This work derives a nonlinear optical spatio-temporal instability. It is a perturbative analysis that begins from Maxwell’s equations and its constituent relations to derive a vectorial nonlinear wave equation. In fact, it is a new theoretical method that has been developed that builds on previous aspects of nonlinear optics in a more general way. The perturbation in the wave equation derived is coupled with its complex conjugate which has been taken for granted so far. Once decoupled it gives rise to a second-order equation and thus a true instability regime because the wavevector can become complex. The solution obtained for the perturbation that co-propagates with the driving laser is a generalization to modulation and filamentation instability, extending beyond the nonlinear Schrodinger and nonlinear transverse diffusion equations[1][2]. As a result of this new mechanism, new phenomena can be explored. For example, the Kerr Nonlinear Instability can lead to exponential growth, and hence amplification. This can occur even at wavelengths that are typically hard to operate at, such as into far infrared wave- lengths. This provides a mechanism for obtaining amplification in the far infrared from a small seed pulse without the need for population inversion. The analysis provides the basic framework that can be extended to many different avenues. This will be the subject of future work, as outlined in the conclusion of this thesis.

Dans un contexte de tertiarisation croissante de la société, nous questionnons l’impact des services organisés en réseau sur les rapports sociaux. Pour cela, il s’agit de comprendre les influences réciproques de la production de service sur les modalités d’organisation spatio-temporelle des Français. Une série d’entretiens individuels interroge les modalités d’organisation des activités sociales du quotidien. Elle permet d’établir une typologie de stratégies d’organisations spatio-temporelles (routine, optimisation, conciliation, spontanéité, escamotage). En miroir, est interrogée la façon dont les niveaux hiérarchiques du Réseau postal (directions nationales, départementales et bureaux de poste) se figurent le client, en prenant en compte les différentes opérations de cadrages (éthiques, cognitifs, opératoires) qui déterminent l’action. Finalement nous montrons l’influence du réseau de la Poste sur l’organisation sociale d’individus de plus en plus rationnels, individuels et mobiles / In a context of growing service sector of society, we question the impact of networked services on social relations. To do this we strive to understand the reciprocal influences of production services on the terms of spatio-temporal organization of French. A first of interviews questioning the methods of organizing social activities of daily life and provides a typology of Conduct of everyday life characterizing different spatio-temporal strategies (routine, optimization, balance, spontaneity, retraction). Mirror, we question how all levels of Network Post organization ((National, departmental and local post offices) will include the client, taking into account the various operations of framing (ethical, cognitive processes) that determine action taken. Finally we show the influence of network position on the social organization of individuals more rational, individual and mobile

As video capturing devices become more ubiquitous from surveillance cameras to smart phones, the demand of automated video analysis is increasing as never before. One obstacle in this process is to efficiently locate where a human operator’s attention should be, and another is to determine the specific types of activities or actions without ambiguity. It is the special interest of this dissertation to locate spatial and temporal regions of interest in videos and to develop a better action representation for video-based activity analysis. This dissertation follows the scheme of “locating then recognizing” activities of interest in videos, i.e., locations of potentially interesting activities are estimated before performing in-depth analysis. Theoretical properties of regions of interest in videos are first exploited, based on which a unifying framework is proposed to locate both spatial and temporal regions of interest with the same settings of parameters. The approach estimates the distribution of motion based on 3D structure tensors, and locates regions of interest according to persistent occurrences of low probability. Two contributions are further made to better represent the actions. The first is to construct a unifying model of spatio-temporal relationships between reusable mid-level actions which bridge low-level pixels and high-level activities. Dense trajectories are clustered to construct mid-level actionlets, and the temporal relationships between actionlets are modeled as Action Graphs based on Allen interval predicates. The second is an effort for a novel and efficient representation of action graphs based on a sparse coding framework. Action graphs are first represented using Laplacian matrices and then decomposed as a linear combination of primitive dictionary items following sparse coding scheme. The optimization is eventually formulated and solved as a determinant maximization problem, and 1-nearest neighbor is used for action classification. The experiments have shown better results than existing approaches for regions-of-interest detection and action recognition.

