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Der Titel „Organisatorische Entscheidungen treffen!“ führt in grundlegende Fragen der Organisation ein. Erläutert wird, woraus eine Organisation besteht und wie man sie durch gezielte Entscheidungen an die Bedürfnisse des Unternehmens anpasst. Die allgemeingültigen Aussagen werden durch zahlreiche konkrete Beispiele illustriert.
Das Buch konzentriert sich auf die wichtigsten Aspekte der organisatorischen Gestaltung. Es möchte daher nicht mit den Grundlagenwerken der Organisationslehre konkurrieren, vielmehr begleitet es eine Lehrveranstaltung, deren Stil sich ständig zwischen Vorlesung und Übung abwechselt. Die Übungsaufgaben, die im Unterricht behandelt werden, stehen auch online zur Verfügung und sind dort um Musterlösungen ergänzt. Darüber hinaus gibt es in der Online-Lernumgebung eine Musterklausur, die der zielgerichteten Prüfungsvorbereitung dient.
Wer das Buch sorgfältig durcharbeitet, den Lehrstoff auf die Übungsaufgaben anwendet und die Probeklausur besteht, erwirbt ein solides Grundlagenwissen und ist damit gut vorbereitet, organisatorische Fragen zu analysieren und entsprechende Entscheidungen vorzubereiten.
In this paper, we describe the PALM model system 6.0. PALM (formerly an abbreviation for Parallelized Large-eddy Simulation Model and now an independent name) is a Fortran-based code and has been applied for studying a variety of atmospheric and oceanic boundary layers for about 20 years. The model is optimized for use on massively parallel computer architectures. This is a follow-up paper to the PALM 4.0 model description in Maronga et al. (2015). During the last years, PALM has been significantly improved and now offers a variety of new components. In particular, much effort was made to enhance the model with components needed for applications in urban environments, like fully interactive land surface and radiation schemes, chemistry, and an indoor model. This paper serves as an overview paper of the PALM 6.0 model system and we describe its current model core. The individual components for urban applications, case studies, validation runs, and issues with suitable input data are presented and discussed in a series of companion papers in this special issue.
The PHOTOPUR project aims to develop a photocatalytic process as a type of AOPs (Advanced Oxidation Processes) for the elimination of plant protection products (PPP) of the cleaning water used to wash sprayers. At INES a PV based energy supply for the photocatalytic cleaning system was developed within the framework of two bachelor theses and assembled as a demonstration unit. Then the system was step by step extended with further process automation features and pushed to a remote operating device. The final system is now available as a mobile unit mounted on a lab table. The latest step was the photocatalytic reactor module which completed the first PHOTOPUR prototype. The system is actually undergoing an intensive testing phase with performance checks at the consortium partners. First results give an overview about the successful operation.
We introduce an open source python framework named PHS-Parallel Hyperparameter Search to enable hyperparameter optimization on numerous compute instances of any arbitrary python function. This is achieved with minimal modifications inside the target function. Possible applications appear in expensive to evaluate numerical computations which strongly depend on hyperparameters such as machine learning. Bayesian optimization is chosen as a sample efficient method to propose the next query set of parameters.
Interaction and capturing information from the surrounding is dominated by vision and hearing. Haptics on the other side, widens the bandwidth and could also replace senses (sense switching) for impaired. Haptic technologies are often limited to point-wise actuation. Here, we show that actuation in two-dimensional matrices instead creates a richer input. We describe the construction of a full-body garment for haptic communication with a distributed actuating network. The garment is divided into attachable-detachable panels or add-ons that each can carry a two dimensional matrix of actuating haptic elements. Each panel adds to an enhanced sensoric capability of the human- garment system so that together a 720° system is formed. The spatial separation of the panels on different body locations supports semantic and theme-wise separation of conversations conveyed by haptics. It also achieves directional faithfulness, which is maintaining any directional information about a distal stimulus in the haptic input.
Die industrielle Kommunikation war früher von relativ eingeschränkten, geschlossenen Feldbussystemen geprägt. Mit der zunehmenden Öffnung von Automatisierungsnetzen durch die horizontale und vertikale Integration in Produktionsanlagen entstehen gefährliche Angriffsflächen, die zum Diebstahl von Produktionsgeheimnissen, der Manipulation oder dem kompletten Lahmlegen der Produktionsprozesse führen können. Hieraus ergeben sich grundlegend neue Anforderung an die Datensicherheit, denen mit innovativen Lösungsansätzen begegnet werden muss.
Ziel des Forschungsvorhabens „SecureField“ war es, die Umsetzbarkeit und Anwendbarkeit des Ansatzes „(D)TLS-over-Anything“ zu untersuchen und nachzuweisen, sowie einen Werkzeugkasten zur Definition und Implementierung entsprechender Sicherheitslösungen vorzubereiten. Als langjährig etablierter Standard im IT-Umfeld stellte sich das (Datagram) Transport Layer Security ((D)TLS) Protokoll in Kombination mit einer industrie- bzw. automatisierungskompatiblen Public-Key-Infrastruktur (PKI) als äußerst vielversprechende Möglichkeit dar, Datensicherheit auch im OT-Umfeld zu erzielen. Hierbei sollten insbesondere KMU adressiert werden, für welche eigene Entwicklungsarbeiten in diesem Umfeld häufig zu aufwändig und technisch sowie wirtschaftlich zu riskant sind.
