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Despite the unstoppable global drive towards electric mobility, the electrification of sub-Saharan Africa’s ubiquitous informal multi-passenger minibus taxis raises substantial concerns. This is due to a constrained electricity system, both in terms of generation capacity and distribution networks. Without careful planning and mitigation, the additional load of charging hundreds of thousands of electric minibus taxis during peak demand times could prove catastrophic. This paper assesses the impact of charging 202 of these taxis in Johannesburg, South Africa. The potential of using external stationary battery storage and solar PV generation is assessed to reduce both peak grid demand and total energy drawn from the grid. With the addition of stationary battery storage of an equivalent of 60 kWh/taxi and a solar plant of an equivalent of 9.45 kWpk/taxi, the grid load impact is reduced by 66%, from 12 kW/taxi to 4 kW/taxi, and the daily grid energy by 58% from 87 kWh/taxi to 47 kWh/taxi. The country’s dependence on coal to generate electricity, including the solar PV supply, also reduces greenhouse gas emissions by 58%.
Im Team zum fliegenden Traum
(2024)
Different network architectures are being used to build remote laboratories. Historically, it has been difficult to integrate industrial control systems with higher level IT systems like enterprise resource planning (ERP), manufacturing execution systems (MES), and manufacturing operations management (MOM). Getting these systems to communicate with one another has proven to be relatively difficult due to the absence of shared protocols between them. The Open Platform Communications United Architecture (OPC-UA) protocol was introduced as a remedy for this issue and is gaining popularity, but what if open-source protocols that are widely used in the IT industry could be used instead? This paper presents the development of an IT-Architecture for a cyber-physical industrial control systems laboratory that enables a seamless interconnection and integration of its elements. The architecture utilises Node-Red technology. Node-RED is an open-source programming platform developed by IBM that is focused on making it simple to link physical components, APIs, and web services. This cyber-physical laboratory is for learning principles of an industrial cascaded process control factory. Finally, this text will also discuss future work relating to digital twin (DT). A coupled tank system is selected as a teaching factory to illustrate a range of fluid control application in a typical chemical process factory.
Mit zunehmender Dynamik im Forschungsumfeld – Digitalisierung der Produktentwicklung – steigen neben der Komplexität auch die technischen Anforderungen an die künftigen Entscheidungsprozesse. Die Einführung von neuen IT-Systemen zur Automation von Entscheidungen haben Anpassungen in den derzeitigen Geschäftsprozessen der Unternehmen zur Folge. Für eine erfolgreiche Implementierung neuer IT-Informationstools gilt es im Voraus mögliche Auswirkungen auf die bisherigen Anwendersysteme genauer zu untersuchen. Neue Technologien, KI-Informationssysteme oder auch neues Wissen entstehen in der Wissenschaft oft durch Interpretation und Synthese von bestehendem Wissen. Aus diesem Grund nimmt die Qualität von Literaturanalysen eine immer größere Relevanz in der Ingenieur- und Informatikwissenschaft ein. Neben der Anzahl an Publikationen wächst auch der Aufwand für die strukturierte Literaturrecherche (SLA). Die Autoren stellen in diesem Paper den Rechercheprozess und die Ergebnisse einer SLA vor. Mit dieser Arbeit soll der derzeitige Forschungsstand zur Entscheidungsunterstützung in der Produktentwicklung von Klein- und mittelständischen Unternehmen sowie Großunternehmen in der
Automobilbranche ermittelt und nach Analyse sowie Bewertung mögliche Forschungslücken zu automatisierten Entscheidungsunterstützungssystemen (aEUS) aufgezeigt werden.
Impact of a large distribution network on radiation characteristics of planar spiral antenna arrays
(2023)
Designing antenna arrays with a central feed point has gained ground in the antenna technique. This approach, which is usually applied because of manufacturing costs, is difficult to achieve and leads to a large feeding network. The impact of which is numerically investigated in the present work. Upon comparing three different antennas, it is shown that the enlargement of the feed strongly affects the antenna's overall dimensions and the antenna's radiation characteristics. The antenna with the plug-in solution is not only small in size but also performs better compared to antennas with a central feed point. Considering the high effort in designing the feed network with a central point and the influence of the resulting enlarged network on the dimensions and radiation characteristics of the antenna, the cost saving in production can be put into perspective.
Advancing mental health diagnostics: AI-based method for depression detection in patient interviews
(2023)
In this paper, we present a novel artificial intelligence (AI) application for depression detection, using advanced transformer networks to analyse clinical interviews. By incorporating simulated data to enhance traditional datasets, we overcome limitations in data protection and privacy, consequently improving the model’s performance. Our methodology employs BERT-based models, GPT-3.5, and ChatGPT-4, demonstrating state-of-the-art results in detecting depression from linguistic patterns and contextual information that significantly outperform previous approaches. Utilising the DAIC-WOZ and Extended-DAIC datasets, our study showcases the potential of the proposed application in revolutionising mental health care through early depression detection and intervention. Empirical results from various experiments highlight the efficacy of our approach and its suitability for real-world implementation. Furthermore, we acknowledge the ethical, legal, and social implications of AI in mental health diagnostics. Ultimately, our study underscores the transformative potential of AI in mental health diagnostics, paving the way for innovative solutions that can facilitate early intervention and improve patient outcomes.
Verschleiß an Zerspanwerkzeugen mit geometrisch definierter Schneide führt zu schlechter Oberflächenqualität, erhöhten Kräften, Maßabweichungen und Bruch. Bisher wird dieser Verschleiß außerhalb der Maschine oder indirekt (z. B. Durchmesser) erfasst. Der Tausch der Werkzeuge findet nach einer bestimmten Werkstückzahl, Zeit, oder einem Standweg statt. In diesem Beitrag wird ein neuartiges System zur direkten Ermittlung des Freiflächenverschleißes im Arbeitsraum eines Bearbeitungszentrums dargestellt. Dabei wird eine geschützt integrierte Industriekamera mit Objektiv im Arbeitsraum installiert. Die Maschinenachsen bzw. die Bearbeitungsspindel positionieren das Werkzeug davor. Nach einer nur wenige Sekunden dauernden Messung findet die Auswertung des Verschleißes hauptzeitparallel statt.
In recent years, the demand for accurate and efficient 3D body scanning technologies has increased, driven by the growing interest in personalised textile development and health care. This position paper presents the implementation of a novel 3D body scanner that integrates multiple RGB cameras and image stitching techniques to generate detailed point clouds and 3D mesh models. Our system significantly enhances the scanning process, achieving higher resolution and fidelity while reducing the cost, time and effort required for data acquisition and processing. Furthermore, we evaluate the potential use cases and applications of our 3D body scanner, focusing on the textile technology and health sectors. In textile development, the 3D scanner contributes to bespoke clothing production, allowing designers to construct made-to-measure garments, thus minimising waste and enhancing customer satisfaction through fitting clothing. In mental health care, the 3D body scanner can be employed as a tool for body image analysis, providing valuable insights into the psychological and emotional aspects of self-perception. By exploring the synergy between the 3D body scanner and these fields, we aim to foster interdisciplinary collaborations that drive advancements in personalisation, sustainability, and well-being.
Patterns are virtually simulated in 3D CAD programs before production to check the fit. However, achieving lifelike representations of human avatars, especially regarding soft tissue dynamics, remains challenging. This is mainly since conventional avatars in garment CAD programs are simulated with a continuous hard surface and not corresponding to the human physical and mechanical body properties of soft tissue. In the real world, the human body’s natural shape is affected by the contact pressure of tight-fitting textiles. To verify the fit of a simulated garment, the interactions between the individual body shape and the garment must be considered. This paper introduces an innovative approach to digitising the softness of human tissue using 4D scanning technology. The primary objective of this research is to explore the interactions between tissue softness and different compression levels of apparel, exerting pressure on the tissue to capture the changes in the natural shape. Therefore, to generate data and model an avatar with soft body physics, it is essential to capture the deform ability and elasticity of the soft tissue and map it into the modification options for a simulation. To aim this, various methods from different fields were researched and compared to evaluate 4D scanning as the most suitable method for capturing tissue deformability in vivo. In particular, it should be considered that the human body has different deformation capabilities depending on age, the amount of muscle and body fat. In addition, different tissue zones have different mechanical properties, so it is essential to identify and classify them to back up these properties for the simulation. It has been shown that by digitising the obtained data of the different defined applied pressure levels, a prediction of the deformation of the tissue of the exact person becomes possible. As technology advances and data sets grow, this approach has the potential to reshape how we verify fit digitally with soft avatars and leverage their realistic soft tissue properties for various practical purposes.
With the rapid development of globalization, the demand for translation between different languages is also increasing. Although pre-training has achieved excellent results in neural machine translation, the existing neural machine translation has almost no high-quality suitable for specific fields. Alignment information, so this paper proposes a pre-training neural machine translation with alignment information via optimal transport. First, this paper narrows the representation gap between different languages by using OTAP to generate domain-specific data for information alignment, and learns richer semantic information. Secondly, this paper proposes a lightweight model DR-Reformer, which uses Reformer as the backbone network, adds Dropout layers and Reduction layers, reduces model parameters without losing accuracy, and improves computational efficiency. Experiments on the Chinese and English datasets of AI Challenger 2018 and WMT-17 show that the proposed algorithm has better performance than existing algorithms.
Analog integrated circuit sizing still relies heavily on human expert knowledge as previous automation approaches have not found wide-spread acceptance in industry. One strand, the optimization-based automation, is often discarded due to inflated constraining setups, infeasible results or excessive run times. To address these deficits, this work proposes a alternative optimization flow featuring a designer’s intuition for feasible design spaces through integration of expert knowledge based on the gm/ID-method. Moreover, the extensive run times of simulation-based optimization flows are overcome by incorporating computationally efficient machine learning methods. Neural network surrogate models predicting eleven performance parameters increase the evaluation speed by 3 400× on average compared to a simulator. Additionally, they enable the use of optimization algorithms dependent on automatic differentiation, that would otherwise be unavailable in this field. First, an up to 4× more efficient way for sampling training data based on the aforementioned space is detailed. After presenting the architecture and training effort regarding the surrogate models, they are employed as part of the objective function for sizing three operational amplifiers with three different optimization algorithms. Additionally, the benefits of using the gm/ID-method become evident when considering technology migration, as previously found solutions may be reused for other technologies.
This article presents a modified method of performing power flow calculations as an alternative to pure energy-based simulations of off-grid hybrid systems. The enhancement consists in transforming the scenario-based power flow method into a discrete time-dependent algorithm with the inclusion of bus and controller dynamics.
