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Modelling and Use of Adaptive Control Using Petri Nets

Procedia computer Science 2023年 225卷 1438-1447页

作者： Zoltán Balogh Kristián Fodor Jan Francisti Martin Drozda Maroš Čavojský Department of Computer Science Constantine the Philosopher University in Nitra 949 01 Nitra Slovakia Kándó Kálmán Faculty of Electrical Engineering Óbuda University Budapest Hungary Institute of Informatics and Mathematics Slovak University of Technology in Bratislava 811 07 Bratislava Slovakia

The issue of modeling holds significant importance for the applicability of control theory, particularly at higher control levels where the verbal description of control objects becomes increasingly crucial. However, a notable disadvantage of such verbal descriptions is the inherent ambiguity and vagueness of the obtained results. This article aims to address this challenge by proposing an approach that utilizes Petri nets (PN) to model and control a specific component within an intelligent home. Additionally, the Simulink modeling tool and Petri net analysis tools are introduced as aids in the modeling process. The article focuses on creating a model that accurately represents the temperature regulation system in the home, considering the constant rise in energy consumption and costs. Furthermore, the transfer of the model to the Simulink environment using IF THEN rules is demonstrated, allowing for an evaluation of its performance. Through the comprehensive application of this approach, the aim is to optimize energy usage and reduce costs within household environments.

关键词： Petri nets Simulation Matlab Smart homes

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A study of integrating digital health network with UPnP in an elderly nursing home

A study of integrating digital health network with UPnP in a...

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computer Systems Architecture Conference (ACSAC), Australasian

作者： Yaw-Jen Lin Mei-Ju Su Heng-Shuen Chen Chiou-I Lin Hang An Nursing Home Taipei Taiwan Department of Medical Informatics College of Medicine National Taiwan University Taiwan Institute of Electronic Engineering College of Electrical Engineering and Computer Science National Taiwan University Taiwan Department of Information Management Central Taiwan University of Science and Technology Taiwan

The percentage of the elderly population grew rapidly in recent years, so the tremendous life and health care needs became an issue of focus in an aging society. The elderly nursing home plays an important role and intends to provide a comfortable environment and living space and serve as safe and healthy place for the elderly. However, the frailty and fragility of the elderly in both physiologically and psychologically make it an uneasy task. To enhance the service and care quality of an elderly nursing home, a ubiquitous monitor system integrated with biosensors and wireless network technology was implemented as a prototyping system. For managing sensors easily, the universal plug and play (UPnP) technology from digital living network alliance (DLNA) is adopted. The system was expected to be a digital health network to improve the activity of daily living (ADL) of the residents, to detect the emergencies or accidents such as stroke, falling down, fainting, and heart attack, in order to enhance the quality of care and promote efficiency at the same time.

关键词： Sensors Medical services Biomedical monitoring Monitoring Base stations Temperature sensors Sensor systems

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A Two-Tier Anomaly-based Intrusion Detection Approach for IoT-Enabled Smart Cities

A Two-Tier Anomaly-based Intrusion Detection Approach for Io...

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IEEE Conference on computer Communications Workshops, INFOCOM Wksps

作者： Mosab Hamdan Arwa M. Eldhai Samah Abdelsalam Kifayat Ullah Ali Kashif Bashir MN Marsono Fabio Kon Daniel Macêdo Batista Department of Computer Science University of Sao Paulo (USP) Brazil Faculty of Engineering University of Science and Technology Sudan Faculty of Mathematical Sciences and Informatics Khartoum University Sudan Department of Computing and Mathematics Manchester Metropolitan University UK Faculty of Electrical Engineering Universiti Teknologi Malaysia Malaysia

