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BaTiO3 dotiert mit 3d-Ionen: Valenzen, Leerstellen und ihre Auswirkungen. Hagemann, H. J.; Ihrig, H.
(1980)
In the future, we expect manufacturing companies to follow a new paradigm that mandates more automation and autonomy in production processes. Such smart factories will offer a variety of production technologies as services that can be combined ad hoc to produce a large number of different product types and variants cost-effectively even in small lot sizes. This is enabled by cyber-physical systems that feature flexible automated planning methods for production scheduling, execution control, and in-factory logistics.
During development, testbeds are required to determine the applicability of integrated systems in such scenarios. Furthermore, benchmarks are needed to quantify and compare system performance in these industry-inspired scenarios at a comprehensible and manageable size which is, at the same time, complex enough to yield meaningful results.
In this chapter, based on our experience in the RoboCup Logistics League (RCLL) as a specific example, we derive a generic blueprint for how a holistic benchmark can be developed, which combines a specific scenario with a set of key performance indicators as metrics to evaluate the overall integrated system and its components.
Benchmarking of various LiDAR sensors for use in self-driving vehicles in real-world environments
(2022)
Abstract
In this paper, we report on our benchmark results of the LiDAR sensors Livox Horizon, Robosense M1, Blickfeld Cube, Blickfeld Cube Range, Velodyne Velarray H800, and Innoviz Pro. The idea was to test the sensors in different typical scenarios that were defined with real-world use cases in mind, in order to find a sensor that meet the requirements of self-driving vehicles. For this, we defined static and dynamic benchmark scenarios. In the static scenarios, both LiDAR and the detection target do not move during the measurement. In dynamic scenarios, the LiDAR sensor was mounted on the vehicle which was driving toward the detection target. We tested all mentioned LiDAR sensors in both scenarios, show the results regarding the detection accuracy of the targets, and discuss their usefulness for deployment in self-driving cars.
In the context of the increasing digitalization, the Internet of Things (IoT) is seen as a technological driver through which completely new business models can emerge in the interaction of different players. Identified key players include traditional industrial companies, municipalities and telecommunications companies. The latter, by providing connectivity, ensure that small devices with tiny batteries can be connected almost anywhere and directly to the Internet. There are already many IoT use cases on the market that provide simplification for end users, such as Philips Hue Tap. In addition to business models based on connectivity, there is great potential for information-driven business models that can support or enhance existing business models. One example is the IoT use case Park and Joy, which uses sensors to connect parking spaces and inform drivers about available parking spaces in real time. Information-driven business models can be based on data generated in IoT use cases. For example, a telecommunications company can add value by deriving more decision-relevant information – called insights – from data that is used to increase decision agility. In addition, insights can be monetized. The monetization of insights can only be sustainable, if careful attention is taken and frameworks are considered. In this chapter, the concept of information-driven business models is explained and illustrated with the concrete use case Park and Joy. In addition, the benefits, risks and framework conditions are discussed.
Benutzerzentrierte Entwicklung mobiler Unternehmenssoftware, Teil 2 : die Iterative Entwicklung
(2008)
Um die Forschungsdatenmanagement-Plattform Coscine optimal für Forschungsprojekte nutzen zu können, ist es sinnvoll, einige Fragen im Vorhinein zu klären. So können aufwendige Änderungen der Datenverwaltung im Nachhinein vermieden werden. Hierzu bietet die Handreichung hilfreiche Leitfragen und Erläuterungen für Forschende und FDM-Service-Personal an HAW in NRW (DH.NRW-Hochschulen).
FDM-Service-Mitarbeitende können die Handreichung in ihrer Beratung zu Coscine einsetzen und mit der Eingabemaske in der Kopfzeile des Dokuments auf ihre Hochschule anpassen.
Die Erfindung betrifft ein Bussystem enthaltend Busleitungen, an denen eine Anzahl von Busteilnehmern über einen Transceiver anschließbar sind, wobei der Transceiver eine bidirektionale Kommunikation zwischen mindestens zwei Busteilnehmern bewirkt, wobei auf einer busabgewandten Seite des Transceivers sich an denselben eine Zwischenbrückeneinheit anschließt, die mindestens zwei Sender-/Empfänger-Paare enthaltend jeweils einen Sender und einen Empfänger aufweist, wobei der Sender einen Senderoszillator, eine Amplituden- und/oder Phasen- und/oder Frequenzmodulator sowie eine Antenne aufweist und wobei der Empfänger einen Mischer aufweisenden Demodulator sowie eine Antenne aufweist, wobei ein erstes Sender-/Empfänger-Paar über eine Funkschnittstelle mit dem zweiten Sender-/Empfänger-Paar miteinander gekoppelt sind.
