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The advent of social media and its commodification have created a never-ending feedback loop between businesses and their customers. In this context, constant negative Word-of-Mouth (NWOM) may jeopardize a corporate image and cause defensiveness in corporate communication. This paper presents a case study of several customer service accounts of the railway company Deutsche Bahn on Twitter to investigate the management and control of constant NWOM and the impact of accountability strategies on customers’ perception of the firm. To this end, a sample of 36,757 Twitter postings was drawn and analyzed by means of sentiment and content analysis techniques. The findings suggest that the perceived accountability towards the firm declined in case of an attitude shift towards the user. In contrast, the firm was being held accountable more insistently after expressed defensiveness, regardless of the firm’s actual accountableness. With this paper, we introduce the notion of accountability management and an accompanying theoretical framework to the literature. This provides a novel perspective on constant NWOM countermeasures for organizations that are part of ‘toxic’ industries or face unrightfully claimed accusations, i.e., when being held accountable for outer circumstances beyond their control.

In this article, we consider the load frequency control problem for a class of power systems based on the dynamic event-triggered control (ETC) approach. The transmission networks are unreliable in the sense that malicious denial-of-service (DoS) attacks may arise in the power system. First, a model-based feedback controller is designed, which utilizes estimated states, and thus can compensate the error between plant states and the feedback data. Then, a dynamic event-triggered mechanism (DETM) is proposed by introducing an internal dynamic variable and a timer variable with jump dynamics. The proposed (DETM) can exclude Zeno behavior by regularizing a prescribed strictly positive triggering interval. Incorporated in the ETC scheme, a novel hybrid model is established to describe the flow and jump dynamics of the power system in the presence of DoS attacks. Based on the hybrid dynamic ETC scheme, the power system stability can be preserved if the attacks frequency and duration sustain within an explicit range. In addition, the explicit range is further maximized based on the measurement trigger-resetting property. Finally, a numerical example is presented to show the effectiveness of our results.

National Natural Science Foundation of China (Grant Number: 61973102, 61933007 and U22A2044); China Postdoctoral Science Foundation (Grant Number: 2022M710683); Jiangsu Funding Program for Excellent Postdoctoral Talent of China (Grant Number: 2022ZB128); Royal Society of the U.K., the Alexander von Humboldt Foundation of Germany.

Autonomous driving can make traffic safer by reducing human errors. Different sensor types in autonomous vehicles could introduce additional technical failures. We offer a target simulator testing LiDAR systems under automotive conditions. Therefore, data are projected over-the-air by laser signals on the LiDAR detector. This work presents a concept of a LiDAR target simulator with regards to LiDAR systems using the direct time-of-flight principle. We develope design considerations for a screen discussing undesired screen reflections, a curved screen form and the positioning of light sources on this screen. As one main solution, we introduce a concept of an antireflective screen. For the scenario simulation, we derive a model delivering the required optical power representing a simulated target, which is combined with the simulated time-of-flight. Considering no prior knowledge of the LiDAR system under test, we discuss the required calibration data and timing resolution. Thereby, we suggest an optimized time-of-flight concept requireing only one optical trigger to determine the LiDAR measurement start. All requirements are supported by calculated example parameters based on real LiDAR systems. Altogether, we discuss main challenges and possible solutions of our LiDAR target simulator, which will allow a safer and more efficient development of LiDAR systems.

In gate-defined quantum dot systems, the conductance change of electrostatically coupled sensor dots allows the observation of the quantum dots' charge and spin states. Therefore, the sensor dot must be optimally sensitive to changes in its electrostatic environment. A series of conductance measurements varying the two sensor-dot-forming barrier gate voltages serve to tune the dot into a corresponding operating regime. In this article, we analyze the noise characteristics of the measured data and define a criterion to identify continuous regions with a sufficient signal-gradient-to-noise ratio. Hence, accurate noise estimation is required when identifying the optimal operating regime. Therefore, we evaluate several existing noise estimators, modify them for 1-D data, optimize their parameters, and analyze their quality based on simulated data. The estimator of Chen et al. turns out to be best suited for our application concerning minimally scattering results. Furthermore, using this estimator in an algorithm for flank-of-interest classification in measured data shows the relevance and applicability of our approach. CA extern

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As the maximum frequency of electronics is rising, on-wafer measurements play an important role in modeling of integrated devices. Most of the time, due to the lack of measurement accuracy beyond 110 GHz, such models are usually extracted at frequencies much below their working frequencies and are subsequently extrapolated. The validity of such models is then mostly verified after fabrication of the complete chip, with a simple pass and fail test. This is stating the necessity of enhancing measurement results by any means possible, i.e., to reduce the overall uncertainty in such measurements. It is widely accepted that one of the main sources of uncertainty in such measurements is probe contact repeatability, since it is difficult to reach position accuracy below a few micrometers. We are presenting in this article a method to model the S -parameter variation with probe position on the pads, which can then be used to either estimate contact repeatability uncertainty or further enhance measurement results. The approach is validated based on the measurements performed at 500 GHz.

