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European Conference on Mobile Robots (ECMR)

作者： Aleksa Marusic Louis Annabi Sao Mai Nguyen Adriana Tapus Autonomous Systems and Robotics Lab Computer Science and System Engineering (U2IS) ENSTA Paris Institut Polytechnique de Paris Palaiseau France Dep. Informatique IMT Atlantique

Physical rehabilitation focuses on the improvement of body functions, usually after injury or surgery. Patients undergoing rehabilitation often need to perform exercises at home without the presence of a physiotherapist. computer-aided assessment of physical rehabilitation can improve patients' performance and help in completing prescribed rehabilitation exercises. In this work, we focus on human motion analysis in the context of physical rehabilitation for Low Back Pain (LBP). As 2D and 3D human pose estimation from RGB images had made impressive improvements, we aim to compare the assessment of physical rehabilitation exercises using movement data acquired from RGB videos and human pose estimation from those. In this work, we provide an analysis of two types of algorithms on a Low Back Pain rehabilitation datasets. One is based on a Gaussian Mixture Model (GMM), with performance metrics based on the log-Likelihood values from GMM. Furthermore, with the recent development of Deep Learning and Graph Neural Networks, algorithms based on Spatio-Temporal Graph Convolutional Networks (STGCN) are taken as a novel approach. We compared the algorithms in terms of data efficiency and performance, with evaluation performed on two LBP rehabilitation datasets: KIMORE and Keraal. Our study confirms that Kinect, OpenPose, and BlazePose data yield similar evaluation scores, and shows that STGCN outperforms GMM in most configurations.

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Intelligent Recognition of Immune Cells: Analysis and Research

Intelligent Recognition of Immune Cells: Analysis and Resear...

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IEEE International Conference on e-Business engineering (ICEBE)

作者： Chih-En Li Wei-Lun Liu Kun-Yi Lai Yu-Hsiang Chiang Xiaowei Yan Hao-Xiang Chen Hsu-Ching Li Wan-Shu Cheng Department of Electrical Engineering National Kaohsiung University of Science and Technology Kaohsiung Taiwan Institute for Systems Biology Seattle Washington U.S.A Dep. of Computer Science and Information Management Providence University Taichung Taiwan

Immunotherapy utilizes the potential of the patient's immune system to fight disease. T-lymphocytes have become the central focus of the immune system in the fight against cancer. One of the fundamental studies in immunotherapy is how to accurately identify various types of immune cells. Therefore, the study of immune-related cells will be an important reference for the treatment of COVID19 or other related diseases. In this paper, a series of experiments were conducted with COVID-19 patients as the starting point to design a strategy to identify the important subtypes of CD$4^{+}$T cells. In this paper, an intelligent machine learning algorithm is proposed according to the results of different experiments of linear and nonlinear dimension reduction algorithms, integrating the important characteristics of these two algorithms and improving the performance. Our experimental results show that the algorithm designed based on the front-end experiments can effectively distinguish the important lymphocytes. The proposed algorithm not only improves the performance, but also the dimension reduction procedure keeps the important features of both global and regional data. The experimental results of this paper will be beneficial for the subsequent analysis of the clustering in identifying important subtypes of CD$4^{+}$T cells. Most importantly, this wm significantly improve the procedure of manually integrating and labeling the recorded data after several tedious and monotonous analyses with external software.

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Improving Obstacle Avoidance Strategies in Autonomous Navigation of a Sailboat

Improving Obstacle Avoidance Strategies in Autonomous Naviga...

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On-Line Conference (ONCON), Industrial Electronics Society Annual

作者： Pedro Paiva Luís Gomes Dep. Electrical and Computer Engineering NOVA School of Science and Technology — FCT-NOVA NOVA University Lisbon Caparica Portugal School of Science and Technology Center of Technology and Systems (UNINOVA-CTS) and Associated Lab of Intelligent Systems (LASI) NOVA University Lisbon Caparica Portugal

This work explores the different mechanisms involved in creating a behavioural system for route planning and collision avoidance, taking into account the constraints imposed by the navigational characteristics of the sailboat. The implementation of these mechanisms is accompanied by an introduction to fundamental concepts, including Artificial Potential Fields, Histograms of Vector Fields, Navigation in the No-Go Zone, Differentiation of the Nature of Obstacles resulting in Different Operations, and the Constitution of Different Areas of Actuation. Finally, multiple simulations are conducted in a virtual environment to verify the resilience of the proposed navigation strategy.

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A Safety and Security Requirements Management Methodology in Reconfigurable Collaborative Human-Robot Application

A Safety and Security Requirements Management Methodology in...

