Academic literature on the topic 'Event Tracing'

Data integration for the purposes of tracking, tracing and transparency are important challenges in the agri-food supply chain. The Electronic Product Code Information Services (EPCIS) is an event-oriented GS1 standard that aims to enable tracking and tracing of products through the sharing of event-based datasets that encapsulate the Electronic Product Code (EPC). In this paper, the authors propose a framework that utilises events and EPCs in the generation of “linked pedigrees” - linked datasets that enable the sharing of traceability information about products as they move along the supply chain. The authors exploit two ontology based information models, EEM and CBVVocab within a distributed and decentralised framework that consumes real time EPCIS events as linked data to generate the linked pedigrees. The authors exemplify the usage of linked pedigrees within the fresh fruit and vegetables supply chain in the agri-food sector.

Although the typological contrast between Romance and Germanic languages as verb-framed versus satellite-framed (Talmy 1985) forms the background for many empirical studies on L2 acquisition, the inconclusive picture to date calls for more differentiated, fine-grained analyses. The present study goes beyond explanations based on this typological contrast and takes into account the sources from which spatial concepts are mainly derived in order to shape the trajectory traced by the entity in motion when moving through space: the entity in V-languages versus features of the ground in S-languages. It investigates why advanced French learners of English and German have difficulty acquiring the use of spatial concepts typical of the L2s to shape the trajectory, although relevant concepts can be expressed in their L1. The analysis compares motion event descriptions, based on the same sets of video clips, of L1 speakers of the three languages to L1 French-L2 English and L1 French-L2 German speakers, showing that the learners do not fully acquire the use of L2-specific spatial concepts. We argue that encoded concepts derived from the entity in motion vs. the ground lead to a focus on different aspects of motion events, in accordance with their compatibility with these sources, and are difficult to restructure in L2 acquisition.

Firstly, the requirements of production control and the features of discrete manufacturing process were researched , the production process control system architecture was built. Then, the key technologies used in the system realization were studied. Automatic identification technology was used in data acquisition; product tracking and event tracking technologies were used to implement production monitor, abnormal monitor respectivly in application server; Web technology was used in production statistics and analysis in presentation layer. Data acquisition and statement analysis implementation were separately based on the Windows and Web application of NET platform; products tracing and event tracking implementtation were based on the configuration visual software platform: GE Cimplicity. Every layer is distinct and seamless integration in the entire system, the whole architecture has strongly robustness and expandability. Finally, a case proved the validity of this system.

This thesis contributes to the field of performance analysis in High Performance Computing with new concepts for in-memory event tracing. Event tracing records runtime events of an application and stores each with a precise time stamp and further relevant metrics. The high resolution and detailed information allows an in-depth analysis of the dynamic program behavior, interactions in parallel applications, and potential performance issues. For long-running and large-scale parallel applications, event-based tracing faces three challenges, yet unsolved: the number of resulting trace files limits scalability, the huge amounts of collected data overwhelm file systems and analysis capabilities, and the measurement bias, in particular, due to intermediate memory buffer flushes prevents a correct analysis. This thesis proposes concepts for an in-memory event tracing workflow. These concepts include new enhanced encoding techniques to increase memory efficiency and novel strategies for runtime event reduction to dynamically adapt trace size during runtime. An in-memory event tracing workflow based on these concepts meets all three challenges: First, it not only overcomes the scalability limitations due to the number of resulting trace files but eliminates the overhead of file system interaction altogether. Second, the enhanced encoding techniques and event reduction lead to remarkable smaller trace sizes. Finally, an in-memory event tracing workflow completely avoids intermediate memory buffer flushes, which minimizes measurement bias and allows a meaningful performance analysis. The concepts further include the Hierarchical Memory Buffer data structure, which incorporates a multi-dimensional, hierarchical ordering of events by common metrics, such as time stamp, calling context, event class, and function call duration. This hierarchical ordering allows a low-overhead event encoding, event reduction and event filtering, as well as new hierarchy-aided analysis requests. An experimental evaluation based on real-life applications and a detailed case study underline the capabilities of the concepts presented in this thesis. The new enhanced encoding techniques reduce memory allocation during runtime by a factor of 3.3 to 7.2, while at the same do not introduce any additional overhead. Furthermore, the combined concepts including the enhanced encoding techniques, event reduction, and a new filter based on function duration within the Hierarchical Memory Buffer remarkably reduce the resulting trace size up to three orders of magnitude and keep an entire measurement within a single fixed-size memory buffer, while still providing a coarse but meaningful analysis of the application. This thesis includes a discussion of the state-of-the-art and related work, a detailed presentation of the enhanced encoding techniques, the event reduction strategies, the Hierarchical Memory Buffer data structure, and a extensive experimental evaluation of all concepts.