The power generated from the photovoltaic module is directly related to the magnitude of total incident solar radiation on the surface of the solar module. The total incident solar radiation depends on the location, tilt angle, and orientation of the solar module. In this paper, generic models were developed that determine the seasonal and annual optimal tilt angle of the Photovoltaic module at any location in Ethiopia without using meteorological data. Both isotropic and anisotropic diffuse solar radiation models were used to estimate monthly, seasonal, and annual optimal tilt angles. The monthly average daily global horizontal solar radiation for a total of 44 cities -32 for training and 12 for testing were obtained from the National Aeronautical and Space Administration database, and algorithms were developed and implemented using MATLAB and R programming software to obtain optimum tilt angle and regression models. The study showed that the developed model accurately estimates the optimal tilt angle with the minimum statistical validation errors. It is also found that 5.11% to 6.275% (isotropic) and 5.72% to 6.346% (anisotropic models) solar radiation energy is lost when using the yearly average fixed optimal tilt angle as compared with the monthly optimal tilt angle. The result of this study was also validated by comparing it with the previously published works, PVGIS and PVWatt online software. The graphical abstract is included in the supplementary file.

This article is concerned with the development of a new event-triggered parity space fault detection (FD) scheme. A linear discrete-time system model with varying sampling periods is presented for handling the problem of event-triggered FD and a new parity relation is established. Based on this, an event-triggered residual generator is constructed and the generated residual is completely decoupled from event-triggered transmission error. The design of the parity matrix is formulated into an optimization problem and an optimal solution of the parity matrix is obtained by using singular value decomposition. The issue of residual evaluation is also considered in the event-triggering implementation. The novelties of this article are twofold. First, a new event-triggered parity relation is obtained and the parity space-based residual signal achieves complete decoupling with the event-triggered transmission error. Second, the calculation of the parity matrix is independent of event parameters. So the design of the parity space-based residual generator and event generator can be carried out independently. Finally, a simulation example is considered to demonstrate the effectiveness of the proposed method.

This paper describes a low-cost extension for an imaging observation instrument as a radiation monitor. Adapted image processing methods enable discrimination between measured data and sensor / radiation-specific hazards and drives mitigation techniques to improve mission lifetime.

This study proposes a hierarchical structure-based fault-tolerant tracking control methodology for multiple 3-DOF helicopters in the presence of system nonlinearities, uncertainties and simultaneous actuator faults (partial loss of effectiveness, stuck, and saturation), and sensor faults (bias and drift). The hierarchical structure consists of the decentralized fault estimation hierarchy and distributed fault-tolerant tracking control hierarchy. The distributed constant gain-based, node-based, and edge-based adaptive fault-tolerant tracking control designs are developed to cope with bidirectional interactions and to guarantee the robust asymptotic stability and the good tracking property of multihelicopter systems, respectively. Simulation results validate the effectiveness of the proposed hierarchical structure-based tracking control algorithm.

A standard method for distance determination is light detection and ranging (LiDAR), which relies on the emission and detection of reflected laser pulses. When LiDAR systems become common for every vehicle, many simultaneous laser signals will produce mutual LiDAR interference between LiDAR systems. In this paper, we analyze the possibility to recognize mutual interference in time-correlated single photon counting (TCSPC) LiDAR with particular focus on flash systems. We evaluate the LiDAR interference appearance by deriving the expected event distribution for ego and aggressor signal. From that, we calculate the probability of photon detection within each measured signal. This paper shows the high potential of different pulse repetition frequencies to reduce LiDAR interference. Using signal-to-noise ratio (SNR), we define the extinction distance, beyond which the aggressor signal completely extinguishes the ego signal. Applied on different background and laser event rates, we find the connection between ideal LiDAR system designs and lowest probability for unrecognized LiDAR interference. Furthermore, we show the relationship to a specific LiDAR design, which must fulfill eye safety condition and receives lower intensities with increasing target distances. Finally, we present different solutions for the recognition and reduction of LiDAR interference based on our previous results.

With recent developments, terahertz (THz) technology has attracted great interest in many different fields of research and application. In particular, biosensors that detect a thin film of captured pathogens are in high demand for rapid diagnosis. Based on the interaction between analytes under test and electromagnetic (EM) field, THz resonators are sensitive to changes in the permittivity of the analyte and have the potential to become sensitive thin-film sensors. However, conventional metamaterial methods have low Q factors, leading to small amplitude variations and ambiguous detection. Here, we present a photonic crystal (PhC)–based resonator with a high Q factor that is sensitive to a monolayer of beads in the µm size range. The PhC resonator made of high resistivity silicon (HRSi) shows a Q factor of 750, which is much higher compared to metamaterial-based methods. Its resonance shift is linearly related to the coverage of the micron-sized beads on its surface. Moreover, simulation results with a thin film model of a single layer of the beads showed agreement with the experimental results. Although the achieved sensitivity needs to be improved by enhancing the field concentration on the analyte, our results suggest that THz PhC resonators with high Q factor are promising for biosensing applications. We anticipate our work to be a starting point for biochips with improved sensing capabilities and more functionality.

