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This contribution quantifies the birefringence within injection-molded cyclic olefin copolymer plates and discusses its impact on the mechanical properties of the plates. It also focuses on the impact of birefringence on integrated waveguides and Bragg gratings and provides fabrication guidelines for such structures. The anisotropy in all three dimensions of the workpiece is examined by means of polarimetry and a prism coupler. It is found that the birefringence is inhomogenously distributed within the workpieces, whereas the maximum birefringence not only varies locally, but also depends on the observation direction. Overall, a maximum birefringence of 10 × 10−4 is found at the plate’s surface near the injection gate. The anisotropy then reduces exponentially towards the center of the workpiece and saturates at 1.8 × 10−4, in a depth of 0.4 mm. Thus, the birefringence strongly affects near-surface photonic structures. It is found that, depending on their orientation and the local birefringence of the substrate, waveguides and Bragg gratings fabricated with comparable parameters behave completely differently in terms of polarization-dependent optical attenuation, cross-sectional intensity distribution and Bragg reflection signal. For example, the support of the TM mode can vary between total loss and an optical attenuation of 0.9 dB × cm−1. In consequence, this study underlines the importance of quantifying the birefringent state of an injection-molded cyclic olefin copolymer workpiece if it is supposed to serve as a substrate for integrated photonic structures. The study furthermore demonstrates that birefringence effects can be omitted by burying the photonic structures deeper into the volume of the thermoplastic.
Predicting Autonomous Driving Behavior through Human Factor Considerations in Safety-Critical Events
(2024)
This paper investigates the ability of autonomous driving systems to predict outcomes by
considering human factors like gender, age, and driving experience, particularly in the context of
safety-critical events. The primary objective is to equip autonomous vehicles with the capacity to
make plausible deductions, handle conflicting data, and adjust their responses in real-time during
safety-critical situations. A foundational dataset, which encompasses various driving scenarios
such as lane changes, merging, and navigating complex intersections, is employed to enable vehicles
to exhibit appropriate behavior and make sound decisions in critical safety events. The deep
learning model incorporates personalized cognitive agents for each driver, considering their distinct
preferences, characteristics, and requirements. This personalized approach aims to enhance the
safety and efficiency of autonomous driving, contributing to the ongoing development of intelligent
transportation systems. The efforts made contribute to advancements in safety, efficiency, and overall
performance within autonomous driving systems. To describe the causal relationship between external
factors like weather conditions and human factors, and safety-critical driver behaviors, various
data mining techniques can be applied. One commonly used method is regression analysis. Additionally,
correlation analysis is employed to reveal relationships between different factors, helping to
identify the strength and direction of their impact on safety-critical driver behavior.
Keywords: car following; decision making; driving behavior; naturalistic driving studies; safety-critical
events; cognitive vehicles
1. Introduction
Despite the increasing prevalence of vehicle automation, the persistently high number
of car crashes remains a concern. Safety-critical events in human-driven scenarios have
become more intricate and partially uncontrollable due to unforeseen circumstances. Investigating
human driving behavior is imperative to establish traffic baselines for mixed
traffic, encompassing traditional, automated, and autonomous vehicles (AVs). Various
factors, such as weather conditions affecting visibility in longitudinal car-following (CF)
behavior [1,2], influence human driving behavior [3].
Car-following behavior, illustrating how a following vehicle responds to the lead
vehicle in the same lane, is a crucial aspect. Existing car-following models often make
assumptions about homogeneous drivers, neglecting significant heterogeneity in driving
experience, gender, character, emotions, and sociological, psychological, and physiological
traits. Failing to account for this heterogeneity hampers a comprehensive understanding of
car-following behavior, limiting model accuracy and applicability. In the development of
more realistic car-following models for mixed traffic, acknowledging the diversity among
drivers is crucial. By including individual variations such as risk-taking tendencies, reaction
times, decision-making processes, and driving styles, the modeling of real-world
driving complexities can be improved. Simplifying drivers into a few categories overlooks
the richness and variety of their characteristics, prompting the need for a more comprehensive
approach to capture nuances within different driver profiles. To address these
Smart Cities
In recent years, the demand for sustainable and degradable materials and electronic devices has increased significantly.
Among a range of biodegradable polymers, poly(lactic acid) (PLA) is a good alternative to conventional petrol-based polymers because of its attractive mechanical properties and its easy processability. Recently, PLA has also been described as a promising dielectric material with piezoelectric and electret properties. We expect that PLA—after further optimization— will play an important role as a material for environmentally friendly sensors in the future, where first applications such as air filters and pressure sensors have already been proposed. However, degradation under normal ambient conditions is very slow, and an accelerated and controllable degradation process is highly desirable for any type of PLA-based sensors.
