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Prognostics and System Health Management Conference (PHM)

作者： Peng Su Yeqi Wang Conglei Xiang Erik Wendel Madhav Mishra DeJiu Chen Department of Engineering Design Mechatronics Division KTH Royal Institute of Technology Stockholm Sweden Embedded Systems Master Program of Electrical Engineering and Computer Science (EECS) School KTH Royal Institute of Technology Stockholm Sweden Digital Systems Division RISE Research Institutes of Sweden Gothenburg Sweden

ISBN: (数字)9798350360585

ISBN: (纸本)9798350360592

Prognostics and health management (PHM) is an engineering discipline that aims to maintain system behaviour and function and ensure mission success, safety and effectiveness. Addressing the challenges in prognostics and health management for modern intelligent systems, especially automated driving systems, is complex due to the contextual nature of faults. This complexity necessitates a thorough understanding of spatial, and temporal conditions, and relationships within operational scenarios and life-cycle stages. This paper introduces a framework designed to automatically recognize driving scenarios in automated driving systems using graph neural networks (GNNs). The framework extracts relational data from image frames, constructing graph-based models and transforming unstructured sensory data into structured data with diverse node types and relationships. A specific graph neural network processes the graph model to reveal and detect operational conditions and relationships. The proposed framework is evaluated using the KITTI dataset, demonstrating superior performance compared to conventional feed-forward networks such as MLP, particularly in handling relational data.

关键词： Graph neural networks Data models Safety Complexity theory Data mining Prognostics and health management Intelligent systems

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"It Is Hard to Remove from My Eye": design Makeup Residue Visualization System for Chinese Traditional Opera (Xiqu) Performers

arXiv

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arXiv 2024年

作者： Xiong, Zeyu Fu, Shihan Zhu, Yanying Zhu, Chenqing Ma, Xiaojuan Fan, Mingming Computational Media and Arts Thrust The Hong Kong University of Science and Technology Guangzhou China Data Science and Analysis Thrust The Hong Kong University of Science and Technology Guangzhou China Internet of Things Thrust The Hong Kong University of Science and Technology Guangzhou China Department of Computer Science and Engineering The Hong Kong University of Science and Technology Hong Kong Division of Integrative Systems and Design Department of Computer Science and Engineering The Hong Kong University of Science and Technology Hong Kong

Chinese traditional opera (Xiqu) performers often experience skin problems due to the long-term use of heavy-metal-laden face paints. To explore the current skincare challenges encountered by Xiqu performers, we conducted an online survey (N=136) and semi-structured interviews (N=15) as a formative study. We found that incomplete makeup removal is the leading cause of human-induced skin problems, especially the difficulty in removing eye makeup. Therefore, we proposed EyeVis, a prototype that can visualize the residual eye makeup and record the time make-up was worn by Xiqu performers. We conducted a 7-day deployment study (N=12) to evaluate EyeVis. Results indicate that EyeVis helps to increase Xiqu performers' awareness about removing makeup, as well as boosting their confidence and security in skincare. Overall, this work also provides implications for studying the work of people who wear makeup on a daily basis, and helps to promote and preserve the intangible cultural heritage of practitioners. © 2024, CC BY-NC-ND.

关键词： computer vision

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Towards Enhanced I/O Performance of NVM File Systems

Towards Enhanced I/O Performance of NVM File Systems

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International Conference on High Performance Computing

作者： Jiwoo Bang Chungyong Kim Eun-Kyu Byun Hanul Sung Jaehwan Lee Hyeonsang Eom Department of Computer Science and Engineering Seoul National University Seoul Korea Division of National Supercomputing Korea Institute of Science and Technology Information Daejeon Korea Department of Game Design and Development Sangmyung University Seoul Korea Department of Computer Engineering Korea Aerospace University Goyang Korea

