Refine
Year of publication
Document Type
- Article (5464)
- Conference Proceeding (1393)
- Book (1056)
- Part of a Book (544)
- Patent (172)
- Bachelor Thesis (156)
- Report (81)
- Doctoral Thesis (78)
- Other (68)
- Contribution to a Periodical (19)
- Master's Thesis (17)
- Review (17)
- Working Paper (8)
- Talk (5)
- Habilitation (4)
- Preprint (4)
- Diploma Thesis (3)
- Poster (3)
- Part of Periodical (2)
- Examination Thesis (1)
Language
Has Fulltext
- no (9096) (remove)
Keywords
- Corporate Design (9)
- Illustration (9)
- Erscheinungsbild (8)
- Gamification (8)
- Nachhaltigkeit (8)
- Redesign (7)
- Animation (6)
- Datenschutz (6)
- Digitalisierung (6)
- avalanche (6)
- App (5)
- Earthquake (5)
- Editorial (5)
- Enterprise Architecture (5)
- Fotografie (5)
- Geschichte (5)
- MINLP (5)
- solar sail (5)
- Aktionskunst (4)
- Design (4)
Institute
- Fachbereich Medizintechnik und Technomathematik (1907)
- Fachbereich Elektrotechnik und Informationstechnik (1116)
- Fachbereich Wirtschaftswissenschaften (1100)
- Fachbereich Energietechnik (1056)
- Fachbereich Chemie und Biotechnologie (829)
- Fachbereich Maschinenbau und Mechatronik (799)
- Fachbereich Luft- und Raumfahrttechnik (749)
- Fachbereich Bauingenieurwesen (658)
- IfB - Institut für Bioengineering (623)
- INB - Institut für Nano- und Biotechnologien (584)
- Solar-Institut Jülich (334)
- Fachbereich Gestaltung (333)
- Fachbereich Architektur (161)
- ECSM European Center for Sustainable Mobility (106)
- MASKOR Institut für Mobile Autonome Systeme und Kognitive Robotik (66)
- Nowum-Energy (64)
- ZHQ - Bereich Hochschuldidaktik und Evaluation (62)
- Institut fuer Angewandte Polymerchemie (32)
- Sonstiges (24)
- IBB - Institut für Baustoffe und Baukonstruktionen (21)
Autonomous agents require rich environment models for fulfilling their missions. High-definition maps are a well-established map format which allows for representing semantic information besides the usual geometric information of the environment. These are, for instance, road shapes, road markings, traffic signs or barriers. The geometric resolution of HD maps can be as precise as of centimetre level. In this paper, we report on our approach of using HD maps as a map representation for autonomous load-haul-dump vehicles in open-pit mining operations. As the mine undergoes constant change, we also need to constantly update the map. Therefore, we follow a lifelong mapping approach for updating the HD maps based on camera-based object detection and GPS data. We show our mapping algorithm based on the Lanelet 2 map format and show our integration with the navigation stack of the Robot Operating System. We present experimental results on our lifelong mapping approach from a real open-pit mine.
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.
AI-based systems are nearing ubiquity not only in everyday low-stakes activities but also in medical procedures. To protect patients and physicians alike, explainability requirements have been proposed for the operation of AI-based decision support systems (AI-DSS), which adds hurdles to the productive use of AI in clinical contexts. This raises two questions: Who decides these requirements? And how should access to AI-DSS be provided to communities that reject these standards (particularly when such communities are expert-scarce)? This chapter investigates a dilemma that emerges from the implementation of global AI governance. While rejecting global AI governance limits the ability to help communities in need, global AI governance risks undermining and subjecting health-insecure communities to the force of the neo-colonial world order. For this, this chapter first surveys the current landscape of AI governance and introduces the approach of relational egalitarianism as key to (global health) justice. To discuss the two horns of the referred dilemma, the core power imbalances faced by health-insecure collectives (HICs) are examined. The chapter argues that only strong demands of a dual strategy towards health-secure collectives can both remedy the immediate needs of HICs and enable them to become healthcare independent.
