Modeling and optimization techniques for advanced vehicular networking

This thesis deals with optimization techniques and modeling of vehicular networks. Thanks to the models realized with the integer linear programming (ILP) and the heuristic ones, it was possible to study the performances in 5G networks for the vehicular. Thanks to Software-defined networking (SDN) and Network functions virtualization (NFV) paradigms it was possible to study the performances of different classes of service, such as the Ultra Reliable Low Latency Communications (URLLC) class and enhanced Mobile BroadBand (eMBB) class, and how the functional split can have positive effects on network resource management. Two different protection techniques have been studied: Shared Path Protection (SPP) and Dedicated Path Protection (DPP). Thanks to these different protections, it is possible to achieve different network reliability requirements, according to the needs of the end user. Finally, thanks to a simulator developed in Python, it was possible to study the dynamic allocation of resources in a 5G metro network. Through different provisioning algorithms and different dynamic resource management techniques, useful results have been obtained for understanding the needs in the vehicular networks that will exploit 5G. Finally, two models are shown for reconfiguring backup resources when using shared resource protection.

A study of brain functional connectivity and cognitive processes in long COVID-19 patients

In this work, a prospective study conducted at the IRCCS Istituto delle Scienze Neurologiche di Bologna is presented. The aim was to investigate the brain functional connectivity of a cohort of patients (N=23) suffering from persistent olfactory dysfunction after SARS-CoV-2 infection (Post-COVID-19 syndrome), as compared to a matching group of healthy controls (N=26). In particular, starting from individual resting state functional-MRI data, different analytical approaches were adopted in order to find potential alterations in the connectivity patterns of patients’ brains. Analyses were conducted both at a whole-brain level and with a special focus on brain regions involved in the processing of olfactory stimuli (Olfactory Network). Statistical correlations between functional connectivity alterations and the results of olfactory and neuropsychological tests were investigated, to explore the associations with cognitive processes. The three approaches implemented for the analysis were the seed-based correlation analysis, the group-level Independent Component analysis and a graph-theoretical analysis of brain connectivity. Due to the relative novelty of such approaches, many implementation details and methodologies are not standardized yet and represent active research fields. Seed-based and group-ICA analyses’ results showed no statistically significant differences between groups, while relevant alterations emerged from those of the graph-based analysis. In particular, patients’ olfactory sub-graph appeared to have a less pronounced modular structure compared to the control group; locally, a hyper-connectivity of the right thalamus was observed in patients, with significant involvement of the right insula and hippocampus. Results of an exploratory correlation analysis showed a positive correlation between the graphs global modularity and the scores obtained in olfactory tests and negative correlations between the thalamus hyper-connectivity and memory tests scores.

An integer programming framework for sequencing cutting patterns based on interval graph completion

We derived a framework in integer programming, based on the properties of a linear ordering of the vertices in interval graphs, that acts as an edge completion model for obtaining interval graphs. This model can be applied to problems of sequencing cutting patterns, namely the minimization of open stacks problem (MOSP). By making small modifications in the objective function and using only some of the inequalities, the MOSP model is applied to another pattern sequencing problem that aims to minimize, not only the number of stacks, but also the order spread (the minimization of the stack occupation problem), and the model is tested.

Modelling the Distribution of Ischaemic Stroke-Specific Survival Time Using an EM-based Mixture Approach with Random Effects Adjustment

A two-component survival mixture model is proposed to analyse a set of ischaemic stroke-specific mortality data. The survival experience of stroke patients after index stroke may be described by a subpopulation of patients in the acute condition and another subpopulation of patients in the chronic phase. To adjust for the inherent correlation of observations due to random hospital effects, a mixture model of two survival functions with random effects is formulated. Assuming a Weibull hazard in both components, an EM algorithm is developed for the estimation of fixed effect parameters and variance components. A simulation study is conducted to assess the performance of the two-component survival mixture model estimators. Simulation results confirm the applicability of the proposed model in a small sample setting. Copyright (C) 2004 John Wiley Sons, Ltd.

