Sensors, Vol. 24, Pages 2650: Vehicle-Type Recognition Method for Images Based on Improved Faster R-CNN Model
anfa Wang
The rapid increase in the number of vehicles has led to increasing traffic congestion, traffic accidents, and motor vehicle crime rates. The management of various parking lots has also become increasingly challenging. Vehicle-type recognition technology can reduce the workload of humans in vehicle management operations. Therefore, the application of image technology for vehicle-type recognition is of great significance for integrated traffic management. In this paper, an improved faster region with convolutional neural network features (Faster R-CNN) model was proposed for vehicle-type recognition. Firstly, t...
Source: Sensors - April 21, 2024 Category: Biotechnology Authors: Tong Bai Jiasai Luo Sen Zhou Yi Lu Yuanfa Wang Tags: Article Source Type: research
Sensors, Vol. 24, Pages 2651: Robust Cooperative Fault-Tolerant Control for Uncertain Multi-Agent Systems Subject to Actuator Faults
This article investigates the robust cooperative fault-tolerant control problem of multi-agent systems subject to mismatched uncertainties and actuator faults. During the design process of the intermediate variable estimator, there is no need to satisfy fault estimation matching conditions, and this overcomes a crucial constraint of traditional observers and estimators. The feedback term of the designed estimator contains the centralized estimation errors and the distributed estimation errors of the agent, and this further improves the design freedom of the proposed estimator. A novel fault-tolerant control protocol is des...
Source: Sensors - April 21, 2024 Category: Biotechnology Authors: Jiantao Shi Xiang Chen Shuangqing Xing Anning Liu Chuang Chen Tags: Article Source Type: research
Sensors, Vol. 24, Pages 2652: Machine Tool Wear Prediction Technology Based on Multi-Sensor Information Fusion
jun Xie
The intelligent monitoring of cutting tools used in the manufacturing industry is steadily becoming more convenient. To accurately predict the state of tools and tool breakages, this study proposes a tool wear prediction technique based on multi-sensor information fusion. First, the vibrational, current, and cutting force signals transmitted during the machining process were collected, and the features were extracted. Next, the Kalman filtering algorithm was used for feature fusion, and a predictive model for tool wear was constructed by combining the ResNet and long short-term memory (LSTM) models (called ResN...
Source: Sensors - April 21, 2024 Category: Biotechnology Authors: Kang Wang Aimin Wang Long Wu Guangjun Xie Tags: Article Source Type: research
Sensors, Vol. 24, Pages 2644: Characterization of Running Intensity in Canadian Football Based on Tactical Position
This study aimed to use a data-driven approach to identify individualized speed thresholds to characterize running demands and athlete workload during games and practices in skill and linemen football players. Data were recorded from wearable sensors over 28 sessions from 30 male Canadian varsity football athletes, resulting in a total of 287 performances analyzed, including 137 games and 150 practices, using a global positioning system. Speed zones were identified for each performance by fitting a 5-dimensional Gaussian mixture model (GMM) corresponding to 5 running intensity zones from minimal (zone 1) to maximal (zone 5...
Source: Sensors - April 21, 2024 Category: Biotechnology Authors: Abdullah Zafar Samuel Guay Sophie-Andr ée Vinet Am élie Apinis-Deshaies Rapha ëlle Creniault G éraldine Martens Fran çois Prince Louis De Beaumont Tags: Article Source Type: research
Sensors, Vol. 24, Pages 2645: Exploring Human & ndash;Exoskeleton Interaction Dynamics: An In-Depth Analysis of Knee Flexion & ndash;Extension Performance across Varied Robot Assistance & ndash;Resistance Configurations
Sensors, Vol. 24, Pages 2645: Exploring Human–Exoskeleton Interaction Dynamics: An In-Depth Analysis of Knee Flexion–Extension Performance across Varied Robot Assistance–Resistance Configurations
Sensors doi: 10.3390/s24082645
Authors:
Denis Mosconi
Yecid Moreno
Adriano Siqueira
Knee rehabilitation therapy after trauma or neuromotor diseases is fundamental to restore the joint functions as best as possible, exoskeleton robots being an important resource in this context, since they optimize therapy by applying tailored forces to assist or resist movements, contributing to improved p...
