Now showing 1 - 10 of 4271
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Quantum computer-aided job scheduling for storage and retrieval systems

2024 , Windmann, Stefan

In this paper, a quantum computer-aided approach to job scheduling for automated storage and retrieval systems is introduced. The approach covers application cases, where various objects need to be transported between storage positions and the order of transport operations can be freely chosen. The objective of job scheduling is to arrange the transport operations in a sequence, where the cumulative costs of the transport operations and empty runs between subsequent transport operations are minimized. The scheduling problem is formulated as an asymmetric quadratic unconstrained binary optimization (QUBO) problem, in which the transport operations are modeled as nodes and empty runs are modeled as edges, with costs assigned to each node and each edge. An Quantum Approximate Optimization Algorithm (QAOA) is used to solve the QUBO. Evaluations of the quantum computer-aided job scheduling approach have been conducted on the IBM Q System One quantum computer in Ehningen. In particular, the running time for the solution of the QUBO has been investigated, as well as the scalability of the approach with respect to the required number of qubits.

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Evaluation of XAI Methods in a FinTech Context

2024 , Gawantka, Falko , Just, Franz , Ullrich, Markus , Savelyeva, Marina , Lässig, Jörg

As humans, we automate more and more critical areas of our lives while using machine learning algorithms to make autonomous decisions. For example, these algorithms may approve or reject job applications/loans. To ensure the fairness and reliability of the decision-making process, a validation is required. The solution for explaining the decision process of ML models is Explainable Artificial Intelligence (XAI). In this paper, we evaluate four different XAI approaches - LIME, SHAP, CIU, and Integrated Gradients (IG) - based on the similarity of their explanations. We compare their feature importance values (FIV) and rank the approaches from the most trustworthy to the least trustworthy. This ranking can serve as a specific fidelity measure of the explanations provided by the XAI methods.

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Investigation of the polymer material perforation time: comparison between two fiber laser wavelengths

2024 , Romano, Clément , Ritt, Gunnar , Henrichsen, Michael , Eichhorn, Marc , Kieleck, Christelle

This study investigated the perforation time of polyamide 6.6 using fiber lasers at two different wavelengths: 1070 and 1943 nm. The novelty of this research lies in the comparison of perforation times at equivalent laser irradiances on the polymer sample with two different colors of polyamide 6.6: natural and black. The results revealed that, at comparable irradiance levels and beam diameters, the 1943 nm laser source perforated the polyamide 6.6 sample faster than the 1070 nm laser source. The difference in perforation time was found to be significantly higher for natural-colored polyamide 6.6 compared to black-colored polyamide 6.6. These findings suggest that, for material processing of polyamide 6.6, especially in terms of perforation, the use of 2 μm laser sources should be privileged over 1 μm laser sources.

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Fault detection in automated production systems based on a long short-term memory autoencoder

2024 , Windmann, Stefan , Westerhold, Tim

In this paper, a hybrid model of regularized Long Short-Term Memory (LSTM) and autoencoder for fault detection in automated production systems is proposed. The presented LSTM autoencoder is used as a stochastic process model, which captures the normal behavior of a production system and allows to predict the probability distribution of sensor data. Discrepancies between the observed sensor data and the predicted probability density distribution are detected as potential faults. The approach combines the advantages of LSTMs and autoencoders: The correlations between individual sensor signals are exploited by an autoencoder, while the temporal dependencies are captured by LSTM neurons. A key challenge in training such a process model from historical data is to control the information passed through the latent space of the autoencoder. Different regularization methods are investigated for this purpose. Fault detection with the proposed LSTM autoencoder has been evaluated on the use case of an industrial penicillin production, achieving significantly improved results in comparison to the baseline LSTM.

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The K-functional and reiteration theorems for left and right spaces, Part I

2024 , Doktorski, Leo , Fernández-Martínez, Pedro , Signes, Teresa

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Temperature investigation of low SWaP thulium-doped fiber lasers

2024 , Panitzek, Dieter , Romano, Clément , Eichhorn, Marc , Kieleck, Christelle

We investigate the temperature dependence of an in-band core-pumped thulium-doped fiber laser with a low SWaP (size, weight, and power) architecture. The temperature investigation is carried out both experimentally and numerically by a simulation model. We demonstrate experimentally that the investigated setup is resistant for temperatures till 353 K. In addition, we explain the observed behavior by considering the temperature depended spectroscopic parameters of thulium-doped silica fibers. Finally, a numerical investigation is carried out for higher temperatures up to 573 K and higher output powers up to 12 W as well as for different wavelengths and show that the considered fiber lasers works still efficient at these temperature ranges. We show the reliability of the considered thulium-doped fiber laser architecture for applications in harsh environment.

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W-Net 4.0: Cloud-basierte Plattform zur Dokumentation, Simulation und Betriebsoptimierung von rohrgebundenen Versorgungssystemen

2024 , Bernard, Thomas , Ziebarth, Mathias , Canzler, Armin , Keifenheim, Heiko , Wiese, Susanne , Deuerlein, Jochen , Parra, Salomé

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High-power thulium-doped fiber MOPA emitting at 2036 nm

2024 , Romano, Clément , Panitzek, Dieter , Lorenz, Dominik , Forster, Patrick , Eichhorn, Marc , Kieleck, Christelle

An all-fiber laser system is presented with a simple MOPA configuration composed of a seed laser followed by a one-stage high-power amplifier. The seed delivers 10 W of output power at 2036 nm. The high-power amplifier operates with a high slope efficiency of 59 %. An output power of 937 W is demonstrated with a close to diffraction limited beam quality. No nonlinear effects were observed.

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Cognitive User Modeling for Adaptivity in Serious Games

2024 , Streicher, Alexander , Bauer, Kolja

Accurate user models that capture information such as needs and knowledge levels are a central part of adaptive e-learning systems, which is all the more important in a post-pandemic world with more individualized learning. In this article, we report on the application of a Bayesian cognitive state modeling approach to adaptive educational serious games. Adaptivity needs information on the users as control variables, e.g., high or low cognitive load. Typically, this information is encoded in user models. One approach to building user models is to use tools from cognitive sciences such as Bayesian cognitive state modeling. However, cognitive modeling tools for adaptivity are sparse and can be difficult to implement. The main research question of this work is how to apply cognitive modeling tools to serious games to control adaptivity. The contribution of this article is the concept of how to implement cognitive modeling for adaptive serious games. Our approach makes use of standardized Experience API (xAPI) tracking data to facilitate applicability. We investigate how to compute quantitative measures of user performance to control adaptive responses. The implemented system has been evaluated in a user study with a serious game for image interpretation. The study results show a moderate correlation between self-assessed and computed variables.

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A survey of the state of the art in sensor-based sorting technology and research

2024 , Maier, Georg , Gruna, Robin , Längle, Thomas , Beyerer, Jürgen

Sensor-based sorting describes a family of systems that enable the removal of individual objects from a material stream. The technology is widely used in various industries such as agriculture, food, mining, and recycling. Examples of sorting tasks include the removal of fungus-infested grains, the enrichment of copper content in copper mining or the sorting of plastic waste according to the type of plastic. Sorting decisions are made based on information acquired by one or more sensors. A particular strength of the technology is the flexibility in sorting decisions, which is achieved by using various sensors and programming the data analysis. However, a comprehensive understanding of the process is necessary for the development of new sorting systems that can address previously unresolved tasks. This survey is aimed at innovative researchers and practitioners who are unfamiliar with sensor-based sorting or have only encountered certain aspects of the overall process. The references provided serve as starting points for further exploration of specific topics.