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K3 User Guide
(2000)
his report summarizes the results of a workshop on Groupware related task design which took place at the International Conference on Supporting Group Work Group'99, Arizona, from 14 th to 17 th November 1999.
The workshop was addressed to people from different
viewpoints, backgrounds, and domains:
- Researchers dealing with questions of task analysis
and task modeling for Groupware application from an
academic point of view. They may contribute modelbased design
approaches or theoretically oriented
work
- Practitioners with experience in the design and
everyday use of groupware systems. They might refer
to the practical side of the topic: "real" tasks, "real"
problems, "real" users, etc.
In this paper, the use of reinforcement learning (RL) in control systems is investigated using a rotatory inverted pendulum as an example. The control behavior of an RL controller is compared to that of traditional LQR and MPC controllers. This is done by evaluating their behavior under optimal conditions, their disturbance behavior, their robustness and their development process. All the investigated controllers are developed using MATLAB and the Simulink simulation environment and later deployed to a real pendulum model powered by a Raspberry Pi. The RL algorithm used is Proximal Policy Optimization (PPO). The LQR controller exhibits an easy development process, an average to good control behavior and average to good robustness. A linear MPC controller could show excellent results under optimal operating conditions. However, when subjected to disturbances or deviations from the equilibrium point, it showed poor performance and sometimes instable behavior. Employing a nonlinear MPC Controller in real time was not possible due to the high computational effort involved. The RL controller exhibits by far the most versatile and robust control behavior. When operated in the simulation environment, it achieved a high control accuracy. When employed in the real system, however, it only shows average accuracy and a significantly greater performance loss compared to the simulation than the traditional controllers. With MATLAB, it is not yet possible to directly post-train the RL controller on the Raspberry Pi, which is an obstacle to the practical application of RL in a prototyping or teaching setting. Nevertheless, RL in general proves to be a flexible and powerful control method, which is well suited for complex or nonlinear systems where traditional controllers struggle.
Ga-doped Li7La3Zr2O12 garnet solid electrolytes exhibit the highest Li-ion conductivities among the oxide-type garnet-structured solid electrolytes, but instabilities toward Li metal hamper their practical application. The instabilities have been assigned to direct chemical reactions between LiGaO2 coexisting phases and Li metal by several groups previously. Yet, the understanding of the role of LiGaO2 in the electrochemical cell and its electrochemical properties is still lacking. Here, we are investigating the electrochemical properties of LiGaO2 through electrochemical tests in galvanostatic cells versus Li metal and complementary ex situ studies via confocal Raman microscopy, quantitative phase analysis based on powder X-ray diffraction, energy-dispersive X-ray spectroscopy, X-ray photoelectron spectroscopy, and electron energy loss spectroscopy. The results demonstrate considerable and surprising electrochemical activity, with high reversibility. A three-stage reaction mechanism is derived, including reversible electrochemical reactions that lead to the formation of highly electronically conducting products. The results have considerable implications for the use of Ga-doped Li7La3Zr2O12 electrolytes in all-solid-state Li-metal battery applications and raise the need for advanced materials engineering to realize Ga-doped Li7La3Zr2O12for practical use.
In this article we describe an Internet-of-Things sensing device with a wireless interface which is powered by the oftenoverlooked harvesting method of the Wiegand effect. The sensor can determine position, temperature or other resistively measurable quantities and can transmit the data via an ultra-low power ultra-wideband (UWB) data transmitter. With this approach we can energy-self-sufficiently acquire, process, and wirelessly transmit data in a pulsed operation. A proof-of-concept system was built up to prove the feasibility of the approach. The energy consumption of the system is analyzed and traced back in detail to the individual components, compared to the generated energy and processed to identify further optimization options. Based on the proof-of-concept, an application demonstrator was developed. Finally, we point out possible use cases.
With the growing interest in small distributed sensors for the “Internet of Things”, more attention is being paid to energy harvesting techologies. Reducing or eliminating the need for external power sources or batteries make devices more self-sufficient, more reliable, and reduces maintenance requirements. The Wiegand effect is a proven technology for harvesting small amounts of electrical power from mechanical motion.
