité et analysons leur précision. Cette approche nous aide à identifier l’origine des menaces et constitue un premier pas vers la conception de contre-mesures efficaces. Nous avons d’abord introduit une mesure de sensibilité des sujets à travers une enquête par questionnaire. Puis, nous avons conçu des attaques de divulgation (avec certitude) des liens d’amitié et des liens d’appartenance aux groupes sur “Facebook”. Ces attaques permettent de découvrir le réseau local d’une cible en utilisant uniquement des requêtes légitimes. Nous avons également conçu une technique d’échantillonnage pour collecter rapidement des données utiles autour d’une cible. Les données collectées sont ensuite représentées par des graphes et utilisées pour effectuer des inférences d’attributs (avec incertitude). Pour augmenter la précision des attaques, nous avons conçu des algorithmes de nettoyage. Ces algorithmes quantifient la corrélation entre les sujets, sélectionnent les plus pertinents et permettent de gérer la rareté (sparsity) des données. Enfin, nous avons utilisé un réseau de neurones pour classer les données et déduire les valeurs secrètes d’un attribut sensible d’une cible donnée avec une précision élevée mesurée par AUC sur des données réelles. Les algorithmes proposés dans ce travail sont inclus dans un système appelé SONSAI qui aide les utilisateurs finaux à contrôler la collecte d’informations sur leur vie privé