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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.
Wirkungen gestalten
(2016)
Durch den Einsatz von mobilen Endgeräten (z.B. Tablets, Smartphones) erschließen sich immer mehr Möglichkeiten, die Ausführung von Geschäftsprozessen zu unterstützen. Beispielsweise können Geschäftsprozessaktivitäten (z.B. Genehmigung eines Angebots) ortsunabhängig bearbeitet werden, wodurch die Durchlaufzeit signifikant reduziert wird. Die Nutzung von mobilen Apps beschränkt sich hierbei meist nur auf die Unterstützung von effizienter und flexibler Interaktion zwischen den verschiedenen ausführenden Rollen. Dieser Artikel beschreibt, wie mobile Apps nicht nur die Ausführung, sondern auch die Optimierung von Geschäftsprozessen unterstützen können. Hierzu werden vordefinierte Qualitätskriterien kontextabhängig während der Ausführung von Aktivitäten erfasst. Die durch traditionelle Methoden erfassten Daten (z.B. Messung von Kennzahlen) werden somit durch in Echtzeit gesammeltes User Feedback ergänzt. Der Ansatz wird am Beispiel einer eigens entwickelten mobilen App demonstriert und evaluiert.
The cornerstone of cognitive systems is environment awareness which enables agile and adaptive use of channel resources. Whitespace prediction based on learning the statistics of the wireless traffic has proven to be a powerful tool to achieve such awareness. In this paper, we propose a novel Hidden Markov Model (HMM) based spectrum learning and prediction approach which accurately estimates the exact length of the whitespace in WiFi channels within the shared industrial scientific medical ISM) bands. We show that extending the number of hidden states and formulating the prediction problem as a maximum likelihood (ML) classification leads to a substantial increase in the prediction horizon compared to classical approaches that predict the immediate (short-term) future. We verify the proposed algorithm through simulations which utilize a model for WiFi traffic based on extensive measurement campaigns.
Digital bedruckte Oberflächen müssen strengen funktionalen und ästhetischen Anforderungen genügen. Diese Eigenschaften werden im Rahmen der Qualitätsprüfung kontrolliert. Hierbei wirken sich Oberflächendefekte oftmals erst dann aus, wenn diese auch vom Menschen wahrgenommen werden. Aufgrund der hohen Produktionsgeschwindigkeit kann eine solche Bewertung der Sichtbarkeit von Defekten bisher nur außerhalb des Produktionsflusses durch manuelle - subjektiv geprägte - Inspektion erfolgen. Ziel des Projektes ist (1) die Modellierung von Texturen in einer Form, die an das menschliche visuelle System angepasst ist und (2) die automatisierte Beurteilung der Wahrnehmung von Texturfehlern. Im Rahmen des Projekts wurde ein prototypisches System zur Inline-Erfassung von texturierten Oberflächen entwickelt. Auf Basis von realen Aufnahmen industriell produzierter Holzdekore wurde eine repräsentative Texturdatenbank erstellt. Gezeigt werden erste Resultate im Bereich der Defektdetektion auf Basis von statistischen Merkmalen. Diese Ergebnisse dienen als Grundlage für die spätere wahrnehmungsorientierte Bewertung. Letztlich sollen die im Rahmen des Projekts erlangten Ergebnisse in einen prototypischen Aufbau zur Inspektion von digital bedruckten Dekoren einfließen.
Die vorausschauende Instandhaltung (engl. Predictive Maintenance) gewinnt für die produzierende Industrie weltweit an Bedeutung, da Produktionsmodernisierungen im Rahmen der Industrie 4.0 sowie die zunehmende Verwendung von heterogenen Sensoreinheiten die Instandhaltungsplanung immer komplexer gestalten. Darüber hinaus ist das Service-Kontingent, welches ein Maschinenbauer seinen Kunden im Bereich der Instandhaltung anbieten kann, durch die Ressource Mensch stark limitiert und nur ortsgebunden einsetzbar. Durch herkömmliche Instandhaltungsprozesse entstehen somit oft hohe Kosten, sowohl für den Maschinenbauer als auch für den Anwender. Dieser Beitrag gibt einen Einblick in aktuelle Forschungen der Sybit GmbH in direkter Zusammenarbeit mit der HTWG Konstanz und renommierten Maschinenbau-Unternehmen. Gemeinsames Ziel ist es, vorhandene Instandhaltungsprozesse durch die Verwendung von Augmented Reality (AR) und weiterführenden Technologien zu unterstützen. Hierbei wird ein Stufenplan erarbeitet und vorgestellt, in dem die notwendigen Erweiterungen auf dem Weg von der Implementierung eines Pilotprojekts bis hin zur vollwertigen Industrie-4.0-Anwendung diskutiert werden. Abschließend wird die plausible Erweiterbarkeit der vorgestellten Entwicklungen erörtert und die Übertragbarkeit der Ergebnisse auf andere Domänen vorgestellt.
Visualization-Assisted Development of Deep Learning Models in Offline Handwriting Recognition
(2018)
Deep learning is a field of machine learning that has been the focus of active research and successful applications in recent years. Offline handwriting recognition is one of the research fields and applications were deep neural networks have shown high accuracy. Deep learning models and their training pipeline show a large amount of hyper-parameters in their data selection, transformation, network topology and training process that are sometimes interdependent. This increases the overall difficulty and time necessary for building and training a model for a specific data set and task at hand. This work proposes a novel visualization-assisted workflow that guides the model developer through the hyper-parameter search in order to identify relevant parameters and modify them in a meaningful way. This decreases the overall time necessary for building and training a model. The contributions of this work are a workflow for hyper-parameter search in offline handwriting recognition and a heat map based visualization technique for deep neural networks in multi-line offline handwriting recognition. This work applies to offline handwriting recognition, but the general workflow can possibly be adapted to other tasks as well.