The Internet of Things (IoT), like other network infrastructures, requires Intrusion Detection Systems (IDSs) to be protected against attacks. When deploying an IDS in IoT-based smart city environments, the balance between latency and node capacity must be considered, which justifies a distributed IDS with specific classifiers based on the location of the system processing nodes. This paper proposes a two-level classification technique for collaborative anomaly-based IDSs deployed on fog and edge nodes. A Gradient Boosting Classifier (GBC) is used in the lower layer classifier at the edge, while a Convolutional Neural Network (CNN) is used in the upper layer classifier at the fog. Experimentation has demonstrated that the suggested IDS architecture outperforms previous solutions. For instance, in some scenarios, when comparing our proposal with Random Forest, the former obtained an accuracy equal to 99.1%, while the latter obtained 95.3%. Furthermore, our proposal can better select the most important network traffic features, reducing 76% of the data to be analyzed and improving privacy.

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Advanced underwater acoustic networking and cooperation of multiple marine robots

Advanced underwater acoustic networking and cooperation of m...

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MTS/IEEE OCEANS 2015 - Genova

作者： Djapic, Vladimir Dong, Wenjie Jones, Anthony Cario, Gianni Casavola, Alessandro Lupia, Marco Rosace, Claudio Gjanci, Petrika Petroccia, Roberto Petrioli, Chiara Spaccini, Daniele Tommaselli, Domenico SPAWAR Systems Center Pacific San DiegoCA United States Department of Electrical Engineering University of Texas-Pan American EdinburgTX United States Computer Science Department University of Rome La Sapienza Italy Department of Informatics Modelling Electronics and Systems University of Calabria Rende Italy WSENSE s.r.l. Rome Italy Applicon s.r.l. Rende Italy

ISBN: (纸本)9781479987368

In this paper we present the initial implementation of an advanced communication and networking solution that can enable the coordination and cooperation of autonomous mobile marine robots. To enable such a heterogeneous network three main research areas have been blended: 1) communications, 2) networking, and 3) decentralized cooperative localization and control. This paper focuses on the first two components and addresses the integration of the third one. Due to the challenges of the underwater environment, novel communication software and hardware have to be investigated to provide the level of flexibility and features that are required for efficient networking and robots cooperation. Robust and reliable distributed networking protocols have to be developed and implemented to enable an efficient sharing of data and control messages among heterogeneous surface and underwater platforms. Moreover, the combination of communications, networking and cooperative navigation has to be addressed in order to develop more capable, distributed and efficient underwater systems. ©2015 IEEE.

关键词： Underwater acoustics

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Covert Vehicle Misguidance and Its Detection: A Hypothesis Testing Game over Continuous-Time Dynamics

arXiv

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arXiv 2024年

作者： Tanaka, Takashi Sawada, Kenji Watanabe, Yohei Iwamoto, Mitsugu School of Aeronautics and Astronautics School of Electrical and Computer Engineering Purdue University United States The Info-Powered Energy System Research Center The University of Electro-Communications Japan Department of Informatics The University of Electro-Communications Japan

We formulate a stochastic zero-sum game over continuous-time dynamics to analyze the competition between the attacker, who tries to covertly misguide the vehicle to an unsafe region, versus the detector, who tries to detect the attack signal based on the observed trajectory of the vehicle. Based on Girsanov’s theorem and the generalized Neyman-Pearson lemma, we show that a constant bias injection attack as the attacker’s strategy and a likelihood ratio test as the detector’s strategy constitute the unique saddle point of the game. We also derive the first-order and the second-order exponents of the type II error as a function of the data length. Copyright © 2024, The Authors. All rights reserved.

