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Faculty / Organisational entity
Optical Character Recognition (OCR) system plays an important role in digitization of data acquired as images from a variety of sources. Although the area is very well explored for Latin languages, some of the languages based on Arabic cursive script are not yet explored. It is due to many factors: Most importantly are the unavailability of proper data sets and complexities posed by cursive scripts. The Pashto language is one of such languages which needs considerable exploration towards OCR. In order to develop such an OCR system, this thesis provides a pioneering study that explores deep learning for the Pashto language in the field of OCR.
The Pashto language is spoken by more than $50$ million people across the world, and it is an active medium both for oral as well as written communication. It is associated with rich literary heritage and contains huge written collection. These written materials present contents of simple to complex nature, and layouts from hand-scribed to printed text. The Pashto language presents mainly two types of complexities (i) generic w.r.t. cursive script, (ii) specific w.r.t. Pashto language. Generic complexities are cursiveness, context dependency, and breaker character anomalies, as well as space anomalies. Pashto specific complexities are variations in shape for a single character and shape similarity for some of the additional Pashto characters. Existing research in the area of Arabic OCR did not lead to an end-to-end solution for the mentioned complexities and therefore could not be generalized to build a sophisticated OCR system for Pashto.
The contribution of this thesis spans in three levels, conceptual level, data level, and practical level. In the conceptual level, we have deeply explored the Pashto language and identified those characters, which are responsible for the challenges mentioned above. In the data level, a comprehensive dataset is introduced containing real images of hand-scribed contents. The dataset is manually transcribed and has the most frequent layout patterns associated with the Pashto language. The practical level contribution provides a bridge, in the form of a complete Pashto OCR system, and connects the outcomes of the conceptual and data levels contributions. The practical contribution comprises of skew detection, text-line segmentation, feature extraction, classification, and post-processing. The OCR module is more strengthened by using deep learning paradigm to recognize Pashto cursive script by the framework of Recursive Neural Networks (RNN). Proposed Pashto text recognition is based on Long Short-Term Memory Network (LSTM) and realizes a character recognition rate of $90.78\%$ on Pashto real hand-scribed images. All these contributions are integrated into an application to provide a flexible and generic End-to-End Pashto OCR system.
The impact of this thesis is not only specific to the Pashto language, but it is also beneficial to other cursive languages like Arabic, Urdu, and Persian e.t.c. The main reason is the Pashto character set, which is a superset of Arabic, Persian, and Urdu languages. Therefore, the conceptual contribution of this thesis provides insight and proposes solutions to almost all generic complexities associated with Arabic, Persian, and Urdu languages. For example, an anomaly caused by breaker characters is deeply analyzed, which is shared among 70 languages, mainly use Arabic script. This thesis presents a solution to this issue and is equally beneficial to almost all Arabic like languages.
The scope of this thesis has two important aspects. First, a social impact, i.e., how a society may benefit from it. The main advantages are to bring the historical and almost vanished document to life and to ensure the opportunities to explore, analyze, translate, share, and understand the contents of Pashto language globally. Second, the advancement and exploration of the technical aspects. Because, this thesis empirically explores the recognition and challenges which are solely related to the Pashto language, both regarding character-set and the materials which present such complexities. Furthermore, the conceptual and practical background of this thesis regarding complexities of Pashto language is very beneficial regarding OCR for other cursive languages.
In recent years the demand on business process modelling (BPM) became apparent in many different communities, e.g. information systems engineering, requirements engineering [KiB94], software engineering and knowledge engineering (e.g. [BrV94], [SWH+94]). This suggests to aim at a unifying view on business process modelling in all these disciplines. To achieve the business goals some problems which obstruct these goals must be solved. This can be done either by restructuring the business process, by application of standard software, or by developing individual software components such as knowledge based systems (KBSs). To be able to model business goals and to analyse problems occurring during the business processes these processes including organisational structures and activities have to be modelled. This is also true when building a KBS in an enterprise environment. Because the KBS is only a small part of the whole business organisation, it must be embedded into or at least linked to all relevant business processes, i.e. it should not be a stand-alone solution. For this purpose we extend the MIKE approach [AFS96] in the BMBF project WORKS (Work Oriented Design of Knowledge Systems) by offering business models for modelling relevant aspects of an enterprise. To be able to define an integrated framework with other possibilties to improve an enterprise (e.g. information systems engineering) we determine the standard views of an enterprise. Next we define the views, that are necessary for developing a KBS.
We present an approach to systematically describing case-based reasoning systems bydifferent kinds of criteria. One main requirement was the practical relevance of these criteria and their usability for real-life applications. We report on the results we achieved from a case study carried out in the INRECA1 Esprit project.
The development of complex software systems is driven by many diverse and sometimes contradictory requirements such as correctness and maintainability of resulting products, development costs, and time-to-market. To alleviate these difficulties, we propose a development method for distributed systems that integrates different basic approaches. First, it combines the use of the formal description technique SDL with software reuse concepts. This results in the definition of a use-case driven, incremental development method with SDL-patterns as the main reusable artifacts. Experience with this approach has shown that there are several other factors of influence, such as the quality of reuse artifacts or the experience of the development team. Therefore, we further combined our SDL-pattern approach with an improvement methodology known from the area of experimental software engineering. In order to demonstrate the validity of this integrating approach, we sketch some representative outcomings of a case study.
Mechanised reasoning systems and computer algebra systems have apparentlydifferent objectives. Their integration is, however, highly desirable, since in manyformal proofs both of the two different tasks, proving and calculating, have to beperformed. Even more importantly, proof and computation are often interwoven andnot easily separable. In the context of producing reliable proofs, the question howto ensure correctness when integrating a computer algebra system into a mechanisedreasoning system is crucial. In this contribution, we discuss the correctness prob-lems that arise from such an integration and advocate an approach in which thecalculations of the computer algebra system are checked at the calculus level of themechanised reasoning system. This can be achieved by adding a verbose mode to thecomputer algebra system which produces high-level protocol information that can beprocessed by an interface to derive proof plans. Such a proof plan in turn can beexpanded to proofs at different levels of abstraction, so the approach is well-suited forproducing a high-level verbalised explication as well as for a low-level machine check-able calculus-level proof. We present an implementation of our ideas and exemplifythem using an automatically solved extended example.
The paper presents a process-oriented view on knowledge management in software development. We describe requirements on knowledge management systems from a process-oriented perspective, introduce a process modeling language MILOS and its use for knowledge management. Then we explain how a process-oriented knowledge management system can be implemented using advanced but available information technologies.
This paper describes an Internet-scalable knowledge base infrastructure for managing the knowledge used by an in-telligent software productivity infrastructure system. The infrastructure provides workable solutions for several significant issues: (1) Internetunique names for pieces of knowledge; (2) multi-platform, multi-language support; (3) distributed knowledge base synchronization mechanisms; (4) support for extensive customized variations in knowledge content, and (5) knowledge caching mechanisms for improved system performance. The infrastructure described here is a workable example of the kind of infrastructure that will be required to manage the evolution and reuse of millions of pieces of knowledge in the future.
This report explains basic notions and concepts of Abstract State Machines (ASM) as well as notation for defining ASM models. The objective here is to provide an intuitive understanding of the formalism; for a rigorous definition of the mathematical foundations of ASM, the reader is referred to [2] and [3]. Further references on ASM-related material can be found on the ASM Web Pages [1].
A natural extension of SLD-resolution is introduced as a goal directed proof procedure
for the full first order implicational fragment of intuitionistic logic. Its intuitionistic semantic fits a procedural interpretation of logic programming. By allowing arbitrary nested implications it can be used for implementing modularity in logic programs. With adequate negation axioms it gives an alternative to negation as failure and leads to a proof procedure for full first order predicate logic.
User interfaces for large distributed applications have to handle specific problems: the complexity of the application itself and the integration of online-data into the user interface. A main task of the user interface architecture is to provide powerful tools to design and augment the end-user system easily, hence giving the designer more time to focus on user requirements. Our experiences developing a user interface system for a process control room showed that a lot of time during the development process is wasted for the integration of online-data residing anywhere but not in the user interface itself. Furtheron external data may be kept by different kinds of programs, e.g. C-programs running
a numerical process model or PROLOG-programs running a diagnosis system, both in parallel to the process and in parallel to the user interface. Facing these specific requirements, we developed a user interface architecture following two main goals: 1. integration of external information into high-level graphical objects and 2. the system should be open for any program running as a separate process using its own problem-oriented language. The architecture is based on two approaches: an asynchronous, distributed and language independent communication model and an object model describing the problem domain and the interface using object-oriented techniques. Other areas like rule-based programming are involved, too. With this paper, we will present the XAVIA user interface architecture, the (as far as we know) first user inteface architecture, which is consequently based on a distributed object model.
The increasing use of distributed computer systems leads to an increasingneed for distributed applications. Their development in various domains like of-fice automation or computer integrated manufacturing is not sufficiently sup-ported by current techniques. New software engineering concepts are needed inthe three areas 'languages', 'tools', and 'environments'. We believe that object-oriented techniques and graphics support are key approaches to major achieve-ments in all three areas. As a consequence, we developed a universal object-oriented graphical editor ODE as one of our basic tools (tool building tool).ODE is based on the object-oriented paradigm, with some important extensionslike built-in object relations. It has an extensible functional language which al-lows for customization of the editor. ODE was developed as part of DOCASE, asoftware production environment for distributed applications. The basic ideas ofDOCASE will be presented and the requirements for ODE will be pointed out.Then ODE will be described in detail, followed by a sample customization ofODE: the one for the DOCASE design language.
Several activities around the world aim at integrating object-oriented data models with relational ones in order to improve database management systems. As a first result of these activities, object-relational database management systems (ORDBMS) are already commercially available and, simultaneously, are subject to several research projects. This (position) paper reports on our activities in exploiting object-relational database technology for establishing repository manager functionality supporting software engineering (SE) processes. We argue that some of the key features of ORDBMS can directly be exploited to fulfill many of the needs of SE processes. Thus, ORDBMS, as we think, are much better suited to support SE applications than any others. Nevertheless, additional functionality, e. g., providing adequate version management, is required in order to gain a completely satisfying SE repository. In order to remain flexible, we have developed a generative approach for providing this additional functionality. It remains to be seen whether this approach, in turn, can effectively exploit ORDBMS features. This paper, therefore, wants to show that ORDBMS can substantially contribute to both establishing and running SE repositories.
The local solution problem of multivariate Fredholm integral equations is studied. Recent research proved that for several function classes the complexity of this problem is closely related to the Gelfand numbers of some characterizing operators. The generalization of this approach to the situation of arbitrary Banach spaces is the subject of the present paper.
Furthermore, an iterative algorithm is described which - under some additional conditions - realizes the optimal error rate. The way these general theorems work is demonstrated by applying them to integral equations in a Sobolev space of periodic functions with dominating mixed derivative of various order.
Comprehensive reuse and systematic evolution of reuse artifacts as proposed by the Quality Improvement Paradigm (QIP) do not only require tool support for mere storage and retrieval. Rather, an integrated management of (potentially reusable) experience data as well as project-related data is needed. This paper presents an approach exploiting object-relational database technology to implement QIP-driven reuse repositories. Requirements, concepts, and implementational aspects are discussed and illustrated through a running example, namely the reuse and continuous improvement of SDL patterns for developing distributed systems. Our system is designed to support all phases of a reuse process and the accompanying improvement cycle by providing adequate functionality. Its implementation is based on object-relational database technology along with an infrastructure well suited for these purposes.
Typical examples, that is, examples that are representative for a particular situationor concept, play an important role in human knowledge representation and reasoning.In real life situations more often than not, instead of a lengthy abstract characteriza-tion, a typical example is used to describe the situation. This well-known observationhas been the motivation for various investigations in experimental psychology, whichalso motivate our formal characterization of typical examples, based on a partial orderfor their typicality. Reasoning by typical examples is then developed as a special caseof analogical reasoning using the semantic information contained in the correspondingconcept structures. We derive new inference rules by replacing the explicit informa-tion about connections and similarity, which are normally used to formalize analogicalinference rules, by information about the relationship to typical examples. Using theseinference rules analogical reasoning proceeds by checking a related typical example,this is a form of reasoning based on semantic information from cases.
This case study examines in detail the theorems and proofs that are shownby analogy in a mathematical textbook on semigroups and automata, thatis widely used as an undergraduate textbook in theoretical computer scienceat German universities (P. Deussen, Halbgruppen und Automaten, Springer1971). The study shows the important role of restructuring a proof for findinganalogous subproofs, and of reformulating a proof for the analogical trans-formation. It also emphasizes the importance of the relevant assumptions ofa known proof, i.e., of those assumptions actually used in the proof. In thisdocument we show the theorems, the proof structure, the subproblems andthe proofs of subproblems and their analogues with the purpose to providean empirical test set of cases for automated analogy-driven theorem proving.Theorems and their proofs are given in natural language augmented by theusual set of mathematical symbols in the studied textbook. As a first step weencode the theorems in logic and show the actual restructuring. Secondly, wecode the proofs in a Natural Deduction calculus such that a formal analysisbecomes possible and mention reformulations that are necessary in order toreveal the analogy.