Anisotropy-based performance analysis of linear discrete time invariant control systems

The anisotropic norm of a linear discrete-time-invariant system measures system output sensitivity to stationary Gaussian input disturbances of bounded mean anisotropy. Mean anisotropy characterizes the degree of predictability (or colouredness) and spatial non-roundness of the noise. The anisotropic norm falls between the H-2 and H-infinity norms and accommodates their loss of performance when the probability structure of input disturbances is not exactly known. This paper develops a method for numerical computation of the anisotropic norm which involves linked Riccati and Lyapunov equations and an associated special type equation.

Modelling an e-learning environment for learning programming languages

It is widely accepted that solving programming exercises is fundamental to learn how to program. Nevertheless, solving exercises is only effective if students receive an assessment on their work. An exercise solved wrong will consolidate a false belief, and without feedback many students will not be able to overcome their difficulties. However, creating, managing and accessing a large number of exercises, covering all the points in the curricula of a programming course, in classes with large number of students, can be a daunting task without the appropriated tools working in unison. This involves a diversity of tools, from the environments where programs are coded, to automatic program evaluators providing feedback on the attempts of students, passing through the authoring, management and sequencing of programming exercises as learning objects. We believe that the integration of these tools will have a great impact in acquiring programming skills. Our research objective is to manage and coordinate a network of eLearning systems where students can solve computer programming exercises. Networks of this kind include systems such as learning management systems (LMS), evaluation engines (EE), learning objects repositories (LOR) and exercise resolution environments (ERE). Our strategy to achieve the interoperability among these tools is based on a shared definition of programming exercise as a Learning Object (LO).

An integer programming model for the minimum interval graph completion problem

The minimum interval graph completion problem consists of, given a graph G = ( V, E ), finding a supergraph H = ( V, E ∪ F ) that is an interval graph, while adding the least number of edges |F| . We present an integer programming formulation for solving the minimum interval graph completion problem recurring to a characteri- zation of interval graphs that produces a linear ordering of the maximal cliques of the solution graph.

A Fractional Perspective to the Bond Graph Modelling of World Economies

Inspired in dynamic systems theory and Brewer’s contributions to apply it to economics, this paper establishes a bond graph model. Two main variables, a set of inter-connectivities based on nodes and links (bonds) and a fractional order dynamical perspective, prove to be a good macro-economic representation of countries’ potential performance in nowadays globalization. The estimations based on time series for 50 countries throughout the last 50 decades confirm the accuracy of the model and the importance of scale for economic performance.

Energy-based modelling and simulation of the interconnection of a back-to-back converter and a doubly-fed induction machine

This paper describes the port interconnection of two subsystems: a power electronics subsystem (a back-to-back AC/CA converter (B2B), coupled to a phase of the power grid), and an electromechanical subsystem (a doubly-fed induction machine (DFIM). The B2B is a variable structure system (VSS), due to presence of control-actuated switches: however, from a modelling simulation, as well as a control-design, point of view, it is sensible to consider modulated transformers (MTF in the bond graph language) instead of the pairs of complementary switches. The port-Hamiltonian models of both subsystems are presented and, using a power-preserving interconnection, the Hamiltonian description of the whole system is obtained; detailed bond graphs of all subsystems and the complete system are also provided. Using passivity-based controllers computed in the Hamiltonian formalism for both subsystems, the whole model is simulated; simulations are run to rest the correctness and efficiency of the Hamiltonian network modelling approach used in this work.

