VariantFlow: Interactive Storyline Visualization Using Force Directed Layout

The study of literature is changing dramatically by incorporating new opportu- nities that digital technology presents. Data visualization overturns the dynamic for literary analysis by revealing and displaying connections and patterns be- tween elements in text. Literary scholars compare and analyze textual variations in different versions of a lost original text and work to reconstruct the original text in the form of a critical edition. A critical edition notes textual variations in extensive footnotes, collectively called a critical apparatus. Information in the apparatus is of great interest to scholars who seek to explore complex relation- ships between text versions. Motivated by application to classical Latin texts, we adapted the storyline technique to visualize a critical apparatus. The visualiza- tion facilitates guided discovery of similarities and dissimilarities between prior text versions, which are difficult to detect and reason about with traditional deep reading and spreadsheet-based methods. Storyline visualizations help users understand and analyze the interactions between entities in a story and explore how entity relationships evolve over time. Typical design considerations in existing storyline techniques include minimiz- ing line crossing and line wiggling, which are computationally intense problems. Generating storyline layouts in real time is a substantial challenge to interactive visualization. Existing storyline techniques support limited user interaction dueto the high cost of layout. We contribute a force directed layout algorithm that dynamically reflows storyline layouts with best effort response to internal and coordinated interactions. We anticipate that the characteristics of our layout algorithm will allow for graceful response to a wide variety of interaction types, speeds, and patterns. We conducted a user study to evaluate the legibility of our storyline layout after convergence. The evaluation results demonstrate that most users can accurately complete a wide variety of visual metaphor interpretation, reading, and pattern recognition tasks within 20 seconds

A hardware abstraction layer for the MicroTCA-based Global Trigger for the CMS experiment at CERN

Der Large Hadron Collider (LHC) am CERN bei Genf produziert mit einer Frequenz von 40 MHz Teilchenkollisionen. Jede dieser Kollisionen benötigt nachdem sie vom CMS Detektor aufgezeichnet worden ist etwa 1 MB an Speicher. Um diese enorme Menge an Daten zu reduzieren wurde ein komplexes Filter-System entwickelt. Die erste Stufe dieses Systems nimmt der Level-1 Trigger ein, der die Rate an aufgezeichneten Kollisionen auf 100 kHz reduziert. Diese Kollisionen können anschließend von einer großen Rechenfarm analysiert und weiter gefiltert werden. Der LHC wird in absehbarer Zukunft ausgebaut werden um Kollisionen mit noch mehr beteiligten Teilchen zu produzieren, was eine Verbesserung des Level-1 Triggers notwendig macht. Diese Arbeit beschäftigt sich mit den Plänen zu diesem Ausbau innerhalb des Global Trigger (GT) Projekts und führte schlussendlich zur Entwicklung einer hardware abstraction layer (HAL), die entfernten Zugriff auf Hardware-Register über Ethernet erlaubt wie auch abstrakte Elemente zur Verfügung stellt um die Information in den Registern zu repräsentieren. Abschließend wird eine Studie über die Effizienz des Global Muon Trigger präsentiert die zu Verbesserungen für die Datennahme ab dem Jahr 2011 geführt hat.The Large Hadron Collider (LHC) based at CERN near Geneva collides proton bunches at a rate of 40 MHz. Each collision produces approximately 1 MB of data in the Compact Muon Solenoid (CMS) detector. In order to reduce this event rate to a more manageable amount, a complex filter system was developed. The first stage of this filter is the so-called Level-1 trigger. This system reduces the incoming event rate to 100 kHz which can then be analyzed and filtered further in a massive computing farm. The LHC is scheduled to be upgraded to provide collisions with even more particles involved thus making an upgrade of the Level-1 trigger necessary. This thesis is concerned with the upgrade plans of the GlobalTrigger (GT) project and ultimately lead to the development ofa hardware abstraction layer (HAL) which can provide remote register-level access via Ethernet as well as abstract items to represent the information stored in the registers. Finally a study of the Global Muon Trigger (GMT) efficiency is presented

Operationalization of Remote Sensing Solutions for Sustainable Forest Management

The great potential of remote sensing technologies for operational use in sustainable forest management is addressed in this book, which is the reprint of papers published in the Remote Sensing Special Issue “Operationalization of Remote Sensing Solutions for Sustainable Forest Management”. The studies come from three continents and cover multiple remote sensing systems (including terrestrial mobile laser scanning, unmanned aerial vehicles, airborne laser scanning, and satellite data acquisition) and a diversity of data processing algorithms, with a focus on machine learning approaches. The focus of the studies ranges from identification and characterization of individual trees to deriving national- or even continental-level forest attributes and maps. There are studies carefully describing exercises on the case study level, and there are also studies introducing new methodologies for transdisciplinary remote sensing applications. Even though most of the authors look forward to continuing their research, nearly all studies introduced are ready for operational use or have already been implemented in practical forestry