Analogy in CLAM
(1999)
CL A M is a proof planner, developed by the Dream group in Edinburgh,that mainly operates for inductive proofs. This paper addresses the questionhow an analogy model that I developed independently of CL A M can beapplied to CL A M and it presents analogy-driven proof plan construction as acontrol strategy of CL A M . This strategy is realized as a derivational analogythat includes the reformulation of proof plans. The analogical replay checkswhether the reformulated justifications of the source plan methods hold inthe target as a permission to transfer the method to the target plan. SinceCL A M has very efficient heuristic search strategies, the main purpose ofthe analogy is to suggest lemmas, to replay not commonly loaded methods,to suggest induction variables and induction terms, and to override controlrather than to construct a target proof plan that can be built by CL A Mitself more efficiently.
The amount of user interaction is the prime cause of costs in interactiveprogram verification. This paper describes an internal analogy techniquethat reuses subproofs in the verification of state-based specifications. Itidentifies common patterns of subproofs and their justifications in orderto reuse these subproofs; thus significant savings on the number of userinteractions in a verification proof are achievable.
Many mathematical proofs are hard to generate forhumans and even harder for automated theoremprovers. Classical techniques of automated theoremproving involve the application of basic rules, of built-in special procedures, or of tactics. Melis (Melis 1993)introduced a new method for analogical reasoning inautomated theorem proving. In this paper we showhow the derivational analogy replay method is relatedand extended to encompass analogy-driven proof planconstruction. The method is evaluated by showing theproof plan generation of the Pumping Lemma for con-text free languages derived by analogy with the proofplan of the Pumping Lemma for regular languages.This is an impressive evaluation test for the analogicalreasoning method applied to automated theorem prov-ing, as the automated proof of this Pumping Lemmais beyond the capabilities of any of the current auto-mated theorem provers.
Die vorliegende Arbeit konzentriert sich auf Analysen unterschiedlicher Lernstrategien für CBL-Systeme anhand einer universellen Testumgebung mit variablen Fallbasen. Keine der untersuchten dynamischen Lernregeln und keine feste Belegung der globalen Konstanten im Ähnlichkeitsmass besitzt im statistischen Mittel signifikante Vorzüge. Dagegen zeigen sich Abhängigkeiten des Lernerfolgs von bestimmten Merkmalen der Fallbasis. Deswegen wird als Synthese ein auto-adaptives Lernschema vorgeschlagen, das die Eigenheiten verschiedener Fallbasen berücksichtigt und durch die Wahl spezifischer Lernstrategien ein deutlich verbessertes Ergebnis zu erzielen vermag.
Die vorliegende Arbeit beschäftigt sich mit der visuellen Kontrolle raumplanerischer Entwürfe. Grundlage der Überlegungen ist das gegenwärtige Verfahren, der Planungsprozess, das zur Erstellung der Entwürfe führt. Der Entscheidungsweg hin zum endgültigen Ergebnis erfolgt zurzeit noch ohne Rechnerunterstützung. Die in den Planungsprozess Involvierten stützen ihre Entscheidungen bspw. auf Pläne, eigene Erfahrungen und Statistiken und fertigen im Verlauf von Diskussionsrunden verschiedene Entwürfe an. Dieser Ablauf ist komplex, aufgrund der eingehenden Daten und der damit zusammenhängenden Diskussionen, und langwierig da erst nach einigen Iterationsschritten ein Ergebnis vorliegt. Die Arbeit verfolgt das Ziel, die Akteure durch eine Rechnerunterstützung schneller und zielgerichtet zu einer Entscheidungsfindung zu führen. Meine Untersuchung des Anwendungsumfeldes hat ergeben, dass dies nur möglich ist, wenn zum Einen das entstehende System in der Lage ist, die großen, heterogenen Datenmengen zu verarbeiten und andererseits die Visualisierung der Ergebnisse in einer Form erfolgt, die den Akteuren vom bisherigen Planungsprozess her bekannt ist. Die Visualisierung darf dabei keine bewertende Aussage treffen, sondern muss die Informationen der Analyse neutral in einem dem Nutzer bekannten Format abbilden. Als Ansatzpunkt stellt sich der informelle Bereich der Entscheidungsfindung dar. Es werden zwei Lösungswege aus dem Bereich der Clusteringalgorithmen verfolgt, die die großen Datenmengen verarbeiten und analysieren. Als Ergebnis erhalten die Akteure durch das Voronoi-Diagramm direkt einen Entwurf, der die Einschätzungen aller Akteure widerspiegelt und durch ein Übereinanderlegen mit der Karte des Plangebietes dem klassischen Format im Rahmen des Planungsprozesses entspricht. Dadurch wird die Akzeptanz der Rechnerunterstützung bei den Beteiligten des Planungsprozesses gesteigert. Sollte dieser Entwurf noch keine direkte Zustimmung finden, kann über die entwickelte Informationsvisualisierung eine Anzeige und in der Folge eine Anpassung der Eingangsgrößen erfolgen und somit sehr schnell ein neuer Entwurf entwickelt werden. Die Visualisierung übernimmt dabei die Funktion der bisher in Papierform erstellten Pläne im Entscheidungsprozess und bietet damit auch fachfremden Beteiligten eine visuelle Kontrollmöglichkeit der Qualität des Entwurfes. Insgesamt werden mit dem Tool IKone die Akteure in Anlehnung an die standardmäßigen Abläufe und visuellen Darstellungen mittels eines rechnergestützten Systems unterstützt.
Industrial manufacturing companies have different IT control functions that can be represented with a so-called hierarchical automation pyramid. While these conventional software systems especially support the mass production with consistent demand, the future project “Industry 4.0” focuses on customer-oriented and adaptable production processes. In order to move from conventional production systems to a factory of the future, the control levels must be redistributed. With the help of cyber-physical production systems, an interoperable architecture must be, implemented which removes the hierarchical connection of the former control levels. The accompanied digitalisation of industrial companies makes the transition to modular production possible. At the same time, the requirements for production planning and control are increasing, which can be solved with approaches such as multi-agent systems (MASs). These software solutions are autonomous and intelligent objects with a distinct collaborative ability. There are different modelling methods, communication and interaction structures, as well as different development frameworks for these new systems. Since multi-agent systems have not yet been established as an industrial standard due to their high complexity, they are usually only tested in simulations. In this bachelor thesis, a detailed literature review on the topic of MASs in the field of production planning and control is presented. In addition, selected multi-agent approaches are evaluated and compared using specific classification criteria. In addition, the applicability of using these systems in digital and modular production is assessed.
Automatic proof systems are becoming more and more powerful.However, the proofs generated by these systems are not met withwide acceptance, because they are presented in a way inappropriatefor human understanding.In this paper we pursue two different, but related, aims. First wedescribe methods to structure and transform equational proofs in away that they conform to human reading conventions. We developalgorithms to impose a hierarchical structure on proof protocols fromcompletion based proof systems and to generate equational chainsfrom them.Our second aim is to demonstrate the difficulties of obtaining suchprotocols from distributed proof systems and to present our solutionto these problems for provers using the TEAMWORK method. Wealso show that proof systems using this method can give considerablehelp in structuring the proof listing in a way analogous to humanbehaviour.In addition to theoretical results we also include descriptions onalgorithms, implementation notes, examples and data on a variety ofexamples.
The development of autonomous mobile robots is a major topic of current research. As those robots must be able to react to changing environments and avoid collisions also with moving obstacles, the fulfilment of safety requirements is an important aspect. Behaviour-based systems (BBS) have proven to meet several of the properties required for these kindsof robots, such as reactivity, extensibility and re-usability of individual components. BBS consist of a number of behavioural components that individually realise simple tasks. Their interconnection allows to achieve complex robot behaviour, which implies that correct
connections are crucial. The resulting networks can get very large making them difficult to verify. This dissertation presents a novel concept for the analysis and verification of complex autonomous robot systems controlled by behaviour-based software architectures with special focus on the integration of environmental aspects into the processes.
Several analysis techniques have been investigated and adapted to the special requirements of BBS. These include a structural analysis, which is used to find constraint violations and faults in the network layout. Fault tree analysis is applied to identify root causes of hazards and the relationship of system events. For this, a technique to map the behaviour-based control network to the structure of a fault tree has been developed. Testing and data analysis are used for the detection of failures and their root causes. Here, a new concept that identifies patterns in data recorded during test runs has been introduced.
All of these methods cannot guarantee failure-free and safe robot behaviour and can never prove the absence of failures. Therefore, model checking as formal verification technique that proves a property to be correct for the given system, has been chosen to complement the set of analysis techniques. A novel concept for the integration of environmental influences into the model checking process is proposed. Environmental situations and the sensor processing chain are represented as synchronised automata similar to the modelling of the behavioural network. Tools supporting the whole verification process including the creation of formal queries in its environment have been developed.
During the verification of large behavioural networks, the scalability of the model checking approach appears as a big problem. Several approaches that deal with this problem have been investigated and the selection of slicing and abstraction methods has been justified. A concept for the application of these methods is provided, that reduces the behavioural network to the relevant parts before the actual verification process.
All techniques have been applied to the behaviour-based control system of the autonomous outdoor robot RAVON. Its complex network with more than 400 components allows for demonstrating the soundness of the presented concepts. The set of different techniques provides a fundamental basis for a comprehensive analysis and verification of BBS acting in changing environments.
This thesis is concerned with different null-models that are used in network analysis. Whenever it is of interest whether a real-world graph is exceptional regarding a particular measure, graphs from a null-model can be used to compare the real-world graph to. By analyzing an appropriate null-model, a researcher may find whether the results of the measure on the real-world graph is exceptional or not.
Deciding which null-model to use is hard and sometimes the difference between the null-models is not even considered. In this thesis, there are several results presented: First, based on simple global measures, undirected graphs are analyzed. The results for these measures indicates that it is not important which null-model is used, thus, the fastest algorithm of a null-model may be used. Next, local measures are investigated. The fastest algorithm proves to be the most complicated to analyze. The model includes multigraphs which do not meet the conditions of all the measures, thus, the measures themselves have to be altered to take care of multigraphs as well. After careful consideration, the conditions are met and the analysis shows, that the fastest is not always the best.
The same applies for directed graphs, as is shown in the last part. There, another more complex measure on graphs is introduced. I continue testing the applicability of several null-models; in the end, a set of equations proves to be fast and good enough as long as conditions regarding the degree sequence are met.
In recent decades, there has been increasing interest in analyzing the behavior of complex systems. A popular approach for analyzing such systems is a network analytic approach where the system is represented by a graph structure (Wassermann&Faust 1994, Boccaletti et al. 2006, Brandes&Erlebach 2005, Vespignani 2018): Nodes represent the system’s entities, edges their interactions. A large toolbox of network analytic methods, such as measures for structural properties (Newman 2010), centrality measures (Koschützki et al. 2005), or methods for identifying communities (Fortunato 2010), is readily available to be applied on any network structure. However, it is often overlooked that a network representation of a system and the (technically applicable) methods contain assumptions that need to be met; otherwise, the results are not interpretable or even misleading. The most important assumption of a network representation is the presence of indirect effects: If A has an impact on B, and B has an impact on C, then A has an impact on C (Zweig 2016, Brandes et al. 2013). The presence of indirect effects can be explained by ”something” flowing through the network by moving from node to node. Such network flows (or network processes) may be the propagation of information in social networks, the spread of infections, or entities using the network as infrastructure, such as in transportation networks. Also several network measures, particularly most centrality measures, assume the presence of such a network process, but additionally assume specific properties of the network processes (Borgatti 2005). Then, a centrality value indicates a node’s importance with respect to a process with these properties.
While this has been known for several years, only recently have datasets containing real-world network flows become accessible. In this context, the goal of this dissertation is to provide a better understanding of the actual behavior of real-world network processes, with a particular focus on centrality measures: If real-world network processes turn out to show different properties than those assumed by classic centrality measures, these measures might considerably under- or overestimate the importance of nodes for the actual network flow. To the best of our knowledge, there are only very few works addressing this topic.
The contributions of this thesis are therefore as follows: (i) We investigate in which aspects real-world network flows meet the assumptions contained about them in centrality measures. (ii) Since we find that the real-world flows show considerably different properties than assumed, we test to which extent the found properties can be explained by models, i.e., models based on shortest paths or random walks. (iii) We study whether the deviations from the assumed behavior have an impact on the results of centrality measures.
To this end, we introduce flow-based variants of centrality measures which are either based on the assumed behavior or on the actual behavior of the real-world network flow. This enables systematic evaluation of the impact of each assumption on the resulting rankings of centrality measures.
While–on a large scale–we observe a surprisingly large robustness of the measures against deviations in their assumptions, there are nodes whose importance is rated very differently when the real-world network flow is taken into account. (iv) As a technical contribution, we provide a method for an efficient handling of large sets of flow trajectories by summarizing them into groups of similar trajectories. (v) We furthermore present the results of an interdisciplinary research project in which the trajectories of humans in a network were analyzed in detail. In general, we are convinced that a process-driven perspective on network analysis in which the network process is considered in addition to the network representation, can help to better understand the behavior of complex systems.