GIS and geodatabases application to global scale plate tectonics modelling

Les reconstructions palinspastiques fournissent le cadre idéal à de nombreuses études géologiques, géographiques, océanographique ou climatiques. En tant qu?historiens de la terre, les "reconstructeurs" essayent d?en déchiffrer le passé. Depuis qu?ils savent que les continents bougent, les géologues essayent de retracer leur évolution à travers les âges. Si l?idée originale de Wegener était révolutionnaire au début du siècle passé, nous savons depuis le début des années « soixante » que les continents ne "dérivent" pas sans but au milieu des océans mais sont inclus dans un sur-ensemble associant croûte « continentale » et « océanique »: les plaques tectoniques. Malheureusement, pour des raisons historiques aussi bien que techniques, cette idée ne reçoit toujours pas l'écho suffisant parmi la communauté des reconstructeurs. Néanmoins, nous sommes intimement convaincus qu?en appliquant certaines méthodes et certains principes il est possible d?échapper à l?approche "Wégenerienne" traditionnelle pour enfin tendre vers la tectonique des plaques. Le but principal du présent travail est d?exposer, avec tous les détails nécessaires, nos outils et méthodes. Partant des données paléomagnétiques et paléogéographiques classiquement utilisées pour les reconstructions, nous avons développé une nouvelle méthodologie replaçant les plaques tectoniques et leur cinématique au coeur du problème. En utilisant des assemblages continentaux (aussi appelés "assemblées clés") comme des points d?ancrage répartis sur toute la durée de notre étude (allant de l?Eocène jusqu?au Cambrien), nous développons des scénarios géodynamiques permettant de passer de l?une à l?autre en allant du passé vers le présent. Entre deux étapes, les plaques lithosphériques sont peu à peu reconstruites en additionnant/ supprimant les matériels océaniques (symbolisés par des isochrones synthétiques) aux continents. Excepté lors des collisions, les plaques sont bougées comme des entités propres et rigides. A travers les âges, les seuls éléments évoluant sont les limites de plaques. Elles sont préservées aux cours du temps et suivent une évolution géodynamique consistante tout en formant toujours un réseau interconnecté à travers l?espace. Cette approche appelée "limites de plaques dynamiques" intègre de multiples facteurs parmi lesquels la flottabilité des plaques, les taux d'accrétions aux rides, les courbes de subsidence, les données stratigraphiques et paléobiogéographiques aussi bien que les évènements tectoniques et magmatiques majeurs. Cette méthode offre ainsi un bon contrôle sur la cinématique des plaques et fournit de sévères contraintes au modèle. Cette approche "multi-source" nécessite une organisation et une gestion des données efficaces. Avant le début de cette étude, les masses de données nécessaires était devenues un obstacle difficilement surmontable. Les SIG (Systèmes d?Information Géographiques) et les géo-databases sont des outils informatiques spécialement dédiés à la gestion, au stockage et à l?analyse des données spatialement référencées et de leurs attributs. Grâce au développement dans ArcGIS de la base de données PaleoDyn nous avons pu convertir cette masse de données discontinues en informations géodynamiques précieuses et facilement accessibles pour la création des reconstructions. Dans le même temps, grâce à des outils spécialement développés, nous avons, tout à la fois, facilité le travail de reconstruction (tâches automatisées) et amélioré le modèle en développant fortement le contrôle cinématique par la création de modèles de vitesses des plaques. Sur la base des 340 terranes nouvellement définis, nous avons ainsi développé un set de 35 reconstructions auxquelles est toujours associé un modèle de vitesse. Grâce à cet ensemble de données unique, nous pouvons maintenant aborder des problématiques majeurs de la géologie moderne telles que l?étude des variations du niveau marin et des changements climatiques. Nous avons commencé par aborder un autre problème majeur (et non définitivement élucidé!) de la tectonique moderne: les mécanismes contrôlant les mouvements des plaques. Nous avons pu observer que, tout au long de l?histoire de la terre, les pôles de rotation des plaques (décrivant les mouvements des plaques à la surface de la terre) tendent à se répartir le long d'une bande allant du Pacifique Nord au Nord de l'Amérique du Sud, l'Atlantique Central, l'Afrique du Nord, l'Asie Centrale jusqu'au Japon. Fondamentalement, cette répartition signifie que les plaques ont tendance à fuir ce plan médian. En l'absence d'un biais méthodologique que nous n'aurions pas identifié, nous avons interprété ce phénomène comme reflétant l'influence séculaire de la Lune sur le mouvement des plaques. La Lune sur le mouvement des plaques. Le domaine océanique est la clé de voute de notre modèle. Nous avons attaché un intérêt tout particulier à le reconstruire avec beaucoup de détails. Dans ce modèle, la croûte océanique est préservée d?une reconstruction à l?autre. Le matériel crustal y est symbolisé sous la forme d?isochrones synthétiques dont nous connaissons les âges. Nous avons également reconstruit les marges (actives ou passives), les rides médio-océaniques et les subductions intra-océaniques. En utilisant ce set de données très détaillé, nous avons pu développer des modèles bathymétriques 3-D unique offrant une précision bien supérieure aux précédents.