The thesis presents a contribution to the analysis and visualization of computational performance based on event traces with a particular focus on parallel programs and High Performance Computing (HPC). Event traces contain detailed information about specified incidents (events) during run-time of programs and allow minute investigation of dynamic program behavior, various performance metrics, and possible causes of performance flaws. Due to long running and highly parallel programs and very fine detail resolutions, event traces can accumulate huge amounts of data which become a challenge for interactive as well as automatic analysis and visualization tools. The thesis proposes a method of exploiting redundancy in the event traces in order to reduce the memory requirements and the computational complexity of event trace analysis. The sources of redundancy are repeated segments of the original program, either through iterative or recursive algorithms or through SPMD-style parallel programs, which produce equal or similar repeated event sequences. The data reduction technique is based on the novel Complete Call Graph (CCG) data structure which allows domain specific data compression for event traces in a combination of lossless and lossy methods. All deviations due to lossy data compression can be controlled by constant bounds. The compression of the CCG data structure is incorporated in the construction process, such that at no point substantial uncompressed parts have to be stored. Experiments with real-world example traces reveal the potential for very high data compression. The results range from factors of 3 to 15 for small scale compression with minimum deviation of the data to factors > 100 for large scale compression with moderate deviation. Based on the CCG data structure, new algorithms for the most common evaluation and analysis methods for event traces are presented, which require no explicit decompression. By avoiding repeated evaluation of formerly redundant event sequences, the computational effort of the new algorithms can be reduced in the same extent as memory consumption. The thesis includes a comprehensive discussion of the state-of-the-art and related work, a detailed presentation of the design of the CCG data structure, an elaborate description of algorithms for construction, compression, and analysis of CCGs, and an extensive experimental validation of all components
Diese Dissertation stellt einen neuartigen Ansatz für die Analyse und Visualisierung der Berechnungs-Performance vor, der auf dem Ereignis-Tracing basiert und insbesondere auf parallele Programme und das Hochleistungsrechnen (High Performance Computing, HPC) zugeschnitten ist. Ereignis-Traces (Ereignis-Spuren) enthalten detaillierte Informationen über spezifizierte Ereignisse während der Laufzeit eines Programms und erlauben eine sehr genaue Untersuchung des dynamischen Verhaltens, verschiedener Performance-Metriken und potentieller Performance-Probleme. Aufgrund lang laufender und hoch paralleler Anwendungen und dem hohen Detailgrad kann das Ereignis-Tracing sehr große Datenmengen produzieren. Diese stellen ihrerseits eine Herausforderung für interaktive und automatische Analyse- und Visualisierungswerkzeuge dar. Die vorliegende Arbeit präsentiert eine Methode, die Redundanzen in den Ereignis-Traces ausnutzt, um sowohl die Speicheranforderungen als auch die Laufzeitkomplexität der Trace-Analyse zu reduzieren. Die Ursachen für Redundanzen sind wiederholt ausgeführte Programmabschnitte, entweder durch iterative oder rekursive Algorithmen oder durch SPMD-Parallelisierung, die gleiche oder ähnliche Ereignis-Sequenzen erzeugen. Die Datenreduktion basiert auf der neuartigen Datenstruktur der "Vollständigen Aufruf-Graphen" (Complete Call Graph, CCG) und erlaubt eine Kombination von verlustfreier und verlustbehafteter Datenkompression. Dabei können konstante Grenzen für alle Abweichungen durch verlustbehaftete Kompression vorgegeben werden. Die Datenkompression ist in den Aufbau der Datenstruktur integriert, so dass keine umfangreichen unkomprimierten Teile vor der Kompression im Hauptspeicher gehalten werden müssen. Das enorme Kompressionsvermögen des neuen Ansatzes wird anhand einer Reihe von Beispielen aus realen Anwendungsszenarien nachgewiesen. Die dabei erzielten Resultate reichen von Kompressionsfaktoren von 3 bis 5 mit nur minimalen Abweichungen aufgrund der verlustbehafteten Kompression bis zu Faktoren > 100 für hochgradige Kompression. Basierend auf der CCG_Datenstruktur werden außerdem neue Auswertungs- und Analyseverfahren für Ereignis-Traces vorgestellt, die ohne explizite Dekompression auskommen. Damit kann die Laufzeitkomplexität der Analyse im selben Maß gesenkt werden wie der Hauptspeicherbedarf, indem komprimierte Ereignis-Sequenzen nicht mehrmals analysiert werden. Die vorliegende Dissertation enthält eine ausführliche Vorstellung des Stands der Technik und verwandter Arbeiten in diesem Bereich, eine detaillierte Herleitung der neu eingeführten Daten-strukturen, der Konstruktions-, Kompressions- und Analysealgorithmen sowie eine umfangreiche experimentelle Auswertung und Validierung aller Bestandteile

The thesis presents a contribution to the analysis and visualization of computational performance based on event traces with a particular focus on parallel programs and High Performance Computing (HPC). Event traces contain detailed information about specified incidents (events) during run-time of programs and allow minute investigation of dynamic program behavior, various performance metrics, and possible causes of performance flaws. Due to long running and highly parallel programs and very fine detail resolutions, event traces can accumulate huge amounts of data which become a challenge for interactive as well as automatic analysis and visualization tools. The thesis proposes a method of exploiting redundancy in the event traces in order to reduce the memory requirements and the computational complexity of event trace analysis. The sources of redundancy are repeated segments of the original program, either through iterative or recursive algorithms or through SPMD-style parallel programs, which produce equal or similar repeated event sequences. The data reduction technique is based on the novel Complete Call Graph (CCG) data structure which allows domain specific data compression for event traces in a combination of lossless and lossy methods. All deviations due to lossy data compression can be controlled by constant bounds. The compression of the CCG data structure is incorporated in the construction process, such that at no point substantial uncompressed parts have to be stored. Experiments with real-world example traces reveal the potential for very high data compression. The results range from factors of 3 to 15 for small scale compression with minimum deviation of the data to factors > 100 for large scale compression with moderate deviation. Based on the CCG data structure, new algorithms for the most common evaluation and analysis methods for event traces are presented, which require no explicit decompression. By avoiding repeated evaluation of formerly redundant event sequences, the computational effort of the new algorithms can be reduced in the same extent as memory consumption. The thesis includes a comprehensive discussion of the state-of-the-art and related work, a detailed presentation of the design of the CCG data structure, an elaborate description of algorithms for construction, compression, and analysis of CCGs, and an extensive experimental validation of all components.
Diese Dissertation stellt einen neuartigen Ansatz für die Analyse und Visualisierung der Berechnungs-Performance vor, der auf dem Ereignis-Tracing basiert und insbesondere auf parallele Programme und das Hochleistungsrechnen (High Performance Computing, HPC) zugeschnitten ist. Ereignis-Traces (Ereignis-Spuren) enthalten detaillierte Informationen über spezifizierte Ereignisse während der Laufzeit eines Programms und erlauben eine sehr genaue Untersuchung des dynamischen Verhaltens, verschiedener Performance-Metriken und potentieller Performance-Probleme. Aufgrund lang laufender und hoch paralleler Anwendungen und dem hohen Detailgrad kann das Ereignis-Tracing sehr große Datenmengen produzieren. Diese stellen ihrerseits eine Herausforderung für interaktive und automatische Analyse- und Visualisierungswerkzeuge dar. Die vorliegende Arbeit präsentiert eine Methode, die Redundanzen in den Ereignis-Traces ausnutzt, um sowohl die Speicheranforderungen als auch die Laufzeitkomplexität der Trace-Analyse zu reduzieren. Die Ursachen für Redundanzen sind wiederholt ausgeführte Programmabschnitte, entweder durch iterative oder rekursive Algorithmen oder durch SPMD-Parallelisierung, die gleiche oder ähnliche Ereignis-Sequenzen erzeugen. Die Datenreduktion basiert auf der neuartigen Datenstruktur der "Vollständigen Aufruf-Graphen" (Complete Call Graph, CCG) und erlaubt eine Kombination von verlustfreier und verlustbehafteter Datenkompression. Dabei können konstante Grenzen für alle Abweichungen durch verlustbehaftete Kompression vorgegeben werden. Die Datenkompression ist in den Aufbau der Datenstruktur integriert, so dass keine umfangreichen unkomprimierten Teile vor der Kompression im Hauptspeicher gehalten werden müssen. Das enorme Kompressionsvermögen des neuen Ansatzes wird anhand einer Reihe von Beispielen aus realen Anwendungsszenarien nachgewiesen. Die dabei erzielten Resultate reichen von Kompressionsfaktoren von 3 bis 5 mit nur minimalen Abweichungen aufgrund der verlustbehafteten Kompression bis zu Faktoren > 100 für hochgradige Kompression. Basierend auf der CCG_Datenstruktur werden außerdem neue Auswertungs- und Analyseverfahren für Ereignis-Traces vorgestellt, die ohne explizite Dekompression auskommen. Damit kann die Laufzeitkomplexität der Analyse im selben Maß gesenkt werden wie der Hauptspeicherbedarf, indem komprimierte Ereignis-Sequenzen nicht mehrmals analysiert werden. Die vorliegende Dissertation enthält eine ausführliche Vorstellung des Stands der Technik und verwandter Arbeiten in diesem Bereich, eine detaillierte Herleitung der neu eingeführten Daten-strukturen, der Konstruktions-, Kompressions- und Analysealgorithmen sowie eine umfangreiche experimentelle Auswertung und Validierung aller Bestandteile.