Language Design for Reactive Systems: On Modal Models, Time, and Object Orientation in Lingua Franca and SCCharts

Reactive systems play a crucial role in the embedded domain. They continuously interact with their environment, handle concurrent operations, and are commonly expected to provide deterministic behavior to enable application in safety-critical systems. In this context, language design is a key aspect, since carefully tailored language constructs can aid in addressing the challenges faced in this domain, as illustrated by the various concurrency models that prevent the known pitfalls of regular threads. Today, many languages exist in this domain and often provide unique characteristics that make them specifically fit for certain use cases. This thesis evolves around two distinctive languages: the actor-oriented polyglot coordination language Lingua Franca and the synchronous statecharts dialect SCCharts. While they take different approaches in providing reactive modeling capabilities, they share clear similarities in their semantics and complement each other in design principles. This thesis analyzes and compares key design aspects in the context of these two languages. For three particularly relevant concepts, it provides and evaluates lean and seamless language extensions that are carefully aligned with the fundamental principles of the underlying language. Specifically, Lingua Franca is extended toward coordinating modal behavior, while SCCharts receives a timed automaton notation with an efficient execution model using dynamic ticks and an extension toward the object-oriented modeling paradigm

Using interaction data for improving the offline and online evaluation of search engines

This thesis investigates how web search evaluation can be improved using historical interaction data. Modern search engines combine offline and online evaluation approaches in a sequence of steps that a tested change needs to pass through to be accepted as an improvement and subsequently deployed. We refer to such a sequence of steps as an evaluation pipeline. In this thesis, we consider the evaluation pipeline to contain three sequential steps: an offline evaluation step, an online evaluation scheduling step, and an online evaluation step. In this thesis we show that historical user interaction data can aid in improving the accuracy or efficiency of each of the steps of the web search evaluation pipeline. As a result of these improvements, the overall efficiency of the entire evaluation pipeline is increased. Firstly, we investigate how user interaction data can be used to build accurate offline evaluation methods for query auto-completion mechanisms. We propose a family of offline evaluation metrics for query auto-completion that represents the effort the user has to spend in order to submit their query. The parameters of our proposed metrics are trained against a set of user interactions recorded in the search engine’s query logs. From our experimental study, we observe that our proposed metrics are significantly more correlated with an online user satisfaction indicator than the metrics proposed in the existing literature. Hence, fewer changes will pass the offline evaluation step to be rejected after the online evaluation step. As a result, this would allow us to achieve a higher efficiency of the entire evaluation pipeline. Secondly, we state the problem of the optimised scheduling of online experiments. We tackle this problem by considering a greedy scheduler that prioritises the evaluation queue according to the predicted likelihood of success of a particular experiment. This predictor is trained on a set of online experiments, and uses a diverse set of features to represent an online experiment. Our study demonstrates that a higher number of successful experiments per unit of time can be achieved by deploying such a scheduler on the second step of the evaluation pipeline. Consequently, we argue that the efficiency of the evaluation pipeline can be increased. Next, to improve the efficiency of the online evaluation step, we propose the Generalised Team Draft interleaving framework. Generalised Team Draft considers both the interleaving policy (how often a particular combination of results is shown) and click scoring (how important each click is) as parameters in a data-driven optimisation of the interleaving sensitivity. Further, Generalised Team Draft is applicable beyond domains with a list-based representation of results, i.e. in domains with a grid-based representation, such as image search. Our study using datasets of interleaving experiments performed both in document and image search domains demonstrates that Generalised Team Draft achieves the highest sensitivity. A higher sensitivity indicates that the interleaving experiments can be deployed for a shorter period of time or use a smaller sample of users. Importantly, Generalised Team Draft optimises the interleaving parameters w.r.t. historical interaction data recorded in the interleaving experiments. Finally, we propose to apply the sequential testing methods to reduce the mean deployment time for the interleaving experiments. We adapt two sequential tests for the interleaving experimentation. We demonstrate that one can achieve a significant decrease in experiment duration by using such sequential testing methods. The highest efficiency is achieved by the sequential tests that adjust their stopping thresholds using historical interaction data recorded in diagnostic experiments. Our further experimental study demonstrates that cumulative gains in the online experimentation efficiency can be achieved by combining the interleaving sensitivity optimisation approaches, including Generalised Team Draft, and the sequential testing approaches. Overall, the central contributions of this thesis are the proposed approaches to improve the accuracy or efficiency of the steps of the evaluation pipeline: the offline evaluation frameworks for the query auto-completion, an approach for the optimised scheduling of online experiments, a general framework for the efficient online interleaving evaluation, and a sequential testing approach for the online search evaluation. The experiments in this thesis are based on massive real-life datasets obtained from Yandex, a leading commercial search engine. These experiments demonstrate the potential of the proposed approaches to improve the efficiency of the evaluation pipeline

