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We investigate the ergodic properties of a random walker performing (anomalous) diffusion on a random fractal geometry. Extensive Monte Carlo simulations of the motion of tracer particles on an ensemble of realisations of percolation clusters are performed for a wide range of percolation densities. Single trajectories of the tracer motion are analysed to quantify the time averaged mean squared displacement (MSD) and to compare this with the ensemble averaged MSD of the particle motion. Other complementary physical observables associated with ergodicity are studied, as well. It turns out that the time averaged MSD of individual realisations exhibits non-vanishing fluctuations even in the limit of very long observation times as the percolation density approaches the critical value. This apparent non-ergodic behaviour concurs with the ergodic behaviour on the ensemble averaged level. We demonstrate how the non-vanishing fluctuations in single particle trajectories are analytically expressed in terms of the fractal dimension and the cluster size distribution of the random geometry, thus being of
purely geometrical origin. Moreover, we reveal that the convergence scaling law to ergodicity, which is known to be inversely proportional to the observation time T for ergodic diffusion processes, follows a power-law BT� h with h o 1 due to the fractal structure of the accessible space. These results provide useful measures for differentiating the subdiffusion on random fractals from an otherwise closely related process, namely, fractional Brownian motion. Implications of our results on the analysis of single particle tracking experiments are provided.
The interruption of learning processes by breaks filled with diverse activities is common in everyday life. We investigated the effects of active computer gaming and passive relaxation (rest and music) breaks on working memory performance. Young adults were exposed to breaks involving (i) eyes-open resting, (ii) listening to music and (iii) playing the video game “Angry Birds” before performing the n-back working memory task. Based on linear mixed-effects modeling, we found that playing the “Angry Birds” video game during a short learning break led to a decline in task performance over the course of the task as compared to eyes-open resting and listening to music, although overall task performance was not impaired. This effect was associated with high levels of daily mind wandering and low self-reported ability to concentrate. These findings indicate that video games can negatively affect working memory performance over time when played in between learning tasks. We suggest further investigation of these effects because of their relevance to everyday activity.
The Brazilian Cerrado is recognised as one of the most threatened biomes in the world, as the region has experienced a striking change from natural vegetation to intense cash crop production. The impacts of rapid agricultural expansion on soil and water resources are still poorly understood in the region. Therefore, the overall aim of the thesis is to improve our understanding of the ecohydrological processes causing water and soil degradation in the Brazilian Cerrado.
I first present a metaanalysis to provide quantitative evidence and identifying the main impacts of soil and water alterations resulting from land use change. Second, field studies were conducted to (i) examine the effects of land use change on soils of natural cerrado transformed to common croplands and pasture and (ii) indicate how agricultural production affects water quality across a meso-scale catchment. Third, the ecohydrological process-based model SWAT was tested with simple scenario analyses to gain insight into the impacts of land use and climate change on the water cycling in the upper São Lourenço catchment which experienced decreasing discharges in the last 40 years.
Soil and water quality parameters from different land uses were extracted from 89 soil and 18 water studies in different regions across the Cerrado. Significant effects on pH, bulk density and available P and K for croplands and less-pronounced effects on pastures were evident. Soil total N did not differ between land uses because most of the cropland sites were N-fixing soybean cultivations, which are not artificially fertilized with N. By contrast, water quality studies showed N enrichment in agricultural catchments, indicating fertilizer impacts and potential susceptibility to eutrophication. Regardless of the land use, P is widely absent because of the high-fixing capacities of deeply weathered soils and the filtering capacity of riparian vegetation. Pesticides, however, were consistently detected throughout the entire aquatic system. In several case studies, extremely high-peak concentrations exceeded Brazilian and EU water quality limits, which pose serious health risks.
My field study revealed that land conversion caused a significant reduction in infiltration rates near the soil surface of pasture (–96 %) and croplands (–90 % to –93 %). Soil aggregate stability was significantly reduced in croplands than in cerrado and pasture. Soybean crops had extremely high extractable P (80 mg kg–1), whereas pasture N levels declined. A snapshot water sampling showed strong seasonality in water quality parameters. Higher temperature, oxi-reduction potential (ORP), NO2–, and very low oxygen concentrations (<5 mg•l–1) and saturation (<60 %) were recorded during the rainy season. By contrast, remarkably high PO43– concentrations (up to 0.8 mg•l–1) were measured during the dry season. Water quality parameters were affected by agricultural activities at all sampled sub-catchments across the catchment, regardless of stream characteristic. Direct NO3– leaching appeared to play a minor role; however, water quality is affected by topsoil fertiliser inputs with impact on small low order streams and larger rivers. Land conversion leaving cropland soils more susceptible to surface erosion by increased overland flow events.