Mit „SecureField“ konnten Ergebnisse auf mehreren Ebenen erzielt werden. Zunächst konnte im Projektverlauf ein umfassendes und generisches Konzept zur Ende-zu-Ende-Absicherung von Kommunikationspfaden und -protokollen im industriellen Umfeld erarbeitet werden. Dieses Konzept besteht aus einem generischen Kommunikationsmodell sowie aus einem generischen Authentifikationsmodell.
Zur Herstellung von Spritzgussformeinsätzen kommen in der Regel spanende Verfahren zum Einsatz. In den letzten Jahren hat sich allerdings auch die additive Herstellung dieser Werkzeuge als zweckmäßig erwiesen. In der Produktentwicklung spielt die Agilität heute eine immer wichtigere Rolle. Um mögliche Potentiale des Additive Tooling im Rahmen des Agile Prototyping und um Unterschiede zu den konventionellen Herstellverfahren aufzuzeigen, werden Angebote für die Fertigung mehrerer Formeinsätze durch eine CNC- und HSC-Fertigung, sowie durch additive Herstellung angefragt und hinsichtlich Beschaffungskosten und -zeiten miteinander verglichen. Zudem erfolgt eine Bewertung der technischen Unterschiede. Aus diesen beiden Betrachtungen kann schließlich ein Profil über die drei Herstellverfahren abgeleitet werden, welches bei der anwendungsfallspezifischen Verfahrensauswahl unterstützen soll.
Modern society is more than ever striving for digital connectivity -- everywhere and at any time, giving rise to megatrends such as the Internet of Things (IoT). Already today, 'things' communicate and interact autonomously with each other and are managed in networks. In the future, people, data, and things will be interlinked, which is also referred to as the Internet of Everything (IoE). Billions of devices will be ubiquitously present in our everyday environment and are being connected over the Internet.
As an emerging technology, printed electronics (PE) is a key enabler for the IoE offering novel device types with free form factors, new materials, and a wide range of substrates that can be flexible, transparent, as well as biodegradable. Furthermore, PE enables new degrees of freedom in circuit customizability, cost-efficiency as well as large-area fabrication at the point of use.
These unique features of PE complement conventional silicon-based technologies. Additive manufacturing processes enable the realization of many envisioned applications such as smart objects, flexible displays, wearables in health care, green electronics, to name but a few.
From the perspective of the IoE, interconnecting billions of heterogeneous devices and systems is one of the major challenges to be solved. Complex high-performance devices interact with highly specialized lightweight electronic devices, such as e.g. smartphones and smart sensors. Data is often measured, stored, and shared continuously with neighboring devices or in the cloud. Thereby, the abundance of data being collected and processed raises privacy and security concerns.
Conventional cryptographic operations are typically based on deterministic algorithms requiring high circuit and system complexity, which makes them unsuitable for lightweight devices.
Many applications do exist, where strong cryptographic operations are not required, such as e.g. in device identification and authentication. Thereby, the security level mainly depends on the quality of the entropy source and the trustworthiness of the derived keys. Statistical properties such as the uniqueness of the keys are of great importance to precisely distinguish between single entities.
In the past decades, hardware-intrinsic security, particularly physically unclonable functions (PUFs), gained a lot of attraction to provide security features for IoT devices. PUFs use their inherent variations to derive device-specific unique identifiers, comparable to fingerprints in biometry.
The potentials of this technology include the use of a true source of randomness, on demand key derivation, as well as inherent key storage.
Combining these potentials with the unique features of PE technology opens up new opportunities to bring security to lightweight electronic devices and systems. Although PE is still far from being matured and from being as reliable as silicon technology, in this thesis we show that PE-based PUFs are promising candidates to provide key derivation suitable for device identification in the IoE.
Thereby, this thesis is primarily concerned with the development, investigation, and assessment of PE-based PUFs to provide security functionalities to resource constrained printed devices and systems.
As a first contribution of this thesis, we introduce the scalable PE-based Differential Circuit PUF (DiffC-PUF) design to provide secure keys to be used in security applications for resource constrained printed devices. The DiffC-PUF is designed as a hybrid system architecture incorporating silicon-based and inkjet-printed components. We develop an embedded PUF platform to enable large-scale characterization of silicon and printed PUF cores.
In the second contribution of this thesis, we fabricate silicon PUF cores based on discrete components and perform statistical tests under realistic operating conditions. A comprehensive experimental analysis on the PUF security metrics is carried out. The results show that the silicon-based DiffC-PUF exhibits nearly ideal values for the uniqueness and reliability metrics. Furthermore, the identification capabilities of the DiffC-PUF are investigated and it is shown that additional post-processing can further improve the quality of the identification system.
In the third contribution of this thesis, we firstly introduce an evaluation workflow to simulate PE-based DiffC-PUFs, also called hybrid PUFs. Hereof, we introduce a Python-based simulation environment to investigate the characteristics and variations of printed PUF cores based on Monte Carlo (MC) simulations. The simulation results show, that the security metrics to be expected from the fabricated devices are close to ideal at the best operating point.
Secondly, we employ fabricated printed PUF cores for statistical tests under varying operating conditions including variations in ambient temperature, relative humidity, and supply voltage. The evaluations of the uniqueness, bit aliasing, and uniformity metrics are in good agreement with the simulation results. The experimentally determined mean reliability value is relatively low, which can be explained by the missing passivation and encapsulation of the printed transistors. The investigation of the identification capabilities based on the raw PUF responses shows that the pure hybrid PUF is not suitable for cryptographic applications, but qualifies for device identification tasks.
