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CNT-PUFs: highly robust and heat-tolerant carbon-nanotube-based physical unclonable functions
(2023)
In this work, we explored a highly robust and unique Physical Unclonable Function (PUF) based on the stochastic assembly of single-walled Carbon NanoTubes (CNTs) integrated within a wafer-level technology. Our work demonstrated that the proposed CNT-based PUFs are exceptionally robust with an average fractional intra-device Hamming distance well below 0.01 both at room temperature and under varying temperatures in the range from 23 °C to 120 °C. We attributed the excellent heat tolerance to comparatively low activation energies of less than 40 meV extracted from an Arrhenius plot. As the number of unstable bits in the examined implementation is extremely low, our devices allow for a lightweight and simple error correction, just by selecting stable cells, thereby diminishing the need for complex error correction. Through a significant number of tests, we demonstrated the capability of novel nanomaterial devices to serve as highly efficient hardware security primitives.
Der vorliegende Band rückt verschiedene Aspekte und Diskurse rund um Elias’ Schaffen in den Vordergrund und kontextualisiert die generelle soziologische Relevanz seines Schaffens. Er liefert einen Überblick über die aktuelle Elias-Forschung und verdeutlicht den Stellenwert und die Anschlussfähigkeit des Elias’schen Werks für sozialwissenschaftliche bzw. sozialtheoretische Debatten, insbesondere hinsichtlich zeitgenössischer gesellschaftlicher Entwicklungen. Dabei zeigt sich: Die Wissenschaft selbst, so Elias, läuft Gefahr, sich in Mythen zu verfangen, während sie die Mythen der Wirklichkeit unter die Lupe nimmt. Somit ist Mythenjagd nicht nur ein Schlagwort, sondern auch eine Devise, unter die sich Elias’ Gesamtwerk stellen lässt.
Vanadium redox-flow batteries (VRFBs) have played a significant role in hybrid energy storage systems (HESSs) over the last few decades owing to their unique characteristics and advantages. Hence, the accurate estimation of the VRFB model holds significant importance in large-scale storage applications, as they are indispensable for incorporating the distinctive features of energy storage systems and control algorithms within embedded energy architectures. In this work, we propose a novel approach that combines model-based and data-driven techniques to predict battery state variables, i.e., the state of charge (SoC), voltage, and current. Our proposal leverages enhanced deep reinforcement learning techniques, specifically deep q-learning (DQN), by combining q-learning with neural networks to optimize the VRFB-specific parameters, ensuring a robust fit between the real and simulated data. Our proposed method outperforms the existing approach in voltage prediction. Subsequently, we enhance the proposed approach by incorporating a second deep RL algorithm—dueling DQN—which is an improvement of DQN, resulting in a 10% improvement in the results, especially in terms of voltage prediction. The proposed approach results in an accurate VFRB model that can be generalized to several types of redox-flow batteries.
The worldwide adoption of Electric Vehicles (EVs) has embraced promising advancements toward a sustainable transportation system. However, the effective charging scheduling of EVs is not a trivial task due to the increase in the load demand in the Charging Stations (CSs) and the fluctuation of electricity prices. Moreover, other issues that raise concern among EV drivers are the long waiting time and the inability to charge the battery to the desired State of Charge (SOC). In order to alleviate the range of anxiety of users, we perform a Deep Reinforcement Learning (DRL) approach that provides the optimal charging time slots for EV based on the Photovoltaic power prices, the current EV SOC, the charging connector type, and the history of load demand profiles collected in different locations. Our implemented approach maximizes the EV profit while giving a margin of liberty to the EV drivers to select the preferred CS and the best charging time (i.e., morning, afternoon, evening, or night). The results analysis proves the effectiveness of the DRL model in minimizing the charging costs of the EV up to 60%, providing a full charging experience to the EV with a lower waiting time of less than or equal to 30 min.