关键词： Stochastic systems

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Graph Representation Learning For Stroke Recurrence Prediction

Graph Representation Learning For Stroke Recurrence Predicti...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Nicholas Glaze Artun Bayer Xiaoqian Jiang Sean Savitz Santiago Segarra Department of Electrical and Computer Engineering Rice University Houston TX School of Biomedical Informatics University of Texas Health Science Center Houston TX Department of Neurology University of Texas Health Science Center Houston TX

Stroke is one of the leading causes of death worldwide, and its mortality rate is drastically higher for patients who suffer recurrent strokes. Motivated by the recent success of graph learning methods on medical tasks, we introduce a graph representation framework for stroke recurrence prediction (GraSReP) based on patient data. In a nutshell, GraSReP sequentially consists of: i) a procedure for converting tabular, time-series patient data to a series of graphs, ii) a graph deep learning architecture that provides embeddings for the patients and, iii) a random forest classifier that predicts the patients’ risk of recurrent stroke based on these graph embeddings. We demonstrate GraSReP’s effectiveness for predicting recurrent strokes using real-world electronic health records, and discuss how it can be leveraged for the efficient application of preventive care.

关键词： Representation learning Learning systems Deep architecture Stroke (medical condition) Signal processing Acoustics Task analysis

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Preparation and physico-chemical characterization of AISI 304 stainless steel film deposited by DC magnetron sputtering

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Journal of Magnetism and Magnetic Materials 2025年 628卷

作者： Samuel Tomko Jiří Pechoušek Jiří Tuček Ernő Kuzmann Vítězslav Heger Stanislaw M. Dubiel Libor Machala Department of Experimental Physics Faculty of Science Palacký University 17. Listopadu 1192/12 779 00 Olomouc Czech Republic Hella Autotechnik Nova s.r.o. Družstevní 16 789 85 Mohelnice Czech Republic Research Centre Faculty of Electrical Engineering and Informatics University of Pardubice Studentská 95 530 02 Pardubice Czech Republic Institute of Chemistry Eötvös Loránd University 1117 Budapest Pázmány Péter Sétány 1/A Hungary Faculty of Physics and Applied Computer Science AGH University of Krakow Al. A. Mickiewicza 30 30-059 Kraków Poland

The present study reports on the preparation and physico-chemical investigation of a 2 µm thick film produced from AISI 304 stainless steel by DC magnetron sputtering. A phase transformation from the conventionally non-magnetic Face-Centered Cubic (FCC) phase of austenite (γ-Fe) nature to a predominantly Body-Centered Cubic (BCC) ferromagnetic single phase (α-Fe) during the deposition is observed upon the deposition process. The deposited films are characterized by various experimental techniques including Scanning Electron Microscopy (SEM) with Energy-Dispersive X-ray spectroscopy (EDX), X-Ray powder Diffraction (XRD), Grazing-Incidence X-Ray powder Diffraction (GIXRD), and Mössbauer Spectroscopy (MS) in both transmission and back-scattered geometry. For interpretation of the Mössbauer spectra of the film, a physico-chemical model based on distinct micromagnetic environments evolved due to alloying elements is suggested. The results, presented within this study, may stimulate further and detailed research in identifying the causes for the phase transition from both theoretical and experimental perspectives and understanding the underlying mechanisms.

关键词： Sputtering

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Muscle Magnetic Signal Measurement Using High Sensitive Superconducting Sensor

Muscle Magnetic Signal Measurement Using High Sensitive Supe...

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International Conference on Applied Superconductivity and Electromagnetic Devices, ASEMD

作者： Zhidan Zhang Hai Wang Bao Wu Zihan Xu Xiangyan Kong Tiantian Liang Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo China State Key Laboratory of Functional Materials for Informatics Shanghai Institute of Microsystem and Information Technology (SIMIT) Chinese Academy of Sciences (CAS) Shanghai China

ISBN: (数字)9781728152158

ISBN: (纸本)9781728152165

At present, the electromyography (EMG) method used to detect some muscle diseases is blind and random. And it has certain harm to the patients. Therefore, it is very important to develop an efficient and non-invasive method. First-order axial gradiometer based on SQUID is used to detect magnetic signal in muscles. The magnetic noise of the gradiometer is 3.5 fT/√Hz, and its sensitivity fully meet the demands of muscle magnetic detection. We measured the muscle's magnetic field under different intensities of stimulation, as well as the magnetic field generated by the muscle's spontaneous contraction. This is the first try to measure the muscle magnetic signal in China. The results are of great significance for the clinical application of muscle magnetic detection.

