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Bauen nach dem Bauhaus
(2018)
A growing share of modern trade policy instruments is shaped by non-tariff barriers (NTBs). Based on a structural gravity equation and the recently updated Global Trade Alert database, we empirically investigate the effect of NTBs on imports. Our analysis reveals that the implementation of NTBs reduces imports of affected products by up to 12%. Their trade dampening effect is thus comparable to that of trade defence instruments such as anti-dumping duties. It is smaller for exporters that have a free trade agreement with the importing country. Different types of NTBs affect trade to a different extent. Finally, we investigate the effect of behind-the-border measures, showing that they significantly lower the importer’s market access.
Due to their structure of crossed yarns embedded in coating, woven fabric membranes are characterised by a highly nonlinear stress-strain behaviour. In order to determine an accurate structural response of membrane structures, a suitable description of the material behaviour is required. Typical phenomenological material models like linear-elastic orthotropic models only allow a limited determination of the real material behaviour. A more accurate approach becomes evident by focusing on the meso-scale, which reveals an inhomogeneous however periodic structure of woven fabrics. The present work focuses on an established meso-scale model. The novelty of this work is an enhancement of this model with regard to the coating stiffness. By performing an inverse process of parameter identification using a state-of-the-art Levenberg-Marquardt algorithm, a close fit w.r.t. measured data from a common biaxial test is shown and compared to results applying established models. Subsequently, the enhanced meso-scale model is processed into a multi-scale model and is implemented as a material law into a finite element program. Within finite element analyses of an exemplary full scale membrane structure by using the implemented material model as well as by using established material models, the results are compared and discussed.
Advanced approaches for analysis and form finding of membrane structures with finite elements
(2018)
Part I deals with material modelling of woven fabric membranes. Due to their structure of crossed yarns embedded in coating, woven fabric membranes are characterised by a highly nonlinear stress-strain behaviour. In order to determine an accurate structural response of membrane structures, a suitable description of the material behaviour is required. A linear elastic orthotropic model approach, which is current practice, only allows a relative coarse approximation of the material behaviour. The present work focuses on two different material approaches: A first approach becomes evident by focusing on the meso-scale. The inhomogeneous, however periodic structure of woven fabrics motivates for microstructural modelling. An established microstructural model is considered and enhanced with regard to the coating stiffness. Secondly, an anisotropic hyperelastic material model for woven fabric membranes is considered. By performing inverse processes of parameter identification, fits of the two different material models w.r.t. measured data from a common biaxial test are shown. The results of the inversely parametrised material models are compared and discussed.
Part II presents an extended approach for a simultaneous form finding and cutting patterning computation of membrane structures. The approach is formulated as an optimisation problem in which both the geometries of the equilibrium and cutting patterning configuration are initially unknown. The design objectives are minimum deviations from prescribed stresses in warp and fill direction along with minimum shear deformation. The equilibrium equations are introduced into the optimisation problem as constraints. Additional design criteria can be formulated (for the geometry of seam lines etc.). Similar to the motivation for the Updated Reference Strategy [4] the described problem is singular in the tangent plane. In both the equilibrium and the cutting patterning configuration finite element nodes can move without changing stresses. Therefore, several approaches are presented to stabilise the algorithm. The overall result of the computation is a stressed equilibrium and an unstressed cutting patterning geometry. The interaction of both configurations is described in Total Lagrangian formulation.
The microstructural model, which is focused in Part I, is applied. Based on this approach, information about fibre orientation as well as the ending of fibres at cutting edges are available. As a result, more accurate results can be computed compared to simpler approaches commonly used in practice.
This paper describes the effectiveness and efficiency of Virtual Reality training during a commissioning process. Therefore, 500 picking orders with more than 2000 part-picking operations with 30 test persons have been conducted and analyzed in the Modellfabrik Bodensee. The study points out the advantages and disadvantages of virtual training in comparison to a real execution of a picking process with and without any training.
In tourism, energy demands are particularly high.Tourism facilities such as hotels require large amounts ofelectric and heating resp. cooling energy. Their supply howeveris usually still based on fossil energies. This research approachanalyses the potential of promoting renewable energies in BlackForest tourism. It focuses on a combined and hence highlyefficient production of both electric and thermal energy bybiogas plants on the one hand and its provision to local tourismfacilities via short distance networks on the other. Basing onsurveys and qualitative empiricism and considering regionalresource availability as well as socio-economic aspects, it thusexamines strengths, weaknesses, opportunities and threats thatcan arise from such a cooperation.
It is widely recognized that sustainability is a new challenge for many manufacturing companies. In this paper, we tackle this issue by presenting an approach that deals with material and substance compliance within Product Lifecycle Management in a complex value chain. Our analysis explains why, how and when sustainable manufacturing arises, and it identifies, quantifies and evaluates the environmental impact of a new product. We propose (I) a Life Cycle Assessment tool (LCA) and (II) a model to validate this approach and evaluate the risk of non-compliance in supply chain. Our LCA approach provides comprehensive information on environmental impacts of a product.
