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SensorClouds: A Framework for Real-Time Processing of Multi-modal Sensor Data for Human-Robot-Collaboration

SensorClouds: A Framework for Real-Time Processing of Multi-...

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International Conference on Autonomous Robots and Agents, ICARA

作者： Alexander Poeppel Christian Eymüller Wolfgang Reif Institute for Software and Systems Engineering University of Augsburg Augsburg Germany

Human-robot-collaboration (HRC) requires fast and reliable sensor data to ensure the safety of humans in the workspace. Current solutions for processing multi-modal sensor data in HRC are either highly performant in specific scenarios or offer more flexibility at the cost of decreased performance. Our GPU accelerated SensorClouds framework, however, combines both high flexibility and real-time performance. The architecture aids developers in quickly implementing complex HRC applications with multiple sensors by encapsulating all functionality into reusable modules. The resulting pipeline is optimized by the framework and executed in real-time.

关键词： Solid modeling Multimodal sensors Pipelines Graphics processing units Computer architecture Robot sensing systems Real-time systems

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Identifying Challenges for OSS Vulnerability Scanners - A Study & Test Suite (Short Summary)

Identifying Challenges for OSS Vulnerability Scanners - A St...

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Fachtagung des GI-Fachbereichs softwaretechnik, software engineering 2022 - Conference of the GI software engineering Section, software engineering 2022

作者： Dann, Andreas Plate, Henrik Hermann, Ben Ponta, Serena Elisa Bodden, Eric The Secure Software Engineering Group Heinz Nixdorf Institute Paderborn University Germany SAP Security Research Mougins France Technical University of Dortmund Germany Paderborn University Germany Software Engineering IT-Security at Fraunhofer IEM Paderborn Germany

ISBN: (纸本)9783885797142

This short paper5 presents a study investigating the impact of typical development practices, like re-compilation, re-bundling, on the performance of vulnerability scanners to detect known vulnerabilities in used open-source dependencies. In particular, the paper studies (i) types of modifications that affect the detection of vulnerable open-source dependencies and (ii) their impact on the performance of vulnerability scanners through an empirical study on 7024 Java projects developed at SAP. © 2022 Gesellschaft fur Informatik (GI). All rights reserved.

关键词： Open source software

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Combining Simulation and Recurrent Neural Networks for Model-Based Condition Monitoring of Machines

Combining Simulation and Recurrent Neural Networks for Model...

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Simulation Winter Conference

作者： Alexander Wuttke Markus Rabe Joachim Hunker Jan-Philipp Diepenbrock Dept. IT in Production and Logistics TU Dortmund University Dortmund GERMANY Fraunhofer Institute for Software and Systems Engineering Dortmund GERMANY IVA Schmetz GmbH Menden GERMANY

ISBN: (数字)9798331534202

ISBN: (纸本)9798331534219

Maintenance is pivotal in industry, with condition-based maintenance emerging as a key strategy. This involves monitoring the machine condition through sensor data analysis. Model-based approaches compare observed data with expected values from models, which requires high-quality models. An established method is to use simulation models, which in many cases produce good results but may lack precision due to uncertainties. Alternatively, models created by machine learning can detect patterns directly from data. This paper proposes combining simulation models with machine learning models, leveraging the simulation's a-priori knowledge and machine learning's data patterns to enhance models for condition monitoring. Recurrent neural networks are suggested as the machine learning method. The paper outlines a systematic approach and demonstrates its application in an industrial use case, which investigates vacuum processes in industrial furnaces.

关键词： Condition monitoring Industries Recurrent neural networks Vacuum systems Uncertainty Systematics Machine learning Data models Maintenance Monitoring

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Architecture for Emergency Control of Autonomous UAV Ensembles∗∗This work is partly funded by the German Research Foundation (DFG) under the COMBO grant 3

Architecture for Emergency Control of Autonomous UAV Ensembl...