Enzymatic hydrolysis with embedded enzymes has been proposed as an approach to accelerate and control degradation. In this work, we investigate the properties of PLA in terms of dielectric and mechanical properties with a focus on its ability to store charges after the enzyme proteinase K (Trit. album) has been incorporated. Results reveal that proteinase K has a positive effect on the charge stability of solvent-cast PLA electrets after complete evaporation of the solvent. Furthermore, we observed a concentration-dependent acceleration of mass loss in a Tris-HCl buffer. A fast degradation within only one day occurred at a concentration of 6 wt% proteinase K.
Integrating artificial intelligence (AI) into decision-making processes is key to improving organizational performance. However, trust in AI-based decision support systems (DSSs), similar to other information systems, is important for successful integration. A disruptive phenomenon, “algorithm aversion”, can impede AI trust and, thus, acceptance. Although AI recommendations outperform human recommendations in different decision-making fields, individuals underweight recommendations from AI-based DSSs compared to human decision-makers due to a lack of AI trust. We conducted a lab experiment to investigate the role of AI recommendations in workplace-related tasks, first focusing on the mediating effect of AI trust and the negative impact of algorithm aversion on decision-making performance and the moderating effect of technical competence. Second, we analyzed the ability of gamification to reduce this phenomenon. We provide evidence regarding how to enhance decision-making performance when AI recommendations are deployed and identify countermeasures against algorithm aversion to facilitate the adoption of AI-based DSSs.
This paper presents an extended control concept for automatic track guidance of industrial trucks in intralogistic systems. It is based on Reinforcement Learning (RL), a method of Artificial Intelligence (AI). The presented approach is able to adapt itself to different industrial truck variants and to the associated specific vehicle parameters. In order to avoid starting the whole
training of the controller for each truck variant from scratch, the training process is divided into two steps. In the first step, the controller is trained on a simplified linear model using parameters
of a nominal vehicle variant. Based on this, the control parameters are only fine-tuned in the second step using a more complex nonlinear model, representing the real industrial truck. In this
way, the controller is adapted to the actual truck variant and the corresponding parameter values. By using the nonlinear model, it can be ensured that the forklift’s dynamic is approximated
within the entire operating range, even at high steering angles. Moreover, the influence of the disturbance variable of the system (path curvature) is compensated by considering this a priori
knowledge within the control design. Therefore, the
Artificial Neural Networks (ANN) of the RL controller and the observation vector are suitably adjusted. In this way, the occurring path curvatures can be considered in both training steps and the control parameters can be optimized accordingly. Thus, the influence of the disturbance variable can be compensated, which significantly improves the control quality. In order to demonstrate this, the new approach is compared
to an RL control concept, which is not considering the disturbance variable and to a classical
two-degrees-of-freedom (2DoF) control approach.
In this article, we contribute to the longstanding debate among economists regarding the question of “nature or nurture” with respect to economics students’ attitudes toward various allocation mechanisms for a scarce resource. While previous research starts the debate by beginning with first-year economics students, we aim to evaluate pre-firstyear individuals, i.e., school pupils. Drawing on the seminal works of Haucap, J., & Just, T. (2010). Not guilty? Another look at the nature and nurture of economics students. European Journal of Law and Economics, 29(2), 239–254 and Frey, B. S., Pommerehne,W.W., & Gygi, B. (1993). Economics indoctrination or selection? Some empirical results. The Journal of Economic Education, 24(3), 271–281, we investigate a sample of pupils ranging from the 5th to the 13th grades to determine whether pupils are “born economists” (nature), develop economic thinking (nurture), or both. We find that young individuals start to think differently in early grades and that their thinking and attitudes are shaped differently throughout their school careers, thereby providing support for the effects of both nature and nurture. Our findings show that school time impacts fairness judgments, particularly regarding price mechanisms. Regarding learning or indoctrination, we find that economics-inclined pupils are positively affected by lessons in economics in school, while pupils who are economics-averse draw completely diametric conclusions from economics lessons, thereby exhibiting increased disapproval of price allocation over the course of these classes and increased approval of the first come, first served and governmental action mechanisms.Moreover, we find strong effects of gender and migration background in this context. This study is the first to elucidate the development of economic thinking in 5th–13th grade pupils. Our results are important for economists, educators,
and researchers because they can serve as a starting point for subsequent investigations in this under-researched field.
