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Error correction coding (ECC) for optical communication and persistent storage systems require high rate codes that enable high data throughput and low residual errors. Recently, different concatenated coding schemes were proposed that are based on binary Bose-Chaudhuri-Hocquenghem (BCH) codes that have low error correcting capabilities. Commonly, hardware implementations for BCH decoding are based on the Berlekamp-Massey algorithm (BMA). However, for single, double, and triple error correcting BCH codes, Peterson's algorithm can be more efficient than the BMA. The known hardware architectures of Peterson's algorithm require Galois field inversion. This inversion dominates the hardware complexity and limits the decoding speed. This work proposes an inversion-less version of Peterson's algorithm. Moreover, a decoding architecture is presented that is faster than decoders that employ inversion or the fully parallel BMA at a comparable circuit size.
The investigation of stress requires to distinguish between stress caused by physical activity and stress that is caused by psychosocial factors. The behaviour of the heart in response to stress and physical activity is very similar in case the set of monitored parameters is reduced to one. Currently, the differentiation remains difficult and methods which only use the heart rate are not able to differentiate between stress and physical activity, without using additional sensor data input. The approach focusses on methods which generate signals providing characteristics that are useful for detecting stress, physical activity, no activity and relaxation.
The Lempel-Ziv-Welch (LZW) algorithm is an important dictionary-based data compression approach that is used in many communication and storage systems. The parallel dictionary LZW (PDLZW) algorithm speeds up the LZW encoding by using multiple dictionaries. The PDLZW algorithm applies different dictionaries to store strings of different lengths, where each dictionary stores only strings of the same length. This simplifies the parallel search in the dictionaries for hardware implementations. The compression gain of the PDLZW depends on the partitioning of the address space, i.e. on the sizes of the parallel dictionaries. However, there is no universal partitioning that is optimal for all data sources. This work proposes an address space partitioning technique that optimizes the compression rate of the PDLZW using a Markov model for the data. Numerical results for address spaces with 512, 1024, and 2048 entries demonstrate that the proposed partitioning improves the performance of the PDLZW compared with the original proposal.
The first part of this work shows the development and application of a new material system using high strength duplex stainless steel wires as net material with environmentally compatible antifouling properties for off-shore fish farm cages. Current net materials from textiles (polyamide) shall be partially replaced by high strength duplex stainless steel in order to have a more environmentally compatible system which meets the more severe mechanical loads (waves, storms, predatores (sharks, seals)). With a new antifouling strategy current issues like reduced ecological damage (e.g. due to copper disposal), lower maintenance costs (e.g. cleaning) and reduced durability shall be resolved.
High strength steel wires are also widely used in geological protection systems, for example rockfall protection or slope stabilisation. Normally hot-dip galvanised carbon steel is used in this case. But in highly corrosive environments like coastal areas, volcanic areas or mines for example, other solutions with a high corrosion resistance and sufficient mechanical properties are necessary. Protection systems made of high strength duplex stainless steel wires enable a significantly longer service life of the portection systems and therefore a higher level of security.
Today, many resource-constrained systems, such as embedded systems, still rely on symmetric cryptography for authentication and digital signatures. Asymmetric cryptography provide a higher security level, but software implementations of public-key algorithms on small embedded systems are extremely slow. Hence, such embedded systems require hardware assistance, i.e. crypto coprocessors optimized for public key operations. Many such coprocessor designs aim on high computational performance. In this work, an area efficient elliptic curve cryptography (ECC) coprocessor is presented for applications in small embedded systems where high performance coprocessors are too costly. We propose a simple control unit with a small instruction set that supports different ECC point multiplication (PM) algorithms. The control unit reduces the logic and number of registers compared with other implementations of ECC point multiplications.
We present an alternative approach to grid management in low voltage grids by the use of artificial intelligence. The developed decision support system is based on an artificial neural network (ANN). Due to the fast reaction time of our system, real time grid management will be possible. Remote controllable switches and tap changers in transformer stations are used to actively manage the grid infrastructure. The algorithm can support the distribution system operators to keep the grid in a safe state at any time. Its functionality is demonstrated by a case study using a virtual test grid. The ANN achieves a prediction rate of around 90% for the different grid management strategies. By considering the four most likely solutions proposed by the ANN, the prediction rate increases to 98.8%, with a 0.1 second increase in the running time of the model.