关键词： Muscles Superconducting magnets Magnetic shielding Magnetic noise Magnetic domains Magnetic field measurement Magnetic fields

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Cramér-Rao Lower Bounds of Model-Based Electrocardiogram Parameter Estimation

TechRxiv

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TechRxiv 2022年

作者： Fattahi, Davood Sameni, Reza The School of Electrical and Computer Engineering Shiraz University Mollasadra Avenue Shiraz71348–51154 Iran The Department of Biomedical Informatics School of Medicine Emory University 101 Woodruff Circle AtlantaGA30322 United States

Clinical parameter estimation from the electrocardiogram (ECG) is a recurrent field of research. It is debated that ECG parameter estimation by human experts and machines/algorithms is always model-based (implicitly or explicitly). Therefore, all estimation algorithms used in this context have performance bounds in terms of the achievable mean squared error, which are not exceedable. These bounds depend on the adopted data-model, the estimation scheme (least-squares error, maximum likelihood, or Bayesian), and prior assumptions on the model parameters and noise distributions. In this research, we develop a comprehensive theoretical framework for ECG parameter estimation and derive the Cramér-Rao lower bounds (CRLBs) for the most popular signal models used in the ECG modeling literature, namely functional expansions (including polynomials) and sum of Gaussian functions. The developed framework is evaluated over real and synthetic data for three popular applications: T-to-R wave ratio estimation, ST-segment analysis and QT-interval estimation, using the state-of-the-art estimators in each context. The proposed framework and the derived CRLBs provide practical guidelines for the selection of data-models, sampling frequency (beyond the Nyquist rate), modeling segment length, number of beats required for ECG beat averaging, and other factors that influence the accuracy of ECG-based clinical parameter estimation. © 2022, CC BY.

关键词： Electrocardiograms

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Binaural SoundNet: Predicting Semantics, Depth and Motion with Binaural Sounds

arXiv

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arXiv 2021年

作者： Dai, Dengxin Vasudevan, Arun Balajee Matas, Jiri Van Gool, Luc The Vision for Autonomous Systems Group MPI for Informatics The Computer Vision Lab ETH Zürich Switzerland The Center for Machine Perception Czech Technical University Czech Republic The Department of Electrical Engineering KU Leuven Belgium

Humans can robustly recognize and localize objects by using visual and/or auditory cues. While machines are able to do the same with visual data already, less work has been done with sounds. This work develops an approach for scene understanding purely based on binaural sounds. The considered tasks include predicting the semantic masks of sound-making objects, the motion of sound-making objects, and the depth map of the scene. To this aim, we propose a novel sensor setup and record a new audio-visual dataset of street scenes with eight professional binaural microphones and a 360°camera. The co-existence of visual and audio cues is leveraged for supervision transfer. In particular, we employ a cross-modal distillation framework that consists of multiple vision 'teacher' methods and a sound 'student' method-the student method is trained to generate the same results as the teacher methods do. This way, the auditory system can be trained without using human annotations. To further boost the performance, we propose another novel auxiliary task, coined Spatial Sound Super-Resolution, to increase the directional resolution of sounds. We then formulate the four tasks into one end-to-end trainable multi-tasking network aiming to boost the overall performance. Experimental results show that 1) our method achieves good results for all four tasks, 2) the four tasks are mutually beneficial-training them together achieves the best performance, 3) the number and orientation of microphones are both important, and 4) features learned from the standard spectrogram and features obtained by the classic signal processing pipeline are complementary for auditory perception tasks. The data and code are released on the project page: https://***/publications/2020/sound perception/***. Copyright © 2021, The Authors. All rights reserved.

关键词： Semantics

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