[EN] Over the last years, multiagent systems have been proven to be a powerful and versatile paradigm, with a big potential when it comes to solving complex problems in dynamic and distributed environments, due to their flexible and adaptive behavior. This potential does not only come from the individual features of agents (such as autonomy, reactivity or reasoning power), but also to their capability to communicate, cooperate and coordinate in order to fulfill their goals. In fact, it is this social behavior what makes multiagent systems so powerful, much more than the individual capabilities of agents. The social behavior of multiagent systems is usually developed by means of high level abstractions, protocols and languages, which normally rely on (or at least, benefit from) agents being able to communicate and interact indirectly. However, in the development process, such high level concepts habitually become weakly supported, with mechanisms such as traditional messaging, massive broadcasting, blackboard systems or ad hoc solutions. This lack of an appropriate way to support indirect communication in actual multiagent systems compromises their potential. This PhD thesis proposes the use of event tracing as a flexible, effective and efficient support for indirect interaction and communication in multiagent systems. The main contribution of this thesis is TRAMMAS, a generic, abstract model for event tracing support in multiagent systems. The model allows all entities in the system to share their information as trace events, so that any other entity which require this information is able to receive it. Along with the model, the thesis also presents an abstract architecture, which redefines the model in terms of a set of tracing facilities that can be then easily incorporated to an actual multiagent platform. This architecture follows a service-oriented approach, so that the tracing facilities are provided in the same way than other traditional services offered by the platform. In this way, event tracing can be considered as an additional information provider for entities in the multiagent system, and as such, it can be integrated from the earliest stages of the development process.
[ES] A lo largo de los últimos años, los sistemas multiagente han demostrado ser un paradigma potente y versátil, con un gran potencial a la hora de resolver problemas complejos en entornos dinámicos y distribuidos, gracias a su comportamiento flexible y adaptativo. Este potencial no es debido únicamente a las características individuales de los agentes (como son su autonomía, y su capacidades de reacción y de razonamiento), sino que también se debe a su capacidad de comunicación y cooperación a la hora de conseguir sus objetivos. De hecho, por encima de la capacidad individual de los agentes, es este comportamiento social el que dota de potencial a los sistemas multiagente. El comportamiento social de los sistemas multiagente suele desarrollarse empleando abstracciones, protocolos y lenguajes de alto nivel, los cuales, a su vez, se basan normalmente en la capacidad para comunicarse e interactuar de manera indirecta de los agentes (o como mínimo, se benefician en gran medida de dicha capacidad). Sin embargo, en el proceso de desarrollo software, estos conceptos de alto nivel son soportados habitualmente de manera débil, mediante mecanismos como la mensajería tradicional, la difusión masiva, o el uso de pizarras, o mediante soluciones totalmente ad hoc. Esta carencia de un soporte genérico y apropiado para la comunicación indirecta en los sistemas multiagente reales compromete su potencial. Esta tesis doctoral propone el uso del trazado de eventos como un soporte flexible, efectivo y eficiente para la comunicación indirecta en sistemas multiagente. La principal contribución de esta tesis es TRAMMAS, un modelo genérico y abstracto para dar soporte al trazado de eventos en sistemas multiagente. El modelo permite a cualquier entidad del sistema compartir su información en forma de eventos de traza, de tal manera que cualquier otra entidad que requiera esta información sea capaz de recibirla. Junto con el modelo, la tesis también presenta una arquitectura {abs}{trac}{ta}, que redefine el modelo como un conjunto de funcionalidades que pueden ser fácilmente incorporadas a una plataforma multiagente real. Esta arquitectura sigue un enfoque orientado a servicios, de modo que las funcionalidades de traza son ofrecidas por parte de la plataforma de manera similar a los servicios tradicionales. De esta forma, el trazado de eventos puede ser considerado como una fuente adicional de información para las entidades del sistema multiagente y, como tal, puede integrarse en el proceso de desarrollo software desde sus primeras etapas.
[CAT] Al llarg dels últims anys, els sistemes multiagent han demostrat ser un paradigma potent i versàtil, amb un gran potencial a l'hora de resoldre problemes complexes a entorns dinàmics i distribuïts, gràcies al seu comportament flexible i adaptatiu. Aquest potencial no és només degut a les característiques individuals dels agents (com són la seua autonomia, i les capacitats de reacció i raonament), sinó també a la seua capacitat de comunicació i cooperació a l'hora d'aconseguir els seus objectius. De fet, per damunt de la capacitat individual dels agents, es aquest comportament social el que dóna potencial als sistemes multiagent. El comportament social dels sistemes multiagent solen desenvolupar-se utilitzant abstraccions, protocols i llenguatges d'alt nivell, els quals, al seu torn, es basen normalment a la capacitat dels agents de comunicar-se i interactuar de manera indirecta (o com a mínim, es beneficien en gran mesura d'aquesta capacitat). Tanmateix, al procés de desenvolupament software, aquests conceptes d'alt nivell son suportats habitualment d'una manera dèbil, mitjançant mecanismes com la missatgeria tradicional, la difusió massiva o l'ús de pissarres, o mitjançant solucions totalment ad hoc. Aquesta carència d'un suport genèric i apropiat per a la comunicació indirecta als sistemes multiagent reals compromet el seu potencial. Aquesta tesi doctoral proposa l'ús del traçat d'esdeveniments com un suport flexible, efectiu i eficient per a la comunicació indirecta a sistemes multiagent. La principal contribució d'aquesta tesi és TRAMMAS, un model genèric i abstracte per a donar suport al traçat d'esdeveniments a sistemes multiagent. El model permet a qualsevol entitat del sistema compartir la seua informació amb la forma d'esdeveniments de traça, de tal forma que qualsevol altra entitat que necessite aquesta informació siga capaç de rebre-la. Junt amb el model, la tesi també presenta una arquitectura abstracta, que redefineix el model com un conjunt de funcionalitats que poden ser fàcilment incorporades a una plataforma multiagent real. Aquesta arquitectura segueix un enfoc orientat a serveis, de manera que les funcionalitats de traça són oferides per part de la plataforma de manera similar als serveis tradicionals. D'aquesta manera, el traçat d'esdeveniments pot ser considerat com una font addicional d'informació per a les entitats del sistema multiagent, i com a tal, pot integrar-se al procés de desenvolupament software des de les seues primeres etapes.
Búrdalo Rapa, LA. (2016). TRAMMAS: Enhancing Communication in Multiagent Systems [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/61765
TESIS

