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Total 283 results found since Jan 2013.

Sensors, Vol. 23, Pages 7792: Spectrum Sensing, Clustering Algorithms, and Energy-Harvesting Technology for Cognitive-Radio-Based Internet-of-Things Networks
iu The aim of this systematic review was to identify the correlations between spectrum sensing, clustering algorithms, and energy-harvesting technology for cognitive-radio-based internet of things (IoT) networks in terms of deep-learning-based, nonorthogonal, multiple-access techniques. The search results and screening procedures were configured with the use of a web-based Shiny app in the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) flow design. AMSTAR, DistillerSR, Eppi-Reviewer, PICO Portal, Rayyan, and ROBIS were the review software systems harnessed for screening and quality assessme...
Source: Sensors - September 11, 2023 Category: Biotechnology Authors: Xavier Fernando George L ăzăroiu Tags: Review Source Type: research

Sensors, Vol. 23, Pages 7766: Anthropogenic Object Localization: Evaluation of Broad-Area High-Resolution Imagery Scans Using Deep Learning in Overhead Imagery
We present algorithms for localizing object detection results, as well as a methodology for the evaluation of the results of broad-area scans. Our research explores the challenges of transitioning these models out of the training–validation laboratory setting and into the real-world application domain. We show a scalable approach to leverage state-of-the-art deep convolutional neural networks for the search, detection, and annotation of objects within large swaths of imagery, with the ultimate goal of providing a methodology for evaluating object detection machine learning models in real-world scenarios.
Source: Sensors - September 8, 2023 Category: Biotechnology Authors: J. Alex Hurt Ilinca Popescu Curt H. Davis Grant J. Scott Tags: Article Source Type: research

Sensors, Vol. 23, Pages 7513: Driving Force Analysis of Natural Wetland in Northeast Plain Based on SSA-XGBoost Model
This study provides a new method of quantitative analysis based on machine learning theory for determining the causes of natural wetland changes; it can be applied to large spatial scale areas, which is essential for a rapid monitoring of natural wetlands’ resources and an accurate decision-making on the ecological environment’s security.
Source: Sensors - August 29, 2023 Category: Biotechnology Authors: Hanlin Liu Nan Lin Honghong Zhang Yongji Liu Chenzhao Bai Duo Sun Jiali Feng Tags: Article Source Type: research

Sensors, Vol. 23, Pages 7370: A White Shark Equilibrium Optimizer with a Hybrid Deep-Learning-Based Cybersecurity Solution for a Smart City Environment
d S. Salama Smart grids (SGs) play a vital role in the smart city environment, which exploits digital technology, communication systems, and automation for effectively managing electricity generation, distribution, and consumption. SGs are a fundamental module of smart cities that purpose to leverage technology and data for enhancing the life quality for citizens and optimize resource consumption. The biggest challenge in dealing with SGs and smart cities is the potential for cyberattacks comprising Distributed Denial of Service (DDoS) attacks. DDoS attacks involve overwhelming a system with a huge volume of traffic, c...
Source: Sensors - August 24, 2023 Category: Biotechnology Authors: Latifah Almuqren Sumayh S. Aljameel Hamed Alqahtani Saud S. Alotaibi Manar Ahmed Hamza Ahmed S. Salama Tags: Article Source Type: research

Sensors, Vol. 23, Pages 7398: Multi-UAV Collaborative Search and Attack Mission Decision-Making in Unknown Environments
ng Fu To address the challenge of coordinated combat involving multiple UAVs in reconnaissance and search attacks, we propose the Multi-UAV Distributed Self-Organizing Cooperative Intelligence Surveillance and Combat (CISCS) strategy. This strategy employs distributed control to overcome issues associated with centralized control and communication difficulties. Additionally, it introduces a time-constrained formation controller to address the problem of unstable multi-UAV formations and lengthy formation times. Furthermore, a multi-task allocation algorithm is designed to tackle the issue of allocating multiple tasks t...
Source: Sensors - August 24, 2023 Category: Biotechnology Authors: Zibin Liang Qing Li Guodong Fu Tags: Article Source Type: research

