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The International Symposium on Memory systems

作者： L J Gokul Vasan Éder F. Zulian Christian Weis Matthias Jung Norbert Wehn Nvidia Germany Microelectronic Systems Design Research Group University of Kaiserslautern Germany Fraunhofer Institute for Experimental Software Engineering (IESE) Germany Microelectronic Systems Design Research Group TU Kaiserslautern Germany

ISBN: (纸本)9781450385701

In advanced scalable multiprocessor systems with multiple applications running concurrently, the optimal utilization of memory resources plays an essential role in achieving high system performance and energy efficiency. Locality of reference is one of the basis of memory management techniques. In operating systems, the memory management benefits from temporal and spatial locality when deciding which page shall be moved down the memory hierarchy to make room for a new page. However, current algorithms are oblivious to the moments when individual tasks transition to a new working set, which leads to suboptimal decisions. Furthermore, the eviction of idle pages from main memory is postponed to the last minute, which leads to system unresponsiveness and thrashing. In this context, memory locality reasoning based on the phase transition model is a central aspect to consider. We perceive that incorporating such a model in memory management algorithms provides the operating system with ways to trigger proactive page reclamation or compaction, to collect memory related statistics, and to trigger other crucial decision-making. In this paper, we present for the first time a hardware-agnostic online working set change detection algorithm for each process in a system. The working set change is detected with incomplete knowledge of a task’s memory access behavior. Our novel online algorithm perceives the occurrence of concavity in a program’s lifetime function as an outlier and heuristically attempts to classify such from the normal observations. Furthermore, we implemented and evaluated our solution in the Linux kernel. It executes with time and space complexity. Evaluations using real-world data-intensive applications show that the algorithm detects the working set change with an average accuracy of 89% and F0.5-Score of 74%, adding negligible computation overhead of 0.506% in average.

关键词： online detection memory management locality of reference phase transition behavior working set paging

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Transfer of Acoustic Wireless Power and data Through a Metal Wall Using a Common Link with Higher Resonance Modes

Transfer of Acoustic Wireless Power and data Through a Metal...

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Micro and Nanotechnology for Power Generation and Energy Conversion Applications (PowerMEMS)

作者： Bibhu Kar Thomas Schaechtle Stefan J. Rupitsch Ulrike Wallrabe IMTEK - Department of Microsystems Engineering Laboratory for Microactuators University of Freiburg Germany IMTEK - Department of Microsystems Engineering Laboratory for Electrical Instrumentation and Embedded Systems University of Freiburg Germany Fraunhofer Institute for Highspeed Dynamics Ernst-Mach-Institute (EMI) Freiburg Germany

ISBN: (纸本)9781665493079

For a wireless power and data transmission system, when a shared link is used for both purposes, the cross-talk interference from higher harmonics of the power transfer interface affects the reliability of bidirectional data communication. In literature [1] and most applications, the carrier frequency for data transfer is kept at least one order of magnitude higher than the power transfer frequency so that the cross-talk can be minimized, but not eradicated completely. The opposite, however, selecting an operational frequency of the data transfer lower than that of the power allows for extracting the data with a simple low pass filter instead of bandpass filters. Moreover, harmonics from the power transfer interface cannot fall into the data communication band. To exploit this possibility for a shared ultrasonic link, we present a novel technique to transfer power and data through a 20 mm thick metal wall, involving only one pair of transducers while keeping the data transfer frequency lower than the power transfer frequency.

关键词： Wireless communication Wireless sensor networks Transducers Resonant frequency Data transfer Harmonic analysis Acoustics

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Self-Organization and Collaboration in Robotic Manufacturing systems

Self-Organization and Collaboration in Robotic Manufacturing...

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IEEE International Conference on Automation Science and engineering (CASE)

作者： Andreas Frotzscher Xiao Chen Duy Lam Tran Thore Goll Hamid Sadeghian Fan Wu Martin Dehmel Tommy Wohlfahrt Matthias Riedl Sami Haddadin Fraunhofer Institute for Integrated Circuits IIS Engineering of Adaptive Systems EAS Dresden Germany Munich Institute of Robotics and Machine Intelligence (MIRMI) Technical University of Munich Munich Germany ifak e.V. Magdeburg Germany Franka Emika GmbH Munich Germany

The flexibility and adaptability of smart production systems are achieved through the use of autonomous and collaborating production assets. However, these systems still heavily rely on a central control unit to supervise and coordinate assets, as well as adapt to new demands. Additionally, these systems require reliable wireless connectivity to function effectively. This paper summarizes three contributions to autonomous manufacturing systems. Firstly, a system architecture that co-designs communication control for collaborating production assets is proposed, enabling dynamic trade-off negotiations between the control application and the communication network. Secondly, a novel approach for the self-organization of assets that can adapt in real-time is introduced. Finally, we present a collaborating strategy that facilitates close collaboration between robots while considering the performance of the wireless communication system in use.