Martensitic stainless steels has a wide use, for example for blades, knifes or cutter. The best corrosion resistance of these materials is in hardened condition. For better mechanical properties a tempering is normally applied to increase the durability. The tempering is also reducing the hardness and finally the corrosion resistance. Austempering is meanly used at low alloyed steels and brings a good compromise between durability, hardness and corrosion resistance. For martensitic stainless steels, austempering is normally not a topic because of the very long tempering times.
This work shows first results of austempering of some standard martensitic stainless steels and the influence to corrosion resistance. For reference, hardened and also hardened and tempered specimens were investigated. The corrosions resistance was investigated by electrochemical methods.
It is well known that signal constellations which are based on a hexagonal grid, so-called Eisenstein constellations, exhibit a performance gain over conventional QAM ones. This benefit is realized by a packing and shaping gain of the Eisenstein (hexagonal) integers in comparison to the Gaussian (complex) integers. Such constellations are especially relevant in transmission schemes that utilize lattice structures, e.g., in MIMO communications. However, for coded modulation, the straightforward approach is to combine Eisenstein constellations with ternary channel codes. In this paper, a multilevel-coding approach is proposed where encoding and multistage decoding can directly be performed with state-of-the-art binary channel codes. An associated mapping and a binary set partitioning are derived. The performance of the proposed approach is contrasted to classical multilevel coding over QAM constellations. To this end, both the single-user AWGN scenario and the (multiuser) MIMO broadcast scenario using lattice-reduction-aided preequalization are considered. Results obtained from numerical simulations with LDPC codes complement the theoretical aspects.
A significant proportion of road traffic accidents are due to inattentiveness or fatigue at the wheel. Approaches to monitoring the driver's condition range from eye tracking and driving behavior analysis to yawn and blink detection and ECG measurement. This work describes the development of a mobile system for the measurement and processing of ECG data. The aim of the signal processing is to quantify the driver’s fatigue with the heartrate variability (HRV). The work includes the hardware and software design of the sensor. First, the development of low-noise electronics including AD conversion is described. Then the software signal processing with QRS complex detection and plotting front end is explained. The resulting sensor is compact, low-cost and provides a good signal for HRV extraction.
Vortrag und Abstract
Why does a teacher use drama elements in her language classes? This article critically reflects on the author's experiences with employing drama elements in a compulsory class of German as a Foreign Language at college level. Motives for using drama are discussed, with regard to possible positive effects for the teacher-such as rapport with learners and personal confidence-and potential benefits for the language learners-such as promoting vocabulary and grammar learning, fostering oral skills and increasing motivation. After that the drama activities used in class are briefly described. However, two years of experimentation have also shown up a number of problems with implementing drama elements in class and still leave questions open, requiring further iterations of the drama-based approach in this context. The paper was developed from a talk given at the Drama in Education Days in Konstanz 2018.
Dramapädagogik-Tage 2018
(2019)
Der Tagungsband zur 4. Konferenz zu Drama und Theater im Fremd- und Zweitsprachenunterricht versammelt Tagungsbeiträge aus den Bereichen Grundlagen, Forschung und Praxis. Die Beiträge reichen von Begriffsklärungen zur Dramapädagogik über Skizzen aktueller Forschungprojekte hin zu Praxisbeiträgen zu den Themen Process Drama und interkulturelles Lernen, Körpersprache und Fremdsprachenlernen, Fremdsprachenlernen mit Gedichten, reflektiver Praxis, Drama Grammatik und performativer Literatur- und Kulturdidaktik.
Fachvortrag auf dem Swiss Tribology Symposium, 12.11.2019, Hightechzentrum Aargau, Brugg, Schweiz
Fatigue and drowsiness are responsible for a significant percentage of road traffic accidents. There are several approaches to monitor the driver’s drowsiness, ranging from the driver’s steering behavior to analysis of the driver, e.g. eye tracking, blinking, yawning or electrocardiogram (ECG). This paper describes the development of a low-cost ECG sensor to derive heart rate variability (HRV) data for the drowsiness detection. The work includes the hardware and the software design. The hardware has been implemented on a printed circuit board (PCB) designed so that the board can be used as an extension shield for an Arduino. The PCB contains a double, inverted ECG channel including low-pass filtering and provides two analog outputs to the Arduino, that combined them and performs the analog-to-digital conversion. The digital ECG signal is transferred to an NVidia embedded PC where the processing takes place, including QRS-complex, heart rate and HRV detection as well as visualization features. The compact resulting sensor provides good results in the extraction of the main ECG parameters. The sensor is being used in a larger frame, where facial-recognition-based drowsiness detection is combined with ECG-based detection to improve the recognition rate under unfavorable light or occlusion conditions.
