Spontaneous emergence of rogue waves in partially coherent waves: a quantitative experimental comparison between hydrodynamics and optics

Rogue waves are extreme and rare fluctuations of the wave field that have been discussed in many physical systems. Their presence substantially influences the statistical properties of an incoherent wave field. Their understanding is fundamental for the design of ships and offshore platforms. Except for very particular meteorological conditions, waves in the ocean are characterised by the so-called JONSWAP (Joint North Sea Wave Project) spectrum. Here we compare two unique experimental results: the first one has been performed in a 270-meter wave tank and the other in optical fibers. In both cases, waves characterised by a JONSWAP spectrum and random Fourier phases have been launched at the input of the experimental device. The quantitative comparison, based on an appropriate scaling of the two experiments, shows a very good agreement between the statistics in hydrodynamics and optics. Spontaneous emergence of heavy tails in the probability density function of the wave amplitude is observed in both systems. The results demonstrate the universal features of rogue waves and provide a fundamental and explicit bridge between two important fields of research. Numerical simulations are also compared with experimental results

Modélisation centrée utilisateur pour la configuration logicielle en environnement ambiant

Ambient intelligence aims to provide to human users applications and services that are personalized and adapted to the current situation. The ambient environment which surrounds the human consists of a set of connected objects and software components that are bricks used for the construction of applications by composition. The availability of these components can vary dynamically, in case of mobility for example. In addition, their appearance or disappearance is usually unanticipated. Moreover, in these dynamic and open environments, the user needs are not stable nor always well defined. To build these applications and provide the user with "the right applications at the right time", our team explores an original approach called "opportunistic software composition": the idea is to build applications on the fly by assembling software components present in the environment at the time, without relying on explicit user needs or predefined applications models. Here, it is the availability of the components that triggers opportunistically the on-the-fly building of applications. It is controlled by an intelligent system, called opportunistic composition engine, which decides on the "right" compositions to be made without user input. In such a way, the applications "emerge" dynamically from the ambient environment. Thus, emerging applications can be unexpected or unknown to the user. At the center of the system, the latter must be informed of these applications. On the first hand, she/he must be able to control them, i.e., accept or reject them, and if she/he has the required skills, modify them or eventually build applications herself/himself by assembling software components present in the ambient environment. However, in the control tasks, the user must be assisted as well as possible. On the other hand, in order for the opportunistic composition engine to build relevant assemblies in the absence of explicit needs, it must receive information from the user. In this thesis, we propose an approach based on Model Driven Engineering (MDE) in order to put the user "at the center of the loop". The objective is to present the emerging applications to the user, to assist him in his interventions and to extract useful feedback data to provide to the "intelligent" composition engine. Our solution is based on a metamodel for assembling software components, on different domain-specific languages (DSL) that support application descriptions, and on a graphical editor for editing applications and capturing user feedback. Different methods for model transformations are used to generate structural and semantic application descriptions for different users, from the applications models build by the intelligent engine. In addition, the descriptions can be easily adjusted to a particular human, by changing or adapting the DSL and the model transformations to the user's profile. Unlike the traditional use of MDE where tools and techniques are used by engineers to develop software and generate code, the focus in our approach is on the end users. The entire solution has been implemented and works coupled with the engine. That is to say, our solution is able to intercept the applications models built by the engine, to transform them into presentable models that can be understood and modified by the user, and finally to capture the user feedback and give it back to the engine to update its knowledge.L'intelligence ambiante vise à offrir à un utilisateur humain des applications et des services personnalisés et adaptés à la situation courante. L'environnement ambiant, dans lequel cet humain est plongé, est composé d'un ensemble d'objets connectés et de composants logiciels qui sont des briques de base pour la construction d'applications par composition. La disponibilité de ces composants peut varier dynamiquement, en cas de mobilité par exemple. Ceux-ci peuvent apparaître ou disparaître de manière non anticipée. De plus, dans ces environnements dynamiques et ouverts, le besoin de l'utilisateur humain n'est pas stable ni toujours bien défini. Pour construire des applications dans un tel contexte, et fournir à l'utilisateur "les bonnes applications au bon moment", notre équipe explore une approche originale appelée "composition logicielle opportuniste" : l'idée est de construire des applications à la volée par assemblage de composants logiciels présents dans l'environnement sur le moment, sans se baser sur des besoins explicites ni sur des schémas de construction prédéfinis. C'est l'opportunité qui déclenche la construction des applications à la volée. Elle est contrôlée par un système intelligent, appelé moteur de composition opportuniste, qui doit décider des "bonnes" compositions à effectuer sans contribution explicite de l'utilisateur. Ainsi, les applications "émergent" dynamiquement. Les applications émergentes peuvent être imprévues ou inconnues de l'utilisateur. Au centre du système, ce dernier doit être en informé. Il doit pouvoir les contrôler, c'est-à-dire les accepter ou les rejeter, et s'il a les compétences requises, les modifier ou même construire lui-même des applications en assemblant des composants logiciels présents dans l'environnement ambiant. Dans les tâches de contrôle, l'utilisateur doit être assisté au mieux. D'autre part, pour que le moteur de composition opportuniste construise des assemblages pertinents en l'absence de besoins explicites, il doit recevoir des informations de l'utilisateur. Ceci ne doit cependant pas entraîner, pour l'utilisateur, une surcharge d'information ou d'opérations à effectuer. Dans cette thèse, nous proposons une approche basée sur l'ingénierie dirigée par les modèles (IDM) afin de mettre l'utilisateur "au centre de la boucle". Il s'agit de lui présenter les applications émergentes, de l'assister dans son contrôle et d'extraire des données de feedback utiles à fournir au moteur de composition "intelligent". Notre solution repose sur un métamodèle d'assemblage de composants logiciels, des langages spécifiques à un domaine (DSL) qui supportent la description des applications, un éditeur graphique qui permet d'éditer les applications et de capturer le feedback de l'utilisateur. Différentes transformations de modèle permettent l'interfaçage avec le moteur de composition et la génération de différentes formes de descriptions structurelles et sémantiques des applications pour des utilisateurs différents. En outre, les descriptions peuvent être facilement ajustées à un humain particulier, en changeant ou en adaptant les DSL et les transformations de modèle au profil de l'utilisateur. Dans notre approche, contrairement à l'utilisation classique de l'IDM où les outils et les techniques sont utilisés par les ingénieurs pour développer des logiciels et générer du code, le focus est sur les utilisateurs finaux qui prennent la place des ingénieurs. L'ensemble de la solution a été implémentée et fonctionne de manière couplée avec le moteur de composition opportuniste : notre solution prend en entrée les applications proposées par le moteur, les transforme en des modèles présentables, compréhensibles et modifiables par l'utilisateur, et enfin capture le feedback de l'utilisateur pour le transmettre au moteur pour mettre à jour sa connaissance