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Integration of the A2C Algorithm for Production Scheduling in a Two-Stage Hybrid Flow Shop Environment

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Procedia Computer Science 2022年 200卷 585-594页

作者： Falk T. Gerpott Sebastian Lang Tobias Reggelin Hartmut Zadek Poti Chaopaisarn Sakgasem Ramingwong Institute of Logistics and Material Handling Systems Otto von Guericke University Magdeburg Universitätsplatz 2 39106 Magdeburg Germany Fraunhofer Institute for Factory Operation and Automation IFF Sandtorstraße 22 39106 Magdeburg Germany Department of Industrial Engineering Faculty of Engineering Chiang Mai University Chiang Mai 50200 Thailand

The paper introduces an approach to apply reinforcement learning (RL) for production scheduling in a two-stage hybrid flow shop (THFS) production system. The Advantage-Actor Critic (A2C) method is used to train multiple agents to minimize the total tardiness and makespan of a production program. The two-stage hybrid flow shop scheduling problem is a NP-hard combinatorial optimization problem that describes a production system with two stages, each consisting of a set of parallel machines. Our concept combines a Discrete-Event Simulation with a pre-implemented RL algorithm using Stable Baselines3. Since similar research often lacks concrete implementation information, the configuration of the OpenAI Gym interface and the agent-environment interaction is presented.

关键词： Artificial intelligenece Reinforcement learning Advantage Actor-Critic Flow shop Scheduling

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Drivetrain simulation using variational autoencoders

arXiv

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arXiv 2025年

作者： Sharma, Pallavi Urrea-Quintero, Jorge-Humberto Bogdan, Bogdan Ciotec, Adrian-Dumitru Vasilie, Laura Wessels, Henning Skull, Matteo Porsche Engineering Etzelstraße 1 Bietigheim-Bissingen74321 Germany Graduate Program Computational Sciences in Engineering Technische Universität Braunschweig Braunschweig Germany Fraunhofer Institute for Energy Economics and Energy System Technology Joseph-Beuys-Straße 8 Kassel34117 Germany Institute of Applied Mechanics Division Data-Driven Modeling of Mechanical Systems Technische Universität Braunschweig Pockelsstraße 3 Braunschweig38106 Germany

This work proposes variational autoencoders (VAEs) to predict a vehicle’s jerk from a given torque demand, addressing the limitations of sparse real-world datasets. Specifically, we implement unconditional and conditional VAEs to generate jerk signals that integrate features from different drivetrain scenarios. The VAEs are trained on experimental data collected from two variants of a fully electric SUV, which differ in maximum torque delivery and drivetrain configuration. New meaningful jerk signals are generated within an engineering context through the interpretation of the VAE’s latent space. A performance comparison with baseline physics-based and hybrid models confirms the effectiveness of the VAEs. We show that VAEs bypass the need for exhaustive manual system parametrization while maintaining physical plausibility by conditioning data generation on specific inputs. © 2025, CC BY.

关键词： Signal encoding

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A Generative Model for Anomaly Detection in Time Series Data

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Procedia Computer Science 2022年 200卷 629-637页

作者： Maximilian Hoh Alfred Schöttl Henry Schaub Franz Wenninger University of Applied Sciences Munich Dept. of Electrical Engineering and Information Technology Institute for Applications of Machine Learning and Intelligent Systems (IAMLIS) Munich 80335 Germany Fraunhofer Research Institute for Microsystems and Solid State Technologies (EMFT) Munich 80686 Germany

Machine and deep learning models are receiving increasing attention in smart manufacturing to optimize processes or to identify anomalous behavior. To be able to compute time series data in generative networks is a challenging task and becomes more attractive to the present date, as there are a lot of use cases. Also, creating novel audio files or detecting failures in an industrial environment gains importance. In this paper, the generator of a conditional Generative Adversarial Network (GAN) is fed directly with high-frequency data. Its encoder-decoder structure is able to learn a representation of the signal. The code is kept sparse by an additional regularization net during training. Comparing the code of the input and the reconstructed signal allows the calculation of an anomaly score for each sample and to classify the input as normal or anomalous.

关键词： Anomaly Detection Time Series Data Conditional GAN Sparsity

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Evaluation of Robustness Metrics for Defense of Machine Learning systems

Evaluation of Robustness Metrics for Defense of Machine Lear...