Low temperature carburizing of a series of austenitic stainless with various combinations of chromium and nickel equivalents was performed. The investigation of the response towards low temperature carburized for three stainless steels with various Cr- and Ni-equivalents showed that the carbon uptake depends significantly on the chemical composition of the base material. The higher carbon content in the expanded austenite layer of specimen 6 (1.4565) and specimen 4 (1.4539/AISI 904L) compared to specimen 2 (1.4404/AISI 316L) is assumed to be mainly related to the difference in the specimens’ chromium content. More chromium leads to more lattice expansion. Along with the higher carbon content, higher hardness values and higher compressive residual stresses in the expanded austenite zone are introduced than for low temperature carburized AISI 316L. The residual stresses obtained from X-ray diffraction lattice strain investigation depend strongly on the chosen X-ray elastic constants. Presently, no values are known for carbon (or nitrogen) stabilized expanded austenite. Nevertheless, first principle elastic constants for γ′&minus Fe4C appear to provide realistic residual stress values. Magnetic force microscopy and measurement with an eddy current probe indicate that austenitic stainless steels can become ferromagnetic upon carburizing, similar for low temperature nitriding. The apparent transition from para- to ferromagnetism cannot be attributed entirely to the interstitially dissolved carbon content in the formed expanded austenite layer but appears to depend also on the metallic composition of the alloy, in particular the Ni content.
The goal of this paper pretends to show how a bed system with an embedded system with sensor is able to analyze a person’s movement, breathing and recognizing 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 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.
The reliable supply of energy is an essential prerequisite for the economic success of a country. Questions of sustainability and the replacement of import dependencies require new tasks with new approaches. This contribution provides an overview of dependencies using the example of German electrical power grids integrating renewable energies. Aspects of energy trading and grid stability are brought into connection, stock exchange trading, grid codes and volatility of used primary energies are discussed.
Engineering and management
(2019)
Entrepreneurial employees
(2019)
Volatile markets and accelerating innovation cycles progressively force established companies to adopt alternative innovation strategies such as entrepreneurship. Due to the key role entrepreneurial employees play for strengthening the company's abilities for innovation and change, various concepts have emerged like corporate entrepreneurship or intrapreneurship. While the extant literature has increasingly examined only specific issues of entrepreneurial employees, an overall view on it lacks investigation. Therefore, the purpose of this paper is to structurally present current research on entrepreneurial employees by conducting a broad systematic literature review. The resulting research streams contribute to a clearer justification for future research and are a first step towards a comprehensive research view related to intrapreneurship.
Fast and reliable acquisition of truth data for document analysis using cyclic suggest algorithms
(2019)
In document analysis the availability of ground truth data plays a crucial role for the success of a project. This is even more true at the rise of new deep learning methods which heavily rely on the availability of training data. But even for traditional, hand crafted algorithms that are not trained on data, reliable test data is important for the improvement and evaluation of the methods. Because ground truth acquisition is expensive and time consuming, semi-automatic methods are introduced which make use of suggestions coming from document analysis systems. The interaction between the human operator and the automatic analysis algorithms is the key to speed up the process while improving the quality of the data. The final confirmation of data may always be done by the human operator. This paper demonstrates a use case for acquisition of truth data in a mail processing system. It shows why a new, extended view on truth data is necessary in development and engineering of such systems. An overview over the tool and the data handling is given, the advantages in the workflow are shown, and consequences for the construction of analysis algorithms are discussed. It can be shown that the interplay between suggest algorithms and human operator leads to very fast truth data capturing. The surprising finding is the fact that if multiple suggest algorithms circularly depend on data, they are especially effective in terms of speed and accuracy.