In this paper we present CAESAR, an intelligent domestic service robot. In domestic settings for service robots complex tasks have to be accomplished. Those tasks benefit from deliberation, from robust action execution and from flexible methods for human–robot interaction that account for qualitative notions used in natural language as well as human fallibility. Our robot CAESAR deploys AI techniques on several levels of its system architecture. On the low-level side, system modules for localization or navigation make, for instance, use of path-planning methods, heuristic search, and Bayesian filters. For face recognition and human–machine interaction, random trees and well-known methods from natural language processing are deployed. For deliberation, we use the robot programming and plan language READYLOG, which was developed for the high-level control of agents and robots; it allows combining programming the behaviour using planning to find a course of action. READYLOG is a variant of the robot programming language Golog. We extended READYLOG to be able to cope with qualitative notions of space frequently used by humans, such as “near” and “far”. This facilitates human–robot interaction by bridging the gap between human natural language and the numerical values needed by the robot. Further, we use READYLOG to increase the flexible interpretation of human commands with decision-theoretic planning. We give an overview of the different methods deployed in CAESAR and show the applicability of a system equipped with these AI techniques in domestic service robotics
Calibration of a Network Analyzer Without a Thru Connection for Nonlinear and Multiport Measurements
(2008)
Calibration procedures with series impedances and unknown lines simplify on-wafer measurements
(1999)
This paper describes the development of a capacitively coupled high-pressure lamp with input power between 20 and 43 W at 2.45 GHz, using a coaxial line network. Compared with other electrodeless lamp systems, no cavity has to be used and a reduction in the input power is achieved. Therefore, this lamp is an alternative to the halogen incandescent lamp for domestic lighting. To serve the demands of domestic lighting, the filling of the lamp is optimized over all other resulting requirements, such as high efficacy at low induced powers and fast startups. A workflow to develop RF-driven plasma applications is presented, which makes use of the hot S-parameter technique. Descriptions of the fitting process inside a circuit and FEM simulator are given. Results of the combined ignition and operation network from simulations and measurements are compared. An initial prototype is built and measurements of the lamp's lighting properties are presented along with an investigation of the efficacy optimizations using large signal amplitude modulation. With this lamp, an efficacy of 135 lmW -1 is achieved.
Objectives
Interest in cardiovascular magnetic resonance (CMR) at 7 T is motivated by the expected increase in spatial and temporal resolution, but the method is technically challenging. We examined the feasibility of cardiac chamber quantification at 7 T.
Methods
A stack of short axes covering the left ventricle was obtained in nine healthy male volunteers. At 1.5 T, steady-state free precession (SSFP) and fast gradient echo (FGRE) cine imaging with 7 mm slice thickness (STH) were used. At 7 T, FGRE with 7 mm and 4 mm STH were applied. End-diastolic volume, end-systolic volume, ejection fraction and mass were calculated.
Results
All 7 T examinations provided excellent blood/myocardium contrast for all slice directions. No significant difference was found regarding ejection fraction and cardiac volumes between SSFP at 1.5 T and FGRE at 7 T, while volumes obtained from FGRE at 1.5 T were underestimated. Cardiac mass derived from FGRE at 1.5 and 7 T was larger than obtained from SSFP at 1.5 T. Agreement of volumes and mass between SSFP at 1.5 T and FGRE improved for FGRE at 7 T when combined with an STH reduction to 4 mm.
Conclusions
This pilot study demonstrates that cardiac chamber quantification at 7 T using FGRE is feasible and agrees closely with SSFP at 1.5 T.