Product and materials cycles are parallel and intersecting, making it challenging to integrate Material Selection Process across Product Lifecycle Management, Integration of LCA with PLM. We provide only a foundation. Further research in systems engineering is necessary. LCA is sensitive to data quality. Outsourcing production and having problems in supplier cooperation can result in material mismatch (such as property, composition mismatching) in the production process due to that may cause misleading of LCA results. This paper also describes research challenges using risk-based due diligence.
Nachhaltiges Wirtschaften und insbesondere nachhaltigerer Konsum sind längst als zentrale Herausforderung des 21. Jahrhunderts erkannt worden. Unternehmen und Verbraucher/innen sind dabei gleichermaßen gefordert, sich gegenseitig in Prozessen gemeinsamer Wertschöpfung zu befähigen. Das Potential dieser Prozesse liegt jedoch nicht alleine in einer klugen Mäßigung der Akteure, sondern in einer sichtbaren Aufwertung der vielfältigen nachhaltigen Konsumoptionen. Eine Möglichkeit, dies zu erreichen, liegt darin, Nachhaltigkeit als Qualität für ein breites Spektrum von Konsumgütern erkennbar und erlebbar werden zu lassen. Eine Nachhaltigkeitsdeklarierung kann dabei weit mehr leisten als nur eine weitere visuelle Auszeichnung. Unternehmen können die kulturellen Kontexte von Verbraucher/innen erkennen und zielgerichtet agieren. Dabei können die vielfältigen Möglichkeiten digitaler Medien hilfreich sein. Die vorliegende Arbeit schlägt vor, dies stets mit Blick auf die lebendige Realität auf Anbieter- und Nachfragerseite zu tun.
Überlegungen im Rahmen der Energiewende bezüglich der zukünftigen Technologieplattformen und Infrastrukturen der Energieversorgung müssen als wichtigen ökonomischen Faktor die zukünftig zu erwartenden Kosten dieser Technologien und Infrastrukturen einbeziehen. Hierbei spielen regelmäßig auch Überlegungen bzgl. der jeweils zugrunde liegenden Skaleneffekte eine große Rolle, sowohl in ihrer Variante als statische als auch dynamische Skaleneffekte. Häufig mangelt es einschlägigen Darstellungen dieser Aspekte jedoch an einer präzisen Unterscheidung der verschiedenen Ausprägungen von Skaleneffekten; dies gilt insbesondere auch für die konkrete Ausprägung als Größendegressionseffekt. Daher wird in diesem Papier eine systematische Klärung der entsprechenden Zusammenhänge speziell für Technologien des Energiesektors vorgenommen.
Mauermörtel und Putze
(2018)
Für mehr Qualität am Bau
(2018)
Die Putzstrukturen an Fassaden werden maßgeblich durch die Fachhandwerker geprägt. Deshalb wird ihre Ebenmäßigkeit auch nie mit der von industriell gefertigten Fassadenplatten und Ähnlichem vergleichbar sein – aber genau das macht einen Teil des Charmes von Putzfassaden aus. Dies ist auch bei der Bearbeitung von Schadstellen zu berücksichtigen.
Ziegelsplittbetone der Nachkriegsjahre und moderne RC-Betone - Nachhaltigkeit an Objektbeispielen
(2018)
Das Bauwesen gehört zu den größten Verbrauchern an natürlichen Ressourcen und Energie in der deutschen Wirtschaft. Das ist in vielen Fällen trotzdem ökologisch und ökonomisch vertretbar, weil die Bauteile und Bauwerke verglichen mit anderen "Produkten" eine deutlich längere technische Lebensdauer haben - im Fall des Betons zwischen ca. 25 und 100 Jahren - und wenn nach dem Rückbau hohe Recyclingquoten erzielt werden. In Bezug auf Einsparmöglichkeiten spielt der Massenbaustoff Beton eine ganz zentrale Rolle. Neben der Einsparung des sehr energieintensiven Zements und der Entwicklung von Substitutionsbindemitteln, stehen auch die Gesteinskörnungen im Fokus, die den größten Anteil am Beton ausmachen. Im Artikel werden auf der Basis eigener Ergebnisse aus einem DBU?geförderten Forschungsprojekt zu RC?Betonen die Nachhaltigkeit von Beton an Objektbeispielen vorgestellt und über den Sachstand zur aktuellen Nutzung von R-Betonen in Deutschland informiert. Der Fokus liegt dabei auf der Wertigkeit mineralischer Baustoffe aus vergleichsweise wenigen, überwiegend natürlichen Komponenten wie beim Beton, dessen Instandsetzungsmöglichkeiten und bessere Voraussetzungen für späteres Recycling gegenüber vielen modernen, kunststoffhaltigen Verbundbaustoffen.