Supply chains in many industries are experiencing an ever-growing complexity. They involve many actors and, similar to intra-organizational processes, visibility is an important enabler for managing supply chains in an inter-organizational setting. It is the backbone of advanced sup-ply chain (event) management solutions, which serve to detect critical incidents in time and to determine alternative actions. Due to the numerous parties involved, distributed supply chains call for a modular system architecture that aims at re-using visibility data from standardized sources. Following the wide variety of supply chain configurations in many industries there are also many options to design such services. This paper sheds light on these aspects by conduct-ing a case study on EPCIS, a global service specification for capturing and sharing visibility data. Based on three implementations, it shows the main design options for a supply chain vis-ibility service, generic operator models as well as major potentials.:1. Introduction and motivation 2. Research questions and methodology 3. Literature analysis 4. EPCIS case study 4.1. Deutsche Post DHL 4.2. ThyssenKrupp 4.3. GS1 Germany 5. Discussion and findinds 5.1.Design options 5.2. Operator models 5.3. Potentials 6. Conclusions

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O reconhecimento automático de eventos de interesse em vídeos envolvendo conjuntos de ações ou de interações entre objetos. Pode agregar valor a sistemas de vigilância,aplicações de cidades inteligentes, monitoramento de pessoas com incapacidades físicas ou mentais, dentre outros. Entretanto, conceber um arcabouço que possa ser adaptado a diversas situações sem a necessidade de um especialista nas tecnologias envolvidas, continua sendo um desafio para a área. Neste contexto, a pesquisa realizada tem como base a criação de um arcabouço genérico para detecção de eventos em vídeo com base em regras. Para criação das regras, os usuários formam expressões lógicas utilizando Lógica de Primeira Ordem e relacionamos termos com a álgebra de intervalos de Allen, adicionando assim um contexto temporal às regras. Por ser um arcabouço, ele é extensível, podendo receber módulos adicionais para realização de novas detecções e inferências Foi realizada uma avaliação experimental utilizando vídeos de teste disponíveis no site Youtube envolvendo um cenário de trânsito, com eventos de ultrapassagem do sinal vermelho e vídeos obtidos de uma câmera ao vivo do site Camerite, contendo eventos de carros estacionando. O foco do trabalho não foi criar detectores de objetos (e.g. carros ou pessoas) melhores do que aqueles existentes no estado da arte, mas propor e desenvolver uma estrutura genérica e reutilizável que integra diferentes técnicas de visão computacional. A acurácia na detecção dos eventos ficou no intervalo de 83,82% a 90,08% com 95% de confiança. Obteve acurácia máxima (100%) na detecção dos eventos, quando substituído os detectores de objetos por rótulos atribuídos manualmente, o que indicou a eficácia do motor de inferência desenvolvido para o arcabouço.
Automatic recognition of relevant events in videos involving sets of actions or interactions between objects can improve surveillance systems, smart cities applications, monitoring of people with physical or mental disabilities, among others. However, designing a framework that can be adapted to several situations without an expert in the involved technologies remains a challenge. In this context, this work is based on the creation of a rule-based generic framework for event detection in video. To create the rules, users form logical expressions using firstorder logic (FOL) and relate the terms with the Allen’s interval algebra, adding a temporal context to the rules. Once it is a framework, it is extensible, and may receive additional modules for performing new detections and inferences. Experimental evaluation was performed using test videos available on Youtube, involving a scenario of traffic with red light crossing events and videos from Camerite website containing parking car events. The focus of the work was not to create object detectors (e.g. cars or people) better than those existing in the state-of-the-art, but, propose and develop a generic and reusable framework that integrates differents computer vision techniques. The accuracy in the detection of the events was within the range of 83.82% and 90.08% with 95% confidence. Obtained maximum accuracy (100 %) in the detection of the events, when replacing the objects detectors by labels manually assigned, what indicated the effectiveness of the inference engine developed for this framework.