The final contribution is to switch to the perspective of an attacker. To judge on the security capabilities of the hybrid PUF, a comprehensive security analysis in the manner of a cryptanalysis is performed. The analysis of the entropy of the hybrid PUF shows that its vulnerability against model-based attacks mainly depends on the selected challenge building method. Furthermore, an attack methodology is introduced to assess the performances of different mathematical cloning attacks on the basis of eavesdropped challenge-response pairs (CRPs). To clone the hybrid PUF, a sorting algorithm is introduced and compared with commonly used supervised machine learning (ML) classifiers including logistic regression (LR), random forest (RF), as well as multi-layer perceptron (MLP).
The results show that the hybrid PUF is vulnerable against model-based attacks. The sorting algorithm benefits from shorter training times compared to the ML algorithms. If the eavesdropped CRPs are erroneous, the ML algorithms outperform the sorting algorithm.
Electrolyte-gated thin-film transistors (EGTs) with indium oxide channel, and expected lifetime of three months, enable low-voltage operation (~1 V) in the field of printed electronics (PEs). The channel width of our printed EGTs is varied between 200 and 1000 μm, whereas a channel length between 10 and 100 μm is used. Due to the lack of uniform performance p-type metal oxide semiconductors, n-type EGTs and passive elements are used to design circuits. For logic gates, transistor-resistor logic has been employed so far, but depletion and enhancement-mode EGTs in a transistor-transistor logic boost the circuit performance in terms of delay and signal swing. In this article, the threshold voltage of the EGT, which determines the operation mode, is tuned through sizing of the EGTs channel geometry. The feasibility of both transistor operation modes is demonstrated for logic gates and ring oscillators. An inverter operating at a supply voltage of 1 V shows a maximum gain of 9.6 and a propagation delay time of 0.7 ms, which represents an improvement of ~ 2x for the gain and oscillation frequency, in comparison with the resistor-transistor logic design. Moreover, the power consumption is reduced by 6x.
Many different methods, such as screen printing, gravure, flexography, inkjet etc., have been employed to print electronic devices. Depending on the type and performance of the devices, processing is done at low or high temperature using precursor- or particle-based inks. As a result of the processing details, devices can be fabricated on flexible or non-flexible substrates, depending on their temperature stability. Furthermore, in order to reduce the operating voltage, printed devices rely on high-capacitance electrolytes rather than on dielectrics. The printing resolution and speed are two of the major challenging parameters for printed electronics. High-resolution printing produces small-size printed devices and high-integration densities with minimum materials consumption. However, most printing methods have resolutions between 20 and 50 μm. Printing resolutions close to 1 μm have also been achieved with optimized process conditions and better printing technology.
The final physical dimensions of the devices pose severe limitations on their performance. For example, the channel lengths being of this dimension affect the operating frequency of the thin-film transistors (TFTs), which is inversely proportional to the square of channel length. Consequently, short channels are favorable not only for high-frequency applications but also for high-density integration. The need to reduce this dimension to substantially smaller sizes than those possible with today’s printers can be fulfilled either by developing alternative printing or stamping techniques, or alternative transistor geometries. The development of a polymer pen lithography technique allows scaling up parallel printing of a large number of devices in one step, including the successive printing of different materials. The introduction of an alternative transistor geometry, namely the vertical Field Effect Transistor (vFET), is based on the idea to use the film thickness as the channel length, instead of the lateral dimensions of the printed structure, thus reducing the channel length by orders of magnitude. The improvements in printing technologies and the possibilities offered by nanotechnological approaches can result in unprecedented opportunities for the Internet of Things (IoT) and many other applications. The vision of printing functional materials, and not only colors as in conventional paper printing, is attractive to many researchers and industries because of the added opportunities when using flexible substrates such as polymers and textiles. Additionally, the reduction of costs opens new markets. The range of processing techniques covers laterally-structured and large-area printing technologies, thermal, laser and UV-annealing, as well as bonding techniques, etc. Materials, such as conducting, semiconducting, dielectric and sensing materials, rigid and flexible substrates, protective coating, organic, inorganic and polymeric substances, energy conversion and energy storage materials constitute an enormous challenge in their integration into complex devices.
In the work at hand, we state that privacy and malleability of data are two aspects highly desired but not easy to associate. On the one hand, we are trying to shape data to make them usable and editable in an intelligible way, namely without losing their initial information. On the other hand, we are looking for effective privacy on data such that no external or non-authorized party could learn about their content. In such a way, we get overlapping requirements by pursuing different goals; it is trivial to be malleable without being secure, and vice versa. We propose four “real-world” use cases identified as scenarios where these two contradictory features are required and taking place in distinct environments. These considered backgrounds consist of firstly, cloud security auditing, then privacy of mobile network users and industry 4.0 and finally, privacy of COVID-19 tracing app users. After presenting useful background material, we propose to employ multiple approaches to design solutions to solve the use cases. We combine homomorphic encryption with searchable encryption and private information retrieval protocol to build an effective construction for the could auditing use case. As a second step, we develop an algorithm to generate the appropriate parameters to use the somewhat homomorphic encryption scheme by considering correctness, performance and security of the respective application. Finally, we propose an alternative use of Bloom filter data structure by adding an HMAC function to allow an outsourced third party to perform set relations in a private manner. By analyzing the overlapping bits occurring on Bloom filters while testing the inclusiveness or disjointness of the sets, we show how these functions maintain privacy and allow operations directly computed on the data structure. Then, we show how these constructions could be applied to the four selected use cases. Our obtained solutions have been implemented and we provide promising results that validate their efficiency and thus relevancy.