Ziel der Masterarbeit war es, die Feuchtigkeitseigenschaften von Estrichen bei unterschiedlichen Klimaten mithilfe von Sorptionsisothermen zu charakterisieren. Die wenigen Literaturangaben zu Sorptionsisothermen von mineralischen Estrichen beziehen sich im Wesentlichen auf Calciumsulfatestriche und genormte Zementestriche (ohne dass die Zementart: Portlandzemente, Hochofenzemente bzw. CEM I, CEM II, CEM III etc. unterschieden werden) und i.d.R. nur auf eine Lufttemperatur (= 20 Grad C). Anliegen der Arbeit war es, zusätzlich die seit ca. 20 Jahren marktüblichen ternären Schnellzemente mit zu untersuchen und die baupraktisch interessanten Temperaturen von 15 Grad C und 25 Grad C einzubeziehen. Ebenso wurden die Auswirkungen der Klimabedingung auf der Baustelle (Jahreszeit, Luftfeuchtigkeit, Temperatur) auf den Hydratationsvorgang der Estriche untersucht. Dabei wurden jeweils nicht nur ein Vertreter der verschiedenen Bindemittelsysteme, sondern mindestens zwei verschiedene Estriche unterschiedlicher Hersteller mit einbezogen. In Kombination mit den Ergebnissen der Gefügeuntersuchungen (u. a. Hg-Porosametrie) wird belegt, weshalb sich die zement- und schnellzementgebundenen Estriche vollkommen anders verhalten als die calciumsulfatgebundenen Estriche. Dieses unterschiedliche Verhalten ist auch einer der Gründe, warum Estriche mit der KRL-Methode in Bezug auf ihren Feuchtegehalt nicht bewertet werden können. Aus diesem Grund folgt ein Vergleich der Materialfeuchtemessungen "KRL-Methode" mit der handwerksüblichen und seit Jahrzehnten in der Praxis bewährten "CM-Methode".
Flatness-based feed-forward control of solenoid actuators is considered. For precise motion planning and accurate steering of conventional solenoids, eddy currents cannot be neglected. The system of ordinary differential equations including eddy currents, that describes the nonlinear dynamics of such actuators, is not differentially flat. Thus, a distributed parameter approach based on a diffusion equation is considered, that enables the parametrization of the eddy current by the armature position and its time derivatives. In order to design the feedforward control, the distributed parameter model of the eddy current subsystem is combined with a typical nonlinear lumped parameter model for the electrical and mechanical subsystems of the solenoid. The control design and its application are illustrated by numerical and practical results for an industrial solenoid actuator.
Flooded Edge Gateways
(2019)
Increasing numbers of internet-compatible devices, in particular in the context of IoT, usually cause increasing amounts of data. The processing and analysis of a continuously growing amount of data in real-time by means of cloud platforms cannot be guaranteed anymore. Approaches of Edge Computing decentralize parts of the data analysis logics towards the data sources in order to control the data transfer rate to the cloud through pre-processing with predefined quality-of-service parameters. In this paper, we present a solution for preventing overloaded gateways by optimizing the transfer of IoT data through a combination of Complex Event Processing and Machine Learning. The presented solution is completely based on open-source technologies and can therefore also be used in smaller companies.
Generative Design Software - How does digitalization change the professional profile of architects
(2019)
Abstract, Poster und Vortrag
Extracting suitable features from acquired data to accurately depict the current health state of a system is crucial in data driven condition monitoring and prediction. Usually, analogue sensor data is sampled at rates far exceeding the Nyquist-rate containing substantial amounts of redundancies and noise, imposing high computational loads due to the subsequent and necessary feature processing chain (generation, dimensionality reduction, rating and selection). To overcome these problems, Compressed Sensing can be used to sample directly to a compressed space, provided the signal at hand and the employed compression/measurement system meet certain criteria. Theory states, that during this compression step enough information is conserved, such that a reconstruction of the original signal is possible with high probability. The proposed approach however does not rely on reconstructed data for condition monitoring purposes, but uses directly the compressed signal representation as feature vector. It is hence assumed that enough information is conveyed by the compression for condition monitoring purposes. To fuse the compressed coefficients into one health index that can be used as input for remaining useful life prediction algorithms and is limited to a reasonable range between 1 and 0, a logistic regression approach is used. Run-to-failure data of three translational electromagnetic actuators is used to demonstrate the health index generation procedure. A comparison to the time domain ground truth signals obtained from Nyquist sampled coil current measurements shows reasonable agreement. I.e. underlying wear-out phenomena can be reproduced by the proposed approach enabling further investigation of the application of prognostic methods.
