Kaiserslautern - Fachbereich Informatik
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Faculty / Organisational entity
Die Sichten von Projektmitgliedern auf Prozesse von Software-Entwicklungen sollen in der Prozeßmodellierungssprache MVP-L formuliert und anschließend in ein Umfassendes Prozeßmodell integriert werden. Dabei ist die Identifikation ähnlicher Informationen in verschiedenen Sichten von Bedeutung. In dieser Arbeit berichten
wir über die Adaption und Synthese verschiedener Ansätze zum Thema Ähnlichkeit aus unterschiedlichen Domänen (Schema-Integration beim Datenbank-Entwurf, Analoges und Fallbasiertes Schließen, Wiederverwendung und System-Spezifikation). Das Ergebnis, die Ähnlichkeitsfunktion vsim, wird anhand eines Referenzbeispiels illustriert. Dabei gehen wir insbesondere auf die Eigenschaft der Funktion vsim ein und berichten über Erfahrungen im Umgang mit dieser Funktion zur Berechnung der Ähnlichkeit zwischen Prozeßmodellen.
In der aktuellen technologischen Entwicklung spielen verteilte eingebettete Echtzeitsysteme eine immer zentralere Rolle und werden zunehmend zum Träger von Innovationen. Durch den hiermit verbundenen steigenden Funktionsumfang der verteilten Echtzeitsysteme und deren zunehmenden Einsatz in sicherheitsrelevanten Anwendungsgebieten stellt die Entwicklung solcher Systeme eine immer größere Herausforderung dar. Hierbei handelt es sich einerseits um Herausforderungen bezogen auf die Kommunikation hinsichtlich Echtzeitfähigkeit und effizienter Bandbreitennutzung, andererseits werden geeignete Methoden benötigt, um den Entwicklungsprozess solcher komplexen Systeme durch Tests und Evaluationen zu unterstützen und zu begleiten. Die hier vorgestellte Arbeit adressiert diese beiden Aspekte und ist entsprechend in zwei Teile untergliedert.
Der erste Teil der Arbeit beschäftigt sich mit der Entwicklung neuer Kommunikationslösungen, um den gestiegenen Kommunikationsanforderungen begegnen zu können. So erfordert die Nutzung verteilter Echtzeitsysteme im Kontext sicherheitsrelevanter Aufgaben den Einsatz zeitgetriggerter Kommunikationssysteme, die in der Lage sind, deterministische Garantien bezüglich der Echtzeitfähigkeit zu gewähren. Diese klassischen auf exklusiven Reservierungen basierenden Ansätze sind jedoch gerade bei (seltenen) sporadischen Nachrichten sehr ineffizient in Bezug auf die Nutzung der Bandbreite.
Das in dieser Arbeit verwendete Mode-Based Scheduling with Fast Mode-Signaling (modusbasierte Kommunikation) ist ein Verfahren zur Verbesserung der Bandbreitennutzung zeitgetriggerter Kommunikation, bei gleichzeitiger Gewährleistung der Echtzeitfähigkeit. Um dies zu ermöglichen, erlaubt Mode-Based Scheduling einen kontrollierten, slotbasierten Wettbewerb, welcher durch eine schnelle Modussignalisierung (Fast Mode-Signaling) aufgelöst wird. Im Zuge dieser Arbeit werden verschiedene robuste, zuverlässige und vor allem deterministische Realisierungen von Mode-Based Scheduling with Fast Mode-Signaling auf Basis existierender drahtgebundener Kommunikationsprotokolle (TTCAN und FlexRay) vorgestellt sowie Konzepte präsentiert, welche eine einfache Integration in weitere Kommunikationstechnologien (wie drahtlose Ad-Hoc-Netze) ermöglichen.
Der zweite Teil der Arbeit konzentriert sich nicht nur auf Kommunikationsaspekte, sondern stellt einen Ansatz vor, den Entwicklungsprozess verteilter eingebetteter Echtzeitsysteme durch kontinuierliche Tests und Evaluationen in allen Entwicklungsphasen zu unterstützen und zu begleiten. Das im Kontext des Innovationszentrums für Applied Systems Modeling mitentwickelte und erweiterte FERAL (ein Framework für die Kopplung spezialisierter Simulatoren) bietet eine ideale Ausgangsbasis für das Virtual Prototyping komplexer verteilter eingebetteter Echtzeitsysteme und ermöglicht Tests und Evaluationen der Systeme in einer realistisch simulierten Umgebung. Die entwickelten Simulatoren für aktuelle Kommunikationstechnologien ermöglichen hierbei realistische Simulationen der Interaktionen innerhalb des verteilten Systems. Durch die Unterstützung von Simulationssystemen mit Komponenten auf unterschiedlichen Abstraktionsstufen kann FERAL in allen Entwicklungsphasen eingesetzt werden. Anhand einer Fallstudie wird gezeigt, wie FERAL verwendet werden kann, um ein Simulationssystem zusammen mit den zu realisierenden Komponenten schrittweise zu verfeinern. Auf diese Weise steht während jeder Entwicklungsphase ein ausführbares Simulationssystem für Tests zur Verfügung. Die entwickelten Konzepte und Simulatoren für FERAL ermöglichen es, Designalternativen zu evaluieren und die Wahl einer Kommunikationstechnologie durch die Ergebnisse von Simulationen zu stützen.
Das Thema dieser Arbeit ist die Erweiterung von CoMo-Kit um eine Zeitplanungskomponente. Man möchte Informationen über die Dauer der einzelnen Teilaufgaben gewinnen und diese zu Dauern der übergeordneten abstrakten Aufgaben abschätzen. Auf diese Weise kann sich ein Manager über die voraussichtliche Gesamtdauer des Projektes und dessen Fortgang informieren. Dazu werden frühestmögliche und spätestmögliche Anfangs- und Endzeitpunkte der Vorgänge berechnet. Die Differenz zwischen frühesten und spätesten Zeitpunkten gibt dem Projektmanager eine Aussage über den Dispositionsspielraum der einzelnen Vorgänge. Ist kein Spielraum vorhanden, kann man erkennen, daß dieser Vorgang die Projektdauer determiniert und eventuell für Verzögerungen verantwortlich sein kann. Im Rahmen dieser Diplomarbeit ist das Verfahren der Allgemeine Hierarchischen Netzplantechnik entwickelt und als Zeitplanungskomponente in das System CoMo-Kit integriert worden.
We present a convenient notation for positive/negativeADconditional equations. Theidea is to merge rules specifying the same function by using caseAD, ifAD, matchAD, and letADexpressions.Based on the presented macroADruleADconstruct, positive/negativeADconditional equational specifiADcations can be written on a higher level. A rewrite system translates the macroADruleADconstructsinto positive/negativeADconditional equations.
Distributed systems are omnipresent nowadays and networking them is fundamental for the continuous dissemination and thus availability of data. Provision of data in real-time is one of the most important non-functional aspects that safety-critical networks must guarantee. Formal verification of data communication against worst-case deadline requirements is key to certification of emerging x-by-wire systems. Verification allows aircraft to take off, cars to steer by wire, and safety-critical industrial facilities to operate. Therefore, different methodologies for worst-case modeling and analysis of real-time systems have been established. Among them is deterministic Network Calculus (NC), a versatile technique that is applicable across multiple domains such as packet switching, task scheduling, system on chip, software-defined networking, data center networking and network virtualization. NC is a methodology to derive deterministic bounds on two crucial performance metrics of communication systems:
(a) the end-to-end delay data flows experience and
(b) the buffer space required by a server to queue all incoming data.
NC has already seen application in the industry, for instance, basic results have been used to certify the backbone network of the Airbus A380 aircraft.