Many agricultural landscapes in India are irrigated with wastewater, and it is a common livelihood practice particularly in urban and peri-urban areas. Farmers around urban agglomerations continuously depend on the wastewater released from nearby urban centres. While providing opportunities with respect to water and nutrient supply, irrigating with wastewater has adverse environmental impacts, particularly on the local aquifer systems. Therefore, addressing the wastewater irrigation influence on local aquifer systems is crucial for sustainable groundwater management. The present research demonstrates the impacts of wastewater irrigation, seasonality and spatio-temporal variations in the groundwater quality and its geochemical evolution and mixing processes in different land use and crop settings. The doctoral research aims at understanding the aquifer heterogeneity, land use conditions, groundwater dynamics and contaminant fate and transport in the long-term wastewater irrigation system to develop sustainable and suitable groundwater management strategies. The selected study watershed is located on the banks of Musi River in a peri-urban catchment of the Musi River basin in India. Statistical techniques, land use change modelling and solute flow and transport modelling tools are employed to identify and quantify the linkages between contaminants, agricultural use and environmental variables, particularly those characterizing the groundwater qualities. The research results suggest that concentrations of the major ionic substances increase after the monsoon season, especially in wastewater irrigated areas and the major polluted groundwaters to come from the wastewater irrigated parts of the watershed. Clusters of chemical variables identified indicate that groundwater pollution is highly impacted by mineral interactions and long-term wastewater irrigation. The groundwater geochemistry of the watershed is largely controlled by long-term wastewater irrigation, local rainfall patterns and water-rock interactions. The detected land use changes in the watershed indicate that, as a consequence of urban pressures, agricultural landscapes are being converted into built-up areas and, at the same time, former barren land is converted to agricultural plots. The mapped land use data are used in modelling the aquifer conditions and to observe the groundwater dynamics in the peri-urban environment. The study results provide the basis for sustainable agriculture and groundwater development using the efficient scenarios identified for wastewater irrigation management. The resulting strategies for integrated management of water and waste will contribute to the water security and achieve the respective Sustainable Development Goals (SDGs 2, 3, 6, 11 and 15).

The aim of this master's thesis is to get familiar with problems of data mining and classification. This thesis also continues with application SUNAR, which is upgraded in practical part with SVM classification of persons passing between cameras. In the conclusion, we discuss ways to improve classification and person recognition in application SUNAR.

Ce travail présente une architecture logicielle concrète dédiée aux besoins et caractéristiques des systèmes d'Intelligence Ambiante (AmI). Le modèle comportemental proposé, appelé Higher-order Agent (HoA), capture simultanément l'évolution de l'état mental de l'agent ainsi que l'état de son plan d'actions. Les expressions du plan sont écrites et composées en utilisant un langage algébrique formel, nommé AgLOTOS. Les plans sont construits automatiquement et à la volée, comme un système de processus concurrents, déduits des intentions de l'agent et de ses préférences d'exécution. Basé sur une sémantique de plans et d'actions concurrentes, un service de guidance est aussi proposé afin d'assister l'agent dans le choix de ses prochaines exécutions. Cette guidance permet d'améliorer la satisfaction des intentions de l'agent au regard des plans concurrents possibles et en fonction du contexte actuel de l'agent. La "localité" et le "temps" étant considérés comme des informations contextuelles clés dans l'activité de l'agent, nous les prenons en compte au travers de deux fonctions utilitaires originales conçues à partir des expériences des exécutions d'action et pouvant être combinées suivant les préférences stratégiques de l'agent. La structure compositionnelle des expressions AgLOTOS est mise à profit pour permettre des révisions ciblées du plan de l'agent, Les révisions des sous-plans sont donc réalisées automatiquement en fonction des mises à jour apportées aux intentions, tout en maintenant la consistance du comportement de l'agent. Un cas d'étude est développé afin de montrer comment l'agent peut agir, même s'il subit des changements inattendus de son contexte, en fonction de ses expériences passées qui révèlent certains cas de d'échecs. / This work presents a concrete software architecture dedicated to ambient intelligence (AmI) features and requirements. The proposed behavioral model, called Higher-order Agent (HoA) captures the evolution of the mental representation of the agent and the one of its plan simultaneously. Plan expressions are written and composed using a formal algebraic language, namely AgLOTOS, so that plans are built automatically and on the fly, as a system of concurrent processes. Due to the compositional structure of AgLOTOS expressions, the updates of sub-plans are realized automatically accordingly to the revising of intentions, hence maintaining the consistency of the agent. Based on a specific semantics, a guidance service is also proposed to assist the agent in its execution. This guidance allows to improve the satisfaction of the agent's intentions with respect to the possible concurrent plans and the current context of the agent. Adopting the idea that "location" and "time" are key stones information in the activity of the agent, we show how to enforce guidance by ordering the different possible plans. As a major contribution, we demonstrate two original utility functions that are designed from the past-experiences of the action executions, and that can be combined accordingly to the current balance policy of the agent. A use case scenario is developed to show how the agent can act, even if it suffers from unexpected changes of contexts, it does not have many experiences and whose past experiences reveals some failure cases.