Non-volatile memory (NVM) provides bulk storage capacity, like NAND flash, while providing low latency, like DRAM, at the same time. NVM enables high-performance, reliable, and cost-effective high performance systems by providing low-latency data access and high capacity storage compared to traditional disk-based system. As NVM becomes a novel tier in the memory hierarchy, efficiently utilizing NVM I/O capability is important. In this work, we evaluate the I/O performance of NVM in three aspects: the performance change with a varying number of concurrent accesses, the performance dif-ference between remote and local accesses, and the performance change with various access granularity. We also compare the performance of NVM file systems that handle the different I/O characteristics of NVM. Specifically, Odinfs is the state-of-the-art NVM file system that solves the performance degradation of NVM with large number of threads and remote NUMA node accesses. We further optimize Odinfs by solving the I/O performance degradation with a small number of threads. We evaluate the optimized version of Odinfs and show that the throughput of Odinfs is increased by 30.91 % with four or fewer threads.

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AIR-HLoc: Adaptive Retrieved Images Selection for Efficient Visual Localisation

arXiv

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arXiv 2024年

作者： Liu, Changkun Jiao, Jianhao Huang, Huajian Ma, Zhengyang Kanoulas, Dimitrios Braud, Tristan Department of Computer Science and Engineering HKUST Hong Kong Department of Computer Science University College London London United Kingdom Division of Emerging Interdisciplinary Areas HKUST Hong Kong Division of Integrated Systems Design HKUST Hong Kong AI Centre Department of Computer Science University College London Gower Street LondonWC1E 6BT United Kingdom Archimedes/Athena RC Greece

State-of-the-art hierarchical localisation pipelines (HLoc) employ image retrieval (IR) to establish 2D-3D correspondences by selecting the top-k most similar images from a reference database. While increasing k improves localisation robustness, it also linearly increases computational cost and runtime, creating a significant bottleneck. This paper investigates the relationship between global and local descriptors, showing that greater similarity between the global descriptors of query and database images increases the proportion of feature matches. Low similarity queries significantly benefit from increasing k, while high similarity queries rapidly experience diminishing returns. Building on these observations, we propose an adaptive strategy that adjusts k based on the similarity between the query’s global descriptor and those in the database, effectively mitigating the feature-matching bottleneck. Our approach reduces computational costs and processing time without sacrificing accuracy. Experiments on three indoor and outdoor datasets show that AIR-HLoc reduces feature matching time by up to 30% while preserving state-of-the-art accuracy. The results demonstrate that AIR-HLoc facilitates a latency-sensitive localisation system. Copyright © 2024, The Authors. All rights reserved.

关键词： Data description

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Obtaining parallax-free X-ray powder diffraction computed tomography data with a self-supervised neural network

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npj Computational Materials 2024年第1期10卷 1133-1144页

作者： H.Dong S.D.M.Jacques K.T.Butler O.Gutowski A.-C.Dippel M.von Zimmerman A.M.Beale A.Vamvakeros Department of Chemistry University College London20 Gordon StreetLondonWC1H 0AJUK Finden Limited Merchant House5 East St Helens StreetAbingdonOX145EGUK SciML Scientific Computer DivisionRutherford Appleton LaboratoryHarwellOX110QXUK Deutsches Elektronen-Synchrotron DESY Notkestraße 8522607 HamburgGermany Research Complex at Harwell Rutherford Appleton LaboratoryHarwell Science and Innovation CampusDidcotOxfordshireOX110FAUK Dyson School of Design Engineering Imperial College LondonLondonSW72DBUK

In this study,we introduce a method designed to eliminate parallax artefacts present in X-ray powder diffraction computed tomography data acquired from large *** parallax artefactsmanifest as artificial peak shifting,broadening and splitting,leading to inaccurate physicochemical information,such as lattice parameters and crystallite *** approach integrates a 3D artificial neural network architecture with a forward projector that accounts for the experimental geometry and sample *** is a self-supervised tomographic volume reconstruction approach designed to be chemistry-agnostic,eliminating the need for prior knowledge of the sample’s chemical *** showcase the efficacy of this method through its application on both simulated and experimental X-ray powder diffraction tomography data,acquired from a phantom sample and an NMC532 cylindrical lithium-ion battery.

关键词： neural artificial network

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Marine Video Cloud: A Cloud-Based Video Analytics Platform for Collaborative Marine Research

Marine Video Cloud: A Cloud-Based Video Analytics Platform f...

