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An electric traction machine for an electric or a hybrid electric vehicle is usually designed for a specific operating point or cycle. For such an operating point or cycle, the masses and the cooling circuit of the electric machine determine the time dependent temperature distribution within the machine. For a specific load cycle, the thermal simulation of the machine can reveal possible mass and size reductions for a given insulation class of the machine. In addition, such simulations allow the comparison of various cooling concepts. In the machine design process, the first step is a conventional electromagnetic machine design. From the geometric data of this design and the material properties, the parameters of a thermal equivalent circuit can be derived. The differential and algebraic equations of the thermal equivalent circuit are solved by a simulation tool to predict the temperatures of the critical parts in the electric machine. A thermal equivalent circuit is accurate enough to predict the thermal behavior of the critical parts in the electric machine, and yet not too complex, to obtain simulation results with moderate numerical effort. This enables an iterative design process to optimize the drive.
It remains difficult to segregate pelagic habitats since structuring processes are dynamic on a wide range of scales and clear boundaries in the open ocean are non-existent. However, to improve our knowledge about existing ecological niches and the processes shaping the enormous diversity of marine plankton, we need a better understanding of the driving forces behind plankton patchiness. Here we describe a new machine-learning method to detect and quantify pelagic habitats based on hydrographic measurements. An Autoencoder learns two-dimensional, meaningful representations of higher-dimensional micro-habitats, which are characterized by a variety of biotic and abiotic measurements from a high-speed ROTV. Subsequently, we apply a density-based clustering algorithm to group similar micro-habitats into associated pelagic macro-habitats in the German Bight of the North Sea. Three distinct macro-habitats, a “surface mixed layer,” a “bottom layer,” and an exceptionally “productive layer” are consistently identified, each with its distinct plankton community. We provide evidence that the model detects relevant features like the doming of the thermocline within an Offshore Wind Farm or the presence of a tidal mixing front.
One of the tasks PAULE[1, 2] solves is finding suitable control parameter (cp-)trajectories for a given target acoustic. These cp-trajectories can be used to synthesize speech with the articulatory speech synthesizer of the VocalTractLab (VTL) [3]. If the target acoustic contains substantial microphone noise or other background noises, occasionally PAULE optimizes not for the speech in the target, but for this background noises. By adding a speech/non-speech classifier to the feedback and planning-loop in PAULE this resynthesis of background noises should be mitigated. Unfortunately, the improvements were minor, which might be due to uninformative gradients of the classifier. The importance of informative gradients and the use classifiers to adapt PAULE to different tasks are explained and discussed.
There is high confidence for the hypothesis that in speech perception the cycles of a θ-oscillation segment the auditory signal into syllables [8]. Yet the functionality of the oscillator generating the θ-oscillation is unknown. We follow the finding that, within an auditory scene, speech is perceived as a stream given by temporal coherence [12]. We work with the hypotheses that the θ-oscillator is driven by temporal features providing this coherence. We propose a new temporal feature called O-distance, which detects the onset of a syllable - the starting point to of a θ-cycle–triggered by the temporal distance from to to the instance of the maximal rise of the loudness curve of the vowel. To extract to from the auditory signal, we use the statistical properties of this distance based on the C-center hypothesis [25], which predicts a close temporal relation of the onset consonants to the onset of a vowel. The statistics are derived from reference O-distance extracted from an articulatory database, where the minima and maxima of the loudness are related to maxima and minima of the lower incisor and tongue tip. To judge the quality of the O-distance extracted from the auditory signal, we regard the temporal deviation of the O-distance to the reference O-distance. Currently we achieve a mean deviation of 34ms.
This paper addresses the challenges and advancements in speech recognition for singing, a domain distinctly different from standard speech recognition. Singing encompasses unique challenges, including extensive pitch variations, diverse vocal styles, and background music interference. We explore key areas such as phoneme recognition, language identification in songs, keyword spotting, and full lyrics transcription. I will describe some of my own experiences when performing research on these tasks just as they were starting to gain traction, but will also show how recent developments in deep learning and large-scale datasets have propelled progress in this field. My goal is to illuminate the complexities of applying speech recognition to singing, evaluate current capabilities, and outline future research directions.
Measured building survey
(2022)
The precisely measured documentation of historical buildings by means of drawings – the building survey – serves several purposes: it is not only an important part of the scientific study of architecture, but also an essential basis for building measures in existing contexts. It is the only way to undertake well-founded research respectively detailed architectural planning, from structural improvement to conservation and restoration measures. In addition to a historical overview of building surveying as a method, this volume mainly offers practical assistance regarding the different methods for documenting historic buildings – starting from manual methods of measuring up to electronic and computer-aided utilities available today. The content is complemented by many illustrations and examples as well as an introduction to methods, that go beyond the mere graphic documentation and thus represent ways of conducting thorough building examinations. The book offers easy access to the topic of building surveying, both for students as well as for anyone dealing professionally with historic buildings