Source: Sensors - April 21, 2024 Category: Biotechnology Authors: Denis Mosconi Yecid Moreno Adriano Siqueira Tags: Article Source Type: research
Sensors, Vol. 24, Pages 2646: A g\({_m}\)/I\({_D}\)-Based Low-Power LNA for Ka-Band Applications
This article presents the design of a low-power low noise amplifier (LNA) implemented in 45 nm silicon-on-insulator (SOI) technology using the gm/ID methodology. The Ka-band LNA achieves a very low power consumption of only 1.98 mW andis the first time the gm/ID approach is applied at such a high frequency. The circuit is suitable for Ka-band applications with a central frequency of 28 GHz, as the circuit is intended to operate in the n257 frequency band defined by the 3GPP 5G new radio (NR) specification. The proposed cascode LNA uses the gm/ID methodology in an RF/MW scenario to exploit the advantages of moderate inversi...
Source: Sensors - April 21, 2024 Category: Biotechnology Authors: David Galante-Sempere Jeffrey Torres-Clarke Javier del Pino Sunil Lalchand Khemchandani Tags: Article Source Type: research
Sensors, Vol. 24, Pages 2647: Smart Sensors and Smart Data for Precision Agriculture: A Review
rco Fossa
Precision agriculture, driven by the convergence of smart sensors and advanced technologies, has emerged as a transformative force in modern farming practices. The present review synthesizes insights from a multitude of research papers, exploring the dynamic landscape of precision agriculture. The main focus is on the integration of smart sensors, coupled with technologies such as the Internet of Things (IoT), big data analytics, and Artificial Intelligence (AI). This analysis is set in the context of optimizing crop management, using resources wisely, and promoting sustainability in the agricultural sector. ...
Source: Sensors - April 21, 2024 Category: Biotechnology Authors: Abdellatif Soussi Enrico Zero Roberto Sacile Daniele Trinchero Marco Fossa Tags: Review Source Type: research
Sensors, Vol. 24, Pages 2648: Understanding the Nonlinear Response of SiPMs
do
A systematic study of the nonlinear response of Silicon Photomultipliers (SiPMs) was conducted through Monte Carlo (MC) simulations. The MC code was validated against experimental data for two different SiPMs. Nonlinearity mainly depends on the balance between the photon rate and the pixel recovery time. Additionally, nonlinearity has been found to depend on the light pulse shape, the correlated noise, the overvoltage dependence of the photon detection efficiency, and the impedance of the readout circuit. Correlated noise has been shown to have a minor impact on nonlinearity, but it can significantly affect the shap...
Source: Sensors - April 21, 2024 Category: Biotechnology Authors: V íctor Moya-Zamanillo Jaime Rosado Tags: Article Source Type: research
Sensors, Vol. 24, Pages 2649: Implementing Gait Kinematic Trajectory Forecasting Models on an Embedded System
Chomiak
Smart algorithms for gait kinematic motion prediction in wearable assistive devices including prostheses, bionics, and exoskeletons can ensure safer and more effective device functionality. Although embedded systems can support the use of smart algorithms, there are important limitations associated with computational load. This poses a tangible barrier for models with increased complexity that demand substantial computational resources for superior performance. Forecasting through Recurrent Topology (FReT) represents a computationally lightweight time-series data forecasting algorithm with the ability to update...
Source: Sensors - April 21, 2024 Category: Biotechnology Authors: Madina Shayne Leonardo A. Molina Bin Hu Taylor Chomiak Tags: Article Source Type: research
Sensors, Vol. 24, Pages 2632: Assessing the Effect of Data Quality on Distance Estimation in Smartphone-Based Outdoor 6MWT
rio Salvi
As a result of technological advancements, functional capacity assessments, such as the 6-minute walk test, can be performed remotely, at home and in the community. Current studies, however, tend to overlook the crucial aspect of data quality, often limiting their focus to idealised scenarios. Challenging conditions may arise when performing a test given the risk of collecting poor-quality GNSS signal, which can undermine the reliability of the results. This work shows the impact of applying filtering rules to avoid noisy samples in common algorithms that compute the walked distance from positioning data. The...
Source: Sensors - April 20, 2024 Category: Biotechnology Authors: Sara Caramaschi Carl Magnus Olsson Elizabeth Orchard Jackson Molloy Dario Salvi Tags: Article Source Type: research
Sensors, Vol. 24, Pages 2633: Anomaly Detection in Railway Sensor Data Environments: State-of-the-Art Methods and Empirical Performance Evaluation
hbroth
To date, significant progress has been made in the field of railway anomaly detection using technologies such as real-time data analytics, the Internet of Things, and machine learning. As technology continues to evolve, the ability to detect and respond to anomalies in railway systems is once again in the spotlight. However, railway anomaly detection faces challenges related to the vast infrastructure, dynamic conditions, aging infrastructure, and adverse environmental conditions on the one hand, and the scale, complexity, and critical safety implications of railway systems on the other. Our study is underpinned...