In a third study, the field data were used to parameterise SWAT. The model was tested with different input data and calibrated in SWAT-CUP using the SUFI-2 algorithm. The model was judged reliable to simulate the water balance in the Cerrado. A complete cerrado, pasture and cropland cover was used to analyse the impact of land use on water cycling as well as climate change projections (2039–2058) according to the projections of the RCP 8.5 scenario. The actual evapotranspiration (ET) for the cropland scenario was higher compared to the cerrado cover (+100 mm a–1). Land use change scenarios confirmed that deforestation caused higher annual ET rates explaining partly the trend of decreased streamflow. Taking all climate change scenarios into account, the most likely effect is a prolongation of the dry season (by about one month), with higher peak flows in the rainy season. Consequently, potential threats for crop production with lower soil moisture and increased erosion and sediment transport during the rainy season are likely and should be considered in adaption plans.
From the three studies of the thesis I conclude that land use intensification is likely to seriously limit the Cerrado’s future regarding both agricultural productivity and ecosystem stability. Because only limited data are available for the vast biome, we recommend further field studies to understand the interaction between terrestrial and aquatic systems. This thesis may serve as a valuable database for integrated modelling to investigate the impact of land use and climate change on soil and water resources and to test and develop mitigation measures for the Cerrado in the future.
Nowadays, business processes are increasingly supported by IT services that produce massive amounts of event data during process execution. Aiming at a better process understanding and improvement, this event data can be used to analyze processes using process mining techniques. Process models can be automatically discovered and the execution can be checked for conformance to specified behavior. Moreover, existing process models can be enhanced and annotated with valuable information, for example for performance analysis. While the maturity of process mining algorithms is increasing and more tools are entering the market, process mining projects still face the problem of different levels of abstraction when comparing events with modeled business activities. Mapping the recorded events to activities of a given process model is essential for conformance checking, annotation and understanding of process discovery results. Current approaches try to abstract from events in an automated way that does not capture the required domain knowledge to fit business activities. Such techniques can be a good way to quickly reduce complexity in process discovery. Yet, they fail to enable techniques like conformance checking or model annotation, and potentially create misleading process discovery results by not using the known business terminology.
In this thesis, we develop approaches that abstract an event log to the same level that is needed by the business. Typically, this abstraction level is defined by a given process model. Thus, the goal of this thesis is to match events from an event log to activities in a given process model. To accomplish this goal, behavioral and linguistic aspects of process models and event logs as well as domain knowledge captured in existing process documentation are taken into account to build semiautomatic matching approaches. The approaches establish a pre--processing for every available process mining technique that produces or annotates a process model, thereby reducing the manual effort for process analysts. While each of the presented approaches can be used in isolation, we also introduce a general framework for the integration of different matching approaches.
The approaches have been evaluated in case studies with industry and using a large industry process model collection and simulated event logs. The evaluation demonstrates the effectiveness and efficiency of the approaches and their robustness towards nonconforming execution logs.
Business process management (BPM) is a systematic and structured approach to model, analyze, control, and execute business operations also referred to as business processes that get carried out to achieve business goals. Central to BPM are conceptual models. Most prominently, process models describe which tasks are to be executed by whom utilizing which information to reach a business goal. Process models generally cover the perspectives of control flow, resource, data flow, and information systems.
Execution of business processes leads to the work actually being carried out. Automating them increases the efficiency and is usually supported by process engines. This, though, requires the coverage of control flow, resource assignments, and process data. While the first two perspectives are well supported in current process engines, data handling needs to be implemented and maintained manually. However, model-driven data handling promises to ease implementation, reduces the error-proneness through graphical visualization, and reduces development efforts through code generation.
This thesis addresses the modeling, analysis, and execution of data in business processes and presents a novel approach to execute data-annotated process models entirely model-driven. As a first step and formal grounding for the process execution, a conceptual framework for the integration of processes and data is introduced. This framework is complemented by operational semantics through a Petri net mapping extended with data considerations. Model-driven data execution comprises the handling of complex data dependencies, process data, and data exchange in case of communication between multiple process participants. This thesis introduces concepts from the database domain into BPM to enable the distinction of data operations, to specify relations between data objects of the same as well as of different types, to correlate modeled data nodes as well as received messages to the correct run-time process instances, and to generate messages for inter-process communication. The underlying approach, which is not limited to a particular process description language, has been implemented as proof-of-concept.
Automation of data handling in business processes requires data-annotated and correct process models. Targeting the former, algorithms are introduced to extract information about data nodes, their states, and data dependencies from control information and to annotate the process model accordingly. Usually, not all required information can be extracted from control flow information, since some data manipulations are not specified. This requires further refinement of the process model. Given a set of object life cycles specifying allowed data manipulations, automated refinement of the process model towards containment of all data manipulations is enabled. Process models are an abstraction focusing on specific aspects in detail, e.g., the control flow and the data flow views are often represented through activity-centric and object-centric process models. This thesis introduces algorithms for roundtrip transformations enabling the stakeholder to add information to the process model in the view being most appropriate.