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OCEANS

作者： Ziqiang Zheng Tan-Sang Ha Yingshu Chen Haixin Liang Apple Pui-Yi Chui Yue-Him Wong Sai-Kit Yeung Department of Computer Science and Engineering The Hong Kong University of Science and Technology Division of Integrative Systems and Design Hong Kong University of Science and Technology School of Life Sciences The Chinese University of Hong Kong Institute for Advanced Study Shenzhen University

With the increasing attention and corresponding developments of data collection of underwater surveying/diving videos, a large number of underwater videos have been yielded for different purposes. However, it is time-consuming and requires the corresponding expertise to yield a hierarchical and comprehensive biological analysis report based on the collected underwater videos. The development of the underwater video analysis platform is an emergency and users of such a platform should not be limited to some specific groups (e.g., biological experts). The existing VIAME provides an intelligent solution for fishery and marine organism analysis with an installable platform. Differently, in this paper, we develop a novel cloud-based underwater video analysis platform, which focuses on more diverse marine species such as coral reefs and sea urchins. The proposed platform could provide hierarchical and comprehensive services for a wider user group. We aim to build a one-stop platform, which could allow every user to upload their surveying or diving videos and build a centralized database for more robust and accurate data analysis.

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Autonomous Realization of Safety- and Time-Critical Embedded Artificial Intelligence

Autonomous Realization of Safety- and Time-Critical Embedded...

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design, Automation and Test in Europe Conference and Exhibition

作者： Joakim Lindén Andreas Ermedahl Hans Salomonsson Masoud Daneshtalab Björn Forsberg Paris Carbone Department of Aeronautical Engineering SAAB AB Linköping Sweden School of Innovation Design and Engineering Mälardalens Universitet Västerås Sweden Network Division Ericsson AB Kista Sweden School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Kista Sweden EMBEDL AB Gothenburg Sweden Department of Computer Science RISE Research Institutes of Sweden AB Kista Sweden

ISBN: (数字)9783981926385

ISBN: (纸本)9798350348606

There is an evident need to complement embedded critical control logic with AI inference, but today's AI-capable hardware, software, and processes are primarily targeted towards the needs of cloud-centric actors. Telecom and defense airspace industries, which make heavy use of specialized hardware, face the challenge of manually hand-tuning AI workloads and hardware, presenting an unprecedented cost and complexity due to the diversity and sheer number of deployed instances. Furthermore, embedded AI functionality must not adversely affect real-time and safety requirements of the critical business logic. To address this, end-to-end AI pipelines for critical platforms are needed to automate the adaption of networks to fit into resource-constrained devices under critical and real-time constraints, while remaining interoperable with de-facto standard AI tools and frameworks used in the cloud. We present two industrial applications where such solutions are needed to bring AI to critical and resource-constrained hardware, and a generalized end-to-end AI pipeline that addresses these needs. Crucial steps to realize it are taken in the industry-academia collaborative FASTER-AI project.

关键词： Pipelines Process control Hardware Real-time systems Software Telecommunications Safety

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Towards Trustworthy AI: Sandboxing AI-Based Unverified Controllers for Safe and Secure Cyber-Physical Systems

Towards Trustworthy AI: Sandboxing AI-Based Unverified Contr...

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IEEE Conference on Decision and Control

作者： Bingzhuo Zhong Siyuan Liu Marco Caccamo Majid Zamani TUM School of Engineering and Design Technical University of Munich Germany Division of Decision and Control Systems KTH Royal Institute of Technology Stockholm Sweden Department of Computer Science University of Colorado Boulder USA

