Event-based data are encountered daily in many disciplines and are used for various purposes. They are collections of ordered sequences of events where each event has a start time and a duration. Examples of such data include medical records, internet surfing records, transaction records, industrial process or system control records, and activity diary data. This thesis is concerned with the exploration of event-based data, and in particular the identification and analysis of sequences within them. Sequences are interesting in this context since they enable the understanding of the evolving character of event data records over time. They can reveal trends, relationships and similarities across the data, allow for comparisons to be made within and between the records, and can also help predict forthcoming events.The presented work has researched methods for identifying and exploring such event-sequences which are based on modern visualization, interaction and data mining techniques. An interactive visualization environment that facilitates analysis and exploration of event-based data has been designed and developed, which permits a user to freely explore different aspects of this data and visually identify interesting features and trends. Visual data mining methods have been developed within this environment, that facilitate the automatic identification and exploration of interesting sequences as patterns. The first method makes use of a sequence mining algorithm that identifies sequences of events as patterns, in an iterative fashion, according to certain user-defined constraints. The resulting patterns can then be displayed and interactively explored by the user.The second method has been inspired by web-mining algorithms and the use of graph similarity. A tree-inspired visual exploration environment has been developed that allows a user to systematically and interactively explore interesting event-sequences.Having identified interesting sequences as patterns it becomes interesting to further explore how these are incorporated across the data and classify the records based on the similarities in the way these sequences are manifested within them. In the final method developed in this work, a set of similarity metrics has been identified for characterizing event-sequences, which are then used within a clustering algorithm in order to find similarly behavinggroups. The resulting clusters, as well as attributes of the clusteringparameters and data records, are displayed in a set of linked views allowing the user to interactively explore relationships within these. The research has been focused on the exploration of activity diary data for the study of individuals' time-use and has resulted in a powerful research tool facilitating understanding and thorough analysis of the complexity of everyday life.

Les systèmes hybrides sont des systèmes dynamiques, caractérisés par un comportementdual, une interaction entre une partie discrète et une partie continue de fonctionnement.Dans le centre de notre travail se trouve une classe particulière de systèmeshybrides, plus spécifiquement les systèmes stochastiques à commutation que nous modélisonsà l’aide des Chaînes de Markov en temps continu et des équations différentielles.Le comportement aléatoire de ce type de système nécessite une commande spécialequi s’adapte aux événements arbitraires qui peuvent changer complètement l’évolutiondu système. Nous avons choisi une politique de contrôle basée sur les événements quiest déclenchée seulement quand il est nécessaire (sur un événement incontrôlable - parexemple un seuil qui est atteint), et jusqu’à ce que certaines conditions de fonctionnementsont remplies (le système revient dans l’état normal).Notre approche vise le développement d’un modèle probabiliste qui permet de calculerun critère de performance (en occurrence l’énergie du système) pour la politiquede contrôle choisie. Nous proposons d’abord une méthode de simulation à événementsdiscrets pour le système stochastique à commutation commandé, qui nous donne la possibilitéde réaliser une optimisation directe de la commande appliquée sur le système etaussi de valider les modèles analytiques que nous avons construit pour l’application ducontrôle.Un modèle analytique pour déterminer l’énergie consommée par le système a étéconçu en utilisant les probabilités de sortie de la région de contrôle, respectivement lestemps de séjour dans la chaîne de Markov avant et après avoir atteint les limites decontrôle. La dernière partie du travail présente la comparaison des résultats obtenusentre la méthode analytique et la simulation. / Hybrid systems are dynamical systems, characterized by a dual behaviour, a continuousinteraction between a discrete and a continuous functioning part. The center ofour work is represented by a particular class of hybrid systems, more specific by thestochastic switching systems which we model using continuous time Markov chains anddifferential equations.The random behaviour of such systems requires a special command which adapts tothe arbitrary events that can completely change the evolution of the system. We chose anevent-based control policy which is triggered only when it’s necessary (on an unforeseenevent - for example when a threshold that is reached), and until certain functioningconditions are met (the system returns in the normal state).Our approach aims to develop a probabilistic model that calculates a performancecriterion (in this case the energy of the system) for the proposed control policy. We startby proposing a discrete event simulation for the controlled stochastic switching system,which gives us the opportunity of applying a direct optimisation of the control command.It also allows us to compare the results with the ones obtained by the analytical modelswe have built when the event-based control is applied.An analytical model for computing the energy consumed by the system to apply thecontrol is designed by using the exit probabilities of the control region, respectively, thesojourn times of the Markov chain before and after reaching the control limits. The lastpart of this work presents the results we have obtained when comparing the analyticaland the simulation method.

