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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Victor Ticllacuri Renato Mio Biomedical Engineering Program PUCP-UPCH Lima Perú Laboratory of Biomechanics and Applied Robotics Pontificia Universidad Catolica del Peru Lima Perú Laboratory of Biomedical Engineering Universidad Peruana Cayetano Heredia Lima Perú Chair of Digital Health with a Focus on Data Science University of Bayreuth Germany

ISBN: (数字)9798350371499

ISBN: (纸本)9798350371505

Treatments of disuse-induced muscle atrophy entail unmet clinical needs due to the lack of medical devices capable of mimicking physicians manual therapies. Therefore, in this paper we develop and model a wearable soft pneumatic elastomeric actuator to perform deep cyclic compression stimuli on human soft tissues for muscle rehabilitation by mechanotherapy. Static and dynamic characterization of the prototype demonstrate a 2.5 mm active deformation at 100 kPa with 600 mm 3 /s and a 5 Hz bandwidth. We estimate the transfer function of the experimentally acquired pressure, flow and deformation signals, processed by a Gaussian kernel-based approach. Our mathematical model accurately describes the actuator behavior and enables to extract its mechanical parameters. Then, through computational simulations, we illustrate its efficacy in emulating multiple complex bio-inspired movements. Our proposed methodology aims to improve the control efficiency in wearable soft robotics for muscle atrophy treatment.

关键词： Atrophy Actuators Deformation Computational modeling Biological system modeling Transfer functions Prototypes Muscles Soft robotics Mathematical models

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Parameter Estimation for Partially Observed McKean-Vlasov Diffusions

arXiv

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arXiv 2024年

作者： Jasra, Ajay Maama, Mohamed Tempone, Raul School of Data Science The Chinese University of Hong Kong CN Shenzhen China Applied Mathematics and Computational Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia Chair of Mathematics for Uncertainty Quantification RWTH Aachen University Aachen52062 Germany

In this article we consider likelihood-based estimation of static parameters for a class of partially observed McKean-Vlasov (POMV) diffusion process with discrete-time observations over a fixed time interval. In particular, using the framework of [5] we develop a new randomized multilevel Monte Carlo method for estimating the parameters, based upon Markovian stochastic approximation methodology. New Markov chain Monte Carlo algorithms for the POMV model are introduced facilitating the application of [5]. We prove, under assumptions, that the expectation of our estimator is biased, but with expected small and controllable bias. Our approach is implemented on several examples. Copyright © 2024, The Authors. All rights reserved.

关键词： Stochastic systems

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Clarifying Assumptions about Artificial Intelligence before Revolutionising Patent Law

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GRUR International 2022年第4期71卷 295-321页

作者： Kim, Daria Alber, Maximilian Kwok, Man Wai Mitrovic, Jelena Ramirez-Atencia, Cristian Perez, Jesus Alberto Rodriguez Zille, Heiner Max Planck Institute for Innovation and Competition Munich Germany Charite Institute of Pathology Berlin Germany Chinese University of Hong Kong Department of Physics (Formerly) Hong Kong BMBF Program for Women in AI Faculty of Computer Science and Mathematics Chair of Data Science University of Passau Germany Department of Computer Systems Universidad Politecnica de Madrid Spain School of Computing Science College of Science and Engineering University of Glasgow United Kingdom Faculty of Computer Science Otto von Guericke University Magdeburg Germany

This paper examines several widespread assumptions about artificial intelligence, particularly machine learning, that are often taken as factual premises in discussions on the future of patent law in the wake of 'artificial ingenuity'. The objective is to draw a more realistic and nuanced picture of the human-computer interaction in solving technical problems than where 'intelligent' systems autonomously yield inventions. A detailed technical perspective is presented for each assumption, followed by a discussion of pertinent uncertainties for patent law. Overall, it is argued that implications of machine learning for the patent system in its core tenets appear far less revolutionary than is often posited. © 2022 Published by OUP and CH Beck on behalf of GRUR e.V.

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GlobalBuildingMap — Unveiling the Mystery of Global Buildings

arXiv

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arXiv 2024年

作者： Zhu, Xiao Xiang Li, Qingyu Shi, Yilei Wang, Yuanyuan Stewart, Adam J. Prexl, Jonathan Chair of Data Science in Earth Observation Technical University of Munich Arcisstraße 21 Munich80333 Germany Munich Center for Machine Learning Munich80333 Germany School of Engineering and Design Technical University of Munich Arcisstraße 21 Munich80333 Germany

Understanding how buildings are distributed globally is crucial to revealing the human footprint on our home planet. This built environment affects local climate, land surface albedo, resource distribution, and many other key factors that influence well-being and human health. Despite this, quantitative and comprehensive data on the distribution and properties of buildings worldwide is lacking. To this end, by using a big data analytics approach and nearly 800,000 satellite images, we generated the highest resolution and highest accuracy building map ever created: the GlobalBuildingMap (GBM). A joint analysis of building maps and solar potentials indicates that rooftop solar energy can supply the global energy consumption need at a reasonable cost. Specifically, if solar panels were placed on the roofs of all buildings, they could supply 1.1–3.3 times — depending on the efficiency of the solar device — the global energy consumption in 2020, which is the year with the highest consumption on record. We also identified a clear geospatial correlation between building areas and key socioeconomic variables, which indicates our global building map can serve as an important input to modeling global socioeconomic needs and drivers. © 2024, CC BY-NC-ND.