Sensors, Vol. 23, Pages 7292: Human Activity Recognition via Score Level Fusion of Wi-Fi CSI Signals
In this study, we investigate a score-level fusion structure for human activity recognition using the Wi-Fi channel state information (CSI) signals. The raw CSI signals undergo an important preprocessing stage before being classified using conventional classifiers at the first level. The output scores of two conventional classifiers are then fused via an analytic network that does not require iterative search for learning. Our experimental results show that the fusion provides good generalization and a shorter learning processing time compared with state-of-the-art networks.
Source: Sensors - August 21, 2023 Category: Biotechnology Authors: Gunsik Lim Beomseok Oh Donghyun Kim Kar-Ann Toh Tags: Article Source Type: research

Sensors, Vol. 23, Pages 7264: Unmanned Ariel Vehicle (UAV) Path Planning for Area Segmentation in Intelligent Landmine Detection Systems
This study presents a framework for autonomous UAV-based landmine detection to determine the coverage route for scanning the target area. It is performed by extracting the area of interest using segmentation based on deep learning and then constructing the coverage route plan for the aerial survey. Multiple coverage path patterns are used to identify the ideal UAV route. The effectiveness of the suggested framework is evaluated using several target areas of differing sizes and complexities.
Source: Sensors - August 18, 2023 Category: Biotechnology Authors: Ahmed Barnawi Krishan Kumar Neeraj Kumar Nisha Thakur Bander Alzahrani Amal Almansour Tags: Article Source Type: research

Sensors, Vol. 23, Pages 7135: Dynamic Adaptation Attack Detection Model for a Distributed Multi-Access Edge Computing Smart City
Kamel The internet of things (IoT) technology presents an intelligent way to improve our lives and contributes to many fields such as industry, communications, agriculture, etc. Unfortunately, IoT networks are exposed to many attacks that may destroy the entire network and consume network resources. This paper aims to propose intelligent process automation and an auto-configured intelligent automation detection model (IADM) to detect and prevent malicious network traffic and behaviors/events at distributed multi-access edge computing in an IoT-based smart city. The proposed model consists of two phases. The first phase...
Source: Sensors - August 12, 2023 Category: Biotechnology Authors: Nouf Saeed Alotaibi Hassan Ibrahim Ahmed Samah Osama M. Kamel Tags: Article Source Type: research

Sensors, Vol. 23, Pages 7062: User Pairing for Delay-Limited NOMA-Based Satellite Networks with Deep Reinforcement Learning
Yuli Wang In this paper, we investigate a user pairing problem in power domain non-orthogonal multiple access (NOMA) scheme-aided satellite networks. In the considered scenario, different satellite applications are assumed with various delay quality-of-service (QoS) requirements, and the concept of effective capacity is employed to characterize the effect of delay QoS limitations on achieved performance. Based on this, our objective was to select users to form a NOMA user pair and utilize resource efficiently. To this end, a power allocation coefficient was firstly obtained by ensuring that the achieved capacity of use...
Source: Sensors - August 9, 2023 Category: Biotechnology Authors: Qianfeng Zhang Kang An Xiaojuan Yan Hongxia Xi Yuli Wang Tags: Article Source Type: research

Sensors, Vol. 23, Pages 6898: Adherence and the Diabetic Foot: High Tech Meets High Touch?
We examined the potential benefits of personalized content and clinician support for those receiving mobile health interventions. These findings may help to demonstrate the current and future utility of advanced technologies in improving patient adherence and outcomes, particularly in the context of diabetes management and the link between behavior and complications in diabetes, such as diabetic foot ulcers.
Source: Sensors - August 3, 2023 Category: Biotechnology Authors: Hadia Srass J. Karim Ead David G. Armstrong Tags: Review Source Type: research

