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Ubiquitous connectivity plays an important role in improving the quality of life in terms of economic development, health and well being, social justice and equity, as well as in providing new educational opportunities. However, rural communities which account for 46% of the world's population lacks access to proper connectivity to avail such societal benefits, creating a huge "digital divide" between the urban and rural areas. A primary reason is that the Information and Communication Technologies (ICT) providers have less incentives to invest in rural areas due to lack of promising revenue returns. Existing research and industrial attempts in providing connectivity to rural communities suffer from severe drawbacks, such as expensive wireless spectrum licenses and infrastructures, under- and over-provisioning of spectrum resources while handling heterogeneous traffic, lack of novel wireless technologies tailored to the unique challenges and requirements of rural communities (e.g., agricultural fields). Leveraging the recent advances in Dynamic Spectrum Access (DSA) technologies like wide band spectrum analyzers and spectrum access systems, and multi-radio access technologies (multi-RAT), this dissertation proposes a novel Diverse Band-aware DSA (d-DSA) network architecture, that addresses the drawbacks of existing standard and DSA wireless solutions, and extends ubiquitous connectivity to rural communities; a step forward in the direction of the societal and economic improvements in rural communities, and hence, narrowing the "digital divide" between the rural and urban societies. According to this paradigm, a certain wireless device is equipped with software defined radios (SDRs) that are capable of accessing multiple (un)licensed spectrum bands, such as, TV, LTE, GSM, CBRS, ISM, and possibly futuristic mmWaves. In order to fully exploit the potential of the d-DSA paradigm, while meeting heterogeneous traffic demands that may be generated in rural communities, we design efficient routing strategies and optimization techniques, which are based on a variety of tools such as graph modeling, integer linear programming, dynamic programming, and heuristic design. Our results on realistic traces in a large variety of rural scenarios show that the proposed techniques are able to meet the heterogeneous traffic requirements of rural applications, while ensuring energy efficiency and robustness of the architecture for providing connectivity to rural communities.

abstract: What causes social systems to resist change? Studies of the emergence of social complexity in archaeology have focused primarily on drivers of change with much less emphasis on drivers of stability. Social stability, or the persistence of social systems, is an essential feature without which human society is not possible. By combining quantitative modeling (Exponential Random Graph Modeling) and the comparative archaeological record where the social system is represented by networks of relations between settlements, this research tests several hypotheses about social and geographic drivers of social stability with an explicit focus on a better understanding of contexts and processes that resist change. The Valencian Bronze Age in eastern Spain along the Mediterranean, where prior research appears to indicate little, regional social change for 700 years, serves as a case study. The results suggest that social stability depends on a society’s ability to integrate change and promote interdependency. In part, this ability is constrained or promoted by social structure and the different, relationship dependencies among individuals that lead to a particular social structure. Four elements are important to constraining or promoting social stability—structural cohesion, transitivity and social dependency, geographic isolation, and types of exchange. Through the framework provided in this research, an archaeologist can recognize patterns in the archaeological data that reflect and promote social stability, or lead to collapse. Results based on comparisons between the social networks of the Northern and Southern regions of the Valencian Bronze Age show that the Southern Region’s social structure was less stable through time. The Southern Region’s social structure consisted of competing cores of exchange. This type of competition often leads to power imbalances, conflict, and instability. Strong dependencies on the neighboring Argaric during the Early and Middle Bronze Ages and contributed to the Southern Region’s inability to maintain social stability after the Argaric collapsed. Furthermore, the Southern Region participated in the exchange of more complex technology—bronze. Complex technologies produce networks with hub and spoke structures highly vulnerable to collapse after the destruction of a hub. The Northern Region’s social structure remained structurally cohesive through time, promoting social stability. / Dissertation/Thesis / Webpage with data tables and R code / Doctoral Dissertation Anthropology 2020

