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In times of dynamic markets, enterprises have to be agile to be able to quickly react to market influences. Due to the increasing digitization of products, the enterprise IT often is affected when business models change. Enterprise Architecture Management (EAM) targets a holistic view of the enterprise’ IT and their relations to the business. However, Enterprise Architectures (EA) are complex structures consisting of many layers, artifacts and relationships between them. Thus, analyzing EA is a very complex task for stakeholders. Visualizations are common vehicles to support analysis. However, in practice visualization capabilities lack flexibility and interactivity. A solution to improve the support of stakeholders in analyzing EAs might be the application of visual analytics. Starting from a systematic literature review, this article investigates the features of visual analytics relevant for the context of EAM.
In this paper we describe an interactive web-based visual analysis tool for Formula one races. It first provides an overview about all races on a yearly basis in a calendar-like representation. From this starting point, races can be selected and visually inspected in detail. We support a dynamic race position diagram as well as a more detailed lap times line plot for showing the drivers’ lap times in comparison. Many interaction techniques are supported like selections, filtering, highlighting, color coding, or details-on demand. We illustrate the usefulness of our visualization tool by applying it to a Formula one dataset while we describe the different dynamic visual racing patterns for a number of selected races and drivers.
Based on well-established robotic concepts of autonomous localization and navigation we present a system prototype to assist camera-based indoor navigation for human utilization implemented in the Robot Operating System (ROS). Our prototype takes advantage of state-of-the-art computer vision and robotic methods. Our system is designed for assistive indoor guidance. We employ a vibro tactile belt to serve as a guiding device to render derived motion suggestions to the user via vibration patterns. We evaluated the effectiveness of a variety of vibro-tactile feedback patterns for guidance of blindfolded users. Our prototype demonstrates that a vision-based system can support human navigation, and may also assist the visually impaired in a human-centered way.
Enterprises and societies currently face crucial challenges, while Society 5.0 can contribute to a supersmart society, especially for manufacturing and healthcare, and Industry 4.0 becomes important in the global manufacturing industry. Smart energy digital platforms are architected to manage energy supply efficiently. Furthermore, the above digital platforms are expected to collect various kinds of data and analyze Big Data for the trends in the sharing economy in ecosystems. The adaptive integrated digital architecture framework (AIDAF) for Design Thinking Approach with Risk Management is expected to make an alignment with digital IT strategy. In this paper, we propose that various energy management systems and related digital platforms are designed and implemented in an alignment to digital IT strategy for sharing economy toward Society 5.0, with the AIDAF framework for Design Thinking Approach with Risk Management. The vision of AIDAF applications to enable sharing economy and digital platforms is explained and extended in the context of Society 5.0. In addition, challenges and future activities for this area are discussed that cover the directions of smart energy for Society 5.0.
In order to evaluate the performance of different stapes prosthesis types, a coupled finite element (FE) model of human ear was developed. First, the middle-ear FE model was developed and validated using the middle-ear transfer function measurements available in literature including pathological cases. Then, the inner-ear FE model was developed and validated using tonotopy, impedance, and level of cochlea amplification curves from literature. Both models are based on pre-existing research with some improvements and were combined into one coupled FE model. The stapes in the coupled FE ear model was replaced with a model of a stapes prosthesis to create a reconstructed ear model that can be used to estimate how different types of protheses perform relative to each other as well as to the natural ear. This will help in designing of new innovative types of stapes prostheses or any other type of middle-ear prostheses as well as to improve the ones that are already available on the market.
The Virtual Power Plant Neckar-Alb is a demonstration platform for operation, optimization and control of distributed energy resources, which are able to produce, store or consume electric energy. A heterogeneous set of distributed energy devices has been installed at the Campus of Reutlingen University by the Reutlingen Energy Centre (REZ) of the School of Engineering. The distributed energy devices have been combined to local microgrids and connected to an operative central power plant with additional participants. The demonstration platform serves students, researchers and industry experts for education and investigation of new technologies, devices and software.