CA Makhlouf The rapid progress in semiconductor technology has vastly boosted the development of terahertz sources and receivers in terms of compactness, reliability, operation frequency, and output power. In this manuscript, we report on the latest achievements in terahertz sources and receivers and provide a comprehensive overview of their working principles and applications in THz systems.

Thermoelectric (TE) technology has the ability to convert heat into electricity and is therefore attractive in the context of the search for new green energy sources. The aim of this thesis is to successfully build, characterize and model eco-friendly TE generators (TEG) made of p- and n-type Mg2(Si,Sn) TE materials. The TE materials are already well-researched but a compatible electrode, electrically interconnecting the TE elements, is missing on the road towards a TEG. Moderately satisfying electrodes were reported in literature, but lacked chemical or mechanical stability. In this work, we find Al to be a promising electrode for Mg2(Si,Sn): we report no cracking nor delamination, a stable interface through annealing and contact resistivities below 10 μΩcm² and stable TE materials directly after joining. This is an essential milestone towards the TEG. We then successfully build and characterize a full Mg2(Si,Sn)-based TEG. The first efficiency measurement of such a module is reported and we measure a high power density of 0.9 W/cm². We combine the TEG characterization with an analysis based on constant property model (CPM) to identify loss mechanisms. An increase of the inner resistance of the TEG, attributed to cracking due to high thermal stress, is observed. It is predicted that both efficiency and power output could be realistically increased by 30% solely by preventing this cracking. Finally, we test the hypothesis that the TEG mechanical failure is due to the ceramic plate by using an open module design with bare Cu bridges. Additional voltage probes are soldered to monitor the resistance of each leg during the measurement. This innovative approach consistently shows that the resistance of the n-type legs systematically increases even at low temperatures. It is found that increasing the cross-section of the legs solves the issue when the hot side temperature remains below 300 °C; suggestions for even further improvement are given. Overall, we identify the first truly promising electrode for Mg 2(Si,Sn) and use it to successfully build one of the first eco-friendly Mg2(Si,Sn)-based TEGs. We report the first efficiency measurement for such a module and implement a different design to improve the performance. Strategies for further improvement are identified and tested with innovative measurement and modelling techniques. Dissertation, Universität Duisburg-Essen, 2023

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Der Bedarf an schneller Datenkommunikation wächst in unserer Gesellschaft mit jedem Tag. „Visible Light Communication“ über den Freiraum oder über Polymer-Optische-Fasern ist ein innovativer Ansatz zur Deckung des Bedarfs, benötigt jedoch kostengünstige und schnell schaltbare Lichtemitter, wie Nitrid-basierte Leuchtdioden (LEDs). Die minimal erreichbare Schaltzeit handelsüblicher LEDs ist allerdings begrenzt, da interne elektrische Felder innerhalb der Kristallschichten der LED die Licht-Abschaltung verzögern. Kern-Hülle Nanodraht-LEDs (ND-LEDs) unterliegen dieser zeitlichen Limitierung nicht und sind daher höchst attraktiv. Bis dato konnten sie sich jedoch nicht durchsetzen, da die technologische Kontaktierung der dreidimensionalen ND-Struktur komplex und die industrielle Skalierbarkeit der verwendeten Herstellungsmethoden nicht gegeben sind. Daher ist das Ziel dieser Arbeit hochfrequenz-taugliche Kristallstrukturen mittels eines industriell-relevanten Epitaxie-Prozesses herzustellen, welche zur einfachen technologischen Herstellung von ND-LEDs genutzt werden können. Dieses gelang zum einem, indem die Kristallstrukturen auf leitfähigem Si-Substraten mittels MOVPE gewachsen wurden, wodurch eine einfache Rückseitenkontaktierung möglich ist. Zum anderem konnte das sonst übliche räumlich-zufällige Wachstum der Nitride auf Si durch ein periodisch-angeordnetes Wachstum von ND-LED-Kristallstrukturen ersetzt werden. Hierzu wurde eine ganze neue Methode der räumlich-selektiven Epitaxie (SAE) entwickelt, welche auf der Kontrolle der lokalen Polarität der Nitridkristalle auf der Si-Oberfläche beruht. Das erreichte polaritäts- und ortsgesteuerte Wachstum ermöglichte die Herstellung von bis zu 5 µm-hohen Nanodrähten mit koaxialen LED-Hüllen, welche den Draht gezielt nur lokal im oberen Teil einhüllten. Die gewonnene dreidimensionale Epitaxiekontrolle wurde dabei stets über detaillierte kristallfacetten -und parameterabhängige Wachstumsmodelle erläutert. Anhand der erreichten Kristallstruktur konnte eine einfache Kontaktierungstechnologie entwickelt werden, welche ohne elektrische Isolationsschichten auskommt, womit die Herstellung von ND-LED-Prototypen in nur wenigen Prozessschritten gelang. Durch zusätzliche elektro-optische Charakterisierungen der Prototypen und Nachmodellierung der gemessenen Daten, konnten weitere Erkenntnisse zur Optimierung des entwickelten Konzepts gewonnen werden und das Vorliegen des Quanten-Confined-Stark-Effekt ausgeschlossen werden (strahlende Lebensdauer ≈ 500 ps). Die Ergebnisse zeigen, dass sich die Kern-Hülle Nitridhalbleiterstrukturen auf Si zur relativ simplen Bauelementherstellung von ND-LEDs für zukünftige Datenkommunikations-Anwendungen eignen., The demand for high-speed data communication is growing with each passing day in our modern society. "Visible Light Communication" via free space or by polymer optical fibers is an innovative approach to meet the demand but requires low-cost and fast light on/off-switching light emitters, such as nitride-based light emitting diodes (LEDs). However, the switching time of commercially available LEDs is limited due to the presence of internal electric fields in the crystal layers of the LED. These fields cause the LED to emit light for periods longer than desired, preventing fast switching. Core-shell nanowire LEDs (NW-LEDs) are not subject to this time limitation. Therefore NW-LEDs are highly attractive, but they have not been able to gain acceptance because the technological contacting of the three-dimensional structure is complex and the industrial scalability of the production methods used is not given. Therefore, the aim of this work is to fabricate crystal structures by an industry-relevant epitaxial process, which offer the possibility of high-speed light switching and can be used relatively easy for the technological fabrication of NW-LEDs. This was achieved on the one hand by growing the crystal structures on conductive Si substrates using MOVPE, which enables simple backside contacting. On the other hand, the otherwise usual spatially random growth of nitrides on Si could be replaced by a periodically ordered growth of NW-LED crystal structures. For this purpose, a whole new method of Selective Area Epitaxy (SAE) was developed, which is based on the spatial control of the nitride crystal polarity on the Si surface. The achieved polarity- and site-controlled growth enabled the fabrication of up to 5 µm-high nanowires with coaxial LED shells, which selectively enveloped the nanowire locally in the upper part. The obtained three-dimensional epitaxial control has been explained by detailed crystal facet and parameter dependent growth models. Based on the achieved crystal structure, a relatively simple contacting technology was developed, which does not require additive electrical isolation layers, thus enabling the fabrication of NW-LED prototypes in a few technological process steps, only. Additional electro-optical characterization of the prototypes and electrical post-modelling of the measured data provided further insights into the optimizations of the developed concept and ruled out the presence of the Quantum-Confined Stark effect (radiative lifetime ≈ 500 ps). The results show that the nitride semiconductor crystal structures on Si are suitable for relatively simple device fabrication of NW-LEDs for future high-speed data communication applications.