When mobile devices at the network edge want to communicate with each other, they too often depend on the availability of faraway resources. For direct communication, feasible user-friendly service discovery is essential. DNS Service Discovery over Multicast DNS (DNS-SD/mDNS) is widely used for configurationless service discovery in local networks, due inno small part to the fact that it is based on the well establishedDNS, and efficient in small networks. In our research, we enhance DNS-SD/mDNS providing versatility, user control, efficiency, and privacy, while maintaining the deployment simplicity and backward compatibility. These enhancements are necessary to make it a solid, flexible foundationfor device communication in the edge of the Internet. In this paper, we focus on providing multi-link capabilities and scalable scopes for DNS-SD while being mindful of both user-friendliness and efficiency. We propose DNS-SD over StatelessDNS (DNS-SD/sDNS), a solution that allows configurationless service discovery in arbitrary self-named scopes - largely independentof the physical network layout - by leveraging ourStateless DNS technique and the Raft consensus algorithm.
Konventionelle, von Dieselmotoren angetriebene Radlader beeinträchtigen die Lebensqualität der Menschen in ihrer unmittelbaren Umgebung mit Lärm- und Schadstoffemissionen. Das vom BMBF geförderte Forschungsvorhaben "Emissionsarmer Elektroradlader" verfolgt das Ziel, die lokalen Emissionen von Radladern deutlich herabzusetzen und die Effizienz des Fahrzeugs zu steigern. Im Rahmen des Vorhabens wurde ein konventioneller Radlader auf elektrische Antriebe umgerüstet. Als Energiespeicher dient eine LiFeYPO4-Batterie, die für eine Betriebsdauer von vier Stunden ausgelegt ist. In ersten praktischen Untersuchungen wurde die Energiebilanz des Emissionsarmen Elektro-Radladers mit der des konventionellen Serienfahrzeugs verglichen. Dazu wurde ein modifizierter Y-Arbeitszyklus entworfen, der sich an den üblichen Arbeitsaufgaben des Radladers orientiert und sich durch eine hohe Reproduzierbarkeit auszeichnet. Für die vollständige Bewertung wird die komplette Kette der Energieumwandlung betrachtet, beginnend mit der Energie im Kraftstoff bzw. der dem Stromnetz entnommenen Energie, bis zur mechanischen Arbeit, die das Gerät verrichtet. Daraus lassen sich Rückschlüsse auf die unterschiedlichen CO2-Emissionen beider Fahrzeuge ableiten.
Ballistocardiography (BCG) can be used to monitor heart rate activity. Besides, the accelerometer should have high sensitivity and minimal internal noise; a low-cost approach was taken into consideration. Several measurements have been executed to determine the optimal positioning of a sensor under the mattress to obtain a signal strong enough for further analysis. A prototype for an unobtrusive accelerometer-based measurement system has been developed and tested in a conventional bed without any specific extras. The influence of the human sleep position for the output accelerometer data was tested. The obtained results indicate the potential to capture BCG signals using accelerometers. The measurement system can detect heart rate in an unobtrusive form in the home environment.
This article describes a research project that aims at investigating individual entrepreneurial founders concerning their shift tendencies of decision-making logics - especially during the respective phases of the venture creating process. Prior studies found that team founders show a hybrid perspective on strategic decision-making. They not only combine causation (planning-based) and effectuation (flexible) logics but also show logic shifts and also re-shifts over time. Due to the fact, that founders' social identity shapes early structuring processes, this article describes the necessity of elimination of in-group influences of multi-founding ventures and focus on individuals in order to make specific assessments on logic shifts and re-shifts. Based on an extensive literature review, a pre-selection-test and a qualitative case study design from the empirical body of the paper. Insofar, this study applies a qualitative design of a process research approach to investigate shifts of decision-making logics of individual founders in new venture creation over time.
Ulrich Finsterwalder
(2016)
Ulrich Finsterwalder
(2016)
Putze und Fugenmoertel, insbesondere in Sichtmauerwerken uebernehmen wesentliche technische, bauphysikalische und aesthetische Aufgaben fuer die Fassade und tragen massgeblich zum Erhalt der historischen Bausubstanz bei. Dabei sind an Denkmalen haeufig Befunde historischer Putze und Fugenmoertel sowie Verarbeitungsweisen und Handwerkstechniken vorhanden, die heute nicht mehr gebraeuchlich sind und beherrscht werden. Deshalb kommt ihrer Erhaltung besondere Bedeutung zu. Als aeusserster 'Angriffspunkt' der Gebaeudehuelle sind die Putze und Fugenmoertel der Witterung und zum Teil chemischen, biologischen und mechanischen Belastungen frei ausgesetzt und werden in Spritzwasserbereichen auch durch Tausalze beansprucht. Die dadurch sowie durch Alterung und Ermuedung entstehenden Schaeden werden beschrieben und Moeglichkeiten fuer die Erhaltung und Instandsetzung der Putze aufgezeigt.
TU Darmstadt HUMVIB-Bridge
(2016)
The simulation of the human-induced vibrations of lightweight footbridges is in general a complex problem where the dynamics of the pedestrian system meets the structural dynamics of the bridge. However, standard methods for numerical analysis of pedestrian bridges deal with this issue by using simplified approaches. The structure is mostly represented either by discretised multi mass systems or through a formulation in modal coordinates, while the excitation is typically described by a moving load.