Today the optimization of metal forming processes is done using advanced simulation tools in a virtual process, e.g. FEM-studies. The modification of the free parameters represents the different variants to be analysed. So experienced engineers may derive useful proposals in an acceptable time if good initial proposals are available. As soon as the number of free parameters growths or the total process takes long times and uses different succeeding forming steps it might be quite difficult to find promising initial ideas. In metal forming another problem has to be considered. The optimization using a series of local improvements, often called a gradient approach may find a local optimum, but this could be far away from a satisfactory solution. Therefore non-deterministic approaches, e.g. Bionic Optimization have to be used. These approaches like Evolutionary Optimization or Particle Swarm Optimization are capable to cover a large range of high dimensional optimization spaces and discover many local optima. So the chance to include the global optimum increases when using such non-deterministic methods. Unfortunately these bionic methods require large numbers of studies of different variants of the process to be optimized. The number of studies tends to increase exponentially with the number of free parameters of the forming process. As the time for one single study might be not too small as well, the total time demand will be inacceptable, taking weeks to months even if high performance computing will be used. Therefore the optimization process needs to be accelerated. Among the many ideas to reduce the time and computer power requirement Meta- and Hybrid Optimization seem to produce the most efficient results. Hybrid Optimization often consists of global searches of promising regions within the parameter space. As soon as the studies indicate that there could be a local optimum, a deterministic study tries to identify this local region. If it shows better performance than other optima found until now, it is preserved for a more detailed analysis. If it performs worse than other optima the region is excluded from further search. Meta-Optimization is often understood as the derivation of Response Surfaces of the functions of free parameters. Once there are enough studies performed, the optimization is done using the Response Surfaces as representatives e.g. for the goal and the restrictions of the optimization problem. Having found regions where interesting solutions are to be expected, the studies available up to now are used to define the Response Surfaces. In many cases low degree polynomials are used, defining their coefficients by least square methods. Both proposals Hybrid Optimization and Meta-Optimization, sometimes used in combination often help to reduce the total optimization processes by large numbers of variants to be studied. In consequence they are highly recommended when dealing with time consuming optimization studies.
The purpose of this article is to provide insight of a new simple forecasting method based on a state-estimation algorithm known as the Kalman filter. While the accuracy of such algorithm is not comparable to state-of-the-art forecasting algorithms for PV-power production it does not require any internet connection, eyefish cameras or time intensive training. The algorithm was tested with several months of real high-resolution data with adequate results for the intended applications. The minimization of the necessary spinning reserve on a PV-diesel hybrid system to increase the solar fraction and reduce diesel consumption.
Verification of an active time constant tuning technique for continuous-time delta-sigma modulators
(2022)
In this work we present a technique to compensate the effects of R-C / g m -C time-constant (TC) errors due to process variation in continuous-time delta-sigma modulators. Local TC error compensation factors are shifted around in the modulator loop to positions where they can be implemented efficiently with finely tunable circuit structures, such as current-steering digital-to-analog converters (DAC). We apply our technique to a third-order, single-bit, low-pass continuous-time delta-sigma modulator in cascaded integrator feedback structure, implemented in a 0.35-μm CMOS process. A tuning scheme for the reference currents of the feedback DACs is derived as a function of the individual TC errors and verified by circuit simulations. We confirm the tuning technique experimentally on the fabricated circuit over a TC parameter variation range of ±20%. Stable modulator operation is achieved for all parameter sets. The measured performances satisfy the expectations from our theoretical calculations and circuit-level simulations.
Artificial Intelligence enables innovative applications, and applications based on Artificial Intelligence are increasingly important for all aspects of the Digital Economy. However, the question of how AI resources such as tools and data can be linked to provide an AI-capability and create business value is still open. Therefore, this paper identifies the value-creating mechanisms of connectionist artificial intelligence using a capability-oriented view and points out the connections to different kinds of business value. The analysis supports an agenda that identifies areas that need further research to understand the mechanism of value creation in connectionist artificial intelligence.
Product engineering and subsequent phases of product lifecycles are predominantly managed in isolation. Companies therefore do not fully exploit potentials through using data from smart factories and product usage. The novel intelligent and integrated Product Lifecycle Management (i²PLM) describes an approach that uses these data for product engineering. This paper describes the i²PLM, shows the cause-and-effect relationships in this context and presents in detail the validation of the approach. The i²PLM is applied and validated on a smart product in an industrial research environment. Here, the subsequent generation of a smart lunchbox is developed based on production and sensor data. The results of the validation give indications for further improvements of the i²PLM. This paper describes how to integrate the i²PLM into a learning factory.
The paper illustrates the status quo of a research project for the development of a control system enabling CHP units for a demand-oriented electricity production by an intelligent management of the heat storage tank. Thereby the focus of the project is twofold. One is the compensation of the fluctuating power production by the renewable energies solar and wind. Secondly, a reduction of the load on the power grid is intended by better matching local electricity demand and production.
In detail, the general control strategy is outlined, the method utilized for forecasting heat and electricity demand is illustrated as well as a correlation method for the temperature distribution in the heat storage tank based on a Sigmoid function is proposed. Moreover, the simulation model for verification and optimization of the control system and the two field test sites for implementing and testing the system are introduced.
Applications often need to be deployed in different variants due to different customer requirements. However, since modern applications often need to be deployed using multiple deployment technologies in combination, such as Ansible and Terraform, the deployment variability must be considered in a holistic way. To tackle this, we previously developed Variability4TOSCA and the prototype OpenTOSCA Vintner, which is a TOSCA preprocessing and management layer that implements Variability4TOSCA. In this demonstration, we present a detailed case study that shows how to model a deployment using Variability4TOSCA, how to resolve the variability using Vintner, and how the result can be deployed.
