In the last decades, there has been an increasing interest in animal protection and welfare issues. Heart rate variability (HRV) measurement with portable heart rate monitors on cows has established itself as a suitable method for assessing physiological states. However, more forward-looking technologies, already successfully applied to evaluate HRV data, are pushing the market. This study examines the validity and usability of collecting HRV data by exchanging the Polar watch V800 as a receiving unit of the data compared to a custom smartphone application on cows. Therefore, both receivers tap one signal sent by the Polar H7 transmitter simultaneously. Furthermore, there is a lack of suitable methods for the preparation and calculation of HRV parameters, especially for livestock. A method is presented for calculating more robust time domain HRV parameters via median formation. The comparisons of the respective simultaneous recordings were conducted after artifact correction for time domain HRV parameters. High correlations (r = 0.82–0.98) for cows as well as for control data set in human being (r = 0.98–0.99) were found. The utilization of smart devices and the robust method to determine time domain HRV parameters may be suitable to generate valid HRV data on cows in field-based settings.

ABSTRACT:Data acquisition using unmanned aerial vehicles (UAVs) has gotten more and more attention over the last years. Especially in the field of building reconstruction the incremental interpretation of such data is a demanding task. In this context formal grammars play an important role for the top-down identification and reconstruction of building objects. Up to now, the available approaches expect offline data in order to parse an a-priori known grammar. For mapping on demand an on the fly reconstruction based on UAV data is required. An incremental interpretation of the data stream is inevitable. This paper presents an incremental parser of grammar rules for an automatic 3D building reconstruction. The parser enables a model refinement based on new observations with respect to a weighted attribute context-free grammar (WACFG). The falsification or rejection of hypotheses is supported as well. The parser can deal with and adapt available parse trees acquired from previous interpretations or predictions. Parse trees derived so far are updated in an iterative way using transformation rules. A diagnostic step searches for mismatches between current and new nodes. Prior knowledge on façades is incorporated. It is given by probability densities as well as architectural patterns. Since we cannot always assume normal distributions, the derivation of location and shape parameters of building objects is based on a kernel density estimation (KDE). While the level of detail is continuously improved, the geometrical, semantic and topological consistency is ensured. MOTIVATION AND CONTEXT3D building models are nowadays essential for several tasks such as urban and telecommunication planning (Köninger and Bartel, 1998;Knapp and Coors, 2008) and disaster and rescue management (Kolbe et al., 2008) in particular flooding simulations (Schulte and Coors, 2008). Further, the data model CityGML supporting several levels of detail (LoD) is widely used in order to address semantics and exchange city data models. For many applications such as disaster management and visualization in particular in the navigation context, façades (LoD3 models) are important. In order to achieve an interpretation of the observations with good quality models providing prior knowledge are needed. In this context, formal grammars receive increasing attention (Musialski et al., 2012). For the reconstruction of façades Becker (2009) introduced a hybrid approach by the integration of inferred grammar rules into a nonparametric reconstruction process. Ripperda and Brenner (2009) used a probabilistic grammar for the description of façades. The production rules are expanded by the relative frequency of a single rule extracted from a manually collected rule database. Martinović and Van Gool (2013) proposed an approach to learn stochastic attributed grammar rules for two-dimensional façade generation and reconstruction from imagery data. Dehbi et al. (2016) presented a statistical relational based approach for automatic learning of an attribute grammar for bui...

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