In clothing e-commerce, the challenge of optimally recommending clothing that suits a user’s unique characteristics remains a pressing issue. Many platforms simply recommend best-selling or popular clothing, without taking into account important attributes like user’s face color, pupil color, face shape, age, etc. To solve this problem, this paper proposes a personalized clothing recommendation algorithm that incorporates the established 4-Season Color System and user-specific biological characteristics. Firstly, the attributes and colors of clothing are classified by Fnet network, that can learn disjoint label combinations and mitigate the issue of excessive labels. Secondly, on the basis of the 4-Season Color System, the user’s face color model is trained by combined MobileNetV3_DTL, which ensures the model’s generalization and improves the training speed. Thirdly, user’s face shape and age are divided into different categories by an Inception network. Finally, according to the users’ face color, age, face shape and other information, personalized clothing is recommended in a coarse-to-fine manner. Experiments on five datasets demonstrate that the algorithm proposed in this paper achieves state-of-the-art results.
Online-Portal "MINTFabrik"
(2023)
Das browserbasierte Online-Portal "MINTFabrik" entstand im Zuge der Maßnahmen zur Minderung von Lernrückständen mit der Idee, eine Lücke zu schließen, die es oft bei großen Online-Brückenkursen gibt: Ein Mangel an Übungsaufgaben, die schnell zugänglich sind, einfach ausgesucht werden können und gut auf bestimmte Lehrveranstaltungen und deren Anforderungen zugeschnitten sind. Die Entwicklung erfolgte in einer Kooperation der Hochschule Reutlingen mit der Tübinger Softwarefirma "Let´s Make Sense GmbH". Das Portal verzichtet bewusst auf eine Lektionsstruktur und besteht ausschließlich aus einzelnen Lernbausteinen (Items), d.h. Video-Tutorials, VisuApps und Aufgaben, die über eine komfortable Suche mit Filtern erreichbar sind und direkt bearbeitet werden können. Ein besonderes Merkmal der MINTFabrik sind Mikrokurse, die von Lehrenden und Studierenden erstellt werden können. Das sind kleine Einheiten aus einigen wenigen Items, die beliebig miteinander kombinierbar sind.
Most Question-answering (QA) systems rely on training data to reach their optimal performance. However, acquiring training data for supervised systems is both time-consuming and resource-intensive. To address this, in this paper, we propose TFCSG, an unsupervised similar question retrieval approach that leverages pre-trained language models and multi-task learning. Firstly, topic keywords in question sentences are extracted sequentially based on a latent topic-filtering algorithm to construct unsupervised training corpus data. Then, the multi-task learning method is used to build the question retrieval model. There are three tasks designed. The first is a short sentence contrastive learning task. The second is the question sentence and its corresponding topic sequence similarity judgment task. The third is using question sentences to generate their corresponding topic sequence task. The three tasks are used to train the language model in parallel. Finally, similar questions are obtained by calculating the cosine similarity between sentence vectors. The comparison experiment on public question datasets that TFCSG outperforms the comparative unsupervised baseline method. And there is no need for manual marking, which greatly saves human resources.
Externe Ladeinfrastruktur kann rechtskonform aus dem Stromnetz einer öffentlichen Liegenschaft versorgt werden. Bisher war die Vorgabe, die Versorgung über einen eigenen (neuen) Netzanschlusspunkt zu realisieren. Die hier vorgestellte Lösung ist ökologisch, wirtschaftlich und technisch deutlich günstiger und dient als Muster für die weitere Erschließung landeseigenen Parkraums in ganz Baden-Württemberg. Ein virtuelles Kraftwerk ermöglicht den gemeinschaftsdienlichen Betrieb.
Projektbasiertes Lernen (PBL) ist eine ideale Methode, um Studierenden an Hochschulen praktische Projektmanagement-Kompetenzen zu vermitteln. Selbst anspruchsvolle Projekte werden hierdurch möglich. Jedoch ist die Balance zwischen den angestrebten Lernzielen und der praktischen Projektdurchführung in der Hochschulpraxis herausfordernd. Mit Hilfe des ‚PBL-Gold Standards‘ lassen sich PBL-Projekte zielgerichtet entwerfen und auf Effektivität hinsichtlich der Lernziele überprüfen. Am Beispiel des Projekts ‚IP Plane‘ der Hochschule Reutlingen, dem Bau eines Motorflugzeugs durch Studierende, wird die praktische Umsetzung eines PBL-Projektes demonstriert.
The presented research is dedicated to estimation of the correlation between the level of renewable energy sources and the costs of congestion management in electric networks in selected European countries. Data of six countries in North-West European area (Italy, Spain, Germany, France, Poland and Austria) were investigated. Factors considered included grid congestion costs including re-dispatching costs as well as countertrading costs, gross electricity generation, installed capacity of electric generating facilities, installed capacity of electric non-dispatchable renewable energy sources and total electricity consumption. Special attention is paid to the share of renewable energy sources. It is found that the grid congestion costs are not clearly affected by penetration of non-dispatchable renewables in all the analysed countries and therefore a clear mathematical correlation cannot no be extrapolated with the available data. The results of this research show in general a loose dependency of the grid congestion costs on the penetration of renewables and a strong dependency on the total electrical consumption of the country.
The efficient production and utilization of green hydrogen is vital to succeed in the global strive for a sustainable future. To provide the necessary amount of green hydrogen a high number of electrolyzers will be connected as decentralized power consumers to the grid. A large amount of decentralized renewable power sources will provide the energy. In such a system a control method is necessary to dispatch the available power most efficiently. In particular, the shutdown of renewable energy sources due to temporary overproduction must be avoided. This paper presents a decentralized tertiary control algorithm that provides a new decentralized control approach, thus creating a flexible, robust and easily scalable system. The operation of each grid participant within this grid connected microgrid is optimized for maximum financial profit, while minimizing the exchange of power with the mains grid and reducing the shutdown of renewable power sources.
The increase in distributed energy generation, such as photovoltaic systems (PV) or combined heat and power plants (CHP), poses new challenges to almost every distribution network operator (DNO). In the low-voltage (LV) grids, where installed PV capacity approaches the magnitude of household load, reverse power flow occurs at the secondary substa-tions. High PV penetration leads to voltage rise, flicker and loading problems. These problems have been addressed by the application of various techniques amongst which is the deployment of step voltage regulators (SVR). SVR can solve the voltage problem, but do not prevent or reduce reverse power flows. Therefore, the application of SVR in low voltage grids can result in significant power losses upstream. In this paper we present part of a research project investi-gating the application of remote-controlled cable cabinets (CC) with metering units in a low-voltage network as a possible alternative for SVR. A new generation of custom-made remote-control cable cabinets has been deployed and dynamic network reconfigurations (NR) have been realized with the following objectives: (i) reduction of reverse power flow through the secondary substation to the upstream network and therefore a reduction of upstream losses, (ii) reduction of the voltage rise caused by distributed energy resources and (iii) load balancing in the low-voltage grid. Secondary objec-tives are to improve the DNO's insight into the state of the network and to provide further information on future smart grid integration.
Werkzeugmaschinen sind im Bereich des Maschinen- und Anlagenbau die größte Branche, mit denen auch in Unternehmen anderer Bereiche (z. B. Automobilbau, Aerospace) wesentliche Teile der Bruttowertschöpfung stattfinden. (Destatis, 2022) Das dynamische Verhalten von Werkzeugmaschinen beeinflusst in entscheidendem Maße die Produktivität der Produktionsanlage und die Qualität der darauf erzeugten Werkstücke. Sowohl fremderregte Schwingungen (z. B. Unwucht, Pulsation, periodisch schwankende Prozesskräfte) als auch selbsterregte Schwingungen (z. B. Rattern) führen zu schlechter Qualität der gefertigten Bauteile. Das dynamische Verhalten vonWerkzeugmaschinen wird durch die Masse, Dämpfung und Steifigkeit der einzelnen Komponenten (z. B. Maschinenbett, Ständer, Schlitten) als auch der im Kraftfluss liegenden Fügestellen (z. B. Führungen, Antriebe) beeinflusst. In diesem Beitrag werden die Auswirkungen von konstruktiven Modifikationen der Dämpfung in Gestellbauteilen bezüglich des dynamischen Verhaltens an der Zerspanstelle näher beleuchtet.
Offshore-Windenergie wird global zunehmend intensiver ausgebaut. Auch die deutsche Bundesregierung hat die Ausbauziele auf 30 GW installierte Leistung bis 2030 erhöht, von derzeit ca. 8 GW. Wie kann die deutsche Offshore-Windenergiebranche dies erreichen und was bedeutet das für ihre Zulieferer und Dienstleister? Vier Szenarien beschreiben mögliche Zukünfte. Technischer Fortschritt entlang der gesamten Wertschöpfungskette, Lieferkettensicherheit, Regulatorik sowie Fachkräfteverfügbarkeit sind die kritischen Erfolgsfaktoren.
Silicon neurons represent different levels of biological details and accuracies as a trade-off between complexity and power consumption. With respect to this trade-off and high similarity to neuron behaviour models, relaxation-type oscillator circuits often yield a good compromise to emulate neurons. In this chapter, two exemplified relaxation-type silicon neurons are presented that emulate neural behaviour with energy consumption under the scale of nJ/spike. The first proposed fully CMOS relaxation SiN is based on mathematical Izhikevich model and can mimic a broad range of physiologically observable spike patterns. The results of kinds of biologically plausible output patterns and coupling process of two SiNs are presented in 0.35 μm CMOS technology. The second type is a novel ultra-low-frequency hybrid CMOS-memristive SiN based on relaxation oscillators and analog memristive devices. The hybrid SiN directly emulates neuron behaviour in the range of physiological spiking frequencies (less than 100 Hz). The relaxation oscillator is implemented and fabricated in 0.13 μm CMOS technology. An autonomous neuronal synchronization process is demonstrated with two relaxation oscillators coupled by an analog memristive device in the measurement to emulate the synchronous behaviour between spiking neurons.
Distributed Ledger Technologies for the energy sector: facilitating interoperability analysis
(2023)
The use of distributed data storage and management structures, such as Distributed Ledger Technologies (DLT), in the energy sector has gained great interest in recent times. This opens up new possibilities in e.g. microgrid management, aggregation of distributed resources, peer-to- peer trading, integration of electromobility or proof-of-origin strategies. However, in order to benefit from those new possibilities, new challenges have to be overcome. This work focuses on one of these challenges, which is the need to ensure interoperability when integrating DLT-enabled devices in energy use cases. Firstly, the use of DLTs in the energy sector will be analyzed and the main use cases will be presented. Then, a classification of DLT-Energy use cases will be proposed. Secondly, the need for a common reference architecture framework to analyze those use cases with a focus on interoperability will be discussed and the current activities in research and standardization in this field will be presented. Finally, a new common reference architecture framework based on current activities in standardization will be presented.
