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Latin American Test Workshop, LATW

作者： María L. Pinto-Salamanca Josie E. Rodriguez Condia José A. Hidalgo-López Wilson J. Pérez-Holguín GIRA Research Group Universidad Pedagógica y Tecnológica de Colombia (UPTC) Departamento de Electrónica Universidad de Málaga Department of Control and Computer Engineering (DAUIN) Politecnico di Torino

ISBN: (数字)9798350365559

ISBN: (纸本)9798350365566

1 Today, advances in scientific and embedded computing and the incredible proliferation of machine learning algorithms take advantage of specialized hardware accelerators to provide exceptional performance and good accuracy. In some safety-critical applications like autonomous robotics, healthcare, and automotive, crucial mathematical operations such as convolutions are often efficiently mapped in hardware as Matrix-Vector(MxV) and Matrix-Matrix (MxM) multiplications. Moreover, sophisticated sparsity algorithms aim to improve performance and power consumption. Unfortunately, technology scaling trends may increase the proliferation of faults on hardware during the in-field operation, so there is a rising interest in the reliability assessment and analysis of sparsity-based accelerators. This work evaluates the impact of soft errors (bit-flips) on sparse-matrix dense-vector multiplication (SpMV) cores for safety-critical tactile sensing applications by resorting to a High-Level Synthesis (HLS) strategy. The experiments are performed on an open-source streaming SpMV core using the Compressed Sparse Row (CSR) format when processing characteristic medium-size sparse matrices (100x100 and 494x494). Our results indicate that data-path pipeline registers in the (SpMV) core are resilient to transient faults (< 1.3% of observed corruption effects), while large magnitude errors can be associated with the type of sparse matrix describing the system (e.g., number of non-zero values) and the type and features of the input vector sensor.

关键词： Machine learning algorithms Power demand Pipelines Robot sensing systems Vectors Sensors Registers

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Evaluation of the Performance of Wearables’ Inertial Sensors for the Diagnosis of Resting Tremor in Parkinson’s Disease

Evaluation of the Performance of Wearables’ Inertial Sensor...

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17th International Joint Conference on Biomedical engineering Systems and Technologies, BIOSTEC 2024

作者： Polvorinos-Fernández, Carlos Sigcha, Luis de Pablo, Laura Pereira Borzí, Luigi Cardoso, Paulo Costa, Nelson Costa, Susana López, Juan Manuel de Arcas, Guillermo Pavón, Ignacio Mechanical Engineering Department ETSI Industriales Universidad Politécnica de Madrid Spain Group University of Limerick LimerickV94 T9PX Ireland ALGORITMI Research Center School of Engineering University of Minho Guimarães Portugal PolitoBIOMed Lab–Biomedical Engineering Lab Politecnico di Torino Turin10129 Italy ANTHEA Lab–Data Analytics and Technologies for Health Lab Department of Control and Computer Engineering Politecnico di Torino Turin10129 Italy Physical Electronics Electrical Engineering and Applied Physics Department ETS de Ingeniería y Sistemas de Telecomunicación Universidad Politécnica de Madrid Spain

Currently, objective monitoring of resting tremor in Parkinson’s disease (PD) involves wearable devices and machine learning. Smartwatches may present an affordable method for remote and unintrusive tremor monitoring. However, the development of optimized systems is necessary to perform accurate monitoring in free-living settings. In this study, the potential of inertial sensors to detect resting tremors is evaluated. A smartwatch was placed on the wrist of six subjects with PD during the execution of MDS-UPDRS motor tasks. Data were collected over eight weeks from triaxial accelerometer and gyroscope simultaneously and used to implement machine learning algorithms to detect resting tremor. The best performance (accuracy 97.0% in tremor detection) was achieved using accelerometer data analysed with a Random Forest classifier, while the gyroscope showed lower performance (93.0%). The results indicates that the use of the accelerometer in commercial smartwatches can offer effective results for detecting resting tremors, while reducing computational workload. These results show opportunities for the development of robust free-living tremor monitoring systems using commodity devices and algorithms using a single sensor. © 2024 by SCITEPRESS–Science and Technology Publications, Lda.