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3rd IEEE/ACM International Workshop on Robotics software engineering, RoSE 2021

作者： Schorner, Martin Wanninger, Constantin Hoffmann, Alwin Kosak, Oliver Reif, Wolfgang Institute for Software and Systems Engineering University of Augsburg Germany

ISBN: (纸本)9781665444743

Applying unmanned aerial vehicles (UAV) has benefits for many different use-cases. Existing implementations of ground control stations (GCS) to manage UAVs in such scenarios already provide some support for the operation of multi-unit systems, i.e., ensembles. However, since they are usually designed for the operation of only one copter at once, this is often not sufficient to react quickly in dangerous situations, e.g., search and rescue scenarios. To address this problem, we propose an approach for easy observation and control of complete autonomous UAV ensembles: The Intention of our approach is to greatly reduce the number of personnel required for the operation of an UAV ensemble. Thereby, we generate the possibility for rapid intervention in potentially dangerous situations in order to prevent damage to the UAVs and the environment. In this paper, we present a software architecture for this safety-critical multi UAV ground control station including a fully implemented prototype which we also tested in a realistic environment. © 2021 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Artificial Intelligence Applications for Resilience in Manufacturing — A Systematic Literature Review

Artificial Intelligence Applications for Resilience in Manuf...

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International Conference on Artificial Intelligence in Information and Communication (ICAIIC)

作者： Florian A. Maier Sivaphani Puppala Michael Oberle Software Defined Energy-Cell Manufacturing Fraunhofer Institute for Manufacturing Engineering and Automation IPA Stuttgart Germany Center for Digitalized Battery Cell Manufacturing Fraunhofer Institute for Manufacturing Engineering and Automation IPA Stuttgart Germany Centre for Digital Tools in Manufacturing Fraunhofer Institute for Manufacturing Engineering and Automation IPA Stuttgart Germany

This review provides a structured literature analysis of Artificial Intelligence (AI) applications in enhancing manufacturing resilience. The research is guided by three primary questions addressing the use cases, technologies, and benefits of AI across the five resilience phases: Prepare, Prevent, Protect, Respond, and Recover. Findings from 78 papers reveal that AI significantly contributes to predictive maintenance, risk mitigation, and quality control, with machine learning and deep learning being the predominant technologies. The study highlights the pivotal role of AI in advancing manufacturing towards proactive, resilient, and adaptable operations. The insights gleaned offer a roadmap for future research and practical AI integration in manufacturing, underscoring the value of AI in driving industrial innovation and efficiency.

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Sea Level Anomalies Prediction Via Two-Stage Spatiotemporal Transformer 21

Sea Level Anomalies Prediction Via Two-Stage Spatiotemporal ...

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21st International Conference on Networking, Sensing and Control, ICNSC 2024

作者： Fang, Shaoteng Zhao, Yuehao Wang, Kefan Tian, Chenyu Kang, Qi Tongji University Department of Control Science and Engineering Shanghai China The School of Aerospace Mechanical and Mechatronic Engineering The University of Sydney Sydney Australia Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai China School of Software Technology Dalian University of Technology Dalian China

ISBN: (纸本)9798350365221

This study successfully applies the spatiotemporal transformer-based model to sea surface height anomaly prediction task. An improved ResNet autoencoder, named SW-GD Autoencoder, is proposed based on Sliced-Wasserstein distance and Gradient Difference loss functions to extract spatial feature information. This autoencoder demonstrates a reduced complexity and training difficulty compared to GAN-based architectures while maintaining high data generation quality. Additionally, the VidHRFormer model is employed for inference, introducing a large receptive field spatial feed-forward network module that enhances information transmission between adjacent patches in the feature map, thereby improving the observability of prediction results. To simplify training, we used a two-stage approach: first training the autoencoder separately, then combining it with VidHRFormer for final training. Compared to state-of-the-art ConvLSTM models, our method yields superior results. © 2024 IEEE.

关键词： Sea level

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***-Processor-Towards Development of AI-enhanced End-To-End BCIs

***-Processor-Towards Development of AI-enhanced End-To-End ...

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作者： Buron, Leo Erbslöh, Andreas Seidl, Karsten Schiele, Gregor Seidl, Karsten Ur-Rehman, Zia Klaes, Christian University of Duisburg-Essen Faculty of Engineering Duisburg Germany Fraunhofer Institute of Microelectronic Circuit and Systems Business Unit Health Duisburg Germany Ruhruniversity Bochum Faculty of Medicine Bochum Germany

This paper presents a software-based Python framework for developing future AI-enhanced end-To-end Brain-Computer-Interfaces (BCI). This framework contains modules from the emulated analogue front-end and from neural signal pre-processing for invasive neural applications. These modules can be assembled into several pipeline versions for evaluation and benchmarking. The aim of this framework is to accelerate the development of BCIs due to system-wide optimizations in order to set the requirements for hardware development without prior knowledge on the basis of accuracy (recall and precision) and latency. In the next step, the pipeline can be optimised for on-chip and embedded execution. © 2023 the author(s), published by Walter de Gruyter Berlin/Boston.