Positive effects of the interaction between the two systems (pedestrian and structure) are usually completely neglected. This paper, which is partially
extracted from an actual research report of the Institute of Structural Mechanics and Design (TU Darmstadt), presents an experimental set-up developed for investigations of the human-structure interaction (HSI), as well as results of the preliminary investigations carried out in the same context.
This paper summarizes the trends in metallization and interconnection technology in the eyes of the participants of the 8th Metallization and Interconnection Workshop. Participants were asked in a questionnaire to share their view on the future development of metallization technology, the kind of metal used for front side metallization and the future development of interconnection technology. The continuous improvement of the screen-printing technology is reflected in the high expected percentage share decreasing from 88% in three years to still 70% in ten years. The dominating front side metal in the view of the participants will be silver with an expected percentage share of nearly 70% in 2029. Regarding interconnection technologies, the experts of the workshop expect new technologies to gain significant technology shares faster. Whereas in three years soldering on busbars is expected to dominate with a percentage share of 71% it will drop in ten years to 35% in the eyes of the participants. Multiwire and shingling technologies are seen to have the highest potential with expected percentage shares of 33% (multiwire) and 16% (shingling) in ten years.
Trajectory Tracking of a Fully-actuated Surface Vessel using Nonlinear Model Predictive Control
(2021)
The trajectory tracking problem for a fully-actuated real-scaled surface vessel is addressed in this paper. The unknown hydrodynamic and propulsion parameters of the vessel’s dynamic model were identified using an experimental maneuver-based identification process. Then, a nonlinear model predictive control (NMPC) scheme is designed and the controller’s performance is assessed through the variation of NMPC parameters and constraints tightening for tracking a curved trajectory.
Corporate entrepreneurship (CE) is experiencing continuously increasing interest from scholars and practitioners. One reason for this seems to be rooted in the organizational structures of established companies, which are cumbersome for implementing organizational agility and for developing radical innovations. In view of the advancing digitalization, however, exactly this is required in order to be successful in the long-term. CE is a promising managerial tool that offers a wide range of options to pursue the creation of new businesses and to support the companies' transformation in order to adapt to changes in the environment. Even though CE offers a broad range of opportunities, the effective management is a challenge. One reason for this is the ambiguity when it comes to the differences between the various CE forms and the objectives that can be achieved by those. This study, which is based on 13 in-depth interviews from eight high-tech companies, contributes to a better understanding of CE by offering a first harmonized set of CE objectives that is suitable to compare and differentiate across the different forms. In addition to that, three CE types, offering a new perspective on how to differentiate CE forms, are identified and give implications for a more effective management.
Realistic traffic modeling plays a key role in efficient Dynamic Spectrum Access (DSA) which is considered as enabler for the employment of wireless technologies in critical industrial automation applications (IAA). The majority of models of spectrum usage are not suitable for this specific use case as they are based on measurement campaigns conducted in urban or controlled laboratory environments. In this work we present a time-domain traffic model for industrial communication in the 2.4 GHz industrial, scientific, medical (ISM) band based on measurements in an industrial automotive production site. As DSA is usually implemented on Software Defined Radios (SDR), our measurement campaign is based on SDR platforms rather than sophisticated spectrum analyzers. We show through the estimation of the Hurst parameter that industrial wireless traffic possesses inherent self-similarity that could be exploited for efficient DSA. We also show that wireless traffic could be modeled as a semi-Markov model with channel on and off durations Log-normally and Pareto distributed, respectively. We finally estimate the parameters of the derived models using Maximum Likelihood estimation.
Business units are increasingly able to fuel the transformation that digitalization demands of organizations. Thereby, they implement Shadow IT (SIT) to create flexible and innovative solutions. However, the individual implementation of SIT leads to high complexities and redundancies. Integration suggests itself to meet these challenges but can also eliminate the described benefits. In this emergent research, we develop propositions for a conceptual decision framework, that balances the benefits and drawbacks of an integration of SIT using a literature review as well as a multiple-case study. We thereby integrate the perspective of the overall organization as well as the specific business unit. We then pose six propositions regarding SIT integration that will serve to evaluate our conceptual framework in future research.
Tourist tracking
(2015)
The aim of the paper is to present the simulation of the sweeping process based on a mathematical model that includes the drag force, the lift force, the sideway force, and the gravity. At the beginning, it is presented a short history of the street sweepers, some considerations about the sweeping process and the parameters of the sweeping process. Considering the developed model, in Matlab there is done some simulation for the trajectory of a spherical pebble. The obtained results are presented in graphical shape.
Due to the rising need for palliative care in Russia, it is crucial to provide timely and high-quality solutions for patients, relatives, and caregivers. A methodology for remote monitoring of patients in need of palliative care and the requirements will be developed for a hardware-software complex for remote monitoring of patients' health at home.
The Role of Support-Activities for the successful Implementation of Internal Corporate Accelerators
(2018)
Shadow information technology systems (SITS) coexist with formal enterprise systems in organisations. SITS pose risks but also increase flexibility of business units. Practice shows that SITS emerge, despite that Enterprise Architecture Management (EAM) aims at controling all IT systems in an organization. Studies acknowledge this problem in general. However, they neither show the specific influencing areas of SITS nor provide approaches to address them. To close this gap, we use a literature review to analyse examples of practical SITS and their interference with EAM concerns. Thus, we find that they hinder especially transparency, reduction of EA complexity and governance. Research has focused on achieving transparency, governing the evolution of the EA but lacks strategies for reducing complexity. This study contributes to research and practice by uncovering the main influencing areas of SITS on EAM, as well as by laying a foundation for future research on this topic.
