Life, Universe and Everything

The iroha song of human concepts (2021) The iroha is a Japanese poem of a perfect pangram and isogram, containing each character of the Japanese syllabary exactly once. It also mimics an ultimate conceptual engineering, in that there is more and more restricted scope for meaningful expressions, given more and more condensed means of description. This culminates in crystallizations of human values by auto-condensations of meaningful concepts. Instead of distilling Japanese values of 11th century, I try for those of human concepts, given our merging mind, language and culture

Beamforming design and power control for spectrum sharing systems

In order to provide wireless services for the current demand of high data rate mobile applications, more spectrally efficient systems are needed. As a matter of fact, the current wireless systems are limited by a frequency splitting spectrum management which in one hand minimizes the multiuser interference but; on the other hand, it precludes the use of wider bandwidth signals. As a more aggressive frequency reuse is targeted (ideally, all transmitters might eventually share the same frequency band), the use of multiple antennas for interference reliving, jointly with a smart power allocation is compulsory. In addition, novel spectrum management regulatory policies are required for ensuring a peaceful coexistence between adjacent spectrum sharing networks and for promoting their development. The aim of this dissertation is provide a beamforming and power allocation design for these novel spectrum sharing systems which are meant to exponentially increase the spectral efficiency of the systems. A mathematical framework based on multicriteria optimization for analyzing the beamforming design is provided which serves as a fundamental tool for describing the state-of-the-art studies in multiantenna interference networks. Indeed, the achievable rates are described and several ways of computing the Pareto rate region of MISO interference channel (i.e. the communication model that represents the spectrum sharing network when the transmitters use multiple antennas) are studied. Nevertheless, as the system designer aims to work in a single efficient rate point, the sum-rate optimal beamforming design is studied. Curiously, it results that under some realistic assumptions on both the desired and interference power levels, the obtained beamformer is the reciprocal version of a known receiving one and it optimizes a notion of antenna directivity for multiuser communications. Neverthelss, it is important to remark that the higher transmit power is used, the more interference dominated is the medium, not only within the wireless network, but also to eventually adjacent networks that might suffer from inter-network interference. In order to cope with this problem, a spectrum licensing system is revisited, namely time-area-spectrum license. Under this spectrum management mechanism, a license holder is able to radiate signals under a certain portion of time, within a concrete area and in a given band. Moreover, the amount of signal strength within the area is constraint by a certain value. Since controlling the signal power levels in a given area is cumbersome, we propose to restrict the receive power as an estimation of the overall accumulated signal strength. Therefore, the optimal transmit beamformers and power allocations are studied. Concretely, the achievable rates are derived and an operational working point is envisaged. In addition, a suboptimal yet low computationally complex and decentralized beamforming design is presented and it shows a good performance in front of other decentralized designs

Partitionnement d’instances de processus basé sur les techniques de conformité de modèles

