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The collection of personal information by organizations has become increasingly essential for social interactions. Nevertheless, according to the GDPR (General Data Protection Regulation), the organizations have to protect collected data. Access Control (AC) mechanisms are traditionally used to secure information systems against unauthorized access to sensitive data. The increased availability of personal sensor data, thanks to IoT-oriented applications, motivates new services to offer insights about individuals. Consequently, data mining algorithms have been proposed to infer personal insights from collected sensor data. Although they can be used for genuine purposes, attackers can leverage those outcomes, combining them with other type of data, and further breaching individuals’ privacy. Thus, bypassing AC mechanisms thanks to such insights is a concrete problem.
We propose an inference detection system based on the analysis of queries issued on a sensor database. The knowledge obtained through these queries, and the inference channels corresponding to the use of data mining algorithms on sensor data to infer individual information, are described using Raw sensor data based Inference ChannEl Model (RICE-M). The detection is carried out by RICE-M based inference detection System (RICE-Sy). RICE-Sy considers at the time of the query, the knowledge that a user obtains via a new query and has obtained via his query history, and determines whether this is sufficient to allow that user to operate a channel. Thus, privacy protection systems can take advantage of the inferences detected by RICE-Sy, taking into account individuals’ information obtained by the attackers via a database of sensors, to further protect these individuals.
Welcher „Idee“ folgt die Universität und welchem Auftrag ist sie verpflichtet? Diese Fragen von Karl Jaspers 1923, 1946 und 1961 ausdrücklich aufgeworfen, bleiben stets aktuell.
Sie müssen im Horizont eines permanenten Wandels immer wieder neu reflektiert werden. Die Antworten nehmen die Universität insgesamt und die jeweils konkrete Hochschule in den Blick. Universität realisiert sich in konkreten Bedingungen in Auseinandersetzung mit den Fragen der Zeit.
Das Buch verbindet generelle Perspektive und spezielle Umsetzung durch Beiträge von außen und innen (hier aus der Universität Passau). Wissenschaft, Politik, Bildung, Wirtschaft treten somit in der Bestimmung der Idee der Universität in einen vielschichtigen Dialog.
Inhalt:
Ulrich Bartosch
Vorwort: Eine Idee der Universität – heute?
Rudolf Speth
Einleitung: Den Kern behalten und sich wandeln: Die Universität vor neuen Herausforderungen
I. Die historische Tiefendimension
Herfried Münkler
Ein virtueller Brückenschlag aus der europäischen Universitätsgeschichte in die Zukunft der Universität Passau
II. Die Universität und die Wissenschaft
Anna Henkel
Disziplinarität zwischen Wissenschaft und Universität
Horst Bischof
Universitäre Forschung quo vadis
Sabine Doering-Manteuffel
Die Universität als Ort des bewussten Widerspruchs
Brigitte Forster-Heinlein
Die Universität als Ort des bewussten Widerspruchs – auch aus Sicht der jungen Forscherinnen und Forscher?
Barbara Zehnpfennig
Universität und Wahrheit
Gesine Schwan
Was ist die Aufgabe von Universitäten?
Carolin Häussler
Wissenschaft: Normen, Spannungsfelder und die Dissemination von wissenschaftlichen Erkenntnissen in die Wirtschaft
III. Reformansätze und Ökonomisierung
Richard Münch
Alle Macht dem Präsidium! Von der Herrschaft der Ordinarien zur unternehmerischen und total administrierten Universität?
Wolfgang A. Herrmann
Die unternehmerische Universität
Ernst Ulrich von Weizsäcker
Virtueller Brückenschlag in die Zukunft der Universität Passau
IV. Das Bayerische Hochschulinnovationsgesetz
Bernd Sibler
Erfolgreiche Hochschulen brauchen exzellente Rahmenbedingungen
Heinrich Oberreuter
Wissenschaft als Dienst am Wissen
Karsten Fitz
Die Universität und die Grenzen des Wettbewerbs
V. Die Universität der Studierenden
Simon Pagany
Die Anfänge der studentischen Vizepräsidentschaft an der Zeppelin Universität
Lorena Puqja und Sophia Rockenmaier
Mitgestaltung auf Augenhöhe: Eine studentische Vizepräsidentschaft für die Universität Passau
Thomas Girst
Umweg statt Abkürzung: Über das Prinzip funktionaler Serendipität für die Lehranstalten der Zukunft
Birgit Beumers
Serendipität und Funktionalität?