Analyzing Centrality Indices in Complex Networks: an Approach Using Fuzzy Aggregation Operators
(2018)
The identification of entities that play an important role in a system is one of the fundamental analyses being performed in network studies. This topic is mainly related to centrality indices, which quantify node centrality with respect to several properties in the represented network. The nodes identified in such an analysis are called central nodes. Although centrality indices are very useful for these analyses, there exist several challenges regarding which one fits best
for a network. In addition, if the usage of only one index for determining central
nodes leads to under- or overestimation of the importance of nodes and is
insufficient for finding important nodes, then the question is how multiple indices
can be used in conjunction in such an evaluation. Thus, in this thesis an approach is proposed that includes multiple indices of nodes, each indicating
an aspect of importance, in the respective evaluation and where all the aspects of a node’s centrality are analyzed in an explorative manner. To achieve this
aim, the proposed idea uses fuzzy operators, including a parameter for generating different types of aggregations over multiple indices. In addition, several preprocessing methods for normalization of those values are proposed and discussed. We investigate whether the choice of different decisions regarding the
aggregation of the values changes the ranking of the nodes or not. It is revealed that (1) there are nodes that remain stable among the top-ranking nodes, which
makes them the most central nodes, and there are nodes that remain stable
among the bottom-ranking nodes, which makes them the least central nodes; and (2) there are nodes that show high sensitivity to the choice of normalization
methods and/or aggregations. We explain both cases and the reasons why the nodes’ rankings are stable or sensitive to the corresponding choices in various networks, such as social networks, communication networks, and air transportation networks.
Ein typisches Mittelklassefahrzeug hat mittlerweile 100 Computerprozessoren,die miteinander kommunizieren, und bildet damit ein komplexes Softwaresystem. Die steigende Anzahl der miteinander kommunzierenden Funktionen trägt dazu bei, dass die Komplexität der Steurungssoftware immer schwerer zu beherrschen ist. Trotz eines enormen Kostenaufwands zur Entwicklung der entsprechenden Softwarekomponenten sind Softwarefehler bei Fahrzeugen der automobilen Oberklasse eine der am häufigsten angeführten Ursachen in der Pannenstatistik. Die Tatsache, dass die angeführten Funktionalitäten verteilt und parallel auf einer steigenden Anzahl unterschiedlicher Mikrokontroller abgearbeitet werden, birgt zusätzliche Probleme. Es ist jedoch Fakt, dass der Markt nach Funktionalitäten wie ABS, ASR und ESP verlangt, die zu einem wesentlichen Teil aus Software bestehen. Es ist also notwendig, einen alternativen Softwareansatz zu finden, der die Komplexität der Steuerungssoftware beherrschbar werden lässt und dennoch den Anforderungen des automobilen Umfelds, wie zum Beispiel der Verlässlichkeit gerecht wird. Dies wird in dieser Arbeit mit hilfe einer verhaltensbasierten steuerung erreicht.
Anwendungen effizienter Verfahren in Automation - Universität Karlsruhe auf der SPS97 in Nürnberg -
(1998)
We present a new software architecture in which all concepts necessary to achieve fault tolerance can be added to an appli- cation automatically without any source code changes. As a case study, we consider the problem of providing a reliable service despite node failures by executing a group of replicat- ed servers. Replica creation and management as well as fail- ure detection and recovery are performed automatically by a separate fault tolerance layer (ft-layer) which is inserted be- tween the server application and the operating system kernel. The layer is invisible for the application since it provides the same functional interface as the operating system kernel, thus making the fault tolerance property of the service completely transparent for the application. A major advantage of our ar- chitecture is that the layer encapsulates both fault tolerance mechanisms and policies. This allows for maximum flexibility in the choice of appropriate methods for fault tolerance with- out any changes in the application code.
This thesis discusses several applications of computational topology to the visualization
of scalar fields. Scalar field data come from different measurements and simulations. The
intrinsic properties of this kind of data, which make the visualization of it to a complicated
task, are the large size and presence of noise. Computational topology is a powerful tool
for automatic feature extraction, which allows the user to interpret the information contained
in the dataset in a more efficient way. Utilizing it one can make the main purpose of
scientific visualization, namely extracting knowledge from data, a more convenient task.
Volume rendering is a class of methods designed for realistic visual representation of 3D
scalar fields. It is used in a wide range of applications with different data size, noise
rate and requirements on interactivity and flexibility. At the moment there is no known
technique which can meet the needs of every application domain, therefore development
of methods solving specific problems is required. One of such algorithms, designed for
rendering of noisy data with high frequencies is presented in the first part of this thesis.
The method works with multidimensional transfer functions and is especially suited for
functions exhibiting sharp features. Compared with known methods the presented algorithm
achieves better visual quality with a faster performance in presence of mentioned
features. An improvement on the method utilizing a topological theory, Morse theory, and
a topological construct, Morse-Smale complex, is also presented in this part of the thesis.
The improvement allows for performance speedup at a little precomputation and memory
cost.
The usage of topological methods for feature extraction on a real world dataset often
results in a very large feature space which easily leads to information overflow. Topology
simplification is designed to reduce the number of features and allow a domain expert
to concentrate on the most important ones. In the terms of Morse theory features are
represented by critical points. An importance measure which is usually used for removing
critical points is called homological persistence. Critical points are cancelled pairwise
according to their homological persistence value. In the presence of outlier-like noise
homological persistence has a clear drawback: the outliers get a high importance value
assigned and therefore are not being removed. In the second part of this thesis a new
importance measure is presented which is especially suited for data with outliers. This
importance measure is called scale space persistence. The algorithm for the computation
of this measure is based on the scale space theory known from the area of computer
vision. The development of a critical point in scale space gives information about its
spacial extent, therefore outliers can be distinguished from other critical points. The usage
of the presented importance measure is demonstrated on a real world application, crater
identification on a surface of Mars.
The third part of this work presents a system for general interactive topology analysis
and exploration. The development of such a system is motivated by the fact that topological
methods are often considered to be complicated and hard to understand, because
application of topology for visualization requires deep understanding of the mathematical
background behind it. A domain expert exploring the data using topology for feature
extraction needs an intuitive way to manipulate the exploration process. The presented
system is based on an intuitive notion of a scene graph, where the user can choose and
place the component blocks to achieve an individual result. This way the domain expert
can extract more knowledge from given data independent on the application domain. The
tool gives the possibility for calculation and simplification of the underlying topological
structure, Morse-Smale complex, and also the visualization of parts of it. The system also
includes a simple generic query language to acquire different structures of the topological
structure at different levels of hierarchy.
The fourth part of this dissertation is concentrated on an application of computational
geometry for quality assessment of a triangulated surface. Quality assessment of a triangulation
is called surface interrogation and is aimed for revealing intrinsic irregularities
of a surface. Curvature and continuity are the properties required to design a visually
pleasing geometric object. For example, a surface of a manufactured body usually should
be convex without bumps of wiggles. Conventional rendering methods hide the regions
of interest because of smoothing or interpolation. Two new methods which are presented
here: curvature estimation using local fitting with B´ezier patches and computation of reflection
lines for visual representation of continuity, are specially designed for assessment
problems. The examples and comparisons presented in this part of the thesis prove the
benefits of the introduced algorithms. The methods are also well suited for concurrent visualization
of the results from simulation and surface interrogation to reveal the possible
intrinsic relationship between them.
For transferring existing knowledge into new projects, reuse has become an important factor in today's software industry. However, to set reuse into practice, reusable artifacts have to be stored somewhere, and must be offered to (re-)users on demand. For this purpose, advanced reuse repository systems like, for instance, instantiations of the Experience Base concept, are quite frequently used. Many people, from different projects, have to access such a repository at various phases of software development processes to retrieve or store reusable data. In order to fulfill the given tasks, each of these user has specific needs. Taking this into account, a reuse repository has to offer tailored user interfaces and functions for different user groups. Furthermore, since the contents of such a repository usually represent the state of the art of an organization's (core) competencies, not everyone should be allowed to freely access each and every repository entry. This isespecially true for persons that are not part of the organization. This report discusses role concepts that can be applied to reuse repository systems to overcome some of the stated access problems. Commonly used roles for software development and reuse repository management are listed. Based on these roles, a basic set of roles, as implemented in the SFB 501 Experience Base, is introduced.
With the ever-increasing amount of satellite-backed communication, constellations covering the entire world, and the rise of Software Defined Radios (SDRs), satellite signals have already become prime targets for scientific research all over the globe. However, due to logistical challenges like capture time/location and peripheral/system management for the sensors and the wide variety of protocols/encoding schemes used, no one-fits-all sniffing solution exists for capturing their wide variety of signals. Therefore, this thesis aims to analyze, design, and implement a system that makes it possible to study LEO (Low Earth Orbit) L-Band satellite signals with readily available Single Board Computers (SBCs) in a widely distributed, location, and time-aware way. The key design factors were useability, maintainability, adaptability, and security in a centrally managed client-server architecture. The research presented yielded a Satellite probe Operating System called SATOS, which aims to implement on-sensor data decoding driven by GNU Radio and secure Over The Air (OTA) updates inside the Buildroot build environment. Its intended use case is the future deployment of DISCOSAT on a university working group scale.
The proliferation of sensors in everyday devices – especially in smartphones – has led to crowd sensing becoming an important technique in many urban applications ranging from noise pollution mapping or road condition monitoring to tracking the spreading of diseases. However, in order to establish integrated crowd sensing environments on a large scale, some open issues need to be tackled first. On a high level, this thesis concentrates on dealing with two of those key issues: (1) efficiently collecting and processing large amounts of sensor data from smartphones in a scalable manner and (2) extracting abstract data models from those collected data sets thereby enabling the development of complex smart city services based on the extracted knowledge.
Going more into detail, the first main contribution of this thesis is the development of methods and architectures to facilitate simple and efficient deployments, scalability and adaptability of crowd sensing applications in a broad range of scenarios while at the same time enabling the integration of incentivation mechanisms for the participating general public. During an evaluation within a complex, large-scale environment it is shown that real-world deployments of the proposed data recording architecture are in fact feasible. The second major contribution of this thesis is the development of a novel methodology for using the recorded data to extract abstract data models which are representing the inherent core characteristics of the source data correctly. Finally – and in order to bring together the results of the thesis – it is demonstrated how the proposed architecture and the modeling method can be used to implement a complex smart city service by employing a data driven development approach.
In der CAGD Literatur werden häufig Ableitungen und Graderhöhungen von Bezierkurven und -flächen wiederum in Bezierform angegeben [1][2][3][6]. Meistens werden diese Darstellungen nur für theoretische Betrachtungen verwendet, z.B. geometrischer Deutung von Stetigkeiten zwischen angrenzenden Flächenstücken. Für praktische Anwendungen reicht die Menge der Operationen jedoch nicht aus. Farouki und Rajan [4] zeigten, daß die Resultate arithmetischer Operationen, wie Addition und Multiplikation auf Bezierkurven auch als Bezierkurven darstellbar sind. Hier werden wir die Operationen auf polynomiale und rationale Tensorprodukt Bezierflächen und Flächen über Dreiecken ausdehnen. Eine Erweiterung auf rationale Flächen ermöglicht insbesondere die Ausführung einer Division, wie sie für viele Anwendungen benötigt wird. Das Rechnen mit Flächen hat im Gegensatz zu punktweisen Auswertungen den Vorteil gleichzeitig mit Hilfe von notwendigen Bedingungen an das entstandene Beziernetz sichere Ergebnisabschätungen angeben zu können. Diese lassen sich für adaptive Verfahren nutzen und sind insbesondere dort wichtig, wo es auf exakte Aussagen über das Verhalten von Flächen ankommt, wie z.B. bei der Qualitätsanalyse von Freiformflächen [5]. Mit Hilfe der hier vorgestellten Operationen läßt sich u.a. an Vorzeichenwechseln erkennen, ob eine zu untersuchende Bezierfläche konvex ist oder nicht (siehe Kapitel 4). Außerdem können Fehler, die bei punktweisen Auswertungen auf Gittern mit großer Maschenweite entstehen, vermieden werden. Nachdem in Kapitel 2 die zum Verständnis nötigen Definitionen und Schreibweisen erläutert wurden, werden in Kapitel 3 die grundlegenden Operationen für eine Arithmetik
auf Bezierflächen beschrieben. Dabei werden Formeln angegeben, die die Bezierpunkte und Gewichte der Ergebnisfläche aus denen der Operandenflächen bestimmen. Durch Aneinanderreihung und Verkettung einzelner Operationen lassen sich dann komplexe Berechnungen mit der gesamten Fläche ausführen. Zum Schluß werden in Kapitel 4 einige Beispiele aus dem Bereich der Qualitätsanalyse von Freiformflächen angegeben.