This dissertation deals with the coupling of reinforcement learning (RL) algorithms with digital twins based on the discrete element method (DEM). These digital twins are developed to act as environments to solve RL problems of machine control and parameter optimization. Due to the remarkable performance of modern RL algorithms and the versatility of DEM simulation, the coupling of these two fields opens up possibilities for solutions to many problems of modern machines or processes. In order to achieve a suitable coupling and handle the computationally slow DEM simulations, appropriate methodologies are developed. By applying these methodologies and state-of-the-art RL algorithms to two specific applications, the applicability of the entire approach is presented. In the first application, RL is used to solve the single- and multi-actuation task of the novel peristaltic sortation machine. Therefore, a DEM based digital twin is developed to properly represent the complex interaction of the individual parts of this machine. The second application deals with the problem of the DEM input parameter optimization which is always required to research new materials are researched with the DEM. A newly developed approach to optimize the parameters using RL leads to remarkable results and lower computation times. The developed approaches and methodologies of this dissertation are generally adaptable to other problems and contribute to the usage of the combination of RL and DEM in many other research fields. Dissertation, Universität Duisburg-Essen, 2022

Non-fullerene acceptors have recently revolutionized indoor organic photovoltaics (OPVs) with power conversion efficiencies exceeding 30% in laboratory scale. Nevertheless, transferring their superior performance to larger-scale prototyping, i.e., air-processing via roll-to-roll compatible techniques, still shows severe challenges. Herein, the industrial potential of the PM6:IO4Cl blend, which is one of the most successful indoor OPV photoactive layers (PALs), is thoroughly investigated. The corresponding thick and semitransparent laminated devices are fabricated entirely in air, by blade and slot-die coating. Their current–voltage (J–V) characteristics show anomalous features depending on the illumination side, with the cathode side generally outperforming the anode counterpart. Electrical and optical modeling reveal that a plausible cause of such a phenomenon is a dead layer that forms at the PAL/anode contact interface that does not contribute to the photocurrent. Said layer becomes undetectable when the PALs are made thin enough (

In this paper, the joint effect of quantization and clipping done by the Analog-to-Digital Converter (ADC) in the receiver of a Wireless Sensor and Actuator Network (WSAN) is investigated. As an Ultra Reliable Low-Latency Communication (URLLC) system, a combination of Code Division Multiple Access (CDMA) and Orthogonal Frequency Division Multiplexing (OFDM) that uses Offset Quadrature Amplitude Modulation (OQAM) is applied. It is shown that under an industrial Non-Line-Of-Sight (NLOS) channel, CDMA-OQAM-OFDM outperforms CDMA-OFDM when both transmissions are attacked by Random Frequency Hopping Jamming (RFHJ).