The NC methodology for worst-case performance analysis of distributed real-time systems consists of two branches. Both share the NC network model but diverge regarding their respective derivation of performance bounds, i.e., their analysis principle. NC was created as a deterministic system theory for queueing analysis and its operations were later cast in a (min,+)-algebraic framework. This branch is known as algebraic Network Calculus (algNC). While algNC can efficiently compute bounds on delay and backlog, the algebraic manipulations do not allow NC to attain the most accurate bounds achievable for the given network model. These tight performance bounds can only be attained with the other, newly established branch of NC, the optimization-based analysis (optNC). However, the only optNC analysis that can currently derive tight bounds was proven to be computationally infeasible even for the analysis of moderately sized networks other than simple sequences of servers.
This thesis makes various contributions in the area of algNC: accuracy within the existing framework is improved, distributivity of the sensor network calculus analysis is established, and most significantly the algNC is extended with optimization principles. They allow algNC to derive performance bounds that are competitive with optNC. Moreover, the computational efficiency of the new NC approach is improved such that this thesis presents the first NC analysis that is both accurate and computationally feasible at the same time. It allows NC to scale to larger, more complex systems that require formal verification of their real-time capabilities.
The Internet has fallen prey to its most successful service, the World-Wide Web. The networksdo not keep up with the demands incurred by the huge amount of Web surfers. Thus, it takeslonger and longer to obtain the information one wants to access via the World-Wide Web.Many solutions to the problem of network congestion have been developed in distributed sys-tems research in general and distributed file and database systems in particular. The introduc-tion of caching and replication strategies has proven to help in many situations and thereforethese techniques are also applied to the WWW. Although most problems and associated solu-tions are known, some circumstances are different with the Web, forcing the adaptation ofknown strategies. This paper gives an overview about these differences and about currentlydeployed, developed, and evaluated solutions.
We have developed a middleware framework for workgroup environments that can support distributed software development and a variety of other application domains requiring document management and change management for distributed projects. The framework enables hypermedia-based integration of arbitrary legacy and new information resources available via a range of protocols, not necessarily known in advance to us as the general framework developers nor even to the environment instance designers. The repositories in which such information resides may be dispersed across the Internet and/or an organizational intranet. The framework also permits a range of client models for user and tool interaction, and applies an extensible suite of collaboration services, including but not limited to multi-participant workflow and coordination, to their information retrievals and updates. That is, the framework is interposed between clients, services and repositories - thus "middleware". We explain how our framework makes it easy to realize a comprehensive collection of workgroup and workflow features we culled from a requirements survey conducted by NASA.
Crowd condition monitoring concerns the crowd safety and concerns business performance metrics. The research problem to be solved is a crowd condition estimation approach to enable and support the supervision of mass events by first-responders and marketing experts, but is also targeted towards supporting social scientists, journalists, historians, public relations experts, community leaders, and political researchers. Real-time insights of the crowd condition is desired for quick reactions and historic crowd conditions measurements are desired for profound post-event crowd condition analysis.
This thesis aims to provide a systematic understanding of different approaches for crowd condition estimation by relying on 2.4 GHz signals and its variation in crowds of people, proposes and categorizes possible sensing approaches, applies supervised machine learning algorithms, and demonstrates experimental evaluation results. I categorize four sensing approaches. Firstly, stationary sensors which are sensing crowd centric signals sources. Secondly, stationary sensors which are sensing other stationary signals sources (either opportunistic or special purpose signal sources). Thirdly, a few volunteers within the crowd equipped with sensors which are sensing other surrounding crowd centric device signals (either individually, in a single group or collaboratively) within a small region. Fourthly, a small subset of participants within the crowd equipped with sensors and roaming throughout a whole city to sense wireless crowd centric signals.
I present and evaluate an approach with meshed stationary sensors which were sensing crowd centric devices. This was demonstrated and empirically evaluated within an industrial project during three of the world-wide largest automotive exhibitions. With over 30 meshed stationary sensors in an optimized setup across 6400m2 I achieved a mean absolute error of the crowd density of just 0.0115
people per square meter which equals to an average of below 6% mean relative error from the ground truth. I validate the contextual crowd condition anomaly detection method during the visit of chancellor Mrs. Merkel and during a large press conference during the exhibition. I present the approach of opportunistically sensing stationary based wireless signal variations and validate this during the Hannover CeBIT exhibition with 80 opportunistic sources with a crowd condition estimation relative error of below 12% relying only on surrounding signals in influenced by humans. Pursuing this approach I present an approach with dedicated signal sources and sensors to estimate the condition of shared office environments. I demonstrate methods being viable to even detect low density static crowds, such as people sitting at their desks, and evaluate this on an eight person office scenario. I present the approach of mobile crowd density estimation by a group of sensors detecting other crowd centric devices in the proximity with a classification accuracy of the crowd density of 66 % (improvement of over 22% over a individual sensor) during the crowded Oktoberfest event. I propose a collaborative mobile sensing approach which makes the system more robust against variations that may result from the background of the people rather than the crowd condition with differential features taking information about the link structure between actively scanning devices, the ratio between values observed by different devices, ratio of discovered crowd devices over time, team-wise diversity of discovered devices, number of semi- continuous device visibility periods, and device visibility durations into account. I validate the approach on multiple experiments including the Kaiserslautern European soccer championship public viewing event and evaluated the collaborative mobile sensing approach with a crowd condition estimation accuracy of 77 % while outperforming previous methods by 21%. I present the feasibility of deploying the wireless crowd condition sensing approach to a citywide scale during an event in Zurich with 971 actively sensing participants and outperformed the reference method by 24% in average.
In recent years several computational systems and techniques fortheorem proving by analogy have been developed. The obvious prac-tical question, however, as to whether and when to use analogy hasbeen neglected badly in these developments. This paper addresses thisquestion, identifies situations where analogy is useful, and discussesthe merits of theorem proving by analogy in these situations. Theresults can be generalized to other domains.
In this paper we present the results of the project “#Datenspende” where during the German election in 2017 more than 4000 people contributed their search results regarding keywords connected to the German election campaign.
Analyzing the donated result lists we prove, that the room for personalization of the search results is very small. Thus the opportunity for the effect mentioned in Eli Pariser’s filter bubble theory to occur in this data is also very small, to a degree that it is negligible. We achieved these results by applying various similarity measures to the result lists that were donated. The first approach using the number of common results as a similarity measure showed that the space for personalization is less than two results out of ten on average when searching for persons and at most four regarding the search for parties. Application of other, more specific measures show that the space is indeed smaller, so that the presence of filter bubbles is not evident.
Moreover this project is also a proof of concept, as it enables society to permanently monitor a search engine’s degree of personalization for any desired search terms. The general design can also be transferred to intermediaries, if appropriate APIs restrict selective access to contents relevant to the study in order to establish a similar degree of trustworthiness.
Wearable activity recognition aims to identify and assess human activities with the help
of computer systems by evaluating signals of sensors which can be attached to the human
body. This provides us with valuable information in several areas: in health care, e.g. fluid
and food intake monitoring; in sports, e.g. training support and monitoring; in entertainment,
e.g. human-computer interface using body movements; in industrial scenarios, e.g.
computer support for detected work tasks. Several challenges exist for wearable activity
recognition: a large number of nonrelevant activities (null class), the evaluation of large
numbers of sensor signals (curse of dimensionality), ambiguity of sensor signals compared
to the activities and finally the high variability of human activity in general.
This thesis develops a new activity recognition strategy, called invariants classification,
which addresses these challenges, especially the variability in human activities. The
core idea is that often even highly variable actions include short, more or less invariant
sub-actions which are due to hard physical constraints. If someone opens a door, the
movement of the hand to the door handle is not fixed. However the door handle has to
be pushed to open the door. The invariants classification algorithm is structured in four
phases: segmentation, invariant identification, classification, and spotting. The segmentation
divides the continuous sensor data stream into meaningful parts, which are related
to sub-activities. Our segmentation strategy uses the zero crossings of the central difference
quotient of the sensor signals, as segment borders. The invariant identification finds
the invariant sub-activities by means of clustering and a selection strategy dependent on
certain features. The classification identifies the segments of a specific activity class, using
models generated from the invariant sub-activities. The models include the invariant
sub-activity signal and features calculated on sensor signals related to the sub-activity. In
the spotting, the classified segments are used to find the entire activity class instances in
the continuous sensor data stream. For this purpose, we use the position of the invariant
sub-activity in the related activity class instance for the estimation of the borders of the
activity instances.
