(E)motion pictures : zwischen Authentizität und Künstlichkeit ; Konzertfilme von Bob Dylan bis Neil Young

Schon im Jahr 1970 rechnet der noch junge und von Film und Rockmusik gleichermaßen begeisterte Wim Wenders mit einem Genre ab, "das es nicht gibt": mit dem Musikfilm, vor allem mit den "Rock'n'Roll- und Popmusikfilmen" (Wenders 1989, 82), die bis dato entstanden und denen er insgesamt vorwirft, gerade an der Darstellung der Musik zu scheitern. "Sie zeigen mehr ihr Desinteresse, ihr Missfallen oder ihre Verachtung als ihren Gegenstand. Das, was es zu sehen gibt, die Musiker, die Instrumente, die Bühne, die Arbeit, der Spaß oder die Anstrengung, Musik zu machen, erscheint ihnen nicht wert genug, so wie es ist, gezeigt zu werden" (83). Wenders wirft den Musikfilmen vor, nicht dem authentischen Entstehen der Musik im Augenblick, also live auf der Bühne, und nicht dem Ausdruck der Musik gerecht werden, sondern die eigene Sprache der Rockmusik in eine andere, in die des Films zu übertragen

The Power of the Weisfeiler-Leman Algorithm to Decompose Graphs

The Weisfeiler-Leman procedure is a widely-used approach for graph isomorphism testing that works by iteratively computing an isomorphism-invariant coloring of vertex tuples. Meanwhile, a fundamental tool in structural graph theory, which is often exploited in approaches to tackle the graph isomorphism problem, is the decomposition into 2- and 3-connected components. We prove that the 2-dimensional Weisfeiler-Leman algorithm implicitly computes the decomposition of a graph into its 3-connected components. Thus, the dimension of the algorithm needed to distinguish two given graphs is at most the dimension required to distinguish the corresponding decompositions into 3-connected components (assuming it is at least 2). This result implies that for k >= 2, the k-dimensional algorithm distinguishes k-separators, i.e., k-tuples of vertices that separate the graph, from other vertex k-tuples. As a byproduct, we also obtain insights about the connectivity of constituent graphs of association schemes. In an application of the results, we show the new upper bound of k on the Weisfeiler-Leman dimension of graphs of treewidth at most k. Using a construction by Cai, F\"urer, and Immerman, we also provide a new lower bound that is asymptotically tight up to a factor of 2.Comment: 30 pages, 4 figures, full version of a paper accepted at MFCS 201

Artificial Intelligence in Supply Chain Management: Investigation of Transfer Learning to Improve Demand Forecasting of Intermittent Time Series with Deep Learning

Demand forecasting intermittent time series is a challenging business problem. Companies have difficulties in forecasting this particular form of demand pattern. On the one hand, it is characterized by many non-demand periods and therefore classical statistical forecasting algorithms, such as ARIMA, only work to a limited extent. On the other hand, companies often cannot meet the requirements for good forecasting models, such as providing sufficient training data. The recent major advances of artificial intelligence in applications are largely based on transfer learning. In this paper, we investigate whether this method, originating from computer vision, can improve the forecasting quality of intermittent demand time series using deep learning models. Our empirical results show that, in total, transfer learning can reduce the mean square error by 65 percent. We also show that especially short (65 percent reduction) and medium long (91 percent reduction) time series benefit from this approach

Beating resonance patterns and orthogonal wave propagation due to zero-group-velocity guided elastic waves

Elastic waves in anisotropic media can exhibit a power flux that is not collinear with the wave vector. We show that this has remarkable consequences for the zero-group-velocity (ZGV) resonances that appear in an infinite plate. True ZGV resonances, in the sense that the guided wave's overall power flux vanishes while its wavelength remains finite, are only found when the wave vector is oriented along a principal axis of the material. At other propagation angles, "quasi-ZGV" waves are found for which the power flux is orthogonal to the wave vector. We present original measurements of such a wave field in a single crystal silicon wafer. As a consequence of the nonzero power flux of qZGV waves, time acts as a filter in the wave vector domain that selects precisely the eight plane waves corresponding to true ZGV resonances. This intuitively explains the highly symmetric resonance pattern that emerges naturally on the surface of the plate after a pulsed point source excitation. We showcase a direct measurement of this beating pattern. The developed physical understanding paves the way towards novel designs of surface acoustic wave devices and is of high relevance for ultrasonic nondestructive evaluation.Comment: 10 pages, 9 figure

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

The Time has Come – Application of Artificial Intelligence in Small- and Medium-Sized Enterprises