关键词： Gyroscopes

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The Dark Side of the Language: Pre-trained Transformers in the DarkNet

arXiv

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arXiv 2022年

作者： Ranaldi, Leonardo Nourbakhsh, Aria Patrizi, Arianna Ruzzetti, Elena Sofia Onorati, Dario Fallucchi, Francesca Zanzotto, Fabio Massimo Mastromattei, Michele Human-Centric ART Group Department of Enterprise Engineering University of Rome Tor Vergata Italy Department of Computer Control and Management Engineering University of Rome "Sapienza" Italy

Pre-trained Transformers are challenging human performances in many NLP tasks. The massive datasets used for pre-training seem to be the key to their success on existing tasks. In this paper, we explore how a range of pretrained Natural Language Understanding models perform on definitely unseen sentences provided by classification tasks over a DarkNet corpus. Surprisingly, results show that syntactic and lexical neural networks perform on par with pre-trained Transformers even after fine-tuning. Only after what we call extreme domain adaptation, that is, retraining with the masked language model task on all the novel corpus, pre-trained Transformers reach their standard high results. This suggests that huge pre-training corpora may give Transformers unexpected help since they are exposed to many of the possible sentences. © 2022, CC BY.

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DEVELOPMENT OF A MULTI-SENSOR DEVICE FOR INDOOR ENVIRONMENTAL QUALITY ASSESSMENT 10

DEVELOPMENT OF A MULTI-SENSOR DEVICE FOR INDOOR ENVIRONMENTA...

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10th Convention of the European Acoustics Association, EAA 2023

作者： Fissore, Virginia Isabella Barbaro, Alberto Chiavassa, Pietro Espinosa, Gustavo Adolfo Ramirez Puglisi, Giuseppina Emma Raviola, Erica Giusto, Edoardo Shtrepi, Louena Servetti, Antonio Montrucchio, Bartolomeo Fiori, Franco Pellegrino, Anna Clerici, Jana Sassoli, Nicolas Paduos, Simona Corrado, Vincenzo Astolfi, Arianna Department of Energy Politecnico di Torino Italy Department of Electronics and Telecommunications Politecnico di Torino Italy Department of Control and Computer Engineering Politecnico di Torino Italy PROGES Politecnico di Torino Turin Italy Geoside S.p.A. Italgas Group Bologna Italy Intesa Sanpaolo Piazza San Carlo 156 Turin Italy C2R Energy Consulting S.r.l. Turin Italy

ISBN: (纸本)9788888942674

Indoor Environmental Quality (IEQ) assessment in offices is demanded for the analysis of building performances, management of energy consumptions and occupants' well-being, comfort and work productivity. The present work presents the PROMET&O (PROactive Monitoring for indoor EnvironmenTal quality & cOmfort) system, composed by a low-cost and accurate multi-sensor and a tablet for the acquisition, analysis and communication of the quality conditions of indoor environments to different categories of users. Thermal, lighting, acoustic and air quality conditions will be monitored and displayed, through a user-friendly interface, both to the building infrastructures managers and to the occupants, with the further aim of enhancing their awareness and proactive behavior. © 2023 First author et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 3.0 Unported License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

关键词： Air quality

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Visual Tracking Nonlinear Model Predictive control Method for Autonomous Wind Turbine Inspection

Visual Tracking Nonlinear Model Predictive Control Method fo...

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International Conference on Advanced Robotics (ICAR)

作者： Abdelhakim Amer Mohit Mehndiratta Jonas le Fevre Sejersen Huy Xuan Pham Erdal Kayacan Department of Electrical and Computer Engineering Artificial Intelligence in Robotics Laboratory (AiR Lab) Aarhus University Aarhus C Denmark GIM Robotics Espoo Finland Department of Electrical Engineering and Information Technology Automatic Control Group Paderborn University Paderborn Germany

Automated visual inspection of on- and off-shorewind turbines using aerial robots provides several benefits, namely, a safe working environment by circumventing the need for workers to be suspended high above the ground, reduced inspection time, preventive maintenance, and access to hard-to-reach areas. A novel nonlinear model predictive control (NMPC) framework alongside a global wind turbine path planner is proposed to achieve distance-optimal coverage for wind turbine inspection. Unlike traditional MPC formulations, visual tracking NMPC (VT-NMPC) is designed to track an inspection surface, instead of a position and heading trajectory, thereby circumventing the need to provide an accurate predefined trajectory for the drone. An additional capability of the proposed VT-NMPC method is that by incorporating inspection requirements as visual tracking costs to minimize, it naturally achieves the inspection task successfully while respecting the physical constraints of the drone. Multiple simulation runs and real-world tests demonstrate the efficiency and efficacy of the proposed automated inspection framework, which outperforms the traditional MPC designs, by providing full coverage of the target wind turbine blades as well as its robustness to changing wind conditions. The implementation codes 1 1 https://***/open-airlab/VTNMPC-Autonomous-Wind-Turbine-Inspection are open-sourced.

