Refine
Year of publication
Document Type
- Conference Proceeding (60) (remove)
Conference Type
- Konferenzartikel (52)
- Konferenzband (4)
- Konferenz-Abstract (3)
Language
- English (60) (remove)
Has Fulltext
- yes (60) (remove)
Keywords
- Communication Systems (3)
- Information Systems (3)
- Sound Synthesis (3)
- Deep Learning (2)
- Generative Art (2)
- Improvisation (2)
- Simulation-based Interaction (2)
- VR (2)
- artificial dancer (2)
- cardiac ablation (2)
Institute
- Fakultät Maschinenbau und Verfahrenstechnik (M+V) (19)
- Fakultät Elektrotechnik und Informationstechnik (E+I) (bis 03/2019) (15)
- INES - Institut für nachhaltige Energiesysteme (14)
- Fakultät Medien (M) (ab 22.04.2021) (8)
- Fakultät Elektrotechnik, Medizintechnik und Informatik (EMI) (ab 04/2019) (7)
- ivESK - Institut für verlässliche Embedded Systems und Kommunikationselektronik (6)
- Fakultät Medien und Informationswesen (M+I) (bis 21.04.2021) (5)
- Fakultät Wirtschaft (W) (5)
- ACI - Affective and Cognitive Institute (2)
- POIM - Peter Osypka Institute of Medical Engineering (2)
Open Access
- Open Access (56)
- Bronze (19)
- Diamond (9)
- Grün (7)
- Closed (3)
- Gold (3)
- Closed Access (1)
- Hybrid (1)
Digital, virtual environments and the metaverse are rapidly taking shape and will generate disruptive changes in the areas of ethics, privacy, safety, and how the relationships between human beings will be developed. To uncover some of some of the implications that will impact those areas, this study investigates the perceptions of 101 younger people from the generations Y and Z. We present a first exploratory analysis of the findings, focusing on knowledge and self-perception. Results show that these young generations are seriously doubting their knowledge on the metaverse and virtual worlds – regarding both the definition and the usage. It is interesting to see only a medium confidence level, considering that the participants are young and from an academic environment, which should increase their interest in and the affinity towards virtual worlds. Males from both generations perceive themselves as significantly more knowledgeable than females. Regarding a fitting definition, almost 40% agreed on the metaverse as a “universal and immersive virtual world that is made accessible using virtual reality and augmented reality technologies”. Regarding the topic in general, several participants (almost 40%) considered themselves sceptics or “just” users (38%). Interestingly, generation Y participants were more likely than the younger generation Z participants to identify themselves as early adopters or innovators. In result, the considerable amount of “mixed feelings” regarding digital, virtual environments and the metaverse shows that in-depth studies on the perception of the metaverse as well as its ethical and integrity implications are required to create more accessible, inclusive, safe, and inclusive digital, virtual environments.
Activities for rehabilitation and prevention are often lengthy and associated with pain and frustration. Their playful enrichment (hereafter: gamification) can counteract this, resulting in so-called “exergames”. However, in contrast to games designed solely for entertainment, the increased motivation and immersion in gamified training can lead to a reduced perception of pain and thus to health deterioration. Therefore, it is necessary to monitor activities continuously. However, only an AI-based system able to generate autonomous interventions could vacate the therapists’ costly time and allow better training at home. An automated adjustment of the movement training’s difficulty as well as individualized goal setting and control are essential to achieve such autonomy. This article’s contribution is two-fold: (1) We portray the potentials of gamification in the health area. (2) We present a framework for smart rehabilitation and prevention training allowing autonomous, dynamic, and gamified interactions.
Established robot manufacturers have developed methods to determine and optimize the accuracy of their robots. These methods vary from robot manufacturers to their competitors. Due to the lack of published data, a comparison of robot performance is difficult. The aim of this article is to find methods to evaluate important characteristics of a robot with an accurate and cost-effective setup. A laser triangulation sensor and geometric referenced spheres were used as a base to compare the robot performance.
Strings
(2020)
This article presents the currently ongoing development of an audiovisual performance work with the title Strings. This work provides an improvisation setting for a violinist, two laptop performers, and two generative systems. At the core of Strings lies an approach that establishes a strong correlation among all participants by means of a shared physical principle. The physical principle is that of a vibrating string. The article discusses how this principle is used in both natural and simulated forms as main interaction layer between all performers and as natural or generative principle for creating audio and video.
In the railway technical centers, scheduling the maintenance activities is a very complex task, it consists in ordering, in the time, all the maintenance operations on the workstations, while respecting the number of resources, precedence constraints, and the workstations' availabilities. Currently, this process is not completely automatic. For improving this situation, this paper presents a mathematical model for the maintenance activities scheduling in the case of railway remanufacturing systems. The studied problem is modeled as a flexible job-shop, with the possibility for a job to be executed several times on a stage. MILP formulation is implemented with the Makespan as an objective, representing the time for remanufacturing the train. The aim is to create a generic model for optimizing the planning of the maintenance activities and improving the performance of the railway technical centers. At last, numerical results are presented, discussing the impact of the instances size on the computing time to solve the described problem.