As fuel prices climb and the global automotive sector migrates to more sustainable vehicle technologies, the future of South Africa’s minibus taxis is in flux. The authors’ previous research has found that battery electric technology struggles to meet all the mobility requirements of minibus taxis. They investigate the technical feasibility of powering taxis with hydrogen fuel cells instead. The following results are projected using a custom-built simulator, and tracking data of taxis based in Stellenbosch, South Africa. Each taxi requires around 12 kg of hydrogen gas per day to travel an average distance of 360 km. 465 kWh of electricity, or 860 m2 of solar panels, would electrolyse the required green hydrogen. An economic analysis was conducted on the capital and operational expenses of a system of ten hydrogen taxis and an electrolysis plant. Such a pilot project requires a minimum investment of € 3.8 million (R 75 million), for a 20 year period. Although such a small scale roll-out is technically feasible and would meet taxis’ performance requirements, the investment cost is too high, making it financially unfeasible. They conclude that a large scale solution would need to be investigated to improve financial feasibility; however, South Africa’s limited electrical generation capacity poses a threat to its technical feasibility. The simulator is uploaded at: https://gitlab.com/eputs/ev-fleet-sim-fcv-model.
Modern wide bandgap power devices promise higher power conversion performance if the device can be operated reliably. As switching speed increases, the effects of parasitic ringing become more prominent, causing potentially damaging overvoltages during device turn-off. Estimating the expected additional voltage caused by such ringing enables more reliable designs. In this paper, we present an analytical expression to calculate the expected overvoltage caused by parasitic ringing based on parasitic element values and operating point parameters. Simulations and measurements confirm that the expression can be used to find the smallest rise time of the switches’ drain-source voltage for minimum overvoltage. The given expression also allows the prediction of the trade off overvoltage amplitude in case of faster required rise times.
We present the results of an extensive characterization of the performance and stability of a third-order continuous-time delta-sigma modulator with active coefficient error compensation. Using our previously published coefficient tuning technique, process variation induced R-C time-constant (TC) errors in the forward signal path can be compensated indirectly using continuously tunable DACs in the feedback path. To validate our technique experimentally with a range of real TC variations, we designed a modulator with discretely configurable integration capacitor arrays in a 0.35-μm CMOS process. We configured the capacitors of the fabricated device for a range of total TC variations from -28.4 % to +19.3 % and measured the signal-to-noise ratio (SNR) as a function of the input amplitude before and after compensating the variations electrically using the feedback DACs. The results show that our tuning technique is capable of restoring the desired nominal modulator performance over the entire parameter variation range, including the system’s nominal maximum stable amplitude (MSA).
In the course of a more intensive energy generation from regenerative sources, an increased number of energy storages is required. In addition to the widespread means of storing electric energy, storing energy thermally can contribute significantly. However, limited research exists on the behaviour of thermal energy storages (TES) in practical operation. While the physical processes are well known, it is nevertheless often not possible to adequately evaluate its performance with respect to the quality of thermal stratification inside the tank, which is crucial for the thermodynamic effectiveness of the TES. The behaviour of a TES is experimentally investigated in cyclic charging and discharging operation in interaction with a cogeneration (CHP) unit at a test rig in the lab. From the measurements the quality of thermal stratification is evaluated under varying conditions using different metrics such as normalised stratification factor, modified MIX number, exergy number and exergy efficiency, which extends the state of art for CHP applications. The results show that the positioning of the temperature sensors for turning the CHP unit on and off has a significant influence on both the effective capacity of a TES and the quality of thermal stratification inside the tank. It is also revealed that the positioning of at least one of these sensors outside the storage tank, i.e. in the return line to the CHP unit, prevents deterioration of thermal stratification, thereby enhancing thermodynamic effectiveness. Furthermore, the effects of thermal load and thermal load profile on effective capacity and thermal stratification are discussed, even though these are much smaller compared to the effect of positioning the temperature sensors.
In this paper, it aims to model wind speed time series at multiple sites. The five-parameter Johnson distribution is deployed to relate the wind speed at each site to a Gaussian time series, and the resultant m-dimensional Gaussian stochastic vector process Z(t) is employed to model the temporal-spatial correlation of wind speeds at m different sites. In general, it is computationally tedious to obtain the autocorrelation functions (ACFs) and cross-correlation functions (CCFs) of Z(t), which are different to those of wind speed times series. In order to circumvent this correlation distortion problem, the rank ACF and rank CCF are introduced to characterize the temporal-spatial correlation of wind speeds, whereby the ACFs and CCFs of Z(t) can be analytically obtained. Then, Fourier transformation is implemented to establish the cross-spectral density matrix of Z(t), and an analytical approach is proposed to generate samples of wind speeds at m different sites. Finally, simulation experiments are performed to check the proposed methods, and the results verify that the five-parameter Johnson distribution can accurately match distribution functions of wind speeds, and the spectral representation method can well reproduce the temporal-spatial correlation of wind speeds.
Verteilnetzbetreiber müssen verschiedene Maßnahmen ergreifen, um den Herausforderungen der zunehmenden Installation dezentraler Erzeugungsanlagen zu begegnen. Die meisten dieser Maßnahmen führen zwar zur Einhaltung der Spannungsgrenzwerte, sie läsen jedoch nicht das Problem der Rückspeisung in die überlagerte Netzebene und die damit verbundenen Leistungsverluste. Im Projekt „Demo-rONT-Alternative“ wurde ein Prototyp für einen fernsteuerbaren Kabelverteiler entwickelt, um die Trennstellenverschiebung automatisiert durchführen zu können.
Simulation eines dezentralen Regelungssystems zur netzdienlichen Erzeugung von grünem Wasserstoff
(2023)
Wasserstoff wird einen bedeutenden Beitrag zum Wandel von Industrie und Gesellschaft in eine klimaneutrale Zukunft leisten. Der Aufbau und die ökologisch und ökonomisch sinnvolle Nutzung einer Wasserstoffinfrastruktur sind hierbei die zentralen Herausforderungen. Ein notwendiger Baustein ist die effiziente Bereitstellung von grünem Strom und dem daraus produzierten grünen Wasserstoff. Der vorliegende Beitrag stellt ein dezentrales Regel- und Kommunikationssystem vor, mit dem Angebot und Nachfrage von grünem Strom und Wasserstoff in einem System aus dezentralen Akteuren in Einklang gebracht werden. In einer hierzu entwickelten Simulationsumgebung wird die Funktion und der Nutzen dieses dezentralen Ansatzes verdeutlicht.
In recent years, 3D facial reconstructions from single images have garnered significant interest. Most of the approaches are based on 3D Morphable Model (3DMM) fitting to reconstruct the 3D face shape. Concurrently, the adoption of Generative Adversarial Networks (GAN) has been gaining momentum to improve the texture of reconstructed faces. In this paper, we propose a fundamentally different approach to reconstructing the 3D head shape from a single image by harnessing the power of GAN. Our method predicts three maps of normal vectors of the head’s frontal, left, and right poses. We are thus presenting a model-free method that does not require any prior knowledge of the object’s geometry to be reconstructed.
The key advantage of our proposed approach is the substantial improvement in reconstruction quality compared to existing methods, particularly in the case of facial regions that are self-occluded in the input image. Our method is not limited to 3d face reconstruction. It is generic and applicable to multiple kinds of 3D objects. To illustrate the versatility of our method, we demonstrate its efficacy in reconstructing the entire human body.
By delivering a model-free method capable of generating high-quality 3D reconstructions, this paper not only advances the field of 3D facial reconstruction but also provides a foundation for future research and applications spanning multiple object types. The implications of this work have the potential to extend far beyond facial reconstruction, paving the way for innovative solutions and discoveries in various domains.
The aim of this work is the development of artificial intelligence (AI) application to support the recruiting process that elevates the domain of human resource management by advancing its capabilities and effectiveness. This affects recruiting processes and includes solutions for active sourcing, i.e. active recruitment, pre-sorting, evaluating structured video interviews and discovering internal training potential. This work highlights four novel approaches to ethical machine learning. The first is precise machine learning for ethically relevant properties in image recognition, which focuses on accurately detecting and analysing these properties. The second is the detection of bias in training data, allowing for the identification and removal of distortions that could skew results. The third is minimising bias, which involves actively working to reduce bias in machine learning models. Finally, an unsupervised architecture is introduced that can learn fair results even without ground truth data. Together, these approaches represent important steps forward in creating ethical and unbiased machine learning systems.
Der Erfolg der Energiewende in Deutschland setzt eine zunehmende Anzahl an dezentralen elektrischen Erzeugungsanlagen (EZA) voraus. Diese dezentralen EZA, wie Photovoltaikanlagen oder Blockheizkraftwerke, bringen für Verteilnetzbetreiber große Herausforderungen mit sich. Im Rahmen des geförderten Forschungsprojekts „Demonstrator Automatisierte Kabelverteil (KV) als Alternative zum regelbaren Ortsnetztransformator (DEMO rONT-Alternative)“ wurde ein neuer Ansatz für die Lösung der bestehenden Problematik erforscht. Dieser besteht in der aktiven Änderung der Topologie der Netzgebiete je nach elektrischer Last und PV-Einspeisung (Trennstellenverlagerung).
Analog integrated circuit sizing is notoriously difficult to automate due to its complexity and scale; thus, it continues to heavily rely on human expert knowledge. This work presents a machine learning-based design automation methodology comprising pre-defined building blocks such as current mirrors or differential pairs and pre-computed look-up tables for electrical characteristics of primitive devices. Modeling the behavior of primitive devices around the operating point with neural networks combines the speed of equation-based methods with the accuracy of simulation-based approaches and, thereby, brings quality of life improvements for analog circuit designers using the gm/Id method. Extending this procedural automation method for human design experts, we present a fully autonomous sizing approach. Related work shows that the convergence properties of conventional optimization approaches improve significantly when acting in the electrical domain instead of the geometrical domain. We, therefore, formulate the circuit sizing task as a sequential decision-making problem in the alternative electrical design space. Our automation approach is based entirely on reinforcement learning, whereby abstract agents learn efficient design space navigation through interaction and without expert guidance. These agents’ learning behavior and performance are evaluated on circuits of varying complexity and different technologies, showing both the feasibility and portability of the work presented here.