L'objectif principal de cette thèse est le développement d'algorithmes événementiels pour la détection et le suivi d'objets. Ces algorithmes sont spécifiquement conçus pour travailler avec une sortie produite par des caméras neuromorphiques. Ce type de caméras sont un nouveau type de capteurs bio inspirés, dont le principe de fonctionnement s'inspire de la rétine: chaque pixel est indépendant et génère des événements de manière asynchrone lorsqu'un changement de luminosité suffisamment important est détecté à la position correspondante du plan focal. Cette nouvelle façon d'encoder l'information visuelle requiert de nouvelles méthodes pour la traiter. D'abord, un suiveur (tracker) plan est décrit. Cet algorithme associe à un objet une série de formes simples reliées par des ressorts. Le système mécanique virtuel résultant est mis à jour pour chaque événement. Le chapitre suivant présente un algorithme de détection de lignes et de segments, pouvant constituer une caractéristique (feature) événementielle de bas niveau. Ensuite, deux méthodes événementielles pour l'estimation de la pose 3D sont présentées. Le premier de ces algorithmes 3D est basé sur l'hypothèse que l'estimation de la pose est toujours proche de la position réelle, et requiert donc une initialisation manuelle. Le deuxième de ces algorithmes 3D est conçu pour surmonter cette limitation. Toutes les méthodes présentées mettent à jour l'estimation de la position (2D ou 3D) pour chaque événement. Cette thèse montre que la vision événementielle permet de reformuler une vaste série de problèmes en vision par ordinateur, souvent donnant lieu à des algorithmes plus simples mais toujours précis
The main goal of this thesis is the development of event-based algorithms for visual detection and tracking. This algorithms are specifically designed to work on the output of neuromorphic event-based cameras. This type of cameras are a new type of bioinspired sensors, whose principle of operation is based on the functioning of the retina: every pixel is independent and generates events asynchronously when a sufficient amount of change is detected in the luminance at the corresponding position on the focal plane. This new way of encoding visual information calls for new processing methods. First, a part-based shape tracking is presented, which represents an object as a set of simple shapes linked by springs. The resulting virtual mechanical system is simulated with every incoming event. Next, a line and segment detection algorithm is introduced, which can be employed as an event-based low level feature. Two event-based methods for 3D pose estimation are then presented. The first of these 3D algorithms is based on the assumption that the current estimation is close to the true pose of the object, and it consequently requires a manual initialization step. The second of the 3D methods is designed to overcome this limitation. All the presented methods update the estimated position (2D or 3D) of the tracked object with every incoming event. This results in a series of trackers capable of estimating the position of the tracked object with microsecond resolution. This thesis shows that event-based vision allows to reformulate a broad set of computer vision problems, often resulting in simpler but accurate algorithms

This study examines the interdependence of gender, sexuality and space in the early modern period, which saw the inception of architecture as a discipline and gave rise to the first custodial institutions for women, including convents for reformed prostitutes. Meanwhile, conduct manuals established prescriptive mandates for female use of space, concentrating especially on the liminal spaces of the home. This work traces literary prostitution in the Spanish Mediterranean through the sixteenth and seventeenth centuries, from the rise of courtesan culture in several key areas through the shift from tolerance of prostitution toward repression. Kuffner’s analysis pairs canonical and noncanonical works of fiction with didactic writing, architectural treatises, and legal mandates, tying the literary practice of prostitution to increasing control over female sexuality during the Counter Reformation. By tracing erotic negotiations in the female picaresque novel from its origins through later manifestations, she demonstrates that even as societal attitudes towards prostitution shifted dramatically, a countervailing tendency to view prostitution as an essential part of the social fabric undergirds many representations of literary prostitutes. Kuffner’s analysis reveals that the semblance of domestic enclosure figures as a primary erotic strategy in female picaresque fiction, allowing readers to assess the variety of strategies used by authors to comment on the relationship between unruly female sexuality and social order.

"This book is the fruit of "excavations" carried out in memory of Prof. Corrado Corghi between 2004 and 2005. At the time Corghi was a member of the Presiding Council of the Istituto degli Innocenti of Florence. When the meetings of the Council were held, Corghi came down from Reggio Emilia to Florence, and in the evenings he was frequently my guest at dinner. These meetings enabled me to enjoy extensive tracking shots of the past, thanks to the extraordinary lucidity of a man born in 1920 who had devoted most of his life to politics. On the basis of our lengthy discussions I was able to revoke people and events from Fascism to the Resistance, from the times of Democrazia Cristiana to the funerals of the "victims of Reggio Emilia" (1960), through to the Vatican Council and the season of '68. These talks of ours gave rise to singular documents of the life and social history of the Italians. With this volume, the historic-social Archive on contemporary religion of San Gimignano presents itself with its distinctive features to the broad public and to researchers." (A. Nesti)

This chapter focuses on the distinctions between historical research and social scientific research, and how these are being challenged by scholars in pursuit of a genuinely ‘historical social science’. It begins with a discussion of historical approaches in Politics and International Relations, including historical events research, historical process research, and cross-sectional comparative research. It then examines three approaches for addressing temporality as the sequential active unfolding of social action and events: historical institutionalism, process tracing, and event structure analysis. It also explains how to locate essential historical information and evaluate various types of sources, and what special considerations need to be made in using documents, archival sources, and historical writing as data in historical research.

This article provides an overview of process tracing, concentrating on the dimensions of this method that are relevant to Bayesian logic. It also briefly outlines the logic of Bayesian inference, emphasizing parallels with the logic of process tracing. The article shows these points with examples from the historical explanation of political events, including the 1898 Fashoda crisis, the end of the First World War, and the end of the Cold War. It concludes that Bayesianism helps in understanding the strengths of case-study methods, including their potential to develop and test explanations even with limited evidence drawn from one or a few cases, and their limits, including the provisional nature of historical explanations and the challenges of generalizing from small numbers of cases. The ‘Degrees of Freedom’ problem is inapplicable to process tracing, even though the more fundamental problem of underdetermination remains.

In this chapter, it is argued that a pivotal episode in Esther, Mordecai’s refusal to bow to Haman, is to be read literarily, as a topos, rather than literally, as a historical event. Drawing on materials from the ancient Near East, the Hebrew Bible, the New Testament, Late Antiquity, the Qur’an, and the Islamic era, it is shown that Mordecai’s refusal to bow to Haman is but one link in a very long chain of comparable episodes in Near and Middle Eastern literature. Furthermore, in tracing this topos through history, we are able to cast new light on the Qur’anic passages in which Satan (“Iblis”) refuses to bow to the newly created Adam.

This chapter examines the rules that apply in the special context where a defendant has mixed the claimant's assets with those of other innocent parties. It argues that the courts have begun to adopt a similar disregard for the defendant's intentions in such cases as they do when determining the consequences of a mixed substitution involving his own assets. It argues that the principle of preserving defendant autonomy explains how, even as between innocent co-contributors, the principle is limited to contexts where the assets of the various contributors have been mixed so that it is impossible to tell whether the decision of the defendant involves a power affecting one claimant rather than another.

