One or Two Things We know about Concept Drift -- A Survey on Monitoring Evolving Environments

The world surrounding us is subject to constant change. These changes, frequently described as concept drift, influence many industrial and technical processes. As they can lead to malfunctions and other anomalous behavior, which may be safety-critical in many scenarios, detecting and analyzing concept drift is crucial. In this paper, we provide a literature review focusing on concept drift in unsupervised data streams. While many surveys focus on supervised data streams, so far, there is no work reviewing the unsupervised setting. However, this setting is of particular relevance for monitoring and anomaly detection which are directly applicable to many tasks and challenges in engineering. This survey provides a taxonomy of existing work on drift detection. Besides, it covers the current state of research on drift localization in a systematic way. In addition to providing a systematic literature review, this work provides precise mathematical definitions of the considered problems and contains standardized experiments on parametric artificial datasets allowing for a direct comparison of different strategies for detection and localization. Thereby, the suitability of different schemes can be analyzed systematically and guidelines for their usage in real-world scenarios can be provided. Finally, there is a section on the emerging topic of explaining concept drift

Localization of Small Leakages in Water Distribution Networks using Concept Drift Explanation Methods

Facing climate change the already limited availability of drinking water will decrease in the future rendering drinking water an increasingly scarce resource. Considerable amounts of it are lost through leakages in water transportation and distribution networks. Leakage detection and localization are challenging problems due to the complex interactions and changing demands in water distribution networks. Especially small leakages are hard to pinpoint yet their localization is vital to avoid water loss over long periods of time. While there exist different approaches to solving the tasks of leakage detection and localization, they are relying on various information about the system, e.g. real-time demand measurements and the precise network topology, which is an unrealistic assumption in many real-world scenarios. In contrast, this work attempts leakage localization using pressure measurements only. For this purpose, first, leakages in the water distribution network are modeled employing Bayesian networks, and the system dynamics are analyzed. We then show how the problem is connected to and can be considered through the lens of concept drift. In particular, we argue that model-based explanations of concept drift are a promising tool for localizing leakages given limited information about the network. The methodology is experimentally evaluated using realistic benchmark scenarios

Model Driven Machine Improvement of COSY Based on ORM Data

The COoler SYnchrotron in Jülich accelerates and stores unpolarized and polarized proton or deuteron beams in the momentum range between 0.3 GeV/c and 3.65 GeV/c [*,**]. This, in combination with its diverse capabilities of phase space cooling and the flexibility of the lattice with respect to ion-optical settings makes COSY an ideal test facility for accelerator technology development. High demands on beam control and beam based measurements have to be fulfilled for future experiments such as the proposed precursor experiment for a direct measurement of the electric dipole moment of the deuteron (see [***] and references within). The analysis of measured orbit response matrices (ORM), which com- prise the focussing structure of the ring, allows for a better understand- ing of machine imperfections such as gradient errors and misalignments of quadrupole magnets. This contribution presents the development of a MAD-X based LOCO (Linear Optics from Closed Orbits) algorithm [****] in a C++ program aiming to calibrate and correct linear optics as well as improving beam control at COSY

Phase locking the spin precession in a storage ring

This letter reports the successful use of feedback from a spin polarization measurement to the revolution frequency of a 0.97 GeV/$c$ bunched and polarized deuteron beam in the Cooler Synchrotron (COSY) storage ring in order to control both the precession rate ($\approx 121$ kHz) and the phase of the horizontal polarization component. Real time synchronization with a radio frequency (rf) solenoid made possible the rotation of the polarization out of the horizontal plane, yielding a demonstration of the feedback method to manipulate the polarization. In particular, the rotation rate shows a sinusoidal function of the horizontal polarization phase (relative to the rf solenoid), which was controlled to within a one standard deviation range of $\sigma = 0.21$ rad. The minimum possible adjustment was 3.7 mHz out of a revolution frequency of 753 kHz, which changes the precession rate by 26 mrad/s. Such a capability meets a requirement for the use of storage rings to look for an intrinsic electric dipole moment of charged particles

Numerical simulations of black-hole binaries and gravitational wave emission

We review recent progress in numerical relativity simulations of black-hole (BH) spacetimes. Following a brief summary of the methods employed in the modeling, we summarize the key results in three major areas of BH physics: (i) BHs as sources of gravitational waves (GWs), (ii) astrophysical systems involving BHs, and (iii) BHs in high-energy physics. We conclude with a list of the most urgent tasks for numerical relativity in these three areas.Comment: Updated version, references added; 47 pages, 3 figure

Development of beam diagnostic systems for electric dipole moment measurements at particle accelerators

