Refine
Year of publication
Document Type
- Article (401)
- Conference Proceeding (230)
- Part of a Book (35)
- Book (23)
- Patent (2)
- Doctoral Thesis (1)
- Poster (1)
Language
- English (693) (remove)
Keywords
- Enterprise Architecture (5)
- MINLP (5)
- Engineering optimization (4)
- Optimization (3)
- Powertrain (3)
- Technical Operations Research (3)
- Telecommunication (3)
- Competence Developing Games (2)
- Energy efficiency (2)
- Experimental validation (2)
- Gamification (2)
- Hot S-parameter (2)
- Machine Learning (2)
- Optimal Topology (2)
- Process engineering (2)
- Pump System (2)
- Robotic Process Automation (2)
- Serious Game (2)
- Ventilation System (2)
- Water (2)
Institute
- Fachbereich Elektrotechnik und Informationstechnik (693) (remove)
7T MR Safety
(2021)
In this paper we investigate the use of deep neural networks for 3D object detection in uncommon, unstructured environments such as in an open-pit mine. While neural nets are frequently used for object detection in regular autonomous driving applications, more unusual driving scenarios aside street traffic pose additional challenges. For one, the collection of appropriate data sets to train the networks is an issue. For another, testing the performance of trained networks often requires tailored integration with the particular domain as well. While there exist different solutions for these problems in regular autonomous driving, there are only very few approaches that work for special domains just as well. We address both the challenges above in this work. First, we discuss two possible ways of acquiring data for training and evaluation. That is, we evaluate a semi-automated annotation of recorded LIDAR data and we examine synthetic data generation. Using these datasets we train and test different deep neural network for the task of object detection. Second, we propose a possible integration of a ROS2 detector module for an autonomous driving platform. Finally, we present the performance of three state-of-the-art deep neural networks in the domain of 3D object detection on a synthetic dataset and a smaller one containing a characteristic object from an open-pit mine.
Subject of this case is Deutsche Telekom Services Europe (DTSE), a service center for administrative processes. Due to the high volume of repetitive tasks (e.g., 100k manual uploads of offer documents into SAP per year), automation was identified as an important strategic target with a high management attention and commitment. DTSE has to work with various backend application systems without any possibility to change those systems. Furthermore, the complexity of administrative processes differed. When it comes to the transfer of unstructured data (e.g., offer documents) to structured data (e.g., MS Excel files), further cognitive technologies were needed.
Robotic process automation (RPA) has attracted increasing attention in research and practice. This chapter positions, structures, and frames the topic as an introduction to this book. RPA is understood as a broad concept that comprises a variety of concrete solutions. From a management perspective RPA offers an innovative approach for realizing automation potentials, whereas from a technical perspective the implementation based on software products and the impact of artificial intelligence (AI) and machine learning (ML) are relevant. RPA is industry-independent and can be used, for example, in finance, telecommunications, and the public sector. With respect to RPA this chapter discusses definitions, related approaches, a structuring framework, a research framework, and an inside as well as outside architectural view. Furthermore, it provides an overview of the book combined with short summaries of each chapter.
The benefits of robotic process automation (RPA) are highly related to the usage of commercial off-the-shelf (COTS) software products that can be easily implemented and customized by business units. But, how to find the best fitting RPA product for a specific situation that creates the expected benefits? This question is related to the general area of software evaluation and selection. In the face of more than 75 RPA products currently on the market, guidance considering those specifics is required. Therefore, this chapter proposes a criteria-based selection method specifically for RPA. The method includes a quantitative evaluation of costs and benefits as well as a qualitative utility analysis based on functional criteria. By using the visualization of financial implications (VOFI) method, an application-oriented structure is provided that opposes the total cost of ownership to the time savings times salary (TSTS). For the utility analysis a detailed list of functional criteria for RPA is offered. The whole method is based on a multi-vocal review of scientific and non-scholarly literature including publications by business practitioners, consultants, and vendors. The application of the method is illustrated by a concrete RPA example. The illustrated
structures, templates, and criteria can be directly utilized by practitioners in their real-life RPA implementations. In addition, a normative decision process for selecting RPA alternatives is proposed before the chapter closes with a discussion and outlook.
Intelligent autonomous software robots replacing human activities and performing administrative processes are reality in today’s corporate world. This includes, for example, decisions about invoice payments, identification of customers for a marketing campaign, and answering customer complaints. What happens if such a software robot causes a damage? Due to the complete absence of human activities, the question is not trivial. It could even happen that no one is liable for a damage towards a third party, which could create an uncalculatable legal risk for business partners. Furthermore, the implementation and operation of those software robots involves various stakeholders, which result in the unsolvable endeavor of identifying the originator of a damage. Overall it is advisable to all involved parties to carefully consider the legal situation. This chapter discusses the liability of software robots from an interdisciplinary perspective. Based on different technical scenarios the legal aspects of liability are discussed.