Since the launch of the BRI, particular modes of movement are integral to its vision of what it means to be a modern world citizen. Nowhere is this more apparent than in Southeast Asia, where China-backed infrastructure projects expand, and at great speed. Such infrastructure projects are carriers of particular versions of modernity, promising rapid mobility to populations better connected than ever before. Yet, until now, little attention has been paid to how mobility and promises of mobility intersect with local understandings of development. In the introduction to this special issue, we argue that it is essential to think about the role infrastructure plays in forms of development that place connectivity at the center. We suggest that considering development, mobility and mo-dernity together is enlightening because it interrogates the connections between these interlocking themes. Through an introduction to five ethnographically grounded papers and two commentaries, all of which engage with infrastructures in different contexts throughout Southeast Asia, we demonstrate that there are significant gaps between of-ficial policy and lived experience. This makes the need to interrogate what infrastructure, mobilities, and global China really mean all the more pressing.
ChatGPT and similar generative AI models have attracted hundreds of millions of users and have become part of the public discourse. Many believe that such models will disrupt society and lead to significant changes in the education system and information generation. So far, this belief is based on either colloquial evidence or benchmarks from the owners of the models—both lack scientific rigor. We systematically assess the quality of AI-generated content through a large-scale study comparing human-written versus ChatGPT-generated argumentative student essays. We use essays that were rated by a large number of human experts (teachers). We augment the analysis by considering a set of linguistic characteristics of the generated essays. Our results demonstrate that ChatGPT generates essays that are rated higher regarding quality than human-written essays. The writing style of the AI models exhibits linguistic characteristics that are different from those of the human-written essays. Since the technology is readily available, we believe that educators must act immediately. We must re-invent homework and develop teaching concepts that utilize these AI models in the same way as math utilizes the calculator: teach the general concepts first and then use AI tools to free up time for other learning objectives.
Das Thema dieser Arbeit begibt sich ins Zentrum der Befreiungstheologie. Es geht um die Befähigung des Armen, sein Subjektsein deuten zu lernen und es so verantwortungsfähig entfalten zu können. Der Arme ist dazu auf Unterstützung angewiesen. Er braucht jemanden, der sich für ihn entscheidet und gegen die Realität der Unterdrückung stellt. Jeder, der das konsequent tut, muss wissen, dass er dabei sein eigenes Leben riskiert. Gerade deswegen ist nach den Gründen solchen Handelns zu fragen.
Der jüdische Philosoph Hans Jonas legte 1979 mit „Das Prinzip Verantwortung. Versuch einer Ethik für die technologische Zivilisation“ eines der am meisten gelesenen moralphilosophischen Bücher der Nachkriegszeit vor. Er reagiert damit auf die Tatsache, dass „die Verheißung der modernen Technik in Drohung umgeschlagen ist oder diese sich mit jener unlösbar verbunden hat“. Der Beitrag beleuchtet mit dem Abstand von drei Jahrzehnten die zentralen Thesen und die bleibende Bedeutung dieses Entwurfs.
Der aus Malta stammende Jesuit Tony Mifsud, Professor für Moraltheologie an der Universität Alberto Hurtado (Santiago de Chile), legte 1984 erstmals ein vierbändiges Werk unter dem Titel „Moral de Discernimiento“ vor. Fast zwei Jahrzehnte lang überarbeitet er dieses umfangreiche Konzept und publizierte es in aktualisierten Neuauflagen. Die „Moral de Discernimiento“ gilt als der erste Versuch, die Ideen der Theologie der Befreiung in eine Gesamtsystematik der Moraltheologie zu integrieren.
Die theologisch-ethische Bearbeitung von Themen – wie Freiheit, Sünde und Vergebung – muss erklären können, wie mit biblischen Texten umzugehen ist, wenn durch sie ein erfahrenes Interaktionsgeschehen mit Gott zum Ausdruck kommt. Schließlich besteht die Aufgabe, normative Aussagen für heutiges Handeln begründen zu können. Der Beitrag argumentiert für eine Methodik verhältnismäßiger, historischer Erfahrung.