One puzzle of modern physics is the observed matter over antimatter dominance in the universe. A common explanation for this dominance is based on CP violating sources. In general CP violation is included in the Standard Model (SM) of particle physics, but the amount of CP violation is not sufficient to explain the measured matter-antimatter-asymmetry. Therefore, additional sources beyond the SM are searched for. One way of finding these sources is the search for permanent Electric Dipole Moments (EDMs) of fundamental particles, since they violate CP symmetry. The search for EDMs started decades ago in the sector of neutral particles. Up to now all measurements of EDMs are compatible with zero. Complementary to the neutral particles, the EDMs of charged particles, like the proton or deuteron, are of interest to disentangle possible sources of CP violation. For the charged particles, new experimental methods are needed. These methods are based on the usage of dedicated particle storage rings. In order to develop a dedicated storage ring, the JEDI (Jülich Electric Dipole moment Investigations) collaboration started experiments at the existing magnetic storage ring COSY(Cooler Synchrotron), at Forschungszentrum Jülich in Germany. Within the years 2017 to 2019, a first direct EDM measurement of the deuteron by using a radio frequency Wien filter is planned. In this experimental setup, a non zero EDM would lead to a polarization buildup out of the storage ring plane into the vertical direction. This buildup can also be created by interactions of the magnetic dipole moment with magnetic fields, if the trajectory of the particle beam is not centered in the magnetic elements of the accelerator. In order to counteract this systematic error sources, an orbit correction scheme, including Beam Position Monitors (BPMs) and corrector magnets is needed. The existing BPM system at COSY, including the readout electronics, allows a position measurement with a statistical resolution of 1 μm for a centered beam. In addition to the statistical resolution, the accuracy is one important characteristic for a beam position measurement. This accuracy is in the order of 0.1mm for the existing electronics and one major source of systematic uncertainties for EDM experiments. As a conclusion of this result, an upgrade program of the BPM readout has started with the goal to reach an accuracy and resolution of 4 μm. In order to correct the measured beam position to zero, a correction algorithm is developed and benchmarked. This correction algorithm includes the soft-ware development of an automated measurement of the Orbit Response Matrix (ORM) and a detailed analysis of the inversion of this matrix. The inverted matrix is used to calculate deflection angles for the corrector magnets in order to correct the beam position in all elements. Applying the correction algorithm results in an orbit RMS (Root Mean Square) of 2mm, which is not sufficient for EDM measurements and much worse than the theoretical limit derived from the BPM resolution and accuracy. Simulations have been performed to explain this discrepancy. The simulations indicate, that the magnets positions are known to a precision of 0.5mm. In a survey of all magnets this prediction was confirmed. Based on these results an alignment campaign started and is ongoing. Besides the realignment of the magnets, additional corrector magnets and additional BPMs can be placed within the simulations to improve the orbit quality. Upgrading COSY with additional elements and realigning the magnets should lead to an orbit RMS of 10 μm, which is in the same range as the resolution and accuracy of the upgraded BPM electronics. Besides the correction algorithm, which is a starting point of a live orbit feedback, the connection of spin tune changes and ORM measurements was analyzed. As a result of this analysis, a new method to measure the dispersion function at corrector magnets is developed and presented in this thesis

Towards non-parametric drift detection via Dynamic Adapting Window Independence Drift Detection (DAWIDD)

Hinder F, Artelt A, Hammer B. Towards non-parametric drift detection via Dynamic Adapting Window Independence Drift Detection (DAWIDD). In: Proceedings of the 37th International Conference on Machine Learning. 2020

Feature Selection for Concept Drift Detection

Hinder F, Hammer B. Feature Selection for Concept Drift Detection. In: Verleysen M, ed. ESANN 2023 Proceedings. 2023

DeepView: Visualizing Classification Boundaries of Deep Neural Networks as Scatter Plots Using Discriminative Dimensionality Reduction

Schulz A, Hinder F, Hammer B. DeepView: Visualizing Classification Boundaries of Deep Neural Networks as Scatter Plots Using Discriminative Dimensionality Reduction. In: Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, {IJCAI-20}. 2020.Machine learning algorithms using deep architectures have been able to implement increasingly powerful and successful models. However, they also become increasingly more complex, more difficult to comprehend and easier to fool. So far, most methods in the literature investigate the decision of the model for a single given input datum. In this paper, we propose to visualize a part of the decision function of a deep neural network together with a part of the data set in two dimensions with discriminative dimensionality reduction. This enables us to inspect how different properties of the data are treated by the model, such as outliers, adversaries or poisoned data. Further, the presented approach is complementary to the mentioned interpretation methods from the literature and hence might be even more useful in combination with those. Code is available at https://github.com/LucaHermes/DeepVie