Targeting process model correctness, this thesis introduces the notion of weak conformance that checks for consistency between given object life cycles and the process model such that the process model may only utilize data manipulations specified directly or indirectly in an object life cycle. The notion is computed via soundness checking of a hybrid representation integrating control flow and data flow correctness checking. Making a process model executable, identified violations must be corrected. Therefore, an approach is proposed that identifies for each violation multiple, alternative changes to the process model or the object life cycles.
Utilizing the results of this thesis, business processes can be executed entirely model-driven from the data perspective in addition to the control flow and resource perspectives already supported before. Thereby, the model creation is supported by algorithms partly automating the creation process while model consistency is ensured by data correctness checks.
In diesem Papier wird das Konzept eines Lernzentrums für die Informatik (LZI) an der Universität Paderborn vorgestellt. Ausgehend von den fachspezifischen Schwierigkeiten der Informatik Studierenden werden die Angebote des LZIs erläutert, die sich über die vier Bereiche Individuelle Beratung und Betreuung, „Offener Lernraum“, Workshops und Lehrveranstaltungen sowie Forschung erstrecken. Eine erste Evaluation mittels Feedbackbögen zeigt, dass das Angebot bei den Studierenden positiv aufgenommen wird. Zukünftig soll das Angebot des LZIs weiter ausgebaut und verbessert werden. Ausgangsbasis dazu sind weitere Studien.
Die Wahl des richtigen Studienfaches und die daran anschließende
Studieneingangsphase sind oft entscheidend für den erfolgreichen Verlauf eines Studiums. Eine große Herausforderung besteht dabei darin, bereits in den ersten Wochen des Studiums bestehende Defizite in vermeintlich einfachen Schlüsselkompetenzen zu erkennen und diese so bald wie möglich zu beheben. Eine zweite, nicht minder wichtige Herausforderung ist es, möglichst frühzeitig für jeden einzelnen Studierenden zu erkennen, ob er bzw. sie das individuell richtige Studienfach gewählt hat, das den jeweiligen persönlichen Neigungen, Interessen und Fähigkeiten entspricht und zur Verwirklichung der eigenen Lebensziele beiträgt. Denn nur dann sind Studierende ausreichend stark und dauerhaft intrinsisch motiviert, um ein anspruchsvolles, komplexes Studium erfolgreich durchzuziehen. In diesem Beitrag fokussieren wir eine Maßnahme, die die Studierenden an einen Prozess zur systematischen Reflexion des eigenen Lernprozesses und der eigenen Ziele heranführt und beides in Relation setzt.
Ziel einer neuen Studieneingangsphase ist, den Studierenden bis zum Ende des ersten Semesters ein vielfältiges Berufsbild der Informatik und Wirtschaftsinformatik mit dem breiten Aufgabenspektrum aufzublättern und damit die Zusammenhänge zwischen den einzelnen Modulen des Curriculums zu verdeutlichen. Die Studierenden sollen in die Lage versetzt werden, sehr eigenständig die Planung und Gestaltung ihres Studiums in die Hand zu nehmen.
Es wird ein Informatik-Wettbewerb für Schülerinnen und Schüler der Sekundarstufe II beschrieben, der über mehrere Wochen möglichst realitätsnah die Arbeitswelt eines Informatikers vorstellt. Im Wettbewerb erarbeiten die Schülerteams eine Android-App und organisieren ihre Entwicklung durch Projektmanagementmethoden, die sich an professionellen, agilen Prozessen orientieren. Im Beitrag werden der theoretische Hintergrund zu Wettbewerben, die organisatorischen und didaktischen Entscheidung, eine erste Evaluation sowie Reflexion und Ausblick dargestellt.
In der Lehre zur MCI (Mensch-Computer-Interaktion) stellt sich immer wieder die Herausforderung, praktische Übungen mit spannenden Ergebnissen durchzuführen, die sich dennoch nicht in technischen Details verlieren sondern MCI-fokussiert bleiben. Im Lehrmodul „Interaktionsdesign“ an der Universität Hamburg werden von Studierenden innerhalb von drei Wochen prototypische Interaktionskonzepte für das Spiel Neverball entworfen und praktisch umgesetzt. Anders als in den meisten Grundlagenkursen zur MCI werden hier nicht Mock-Ups, sondern lauffähige Software entwickelt. Um dies innerhalb der Projektzeit zu ermöglichen, wurde Neverball um eine TCP-basierte Schnittstelle erweitert. So entfällt die aufwändige Einarbeitung in den Quellcode des Spiels und die Studierenden können sich auf ihre Interaktionsprototypen konzentrieren. Wir beschreiben die Erfahrungen aus der
mehrmaligen Durchführung des Projektes und erläutern unser Vorgehen bei der Umsetzung. Die Ergebnisse sollen Lehrende im Bereich MCI unterstützen, ähnliche praxisorientierte Übungen mit Ergebnissen „zum Anfassen“ zu gestalten.