In this thesis, we show that our new activity recognition strategy, built on invariant
sub-activities, is beneficial. We tested it on three human activity datasets with wearable
inertial measurement units (IMU). Compared to previous publications on the same
datasets we got improvement in the activity recognition in several classes, some with a
large margin. Our segmentation achieves a sensible method to separate the sensor data in
relation to the underlying activities. Relying on sub-activities makes us independent from
imprecise labels on the training data. After the identification of invariant sub-activities,
we calculate a value called cluster precision for each sensor signal and each class activity.
This tells us which classes can be easily classified and which sensor channels support
the classification best. Finally, in the training for each activity class, our algorithm selects
suitable signal channels with invariant sub-activities on different points in time and
with different length. This makes our strategy a multi-dimensional asynchronous motif
detection with variable motif length.
We study the global solution of Fredholm integral equations of the second kind by the help of Monte Carlo methods. Global solution means that we seek to approximate the full solution function. This is opposed to the usual applications of Monte Carlo, were one only wants to approximate a functional of the solution. In recent years several researchers developed Monte Carlo methods also for the global problem. In this paper we present a new Monte Carlo algorithm for the global solution of integral equations. We use multiwavelet expansions to approximate the solution. We study the behaviour of variance on increasing levels, and based on this, develop a new variance reduction technique. For classes of smooth kernels and right hand sides we determine the convergence rate of this algorithm and show that it is higher
than those of previously developed algorithms for the global problem. Moreover, an information-based complexity analysis shows that our algorithm is optimal among all stochastic algorithms of the same computational
cost and that no deterministic algorithm of the same cost can reach its convergence rate.
In this report we give an overview of the development of our new Waldmeisterprover for equational theories. We elaborate a systematic stepwise design process, startingwith the inference system for unfailing Knuth - Bendix completion and ending up with animplementation which avoids the main diseases today's provers suffer from: overindulgencein time and space.Our design process is based on a logical three - level system model consisting of basicoperations for inference step execution, aggregated inference machine, and overall controlstrategy. Careful analysis of the inference system for unfailing completion has revealed thecrucial points responsible for time and space consumption. For the low level of our model,we introduce specialized data structures and algorithms speeding up the running system andcutting it down in size - both by one order of magnitude compared with standard techniques.Flexible control of the mid - level aggregation inside the resulting prover is made possible by acorresponding set of parameters. Experimental analysis shows that this flexibility is a pointof high importance. We go on with some implementation guidelines we have found valuablein the field of deduction.The resulting new prover shows that our design approach is promising. We compare oursystem's throughput with that of an established system and finally demonstrate how twovery hard problems could be solved by Waldmeister.
W-Lisp Sprachbeschreibung
(1993)
W-Lisp [Wippennann 91] ist eine Sprache, die im Bereich der Implementierung höherer
Programmiersprachen verwendet wird. Ihre Anwendung ist nicht auf diesen Bereich beschränkt. Gute Lesbarkeit der W-Lisp-Notation wird durch zahlreiche Anleihen aus dem Bereich der bekannten imperativen Sprachen erzielt. W-Lisp-Programme können im Rahmen eines Common Lisp-Systems ausgeführt werden. In der WLisp Notation können alle Lisp-Funktionen (inkl. MCS) verwendet werden, so daß die Mächtigkeit von Common-Lisp [Steele 90] in dieser Hinsicht auch in W-Lisp verfügbar ist.
In urban planning, sophisticated simulation models are key tools to estimate future population growth for measuring the impact of planning decisions on urban developments and the environment. Simulated population projections usually result in large, macro-scale, multivariate geospatial data sets. Millions of records have to be processed, stored, and visualized to help planners explore and analyze complex population patterns. We introduce a database driven framework for visualizing geospatial multidimensional simulation data based on the output from UrbanSim, a software for the analysis and planning of urban developments. The designed framework is extendable and aims at integrating empirical-stochastic methods and urban simulation models with techniques developed for information visualization and cartography. First, we develop an empirical model for the estimation of residential building types based on demographic household characteristics. The predicted dwelling type information is important for the analysis of future material use, carbon footprint calculations, and for visualizing simultaneously the results of land usage, density, and other significant parameters in 3D space. Our model uses multinomial logistic regression to derive building types at different scales. The estimated regression coefficients are applied to UrbanSim output in order to predict residential building types. The simulation results and the estimated building types are managed in an object-relational geodatabase. From the database, density, building types, and significant demographic variables are visually encoded as scalable, georeferenced 3D geometries and displayed on top of aerial photographs in a Google Earth visual synthesis. The geodatabase can be accessed and the visualization parameters can be chosen through a web-based user interface. The geometries are encoded in KML, Google's markup language, as ready-to-visualize data sets. The goal is to enhance human cognition by displaying abstract representations of multidimensional data sets in a realistic context and thus to support decision making in planning processes.
Due to the steadily growing flood of data, the appropriate use of visualizations for efficient data analysis is as important today as it has never been before. In many application domains, the data flood is based on processes that can be represented by node-link diagrams. Within such a diagram, nodes may represent intermediate results (or products), system states (or snapshots), milestones or real (and possibly georeferenced) objects, while links (edges) can embody transition conditions, transformation processes or real physical connections. Inspired by the engineering sciences application domain and the research project “SinOptiKom: Cross-sectoral optimization of transformation processes in municipal infrastructures in rural areas”, a platform for the analysis of transformation processes has been researched and developed based on a geographic information system (GIS). Caused by the increased amount of available and interesting data, a particular challenge is the simultaneous visualization of several visible attributes within one single diagram instead of using multiple ones. Therefore, two approaches have been developed, which utilize the available space between nodes in a diagram to display additional information.
Motivated by the necessity of appropriate result communication with various stakeholders, a concept for a universal, dashboard-based analysis platform has been developed. This web-based approach is conceptually capable of displaying data from various data sources and has been supplemented by collaboration possibilities such as sharing, annotating and presenting features.
In order to demonstrate the applicability and usability of newly developed applications, visualizations or user interfaces, extensive evaluations with human users are often inevitable. To reduce the complexity and the effort for conducting an evaluation, the browser-based evaluation framework (BREF) has been designed and implemented. Through its universal and flexible character, virtually any visualization or interaction running in the browser can be evaluated with BREF without any additional application (except for a modern web browser) on the target device. BREF has already proved itself in a wide range of application areas during the development and has since grown into a comprehensive evaluation tool.
Computer processing of free form surfaces forms the basis of a closed construction process starting with surface design and up to NC-production.
Numerical simulation and visualization allow quality analysis before manufacture. A new aspect in surface analysis is described, the stability
of surfaces versus infinitesimal bendings. The stability concept is derived
from the kinetic meaning of a special vector field which is given by the deformation. Algorithms to calculate this vector field together with an appropriate visualization method give a tool able to analyze surface stability.