Ce travail est consacré à l’étude et à la mise au point de récupérateurs d’énergie intégrés à une suspension automobile afin par exemple d’alimenter soit un microcontrôleur, soit des capteurs, soit de réaliser le contrôle santé des pièces ou encore de rendre l’amortisseur au sein d’une suspension d’un véhicule semi-actif autonome en fonction du niveau d’énergie disponible. Compte tenu des types de déplacement disponible dans la suspension, il est naturel de s’orienter vers des techniques électromagnétiques pour la récupération d’énergie liée aux grands déplacements et vers des techniques piézoélectriques pour les vibrations. L’utilisation de tels systèmes s’avère cependant complexe et un certain nombre de points techniques doivent être résolus pour les mettre en œuvre. En premier lieu, une parfaite connaissance des techniques de conversion piézoélectrique et électromagnétique est nécessaire. Dans ce but, le langage Bond Graph est utilisé et appliqué avec succès sur l’ensemble du système de suspension ainsi que sur les récupérateurs d’énergie en raison de sa capacité à traduire les effets physiques et les échanges énergétiques au sein de systèmes multiphysiques. D’autre part, des confrontations simulation/expérience sont réalisées en laboratoire sur chacun des récupérateurs d’énergie piézoélectrique et électromagnétique, afin de s’assurer du bon fonctionnement de ces systèmes lors de leurs intégrations dans un véhicule réel. Ainsi, des défauts de nature différente comme la force magnétique déformant le mouvement de translation de l’amortisseur, la mauvaise conduction des lignes de champ magnétique ou les endommagements du matériau piézoélectrique lors d’essais répétés, sont analysés dans les premiers démonstrateurs afin d'être ensuite corrigés. Enfin, un modèle global de suspension automobile intégrant simultanément les deux sous-systèmes de récupération d’énergie est étudié. Afin de compléter cette analyse, une modélisation du circuit de restitution et du stockage d’énergie est également proposée et permet une étude qualitative et quantitative des performances des systèmes de récupération d’énergie piézoélectrique et électromagnétique. Les résultats issus de ces modèles sont exploités dans le but de concevoir des récupérateurs d’énergie s’adaptant au mieux au domaine de l'automobile. Pour conclure, des tests sur route avec le récupérateur d’énergie piézoélectrique démontrent la validité de l’analyse théorique et la faisabilité des techniques développées. / This work is devoted to the study and the development of energy harvesters integrated in an automobile suspension, for example to supply either a microcontroller or sensors, or to perform an health check of parts or render semi-active the shock absorber within a suspension of an autonomous vehicle according to the level of energy available. Given the types of displacement available in the suspension, it is natural to move towards electromagnetic techniques for energy recovery related to large displacements and to piezoelectric techniques for vibrations. However, the use of such systems is complex and a number of technical issues need to be addressed to implement them. First, a perfect knowledge of piezoelectric and electromagnetic conversion techniques is required. To this end, the Bond Graph language is used and successfully applied to the entire suspension system as well as energy harvesters because of its ability to translate physical effects and energy exchanges into multiphysics systems. Furthermore, simulation / experiment confrontations are carried out in the laboratory on each of the piezoelectric and electromagnetic energy harvesters, to ensure the proper functioning of these systems during their integration into a real vehicle. Thus, defects of different nature such as the magnetic force deforming the translation movement of the damper, the poor conduction of the magnetic field lines or the damage of the piezoelectric material during repeated tests, are analyzed in the first demonstrators in order to be corrected. Finally, a global model of automobile suspension simultaneously integrating the two subsystems of energy recovery is studied. To complete this analysis, a modeling of the circuit of restitution and energy storage is also proposed and allows a qualitative and quantitative study of the performances of piezoelectric and electromagnetic energy recovery systems. The results from these models are used to design energy recovery systems that best fit the automotive field. To conclude, road tests with the piezoelectric energy harvesters demonstrate the validity of the theoretical analysis and the feasibility of the techniques developed.

Pattern matching approaches in reverse engineering aim to incorporate domain knowledge and system documentation in the software architecture extraction process, hence provide a user/tool collaborative environment for architectural design recovery. This thesis presents a model and an environment for recovering the high level design of legacy software systems based on user defined architectural patterns and graph matching techniques. In the proposed model, a high-level view of a software system in terms of the system components and their interactions is represented as a query, using a description language. A query is mapped onto a pattern-graph, where a module and its interactions with other modules are represented as a group of graph-nodes and a group of graph-edges, respectively. Interaction constraints can be modeled by the description language as a part of the query. Such a pattern-graph is applied against an entity-relation graph that represents the information extracted from the source code of the software system. An approximate graph matching process performs a series of graph edit operations (i. e. , node/edge insertion/deletion) on the pattern-graph and uses a ranking mechanism based on data mining association to obtain a sub-optimal solution. The obtained solution corresponds to an extracted architecture that complies with the given query. An interactive prototype toolkit implemented as part of this thesis provides an environment for architecture recovery in two levels. First the system is decomposed into a number of subsystems of files. Second each subsystem can be decomposed into a number of modules of functions, datatypes, and variables.

