Dynamically Weighted Federated k-Means

Federated clustering, an integral aspect of federated machine learning, enables multiple data sources to collaboratively cluster their data, maintaining decentralization and preserving privacy. In this paper, we introduce a novel federated clustering algorithm named Dynamically Weighted Federated k-means (DWF k-means) based on Lloyd's method for k-means clustering, to address the challenges associated with distributed data sources and heterogeneous data. Our proposed algorithm combines the benefits of traditional clustering techniques with the privacy and scalability benefits offered by federated learning. The algorithm facilitates collaborative clustering among multiple data owners, allowing them to cluster their local data collectively while exchanging minimal information with the central coordinator. The algorithm optimizes the clustering process by adaptively aggregating cluster assignments and centroids from each data source, thereby learning a global clustering solution that reflects the collective knowledge of the entire federated network. We address the issue of empty clusters, which commonly arises in the context of federated clustering. We conduct experiments on multiple datasets and data distribution settings to evaluate the performance of our algorithm in terms of clustering score, accuracy, and v-measure. The results demonstrate that our approach can match the performance of the centralized classical k-means baseline, and outperform existing federated clustering methods like k-FED in realistic scenarios

Recovering Short Generators of Principal Fractional Ideals in Cyclotomic Fields of Conductor p^\alpha q^\beta

Some recent cryptographic schemes rely on the hardness of finding a shortest generator of a principal (fractional) ideal in an algebraic number field $K$ in the logarithmic embedding with some guaranteed small generator, given some $\mathbb{Z}$-basis of the principal ideal. This problem can be split into two parts. First, recover some arbitrary generator of the ideal, which is known as the principal ideal problem (PIP). Second, transform this generator into some shortest generator. The first part is known to be solvable in polynomial time on quantum computers for cyclotomic fields of prime-power conductor and for arbitrary number fields under the generalized Riemann hypothesis, see Campbell, Biasse et al. The second part is known to be solvable in polynomial time on classical computers for cyclotomic number fields of prime-power conductor, see Cramer, Ducert Peikert and Regev. In this work we entirely focus on the second task and extend the work of Cramer, Ducas, Peikert and Regev to cyclotomic fields K=\Q(\xi_m) of conductor $m=p^\alpha q^\beta$, where $p,q$ are distinct odd primes. Their algorithmic approach mainly relies on the fact that there is a well suited basis of the group of cyclotomic units which are a subgroup of \OK^\times=\mathbb{Z}[\xi_m]^\times with small enough finite index. We consider the group generated by these elements in the case that $m=p^\alpha q^\beta$ and introduce a new notion for odd prime pairs $(p,q)$, named generator prime pairs, which provides a criterion to check whether the index of this subgroup in \OK^\times is finite or not. We prove, that this basis is well suited to recover some shortest generator of a principal ideal in quantum polynomial time in the finite case, i.e., if $m=p^\alpha q^\beta$ for some generator prime pair $(p,q)$ with sufficiently large $\alpha,\beta \in \mathbb{n}$ with bounded distance. Further, we consider the approximate ideal shortest vector problem in cyclotomic fields \Q(\xi_m), where the task is to find short elements in arbitrary ideals $\mathfrak{a}$ in \OK in the Minkowski embedding. In our second main contribution, we generalize the results of Cramer and argue, that one can efficiently solve the ideal shortest vector problem with an approximation factor $\exp(O(\sqrt{m}))$ in cyclotomic fields of conductor $m=p^\alpha q^\beta$ on quantum computers, if $(p,q)$ is an $(\alpha,\beta)$-generator prime pair

Modeling of Self-Organizing Systems: An Overview

This paper gives a systematic overview on modeling formalisms suitable for modeling self-organizing systems. We distinguish between micro-level modeling and macro-level modeling. On the micro level, the behavior of each entity and the interaction between different object must be described by the model. Macrolevel modeling abstracts from the individual entities and only looks at the behavior of the system variables of interest. The differentiations between discrete and continuous time and between discrete and continuous state space lead to different descriptions of the model