Recognizing actions of humans, reliably inferring their meaning and being able to potentially exchange mutual social information are core challenges for autonomous systems when they directly share the same space with humans. Today’s technical perception solutions have been developed and tested mostly on standard vision benchmark datasets where manual labeling of sensory ground truth is a tedious but necessary task. Furthermore, rarely occurring human activities are underrepresented in such data leading to algorithms not recognizing such activities. For this purpose, we introduce a modular simulation framework which offers to train and validate algorithms on various environmental conditions. For this paper we created a dataset, containing rare human activities in urban areas, on which a current state of the art algorithm for pose estimation fails and demonstrate how to train such rare poses with simulated data only.
Engineers of the research project “Digital Product Life-Cycle” are using a graph-based design language to model all aspects of the product they are working on. This abstract model is the base for all further investigations, developments and implementations. In particular at early stages of development, collaborative decision making is very important. We propose a semantic augmented knowledge space by means of mixed reality technology, to support engineering teams. Therefore we present an interaction prototype consisting of a pico projector and a camera. In our usage scenario engineers are augmenting different artefacts in a virtual working environment. The concept of our prototype contains both an interaction and a technical concept. To realise implicit and natural interactions, we conducted two prototype tests: (1) A test with a low-fidelity prototype and (2) a test by using the method Wizard of Oz. As a result, we present a prototype with interaction selection using augmentation spotlighting and an interaction zoom as a semantic zoom.
Using measurement and simulation for understanding distributed development processes in the Cloud
(2017)
Organizations increasingly develop software in a distributed manner. The Cloud provides an environment to create and maintain software-based products and services. Currently, it is widely unknown which software processes are suited for Cloud-based development and what their effects in specific contexts are. This paper presents a process simulation to study distributed development in the Cloud. We contribute a simulation model, which helps analyzing different project parameters and their impact on projects carried out in the Cloud. The simulator helps reproducing activities, developers, issues and events in the project, and it generates statistics, e.g., on throughput, total time, and lead and cycle time. The aim of this simulation model is thus to analyze the tradeoffs regarding throughput, total time, project size, and team size. Furthermore, the modified simulation model aims to help project managers select the most suitable planning alternative. Based on observed projects in Finland and Spain, we simulated a distributed project using artificial and real data. Particularly, we studied the variables project size, team size, throughput, and total project duration. A comparison of the real project data with the results obtained from the simulation shows the simulation producing results close to the real data, and we could successfully replicate a distributed software project. By improving the understanding of distributed development processes, our simulation model thus supports project managers in their decision-making.
A sequence of transactions represents a complex and multi dimensional type of data. Feature construction can be used to reduce the data´s dimensionality to find behavioural patterns within such sequences. The patterns can be expressed using the blue prints of the constructed relevant features. These blue prints can then be used for real time classification on other sequences.
The coupling of the heat and power sector is required as supply and demand in the German electricity mix drift further and further apart with a high percentage of renewable energy. Heat pumps in combination with thermal energy storage systems can be a useful way to couple the heat and power sectors. This paper presents a hardware-in the-loop test bench for experimental investigation of optimized control strategies for heat pumps. 24-hour experiments are carried out to test whether the heat pump is able to serve optimized schedules generated by a MATLAB algorithm. The results show that the heat pump is capable of following the generated schedules, and the maximum deviation of the operational time between schedule and experiment is only 3%. Additionally, the system can serve the demand for space heating and DHW at any time.
Avatars are in use when interacting in virtual environments in different contexts, in collaborative work, as well as in gaming and also in virtual meetings with friends. Therefore it is important to understand how the relationship between user and avatar works. In this study, an online survey is used to determine how the perception of an avatar changes in different contexts by relating it to existing avatar relationship typologies. Additionally, it is determined whether in each context a realistic, abstract or comic-like representation is preferred by the participants. One result was a preference of low poly representations in the work context, which are associated with the perception of the avatar as a tool. In the context of meeting friends, a realistic representation is perceived as more appropriate, which is perceived as an accurate self-representation. In the gaming context, the results are less clear, which can be attributed to different gaming preferences. Here, unlike in the other contexts, a comic-like representation is also perceived as appropriate, which is associated with the perception of the avatar as a friend. A symbiotic user-avatar relationship is not directly related to any form of representation, but always lies in the midfield, which is attributed to the fact that it represents a whole spectrum between other categories.
Going forward with the requirements of missions to the Moon and further into deep space, the European Space Agency is investigating new methods of astronaut training that can help accelerate learning, increase availability and reduce complexity and cost in comparison to currently used methods. To achieve this, technologies such as virtual reality may be utilized. In this paper, an investigation into the benefits of using virtual reality as a means for extravehicular activity training in comparison to conventional training methods, such as neutral buoyancy pools is given. To help determine the requirements and current uses of virtual reality for extravehicular activity training first hand tests of currently available software as well as expert interviews are utilized. With this knowledge a concept is developed that may be used to further advance training methods in virtual reality. The resulting concept is used as a basis for development of a prototype to showcase user interactions and locomotion in microgravity simulations.