In kleinen und mittleren Unternehmen (KMU) werden Energieeffizienz-Potentiale in geringerem Maße ausgeschöpft als in Großunternehmen. Zugleich bilden KMU den überwältigenden Anteil deutscher Unternehmen. Die Steigerung der Energieeffizienz verspricht einen substanziellen Beitrag zur Umweltentlastung. Energiemanagement wird gemeinhin als wesentlicher Treiber von Energieeffizienz Maßnahmen in Deutschland betrachtet. Im Kontext von Unternehmen wird Energiemanagement üblicherweise synonym mit dem Energiemanagement-standard ISO 50001 betrachtet. Problematisch zeigt sich diese Perspektive mit Blick auf KMU, für die eine aufwändige Implementierung eines solchen System in den überwiegenden Fällen nicht infrage kommt. Vor diesem Hintergrund darf sich eine Förderung von Energiemanagement in KMU jedoch nicht entmutigen lassen. Im Rahmen des Projekts wurde ein bedarfsgerechtes und an den Bedürfnissen von KMU orientiertes Konzept von Energiemanagement für KMU entwickelt. Die Ausarbeitung erfolgte in einem sogenannten Reallabor, das gleichsam als Partner-Netzwerk die Ergebnisse des Projekts kooperativ produziert hat. Das Reallabor setzte sich zusammen aus den koordinierenden Partnern aus der Wissenschaft (REZ Hochschule Reutlingen, Institut für Energieeffizienz in der Produktion EEP), sechs KMU aus der Region Reutlingen und einem Sounding-Board bestehend aus vier weiteren Partnern.
Im Rahmen des Reallabors wurden jene Bausteine definiert, die Energiemanagement für KMU ausmachen. Sensibilität und Basiswissen ist für KMU unumgänglich in den Bereichen: 1. Motivation für Energieeffizienz & Klimaneutralität, 2. Organisation-Entscheiden-Verhalten, 3. Energie-Daten Management und 4. Energieeffizienz-Maßnahmen (Querschnitt-Technologien). Den vier festgelegten Bausteinen wurden unterschiedliche Inhalte Schwerpunkte zugeordnet. Die Bausteine und Schwerpunkte wurden jeweils begründet und mit konkreten Lehr-, Lern- und Sensibilisierungszielen benannt. Parallel zur Festlegung der Bausteine und Schwerpunkte von Energiemanagement wurden Lehr-, Lern- und Sensibilisierungs-Materialien ausgearbeitet, bestehend aus Leitfäden und Checklisten. Die Ausarbeitung wurde jeweils mit Themen-Workshops parallel begleitet. Die entwickelten Lehr-, Lern- und Sensibilisierungs-Materialien wurden in und mit den Partnerunternehmen getestet. Alle Materialien stehen mit Abschluss des Projekts für die Verbreitung zur freien Verfügung.
Der zukünftige Beitrag zur Umweltentlastung hängt von der breiten Umsetzung außerhalb des Projektkontexts ab. Die Sensibilisierung und Qualifizierung für Energiemanagement schafft eine nachhaltige Energiesparkultur in KMU. Eine breite Anwendung des entwickelten Konzepts im Rahmen von moderierten Unternehmens-Netzwerken fördert die nachhaltige Befähigung von KMU Energieeffizienz zu planen und umzusetzen.
Dieses Buch vermittelt die grundlegenden Kenntnisse für den Layoutentwurf digitaler und analoger Schaltungen. Neben den ingenieurwissenschaftlichen Grundlagen werden auch Werkzeugaspekte behandelt. Das Werk befähigt Ingenieure, einen Schaltplan oder eine Netzliste in eine Layoutdarstellung zur Fertigung eines integrierten Schaltkreises (IC) oder einer Leiterplatte umzusetzen. Nach einer einleitenden Übersicht zu Fertigungstechnologien, Besonderheiten der Mikroelektronik und den Aufgaben des Layoutentwurfs behandelt Kap. 2 zunächst die technologischen Grundlagen der IC-Fertigung. Darauf aufbauend werden nachfolgend alle Aspekte des Layoutentwurfs vertieft: Schnittstellen, Entwurfsregeln und Bibliotheken (Kap. 3), Entwurfsstile, -modelle und -flüsse (Kap. 4), Entwurfsschritte (Kap. 5), Besonderheiten des analogen IC-Entwurfs (Kap. 6) und schließlich Zuverlässigkeitsmaßnahmen (Kap. 7). Das Buch eignet sich als Lehrbuch in den Ingenieurwissenschaften und als Nachschlagewerk für Schaltungs- und Layoutentwickler in der Industrie.
This article proposes several modified quasi Z-source dc/dc boost converters. These can achieve soft-switching by using a clamp-switch network comprised of an active switch and a diode in parallel with a capacitor connected across one of the inductors of the Z-source network. In this way, ringing at the transistor switching node is mitigated, and the voltage at the turn-on of the transistor is reduced. Even a zero voltage switching (ZVS) of the main transistor is possible if the capacitor in the clamp-switch network is adequately chosen. The proposed circuit structure and operating mode are described and validated through simulations and measurements on a low-power prototype.
AI-based prediction and recommender systems are widely used in various industry sectors. However, general acceptance of AI-enabled systems is still widely uninvestigated. Therefore, firstly we conducted a survey with 559 respondents. Findings suggested that AI-enabled systems should be fair, transparent, consider personality traits and perform tasks efficiently. Secondly, we developed a system for the Facial Beauty Prediction (FBP) benchmark that automatically evaluates facial attractiveness. As our previous experiments have proven, these results are usually highly correlated with human ratings. Consequently they also reflect human bias in annotations. An upcoming challenge for scientists is to provide training data and AI algorithms that can withstand distorted information. In this work, we introduce AntiDiscriminationNet (ADN), a superior attractiveness prediction network. We propose a new method to generate an unbiased convolutional neural network (CNN) to improve the fairn ess of machine learning in facial dataset. To train unbiased networks we generate synthetic images and weight training data for anti-discrimination assessments towards different ethnicities. Additionally, we introduce an approach with entropy penalty terms to reduce the bias of our CNN. Our research provides insights in how to train and build fair machine learning models for facial image analysis by minimising implicit biases. Our AntiDiscriminationNet finally outperforms all competitors in the FBP benchmark by achieving a Pearson correlation coefficient of PCC = 0.9601.
Repräsentativ zur Erkenntnis
(2022)
In einer immer komplexeren Welt wird es zunehmend schwierig, den Blick aufs große Ganze zu bewahren. Trainingsprofis können Führungskräfte und Teams dabei unterstützen -etwas mit einer speziellen Aufstellungstechnik, der prototypischen Strukturaufstellung. Kerstin Reich erklärt anhand eines Praxisbeispiels, wie sie funktioniert.
Für das Gelingen der Wärmewende und des von Klimaschutzminister Robert Habeck eingeforderten Wärmepumpenhochlaufs gilt es mannigfaltige Herausforderungen zu lösen. Welche Chancen in diesem Zusammenhang eine Kombination von Wärmepumpe und Kraft-Wärme-Kopplung (KWK) eröffnet, wird im folgenden Beitrag erörtert.
Der ›AM Field Guide‹ gibt einen ersten strukturierten Überblick in die komplexe und vielschichtige Welt der additiven Fertigungsverfahren. Getrennt nach den Materialien Polymere, Metalle und weitere Materialien werden die gängigsten jeweils auf dem Markt angebotenen AM-Verfahren schematisch dargestellt und der Verfahrenskern in Kurzform beschrieben. Neben den hier dargestellten Hauptverfahren gibt es viele Derivate und Sonderverfahren, die ebenfalls ein gesetzt werden jedoch nicht explizit gezeigt sind. Zu beachten ist, dass in dem jungen Bereich der additiven Fertigung viele Hersteller ihren AM-Anwendungen eigene Namen geben, so dass eine allgemeingültige umfassende Klassifizierung nur ansatzweise erreichbar ist.
Verification of an active time constant tuning technique for continuous-time delta-sigma modulators
(2022)
In this work we present a technique to compensate the effects of R-C / g m -C time-constant (TC) errors due to process variation in continuous-time delta-sigma modulators. Local TC error compensation factors are shifted around in the modulator loop to positions where they can be implemented efficiently with finely tunable circuit structures, such as current-steering digital-to-analog converters (DAC). We apply our technique to a third-order, single-bit, low-pass continuous-time delta-sigma modulator in cascaded integrator feedback structure, implemented in a 0.35-μm CMOS process. A tuning scheme for the reference currents of the feedback DACs is derived as a function of the individual TC errors and verified by circuit simulations. We confirm the tuning technique experimentally on the fabricated circuit over a TC parameter variation range of ±20%. Stable modulator operation is achieved for all parameter sets. The measured performances satisfy the expectations from our theoretical calculations and circuit-level simulations.
A single-phase fixed-frequency operated power factor correction circuit with reduced switching losses is proposed. The circuit uses the combination of a boost converter with an added clamp-switch, a pulse wave shaping circuit, and a standard control IC to discharge the transistor's output capacitance prior to its turn-on. In this way, a very low-complexity control circuit implementation to reduce switching losses or even achieve complete zero-voltage switching without additional sensors is possible. Moreover, this operation method is achieved at a constant switching frequency, possibly simplifying the design of the EMI filter and the converter's inductor. Experimental test results for a 100 W prototype converter are presented to validate the feasibility of the proposed operating method and corresponding circuit structure.
On the influence of ground and substrate on the radiation characteristics of planar spiral antennas
(2022)
The unidirectional radiation of spiral antennas mounted on a substrate requires the presence of a ground plane. In this work, we successively illustrate the impact of dielectric material and ground plane on the key metrics of a planar equiangular spiral antenna (PESA). For this purpose, a PESA mounted on several substrates with different dielectric properties and thicknesses is modeled and simulated. We introduce the tertiary current flowing on spiral arms when backed by a ground plane.
This paper presents a compact four-arm spiral antenna, which may be used in direction-finding applications but also mobile communication systems. The antenna is fed sequentially at its outside-ends using a sequential phase network embedded in grounded multilayer dielectric media. Sequential rotation is applied to generate the axial mode M1 but also the conical mode M2 in the same frequency band. The antenna exhibits good radiation characteristics in the frequency band of interest.
Class Phi2 amplifier using GaN HEMTs at 13.56MHz with tuned transformer for wireless power transfer
(2022)
This paper discusses a design procedure of a wireless power transfer system at a RF switching frequency of 13.56MHz. The wireless power transfer amplifier uses GaN HEMTs in aClass phi2 topology and is designed in order to achieve high efficiency and high power density. A design method for the load over a certain bandwidth is presented for a transformer with its tuning network.