With its need for high SNR and short acquisition times, Cardiac MRI (CMR) is an intriguing target application for ultrahigh field MRI. Due to the sheer size of the upper torso, however, the known RF issues of 7T MRI are also most prominent in CMR. Recent years brought substantial progress but the full potential of the ultrahigh field for CMR is yet to be exploited. Parallel transmission (pTx) is a promising approach in this context and several groups have already reported B1 shimming for 7T CMR. In such a static pTx application amplitudes and phases of all Tx channels are adjusted individually but otherwise imaging techniques established in current clinical practice 1.5 T and 3 T are applied. More advanced forms of pTx as spatially selective excitation (SSE) using Transmit SENSE promise additional benefits like faster imaging with reduced fields of view or improved SAR control. SSE requires the full dynamic capabilities of pTx, however, and for the majority of today's implemented pTx hardware the internal synchronization of the Tx array does not easily permit external triggering as needed for CMR. Here we report a software solution to this problem and demonstrate the feasibility of CINE CMR at 7 T using a Tx array.
The assessment of the right ventricle (RV) is a challenge in today's cardiology, but of growing clinical impact regarding patient prognosis in different cardiac diseases. The detection and differentiation of small wall motion abnormalities may help to enhance the differentiation of cardiomyopathies including Arrhythmogenic Rightventricular Cardiomyopathy. Cardiovascular magnetic resonance (CMR) at 1.5T is the accepted gold standard for RV quantification. The higher spatial resolution achievable at ultrahigh field strength (UHF) offers the potential to gain new insights into the structure and function of the RV. To approach this goal accurate RV chamber quantification at 7T has to be proven. Consequently this study examines the feasibility of assessment of RV dimensions and function at 7T using improved spatial resolution enabled by the intrinsic sensitivity gain of UHF CMR. For this purpose, a dedicated 16 channel TX/RX RF coil array is used together with 2D CINE fast gradient echo (FGRE) imaging. For comparison RV chamber quantification is conducted at 1.5T using a SSFP based state of the art clinical protocol.
Today, the assembly of laser systems requires a large share of manual operations due to its complexity regarding the optimal alignment of optics. Although the feasibility of automated alignment of laser optics has been shown in research labs, the development effort for the automation of assembly does not meet economic requirements – especially for low-volume laser production. This paper presents a model-based and sensor-integrated assembly execution approach for flexible assembly cells consisting of a macro-positioner covering a large workspace and a compact micromanipulator with camera attached to the positioner. In order to make full use of available models from computer-aided design (CAD) and optical simulation, sensor systems at different levels of accuracy are used for matching perceived information with model data. This approach is named "chain of refined perception", and it allows for automated planning of complex assembly tasks along all major phases of assembly such as collision-free path planning, part feeding, and active and passive alignment. The focus of the paper is put on the in-process image-based metrology and information extraction used for identifying and calibrating local coordinate systems as well as the exploitation of that information for a part feeding process for micro-optics. Results will be presented regarding the processes of automated calibration of the robot camera as well as the local coordinate systems of part feeding area and robot base.
High-intensity discharge lamps can be driven by radio-frequency signals in the ISM frequency band at 2.45 GHz, using a matching network to transform the impedance of the plasma to the source impedance. To achieve an optimal operating condition, a good characterization of the lamp in terms of radio frequency equivalent circuits under operating conditions is necessary, enabling the design of an efficient matching network. This paper presents the characterization technique for such lamps and presents the design of the required matching network. For the characterization, a high-intensity discharge lamp was driven by a monofrequent large signal at 2.45 GHz, whereas a frequency sweep over 300 MHz was performed across this signal to measure so-called small-signal hot S-parameters using a vector network analyzer. These parameters are then used as an equivalent load in a circuit simulator to design an appropriate matching network. Using the measured data as a black-box model in the simulation results in a quick and efficient method to simulate and design efficient matching networks in spite of the complex plasma behavior. Furthermore, photometric analysis of high-intensity discharge lamps are carried out, comparing microwave operation to conventional operation.