Dieses Buch verspricht unter dem Titel „… Wie Unternehmen den Wandel meistern“ Antworten zu geben, aber: Prognosen sind schwierig, vor allem, wenn sie die Zukunft betreffen. Dieses mal Winston Churchill, mal Kurt Tucholsky oder anderen zugeschriebene Zitat macht deutlich, dass jeder Unternehmer – Geschäftsführer, Vorstandsmitglied, Inhaber – die Notwendigkeit des Wandels für sich selbst erkennen und diesen zum richtigen Zeitpunkt in angemessenem Umfang einleiten muss. Dabei besteht die Gesamtheit aller betrieblichen Tätigkeiten zu einem ganz wesentlichen Teil aus Projekten und auch der (mehr oder weniger technologiegetriebene) Wandel des Unternehmens selbst wird ein Projekt sein.
Neuromorphic computing systems have demonstrated many advantages for popular classification problems with significantly less computational resources. We present in this paper the design, fabrication and training of a programmable neuromorphic circuit, which is based on printed electrolytegated field-effect transistor (EGFET). Based on printable neuron architecture involving several resistors and one transistor, the proposed circuit can realize multiply-add and activation functions. The functionality of the circuit, i.e. the weights of the neural network, can be set during a post-fabrication step in form of printing resistors to the crossbar. Besides the fabrication of a programmable neuron, we also provide a learning algorithm, tailored to the requirements of the technology and the proposed programmable neuron design, which is verified through simulations. The proposed neuromorphic circuit operates at 5V and occupies 385mm 2 of area.
OVVL (the Open Weakness and Vulnerability Modeller) is a tool and methodology to support threat modeling in the early stages of the secure software development lifecycle. We provide an overview of OVVL (https://ovvl.org), its data model and browser-based UI. We equally provide a discussion of initial experiments on how identified threats in the design phase can be aligned with later activities in the software lifecycle (issue management and security testing).
Ein Windenergieprojekt ist eine hochindividuelle Kraftwerksplanung und das Projektmanagement hierzu ist geprägt von zahlreichen Besonderheiten, die berücksichtigt werden müssen. Die mehrjährigen Planungszeiträume, die Energiewende, der technische Fortschritt, die hohen Kosten, die Internationalisierung der Branche und die Diskussionen über den Klimawandel beeinflussen die Durchführung der Projekte, die Entscheidungen eines Projektmanagers und die der weiteren Projektbeteiligten.
Das Buch richtet sich an alle Projektentwickler, Anlagenhersteller und Gutachter aus der Windenergiebranche und jene, die mit dieser Branche zusammenarbeiten. Es vermittelt bewusst praxisnahe Erfahrungen und Erkenntnisse von Projektmanagementthemen über die gesamte Wertschöpfungskette von Wind Onshore.
Automotive service suppliers are keen to invent products that help to reduce particulate matter pollution substantial, but governance worldwide are not yet ready to introduce this retrofitting of helpful devices statutory. To develop a strategy how to introduce these devices to the market based on user needs is the objective of our research. The contribution of this paper is three-fold: we will provide an overview of the current options of particulate matter pollution solutions (I). This corpus is used to come to a more precise description of the specific needs and wishes of target groups (II). Finally, a representative empirical study via social media channels with German car owners will help to develop a strategy to introduce retrofit devices into the German market (III).
The recent successes and wide spread application of compute intensive machine learning and data analytics methods have been boosting the usage of the Python programming language on HPC systems. While Python provides many advantages for the users, it has not been designed with a focus on multiuser environments or parallel programming - making it quite challenging to maintain stable and secure Python workflows on a HPC system. In this paper, we analyze the key problems induced by the usage of Python on HPC clusters and sketch appropriate workarounds for efficiently maintaining multi-user Python software environments, securing and restricting resources of Python jobs and containing Python processes, while focusing on Deep Learning applications running on GPU clusters.
Short-term load forecasting (STLF) has been playing a key role in the electricity sector for several decades, due to the need for aligning energy generation with the demand and the financial risk connected with forecasting errors. Following the top-down approach, forecasts are calculated for aggregated load profiles, meaning the sum of singular loads from consumers belonging to a balancing group. Due to the emerging flexible loads, there is an increasing relevance for STLF of individual factories. These load profiles are typically more stochastic compared to aggregated ones, which imposes new requirements to forecasting methods and tools with a bottom-up approach. The increasing digitalization in industry with enhanced data availability as well as smart metering are enablers for improved load forecasts. There is a need for STLF tools processing live data with a high temporal resolution in the minute range. Furthermore, behin-the-meter (BTM) data from various sources like submetering and production planning data should be integrated in the models. In this case, STLF is becoming a big data problem so that machine learning (ML) methods are required. The research project “GaIN” investigates the improvement of the STLF quality of an energy utility using BTM data and innovative ML models. This paper describes the project scope, proposes a detailed definition for a benchmark and evaluates the readiness of existing STLF methods to fulfil the described requirements as a reviewing paper.
The review highlights that recent STLF investigations focus on ML methods. Especially hybrid models gain more and more importance. ML can outperform classical methods in terms of automation degree and forecasting accuracy. Nevertheless, the potential for improving forecasting accuracy by the use of ML models depends on the underlying data and the types of input variables. The described methods in the analyzed publications only partially fulfil the tool requirements for STLF on company level. There is still a need to develop suitable ML methods to integrate the expanded data base in order to improve load forecasts on company level.
