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IT environments that consist of a very large number of rather small structures like microservices, Internet of Things (IoT) components, or mobility systems are emerging to support flexible and agile products and services in the age of digital transformation. Biological metaphors of living and adaptable ecosystems with service-oriented enterprise architectures provide the foundation for self-optimizing, resilient run-time environments and distributed information systems. We are extending Enterprise Architecture (EA) methodologies and models that cover a high degree of heterogeneity and distribution to support the digital transformation and related information systems with micro-granular architectures. Our aim is to support flexibility and agile transformation for both IT and business capabilities within adaptable digital enterprise architectures. The present research paper investigates mechanisms for integrating Microservice Architectures (MSA) by extending original enterprise architecture reference models with elements for more flexible architectural metamodels and EA-mini-descriptions.
The deterioration of the shielding performance of electromagnetic interference finger stock gaskets in a corrosive environment is investigated. The visualization of the real contact area shows a drastic reduction of the engaged active contact region between fingers and their mating surfaces in presence of corrosives residues. In fact, additional openings occur besides the “Tlike” holes due to the porous nature of gaskets. This leads to a strong degradation of the shielding effectiveness. Modified Bethe’s theory is used to estimate the equivalent circuit parameters while the shielding effectiveness in terms of ratio between two transfer functions is obtained upon applying the filter theory. Quantitative measurements carried out for different gasket types show a good agreement with calculated results, demonstrating thus the validity of the approach.
Significant advances have been achieved in mobile robot localization and mapping in dynamic environments, however these are mostly incapable of dealing with the physical properties of automotive radar sensors. In this paper we present an accurate and robust solution to this problem, by introducing a memory efficient cluster map representation. Our approach is validated by experiments that took place on a public parking space with pedestrians, moving cars, as well as different parking configurations to provide a challenging dynamic environment. The results prove its ability to reproducibly localize our vehicle within an error margin of below 1% with respect to ground truth using only point based radar targets. A decay process enables our map representation to support local updates.
The loss contribution of a 2.3kW synchronous GaN-HEMT boost converter for an input voltage of 250V and an output voltage of 500V was analyzed. A simulation model which consists of two parts is introduced. First, a physics-based model is used to determine the switching losses. Then, a system simulation is applied to calculate the losses of the specific elements. This approach allows a fast and accurate system evaluation as required for further system optimization.
In this work, a hard- and a zero-voltage turn-on switching converter are compared. Measurements were performed to verify the simulation model, showing a good agreement. A peak efficiency of 99% was achieved for an output power of 1.4kW. Even with an output power above 400W, it was possible to obtain a system efficiency exceeding 98 %.
In many automotive applications, repetitive selfheating is the most critical operation condition for LDMOS transistors in smart power ICs. This is attributed to thermomechanical stress in the on-chip metallization, which results from the different thermal expansion coefficients of the metal and the intermetal dielectric. After many cycles, the accumulated strain in the metallization can lead to short circuits, thus limiting the lifetime. Increasing the LDMOS size can help to lower peak temperatures and therefore to reduce the stress. The downside of this is a higher cost. Hence, it has been suggested to use resilient systems that monitor the LDMOS metallization and lower the stress once a certain level of degradation is reached. Then, lifetime requirements can be fulfilled without oversizing LDMOS transistors, even though a certain performance loss has to be accepted. For such systems, suitable sensors for metal degradation are required. This work proposes a floating metal line embedded in the LDMOS metallization. The suitability of this approach has been investigated experimentally by test structures and shown to be a promising candidate. The obtained results will be explained by means of numerical thermo-mechanical simulations.