One important skill for engineers is the ability of optimizing their experiments. On their job they will often spend a lot more time designing and improving an experimental setup compared to running the actual experiment itself. Is it possible to teach this complex task in physics labs? A method for reaching this goal is proposed an example is given and discussed.
Autismus-Spektrum-Störungen (ASD) bei Kindern werden häufig zu spät diagnostiziert und die Begleitung der chronischen Krankheit gestaltet sich schwierig. Der vorgestellte Ansatz erlaubt die Behandlung der Kinder in dem bekannten häuslichen Umfeld und versucht die Beziehungen zwischen Schlaf und Verhalten herauszuarbeiten. Die gewonnenen Erkenntnisse sollen die Lebensqualität der Patienten verbessern und den Eltern Hilfestellung geben. Die notwendige infrastrukturelle Unterstützung wird durch medizinisches Fachpersonal geleistet, das auf einen web-basierten Service zurückgreifen kann, der sämtliche Prozesse (Diagnostik, Datenerfassung, -aufzeichnung und Training etc.) begleitet. Die anonymisierten Daten werden in einem Diagnosesystem zentral abgelegt und können so für zukünftige Behandlungsstrategien nutzbar sein. Die umfassende Lösung setzt auf zentrale Elemente von Smart-Homes und AAL auf.
The Industrial Internet of Things (IIoT) will leverage on wireless network technologies to integrate in a seamless manner Cyber-Physical Systems into existing information systems. In this context, the 6TiSCH architecture, proposed by IETF, represents the current leading standardization effort to enable timed and reliable data communication within IPv6 networks for industrial applications. In wireless networks, Link Quality Estimation (LQE) is a crucial task to select the best routes for data forwarding, regardless of unpredictable time varying conditions. Although, many solutions for LQE have been proposed in literature, the majority of them are not designed specifically for 6TiSCH networks. In this paper, we analyze the performance of existing LQE strategies on 6TiSCH networks.
First, we run a set of simulations to measure the performance of one existing LQE strategy in 6TiSCH. Our simulations show that such strategy can result in measurements with low accuracy due to the 6TiSCH default timeslot allocation strategy. Consequently, we propose an extension of the 6TiSCH Minimal Configuration that allocates specific timeslots for the transmission of probing messages to mitigate the problem. The proposed methodology is demonstrated to effectively reduce the LQE error.
Corporate Entrepreneurship (CE) became the new paradigm for organizations to cope with the accelerated development of innovations. Therefore, especially established organizations increasingly implement CE activities, even in combination. Scholars point out that a coordinated portfolio of CE activities could yield synergies and thus higher value for the organization and further call for more scientific examinations. This literature review aims to better the understanding of the combined and coordinated use of CE activities as well as about resulting synergies. Results show that there are only very few studies that addressed a combination and/or coordination of CE activities with respect to the creation of additional value, however, without empirical analyses. Yet, five categories of direct and indirect synergies could be derived. Discussing the results as well as the heterogenous use of terminology and concepts, this paper concludes with a research agenda for future analyses.
This PhD investigation lies at the intersection of Architecture, Textile Design and Interaction Design and speculates about sustainable forms of future living, focussing on bionic principles to create alternative lightweight building structures with textiles and digital fabrication techniques. In an interdisciplinary, practice- based design approach, informed by radical case studies from the 1960s to 80s on soft architectures like Archigram, Buckminster Fuller, Cedric Price, or Yona Friedman and critical theory on new materialism, (D. Haraway 1997, K. Barad 1998, J. Bennett 2007) sociological, philosophical (B. Latour 2005, G.Deleuze F., Guattari F 1987) and phenomenological thinkers (L. Malafouris 2005, J.Rancière 2004, B. Massumi 2002, N. Bourriaud 2002 , M. Merleau-Ponty 1963) this research investigates the cultural and social rootedness (Verortung) of novel materials and technologies, exploring in between prosthetic relations between the body and the environment.
The exposure to the light has a great influence on human beings in their everyday life. Various lighting sources produce light that reaches the human eye and influences a rhythmic release of melatonin hormone, that is a sleep promoting factor.