This paper explains the realization of a concept for research-oriented photonics education. Using the example of the integration of an actual PhD project, it is shown how students are familiarized with the topic of research and scientific work in the first semesters. Typical research activities are included as essential parts of the learning process. Research should be made visible and tangible for the students. The authors will present all aspects of the learning environment, their impressions and experiences with the implemented scenario, as well as first evaluation results of the students.
Sustainable design of equipment for process intensification requires a comprehensive and correct identification of relevant stakeholder requirements, design problems and tasks crucial for innovation success. Combining the principles of the Quality Function Deployment with the Importance-Satisfaction Analysis and Contradiction Analysis of requirements gives an opportunity to define a proper process innovation strategy more reliably and to develop an optimal process intensification technology with less secondary engineering and ecological problems.
With the increasing degree of interconnectivity in industrial factories, security becomes more and more the most important stepping-stone towards wide adoption of the Industrial Internet of Things (IIoT). This paper summarizes the most important aspects of one keynote of DESSERT2020 conference. It highlights the ongoing and open research activities on the different levels, from novel cryptographic algorithms over security protocol integration and testing to security architectures for the full lifetime of devices and systems. It includes an overview of the research activities at the authors' institute.
RETIS – Real-Time Sensitive Wireless Communication Solution for Industrial Control Applications
(2020)
Ultra-Reliable Low Latency Communications (URLLC) has been always a vital component of many industrial applications. The paper proposes a new wireless URLLC solution called RETIS, which is suitable for factory automation and fast process control applications, where low latency, low jitter, and high data exchange rates are mandatory. In the paper, we describe the communication protocol as well as the hardware structure of the network nodes for implementing the required functionality. Many techniques enabling fast, reliable wireless transmissions are used – short Transmission Time Interval (TTI), Time-Division Multiple Access (TDMA), MIMO, optional duplicated data transfer, Forward Error Correction (FEC), ACK mechanism. Preliminary tests show that reliable end-to-end latency down to 350 μs and packet exchange rate up to 4 kHz can be reached (using quadruple MIMO and standard IEEE 802.15.4 PHY at 250 kbit/s).
Unternehmerische Entscheidungen sind im Regelfall riskant. Um das Ausmaß des Risikos deutlich zu machen, hat sich in der Praxis die Anfertigung von Szenarioanalysen durchgesetzt. Damit jedoch werden vorliegende Risiken systematisch unterschätzt. Bei wichtigen Entscheidungen sollte besser eine Sensitivitätsanalyse oder eine Simulation durchgeführt werden.
„Nichts geschieht ohne Risiko, aber ohne Risiko geschieht auch nichts“, sagte der ehemalige Bundespräsident Walther Scheel. Der Ausspruch sensibilisiert dafür, dass in fast allen Themen und Prozessen Risiken stecken und die Akteure ein kalkulierbares Risiko eingehen sollten, um auch in komplexen Themen einen signifikanten Fortschritt zu erlangen. In unserem Fall sind die Akteure Projektleiter und Projektteammitglieder, die kaum eigene/persönliche Risiken eingehen, sondern Projektrisiken professionell managen müssen. Die Teammitglieder sind dabei von den Projekten selten persönlich bedroht, sondern das Projekt oder das Unternehmen und entsprechend sind die Risiken oft auch deutlich größer, als eine einzelne Person es sich vorstellen oder persönlich verantworten kann.
Die Erfindung betrifft eine Schaltungsanordnung (10) für ein Kraftfahrzeug, mit einer Hochvolt-Batterie (12) zum Speichern von elektrischer Energie, mit wenigstens einer elektrischen Maschine (14) zum Antreiben des Kraftfahrzeugs, mit einem Stromrichter (16), mittels welchem von der Hochvolt-Batterie (12) bereitstellbare Hochvolt-Gleichspannung in Hochvolt-Wechselspannung zum Betreiben der elektrischen Maschine (14) umwandelbar ist, und mit einem Ladeanschluss (20) zum Bereitstellen von elektrischer Energie zum Laden der Hochvolt-Batterie (12), wobei der Stromrichter (16) als ein Drei-Stufen-Stromrichter ausgebildet ist und wenigstens eine einer Phase (u) der elektrischen Maschine (14) zugeordnete Schaltereinheit (46) aufweist, welche zwei in Reihe geschaltete Schaltergruppen (52, 54) umfasst, die jeweils zwei in Reihe geschaltete IGBTs (T11, T12, T13, T14) aufweisen, wobei zwischen den IGBTs (T11, T12) einer der Schaltergruppen (52, 54) ein Anschluss (64) angeordnet ist, welcher direkt mit einer Leitung (34) des Ladeanschlusses (20) elektrisch verbunden ist.
Schlussbericht IntelliKOMP
(2020)
Im Rahmen des Verbundprojektes IntelliKOMP sollten smarte Werkzeughalter und Spannfutter für Werkzeugmaschinen im Hinblick auf Industrie 4.0 entwickelt werden. Durch eine hochintegrierte Elektronik in den peripheren Maschinenkomponenten soll mittels Sensoren eine Datenerfassung, -verarbeitung und drahtlose -übertragung erfolgen. Durch diese Daten soll bspw. eine prädiktive Wartung ermöglicht werden.
