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Correction: Experimental evaluation of the impact of sEMG interfaces in enhancing embodiment of virtual myoelectric prostheses

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Journal of neuroengineering and rehabilitation 2024年第1期21卷 64页

作者： Theophil Spiegeler Castañeda Mathilde Connan Patricia Capsi-Morales Philipp Beckerle Claudio Castellini Cristina Piazza Department of Computer Engineering Technical University of Munich (TUM) Garching bei Munich Germany. Institute of Robotics and Mechatronics German Aerospace Center (DLR) Oberpfaffenhofen Germany. Department of Computer Engineering Technical University of Munich (TUM) Garching bei Munich Germany. patricia.capsi-morales@tum.de. Munich Institute of Robotics and Machine Intelligence Technical University of Munich (TUM) Munich Germany. patricia.capsi-morales@tum.de. Department Artificial Intelligence in Biomedical Engineering Friedrich-Alexander-Universität Erlangen- Nürnberg (FAU) Erlangen Germany. Department of Electrical Engineering Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) Erlangen Germany. Munich Institute of Robotics and Machine Intelligence Technical University of Munich (TUM) Munich Germany.

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Prediction of cardiovascular disease using MLP

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AIP Conference Proceedings 2023年第1期2495卷

作者： Sritha Zith Dey Babu Digvijay Pandey Vishali Pathania Jaspinder Kaur Nidhi Sindhwani Rohit Anand Department of Computer Science Chandigarh University Mohali India Department of Electronics Engineering Institute of Engineering and Technology Dr. A.P.J. Abdul Kalam Technical University Lucknow India Department of Mechatronics Engineering Chandigarh University Mohali India AIIT Amity University Noida India Department of ECE DSEU Okhla-1 Campus GBPEC New Delhi India

Machine getting to know and records mining-primarily based strategies to prediction and detection of heart disease could be of exceptional clinical application, however they are distinctly tough to expand. In most countries, there may be a loss of cardiovascular understanding and a vast fee of incorrectly recognized instances will get determined with correct and green early-level heart ailment prediction through analytical aid of clinical selection-making with virtual affected person records. Our research shows the perceived gadget mastering classifiers with the highest accuracy for such diagnostic functions. Multilayer Perceptron techniques have been carried out here for purchasing the extra accuracy with the patient analysis of cardiovascular disease. This examination determined that by the usage of the cardiovascular disease dataset accumulated from Kaggle, the MLP approach executed 74% accuracy together with 70000 vales, 12 attributes and 3 input classifiers. Hence, we discovered that an enormously easy supervised system gaining knowledge of set of rules may be used to make heart ailment predictions with excessive accuracy and awesome capacity utility.

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Efficient State Abstraction using Object-centered Predicates for Manipulation Planning

arXiv

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arXiv 2020年

作者： Agostini, Alejandro Lee, Dongheui Human-centered Assistive Robotics Department of Electrical and Computer Engineering Technical University of Munich Munich80333 Germany Intelligent and Interactive Systems Department of Computer Science University of Innsbruck Innsbruck6020 Austria Institute of Robotics and Mechatronics Wessling Germany

The definition of symbolic descriptions that consistently represent relevant geometrical aspects in manipulation tasks is a challenging problem that has received little attention in the robotic community. This definition is usually done from an observer perspective of a finite set of object relations and orientations that only satisfy geometrical constraints to execute experiments in laboratory conditions. This restricts the possible changes with manipulation actions in the object configuration space to those compatible with that particular external reference definitions, which greatly limits the spectrum of possible manipulations. To tackle these limitations we propose an object-centered representation that permits characterizing a much wider set of possible changes in configuration spaces than the traditional observer perspective counterpart. Based on this representation, we define universal planning operators for picking and placing actions that permits generating plans with geometric and force consistency in manipulation tasks. This object-centered description is directly obtained from the poses and bounding boxes of objects using a novel learning mechanisms that permits generating signal-symbols relations without the need of handcrafting these relations for each particular scenario. Copyright © 2020, The Authors. All rights reserved.

关键词： Wave functions

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Dynamic independent component/vector analysis: Time-variant linear mixtures separable by time-invariant beamformers

arXiv

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arXiv 2020年

作者： Koldovský, Zbyněk Kautský, Václav Tichavský, Petr Čmejla, Jaroslav Málek, Jiří Acoustic Signal Analysis and Processing Group Faculty of Mechatronics Informatics and Interdisciplinary Studies Technical University of Liberec Studentská 2 Liberec461 17 Czech Republic Faculty of Nuclear Sciences and Physical Engineering Czech Technical University Prague Czech Republic The Czech Academy of Sciences Institute of Information Theory and Automation Pod vodárenskou věží 4 P.O. Box 18 Praha 8182 08 Czech Republic