The initial idea of Robotic Process Automation (RPA) is the automation of business processes through a simple emulation of user input and output by software robots. Hence, it can be assumed that no changes of the used software systems and existing Enterprise Architecture (EA) is
required. In this short, practical paper we discuss this assumption based on a real-life implementation project. We show that a successful RPA implementation might require architectural work during analysis, implementation, and migration. As practical paper we focus on exemplary lessons-learned and new questions related to RPA and EA.
Through a mirror darkly – On the obscurity of teaching goals in game-based learning in IT security
(2021)
Teachers and instructors use very specific language communicating teaching goals. The most widely used frameworks of common reference are the Bloom’s Taxonomy and the Revised Bloom’s Taxonomy. The latter provides distinction of 209 different teaching goals which are connected to methods. In Competence Developing Games (CDGs - serious games to convey knowledge) and in IT security education, a two- or three level typology exists, reducing possible learning outcomes to awareness, training, and education. This study explores whether this much simpler framework succeeds in achieving the same range of learning outcomes. Method wise a keyword analysis was conducted. The results were threefold: 1. The words used to describe teaching goals in CDGs on IT security education do not reflect the whole range of learning outcomes. 2. The word choice is nevertheless different from common language, indicating an intentional use of language. 3. IT security CDGs use different sets of terms to describe learning outcomes, depending on whether they are awareness, training, or education games. The interpretation of the findings is that the reduction to just three types of CDGs reduces the capacity to communicate and think about learning outcomes and consequently reduces the outcomes that are intentionally achieved.
This paper introduces a new maritime search and rescue system based on S-band illumination harmonic radar (HR). Passive and active tags have been developed and tested while attached to life jackets and a small boat. In this demonstration test carried out on the Baltic Sea, the system was able to detect and range the active tags up to a distance of 5800 m using an illumination signal transmit-power of 100 W. Special attention is given to the development, performance, and conceptual differences between passive and active tags used in the system. Guidelines for achieving a high HR dynamic range, including a system components description, are given and a comparison with other HR systems is performed. System integration with a commercial maritime X-band navigation radar is shown to demonstrate a solution for rapid search and rescue response and quick localization.
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.
In this paper we present SMART-FACTORY, a setup for a research and teaching facility in industrial robotics that is based on the RoboCup Logistics League. It is driven by the need for developing and applying solutions for digital production. Digitization receives constantly increasing attention in many areas, especially in industry. The common theme is to make things smart by using intelligent computer technology. Especially in the last decade there have been many attempts to improve existing processes in factories, for example, in production logistics, also with deploying cyber-physical systems. An initiative that explores challenges and opportunities for robots in such a setting is the RoboCup Logistics League. Since its foundation in 2012 it is an international effort for research and education in an intra-warehouse logistics scenario. During seven years of competition a lot of knowledge and experience regarding autonomous robots was gained. This knowledge and experience shall provide the basis for further research in challenges of future production. The focus of our SMART-FACTORY is to create a stimulating environment for research on logistics robotics, for teaching activities in computer science and electrical engineering programmes as well as for industrial users to study and explore the feasibility of future technologies. Building on a very successful history in the RoboCup Logistics League we aim to provide stakeholders with a dedicated facility oriented at their individual needs.
Objective
In local SAR compression algorithms, the overestimation is generally not linearly dependent on actual local SAR. This can lead to large relative overestimation at low actual SAR values, unnecessarily constraining transmit array performance.
Method
Two strategies are proposed to reduce maximum relative overestimation for a given number of VOPs. The first strategy uses an overestimation matrix that roughly approximates actual local SAR; the second strategy uses a small set of pre-calculated VOPs as the overestimation term for the compression.
Result
Comparison with a previous method shows that for a given maximum relative overestimation the number of VOPs can be reduced by around 20% at the cost of a higher absolute overestimation at high actual local SAR values.
Conclusion
The proposed strategies outperform a previously published strategy and can improve the SAR compression where maximum relative overestimation constrains the performance of parallel transmission.
Water distribution systems are an essential supply infrastructure for cities. Given that climatic and demographic influences will pose further challenges for these infrastructures in the future, the resilience of water supply systems, i.e. their ability to withstand and recover from disruptions, has recently become a subject of research. To assess the resilience of a WDS, different graph-theoretical approaches exist. Next to general metrics characterizing the network topology, also hydraulic and technical restrictions have to be taken into account. In this work, the resilience of an exemplary water distribution network of a major German city is assessed, and a Mixed-Integer Program is presented which allows to assess the impact of capacity adaptations on its resilience.