Source: Sensors - April 20, 2024 Category: Biotechnology Authors: Micha ł Bałdyga Kacper Bara ński Jakub Belter Mateusz Kalinowski Pawe ł Weichbroth Tags: Article Source Type: research
Sensors, Vol. 24, Pages 2634: Analysis and Prediction of Urban Surface Transformation Based on Small Baseline Subset Interferometric Synthetic Aperture Radar and Sparrow Search Algorithm & ndash;Convolutional Neural Network & ndash;Long Short-Term Memory Model
Sensors, Vol. 24, Pages 2634: Analysis and Prediction of Urban Surface Transformation Based on Small Baseline Subset Interferometric Synthetic Aperture Radar and Sparrow Search Algorithm–Convolutional Neural Network–Long Short-Term Memory Model
Sensors doi: 10.3390/s24082634
Authors:
Yuejuan Chen
Siai Du
Pingping Huang
Huifang Ren
Bo Yin
Yaolong Qi
Cong Ding
Wei Xu
With the acceleration of urbanisation, urban areas are subject to the combined effects of the accumulation of various natural factors, such as changes in temperature leading to the thermal expansion or contraction of sur...
Source: Sensors - April 20, 2024 Category: Biotechnology Authors: Yuejuan Chen Siai Du Pingping Huang Huifang Ren Bo Yin Yaolong Qi Cong Ding Wei Xu Tags: Article Source Type: research
Sensors, Vol. 24, Pages 2635: Assessing the Impact of COVID-19 on Amateur Runners & rsquo; Performance: An Analysis through Monitoring Devices
Sensors, Vol. 24, Pages 2635: Assessing the Impact of COVID-19 on Amateur Runners’ Performance: An Analysis through Monitoring Devices
Sensors doi: 10.3390/s24082635
Authors:
María García-Arrabé
María-José Giménez
Juliette Moriceau
Amandine Fevre
Jean-Sebastien Roy
Ángel González-de-la-Flor
Marta de la Plaza San Frutos
This retrospective study aimed to analyze the return to running of non-professional runners after experiencing asymptomatic or mild COVID-19. Participants aged 18–55 years who maintained a training load of ≥10 km/week for at least three months pr...
Source: Sensors - April 20, 2024 Category: Biotechnology Authors: Mar ía García-Arrabé Mar ía-José Giménez Juliette Moriceau Amandine Fevre Jean-Sebastien Roy Ángel González-de-la-Flor Marta de la Plaza San Frutos Tags: Article Source Type: research
Sensors, Vol. 24, Pages 2636: Comparative Analysis of Anomaly Detection Approaches in Firewall Logs: Integrating Light-Weight Synthesis of Security Logs and Artificially Generated Attack Detection
This study focuses on analyzing firewall logs from a large industrial control network and presents a novel method for generating anomalies that simulate real attacker actions within the network without the need for a dedicated testbed or installed security controls. To demonstrate that the proposed method is feasible and that the constructed logs behave as one would expect real-world logs to behave, different supervised and unsupervised learning models were compared using different feature subsets, feature construction methods, scaling methods, and aggregation levels. The experimental results show that unsupervised learnin...
Source: Sensors - April 20, 2024 Category: Biotechnology Authors: Adrian Komadina Ivan Kova čević Bruno Štengl Stjepan Gro š Tags: Article Source Type: research
Sensors, Vol. 24, Pages 2637: Learning Ground Displacement Signals Directly from InSAR-Wrapped Interferograms
irichai
Monitoring ground displacements identifies potential geohazard risks early before they cause critical damage. Interferometric synthetic aperture radar (InSAR) is one of the techniques that can monitor these displacements with sub-millimeter accuracy. However, using the InSAR technique is challenging due to the need for high expertise, large data volumes, and other complexities. Accordingly, the development of an automated system to indicate ground displacements directly from the wrapped interferograms and coherence maps could be highly advantageous. Here, we compare different machine learning algorithms to eval...
Source: Sensors - April 20, 2024 Category: Biotechnology Authors: Lama Moualla Alessio Rucci Giampiero Naletto Nantheera Anantrasirichai Tags: Article Source Type: research