Understanding the negative emotions, consumer complaint behaviour responses and social dynamics occurring during dissatisfactory incidents in restaurants

This thesis investigates how the social dynamics that naturally occur during dissatisfactory incidents in restaurants influence the consumer complaint behaviour process. It further explores what negative emotions consumers experience, how they respond to such dissatisfactory incidents and what stimulates these emotions and responses. Consumer complaint behaviour (CCB) in services is a complex and dynamic process and not a static phenomenon. The emotions and responses are the result of the ongoing evaluations consumers undertake and the continuous human interactions occurring. Although the literature acknowledges the influence of service providers on the CCB responses and negative emotions, little is known about how other customers impact the CCB process. Furthermore, much of the existing research on CCB has been undertaken using purely quantitative approaches that tend to focus on hypothetical scenarios and the measurement of behavioural intentions. This has meant a failing to understand the actual behaviour of the participant, to explore dissatisfying incidents holistically and within their contextual natural settings and to capture the social dynamics and interactions. This thesis has addressed these limitations and assumed a social constructionist paradigm and followed an interpretivist approach. The methodology draws upon the principles of critical incident technique and is multi-method over two phases: qualitative research diaries followed by semistructured interviews. A total of 20 semi-structured interviews were conducted with Lebanese consumers who shared their subjective accounts of the dissatisfactory incidents they recently experienced in restaurants. The data from the interviews was analysed using template analysis. The findings show that the CCB process within a restaurant context has a social dimension. The continuous human interactions between the consumer, service provider and other customers throughout the dining occasion influence the service failure, cognitive appraisal, negative emotions and CCB responses both directly and indirectly. Furthermore, negative emotions such as feeling fed up and disgust are experienced following a restaurant dissatisfactory incident. The findings also demonstrate that some CCB responses have different variants depending on the context, for example exit and negative word of mouth. Additionally, the findings identified what stimulates both the negative emotions and CCB responses. This study advances the understanding of CCB within services and restaurants in particular by explaining the impact of social dynamics on the CCB process. It presents a model that acknowledges this social aspect and demonstrates its influences. Furthermore it identifies a broad range of negative emotions and CCB responses specific to restaurant dissatisfactory incidents and elaborates on what stimulates them. This study draws attention to the importance of studying CCB in services using an interpretivist approach, as it will result in an in-depth understanding of the phenomenon

