Refine
Year of publication
- 2021 (282) (remove)
Document Type
- Article (102)
- Bachelor Thesis (89)
- Conference Proceeding (50)
- Part of a Book (17)
- Book (9)
- Master's Thesis (4)
- Report (3)
- Doctoral Thesis (2)
- Review (2)
- Other (1)
- Part of Periodical (1)
- Preprint (1)
- Working Paper (1)
Keywords
- Corporate Design (6)
- Animation (5)
- Fotografie (4)
- Illustration (4)
- Nachhaltigkeit (4)
- UX Design (4)
- App (3)
- Botanik (3)
- Dokumentation (3)
- Gamification (3)
- Gesundheit (3)
- Holz (3)
- Layout (3)
- Lebensmittel (3)
- Mode (3)
- Museum (3)
- Redesign (3)
- Baukastensystem (2)
- Bookazine (2)
- Corona (2)
Institute
- Fachbereich Gestaltung (94)
- Fachbereich Medizintechnik und Technomathematik (55)
- IfB - Institut für Bioengineering (36)
- Fachbereich Elektrotechnik und Informationstechnik (26)
- Fachbereich Energietechnik (23)
- Fachbereich Wirtschaftswissenschaften (21)
- Fachbereich Luft- und Raumfahrttechnik (20)
- INB - Institut für Nano- und Biotechnologien (15)
- Fachbereich Bauingenieurwesen (13)
- Fachbereich Chemie und Biotechnologie (11)
- Fachbereich Maschinenbau und Mechatronik (11)
- Solar-Institut Jülich (11)
- ECSM European Center for Sustainable Mobility (9)
- MASKOR Institut für Mobile Autonome Systeme und Kognitive Robotik (7)
- Nowum-Energy (5)
- IBB - Institut für Baustoffe und Baukonstruktionen (3)
- Fachbereich Architektur (2)
- IMP - Institut für Mikrowellen- und Plasmatechnik (2)
- ZHQ - Bereich Hochschuldidaktik und Evaluation (2)
- Arbeitsstelle fuer Hochschuldidaktik und Studienberatung (1)
The fourth industrial revolution introduces disruptive technologies to production environments. One of these technologies are multi-agent systems (MASs), where agents virtualize machines. However, the agent's actual performances in production environments can hardly be estimated as most research has been focusing on isolated projects and specific scenarios. We address this gap by implementing a highly connected and configurable reference model with quantifiable key performance indicators (KPIs) for production scheduling and routing in single-piece workflows. Furthermore, we propose an algorithm to optimize the search of extrema in highly connected distributed systems. The benefits, limits, and drawbacks of MASs and their performances are evaluated extensively by event-based simulations against the introduced model, which acts as a benchmark. Even though the performance of the proposed MAS is, on average, slightly lower than the reference system, the increased flexibility allows it to find new solutions and deliver improved factory-planning outcomes. Our MAS shows an emerging behavior by using flexible production techniques to correct errors and compensate for bottlenecks. This increased flexibility offers substantial improvement potential. The general model in this paper allows the transfer of the results to estimate real systems or other models.
Photoelectrochemical (PEC) biosensors are a rather novel type of biosensors thatutilizelighttoprovideinformationaboutthecompositionofananalyte,enablinglight-controlled multi-analyte measurements. For enzymatic PEC biosensors,amperometric detection principles are already known in the literature. In con-trast, there is only a little information on H+-ion sensitive PEC biosensors. Inthis work, we demonstrate the detection of H+ions emerged by H+-generatingenzymes, exemplarily demonstrated with penicillinase as a model enzyme on atitanium dioxide photoanode. First, we describe the pH sensitivity of the sensorand study possible photoelectrocatalytic reactions with penicillin. Second, weshow the enzymatic PEC detection of penicillin.
Bitcoin is a cryptocurrency and is considered a high-risk asset
class whose price changes are difficult to predict. Current research focusses
on daily price movements with a limited number of predictors. The paper at
hand aims at identifying measurable indicators for Bitcoin price movement s
and the development of a suitable forecasting model for hourly changes. The
paper provides three research contributions. First, a set of significant
indicators for predicting the Bitcoin price is identified. Second, the results of
a trained Long Short-term Memory (LSTM) neural network that predicts
price changes on an hourly basis is presented and compared with other
algorithms. Third, the results foster discussions of the applicability of neural
nets for stock price predictions. In total, 47 input features for a period of
over 10 months could be retrieved to train a neural net that predicts the
Bitcoin price movements with an error rate of 3.52 %.
In jeder Schulklasse in Deutschland gibt es laut Statistik einen bis zwei Young Carer. Das sind Kinder und Jugendliche, die ein Familienmitglied pflegen. Doch wegen Unverständnis und Ausgrenzung seitens ihres sozialen Umfeldes vertrauen sich Young Carer niemandem an. Es mangelt schlichtweg an öffentlichem Bewusstsein für das Phänomen.
Die Kampagne #nichtbloßjung soll das ändern. Sie zeigt einer jungen Zielgruppe, was es bedeutet, nicht bloß jung, sondern Young Carer zu sein. Dabei regt sie dazu an, ebenfalls #nichtbloßjung zu bleiben, sondern als „Young Supporter“ die Young Carer zu unterstützen. Dazu wird diverse Informationsmaterial sowie ein kostenloses Armband bereitgestellt. Die Armbandtragenden zeigen so, dass sie Young Carer unterstützen und als Ansprechpersonen zur Verfügung stehen. So lernen Young Carer, dass sie mit ihrer Situation nicht allein sind und an wen sie sich gegebenenfalls wenden können.
Motile cilia are hair-like cell extensions present in multiple organs of the body. How cilia coordinate their regular beat in multiciliated epithelia to move fluids remains insufficiently understood, particularly due to lack of rigorous quantification. We combine here experiments, novel analysis tools, and theory to address this knowledge gap. We investigate collective dynamics of cilia in the zebrafish nose, due to its conserved properties with other ciliated tissues and its superior accessibility for non-invasive imaging. We revealed that cilia are synchronized only locally and that the size of local synchronization domains increases with the viscosity of the surrounding medium. Despite the fact that synchronization is local only, we observed global patterns of traveling metachronal waves across the multiciliated epithelium. Intriguingly, these global wave direction patterns are conserved across individual fish, but different for left and right nose, unveiling a chiral asymmetry of metachronal coordination. To understand the implications of synchronization for fluid pumping, we used a computational model of a regular array of cilia. We found that local metachronal synchronization prevents steric collisions and improves fluid pumping in dense cilia carpets, but hardly affects the direction of fluid flow. In conclusion, we show that local synchronization together with tissue-scale cilia alignment are sufficient to generate metachronal wave patterns in multiciliated epithelia, which enhance their physiological function of fluid pumping.