<br/><br/>Palinspastic reconstructions offer an ideal framework for geological, geographical, oceanographic and climatology studies. As historians of the Earth, "reconstructers" try to decipher the past. Since they know that continents are moving, geologists a trying to retrieve the continents distributions through ages. If Wegener?s view of continent motions was revolutionary at the beginning of the 20th century, we know, since the Early 1960?s that continents are not drifting without goal in the oceanic realm but are included in a larger set including, all at once, the oceanic and the continental crust: the tectonic plates. Unfortunately, mainly due to technical and historical issues, this idea seems not to receive a sufficient echo among our particularly concerned community. However, we are intimately convinced that, by applying specific methods and principles we can escape the traditional "Wegenerian" point of view to, at last, reach real plate tectonics. This is the main aim of this study to defend this point of view by exposing, with all necessary details, our methods and tools. Starting with the paleomagnetic and paleogeographic data classically used in reconstruction studies, we developed a modern methodology placing the plates and their kinematics at the centre of the issue. Using assemblies of continents (referred as "key assemblies") as anchors distributed all along the scope of our study (ranging from Eocene time to Cambrian time) we develop geodynamic scenarios leading from one to the next, from the past to the present. In between, lithospheric plates are progressively reconstructed by adding/removing oceanic material (symbolized by synthetic isochrones) to major continents. Except during collisions, plates are moved as single rigid entities. The only evolving elements are the plate boundaries which are preserved and follow a consistent geodynamical evolution through time and form an interconnected network through space. This "dynamic plate boundaries" approach integrates plate buoyancy factors, oceans spreading rates, subsidence patterns, stratigraphic and paleobiogeographic data, as well as major tectonic and magmatic events. It offers a good control on plate kinematics and provides severe constraints for the model. This multi-sources approach requires an efficient data management. Prior to this study, the critical mass of necessary data became a sorely surmountable obstacle. GIS and geodatabases are modern informatics tools of specifically devoted to store, analyze and manage data and associated attributes spatially referenced on the Earth. By developing the PaleoDyn database in ArcGIS software we converted the mass of scattered data offered by the geological records into valuable geodynamical information easily accessible for reconstructions creation. In the same time, by programming specific tools we, all at once, facilitated the reconstruction work (tasks automation) and enhanced the model (by highly increasing the kinematic control of plate motions thanks to plate velocity models). Based on the 340 terranes properly defined, we developed a revised set of 35 reconstructions associated to their own velocity models. Using this unique dataset we are now able to tackle major issues of the geology (such as the global sea-level variations and climate changes). We started by studying one of the major unsolved issues of the modern plate tectonics: the driving mechanism of plate motions. We observed that, all along the Earth?s history, plates rotation poles (describing plate motions across the Earth?s surface) tend to follow a slight linear distribution along a band going from the Northern Pacific through Northern South-America, Central Atlantic, Northern Africa, Central Asia up to Japan. Basically, it sighifies that plates tend to escape this median plan. In the absence of a non-identified methodological bias, we interpreted it as the potential secular influence ot the Moon on plate motions. The oceanic realms are the cornerstone of our model and we attached a particular interest to reconstruct them with many details. In this model, the oceanic crust is preserved from one reconstruction to the next. The crustal material is symbolised by the synthetic isochrons from which we know the ages. We also reconstruct the margins (active or passive), ridges and intra-oceanic subductions. Using this detailed oceanic dataset, we developed unique 3-D bathymetric models offering a better precision than all the previously existing ones.