The visualization of numerical fluid flow datasets is essential to the engineering processes that motivate their computational simulation. To address the need for visual representations that convey meaningful relations and enable a deep understanding of flow structures, the discipline of Flow Visualization has produced many methods and schemes that are tailored to a variety of visualization tasks. The ever increasing complexity of modern flow simulations, however, puts an enormous demand on these methods. The study of vortex breakdown, for example, which is a highly transient and inherently three-dimensional flow pattern with substantial impact wherever it appears, has driven current techniques to their limits. In this thesis, we propose several novel visualization methods that significantly advance the state of the art in the visualization of complex flow structures. First, we propose a novel scheme for the construction of stream surfaces from the trajectories of particles embedded in a flow. These surfaces are extremely useful since they naturally exploit coherence between neighboring trajectories and are highly illustrative in nature. We overcome the limitations of existing stream surface algorithms that yield poor results in complex flows, and show how the resulting surfaces can be used a building blocks for advanced flow visualization techniques. Moreover, we present a visualization method that is based on moving section planes that travel through a dataset and sample the flow. By considering the changes to the flow topology on the plane as it moves, we obtain a method of visualizing topological structures in three-dimensional flows that are not accessible by conventional topological methods. On the same algorithmic basis, we construct an algorithm for the tracking of critical points in such flows, thereby enabling the treatment of time-dependent datasets. Last, we address some problems with the recently introduced Lagrangian techniques. While conceptually elegant and generally applicable, they suffer from an enormous computational cost that we significantly use by developing an adaptive approximation algorithm. This allows the application of such methods on very large and complex numerical simulations. Throughout this thesis, we will be concerned with flow visualization aspect of general practical significance but we will particularly emphasize the remarkably challenging visualization of the vortex breakdown phenomenon.
In urban planning, both measuring and communicating sustainability are among the most recent concerns. Therefore, the primary emphasis of this thesis concerns establishing metrics and visualization techniques in order to deal with indicators of sustainability.
First, this thesis provides a novel approach for measuring and monitoring two indicators of sustainability - urban sprawl and carbon footprints – at the urban neighborhood scale. By designating different sectors of relevant carbon emissions as well as different household categories, this thesis provides detailed information about carbon emissions in order to estimate impacts of daily consumption decisions and travel behavior by household type. Regarding urban sprawl, a novel gridcell-based indicator model is established, based on different dimensions of urban sprawl.
Second, this thesis presents a three-step-based visualization method, addressing predefined requirements for geovisualizations and visualizing those indicator results, introduced above. This surface-visualization combines advantages from both common GIS representation and three-dimensional representation techniques within the field of urban planning, and is assisted by a web-based graphical user interface which allows for accessing the results by the public.
In addition, by focusing on local neighborhoods, this thesis provides an alternative approach in measuring and visualizing both indicators by utilizing a Neighborhood Relation Diagram (NRD), based on weighted Voronoi diagrams. Thus, the user is able to a) utilize original census data, b) compare direct impacts of indicator results on the neighboring cells, and c) compare both indicators of sustainability visually.
Nowadays, the increasing demand for ever more customizable products has emphasized the need for more flexible and fast-changing manufacturing systems. In this environment, simulation has become a strategic tool for the design, development, and implementation of such systems. Simulation represents a relatively low-cost and risk-free alternative for testing the impact and effectiveness of changes in different aspects of manufacturing systems.
Systems that deal with this kind of data for its use in decision making processes are known as Simulation-Based Decision Support Systems (SB-DSS). Although most SB-DSS provide a powerful variety of tools for the automatic and semi-automatic analysis of simulations, visual and interactive alternatives for the manual exploration of the results are still open to further development.
The work in this dissertation is focused on enhancing decision makers’ analysis capabilities by making simulation data more accessible through the incorporation of visualization and analysis techniques. To demonstrate how this goal can be achieved, two systems were developed. The first system, viPhos – standing for visualization of Phos: Greek for light –, is a system that supports lighting design in factory layout planning. viPhos combines simulation, analysis, and visualization tools and techniques to facilitate the global and local (overall factory or single workstations, respectively) interactive exploration and comparison of lighting design alternatives.
The second system, STRAD - standing for Spatio-Temporal Radar -, is a web-based systems that considers the spatio/attribute-temporal analysis of event data. Since decision making processes in manufacturing also involve the monitoring of the systems over time, STRAD enables the multilevel exploration of event data (e.g., simulated or historical registers of the status of machines or results of quality control processes).
A set of four case studies and one proof of concept prepared for both systems demonstrate the suitability of the visualization and analysis strategies adopted for supporting decision making processes in diverse application domains. The results of these case studies indicate that both, the systems as well as the techniques included in the systems can be generalized and extended to support the analysis of different tasks and scenarios.
Due to remarkable technological advances in the last three decades the capacity of computer systems has improved tremendously. Considering Moore's law, the number of transistors on integrated circuits has doubled approximately every two years and the trend is continuing. Likewise, developments in storage density, network bandwidth, and compute capacity show similar patterns. As a consequence, the amount of data that can be processed by today's systems has increased by orders of magnitude. At the same time, however, the resolution of screens has hardly increased by a factor of ten. Thus, there is a gap between the amount of data that can be processed and the amount of data that can be visualized. Large high-resolution displays offer a way to deal with this gap and provide a significantly increased screen area by combining the images of multiple smaller display devices. The main objective of this dissertation is the development of new visualization and interaction techniques for large high-resolution displays.
This dissertation focuses on the visualization of urban microclimate data sets,
which describe the atmospheric impact of individual urban features. The application
and adaptation of visualization and analysis concepts to enhance the
insight into observational data sets used this specialized area are explored, motivated
through application problems encountered during active involvement
in urban microclimate research at the Arizona State University in Tempe, Arizona.
Besides two smaller projects dealing with the analysis of thermographs
recorded with a hand-held device and visualization techniques used for building
performance simulation results, the main focus of the work described in
this document is the development of a prototypic tool for the visualization
and analysis of mobile transect measurements. This observation technique involves
a sensor platform mounted to a vehicle, which is then used to traverse
a heterogeneous neighborhood to investigate the relationships between urban
form and microclimate. The resulting data sets are among the most complex
modes of in-situ observations due to their spatio-temporal dependence, their
multivariate nature, but also due to the various error sources associated with
moving platform observations.
The prototype enables urban climate researchers to preprocess their data,
to explore a single transect in detail, and to aggregate observations from multiple
traverses conducted over diverse routes for a visual delineation of climatic
microenvironments. Extending traditional analysis methods, the suggested visualization
tool provides techniques to relate the measured attributes to each
other and to the surrounding land cover structure. In addition to that, an
improved method for sensor lag correction is described, which shows the potential
to increase the spatial resolution of measurements conducted with slow
air temperature sensors.
In summary, the interdisciplinary approach followed in this thesis triggers
contributions to geospatial visualization and visual analytics, as well as to urban
climatology. The solutions developed in the course of this dissertation are
meant to support domain experts in their research tasks, providing means to
gain a qualitative overview over their specific data sets and to detect patterns,
which can then be further analyzed using domain-specific tools and methods.
The focus of this work is to provide and evaluate a novel method for multifield topology-based analysis and visualization. Through this concept, called Pareto sets, one is capable to identify critical regions in a multifield with arbitrary many individual fields. It uses ideas found in graph optimization to find common behavior and areas of divergence between multiple optimization objectives. The connections between the latter areas can be reduced into a graph structure allowing for an abstract visualization of the multifield to support data exploration and understanding.
The research question that is answered in this dissertation is about the general capability and expandability of the Pareto set concept in context of visualization and application. Furthermore, the study of its relations, drawbacks and advantages towards other topological-based approaches. This questions is answered in several steps, including consideration and comparison with related work, a thorough introduction of the Pareto set itself as well as a framework for efficient implementation and an attached discussion regarding limitations of the concept and their implications for run time, suitable data, and possible improvements.
Furthermore, this work considers possible simplification approaches like integrated single-field simplification methods but also using common structures identified through the Pareto set concept to smooth all individual fields at once. These considerations are especially important for real-world scenarios to visualize highly complex data by removing small local structures without destroying information about larger, global trends.
To further emphasize possible improvements and expandability of the Pareto set concept, the thesis studies a variety of different real world applications. For each scenario, this work shows how the definition and visualization of the Pareto set is used and improved for data exploration and analysis based on the scenarios.
In summary, this dissertation provides a complete and sound summary of the Pareto set concept as ground work for future application of multifield data analysis. The possible scenarios include those presented in the application section, but are found in a wide range of research and industrial areas relying on uncertainty analysis, time-varying data, and ensembles of data sets in general.