As event data becomes an ubiquitous source of information, data science techniques represent an unprecedented opportunity to analyze and react to the processes that generate this data. Process Mining is an emerging field that bridges the gap between traditional data analysis techniques, like Data Mining, and Business Process Management. One core value of Process Mining is the discovery of formal process models like Petri nets or BPMN models which attempt to make sense of the events recorded in logs. Due to the complexity of event data, automated process discovery algorithms tend to create dense process models which are hard to interpret by humans. Fortunately, Conformance Checking, a sub-field of Process Mining, enables relating observed and modeled behavior, so that humans can map these two pieces of process information. Conformance checking is possible through alignment artefacts, which associate process models and event logs. Different types of alignment artefacts exist, namely alignments, multi-alignments and anti-alignments. Currently, only alignment artefacts are deeply addressed in the literature. It allows to relate the process model to a given process instance. However, because many behaviors exist in logs, identifying an alignment per process instance hinders the readability of the log-to-model relationships.The present thesis proposes to exploit the conformance checking artefacts for clustering the process executions recorded in event logs, thereby extracting a restrictive number of modeled representatives. Data clustering is a common method for extracting information from dense and complex data. By grouping objects by similarities into clusters, data clustering enables to mine simpler datasets which embrace the similarities and the differences contained in data. Using the conformance checking artefacts in a clustering approach allows to consider a reliable process model as a baseline for grouping the process instances. Hence, the discovered clusters are associated with modeled artefacts, that we call model-based trace variants, which provides opportune log-to-model explanations.From this motivation, we have elaborated a set of methods for computing conformance checking artefacts. The first contribution is the computation of a unique modeled behavior that represents of a set of process instances, namely multi-alignment. Then, we propose several alignment-based clustering approaches which provide clusters of process instances associated to a modeled artefact. Finally, we highlight the interest of anti-alignment for extracting deviations of process models with respect to the log. This latter artefact enables to estimate model precision, and we show its impact in model-based clustering. We provide SAT encoding for all the proposed techniques. Heuristic algorithms are then added to deal with computing capacity of today’s computers, at the expense of loosing optimality.Les données d'événements devenant une source d'information omniprésente, les techniques d'analyse de données représentent une opportunité sans précédent pour étudier et réagir aux processus qui génèrent ces données. Le Process Mining est un domaine émergent qui comble le fossé entre les techniques d'analyse de données, comme le Data Mining, et les techniques de management des entreprises, à savoir, le Business Process Management. L'une des bases fondamentales du Process Mining est la découverte de modèles de processus formels tels que les réseaux de Petri ou les modèles BPMN qui tentent de donner un sens aux événements enregistrés dans les journaux. En raison de la complexité des données d'événements, les algorithmes de découverte de processus ont tendance à créer des modèles de processus denses, qui sont difficiles à interpréter par les humains. Heureusement, la Vérification de Conformité, un sous-domaine du Process Mining, permet d'établir des liens entre le comportement observé et le comportement modélisé, facilitant ainsi la compréhension des correspondance entre ces deux éléments d'information sur les processus. La Vérification de Conformité est possible grâce aux artefacts d'alignement, qui associent les modèles de processus et les journaux d'événements. Il existe différents types d'artefacts d'alignement, à savoir les alignements, les multi-alignements et les anti-alignements. Actuellement, seuls les alignements sont traités en profondeur dans la littérature scientifique. Un alignement permet de relier le modèle de processus à une instance de processus donnée. Cependant, étant donné que de nombreux comportements existent dans les logs, l'identification d'un alignement par instance de processus nuit à la lisibilité des relations log-modèle.La présente thèse propose d'exploiter les artefacts de conformité pour regrouper les exécutions de processus enregistrées dans les journaux d'événements, et ainsi extraire un nombre restrictif de représentations modélisées. Le regroupement de données, communément appelé partitionnement, est une méthode courante pour extraire l'information de données denses et complexes. En regroupant les objets par similarité dans des clusters, le partitionnement permet d'extraire des ensembles de données plus simples qui englobent les similarités et les différences contenues dans les données. L'utilisation des artefacts de conformité dans une approche de partitionnement permet de considérer un modèle de processus fiable comme une base de référence pour le regroupement des instances de processus. Ainsi, les clusters découverts sont associés à des artefacts modélisés, que nous appelons variantes modélisées des traces, ce qui fournit des explications opportunes sur les relations entre le journal et le modèle.Avec cette motivation, nous avons élaboré un ensemble de méthodes pour calculer les artefacts de conformité. La première contribution est le calcul d'un comportement modélisé unique qui représente un ensemble d'instances de processus, à savoir le multi-alignement. Ensuite, nous proposons plusieurs approches de partitionnement basées sur l'alignement qui fournissent des clusters d'instances de processus associés à un artefact modélisé. Enfin, nous soulignons l'intérêt de l'anti-alignement pour extraire les déviations des modèles de processus par rapport au journal. Ce dernier artefact permet d'estimer la précision du modèle. Nous montrons son impact sur nos approches de partitionnement basées sur des modèles. Nous fournissons un encodage SAT pour toutes les techniques proposées. Des heuristiques sont ensuite ajoutées pour tenir compte de la capacité de calcul des ordinateurs actuels, au prix d'une perte d'optimalité