The number of use cases for autonomous vehicles is increasing day by day especially in commercial applications. One important application of autonomous vehicles can be found within the parcel delivery section. Here, autonomous cars can massively help to reduce delivery efforts and time by supporting the courier actively. One important component of course is the autonomous vehicle itself. Nevertheless, beside the autonomous vehicle, a flexible and secure communication architecture also is a crucial key component impacting the overall performance of such system since it is required to allow continuous interactions between the vehicle and the other components of the system. The communication system must provide a reliable and secure architecture that is still flexible enough to remain practical and to address several use cases. In this paper, a robust communication architecture for such autonomous fleet-based systems is proposed. The architecture provides a reliable communication between different system entities while keeping those communications secure. The architecture uses different technologies such as Bluetooth Low Energy (BLE), cellular networks and Low Power Wide Area Network (LPWAN) to achieve its goals.
Die transösophageale Neurostimulation ist eine neue Therapieform und könnte unter anderem zur Schmerzlinderung während einer transösophagealen Linksherzstimulation angewendet werden. Sie ist in die Kategorie der Rückenmarksstimulation (SCS) einzuordnen, die die meist verwendete Technik der Neurostimulation ist. Die derzeit auf dem Markt vorhandenen Ösophaguskatheter werden bei einer elektrophysiologischen Untersuchung mit Ablation und transösophagealer Echokardiographie zur Temperaturüberwachung eingesetzt. Das Ziel dieser Arbeit war, das vorhandene Offenburger Herzrhythmusmodell, um die Wirbelsäule zu erweitern, einen neuen Ösophagus-Elektroden- Katheter für die transösophageale elektrische Stimulation des Rückenmarks zu modellieren und mittels 3D-Computer-Simulationen auf Ihre Wirksamkeit zu untersuchen.
Due to the rapidly increasing storage consumption worldwide, as well as the expectation of continuous availability of information, the complexity of administration in today’s data centers is growing permanently. Integrated techniques for monitoring hard disks can increase the reliability of storage systems. However, these techniques often lack intelligent data analysis to perform predictive maintenance. To solve this problem, machine learning algorithms can be used to detect potential failures in advance and prevent them. In this paper, an unsupervised model for predicting hard disk failures based on Isolation Forest is proposed. Consequently, a method is presented that can deal with the highly imbalanced datasets, as the experiment on the Backblaze benchmark dataset demonstrates.
Social Media Marketing
(2020)
In diesem Beitrag wird ein Planungsprozess mit seinen einzelnen Phasen für ein Social Media Marketing vorgestellt. Darüber hinaus werden zentrale Implementierungsoptionen beschrieben. Hierzu gehören Werbung (über Plattformen und Influencer), Kundenservice, Community Management, Social Recruitment, interne Nutzung und Business Profile.
We propose in this work to solve privacy preserving set relations performed by a third party in an outsourced configuration. We argue that solving the disjointness relation based on Bloom filters is a new contribution in particular by having another layer of privacy on the sets cardinality. We propose to compose the set relations in a slightly different way by applying a keyed hash function. Besides discussing the correctness of the set relations, we analyze how this impacts the privacy of the sets content as well as providing privacy on the sets cardinality. We are in particular interested in how having bits overlapping in the Bloom filters impacts the privacy level of our approach. Finally, we present our results with real-world parameters in two concrete scenarios.
Innovationen sind wichtige Treiber für ökonomisches Wachstum und sind für erfolgreiche Volkswirtschaften von zentraler Bedeutung. In Ländern wie Deutschland, Finnland oder Großbritannien sorgen ein innovationsfreundliches gesellschaftliches Klima, die Entwicklung von Spitzentechnologien an Universitäten und Hochschulen sowie privatwirtschaftliche Innovationstätigkeit für langfristigen Wohlstand. Neben multinationalen Konzernen sind kleine und mittlere Unternehmen (KMU) häufig Treiber von innovativen Ideen.
Alle drei Anträge argumentieren technikdeterministisch, als sei (Digital)Technik mehr als ein mögliches, nicht notwendiges Hilfsmittel im Unterricht. Seit über 30 Jahren wird jede neue Geräte-Generation (PC, Laptops, heute Tablets) mit identischen Argumenten (innovativ, modern, motivationsfördernd) für den Einsatz im Unterricht reklamiert. Doch entscheidend für Lernerfolge und Bildungsprozesse sind die Lehrer-Schülerbeziehung, die direkte Interaktion zwischen Lehrenden und Lernenden und die Sozial- und Klassengemeinschaft, nicht die technische Ausstattung von Schulen. Lernprozesse in Bildungseinrichtungen beruhen auf dem sozialen Miteinander und wechselseitigem Vertrauen. Lernen ist ein individueller und sozialer Prozess, kein technischer Vorgang. Kein Mensch lernt digital.
Keiner der Anträge unterscheidet nach dem Alter der Schülerinnen und Schüler als dem entscheidenden Kriterium für den Einsatz von Medientechnik im Unterricht. Stattdessen wird technikeuphorisch einer zunehmenden Automatisierung des Beschulens und Testens das Wort geredet (Lernsoftware, Lernmanagementsysteme, Lernprofile u.a.). Stand der Wissenschaft (einschließlich der Erfahrungen mit Covid-19 und erzwungenen Schulschließungen) ist aber, dass Präsenzunterricht das oberstes Primat der Schulen sein muss. Schulen sind die Orte des sozialen Miteinander und Schutzraum gerade für sozial Benachteiligte. Das Ziel sind Lern- und Verstehensprozesse der Schülerinnen und Schüler, die Entwicklung ihrer Persönlichkeit und ihre Bildungschancen, nicht quantitative Vergleiche über die technische Ausstattung von Schulen in anderen Bundesländern oder dem Ausland. Pädagogisch argumentierend würde nicht auf digitale Medien(technik) verkürzt; es würden analoge wie technische Medien gleichwertig einbezogen. Ob und ggf. für was man Digitaltechniken altersangemessen und ohne Rückkanal (!) für Nutzerdaten einsetzen kann, ist hingegen erst durch ergebnisoffene Studien zu belegen. Was in allen Anträgen fehlt, ist daher ein klares Verbot der Profilierung Minderjähriger.