In this paper we report on CO2 Meter, a do-it-yourself carbon dioxide measuring device for the classroom. Part of the current measures for dealing with the SARS-CoV-2 pandemic is proper ventilation in indoor settings. This is especially important in schools with students coming back to the classroom even with high incidents rates. Static ventilation patterns do not consider the individual situation for a particular class. Influencing factors like the type of activity, the physical structure or the room occupancy are not incorporated. Also, existing devices are rather expensive and often provide only limited information and only locally without any networking. This leaves the potential of analysing the situation across different settings untapped. Carbon dioxide level can be used as an indicator of air quality, in general, and of aerosol load in particular. Since, according to the latest findings, SARS-CoV-2 can be transmitted primarily in the form of aerosols, carbon dioxide may be used as a proxy for the risk of a virus infection. Hence, schools could improve the indoor air quality and potentially reduce the infection risk if they actually had measuring devices available in the classroom. Our device supports schools in ventilation and it allows for collecting data over the Internet to enable a detailed data analysis and model generation. First deployments in schools at different levels were received very positively. A pilot installation with a larger data collection and analysis is underway.
To maximize the travel distances of battery electric vehicles such as cars or buses for a given amount of stored energy, their powertrains are optimized energetically. One key part within optimization models for electric powertrains is the efficiency map of the electric motor. The underlying function is usually highly nonlinear and nonconvex and leads to major challenges within a global optimization process. To enable faster solution times, one possibility is the usage of piecewise linearization techniques to approximate the nonlinear efficiency map with linear constraints. Therefore, we evaluate the influence of different piecewise linearization modeling techniques on the overall solution process and compare the solution time and accuracy for methods with and without explicitly used binary variables.
Es existieren verschiedenste Arten von Spielen, die versuchen, die Motivation einer Spielsituation in einen ernsten Kontext zu überführen. In diesem Artikel wird der Überbegriff „Competence Developing Games“ definiert und anhand von Beispielen erläutert. Dafür werden Erkennungskriterien vorgestellt, entsprechende Spieltypen erläutert und eine Zuordnung durch-geführt.
The Robot Operating System (ROS) is the current de-facto standard in robot middlewares. The steadily increasing size of the user base results in a greater demand for training as well. User groups range from students in academia to industry professionals with a broad spectrum of developers in between. To deliver high quality training and education to any of these audiences, educators need to tailor individual curricula for any such training. In this paper, we present an approach to ease compiling curricula for ROS trainings based on a taxonomy of the teaching contents. The instructor can select a set of dedicated learning units and the system will automatically compile the teaching material based on the dependencies of the units selected and a set of parameters for a particular training. We walk through an example training to illustrate our work.
Computer Supported Communication and Cooperation – Making Information Aware / Luczak, H. ; Wolf, M.
(1999)
In: Unterrichtsblätter / Deutsche Telekom AG. 54. 2001. 7. S. 410-420 (11 S. ) Angesichts der zunehmenden Globalisierung von Informationen und Informationsdiensten können Inhalte (Contents) für mehrere unterschiedliche Dienste genutzt und auf verschiedenen Endgeräten ausgegeben werden. Hier setzt ein Content-Management-System (CMS) an, welches sowohl für die Kunden als auch für die Anbieter der unterschiedlich distribuierten Dienste Synergien und somit Einsparpotenziale bietet. Darüber hinaus werden für die Anbieter dieser Dienste durch die allgemeine Definition von Leistungstools und die Definition von Wertschöpfungsketten künftige Produktentwicklungen vereinheitlicht und optimiert werden. Mit der Entwicklung und Vertriebsfreigabe immer weiterer Informationsdienste, die von verschiedenen Dienste-Providern betrieben werden, ist der Bedarf an einer Koordinierung der Entwicklungen und Investitionen im Bereich der Content-Akquisition und des Content-Management (CM) bedeutend angestiegen. Neben Akquisition, lizenzrechtlichen Fragen und Verwaltung des im Rahmen von Diensten angebotenen Content rücken vor allem auch Fragen der Gestaltung von Content-Management-Plattformen (CMP) immer stärker in den Blickpunkt. Der Beitrag stellt die globalen Ergebnisse dar, die in einem Forschungs- und Entwicklungsauftrag des Zentralbereichs Innovationsmanagement der Deutschen Telekom zu diesem Thema ermittelt wurden. Es werden die Kernmodule für eine Content- Management-Plattform beschrieben, die die Anforderungen an die Bereitstellung vielfältiger Content-Angebote erfüllt. Die folgenden Themen werden behandelt: + Begriffsbestimmung, + Content- und Dienste-Portfolio, + Standard Content-Prozess, + synergetische Content-Plattform (sCP), + Modelle der sCP, + Aspekte beim Betrieb und + Nutzen eines Content-Management.