Since the development of new technologies provides more control over illuminance, this work uses an IoT based lighting system to set up dim and bright scenarios. A small study has been performed on the influence of illuminance on sleep latency. The system consists of different light bulbs, sensors and a central bridge which are interconnected like a mesh network. Also, a mobile app has been developed, that allows to adjust the lighting in various rooms. With the help of a ferro-electret sensor, like applied in sleep monitoring systems, a subject’s sleep was monitored. The sensor is placed below the mattress and it collects data, which is stored and processed in a cloud or in other alternative locations.
The research was conducted on healthy young subjects after being previously exposed to the preconfigured illuminance for at least three hours before bedtime. The results indicate correlation between sleep onset latency and exposure to different illuminance before bedtime. In a dimmed environment, the subject fell asleep in average 28% faster compared to the brighter environment.
We present an innovative decision support system (DSS) for distribution system operators (DSO) based on an artificial neural network (ANN). A trained ANN has the ability to recognize problem patterns and to propose solutions that can be implemented directly in real time grid management. The principle functionality of this ANN based optimizer has been demonstrated by means of a simple virtual electrical grid. For this grid, the trained ANN predicted the solution minimizing the total line power dissipation in 98 percent of the cases considered. In 99 percent of the cases, a valid solution in compliance with the specified operating conditions was found. First ANN tests on a more realistic grid, calibrated with household load measurements, revealed a prediction rate between 88 and 90 percent depending on the optimization criteria. This approach promises a faster, more cost-efficient and potentially secure method to support distribution system operators in grid management.
A physics lab-setup has been developed for engineering students in their first year at university. The so-called LabTeamCoaching helps to improve general lab skills, such as preparing an experiment, writing a documentation, using graphs and drawing conclusions. By using a flipped classroom approach, students get better involved than in our former physics labs when we applied classical methods. This approach will be described and an overview of our 10 years of experience using this method will be given.
CO2 compensation measures, in particular the compensation of flights, are becoming more and more popular. Carbon offsetting is defined as measures financed by donations that save greenhouse gases previously emitted elsewhere through climate protection projects.
CO2 abatement costs are often low in developing countries. This is why most offset projects are implemented there. Nevertheless, this does not mean that the holiday resort and the project country are in any way related to each other.
By linking carbon offset projects with the destination country, the tourist is able to get an impression of the co-financed project. In case such projects are realized in cooperation with the hotel, the hotel operator obtains a new tourist attraction and can demonstrate its efforts to climate protection in a PR-effective way.
This work proposes a suboptimal detection algorithm for generalized multistream spatial modulation. Many suboptimal detection algorithms for spatial modulation use two-stage detection schemes where the set of active antennas is detected in the first stage and the transmitted symbols in the second stage. For multistream spatial modulation with large signal constellations the second detection step typically dominates the detection complexity. With the proposed detection scheme, the modified Gaussian approximation method is used for detecting the antenna pattern. In order to reduce the complexity for detecting the signal points, we propose a combined equalization and list decoding approach. Simulation results demonstrate that the new algorithm achieves near-maximum-likelihood performance with small list sizes. It significantly reduces the complexity when compared with conventional two-stage detection schemes.
The computational complexity of the optimal maximum likelihood (ML) detector for spatial modulation increases rapidly as more transmit antennas or larger modulation orders are employed. Hence, ML detection may be infeasible for higher bit rates. This work proposes an improved suboptimal detection algorithm based on the Gaussian approximation method. It is demonstrated that the new method is closely related to the previously published signal vector based detection and the modified maximum ratio combiner, but can improve the detection performance compared to these methods. Furthermore, the performance of different signal constellations with suboptimal detection is investigated. Simulation results indicate that the performance loss compared to ML detection depends heavily on the signal constellation, where the recently proposed Eisenstein integer constellations are beneficial compared to classical QAM or PSK constellations.
Magnetic effects on austenitic stainless steels, formed during a low temperature carburizing depending on the alloy composition are discussed in this paper. Samples of different austenitic stainless steel alloys have been subjected to a multiple low-temperature carburization. Layer characteriszation with light microscope and hardness profiles show a growth of the layer thickness. The formation of an expanded austenite layer (lattice expansion) could be detected by X-ray diffraction (XRD). Feritscope was used to determine the magnetizability, whereby not all austenitic alloys form a magnetizability after treatment. Furthermore, test procedures were developed to visualize the magnetizability. For this purpose, magnetic force microscope measurements and investigations with ferrofluid were carried out and a fir tree ferromagnetic layer strucure could be proven.
