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Breaking down complexity
(2015)
The unbounded expressive capacity of human language cannot boil down to an infinite list of sentences stored in a finite brain. Our linguistic knowledge is rather grounded around a rule-based universal syntactic computation—called Merge—which takes categorized units in input (e.g. this and ship), and generates structures by binding words recursively into more complex hierarchies of any length (e.g. this ship; this ship sinks…). Here we present data from different fMRI datasets probing the cortical implementation of this fundamental process. We first pushed complexity down to a three-word level, to explore how Merge creates minimally hierarchical phrases and sentences. We then moved to the most fundamental two-word level, to directly assess the universal invariant nature of Merge, when no additive mechanisms are involved. Our most general finding is that Merge as the basic syntactic operation is primarily performed by confined area, namely BA 44 in the IFG. Activity reduces to its most ventral-anterior portion at the most fundamental level, following fine-grained sub-anatomical parcellation proposed for the region. The deep frontal operculum/anterior-dorsal insula (FOP/adINS), a phylogenetically older and less specialized region, rather appears to support word-accumulation processing in which the categorical information of the word is first accessed based on its lexical status, and then maintained on hold before further processing takes place. The present data confirm the general notion of BA 44 being activated as a function of complex structural hierarchy, but they go beyond this view by proposing that structural sensitivity in BA 44 is already appreciated at the lowest levels of complexity during which minimal phrase-structures are build up, and syntactic Merge is assessed. Further, they call for a redefinition of BA 44 from multimodal area to a macro-region with internal localizable functional profiles
Business Process Management has become an integral part of modern organizations in the private and public sector for improving their operations. In the course of Business Process Management efforts, companies and organizations assemble large process model repositories with many hundreds and thousands of business process models bearing a large amount of information. With the advent of large business process model collections, new challenges arise as structuring and managing a large amount of process models, their maintenance, and their quality assurance.
This is covered by business process architectures that have been introduced for organizing and structuring business process model collections. A variety of business process architecture approaches have been proposed that align business processes along aspects of interest, e. g., goals, functions, or objects. They provide a high level categorization of single processes ignoring their interdependencies, thus hiding valuable information. The production of goods or the delivery of services are often realized by a complex system of interdependent business processes. Hence, taking a holistic view at business processes interdependencies becomes a major necessity to organize, analyze, and assess the impact of their re-/design. Visualizing business processes interdependencies reveals hidden and implicit information from a process model collection.
In this thesis, we present a novel Business Process Architecture approach for representing and analyzing business process interdependencies on an abstract level. We propose a formal definition of our Business Process Architecture approach, design correctness criteria, and develop analysis techniques for assessing their quality. We describe a methodology for applying our Business Process Architecture approach top-down and bottom-up. This includes techniques for Business Process Architecture extraction from, and decomposition to process models while considering consistency issues between business process architecture and process model level. Using our extraction algorithm, we present a novel technique to identify and visualize data interdependencies in Business Process Data Architectures. Our Business Process Architecture approach provides business process experts,managers, and other users of a process model collection with an overview that allows reasoning about a large set of process models,
understanding, and analyzing their interdependencies in a facilitated way. In this regard we evaluated our Business Process Architecture approach in an experiment and provide implementations of selected techniques.
The sea level rise induced intensification of coastal floods is a serious threat to many regions in proximity to the ocean. Although severe flood events are rare they can entail enormous damage costs, especially when built-up areas are inundated. Fortunately, the mean sea level advances slowly and there is enough time for society to adapt to the changing environment. Most commonly, this is achieved by the construction or reinforcement of flood defence measures such as dykes or sea walls but also land use and disaster management are widely discussed options. Overall, albeit the projection of sea level rise impacts and the elaboration of adequate response strategies is amongst the most prominent topics in climate impact research, global damage estimates are vague and mostly rely on the same assessment models. The thesis at hand contributes to this issue by presenting a distinctive approach which facilitates large scale assessments as well as the comparability of results across regions. Moreover, we aim to improve the general understanding of the interplay between mean sea level rise, adaptation, and coastal flood damage.
Our undertaking is based on two basic building blocks. Firstly, we make use of macroscopic flood-damage functions, i.e. damage functions that provide the total monetary damage within a delineated region (e.g. a city) caused by a flood of certain magnitude. After introducing a systematic methodology for the automatised derivation of such functions, we apply it to a total of 140 European cities and obtain a large set of damage curves utilisable for individual as well as comparative damage assessments. By scrutinising the resulting curves, we are further able to characterise the slope of the damage functions by means of a functional model. The proposed function has in general a sigmoidal shape but exhibits a power law increase for the relevant range of flood levels and we detect an average exponent of 3.4 for the considered cities. This finding represents an essential input for subsequent elaborations on the general interrelations of involved quantities.
The second basic element of this work is extreme value theory which is employed to characterise the occurrence of flood events and in conjunction with a damage function provides the probability distribution of the annual damage in the area under study. The resulting approach is highly flexible as it assumes non-stationarity in all relevant parameters and can be easily applied to arbitrary regions, sea level, and adaptation scenarios. For instance, we find a doubling of expected flood damage in the city of Copenhagen for a rise in mean sea levels of only 11 cm. By following more general considerations, we succeed in deducing surprisingly simple functional expressions to describe the damage behaviour in a given region for varying mean sea levels, changing storm intensities, and supposed protection levels. We are thus able to project future flood damage by means of a reduced set of parameters, namely the aforementioned damage function exponent and the extreme value parameters. Similar examinations are carried out to quantify the aleatory uncertainty involved in these projections. In this regard, a decrease of (relative) uncertainty with rising mean sea levels is detected. Beyond that, we demonstrate how potential adaptation measures can be assessed in terms of a Cost-Benefit Analysis. This is exemplified by the Danish case study of Kalundborg, where amortisation times for a planned investment are estimated for several sea level scenarios and discount rates.