In this chapter, we report on our activities to create and maintain a fleet of autonomous load haul dump (LHD) vehicles for mining operations. The ever increasing demand for sustainable solutions and economic pressure causes innovation in the mining industry just like in any other branch. In this chapter, we present our approach to create a fleet of autonomous special purpose vehicles and to control these vehicles in mining operations. After an initial exploration of the site we deploy the fleet. Every vehicle is running an instance of our ROS 2-based architecture. The fleet is then controlled with a dedicated planning module. We also use continuous environment monitoring to implement a life-long mapping approach. In our experiments, we show that a combination of synthetic, augmented and real training data improves our classifier based on the deep learning network Yolo v5 to detect our vehicles, persons and navigation beacons. The classifier was successfully installed on the NVidia AGX-Drive platform, so that the abovementioned objects can be recognised during the dumper drive. The 3D poses of the detected beacons are assigned to lanelets and transferred to an existing map.
Objective
This study assesses and quantifies impairment of postoperative magnetic resonance imaging (MRI) at 7 Tesla (T) after implantation of titanium cranial fixation plates (CFPs) for neurosurgical bone flap fixation.
Materials and methods
The study group comprised five patients who were intra-individually examined with 3 and 7 T MRI preoperatively and postoperatively (within 72 h/3 months) after implantation of CFPs. Acquired sequences included T₁-weighted magnetization-prepared rapid-acquisition gradient-echo (MPRAGE), T₂-weighted turbo-spin-echo (TSE) imaging, and susceptibility-weighted imaging (SWI). Two experienced neurosurgeons and a neuroradiologist rated image quality and the presence of artifacts in consensus reading.
Results
Minor artifacts occurred around the CFPs in MPRAGE and T2 TSE at both field strengths, with no significant differences between 3 and 7 T. In SWI, artifacts were accentuated in the early postoperative scans at both field strengths due to intracranial air and hemorrhagic remnants. After resorption, the brain tissue directly adjacent to skull bone could still be assessed. Image quality after 3 months was equal to the preoperative examinations at 3 and 7 T.
Conclusion
Image quality after CFP implantation was not significantly impaired in 7 T MRI, and artifacts were comparable to those in 3 T MRI.
Cyber-physical systems are ever more common in manufacturing industries. Increasing their autonomy has been declared an explicit goal, for example, as part of the Industry 4.0 vision. To achieve this system intelligence, principled and software-driven methods are required to analyze sensing data, make goal-directed decisions, and eventually execute and monitor chosen tasks. In this chapter, we present a number of knowledge-based approaches to these problems and case studies with in-depth evaluation results of several different implementations for groups of autonomous mobile robots performing in-house logistics in a smart factory. We focus on knowledge-based systems because besides providing expressive languages and capable reasoning techniques, they also allow for explaining how a particular sequence of actions came about, for example, in the case of a failure.
This paper introduces a Competence Developing Game (CDG) for the purpose of a cybersecurity awareness training for businesses. The target audience will be discussed in detail to understand their requirements. It will be explained why and how a mix of business simulation and serious game meets these stakeholder requirements. It will be shown that a tablet and touchscreen based approach is the most suitable solution. In addition, an empirical study will be briefly presented. The study was carried out to examine how an interaction system for a 3D-tablet based CDG has to be designed, to be manageable for non-game experienced employees. Furthermore, it will be explained which serious content is necessary for a Cybersecurity awareness training CDG and how this content is wrapped in the game
Das Ich ist eine Illusion
(1990)
In this paper we present an extension of the action language Golog that allows for using fuzzy notions in non-deterministic argument choices and the reward function in decision-theoretic planning. Often, in decision-theoretic planning, it is cumbersome to specify the set of values to pick from in the non-deterministic-choice-of-argument statement. Also, even for domain experts, it is not always easy to specify a reward function. Instead of providing a finite domain for values in the non-deterministic-choice-of-argument statement in Golog, we now allow for stating the argument domain by simply providing a formula over linguistic terms and fuzzy uents. In Golog’s forward-search DT planning algorithm, these formulas are evaluated in order to find the agent’s optimal policy. We illustrate this in the Diner Domain where the agent needs to calculate the optimal serving order.