Switched reluctance motors are particularly attractive due to their simple structure. The control of this machine type requires the instants, to switch the currents in the motor phases in an appropriate sequence. These switching instants are determined either based on a position sensor, or on signals generated by a sensorless method. A very simple sensorless method uses the switching frequency of the hysteresis controllers used for phase current control. This paper first presents an automatic commissioning method for this sensorless method and second a startup procedure, thus enhancing this approach towards an application in industry.
The majority of people in sub-Saharan Africa (SSA) rely on so-called “paratransit” for their mobility needs. The term refers to a large informal transport sector that runs independent of government, of which 83% comprises minibus taxis (MBT). MBT technology is often old and contribute significantly to climate change with their high carbon dioxide (CO2) emissions. Issues related to sustainability and climate change are becoming more important world-wide and hardly any attention is given to MBTs. Converting the MBTs from internal combustion engines (ICEs) to electric motors could be a possible solution. The existing power grid in SSA is largely based on fossil power plants and is unstable. This can be seen by frequent local power blackouts. To avoid further strain on the existing power grid, it would therefore make sense to charge the electric minibus taxis (eMBTs) through a grid consisting of renewable energies. A mobility map is created via simulations with collected data points of the MBTs. By using this mobility map, the energy demand of the eMBTs is calculated. Furthermore, a region-specific photovoltaic (PV) and wind simulation can be realised based on existing weather data, and a tool to size the supply system to charge the eMBTs is developed after all data has been collected. With the help of this work, it can be determined to what extent renewable energies such as PV and wind power can be used to support the transition from ICEs to electric engines in the MBT sector.
Perforations of the tympanic membrane (TM) can occur as a result of injury or inflammation of the middle ear. These perforations can lead to conductive hearing loss (HL), where in some cases the magnitude of HL exceeds that attributable to the observed TM perforation alone. We aim with this study to better understand the effects of location and size of TM perforations on the sound transmitting properties of the middle ear.
The middle ear transfer function (METF) of six human temporal bones (TB; freshly frozen specimen of body donors) were compared before and after perforation of the TM at different locations (anterior or posterior lower quadrant) and of different sizes (1mm, ¼ of the TM, ½ of the TM, and full ablation). The
METF were correlated with a Finite Element (FE) model of the middle ear, in which similar alterations were simulated.
The measured and simulated FE model METFs exhibited frequency and perforation size dependent amplitude losses at all locations and severities. In direct comparison, posterior TM perforations affected the transmission properties to a larger degree than perforations of the anterior quadrant. This could possibly be caused by an asymmetry of the TM, where the malleus-incus complex rotates and results in larger deflections in the posterior TM half than in the anterior TM half. The FE model of the TM with a sealed cavity suggest that small perforations result in a decrease of TM rigidity and thus to an increase in oscillation amplitude of the TM, mostly above 1 kHz.
The location and size of TM perforations influence the METF in a reproducible way. Correlating our data with the FE model could help to better understand the pathologic mechanisms of middle-ear diseases. If small TM perforations with uncharacteristically significant HL are observed in daily clinical practice, additional middle ear pathologies should be considered. Further investigations on the loss of TM pretension due to perforations may be informative.
For optimization of production processes and product quality, often knowledge of the factors influencing the process outcome is compulsory. Thus, process analytical technology (PAT) that allows deeper insight into the process and results in a mathematical description of the process behavior as a simple function based on the most important process factors can help to achieve higher production efficiency and quality. The present study aims at characterizing a well-known industrial process, the transesterification reaction of rapeseed oil with methanol to produce fatty acid methyl esters (FAME) for usage as biodiesel in a continuous micro reactor set-up. To this end, a design of experiment approach is applied, where the effects of two process factors, the molar ratio and the total flow rate of the reactants, are investigated. The optimized process target response is the FAME mass fraction in the purified nonpolar phase of the product as a measure of reaction yield. The quantification is performed using attenuated total reflection infrared spectroscopy in combination with partial least squares regression. The data retrieved during the conduction of the DoE experimental plan were used for statistical analysis. A non-linear model indicating a synergistic interaction between the studied factors describes the reactor behavior with a high coefficient of determination (R²) of 0.9608. Thus, we applied a PAT approach to generate further insight into this established industrial process.
The current paper proposes a design method for an active damping approach for LC output filters in a power stage for motor control with continuous output voltage. The power stage uses GaN-HEMTs and operates at switching frequencies in a range between 500 kHz and 1MHz. The active damping of the output filter is achieved here by a feedback of the filter inductor current using a high-pass structure. The paper discusses the impact of this feedback on the system behavior and proposes a design method.
In order to evaluate the performance of different stapes prosthesis types, a coupled finite element (FE) model of human ear was developed. First, the middle-ear FE model was developed and validated using the middle-ear transfer function measurements available in literature including pathological cases. Then, the inner-ear FE model was developed and validated using tonotopy, impedance, and level of cochlea amplification curves from literature. Both models are based on pre-existing research with some improvements and were combined into one coupled FE model. The stapes in the coupled FE ear model was replaced with a model of a stapes prosthesis to create a reconstructed ear model that can be used to estimate how different types of protheses perform relative to each other as well as to the natural ear. This will help in designing of new innovative types of stapes prostheses or any other type of middle-ear prostheses as well as to improve the ones that are already available on the market.
Simulation models of the middle ear have rarely been used for diagnostic purposes due to their limited predictive ability with respect to pathologies. One big challenge is the large uncertainty and ambiguity in the choice of material parameters of the model.
Typically, the model parameters are determined by fitting simulation results to validation measurements. In a previous study, it was shown that fitting the model parameters of a finite-element model using the middle-ear transfer function and various other measurable output variables from normal ears alone is not sufficient to obtain a good predictive ability of the model on pathological middle-ear conditions. However, the inclusion of validation measurements on one pathological case resulted in a very good predictive ability also for other pathological cases. Although the found parameter set was plausible in all aspects, it was not yet possible to draw conclusions about the uniqueness and the accuracy or the uncertainty of the parameter set.
To answer these questions, statistical solution approaches are used in this study. Using the Monte Carlo method, a large number of plausible model data sets are generated that correctly represent the normal and pathological middle-ear characteristics in terms of various output variables like e.g., impedance, reflectance, umbo, and stapes transfer function. Subsequent principal component analyses (PCA) allow to draw conclusions about correlations, quantitative limits and statistical density of parameter values.
Furthermore, applying inverse PCA yields numerous plausible parameterizations of the middle-ear model, which can be used for data augmentation and training of a neural network which is capable of distinguishing between a normal middle ear and pathologies like otosclerosis, malleus fixation, and disarticulation based on objectively measured quantities like impedance, reflectance, and umbo velocity.
There is still a great reliance on human expert knowledge during the analog integrated circuit sizing design phase due to its complexity and scale, with the result that there is a very low level of automation associated with it. Current research shows that reinforcement learning is a promising approach for addressing this issue. Similarly, it has been shown that the convergence of conventional optimization approaches can be improved by transforming the design space from the geometrical domain into the electrical domain. Here, this design space transformation is employed as an alternative action space for deep reinforcement learning agents. The presented approach is based entirely on reinforcement learning, whereby agents are trained in the craft of analog circuit sizing without explicit expert guidance. After training and evaluating agents on circuits of varying complexity, their behavior when confronted with a different technology, is examined, showing the applicability, feasibility as well as transferability of this approach.
The hearing contact lens® (HCL) is a new type of hearing aid devices. One of its main components is a piezo-electric actuator. In order to evaluate and maximize the HCL’s performance, a model of the HCL coupled to the middle ear was developed using finite element approach. The model was validated step by step starting with the HCL only. To validate the HCL model, vibrational measurements on the HCL were performed using a Laser-Doppler-Vibrometer (LDV). Then, a silicone cap was placed onto the HCL to provide an interface between the HCL and the tympanic membrane of the middle-ear model and additional LDV measurements on temporal bones were performed to validate the coupled model. The coupled model was used to evaluate the equivalent sound pressure of the HCL. Moreover, a deeper insight was gained into the contact between the HCL and tympanic membrane and its effects on the HCL performance. The model can be used to investigate the sensitivity of geometrical and material parameters with respect to performance measures of the HCL and evaluate the feedback behavior.
A MATLAB toolbox was developed both for teachers performing quick experimental demonstrations during lectures and for students practicing measurement and frequency analysis procedures. The conceptual purpose was to support fundamental acoustics courses with contents defined by the DEGA recommendation 102. All implemented functions and parameters are visible at once and quickly adjustable by a GUI without submenus. A user manual is provided with explanations of how to get started and how all implemented functions can be applied. The toolbox probably still contains bugs. All users are welcome to inform the author about their experiences and proposals for improvement. In future it is planned to convert "Acoustics" to the MATLAB app designer format as Mathworks announced GUIDE to be replaced. Useful extensions would be additional tabs containing animations of sound propagation phenomena or sound fields caused by different sources.
Eine Organisation hin zur Klimaneutralität zu transformieren, ist nicht nur Neuland für praktisch jeden, der loslegt: Es geht los mit dem „Wollen“, also dem Ziel, dann wird der Weg skizziert, und schließlich muss es auch noch jemand umsetzen. Aus ihren Projekten der Begleitung von Organisationen auf dem Weg zur Klimaneutralität erscheint den Autoren folgende Erfahrung des Geschäftsführers Philipp Tiefenbach der Dorfbäckerei Tiefenbach, St. Johann-Würtingen, besonders treffend: „Machen ist wie Wollen, nur krasser.“ Für eine Kommune gerät dieser Prozess zu einem „wicked problem“. Sechs Lösungswege für Kommunen erscheinen attraktiv.
Modern production systems are characterized by the increasingly use of CPS and IoT networks. However, processing the available information for adaptation and reconfiguration often occurs in relatively large time cycles. It thus does not take advantage of the optimization potential available in the short term. In this paper, a concept is presented that, considering the process information of the individual heterogeneous system elements, detects optimization potentials and performs or proposes adaptation or reconfiguration. The concept is evaluated utilizing a case study in a learning factory. The resulting system thus enables better exploitation of the potentials of the CPPS.
In this work, a brushless, harmonic-excited wound-rotor synchronous machine without any auxiliary windings which can provide full torque at startup is investigated experimentally. The excitation power is transferred inductively by superimposing an additional harmonic field of different pole-pair number on top of the airgap field. This is achieved by feeding the parallel paths of the stator and rotor winding separately. A prototype for the harmonic-excited synchronous machine has been constructed and experimental results are presented to verify the concept. The main loss contributors are identified and the importance of considering core losses under harmonic excitation is discussed. A general analytical model for harmonic excited synchronous machines is proposed which enables a quick estimation of the iron core flux densities and the core losses generated by the additional harmonic currents.