Wer darüber hinaus das Ziel der digitalen Transformation der gesamten Gesellschaft mit dem Ziel der digitalen Organisation aller Lebensbereiche kennt, weiß, dass wir IT erst neu denken und alternative Infrastrukturen aufbauen müssen, bevor Digitaltechnik in Schulen einsetzbar wird. Datensparsamkeit und Dezentralisierung, Hoheit über die eigenen Daten und DSGVO-konforme Systeme sind zukunftsweisende Stichworte für IT in Schulen, nicht EdTech als Big Business der Global Education Industries (GEI).
Diffracted waves carry high resolution information that can help interpreting fine structural details at a scale smaller than the seismic wavelength. Because of the low signal-to-noise ratio of diffracted waves, it is challenging to preserve them during processing and to identify them in the final data. It is, therefore, a traditional approach to pick manually the diffractions. However, such task is tedious and often prohibitive, thus, current attention is given to domain adaptation. Those methods aim to transfer knowledge from a labeled domain to train the model, and then infer on the real unlabeled data. In this regard, it is common practice to create a synthetic labeled training dataset, followed by testing on unlabeled real data. Unfortunately, such procedure may fail due to the existing gap between the synthetic and the real distribution since quite often synthetic data oversimplifies the problem, and consequently the transfer learning becomes a hard and non-trivial procedure. Furthermore, deep neural networks are characterized by their high sensitivity towards cross-domain distribution shift. In this work, we present deep learning model that builds a bridge between both distributions creating a semi-synthetic datatset that fills in the gap between synthetic and real domains. More specifically, our proposal is a feed-forward, fully convolutional neural network for imageto-image translation that allows to insert synthetic diffractions while preserving the original reflection signal. A series of experiments validate that our approach produces convincing seismic data containing the desired synthetic diffractions.
A novel approach for synchronization and calibration of a camera and an inertial measurement unit (IMU) in the research-oriented visual-inertial mapping-and localization-framework maplab is presented. Mapping and localization are based on detecting different features in the environment. In addition to the possibility of creating single-case maps, the included algorithms allow merging maps to increase mapping accuracy and obtain large-scale maps. Furthermore, the algorithms can be used to optimize the collected data. The preliminary results show that after appropriate calibration and synchronization maplab can be used efficiently for mapping, especially in rooms and small building environments.
This book constitutes the refereed proceedings of the 20th International TRIZ Future Conference, TFC 2020, held online at the University Cluj-Napoca, Romania, in October 2020 and sponsored by the International Federation for Information Processing.
34 chapters were carefully peer reviewed and selected from 91 conference submissions. They are organized in the following thematic sections: computing TRIZ; education and pedagogy; sustainable development; tools and techniques of TRIZ for enhancing design; TRIZ and system engineering; TRIZ and complexity; and cross-fertilization of TRIZ for innovation management.
Deafblindness, also known as dual sensory loss, is the combination of sight and hearing impairments of such extent that it becomes difficult for one sense to compensate for the other. Communication issues are a key concern for the Deafblind community. We present the design and technical implementation of the Tactile Board: a mobile Augmentative and Alternative Communication (AAC) device for individuals with deafblindness. The Tactile Board allows text and speech to be translated into vibrotactile signs that are displayed real-time to the user via a haptic wearable. Our aim is to facilitate communication for the deafblind community, creating opportunities for these individuals to initiate and engage in social interactions with other people without the direct need of an intervener.
Tactile Navigation with Checkpoints as Progress Indicators?: Only when Walking Longer Straight Paths
(2020)
Persons with both vision and hearing impairments have to rely primarily on tactile feedback, which is frequently used in assistive devices. We explore the use of checkpoints as a way to give them feedback during navigation tasks. Particularly, we investigate how checkpoints can impact performance and user experience. We hypothesized that individuals receiving checkpoint feedback would take less time and perceive the navigation experience as superior to those who did not receive such feedback. Our contribution is two-fold: a detailed report on the implementation of a smart wearable with tactile feedback (1), and a user study analyzing its effects (2). The results show that in contrast to our assumptions, individuals took considerably more time to complete routes with checkpoints. Also, they perceived navigating with checkpoints as inferior to navigating without checkpoints. While the quantitative data leave little room for doubt, the qualitative data open new aspects: when walking straight and not being "overwhelmed" by various forms of feedback in succession, several participants actually appreciated the checkpoint feedback.
Silicon (Si) has turned out to be a promising active material for next‐generation lithium‐ion battery anodes. Nevertheless, the issues known from Si as electrode material (pulverization effects, volume change etc.) are impeding the development of Si anodes to reach market maturity. In this study, we are investigating a possible application of Si anodes in low‐power printed electronic applications. Tailored Si inks are produced and the impact of carbon coating on the printability and their electrochemical behavior as printed Si anodes is investigated. The printed Si anodes contain active material loadings that are practical for powering printed electronic devices, like electrolyte gated transistors, and are able to show high capacity retentions. A capacity of 1754 mAh/gSi is achieved for a printed Si anode after 100 cycles. Additionally, the direct applicability of the printed Si anodes is shown by successfully powering an ink‐jet printed transistor.