The Thread protocol is a recent development based on 6LoWPAN (IPv6 over IEEE 802.15.4), but with extensions regarding a more media independent approach, which – additionally – also promises true interoperability. To evaluate and analyse the operation of a Thread network a given open source 6LoWPAN stack for embedded devices (emb::6) has been extended in order to comply with the Thread specification. The implementation covers Mesh Link Establishment (MLE) and network layer functionality as well as 6LoWPAN mesh under routing mechanism based on MAC short addresses. The development has been verified on a virtualization platform and allows dynamical establishment of network topologies based on Thread's partitioning algorithm.
OPC UA (Open Platform Communications Unified Architecture) is already a well-known concept used widely in the automation industry. In the area of factory automation, OPC UA models the underlying field devices such as sensors and actuators in an OPC UA server to allow connecting OPC UA clients to access device-specific information via a standardized information model. One of the requirements of the OPC UA server to represent field device data using its information model is to have advanced knowledge about the properties of the field devices in the form of device descriptions. The international standard IEC 61804 specifies EDDL (Electronic Device Description Language) as a generic language for describing the properties of field devices. In this paper, the authors describe a possibility to dynamically map and integrate field device descriptions based on EDDL into OPCUA.
Legacy industrial communication protocols are proved robust and functional. During the last decades, the industry has invented completely new or advanced versions of the legacy communication solutions. However, even with the high adoption rate of these new solutions, still the majority industry applications run on legacy, mostly fieldbus related technologies. Profibus is one of those technologies that still keep on growing in the market, albeit a slow in market growth in recent years. A retrofit technology that would enable these technologies to connect to the Internet of Things, utilize the ever growing potential of data analysis, predictive maintenance or cloud-based application, while at the same time not changing a running system is fundamental.
The research project Ko-TAG [2], as part of the research initiative Ko-FAS [1], funded by the German Ministry of Economics and Technologies (BMWi), deals with the development of a wireless cooperative sensor system that shall pro-vide a benefit to current driver assistance systems (DAS) and traffic safety applications (TSA). The system’s primary function is the localization of vulnerable road users (VRU) e.g. pedestrians and powered two-wheelers, using communication signals, but can also serve as pre-crash (surround) safety system among vehicles. The main difference of this project, compared to previous ones that dealt with this topic, e.g. the AMULETT project, is an underlying FPGA based Hardware-Software co-design. The platform drives a real-time capable communication protocol that enables highly scalable network topologies fulfilling the hard real-time requirements of the single localization processes. Additionally it allows the exchange of further data (e.g. sensor data) to support the accident pre-diction process and the channel arbitration, and thus supports true cooperative sensing. This paper gives an overview of the project’s current system design as well as of the implementations of the key HDL entities supporting the software parts of the communication protocol. Furthermore, an approach for the dynamic reconfiguration of the devices is described, which provides several topology setups using a single PCB design.
Robust scheduling problem is a major decision problem that is addressed in the literature, especially for remanufacturing systems; this problem is complex because of the high uncertainty and complex constraints involved. Generally, the existing approaches are dedicated to specific processes and do not enable the quick and efficient generation and evaluation of schedules. With the emergence of the Industry 4.0 paradigm, data availability is now considered an opportunity to facilitate the decision-making process. In this study, a data-driven decisionmaking process is proposed to treat the robust scheduling problem of remanufacturing systems in uncertain environments. In particular, this process generates simulation models based on a data-driven modeling approach. A robustness evaluation approach is proposed to answer several decision questions. An application of the decision process in an industrial case of a remanufacturing system is presented herein, illustrating the impact of robustness evaluation results on real-life decisions.
A coordinated operation of decentralised micro-scale hybrid energy systems within a locally managed network such as a district or neighbourhood will play a significant role in the sector-coupled energy grid of the future. A quantitative analysis of the effects of the primary energy factors, energy conversion efficiencies, load profiles, and control strategies on their energy-economic balance can aid in identifying important trends concerning their deployment within such a network. In this contribution, an analysis of the operational data from five energy laboratories in the trinational Upper-Rhine region is evaluated and a comparison to a conventional reference system is presented. Ten exemplary data-sets representing typical operation conditions for the laboratories in different seasons and the latest information on their national energy strategies are used to evaluate the primary energy consumption, CO2 emissions, and demand-related costs. Various conclusions on the ecologic and economic feasibility of hybrid building energy systems are drawn to provide a toe-hold to the engineering community in their planning and development.
To achieve Germany's climate targets, the industrial sector, among others, must be transformed. The decarbonization of industry through the electrification of heating processes is a promising option. In order to investigate this transformation in energy system models, high-resolution temporal demand profiles of the heat and electricity applications for different industries are required. This paper presents a method for generating synthetic electricity and heat load profiles for 14 industry types. Using this methodology, annual profiles with a 15-minute resolution can be generated for both energy demands. First, daily profiles for the electricity demand were generated for 4 different production days. These daily profiles are additionally subdivided into eight end-use application categories. Finally, white noise is applied to the profile of the mechanical drives. The heat profile is similar to the electrical but is subdivided into four temperature ranges and the two applications hot water and space heating. The space heating application is additionally adjusted to the average monthly outdoor temperature. Both time series were generated for the analysis of an electrification of industrial heat application in energy system modelling.