The Indiana Department of Transportation (INDOT) operates a fleet of nearly 1100 snowplows and spends up to $60M annually on snow removal and de-icing as part of their winter operation maintenance activities. Systematically allocating resources and optimizing material application rates can potentially save revenue that can be reallocated for other roadway maintenance operations. Modern snowplows are beginning to be equipped with a variety of Mobile Road Weather Information Sensors (MARWIS) which can provide a host of analytical data characterizing on-the-ground conditions during periods of wintry precipitation. Traffic speeds fused with road conditions and precipitation data from weather stations provide a uniquely detailed look at the progression of a winter event and the performance of the fleet. This research uses a combination of traffic speeds, MARWIS and North American Land Data Assimilation System (NLDAS) data to develop real-time dashboards characterizing the impact of precipitation and pavement surface temperature on mobility. Twenty heavy snow events were identified for the state of Indiana from November 2018 through April 2019. Two particular instances, that impacted 182 miles and 231 miles of interstate at their peaks occurred in January and March, respectively, and were used as a case study for this paper. The dashboards proposed in this paper may prove to be particularly useful for agencies in tracking fleet activity through a winter storm, helping in resource allocation and scheduling and forecasting resource needs.

In this working paper, our focus is on the constitutional debates and case law regarding the right to privacy, adopting a method that is largely theoretical. In an accompanying separate working paper, A South African Public Law Perspective on Digitalisation in the Health Sector, we employ the analysis developed here and focus on the specific case of digital technologies in the health sector. The topic and task of these papers lie at the confluence of many areas of contemporary society. To demonstrate and apply the argument of this paper, it would be possible and valuable to extend its analysis into any of numerous spheres of social life, from energy to education to policing to child care. In our accompanying separate paper, we focus on only one policy domain – the health sector. Our aim is to demonstrate our argument about the significance of a public law perspective on the constitutional right to privacy in the age of digitalisation, and attend to several issues raised by digitalisation’s impact in the health sector. For the most part, we focus on technologies that have health benefits and privacy costs, but we also recognise that certain technologies have health costs and privacy benefits. We also briefly outline the recent establishment (and subsequent events) in South Africa of a contact tracing database responding to the COVID-19 pandemic – the COVID-19 Tracing Database – a development at the interface of the law enforcement and health sectors. Our main point in this accompanying paper is to demonstrate the value that a constitutional right to privacy can bring to the regulation of digital technologies in a variety of legal frameworks and technological settings – from public to private, and from the law of the constitution to the ‘law’ of computer coding.

This research sought to understand the impact of probation inspection on probation policy, practice and practitioners. This important but neglected area of study has significant ramifications because the Her Majesty’s Inspectorate of Probation has considerable power to influence policy through its inspection regime and research activities. The study utilised a mixed methodological approach comprising observations of inspections and interviews with people who work in probation, the Inspectorate and external stakeholders. In total, 77 people were interviewed or took part in focus groups. Probation practitioners, managers and leaders were interviewed in the weeks after an inspection to find out how they experienced the process of inspection. Staff at HMI Probation were interviewed to understand what inspection is for and how it works. External stakeholders representing people from the voluntary sector, politics and other non-departmental bodies were interviewed to find out how they used the work of inspection in their own roles. Finally, leaders within the National Probation Service and Her Majesty’s Prisons and Probation Service were interviewed to see how inspection impacts on policy more broadly. The data were analysed thematically with five key themes being identified. Overall, participants were positive about the way inspection is carried out in the field of probation. The main findings are: 1. Inspection places a burden on practitioners and organisations. Practitioners talked about the anxiety that a looming inspection created and how management teams created additional pressures which were hard to cope with on top of already high workloads. Staff responsible for managing the inspection and with leadership positions talked about the amount of time the process of inspection took up. Importantly, inspection was seen to take people away from their day jobs and meant other priorities were side-lined, even if temporarily. However, the case interviews that practitioners take part in were seen as incredibly valuable exercises which gave staff the opportunity to reflect on their practice and receive positive feedback and validation for their work. 2. Providers said that the findings and conclusions from inspections were often accurate and, to some extent, unsurprising. However, they sometimes find it difficult to implement recommendations due to reports failing to take context into account. Negative reports have a serious impact on staff morale, especially for CRCs and there was concern about the impact of negative findings on a provider’s reputation. 3. External stakeholders value the work of the Inspectorate. The Inspectorate is seen to generate highly valid and meaningful data which stakeholders can use in their own roles. This can include pushing for policy reform or holding government to account from different perspectives. In particular, thematic inspections were seen to be useful here. 4. The regulatory landscape in probation is complex with an array of actors working to hold providers to account. When compared to other forms of regulation such as audit or contract management the Inspectorate was perceived positively due to its methodological approach as well as the way it reflects the values of probation itself. 5. Overall, the inspectorate appears to garner considerable legitimacy from those it inspects. This should, in theory, support the way it can impact on policy and practice. There are some areas for development here though such as more engagement with service users. While recognising that the Inspectorate has made a concerted effort to do this in the last two years participants all felt that more needs to be done to increase that trust between the inspectorate and service users. Overall, the Inspectorate was seen to be independent and 3 impartial although this belief was less prevalent amongst people in CRCs who argued that the Inspectorate has been biased towards supporting its own arguments around reversing the now failed policy of Transforming Rehabilitation. There was some debate amongst participants about how the Inspectorate could, or should, enforce compliance with its recommendations although most people were happy with the primarily relational way of encouraging compliance with sanctions for non-compliance being considered relatively unnecessary. To conclude, the work of the Inspectorate has a significant impact on probation policy, practice and practitioners. The majority of participants were positive about the process of inspection and the Inspectorate more broadly, notwithstanding some of the issues raised in the findings. There are some developments which the Inspectorate could consider to reduce the burden inspection places on providers and practitioners and enhance its impact such as amending the frequency of inspection, improving the feedback given to practitioners and providing more localised feedback, and working to reduce or limit perceptions of bias amongst people in CRCs. The Inspectorate could also do more to capture the impact it has on providers and practitioners – both positive and negative - through existing procedures that are in place such as post-case interview surveys and tracking the implementation of recommendations.