This paper examines the corporate organisational aspects of the implementation of Industry 4.0. Industry 4.0 builds on new technologies and appears as a disruptive innovation to manufacturing firms. Although we do have a good understanding of the technical components, the implementation of the management and organisational aspects of Industry 4.0 is under-researched. It is challenging to find qualitative empirical evidence which provides comprehensive insights about real implementation cases. Based on a case study in a German high value manufacturing firm, we explore the corporate organisation and implementation of Industry 4.0. By using the framework of Complex Adaptive System (CAS), we have identified three key factors which facilitate the implementation of Industry 4.0 namely 1.) Organisational structure changes such as the foundation of a central department for digital transformation, 2.) The election of a Chief Digital Officer as a personnel change, and 3.) Corporate opening up towards cooperating with partners as a cultural change. We have furthermore found that Lean Management is an important enabler that ensures readiness for the adoption of Industry 4.0.
Business coaching is believed to effectively improve survival and success chances of new technology-based firms (NTBFs). However, not much empirical evidence on the support measure's effectiveness is available. Therefore, a pragmatic two-armed Randomized Controlled Trial (RCT) to test the effect of tactical business coaching on NTBF survival capabilities was designed and, for the most part, carried out. However, due to a lower than expected sample size and great attrition between groups, the RCT reveals deviations from the trial design that impede a thorough data assessment. Based on the data given, a first data analysis does not reveal significant differences in survival capability between the two groups. Thus, to provide guidance for future RCTs in business contexts, lessons learned about how to deal with trickle samples and experiment constellations with third parties carrying out the intervention are drawn.
The corporate entrepreneur
(2016)
Corporate entrepreneurship is one tool for established companies to strengthen their capabilities for strategic renewal and innovativeness. The question, however, which factors are influencing the success of a corporate entrepreneurship initiative requires further attention. The corporate entrepreneur who is acting as both the leader of embedded entrepreneurial teams and linking pin to the corporate, is providing one possible perspective. Based on 6 interviews conducted in 6 German organizations this study contributes to the understanding of the role of the corporate entrepreneur and how this role can be distinguished from other roles in the context of innovation.
At the University of Applied Sciences Konstanz, Germany, a modern electronically controlled dynamometer and several cars are available for tests. Numerous studies have been carried out, and the latest results will be presented. The paper is intended to explain different tests under load. One focus is the driving cycle WLTC (Worldwide harmonized Light vehicles Test Cycle) and the requirements for the proper conduct of investigation with this driving cycle. Two and three wheelers have a great importance for mobility in various Asian countries. But also in other countries, this segment is very important for the so-called First or Last Mile Vehicles. Because of this, a short explanation of the driving cycle WMTC (Worldwide harmonized Motorcycle Emissions Certification/Test Procedure) is given. The various possibilities for the operation of the dynamometer and for carrying out various experiments are shown.
Other important figures that can be determined on a dynamometer are the wheel power, the power losses and eventually the engine performance. With the brake specific torque, the traction force at the propelled wheels, the maximum acceleration or maximum gradeability of a car can be determined.
As well the slippage related to load can be measured on the dynamometer. The dynamic wheel radius of the driven wheels has a significant influence on the slippage. Because of the temperature increase of the tires during the tests the tire pressure increases. A rise of tire temperature, tire pressure, and wheel speed results in an increase of the dynamic wheel radius and slippage. Equations for the determination of the dynamic wheel radius are presented.
Autism spectrum disorders (ASD) affect a large number of children both in the Russian Federation and in Germany. Early diagnosis is key for these children, because the sooner parents notice such disorders in a child and the rehabilitation and treatment program starts, the higher the likelihood of his social adaptation. The difficulties in raising such a child lie in the complexity of his learning outside of children's groups and the complexity of his medical care. In this regard, the development of digital applications that facilitate medical care and education of such children at home is important and relevant. The purpose of the project is to improve the availability and quality of healthcare and social adaptation at home of children with ASD through the use of digital technologies.
Small vessels or unmanned surface vehicles only have a limited amount of space and energy available. If these vessels require an active sensing collision avoidance system it is often not possible to mount large sensor systems like X-Band radars. Thus, in this paper an energy efficient automotive radar and a laser range sensor are evaluated for tracking surrounding vessels. For these targets, those type of sensors typically generate more than one detection per scan. Therefore, an extended target tracking problem has to be solved to estimate state end extension of the vessels. In this paper, an extended version of the probabilistic data association filter that uses random matrices is applied. The performance of the tracking system using either radar or laser range data is demonstrated in real experiments.
Das hier beschriebene und auf einem FPGA vom Typ Spartan-3A DSP realisierte System dient dazu, auf besonders effiziente Weise die Häufigkeitsverteilung nicht erkannter fehlerhafter Nachrichten mit verschiedenen CRCPolynomen
zu berechnen. Damit die Berechnung in möglichst kurzer Zeit stattfindet, wurde das System aus 64 parallel arbeitenden Instanzen von CRC-Findern in mehrstufiger Fließbandorganisation aufgebaut. In der hier beschriebenen Ausbaustufe erreicht das System eine Gesamtleistung von 6,4 ·109 Operationen in der Sekunde.
The expansion of a given multivariate polynomial into Bernstein polynomials is considered. Matrix methods for the calculation of the Bernstein expansion of the product of two polynomials and of the Bernstein expansion of a polynomial from the expansion of one of its partial derivatives are provided which allow also a symbolic computation.