关键词： data Analytics

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Early Fault Detection in Rolling Element Bearings Using Signal Processing Techniques

Early Fault Detection in Rolling Element Bearings Using Sign...

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International Symposium on High Capacity Optical Networks and Enabling Technologies, HONET

作者： Ali Saeed M. Usman Akram Muazzam A. Khan M. Belal Afsar Department of Computer Science ICESCO Chair Big Data Analytics and Edge Computing Quaid-i-Azam University Islamabad Pakistan Department of Computer and Software Engineering National University of Sciences & Technology Islamabad Pakistan Faculty of Electrical Engineering and Information Technology Otto-von-Guericke University Maddeburg DE

ISBN: (数字)9798350378078

ISBN: (纸本)9798350378085

Many studies show that bearings are the most vulnerable components in low-voltage motors. While advanced bearing diagnostic systems exist, their cost can be a barrier for non-critical machinery due to the potential wait time to see a return on investment. This research explores the feasibility of using basic signal processing techniques on vibration data for bearing condition monitoring. The primary goal is to analyze benchmark data from the Case Western Reserve University (CWRU) dataset and establish a baseline performance for this data-driven approach. The results suggest that, with appropriate signal processing, it's possible to achieve early detection of bearing faults, leading to more efficient time-to-fault identification with higher detection accuracies ranging from 83 % to 100 % for each method.

关键词： Vibrations Fault diagnosis Low voltage Smart cities Rolling bearings Signal processing Motors Robots Monitoring Investment

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Throughput bottleneck detection in manufacturing: a systematic review of the literature on methods and operationalization modes

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Production and Manufacturing Research 2023年第1期11卷

作者： Skoogh, Anders Thürer, Matthias Subramaniyan, Mukund Matta, Andrea Roser, Christoph Department of Industrial and Materials Science Chalmers University of Technology Gothenburg Sweden Department of Mechanical Engineering Chair of Factory Planning and Intralogistics Chemnitz University of Technology Chemnitz Germany Insights & Data Capgemini AB Gothenburg Sweden Department of Mechanical Engineering Politecnico di Milano Milan Italy Department of Management Science and Engineering Karlsruhe University of Applied Sciences Karlsruhe Germany

Throughput is an important parameter to evaluate production system performance. It is typically constrained by one or more resources referred to as ‘throughput bottlenecks’. To start improvement actions, the first step is to identify throughput bottlenecks. Consequently, several bottleneck detection methods were developed in the literature. But this literature remains largely unstructured, which makes it difficult for practitioners to select an appropriate method. To generate clarity and to consolidate the field, a systematic literature review was conducted. The review identified 14 different bottleneck detection methods that are classified according to the information used: queue states, process states, or combined queue and process states. It further identified three different modes used to operationalize the different bottleneck detection methods: gemba walk, discrete event simulation, and data science. This study further presents important research issues, identifies contingency factors for method application, and discusses important guidelines for the choice of operationalization mode in practice. © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

关键词： Throughput

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Advanced Analytics in Smart Factories: Towards an actionable Taxonomy for Prescriptive Analytics Use Cases

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Procedia CIRP 2025年 134卷 229-234页

作者： Julian Weller Sumit Nalavade Oliver Gmelch Nico Migenda Tim Heuwinkel Roman Dumitrescu Fraunhofer Institute for Mechatronic Systems Design Zukunftsmeile 1 33102 Paderborn Germany Technische Hochschule Ingoldstadt“ Esplanade 10 85049 Ingolstadt Center for Applied Data Science Gütersloh Faculty of Engineering and Mathematics Bielefeld University of Applied Sciences and Arts Schulstraße 10 33330 Gütersloh Germany Chair for Advanced Systems Engineering Heinz Nixdorf Institute Fürstenallee 11 33102 Paderborn Germany

Prescriptive analytics use cases support in the decision-making process and focus on providing actionable guidance (e.g. in the smart factory) based on a set of problems and possible solutions. Smart factories represent the core of Industry 4.0 and can greatly benefit from the implementation of advanced analytics use cases. Prescriptive analytics enables operational excellence in smart factories by providing actionable insights and decisions to (autonomously) steer and govern areas of a factory. Still, a widespread adoption of principles of prescriptive analytics is not reached, due to the complexity and interconnectivity of different use cases. Additionally, a lack of methodological support for developing prescriptive analytics use cases is observed. We support the adoption and ideation of prescriptive analytics use cases by providing a taxonomy for prescriptive analytics use cases in smart factories for researchers. To make the findings from the taxonomy actionable, we develop a concept on how to transform existing analytics use cases or use case ideas into prescriptive analytics use cases to support practitioners. We focus on the transformation of existing analytics use cases into prescriptive analytics use cases to lower the barrier to entry for the development of prescriptive use cases. The findings are based on the taxonomy development method by Nickerson. Our evaluation is supported by expert interviews as well as focus groups.

