Optical Flow on Moving Manifolds

Optical flow is a powerful tool for the study and analysis of motion in a sequence of images. In this article we study a Horn-Schunck type spatio-temporal regularization functional for image sequences that have a non-Euclidean, time varying image domain. To that end we construct a Riemannian metric that describes the deformation and structure of this evolving surface. The resulting functional can be seen as natural geometric generalization of previous work by Weickert and Schn\"orr (2001) and Lef\`evre and Baillet (2008) for static image domains. In this work we show the existence and wellposedness of the corresponding optical flow problem and derive necessary and sufficient optimality conditions. We demonstrate the functionality of our approach in a series of experiments using both synthetic and real data.Comment: 26 pages, 6 figure

Model-independent determination of the gluon condensate in four-dimensional SU(3) gauge theory

We determine the non-perturbative gluon condensate of four-dimensional SU(3) gauge theory in a model independent way. This is achieved by carefully subtracting high order perturbation theory results from non-perturbative lattice QCD determinations of the average plaquette. No indications of dimension two condensates are found. The value of the gluon condensate turns out to be of a similar size as the intrinsic ambiguity inherent to its definition.Comment: 5 pages, 5 figures, v2: references added, conclusions improved, contrast of figures improved, 1 typo correcte

Simulation homogener Diesel-Brennverfahren

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Machine Learning in SME: An Empirical Study on Enablers and Success Factors

Machine learning (ML) techniques are rapidly evolving, both in academia and practice. However, enterprises show different maturity levels in successfully implementing ML techniques. Thus, we review the state of adoption of ML in enterprises. We find that ML technologies are being increasingly adopted in enterprises, but that small and medium-size enterprises (SME) are struggling with the introduction in comparison to larger enterprises. In order to identify enablers and success factors we conduct a qualitative empirical study with 18 companies in different industries. The results show that especially SME fail to apply ML technologies due to insufficient ML knowhow. However, partners and appropriate tools can compensate this lack of resources. We discuss approaches to bridge the gap for SME

Assessment of a newly designed double-barreled bullet-shooting stunner for adequate stunning of water buffaloes

To ensure animal welfare at slaughter, rapid stunning is required to render the animal deeply unconscious. In cattle, captive-bolt stunners are typically used for this purpose. However, with regard to their impact force and maximum length of approximately 120 mm, such captive-bolt stunners are not suitable for stunning water buffaloes due to anatomical characteristics of the skull. In water buffaloes the bone layer is thicker and the distance from the point of attachment of the captive-bolt stunner to the relevant brain region is longer. For this reason, a special bullet-shooting stunner was developed, which is similar in size and handling to a standard captive-bolt stunner, but instead of a bolt, it fires a bullet. Actually, even two bullets can be loaded so that a follow-up shot can be fired immediately if necessary. In this study, the bullet-shooting stunner was tested using two different types of hunting ammunition for stunning water buffaloes during regular slaughter

BigBovid- Evaluation of a Newly Developed 9 mm Bullet-Shooting Stunner for Adequate Stunning of Heavy Cattle

The stunning of heavy cattle and water buffalo is an animal welfare problem, as conventional cartridge fired captive-bolt stunners are not suitable due to the thicker skull bones and the greater depth of penetration required to reach and damage the relevant brain regions for deep unconsciousness. This current animal welfare problem requires a suitable and feasible as well as commercially available and legally approved stunning device to ensure deep unconsciousness of these animals. In this study, the use of a newly developed bullet-shooting stunner, the BigBovid, with two different types of hunting ammunition, namely .38 SPL FMJ-TC and .357 MAG FTX ® bullets, was evaluated on 22 heavy cattle (mean weight: 1062.27 kg, standard deviation: 124.09 kg). In ballistic experiments, the BigBovid reached a mean energy density of 8.18 J/mm2 (mean error: 0.45 J/mm2) for the .38 SPL FMJ-TC and 17.56 J/mm2 (mean error: 2.67 J/mm2) for the .357 MAG FTX ®. In in vivo experiments, the use of the .38 SPL FMJ-TC resulted in overpenetration three times. The .357 MAG FTX ® bullets showed to be more advantageous, because on the one hand no overpenetration occurred and on the other hand the bullets fragmented into small parts after penetration into the skull. The fragments were scattered in the brain tissue, such as the thalamus and the brain stem, and thus there is a high probability to damage the brain regions relevant for deep unconsciousness. Based on the results of this study, the use of the BigBovid in combination with the .357 MAG FTX ® bullet is found to be suitable for stunning heavy cattle. Keywords: animal welfare; concussion; desensitization; heavy bulls; slaughterin

Towards an Evaluation Framework for Threat Intelligence Sharing Platforms

Threat intelligence sharing is an important countermeasure against the increasing number of security threats to which companies and governments are exposed. Its objective is the cross-organizational exchange of information about actual and potential threats. In recent years, a heterogeneous market of threat intelligence sharing platforms (TISPs) has emerged. These platforms are inter-organizational systems that support collaborative collection, aggregation, analysis and dissemination of threat-related information. Organizations that consider using TISPs are often faced with the challenge of selecting suitable platforms. To facilitate the evaluation of threat intelligence sharing platforms, we present a framework for analyzing and comparing relevant TISPs. Our framework provides a set of 25 functional and non-functional criteria that support potential users in selecting suitable platforms. We demonstrate the applicability of our evaluation framework by assessing three platforms: MISP, OTX and ThreatQ. We describe common features and differences between the three platforms