User centric modeling for ambient software configuration

L'intelligence ambiante vise à offrir à un utilisateur humain des applications et des services personnalisés et adaptés à la situation courante. L'environnement ambiant, dans lequel cet humain est plongé, est composé d'un ensemble d'objets connectés et de composants logiciels qui sont des briques de base pour la construction d'applications par composition. La disponibilité de ces composants peut varier dynamiquement, en cas de mobilité par exemple. Ceux-ci peuvent apparaître ou disparaître de manière non anticipée. De plus, dans ces environnements dynamiques et ouverts, le besoin de l'utilisateur humain n'est pas stable ni toujours bien défini. Pour construire des applications dans un tel contexte, et fournir à l'utilisateur "les bonnes applications au bon moment", notre équipe explore une approche originale appelée "composition logicielle opportuniste" : l'idée est de construire des applications à la volée par assemblage de composants logiciels présents dans l'environnement sur le moment, sans se baser sur des besoins explicites ni sur des schémas de construction prédéfinis. C'est l'opportunité qui déclenche la construction des applications à la volée. Elle est contrôlée par un système intelligent, appelé moteur de composition opportuniste, qui doit décider des "bonnes" compositions à effectuer sans contribution explicite de l'utilisateur. Ainsi, les applications "émergent" dynamiquement. Les applications émergentes peuvent être imprévues ou inconnues de l'utilisateur. Au centre du système, ce dernier doit être en informé. Il doit pouvoir les contrôler, c'est-à-dire les accepter ou les rejeter, et s'il a les compétences requises, les modifier ou même construire lui-même des applications en assemblant des composants logiciels présents dans l'environnement ambiant. Dans les tâches de contrôle, l'utilisateur doit être assisté au mieux. D'autre part, pour que le moteur de composition opportuniste construise des assemblages pertinents en l'absence de besoins explicites, il doit recevoir des informations de l'utilisateur. Ceci ne doit cependant pas entraîner, pour l'utilisateur, une surcharge d'information ou d'opérations à effectuer. Dans cette thèse, nous proposons une approche basée sur l'ingénierie dirigée par les modèles (IDM) afin de mettre l'utilisateur "au centre de la boucle". Il s'agit de lui présenter les applications émergentes, de l'assister dans son contrôle et d'extraire des données de feedback utiles à fournir au moteur de composition "intelligent". Notre solution repose sur un métamodèle d'assemblage de composants logiciels, des langages spécifiques à un domaine (DSL) qui supportent la description des applications, un éditeur graphique qui permet d'éditer les applications et de capturer le feedback de l'utilisateur. Différentes transformations de modèle permettent l'interfaçage avec le moteur de composition et la génération de différentes formes de descriptions structurelles et sémantiques des applications pour des utilisateurs différents. En outre, les descriptions peuvent être facilement ajustées à un humain particulier, en changeant ou en adaptant les DSL et les transformations de modèle au profil de l'utilisateur. Dans notre approche, contrairement à l'utilisation classique de l'IDM où les outils et les techniques sont utilisés par les ingénieurs pour développer des logiciels et générer du code, le focus est sur les utilisateurs finaux qui prennent la place des ingénieurs. L'ensemble de la solution a été implémentée et fonctionne de manière couplée avec le moteur de composition opportuniste : notre solution prend en entrée les applications proposées par le moteur, les transforme en des modèles présentables, compréhensibles et modifiables par l'utilisateur, et enfin capture le feedback de l'utilisateur pour le transmettre au moteur pour mettre à jour sa connaissance.Ambient intelligence aims to provide to human users applications and services that are personalized and adapted to the current situation. The ambient environment which surrounds the human consists of a set of connected objects and software components that are bricks used for the construction of applications by composition. The availability of these components can vary dynamically, in case of mobility for example. In addition, their appearance or disappearance is usually unanticipated. Moreover, in these dynamic and open environments, the user needs are not stable nor always well defined. To build these applications and provide the user with "the right applications at the right time", our team explores an original approach called "opportunistic software composition": the idea is to build applications on the fly by assembling software components present in the environment at the time, without relying on explicit user needs or predefined applications models. Here, it is the availability of the components that triggers opportunistically the on-the-fly building of applications. It is controlled by an intelligent system, called opportunistic composition engine, which decides on the "right" compositions to be made without user input. In such a way, the applications "emerge" dynamically from the ambient environment. Thus, emerging applications can be unexpected or unknown to the user. At the center of the system, the latter must be informed of these applications. On the first hand, she/he must be able to control them, i.e., accept or reject them, and if she/he has the required skills, modify them or eventually build applications herself/himself by assembling software components present in the ambient environment. However, in the control tasks, the user must be assisted as well as possible. On the other hand, in order for the opportunistic composition engine to build relevant assemblies in the absence of explicit needs, it must receive information from the user. In this thesis, we propose an approach based on Model Driven Engineering (MDE) in order to put the user "at the center of the loop". The objective is to present the emerging applications to the user, to assist him in his interventions and to extract useful feedback data to provide to the "intelligent" composition engine. Our solution is based on a metamodel for assembling software components, on different domain-specific languages (DSL) that support application descriptions, and on a graphical editor for editing applications and capturing user feedback. Different methods for model transformations are used to generate structural and semantic application descriptions for different users, from the applications models build by the intelligent engine. In addition, the descriptions can be easily adjusted to a particular human, by changing or adapting the DSL and the model transformations to the user's profile. Unlike the traditional use of MDE where tools and techniques are used by engineers to develop software and generate code, the focus in our approach is on the end users. The entire solution has been implemented and works coupled with the engine. That is to say, our solution is able to intercept the applications models built by the engine, to transform them into presentable models that can be understood and modified by the user, and finally to capture the user feedback and give it back to the engine to update its knowledge