Classification of point clouds by different types of geometric primitives is an essential part in the reconstruction process of CAD geometry. We use support vector machines (SVM) to label patches in point clouds with the class labels tori, ellipsoids, spheres, cones, cylinders or planes. For the classification features based on different geometric properties like point normals, angles, and principal curvatures are used. These geometric features are estimated in the local neighborhood of a point of the point cloud. Computing these geometric features for a random subset of the point cloud yields a feature distribution. Different features are combined for achieving best classification results. To minimize the time consuming training phase of SVMs, the geometric features are first evaluated using linear discriminant analysis (LDA).
LDA and SVM are machine learning approaches that require an initial training phase to allow for a subsequent automatic classification of a new data set. For the training phase point clouds are generated using a simulation of a laser scanning device. Additional noise based on an laser scanner error model is added to the point clouds. The resulting LDA and SVM classifiers are then used to classify geometric primitives in simulated and real laser scanned point clouds.
Compared to other approaches, where all known features are used for classification, we explicitly compare novel against known geometric features to prove their effectiveness.
Summary of the 9th workshop on metallization and interconnection for crystalline silicon solar cells
(2021)
The 9th edition of the Workshop on Metallization and Interconnection for Crystalline Silicon Solar Cells was held as an online event but nevertheless reached the workshop goals of knowledge sharing and networking. The technology of screen-printed contacts of high temperature pastes continues its fast progress enabled by better understanding of the phenomena taking place during printing and firing, and progress in materials. Great improvements were also achieved in low temperature paste printing and plated metallization. In the field of interconnection, progress was reported on multiwire approaches, electrically conductive adhesives and on foil-based approaches. Common to many contributions at the workshop was the use of advanced laser processes to improve performance or throughput.
Summary of the 8th Workshop on Metallization and Interconnection for Crystalline Silicon Solar Cells
(2019)
This article gives a summary of the 8th Metallization and Interconnection workshop and attempts to place each contribution in the appropriate context. The field of metallization and interconnection continues to progress at a very fast pace. Several printing techniques can now achieve linewidths below 20 μm. Screen printing is more than ever the dominating metallization technology in the industry, with finger widths of 45 μm in routine mass production and values below 20 μm in the lab. Plating technology is also being improved, particularly through the development of lower cost patterning techniques. Interconnection technology is changing fast, with introduction in mass production of multiwire and shingled cells technologies. New models and characterization techniques are being introduced to study and understand in detail these new interconnection technologies.
Stress is recognized as a predominant disease with raising costs for rehabilitation and treatment. Currently there several different approaches that can be used for determining and calculating the stress levels. Usually the methods for determining stress are divided in two categories. The first category do not require any special equipment for measuring the stress. This category useless the variation in the behaviour patterns that occur while stress. The core disadvantage for the category is their limitation to specific use case. The second category uses laboratories instruments and biological sensors. This category allow to measure stress precisely and proficiently but on the same time they are not mobile and transportable and do not support real-time feedback. This work presents a mobile system that provides the calculation of stress. For achieving this, the of a mobile ECG sensor is analysed, processed and visualised over a mobile system like a smartphone. This work also explains the used stress measurement algorithm. The result of this work is a portable system that can be used with a mobile system like a smartphone as visual interface for reporting the current stress level.
In today's volatile world, established companies must be capable of optimizing their core business with incremental innovations while simultaneously developing discontinuous innovations to maintain their long-term competitiveness. Balancing both is a major challenge for companies, since different types of innovation require different organizational structures, operational modes and management styles. Established companies tend to excel in improving their current business through incremental innovations which are closely related to their current knowledge base and competencies. However, this often goes hand in hand with challenges in the exploration of knowledge that is new to the company and that is essential for the development of discontinuous innovations. In this respect, the concept of corporate entrepreneurship is recognized as a way to strengthen the exploration of new knowledge and to support the development of discontinuous innovation. For managing corporate entrepreneurship more effectively, it is crucial to understand which types of knowledge can be created through corporate entrepreneurship and which organizational designs are more suited to gain certain types of knowledge. To answer these questions, this study analyzed 23 semi-structured interviews conducted with established companies that are running such entrepreneurial activities. The results show (1) that three general types of knowledge can be explored through corporate entrepreneurship and (2) that some organizational designs are more suited to explore certain knowledge types than others are.
Strategie der digitalen Ära
(2015)
The evolution of strain induced martensite in austenitic stainless steel AISI 304 was investigated in a rolling contact on a two-discs-tribometer. The effects of surface roughness, slip and normal force as well as the number of load cycles were examined. In comparison to the investigations of martensitic phase transformation during cold rolling, the applied stresses are considerably lower. The formation of strain induced martensite was detected in-situ by means of a FERITSCOPE MP30 and ex-situ by optical microscopy after etching with Kane etchant. Both number of load cycles and magnitude of normal force appeared to be the main influencing factors regarding strain induced martensitic evolution in low stress rolling contacts.
This paper presents a new likelihood-based partitioning method of the measurement set for the extended object probability hypothesis density (PHD) filter framework. Recent work has mostly relied on heuristic partitioning methods that cluster the measurement data based on a distance measure between the single measurements. This can lead to poor filter performance if the tracked extended objects are closely spaced. The proposed method called Stochastic Partitioning (StP) is based on sampling methods and was inspired by a former work of Granström et. al. In this work, the StP method is applied to a Gaussian inverse Wishart (GIW) PHD filter and compared to a second filter implementation that uses the heuristic Distance Partitioning (DP) method. The performance is evaluated in Monte Carlo simulations in a scenario where two objects approach each other. It is shown that the sampling based StP method leads to an improved filter performance compared to DP.