Artificial intelligence (AI) is not yet widely used in small- and medium-sized industrial enterprises (SME). The reasons for this are manifold and range from not understanding use cases, not enough trained employees, to too little data. This article presents a successful design-oriented case study at a medium-sized company, where the described reasons are present. In this study, future demand forecasts are generated based on historical demand data for products at a material number level using a gradient boosting machine (GBM). An improvement of 15% on the status quo (i.e. based on the root mean squared error) could be achieved with rather simple techniques. Hence, the motivation, the method, and the first results are presented. Concluding challenges, from which practical users should derive learning experiences and impulses for their own projects, are addressed

Digital Innovation Culture: A Systematic Literature Review

Digitalization increases the pressure for companies to innovate. While current research on digital transformation mostly focuses on technological and management aspects, less attention has been paid to organizational culture and its influence on digital innovations. The purpose of this paper is to identify the characteristics of organizational culture that foster digital innovations. Based on a systematic literature review on three scholarly databases, we initially found 778 articles that were then narrowed down to a total number of 23 relevant articles through a methodical approach. After analyzing these articles, we determine nine characteristics of organizational culture that foster digital innovations: corporate entrepreneurship, digital awareness and necessity of innovations, digital skills and resources, ecosystem orientation, employee participation, agility and organizational structures, error culture and risk-taking, internal knowledge sharing and collaboration, customer and market orientation as well as open-mindedness and willingness to learn

Relativistic electron mirrors from high intensity laser nanofoil interactions

The reflection of a laser pulse from a mirror moving close to the speed of light could in principle create an X-ray pulse with unprecedented high brightness owing to the increase in photon energy and accompanying temporal compression by a factor of $4\gamma^2$, where $\gamma$ is the Lorentz factor of the mirror. While this scheme is theoretically intriguingly simple and was first discussed by A. Einstein more than a century ago, the generation of a relativistic structure which acts as a mirror is demanding in many different aspects. Recently, the interaction of a high intensity laser pulse with a nanometer thin foil has raised great interest as it promises the creation of a dense, attosecond short, relativistic electron bunch capable of forming a mirror structure that scatters counter-propagating light coherently and shifts its frequency to higher photon energies. However, so far, this novel concept has been discussed only in theoretical studies using highly idealized interaction parameters. This thesis investigates the generation of a relativistic electron mirror from a nanometer foil with current state-of-the-art high intensity laser pulses and demonstrates for the first time the reflection from those structures in an experiment. To achieve this result, the electron acceleration from high intensity laser nanometer foil interactions was studied in a series of experiments using three inherently different high power laser systems and free-standing foils as thin as 3nm. A drastic increase in the electron energies was observed when reducing the target thickness from the micrometer to the nanometer scale. Quasi-monoenergetic electron beams were measured for the first time from ultrathin ($\leq$5nm) foils, reaching energies up to ~35MeV. The acceleration process was studied in simulations well-adapted to the experiments, indicating the transition from plasma to free electron dynamics as the target thickness is reduced to the few nanometer range. The experience gained from those studies allowed proceeding to the central goal, the demonstration of the relativistically flying mirror, which was achieved at the Astra Gemini dual beam laser facility. In this experiment, a frequency shift in the backscatter signal from the visible (800nm) to the extreme ultraviolet (~60nm) was observed when irradiating the interaction region with a counter-propagating probe pulse simultaneously. Complementary to the experimental observations, a detailed numerical study on the dual beam interaction is presented, explaining the mirror formation and reflection process in great depth, indicating a $>10^4$ fold increase in the backscatter efficiency as compared to the expected incoherent signal. The simulations show that the created electron mirrors propagate freely at relativistic velocities while reflecting off the counter-propagating laser, thereby truly acting like the relativistic mirror first discussed in Einstein's thought experiment. The reported work gives an intriguing insight into the electron dynamics in high intensity laser nanofoil interactions and constitutes a major step towards the coherent backscattering from a relativistic electron mirror of solid density, which could potentially generate bright bursts of X-rays on a micro-scale

The First Detection of \u3ci\u3eCeratophyllus\u3c/i\u3e Fleas and an Ischnocera Louse on the Great Cormorant \u3ci\u3ePhalacrocorax carbo\u3c/i\u3e in Mongolia

There are summarized data on ectoparasites of Mongolian birds. The Mongolian-German Biological Expeditions found first records for the flea Ceratophyllus vagabundus and the Ischnocera louse Pectinopygus gyricornis at the host Phalacrocorax carbo