Zielgruppe Mittelstand als Herausforderung für Marketing und Vertrieb der ITK-Hersteller : Ergebnisse und Konsequenzen einer empirischen Erhebung

Seitdem die angestammten Zielmärkte der ITK-Hersteller im Bereich der „Großunternehmen“ etwa ab der Jahrtausendwende weitgehend gesättigt sind, versuchen ITK-Hersteller verstärkt die „Zielgruppe Mittelstand“ zu erschlie ßen, um von dem großen Potential dieses Wachstumsmarktes zu profitieren. Jedoch tun sich insbesondere die internationalen Branchengrößen dabei aufgrund diverser Besonderheiten dieser Zielgruppe oftmals noch immer schwer, hier erfolgreich Fuß zu fassen Vor diesem Hintergrund führte die Marketing- und Vertriebsberatung Homburg & Partner eine Befragung unter 124 kleinen und mittelständischen Unternehmen (KMU) aus verschiedenen Branchen zu ihren Anforderungen im Zusammenhang mit ITK-Beschaffungen durch. Ziel der Studie war es, den ITK- Herstellern auf Basis der gewonnenen Erkenntnisse über die Anforderungen des Mittelstandes Ansätze zur Weiterentwicklung ihres mittels tandsgerichteten Marketing und Vertrieb aufzuzeigen. Dabei standen insbesondere die vier Optimierungsbereiche „Finanzierungsmöglichkeiten“, „Preis-/Abrechnungsmodelle“, „Verkäuferpersönlichkeit“ und "Kundenbetreuungsangebote“ im Vordergrund, die auf Basis von Expertengesprächen und einer breiten Literaturrecherche als besonders relevant identifiziert wurden. Die wesentlichen Ergebnisse der Umfrage und ihre Konsequenzen für ITK-Hersteller werden in der vorliegenden Studie dargestellt und diskutiert

Color Screening and Quark-Quark Interactions in Finite Temperature QCD

We analyze the screening of static diquark sources in 2-flavor QCD and compare results with the screening of static quark-antiquark pairs. We show that a two quark system in a fixed color representations is screened at short distances like a single quark source in the same color representation whereas at large distances the two quarks are screened independently. At high temperatures we observe that the relative strength of the interaction in diquark and quark-antiquark systems, respectively, obeys Casimir scaling. We use this result to examine the possible existence of heavy quark-quark bound states in the high temperature phase of QCD. We find support for the existence of $bb$ states up to about $2T_c$ while $cc$ states are unlikely to be formed above $T_c$.Comment: 8 pages, 6 figure

Estimating mixed quantum states

We discuss single adaptive measurements for the estimation of mixed quantum states of qubits. The results are compared to the optimal estimation schemes using collective measurements. We also demonstrate that the advantage of collective measurements increases when the degree of mixing of the quantum states increases.Comment: RevTeX, 7 pages, 4 figure

Modeling and Control of a Cooperative Road Traffic by means of Petri-Nets and Consensus-Algorithms

