Trade Union Politics as a Countermovement? A Polaniyan Perspective

The article develops a conceptual proposal for the inquiry of trade unions. On the basis of Karl Polanyis theory, four patterns of political mobilization applied by trade unions in the current Transformation are pointed out

Group models for fusion systems

We study group models for fusion systems and construct homology decompositions for the models of Robinson and Leary-Stancu type.Comment: 13 page

Homology decompositions and groups inducing fusion systems

We relate the construction of groups which realize saturated fusion systems and signaliser functors with homology decompositions of p-local finite groups. We prove that the cohomology ring of Robinson's construction is in some precise sense very close to the cohomology ring of the fusion system it realizes

The Free Loop Space Homology of (n−1)(n-1)-connected 2n2n-manifolds

Our goal in this paper is to compute the integral free loop space homology of $(n-1)$-connected $2n$-manifolds $M$, $n\geq 2$. We do this when $n\neq 2,4,8$, or when $n\neq 2$ and $\tilde H^*(M)$ has trivial cup product squares, though the techniques used here should extend to a much wider range of manifolds. We also give partial information concerning the action of the Batalin-Vilkovisky operator.Comment: JHR

The loss of material from the cathode of metal arcs

A study was made of the effect of arc length, cathode thickness, current strength, gas pressure and the chemical nature of the cathode material and filling gases upon the material loss from Cu, Fe, and Ag cathodes in arcs. The results show that the analysis of the phenomenon is complex and the energy balance is difficult to formulate

BINet: Multi-perspective Business Process Anomaly Classification

In this paper, we introduce BINet, a neural network architecture for real-time multi-perspective anomaly detection in business process event logs. BINet is designed to handle both the control flow and the data perspective of a business process. Additionally, we propose a set of heuristics for setting the threshold of an anomaly detection algorithm automatically. We demonstrate that BINet can be used to detect anomalies in event logs not only on a case level but also on event attribute level. Finally, we demonstrate that a simple set of rules can be used to utilize the output of BINet for anomaly classification. We compare BINet to eight other state-of-the-art anomaly detection algorithms and evaluate their performance on an elaborate data corpus of 29 synthetic and 15 real-life event logs. BINet outperforms all other methods both on the synthetic as well as on the real-life datasets