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A flexible analytic wavelet transform and ensemble bagged tree model for electroencephalogram-based meditative mind-wandering detection

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Healthcare Analytics 2024年 5卷 100286-100286页

作者： Dadhich, Ajay Patel, Jaideep Tiwari, Rovin Verma, Richa Mishra, Pratha Jain, Jay Kumar Department of Electronics Instrumentation and Control Engineering Engineering College Ajmer Rajasthan Ajmer India Department of Computer Science and Engineering Sagar Institute of Research & Technology MP Bhopal India Department of Electronics & Communication Engineering Amity University MP Gwalior India Department of Computer Science and Application Makhanlal Chaturvedi University of Journalism and Mass Communication MP Bhopal India Department of Electronics & Communication Engineering Technocrats TIT Group Madhya Pradesh Bhopal India Department of Computer Science & Engineering Indian Institute of Information Technology (IIIT) MP Bhopal India

Mind-wandering (MW) is when an individual's concentration drifts away from the task or activity. Researchers found a greater variability in electroencephalogram (EEG) signals due to MW. Collecting more nuanced information from raw EEG data to examine the harmful effects of MW is time-consuming. This study proposes a multi-resolution assessment of EEG signals using the flexible analytic wavelet transform (FAWT). The FAWT algorithm decomposes raw EEG data into more representative sub-bands (SBs). Several statistical characteristics are derived from the obtained SBs, and the effects of MW during meditation on the EEG signals are investigated. A set of significant characteristics is chosen and fed into the machine learning modules using a 10-fold validation approach to detect MW subjects automatically. Our proposed framework attained the highest classification accuracy of 92.41%, the highest sensitivity of 93.56%, and the highest specificity of 91.97%. The proposed framework can be used to design a suitable brain-computer interface (BCI) system to reduce MW and increase meditation depth for holistic and long-term health in society. © 2023 The Author(s)

关键词： Brain–computer interface Classification Electroencephalogram signals Flexible analytic wavelet transform Machine learning Mind-wandering

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Safe Barrier-Constrained control of Uncertain Systems via Event-triggered Learning

arXiv

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arXiv 2024年

作者： Lederer, Armin Begzadić, Azra Hirche, Sandra Cortés, Jorge Herbert, Sylvia The Learning and Adaptive Systems Group Department of Computer Science ETH Zurich Switzerland The Department of Mechanical and Aerospace Engineering University of California San Diego United States The Chair of Information-oriented Control TUM School of Computation Information and Technology Technical University of Munich Germany

While control barrier functions are employed in addressing safety, control synthesis methods based on them generally rely on accurate system dynamics. This is a critical limitation, since the dynamics of complex systems are often not fully known. Supervised machine learning techniques hold great promise for alleviating this weakness by inferring models from data. We propose a novel control barrier function-based framework for safe control through event-triggered learning, which switches between prioritizing control performance and improving model accuracy based on the uncertainty of the learned model. By updating a Gaussian process model with training points gathered online, the approach guarantees the feasibility of control barrier function conditions with high probability, such that safety can be ensured in a data-efficient manner. Furthermore, we establish the absence of Zeno behavior in the triggering scheme, and extend the algorithm to sampled-data realizations by accounting for inter-sampling effects. The effectiveness of the proposed approach and theory is demonstrated in simulations. Copyright © 2024, The Authors. All rights reserved.

关键词： Gaussian distribution

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Software Implementation of a Smart Bracelet Prototype to Monitor Vital Signs, Locate, and Track COVID-19 Patients in Quarantine Zone

Software Implementation of a Smart Bracelet Prototype to Mon...