Sensors, Vol. 23, Pages 6806: On the Development of a Digital Twin for Underwater UXO Detection Using Magnetometer-Based Data in Application for the Training Set Generation for Machine Learning Models
eczorek Scanning underwater areas using magnetometers in search of unexploded ordnance is a difficult challenge, where machine learning methods can find a significant application. However, this requires the creation of a dataset enabling the training of prediction models. Such a task is difficult and costly due to the limited availability of relevant data. To address this challenge in the article, we propose the use of numerical modeling to solve this task. The conducted experiments allow us to conclude that it is possible to obtain high compliance with the numerical model based on the finite element method with the re...
Source: Sensors - July 30, 2023 Category: Biotechnology Authors: Marcin Blachnik Roman Przy łucki S ławomir Golak Piotr Ściegienka Tadeusz Wieczorek Tags: Article Source Type: research

Sensors, Vol. 23, Pages 6749: IoT System Based on Artificial Intelligence for Hot Spot Detection in Photovoltaic Modules for a Wide Range of Irradiances
ro-Velasco Infrared thermography (IRT) is a technique used to diagnose Photovoltaic (PV) installations to detect sub-optimal conditions. The increase of PV installations in smart cities has generated the search for technology that improves the use of IRT, which requires irradiance conditions to be greater than 700 W/m2, making it impossible to use at times when irradiance goes under that value. This project presents an IoT platform working on artificial intelligence (AI) which automatically detects hot spots in PV modules by analyzing the temperature differentials between modules exposed to irradiances greater than 300...
Source: Sensors - July 28, 2023 Category: Biotechnology Authors: Leonardo Cardinale-Villalobos Efren Jimenez-Delgado Yariel Garc ía-Ramírez Luis Araya-Solano Luis Antonio Sol ís-García Abel M éndez-Porras Jorge Alfaro-Velasco Tags: Article Source Type: research

Sensors, Vol. 23, Pages 6741: Research on Wind Turbine Fault Detection Based on the Fusion of ASL-CatBoost and TtRSA
This study aims to address the limitations of traditional machine learning algorithms in wind turbine fault detection and the imbalance of positive and negative samples in the fault detection dataset. To achieve the real-time detection of wind turbine group faults and to capture wind turbine fault state information, an enhanced ASL-CatBoost algorithm is proposed. Additionally, a crawling animal search algorithm that incorporates the Tent chaotic mapping and t-distribution mutation strategy is introduced to assess the sensitivity of the ASL-CatBoost algorithm toward hyperparameters and the difficulty of manual hyperparamete...
Source: Sensors - July 28, 2023 Category: Biotechnology Authors: Lingchao Kong Hongtao Liang Guozhu Liu Shuo Liu Tags: Article Source Type: research

Sensors, Vol. 23, Pages 6645: Rolling Bearing Fault Diagnosis Based on Support Vector Machine Optimized by Improved Grey Wolf Algorithm
This study targets the low accuracy and efficiency of the support vector machine (SVM) algorithm in rolling bearing fault diagnosis. An improved grey wolf optimizer (IGWO) algorithm was proposed based on deep learning and a swarm intelligence optimization algorithm to optimize the structural parameters of SVM and improve the rolling bearing fault diagnosis. A nonlinear contraction factor update strategy was also proposed. The variable coefficient changes with the shrinkage factor α. Thus, the search ability was balanced at different early and late stages by controlling the dynamic changes of the variable coef...
Source: Sensors - July 24, 2023 Category: Biotechnology Authors: Weijie Shen Maohua Xiao Zhenyu Wang Xinmin Song Tags: Article Source Type: research

Sensors, Vol. 23, Pages 6614: A Safety Warning Model Based on IAHA-SVM for Coal Mine Environment
eng Coal is an important resource that is closely related to people’s lives and plays an irreplaceable role. However, coal mine safety accidents occur from time to time in the process of working underground. Therefore, this paper proposes a coal mine environmental safety early warning model to detect abnormalities and ensure worker safety in a timely manner by assessing the underground climate environment. In this paper, support vector machine (SVM) parameters are optimized using an improved artificial hummingbird algorithm (IAHA), and its safety level is classified by combining various environmental para...
Source: Sensors - July 22, 2023 Category: Biotechnology Authors: Zhen Li Feng Feng Tags: Article Source Type: research