VI. Die Universität als Organisation
Ulrike Beisiegel
Herausforderungen der Universitäten der Zukunft
Andreas König
„Universität als Heimat“ als Teil einer Universitätsstrategie
VII. Der Bezug zur Gesellschaft
Uwe Schneidewind
Die Stadt als Campus
Martina Padmanabhan
Was will internationale transdisziplinäre Nachhaltigkeitsforschung in Niederbayern? Das Versprechen der Kleinstadt
Micha Teuscher
Gesellschaftliche Herausforderungen als Impuls für die Entwicklung der Universität
Hannah Schmid-Petri
Öffentlichkeitsdynamiken im digitalen Zeitalter
Manfred Brocker
Eine politische Idee der Universität heute?
Alexander von Gernler
Ambivalenzen von Informatik und Digitalisierung
Florian Töpfl
Wie wissenschaftsskeptische Gegenöffentlichkeiten neue Medien nutzen
VIII. Der besondere Platz der Universität Passau
Christian Thies
Abschied von Humboldt
Hans-Georg Dederer
Die Idee der Universität heute
Michael Grimm
Die neue Approbationsordnung: Ein Plädoyer zur Schließung von Schnittstellen zwischen Medizin und Sozialwissenschaften
Zielsetzung der vorliegenden Arbeit war es, die Dogmatik der Zahlungsverbote endgültig herauszuarbeiten.
Spätestens seit Inkrafttreten des § 15b InsO durch das SanInsFOG kann nicht mehr geleugnet werden, dass es sich bei der Haftung für einen Verstoß gegen das Zahlungsverbot im Rahmen der Insolvenzverschleppungshaftung um eine schadensrechtliche Anspruchsgrundlage handeln muss.
Bislang beschränkte sich die inhaltsanalytische Populismusforschung überwiegend auf textuelle Botschaften, wie etwa Parteiprogramme, Zeitungsartikel oder Online Foren. Erst seit wenigen Jahren werden zunehmend auch visuell vermittelte Botschaften im Zusammenhang mit Populismus Gegenstand politik- und kommunikationswissenschaftlicher Untersuchung. Durch eine Verknüpfung des Ansatzes der Visuellen Politik mit einer Konzeptualisierung von Populismus als Kommunikationsphänomen versteht sich die vorliegende Dissertation als Beitrag zur Erforschung einer Visuellen Politik des Populismus (Moffitt 2022). Empirisch nimmt der Autor die Medienebene in den Fokus und konzentriert sich hierbei auf die ikonographisch-ikonologische Analyse von Magazincovern. So werden einerseits visuelle Darstellungen populistischer Akteure auf den Titelseiten des Nachrichtenmagazins Der Spiegel (Klumpp 2020, 2022) sowie andererseits visuelle Darstellungen des politischen Personals insgesamt auf Covern von Der Spiegel und Compact mittels Bildtypenanalyse (Klumpp 2023) untersucht.
With the increasing use of digital technologies in the automotive sector, the traditional automobile is undergoing a structural transformation, requiring new technologies and enabling innovative mobility concepts.
In particular, the ability to drive automatically or even fully autonomously, update control software, and remain connected to the environment allows attackers to infiltrate highly critical vehicle systems and take control without adequate protection.
Once not only individual vehicles but entire fleets are dominated by software, cyberattacks could disrupt a significant portion of the infrastructure and expose passengers to substantial risks.
This work follows a holistic approach to protecting highly automated software-defined vehicles from cyberattacks by designing and implementing security concepts in the main phases of a vehicle's lifecycle.
We use SAE level 4 prototype vehicles to evaluate our proposed techniques.
We start with a systematic security requirement analysis using the ISA-62443 standard series, demonstrating how threats can be identified in a collaborative, hierarchical process and how the resulting security risks impact the software and hardware architecture of a self-driving vehicle.