This paper introduces a new mathematical procedure for the calculation of power cable ampacities in the case of water-cooled circuits. Both, internal and external cooling installations are considered. The algorithm permits a non-iterative calculation of the water temperature along the cooling length of the cables, evaluation of the heat absorbed and emitted by the cooling pipes as well as the effect of the water flow on the cable conductor temperature. Numerical examples show the effect of the direct and the indirect cooling on the ampacity of a 230 kV XLPE cable circuit.

This paper studies the disturbance observer-based adaptive fuzzy finite-time control issue of strict-feedback nonlinear systems. Specifically, to meet practical application requirement, the finite-time prescribed performance is considered, which can guarantee the tracking error enters into the prescribed bounded set in a known time. A disturbance observer is proposed to estimate the external disturbance. It is proved that the closed-loop system is semi-globally practically finite-time stable. Finally, simulation studies for a one-link manipulator are shown to verify the effectiveness of the proposed approach.

A compact planar fixed-beam leaky-wave antenna that radiates its main beam at broadside is presented, that consists of two folded branches of periodically distributed series-fed microstrip patches. The antenna is fed from the center through a 50 transmission line that subsequently feeds two constituent 100 parallel branches, each consisting of eight series-fed microstrip patches. Fixed-beam operation is achieved by the combination of the two oppositely-directed beams that are generated by the two branches. The proposed structure achieves a significant reduction of the longitudinal size by incorporating a 180 bend at the center of each branch, thus effectively folding the antenna in half. This results in a longitudinal size that is 1.8 times smaller than the analogous unfolded antenna. The antenna maintains a measured fixed-beam at broadside over a wide zero beam-squinting bandwidth of 3 GHz in the 28 GHz band, with a radiation efficiency above 60% and a maximum measured gain of 14 dBi at 27.4 GHz, with an overall compact size of 5.8 cm 1.1 cm.

Powders and their mixtures are elemental for many industries (e.g., food, pharmaceutical, mining, agricultural, and chemical). The properties of the manufactured products are often directly linked to the particle properties (e.g., particle size and shape distribution) of the utilized powder mixtures. The most straightforward approach to acquire information concerning these particle properties is image capturing. However, the analysis of the resulting images often requires manual labor and is therefore time-consuming and costly. Therefore, the work at hand evaluates the suitability of Mask R-CNN—one of the best-known deep learning architectures for object detection—for the fully automated image-based analysis of particle mixtures, by comparing it to a conventional, i.e., not machine learning-based, image analysis method, as well as the results of a trifold manual analysis. To avoid the need of a laborious manual annotation, the training data required by Mask R-CNN are produced via image synthesis. As an example for an industrially relevant particle mixture, endoscopic images from a fluid catalytic cracking reactor are used as a test case for the evaluation of the tested methods. According to the results of the evaluation, Mask R-CNN is a well-suited method for the fully automatic image-based analysis of particle mixtures. It allows for the detection and classification of particles with an accuracy of 42.7% for the utilized data, as well as the characterization of the particle shape. Also, it enables the measurement of the mixture component particle size distributions with errors (relative to the manual reference) as low as −2±5 for the geometric mean diameter and −6±5% for the geometric standard deviation of the dark particle class of the utilized data, as well as −8±4% for the geometric mean diameter and −6±2% for the geometric standard deviation of the light particle class of the utilized data. Source code, as well as training, validation, and test data publicly available.

in press Deep reinforcement learning (DRL) has been recognized as an efficient technique to design optimal strategies for different complex systems without prior knowledge of the control landscape. To achieve a fast and precise control for quantum systems, we propose a novel DRL approach by constructing a curriculum consisting of a set of intermediate tasks defined by fidelity thresholds, where the tasks among a curriculum can be statically determined before the learning process or dynamically generated during the learning process. By transferring knowledge between two successive tasks and sequencing tasks according to their difficulties, the proposed curriculum-based DRL (CDRL) method enables the agent to focus on easy tasks in the early stage, then move onto difficult tasks, and eventually approaches the final task. Numerical comparison with the traditional methods [gradient method (GD), genetic algorithm (GA), and several other DRL methods] demonstrates that CDRL exhibits improved control performance for quantum systems and also provides an efficient way to identify optimal strategies with few control pulses.

High-speed detection and identification of mobile terminals located in the vicinity of highly directive base stations is essential for future mm-wave communication systems. We propose a novel optoelectronic frequency modulated continuous wave (FMCW) radar system for detection, localization and identification of multiple mobile terminals. The simultaneous localization and identification of multiple mobile terminals is achieved by using frequency scanning mm-wave leaky-wave antennas (LWAs) and backscattering communications. LWAs provide RF-based beam steering for estimating the direction of arrival of the echoes using a FMCW radar signal. Additionally, the implementation of backscattering technology in the mobile terminals allows the identification of users. Hence, simultaneous user localization and identification without the use of any complicated radar signal post-processing algorithms is possible. Finally, the introduced modulated backscattering reflection shifts the signals of the targets at higher frequencies, which exhibit lower noise floor and thus have higher signal to noise ratio (SNR). CA extern