Das System ART (ASF RRL Translation) stellt im wesentlichen eine Umgebung dar,in welcher die Modularisierbarkeit von Beweisen (Induktionsbeweisen über Gleichungs-spezifikationen) untersucht werden kann. Es wurde die bereits bestehende Spezifikati-onsprache ASF (siehe [BeHeKl89]), in welcher modularisierte Spezifikationen möglichsind, so erweitert, daß zusätzlich auch Beweisaufgaben spezifiziert werden können. Imfolgenden wird diese erweiterte Spezifikationsprache auch ASF genannt. Als Bewei-ser für die Beweisaufgaben einer Spezifikation wurde RRL (siehe [KaZh89]) gewählt.RRL kann sowohl Kommandos aus einem File abarbeiten, wie auch Sitzungsprotokolleanfertigen, mit deren Hilfe sich die Beweisverläufe und Benutzereingaben der entspre-chenden RRL-Sitzung rekonstruieren lassen. In ART kann nun eine ASF-Spezifikation,die Beweisaufgaben umfassen kann, in ein File übersetzt werden, welches von RRLabgearbeitet werden kann. Dies wird im folgenden kurz mit 'Übersetzung von ASF nach RRL' bezeichnet. Bei der Abarbeitung eines solchen Files wird von RRL ein Sit-zungsprotokoll angelegt. ART kann dieses Sitzungsprotokoll dazu heranziehen, neueErgebnisse, wie etwa den erfolgreichen Beweis einer Beweisaufgabe, zu ermitteln, umdiese Ergebnisse der ursprüngliche Spezifikation hinzuzufügen. Dies wird im folgendenkurz mit 'Rückübersetzung von RRL nach ASF' bezeichnet. Im Kern besteht ART alsoaus einer Komponente zur Übersetzung von ASF nach RRL und aus einer Komponentezur Rückübersetzung von RRL nach ASF.
Ohne auf wesentliche Aspekte der in [Bergstra&al.89] vorgestellten alge-braischen Spezifikationssprache ASF zu verzichten, haben wir ASF um die folgenden Konzepteerweitert: Während in ASF einmal exportierte Namen bis zur Spitze der Modulhierarchie sichtbarbleiben müssen, ermöglicht ASF + ein differenziertes Verdecken von Signaturnamen. Das fehlerhafteVermischen unterschiedlicher Strukturen, welches in ASF beim Import verschiedener Aktualisie-rungen desselben parametrisierten Moduls auftritt, wird in ASF + durch eine adäquatere Form derParameterbindung vermieden. Das neue Namensraum_Konzept von ASF + erlaubt es dem Spe-zifizierer, einerseits die Herkunft verdeckter Namen direkt zu identifizieren und anderseits beimImport eines Moduls auszudrücken, ob dieses Modul nur benutzt oder in seinen wesentlichen Ei-genschaften verändert werden soll. Im ersten Fall kann er auf eine einzige global zur Verfügungstehende Version zugreifen; im zweiten Fall muß er eine Kopie des Moduls importieren. Schließlicherlaubt ASF + semantische Bedingungen an Parameter und die Angabe von Beweiszielen.
The usage of sensors in modern technical systems and consumer products is in a rapid increase. This advancement can be characterized by two major factors, namely, the mass introduction of consumer oriented sensing devices to the market and the sheer amount of sensor data being generated. These characteristics raise subsequent challenges regarding both the consumer sensing devices' reliability and the management and utilization of the generated sensor data. This thesis addresses these challenges through two main contributions. It presents a novel framework that leverages sentiment analysis techniques in order to assess the quality of consumer sensing devices. It also couples semantic technologies with big data technologies to present a new optimized approach for realization and management of semantic sensor data, hence providing a robust means of integration, analysis, and reuse of the generated data. The thesis also presents several applications that show the potential of the contributions in real-life scenarios.
Due to the broad range, growing feature set and fast release pace of new sensor-based products, evaluating these products is very challenging as standard product testing is not practical. As an alternative, an end-to-end aspect-based sentiment summarizer pipeline for evaluation of consumer sensing devices is presented. The pipeline uses product reviews to extract the sentiment at the aspect level and includes several components namely, product name extractor, aspects extractor and a lexicon-based sentiment extractor which handles multiple sentiment analysis challenges such as sentiment shifters, negations, and comparative sentences among others. The proposed summarizer's components generally outperform the state-of-the-art approaches. As a use case, features of the market leading fitness trackers are evaluated and a dynamic visual summarizer is presented to display the evaluation results and to provide personalized product recommendations for potential customers.
The increased usage of sensing devices in the consumer market is accompanied with increased deployment of sensors in various other fields such as industry, agriculture, and energy production systems. This necessitates using efficient and scalable methods for storing and processing of sensor data. Coupling big data technologies with semantic techniques not only helps to achieve the desired storage and processing goals, but also facilitates data integration, data analysis, and the utilization of data in unforeseen future applications through preserving the data generation context. This thesis proposes an efficient and scalable solution for semantification, storage and processing of raw sensor data through ontological modelling of sensor data and a novel encoding scheme that harnesses the split between the statements of the conceptual model of an ontology (TBox) and the individual facts (ABox) along with in-memory processing capabilities of modern big data systems. A sample use case is further introduced where a smartphone is deployed in a transportation bus to collect various sensor data which is then utilized in detecting street anomalies.
In addition to the aforementioned contributions, and to highlight the potential use cases of sensor data publicly available, a recommender system is developed using running route data, used for proximity-based retrieval, to provide personalized suggestions for new routes considering the runner's performance, visual and nature of route preferences.
This thesis aims at enhancing the integration of sensing devices in daily life applications through facilitating the public acquisition of consumer sensing devices. It also aims at achieving better integration and processing of sensor data in order to enable new potential usage scenarios of the raw generated data.
The Symbol Grounding Problem (SGP) is one of the first attempts to proposed a hypothesis about mapping abstract concepts and the real world. For example, the concept "ball" can be represented by an object with a round shape (visual modality) and phonemes /b/ /a/ /l/ (audio modality).
This thesis is inspired by the association learning presented in infant development.
Newborns can associate visual and audio modalities of the same concept that are presented at the same time for vocabulary acquisition task.
The goal of this thesis is to develop a novel framework that combines the constraints of the Symbol Grounding Problem and Neural Networks in a simplified scenario of association learning in infants. The first motivation is that the network output can be considered as numerical symbolic features because the attributes of input samples are already embedded. The second motivation is the association between two samples is predefined before training via the same vectorial representation. This thesis proposes to associate two samples and the vectorial representation during training. Two scenarios are considered: sample pair association and sequence pair association.
Three main contributions are presented in this work.
The first contribution is a novel Symbolic Association Model based on two parallel MLPs.
The association task is defined by learning that two instances that represent one concept.
Moreover, a novel training algorithm is defined by matching the output vectors of the MLPs with a statistical distribution for obtaining the relationship between concepts and vectorial representations.
The second contribution is a novel Symbolic Association Model based on two parallel LSTM networks that are trained on weakly labeled sequences.
The definition of association task is extended to learn that two sequences represent the same series of concepts.
This model uses a training algorithm that is similar to MLP-based approach.
The last contribution is a Classless Association.
The association task is defined by learning based on the relationship of two samples that represents the same unknown concept.
In summary, the contributions of this thesis are to extend Artificial Intelligence and Cognitive Computation research with a new constraint that is cognitive motivated. Moreover, two training algorithms with a new constraint are proposed for two cases: single and sequence associations. Besides, a new training rule with no-labels with promising results is proposed.
Interconnected, autonomously driving cars shall realize the vision of a zero-accident, low energy mobility in spite of a fast increasing traffic volume. Tightly interconnected medical devices and health care systems shall ensure the health of an aging society. And interconnected virtual power plants based on renewable energy sources shall ensure a clean energy supply in a society that consumes more energy than ever before. Such open systems of systems will play an essential role for economy and society.
Open systems of systems dynamically connect to each other in order to collectively provide a superordinate functionality, which could not be provided by a single system alone. The structure as well as the behavior of an open system of system dynamically emerge at runtime leading to very flexible solutions working under various different environmental conditions. This flexibility and adaptivity of systems of systems are a key for realizing the above mentioned scenarios.
On the other hand, however, this leads to uncertainties since the emerging structure and behavior of a system of system can hardly be anticipated at design time. This impedes the indispensable safety assessment of such systems in safety-critical application domains. Existing safety assurance approaches presume that a system is completely specified and configured prior to a safety assessment. Therefore, they cannot be applied to open systems of systems. In consequence, safety assurance of open systems of systems could easily become a bottleneck impeding or even preventing the success of this promising new generation of embedded systems.
For this reason, this thesis introduces an approach for the safety assurance of open systems of systems. To this end, we shift parts of the safety assurance lifecycle into runtime in order to dynamically assess the safety of the emerging system of system. We use so-called safety models at runtime for enabling systems to assess the safety of an emerging system of system themselves. This leads to a very flexible runtime safety assurance framework.
To this end, this thesis describes the fundamental knowledge on safety assurance and model-driven development, which are the indispensable prerequisites for defining safety models at runtime. Based on these fundamentals, we illustrate how we modularized and formalized conventional safety assurance techniques using model-based representations and analyses. Finally, we explain how we advanced these design time safety models to safety models that can be used by the systems themselves at runtime and how we use these safety models at runtime to create an efficient and flexible runtime safety assurance framework for open systems of systems.
In nebenläufigen Systemen erleichtert das Konzept der Atomarität vonOperationen, konkurrierende Zugriffe in größere, leichter beherrschbareAbschnitte zu unterteilen. Wenn wir aber Spezifikationen in der forma-len Beschreibungstechnik Estelle betrachten, erweist es sich, daß es un-ter bestimmten Umständen schwierig ist, die Atomarität der sogenanntenTransitionen bei Implementationen exakt einzuhalten, obwohl diese Ato-marität eine konzeptuelle Grundlage der Semantik von Estelle ist. Es wirdaufgezeigt, wie trotzdem sowohl korrekte als auch effiziente nebenläufigeImplementationen erreicht werden können. Schließlich wird darauf hinge-wiesen, daß die das Problem auslösenden Aktionen oft vom Spezifiziererleicht von vorneherein vermieden werden können; und dies gilt auch überden Kontext von Estelle hinaus.
Aufbau einer domänenunabhängigen Fallbasis und Fallauswahl mit Zielabhängigkeiten in CAPLAN/CBC
(1995)
Die formale Spezifikation von Kommunikationssystemen stellt durch die mit ihr verbundene Abstraktion und Präzision eine wichtige Grundlage für die formale Verifikation von Systemeigenschaften dar. Diese Abstraktion begrenzt jedoch auch die Ausdrucksfähigkeit der formalen Beschreibungstechnik und kann somit zu problemunangemessenen Spezifikationen führen. Wir untersuchen anhand der formalen Beschreibungstechnik Estelle zunächst zwei solche Aspekte. Beide führen speziell in Hinsicht auf die Domäne von Estelle, der Spezifikation von Kommunikationsprotokollen, zu schwerwiegenden Beeinträchtigungen der Ausdrucksfähigkeit. Eines dieser Defizite zeigt sich bei dem Versuch, in Estelle ein offenes System wie z. B. eine Protokollmaschine oder einen Kommunikationsdienst zu spezifizieren. Da Estelle-Spezifikationen nur geschlossene Systeme beschreiben können, werden solche Komponenten immer nur als Teil einer fest vorgegebenen Umgebung spezifiziert und besitzen auch nur in dieser eine formale Syntax und Semantik. Als Lösung für dieses Problem führen wir die kompatible syntaktische und semantische Estelle-Erweiterung Open-Estelle ein, die eine formale Spezifikation solcher offener Systeme und ihres Imports in verschiedene Umgebungen ermöglicht. Ein anderes Defizit in der Ausdrucksfähigkeit von Estelle ergibt sich aus der strengen Typprüfung. Wir werden zeigen, dass es in heterogenen, hierarchisch strukturierten Kommunikationssystemen im Zusammenhang mit den dort auftretenden horizontalen und vertikalen Typkompositionen zu einer unangemessenen Modellierung von Nutzdatentypen an den Dienstschnittstellen kommt. Dieses Problem erweist sich beim Versuch einer generischen und nutzdatentypunabhängigen Spezifikation eines offenen Systems (z. B. mit Open-Estelle) sogar als fatal. Deshalb führen wir die kompatible Containertyp-Erweiterung ein, durch die eine formale Spezifikation nutzdatentypunabhängiger und somit generischer Schnittstellen von Diensten und Protokollmaschinen ermöglicht wird. Als Grundlage für unsere Implementierungs- und Optimierungsexperimente führen wir den „eXperimental Estelle Compiler“ (XEC) ein. Er ermöglicht aufgrund seines Implementierungskonzeptes eine sehr flexible Modellierung des Systemmanagements und ist insbesondere für die Realisierung verschiedener Auswahloptimierungen geeignet. XEC ist zudem mit verschiedenen Statistik- und Monitoring-Funktionalitäten ausgestattet, durch die eine effiziente quantitative Analyse der durchgeführten Implementierungsexperimente möglich ist. Neben dem vollständigen Sprachumfang von Estelle unterstützt XEC auch die meisten der hier eingeführten Estelle-Erweiterungen. Neben der Korrektheit ist die Effizienz automatisch generierter Implementierungen eine wichtige Anforderung im praktischen Einsatz. Hier zeigt sich jedoch, dass viele der in formalen Protokollspezifikationen verwendeten Konstrukte nur schwer semantikkonform und zugleich effizient implementiert werden können. Entsprechend untersuchen wir anhand des Kontrollflusses und der Handhabung von Nutzdaten, wie die spezifizierten Operationen effizient implementiert werden können, ohne das Abstraktionsniveau senken zu müssen. Die Optimierung des Kontrollflusses geschieht dabei ausgehend von der effizienten Realisierung der Basisoperationen der von XEC erzeugten Implementierungen primär anhand der Transitionsauswahl, da diese speziell bei komplexen Spezifikationen einen erheblichen Teil der Ausführungszeit bansprucht. Wir entwickeln dazu verschiedene heuristische Optimierungen der globalen Auswahl und der modullokalen Auswahl und werten diese sowohl analytisch wie auch experimentell aus. Wesentliche Ansatzpunkte sind dabei verschiedene ereignisgesteuerte Auswahlverfahren auf globaler Ebene und die Reduktion der zu untersuchenden Transitionen auf lokaler Ebene. Die Überprüfung der Ergebnisse anhand der ausführungszeitbezogenen Leistungsbewertung bestätigt diese Ergebnisse. Hinsichtlich der effizienten Handhabung von Daten untersuchen wir unterschiedliche Ansätze auf verschiedenen Ebenen, die jedoch in den meisten Fällen eine problemunangemessene Ausrichtung der Spezifikation auf die effiziente Datenübertragung erfordern. Eine überraschend elegante, problemorientierte und effiziente Lösung ergibt sich jedoch auf Basis der Containertyp-Erweiterung, die ursprünglich zur Steigerung des Abstraktionsniveaus eingeführt wurde. Dieses Ergebnis widerlegt die Vorstellung, dass Maßnahmen zur Steigerung der effizienten Implementierbarkeit auch immer durch eine Senkung des Abstraktionsniveaus erkauft werden müssen.