In this work, a comparison between different brushless harmonic-excited wound-rotor synchronous machines is performed. The general idea of all topologies is the elimination of the slip rings and auxiliary windings by using the already existing stator and rotor winding for field excitation. This is achieved by injecting a harmonic airgap field with the help of power electronics. This harmonic field does not interact with the fundamental field, it just transfers the excitation power across the airgap. Alternative methods with varying number of phases, different pole-pair combinations, and winding layouts are covered and compared with a detailed Finite-Element-parameterized model. Parasitic effects due to saturation and coupling between the harmonic and main windings are considered.
Energy Communities explores core potential systemic benefits and costs in engaging consumers into communities, particularly relating to energy transition. The book evaluates the conditions under which energy communities might be regarded as customer-centered, market-driven and welfare-enhancing. The book also reviews the issue of prevalence and sustainability of energy communities and whether these features are likely to change as opportunities for distributed energy grow. Sections cover the identification of welfare considerations for citizens and for society on a local and national level, and from social, economic and ecological perspectives, while also considering different community designs and evolving business models.
Ausbildung in der Akustik
(2022)
Die Wissenschaft der Akustik mit ihrer Vielfallt und Interdisziplinarität bietet hervorragende Möglichkeiten an beruflichen Betätigungsfeldern und hat viele von uns in ihren Bann gezogen. Ausbildung in der Akustik bedeutet mehr als Studierenden nur Wissen und Fähigkeiten zu vermitteln. Eigentlich ist nach dem Studium auch der Lernprozess nicht abgeschlossen, sondern wie viele Akustiker:innen meinen, fängt dieser erst dann richtig an. Um eine sehr gute Ausbildung zu gestalten, bedarf es neben Vorbildern an Personen auch Lehrformate, Methoden und Tools. Die folgenden sechs Kurzbeiträge sind Beispiele gelungener Maßnahmen in der Ausbildung der Akustik und sollen anregen, die Qualität in der Lehre stetig zu verbessern.
This paper presents a toolbox in Matlab/Octave for procedural design of analog integrated circuits. The toolbox contains all native functions required by analog designers (namely, schematic-generation, simulation setup and execution, integrated look-up tables and functions for design space exploration) to capture an entire design strategy in an executable script. This script - which we call an Expert Design Plan (EDP) - is capable of executing an analog circuit design fully automatically. The toolbox is integrated in an existing design flow. A bandgap reference voltage circuit is designed with this tool in less than 15 min.
GELaZ folgte dem Förderaufruf „Intelligente Netzanbindung von Parkhäusern und Tiefgaragen“ (INPUT), mit dem Pilotprojekte unterstützt werden sollten, bei denen aufgrund des Einbaus von Ladeinfrastruktur für Elektromobilität in Parkhäuser, Parkplätze und Tiefgaragen (PPT) die Anbindung an das Stromnetz beispielhaft aufgezeigt und intelligent gelöst wird. Das Gesamtziel des Vorhabens umfasste deshalb: Errichtung öffentlichkeitswirksamer Demonstrationsanlagen mit vielen Ladeanschlüssen an drei verschiedenen Standorten in Baden-Württemberg: Ludwigsburg, Reutlingen und Konstanz. Es sollte auf bereits erprobte Hardware- und Softwarelösungen zurückgegriffen werden, die auf die örtlichen Gegebenheiten zum gleichzeitigen Laden mehrerer Fahrzeuge angepasst wurden.
Die additive Fertigung hat sich in den vergangenen Jahren wesentlich weiterentwickelt. Dabei wurde die Prozesstechnologie, Anlagen und die Werkstoffe optimiert. Für die industrielle Anwendung auch bei größeren Stückzahlen in der flexiblen Fertigung fehlen noch automatisierte Lösungen für die gesamte Prozesskette. In diesem Beitrag werden Werkzeuge und Technologie für die Reinigung interner Strukturelemente dargestellt.
In dem Beitrag wurden exemplarisch Möglichkeiten aufgezeigt, die mittels der Verknüpfung unterschiedlicher Technologien zur Steigerung von Genauigkeit und Effizienz bei der Bearbeitung genutzt werden können. Dabei sind Kenntnisse aus unterschiedlichen Bereichen erforderlich. Dies sind sowohl Bearbeitungs- und Prozesstechnologie, die Konstruktion von Maschinen, Vorrichtungen und Werkzeugen, sowie Mess- und Steuerungstechnik. Daneben sind auch neue Geschäftsmodelle und Technologien für die Nutzung und Verfügbarmachung von Daten und Informationen erforderlich.
The hearing contact lens® (HCL) is a new type of hearing aid devices. One of its main components is a piezo-electric actuator. In order to evaluate and maximize the HCL's performance, a model of the HCL coupled to a middle-ear model was developed using finite element approach. The model was validated step by step starting with the HCL only. To validate the HCL model, vibrational measurements on the HCL were performed using a laser-doppler-vibrometer (LDV). Then, a silicone cap was placed onto the HCL to provide an interface between the HCL and the tympanic membrane of the middle-ear model, and additional LDV measurements on temporal bones were performed to validate the coupled model that was used to evaluate the equivalent sound pressure of the HCL. Moreover, a de-eper insight was gained into the contact between the HCL and tympanic membrane and its effects on the HCL performance. The model can be used to investigate the sensitivity of geometrical and material parameters with respect to performance measures of the HCL and evaluate the feedback behavior.
This article illustrates a method for sensorless control of a switched reluctance motor. The detection of the time instants for switching between the working phases is determined based on the evaluation of the switching frequency of the hysteresis current controllers for appropriately selected sensing phases. This enables a simple and cost efficient implementation. The method is compared with a pulse injection method in terms of efficiency and resolution.
Sägen ist ein häufig unterschätzter spanender Prozess. Oft kommt das Sägen nur zum Zuschnitt von Rohteilen zum Einsatz. Bei der Bearbeitung von Leichtbauwerkstoffen werden damit jedoch Schichten in Toleranz direkt auf die montagefertigen Konturen zugeschnitten. Zur Steigerung von Qualität und Zuverlässigkeit des Fertigungsprozesses werden maschineninterne und sensorische Daten überwacht, ausgewertet und in den Prozess zurückgekoppelt. Daher kommt es auf die gezielte Kontrolle der entscheidenden Parameter mit möglichst wenigen und robusten Schnittstellen an. Im Rahmen eines ZIM-Kooperationsprojektes (Hochschule Reutlingen, Hema Frickenhausen, Pragmatic Minds Kirchheim) wurde dies für einen Bandsägeprozess erforscht und umgesetzt.
Die additive Fertigung hat sich in den vergangenen Jahren wesentlich weiter entwickelt. Dabei wurde die Prozesstechnologie, Anlagen und die Werkstoffe optimiert. Für die industrielle Anwendung auch bei größeren Stückzahlen in der flexiblen Fertigung fehlen noch automatisierte Lösungen für die gesamte Prozesskette. In diesem Beitrag werden Werkzeuge und Technologie für die Reinigung interner Strukturelemente dargestellt.
Die Charakterisierung und Beschreibung der komplexen Wechselwirkungen an der Zerspanstelle eines Bearbeitungszentrums beeinflusst die Qualität der hergestellten Bauteile. In diesem Beitrag wird die Messung und Beschreibung der Eigenfrequenzen unterschiedlicher Bearbeitungszentren in Abhängigkeit der bei der Bearbeitung verwendeten Werkzeuge und Bearbeitungsstrategien bezüglich der Auswirkungen auf die Stabilität hergeleitet. Dazu werden die gestellseitigen Resonanzfrequenzen analysiert. Ziel der Untersuchungen ist eine Beschreibung der dynamischen Eigenschaften zur Optimierung der NC-Programmierung.
Die Zielsetzung des hier vorgestellten Projekts ist es, eine intelligente Steuerungsalgorithmik für Biogas-Blockheizkraftwerke (Biogas-BHKW) zu entwickeln und zu optimieren. Daran schließt sich eine Testphase an einer realen Biogasanlage an, an der die Algorithmik zu diesem Zweck in die Anlagensteuerung implementiert wird. Um beurteilen zu können inwieweit die Steuerungsalgorithmik einen Beitrag zur Entlastung von Stromnetzen leisten kann, wird für die Versuche neben dem elektrischen Bedarf des landwirtschaftlichen Betriebs, an dem die Anlage angesiedelt ist, zusätzlich die Residuallast des benachbarten Stromnetzes betrachtet. Diese basiert auf Daten vom nächstgelegenen Umspannwerk, die so skaliert werden, dass sie eine Siedlung repräsentieren, die von dem Biogas-BHKW der Anlage mitversorgt werden kann. Die Einbindung der Steuerungsalgorithmik in die Anlagensteuerung erfolgt über eine Kommunikationsstruktur mit einer Datenbank als zentraler Schnittstelle. Eine erste Versuchsreihe, bei der das Biogas-BHKW nach den Fahrplänen der intelligenten Steuerungsalgorithmik geregelt wird, zeigt vielversprechende Ergebnisse. Über die gesamte Versuchsreihe hinweg berechnet die Steuerungsalgorithmik zuverlässig neue Fahrpläne, die vom BHKW weitestgehend auch sehr gut umgesetzt werden. Zudem kann nachgewiesen werden, dass durch den Einsatz der Algorithmik das vorgelagerte Stromnetz entlastet wird.