The safety of embedded systems is becoming more and more important nowadays. Fault Tree Analysis (FTA) is a widely used technique for analyzing the safety of embedded systems. A standardized tree-like structure called a Fault Tree (FT) models the failures of the systems. The Component Fault Tree (CFT) provides an advanced modeling concept for adapting the traditional FTs to the hierarchical architecture model in system design. Minimal Cut Set (MCS) analysis is a method that works for qualitative analysis based on the FTs. Each MCS represents a minimal combination of component failures of a system called basic events, which may together cause the top-level system failure. The ordinary representations of MCSs consist of plain text and data tables with little additional supporting visual and interactive information. Importance analysis based on FTs or CFTs estimates the contribution of each potential basic event to a top-level system failure. The resulting importance values of basic events are typically represented in summary views, e.g., data tables and histograms. There is little visual integration between these forms and the FT (or CFT) structure. The safety of a system can be improved using an iterative process, called the safety improvement process, based on FTs taking relevant constraints into account, e.g., cost. Typically, relevant data regarding the safety improvement process are presented across multiple views with few interactive associations. In short, the ordinary representation concepts cannot effectively facilitate these analyses.
We propose a set of visualization approaches for addressing the issues above mentioned in order to facilitate those analyses in terms of the representations.
Contribution:
1. To support the MCS analysis, we propose a matrix-based visualization that allows detailed data of the MCSs of interest to be viewed while maintaining a satisfactory overview of a large number of MCSs for effective navigation and pattern analysis. Engineers can also intuitively analyze the influence of MCSs of a CFT.
2. To facilitate the importance analysis based on the CFT, we propose a hybrid visualization approach that combines the icicle-layout-style architectural views with the CFT structure. This approach facilitates to identify the vulnerable components taking the hierarchies of system architecture into account and investigate the logical failure propagation of the important basic events.
3. We propose a visual safety improvement process that integrates an enhanced decision tree with a scatter plot. This approach allows one to visually investigate the detailed data related to individual steps of the process while maintaining the overview of the process. The approach facilitates to construct and analyze improvement solutions of the safety of a system.
Using our visualization approaches, the MCS analysis, the importance analysis, and the safety improvement process based on the CFT can be facilitated.
Today's ubiquity of visual content as driven by the availability of broadband Internet, low-priced storage, and the omnipresence of camera equipped mobile devices conveys much of our thinking and feeling as individuals and as a society. As a result the growth of video repositories is increasing at enourmous rates with content now being embedded and shared through social media. To make use of this new form of social multimedia, concept detection, the automatic mapping of semantic concepts and video content has to be extended such that concept vocabularies are synchronized with current real-world events, systems can perform scalable concept learning with thousands of concepts, and high-level information such as sentiment can be extracted from visual content. To catch up with these demands the following three contributions are made in this thesis: (i) concept detection is linked to trending topics, (ii) visual learning from web videos is presented including the proper treatment of tags as concept labels, and (iii) the extension of concept detection with adjective noun pairs for sentiment analysis is proposed.
In order for concept detection to satisfy users' current information needs, the notion of fixed concept vocabularies has to be reconsidered. This thesis presents a novel concept learning approach built upon dynamic vocabularies, which are automatically augmented with trending topics mined from social media. Once discovered, trending topics are evaluated by forecasting their future progression to predict high impact topics, which are then either mapped to an available static concept vocabulary or trained as individual concept detectors on demand. It is demonstrated in experiments on YouTube video clips that by a visual learning of trending topics, improvements of over 100% in concept detection accuracy can be achieved over static vocabularies (n=78,000).
To remove manual efforts related to training data retrieval from YouTube and noise caused by tags being coarse, subjective and context-depedent, this thesis suggests an automatic concept-to-query mapping for the retrieval of relevant training video material, and active relevance filtering to generate reliable annotations from web video tags. Here, the relevance of web tags is modeled as a latent variable, which is combined with an active learning label refinement. In experiments on YouTube, active relevance filtering is found to outperform both automatic filtering and active learning approaches, leading to a reduction of required label inspections by 75% as compared to an expert annotated training dataset (n=100,000).
Finally, it is demonstrated, that concept detection can serve as a key component to infer the sentiment reflected in visual content. To extend concept detection for sentiment analysis, adjective noun pairs (ANP) as novel entities for concept learning are proposed in this thesis. First a large-scale visual sentiment ontology consisting of 3,000 ANPs is automatically constructed by mining the web. From this ontology a mid-level representation of visual content – SentiBank – is trained to encode the visual presence of 1,200 ANPs. This novel approach of visual learning is validated in three independent experiments on sentiment prediction (n=2,000), emotion detection (n=807) and pornographic filtering (n=40,000). SentiBank is shown to outperform known low-level feature representations (sentiment prediction, pornography detection) or perform comparable to state-of-the art methods (emotion detection).
Altogether, these contributions extend state-of-the-art concept detection approaches such that concept learning can be done autonomously from web videos on a large-scale, and can cope with novel semantic structures such as trending topics or adjective noun pairs, adding a new dimension to the understanding of video content.
This PhD thesis is concerned with the visual analysis of time-dependent scalar field ensembles as occur in climate simulations.
Modern climate projections consist of multiple simulation runs (ensemble members) that vary in parameter settings and/or initial values, which leads to variations in the resulting simulation data.
The goal of ensemble simulations is to sample the space of possible futures under the given climate model and provide quantitative information about uncertainty in the results.
The analysis of such data is challenging because apart from the spatiotemporal data, also variability has to be analyzed and communicated.
This thesis presents novel techniques to analyze climate simulation ensembles visually.
A central question is how the data can be aggregated under minimized information loss.
To address this question, a key technique applied in several places in this work is clustering.
The first part of the thesis addresses the challenge of finding clusters in the ensemble simulation data.
Various distance metrics lend themselves for the comparison of scalar fields which are explored theoretically and practically.
A visual analytics interface allows the user to interactively explore and compare multiple parameter settings for the clustering and investigate the resulting clusters, i.e. prototypical climate phenomena.
A central contribution here is the development of design principles for analyzing variability in decadal climate simulations, which has lead to a visualization system centered around the new Clustering Timeline.
This is a variant of a Sankey diagram that utilizes clustering results to communicate climatic states over time coupled with ensemble member agreement.
It can reveal
several interesting properties of the dataset, such as:
into how many inherently similar groups the ensemble can be divided at any given time,
whether the ensemble diverges in general,
whether there are different phases in the time lapse, maybe periodicity, or outliers.
The Clustering Timeline is also used to compare multiple climate simulation models and assess their performance.
The Hierarchical Clustering Timeline is an advanced version of the above.
It introduces the concept of a cluster hierarchy that may group the whole dataset down to the individual static scalar fields into clusters of various sizes and densities recording the nesting relationship between them.
One more contribution of this work in terms of visualization research is, that ways are investigated how to practically utilize a hierarchical clustering of time-dependent scalar fields to analyze the data.
To this end, a system of different views is proposed which are linked through various interaction possibilities.
The main advantage of the system is that a dataset can now be inspected at an arbitrary level of detail without having to recompute a clustering with different parameters.
Interesting branches of the simulation can be expanded to reveal smaller differences in critical clusters or folded to show only a coarse representation of the less interesting parts of the dataset.
The last building block of the suit of visual analysis methods developed for this thesis aims at a robust, (largely) automatic detection and tracking of certain features in a scalar field ensemble.
Techniques are presented that I found can identify and track super- and sub-levelsets.
And I derive “centers of action” from these sets which mark the location of extremal climate phenomena that govern the weather (e.g. Icelandic Low and Azores High).
The thesis also presents visual and quantitative techniques to evaluate the temporal change of the positions of these centers; such a displacement would be likely to manifest in changes in weather.
In a preliminary analysis with my collaborators, we indeed observed changes in the loci of the centers of action in a simulation with increased greenhouse gas concentration as compared to pre-industrial concentration levels.
