Example-Based Urban Modeling

The manual modeling of virtual cities or suburban regions is an extremely time-consuming task, which expects expert knowledge of different fields. Existing modeling tool-sets have a steep learning curve and may need special education skills to work with them productively. Existing automatic methods rely on rule sets and grammars to generate urban structures; however, their expressiveness is limited by the rule-sets. Expert skills are necessary to typeset rule sets successfully and, in many cases, new rule-sets need to be defined for every new building style or street network style. To enable non-expert users, the possibility to construct urban structures for individual experiments, this work proposes a portfolio of novel example-based synthesis algorithms and applications for the controlled generation of virtual urban environments. The notion example-based denotes here that new virtual urban environments are created by computer programs that re-use existing digitized real-world data serving as templates. The data, i.e., street networks, topography, layouts of building footprints, or even 3D building models, necessary to realize the envisioned task is already publicly available via online services. To enable the reuse of existing urban datasets, novel algorithms need to be developed by encapsulating expert knowledge and thus allow the controlled generation of virtual urban structures from sparse user input. The focus of this work is the automatic generation of three fundamental structures that are common in urban environments: road networks, city block, and individual buildings. In order to achieve this goal, the thesis proposes a portfolio of algorithms that are briefly summarized next. In a theoretical chapter, we propose a general optimization technique that allows formulating example-based synthesis as a general resource-constrained k-shortest path (RCKSP) problem. From an abstract problem specification and a database of exemplars carrying resource attributes, we construct an intermediate graph and employ a path-search optimization technique. This allows determining either the best or the k-best solutions. The resulting algorithm has a reduced complexity for the single constraint case when compared to other graph search-based techniques. For the generation of road networks, two different techniques are proposed. The first algorithm synthesizes a novel road network from user input, i.e., a desired arterial street skeleton, topography map, and a collection of hierarchical fragments extracted from real-world road networks. The algorithm recursively constructs a novel road network reusing these fragments. Candidate fragments are inserted into the current state of the road network, while shape differences will be compensated by warping. The second algorithm synthesizes road networks using generative adversarial networks (GANs), a recently introduced deep learning technique. A pre- and postprocessing pipeline allows using GANs for the generation of road networks. An in-depth evaluation shows that GANs faithfully learn the road structure present in the example network and that graph measures such as area, aspect ratio, and compactness, are maintained within the virtual road networks. To fill empty city blocks in road networks we propose two novel techniques. The first algorithm re-uses real-world city blocks and synthesizes building footprint layouts into empty city blocks by retrieving viable candidate blocks from a database. We evaluate the algorithm and synthesize a multitude of city block layouts reusing real-world building footprint arrangements from European and US-cities. In addition, we increase the realism of the synthesized layouts by performing example-based placement of 3D building models. This technique is evaluated by placing buildings onto challenging footprint layouts using different example building databases. The second algorithm computes a city block layout, resembling the style of a real-world city block. The original footprint layout is deformed to construct a textit{guidance map}, i.e., the original layout is transferred to a target city block using warping. This guidance map and the original footprints are used by an optimization technique that computes a novel footprint layout along the city block edges. We perform a detailed evaluation and show that using the guidance map allows transferring of the original layout, locally as well as globally, even when the source and target shapes drastically differ. To synthesize individual buildings, we use the general optimization technique described first and formulate the building generation process as a resource-constrained optimization problem. From an input database of annotated building parts, an abstract description of the building shape, and the specification of resource constraints such as length, area, or a number of architectural elements, a novel building is synthesized. We evaluate the technique by synthesizing a multitude of challenging buildings fulfilling several global and local resource constraints. Finally, we show how this technique can even be used to synthesize buildings having the shape of city blocks and might also be used to fill empty city blocks in virtual street networks. All algorithms presented in this work were developed to work with a small amount of user input. In most cases, simple sketches and the definition of constraints are enough to produce plausible results. Manual work is necessary to set up the building part databases and to download example data from mapping services available on the Internet