Sensors are the key elements for capturing environmental properties and are increasingly important in the industry for the intelligent control of industrial processes. While in many everyday objects highly integrated sensor systems are already state of the art, the situation in an industrial environment is clearly different. Frequently, the use of sensor systems is impossible, because the extreme ambient conditions of industrial processes like high operating temperatures or strong mechanical load do not allow the reliable operation of sensitive electronic components. Fraunhofer is running the Lighthouse Project “eHarsh” to overcome this hurdle. In the course of the project, an integrated sensor readout electronic has been realized based on a set of three chips. A dedicated sensor fron-tend provides the analog sensor interface for resistive sensors typically arranged in a Wheatstone configuration. Furthermore, the chipset includes a 32-bit microcontroller for signal conditioning and sensor control. Finally, it comprises an interface chip including a bus transceiver and voltage regulators. The chipset has been realized in a high-temperature 0.35-micron SOI-CMOS technology focusing operating temperatures up to 300°C. The chipset is assembled on a multilayer ceramic low-temperature cofired ceramics (LTCC) board using flip chip technology. The ceramic board consists of four layers with a total thickness of approximately 0.9 mm. The internal wiring is based on silver paste while the external contacts were alternatively manufactured in silver (sintering/soldering) or in gold alloys (wire bonding). As an interconnection technology, silver sintering has been applied. It has already been shown that a significant increase in lifetime can be reached by using silver sintering for die attach applications. Using silver sintering for flip chip technology is a new and challenging approach. By adjusting the process parameter geared to the chipset design and the design of the ceramic board high-quality flip chip interconnects can be generated.

Solid-state electrolytes such as tantalum (Ta)- and aluminum (Al)-substituted Li7La3Zr2O12 (LLZO) are seen as the key component for the next generation of mainstream battery technology. However, this development often lacks specific information on decisive material parameters. Therefore, this work experimentally investigates the thermal material parameters such as the thermal conductivity (kappa) and the specific heat capacity (C-p) of LLZO between room temperature and 1225 K using laser flash analysis (LFA) and differential scanning calorimetry (DSC). The DSC measurements reveal a C-p of 0.55-0.80 J g(-1) K-1. Furthermore, a decomposition of the cubic LLZO phase to pyrochlore La2Zr2O7 is detected between 1500 K and 1750 K, which is substantiated by Raman- and SEM-analysis. The impact of the grain size on kappa is also considered, as the Al-substitution leads to the formation of significantly larger grain sizes compared to a Ta-substitution. The LFA measurements yield a relatively constant kappa between 1.45-1.55 W m(-1) K-1 for both materials and grain sizes, which is the consequence of a phonon mean free path in the range of the interatomic distance of the LLZO crystal. This implies that phonon scattering at grain boundaries is negligible and the main scattering occurs at inhomogeneities in the crystal lattice.

OA Förderung 2022 With the increase in potential uses of terahertz technology, the need for terahertz transceivers with application-oriented adaptive radiation patterns has emerged. Reconfigurable reflectarrays consisting of actuated sub-wavelength reflectors have been successfully used for terahertz beam steering and beamforming. They do not require a complex feeding network and associated electronics, enabling a compact and power-efficient terahertz beam steering system. However, the current reflectarray-based beam steering is accomplished by forming the reflectarray as a grating structure, which is accompanied by the problems such as grating lobes, limited steering range, and discrete steering angles. Here, we configure a MEMS-based reflectarray with the genetic algorithm to eliminate the grating lobes and open up the possibility of customizing its radiation pattern. We used single- and multi-objective optimization to find the optimal height profile of the reflectarray and verified the results by full-wave electromagnetic simulations. We measured the radiation patterns of four reflectarray phantoms, i.e. reflectarrays without the MEMS actuation systems. The measurement results agree well with the calculated ones, with the main beam deviating at most 2 degrees from the target direction. Our work demonstrates how a genetic algorithm is used to shape a reconfigurable terahertz reflectarray to eliminate the grating lobes and tailor some specific featuress in its radiation pattern.

This paper proposes a novel deep learning architecture for estimating the remaining useful lifetime (RUL) of industrial components, which solely relies on the recently developed transformer architectures. The RUL estimation resorts to analysing degradation patterns within multivariate time series signals. Hence, we propose a novel shared temporal attention block that allows detecting RUL patterns with the progress of time. Furthermore, we develop a split-feature attention block that enables attending to features from different sensor channels. The proposed shared temporal attention layer in the encoder fulfils the goal of attending to temporal degradation patterns in the individual sensor signals before creating a shared correlation across the feature range. We develop two transformer architectures that are specifically designed to operate with multivariate time series data based on these novel attention blocks. We apply the architectures to the well known C-MAPSS benchmark dataset and provide various hyperparameter studies to analyse their impact on the performance. In addition, we provide a thorough comparison with recently presented state-of-the-art approaches and show that the proposed transformer architectures outperform the existing methods by a considerable margin. CA extern

Atomistic details about the hydration of ions in aqueous solutions are still debated due to the disordered and statistical nature of the hydration process. However, many processes from biology, physical chemistry to materials sciences rely on the complex interplay between solute and solvent. Oxygen K-edge X-ray excitation spectra provide a sensitive probe of the local atomic and electronic surrounding of the excited sites. We used ab initio molecular dynamics simulations together with extensive spectrum calculations to relate the features found in experimental oxygen K-edge spectra of a concentration series of aqueous NaCl with the induced structural changes upon solvation of the salt and distill the spectral fingerprints of the first hydration shells around the Na+- and Cl--ions. By this combined experimental and theoretical approach, we find the strongest spectral changes to indeed result from the first hydration shells of both ions and relate the observed shift of spectral weight from the post- to the main-edge to the origin of the post-edge as a shape resonance.