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IEEE International Workshop on Factory Communication systems (WFCS)

作者： Ali M. Hosseini Clara Fischer Mukund Bhole Wolfgang Kastner Thilo Sauter Sebastian Schlund Institute of Computer Technology TU Wien Vienna Austria Institute of Management Science TU Wien Vienna Austria Institute of Computer Engineering TU Wien Vienna Austria Dep. of Integrated Sensor Systems Danube Univ. Krems Wiener Neustadt Austria

The current industry has to adapt to rapidly changing customers' needs. Reconfigurable manufacturing, therefore, provides capacity and functionality on demand which is essential for competitiveness in fast-changing markets. Furthermore, Industry 4.0 or even more so, Industry 5.0 emphasizes human-centred production with collaborative robots, Cobots, to create human-robot interactions. In such scenarios, safety and security are difficult to address due to the intrinsic features of reconfigurable manufacturing, like exposure to numerous requirements changes in a short period. As safety and security can conflict in different phases of the system life-cycle, one of the earliest activities to avoid conflicts is requirements engineering which can significantly diminish the cost and time of fixing issues compared to later phases like operation. This paper proposes a methodology for safety and security requirements interaction management, including conflict detection and resolution, and shows its applicability through a reconfigurable collaborative human-robot use case. Based on the proposed methodology, we detected and resolved two safety and security requirement conflicts.

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A Simplified Variant of Gödel's Ontological Argument

arXiv

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arXiv 2022年

作者： Benzmüller, Christoph Otto-Friedrich-Universität Bamberg AI Systems Engineering Bamberg Germany Freie Universität Berlin Dep. of Mathematics and Computer Science Berlin Germany

A simplified variant of Gödel's ontological argument is presented. The simplified argument is valid already in basic modal logics K or KT, it does not suffer from modal collapse, and it avoids the rather complex predicates of essence (Ess.) and necessary existence (NE) as used by Gödel. The variant presented has been obtained as a side result of a series of theory simplification experiments conducted in interaction with a modern proof assistant system. The starting point for these experiments was the computer encoding of Gödel's argument, and then automated reasoning techniques were systematically applied to arrive at the simplified variant presented. The presented work thus exemplifies a fruitful human-computer interaction in computational metaphysics. Whether the presented result increases or decreases the attractiveness and persuasiveness of the ontological argument is a question I would like to pass on to philosophy and theology. Copyright © 2022, The Authors. All rights reserved.

关键词： Human computer interaction

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Secure Password Using EEG-based BrainPrint System: Unlock Smartphone Password Using Brain-computer Interface Technology

Secure Password Using EEG-based BrainPrint System: Unlock Sm...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Zuwaina Alkhyeli Ayesha Alshehhi Mazna Alhemeiri Salma Aldhanhani Khalil AlBalushi Fatima Ali AlNuaimi Abdelkader Nasreddine Belkacem Dep. Computer Science and Software Engineering CIT UAE University Al Ain UAE Dep. Information Systems and Security CIT UAE University Al Ain UAE Dep. Computer & Network Engineering CIT United Arab Emirates University Al Ain UAE TII Autonomous Robotics Research Center Abu Dhabi UAE

ISBN: (数字)9781665468190

ISBN: (纸本)9781665468206

As security becomes a strong factor in daily activities, finding secure ways to unlock machines and smartphones is a challenge due to hardware limitations and the high risk of hacking. Considering the level of security and privacy in the digital world, attackers tend to be one step ahead. Therefore, this technical paper introduces a brain-computer interface (BCI) for increasing subject-based security using unique biometric features as a solution to build complex passwords. The BCI measures brain changes and extracts relevant bio-features from each subject using non-invasive electroencephalogram (EEG) tests. The proposed system allows users to gain access to their devices using brain waves (bypass) instead of inserting their password manually (normal path), which saves the user time and upgrades the level of privacy as no physical actions are required during this process. This system is also well suited for individuals with mobility impairments. We used the P300-based BCI controlling paradigm which depends on reading the electrical brain activity of the user when observing a particular object. The other feature of the system is that it can extract unique features of each individual brain to produce a network that uniquely identifies them, which is used as a security layer. Users need to enter their unique network to access their device with failed attempts requiring an EEG test to identify the user. The system plays an active role in facilitating user processes for authentication while accessing devices. The system establishes an urgent call whenever the user’s brain currents command it to. The project outcomes were assessed by simulating the BCI before real-time implementation to determine errors and resolve the validity of the project scope.

关键词： Privacy Authentication Passwords Feature extraction Brain-computer interfaces Electroencephalography Security

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Development of a Low-Cost Interrogation System Using a MEMS Fabry-Pérot Tunable Filter 5

Development of a Low-Cost Interrogation System Using a MEMS ...

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5th International Conference on Applications of Optics and Photonics, AOP 2022

作者： Araújo, João C. C. Dias, Bernardo Dos Santos, Paulo S. S. De Almeida, J.M.M.M. Coelho, Luís C. C. INESC TEC - Institute for Systems and Computer Engineering Technology and Science FCUP Univ. of Porto R. Do Campo Alegre Porto4169-007 Portugal FCUP University of Porto Rua do Campo Alegre Porto4169-007 Portugal Dep. of Physics Univ. of Trás-os-Montes e Alto Douro Vila Real5001-801 Portugal

The interrogation of optic fiber sensors usually relies in complex and costly equipment with low portability due to their size such as Optical Spectrum Analyzers (OSA) or high-resolution spectrometers. Because of this, micro spectrometer devices, such as Micro-Electromechanical systems (MEMS) with Fabry-Pérot tunable filters, are emerging as simpler and compact alternatives capable of being used to acquire spectral information in a wide wavelength band. In this work it is described the development of an interrogation system capable of infrared spectroscopy using a MEMS Fabry-Pérot Interferometer (MEMS-FPI) with a spectral response in the 1350nm to 1650nm range. Its performance is tested with the interrogation of long period fiber gratings both as a refractive index sensor and as a temperature sensor. Deconvolution techniques such as Wiener filtering are used to reduce the impact of the tunable filter's impulse response in the measured signal. Results are comparable to those obtained using a typical OSA which shows the system's potential as a cheaper and more transportable alternative. © Published under licence by IOP Publishing Ltd.