We propose a universal method for the evaluation of generalized standard materials that greatly simplifies the material law implementation process. By means of automatic differentiation and a numerical integration scheme, AutoMat reduces the implementation effort to two potential functions. By moving AutoMat to the GPU, we close the performance gap to conventional evaluation routines and demonstrate in detail that the expression level reverse mode of automatic differentiation as well as its extension to second order derivatives can be applied inside CUDA kernels. We underline the effectiveness and the applicability of AutoMat by integrating it into the FFT-based homogenization scheme of Moulinec and Suquet and discuss the benefits of using AutoMat with respect to runtime and solution accuracy for an elasto-viscoplastic example.
The feature interaction problem in telecommunications systems increasingly ob-structs the evolution of such systems. We develop formal detection criteria whichrender a necessary (but less than sufficient) condition for feature interactions. It can be checked mechanically and points out all potentially critical spots. Thesehave to be analysed manually. The resulting resolution decisions are incorporatedformally. Some prototype tool support is already available. A prerequisite forformal criteria is a formal definition of the problem. Since the notions of featureand feature interaction are often used in a rather fuzzy way, we attempt a formaldefinition first and discuss which aspects can be included in a formalization (andtherefore in a detection method). This paper describes ongoing work.
Automata-Theoretic vs. Property-Oriented Approaches for the Detection of Feature Interactions in IN
(1999)
The feature interaction problem in Intelligent Networks obstructs more and morethe rapid introduction of new features. Detecting such feature interactions turns out to be a big problem. The size of the systems and the sheer computational com-plexity prevents the system developer from checking manually any feature against any other feature. We give an overview on current (verification) approaches and categorize them into property-oriented and automata-theoretic approaches. A comparisonturns out that each approach complements the other in a certain sense. We proposeto apply both approaches together in order to solve the feature interaction problem.
Independent development of system components may cause integration problems if their interaction is faulty. This problem may be solved by enforcing required component interactions at the system level. We have developed a system that automatically integrates control-oriented components, to make them consistent with aggregate system behavior re- quirements. Ourmethod is based on the automated synchronization method that modifies independently designed compo-nents to make them satisfy a set of user defined receptive safety properties. The automated synchroniza-tion allows us to design the compo nents as independent controllers that satisfy their individual requirements and to compose a correct executable system by combining the components and enforcing their interaction constraints. This approach gives component designers the freedom to design independently, and produce a functional system by combining the components and specifying their interaction requirements.
Weak memory consistency models capture the outcomes of concurrent
programs that appear in practice and yet cannot be explained by thread
interleavings. Such outcomes pose two major challenges to formal
methods. First, establishing that a memory model satisfies its
intended properties (e.g., supports a certain compilation scheme) is
extremely error-prone: most proposed language models were initially
broken and required multiple iterations to achieve soundness. Second,
weak memory models make verification of concurrent programs much
harder, as a result of which there are no scalable verification
techniques beyond a few that target very simple models.
This thesis presents solutions to both of these problems.
First, it shows that the relevant metatheory of weak memory
models can be effectively decided (sparing years of manual proof
efforts), and presents Kater, a tool that can answer metatheoretic
queries in a matter of seconds. Second, it presents GenMC, the first
(and only) scalable stateless model checker that is parametric in the
choice of the memory model, often improving the prior state of the art
by orders of magnitude.
Today's communication systems are typically structured into several layers, where each layer realizes a fixed set of protocol functionalities. These functionalities have been carefully chosen such that a wide range of applications can be supported and protocols work in a general environment of networks. However, due to evolving network technologies as well as increased and varying demands of modern applications general-purpose protocol stacks are not always adequate. To improve this situation new flexible communication architectures have been developed which enable the configuration of customized communication subsystems by composing a proper set of reusable building blocks. In particular, several approaches to automatic configuration of communication subsystems have been reported in the literature. This report gives an overview of theses approaches (F-CCS, Da CaPo, x-Kernel, and ADAPTIVE) and, in particular, defines a framework, which identifies common architectural issues and configuration tasks.
This paper discusses the problem of automatic off-line programming and motion planning for industrial robots. At first, a new concept consisting of three steps is proposed. The first step, a new method for on-line motion planning is introduced. The motion planning method is based on the A*-search algorithm and works in the implicit configuration space. During searching, the collisions are detected in the explicitly represented Cartesian workspace by hierarchical distance computation. In the second step, the trajectory planner has to transform the path into a time and energy optimal robot program. The practical application of these two steps strongly depends on the method for robot calibration with high accuracy, thus, mapping the virtual world onto the real world, which is discussed in the third step.
The main goal of this thesis is twofold. First, the thesis aims at bridging the gap between existing Pattern Recognition (PR) methods of automatic signature verification and the requirements for their application in forensic science. This gap, attributed by various factors ranging from system definition to evaluation, prevents automatic methods from being used by Forensic Handwriting Examiners (FHEs). Second, the thesis presents novel signature verification methods developed particularly considering the implications of forensic casework, and outperforming the state-of-the-art PR methods.
The first goal of the thesis is attributed by four important factors, i.e., data, terminology, output reporting, and how evaluation of automatic systems is carried out today. It is argued that traditionally the signature data used in PR are not actual/close representative of the real world data (especially that available in forensic cases). The systems trained on such data are, therefore, not suitable for forensic environments. This situation can be tackled by providing more realistic data to PR researchers. To this end, various signature and handwriting datasets are gathered in collaboration with FHEs and are made publicly available through the course of this thesis. A special attention is given to disguised signatures--where authentic authors purposefully make their signatures look like a forgery. This genre was at large neglected in PR research previously.
The terminology used, in the two communities - PR and FHEs, differ greatly. In fact, even in PR, there is no standard terminology and people often differ in the usage of various terms particularly related to various types of forged signatures/handwriting. The thesis presents a new terminology that is equally useful for both forensic scientists and PR researchers. The proposed terminology is hoped to increase the general acceptability of automatic signature analysis systems in forensic science.
The outputs reported by general signature verification systems are not acceptable for FHEs and courts as they are either binary (yes/no) or score (raw evidence) based on similarity/difference. The thesis describes that automatic systems should rather report the probability of observing the evidence (e.g., a certain similarity/difference score) given the signature belongs to the acclaimed identity, and the probability of observing the same evidence given the signature does not belong to the acclaimed identity. This will take automatic systems from hard decisions to soft decisions, thereby enabling them to report likelihood ratios that actually represent the evidential value of the score rather than the raw score (evidence).
When automatic systems report soft decisions (as in the form of likelihood ratios), the thesis argues that there must be some methods to evaluate such systems. This thesis presents one such adaptation. The thesis argues that the state-of-the-art evaluation methods, like equal error rate and area under curve, do not address the needs of forensic science. These needs require an assessment of the evidential value of signature verification, rather than a hard/pure classification (accept/reject binary decision). The thesis demonstrates and validates a relatively simple adaptation of the current verification methods based on the Bayesian inference dependent calibration of continuous scores rather than hard classifications (binary and/or score based classification).
The second goal of this thesis is to introduce various local features based techniques which are capable of performing signature verification in forensic cases and reporting results as anticipated by FHEs and courts. This is an important contribution of the thesis because of the following two reasons. First, to the best of author's knowledge, local feature descriptors are for the first time used for development of signature verification systems for forensic environments (particularly considering disguised signatures). Previously, such methods have been heavily used for recognition tasks, rather than verification of writing behaviors, such as character and digit recognition. Second, the proposed methods not only report the more traditional decisions (like scores-usually reported in PR) but also the Bayesian inference based likelihood ratios (suitable for courts and forensic cases).
Furthermore, the thesis also provides a detailed man vs. machine comparison for signature verification tasks. The men, in this comparison, are forensic scientists serving as forensic handwriting examiners and having experience of varying number of years. The machines are the local features based methods proposed in this thesis, along with various other state-of-the-art signature verification systems. The proposed methods clearly outperform the state-of-the-art systems, and sometimes the human experts.
Finally, the thesis details various tasks that have been performed in the areas closely related to signature verification and its application in forensic casework. These include, developing novel local feature based methods for extraction of signatures/handwritten text from document images, hyper-spectral image analysis for extraction of signatures from forensic documents, and analysis of on-line signatures acquired through specialized pens equipped with Accelerometer and Gyroscope. These tasks are important as they enable the thesis to take PR systems one step further close to direct application in forensic cases.
In recent years, the formal methods community has made significant progress towards the development of industrial-strength static analysis tools that can check properties of real-world production code. Such tools can help developers detect potential bugs and security vulnerabilities in critical software before deployment. While the potential benefits of static analysis tools are clear, their usability and effectiveness in mainstream software development workflows often comes into question and can prevent software developers from using these tools to their full potential. In this dissertation, we focus on two major challenges that can limit their ability to be incorporated into software development workflows.
The first challenge is unintentional unsoundness. Static program analyzers are complicated tools, implementing sophisticated algorithms and performance heuristics. This makes them highly susceptible to undetected unintentional soundness issues. These issues in program analyzers can cause false negatives and have disastrous consequences e.g., when analyzing safety critical software. In this dissertation, we present novel techniques to detect unintentional unsoundness bugs in two foundational program analysis tools namely SMT solvers and Datalog engines. These tools are used extensively by the formal methods community, for instance, in software verification, systematic testing, and program synthesis. We implemented these techniques as easy-to-use open source tools that are publicly available on Github. With the proposed techniques, we were able to detect more than 55 unique and confirmed critical soundness bugs in popular and widely used SMT solvers and Datalog engines in only a few months of testing.
The second challenge is finding the right balance between soundness, precision, and perfor- mance. In an ideal world, a static analyzer should be as precise as possible while maintaining soundness and being sufficiently fast. However, to overcome undecidability issues, these tools have to employ a variety of techniques to be practical for example, compromising on the sound- ness of the analysis or approximating code behavior. Static analyzers therefore are not trivial to integrate into any usage scenario with different program sizes, resource constraints and SLAs. Most of the times, these tools also don’t scale to large industrial code bases containing millions of lines of code. This makes it extremely challenging to get the most out of these analyzers and integrate them into everyday development activities, especially for average software develop- ment teams with little to no knowledge or understanding of advanced static analysis techniques. In this dissertation we present an approach to automatically tailor an abstract interpreter to the code under analysis and any given resource constraints. We implemented our technique as an open source framework, which is publicly available on Github. The second contribution of this dissertation in this challenge area is a technique to horizontally scale analysis tools in cloud-based static analysis platforms by splitting the input to the analyzer into partitions and analyzing the partitions independently. The technique was developed in collaboration with Amazon Web Services and is now being used in production in their CodeGuru service.
This report presents a generalization of tensor-product B-spline surfaces. The new scheme permits knots whose endpoints lie in the interior of the domain rectangle of a surface. This allows local refinement of the knot structure for approximation purposes as well as modeling surfaces with local tangent or curvature discontinuities. The surfaces are represented in terms of B-spline basis functions, ensuring affine invariance, local control, the convex hull property, and evaluation by de Boor's algorithm. A dimension formula for a class of generalized tensor-product spline spaces is developed.
