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Abstract
Effective quality control is essential for efficient and successful manufacturing processes in the era of Industry 4.0. Artificial Intelligence solutions are increasingly employed to enhance the accuracy and efficiency of quality control methods. In Computer Numerical Control machining, challenges involve identifying and verifying specific patterns of interest or trends in a time-series dataset. However, this can be a challenge due to the extensive diversity. Therefore, this work aims to develop a methodology capable of verifying the presence of a specific pattern of interest in a given collection of time-series. This study mainly focuses on evaluating One-Class Classification techniques using Linear Frequency Cepstral Coefficients to describe the patterns on the time-series. A real-world dataset produced by turning machines was used, where a time-series with a certain pattern needed to be verified to monitor the wear offset. The initial findings reveal that the classifiers can accurately distinguish between the time-series' target pattern and the remaining data. Specifically, the One-Class Support Vector Machine achieves a classification accuracy of 95.6 % +/- 1.2 and an F1-score of 95.4 % +/- 1.3.

Abstract
In a competitive business landscape heavily reliant on information and communication technology, organisations must be prepared to address disruptions in their business operations. Business continuity management involves effective planning for the swift reestablishment of business processes in the short term. However, there are still obstacles to implementing business continuity plans, which can be justified by various factors. The purpose of this study is to present the perspectives and future research paths based on a systematic literature review from the peer-reviewed literature published from 1 January 2000 to 31 December 2021. This systematic literature review adheres to the guidelines established by evidence-based software engineering and leverages the Parsifal online tool. The primary research results identify and establish connections between the common components and activities of business continuity management as defined in international standards and frameworks to identify gaps in the existing knowledge. These findings will contribute to the development of a framework that provides a practical approach applicable to organisations of all sizes, taking into account each aspect of business continuity management, with a particular emphasis on information and communication technology systems. This paper's contribution lies in offering insights from a systematic literature review regarding the strategic principles for designing and implementing a business continuity plan, along with a comprehensive overview of related research. Furthermore, it presents a path forward to guide future research efforts aimed at addressing the gaps in the literature concerning continuity planning.

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FIDO2 is becoming a defacto standard for passwordless authentication. Using FIDO2 and WebAuthn, web applications can enable users to associate cryptographic credentials to their profiles, and then rely on an external authenticator (e.g., a hardware token plugged into the USB port) to perform strong signature-based authentication when accessing their accounts. The security of FIDO2 has been theoretically validated, but these analyses follow the threat model adopted in the FIDO2 design and explicitly exclude some attack vectors as being out of scope. In this paper we show that two of these attacks, which appear to be folklore in the community, are actually straightforward to launch in practice (user PIN extraction, impersonation and rogue key registration). We demonstrate a deployment over vanilla Linux distributions and commercial FIDO2 authenticators. We discuss the potential impact of our results, which we believe will contribute to the improvement of future versions of the protocol.

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Approximate agreement has long been relegated to the sidelines compared to exact consensus, with its most notable application being clock synchronisation. Other proposed applications stemming from control theory target multi-agent consensus, namely for sensor stabilisation, coordination in robotics, and trust estimation. Several proposals for approximate agreement follow the Mean Subsequence Reduce approach, simply applying different functions at each phase. However, taking clock synchronisation as an example, applications do not fit neatly into the MSR model: Instead they require adapting the algorithms' internals. Our contribution is two-fold. First, we identify additional configuration points, establishing a more general template of MSR approximate agreement algorithms. We then show how this allows us to implement not only generic algorithms but also those tailored for specific purposes (clock synchronisation). Second, we propose a toolkit for making approximate agreement practical, providing classical implementations as well as allow these to be configured for specific purposes. We validate the implementation with classical algorithms and clock synchronisation.

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