Steps to the stage
(2017)
In this paper we provide a performance analysis framework for wireless industrial networks by deriving a service curve and a bound on the delay violation probability. For this purpose we use the (min,×)stochastic network calculus as well as a recently presented recursive formula for an end-to-end delay bound of wireless heterogeneous networks. The derived results are mapped to WirelessHART networks used in process automation and were validated via simulations. In addition to WirelessHART, our results can be applied to any wireless network whose physical layer conforms the IEEE 802.15.4 standard, while its MAC protocol incorporates TDMA and channel hopping, like e.g. ISA100.11a or TSCH-based networks. The provided delay analysis is especially useful during the network design phase, offering further research potential towards optimal routing and power management in QoS-constrained wireless industrial networks.
Knowing the position of the spool in a solenoid valve, without using costly position sensors, is of considerable interest in a lot of industrial applications. In this paper, the problem of position estimation based on state observers for fast-switching solenoids, with sole use of simple voltage and current measurements, is investigated. Due to the short spool traveling time in fast-switching valves, convergence of the observer errors has to be achieved very fast. Moreover, the observer has to be robust against modeling uncertainties and parameter variations. Therefore, different state observer approaches are investigated, and compared to each other regarding possible uncertainties. The investigation covers a High-Gain-Observer approach, a combined High-Gain Sliding-Mode-Observer approach, both based on extended linearization, and a nonlinear Sliding-Mode-Observer based on equivalent output injection. The results are discussed by means of numerical simulations for all approaches, and finally physical experiments on a valve-mock-up are thoroughly discussed for the nonlinear Sliding-Mode-Observer.
Sprachliche Anforderungen in verschiedenen Fächern, Vermittlungskonzepte und Kursorganisation
(2016)
Der von Ehlich eingeführte Begriff „alltägliche Wissenschaftssprache“ hat die Diskussion um die Sprachvermittlung für den Sprachgebrauch im Studium maßgeblich geprägt. Auch die Abkürzung „AWS“ ist mittlerweile recht verbreitet. Gemeint sind sprachliche Elemente, die neben der Fachterminologie in unterschiedlichen Disziplinen weitgehend ähnlich sind. Man geht davon aus, dass diese Elemente in mehreren Disziplinen verwendet werden. Mit dieser Argumentation lässt sich eine disziplinübergreifende Sprachvermittlung begründen. In diesem Beitrag wird das AWS-Konzept einer neuerlichen Betrachtung unterzogen.
Dazu werden folgende Fragen formuliert:
1. Ist ein disziplinübergreifender Ansatz für die Kursorganisation hilfreich? Das AWS-Konzept bezieht seine Attraktivität auch aus dem praktischen Nutzen für die Planung von Sprachkursen, denn es ist häufig schwierig, gesonderte Sprachkurse für verschiedene Disziplinen anzubieten.
2. Ist das Konzept der AWS aus linguistischer Sicht zutreffend? Zur Frage, wie unterschiedlich die sprachlichen Anforderungen der einzelnen wissenschaftlichen Disziplinen sind, gibt es in der Literatur divergierende Auffassungen. Einige Forschungsansätze und Ergebnisse werden in diesem Beitrag skizziert.
3. Überzeugt das Konzept der AWS als Grundlage für Vermittlungsprozesse? Ein Blick auf Lehrmaterialien verdeutlicht, wie Wissenschaftssprache disziplinübergreifend vermittelt werden kann und welche Probleme sich ergeben.
Die hier vorgestellten Überlegungen münden letztlich in den Appell, die unterschiedlichen sprachlichen Anforderungen in den verschiedenen Fächern nach Möglichkeit zu berücksichtigen.
The development of native user interface components is a time consuming and repetitive process, especially for quite simple components like text fields in a form. In order to save time during development an approach is presented in this paper, abstracting the description of the elements into separate files independent from the source code. With aspects from generative and model-driven approaches this leads to simple reusable UI components without the need of deep knowledge in native programming languages.
Cognitive radio (CR) is a key enabler of wireless in industrial applications especially for those with strict quality-of-service (QoS) requirements. The cornerstone of CR is spectrum occupancy prediction that enables agile and proactive spectrum access and efficient utilization of spectral resources. Hidden Markov Models (HMM) provide powerful and flexible tools for statistical spectrum prediction. In this paper we introduce a HMM-based spectrum prediction algorithm for industrial applications that accurately predicts multiple slots in the future. Traditional HMM prediction approaches use two hidden states enabling the prediction of only one step ahead in the future. This one step is most often not enough due to internal hardware delays that render it outdated. We show in this work that extending the number of hidden states and formulating the prediction problem as a maximum likelihood (ML) classification approach enables a prediction span of multiple slots in the future even with fine spectrum sensing resolution. We verify the suitability of our approach to industrial wireless through extensive simulations that utilize a realistic measurement-based traffic model specifically tailored for industrial automotive settings.
Many secure software development methods and tools are well-known and understood. Still, the same software security vulnerabilities keep occurring. To find out if new source code patterns evolved or the same patterns are reoccurring, we investigate SQL injections in PHP open source projects. SQL injections are well-known and a core part of software security education. For each common part of SQL injections, the source code patterns are analysed. Examples are pointed out showing that developers had software security in mind, but nevertheless created vulnerabilities. A comparison to earlier work shows that some categories are not found as often as expected. Our main contribution is the categorization of source code patterns.