Language in Language Evolution Research: In Defense of a Pluralistic View

Many controversies in language evolution research derive from the fact that language is itself a natural language word, which makes the underlying concept fuzzy and cumbersome, and a common perception is that progress in language evolution research is hindered because researchers do not ‘talk about the same thing’. In this article, we claim that agreement on a single, top-down definition of language is not a sine qua non for good and productive research in the field of language evolution. First, we use the example of the notion FLN (‘faculty of language in the narrow sense’) to demonstrate how the specific wording of an important top-down definition of (the faculty of) language can—surprisingly—be inconsequential to actual research practice. We then review four approaches to language evolution that we estimate to be particularly influential in the last decade. We show how their breadth precludes a single common conceptualization of language but instead leads to a family resemblance pattern, which underwrites fruitful communication between these approaches, leading to cross-fertilisation and synergies

Monotonic and fatigue properties of steel material manufactured by wire arc additive manufacturing

In this study, the monotonic and cyclic material properties of steel material of medium static strength produced additively in the wire arc additive manufacturing (WAAM) process were investigated. This investigated material is expected to be particularly applicable to the field of mechanical engineering, for which practical applications of the WAAM process are still pending and for which hardly any characteristic values can be found in the literature so far. The focus of the investigation was, on the one hand, to determine how the material characteristics are influenced by the load direction in relation to the layered structure and, on the other hand, how they are affected by different interlayer temperatures. For this purpose, monotonic tensile tests were carried out at room temperature as well as at elevated temperatures, and the cyclic material properties were determined. In addition, the hardness of the material and the residual stresses induced during production were measured and compared. In addition to the provision of characteristic properties for the investigated material, it was aimed to determine the extent to which the interlayer temperature influences the strength characteristics, since this can have a considerable influence on the production times and, thus, the economic efficiency of the process

Ability of 18F-FDG Positron Emission Tomography Radiomics and Machine Learning in Predicting KRAS Mutation Status in Therapy-Naive Lung Adenocarcinoma.

OBJECTIVE Considering the essential role of KRAS mutation in NSCLC and the limited experience of PET radiomic features in KRAS mutation, a prediction model was built in our current analysis. Our model aims to evaluate the status of KRAS mutants in lung adenocarcinoma by combining PET radiomics and machine learning. METHOD Patients were retrospectively selected from our database and screened from the NSCLC radiogenomic dataset from TCIA. The dataset was randomly divided into three subgroups. Two open-source software programs, 3D Slicer and Python, were used to segment lung tumours and extract radiomic features from 18F-FDG-PET images. Feature selection was performed by the Mann-Whitney U test, Spearman's rank correlation coefficient, and RFE. Logistic regression was used to build the prediction models. AUCs from ROCs were used to compare the predictive abilities of the models. Calibration plots were obtained to examine the agreements of observed and predictive values in the validation and testing groups. DCA curves were performed to check the clinical impact of the best model. Finally, a nomogram was obtained to present the selected model. RESULTS One hundred and nineteen patients with lung adenocarcinoma were included in our study. The whole group was divided into three datasets: a training set (n = 96), a validation set (n = 11), and a testing set (n = 12). In total, 1781 radiomic features were extracted from PET images. One hundred sixty-three predictive models were established according to each original feature group and their combinations. After model comparison and selection, one model, including wHLH_fo_IR, wHLH_glrlm_SRHGLE, wHLH_glszm_SAHGLE, and smoking habits, was validated with the highest predictive value. The model obtained AUCs of 0.731 (95% CI: 0.619~0.843), 0.750 (95% CI: 0.248~1.000), and 0.750 (95% CI: 0.448~1.000) in the training set, the validation set and the testing set, respectively. Results from calibration plots in validation and testing groups indicated that there was no departure between observed and predictive values in the two datasets (p = 0.377 and 0.861, respectively). CONCLUSIONS Our model combining 18F-FDG-PET radiomics and machine learning indicated a good predictive ability of KRAS status in lung adenocarcinoma. It may be a helpful non-invasive method to screen the KRAS mutation status of heterogenous lung adenocarcinoma before selected biopsy sampling