Ultra-fast statistics and dynamics in nonlinear fiber optics experiments

Le travail de thèse présenté dans ce manuscrit est consacré à l’étude de la statis-tique et de la dynamique d’ondes partiellement cohérentes se propageant dans un milieunon linéaire, la fibre optique. Les études effectuées durant ce travail de thèse se placentprincipalement dans le champ de la turbulence intégrable qui examine la propagationnon linéaire d’ondes partiellement cohérentes dans des systèmes physiques décrits par deséquations intégrables telles que l’équation de Schrödinger non linéaire à une dimension.Nous avons reproduit en optique une expérience déjà réalisée en hydrodynamique.Nous comparons ainsi les déviations de la statistique gaussienne résultant de la propaga-tion non linéaire d’ondes lumineuses dans une fibre optique et de vagues dans un canalunidirectionnel. Afin d’observer la dynamique des ondes partiellement cohérentes se propageant dans unefibre optique en régime de dispersion anormale, nous avons construit un microscope tem-porel qui a permis d’observer des structures cohérentes particulières présentant des pro-priétés de localisation dans l’espace et dans le temps similaires à celles des ondes scélérates.Finalement, nous avons étudié le régime de propagation très faiblement non linéaire. Lathéorie cinétique des ondes (appelée encore théorie de la Turbulence d’ondes) prédit quel’élargissement spectral ne dépend pas du signe de la dispersion et nous avons présentédans ce manuscrit la preuve expérimentale de cette hypothèse.The work presented in this thesis is related to the statistical and dynamical propertiesof partially coherent waves propagating inside an optical fiber. Our work mainly enterswithin the field of Integrable Turbulence that deals with nonlinear partially coherentwaves described by integrable equations, such as the one-dimensional nonlinear Shcrödin-ger equation. We have reproduced an experiment in optics that has been done some years ago inhydrodynamics. We compare the statistics of optical waves propagating inside an opticalfiber to the the statistics of waves propagating inside a water tank. Moreover we have built a time microscope in order to observe the real-time evolution of partially coherent waves. The soliton-like structures that have been observed in our expe-riments have localization properties in space and time that are similar to those typifyingrogue waves found in the field of oceanography. We have also examined the weakly nonlinear regime that can be described by using the so-called wave turbulence (WT) theory. WT theory states that the spectral broadening insuch a weakly nonlinear regime does not depend on the sign of the second-order dispersioncoefficient. In this thesis, we presented an experimental result confirming this theoreticalprediction