In recent years, the topic of embedded machine learning has become very popular in AI research. With the help of various compression techniques such as pruning, quantization and others compression techniques, it became possible to run neural networks on embedded devices. These techniques have opened up a whole new application area for machine learning. They range from smart products such as voice assistants to smart sensors that are needed in robotics. Despite the achievements in embedded machine learning, efficient algorithms for training neural networks in constrained domains are still lacking. Training on embedded devices will open up further fields of applications. Efficient training algorithms would enable federated learning on embedded devices, in which the data remains where it was collected, or retraining of neural networks in different domains. In this paper, we summarize techniques that make training on embedded devices possible. We first describe the need and requirements for such algorithms. Then we examine existing techniques that address training in resource-constrained environments as well as techniques that are also suitable for training on embedded devices, such as incremental learning. At the end, we also discuss which problems and open questions still need to be solved in these areas.
The efficient support of Hardwae-In-theLoop (HIL) in the design process of hardwaresoftware-co-designed systems is an ongoing challenge. This paper presents a network-based integration of hardware elements into the softwarebased image processing tool „ADTF“, based on a high-performance Gigabit Ethernet MAC and a highly-efficient TCP/IP-stack. The MAC has been designed in VHDL. It was verified in a SystemCsimulation environment and tested on several Altera FPGAs.
Patients with focal ventricular tachycardia are at risk of hemodynamic failure and if no treatment is provided the mortality rate can exceed 30%. Therefore, medical professionals must be adequately trained in the management of these conditions. To achieve the best treatment, the origin of the abnormality should be known, as well as the course of the disease. This study provides an opportunity to visualize various focal ventricular tachycardias using the Offenburg cardiac rhythm model.
A simple measuring method for acquiring the radiation pattern of an ultrawide band Vivaldi antenna is presented. The measuring is performed by combining two identical Vivaldi antennas and some of the intrinsic properties of a stepped-frequency continue wave radar (SFCW radar) in the
range from 1.0 GHz to 6.0 GHz. A stepper-motor provided the azimuthal rotation for one of the antennas from 0 ◦ to 360 ◦. The tests have been performed within the conventional environment (laboratory / office) without using an anechoic chamber or absorbing materials. Special measuring devices have not been used either. This method has been tested with different pairs of Vivaldi antennas and it can be also used for different ones (with little or no change in the system), as long as their operational
bandwidth is within the frequency range of the SFCW radar.
Keywords — SFCW Radar, Antenna Gain Characterization,
Azimuthal Radiation Pattern
The paper compares different anti-windup strategies for the current control of inverter-fed permanent magnet synchronous machines (PMSM) controlled by pulse-width modulation. In this respect, the focus is on the drive behavior with a relatively large product of stator frequency and sampling time. A requirement for dynamically high-quality anti-windup measures is, among other things, a sufficiently accurate decoupling of the stator current direct axis and quadrature axis components even at high stator frequencies. Discrete-time models of the electrical subsystem of the PMSM are well suited for this purpose, of which the method found to be the most accurate in a preliminary investigation is used as the basis for all anti-windup methods examined. Simulation studies and measurement results document the performance of the compared methods.
This paper explores the potential of an m-learning environment by introducing the concept of mLab, a remote laboratory environment accessible through the use of handheld devices.
We are aiming to enhance the existing e-learning platform and internet-assisted laboratory settings, where students are offered in-depth tutoring, by providing compact tuition and tools for controlling simulations that are made available to learners via handheld devices. In this way, students are empowered by having access totheir simulations from any place and at any time.
The Metering Bus, also known as M-Bus, is a European standard EN13757-3 for reading out metering devices, like electricity, water, gas, or heat meters. Although real-life M-Bus networks can reach a significant size and complexity, only very simple protocol analyzers are available to observe and maintain such networks. In order to provide developers and installers with the ability to analyze the real bus signals easily, a web-based monitoring tool for the M-Bus has been designed and implemented. Combined with a physical bus interface it allows for measuring and recording the bus signals. For this at first a circuit has been developed, which transforms the voltage and current-modulated M-Bus signals to a voltage signal that can be read by a standard ADC and processed by an MCU. The bus signals and packets are displayed using a web server, which analyzes and classifies the frame fragments. As an additional feature an oscilloscope functionality is included in order to visualize the physical signal on the bus. This paper describes the development of the read-out circuit for the Wired M-Bus and the data recovery.
The increasing diffusion of rapidly developing AI technologies led to the idea of the experiment to combine TRIZ-based automated idea generation with the natural language processing tool ChatGPT, using the chatbot to interpret the automatically generated elementary solution principles. The article explores the opportunities and benefits of a novel AI-enhanced approach to teaching systematic innovation, analyses the learning experience, identifies the factors that affect students' innovation and problem-solving performance, and highlights the main difficulties students face, especially in interdisciplinary problems.