In the past decade, artificial-intelligence-based (AI-based) techniques have been widely applied to design controllers over cyber-physical systems (CPSs) for complex control missions (e.g., motion planning in robotics). Nevertheless, AI-based controllers, particularly those developed based on deep neural networks, are typically very complex and are challenging to be formally verified. To cope with this issue, we propose a secure-by-construction architecture, namely Safe-Sec-visor architecture, to sandbox AI-based unverified controllers. By applying this architecture, the overall safety and security of CPSs can be ensured simultaneously, while formal verification over the AI-based controllers is not required. Here, we consider invariance and opacity properties as the desired safety and security properties, respectively. Accordingly, by leveraging a notion of (augmented) control barrier functions, we design a supervisor to check the control inputs provided by the AI-based controller and decide whether to accept them. At the same time, a safety-security advisor runs in parallel and provides fallback control inputs whenever the AI-based controller is rejected for safety and security reasons. To show the effectiveness of our approaches, we apply them to a case study on a quadrotor controlled by an AI-based controller. Here, the initial state of the quadrotor contains secret information which should not be revealed while the safety of the quadrotor should be ensured.

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A multimodal approach for enhanced disease management in cauliflower crops:integration of spectral sensors, machine learning models and targeted spraying technology

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Frontiers of Agricultural science and engineering 2025年第2期 261-273页

作者： Rohit ANAND Roaf Ahmad PARRAY Indra MANI Tapan Kumar KHURA Harilal KUSHWAHA Brij Bihari SHARMA Susheel SARKAR Samarth GODARA Shideh MOJERLOU Hasan MIRZAKHANINAFCHI Division of Agricultural Engineering ICAR-IARI Vasantrao Naik Marathwada Krishi Vidyapeeth Central Arid Zone Research Institute Division of Vegetable Sciences ICAR-IARI Division of Design of Experiments ICAR-IASRI Division of Computer Applications ICAR-IASRI Department of Agroecology-Entomology and Plant Pathology Aarhus University Electrical Engineering and Computer Science Daktronics Engineering Hall South Dakota State University

This research explored a novel multimodal approach for disease management in cauliflower crops. With the rising challenges in sustainable agriculture, the research focused on a patch spraying method to control disease and reduce crop losses and environmental impact. For non-destructive disease assessment, a spectral sensor was used to collect spectral information from diseased and healthy cauliflower parts. The spectral data sets were analyzed using decision tree and support vector machine（SVM） algorithms to identify the most accurate model for distinguishing diseased and healthy plants. The chosen model was integrated with a low-volume sprayer(50-150 L·ha-1),equipped with an electronic control unit for targeted spraying based on sensor-detected regions. The decision tree model achieved 89.9% testing accuracy, while the SVM model achieved 96.7% accuracy using hyperparameters: cost of 10.0 and tolerance of 0.001. The research successfully demonstrated the integration of spectral sensors, machine learning, and targeted spraying technology for precise input ***, the optimized sprayer achieved a 72.5% reduction in chemical usage and a significant time-saving of 21.0% compared to a standard sprayer for black rot-infested crops. These findings highlight the potential efficiency and resource conservation benefits of innovative sprayer technology in precision agriculture and disease management.

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SECURE-BY-CONSTRUCTION SYNTHESIS FOR CONTROL SYSTEMS

arXiv

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arXiv 2023年

作者： Zhong, Bingzhuo Liu, Siyuan Caccamo, Marco Zamani, Majid Department of Computer Science University of Colorado Boulder United States Division of Decision and Control Systems KTH Royal Institute of Technology Stockholm Sweden TUM School of Engineering and Design Technical University of Munich Germany

In this paper, we present the synthesis of secure-by-construction controllers that address safety and security properties simultaneously in cyber-physical systems. Our focus is on studying a specific security property called opacity, which characterizes the system’s ability to maintain plausible deniability of its secret behavior in the presence of an intruder. These controllers are synthesized based on a concept of so-called (augmented) control barrier functions, which we introduce and discuss in detail. We propose conditions that facilitate the construction of the desired (augmented) control barrier functions and their corresponding secure-by-construction controllers. To compute these functions, we propose an iterative scheme that leverages iterative sum-of-square programming techniques. This approach enables efficient computation of these functions, particularly for polynomial systems. Moreover, we demonstrate the flexibility of our approach by incorporating user-defined cost functions into the construction of secure-by-construction controllers. Finally, we validate the effectiveness of our results through two case studies, illustrating the practical applicability and benefits of our proposed approach. Copyright © 2023, The Authors. All rights reserved.

关键词： Controllers

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