Terahertz time-domain spectroscopy enables the extraction of electrical properties from materials. An extraction of the complex permittivity can be carried out with measurements in transmission or reflection geometry enabling the identification of materials. To perform an exact identification, the sample thickness, and the angle of incidence of the terahertz radiation must be known. However, when those parameters are unknown and additionally the materials show strong absorbances, a precise differentiation between materials is challenging. A promising approach is the use of a neural network for automated material classification of terahertz images from different materials. Here, we show that a trained neural network can differentiate between 16 3D printed dielectric materials with a high accuracy of 98 % from measurements taken in transmission mode. For unknown thicknesses, the accuracy is reduced to 35 %. As the constitution of the dataset has a big impact on the accuracy, various data preparations were investigated as well as the number of traces needed for achieving a well-trained network was determined. Finally, the trained neural network was evaluated with different sample thicknesses, revealing the huge impact of the materials absorbance on the extrapolation ability. This approach can be used in security application to classify harmful substances as well as for the automated generation of material maps.

Der Sammelband dokumentiert die Beiträge der 31. Fachtagung der Bundesarbeitsgemeinschaften für Berufsbildung in den Fachrichtungen Elektro-, Informations-, Metall- und Fahrzeugtechnik. Unter dem Motto „ALL DAYS FOR FUTURE' werden betriebliche Anforderungen an die gewerblich-technische Berufsschulbildung um die Themen Digitalisierung und Nachhaltigkeit erweitert. Die Berufsbildung muss die Auszubildenden in Zeiten von Energiekrise, Klimawandel und Artensterben sowie der Digitalisierung der Arbeitswelt und Gesellschaft durch neue hybride Lehr-/Lernarrangements auf ein nachhaltiges Berufshandeln vorbereiten. In den Beiträgen dieses Bandes werden Fragen der Veränderungen von Aus- und Weiterbildung, der Fachkräftesicherung, der Schulorganisation, der Ausstattung und des Unterrichts sowie der Vernetzung beruflicher Ausbildungsangebote werden ebenso thematisiert wie die Neuordnung der IT-Berufe.

This paper presents a dataset containing recordings of the electroencephalogram (EEG) and the electromyogram (EMG) from eight subjects who were assisted in moving their right arm by an active orthosis device. The supported movements were elbow joint movements, i.e., flexion and extension of the right arm. While the orthosis was actively moving the subject's arm, some errors were deliberately introduced for a short duration of time. During this time, the orthosis moved in the opposite direction. In this paper, we explain the experimental setup and present some behavioral analyses across all subjects. Additionally, we present an average event-related potential analysis for one subject to offer insights into the data quality and the EEG activity caused by the error introduction. The dataset described herein is openly accessible. The aim of this study was to provide a dataset to the research community, particularly for the development of new methods in the asynchronous detection of erroneous events from the EEG. We are especially interested in the tactile and haptic-mediated recognition of errors, which has not yet been sufficiently investigated in the literature. We hope that the detailed description of the orthosis and the experiment will enable its reproduction and facilitate a systematic investigation of the influencing factors in the detection of erroneous behavior of assistive systems by a large community., Comment: Revised references to our datasets, general corrections to typos, and latex template format changes, Overall Content unchanged

Terahertz time-domain spectroscopy (THz-TDS) is a promising tool for high-resolution 3D imaging of objects due to the high center frequency and bandwidth compared to microwave systems. In addition, terahertz waves have a higher penetration depth than visible or near-infrared radiation. Typically, optics are used to focus the terahertz radiation onto an object under test. This limits the imaging capability in the axial dimension to the depth of field and limits simple imaging of complex surfaces. In this work, we adapt a backpropagation algorithm from synthetic aperture radar (SAR) imaging to reconstruct high-resolution 3D images from time-domain traces acquired with a lensless THz-TDS system. For this purpose, an inverse cylindrical aperture is used and an equation that describes the maximum achievable resolution as a function of the beam pattern, the bandwidth, and the length of the synthetic aperture is derived. The calculated resolution is 960 μ m for the linear dimension of the aperture and 75 μ m for the rotationally symmetric dimension of the cylindrical aperture for a bandwidth of 2 THz. The resolving power is verified by measurements on metallic and dielectric objects. In the future, this method can be used for non-destructive testing of objects with complex shaped surfaces and internal structures. CA Kubiczek