Im Bereich des Software Engineering werden komplexe Software-Entwicklungsprojekte betrachtet. Im Rahmen dieser Projekte werden große Mengen von Informationen bearbeitet. Diese Informationen werden in Software-Artefakten (z.B. in Projektplänen oder Entwicklungsdokumenten, wie Anforderungsbeschreibungen)
festgehalten. Die Artefakte werden während der Entwicklung und der Wartung eines Softwaresystems häufig geändert. Änderungen einer Information in einem Artefakt haben häufig Änderungen
im selben und in anderen Artefakten zur Folge, da Beziehungen innerhalb und zwischen den in den Artefakten festgehaltenen Informationen bestehen. Die Beziehungen liegen meist nicht explizit vor, so daß die Konsequenzen einer Änderung schwer zu überblicken sind. In dieser Arbeit wurde ein Verfolgbarkeitsansatz ausgewählt, der den Benutzer bei der Durchführung von Änderungen an Artefakten unterstützt. Unterstützung bedeutet hierbei, daß der Aufwand zur Durchführung einer Änderung reduziert wird und weniger Fehler bei der Durchführung gemacht werden.
In der Arbeit wurden Anforderungen an einen auszuwählenden Verfolgbarkeitsansatz gestellt. Eine Anforderung war, daß er auf verschiedene Bereiche des Software Engineering, wie z.B. Systementwurf oder Meßplanung, mit jeweils sehr unterschiedlichen Artefakten, anwendbar sein sollte. Die durchgeführte
Literaturrecherche und die anschließende Bewertung anhand der gestellten Anforderungen ergaben, daß das Prinzip der Metamodellierung in Verbindung mit Wissensbankverwaltungssystemen ein geeigneter Verfolgbarkeitsansatz ist. Eine Evaluation, die sich auf Fallstudien aus den Bereichen
"Objektorientierter Entwurf mit UML" und "Meßplanung mit GQM" bezog, ergab, daß das Wissensbankverwaltungssystem
ConceptBase, das auf der Wissensrepräsentationssprache 0-Telos basiert, ein geeignetes Werkzeug zur Unterstützung des Verfolgbarkeitsansatzes ist.
Best-Fit Pattern Matching
(1994)
This report shows that dispatching of methods in object oriented languages is in principle the same as best fit pattern matching. A general conceptual description of best fit pattern matching is presented. Many object oriented features are modelled by means of the general concept. This shows that simple methods, multi methods, overloading of functions, pattern matching,
dynamic and union types, and extendable records can be combined in a single comprehensive concept.
Bestimmung der Ähnlichkeit in der fallbasierten Diagnose mit simulationsfähigen Maschinenmodellen
(1999)
Eine Fallbasis mit bereits gelösten Diagnoseproblemen Wissen über die Struktur der Maschine Wissen über die Funktion der einzelnen Bauteile (konkret und abstrakt) Die hier vorgestellte Komponente setzt dabei auf die im Rahmen des Moltke-Projektes entwickelten Systeme Patdex[Wes91] (fallbasierte Diagnose) und iMake [Sch92] bzw. Make [Reh91] (modellbasierte Generierung von Moltke- Wissensbasen) auf.
Zur Zeit haben Industrieroboter nur eine sehr begrenzte Wahrnehmung ihrer Umwelt. Wenn sich Menschen im Arbeitsraum des Roboters aufhalten sind sie daher gefährdet. Durch eine Einteilung der möglichen Roboterbewegung in verschiedene Klassen kann gezeigt werden, dass die für einen Menschen im Arbeitsraum gefährlichste Bewegung die freie Transferbewegung ist. Daher besteht die betrachtete Aufgabe darin, diese Transferbewegung eines Manipulators durchzuführen, ohne mit dynamischen Hindernissen, wie zum Beispiel Menschen, zu kollidieren. Das vorgestellte SIMERO-System realisiert eine globale Ganzarmkollisionsvermeidung auf der Basis von Bildern stationärer Kameras. Das System gliedert sich in die vier Hauptkomponenten Bildverarbeitung, Robotermodellierung, Kollisionserkennung und Bahnplanung. Diese Komponenten werden im einzelnen vorgestellt.
In this paper, a framework for globally distributed soft-ware development and management environments, whichwe call Booster is presented. Additionally, the first experi-ences with WebMake, an application developed to serve asan experimental platform for a software developmentenvironment based on the World Wide Web and theBooster framework is introduced. Booster encompasses thebasic building blocks and mechanisms necessary tosupport a truly cooperative distributed softwaredevelopment from the very beginning to the last steps in asoftware life cycle. It is thus a precursor of the GlobalSoftware Highway, in which providers and users can meetfor the development, management, exchange and usage ofall kind of software.
Die Realisierung zunehmend komplexer Softwareprojekte erfordert das direkte und indirekteZusammenwirken einer immer größer werdenden Zahl von Personen. Die dafür benötigte Infrastrukturist mit der zunehmenden globalen Rechner-Vernetzung bereits vorhanden, doch wird ihr Potential vonherkömmlichen Werkzeugen in der Regel bei weitem nicht ausgeschöpft. Das in diesem Artikelvorgestellte Rahmenmodell für Softwareentwicklung wurde explizit im Hinblick auf die globaleKooperation von Entwicklern entworfen. WebMake, eine auf diesem Modell basierende Software-entwicklungsumgebung, adressiert das Ziel seiner Einsetzbarkeit im globalen Maßstab durch dieVerwendung des World-Wide Web als Datenspeicherungs- und Kommunikationsinfrastruktur.
Edit distances between merge trees of scalar fields have many applications in scientific visualization, such as ensemble analysis, feature tracking or symmetry detection. In this paper, we propose branch mappings, a novel approach to the construction of edit mappings for merge trees. Classic edit mappings match nodes or edges of two trees onto each other, and therefore have to either rely on branch decompositions of both trees or have to use auxiliary node properties to determine a matching. In contrast, branch mappings employ branch properties instead of node similarity information, and are independent of predetermined branch decompositions. Especially for topological features, which are typically based on branch properties, this allows a more intuitive distance measure which is also less susceptible to instabilities from small-scale perturbations. For trees with 𝒪(n) nodes, we describe an 𝒪(n4) algorithm for computing optimal branch mappings, which is faster than the only other branch decomposition-independent method in the literature by more than a linear factor. Furthermore, we compare the results of our method on synthetic and real-world examples to demonstrate its practicality and utility.
As global networks are being used by more and more people,they are becoming increasingly interesting for commercial appli-cations. The recent success and change in direction of the World-Wide Web is a clear indication for this. However, this success meta largely unprepared communications infrastructure. The Inter-net as an originally non-profit network did neither offer the secu-rity, nor the globally available accounting infrastructure byitself.These problems were addressed in the recent past, but in aseemingly ad-hoc manner. Several different accounting schemessensible for only certain types of commercial transactions havebeen developed, which either seem to neglect the problems ofscalability, or trade security for efficiency. Finally, some propos-als aim at achieving near perfect security at the expense of effi-ciency, thus rendering those systems to be of no practical use.In contrast, this paper presents a suitably configurable schemefor accounting in a general, widely distributed client/server envi-ronment. When developing the protocol presented in this paper,special attention has been paid to make this approach work wellin the future setting of high-bandwidth, high-latency internets.The developed protocol has been applied to a large-scale distrib-uted application, a WWW-based software development environ-ment.
Abstraction is one of the most promising approaches to improve the performance of problem solvers. In several domains abstraction by dropping sentences of a domain description - as used in most hierarchical planners - has proven useful. In this paper we present examples which illustrate significant drawbacks of abstraction by dropping sentences. To overcome these drawbacks, we propose a more general view of abstraction involving the change of representation language. We have developed a new abstraction methodology and a related sound and complete learning algorithm that allows the complete change of representation language of planning cases from concrete to abstract. However, to achieve a powerful change of the representation language, the abstract language itself as well as rules which describe admissible ways of abstracting states must be provided in the domain model. This new abstraction approach is the core of PARIS (Plan Abstraction and Refinement in an Integrated System), a system in which abstract planning cases are automatically learned from given concrete cases. An empirical study in the domain of process planning in mechanical engineering shows significant advantages of the proposed reasoning from abstract cases over classical hierarchical planning.^
Undocumented enterprise data can easily pile up in companies in form of datasets and personal information. In absence of a data management strategy, such data becomes rather messy and may not fit for its intended use. Since there is often no documentation available, only a limited number of domain experts are aware of its contents. Therefore, for companies it becomes increasingly difficult to use such data to its full potential. To provide a solution, this PhD thesis investigates the construction of enterprise and personal knowledge graphs by semantically enriching messy data with meaning using semantic technologies. Since real world entities and their interrelations are organized in a graph, knowledge graphs serve as a semantic bridge between domain conceptualization and raw data. Spreadsheets are a prominent example of such enterprise data, since they are widely used by knowledge workers in the industrial sector. Two distinct approaches are investigated to construct knowledge graphs from them: a global extraction & annotation method and a local mapping technique. The latter is further complemented with a predictor of mapping rules on messy data. Different human-in-the-loop strategies are considered to include experts depending on their user group. Since non-technical users usually lack understanding of semantic technologies, they need appropriate tools to be able to give feedback. In case of developers, approaches are proposed to close the technology gap between industry and Semantic Web related concepts. Semantic Web practitioners participate with ontology modeling and linked data applications. Enterprise and personal data is typically confidential which is why it cannot be shared with a research community to discuss its challenges. However, for evaluation and reproducibility reasons publicly available datasets are mandatory. The thesis proposes ways to generate synthetic datasets with the goal to be as authentic as possible. Besides that, for internal evaluations a crawler of personal data on desktops is implemented. There are further contributions related to this thesis in diverse domains. One is about the motivation to support users in their daily work using personal knowledge assistants. Others are the agricultural field and the data science domain which also benefit from knowledge graph approaches. In conclusion, this PhD thesis contributes to the construction of knowledge graphs from especially messy enterprise data, while users from different groups take part in this process in various ways.
In recent years, deep learning has made substantial improvements in various fields like image understanding, Natural Language Processing (NLP), etc. These huge advancements have led to the release of many commercial applications which aim to help users carry out their daily tasks. Personal digital assistants are one such successful application of NLP, having a diverse userbase from all age groups. NLP tasks like Natural Language Understanding (NLU) and Natural Language Generation (NLG) are core components for building these assistants. However, like any other deep learning model, the growth of NLU & NLG models is directly coupled with tremendous amounts of training examples, which are expensive to collect due to annotator costs. Therefore, this work investigates the methodologies to build NLU and NLG systems in a data-constrained setting.
We evaluate the problem of limited training data in multiple scenarios like limited or no data available when building a new system, availability of a few labeled examples when adding a new feature to an existing system, and changes in the distribution of test data during the lifetime of a deployed system.
Motivated by the standard methods to handle data-constrained settings, we propose novel approaches to generate data and exploit latent representations to overcome performance drops emerging from limited training data.We propose a framework to generate high-quality synthetic data when few training examples are available for a newly added feature for dialogue agents. Our interpretation-to-text model uses existing training data for bootstrapping new features and improves the accuracy of downstream tasks of intent classification and slot labeling. Following, we study a few-shot setting and observe that generation systems face a low semantic coverage problem. Hence, we present an unsupervised NLG algorithm that ensures that all relevant semantic information is present in the generated text.
We also study to see if we really need all training examples for learning a generalized model. We propose a data selection method that selects the most informative training examples to train Visual Question Answering (VQA) models without erosion of accuracy. We leverage the already available inter-annotator agreement and design a diagnostic tool, called (EaSe), that leverages the entropy and semantic similarity of answer patterns.
Finally, we discuss two empirical studies to understand the feature space of VQA models and show how language model pre-training and exploiting multimodal embedding space allows for building data constrained models ensuring minimal or no accuracy losses.
The composition of Bézier curves and tensor product Bézier surfaces, polynomial as well as rational, is applied to exactly and explicitely represent trim curves of tensor product Bézier surfaces. Trimming curves are assumed to be defined as Bézier curves in surface parameter domain. A Bézier spline approximation of lower polynomial degree is built up as weil which is based on the exact trim curve representation in coordinate space.
Die Verwendung von existierenden Planungsansätzen zur Lösung von realen Anwendungs- problemen führt meist schnell zur Erkenntnis, dass eine vorliegende Problemstellung im Prinzip zwar lösbar ist, der exponentiell anwachsende Suchraum jedoch nur die Behandlung relativ kleiner Aufgabenstellungen erlaubt. Beobachtet man jedoch menschliche Planungsexperten, so sind diese in der Lage bei komplexen Problemen den Suchraum durch Abstraktion und die Verwendung bekannter Fallbeispiele als Heuristiken, entscheident zu verkleinern und so auch für schwierige Aufgabenstellungen zu einer akzeptablen Lösung zu gelangen. In dieser Arbeit wollen wir am Beispiel der Arbeitsplanung ein System vorstellen, das Abstraktion und fallbasierte Techniken zur Steuerung des Inferenzprozesses eines nichtlinearen, hierarchischen Planungssystems einsetzt und so die Komplexität der zu lösenden Gesamtaufgabe reduziert.