Die vorliegende Arbeit behandelt die Konzeption eines zukünftigen automatisierten Straßenverkehrs für Autobahnen auf Basis von fahrzeuglokalen Entscheidungsmechanismen und Fahrzeug-Fahrzeug-Kommunikation. Der derzeitige Straßenverkehr zeichnet sich durch unterschiedliches und deviantes Fahrzeug- bzw. Fahrerverhalten aus, dessen Konsequenz Phänomene wie Staus und Verkehrsunfälle sind. Die Homogenisierung des Fahrzeugverhaltens soll diese negativen Phänomene eliminieren und durch autonom fahrende Fahrzeuge, die untereinander kommunizieren können, realisiert werden. Hierzu ist der Entwurf einer fahrzeuglokalen homogenen Regelbasis erforderlich, die das spezifizierte Verkehrsverhalten realisiert. Zu diesem Zweck wird der Straßenverkehr als ein Objektsystem auf Basis von Petrinetzen mit zwei Ebenen modelliert. Die Straßennetzebene bildet das globale Verhalten einer Fahrzeuggruppe ab, während die Formationsnetzebene die Interaktionen zwischen den Fahrzeugen repräsentiert. Durch Kombination von Straßen- und Formationsnetzen werden verschiedene Verkehrssituationen generiert. Mit den jeweils assoziierten Formationsnetzen wird eine Erreichbarkeitsanalyse durchgeführt. In jedem Erreichbarkeitsgraphen werden anschließend Zielzustände identifiziert und ein Pfad zu diesen ermittelt, der ein definiertes Gütemaß minimiert und konsekutiven Interaktionen der Fahrzeuge entspricht. Mittels der Analyse fahrzeuglokaler Umgebungsparameter werden die jeweiligen Aktionen der Fahrzeuge zu einer fahrzeuglokalen Regelbasis kombiniert. Zur Koordination der beteiligten Fahrzeuge wird auf dieser Basis ein Kommunikationsprotokoll definiert, das um Konsens-Algorithmen ergänzt wird, welche die Stabilisierung der Formationen sicherstellen. Resultat sind eine Regelbasis und ein Kommunikationsprotokoll, die als verteiltes Regelungssystem ein Verkehrsverhalten erzeugen, das die Straßenkapazität bestmöglich ausnutzt und Unfälle inhärent vermeidet. Ein Rahmenwerk ermöglicht neben der Unterstützung beim Entwurf der Regelbasis auch eine fahrphysikalische Simulation von Fahrzeuggruppen auf begrenzten Fahrbahnabschnitten, sodass das hieraus resultierende Verkehrsverhalten erkennbar wird.This contribution presents a concept of a future automated road traffic for highways, based on vehicle-local decision-making and car2car communication. Present road traffic is characterized by varying and deviant vehicles' and drivers' behavior, that results in phenomena as traffic jams and accidents. A homogenization of the vehicles' behavior shall be a remedy against this, by means of autonomous driving and communicating vehicles. Main objective is the development of a vehicle-local homogenous rule-base realizing a specified traffic behavior. For this purpose road traffic is modeled as an object system by means of Petri Nets, consisting of a system net and an object net. The system net represents the road network, whereas an object net is a representation of a vehicle formation. This concept is used to model different traffic scenarios. For each associated formation net the reachability graph is calculated and analyzed regarding target states and their shortest paths minimizing the predefined cost function. The shortest paths are equivalent to consecutive vehicle interactions, which are furthermore mapped to vehicle-local environmental parameters to construct a well-defined rule-base. For the coordination between the vehicles an associated communication protocol is generated and combined with consensus-algorithms to ensure stability of the vehicle formations. Result is a rule-base realizing a distributed vehicle control which inherently avoids accidents while utilizing full road capacity. According to this, a framework offers, besides support at the rule-base generation, the simulation of the resulting collective behavior of a scalable vehicle formation in certain traffic scenarios with high physical insight

Nanotrimer enhanced optical fiber tips implemented by electron beam lithography

Here we present a novel fabrication approach that allows for the implementation of sophisticated planar nanostructures with deep subwavelength dimensions on fiber end faces by electron beam lithography. Specifically, we planarize the end faces of fiber bundles such that they are compatible with planar nanostructuring technology, with the result that fibers can be treated in the same way as typical wafers, opening up the entire field of nanotechnology for fiber optics. To demonstrate our approach, we have implemented densely-packed arrays of gold nanotrimers on the end face of 50 cm long standard single mode fibers, showing asymmetrical resonance lineshapes that arise due to the interplay of diffractive coupling of the individual timer response at infrared wavelengths that overlap with the single mode regime of typical telecommunication fibers. Refractive index sensing experiments suggest sensitivities of about 390 nm/RIU, representing the state-of-the-art for such a device type. Due to its unique capability of making optical fibers compatible with planar nanostructuring technology, we anticipate our approach to be applied in numerous fields including bioanalytics, telecommunications, nonlinear photonics, optical trapping and beam shaping

Nanograting-Enhanced Optical Fibers for Visible and Infrared Light Collection at Large Input Angles

The efficient incoupling of light into particular fibers at large angles is essential for a multitude of applications; however, this is difficult to achieve with commonly used fibers due to low numerical aperture. Here, we demonstrate that commonly used optical fibers functionalized with arrays of metallic nanodots show substantially improved large-angle light-collection performances at multiple wavelengths. In particular, we show that at visible wavelengths, higher diffraction orders contribute significantly to the light-coupling efficiency, independent of the incident polarization, with a dominant excitation of the fundamental mode. The experimental observation is confirmed by an analytical model, which directly suggests further improvement in incoupling efficiency through the use of powerful nanostructures such as metasurface or dielectric gratings. Therefore, our concept paves the way for high-performance fiber-based optical devices and is particularly relevant within the context of endoscopic-type applications in life science and light collection within quantum technology

A Compartmented Flow Microreactor System for Automated Optimization of Bioprocesses Applying Immobilized Enzymes