1.1 Macroeconomic summary Economic recovery has consistently outperformed the technical staff’s expectations following a steep decline in activity in the second quarter of 2020. At the same time, total and core inflation rates have fallen and remain at low levels, suggesting that a significant element of the reactivation of Colombia’s economy has been related to recovery in potential GDP. This would support the technical staff’s diagnosis of weak aggregate demand and ample excess capacity. The most recently available data on 2020 growth suggests a contraction in economic activity of 6.8%, lower than estimates from January’s Monetary Policy Report (-7.2%). High-frequency indicators suggest that economic performance was significantly more dynamic than expected in January, despite mobility restrictions and quarantine measures. This has also come amid declines in total and core inflation, the latter of which was below January projections if controlling for certain relative price changes. This suggests that the unexpected strength of recent growth contains elements of demand, and that excess capacity, while significant, could be lower than previously estimated. Nevertheless, uncertainty over the measurement of excess capacity continues to be unusually high and marked both by variations in the way different economic sectors and spending components have been affected by the pandemic, and by uneven price behavior. The size of excess capacity, and in particular the evolution of the pandemic in forthcoming quarters, constitute substantial risks to the macroeconomic forecast presented in this report. Despite the unexpected strength of the recovery, the technical staff continues to project ample excess capacity that is expected to remain on the forecast horizon, alongside core inflation that will likely remain below the target. Domestic demand remains below 2019 levels amid unusually significant uncertainty over the size of excess capacity in the economy. High national unemployment (14.6% for February 2021) reflects a loose labor market, while observed total and core inflation continue to be below 2%. Inflationary pressures from the exchange rate are expected to continue to be low, with relatively little pass-through on inflation. This would be compatible with a negative output gap. Excess productive capacity and the expectation of core inflation below the 3% target on the forecast horizon provide a basis for an expansive monetary policy posture. The technical staff’s assessment of certain shocks and their expected effects on the economy, as well as the presence of several sources of uncertainty and related assumptions about their potential macroeconomic impacts, remain a feature of this report. The coronavirus pandemic, in particular, continues to affect the public health environment, and the reopening of Colombia’s economy remains incomplete. The technical staff’s assessment is that the COVID-19 shock has affected both aggregate demand and supply, but that the impact on demand has been deeper and more persistent. Given this persistence, the central forecast accounts for a gradual tightening of the output gap in the absence of new waves of contagion, and as vaccination campaigns progress. The central forecast continues to include an expected increase of total and core inflation rates in the second quarter of 2021, alongside the lapse of the temporary price relief measures put in place in 2020. Additional COVID-19 outbreaks (of uncertain duration and intensity) represent a significant risk factor that could affect these projections. Additionally, the forecast continues to include an upward trend in sovereign risk premiums, reflected by higher levels of public debt that in the wake of the pandemic are likely to persist on the forecast horizon, even in the context of a fiscal adjustment. At the same time, the projection accounts for the shortterm effects on private domestic demand from a fiscal adjustment along the lines of the one currently being proposed by the national government. This would be compatible with a gradual recovery of private domestic demand in 2022. The size and characteristics of the fiscal adjustment that is ultimately implemented, as well as the corresponding market response, represent another source of forecast uncertainty. Newly available information offers evidence of the potential for significant changes to the macroeconomic scenario, though without altering the general diagnosis described above. The most recent data on inflation, growth, fiscal policy, and international financial conditions suggests a more dynamic economy than previously expected. However, a third wave of the pandemic has delayed the re-opening of Colombia’s economy and brought with it a deceleration in economic activity. Detailed descriptions of these considerations and subsequent changes to the macroeconomic forecast are presented below. The expected annual decline in GDP (-0.3%) in the first quarter of 2021 appears to have been less pronounced than projected in January (-4.8%). Partial closures in January to address a second wave of COVID-19 appear to have had a less significant negative impact on the economy than previously estimated. This is reflected in figures related to mobility, energy demand, industry and retail sales, foreign trade, commercial transactions from selected banks, and the national statistics agency’s (DANE) economic tracking indicator (ISE). Output is now expected to have declined annually in the first quarter by 0.3%. Private consumption likely continued to recover, registering levels somewhat above those from the previous year, while public consumption likely increased significantly. While a recovery in investment in both housing and in other buildings and structures is expected, overall investment levels in this case likely continued to be low, and gross fixed capital formation is expected to continue to show significant annual declines. Imports likely recovered to again outpace exports, though both are expected to register significant annual declines. Economic activity that outpaced projections, an increase in oil prices and other export products, and an expected increase in public spending this year account for the upward revision to the 2021 growth forecast (from 4.6% with a range between 2% and 6% in January, to 6.0% with a range between 3% and 7% in April). As a result, the output gap is expected to be smaller and to tighten more rapidly than projected in the previous report, though it is still expected to remain in negative territory on the forecast horizon. Wide forecast intervals reflect the fact that the future evolution of the COVID-19 pandemic remains a significant source of uncertainty on these projections. The delay in the recovery of economic activity as a result of the resurgence of COVID-19 in the first quarter appears to have been less significant than projected in the January report. The central forecast scenario expects this improved performance to continue in 2021 alongside increased consumer and business confidence. Low real interest rates and an active credit supply would also support this dynamic, and the overall conditions would be expected to spur a recovery in consumption and investment. Increased growth in public spending and public works based on the national government’s spending plan (Plan Financiero del Gobierno) are other factors to consider. Additionally, an expected recovery in global demand and higher projected prices for oil and coffee would further contribute to improved external revenues and would favor investment, in particular in the oil sector. Given the above, the technical staff’s 2021 growth forecast has been revised upward from 4.6% in January (range from 2% to 6%) to 6.0% in April (range from 3% to 7%). These projections account for the potential for the third wave of COVID-19 to have a larger and more persistent effect on the economy than the previous wave, while also supposing that there will not be any additional significant waves of the pandemic and that mobility restrictions will be relaxed as a result. Economic growth in 2022 is expected to be 3%, with a range between 1% and 5%. This figure would be lower than projected in the January report (3.6% with a range between 2% and 6%), due to a higher base of comparison given the upward revision to expected GDP in 2021. This forecast also takes into account the likely effects on private demand of a fiscal adjustment of the size currently being proposed by the national government, and which would come into effect in 2022. Excess in productive capacity is now expected to be lower than estimated in January but continues to be