Submitted by Alison Vanceto (alison-vanceto@hotmail.com) on 2017-06-08T17:50:25Z No. of bitstreams: 1 DissTLF.pdf: 1609618 bytes, checksum: 6d556d5f96c86d3bb3f1b5c0803a77f0 (MD5) / Approved for entry into archive by Ronildo Prado (ronisp@ufscar.br) on 2017-06-14T13:32:38Z (GMT) No. of bitstreams: 1 DissTLF.pdf: 1609618 bytes, checksum: 6d556d5f96c86d3bb3f1b5c0803a77f0 (MD5) / Approved for entry into archive by Ronildo Prado (ronisp@ufscar.br) on 2017-06-14T13:32:44Z (GMT) No. of bitstreams: 1 DissTLF.pdf: 1609618 bytes, checksum: 6d556d5f96c86d3bb3f1b5c0803a77f0 (MD5) / Made available in DSpace on 2017-06-14T13:37:27Z (GMT). No. of bitstreams: 1 DissTLF.pdf: 1609618 bytes, checksum: 6d556d5f96c86d3bb3f1b5c0803a77f0 (MD5) Previous issue date: 2017-02-22 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / The causative relation has been, for centuries, an interesting source of research in the most di erent areas of knowledge. In this dissertation, we investigated the possibility of certain unergative and unaccusative verbs to express causality, although not being causatives in their base, such as the children sat on the oor Ð→ the mom sat the children on the oor . Our proposal is that the causativization phenomenon is a syntactic mechanism by which the events can receive a (direct) causative interpretation in the situational domain ([ cause P]). The analysis is developed on the basis of Nanosyntax assumptions (Starke, 2009) and demonstrates the role of the terminals of the event domain, the Spell-out rules and the lexical-encyclopedic knowledge in the license of the causativization process in Brazilian Portuguese. / A relação de causalidade tem sido há séculos uma fonte interessante de pesquisa nas mais diferentes áreas do conhecimento. Nesta dissertação, investigamos a possibilidade de certos predicados inergativos e inacusativos expressarem uma relação de causalidade, embora não sejam causativos em sua base, tal como as crianças sentaram no chão Ð→ a mãe sentou as crianças no chão . Nossa proposta é que o fenômeno da causativização seja um mecanismo sintático por meio do qual os eventos podem receber uma interpretação causativa (direta) no domínio das situações ([ cause P]). A análise é desenvolvida com base em pressupostos da Nanossintaxe (Starke, 2009) e demonstra o papel dos terminais que compõem o domínio acional, das regras de Spell-out e do conteúdo léxico-enciclopédico no licenciamento da causativização no Português Brasileiro.

Traffic simulation is a safe and efficient tool to investigate infrastructural changes as well as traffic conditions. This master thesis aims to analyse a microscopic traffic simulation method for evaluation of bus terminal capacity. The evaluation is performed by investigating a case study of the bus terminal at Norrköping travel centre. The analysed method, referred to as terminal logic in the thesis, uses a combination of time based and event based simulation. Through the combination of time and event, it is possible to capture all movements within the terminal for individual vehicles. The simulation model is built in the software Vissim. A new travel centre for Norrköping is under development. Among the reasons for a new travel centre is the railway project Ostlänken in the eastern part of Sweden. An evaluation of the bus terminal is interesting due to a suspicion of overcapacity and the opportunity of redesigning. To investigate both the terminal capacity and the terminal logic, three scenarios were implemented. Scenario 1: Current design and frequency Scenario 2: Current design with higher frequency Scenario 3: Decreased number of bus stops with current frequency The results from the scenarios confirm the assumption of overcapacity. The capacity was evaluated based on several different measures, all indicating a low utilization. Even so, the utilization was uneven over time and congestion could still occur when several buses departed at the same time. This was also seen when studying the simulation, which showed congestions when several buses departed at the same time. The case study established the terminal logic to be useful when evaluating capacity at bus terminals. It provides a good understanding of how the terminal operates and captures the movements. However, it was time-consuming to adjust the logic to the studied terminal. This is a disadvantage when investigating more than one alternative. The thesis resulted in two main conclusions. Firstly, a more optimised planning of the buses at Norrköping bus terminal would probably be achievable and lead to less congestions at the exits. Secondly, the terminal logic is a good method to use when evaluating bus terminals but it is not straight forward to implement.