Die bedarfsgerechte Steuerung dezentraler thermischer Energiesysteme, wie Kraft-Wärme-Kopplungs- (KWK-) Anlagen und Wärmepumpen, kann einen entscheidenden Beitrag zur Deckung bzw. Reduktion der Residuallast leisten und so für eine Verringerung der konventionellen Reststromversorgung und den damit einhergehenden Treibhausgasemissionen sorgen. Dafür wurde an der Hochschule Reutlingen in mehrjähriger Forschungsarbeit ein prognosebasierter Steuerungsalgorithmus entwickelt. Gegenstand dieses Beitrags bilden neben der Vorstellung eben jenes Steuerungsalgorithmus auch dessen praktische Umsetzungsvarianten: Eine auf einer speicherprogrammierbaren Steuerung (SPS) rein lokal ausführbare Version sowie eine Webservice-Anwendung für den parallelen Betrieb mehrerer Anlagen – ausgehend von einem zentralen Server. Erprobungen am KWK-Prüfstand der Hochschule Reutlingen bestätigen die zuverlässige Funktionsweise des Algorithmus in den verschiedenen Umsetzungsvarianten. Gleichzeitig wird der Vorteil der bedarfsgerechten Steuerung gegenüber dem, insbesondere im Mikro-KWK-Bereich standardmäßig vorliegenden, wärmegeführten Betrieb in Form einer Steigerung der Eigenstromdeckung von bis zu 27 % aufgezeigt. Neben der bedarfsgerechten Steuerung bedient der entwickelte Algorithmus zudem noch ein weiteres Anwendungsgebiet: Den vorhersagbaren KWK-Betrieb, der beispielsweise in Form täglicher Einspeiseprognose im Rahmen des Redispatch 2.0 eingefordert wird. Die Vorhersage des KWK-Betriebs ist dabei auf zwei Weisen möglich: Als erste Option kann der wärmegeführte Betrieb direkt über den Algorithmus abgebildet und prognostiziert werden. Eine andere Möglichkeit stellt wiederum die bedarfsgerechte Steuerung der Anlage dar; der berechnete optimale Fahrplan entspricht dabei gleichzeitig der Betriebsprognose des KWK-Geräts. Damit ist der entwickelte Steuerungsalgorithmus in der Lage, auf unterschiedliche Weisen zum Gelingen der Energiewende beizutragen.
The vast majority of state-of-the-art integrated circuits are mixed-signal chips. While the design of the digital parts of the ICs is highly automated, the design of the analog circuitry is largely done manually; it is very time-consuming; and prone to error. Among the reasons generally listed for this is often the attitude of the analog designer. The fact is that many analog designers are convinced that human experience and intuition are needed for good analog design. This is why they distrust the automated synthesis tools. This observation is quite correct, but this is only a symptom of the real problem. This paper shows that this phenomenon is caused by very concrete technical (and thus very rational) issues. These issues lie in the mode of operation of the typical optimization processes employed for the synthesizing tasks. I will show that the dilemma that arises in analog design with these optimizers is the root cause of the low level of automation in analog design. The paper concludes with a review of proposals for automating analog design
Purpose: Interpretive research in management accounting and control provides rich insights from empirically based studies, but it has been criticised for lacking generalisability and potential subjectivity. On the latter, triangulation is useful, and this paper aims to offer some insights on a triangulation technique thus far not commonly reported in management accounting/control research.
Design/methodology/approach: Drawing on a study of the roles of management accountants in performance management systems, this paper offers some insights from empirical experiences on the use of concept maps as a tool to assist triangulation and improve understanding of complex empirical phenomena.
Findings: The concept maps as utilised revealed additional insights which were not recounted by interviewees during the normal interview time. This is a potentially important finding for consideration of future researchers.
Practical implications: In this paper, how concept maps were used is detailed, and it is hoped that future researchers will find their use beneficial in interview settings.
Originality/value: Thus far, concept maps seem under-utilised in management accounting and control research. This paper gives some initial insights on how they may be used in case study settings.
Lehrbuch zur CAD-Software Creo Parametric und zur Produktdatenverwaltung mit Windchill.
3D-Volumenmodellierung, 3D-Flächenmodellierung, Blechmodellierung, Baugruppen- und Zeichnungserstellung, Definition von Normteilen, Erstellen von Animationen und dynamischen Analysen.
Verfahren zum Umgang mit großen Baugruppen und zur flexiblen Modellierung, Konstruk-tionsvarianten "Top-Down" und "Bottom-Up", Organisation von Konstruktionsprojekten über Skeletttechnik.
Neu: Konstruktion von und mit Mehrkörperobjekten, Rahmenkonstruktion in der Profilumgebung (AFX), intelligente Verbindungen (IFX), Live Simulation und Generatives Design.
For collision and obstacle avoidance as well as trajectory planning, robots usually generate and use a simple 2D costmap without any semantic information about the detected obstacles. Thus a robot’s path planning will simply adhere to an arbitrarily large safety margin around obstacles. A more optimal approach is to adjust this safety margin according to the class of an obstacle. For class prediction, an image processing convolutional neural network can be trained. One of the problems in the development and training of any neural network is the creation of a training dataset. The first part of this work describes methods and free open source software, allowing a fast generation of annotated datasets. Our pipeline can be applied to various objects and environment settings and is extremely easy to use to anyone for synthesising training data from 3D source data. We create a fully synthetic industrial environment dataset with 10 k physically-based rendered images and annotations. Our da taset and sources are publicly available at https://github.com/LJMP/synthetic-industrial-dataset. Subsequently, we train a convolutional neural network with our dataset for costmap safety class prediction. We analyse different class combinations and show that learning the safety classes end-to-end directly with a small dataset, instead of using a class lookup table, improves the quantity and precision of the predictions.
Deep learning-based EEG detection of mental alertness states from drivers under ethical aspects
(2021)
One of the most critical factors for a successful road trip is a high degree of alertness while driving. Even a split second of inattention or sleepiness in a crucial moment, will make the difference between life and death. Several prestigious car manufacturers are currently pursuing the aim of automated drowsiness identification to resolve this problem. The path between neuro-scientific research in connection with artificial intelligence and the preservation of the dignity of human individual’s and its inviolability, is very narrow. The key contribution of this work is a system of data analysis for EEGs during a driving session, which draws on previous studies analyzing heart rate (ECG), brain waves (EEG), and eye function (EOG). The gathered data is hereby treated as sensitive as possible, taking ethical regulations into consideration. Obtaining evaluable signs of evolving exhaustion includes techniques that obtain sleeping stage frequencies, problematic are hereby the correlated interference’s in the signal. This research focuses on a processing chain for EEG band splitting that involves band-pass filtering, principal component analysis (PCA), independent component analysis (ICA) with automatic artefact severance, and fast fourier transformation (FFT). The classification is based on a step-by-step adaptive deep learning analysis that detects theta rhythms as a drowsiness predictor in the pre-processed data. It was possible to obtain an offline detection rate of 89% and an online detection rate of 73%. The method is linked to the simulated driving scenario for which it was developed. This leaves space for more optimization on laboratory methods and data collection during wakefulness-dependent operations.
We propose a novel technique to compensate the effects of R-C / gm-C time-constant (TC) errors due to process variation in continuous-time delta-sigma modulators. Local TC error compensation factors are shifted around in the modulator loop to positions where they can be implemented efficiently with tunable circuit structures, such as current-steering digital-to-analog converters (DAC). This approach constitutes an alternative or supplement to existing compensation techniques, including capacitor or gm tuning. We apply the proposed technique to a third-order, single-bit, low-pass continuous-time delta-sigma modulator in cascaded integrator feedback structure. A feedback path tuning scheme is derived analytically and confirmed numerically using behavioral simulations. The modulator circuit was implemented in a 0.35-μm CMOS process using an active feedback coefficient tuning structure based on current-steering DACs. Post-layout simulations show that with this tuning structure, constant performance and stable operation can be obtained over a wide range of TC variation.
A new planar compact antenna composed of two crossed Cornu spirals is presented. Each Cornu spiral is fed from the center of the linearly part of the curvature between the two spirals, which builds the clothoid. Sequential rotation is applied using a sequential phase network to obtain circular polarization and increase the effective bandwidth. Signal integrity issues have been addressed and designed to ensure high quality of signal propagation. As a result, the antenna shows good radiation characteristics in the bandwidth of interest. Compared to antennas of the same size in the literature, it is broadband and of high gain. Although the proposed antenna has been designed for K- and Ka-band operations, it can also be developed for lower and upper frequencies because of the linearity of the Maxwell equations.
Purpose
The purpose of this study is to examine private households’ preferences for service bundles in the German energy market.
Design/methodology/approach
This investigation is based on survey data collected from 3,663 customers of seven mainly municipal energy suppliers in the German energy market. The data set was analyzed via a binary logistic regression model to identify the most prospective customers and their preferences regarding bundles of energy services.
Findings
The results indicate that potential adopters of energy-related service bundles have greater prior knowledge about service bundles; place higher importance on simplified handling, flat rates and long price guarantees; prefer to purchase a service bundle from an energy supplier; live in urban areas and have a gas tariff; are both less likely to have a green electricity tariff and to support the German energy transition; have a greater intention to purchase a smart home product; are less likely to already be prosumers; and prefer customer centers and social media as communication channels with energy providers.
Practical implications
This paper offers several implications for decision-makers in developing marketing strategies for bundled offerings in a highly competitive energy market.
Originality/value
This paper contributes to the sparse research on service bundles in the energy sector, despite the growing interest of energy suppliers and consumers in this topic. It expands the research focusing on the telecommunications sector.
From the perspective of manufacturing companies, the political, media and economic discourse on decarbonisation in the recent years manifests itself as an increasing social expectation of action. In Germany, in particular, this discourse is also being driven forward by powerful companies, respectively sectors, most notably the automotive industry. Against this background, the present paper examines how German manufacturing companies react to rising societal pressure and emerging policies. It examines which measures the companies have taken or plan to take to reduce their carbon footprint, which aspirations are associated with this and the structural characteristics (company size, energy intensity, and sector) by which these are influenced. A mix methods approach is applied, utilising data gathered from approx. 900 companies in context of the Energy Efficiency Index of German Industry (EEI), along with media research focusing on the announced decarbonisation plans and initiatives. We demonstrate that one-size-serves-all approaches are not suitable to decarbonise industry, as the situation and ambitions differ considerably depending on size, energy intensity and sector. Even though the levels of ambition and urgency are high, micro and energy intensive companies, in particular, are challenged. The present research uncovers a series of questions that call for attention to materialise the ambitions and address the challenges outlined.
Hearing contact lens (HCL) is a new type of hearing aid devices. One of its main components is a piezo-electric actuator (PEA). In order to evaluate and maximizethe HCL´s performance, a model of the HCL coupled to the middle ear was developed using finite element (FE)approach. To validate the model, vibrational measurements on the HCL and temporal bones were performed using a Laser-Doppler-Vibrometer (LDV). The model was validated step by step starting with HCL only. Then a silicone cap was fitted onto the HCL to provide an interface between the HCL and the tympanic membrane. The HCL was placed on the tympanic membrane and additional measurements were performed to validate the coupled model. The model was used to evaluate the sensitivity of geometrical and material parameters with respect to performance measures of the HCL. Moreover, deeper insight was gained into the feedback behavior, which causes whistling sounds, and the contact between the HCL and tympanic membrane.