Synapses play a central role in the information propagation in the nervous system. A better understanding of synaptic structures and processes is vital for advancing nervous disease research. This work is part of an interdisciplinary project that aims at the quantitative examination of components of the neuromuscular junction, a synaptic connection between a neuron and a muscle cell.
The research project is based on image stacks picturing neuromuscular junctions captured by modern electron microscopes, which permit the rapid acquisition of huge amounts of image data at a high level of detail. The large amount and sheer size of such microscopic data makes a direct visual examination infeasible, though.
This thesis presents novel problem-oriented interactive visualization techniques that support the segmentation and examination of neuromuscular junctions.
First, I introduce a structured data model for segmented surfaces of neuromuscular junctions to enable the computational analysis of their properties. However, surface segmentation of neuromuscular junctions is a very challenging task due to the extremely intricate character of the objects of interest. Hence, such problematic segmentations are often performed manually by non-experts and thus requires further inspection.
With NeuroMap, I develop a novel framework to support proofreading and correction of three-dimensional surface segmentations. To provide a clear overview and to ease navigation within the data, I propose the surface map, an abstracted two-dimensional representation using key features of the surface as landmarks. These visualizations are augmented with information about automated segmentation error estimates. The framework provides intuitive and interactive data correction mechanisms, which in turn permit the expeditious creation of high-quality segmentations.
While analyzing such segmented synapse data, the formulation of specific research questions is often impossible due to missing insight into the data. I address this problem by designing a generic parameter space for segmented structures from biological image data. Furthermore, I introduce a graphical interface to aid its exploration, combining both parameter selection as well as data representation.
Graphs and flow networks are important mathematical concepts that enable the modeling and analysis of a large variety of real world problems in different domains such as engineering, medicine or computer science. The number, sizes and complexities of those problems permanently increased during the last decades. This led to an increased demand of techniques that help domain experts in understanding their data and its underlying structure to enable an efficient analysis and decision making process.
To tackle this challenge, this work presents several new techniques that utilize concepts of visual analysis to provide domain scientists with new visualization methodologies and tools. Therefore, this work provides novel concepts and approaches for diverse aspects of the visual analysis such as data transformation, visual mapping, parameter refinement and analysis, model building and visualization as well as user interaction.
The presented techniques form a framework that enriches domain scientists with new visual analysis tools and help them analyze their data and gain insight from the underlying structures. To show the applicability and effectiveness of the presented approaches, this work tackles different applications such as networking, product flow management and vascular systems, while preserving the generality to be applicable to further domains.
Virtual Robot Programming for Deformable Linear Objects: System concept and Prototype Implementation
(2002)
In this paper we present a method and system for robot programming using virtual reality techniques. The proposed method allows intuitive teaching of a manipulation task with haptic feedback in a graphical simulation system. Based on earlier work, our system allows even an operator who lacks specialized knowledge of robotics to automatically generate a robust sensor-based robot program that is ready to execute on different robots, merely by demonstrating the task in virtual reality.
In the presented work, I evaluate if and how Virtual Reality (VR) technologies can be used to support researchers working in the geosciences by providing immersive, collaborative visualization systems as well as virtual tools for data analysis. Technical challenges encountered in the development of theses systems are identified and solutions for these are provided.
To enable geologists to explore large digital terrain models (DTMs) in an immersive, explorative fashion within a VR environment, a suitable terrain rendering algorithm is required. For realistic perception of planetary curvature at large viewer altitudes, spherical rendering of the surface is necessary. Furthermore, rendering must sustain interactive frame rates of about 30 frames per second to avoid sensory confusion of the user. At the same time, the data structures used for visualization should also be suitable for efficiently computing spatial properties such as height profiles or volumes in order to implement virtual analysis tools. To address these requirements, I have developed a novel terrain rendering algorithm based on tiled quadtree hierarchies using the HEALPix parametrization of a sphere. For evaluation purposes, the system is applied to a 500 GiB dataset representing the surface of Mars.
Considering the current development of inexpensive remote surveillance equipment such as quadcopters, it seems inevitable that these devices will play a major role in future disaster management applications. Virtual reality installations in disaster management headquarters which provide an immersive visualization of near-live, three-dimensional situational data could then be a valuable asset for rapid, collaborative decision making. Most terrain visualization algorithms, however, require a computationally expensive pre-processing step to construct a terrain database.
To address this problem, I present an on-the-fly pre-processing system for cartographic data. The system consists of a frontend for rendering and interaction as well as a distributed processing backend executing on a small cluster which produces tiled data in the format required by the frontend on demand. The backend employs a CUDA based algorithm on graphics cards to perform efficient conversion from cartographic standard projections to the HEALPix-based grid used by the frontend.
Measurement of spatial properties is an important step in quantifying geological phenomena. When performing these tasks in a VR environment, a suitable input device and abstraction for the interaction (a “virtual tool”) must be provided. This tool should enable the user to precisely select the location of the measurement even under a perspective projection. Furthermore, the measurement process should be accurate to the resolution of the data available and should not have a large impact on the frame rate in order to not violate interactivity requirements.
I have implemented virtual tools based on the HEALPix data structure for measurement of height profiles as well as volumes. For interaction, a ray-based picking metaphor was employed, using a virtual selection ray extending from the user’s hand holding a VR interaction device. To provide maximum accuracy, the algorithms access the quad-tree terrain database at the highest available resolution level while at the same time maintaining interactivity in rendering.
Geological faults are cracks in the earth’s crust along which a differential movement of rock volumes can be observed. Quantifying the direction and magnitude of such translations is an essential requirement in understanding earth’s geological history. For this purpose, geologists traditionally use maps in top-down projection which are cut (e.g. using image editing software) along the suspected fault trace. The two resulting pieces of the map are then translated in parallel against each other until surface features which have been cut by the fault motion come back into alignment. The amount of translation applied is then used as a hypothesis for the magnitude of the fault action. In the scope of this work it is shown, however, that performing this study in a top-down perspective can lead to the acceptance of faulty reconstructions, since the three-dimensional structure of topography is not considered.
To address this problem, I present a novel terrain deformation algorithm which allows the user to trace a fault line directly within a 3D terrain visualization system and interactively deform the terrain model while inspecting the resulting reconstruction from arbitrary perspectives. I demonstrate that the application of 3D visualization allows for a more informed interpretation of fault reconstruction hypotheses. The algorithm is implemented on graphics cards and performs real-time geometric deformation of the terrain model, guaranteeing interactivity with respect to all parameters.
Paleoceanography is the study of the prehistoric evolution of the ocean. One of the key data sources used in this research are coring experiments which provide point samples of layered sediment depositions at the ocean floor. The samples obtained in these experiments document the time-varying sediment concentrations within the ocean water at the point of measurement. The task of recovering the ocean flow patterns based on these deposition records is a challenging inverse numerical problem, however.
To support domain scientists working on this problem, I have developed a VR visualization tool to aid in the verification of model parameters by providing simultaneous visualization of experimental data from coring as well as the resulting predicted flow field obtained from numerical simulation. Earth is visualized as a globe in the VR environment with coring data being presented using a billboard rendering technique while the
time-variant flow field is indicated using Line-Integral-Convolution (LIC). To study individual sediment transport pathways and their correlation with the depositional record, interactive particle injection and real-time advection is supported.
In diesem Papier beschreiben wir eine Methode zur Spezifikation und Operationalisierung von konzeptuellen Modellen kooperativer wissensbasierter Arbeitsabläufe. Diese erweitert bekannte Ansätze um den Begriff des Agenten und um alternative Aufgabenzerlegungen. Das Papier beschreibt schwerpunktmäßig Techniken, die unserem verteilten Interpreter zugrunde liegen. Dabei gehen wir insbesondere auf Methoden ein, die Abhängigkeiten zwischen Aufgaben behandeln und ein zielgerichtetes Backtracking effizient unterstützen.
To improve efficiency of memory accesses, modern multiprocessor architectures implement a whole range of different weak memory models. The behavior of performance-critical code depends on the underlying hardware. There is a rising demand for verification tools that take the underlying memory model into account. This work examines a variety of prevalent problems in the field of program verification of increasing complexities: testing, reachability, portability and memory model synthesis.