This paper presents an iterative finite element (FE)–based method to calculate the gravity-free shape of nonrigid parts from
an optical measurement performed on a non-over-constrained fixture. Measuring these kinds of parts in a stress-free state
is almost impossible because deflections caused by their weight occur. To solve this problem, a simulation model of the
measurement is created using available methods of reverse engineering. Then, an iterative algorithm calculates the gravityfree
shape. The approach does not require a CAD model of the measured part, implying the whole part can be fully scanned.
The application of this method mainly addresses thin, unstable sheet metal parts, like those commonly used in the automotive
or aerospace industry. To show the performance of the proposed method, validations with simulation and experimental
data are presented. The shown results meet the predefined quality goal to predict shapes within a tolerance of ±0.05 mm
measured in surface normal direction.
We study deterministic conditional rewrite systems, i.e. conditional rewrite systemswhere the extra variables are not totally free but 'input bounded'. If such a systemR is quasi-reductive then !R is decidable and terminating. We develop a critical paircriterion to prove confluence if R is quasi-reductive and strongly deterministic. In thiscase we prove that R is logical, i.e./!R==R holds. We apply our results to proveHorn clause programs to be uniquely terminating.This research was supported by the Deutsche Forschungsgemeinschaft, SFB 314, Project D4
Im Rahmen dieser Arbeit beschreiben wir die wesentlichen Merkmale der CAPlan-Architektur, die die interaktive Bearbeitung von Planungsproblemen ermöglichen. Anhand des SNLP-Algorithmus, der der Architektur zugrunde liegt, werden die im Laufe eines Planungsprozesses auftretenden Entscheidungspunkte charakterisiert. Mit Hilfe von frei definierbaren Kontrollkomponenten kann das Verhalten an diesen Entscheidungspunkte festgelegt werden, wodurch eine flexible Steuerung des Planungsprozesses ermöglicht wird. Planungsziele und -entscheidungen werden in einem gerichteten azyklischen Graphen verwaltet, der ihre kausalen Abhängigkeiten widerspiegelt. Im Gegensatz zu einem Stack, der typischerweise zur Verwaltung von Entscheidungen eingesetzt wird, erlaubt die graphbasierte Repräsentation die flexible Rücknahme einer Entscheidung, ohne alle zeitlich danach getroffenen Entscheidungen ebenfalls zurücknehmen zu müssen.
Although today’s bipeds are capable of demonstrating impressive locomotion skills, in many aspects, there’s still a big gap compared to the capabilities observed in humans. Partially, this is due to the deployed control paradigms that are mostly based on analytical approaches. The analytical nature of those approaches entails strong model dependencies – regarding the robotic platform as well as the environment – which makes them prone to unknown disturbances. Recently, an increasing number of biologically-inspired control approaches have been presented from which a human-like bipedal gait emerges. Although the control structures only rely on proprioceptive sensory information, the smoothness of the motions and the robustness against external disturbances is impressive. Due to the lack of suitable robotic platforms, until today the controllers have been mostly applied to
simulations.
Therefore, as the first step towards a suitable platform, this thesis presents the Compliant Robotic Leg (CARL) that features mono- as well as biarticular actuation. The design is driven by a set of core-requirements that is primarily derived from the biologically-inspired behavior-based bipedal locomotion control (B4LC) and complemented by further functional aspects from biomechanical research. Throughout the design process, CARL is understood as a unified dynamic system that emerges from the interplay of the mechanics, the electronics, and the control. Thus, having an explicit control approach and the respective gait in mind, the influence of each subsystem on the characteristics of the overall system is considered
carefully.
The result is a planar robotic leg whose three joints are driven by five highly integrated linear SEAs– three mono- and two biarticular actuators – with minimized reflected inertia. The SEAs are encapsulated by FPGA-based embedded nodes that are designed to meet the hard application requirements while enabling the deployment of a full-featured robotic framework. CARL’s foot is implemented using a COTS prosthetic foot; the sensor information is obtained from the deformation of its main structure. Both subsystems are integrated into a leg structure that matches the proportions of a human with a size of 1.7 m.
The functionality of the subsystems, as well as the overall system, is validated experimentally. In particular, the final experiment demonstrates a coordinated walking motion and thereby confirms that CARL can produce the desired behavior – a natural looking, human-like gait is emerging from the interplay of the behavior-based walking control and the mechatronic system. CARL is robust regarding impacts, the redundant actuation system can render the desired joint torques/impedances, and the foot system supports the walking structurally while it provides the necessary sensory information. Considering that there is no movement of the upper trunk, the angle and torque profiles are comparable to the ones found in humans.
It is generally agreed that one of the most challenging issues facing the case-based reasoning community is that of adaptation. To date the lion's share of CBR research has concentrated on the retrieval of similar cases, and the result is a wide range of quality retrieval techniques. However, retrieval is just the first part of the CBR equation, because once a similar case has been retrieved it must be adapted. Adaptation research is still in its earliest stages, and researchers are still trying to properly understand and formulate the important issues. In this paper I describe a treatment of adaptation in the context of a case-based reasoning system for software design, called Deja Vu. Deja Vu is particularly interesting, not only because it performs automatic adaptation of retrieved cases, but also because it uses a variety of techniques to try and reduce and predict the degree of adaptation necessary.
Contrary to symbolic learning approaches, that represent a learned concept explicitly, case-based approaches describe concepts implicitly by a pair (CB; sim), i.e. by a measure of similarity sim and a set CB of cases. This poses the question if there are any differences concerning the learning power of the two approaches. In this article we will study the relationship between the case base, the measure of similarity, and the target concept of the learning process. To do so, we transform a simple symbolic learning algorithm (the version space algorithm) into an equivalent case-based variant. The achieved results strengthen the hypothesis of the equivalence of the learning power of symbolic and casebased methods and show the interdependency between the measure used by a case-based algorithm and the target concept.
Case-based knowledge acquisition, learning and problem solving for diagnostic real world tasks
(1999)
Within this paper we focus on both the solution of real, complex problems using expert system technology and the acquisition of the necessary knowledge from a case-based reasoning point of view. The development of systems which can be applied to real world problems has to meet certain requirements. E.g., all available information sources have to be identified and utilized. Normally, this involves different types of knowledge for which several knowledge representation schemes are needed, because no scheme is equally natural for all sources. Facing empirical knowledge it is important to complement the use of manually compiled, statistic and otherwise induced knowledge by the exploitation of the intuitive understandability of case-based mechanisms. Thus, an integration of case-based and alternative knowledge acquisition and problem solving mechanisms is necessary. For this, the basis is to define the "role" which case-based inference can "play" within a knowledge acquisition workbench. We will discuss a concrete casebased architecture, which has been applied to technical diagnosis problems, and its integration into a knowledge acquisition workbench which includes compiled knowledge and explicit deep models, additionally.
Planning means constructing a course of actions to achieve a specified set of goals when starting from an initial situation. For example, determining a sequence of actions (a plan) for transporting goods from an initial location to some destination is a typical planning problem in the transportation domain. Many planning problems are of practical interest.
Case-Based Reasoning for Decision Support and Diagnostic Problem Solving: The INRECA Approach
(1995)
INRECA offers tools and methods for developing, validating, and maintaining decision support systems. INRECA's basic technologies are inductive and case-based reasoning, namely KATE -INDUCTION (cf., e.g., Manago, 1989; Manago, 1990) and S3-CASE, a software product based on PATDEX (cf., e.g., Wess,1991; Richter & Wess, 1991; Althoff & Wess, 1991). Induction extracts decision knowledge from case databases. It brings to light patterns among cases and helps monitoring trends over time. Case-based rea -soning relates the engineer's current problem to past experiences.
A translation contract is a binary predicate corrTransl(S,T) for source programs S and target programs T. It precisely specifies when T is considered to be a correct translation of S. A certifying compiler generates --in addittion to the target T-- a proof for corrTransl(S,T). Certifying compilers are important for the development of safety critical systems to establish the behavioral equivalence of high-level programs with their compiled assembler code. In this paper, we report on a certifying compiler, its proof techniques, and the underlying formal framework developed within the proof assistent Isabelle/HOL. The compiler uses a tiny C-like language as input, has an optimization phase, and generates MIPS code. The underlying translation contract is based on a trace semantics. We investigate design alternatives and discuss our experiences.
Recent progresses and advances in the field of consumer electronics, driven by display
technologies and also the sector of mobile, hand-held devices, enable new ways in
presenting information to users, as well as new ways of user interaction, therefore
providing a basis for user-centered applications and work environments.
My thesis focuses on how arbitrary display environments can be utilized to improve
both the user experience, regarding perception of information, and also to provide
intuitive interaction possibilities. On the one hand advances in display technologies
provide the basis for new ways of visualizing content and collaborative work, on the
other hand forward-pressing developments in the consumer market, especially the
market of smart phones, offer potential to enhance usability in terms of interaction
and therefore can provide additional benefit for users.
Tiled display setups, combining both large screen real estate and high resolution,
provide new possibilities and chances to visualize large datasets and to facilitate col-
laboration in front of a large screen area. Furthermore these display setups present
several advantages over the traditional single-user-workspace environments: con-
trary to single-user-workspaces, multiple users are able to explore a dataset displayed
on a tiled display system, at the same time, thus allowing new forms of collabora-
tive work. Based on that, face-to-face discussions are enabled, an additional value
is added. Large displays also allow the utilization of the user’s spatial memory, al-
lowing physical navigation without the need of switching between different windows
to explore information.
With Tiled++ I contributed a versatile approach to address the bezel problem. The
bezel problem is one of the Top Ten research challenges in the research field of LCD-
based tiled wall setups. By applying the Tiled++ approach a large high resolution
Focus & Context screen is created, combining high resolution focus areas with low
resolution context information, projected onto the bezel area.
Additionally the field of user interaction poses an important challenge, especially
regarding the utilization of large tiled displays, since traditional keyboard & mouse
interaction devices reached their limits. My focus in this thesis is on Mobile HCI.Devices like mobile phones are utilized to interact with large displays, since they
feature various interaction modalities and preserve user mobility.
Large public displays, as a modernized form of traditional bulletin boards, also en-
able new ways of handling information, displaying content, and user interaction.
Utilized in hot spots, Digital Interactive Public Pinboards can provide an adequate
answer to questions like how to approach pressing issues like disaster and crisis man-
agement for both responders as well as citizens and also new ways of how to handle
information flow (contribution & distribution & accession). My contribution to the
research field of public display environments was the conception and implementa-
tion of an easy-to-use and easy-to-set-up architecture to overcome shortcomings of
current approaches and to cover the needs of aid personnel.
Although being a niche, Virtual Reality (VR) environments can provide additional
value for visualizing specific content. Disciplines like earth sciences & geology, me-
chanical engineering, design, and architecture can benefit from VR environments. In
order to consider the variety of users, I introduce a more intuitive and user friendly
interaction metaphor, the ARC metaphor.
Visualization challenges base on being able to cope with more and more complex
datasets and to bridge the gap between comprehensibility and loss of information.
Furthermore the visualization approach has to be reasonable, which is a crucial
factor when working in interdisciplinary teams, where the standard of knowledge
is diverse. Users have to be able to conceive the visualized content in a fast and
reliable way. My contribution are visualization approaches in the field of supportive
visualization.
Finally, my work illuminates how the synthesis of visualization, interaction and dis-
play technologies enhance the user experience. I promote a holistic view. The user
is brought back into the focus of attention, provided with a tool-set to support him,
without overextending the abilities of, for example, non-expert users, a crucial factor
in the more and more interdisciplinary field of computer science.
Constructing an analogy between a known and already proven theorem(the base case) and another yet to be proven theorem (the target case) oftenamounts to finding the appropriate representation at which the base and thetarget are similar. This is a well-known fact in mathematics, and it was cor-roborated by our empirical study of a mathematical textbook, which showedthat a reformulation of the representation of a theorem and its proof is in-deed more often than not a necessary prerequisite for an analogical inference.Thus machine supported reformulation becomes an important component ofautomated analogy-driven theorem proving too.The reformulation component proposed in this paper is embedded into aproof plan methodology based on methods and meta-methods, where the latterare used to change and appropriately adapt the methods. A theorem and itsproof are both represented as a method and then reformulated by the set ofmetamethods presented in this paper.Our approach supports analogy-driven theorem proving at various levels ofabstraction and in principle makes it independent of the given and often acci-dental representation of the given theorems. Different methods can representfully instantiated proofs, subproofs, or general proof methods, and hence ourapproach also supports these three kinds of analogy respectively. By attachingappropriate justifications to meta-methods the analogical inference can oftenbe justified in the sense of Russell.This paper presents a model of analogy-driven proof plan construction andfocuses on empirically extracted meta-methods. It classifies and formally de-scribes these meta-methods and shows how to use them for an appropriatereformulation in automated analogy-driven theorem proving.