We show how this analysis process results in concrete requirements whose consideration reduces the overall security risk to a tolerable level.
Subsequently, we develop technical solutions for selected requirements. We begin by securing the CAN and FlexRay legacy protocols, which we foresee being used in specific areas of SDV in a transitional period despite technological changes.
To enable vehicle-wide security management, we address the management and distribution of cryptographic keys within such networks, mainly focusing on resource-constrained devices.
We propose using lightweight implicit certificates for deriving cryptographic group keys that can be used in CAN networks.
Additionally, we demonstrate how the slot-based frame structure of the FlexRay protocol allows for efficient "multi-slot" authentication, for which we calculate cryptographic keys using hash-based key chains.
SDV use Ethernet-based communication protocols and custom middleware stacks to transmit large amounts of data in real-time.
We develop a three-stage security process for the novel ASOA, which enables the development and central orchestration of system-agnostic functional software components on embedded systems and HPC platforms.
After the central specification of the security architecture at the data flow level, security tokens are automatically calculated and distributed for runtime protection of the service-oriented, DDS-based data transmission.
Our process ensures the strict separation of function and system knowledge, allowing for cost-effective and adaptable security architecture management.
The evaluation in four self-driving, software-defined vehicles demonstrates an average runtime overhead of approximately 5.71%.
As the initial risk analysis and actual cyberattacks have shown, protective measures against the compromise of control units must be taken alongside communication security.
To address this, we develop a method for verifying and validating the software integrity of control units.
A governmental third party confirms a measurement through a digital certificate, proving the examined vehicle's trustworthiness and suitability for participation in automated traffic.
In the final step of this work, we present an assessment scheme that allows software-defined vehicles to evaluate security incidents during operation in terms of their maximum expected damage and initiate appropriate countermeasures.
We follow the ISO/SAE 21434 standard and model attack paths using a graph representing dependencies among internal vehicle assets to account for the propagation effects of cyberattacks.
The assessment of a security incident considers not only the probability of individual attack paths but also the vehicle context.
Our practical evaluation demonstrates that we can detect, report, and assess security incidents below the human reaction time in the earlier mentioned prototype vehicles.
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.
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.
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.
Desinformation ist eine Konstante der politischen Kommunikation. Doch mit der Wahl Donald Trumps zum Präsidenten der Vereinigten Staaten und der Brexit-Abstimmung in Großbritannien erhielten bewusst lancierte Falschnachrichten eine neue gesellschaftliche Bedeutung. Denn nun wurde sichtbar, welche Wirkungen Falschmeldungen für demokratische Systeme haben. Der Band geht diesem Phänomen auf den Grund, indem er herausarbeitet, was “Fake News” sind. Er geht der Frage nach, wie, warum und von wem sie eingesetzt werden und reflektiert, was man gesellschaftlich und persönlich dagegen tun kann. Das Buch gibt zu diesem Zweck einen Überblick über den aktuellen Stand der empirischen Forschung zu Fake News und Desinformation, besonders mit Blick auf deren Verbreitung, Erkennbarkeit und Wirksamkeit. Zugleich diskutiert er in einer Mischung aus Essays, theoretischen Erörterungen und empirischen Studien die Herausforderungen von Desinformation für unsere Gesellschaft und beleuchtet so das Thema von allen Seiten.
The growing demand for electric vehicles (EV) in the last decade and the most recent European Commission regulation to only allow EV on the road from 2035 involved the necessity to design a cost-effective and sustainable EV charging station (CS). A crucial challenge for charging stations arises from matching fluctuating power supplies and meeting peak load demand. The overall objective of this paper is to optimize the charging scheduling of a hybrid energy storage system (HESS) for EV charging stations while maximizing PV power usage and reducing grid energy costs.