This article describes an Internet of things (IoT) sensing device with a wireless interface which is powered by the energy-harvesting method of the Wiegand effect. The Wiegand effect, in contrast to continuous sources like photovoltaic or thermal harvesters, provides small amounts of energy discontinuously in pulsed mode. To enable an energy-self-sufficient operation of the sensing device with this pulsed energy source, the output energy of the Wiegand generator is maximized. This energy is used to power up the system and to acquire and process data like position, temperature or other resistively measurable quantities as well as transmit these data via an ultra-low-power ultra-wideband (UWB) data transmitter. A proof-of-concept system was built to prove the feasibility of the approach. The energy consumption of the system during start-up was analysed, traced back in detail to the individual components, compared to the generated energy and processed to identify further optimization options. Based on the proof of concept, an application prototype was developed.
Aim of the AXON2 project (Adaptive Expert System for Object Recogniton using Neuml Networks) is the development of an object recognition system (ORS) capable of recognizing isolated 3d objects from arbitrary views. Commonly, classification is based on a single feature extracted from the original image. Here we present an architecture adapted from the Mixtures of Eaqerts algorithm which uses multiple neuml networks to integmte different features. During tmining each neural network specializes in a subset of objects or object views appropriate to the properties of the corresponding feature space. In recognition mode the system dynamically chooses the most relevant features and combines them with maximum eficiency. The remaining less relevant features arz not computed and do therefore not decelerate the-recognition process. Thus, the algorithm is well suited for ml-time applications.
We have developed a double-tuned ¹H/¹⁹F birdcage resonator dedicated for hand and wrist imaging at 7 T to locally image non-steroidal anti-inflammatory drugs (NSAID) such as 2-{[3-(Trifluoromethyl) phenyl]amino}benzoic acid. The preliminary in vivo images acquired by the double-tuned ¹H/¹⁹F birdcage resonator demonstrate the feasibility for ¹H/¹⁹F hand- and wrist-imaging at 7 T. While the diagnostic quality of the coil needs to be assessed in patients with inflammatory rheumatoid disease, first ¹⁹F images of the NSAID are encouraging, and point towards the prospect of applying ¹⁹F-MRI to visualize and quantify the concentration of therapeutically-active compound at the sites of inflammation.
Objectives
To assess the image quality of T2-weighted (T2w) magnetic resonance imaging of the prostate and the visibility of prostate cancer at 7 Tesla (T).
Materials & methods
Seventeen prostate cancer patients underwent T2w imaging at 7T with only an external transmit/receive array coil. Three radiologists independently scored images for image quality, visibility of anatomical structures, and presence of artefacts. Krippendorff’s alpha and weighted kappa statistics were used to assess inter-observer agreement. Visibility of prostate cancer lesions was assessed by directly linking the T2w images to the confirmed location of prostate cancer on histopathology.
Results
T2w imaging at 7T was achievable with ‘satisfactory’ (3/5) to ‘good’ (4/5) quality. Visibility of anatomical structures was predominantly scored as ‘satisfactory’ (3/5) and ‘good’ (4/5). If artefacts were present, they were mostly motion artefacts and, to a lesser extent, aliasing artefacts and noise. Krippendorff’s analysis revealed an α = 0.44 between three readers for the overall image quality scores. Clinically significant cancer lesions in both peripheral zone and transition zone were visible at 7T.
Conclusion
T2w imaging with satisfactory to good quality can be routinely acquired, and cancer lesions were visible in patients with prostate cancer at 7T using only an external transmit/receive body array coil.
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.
The management of knowledge in organizations considers both established long-term processes and cooperation in agile project teams. Since knowledge can be both tacit and explicit, its transfer from the individual to the organizational knowledge base poses a challenge in organizations. This challenge increases when the fluctuation of knowledge carriers is exceptionally high. Especially in large projects in which external consultants are involved, there is a risk that critical, company-relevant knowledge generated in the project will leave the company with the external knowledge carrier and thus be lost. In this paper, we show the advantages of an early warning system for knowledge management to avoid this loss. In particular, the potential of visual analytics in the context of knowledge management systems is presented and discussed. We present a project for the development of a business-critical software system and discuss the first implementations and results.
The RoboCup Logistics League (RCLL) is a robotics competition in a production logistics scenario in the context of a Smart Factory. In the competition, a team of three robots needs to assemble products to fulfill various orders that are requested online during the game. This year, the Carologistics team was able to win the competition with a new approach to multi-agent coordination as well as significant changes to the robot’s perception unit and a pragmatic network setup using the cellular network instead of WiFi. In this paper, we describe the major components of our approach with a focus on the changes compared to the last physical competition in 2019.
Objective
To investigate the feasibility of 7T MR imaging of the kidneys utilising a custom-built 8-channel transmit/receive radiofrequency body coil.