A Quantum Computing Approach for the Unit Commitment Problem

Planning energy production is a challenging task due to its cost-sensitivity, fast-moving energy markets, uncertainties in demand, and technical constraints of power plants. Thus, more complex models of this so-called \emph{unit commitment problem (UCP)} have to be solved more rapidly, a task that probably can be solved more efficiently via quantum computing. In this article, we model a UCP with minimum running and idle times as a quadratic unconstrained optimization problem to solve it on quantum computing hardware. First experiments confirm the advantages of our formulation in terms of qubit usage and connectivity and most importantly solution quality.Comment: Accepted at OR Proceedings 202

Recovering Short Generators of Principal Fractional Ideals in Cyclotomic Fields of Conductor pαqβp^\alpha q^\beta

Several recent cryptographic constructions - including a public key encryption scheme, a fully homomorphic encryption scheme, and a candidate multilinear map construction - rely on the hardness of the short generator principal ideal problem (SG-PIP): given a $\mathbb{Z}$-basis of some principal (fractional) ideal in an algebraic number field that is guaranteed to have an exceptionally short generator with respect to the logarithmic embedding, find a shortest generator of the principal ideal. The folklore approach to solve this problem is to split it into two subproblems. First, recover some arbitrary generator of the ideal, which is known as the principal ideal problem (PIP). Second, solve a bounded distance decoding (BDD) problem in the log-unit lattice to transform this arbitrary generator into a shortest generator of the ideal. The first problem, i.e., solving the PIP, is known to be solvable in polynomial time on quantum computers for arbitrary number fields under the generalized Riemann hypothesis due to Biasse and Song. Cramer, Ducas, Peikert, and Regev showed, based on the work of Campbell, Groves, and Shepherd, that the second problem can be solved in polynomial time on classical computers for cyclotomic number fields of prime-power conductor. In this work, we extend the work of Cramer, Ducas, Peikert, and Regev to cyclotomic number fields $K=\mathbb{Q}(\xi_m)$ of conductor $m=p^\alpha q^\beta$, where $p,q$ are distinct odd primes. In more detail, we show that the second problem can be solved in classical polynomial time (with quantum polynomial time precomputation) under some sufficient conditions, if $(p,q)$ is an $(\alpha, \beta)$-generator prime pair, a new notion introduced in this work. We further provide experimental evidence that suggests that roughly $35\%$ of all prime pairs are $(\alpha, \beta)$-generator prime pairs for all $\alpha$ and $\beta$. Combined with the work of Biasse and Song our results show that under sufficient conditions the SG-PIP can be solved in quantum polynomial time in cyclotomic number fields of composite conductor of the form $p^\alpha q^\beta$

Digital Ethics Canvas: A Guide For Ethical Risk Assessment And Mitigation In The Digital Domain

Ethical concerns in the digital domain are growing with the extremely fast evolution of technology and the increasing scale at which software is deployed, potentially affecting our societies globally. It is crucial that engineers evaluate more systematically the impacts their solutions can have on individuals, groups, societies and the environment. Ethical risk analysis is one of the approaches that can help reduce “ethical debt”, the unpaid cost generated by ethically problematic technical solutions. However, previous research has identified that novices struggle with the identification of risks and their mitigation. Our contribution is a visual tool, the Digital Ethics Canvas, specifically designed to help engineers scan digital solutions for a range of ethical risks with six “lenses”: beneficence, non-maleficence, privacy, fairness, sustainability and empowerment. In this paper, we present the literature background behind the design of this tool. We also report on preliminary evaluations of the canvas with novices (N=26) and experts (N=16) showing that the tool is perceived as practical and useful, with positive utility judgements from participants

Vergleichende Sprachbiographieforschung: Migrationsbedingte Brüche in unmittelbarer, erinnerter und vererbter Migration