Conventionalisation and discrimination as competing pressures on continuous speech-like signals

© John Benjamins Publishing Company. Arbitrary communication systems can emerge from iconic beginnings through processes of conventionalisation via interaction. Here, we explore whether this process of conventionalisation occurs with continuous, auditory signals. We conducted an artificial signalling experiment. Participants either created signals for themselves, or for a partner in a communication game. We found no evidence that the speech-like signals in our experiment became less iconic or simpler through interaction. We hypothesise that the reason for our results is that when it is difficult to be iconic initially because of the constraints of the modality, then iconicity needs to emerge to enable grounding before conventionalisation can occur. Further, pressures for discrimination, caused by the expanding meaning space in our study, may cause more complexity to emerge, again as a result of the restrictive signalling modality. Our findings have possible implications for the processes of conventionalisation possible in signed and spoken languages, as the spoken modality is more restrictive than the manual modality

Korpusdokumentation des SiGS-Korpus der Hexenverhörprotokolle

Die vorliegende Korpusdokumentation informiert über die Mehr-Ebenen-Annotation des SiGS-Korpus der Hexenverhörprotokolle. Die Annotation des Korpus umfasst graphematische und syntaktische Tokenisierung, Lemmatisierung, POS-Tagging, Belebtheitskategorisierung von Nomina, Satzgrenzen, semantische Rollen und Satzglieder. Sie ist im Rahmen des DFG-Projekts zur 'Entwicklung der satzinternen Großschreibung im Deutschen' unter Leitung von Renata Szczepaniak (2013-2019) und Klaus-Michael Köpcke (2013-2015) (Projektnummer 228096696) entstande

Detection of inspiratory recruitment of atelectasis by automated lung sound analysis as compared to four-dimensional computed tomography in a porcine lung injury model

Background: Cyclic recruitment and de-recruitment of atelectasis (c-R/D) is a contributor to ventilator-induced lung injury (VILI). Bedside detection of this dynamic process could improve ventilator management. This study investigated the potential of automated lung sound analysis to detect c-R/D as compared to four-dimensional computed tomography (4DCT). Methods: In ten piglets (25 ± 2 kg), acoustic measurements from 34 thoracic piezoelectric sensors (Meditron ASA, Norway) were performed, time synchronized to 4DCT scans, at positive end-expiratory pressures of 0, 5, 10, and 15 cmH2O during mechanical ventilation, before and after induction of c-R/D by surfactant washout. 4DCT was post-processed for within-breath variation in atelectatic volume (Δ atelectasis) as a measure of c-R/D. Sound waveforms were evaluated for: 1) dynamic crackle energy (dCE): filtered crackle sounds (600–700 Hz); 2) fast Fourier transform area (FFT area): spectral content above 500 Hz in frequency and above −70 dB in amplitude in proportion to the total amount of sound above −70 dB amplitude; and 3) dynamic spectral coherence (dSC): variation in acoustical homogeneity over time. Parameters were analyzed for global, nondependent, central, and dependent lung areas. Results: In healthy lungs, negligible values of Δ atelectasis, dCE, and FFT area occurred. In lavage lung injury, the novel dCE parameter showed the best correlation to Δ atelectasis in dependent lung areas (R2 = 0.88) where c-R/D took place. dCE was superior to FFT area analysis for each lung region examined. The analysis of dSC could predict the lung regions where c-R/D originated. Conclusions: c-R/D is associated with the occurrence of fine crackle sounds as demonstrated by dCE analysis. Standardized computer-assisted analysis of dCE and dSC seems to be a promising method for depicting c-R/D