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International Conference on Military Communications and Information systems (ICMCIS)

作者： J. DeMarchi R. Rijken J. Melrose B. Madahar G. Fumera F. Roli E. Ledda M. Aktaş F. Kurth P. Baggenstoss B. Pelzer L. Kanestad Collaborative Engineering Systems & Aerospace Systems Information Supremacy Royal Netherlands Aerospace Centre NLR Amsterdam NLD Cyber & Information Systems Division Defence Science and Technology Laboratory Portondown GBR Department of Electrical and Electronic Engineering University of Cagliari Cagliari ITA Department of Informatics Bioengineering Robotics and Systems Engineering University of Genoa Genoa ITA Department of Computer Control and Management Engineering Sapienza University of Rome Rome ITA Defence Systems Technologies Division ASELSAN Ankara TUR Fraunhofer Institute for Communication Information Processing and Ergonomics Bonn DEU Swedish Defence Research Agency Cyber Defence and C2 Technology Division Stockholm SWE

In this paper we explore some of the potential applications of robustness criteria for machine learning (ML) systems by way of tangible “demonstrator” scenarios. In each demonstrator, ML robustness metrics are applied to real-world scenarios with military relevance, indicating how they might be used to help detect and handle possible adversarial attacks on ML systems. We conclude by sketching promising future avenues of research in order to: (1) help establish useful verification methodologies to facilitate ML robustness compliance assessment; (2) support development of ML accountability mechanisms; and (3) reliably detect, repel, and mitigate adversarial attack.

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JuliaGrid: An Open-Source Julia-Based Framework for Power System State Estimation

arXiv

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arXiv 2025年

作者： Cosovic, Mirsad Kundacina, Ognjen Delalic, Muhamed Teskeredzic, Armin Raca, Darijo Mesanovic, Amer Miskovic, Dragisa Vukobratovic, Dejan Monti, Antonello Faculty of Electrical Engineering University of Sarajevo Bosnia and Herzegovina Institute for Artificial Intelligence Research Development of Serbia Serbia Institute for Automation of Complex Power Systems E.ON Energy Research Center RWTH Aachen University Germany Siemens AG Munich Germany Faculty of Technical Sciences University of Novi Sad Serbia Fraunhofer FIT Aachen Germany

Modern electric power systems have an increasingly complex structure due to rise in power demand and integration of diverse energy sources. Monitoring these large-scale systems, which relies on efficient state estimation (SE), represents a challenging computational task and requires efficient simulation tools for power system steady-state analyses. Motivated by this observation, we propose JuliaGrid, an open-source framework written in the Julia programming language, designed for high performance execution across multiple platforms. The framework implements observability analysis, weighted least-squares and least-absolute value estimators, bad data analysis, and various algorithms related to phasor measurements. To complete power system analysis, the framework includes power flow and optimal power flow, enabling measurement generation for the SE routines. Leveraging computationally efficient algorithms, JuliaGrid solves large-scale systems across all SE routines with competitive execution times compared to other open-source frameworks. These capabilities are validated through simulations on power systems with 10 000, 20 000 and 70 000 buses. © 2025, CC BY.

关键词： Power systems computer aided design

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Attack-based Automation of Security Testing for IoT Applications with Genetic Algorithms and Fuzzing

Attack-based Automation of Security Testing for IoT Applicat...

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IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C)

作者： Steffen Lüdtke Roman Kraus Ramon Barakat Martin A. Schneider Business Unit Quality Engineering (SQC) Fraunhofer Institute for Open Communication Systems Berlin Germany

ISBN: (纸本)9781665478373

The Internet of Things (IoT) has increased the connectivity of systems and fueled the digitalization. However, IoT systems are prone to various security vulnerabilities that may lead to serious incidents that can cause physical harm and financial damage. The security of IoT systems is a major challenge for the their success. If vulnerabilities remain undetected, an attacker can exploit them remotely and thus, gain full access to confidential data, control the connected IoT devices with magnitudes of consequences. This paper presents an approach that exploits information on attacks detected and recorded at runtime to facilitate the development of security patches and uses the information to detect further vulnerabilities. This paper presents work in progress from an ongoing research project.

关键词： Runtime Conferences Software algorithms Software quality Fuzzing Software reliability Internet of Things

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IEC 61508 and ISO 26262 – A Comparison Study

IEC 61508 and ISO 26262 – A Comparison Study

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International Conference on System Reliability and Science (ICSRS)

作者： Abdellatif Nouri Jens Warmuth Division Engineering of Adaptive Systems EAS Fraunhofer Institute for Integrated Circuits IIS Dresden Germany

ISBN: (纸本)9781665400503

In the process of realizing safety critical systems, guaranteeing functional safety is always mandatory. However, multiple factors are challenging functional safety: (i) the complexity of new electrical and electronic architecture leading to different malfunctioning behavior. This malfunctioning behavior can lead to unwanted hazards and then to unreasonable risk, (ii) the availability of various functional safety standards and (iii) high expenses. If functional safety standards are used in the design of a safety critical system, it is important to evaluate the risk accurately. The risk is related to the probability of failure. In this paper, a comparison between two functional safety standards ISO 26262 and IEC 61508 is presented. These standards are used in the automotive field and in the industrial automation field, respectively. Additionally, a limitation in using IEC 61508 to verify ISO 26262 is emphasized. Focus is the safety lifecycle and the failure rate evaluation methods, which are applied by the two standards. The comparison made in this paper represents the opinion of the authors based on their experience and is not intended to be absolute.

关键词： ISO ISO Standards IEC Production Hardware Safety IEC Standards

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