Pattern matching approaches in reverse engineering aim to incorporate domain knowledge and system documentation in the software architecture extraction process, hence provide a user/tool collaborative environment for architectural design recovery. This thesis presents a model and an environment for recovering the high level design of legacy software systems based on user defined architectural patterns and graph matching techniques. In the proposed model, a high-level view of a software system in terms of the system components and their interactions is represented as a query, using a description language. A query is mapped onto a pattern-graph, where a module and its interactions with other modules are represented as a group of graph-nodes and a group of graph-edges, respectively. Interaction constraints can be modeled by the description language as a part of the query. Such a pattern-graph is applied against an entity-relation graph that represents the information extracted from the source code of the software system. An approximate graph matching process performs a series of graph edit operations (i. e. , node/edge insertion/deletion) on the pattern-graph and uses a ranking mechanism based on data mining association to obtain a sub-optimal solution. The obtained solution corresponds to an extracted architecture that complies with the given query. An interactive prototype toolkit implemented as part of this thesis provides an environment for architecture recovery in two levels. First the system is decomposed into a number of subsystems of files. Second each subsystem can be decomposed into a number of modules of functions, datatypes, and variables.

We look at the underlying friendships and relationships between Chinese Internet users. We identify the presence and characteristics of the different types of online friendships and online relationships by analyzing various online social networks. First, we look at the concept of guanxi as it is applied to the interaction between web sites. Guanxi is a type of dyadic social interaction based on feelings and trust which has been well studied by scholars in China. We define guanxi in the web: particular linking patterns that appear in the web as well as supporting textual evidence in the web pages which we believe are indicative of the presence and varying strengths of the underlying guanxi between Chinese web site owners. Through our empirical study of the Chinese web, the general web, and the Japanese, Iranian, and French web, we show that guanxi between web sites is a more prevalent feature in the Chinese web. Next, we study the formation of online friendships in Douban, an online social networking platform frequently used by the youth in China. We look at several factors that can affect the evolution of friendships such as having memberships in the same discussion groups and sharing common interests or common friends. We compare these factors in influencing the formation of online friendships. Our work provides the first study on the underlying relationships between web sites in the Chinese web and the first large scale empirical analysis on the evolution of friendships in a Chinese online social network.

The field of generative graph models has seen increased popularity during recent years as it allows us to model the underlying distribution of a network and thus recreate it. From allowing anonymization of sensitive information in social networks to data augmentation of rare diseases in the brain, the ability to generate synthetic data has multiple applications in various domains. However, most current methods face the bottleneck of trying to generate the entire adjacency matrix and are thus limited to graphs with less than tens of thousands of nodes. In contrast, large real-world graphs like social networks or transaction graphs can extend significantly beyond these boundaries. Furthermore, the current scalable approaches are predominantly based on stochasticity and do not capture local structures and communities. In this paper, we propose Graphwave Edge-Linking CELL or GELCELL, a novel three-step architecture for generating graphs at scale. First, instead of constructing the entire network, GELCELL partitions the data and generates each cluster separately, allowing for efficient and parallelizable training. Then, by encoding the nodes, it trains a classifier to predict the edges between the partitions to patch them together, creating a synthetic version of the original large graph. Although it does suffer from some limitations due to necessary constraints on the cluster sizes, the results showed that GELCELL, given optimized parameters, can produce graphs with reasonable accuracy on all data tested, with the largest having 400 000 nodes and 1 000 000 edges. / Generativa grafmodeller har sett ökad popularitet under de senaste åren eftersom det möjliggör modellering av grafens underliggande distribution, och vi kan på så sätt återskapa liknande kopior. Förmågan att generera syntetisk data har ett flertal applikationsområden i en mängd av områden, allt från att möjligöra anonymisering av känslig data i sociala nätverk till att utöka mängden tillgänglig data av ovanliga hjärnsjukdomar. Dagens metoder har länge varit begränsade till grafer med under tiotusental noder, då dessa inte är tillräckligt skalbara, men grafer som sociala nätverk eller transaktionsgrafer kan sträcka sig långt utöver dessa gränser. Dessutom är de nuvarande skalbara tillvägagångssätten till största delen baserade på stokasticitet och fångar inte lokala strukturer och kluster. I denna rapport föreslår vi ”Graphwave EdgeLinking CELL” eller GELCELL, en trestegsarkitektur för att generera grafer i större skala. Istället för att återskapa hela grafen direkt så partitionerar GELCELL all datat och genererar varje kluster separat, vilket möjliggör både effektiv och parallelliserbar träning. Vi kan sedan koppla samman grafen genom att koda noderna och träna en modell för att prediktera länkarna mellan kluster och återskapa en syntetisk version av originalet. Metoden kräver vissa antaganden gällande max-storleken på dess kluster men är flexibel och kan rymma domänkännedom om en specifik graf i form av informerad parameterinställning. Trots detta visar resultaten på varierade träningsdata att GELCELL, givet optimerade parametrar, är kapabel att genera grafer med godtycklig precision upp till den största beprövade grafen med 400 000 noder och 1 000 000 länkar.