Predictive maintenance plays a major role in operational cost reduction in several industries and the railway industry is no exception. Predictive maintenance relies on real time data to predict and diagnose technical failures. Sensor data is usually utilized for this purpose, however it might not always be available. Events data are a potential substitute as a source of information which could be used to diagnose and predict failures. This thesis investigates the use of events data in the railway industry for failure diagnosis and prediction. The proposed approach turns this problem into a sequence classification task, where the data is transformed into a set of sequences which are used to train the machine learning algorithm. Long Short-Term Memory neural network is used as it has been successfully used in the past for sequence classification tasks. The prediction model is able to achieve high training accuracy, but it is at the moment unable to generalize the patterns and apply them on new sets of data. At the end of the thesis, the approach is evaluated and future steps are proposed to improve failure diagnosis and prediction.

Different paths for trains throughout a railway system are more or less convenient, where intersecting train paths require a safety margin in time between different trains to reduce the risks of accidents. Intersecting train paths are just as much of a challenge on a railway station, especially when multiple trains are entering the station close in time. Some trains might have to wait before entering the station area, which as a result create delays that can affect other trains and passengers. One method of reducing the delay is by allocating trains efficiently to different platforms on the station, which makes it possible for more trains to be at the station at the same time. The purpose of this report was to investigate the effect of different platform allocation strategies in regard to the punctuality of trains, passengers’ convenience, travel time in the system as well as the delay compared to arrival and departure times. Three research questions were formulated to answer to the purpose, which included how a reduction in platforms affect the railway system, how different strategies affect walking time for passengers and whether it was possible to prioritize different train types to different platforms. To investigate how different platform allocation strategies affect the railway system, simulation as a method was used. With simulation, a model could be constructed similar to the real system, which made it possible to perform different experiments quickly without any impact on the real system. Linköping Central Station was chosen as a test case as it was both reasonably large and geographically close for observations. Four experiments were constructed, with four separate platform allocation strategies, all aimed to answer some part of the purpose. Before conducting the experiments, a base scenario was tested that attempted to mimic the current platforming strategy as much as possible and was used to compare the different experiments to. This thesis demonstrates that several different platform allocation strategies are possible to be used in the test case, where a risk of train delays were present when the number of tracks used were decreased. With the help of the experiments, the three research questions and therefore the purpose of the study have been answered. / <p>Examensarbetet är utfört vid Institutionen för teknik och naturvetenskap (ITN) vid Tekniska fakulteten, Linköpings universitet</p>

Cette thèse porte sur l’implémentation d’algorithmes événementiels, en utilisant, dans un premier temps, des données provenant d’une rétine artificielle, mimant le fonctionnement de la rétine humaine, pour ensuite évoluer vers tous types de signaux événementiels. Ces signaux événementiels sont issus d’un changement de paradigme dans la représentation du signal, offrant une grande plage dynamique de fonctionnement, une résolution temporelle importante ainsi qu’une compression native du signal. Sera notamment étudiée la réalisation d’un dispositif de création de cartes de profondeur monoculaires à haute fréquence, un algorithme de tri cellulaire en temps réel, ainsi que l’apprentissage non supervisé pour de la reconnaissance de formes. Certains de ces algorithmes (détection de flot optique, construction de cartes de profondeur en stéréovision) seront développés en parallèle sur des plateformes de simulation neuromorphiques existantes (SpiNNaker, TrueNorth), afin de proposer une chaîne de traitement de l’information entièrement neuromorphique, du capteur au calcul, à faible coût énergétique. / This thesis is about the implementation of neuromorphic algorithms, using, as a first step, data from a silicon retina, mimicking the human eye’s behavior, and then evolve towards all kind of event-based signals. These eventbased signals are coming from a paradigm shift in the data representation, thus allowing a high dynamic range, a precise temporal resolution and a sensor-level data compression. Especially, we will study the development of a high frequency monocular depth map generator, a real-time spike sorting algorithm for intelligent brain-machine interfaces, and an unsupervised learning algorithm for pattern recognition. Some of these algorithms (Optical flow detection, depth map construction from stereovision) will be in the meantime developed on available neuromorphic platforms (SpiNNaker, TrueNorth), thus allowing a fully neuromorphic pipeline, from sensing to computing, with a low power budget.