Methods
In vivo unenhanced MR was performed in 8 healthy volunteers on a 7T whole-body MR system. After B0 shimming the following sequences were obtained: 1) 2D and 3D spoiled gradient-echo sequences (FLASH, VIBE), 2) T1-weighted 2D in and opposed phase 3) True-FISP imaging and 4) a T2-weighted turbo spin echo (TSE) sequence. Visual evaluation of the overall image quality was performed by two radiologists.
Results
Renal MRI at 7T was feasible in all eight subjects. Best image quality was found using T1-weighted gradient echo MRI, providing high anatomical details and excellent conspicuity of the non-enhanced vasculature. With successful shimming, B1 signal voids could be effectively reduced and/or shifted out of the region of interest in most sequence types. However, T2-weighted TSE imaging remained challenging and strongly impaired because of signal heterogeneities in three volunteers.
Conclusion
The results demonstrate the feasibility and diagnostic potential of dedicated 7T renal imaging. Further optimisation of imaging sequences and dedicated RF coil concepts are expected to improve the acquisition quality and ultimately provide high clinical diagnostic value.
This article addresses the need for an innovative technique in plasma shaping, utilizing antenna structures, Maxwell’s laws, and boundary conditions within a shielded environment. The motivation lies in exploring a novel approach to efficiently generate high-energy density plasma with potential applications across various fields. Implemented in an E01 circular cavity resonator, the proposed method involves the use of an impedance and field matching device with a coaxial connector and a specially optimized monopole antenna. This setup feeds a low-loss cavity resonator, resulting in a high-energy density air plasma with a surface temperature exceeding 3500 o C, achieved with a minimal power input of 80 W. The argon plasma, resembling the shape of a simple monopole antenna with modeled complex dielectric values, offers a more energy-efficient alternative compared to traditional, power-intensive plasma shaping methods. Simulations using a commercial electromagnetic (EM) solver validate the design’s effectiveness, while experimental validation underscores the method’s feasibility and practical implementation. Analyzing various parameters in an argon atmosphere, including hot S -parameters and plasma beam images, the results demonstrate the successful application of this technique, suggesting its potential in coating, furnace technology, fusion, and spectroscopy applications.
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.
Due to the decarbonization of the energy sector, the electric distribution grids are undergoing a major transformation, which is expected to increase the load on the operating resources due to new electrical loads and distributed energy resources. Therefore, grid operators need to gradually move to active grid management in order to ensure safe and reliable grid operation. However, this requires knowledge of key grid variables, such as node voltages, which is why the mass integration of measurement technology (smart meters) is necessary. Another problem is the fact that a large part of the topology of the distribution grids is not sufficiently digitized and models are partly faulty, which means that active grid operation management today has to be carried out largely blindly. It is therefore part of current research to develop methods for determining unknown grid topologies based on measurement data. In this paper, different clustering algorithms are presented and their performance of topology detection of low voltage grids is compared. Furthermore, the influence of measurement uncertainties is investigated in the form of a sensitivity analysis.
Vestibular effects of a 7 Tesla MRI examination compared to 1.5 T and 0 T in healthy volunteers
(2014)
Ultra-high-field MRI (7 Tesla (T) and above) elicits more temporary side-effects compared to 1.5 T and 3 T, e.g. dizziness or “postural instability” even after exiting the scanner. The current study aims to assess quantitatively vestibular performance before and after exposure to different MRI scenarios at 7 T, 1.5 T and 0 T. Sway path and body axis rotation (Unterberger's stepping test) were quantitatively recorded in a total of 46 volunteers before, 2 minutes after, and 15 minutes after different exposure scenarios: 7 T head MRI (n = 27), 7 T no RF (n = 22), 7 T only B₀ (n = 20), 7 T in & out B₀ (n = 20), 1.5 T no RF (n = 20), 0 T (n = 15). All exposure scenarios lasted 30 minutes except for brief one minute exposure in 7 T in & out B₀. Both measures were documented utilizing a 3D ultrasound system. During sway path evaluation, the experiment was repeated with eyes both open and closed. Sway paths for all long-lasting 7 T scenarios (normal, no RF, only B₀) with eyes closed were significantly prolonged 2 minutes after exiting the scanner, normalizing after 15 minutes. Brief exposure to 7 T B₀ or 30 minutes exposure to 1.5 T or 0 T did not show significant changes. End positions after Unterberger's stepping test were significantly changed counter-clockwise after all 7 T scenarios, including the brief in & out B₀ exposure. Shorter exposure resulted in a smaller alteration angle. In contrast to sway path, reversal of changes in body axis rotation was incomplete after 15 minutes. 1.5 T caused no rotational changes. The results show that exposure to the 7 Tesla static magnetic field causes only a temporary dysfunction or “over-compensation” of the vestibular system not measurable at 1.5 or 0 Tesla. Radiofrequency fields, gradient switching, and orthostatic dysregulation do not seem to play a role.