To get a better understanding of Cross Site Scripting vulnerabilities, we investigated 50 randomly selected CVE reports which are related to open source projects. The vulnerable and patched source code was manually reviewed to find out what kind of source code patterns were used. Source code pattern categories were found for sources, concatenations, sinks, html context and fixes. Our resulting categories are compared to categories from CWE. A source code sample which might have led developers to believe that the data was already sanitized is described in detail. For the different html context categories, the necessary Cross Site Scripting prevention mechanisms are described.
We investigated 50 randomly selected buffer overflow vulnerabilities in Firefox. The source code of these vulnerabilities and the corresponding patches were manually reviewed and patterns were identified. Our main contribution are taxonomies of errors, sinks and fixes seen from a developer's point of view. The results are compared to the CWE taxonomy with an emphasis on vulnerability details. Additionally, some ideas are presented on how the taxonomy could be used to improve the software security education.
Soft-input decoding of concatenated codes based on the Plotkin construction and BCH component codes
(2020)
Low latency communication requires soft-input decoding of binary block codes with small to medium block lengths.
In this work, we consider generalized multiple concatenated (GMC) codes based on the Plotkin construction. These codes are similar to Reed-Muller (RM) codes. In contrast to RM codes, BCH codes are employed as component codes. This leads to improved code parameters. Moreover, a decoding algorithm is proposed that exploits the recursive structure of the concatenation. This algorithm enables efficient soft-input decoding of binary block codes with small to medium lengths. The proposed codes and their decoding achieve significant performance gains compared with RM codes and recursive GMC decoding.
This work investigates soft input decoding for generalized concatenated (GC) codes. The GC codes are constructed from inner nested binary Bose-Chaudhuri-Hocquenghem (BCH)codes and outer Reed-Solomon (RS) codes. In order to enable soft input decoding for the inner BCH block codes, a sequential stack decoding algorithm is used. Ordinary stack decoding of binary block codes requires the complete trellis of the code.
In this work a representation of the block codes based on the trellises of supercodes is proposed in order to reduce the memory requirements for the representation of the BCH codes. Results for the decoding performance of the overall GC code are presented.
Furthermore, an efficient hardware implementation of the GC decoder is proposed.
Smart factory and education
(2016)
The introduction of cyber physical systems into production companies is highly changing working conditions and processes as well as business models. In practice a growing discrepancy between big and small respectively medium-sized companies can be observed. Bridging that gap a university smart factory is introduced to give that companies a platform to trial, educate employees and access consultancy. Realizing the smart factory a highly integrated, open and standardized automation concept is shown comprising single devices, production lines up to a higher automation system maintaining a community or business models.
To evaluate the quality of a person's sleep it is essential to identify the sleep stages and their durations. Currently, the gold standard in terms of sleep analysis is overnight polysomnography (PSG), during which several techniques like EEG (eletroencephalogram), EOG (electrooculogram), EMG (electromyogram), ECG (electrocardiogram), SpO2 (blood oxygen saturation) and for example respiratory airflow and respiratory effort are recorded. These expensive and complex procedures, applied in sleep laboratories, are invasive and unfamiliar for the subjects and it is a reason why it might have an impact on the recorded data. These are the main reasons why low-cost home diagnostic systems are likely to be advantageous. Their aim is to reach a larger population by reducing the number of parameters recorded. Nowadays, many wearable devices promise to measure sleep quality using only the ECG and body-movement signals. This work presents an android application developed in order to proof the accuracy of an algorithm published in the sleep literature. The algorithm uses ECG and body movement recordings to estimate sleep stages. The pre-recorded signals fed into the algorithm have been taken from physionet1 online database. The obtained results have been compared with those of the standard method used in PSG. The mean agreement ratios between the sleep stages REM, Wake, NREM-1, NREM-2 and NREM-3 were 38.1%, 14%, 16%, 75% and 54.3%.
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.
Deep neural networks (DNNs) are known for their high prediction performance, especially in perceptual tasks such as object recognition or autonomous driving. Still, DNNs are prone to yield unreliable predictions when encountering completely new situations without indicating their uncertainty. Bayesian variants of DNNs (BDNNs), such as MC dropout BDNNs, do provide uncertainty measures. However, BDNNs are slow during test time because they rely on a sampling approach. Here we present a single shot MC dropout approximation that preserves the advantages of BDNNs without being slower than a DNN. Our approach is to analytically approximate for each layer in a fully connected network the expected value and the variance of the MC dropout signal. We evaluate our approach on different benchmark datasets and a simulated toy example. We demonstrate that our single shot MC dropout approximation resembles the point estimate and the uncertainty estimate of the predictive distribution that is achieved with an MC approach, while being fast enough for real-time deployments of BDNNs.
Simulationsmethoden bei der Entwicklung von Extremleichtbaukomponenten in Faserverbundbauweise
(2018)
We consider classes of (Formula presented.)-by-(Formula presented.) sign regular matrices, i.e. of matrices with the property that all their minors of fixed order (Formula presented.) have one specified sign or are allowed also to vanish, (Formula presented.). If the sign is nonpositive for all (Formula presented.), such a matrix is called totally nonpositive. The application of the Cauchon algorithm to nonsingular totally nonpositive matrices is investigated and a new determinantal test for these matrices is derived. Also matrix intervals with respect to the checkerboard ordering are considered. This order is obtained from the usual entry-wise ordering on the set of the (Formula presented.)-by-(Formula presented.) matrices by reversing the inequality sign for each entry in a checkerboard fashion. For some classes of sign regular matrices, it is shown that if the two bound matrices of such a matrix interval are both in the same class then all matrices lying between these two bound matrices are in the same class, too.