关键词： Pipelines

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Comparison of Visual Occupancy Detection Approaches for Parking Lots and Dedicated Containerized REST-API Server Application 9

Comparison of Visual Occupancy Detection Approaches for Park...

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9th Workshop on software Quality Analysis, Monitoring, Improvement, and Applications, SQAMIA 2022

作者： Petričko, Andrej Dakić, Pavle Vranić, Valentino Institute of Informatics Information Systems and Software Engineering Faculty of Informatics and Information Technologies Slovak University of Technology Bratislava Slovakia

With the development of new technology, the urban infrastructure, which is necessary to meet the social, economic, and physical needs of the population, is also gradually improving. Therefore, cities face significant urban planning challenges. With the increasing population and number of cars on the road parking space occupancy detection techniques are of great importance for efficient parking space management. Knowing the availability of parking spaces within a city in real-time and informing residents can be of great help in reducing the number of car park councils, reducing traffic congestion in cities, or improving the scalability of car parks and the time needed to find empty parking space. In many car parks, ground sensors are used to determine occupancy status. However, this requires the installation and maintenance of these sensors in every parking space. This can be expensive, especially in car parks with a large number of available spaces. With increasing computing power, new approaches to parking space occupancy detection using computer vision are emerging. However, these approaches are tailored to the site of application. In this work, we propose a comparison of two general approaches: classification and object detection. The reliability, precision, and scalability of these approaches are compared using a REST-API server application implemented in Python. In order to get as close as possible to general use, we use docker, which enables us easier develop and deploy this application independently of the hardware. © 2022 Copyright for this paper by its authors.

关键词： Object detection

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Identifying and Involving the Real End User in software Development: Towards a Pattern Language 27

Identifying and Involving the Real End User in Software Deve...

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2022 27th European Conference on Pattern Languages of Programs, EuroPLoP 2022

作者： Daud Haiderzai, Mohammad Vranic, Valentino Institute of Informatics Information Systems and Software Engineering Faculty of Informatics and Information Technologies Slovak University of Technology in Bratislava Slovakia

ISBN: (纸本)9781450395946

software development demand and identification of end users involvement have been increasing rapidly, but identifying the real end user and involving them in software development is challenging for software developers reported in the literature. One of the problems is the difficulty of designing the business domain. It takes longer to find the actual business domain when different and inexpert domain end users are engaged with developers. Another problem is the difficulty of incorporating all types of end users needs in software development. Several expectations and different information make the development process more complex and overload the project scope. software development also takes more time, and the project goal is challenging. The above problems are the leading causes that create a complex process and difficulty in software development. To overcome these problems, we established a pattern language composed of eight organizational patterns observed and documented during in practical work on many projects. These patterns and other known organizational patterns relation are described in a patterns story of a real company. © 2022 ACM.

关键词： software design

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Organizational Patterns for Improving the Understanding between a Customer and the Development Team 27

Organizational Patterns for Improving the Understanding betw...

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2022 27th European Conference on Pattern Languages of Programs, EuroPLoP 2022

作者： Khattab, Mohammad Ismail Vranic, Valentino Institute of Informatics Information Systems and Software Engineering Faculty of Informatics and Information Technologies Slovak University of Technology in Bratislava Slovakia

ISBN: (纸本)9781450395946

During a software development process, a customer and the development team need to communicate and understand each other. Poor communication between a customer and the development team is one of the most common challenges in the software development process, which leads to software failures and further increases the budget. In our practical experience and from the literature, we found that lack of customer involvement, no common communication language, complex business processes, end-user resistance toward system development, lack of trust, lack of leadership, and and end-user capacity are the main challenges toward the development team understanding. We bring six newly discovered patterns that address these problems and improve the understanding between a customer and the development team during the software development process. We also bring some of the known organizational patterns that also mitigate these problems into relation to the newly discovered patterns. To create a pattern language from these patterns, we illustrated the sequences of the patterns so that the development team and customer could understand each other. © 2022 ACM.

关键词： software design

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