This master's thesis is devoted to the studies of possibilities, which can be used for representation of moving objects data and for querying such spatio-temporal data. It also shows results of the master's thesis created by Ing. Jaroslav Vališ, that should be used for the solution of this master's thesis. But based on the theoretical grounds defined at the beginning of this work was designed and implemented new database extension for saving and querying spatio-temporal data. Special usage of this extension is demonstrated in an example application. This application uses the database extension for the implementation of its own database functions that are domain specific. At the conclusion, there are presented ways of the farther development of this database extension and the results of this master's thesis are there set into the context of the following project, doctoral thesis "Moving objects database".

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博士(工学) / Doctor of Philosophy in Engineering / 同志社大学 / Doshisha University

There is currently no set standard for evaluating visualization environments. Even though the number of visualizations has increased, there is a tendency to overlook the evaluation of their usability. This thesis investigates how a visualization tool for crowd trajectory data can be made using the visualization technique of animated maps and the JavaScript library D3.js. Furthermore it explores how such a visualization tool can be evaluated according to a suggested framework for spatio-temporal data.     The developed tool uses data taken from the UCY Graphics Lab, consisting of 415 trajectories collected from a video recorded at a campus area. User evaluation was performed through a user test with a total of six participants, measuring effectiveness as completed tasks, and satisfaction as ease of use for three different amounts of trajectories. Qualitative data was recorded through using the think aloud protocol to gather feedback to further improve the implementation. The evaluation shows that the visualization tool is usable and effective, and that the technique of animated maps in combination with a heatmap can aid users when exploring and formulating ideas about data of this kind. It is also concluded that the framework is a possible tool to utilize when validating visualization systems for crowd trajectory data. / Det finns i dagsläget ingen etablerad standard för att utvärdera visualiseringssystem. Även om antalet visualiseringar har ökat finns det en tendens att förbise utvärderandet av deras användbarhet. I det här arbetet undersöker vi hur ett visualiseringsverktyg för data av gångbanor hos folksamlingar kan skapas, med hjälp utav visualiseringsmetoden animated maps och JavaScript-biblioteket D3.js. Vidare undersöker vi hur det är möjligt att evaluera ett visualiseringsverktyg utefter ett givet ramverk.  Visualiseringsverktyget använder data från UCY Graphics Lab. Datan består av 415 gångbanor som är insamlade från en videoinspelning av ett campusområde. En utvärdering genomfördes sedan med sex deltagare, där visualiseringens effektivitet och användarvänlighet mättes. Frågorna ställdes för tre olika mängder av gångbanor. Kvalitativa data dokumenterades genom en så kallad ''think aloud'', för att ge återkoppling och förslag på möjliga förbättringar av visualiseringen. Evalueringen visar på att animated maps i kombination med en heatmap kan hjälpa användare att utforska data av gångbanor hos folksamlingar, samt att verktyget är effektivt och användbart. Det är också visat att det ramverk som användes vid evalueringen är ett möjligt verktyg för att validera visualiseringsverktyg av den typ som gjorts i det här projektet.