A novel extension of Independent Component and Independent Vector Analysis for blind extraction/separation of one or several sources from time-varying mixtures is proposed. The mixtures are assumed to be separable source-by-source in series or in parallel based on a recently proposed mixing model that allows for the movements of the desired source while the separating beamformer is time-invariant. The popular FastICA algorithm is extended for these mixtures in one-unit, symmetric and block-deflation variants. The algorithms are derived within a unified framework so that they are applicable in the real-valued as well as complex-valued domains, and jointly to several mixtures, similar to Independent Vector Analysis. Performance analysis of the one-unit algorithm is provided;it shows its asymptotic efficiency under the given mixing and statistical models. Numerical simulations corroborate the validity of the analysis, confirm the usefulness of the algorithms in separation of moving sources, and show the superior speed of convergence and ability to separate super-Gaussian as well as sub-Gaussian signals. Copyright © 2020, The Authors. All rights reserved.

关键词： Blind source separation

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Critical infrastructure in the railway transport system 22

Critical infrastructure in the railway transport system

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22nd World Multi-Conference on Systemics, Cybernetics and Informatics, WMSCI 2018

作者： Fuchs, Pavel Soušek, Radovan Šustr, Martin Rozová, Dana Šohajek, Petr Institute of Mechatronics and Computer Engineering Technical University of Liberec Studentska 2 Liberec461 17 Czech Republic Jan Perner Transport Faculty University of Pardubice Studentská 95 Pardubice Czech Republic

ISBN: (纸本)9781941763810

The critical infrastructure in the railway transport is very dynamic system. In the last years are created new critical infrastructure elements. The new critical infrastructure element must be protected, like origin, as well. The most critical infrastructure elements are related to the IT development. The new systems haven't sufficient resilience. This article describes the new crisis infrastructure elements in the railway transport. This article suggests ways to improve resilience, too. Copyright 2018. © by the International institute of Informatics and Systemics.

关键词： Critical infrastructures

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Practical approach to criticality assessment 22

Practical approach to criticality assessment

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22nd World Multi-Conference on Systemics, Cybernetics and Informatics, WMSCI 2018

作者： Fuchs, Pavel Republic, Czech Kamenicky, Jan Zajicek, Jaroslav Sousek, Radovan Institute of Mechatronics and Computer Engineering Technical University of Liberec Studentska 2 Liberec461 17 Czech Republic Jan Perner Transport Faculty University of Pardubice Studentská 95 Pardubice Czech Republic

ISBN: (纸本)9781941763810

Throughout our career, while working in several different companies, it appeared apparent that every man has his own explanation of the term "criticality", no matter if the company was from petrochemical, energy or automotive industry. Moreover, every man believes that his understanding of that term is the only correct one. Criticality is often used as the most important factor in the decision making process about maintenance strategy, spare parts purchases etc. There is currently no existing definition which can explain criticality in a general way, hence this paper was made to show the different points of view on this term. This paper presents the practical multi-criterion criticality approach and offers a solution of how to make calculations/evaluations of criticality more universal. Copyright 2018. © by the International institute of Informatics and Systemics.

关键词： Automotive industry

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Retraction Note: Advancements in optical steganography for secure medical data transmission in telehealth systems

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Optical and Quantum Electronics 2024年第11期56卷 1-1页

作者： Patange, Aparna Mahesan, K. V. Manjula, C. Donald, Cecil Babu, Suresh Peroumal, Vijayakumar Arumugam, Mahendran Department of Medicine Krishna Institute of Medical Sciences Krishna Vishwa Vidya Peeth (Deemed University) Karad India Dr. Ambedkar Institute of Technology Bangalore India Department of Mechatronics Oxford College of Engineering Bangalore India Department of Computer Science CHRIST (Deemed to be University) Bangalore India Department of Biochemistry Symbiosis Medical College for Women Symbiosis International (Deemed University) Pune India School of Electronics Engineering Vellore Institute of Technology Chennai India Center for Transdisciplinary Research Saveetha Dental College Saveetha Institute of Medical and Technical Science Chennai India

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Security enhancement of big data in cloud application using block-chain

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AIP Conference Proceedings 2023年第1期2587卷

作者： Avein Jabar Al-Asadi J. V. S. Arundathi Omdev Dahiya Abdul Wahab Hashmi Ankur Gupta Malik Bader Alazzam Dept. of Information Technology Technical College of Informatics TCI Sulaimani Polytechnic University Sulaymaniyah Iraq Dept. of Computer Science SR & BGNR Government Arts and Science Degree & PG College (Autonomous) Khammam Telangana India School of Computer Science and Engineering Lovely Professional University Phagwara Punjab India Advanced Manufacturing and Mechatronics Lab Mechanical Engineering Department Malaviya National Institute of Technology Jaipur India Dept. of Computer Science and Engineering Vaish College of Engineering Rohtak Haryana India Faculty of Computer Science and Informatics Amman Arab University Amman Jordan