Was in Kommunen im benachbarten Ausland, bspw. der Schweiz, Oesterreich oder den Niederlanden, offenbar seit vielen Jahren Stand der Technik ist, ist auf Deutschlands Kommunalstrassen eine 'Sonderbauweise': Verkehrsflaechen aus Beton. Die Gruende fuer die Vernachlaessigung der Betonbauweise im kommunalen Umfeld liegen offenbar in einer aufwendigeren Planung, hoeheren Ausfuehrungskosten, einem komplexeren Einbau (gerade in Zusammenhang mit Einbauten), Instandhaltungsmassnahmen und Massnahmen Dritter an den Ver- und Entsorgungseinrichtungen. Offen ist auch die Frage, inwieweit sich die hoeheren Aufwendungen bei der Betonbauweise hinsichtlich Planung und Ausfuehrung im Rahmen einer Lebenszyklusbetrachtung im Vergleich zur Asphaltbauweise durch einen geringeren Erhaltungsbedarf amortisieren oder ggf. sogar guenstiger darstellen. Infolge vermehrt auftretender typischer Schaeden wie Spurrinnen und Verdrueckungen werden hochbelastete kommunale Verkehrsflaechen wie Bushaltestellen, Busspuren und Kreisverkehre immer haeufiger anstatt in Asphalt oder Pflaster in Beton ausgefuehrt. Die Thematik 'Einsatz von Betonflaechen in Kommunen' ist sehr umfangreich und weitlaeufig. Generell wird hier auch auf die spezifischen Merkblaetter der FGSV verwiesen. Mit den Ausfuehrungen im Fachbeitrag soll demnach grundsaetzlich auf die Belange der Planung, des Baus und die Wirtschaftlichkeit kommunaler Verkehrsflaechen in Betonbauweise eingegangen werden. Es koennen leider nicht alle Besonderheiten und Einzelheiten wie bspw. Baustoffe (Glasfaser) Beruecksichtigung finden. Ziel ist, generelle Moeglichkeiten hinsichtlich des Einsatzes von Betonflaechen im kommunalen Bereich aufzuzeigen. Besonderer Dank gilt dem Strassenbauamt Boeblingen sowie Herrn Baudirektor Andreas Klein, dessen persoenliche Erfahrungen hier einfliessen durften.
Formgedächtnislegierungen
(2018)
Formgedächtnislegierungen sind »Legierungen, die nach geeigneter Behandlung aufgrund einer martensitischen Umwandlung ihre Gestalt in Abhängigkeit von der Temperatur ändern«. Derartige Materialien werden in den nächsten Jahrzehnten eine wachsende Rolle in der Technik spielen. Um die Eigenschaften dieser Werkstoffe optimal nutzen zu können, ist es wichtig, den Einfluss des Herstellungs- und Verarbeitungsprozesses auf ihre Anwendung zu kennen.
Das Buch behandelt die metallkundlichen Hintergründe und die Verwendungsmöglichkeiten der Formgedächtnislegierungen in verständlicher, auf den Anwender zugeschnittener Weise.
When designing drying processes for sensitive biological foodstuffs like fruit or vegetables, energy and time efficiency as well as product quality are gaining more and more importance. These all are greatly influenced by the different drying parameters (e.g. air temperature, air velocity and dew point temperature) in the process. In sterilization of food products the cooking value is widely used as a cross-link between these parameters. In a similar way, the so-called cumulated thermal load (CTL) was introduced for drying processes. This was possible because most quality changes mainly depend on drying air temperature and drying time. In a first approach, the CTL was therefore defined as the time integral of the surface temperature of agricultural products. When conducting experiments with mangoes and pineapples, however, it was found that the CTL as it was used had to be adjusted to a more practical form. So the definition of the CTL was improved and the behaviour of the adjusted CTL (CTLad) was investigated in the drying of pineapples and mangoes. On the basis of these experiments and the work that had been done on the cooking value, it was found, that more optimization on the CTLad had to be done to be able to compare a great variety of different products as well as different quality parameters.
With the increased deployment of biometric authentication systems, some security concerns have also arisen. In particular, presentation attacks directed to the capture device pose a severe threat. In order to prevent them, liveness features such as the blood flow can be utilised to develop presentation attack detection (PAD) mechanisms. In this context, laser speckle contrast imaging (LSCI) is a technology widely used in biomedical applications in order to visualise blood flow. We therefore propose a fingerprint PAD method based on textural information extracted from pre-processed LSCI images. Subsequently, a support vector machine is used for classification. In the experiments conducted on a database comprising 32 different artefacts, the results show that the proposed approach classifies correctly all bona fides. However, the LSCI technology experiences difficulties with thin and transparent overlay attacks.
Online-based business models, such as shopping platforms, have added new possibilities for consumers over the last two decades. Aside from basic differences to other distribution channels, customer reviews on such platforms have become a powerful tool, which bestows an additional source for gaining transparency to consumers. Related research has, for the most part, been labelled under the term electronic word-of-mouth (eWOM). An approach, providing a theoretical basis for this phenomenon, will be provided here. The approach is mainly based on work in the field of consumer culture theory (CCT) and on the concept of co-creation. The work of several authors in these streams of research is used to construct a culturally informed resource-based theory, as advocated by Arnould & Thompson and Algesheimer & Gurâu.