In the course of their development, industrial biocatalysis processes have to be optimized in small-scale, e. g., within microfluidic bioreactors. Recently, we introduced a novel microfluidic reactor device, which can handle defined reaction compartments of up to 250 μL in combination with magnetic micro carriers. By transferring the magnetic carriers between subsequent compartments of differing compositions, small scale synthesis, and bioanalytical assays can be conducted. In the current work, this device is modified and extended to broaden its application range to the screening and optimization of bioprocesses applying immobilized enzymes. Besides scaling the maximum compartment volume up to 3 mL, a temperature control module, as well as a focused infrared spot were integrated. By adjusting the pump rate, compartment volumes can be accurately dosed with an error <5% and adjusted to the requested temperature within less than a minute. For demonstration of bioprocess parameter optimization within such compartments, the influence of pH, temperature, substrate concentration, and enzyme carrier loading was automatically screened for the case of transferring UDP-Gal onto N-acetylglucosamine linked to a tert-butyloxycarbonyl protected amino group using immobilized β1,4-galactosyltransferase-1. In addition, multiple recycling of the enzyme carriers and the use of increased compartment volumes also allows the simple production of preparative amounts of reaction products

Method For Creating A Control Cabinet Model With Realistic Wires

During the assembly of a control cabinet, a major time-consuming step is the wiring of the included components. Hence, automating this step will noticeably reduce production costs. According to the planning, wires are routed through wire ducts and connected to components. While a comprehensive digital twin can be computed for the included components, this twin is missing a proper modelling of the connecting wires. For these, only a rough route through the wire ducts is given. However, a physically plausible model is an important prerequisite to perform reliable path planning for automated assembly. The paper addresses this need for accurate wire path computation during automated cabinet assembly and introduces a method to compute realistic wire paths through the wire ducts. Different models with and without a fixed wire length are presented and compared. An evolutionary algorithm optimizes the corresponding variables of the models. As described, both approaches yield valid paths, although the fixed length model appears to be able to compute more realistic paths

Nanoboomerang-based inverse metasurfaces - a promising path towards ultrathin photonic devices for transmission operation

Metasurfaces have revolutionized photonics due to their ability to shape phase fronts as requested and to tune beam directionality using nanoscale metallic or dielectric scatterers. Here we reveal inverse metasurfaces showing superior properties compared to their positive counterparts if transmission mode operation is considered. The key advantage of such slot-type metasurfaces is the strong reduction of light in the parallel-polarization state, making the crossed-polarization, being essential for metasurface operation, dominant and highly visible. In the experiment, we show an up to four times improvement in polarization extinction for the individual metasurface element geometry consisting of deep subwavelength nanoboomerangs with feature sizes of the order of 100 nm. As confirmed by simulations, strong plasmonic hybridization yields two spectrally separated plasmonic resonances, ultimately allowing for the desired phase and scattering engineering in transmission. Due to the design flexibility of inverse metasurfaces, a large number of highly integrated ultra-flat photonic elements can be envisioned, examples of which include monolithic lenses for telecommunications and spectroscopy, beam shaper or generator for particle trapping or acceleration or sophisticated polarization control for microscopy

The Potential of AutoML for Demand Forecasting

In demand forecasting, which can depend on various internal and external factors, machine learning (ML) methods can capture complex patterns and enable precise forecasts. Accurate forecasts facilitate targeted, demand-oriented planning and control of production and underline the importance of this task. The implementation of ML-algorithms requires knowledge of the specific domain as well as knowledge of data science and involves an elaborate set up process. This often makes the application of ML to potential industrial problems economically unattractive. The major skills shortage in the field of data science further exacerbates this. Automation and better accessibility of ML methods is therefore a key prerequisite for widespread use. This is where the principle of automated ML (AutoML) comes in, automating large parts of a ML pipeline and thus leading to a reduction in human labour input. Therefore, the aim of the publication is to investigate the extent to which AutoML solutions can generate added value for demand planning in the context of production planning and control. For this purpose, publicly available datasets deriving from Walmart as well as an anonymised manufacturing company are used for short-term and long-term forecasting. The AutoML tools from Microsoft, Dataiku and Google conduct these forecasts. Statistical models serve as benchmarks. The results show that the forecasting quality varies depending on the software, the input data and their demand patterns. Overall, the prepared models from Microsoft show the most accurate results in average and the potential of AutoML becomes particularly clear in the short-term forecast. This paper enriches the research field through its broad application, giving valuable insights into the use of AutoML tools for demand planning. The resulting understanding of limitations and benefits of AutoML tools for the case studies presented fosters their suitable application in practice