Organizations are inundated on a daily basis with vast, difficult-to-manage volumes of structured and unstructured data, which is known as “big data.” Analysis of large amounts of data may provide useful information that can be used to improve decision-making and boost employee morale. This kind of data storage makes it almost hard to change, hack, or otherwise deceive. Every computer in a block-chain network has a copy of the block-transaction chain’s log, which is called a “block-chain.” In previous researches it has been observed that security of big data is a major issue. Block chain has been found suitable mechanism to deal with such issues. Block-chain has also been considered a service in the context of cloud computing, termed Block-chain as a Service (BaaS). By using virtual storage nodes, block-chain technology may create whole new cloud storage services that are very resistant to data tampering. The proposed research has focused on the enhancement of security of big data from SQL injection attack that is transferred over cloud application. Research is making use of block chain technology in order to resolve the issue of security. The major objective of research is to propose block chain based security model for big data that should be more secure and efficient in case of SQL injection attack. Research work has proposed modified algorithm enhances the security of big data in cloud application against SQL injection, cross script.

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A human-cyber-physical system approach to lean automation using an industrie 4.0 reference architecture

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Procedia Manufacturing 2020年 51卷 1082-1090页

作者： Matteo Pantano Daniel Regulin Benjamin Lutz Dongheui Lee Functional Materials & Manufacturing Processes Corporate Technology Department Siemens Aktiengesellschaft Munich 81739 Germany Human-Centered Assistive Robotics (HCR) Department of Electrical and Computer Engineering Technical University of Munich Munich 80333 Germany Institute of Robotics and Mechatronics German Aerospace Center (DLR) Oberpfaffenhofen-Weßling 82234 Germany

The factory of the future requires flexibility and adaptability to satisfy market demands. However, these properties are difficult to ensure when collaborative manipulators are considered. Thus, approaches for integrating these devices, fostering the adoption of new engineering methodologies for augmenting manipulators are studied. In this work we address how integration of human operators with robotic manipulators might accommodate flexibility requirements using a concept of lean automation. To answer this question, we compare the current research in the field, and we propose a design structure which addresses safety, interfaces and design methods. Our results show safety hardware posing considerable constraints on flexibility. The human interface influences the workload perceived by an operator and, Industrie 4.0 reference architectures do not foresee the human and reconfigurable production cells yet. From a design prospective, this study emphasizes the need to take into consideration human and engineering aspects while planning for the factory of the future.

关键词： Human-cyber-physical system lean automation human-centred design Industrie 4.0 RAMI 4.0

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A roadmap for AI in robotics

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Nature Machine Intelligence 2025年 1-7页

作者： Aude Billard Alin Albu-Schaeffer Michael Beetz Wolfram Burgard Peter Corke Matei Ciocarlie Ravinder Dahiya Danica Kragic Ken Goldberg Yukie Nagai Davide Scaramuzza Learning Algorithms and Systems Laboratory (LASA) École Polytechnique Fédérale de Lausanne (EPFL) Lausanne Switzerland Institute of Robotics and Mechatronics DLR-German Aerospace Center/Department of Informatics Technical University of Munich Munich Germany Institute for Artificial Intelligence Computer Science Department University of Bremen Bremen Germany Department of Engineering University of Technology Nuremberg Nuremberg Germany Center for Robotics Queensland University of Technology Brisbane Queensland Australia Columbia University New York City NY USA Northeastern University Boston MA USA School of Computer Science and Communication Royal Institute of Technology Stockholm Sweden University of California Berkeley Berkeley CA USA International Research Center for Neurointelligence The University of Tokyo Tokyo Japan Robotics and Perception Group University of Zurich Zurich Switzerland

There is growing excitement about the potential of leveraging artificial intelligence (AI) to tackle some of the outstanding barriers to the full deployment of robots in daily lives. However, action and sensing in the physical world pose greater and different challenges for AI than analysing data in isolation and it is important to reflect on which AI approaches are most likely to be successfully applied to robots. Questions to address, among others, are how AI models can be adapted to specific robot designs, tasks and environments. This Perspective offers an assessment of what AI has achieved for robotics since the 1990s and proposes a research roadmap with challenges and promises. These range from keeping up-to-date large datasets, representatives of a diversity of tasks that robots may have to perform, and of environments they may encounter, to designing AI algorithms tailored specifically to robotics problems but generic enough to apply to a wide range of applications and transfer easily to a variety of robotic platforms. For robots to collaborate effectively with humans, they must predict human behaviour without relying on bias-based profiling. Explainability and transparency in AI-driven robot control are essential for building trust, preventing misuse and attributing responsibility in accidents. We close with describing what are, in our view, primary long-term challenges, namely, designing robots capable of lifelong learning, and guaranteeing safe deployment and usage, as well as sustainable development.

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