Given industrial applications, the costs for the operation and maintenance of a pump system typically far exceed its purchase price. For finding an optimal pump configuration which minimizes not only investment, but life-cycle costs, methods like Technical Operations Research which is based on Mixed-Integer Programming can be applied. However, during the planning phase, the designer is often faced with uncertain input data, e.g. future load demands can only be estimated. In this work, we deal with this uncertainty by developing a chance-constrained two-stage (CCTS) stochastic program. The design and operation of a booster station working under uncertain load demand are optimized to minimize total cost including purchase price, operation cost incurred by energy consumption and penalty cost resulting from water shortage. We find optimized system layouts using a sample average approximation (SAA) algorithm, and analyze the results for different risk levels of water shortage. By adjusting the risk level, the costs and performance range of the system can be balanced, and thus the
system’s resilience can be engineered
Mechatronics consist of the integration of mechanical
engineering, electronic integration and computer science/
engineering. These broad fields are essential for robotic
systems, yet it makes it difficult for the researchers to specialize
and be experts in all these fields. Collaboration between
researchers allow for the integration of experience and specialization,
to allow optimized systems. Collaboration between the
European countries and South Africa is critical, as each country
has different resources available, which the other countries
might not have. Applications with the need for approval of
any restrictions, can also be obtained easier in some countries
compared to others, thus preventing the delays of research.
Some problems that have been experienced are discussed, with
the Robotics Center of South Africa as a possible solution.
Achieving the 17 Sustainable Development Goals (SDGs) set by the United Nations (UN) in 2015 requires global collaboration between different stakeholders. Industry, and in particular engineers who shape industrial developments, have a special role to play as they are confronted with the responsibility to holistically reflect sustainability in industrial processes. This means that, in addition to the technical specifications, engineers must also question the effects of their own actions on an ecological, economic and social level in order to ensure sustainable action and contribute to the achievement of the SDGs. However, this requires competencies that enable engineers to apply all three pillars of sustainability to their own field of activity and to understand the global impact of industrial processes. In this context, it is relevant to understand how industry already reflects sustainability and to identify competences needed for sustainable development.
Highly competitive markets paired with tremendous production volumes demand particularly cost efficient products. The usage of common parts and modules across product families can potentially reduce production costs. Yet, increasing commonality typically results in overdesign of individual products. Multi domain virtual prototyping enables designers to evaluate costs and technical feasibility of different single product designs at reasonable computational effort in early design phases. However, savings by platform commonality are hard to quantify and require detailed knowledge of e.g. the production process and the supply chain. Therefore, we present and evaluate a multi-objective metamodel-based optimization algorithm which enables designers to explore the trade-off between high commonality and cost optimal design of single products.
In product development, numerous design decisions have to be made. Multi-domain virtual prototyping provides a variety of tools to assess technical feasibility of design options, however often requires substantial computational effort for just a single evaluation. A special challenge is therefore the optimal design of product families, which consist of a group of products derived from a common platform. Finding an optimal platform configuration (stating what is shared and what is individually designed for each product) and an optimal design of all products simultaneously leads to a mixed-integer nonlinear black-box optimization model. We present an optimization approach based on metamodels and a metaheuristic. To increase computational efficiency and solution quality, we compare different types of Gaussian process regression metamodels adapted from the domain of machine learning, and combine them with a genetic algorithm. We illustrate our approach on the example of a product family of electrical drives, and investigate the trade-off between solution quality and computational overhead.
20 Years of RoboCup
(2016)
Modeller for Value Systems
(1997)
The understanding that optimized components do not automatically lead to energy-efficient systems sets the attention from the single component on the entire technical system. At TU Darmstadt, a new field of research named Technical Operations Research (TOR) has its origin. It combines mathematical and technical know-how for the optimal design of technical systems. We illustrate our optimization approach in a case study for the design of a ventilation system with the ambition to minimize the energy consumption for a temporal distribution of diverse load demands. By combining scaling laws with our optimization methods we find the optimal combination of fans and show the advantage of the use of multiple fans.