Fachvortrag auf der 10th International European Stainless Steel Conference and 6th European Duplex Stainless Steel Conference (ESSC & DUPLEX 2019), 30.09. – 02.10.2019, Vienna, Austria
Die Studienanfänger in den technischen Studiengängen der Hochschulen für angewandte Wissenschaften haben nicht nur in Mathematik sondern auch in Physik sehr unterschiedliche Vorkenntnisse. Obwohl diese Fächer für das grundlegende Verständnis technischer Vorgänge von großer Bedeutung sind, kann die Ausbildung in diesen Bereichen angesichts der begrenzten dafür im Verlauf des Studiums zur Verfügung stehenden Zeitfenster nicht bei Null anfangen. Für Mathematik wurde daher von der Arbeitsgruppe cosh ein Mindestanforderungskatalog zusammengestellt und 2014 veröffentlicht. Er beschreibt Kenntnisse und Fertigkeiten, die Studienanfänger zur erfolgreichen Aufnahme eines WiMINT-Studiums (Wirtschaft, Mathematik, Informatik, Naturwissenschaft, Technik) an einer Hochschule benötigen. Inzwischen hat sich nun eine Arbeitsgruppe von Physikerinnen und Physikern an Hochschulen in Baden-Württemberg gebildet, deren Ziel es ist, einen analogen Mindestanforderungskatalog für den Bereich Physik zu erstellen. Hier wird der aktuell erreichte Stand der Arbeiten vorgestellt.
This work introduces new signal constellations based on Eisenstein integers, i.e., the hexagonal lattice. These sets of Eisenstein integers have a cardinality which is an integer power of three. They are proposed as signal constellations for representation in the equivalent complex baseband model, especially for applications like physical-layer network coding or MIMO transmission where the constellation is required to be a subset of a lattice. It is shown that these constellations form additive groups where the addition over the complex plane corresponds to the addition with carry over ternary Galois fields. A ternary set partitioning is derived that enables multilevel coding based on ternary error-correcting codes. In the subsets, this partitioning achieves a gain of 4.77 dB, which results from an increased minimum squared Euclidean distance of the signal points. Furthermore, the constellation-constrained capacities over the AWGN channel and the related level capacities in case of ternary multilevel coding are investigated. Simulation results for multilevel coding based on ternary LDPC codes are presented which show that a performance close to the constellation-constrained capacities can be achieved.
Das hier vorgestellte Netzoptimierungstool kann dem Verteilnetzbetreiber bei einem Störfall im Netz in Echtzeit eine Lösung zur Steuerung seiner Betriebsmittel vorschlagen. Dadurch kann das bestehende Netz optimal genutzt werden und ein kostenintensiver Netzausbau im Mittel- und Niederspannungsnetz verringert oder sogar verhindert werden. Als Grundlage für den Netzoptimierer dient ein künstliches neuronales Netz (KNN). Zum Training des KNN wurden Störfälle generiert, die auf reellen Erzeugungs- und Lastprofilen aus dem CoSSMic-Projekt basieren [1]. Für jeden Störfall wurde aus allen möglichen und sinnvollen Netzkonfigurationen eine optimierte Netztopologie anhand von Lastflussberechnungen ermittelt. Durch die Variation der Stufenschalter der Transformatoren und der Stellungen aller installierten Schalter im Netz wurde berechnet, wie der Stromfluss gelenkt werden muss, damit keines der Betriebsmittel die zulässigen Belastungsgrenzen mehr überschreitet. Für ein virtuelles Testnetz konnte mit einem trainierten KNN zu 90 Prozent die optimale Lösung des jeweiligen Störfalls erkannt werden. Durch die Anwendung der N-Best Methode konnte die Vorhersagewahrscheinlichkeit auf annähernd 99 Prozent erhöht werden.
Assistive environments are entering our homes faster than ever. However, there are still various barriers to be broken. One of the crucial points is a personalization of offered services and integration of assistive technologies in common objects and therefore in a regular daily routine. Recognition of sleep patterns for the preliminary sleep study is one of the health services that could be performed in an undisturbing way. This article proposes the hardware system for the measurement of bio-vital signals necessary for initial sleep study in a non-obtrusive way. The first results confirm the potential of measurement of breathing and movement signals with the proposed system.