Side Channel Attack Resistance of the Elliptic Curve Point Multiplication using Gaussian Integers
(2020)
Elliptic curve cryptography is a cornerstone of embedded security. However, hardware implementations of the elliptic curve point multiplication are prone to side channel attacks. In this work, we present a new key expansion algorithm which improves the resistance against timing and simple power analysis attacks. Furthermore, we consider a new concept for calculating the point multiplication, where the points of the curve are represented as Gaussian integers. Gaussian integers are subset of the complex numbers, such that the real and imaginary parts are integers. Since Gaussian integer fields are isomorphic to prime fields, this concept is suitable for many elliptic curves. Representing the key by a Gaussian integer expansion is beneficial to reduce the computational complexity and the memory requirements of a secure hardware implementation.
Side Channel Attack Resistance of the Elliptic Curve Point Multiplication using Eisenstein Integers
(2020)
Asymmetric cryptography empowers secure key exchange and digital signatures for message authentication. Nevertheless, consumer electronics and embedded systems often rely on symmetric cryptosystems because asymmetric cryptosystems are computationally intensive. Besides, implementations of cryptosystems are prone to side-channel attacks (SCA). Consequently, the secure and efficient implementation of asymmetric cryptography on resource-constrained systems is demanding. In this work, elliptic curve cryptography is considered. A new concept for an SCA resistant calculation of the elliptic curve point multiplication over Eisenstein integers is presented and an efficient arithmetic over Eisenstein integers is proposed. Representing the key by Eisenstein integer expansions is beneficial to reduce the computational complexity and the memory requirements of an SCA protected implementation.
These days, medical applications of shape memory alloys (SMAs) can be found in cardiovascular devices, gastroenterology and urology as well as in the area of orthopedic implants, orthodontic devices and clinical instrumentation. Their functional properties combined with excellent biocompatibility increase the possibility and the performance of minimally invasive surgeries. Overviews of existing applications can be found in [1-2]. Within the medical field, most of the applications with shape memory (SM) material take advantage of the superelasticity of NiTi SMAs. In contradiction to the superelastic or mechanical SM effect, the application described in this study uses the thermal SM effect for a new medical implant. Before explaining the SM driven intramedullary bone nail in detail, a short introduction to the bone elongation technique is given.
The background of this application on based in the medical fact that normally any tissue reacts to an injury with repair and healing processes through multiplication of cells. If after a transverse osteotomy a strain stimulus is activated, for example by tensile stress, this multiplication of cells and new formation of tissue may be continued for any length of time. Due to this mechanism, even considerable loss of bone caused by fractures or congenital defective positions, may be compensated without bone grafts. The technique of callus distraction by means of external fixation or intramedullary nail stimulates the formation of callus in the bone gap. Callus is the repair tissue of the bone generated in the fracture gap in case of bone fracture or osteotomy. The gap to be bridged should not be wider than 1 mm per day [3]. The process starts with the exudation of callus around the ends of the broken bone. At first, callus is more like a fibrous tissue. Later it hardens due to deposition of calcium and eventually it is converted into true bone. Three weeks after severance, the vascular system is formed. An overview of current bone lengthening techniques, also called callus distraction, can be found in [3]. External systems are normally used for the extension of bones, the bone fragments being fixed on rings by wires. The decisive disadvantages of those external systems are primarily the considerable risk of infection due to protruding wires, noticeable discomfort for the patient because of the external rings, a coarse cosmetic result because of scarring, as well as rather long hospitalization.
Therefore, internal bone extension systems are of great interest to orthopedic surgery.
In this paper, a novel measurement model based on spherical double Fourier series (DFS) for estimating the 3D shape of a target concurrently with its kinematic state is introduced. Here, the shape is represented as a star-convex radial function, decomposed as spherical DFS. In comparison to ordinary DFS, spherical DFS do not suffer from ambiguities at the poles. Details will be given in the paper. The shape representation is integrated into a Bayesian state estimator framework via a measurement equation. As range sensors only generate measurements from the target side facing the sensor, the shape representation is modified to enable application of shape symmetries during the estimation process. The model is analyzed in simulations and compared to a shape estimation procedure using spherical harmonics. Finally, shape estimation using spherical and ordinary DFS is compared to analyze the effect of the pole problem in extended object tracking (EOT) scenarios.
Shadow IT risk
(2015)
This paper presents the goals, service design approach, and the results of the project “Accessible Tourism around Lake Constance”, which is currently run by different universities, industrial partners and selected hotels in Switzerland, Germany and Austria. In the 1st phase, interviews with different persons with disabilities and elderly persons have been conducted to identify the barriers and pains faced by tourists who want to spend their holidays in the region of Lake Constance as well as possible assistive technologies that help to overcome these barriers. The analysis of the interviews shows that one third of the pains and barriers are due to missing, insufficient, wrong or inaccessible information about the
accessibility of the accommodation, surroundings, and points of interests during the planning phase of the holidays. Digital assistive technologies hence play a
major role in bridging this information gap. In the 2nd phase so-called Hotel-Living-Labs (HLL) have been established where the identified assistive technologies
can be evaluated. Based on these HLLs an overall service for accessible holidays has been designed and developed. In the last phase, this service has been implemented
based on the HLLs as well as the identified assistive technologies and is currently field tested with tourists with disabilities from the three participated countries.