This article discusses the scientifically and industrially important problem of automating the process of unloading goods from standard shipping containers. We outline some of the challenges barring further adoption of robotic solutions to this problem, ranging from handling a vast variety of shapes, sizes, weights, appearances, and packing arrangements of the goods, through hard demands on unloading speed and reliability, to ensuring that fragile goods are not damaged. We propose a modular and reconfigurable software framework in an attempt to efficiently address some of these challenges. We also outline the general framework design and the basic functionality of the core modules developed. We present two instantiations of the software system on two different fully integrated demonstrators: 1) coping with an industrial scenario, i.e., the automated unloading of coffee sacks with an already economically interesting performance; and 2) a scenario used to demonstrate the capabilities of our scientific and technological developments in the context of medium- to long-term prospects of automation in logistics. We performed evaluations that allowed us to summarize several important lessons learned and to identify future directions of research on autonomous robots for the handling of goods in logistics applications.
The internet of things, enterprise social networks, adaptive case management, mobility systems, analytics for big data, and cloud environments are emerging to support smart connected i.e. digital products and services and the digital transformation. Biological metaphors for living and adaptable ecosystems are currently providing the logical foundation for resilient run-time environments with serviceoriented digitization architectures and for self-optimizing intelligent business services and related distributed information systems. We are investigating mechanisms for flexible adaptation and evolution of information systems with digital architecture in the context of the ongoing digital transformation. The goal is to support flexible and agile transformations for both business and related information systems through adaptation and dynamical evolution of their digital architectures. The present research paper investigates mechanisms of decision analytics for digitization architectures, putting a spotlight to internet of things micro-granular architectures, by extending original enterprise architecture reference models with digitization architectures and their multi-perspective architectural decision management.
On the way to achieving higher degrees of autonomy for vehicles in complicated, ever changing scenarios, the localization problem poses a very important role. Especially the Simultaneous Localization and Mapping (SLAM) problem has been studied greatly in the past. For an autonomous system in the real world, we present a very cost-efficient, robust and very precise localization approach based on GraphSLAM and graph optimization using radar sensors. We are able to prove on a dynamically changing parking lot layout that both mapping and localization accuracy are very high. To evaluate the performance of the mapping algorithm, a highly accurate ground truth map generated from a total station was used. Localization results are compared to a high precision DGPS/INS system. Utilizing these methods, we can show the strong performance of our algorithm.
Influence of metallization layout on aging detector lifetime under cyclic thermo-mechanical stress
(2016)
The influence of the layout on early warning detectors in BCD technologies for metallization failure under cyclic thermo-mechanical stress was investigated. Different LDMOS transistors, with narrow or wide metal fingers and with or without embedded detectors, were used. The test structures were repeatedly stressed by pronounced self-heating until failure (a short circuit) was detected. The results show that the layout of the on-chip metallization has a large impact on the lifetime. A significant influence of the detectors on the lifetime was also observed, in our case causing a reduction of more than a factor of two, but only for the test structure with narrow metal fingers. The experimental results are explained by an efficient numerical thermo mechanical simulation approach, giving detailed insights into the strain distribution in the metal system. These results are important for aging detector design and, morever, for LDMOS on-chip metal layout in general.
For decades, Software Process Improvement (SPI) programs have been implemented, inter alia, to improve quality and speed of software development. To set up, guide, and carry out SPI projects, and to measure SPI state, impact, and success, a multitude of different SPI approaches and considerable experience are available. SPI addresses many aspects ranging from individual developer skills to entire organizations. It comprises for instance the optimization of specific activities in the software lifecycle as well as the creation of organization awareness and project culture. In the course of conducting a systematic mapping study on the state-of-the-art in SPI from a general perspective, we observed Global Software Engineering (GSE) becoming a topic of interest in recent years. Therefore, in this paper, we provide a detailed investigation of those papers from the overall systematic mapping study that were classified as addressing SPI in the context of GSE. From the main study’s result set, a set of 30 papers dealing with GSE was selected for an in-depth analysis using the systematic review instrument to study the contributions and to develop an initial picture of how GSE is considered from the perspective of SPI. Our findings show the analyzed papers delivering a substantial discussion of cultural models and how such models can be used to better address and align SPI programs with multi-national environments. Furthermore, experience is shared discussing how agile approaches can be implemented in companies working at the global scale. Finally, success factors and barriers are studied to help companies implementing SPI in a GSE context.