关键词： Fiber optic sensors

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Automating Public Announcement Logic with Relativized Common Knowledge as a Fragment of HOL in LogiKEy

arXiv

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arXiv 2021年

作者： Benzmüller, Christoph Reiche, Sebastian University of Bamberg AI Systems Engineering Bamberg Germany FU Berlin Dep. of Mathematics and Computer Science Berlin Germany

A shallow semantical embedding for public announcement logic with relativized common knowledge is presented. This embedding enables the first-time automation of this logic with off-the-shelf theorem provers for classical higher-order logic. It is demonstrated (i) how meta-theoretical studies can be automated this way, and (ii) how non-trivial reasoning in the target logic (public announcement logic), required e.g. to obtain a convincing encoding and automation of the wise men puzzle, can be realized. Key to the presented semantical embedding is that evaluation domains are modeled explicitly and treated as an additional parameter in the encodings of the constituents of the embedded target logic;in previous related works, e.g. on the embedding of normal modal logics, evaluation domains were implicitly shared between meta-logic and target logic. The work presented in this article constitutes an important addition to the pluralist LogiKEy knowledge engineering methodology, which enables experimentation with logics and their combinations, with general and domain knowledge, and with concrete use cases - all at the same *** Codes 03B42, 03B60, 03B62, 68T27, 68T30 Copyright © 2021, The Authors. All rights reserved.

关键词： Formal logic

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Vegetation and Drought Trends in Sweden's Mälardalen Region-Year-on-Year Comparison by Gaussian Process Regression

Vegetation and Drought Trends in Sweden's Mälardalen Region...

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2020 Swedish Workshop on Data science, SweDS 2020

作者： Paszkowsky, Nuria Agues Brannvall, Rickard Carlstedt, Johan Milz, Mathias Kovacs, Gyorgy Liwicki, Marcus Unit for Data Center Systems and Applied Data Science Research Institutes of Sweden Sweden Luleå University of Technology Dep. of Computer Science Electrical and Space Engineering Sweden

ISBN: (纸本)9781728192048

This article describes analytical work carried out in a pilot project for the Swedish Space Data Lab (SSDL), which focused on monitoring drought in the Mälardalen region in central Sweden. Normalized Difference Vegetation Index (NDVI) and the Moisture Stress Index (MSI)-commonly used to analyse drought- A re estimated from Sentinel 2 satellite data and averaged over a selection of seven grassland areas of interest. To derive a complete time-series over a season that interpolates over days with missing data, we use Gaussian Process Regression, a technique from multivariate Bayesian analysis. The analysis show significant differences at 95% confidence for five out of seven areas when comparing the peak drought period in the dry year 2018 compared to the corresponding period in 2019. A cross-validation analysis indicates that the model parameter estimates are robust for temporal covariance structure (while inconclusive for the spatial dimensions). There were no signs of over-fitting when comparing in-sample and out-of-sample RMSE. © 2020 IEEE.

关键词： Remote sensing

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Minimization of wind power curtailment using dynamic line rating 10

Minimization of wind power curtailment using dynamic line ra...

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10th IEEE PES Innovative Smart Grid Technologies Europe, ISGT-Europe 2020

作者： Chakrapani Manakari, Vageesh Thengius, Sandra Tammanur Ravi, Akshaya Morozovska, Kateryna Hilber, Patrik KTH Royal Institute of Technology Div. of Electric Power and Energy Systems School of Electrical Engineering and Computer Science Stockholm Sweden Heimdall Power AS Oslo Norway KTH Royal Institute of Technology School of Electrical Engineering and Computer Science Dep. of Electromagnetic Engineering Stockholm Sweden

ISBN: (数字)9781728171005

ISBN: (纸本)9781728171005

Large scale penetration of wind power to the grid and unevenly spread power demand can result in the transmission system not being able to dispatch all the produced wind power, causing in wind power *** line rating (DLR) is a technology which uses thermal properties of overhead conductors and weather data to determine the real-time ampacity limits of transmission lines. In general, dynamic rating allows extending capacity limits of power lines and helps to remove congestion in the grid.(/p)(p This study looks into the possibility of using dynamic line rating for removing congestion in the power system to allow dispatching more wind power and minimize the need for curtailment. The results of case-studies have shown that DLR allows to significantly reduce the curtailment of generation, especially during winter, when wind production is highest and day time, when the power demand is the highest. © 2020 IEEE.

关键词： Wind power

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