Social and scientific uncertainties in environmental law

Environmental law aims to provide regulatory mechanisms to protect the environment. This requires sufficient knowledge of the environmental effects of human activities; the functioning, services and carrying capacities of ecosystems; and the technical and societal options available to mitigate the adverse effects of human activity. It also aims to develop energy, food, urban and mobility systems to achieve environmental sustainability. However, major environmental threats prevalent in the 21st century, such as climate change, biodiversity loss and emerging pollutants, pose problems for scientists trying to tackle these issues, due to their complex causes, consequences and solutions required. As clearly shown by the European Green Deal strategies, these environmental threats can only be averted by transformative policies that embrace complexity in environmental and social terms, and by determining long-term transitional pathways. Never before were the makers and subjects of regulation so eminently dependent on scientific expertise and confronted with such uncertainties. The uptake of scientific knowledge and the management of uncertainties are thus among the current challenges in the formation, design and implementation of sustainable environmental laws. Social and Scientific Uncertainties in Environmental Law explores how environmental law is prepared or could be better equipped to employ the best available knowledge and expertise, and addresses the knowledge gaps and uncertainties in the legislative, administrative and judicial branches. Due to its multidisciplinary approach, this volume offers a fresh perspective, with each contribution providing a novel insight into the uncertainty of scientific understanding and making a valuable contribution to the field of environmental law. There is an urgent need for a variety of disciplines to come together to develop a common language to tackle the environmental issues besetting our world today, which this volume strives to meet

A Diagnostics Model for Industrial Communications Networks

Over the past twenty years industrial communications networks have become common place in most industrial plants. The high availability of these networks is crucial in smooth plant operations. Therefore local and remote diagnostics of these networks is of primary importance in solving any existing or emerging network problems. Users for most part consider the “plant networks” as black boxes, and often not sure of the actual health of the networks. The major part of the work outlined in this research concentrates on the proposed “Network Diagnostics Model” for local and remote monitoring. The main objective of the research is to aid the establishment of tools and techniques for diagnosis of the industrial networks, with particular emphasis on PROFIBUS and PROFINET. Additionally this research has resulted in development of a number of devices to aid in network diagnostics. The work outlined in this submission contributes to the developments in the area of online diagnostics systems. The development work was conducted in the following phases: 1. Development of Function Block (FB) for diagnosing PROFIBUS network for implementation on PLC. 2. Development of OPC server for diagnosing PROFIBUS network for implementation on PC. 3. Development of a web based diagnostic software for multiple fieldbuses for implementation on imbedded XP platform. 4. Development of OPC server for diagnosing PROFINET network for implementation on PC 5. Conformance testing of masters (PLC) in PROFIBUS network to increase the health of the network. 6. Use of diagnostics tools for performance analysis of fieldbuses networks for high performance applications. The research work outlined in this submission has made a significant and coherent contribution to online diagnostics of fieldbus communications networks, and has paved the way for the introduction of the online diagnostics devices to the market place. It has shown that the proposed model provides a uniform framework for research and development of diagnostics tools and techniques for fieldbus networks. Organizations that use fieldbus should consider installing advanced online diagnostic systems to boost maintenance efficiency and reduce operating costs, and maintain the availability of plant resources. Based on the experience gained over a number of years a multilayer model is proposed for future development of diagnostics tools

Finding False Assurance in Formal Verification of Software Systems

Formal verification plays a crucial role in enhancing the reliability of computing systems by mathematically checking the correctness of a program. Although recent years have witnessed lots of research and applications that optimize the formal verification process, the issue of false assurance persists in certain stages of the formal verification pipeline. The false assurance problem is critical as it can easily undermine months if not years of verification efforts. In this thesis, we first generalized the formal verification process. We then identified and analyzed specific stages susceptible to false assurance. Subsequently, a systematization of knowledge pertaining to the false assurance issues observed at these stages is provided, accompanied by a discussion on the existing defense mechanisms that are currently available. Specifically, we focused on the problem of formal specification incompleteness. We presented FAST in this thesis, which is short for underlineFuzzing-underlineAssisted underlineSpecification underlineTesting. FAST examines the spec for incompleteness issues in an automated way: it first locates spec gaps via mutation testing, i.e., by checking whether a code variant conforms to the original spec. If so, FAST further leverages the test suites to infer whether the gap is introduced by intention or by mistake. Depending on the codebase size, FAST may choose to generate code variants in either an enumerative or evolutionary way. FAST is applied to two open-source codebases that feature formal verification and helps to confirm 13 and 21 blind spots in their spec respectively. This highlights the prevalence of spec incompleteness in real-world applications