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2022 IEEE International Conference on Blockchain, Smart Healthcare and Emerging Technologies, SmartBlock4Health 2022

作者： Naji, Hasan K. Goga, Nicolae Karkar, Ammar J. M. Ali, Haider Abdullah Falahi, Mandana Marin, Iuliana Ramona-Cristina, Popa Doctoral School of Automatic Control and Computers University POLITEHNICA of Bucharest Bucharest Romania University POLITEHNICA of Bucharest Faculty of Engineering in Foreign Languages Bucharest Romania University of Groningen Molecular Dynamics Group Groningen Netherlands University of Kufa IT Research and Development Centre Department of Electronic and Communication Engineering Najaf Iraq University POLITEHNICA of Bucharest Faculty of Automatic Control and Computers Bucharest Romania Madenat Alelem University Collage Department of Computer Engineering Techniques Baghdad Iraq University POLITEHNICA of Bucharest Bucharest Romania

ISBN: (纸本)9781665460149

This paper describes the design and software implementation of a wearable prototype that allows users to monitor the vital signs of COVID-19 patients in quarantine areas. This prototype consists of two parts, the bracelet, andthe Base control unit (BCU). The bracelet is built with ESP8266 and sensors as main components, as well as the battery and other parts needed to fulfill the system's purpose (monitoring the vital signs of COVID-19 patients). At the same time, the Raspberry Pi (SCB) single board computer and GSM/GPRS/HAT are the main components of the Basic control Unit (BCU). The current work describes the main parts of the pseudocode, as well as the activity diagram for the microcontroller and Raspberry Pi. This paper describes the mechanism of sending alert messages, whereby the system's ability to configure two types of alert messages;(1) physician Messages (these Messages will be sent to the physicianassociated with the patient if one or more vital signs reach a critical value;these messages contain all measurements of a patient's vital signs);(2) Authorize messages (these messages will be sent if the quarantine rules are violated;the patient's location will be sent to the authorized person as a Google Mapslink). Also, this paper describes the graphical user interface for communication, management,. and interaction between the users of the system. © 2022 IEEE.

关键词： COVID-19

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Learning Reduced-Order Linear Parameter-Varying Models of Nonlinear Systems

arXiv

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arXiv 2023年

作者： Koelewijn, Patrick J.W. Singh, Rajiv Seiler, Peter Tóth, Roland Sioux Technologies B.V. Eindhoven Netherlands Control Systems Group Eindhoven University of Technology Eindhoven Netherlands The MathWorks Inc. Natick United States Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor United States Systems and Control Laboratory HUN-REN Institute for Computer Science and Control Budapest Hungary

In this paper, we consider the learning of a Reduced-Order Linear Parameter-Varying Model (ROLPVM) of a nonlinear dynamical system based on data. This is achieved by a two-step procedure. In the first step, we learn a projection to a lower dimensional state-space. In step two, an LPV model is learned on the reduced-order state-space using a novel, efficient parameterization in terms of neural networks. The improved modeling accuracy of the method compared to an existing method is demonstrated by simulation examples. Copyright © 2023, The Authors. All rights reserved.

关键词： Nonlinear dynamical systems

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Machine Learning-based feasibility estimation of digital blocks in BCD technology

arXiv

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arXiv 2024年

作者： Daghero, Francesco Di Carolo, Nicola Faraone, Gabriele Franchino, Giovanna Antonella Grosso, Michelangelo Licastro, Dario Pagliari, Daniele Jahier Serianni, Eugenio Department of Control and Computer Engineering Politecnico di Torino Turin10129 Italy Analog Power & Discrete MEMS and Sensor R&D group STMicroelectronics Agrate Brianza20864 Italy Analog Power & Discrete MEMS and Sensor R&D group STMicroelectronics Turin10129 Italy

Analog-on-Top Mixed Signal (AMS) Integrated Circuit (IC) design is a time-consuming process predominantly carried out by hand. Within this flow, usually, some area is reserved by the top-level integrator for the placement of digital blocks. Specific features of the area, such as size and shape, have a relevant impact on the possibility of implementing the digital logic with the required functionality. We present a Machine Learning (ML)-based evaluation methodology for predicting the feasibility of digital implementation using a set of high-level features. This approach aims to avoid time-consuming Place-and-Route trials, enabling rapid feedback between Digital and Analog Back-End designers during top-level placement. © 2024, CC BY.

关键词： Integrated circuit layout

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