This goal is achieved by forecasting the PV power and the load demand using different deep learning (DL) algorithms such as the recurrent neural network (RNN) and long short-term memory (LSTM). Then, the predicted data are adopted to design a scheduling algorithm that determines the optimal charging time slots for the HESS. The findings demonstrate the efficiency of the proposed approach, showcasing a root-mean-square error (RMSE) of 5.78% for real-time PV power forecasting and 9.70%
for real-time load demand forecasting. Moreover, the proposed scheduling algorithm reduces the total grid energy cost by 12.13%.
People-centred reforestation is one of the ways to achieve natural climate solutions. Ghana has established a people-centred reforestation programme known as the Modified Taunya System (MTS) where local people are assigned degraded forest reserves to practice agroforestry. Given that the MTS is a people-centred initiative, socioeconomic factors are likely to have impact on the reforestation drive. This study aims to understand the role of translocal practices of remittances and visits by migrants on the MTS. Using multi-sited, sequential explanatory mixed methods and the lens of socioecological systems, the study shows that social capital and socioeconomic obligations of cash remittances from, as well as visits by migrants to their communities of origin play positive roles on reforestation under the MTS. Specifically, translocal households have access to, and use remittances to engage relatively better in the MTS than households that do not receive remittances. This shows that translocal practices can have a positive impact on the environment at the area of origin of migrants where there are people-centred environmental policies in place.
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.
Die deutsche Handelsgerichtsbarkeit zeichnet sich bis heute durch die Mitwirkung sachkundiger Laienrichter aus. Die Arbeit zeigt zunächst ausführlich die historischen Wurzeln und die Entwicklung der Handelsrichter in Italien, in Frankreich und in den deutschen Rechtskreisen. Dabei wird insbesondere auf die Entstehungsgeschichte des sog. deutschen Systems eingegangen. Im Anschluss analysiert der Verfasser die Wesensmerkmale der modernen KfH. In einem dritten Schritt werden die historischen Erkenntnisse als Lösungsansätze für aktuelle Reformbemühungen um die Zukunft der KfH nutzbar gemacht.
Trotz digitaler Vermittlung und körperlicher Distanz kommt es während Videokonferenzen zur Wahrnehmung von Nähe oder gemeinsamen Atmosphären. Solche Interaktionen können mit einer erweiterten neophänomenologischen Soziologie nach Hermann Schmitz theoretisch hergeleitet und empirisch untersucht werden. Ein Grounded-Theory-Zugriff mit Interviews als zentralem Erhebungsverfahren erlaubt die Analyse von Möglichkeiten und Grenzen dieses Beieinanderseins an physisch getrennten Orten. Die Videokonferenz zeigt, dass bei digitaler Kommunikation nicht allein die Technik Interaktionen ermöglicht, sondern erst die leidenschaftliche Konstruktionsarbeit der Teilnehmenden einen „Leiberspace“ schaffen kann, um sich digital vermittelt näherzukommen.
The identification and estimation of trends in hydroclimatic time series remains an important task in applied climate research. The statistical challenge arises from the inherent nonlinearity, complex dependence structure, heterogeneity and resulting non-standard distributions of the underlying time series. Quantile regressions are considered an important modeling technique for such analyses because of their rich interpretation and their broad insensitivity to extreme distributions. This paper provides an asymptotic justification of quantile trend regression in terms of unknown heterogeneity and dependence structure and the corresponding interpretation. An empirical application sheds light on the relevance of quantile regression modeling for analyzing monthly Central England temperature anomalies and illustrates their various heterogenous trends. Our results suggest the presence of heterogeneities across the considered seasonal cycle and an increase in the relative frequency of observing unusually high temperatures.
Prior to the emergence of Big Data and technologies such as Learning Analytics (LA), classroom research focused mainly on measuring learning outcomes of a small sample through tests. Research on online environments shows that learners’ engagement is a critical precondition for successful learning and lack of engagement is associated with failure and dropout. LA helps instructors to track, measure and visualize students’ online behavior and use such digital traces to improve instruction and provide individualized support, i.e., feedback. This paper examines 1) metrics or indicators of learners’ engagement as extracted and displayed by LA, 2) their relationship with academic achievement and performance, and 3) some freely available LA tools for instructors and their usability. The paper concludes with making recommendations for practice and further research by considering challenges associated with using LA in classrooms.