Migrationsbedingte „Brüche“, die teilweise indirekt und teilweise direkt geäußert werden, stellen ein häufig wiederkehrendes Thema in der Analyse von Sprachbiographien dar. Der Beitrag verortet zunächst die Untersuchung sprachbiographischer Interviews im Kontext der Migrationslinguistik, sodass die Prozesse des Sprachgebrauchs aus sprecherindividueller Perspektive im Zentrum stehen. Anhand sprachbiographischer Interviewauszüge wird anschließend verdeutlicht, dass sprachbiographische Brüche in der Migration in unterschiedlichen Formen auftreten und dass sie sowohl als unmittelbar erlebte als auch als erinnerte oder von der Elterngeneration vermittelte Ereignisse von sprachbiographischer Bedeutung sind. Analysiert werden Beispiele unterschiedlicher Erhebungen mit jungen Geflüchteten aus Iran, Afghanistan und Syrien sowie Sprecherinnen und Sprechern mit türkischem, bosnischem und irakischem Migrationshintergrund. Durch die Gegenüberstellung von Migrationserfahrungen und den darin enthaltenen sprachbiographischen Brüchen können individuelle und gesellschaftliche Muster deutlich werden, die sich auf den Verlauf von Migration und Inklusion sowie auf Spracherwerb und Spracherhalt auswirken. Keywords: Mehrsprachigkeit, Migration, Flucht, Biographi

A canvas for the ethical design of learning experiences with digital tools

The use of digital tools has drastically increased in engineering education, accelerated by the COVID-19 pandemic. These tools generate important ethical issues, in particular in terms of privacy and fairness. However, very few teacher training programmes address those topics, which means that teachers are often left to figure out by themselves how to address these issues when they want (or have) to use digital tools in their teaching. In this workshop, participants will be introduced to a pragmatic approach to the ethical design of learning experiences that involve digital tools using a visual thinking guide called a ‘canvas’. Applied and hands-on, this workshop will help participants to develop a practical understanding of the specific ethical issues related to the use of digital tools in teaching and to integrate ethical reflection into design processes when digital technology is involved

Rule-Makers or Rule-Takers? Exploring the Transatlantic Trade and Investment Partnership

The Transatlantic Trade and Investment Partnership (TTIP) is an effort by the United States and the European Union to reposition themselves for a world of diffuse economic power and intensified global competition. It is a next-generation economic negotiation that breaks the mould of traditional trade agreements. At the heart of the ongoing talks is the question whether and in which areas the two major democratic actors in the global economy can address costly frictions generated by their deep commercial integration by aligning rules and other instruments. The aim is to reduce duplication in various ways in areas where levels of regulatory protection are equivalent as well as to foster wide-ranging regulatory cooperation and set a benchmark for high-quality global norms. In this volume, European and American experts explain the economic context of TTIP and its geopolitical implications, and then explore the challenges and consequences of US-EU negotiations across numerous sensitive areas, ranging from food safety and public procurement to economic and regulatory assessments of technical barriers to trade, automotive, chemicals, energy, services, investor-state dispute settlement mechanisms and regulatory cooperation. Their insights cut through the confusion and tremendous public controversies now swirling around TTIP, and help decision-makers understand how the United States and the European Union can remain rule-makers rather than rule-takers in a globalising world in which their relative influence is waning

Increasing test specificity without impairing sensitivity: lessons learned from SARS-CoV-2 serology

Background: Serological tests are widely used in various medical disciplines for diagnostic and monitoring purposes. Unfortunately, the sensitivity and specificity of test systems are often poor, leaving room for false-positive and false-negative results. However, conventional methods were used to increase specificity and decrease sensitivity and vice versa. Using SARS-CoV-2 serology as an example, we propose here a novel testing strategy: the € sensitivity improved two-test' or € SIT²' algorithm. Methods: SIT² involves confirmatory retesting of samples with results falling in a predefined retesting zone of an initial screening test, with adjusted cut-offs to increase sensitivity. We verified and compared the performance of SIT² to single tests and orthogonal testing (OTA) in an Austrian cohort (1117 negative, 64 post-COVID-positive samples) and validated the algorithm in an independent British cohort (976 negatives and 536 positives). Results: The specificity of SIT² was superior to single tests and non-inferior to OTA. The sensitivity was maintained or even improved using SIT² when compared with single tests or OTA. SIT² allowed correct identification of infected individuals even when a live virus neutralisation assay could not detect antibodies. Compared with single testing or OTA, SIT² significantly reduced total test errors to 0.46% (0.24-0.65) or 1.60% (0.94-2.38) at both 5% or 20% seroprevalence. Conclusion: For SARS-CoV-2 serology, SIT² proved to be the best diagnostic choice at both 5% and 20% seroprevalence in all tested scenarios. It is an easy to apply algorithm and can potentially be helpful for the serology of other infectious diseases