PurposeThe best algorithm that was implemented on this Brazilian dataset was artificial immune system (AIS) algorithm. But the time and cost of this algorithm are high. Using asexual reproduction optimization (ARO) algorithm, the authors achieved better results in less time. So the authors achieved less cost in a shorter time. Their framework addressed the problems such as high costs and training time in credit card fraud detection. This simple and effective approach has achieved better results than the best techniques implemented on our dataset so far. The purpose of this paper is to detect credit card fraud using ARO.Design/methodology/approachIn this paper, the authors used ARO algorithm to classify the bank transactions into fraud and legitimate. ARO is taken from asexual reproduction. Asexual reproduction refers to a kind of production in which one parent produces offspring identical to herself. In ARO algorithm, an individual is shown by a vector of variables. Each variable is considered as a chromosome. A binary string represents a chromosome consisted of genes. It is supposed that every generated answer exists in the environment, and because of limited resources, only the best solution can remain alive. The algorithm starts with a random individual in the answer scope. This parent reproduces the offspring named bud. Either the parent or the offspring can survive. In this competition, the one which outperforms in fitness function remains alive. If the offspring has suitable performance, it will be the next parent, and the current parent becomes obsolete. Otherwise, the offspring perishes, and the present parent survives. The algorithm recurs until the stop condition occurs.FindingsResults showed that ARO had increased the AUC (i.e. area under a receiver operating characteristic (ROC) curve), sensitivity, precision, specificity and accuracy by 13%, 25%, 56%, 3% and 3%, in comparison with AIS, respectively. The authors achieved a high precision value indicating that if ARO detects a record as a fraud, with a high probability, it is a fraud one. Supporting a real-time fraud detection system is another vital issue. ARO outperforms AIS not only in the mentioned criteria, but also decreases the training time by 75% in comparison with the AIS, which is a significant figure.Originality/valueIn this paper, the authors implemented the ARO in credit card fraud detection. The authors compared the results with those of the AIS, which was one of the best methods ever implemented on the benchmark dataset. The chief focus of the fraud detection studies is finding the algorithms that can detect legal transactions from the fraudulent ones with high detection accuracy in the shortest time and at a low cost. That ARO meets all these demands.

In dieser Arbeit werden kompakte Induktionsspulen als berührungslose elektroma- gnetische Ultraschallwandler (EMATs) ohne zusätzliche Magnete untersucht. Im Vergleich dazu sind klassische, kommerziell verfügbare EMATs auf die Verwendung von voluminösen Permanentmagneten oder separaten Elektromagneten angewiesen. Die Vorteile der EMATs ohne zusätzliche Magnete sind höhere magnetische Flussdichten lokal am Wirkungsort, keine störende Anziehung von ferromagnetischen Fremdobjekten und deutlich kleinere Sensorköpfe, was eine wichtige Voraussetzung für die Herstellung von kompakten EMAT-Phased-Arrays ist. Die Umsetzung solcher EMATs stellt eine Herausforderung dar, weil die Elektronik für die Ultraschallerzeugung mit Spannungen und Strömen im kV- und kA-Bereich umgehen muss. Aufgrund des bei EMATs generell geringen Wirkungsgrads müssen beim Ultraschallempfang Signale im unteren µV-Bereich detektiert werden. Gleichzeitig dürfen keine Störungen durch die impulsartigen kA-Ströme entstehen und die relativ kleinen EMAT-Induktoren, die als Sensorköpfe dienen, müssen den oft wiederholten kA-Impulsen standhalten. Für die Auslegung von EMATs ohne zusätzliche Magnete werden Modellbildungen für die Magnetfeld- und Schallfeldberechnung gezeigt. Als Demonstrationsszenario wird eine 3D-Lokalisierung einer Inhomogenität im Inneren eines mit Flüssigkeit gefüllten dickwandigen Metallbehälters ohne mechanischen Kontakt zum Behälter (1 mm Luftspalt) erfolgreich durchgeführt. Weiterhin wird eine berührungslose Kantenabtastung einer ferromagnetischen Stahlplatte mit unidirektionalen Lamb-Wellen präsentiert. Die Lamb-Wellen werden mit kontrollierten Interferenzeffekten unidirektional ausgesendet und empfangen. Der kompakte Aufbau des phasengenauen Doppel-EMATs bestätigt die Machbarkeit von Phased-Arrays. Des Weiteren wird gezeigt, wie der Ultraschallempfang mit einem EMAT auf einem ferromagnetischen Prüfkörper ohne eine aktive Magnetisierung (Bias-Magnetfeld) möglich ist. Somit wird die Problematik des zeitlich begrenzten (µs-Bereich) Bias-Magnetfeldes gelöst, wodurch sich deutlich längere (ms- bis s-Bereich) Empfangszeitfenster realisieren lassen. Ohne die Verwendung einer aktiven Magnetisierung entfallen auch Probleme wie das Auftreten von Barkhausenrauschen oder Signalstörungen durch Schaltvorgänge von Dioden zum Schutz vor Polaritätsumkehr der Elektrolytkondensatorbänke. Es entstehen mehr Freiheitsgrade, wodurch neuartige EMAT-Konzepte vorstellbar sind, die flächige Induktoren und Ferritrückplatten mit hohen relativen Permeabilitätszahlen verwenden. Dissertation, Universität Duisburg-Essen, 2023