Deep neural networks have become a veritable alternative to classic speaker recognition and clustering methods in recent years. However, while the speech signal clearly is a time series, and despite the body of literature on the benefits of prosodic (suprasegmental) features, identifying voices has usually not been approached with sequence learning methods. Only recently has a recurrent neural network (RNN) been successfully applied to this task, while the use of convolutional neural networks (CNNs) (that are not able to capture arbitrary time dependencies, unlike RNNs) still prevails. In this paper, we show the effectiveness of RNNs for speaker recognition by improving state of the art speaker clustering performance and robustness on the classic TIMIT benchmark. We provide arguments why RNNs are superior by experimentally showing a “sweet spot” of the segment length for successfully capturing prosodic information that has been theoretically predicted in previous work.
We propose a novel end-to-end neural network architecture that, once trained, directly outputs a probabilistic clustering of a batch of input examples in one pass. It estimates a distribution over the number of clusters k, and for each 1≤k≤kmax, a distribution over the individual cluster assignment for each data point. The network is trained in advance in a supervised fashion on separate data to learn grouping by any perceptual similarity criterion based on pairwise labels (same/different group). It can then be applied to different data containing different groups. We demonstrate promising performance on high-dimensional data like images (COIL-100) and speech (TIMIT). We call this “learning to cluster” and show its conceptual difference to deep metric learning, semi-supervise clustering and other related approaches while having the advantage of performing learnable clustering fully end-to-end.
Input–Output modellers are often faced with the task of estimating missing Use tables at basic prices and also valuation matrices of the individual countries. This paper examines a selection of estimation methods applied to the European context where the analysts are not in possession of superior data. The estimation methods are restricted to the use of automated methods that would require more than just the row and column sums of the tables (as in projections) but less than a combination of various conflicting information (as in compilation). The results are assessed against the official Supply, Use and Input–Output tables of Belgium, Germany, Italy, Netherlands, Finland, Austria and Slovakia by using matrix difference metrics. The main conclusion is that using the structures of previous years usually performs better than any other approach.
Industrial growth and a rapidly growing world population have large impacts on the global environment and allocation of material resources. Most changes in the environment are brought about by human activities and these activities result in a flow of materials. The flows of resources from the natural environment to the economy are a prerequisite of production while flows of residuals from the economy to the environment are the consequence of production and consumption. A full understanding of these processes requires a complete description of the physical dimension of the economy and its interaction with the environment.
This letter proposes two contributions to improve the performance of transmission with generalized multistream spatial modulation (SM). In particular, a modified suboptimal detection algorithm based on the Gaussian approximation method is proposed. The proposed modifications reduce the complexity of the Gaussian approximation method and improve the performance for high signal-to-noise ratios. Furthermore, this letter introduces signal constellations based on Hurwitz integers, i.e., a 4-D lattice. Simulation results demonstrate that these signal constellations are beneficial for generalized SM with two active antennas.
Jahresbericht 2018
(2018)
Product development and product manufacturing are entering a new era, namely an era where engineering tasks are executed under collaboration of all involved parties. Engineers and potential customers work together mainly in a virtual world for the design and realization of the product. We address this so called “crowdsourcing” trend in the automotive industry that lowers cost and accelerates production of new car. Current practice and prior studies fail to handle data management and collaboration aspects in sufficient detail. We propose a PLM based crowdsourcing platform that applies best practices to the established approach and adapt it with new methods for handling specific requirements. Our work provides a basis for establishing an improved collaboration platform to support a Gig Economy in the automotive industry.
It is widely recognized that sustainability is a new challenge for many manufacturing companies. In this paper, we tackle this issue by presenting an approach that deals with material and substance compliance within Product Lifecycle Management in a complex value chain. Our analysis explains why, how and when sustainable manufacturing arises, and it identifies, quantifies and evaluates the environmental impact of a new product. We propose (I) a Life Cycle Assessment tool (LCA) and (II) a model to validate this approach and evaluate the risk of noncompliance in supply chain. Our LCA approach provides comprehensive information on environmental impacts of a product.
Product and materials cycles are parallel and intersecting, making it challenging to integrate Material Selection Process across Product Lifecycle Management, Integration of LCA with PLM. We provide only a foundation. Further research in systems engineering is necessary. LCA is sensitive to data quality. Outsourcing production and having problems in supplier cooperation can result in material mismatch (such as property, composition mismatching) in the production process due to that may cause misleading of LCA results.
This paper also describes research challenges using riskbased due diligence.
The paper investigates an innovative actuator combination based on the magnetic shape memory technology. The actuator is composed of an electromagnet, which is activated to produce motion, and a magnetic shape memory element, which is used passively to yield multistability, i.e. the possibility of holding a position without input power. Based on the experimental open-loop frequency characterization of the actuator, a position controller is developed and tested in several experiments.