In diesem Jahr jährte sich der Todestag von Wilhelm Conrad Röntgen, gestorben am 10. Februar 1923, zum hundertsten Mal. Dieser Beitrag ist eine Hommage auf diesen bedeutenden deutschen Wissenschaftler. 1895 entdeckte er eine neue Art von Strahlung, welche in der Lage ist, feste Materialien zu durchdringen. 1901 erhielt Professor Röntgen für diese bahnbrechende Entdeckung den ersten Nobelpreis für Physik. Das Deutsche Röntgen-Museum (DRM) erforscht und dokumentiert das Leben und Werk von W. C. Röntgen und die Auswirkungen seiner Entdeckung auf eine einzigartige und umfassende Weise. Der Standort des DRM in Remscheid ist kein Zufall, denn Röntgens Geburtshaus liegt nur wenige Gehminuten von den Exponaten entfernt. Die Betonung der Vielfalt von Röntgens Erfindung durch das Museum mit einer multimedialen Herangehensweise ermöglicht es den Besuchern, hier ihre ganz persönlichen Entdeckungen zu machen. Jeder Museumsbesuch wird so zu einer einzigartigen Entdeckungsreise durch die Welt der Medizin, Wissenschaft und Technik. Dieser Beitrag würdigt das Lebenswerk von Professor Wilhelm Conrad Röntgen und gibt einen Einblick in die Geschichte der Röntgenstrahlen und ihre Anwendungsgebiete.
„Freude habe ich nur, solange ich es mit dem Experimentieren zu tun habe“, schrieb Wilhelm Conrad Röntgen am 9.6.1920 an Margret Boveri. Das Deutsche Röntgen-Museum und das Remscheider Röntgengymnasium geben getreu diesem Motto Kindern und Jugendlichen die Möglichkeit, selbst aktiv zu werden, zu experimentieren und so auf den Spuren dieses bedeutenden Forschers zu wandeln. Hierzu wurde am 8. November 2011, einem Jahrestag der Entdeckung der Röntgenstrahlen, das Museumslabor RöLab gegründet. Dort werden Themenbrücken in das tägliche Leben geschlagen und so Lernprozesse im MINT-Bereich für die jungen Forschenden anregend, attraktiv und nachhaltig erlebbar. Das RöLab versteht sich als ein überregionales, außerschulisches Bildungsangebot, das Begeisterung für Natur- und Ingenieurwissenschaften, Medizin und Medizintechnik an unterschiedliche Zielgruppen vermittelt und damit einen Beitrag zur Allgemeinbildung und MINT-Förderung leistet. Das didaktische Konzept nimmt den „Hands-on-Science“ Gedanken stringent auf, weckt den Forschergeist und ermöglicht es den Lernenden, Unsichtbares zu erkunden. Dieser Beitrag stellt das Museumslabor RöLab des Deutschen Röntgen-Museums vor.
Due to the recent progress in satellite control engineering, tandem flight arrangements of mini-satellites are currently in discussion and
under consideration for future space missions. CubeSat technologies offer an interesting possibility for space-born telescope payloads
based on this approach. In such a scenario, two small satellites will fly at a constant distance of a few meters up to 100 meters. Thereby,
the front satellite will carry the telescope optics and the second satellite the detector system. Related formation flight requirements were
addressed in the NetSat-Mission, composed of four 3U-CubeSats, launched 2020. Space technology challenges concern in particular orbit
control by an appropriate propulsion system as well as precision attitude pointing towards the joint target, and could be transferred from the
NetSat-mission to the proposed Tandem Mission. This will allow space-based telescopes with a long focal length even placed on board of
small or miniature CubeSat-type satellites. Cost effective Kirkpatrick-Baez type X-ray telescopes represent an important application here as
they have longer focal lengths compared to previous astronomical observatories using Wolter I type X-ray mirrors.
Die voranschreitende Digitalisierung und insbesondere der Einsatz von Künstlicher Intelligenz (KI) in der
Bildung eröffnen neue Möglichkeiten des Lernens. Bildung kann stärker individuell sowie zeitlich und
räumlich entgrenzt stattfinden. ChatGPT verdeutlicht, wie dynamisch die Entwicklungen im Bereich KI
sind. Das in Zunahme begriffene Interesse am Thema KI allgemein sowie KI in der Bildung kommt dem
erforderlichen Austausch zwischen zentralen Akteur:innen zugute. Dieses Diskussionspapier präsentiert
drei Zukunftsszenarien für den Einsatz von KI in der institutionellen Bildung: Hochschule, Weiterbildung
und Schule. Im Fokus stehen die übergeordneten Fragestellungen nach Voraussetzungen und
Gelingensbedingungen einer erfolgreichen Anwendung sowie nach gemeinsamen Handlungsfeldern
für zentrale Stakeholder. Fünf Handlungsfelder für den Einsatz von KI in institutioneller Bildung sind auf
Grundlage der skizzierten Zukunftsszenarien hervorzuheben: (1) Interdisziplinäre Zusammenarbeit, (2)
Qualifizierungsangebote und Kompetenzentwicklung, (3) Digitale Infrastruktur und Personal, (4) Ethik
und Datensouveränität sowie (5) Interoperabilität von Daten in Bildungskontexten. Ziel des
vorliegenden Diskussionspapiers ist es, den kooperativen Austausch zwischen relevanten Stakeholdern
anzuregen.