Machine learning (ML) has become highly relevant in applications across all industries, and specialists in the field are sought urgently. As it is a highly interdisciplinary field, requiring knowledge in computer science, statistics and the relevant application domain, experts are hard to find. Large corporations can sweep the job market by offering high salaries, which makes the situation for small and medium enterprises (SME) even worse, as they usually lack the capacities both for attracting specialists and for qualifying their own personnel. In order to meet the enormous demand in ML specialists, universities now teach ML in specifically designed degree programs as well as within established programs in science and engineering. While the teaching almost always uses practical examples, these are somewhat artificial or outdated, as real data from real companies is usually not available. The approach reported in this contribution aims to tackle the above challenges in an integrated course, combining three independent aspects: first, teaching key ML concepts to graduate students from a variety of existing degree programs; second, qualifying working professionals from SME for ML; and third, applying ML to real-world problems faced by those SME. The course was carried out in two trial periods within a government-funded project at a university of applied sciences in south-west Germany. The region is dominated by SME many of which are world leaders in their industries. Participants were students from different graduate programs as well as working professionals from several SME based in the region. The first phase of the course (one semester) consists of the fundamental concepts of ML, such as exploratory data analysis, regression, classification, clustering, and deep learning. In this phase, student participants and working professionals were taught in separate tracks. Students attended regular classes and lab sessions (but were also given access to e-learning materials), whereas the professionals learned exclusively in a flipped classroom scenario: they were given access to e-learning units (video lectures and accompanying quizzes) for preparation, while face-to-face sessions were dominated by lab experiments applying the concepts. Prior to the start of the second phase, participating companies were invited to submit real-world problems that they wanted to solve with the help of ML. The second phase consisted of practical ML projects, each tackling one of the problems and worked on by a mixed team of both students and professionals for the period of one semester. The teams were self-organized in the ways they preferred to work (e.g. remote vs. face-to-face collaboration), but also coached by one of the teaching staff. In several plenary meetings, the teams reported on their status as well as challenges and solutions. In both periods, the course was monitored and extensive surveys were carried out. We report on the findings as well as the lessons learned. For instance, while the program was very well-received, professional participants wished for more detailed coverage of theoretical concepts. A challenge faced by several teams during the second phase was a dropout of student members due to upcoming exams in other subjects.
One of the main requirements of spatially distributed Internet of Things (IoT) solutions is to have networks with wider coverage to connect many low-power devices. Low-Power Wide-Area Networks (LPWAN) and Cellular IoT(cIOT) networks are promising candidates in this space. LPWAN approaches are based on enhanced physical layer (PHY) implementations to achieve long range such as LoRaWAN, SigFox, MIOTY. Narrowband versions of cellular network offer reduced bandwidth and, simplified node and network management mechanisms, such as Narrow Band IoT (NB-IoT) and Long-Term Evolution for Machines (LTE-M). Since the underlying use cases come with various requirements it is essential to perform a comparative analysis of competing technologies. This article provides systematic performance measurement and comparison of LPWAN and NB-IoT technologies in a unified testbed, also discusses the necessity of future fifth generation (5G) LPWAN solutions.
Time-of-Flight Cameras Enabling Collaborative Robots for Improved Safety in Medical Applications
(2020)
Human-robot collaboration is being used more and more in industry applications and is finding its way into medical applications. Industrial robots that are used for human-robot collaboration, cannot detect obstacles from a distance. This paper introduced the idea of using wireless technology to connect a Time-of-Flight camera to off-the-shelf industrial robots. This way, the robot can detect obstacles up to a distance of five meters. Connecting Time-of-Flight cameras to robots increases the safety in human-robot collaboration by detecting obstacles before a collision. After looking at the state of the art, the authors elaborated the different requirements for such a system. The Time-of-Flight camera from Heptagon is able to work in a range of up to five meters and can connect to the control unit of the robot via a wireless connection.
Multiple Object Tracking (MOT) is a long-standing task in computer vision. Current approaches based on the tracking by detection paradigm either require some sort of domain knowledge or supervision to associate data correctly into tracks. In this work, we present an unsupervised multiple object tracking approach based on visual features and minimum cost lifted multicuts. Our method is based on straight-forward spatio-temporal cues that can be extracted from neighboring frames in an image sequences without superivison. Clustering based on these cues enables us to learn the required appearance invariances for the tracking task at hand and train an autoencoder to generate suitable latent representation. Thus, the resulting latent representations can serve as robust appearance cues for tracking even over large temporal distances where no reliable spatio-temporal features could be extracted. We show that, despite being trained without using the provided annotations, our model provides competitive results on the challenging MOT Benchmark for pedestrian tracking.
To reach customers by dialog marketing campaigns is more and more difficult. This is a common problem of companies and marketing agencies worldwide: information overload, multi-channel-communication and a confusing variety of offers make it hard to gain the attention of the target group. The contribution of this paper is four-fold: we provide an overview of the current state of print dialog marketing activities and trends (I). Based on this corpus we identify the main key performance indicators of dialog marketing customer interaction (II). A qualitative user experience study identifies the customer wishes and needs, focusing on lottery offers for senior citizens (III). Finally, we evaluate the success of two different dialog marketing campaigns with 20,000 clients and compare the key performance indicators of the original hands-on experience-based print mailings with user experience tested and optimized mailings (IV).