关键词： "Smart Factory Advanced Analytics Prescriptive Analytics Taxonomy"

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Generating brick-like melt pools for Laser-Based Powder Bed Fusion using flexible beam shaping: a proof of concept on bead-on-plate single tracks

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Procedia CIRP 2024年 124卷 746-750页

作者： Jonas Grünewald Robin Prudlik Vijaya Holla Philipp Kopp Richard Off Thomas Stoll Stefan Kollmannsberger Katrin Wudy Professorship of Laser-based Additive Manufacturing TUM School of Engineering and Design Technical University of Munich Freisinger Landstraße 52 85748 Garching Germany Oerlikon AM Europe GmbH Freisinger Landstraße 52 85748 Garching Germany Chair of Computational Modeling and Simulation TUM School of Engineering and Design Technical University of Munich Arcisstraße 21 80333 Munich Germany Chair of Data Science in Civil Engineering Bauhaus University Weimar Coudraystraße 13A 99423 Weimar Germany

Despite the highest industrial maturity among additive manufacturing processes, laser-based powder bed fusion of metals (PBF-LB/M) lacks the productivity to further establish as an industrial manufacturing process. One approach for adjusting the melt pool shape to increase productivity in PBF-LB/M is spatial beam shaping. The freedom of beam shaping is almost unlimited, owing to modern optical concepts. The key is a beam shape optimized for a specific target. In this publication, the target is a brick-like melt pool cross-section. The publication demonstrates how the corresponding laser beam shape is designed using numerical optimization. The computed beam shape is reproduced using reflective spatial light phase modulators. The calculation is validated based on single-track experiments. Applying the optimized beam shape results in a melt pool shape similar to the optimization target. The width and depth of the melt track produced deviate by a maximum of 7 % from the specified target values.

关键词： Additive Manufacturing PBF-LB/M LCOS-SLM IN718 Beam Shape Optimization

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Overlooked Aspects of data Governance: Workflow Framework For Enterprise data Deduplication

Overlooked Aspects of Data Governance: Workflow Framework Fo...

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Intelligent Computing, Communication, Networking and Services (ICCNS), International Conference on

作者： Otmane Azeroual Anastasija Nikiforova Kewei Sha German Centre for Higher Education Research and Science Studies (DZHW) Berlin Germany Faculty of Science and Technology Institute of Computer Science Chair of Software Engineering University of Tartu Tartu Estonia Task Force “FAIR Metrics and Data Quality” European Open Science Cloud Brussels Belgium College of Science and Engineering University of Houston Clear Lake Houston USA

data quality in companies is decisive and critical to the benefits their products and services can provide. However, in heterogeneous IT infrastructures where, e.g., different applications for Enterprise Resource Planning (ERP), Customer Relationship Management (CRM), product management, manufacturing, and marketing are used, duplicates, e.g., multiple entries for the same customer or product in a database or information system, occur. There can be several reasons for this, but the result of non-unique or duplicate records is a degraded data quality. This ultimately leads to poorer, inefficient, and inaccurate data-driven decisions. For this reason, in this paper, we develop a conceptual data governance framework for effective and efficient management of duplicate data, and improvement of data accuracy and consistency in large data ecosystems. We present methods and recommendations for companies to deal with duplicate data in a meaningful way.

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Incremental algorithms for the maximum internal spanning tree problem

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science China(Information sciences) 2021年第5期64卷 77-84页

作者： Xianbin ZHU Wenjun LI Yongjie YANG Jianxin WANG School of Computer Science and Engineering Central South University Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation Changsha University of Science and Technology Chair of Economic Theory Saarland University

The maximum internal spanning tree（MIST） problem is utilized to determine a spanning tree in a graph G,with the maximum number of possible internal *** incremental maximum internal spanning tree（IMIST） problem is the incremental version of MIST whose feasible solutions are edge-sequences e1,e2,…,en-1such that the first k edges form trees for all k ∈ [n-1].A solution's quality is measured using maxk∈[n-1]opt（G,k）/|In（Tk）| with lower being ***,opt（G,k） denotes the number of internal vertices in a tree with k edges in G,which has the largest possible number of internal vertices,and |In（Tk）| is the number of internal vertices in the tree comprising the solution's first k *** first obtained an IMIST algorithm with a competitive ratio of 2,followed by a 12/7-competitive algorithm based on an approximation algorithm for MIST.

关键词： maximum internal spanning tree incremental problem approximation algorithm competitive ratio

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