The background of this paper is the area of case-based reasoning. This is a reasoning technique where one tries to use the solution of some problem which has been solved earlier in order to obta in a solution of a given problem. As example of types of problems where this kind of reasoning occurs very often is the diagnosis of diseases or faults in technical systems. In abstract terms this reduces to a classification task. A difficulty arises when one has not just one solved problem but when there are very many. These are called "cases" and they are stored in the case-base. Then one has to select an appropriate case which means to find one which is "similar" to the actual problem. The notion of similarity has raised much interest in this context. We will first introduce a mathematical framework and define some basic concepts. Then we will study some abstract phenomena in this area and finally present some methods developed and realized in a system at the University of Kaiserslautern.
An huge amount of computational models and programming languages have been proposed
for the description of embedded systems. In contrast to traditional sequential programming
languages, they cope directly with the requirements for embedded systems: direct support for
concurrent computations and periodic interaction with the environment are only some of the
features they offer. Synchronous languages are one class of languages for the development of
embedded systems and they follow the fundamental principle that the execution is divided into
a sequence of logical steps. Thereby, each step follows the simplification that the computation
of the outputs is finished directly when the inputs are available. This rigorous abstraction leads
to well-defined deterministic parallel composition in general, and to deterministic abortion
and suspension in imperative synchronous languages in particular. These key features also
allow to translate programs to hardware and software, and also formal verification techniques
like model checking can be easily applied.
Besides the advantages of imperative synchronous languages, also some drawbacks can
be listed. Over-synchronization is an effect being caused by parallel threads which have to
synchronize for each execution step, even if they do not communicate, since the synchronization
is implicitly forced by the control-flow. This thesis considers the idea of clock refinement to
introduce several abstraction layers for communication and synchronization in addition to the
existing single-clock abstraction. Thereby, clocks can be refined by several independent clocks
so that a controlled amount of asynchrony between subsequent synchronization points can be
exploited by compilers. The declarations of clocks form a tree, and clocks can be defined within
the threads of the parallel statement, which allows one to do independent computations based
on these clocks without synchronizing the threads. However, the synchronous abstraction is
kept at each level of the abstraction.
Clock refinement is introduced in this thesis as an extension to the imperative synchronous
language Quartz. Therefore, new program statements are introduced which allow to define
a new clock as a refinement of an existing one and to finish a step based on a certain clock.
Examples are considered to show the impact of the behavior of the new statements to
the already existing statements, before the semantics of this extension is formally defined.
Furthermore, the thesis presents a compile algorithm to translate programs to an intermediate
format, and to translate the intermediate format to a hardware description. The advantages
obtained by the new modeling feature are finally evaluated based on examples.
Scaling up conventional processor architectures cannot translate the ever-increasing number of transistors into comparable application performance. Although the trend is to shift from single-core to multi-core architectures, utilizing these multiple cores is not a trivial task for many applications due to thread synchronization and weak memory consistency issues. This is especially true for applications in real-time embedded systems since timing analysis becomes more complicated due to contention on shared resources. One inherent reason for the limited use of instruction-level parallelism (ILP) by conventional processors is the use of registers. Therefore, some recent processors bypass register usage by directly communicating values from producer processing units to consumer processing units. In widely used superscalar processors, this direct instruction communication is organized by hardware at runtime, adversely affecting its scalability. The exposed datapath architectures provide a scalable alternative by allowing compilers to move values directly from output ports to the input ports of processing units. Though exposed datapath architectures have already been studied in great detail, they still use registers for executing programs, thus limiting the amount of ILP they can exploit. This limitation stems from a drawback in their execution paradigm, code generator, or both.
This thesis considers a novel exposed datapath architecture named Synchronous Control Asynchronous Dataflow (SCAD) that follows a hybrid control-flow dataflow execution paradigm. The SCAD architecture employs first-in-first-out (FIFO) buffers at the output and input ports of processing units. It is programmed by move instructions that transport values from the head of output buffers to the tail of input buffers. Thus, direct instruction communication is facilitated by the architecture. The processing unit triggers the execution of an operation when operand values are available at the heads of its input buffers. We propose a code generation technique for SCAD processors inspired by classical queue machines that completely eliminates the use of registers. On this basis, we first generate optimal code by using satisfiability (SAT) solvers after establishing that optimal code generation is hard. Heuristics based on a novel buffer interference analysis are then developed to compile larger programs. The experimental results demonstrate the efficacy of the execution paradigm of SCAD using our queue-oriented code generation technique.
Collecting Experience on the Systematic Development of CBR Applications using the INRECA Methodology
(1999)
This paper presents an overview of the INRECA methodology for building and maintaining CBR applications. This methodology supports the collection and reuse of experience on the systematic development of CBR applications. It is based on the experience factory and the software process modeling approach from software engineering. CBR development experience is documented using software process models and stored in different levels of generality in a three-layered experience base. Up to now, experience from 9 industrial projects enacted by all INRECA II partners has been collected.
Software development is becoming a more and more distributed process, which urgently needs supporting tools in the field of configuration management, software process/w orkflow management, communication and problem tracking. In this paper we present a new distributed software configuration management framework COMAND. It offers high availabilit y through replication and a mechanism to easily change and adapt the project structure to new business needs. To better understand and formally prove some properties of COMAND, we have modeled it in a formal technique based on distributed graph transformations. This formalism provides an intuitive rule-based description technique mainly for the dynamic behavior of the system on an abstract level. We use it here to model the replication subsystem.
In most cases in a safety analysis the influences of security problems are omitted or even forgotten. Because more and more systems are accessible from outside the system via maintenance interfaces, this missing security analysis is becoming a problem. This is why we propose an approach on how to extend the safety analysis by security aspects. Such a more comprehensive analysis should lead to systems that react in less catastrophic ways to attacks.
Large-scale distributed systems consist of a number of components, take a number of parameter values as input, and behave differently based on a number of non-deterministic events. All these features—components, parameter values, and events—interact in complicated ways, and unanticipated interactions may lead to bugs. Empirically, many bugs in these systems are caused by interactions of only a small number of features. In certain cases, it may be possible to test all interactions of \(k\) features for a small constant \(k\) by executing a family of tests that is exponentially or even doubly-exponentially smaller than the family of all tests. Thus, in such cases we can effectively uncover all bugs that require up to \(k\)-wise interactions of features.
In this thesis we study two occurrences of this phenomenon. First, many bugs in distributed systems are caused by network partition faults. In most cases these bugs occur due to two or three key nodes, such as leaders or replicas, not being able to communicate, or because the leading node finds itself in a block of the partition without quorum. Second, bugs may occur due to unexpected schedules (interleavings) of concurrent events—concurrent exchange of messages and concurrent access to shared resources. Again, many bugs depend only on the relative ordering of a small number of events. We call the smallest number of events whose ordering causes a bug the depth of the bug. We show that in both testing scenarios we can effectively uncover bugs involving small number of nodes or bugs of small depth by executing small families of tests.
We phrase both testing scenarios in terms of an abstract framework of tests, testing goals, and goal coverage. Sets of tests that cover all testing goals are called covering families. We give a general construction that shows that whenever a random test covers a fixed goal with sufficiently high probability, a small randomly chosen set of tests is a covering family with high probability. We then introduce concrete coverage notions relating to network partition faults and bugs of small depth. In case of network partition faults, we show that for the introduced coverage notions we can find a lower bound on the probability that a random test covers a given goal. Our general construction then yields a randomized testing procedure that achieves full coverage—and hence, find bugs—quickly.
In case of coverage notions related to bugs of small depth, if the events in the program form a non-trivial partial order, our general construction may give a suboptimal bound. Thus, we study other ways of constructing covering families. We show that if the events in a concurrent program are partially ordered as a tree, we can explicitly construct a covering family of small size: for balanced trees, our construction is polylogarithmic in the number of events. For the case when the partial order of events does not have a "nice" structure, and the events and their relation to previous events are revealed while the program is running, we give an online construction of covering families. Based on the construction, we develop a randomized scheduler called PCTCP that uniformly samples schedules from a covering family and has a rigorous guarantee of finding bugs of small depth. We experiment with an implementation of PCTCP on two real-world distributed systems—Zookeeper and Cassandra—and show that it can effectively find bugs.
A combination of a state-based formalism and a temporal logic is proposed to get an expressive language for various descriptions of reactive systems. Thereby it is possible to use a model as well as a property oriented specification style in one description. The descriptions considered here are those of the environment, the specification, and the design of a reactive system. It is possible to express e.g. the requirements of a reactive system by states and transitions between them together with further temporal formulas restricting the behaviors of the statecharts. It is shown, how this combined formalism can be used: The specification of a small example is given and a designed controller is proven correct with respect to this specification. The combination of the langugages is based on giving a temporal semantics of a state-based formalism (statecharts) using a temporal logic (TLA).
Real world planning tasks like manufacturing process planning often don't allow to formalize all of the relevant knowledge. Especially, preferences between alternatives are hard to acquire but have high influence on the efficiency of the planning process and the quality of the solution. We describe the essential features of the CAPlan planning architecture that supports cooperative problem solving to narrow the gap caused by absent preference and control knowledge. The architecture combines an SNLP-like base planner with mechanisms for explict representation and maintenance of dependencies between planning decisions. The flexible control interface of CAPlan allows a combination of autonomous and interactive planning in which a user can participate in the problem solving process. Especially, the rejection of arbitrary decisions by a user or dependency-directed backtracking mechanisms are supported by CAPlan.
Comparative Uncertainty Visualization for High-Level Analysis of Scalar- and Vector-Valued Ensembles
(2022)
With this thesis, I contribute to the research field of uncertainty visualization, considering parameter dependencies in multi valued fields and the uncertainty of automated data analysis. Like uncertainty visualization in general, both of these fields are becoming more and more important due to increasing computational power, growing importance and availability of complex models and collected data, and progress in artificial intelligence. I contribute in the following application areas:
Uncertain Topology of Scalar Field Ensembles.
The generalization of topology-based visualizations to multi valued data involves many challenges. An example is the comparative visualization of multiple contour trees, complicated by the random nature of prevalent contour tree layout algorithms. I present a novel approach for the comparative visualization of contour trees - the Fuzzy Contour Tree.
Uncertain Topological Features in Time-Dependent Scalar Fields.
Tracking features in time-dependent scalar fields is an active field of research, where most approaches rely on the comparison of consecutive time steps. I created a more holistic visualization for time-varying scalar field topology by adapting Fuzzy Contour Trees to the time-dependent setting.
Uncertain Trajectories in Vector Field Ensembles.
Visitation maps are an intuitive and well-known visualization of uncertain trajectories in vector field ensembles. For large ensembles, visitation maps are not applicable, or only with extensive time requirements. I developed Visitation Graphs, a new representation and data reduction method for vector field ensembles that can be calculated in situ and is an optimal basis for the efficient generation of visitation maps. This is accomplished by bringing forward calculation times to the pre-processing.
Visually Supported Anomaly Detection in Cyber Security.
Numerous cyber attacks and the increasing complexity of networks and their protection necessitate the application of automated data analysis in cyber security. Due to uncertainty in automated anomaly detection, the results need to be communicated to analysts to ensure appropriate reactions. I introduce a visualization system combining device readings and anomaly detection results: the Security in Process System. To further support analysts I developed an application agnostic framework that supports the integration of knowledge assistance and applied it to the Security in Process System. I present this Knowledge Rocks Framework, its application and the results of evaluations for both, the original and the knowledge assisted Security in Process System. For all presented systems, I provide implementation details, illustrations and applications.
Complete Eager Replay
(1996)
We present an algorithm for completely replaying previous problem solving experiences for plan-space planners. In our approach not only the solution trace is replayed, but also the explanations of failed attempts made by the first-principle planner. In this way, the capability of refitting previous solutions into new problems is improved.
We present an approach to prove several theorems in slightly different axiomsystems simultaneously. We represent the different problems as a taxonomy, i.e.a tree in which each node inherits all knowledge of its predecessors, and solve theproblems using inference steps on rules and equations with simple constraints,i.e. words identifying nodes in the taxonomy. We demonstrate that a substantialgain can be achieved by using taxonomic constraints, not only by avoiding therepetition of inference steps in the different problems but also by achieving runtimes that are much shorter than the accumulated run times when proving eachproblem separately.
We study the complexity of local solution of Fredholm integral equations. This means that we want to compute not the full solution, but rather a functional (weighted mean, value in a point) of it. For certain Sobolev classes of multivariate periodic functions we prove matching upper and lower bounds and construct an algorithm of the optimal order, based on Fourier coefficients and a hyperbolic cross approximation.
In this paper the complexity of the local solution of Fredholm integral equations
is studied. For certain Sobolev classes of multivariate periodic functions with dominating mixed derivative we prove matching lower and upper bounds. The lower bound is shown using relations to s-numbers. The upper bound is proved in a constructive way providing an implementable algorithm of optimal order based on Fourier coefficients and a hyperbolic cross approximation.