Network Similarity Measures and Automatic Construction of Graph Models using Genetic Programming

A complex network is an abstract representation of an intricate system of interrelated elements where the patterns of connection hold significant meaning. One particular complex network is a social network whereby the vertices represent people and edges denote their daily interactions. Understanding social network dynamics can be vital to the mitigation of disease spread as these networks model the interactions, and thus avenues of spread, between individuals. To better understand complex networks, algorithms which generate graphs exhibiting observed properties of real-world networks, known as graph models, are often constructed. While various efforts to aid with the construction of graph models have been proposed using statistical and probabilistic methods, genetic programming (GP) has only recently been considered. However, determining that a graph model of a complex network accurately describes the target network(s) is not a trivial task as the graph models are often stochastic in nature and the notion of similarity is dependent upon the expected behavior of the network. This thesis examines a number of well-known network properties to determine which measures best allowed networks generated by different graph models, and thus the models themselves, to be distinguished. A proposed meta-analysis procedure was used to demonstrate how these network measures interact when used together as classifiers to determine network, and thus model, (dis)similarity. The analytical results form the basis of the fitness evaluation for a GP system used to automatically construct graph models for complex networks. The GP-based automatic inference system was used to reproduce existing, well-known graph models as well as a real-world network. Results indicated that the automatically inferred models exemplified functional similarity when compared to their respective target networks. This approach also showed promise when used to infer a model for a mammalian brain network.

Modelling, control and supervision for a class of hybrid systems

The aim of this thesis is to narrow the gap between two different control techniques: the continuous control and the discrete event control techniques DES. This gap can be reduced by the study of Hybrid systems, and by interpreting as Hybrid systems the majority of large-scale systems. In particular, when looking deeply into a process, it is often possible to identify interaction between discrete and continuous signals. Hybrid systems are systems that have both continuous, and discrete signals. Continuous signals are generally supposed continuous and differentiable in time, since discrete signals are neither continuous nor differentiable in time due to their abrupt changes in time. Continuous signals often represent the measure of natural physical magnitudes such as temperature, pressure etc. The discrete signals are normally artificial signals, operated by human artefacts as current, voltage, light etc. Typical processes modelled as Hybrid systems are production systems, chemical process, or continuos production when time and continuous measures interacts with the transport, and stock inventory system. Complex systems as manufacturing lines are hybrid in a global sense. They can be decomposed into several subsystems, and their links. Another motivation for the study of Hybrid systems is the tools developed by other research domains. These tools benefit from the use of temporal logic for the analysis of several properties of Hybrid systems model, and use it to design systems and controllers, which satisfies physical or imposed restrictions. This thesis is focused in particular types of systems with discrete and continuous signals in interaction. That can be modelled hard non-linealities, such as hysteresis, jumps in the state, limit cycles, etc. and their possible non-deterministic future behaviour expressed by an interpretable model description. The Hybrid systems treated in this work are systems with several discrete states, always less than thirty states (it can arrive to NP hard problem), and continuous dynamics evolving with expression: with Ki ¡ Rn constant vectors or matrices for X components vector. In several states the continuous evolution can be several of them Ki = 0. In this formulation, the mathematics can express Time invariant linear system. By the use of this expression for a local part, the combination of several local linear models is possible to represent non-linear systems. And with the interaction with discrete events of the system the model can compose non-linear Hybrid systems. Especially multistage processes with high continuous dynamics are well represented by the proposed methodology. Sate vectors with more than two components, as third order models or higher is well approximated by the proposed approximation. Flexible belt transmission, chemical reactions with initial start-up and mobile robots with important friction are several physical systems, which profits from the benefits of proposed methodology (accuracy). The motivation of this thesis is to obtain a solution that can control and drive the Hybrid systems from the origin or starting point to the goal. How to obtain this solution, and which is the best solution in terms of one cost function subject to the physical restrictions and control actions is analysed. Hybrid systems that have several possible states, different ways to drive the system to the goal and different continuous control signals are problems that motivate this research. The requirements of the system on which we work is: a model that can represent the behaviour of the non-linear systems, and that possibilities the prediction of possible future behaviour for the model, in order to apply an supervisor which decides the optimal and secure action to drive the system toward the goal. Specific problems can be determined by the use of this kind of hybrid models are: - The unity of order. - Control the system along a reachable path. - Control the system in a safe path. - Optimise the cost function. - Modularity of control The proposed model solves the specified problems in the switching models