We give efficient tools to solve these problems. What sets the presented methods apart is that they are not limited to some few given architectures. They are universal: The memory model is given as part of the input. We make use of the CAT language to succinctly describe axiomatic memory models. CAT has been used to define the semantics of assembly for x86/TSO, ARMv7, ARMv8, and POWER but also the semantics of programming languages such as C/C++, including the Linux kernel concurrency primitives.
This work shows that even the simple testing problem is NP-hard for most memory models. It does so using a general reduction technique that applies to a range of models. It examines the more difficult program verification under a memory model and introduces Dartagnan, a bounded model checker (BMC) that encodes the problem as an SMT-query and makes use of advanced encoding techniques. The program portability problem is shown to be even harder. Despite this, it is solved efficiently by the tool Porthos which uses a guided search to produce fast results for most practical instances. A memory model is synthesized by Aramis for a given set of reachability results. Concurrent program verification is generally undecidable even for sequential consistency. As an alternative to BMC, we propose a new CEGAR method for Petri net invariant synthesis. We again use SMT-queries as a back-end.
Knowing the extent to which we rely on technology one may think that correct programs are nowadays the norm. Unfortunately, this is far from the truth. Luckily, possible reasons why program correctness is difficult often come hand in hand with some solutions. Consider concurrent program correctness under Sequential Consistency (SC). Under SC, instructions of each program's concurrent component are executed atomically and in order. By using logic to represent correctness specifications, model checking provides a successful solution to concurrent program verification under SC. Alas, SC’s atomicity assumptions do not reflect the reality of hardware architectures. Total Store Order (TSO) is a less common memory model implemented in SPARC and in Intel x86 multiprocessors that relaxes the SC constraints. While the architecturally de-atomized execution of stores under TSO speeds up program execution, it also complicates program verification. To be precise, due to TSO’s unbounded store buffers, a program’s semantics under TSO might be infinite. This, for example, turns reachability under SC (a PSPACE-complete task) into a non-primitive-recursive-complete problem under TSO. This thesis develops verification techniques targeting TSO-relaxed programs. To be precise, we present under- and over-approximating heuristics for checking reachability in TSO-relaxed programs as well as state-reducing methods for speeding up such heuristics. In a first contribution, we propose an algorithm to check reachability of TSO-relaxed programs lazily. The under-approximating refinement algorithm uses auxiliary variables to simulate TSO’s buffers along instruction sequences suggested by an oracle. The oracle’s deciding characteristic is that if it returns the empty sequence then the program’s SC- and TSO-reachable states are the same. Secondly, we propose several approaches to over-approximate TSO buffers. Combined in a refinement algorithm, these approaches can be used to determine safety with respect to TSO reachability for a large class of TSO-relaxed programs. On the more technical side, we prove that checking reachability is decidable when TSO buffers are approximated by multisets with tracked per address last-added-values. Finally, we analyze how the explored state space can be reduced when checking TSO and SC reachability. Intuitively, through the viewpoint of Shasha-and-Snir-like traces, we exploit the structure of program instructions to explain several state-space reducing methods including dynamic and cartesian partial order reduction.
A wide range of methods and techniques have been developed over the years to manage the increasing
complexity of automotive Electrical/Electronic systems. Standardization is an example
of such complexity managing techniques that aims to minimize the costs, avoid compatibility
problems and improve the efficiency of development processes.
A well-known and -practiced standard in automotive industry is AUTOSAR (Automotive
Open System Architecture). AUTOSAR is a common standard among OEMs (Original Equipment
Manufacturer), suppliers and other involved companies. It was developed originally with
the goal of simplifying the overall development and integration process of Electrical/Electronic
artifacts from different functional domains, such as hardware, software, and vehicle communication.
However, the AUTOSAR standard, in its current status, is not able to manage the problems
in some areas of the system development. Validation and optimization process of system configuration
handled in this thesis are examples of such areas, in which the AUTOSAR standard
offers so far no mature solutions.
Generally, systems developed on the basis of AUTOSAR must be configured in a way that all
defined requirements are met. In most cases, the number of configuration parameters and their
possible settings in AUTOSAR systems are large, especially if the developed system is complex
with modules from various knowledge domains. The verification process here can consume a
lot of resources to test all possible combinations of configuration settings, and ideally find the
optimal configuration variant, since the number of test cases can be very high. This problem is
referred to in literature as the combinatorial explosion problem.
Combinatorial testing is an active and promising area of functional testing that offers ideas
to solve the combinatorial explosion problem. Thereby, the focus is to cover the interaction
errors by selecting a sample of system input parameters or configuration settings for test case
generation. However, the industrial acceptance of combinatorial testing is still weak because of
the deficiency of real industrial examples.
This thesis is tempted to fill this gap between the industry and the academy in the area
of combinatorial testing to emphasizes the effectiveness of combinatorial testing in verifying
complex configurable systems.
The particular intention of the thesis is to provide a new applicable approach to combinatorial
testing to fight the combinatorial explosion problem emerged during the verification and
performance measurement of transport protocol parallel routing of an AUTOSAR gateway. The
proposed approach has been validated and evaluated by means of two real industrial examples
of AUTOSAR gateways with multiple communication buses and two different degrees of complexity
to illustrate its applicability.
In Laufe der letzten Jahrzehnte ist der Prozeß der Softwareentwicklung methodisiert und zum Teil auch formalisiert worden. I.a. unterteilt man den Vorgang in grobe Stufen, Entwicklungsphasen genannt. Jede dieser Phasen betrachtet den entstehenden Entwurf des Projekts aus verschiedenen Sichtweisen. Aus dieser Sichtweise resultieren etliche Modelle und Darstellungsformen und mit ihnen auch verschiedene rechnergestützte Entwicklungswerkzeuge. In frühen Phasen sind beispielsweise Datenflußdiagramme eine nützliche Darstellungsform, in späteren konkrete Algorithmenbeschreibungen. Entwurfsänderungen im Laufe der Entwicklungszeit müssen in allen betroffenen Ebenen neu formuliert werden, eine automatisierte phasenübergreifende Behandlung ist
daher i.a. nicht oder nur teilweise möglich. Um effizienter und weniger fehleranfällig arbeiten zu können, wurden aus diesem Grund in letzter Zeit Ansätze gemacht, den gesamten Softwareentwicklungsprozeß von der ·Anforderungsanalyse bis hin zur Wartungsphase einem einheitlichen Konzept und einer einheitlichen Darstellungsform zu unterwerfen, die sich darüberhinaus zur Realisation auf Rechnersystemen eignen. Der vorliegende Bericht entstand im Rahmen eines solchen Projekts. Es wurden eine allumfassende Systementwurfssprache und die dazugehörigen Konzepte entwickelt, die sämtliche Entwurfsphasen und die wichtigsten -prinzipien zu unterstützen vermögen. Es liegen bereits zwei Arbeiten zu diesem Projekt vor. Sie stellen im wesentlichen neben der eigentlichen Definition der Systementwurfssprache zwei Entwicklungswerkzeuge vor, die auf einer einheitlichen Datenbasis operieren [GK-91, Kel-90]. Ein Bereich innerhalb der Forschungen ist die Wiederverwendung von Softwareentwürfen. Schon existierende Lösungen sollen bei der Entwicklung eines neuen Entwurfs durch Vergleich und Bewertung des Grades der Ähnlichkeit ausgewählt und dem Entwickler nutzbar gemacht werden. Dieser Bericht beschäftigt sich mit einem Kernpunkt der Wiederverwendung, dem Vergleich zweier Softwareentwürfe. Es werden zunächst grundsätzliche Konzepte ausgearbeitet, die den Ähnlichkeitsaspekt unter verschiedenen Gesichtspunkten charakterisieren. Daraufhin werden Algorithmen konstruiert, die verschiedenartige Vergleichsfunktionen realisieren und zu einer Gesamtfunktion kombinieren. Um zu einem späteren Zeitpunkt die Leistungsfähigkeit dieser
Funktionen in der Praxis untersuchen zu können, liegt darüberhinaus ein lauffähiges
Programm vor.