ICSs (Industrial Control Systems) and its subset SCADA systems (Supervisory Control and Data Acquisition) are getting exposed to a constant stream of new threats. The increasing importance of IT security in ICS requires viable methods to assess the security of ICS, its individual components, and its protocols. This paper presents a security analysis with focus on the communication protocols of a single PLC (Programmable Logic Controller). The PLC, a Beckhoff CX2020, is examined and new vulnerabilities of the system are revealed. Based on these findings recommendations are made to improve security of the Beckhoff system and its protocols.
Modern implementations of driver assistance systems are evolving from a pure driver assistance to a independently acting automation system. Still these systems are not covering the full vehicle usage range, also called operational design domain, which require the human driver as fall-back mechanism. Transition of control and potential minimum risk manoeuvres are currently research topics and will bridge the gap until full autonomous vehicles are available. The authors showed in a demonstration that the transition of control mechanisms can be further improved by usage of communication technology. Receiving the incident type and position information by usage of standardised vehicle to everything (V2X) messages can improve the driver safety and comfort level. The connected and automated vehicle’s software framework can take this information to plan areas where the driver should take back control by initiating a transition of control which can be followed by a minimum risk manoeuvre in case of an unresponsive driver. This transition of control has been implemented in a test vehicle and was presented to the public during the IEEE IV2022 (IEEE Intelligent Vehicle Symposium) in Aachen, Germany.
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.
Reducing poverty, protecting the planet, and improving life on earth for everyone are the essential goals of the "2030 Agenda for Sustainable Development"committed by the United Nations (UN). Achieving those goals will require technological innovation as well as their implementation in almost all areas of our business and day-to-day life. This paper proposes a high-level framework that collects and structures different uses cases addressing the goals defined by the UN. Hence, it contributes to the discussion by proposing technical innovations that can be used to achieve those goals. As an example, the goal "Climate Actionïs discussed in detail by describing use cases related to tackling biodiversity loss in order to conservate ecosystems.
An Analysis of Retransmission Strategies for Reliable Multicast Protocols / Schuba, M. ; Reichl, P.
(1998)
Cybersecurity of Industrial Control Systems (ICS) is an important issue, as ICS incidents may have a direct impact on safety of people or the environment. At the same time the awareness and knowledge about cybersecurity, particularly in the context of ICS, is alarmingly low. Industrial honeypots offer a cheap and easy to implement way to raise cybersecurity awareness and to educate ICS staff about typical attack patterns. When integrated in a productive network, industrial honeypots may not only reveal attackers early but may also distract them from the actual important systems of the network. Implementing multiple honeypots as a honeynet, the systems can be used to emulate or simulate a whole Industrial Control System. This paper describes a network of honeypots emulating HTTP, SNMP, S7communication and the Modbus protocol using Conpot, IMUNES and SNAP7. The nodes mimic SIMATIC S7 programmable logic controllers (PLCs) which are widely used across the globe. The deployed honeypots' features will be compared with the features of real SIMATIC S7 PLCs. Furthermore, the honeynet has been made publicly available for ten days and occurring cyberattacks have been analyzed
Performance Investigations of the IP Multicast Architecture / Hermanns, Oliver ; Schuba, Marko
(1995)
A novel method to determine the extruded length of a metallic wire for a directed energy deposition (DED) process using a microwave (MW) plasma jet with a straight-through wire feed is presented. The method is based on the relative comparison of the measured frequency response obtained by the large-signal scattering parameter (Hot-S) technique. In the practical working range, repeatability of less than 6% for a nonactive plasma and 9% for the active plasma state is found. Measurements are conducted with a focus on a simple solution to decrease the processing time and reduce the integration time of the process into the existing hardware. It is shown that monitoring a single frequency for magnitude and phase changes is sufficient to achieve good accuracy. A combination of different measurement values to determine the length is possible. The applicability to different diameter of the same material is shown as well as a contact detection of the wire and metallic substrate.
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.
Thermal and Optical Study on the Frequency Dependence of an Atmospheric Microwave Argon Plasma Jet
(2019)
Quantitative Farbmessung in laryngoskopischen Bildern. Palm, C; Scholl, I; Lehmann, TM; Spitzer, K.
(1998)
MedicVR : Acceleration and Enhancement Techniques for Direct Volume Rendering in Virtual Reality
(2019)
Recently, novel AI-based services have emerged in the consumer market. AI-based services can affect the way consumers take commercial decisions. Research on the influence of AI on commercial interactions is in its infancy. In this chapter, a framework creating a first overview of the influence of AI on commercial interactions is introduced. This framework summarizes the findings of comparing numerous customer journeys of novel AI-based services with corresponding non-AI equivalents.
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.