The objective of this thesis is to investigate the flow conditions that lead to coarse grain entrainment at near incipient motion conditions. Herein, a new conceptual approach is proposed, which in addition to the magnitude of hydrodynamic force or flow power, takes into account the duration of the flow event. Two criteria for inception of grain entrainment, namely the critical impulse and critical energy concepts, are proposed and compared. These frameworks adopt a force or energy perspective, considering the momentum or energy transfer from each flow event to the particle respectively, to describe the phenomenon. A series of conducted mobile particle experiments, are analyzed to examine the validity of the proposed approaches. First a set of bench-top experiments incorporates an electromagnet which applies pulses of known magnitude and duration to a steel spherical particle in a controlled fashion, so as to identify the critical level for entrainment. The utility of the above criteria is also demonstrated for the case of entrainment by the action of turbulent flow, via analysis of a series of flume experiments, where both the history of hydrodynamic forces exerted on the particle as well as its response are recorded simultaneously. Statistical modeling of the distribution of impulses, as well as conditional excess impulses, is performed using distributions from Extreme Value Theory to effectively model the episodic nature of the occurrence of these events. For the examined uniform and low mobility flow conditions, a power law relationship is proposed for describing the magnitude and frequency of occurrence of the impulse events. The Weibull and exponential distributions provide a good fit for the time between particle entrainments. In addition to these statistical tools, a number of Adaptive Neuro-Fuzzy Inference Systems employing different input representations are used to learn the nonlinear dynamics of the system and perform statistical prediction. The performance of these models is assessed in terms of their broad validity, efficiency and forecast accuracy. Even though the impulse and energy criteria are deeply interrelated, the latter is shown to be advantageous with regard to its performance, applicability and extension ability. The effect of single or multiple highly energetic events carried by certain coherent flow structures (mainly strong sweep events) with regard to the particle response is also investigated. / Ph. D.

Publish/subscribe (P/S) is a communication paradigm of growing popularity for information dissemination in large-scale distributed systems. The weak coupling between information producers and consumers in P/S systems is attractive for loosely coupled and dynamic network infrastructures such as ad hoc networks. However, achieving end-to-end timeliness and reliability properties when P/S events are causally dependent is an open problem in ad hoc networks. In this thesis, we present, evaluate benefits of, and compare with past work, an architecture design that can effectively support timely and reliable delivery of events and causally related events in ad hoc environments, and especially in mobile ad hoc networks (MANETs). With observations from both realistic application model and simulation experiments, we reveal causal dependencies among events and their significance in a typical use notional system. We also examine and propose engineering methodologies to further tailor an event-based system to facilitate its self-reorganizing capability and self-reconfiguration. Our design features a two-layer structure, including novel distributed algorithms and mechanisms for P/S tree construction and maintenance. The trace-based experimental simulation studies illustrate our design's effectiveness in both cases with and without causal dependencies. / Master of Science

In this thesis study, it is aimed to improve the performance of an Internet-based teleoperation system enabling the remote operation of a 6 DOF industrial robot. In order to improve the safety and efficiency of the teleoperation, stability and synchronization (hand-eye coordination) are considered. The selected communication medium between the human operator and remote robot is the Internet. The variable time delays and nondeterministic characteristics of the Internet may lead to instability of the teleoperation system. Considering the disturbing effects of the Internet onto the transmission, an event-based control approach is used in order to improve the stability of the teleoperation system. Besides, a visual feedback system is developed and a force-feedback mouse is designed in order to improve synchronization between the human operator and robot during the command generation according to the feedback obtained from the control system. A client-server software application is developed to interface the human operator with remote environment. It is observed that, using the event-based control approach in the operation makes the teleoperation stable and improves the synchronization ability. Implementation of visual feedback and force-feedback mouse to the teleoperation system improves the human operator&rsquo / s ability to perform remote operation.