Stolperstein Mathematik
(2018)
Traggerüste
(2018)
Schreiben und Rhetorik an einer Hochschule für angewandte Wissenschaften - ein Erfahrungsbericht
(2018)
Zur Rhetorik der Technik
(2018)
Investigation of magnetic effects on austenitic stainless steels after low temperature carburization
(2018)
This work aims at investigating the magnetic effects of austenitc stainless steels which can occur after a low temperature carburisation depending on the alloy. Samples were prepared of different alloys and subjected to a multiple low temperature carburisation to obtain different treatment conditions for each alloy. The layer characterisation was carried out by light microscope and also by hardening profiles and shows that the layer develops with each additional treatment cycle. A lattice expansion could be detected in all treated samples by X-ray diffraction. Magnetisability was measured using Feritscope and SQUID measurements. Not all alloys showed magnetisability after treatment. In addition to MFM measurements, experiments with Ferrofluid were also used to visualize the magnetic areas. These studies show that only about half of the formed layer becomes magnetisable and has a domain-like structure.
Knot placement for curve approximation is a well known and yet open problem in geometric modeling. Selecting knot values that yield good approximations is a challenging task, based largely on heuristics and user experience. More advanced approaches range from parametric averaging to genetic algorithms.
In this paper, we propose to use Support Vector Machines (SVMs) to determine suitable knot vectors for B-spline curve approximation. The SVMs are trained to identify locations in a sequential point cloud where knot placement will improve the approximation error. After the training phase, the SVM can assign, to each point set location, a so-called score. This score is based on geometric and differential geometric features of points. It measures the quality of each location to be used as knots in the subsequent approximation. From these scores, the final knot vector can be constructed exploring the topography of the score-vector without the need for iteration or optimization in the approximation process. Knot vectors computed with our approach outperform state of the art methods and yield tighter approximations.
Deep neural networks have been successfully applied to problems such as image segmentation, image super-resolution, coloration and image inpainting. In this work we propose the use of convolutional neural networks (CNN) for image inpainting of large regions in high-resolution textures. Due to limited computational resources processing high-resolution images with neural networks is still an open problem. Existing methods separate inpainting of global structure and the transfer of details, which leads to blurry results and loss of global coherence in the detail transfer step. Based on advances in texture synthesis using CNNs we propose patch-based image inpainting by a single network topology that is able to optimize for global as well as detail texture statistics. Our method is capable of filling large inpainting regions, oftentimes exceeding quality of comparable methods for images of high-resolution (2048x2048px). For reference patch look-up we propose to use the same summary statistics that are used in the inpainting process.
In this paper we present a method using deep learning to compute parametrizations for B-spline curve approximation. Existing methods consider the computation of parametric values and a knot vector as separate problems. We propose to train interdependent deep neural networks to predict parametric values and knots. We show that it is possible to include B-spline curve approximation directly into the neural network architecture. The resulting parametrizations yield tight approximations and are able to outperform state-of-the-art methods.
Der Begriff "Integrität" nimmt das Verhältnis zwischen individuellem Handeln und der Einhaltung von Regeln und Werten in den Blick. Grüninger/Wanzek betonen, dass integres Handeln nicht blinde Regelbefolgung, sondern die Erfüllung der zugrundeliegenden Werte erfordert. Von Integrität wird gesprochen, wenn die ethischen Werte im individuellen Denken und Tun sowie auf persönlicher und organisationaler Ebene übereinstimmen.
Integrität in Unternehmen
(2018)
Unternehmen stehen in der Verantwortung, eine Vielzahl an Werten in ihrem Geschäft zu beachten, allen voran den der Integrität. Das Buch beantwortet die Frage, was Integrität für Unternehmen bedeutet und wie integres Unternehmenshandeln erreicht werden kann. Die Autorin entwickelt einen theoretisch fundierten und praktisch anwendbaren Ansatz der Unternehmensintegrität und gibt Orientierung, wie dieser durch vielfältige Maßnahmen im Rahmen von Integrity Management umgesetzt werden kann. Dabei werden klassische Compliance-Ansätze um eine werteorientierte Perspektive ergänzt, damit Unternehmen ihre je eigene Verantwortung wahrnehmen können.
Der DEX Deutscher Ethik Index® gibt Auskunft darüber, ob der Erfolg eines Unternehmens auf anständige Weise erreicht wurde. Zielgruppe des veröffentlichten DEX sind alle Anspruchsgruppen (Stakeholder) und die Gesellschaft. Der DEX informiert darüber, ob das Unternehmen einen Mehrwert für alle seine Stakeholder schafft (= Stakeholder Value). Der DEX unterstützt Entscheidungen der Öffentlichkeit, ob einer Organisation aufgrund ihres Beitrags für die Gesellschaft die „License to Operate“ erteilt wird (= Shared Value).
Unternehmen sind nur dann erfolgreich, wenn sie sich dem unternehmensethischen Spannungsfeld proaktiv stellen. Erfolg und Anstand sind zwei Seiten derselben Medaille: Unternehmen sind nicht erfolgreich, obwohl, sondern WEIL sie sich um ethisch korrektes Handeln bemühen! Das Delta zwischen ethischem Anspruch und dem von Markt und Wettbewerb Geforderten lässt sich niemals vollständig aufheben: Es gibt so wenig perfekte Unternehmen wie es perfekte Menschen gibt!