Nachhaltige Technologien, die Ressourcen schonen und Energie gewinnen, erlangen zunehmend an Bedeutung im urbanen Raum. Diese Bachelorarbeit befasst sich mit der Entwicklung eines Corporate Designs für ein Unternehmen, das sich auf die Fertigung und Planung von Bioenergiefassaden spezialisiert hat. Das Unternehmen sorgt durch seinen Fokus auf nachhaltige Energiegewinnung und effiziente Gebäudeplanung für die Verbesserung der ökologischen Herausforderungen. Das Ziel des neuen Corporate Designs ist es, die komplexe Thematik der Bioenergiefassaden der Zielgruppe effektiv zu vermitteln und ihr Interesse für dieses System zu wecken. Dabei werden Illustrationen und Infografiken eingesetzt, um die Technologie verständlich darzustellen, die positiven Umweltauswirkungen sowie Vorteile der Bioenergiefassaden deutlich hervorzuheben und mehr Umsetzungen zu erzielen.
Digital forensics of smartphones is of utmost importance in many criminal cases. As modern smartphones store chats, photos, videos etc. that can be relevant for investigations and as they can have storage capacities of hundreds of gigabytes, they are a primary target for forensic investigators. However, it is exactly this large amount of data that is causing problems: extracting and examining the data from multiple phones seized in the context of a case is taking more and more time. This bears the risk of wasting a lot of time with irrelevant phones while there is not enough time left to analyze a phone which is worth examination. Forensic triage can help in this case: Such a triage is a preselection step based on a subset of data and is performed before fully extracting all the data from the smartphone. Triage can accelerate subsequent investigations and is especially useful in cases where time is essential. The aim of this paper is to determine which and how much data from an Android smartphone can be made directly accessible to the forensic investigator – without tedious investigations. For this purpose, an app has been developed that can be used with extremely limited storage of data in the handset and which outputs the extracted data immediately to the forensic workstation in a human- and machine-readable format.
Experimental determination of the cross sections of proton capture on radioactive nuclei is extremely difficult. Therefore, it is of substantial interest for the understanding of the production of the p-nuclei. For the first time, a direct measurement of proton-capture cross sections on stored, radioactive ions became possible in an energy range of interest for nuclear astrophysics. The experiment was performed at the Experimental Storage Ring (ESR) at GSI by making use of a sensitive method to measure (p,γ) and (p,n) reactions in inverse kinematics. These reaction channels are of high relevance for the nucleosyn-thesis processes in supernovae, which are among the most violent explosions in the universe and are not yet well understood. The cross section of the ¹¹⁸Te(p,γ) reaction has been measured at energies of 6 MeV/u and 7 MeV/u. The heavy ions interacted with a hydrogen gas jet target. The radiative recombination process of the fully stripped ¹¹⁸Te ions and electrons from the hydrogen target was used as a luminosity monitor. An overview of the experimental method and preliminary results from the ongoing analysis will be presented.
Due to the increasing complexity of software projects, software development is becoming more and more dependent on teams. The quality of this teamwork can vary depending on the team composition, as teams are always a combination of different skills and personality types. This paper aims to answer the question of how to describe a software development team and what influence the personality of the team members has on the team dynamics. For this purpose, a systematic literature review (n=48) and a literature search with the AI research assistant Elicit (n=20) were conducted. Result: A person’s personality significantly shapes his or her thinking and actions, which in turn influences his or her behavior in software development teams. It has been shown that team performance and satisfaction can be strongly influenced by personality. The quality of communication and the likelihood of conflict can also be attributed to personality.
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.
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.
Lead and nickel, as heavy metals, are still used in industrial processes, and are classified as “environmental health hazards” due to their toxicity and polluting potential. The detection of heavy metals can prevent environmental pollution at toxic levels that are critical to human health. In this sense, the electrolyte–insulator–semiconductor (EIS) field-effect sensor is an attractive sensing platform concerning the fabrication of reusable and robust sensors to detect such substances. This study is aimed to fabricate a sensing unit on an EIS device based on Sn₃O₄ nanobelts embedded in a polyelectrolyte matrix of polyvinylpyrrolidone (PVP) and polyacrylic acid (PAA) using the layer-by-layer (LbL) technique. The EIS-Sn₃O₄ sensor exhibited enhanced electrochemical performance for detecting Pb²⁺ and Ni²⁺ ions, revealing a higher affinity for Pb²⁺ ions, with sensitivities of ca. 25.8 mV/decade and 2.4 mV/decade, respectively. Such results indicate that Sn₃O₄ nanobelts can contemplate a feasible proof-of-concept capacitive field-effect sensor for heavy metal detection, envisaging other future studies focusing on environmental monitoring.