significant and affected by high levels of uncertainty, as reflected in the wide forecast intervals. The possibility of new waves of the virus (of uncertain intensity and duration) represents a significant downward risk to projected GDP growth, and is signaled by the lower limits of the ranges provided in this report. Inflation (1.51%) and inflation excluding food and regulated items (0.94%) declined in March compared to December, continuing below the 3% target. The decline in inflation in this period was below projections, explained in large part by unanticipated increases in the costs of certain foods (3.92%) and regulated items (1.52%). An increase in international food and shipping prices, increased foreign demand for beef, and specific upward pressures on perishable food supplies appear to explain a lower-than-expected deceleration in the consumer price index (CPI) for foods. An unexpected increase in regulated items prices came amid unanticipated increases in international fuel prices, on some utilities rates, and for regulated education prices. The decline in annual inflation excluding food and regulated items between December and March was in line with projections from January, though this included downward pressure from a significant reduction in telecommunications rates due to the imminent entry of a new operator. When controlling for the effects of this relative price change, inflation excluding food and regulated items exceeds levels forecast in the previous report. Within this indicator of core inflation, the CPI for goods (1.05%) accelerated due to a reversion of the effects of the VAT-free day in November, which was largely accounted for in February, and possibly by the transmission of a recent depreciation of the peso on domestic prices for certain items (electric and household appliances). For their part, services prices decelerated and showed the lowest rate of annual growth (0.89%) among the large consumer baskets in the CPI. Within the services basket, the annual change in rental prices continued to decline, while those services that continue to experience the most significant restrictions on returning to normal operations (tourism, cinemas, nightlife, etc.) continued to register significant price declines. As previously mentioned, telephone rates also fell significantly due to increased competition in the market. Total inflation is expected to continue to be affected by ample excesses in productive capacity for the remainder of 2021 and 2022, though less so than projected in January. As a result, convergence to the inflation target is now expected to be somewhat faster than estimated in the previous report, assuming the absence of significant additional outbreaks of COVID-19. The technical staff’s year-end inflation projections for 2021 and 2022 have increased, suggesting figures around 3% due largely to variation in food and regulated items prices. The projection for inflation excluding food and regulated items also increased, but remains below 3%. Price relief measures on indirect taxes implemented in 2020 are expected to lapse in the second quarter of 2021, generating a one-off effect on prices and temporarily affecting inflation excluding food and regulated items. However, indexation to low levels of past inflation, weak demand, and ample excess productive capacity are expected to keep core inflation below the target, near 2.3% at the end of 2021 (previously 2.1%). The reversion in 2021 of the effects of some price relief measures on utility rates from 2020 should lead to an increase in the CPI for regulated items in the second half of this year. Annual price changes are now expected to be higher than estimated in the January report due to an increased expected path for fuel prices and unanticipated increases in regulated education prices. The projection for the CPI for foods has increased compared to the previous report, taking into account certain factors that were not anticipated in January (a less favorable agricultural cycle, increased pressure from international prices, and transport costs). Given the above, year-end annual inflation for 2021 and 2022 is now expected to be 3% and 2.8%, respectively, which would be above projections from January (2.3% and 2,7%). For its part, expected inflation based on analyst surveys suggests year-end inflation in 2021 and 2022 of 2.8% and 3.1%, respectively. There remains significant uncertainty surrounding the inflation forecasts included in this report due to several factors: 1) the evolution of the pandemic; 2) the difficulty in evaluating the size and persistence of excess productive capacity; 3) the timing and manner in which price relief measures will lapse; and 4) the future behavior of food prices. Projected 2021 growth in foreign demand (4.4% to 5.2%) and the supposed average oil price (USD 53 to USD 61 per Brent benchmark barrel) were both revised upward. An increase in long-term international interest rates has been reflected in a depreciation of the peso and could result in relatively tighter external financial conditions for emerging market economies, including Colombia. Average growth among Colombia’s trade partners was greater than expected in the fourth quarter of 2020. This, together with a sizable fiscal stimulus approved in the United States and the onset of a massive global vaccination campaign, largely explains the projected increase in foreign demand growth in 2021. The resilience of the goods market in the face of global crisis and an expected normalization in international trade are additional factors. These considerations and the expected continuation of a gradual reduction of mobility restrictions abroad suggest that Colombia’s trade partners could grow on average by 5.2% in 2021 and around 3.4% in 2022. The improved prospects for global economic growth have led to an increase in current and expected oil prices. Production interruptions due to a heavy winter, reduced inventories, and increased supply restrictions instituted by producing countries have also contributed to the increase. Meanwhile, market forecasts and recent Federal Reserve pronouncements suggest that the benchmark interest rate in the U.S. will remain stable for the next two years. Nevertheless, a significant increase in public spending in the country has fostered expectations for greater growth and inflation, as well as increased uncertainty over the moment in which a normalization of monetary policy might begin. This has been reflected in an increase in long-term interest rates. In this context, emerging market economies in the region, including Colombia, have registered increases in sovereign risk premiums and long-term domestic interest rates, and a depreciation of local currencies against the dollar. Recent outbreaks of COVID-19 in several of these economies; limits on vaccine supply and the slow pace of immunization campaigns in some countries; a significant increase in public debt; and tensions between the United States and China, among other factors, all add to a high level of uncertainty surrounding interest rate spreads, external financing conditions, and the future performance of risk premiums. The impact that this environment could have on the exchange rate and on domestic financing conditions represent risks to the macroeconomic and monetary policy forecasts. Domestic financial conditions continue to favor recovery in economic activity. The transmission of reductions to the policy interest rate on credit rates has been significant. The banking portfolio continues to recover amid circumstances that have affected both the supply and demand for loans, and in which some credit risks have materialized. Preferential and ordinary commercial interest rates have fallen to a similar degree as the benchmark interest rate. As is generally the case, this transmission has come at a slower pace for consumer credit rates, and has been further delayed in the case of mortgage rates. Commercial credit levels stabilized above pre-pandemic levels in March, following an increase resulting from significant liquidity requirements for businesses in the second quarter of 2020. The consumer credit portfolio continued to recover and has now surpassed February 2020 levels, though overall growth in the portfolio remains low. At the same time, portfolio projections and default indicators have increased, and credit establishment earnings have come down. Despite this, credit disbursements continue to recover and solvency indicators remain well above regulatory minimums. 1.2 Monetary policy decision In its meetings in March and April the BDBR left the benchmark interest rate unchanged at 1.75%.