Die Verfahren der Induktiven Logischen Programmierung (ILP) [Mug93] haben die Aufgabe, aus einer Menge von positiven Beispielen E+, einer Menge von negativen Beispielen E und dem Hintergrundwissen B ein logisches Programm P zu lernen, das aus einer Menge von definiten Klauseln C : l0 l1, : : : ,ln besteht. Da der Hypothesenraum für Hornlogik unendlich ist, schränken viele Verfahren die Hypothesensprache auf eine endliche ein. Auch wird oft versucht, die Hypothesensprache so einzuschränken, dass nur Programme gelernt werden können, für die die Konsistenz entscheidbar ist. Eine andere Motivation, die Hypothesensprache zu beschränken, ist, dass das Wissen über das Zielprogramm, das schon vorhanden ist, ausgenutzt werden soll. So sind für bestimmte Anwendungen funktionsfreie Hypothesenklauseln ausreichend, oder es ist bekannt, dass das Zielprogramm funktional ist.
A new variance reduction technique for the Monte Carlo solution of integral
equations is introduced. It is based on separation of the main part. A neighboring equation with exactly known solution is constructed by the help of a deterministic Galerkin scheme. The variance of the method is analyzed, and an application to the radiosity equation of computer graphics, together with numerical test results is given.
Conditional Compilation (CC) is frequently used as a variation mechanism in software product lines (SPLs). However, as a SPL evolves the variable code realized by CC erodes in the sense that it becomes overly complex and difficult to understand and maintain. As a result, the SPL productivity goes down and puts expected advantages more and more at risk. To investigate the variability erosion and keep the productivity above a sufficiently good level, in this paper we 1) investigate several erosion symptoms in an industrial SPL; 2) present a variability improvement process that includes two major improvement strategies. While one strategy is to optimize variable code within the scope of CC, the other strategy is to transition CC to a new variation mechanism called Parameterized Inclusion. Both of these two improvement strategies can be conducted automatically, and the result of CC optimization is provided. Related issues such as applicability and cost of the improvement are also discussed.
3D joint kinematics can provide important information about the quality of movements. Optical motion capture systems (OMC) are considered the gold standard in motion analysis. However, in recent years, inertial measurement units (IMU) have become a promising alternative. The aim of this study was to validate IMU-based 3D joint kinematics of the lower extremities during different movements. Twenty-eight healthy subjects participated in this study. They performed bilateral squats (SQ), single-leg squats (SLS) and countermovement jumps (CMJ). The IMU kinematics was calculated using a recently-described sensor-fusion algorithm. A marker based OMC system served as a reference. Only the technical error based on algorithm performance was considered, incorporating OMC data for the calibration, initialization, and a biomechanical model. To evaluate the validity of IMU-based 3D joint kinematics, root mean squared error (RMSE), range of motion error (ROME), Bland-Altman (BA) analysis as well as the coefficient of multiple correlation (CMC) were calculated. The evaluation was twofold. First, the IMU data was compared to OMC data based on marker clusters; and, second based on skin markers attached to anatomical landmarks. The first evaluation revealed means for RMSE and ROME for all joints and tasks below 3°. The more dynamic task, CMJ, revealed error measures approximately 1° higher than the remaining tasks. Mean CMC values ranged from 0.77 to 1 over all joint angles and all tasks. The second evaluation showed an increase in the RMSE of 2.28°– 2.58° on average for all joints and tasks. Hip flexion revealed the highest average RMSE in all tasks (4.87°– 8.27°). The present study revealed a valid IMU-based approach for the measurement of 3D joint kinematics in functional movements of varying demands. The high validity of the results encourages further development and the extension of the present approach into clinical settings.
In diesem Papier stellen wir einen Interpreter vor, der die Validierung von konzeptuellen Modellen bereits in fruehen Entwicklungsphasen unterstuetzt. Wir vergleichen Hypermedia- und Expertensystemansaetze zur Wissensverarbeitung und erlaeutern, wie ein integrierter Ansatz die Erstellung von Expertensystemen vereinfacht. Das von uns entwickelte Knowledge Engineering Werkzeug ermoeglicht einen "sanften" Uebergang von initialen Protokollen ueber eine semi-formale Spezifikation in Form eines getypten Hypertextes hin zu einem operationalen Expertensystem. Ein Interpreter nutzt die in diesem Prozess erzeugte Zwischenrepraesentation direkt zur interaktiven Loesung von Problemen, wobei einzelne Aufgaben ueber ein lokales Rechnernetz auf die Bearbeiter verteilt werden. Das heisst, die Spezifikation des Expertensystems wird direkt fuer die Loesung realer Probleme eingesetzt. Existieren zu einzelnen Teilaufgaben Operationalisierungen (d.h. Programme), dann werden diese vom Computer bearbeitet.
For most applications the used transport service providers are predetermined during the development of the application. This makes it difficult to consider the application communication requirements and to exploit specific features of the network technology. Specialized protocols that are more efficient and offer a qualitative improved service are typically not supported by most applications because they are not commonly available. In this paper we propose a concept for the realization of protocol independent transport services. Only a transport service is predetermined during the development of the application and an appropriate transport service provider is dynamically selected at run time. This enables to exploit specialized protocols if possible, but standard protocols could still be used if necessary. The main focus of this paper is how a transport service could provide a new transport service provider transparently to existing applications. A prototype is presented that maps TCP/IP based applications to an ATM specific transport service provider which offers a reliable and unreliable transport service like TCP/IP.
We present a distributed system, Dott, for approximately solving the Trav-eling Salesman Problem (TSP) based on the Teamwork method. So-calledexperts and specialists work independently and in parallel for given time pe-riods. For TSP, specialists are tour construction algorithms and experts usemodified genetic algorithms in which after each application of a genetic operatorthe resulting tour is locally optimized before it is added to the population. Aftera given time period the work of each expert and specialist is judged by a referee.A new start population, including selected individuals from each expert and spe-cialist, is generated by the supervisor, based on the judgments of the referees.Our system is able to find better tours than each of the experts or specialistsworking alone. Also results comparable to those of single runs can be found muchfaster by a team.
Rules are an important knowledge representation formalism in constructive problem solving. On the other hand, object orientation is an essential key technology for maintaining large knowledge bases as well as software applications. Trying to take advantage of the benefits of both paradigms, we integrated Prolog and Smalltalk to build a common base architecture for problem solving. This approach has proven to be useful in the development of two knowledge-based systems for planning and configuration design (CAPlan and Idax). Both applications use Prolog as an efficient computational source for the evaluation of knowledge represented as rules.
The prototype of a rapid authoring tool for reusable learning objects, LOXtractor was extended with the ability for importing PDF files and for direct input of plain text. The ability to process PDF files was a major step forward to the goal of creating an application that integrates the creation of small-scale learning objects, their annotation with metadata and their mapping to an ontology for later retrieval into the task solving workflow, as intended by the SLEAM process. Especially small and medium sized enterprises can profit from this easy and affordable way to conserve individual informal learning effort for the whole company.
Retrieval of cases is one important step within the case-based reasoning paradigm. We propose an improvement of this stage in the process model for finding most similar cases with an average effort of O[log2n], n number of cases. The basic idea of the algorithm is to use the heterogeneity of the search space for a density-based structuring and to employ this precomputed structure, a k-d tree, for efficient case retrieval according to a given similarity measure sim. In addition to illustrating the basic idea, we present the expe- rimental results of a comparison of four different k-d tree generating strategies as well as introduce the notion of virtual bounds as a new one that significantly reduces the retrieval effort from a more pragmatic perspective. The presented approach is fully implemented within the (Patdex) system, a case-based reasoning system for diagnostic applications in engineering domains.