This paper presents a permanent magnet tubular linear generator system for powering passive sensors using vertical vibration harvesting energy. The system consists of a permanent magnet tubular linear vibration generator and electric circuits. By using the design of mechanical resonant movers, the generator is capable of converting low frequencies small amplitude vertical vibration energy into more regular sinusoidal electrical energy. The distribution of the magnetic field and electromotive force are calculated by Finite Element Analysis. The characteristics of the linear vibration generator system are observed. The experimental results show the generator can produce about 0.4W~1.6W electrical power when the vibration source's amplitude is fixed on 2mm and the frequencies are between 13Hz and 22Hz.
This paper presents a modular and scalable power electronics concept for motor control with continuous output voltage. In contrast to multilevel concepts, modules with continuous output voltage are connected in series. The continuous output voltage of each module is obtained by using gallium nitride (GaN) high electron motility transistor (HEMT)s as switches inside the modules with a switching frequency in the range between 500 kHz and 1 MHz. Due to this high switching frequency a LC filter is integrated into the module resulting in a continuous output voltage. A main topic of the paper is the active damping of this LC output filter for each module and the analysis of the series connection of the damping behaviour. The results are illustrated with simulations and measurements.
Fault diagnosis of rolling bearings is an essential process for improving the reliability and safety of the rotating machinery. It is always a major challenge to ensure fault diag- nosis accuracy in particular under severe working conditions. In this article, a deep adversarial domain adaptation (DADA) model is proposed for rolling bearing fault diagnosis. This model con- structs an adversarial adaptation network to solve the commonly encountered problem in numerous real applications: the source domain and the target domain are inconsistent in their distribution. First, a deep stack autoencoder (DSAE) is combined with representative feature learning for dimensionality reduction, and such a combination provides an unsupervised learning method to effectively acquire fault features. Meanwhile, domain adaptation and recognition classification are implemented using a Softmax classifier to augment classification accuracy. Second, the effects of the number of hidden layers in the stack autoencoder network, the number of neurons in each hidden layer, and the hyperparameters of the proposed fault diagnosis algorithm are analyzed. Third, comprehensive analysis is performed on real data to vali- date the performance of the proposed method; the experimental results demonstrate that the new method outperforms the existing machine learning and deep learning methods, in terms of classification accuracy and generalization ability.
Der Verschleiß von Werkzeugen bei der Zerspanung mit geometrisch definierter Schneide ist wesentliches Kriterium für die Qualität der bearbeiteten Werkstücke, die Zuverlässigkeit der Bearbeitungsprozesse sowie der Wirtschaftlichkeit. Die Wirtschaftlichkeit der Bearbeitung wird vor allem durch die Anzahl der mit einem Werkzeug zuverlässig bearbeitbaren Werkstücke beeinflusst. Die Standzeit / der Standweg der Werkzeuge sowie die einsetzbaren Technologieparameter sind von unterschiedlichen Faktoren abhängig. Dabei sind neben dem Werkzeug und deren Eingriffsbedingungen (z. B. axiale und radiale Zustellung) auch die Einflüsse seitens der Maschine (z. B. Steifigkeit, Eigenfrequenzen, Drehmoment), des Werkstückes (z. B. Werkstoff, Genauigkeiten) und des Bearbeitungsprozesses mit den dabei auftretenden Kräften, Drehmomenten, Drehzahlen und Vorschüben abhängig. Trotz verschiedener Bemühungen der vergangenen beiden Jahrzehnte zur Bearbeitung ohne Kühlschmierstoff oder mit Minimalmengenschmierung werden heute immer noch zahlreiche Bearbeitungsprozesse unter Einsatz von Kühlschmierstoff durchgeführt. Dadurch lassen sich aufgrund der geringeren thermischen Belastung von Werkzeug und Werkstück teilweise deutlich höhere Schnittbedingungen und/oder Standzeiten erzielen.
Facial beauty prediction (FBP) aims to develop a machine that automatically makes facial attractiveness assessment. In the past those results were highly correlated with human ratings, therefore also with their bias in annotating. As artificial intelligence can have racist and discriminatory tendencies, the cause of skews in the data must be identified. Development of training data and AI algorithms that are robust against biased information is a new challenge for scientists. As aesthetic judgement usually is biased, we want to take it one step further and propose an Unbiased Convolutional Neural Network for FBP. While it is possible to create network models that can rate attractiveness of faces on a high level, from an ethical point of view, it is equally important to make sure the model is unbiased. In this work, we introduce AestheticNet, a state-of-the-art attractiveness prediction network, which significantly outperforms competitors with a Pearson Correlation of 0.9601. Additionally, we propose a new approach for generating a bias-free CNN to improve fairness in machine learning.
Um den Übergang von der Schule zur Hochschule zu erleichtern, brauchen Studierende technischer Fächer häufig eine Auffrischung ihrer Kenntnisse in Mathematik und Physik. Ein Online-Lernsystem für Physik kann Studierende bei der Beschäftigung mit physikalischen Inhalten unterstützen. Zudem kann ein Physik-Wissenstest Lücken im individuellen Wissensstand aufzeigen und zum Lernen der fehlenden Themen motivieren. Die Arbeitsgruppe "eLearning in der Physik" der Hochschulföderation Süd-West (HfSW) bestehend aus den baden-württembergischen Hochschulen Aalen, Esslingen, Heilbronn, Mannheim und Reutlingen hat einen Aufgabenpool von über 200 Physikaufgaben für Erstsemester erarbeitet. Sie stehen den Studierenden mit Lösungen in Lernmanagementsystemen zum Selbststudium und jetzt auch im "Zentralen Open Educational Resources Repositorium der Hochschulen in Baden-Württemberg" (ZOERR) zur Verfügung. In diesem Beitrag wird über den Einsatz der Online-Übungsaufgaben in 2020/2021 berichtet, über die Ergebnisse der Wissenstests und über die in der Corona-Zeit neu eingerichteten eTutorien.
Business opportunities for energy providers to utilize flexible industrial demand are platform-based, connecting small and medium-sized enterprises (SMEs) to a virtual power plant (VPP) in complex ecosystems. Unlike in other VPPs, the focus is on participation, data, and control sovereignty for the SMEs. An exemplary application for an existing cement mill demonstrates positive margins. Viable VPP business models for small and medium-sized utilities include the “orchestrator,” i.e., adding value by linking services of specialized providers, the “integrator,” i.e., incorporating internal and external processes and resources, as well as the “white label user,” i.e., using a turn-key VPP from an exclusive cooperation partner.
Electronic design automation approaches can roughly be divided into optimizers and procedures. While the former have enabled highly automated synthesis flows for digital integrated circuits, the latter play a vital (but mostly underestimated role) in the analog domain. This paper describes both automation strategies in comparison, identifying two fundamentally different automation paradigms that reflect the two basic design practices known as “top-down” and “bottom-up”. Then, with a focus on the latter, the history of procedural approaches is traced from their
early beginnings until today’s evolvements and future prospects to underline their practical importance and to accentuate their scientific value, both in itself and in the overall context of EDA.
This paper presents an improvement in usability and integrity of simulation-based analog circuit sizing. Instead of using geometrical sizing parameters (width, length), a transformed design-space, consisting exclusively of electrical parameters (branch currents, efficiencies and speed) is utilized. This design-space is explored more efficiently by optimizers. Moreover, this design-space can be reduced without affecting the quality of the result. The method is illustrated on two application examples, a symmetrical and a miller operational amplifier. Sizing the circuits using the transformed design-space showed significant reduction in required circuit simulations (up to 11x faster), better convergence, without loss in quality.
Corporate entrepreneurship in the public sector: exploring the peculiarities of public enterprises
(2021)
Entrepreneurship is predominantly treated as a private-sector phenomenon and consequently its increasing importance in the public sector goes largely unremarked. That impedes the research field of entrepreneurship being capable of spanning multiple sectors. Accordingly, recent research calls for the study of corporate entrepreneurship (CE) as it manifests in the public sector where it can be labeled public entrepreneurship (PE). This dissertation considers government an essential entrepreneurial actor and is led by the central research question: What are the peculiarities of the public sector and how do they impact public enterprises’ entrepreneurial orientation (EO)?
Accordingly, this dissertation includes three studies focusing on public enterprises. Two of the studies set the scope of this thesis by investigating a specific type of organization in a specific context—German majority-government-owned energy suppliers. These enterprises operate in a liberalized market experiencing environmental uncertainties like competitiveness and business transformation.
The aims and results of the studies included in this dissertation can be summarized as follows: The systematic literature review illuminates the stimuli of and barriers to entrepreneurial activities in public enterprises and the potential outcomes of such activities discussed so far. The review reveals that research on EO has tended to focus on the private sector and consequently that barriers to and outcomes of entrepreneurial activities in the public sector remain under-researched. Building on these findings, the qualitative study focuses on the interrelated barriers affecting entrepreneurship in public enterprises and the outcomes of entrepreneurial activities being inhibited. The study adopts an explorative comparative causal mapping approach to address the above-mentioned research goal and the lack of clarity around how barriers identified in the public sphere are interrelated. Furthermore, the study bases its investigation on the different business segments of sales (competitive market) and the distribution grid (natural monopoly) to account for recent calls for fine-grained research on PE. Results were compared with prior findings in the public and private sector. That comparison indicates that the barriers revealed align with aspects discussed in prior research findings relating to both sectors. Examples include barriers associated with the external environment such as legal constraints and barriers originating from within the organization such as employee behavior linked to a value system that hampers entrepreneurial action. However, the most important finding is that a public enterprise’s supervisory board can hinder its progress, a finding running counter to those of previous private-sector research and one that underscores the widespread prejudice that the involvement of a public shareholder and its nominated board of directors has a negative effect on EO. The third study is quantitative (data collection via a questionnaire) and builds on both its predecessors to examine the little understood topic of board behavior and public enterprises’ social orientation as predictors of EO. The study’s results indicate that social orientation represses EO, whereas board strategy control (BSC) does not seem to predict EO. Regarding BSC, we find that the local government owners in our sample are less involved in BSC. The third study also examines board networking and finds its relationship with EO depends on the ownership structure of the public-sector organization. An important finding is that minority shareholders, such as majority privately-owned enterprises and hub firms, repress EO when engaging in board networking.
In summary, this doctoral thesis contributes to the under-researched topic of CE in the public sector. It investigates the peculiarities of this sector by focusing on the supervisory board and social oriented activities and their impact on the enterprise’s EO in the quantitative study. The thesis addresses institutional questions regarding ownership and the last study in particular contributes to expanding resource dependence theory, and invites a nuanced perspective: The original perspective suggests that interorganizational arrangements like interfirm network ties and equity holdings reduce external resource dependency and consequently improve firm performance. The findings within this thesis expose resource delivery to potential contrary effects to extend the understanding of interorganizational action with important implications for practice.