Aber: Individuen wie Organisationen können sich auf den Weg zur ethisch orientierten Business Excellence machen und in einem auf Dauer angelegten, kontinuierlichen Entwicklungsprozess darum ringen!
SDG Voyager - A practical guide to align business excellence with Sustainable Development Goals
(2018)
By now, an inflationary high number of international publications on the topic “Agenda 2030” exist. But unanswered to this day seems to be the question of how the CSR-management of a company can make a concrete contribution to the SDGs. Instead of unilaterally demanding the reporting of companies’ sustainability activities, the SDG Voyager starts earlier in the process with the intention of encouraging companies of all sizes to become familiar with the fields of action for corporate responsibility and to attend to these issues without feeling overwhelmed. Many companies will find that they are already making a big contribution to sustainable development in a number of fields. In other areas, however, there will still be an urgent need for action. The SDG Voyager aims to acquaint companies with these topics and support them to fulfill their responsibilities towards their stakeholders and society.
Die Stiftung – CLUB OF HAMBURG widmet sich wissenschaftlich fundiert und praxisorientiert dem zeitgemäßen Verständnis unternehmerischen Erfolgs. Nach Überzeugung ihrer Stifter und Partner bilden wirtschaftlicher Erfolg und anständige Unternehmensführung eine untrennbare Einheit.
Anständiges Verhalten bedeutet nicht nur die legitimen Erwartungen der Gesellschaft und der eigenen Organisation zu berücksichtigen, sondern auch grundlegende ethische Werte und Prinzipien sowie daraus abgeleitete Normen, Gesetze und Regelungen zu respektieren und einzuhalten. Aus dieser Überzeugung heraus verfolgt die Stiftung das Ziel, Führungskräfte auf allen Managementebenen zur Umsetzung einer umfassend werteorientierten Unternehmensführung anzuregen und praxisorientiert zu unterstützen.
In enger Zusammenarbeit mit Unternehmen und spezialisierten Forschungseinrichtungen wurde das Entwicklungsmodell „Erfolg mit Anstand“ entwickelt. Das Modell verbindet die Inhalte einschlägiger globaler Standards mit den praktischen Erfahrungen aus der Evaluierung und Zertifizierung verantwortlicher, exzellenter Unternehmensführung. Auf diese Weise kann „ehrbares Verhalten“ von Unternehmen nicht nur bewertet und zertifiziert, sondern auch dokumentiert und extern nachvollziehbar gemacht werden. Das Entwicklungsmodell bildet die normative Basis des DEX Deutscher Ethik Index. Als Ergänzung zum rein Shareholder-Value-orientierten DAX steht der DEX Deutscher Ethik Index Unternehmen und Organisationen aller Größen, Branchen und Rechtsformen offen. Er dokumentiert den unternehmensethischen Fortschritt als Basis des wirtschaftlichen Erfolgs unter den Rahmenbedingungen des 21. Jahrhunderts nachweislich und breitenwirksam.
CSR und Compliance
(2018)
Viele Unternehmen befassen sich mit den Themen CSR und Compliance – in erster Linie aufgrund ihrer historischen Entwicklung – im Rahmen paralleler organisationaler Strukturen. Da CSR und Compliance nach heutigem Verständnis jedoch sowohl in der Theorie als auch in der Praxis inhaltlich zunehmend große Schnittmengen aufweisen bzw. einander wechselseitig bedingen, kann dies zu unnötigen Redundanzen und Zielkonflikten in der Umsetzung führen.
Das vorliegende Herausgeberwerk knüpft an dieser Stelle an und zeigt auf, was CSR und Compliance gemein ist, inwiefern sie einander bedingen und folglich synergetisch gemanagt werden können oder sogar sollten. Neben Wissenschaftlern sollen dazu auch explizit Praktiker zu Wort kommen, die mit der Integration von CSR- und/oder Compliancethemen betraut sind und Hinweise zu deren praktischer Umsetzung geben können.
Mit dem vorliegenden Sammelband werden daher nicht nur Wissenschaftler, sondern ausdrücklich auch Anwender angesprochen, die Denkanstöße oder konkrete Hinweise zur ganzheitlichen Integration und Umsetzung der beiden Themen aus der Lektüre mitnehmen möchten.