Real-time Stress Evaluation using Wireless Body Sensor Networks

International audienceStress is a physical, mental or emotional factor that causes bodily or mental tension. It is generally recognized as one of the major factors leading to a spectrum of health problems. Therefore, people with high risks of getting stressedshould be continuously monitored in order to detect any stress signs before it causes health problems. Wireless body sensor networks(WBSNs) provide opportunities to monitor stress and can provide initial treatment. In this paper, we propose anenergy-efficient stress detection and evaluation framework. A WBSN deployed on the patient’s body collects stress-correlatedphysiological signals. First, the skin conductance (SC) is analyzed. Then, if any stress signs are detected, its level is calculatedvia a Fuzzy Inference System (FIS) using the following vital signs: Heart Rate (HR), Respiration Rate (RR) and Systolic Blood Pressure (ABPSys). The results show that the stress evaluation was coherent with the different experimental stages the monitored person has gone through. PAM : ACTI bien que short paper car conf selectiv

Putting the End-User in the Loop in Smart Ambient Systems: an Approach based on Model-Driven Engineering

At the heart of cyber-physical and ambient systems, the user should permanently bene t from applications adapted to the situation and her/his needs. To do this, she/he must be able to con gure her/his software environment and be supported as much as possible in that task. To this end, an intelligent "engine" assembles software components that are present in the ambient environment at the time and makes unanticipated applications emerge. The problem is to put the user "in the loop": provide adapted and intelligible descriptions of the emerging applications, and present them so that the user can accept, modify or reject them. Besides, user feedback must be collected to feed the engine's learning process. Our approach relies on Model-Driven Engineering (MDE). However, di erently from the regular use of MDE tools and techniques by engineers to develop software and generate code, our focus is on end-users. Models of component assemblies are represented and made editable for them. Based on a metamodel that supports modeling and description of component-based applications, a user interface provides multi-faceted representations of the emerging applications and captures user feedback. For that, we have developed a solution based on several domain-speci c languages and a transformation process, based on the established MDE tools (Gemoc studio, Eclipse Modeling Framework, EcoreTools, Sirius, Acceleo). It works in conjunction with the intelligent engine that builds the emerging applications and to which it provides learning data

Automated user-oriented description of emerging composite ambient applications

International audienceAmbient environments consist of components surrounding the user and offering services. Applications can here be composed opportunistically and automatically by an intelligent system that puts together available components. Thus, applications that are a priori unknown emerge from the environment. The problem is in the intelligible presentation to an average user of those emerging composite applications. Our approach consists in automatic generation of user-oriented application descriptions from unit descriptions of each component and service. For that, we propose a well-defined language for component description and a method for combining descriptions. A prototype has been developed and used to experiment the generation of different composite application descriptions. Based on these experiments, we assess the degree of fulfillment of the requirements we have identified for the problem

Model-Driven Engineering for End-Users in the Loop in Smart Ambient Systems

This article is part of: JUCS - Journal of Universal Computer Science 27(7): Advances and Challenges for Model and Data EngineeringInternational audienceAt the heart of cyber-physical and ambient systems, the user should permanently benefit from applications adapted to the situation and her/his needs. To do this, she/he must be able to configure her/his software environment and be supported as much as possible in that task. To this end, an intelligent "engine" assembles software components that are present in the ambient environment at the time and makes unanticipated applications emerge. The problem is to put the user "in the loop", i.e., provide adapted and intelligible descriptions of the emerging applications, and present them so that the user can accept, modify or reject them. Besides, user feedback must be collected to feed the engine's learning process. Our approach relies on Model-Driven Engineering (MDE). However, differently from the regular use of MDE tools and techniques by engineers to develop software and generate code, our focus is on end-users. Models of component assemblies are represented and made editable for them. Based on a metamodel that supports modeling and description of component-based applications, a user interface provides multi-faceted representations of the emerging applications and captures user feedback. Our solution relies on several domainspecific languages and a transformation process, based on the established MDE tools (Gemoc studio, Eclipse Modeling Framework, EcoreTools, Sirius, Acceleo). It works in conjunction with the intelligent engine that builds the emerging applications and to which it provides learning data