problem, the initial condition calculus and the unity of the order models. Continuous and discrete phenomena are represented in Linear hybrid models, defined with defined eighth-tuple parameters to model different types of hybrid phenomena. Applying a transformation over the state vector : for LTI system we obtain from a two-dimensional SS a single parameter, alpha, which still maintains the dynamical information. Combining this parameter with the system output, a complete description of the system is obtained in a form of a graph in polar representation. Using Tagaki-Sugeno type III is a fuzzy model which include linear time invariant LTI models for each local model, the fuzzyfication of different LTI local model gives as a result a non-linear time invariant model. In our case the output and the alpha measure govern the membership function. Hybrid systems control is a huge task, the processes need to be guided from the Starting point to the desired End point, passing a through of different specific states and points in the trajectory. The system can be structured in different levels of abstraction and the control in three layers for the Hybrid systems from planning the process to produce the actions, these are the planning, the process and control layer. In this case the algorithms will be applied to robotics ¡V a domain where improvements are well accepted ¡V it is expected to find a simple repetitive processes for which the extra effort in complexity can be compensated by some cost reductions. It may be also interesting to implement some control optimisation to processes such as fuel injection, DC-DC converters etc. In order to apply the RW theory of discrete event systems on a Hybrid system, we must abstract the continuous signals and to project the events generated for these signals, to obtain new sets of observable and controllable events. Ramadge & Wonham¡¦s theory along with the TCT software give a Controllable Sublanguage of the legal language generated for a Discrete Event System (DES). Continuous abstraction transforms predicates over continuous variables into controllable or uncontrollable events, and modifies the set of uncontrollable, controllable observable and unobservable events. Continuous signals produce into the system virtual events, when this crosses the bound limits. If this event is deterministic, they can be projected. It is necessary to determine the controllability of this event, in order to assign this to the corresponding set, , controllable, uncontrollable, observable and unobservable set of events. Find optimal trajectories in order to minimise some cost function is the goal of the modelling procedure. Mathematical model for the system allows the user to apply mathematical techniques over this expression. These possibilities are, to minimise a specific cost function, to obtain optimal controllers and to approximate a specific trajectory. The combination of the Dynamic Programming with Bellman Principle of optimality, give us the procedure to solve the minimum time trajectory for Hybrid systems. The problem is greater when there exists interaction between adjacent states. In Hybrid systems the problem is to determine the partial set points to be applied at the local models. Optimal controller can be implemented in each local model in order to assure the minimisation of the local costs. The solution of this problem needs to give us the trajectory to follow the system. Trajectory marked by a set of set points to force the system to passing over them. Several ways are possible to drive the system from the Starting point Xi to the End point Xf. Different ways are interesting in: dynamic sense, minimum states, approximation at set points, etc. These ways need to be safe and viable and RchW. And only one of them must to be applied, normally the best, which minimises the proposed cost function. A Reachable Way, this means the controllable way and safe, will be evaluated in order to obtain which one minimises the cost function. Contribution of this work is a complete framework to work with the majority Hybrid systems, the procedures to model, control and supervise are defined and explained and its use is demonstrated. Also explained is the procedure to model the systems to be analysed for automatic verification. Great improvements were obtained by using this methodology in comparison to using other piecewise linear approximations. It is demonstrated in particular cases this methodology can provide best approximation. The most important contribution of this work, is the Alpha approximation for non-linear systems with high dynamics While this kind of process is not typical, but in this case the Alpha approximation is the best linear approximation to use, and give a compact representation.

A new adaptive multiple modelling approach for non-linear and non-stationary systems

This paper proposes a novel adaptive multiple modelling algorithm for non-linear and non-stationary systems. This simple modelling paradigm comprises K candidate sub-models which are all linear. With data available in an online fashion, the performance of all candidate sub-models are monitored based on the most recent data window, and M best sub-models are selected from the K candidates. The weight coefficients of the selected sub-model are adapted via the recursive least square (RLS) algorithm, while the coefficients of the remaining sub-models are unchanged. These M model predictions are then optimally combined to produce the multi-model output. We propose to minimise the mean square error based on a recent data window, and apply the sum to one constraint to the combination parameters, leading to a closed-form solution, so that maximal computational efficiency can be achieved. In addition, at each time step, the model prediction is chosen from either the resultant multiple model or the best sub-model, whichever is the best. Simulation results are given in comparison with some typical alternatives, including the linear RLS algorithm and a number of online non-linear approaches, in terms of modelling performance and time consumption.

Robust State-Derivative Feedback LMI-Based Designs for Linear Descriptor Systems

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)