Viele Unternehmen befassen sich mit Compliance und Corporate Social Responsibility (CSR) getrennt voneinander. Dies mag zum einen der Historie der beiden Themen geschuldet sein, zum anderen aber auch der organisatorischen Verortung vonseiten insbesondere großer Unternehmen, die Compliance häufig der Rechtsabteilung und CSR der Kommunikationsabteilung zuordnen. Durch die isolierte Betrachtung der Themen bleiben aber nicht nur potenzielle Synergien ungenutzt, es werden auch unnötige Konflikte und Redundanzen erzeugt, die sich durch eine integrierte Herangehensweise vermeiden ließen. Bezogen auf die Umsetzung wird ein integriertes Vorgehen durch eine Reihe von Instrumenten begünstigt, die per se sowohl CSR- als auch compliancerelevante Themen ansprechen. Dass eine, aus theoretischer Sicht notwendige und sinnvolle Verknüpfung der beiden Themen auch in der Praxis künftig an Bedeutung gewinnen wird, lässt sich bereits heute an den letzten Überarbeitungen der fünf „großen“ internationalen CSR-Standards bzw. Rahmenwerken erkennen, die allesamt Themen ansprechen, die klassischerweise sowohl dem CSR- als auch dem Compliancemanagement zugeordnet werden können.
In Anlehnung an das Tempcore-Verfahren wurde an wärmebehandeltem Stabstahl das Zugverfestigungsverhalten des Kernes, der Außenhaut sowie dem gesamten Stab experimentell und numerisch ermittelt. Es zeigte sich, dass die Dehnungen am Kern und am äußeren Rand gleich sind und der Einfluss des Kerngefüges entscheidend für den Beginn der Einschnürung in der Außenhaut ist. Eine Verbesserung der Eigenschaften des Kerngefüges kann somit die Bruchempfindlichkeit des gesamten Stabes reduzieren.
Investigation of magnetic effects on austenitic stainless steels after low temperature carburization
(2018)
Sleep study can be used for detection of sleep quality and in general bed behaviors. These results can helpful for regulating sleep and recognizing different sleeping disorders of human. In comparison to the leading standard measuring system, which is Polysomnography (PSG), the system proposed in this work is a non-invasive sleep monitoring device. For continuous analysis or home use, the PSG or wearable Actigraphy devices tends to be uncomfortable. Besides, these methods not only decrease practicality due to the process of having to put them on, but they are also very expensive. The system proposed in this paper classifies respiration and body movement with only one type of sensor and also in a noninvasive way. The sensor used is a pressure sensor. This sensor is low cost and can be used for commercial proposes. The system was tested by carrying out an experiment that recorded the sleep process of a subject. These recordings showed excellent results in the classification of breathing rate and body movements.
We consider the problem of increasing the informative value of electrocardiographic (ECG) surveys using data from multichannel electrocardiographic leads, that include both recorded electrocardiosignals and the coordinates of the electrodes placed on the surface of the human torso. In this area, we were interested in reconstruction of the surface distribution of the equivalent sources during the cardiac cycle at relatively low hardware cost. In our work, we propose to reconstruct the equivalent electrical sources by numerical methods, based on integral connection between the density of electrical sources and potential in a conductive medium. We consider maps of distributions of equivalent electric sources on the heart surface (HSSM), presenting source distributions in the form of a simple or double electrical layer. We indicate the dynamics of the heart electrical activity by the space-time mapping of equivalent electrical sources in HSSM.
The process of restoring our body and brain from fatigue is directly depend-ing on the quality of sleep. It can be determined from the report of the sleep study results. Classification of sleep stages is the first step of this study and this includes the measurement of biovital data and its further processing.
In this work, the sleep analysis system is based on a hardware sensor net, namely a grid of 24 pressure sensors, supporting sleep phase recognition. In comparison to the leading standard, which is polysomnography, the proposed approach is a non-invasive system. It recognises respiration and body move-ment with only one type of low-cost pressure sensors forming a mesh archi-tecture. The nodes implement as a series of pressure sensors connected to a low-power and performant microcontroller. All nodes are connected via a system wide bus with address arbitration. The embedded processor is the mesh network endpoint that enables network configuration, storing and pre-processing of the data, external data access and visualization.
The system was tested by executing experiments recording the sleep of different healthy young subjects. The results obtained have indicated the po-tential to detect breathing rate and body movement. A major difference of this system in comparison to other approaches is the innovative way to place the sensors under the mattress. This characteristic facilitates the continuous using of the system without any influence on the common sleep process.
Long-term sleep monitoring can be done primarily in the home environment. Good patient acceptance requires low user and installation barriers. The selection of parameters in this approach is significantly limited compared to a PSG session. The aim is a qualified selection of parameters, which on the one hand allow a sufficiently good classification of sleep phases and on the other hand can be detected by non-invasive methods.
Einfluss der Oberfläche
(2018)
The overall goal of this work is to detect and analyze a person's movement, breathing and heart rate during sleep in a common bed overnight without any additional physical contact. The measurement is performed with the help of
sensors placed between the mattress and the frame. A two-stage pattern classification algorithm based has been implemented that applies statistics analysis to recognize the position of patients. The system is implemented in a sensors-network, hosting several nodes and communication end-points to support quick and efficient classification. The overall tests show convincing results for the position recognition and a reasonable overlap in matching.
Das häusliche Umfeld kann vor allem für langfristiges Schlafmonitoring verwendet werden. Gute Patientenakzeptanz erfordert niedrige Nutzer- und Installationsbarrieren. Für die Installation zu Hause sind klassische PSG-Systeme aufgrund von ihrer Komplexität wenig passend. Ziel der Entwicklung ist die qualifizierte Erhebung von Parametern, die einerseits eine hinreichend gute Klassifikation von Schlafphasen erlauben und die andererseits durch nicht-invasive Methoden erfasst werden können.
Basierend auf einer Literaturstudie und der Maßgabe nicht-invasive Methoden zu nutzen, wurden folgende Parameter ausgewählt: Körperbewegung, Atmung und Herzschlag. Diese Parameter können nicht-invasiv durch Matratzendrucksensoren erfasst werden. Die Sensorknoten sind als ein Netz von Drucksensoren implementiert, die mit einem leistungsarmen und performanten Mikrocontroller verbunden sind. Alle Knoten sind über einen systemweiten Bus mit Adressarbitrierung verbunden. Der eingebettete Prozessor ist der Mesh-Netzwerk-Endpunkt, der die Netzwerkkonfiguration, Speicherung und Vorverarbeitung der Daten, externen Datenzugriff und Visualisierung ermöglicht.
Das System wurde getestet, indem Experimente durchgeführt wurden, die den Schlaf verschiedener gesunder junger Personen aufzeichneten. Die erhaltenen Ergebnisse bestätigen die Fähigkeit des Systems, Atemfrequenz und Körperbewegung zu erfassen. Ein wesentlicher Unterschied dieses Systems im Vergleich zu anderen Ansätzen ist die innovative Art, die Sensoren unter der Matratze zu platzieren. Diese Eigenschaft erleichtert die kontinuierliche Nutzung des Systems ohne Einfluss auf den gemeinsamen Schlafprozess.
Um Schlafverhalten langfristig zu untersuchen, wird ein Hardwaresystem mit niedrigen Installationsbarrieren für den Einsatz im häuslichen Umfeld. Erste Ergebnisse weisen auf das Potenzial hin, außer Körperbewegung und Atemfrequenz, auch Herzfrequenz erfassen zu können. Die Werte können weiter verbessert werden, wenn die Sensorabfragefrequenz erhöht wird. Nach der Weiterentwicklung des Systems, soll es mit dem Softwarealgorithmus für die Schlafphasenerkennung verbunden werden.
Corporate venturing is one way for corporations to
introduce strategic renewal into their business portfolios, which is
imperative for ongoing success in innovation-driven industries.
Prior research finds that corporate ventures should be separated
from the mainstream business in loosely coupled sub-units, but
scholars continue to discuss how loose or tight the ventures should
be to balance exploration and exploitation. Hence, the antecedents
for successful venture management are yet to be fully explored and
our study contributes to this effort. The study shows that
corporate venture success is enhanced when corporate
management grants job and strategic autonomy to the venture
managers. This is further amplified when corporate management
simultaneously imposes an exploitative policy that forces venture
managers to prioritize extensions to and improvements of existing
competences and product-market offerings.
Corporate venturing has gained much attention due
to challenges and changes that occur because of discontinuous
innovations – which seem to be promoted by digitalization. In this
context, open innovation has become a promising tool for
established companies to strengthen their innovation capabilities.
While the external opening of the innovation process has gained
much attention, the internal opening lacks on investigations.
Especially new organizational forms, such as Internal Corporate
Accelerators, have not been investigated sufficiently. This study,
which is based on 13 interviews from two German tech-companies,
contributes to a better understanding of this new form of corporate
venturing and the resulting effects on the organizational renewal.
Influence of Temperature on the Corrosion behaviour of Stainless Steels under Tribological Stress
(2018)
Posterpräsentation
This paper presents a bed system able to analyze a person’s movement, breathing and recognize the positions that the subject is lying on the bed during the night without any additional physical contact. The measurements are performed with sensors placed between the mattress and the bed-frame. An Intel Edison board was used as an endpoint that served as a communication node from the mesh network to external service. Two nodes and Intel Edison are attached to the bottom of the bed frame and they are connected to the sensors. First test results have indicated the potential of the proposed approach for the recognition of sleep positions with 83% of correct recognized positions.
Know when you don't know
(2018)
Deep convolutional neural networks show outstanding performance in image-based phenotype classification given that all existing phenotypes are presented during the training of the network. However, in real-world high-content screening (HCS) experiments, it is often impossible to know all phenotypes in advance. Moreover, novel phenotype discovery itself can be an HCS outcome of interest. This aspect of HCS is not yet covered by classical deep learning approaches. When presenting an image with a novel phenotype to a trained network, it fails to indicate a novelty discovery but assigns the image to a wrong phenotype. To tackle this problem and address the need for novelty detection, we use a recently developed Bayesian approach for deep neural networks called Monte Carlo (MC) dropout to define different uncertainty measures for each phenotype prediction. With real HCS data, we show that these uncertainty measures allow us to identify novel or unclear phenotypes. In addition, we also found that the MC dropout method results in a significant improvement of classification accuracy. The proposed procedure used in our HCS case study can be easily transferred to any existing network architecture and will be beneficial in terms of accuracy and novelty detection.