This paper presents a benchmark for peak detection algorithms employed in fiber Bragg grating spectrometric interrogation systems. The accuracy, precision, and computational performance of currently used algorithms and those of a new proposed artificial neural network algorithm are compared. Centroid and gaussian fitting algorithms are shown to have the highest precision but produce systematic errors that depend on the FBG refractive index modulation profile. The proposed neural network displays relatively good precision with reduced systematic errors and improved computational performance when compared to other networks. Additionally, suitable algorithms may be chosen with the general guidelines presented.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3231308 | PMC |
| http://dx.doi.org/10.3390/s110403466 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Prediction of hip fracture by high-resolution peripheral quantitative computed tomography in older Swedish women.
J Bone Miner Res
January 2025
Sahlgrenska Osteoporosis Centre, Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, University of Gothenburg, Gothenburg, Sweden.
The socioeconomic burden of hip fractures, the most severe osteoporotic fracture outcome, is increasing and the current clinical risk assessment lacks sensitivity. This study aimed to develop a method for improved prediction of hip fracture by incorporating measurements of bone microstructure and composition derived from high-resolution peripheral quantitative computed tomography (HR-pQCT). In a prospective cohort study of 3028 community-dwelling women aged 75 to 80, all participants answered questionnaires and underwent baseline examinations of anthropometrics and bone by dual x-ray absorptiometry (DXA) and HR-pQCT.
View Article and Find Full Text PDFAlzheimer's disease image classification based on enhanced residual attention network.
PLoS One
January 2025
School of Emergency Management, Institute of Disaster Prevention, Sanhe, Hebei, China.
With the increasing number of patients with Alzheimer's Disease (AD), the demand for early diagnosis and intervention is becoming increasingly urgent. The traditional detection methods for Alzheimer's disease mainly rely on clinical symptoms, biomarkers, and imaging examinations. However, these methods have limitations in the early detection of Alzheimer's disease, such as strong subjectivity in diagnostic criteria, high detection costs, and high misdiagnosis rates.
View Article and Find Full Text PDFIntelligent classification of computer vulnerabilities and network security management system: Combining memristor neural network and improved TCNN model.
PLoS One
January 2025
School of Information and Communication Engineering, Beijing University of Information Science and Technology, Bei Jing City, China.
To enhance the intelligent classification of computer vulnerabilities and improve the efficiency and accuracy of network security management, this study delves into the application of a comprehensive classification system that integrates the Memristor Neural Network (MNN) and an improved Temporal Convolutional Neural Network (TCNN) in network security management. This system not only focuses on the precise classification of vulnerability data but also emphasizes its core role in strengthening the network security management framework. Firstly, the study designs and implements a neural network model based on memristors.
View Article and Find Full Text PDFDual-hybrid intrusion detection system to detect False Data Injection in smart grids.
PLoS One
January 2025
Department of Electrical Engineering, College of Engineering, Taif University, Taif, Saudi Arabia.
Modernizing power systems into smart grids has introduced numerous benefits, including enhanced efficiency, reliability, and integration of renewable energy sources. However, this advancement has also increased vulnerability to cyber threats, particularly False Data Injection Attacks (FDIAs). Traditional Intrusion Detection Systems (IDS) often fall short in identifying sophisticated FDIAs due to their reliance on predefined rules and signatures.
View Article and Find Full Text PDFDistributed Denial of Services (DDoS) attack detection in SDN using Optimizer-equipped CNN-MLP.
PLoS One
January 2025
Faculty of Informatics and Computing, University Sultan Zainal Abidin, Besut, Terengganu, Malaysia.
Software-Defined Networks (SDN) provides more control and network operation over a network infrastructure as an emerging and revolutionary paradigm in networking. Operating the many network applications and preserving the network services and functions, the SDN controller is regarded as the operating system of the SDN-based network architecture. The SDN has several security problems because of its intricate design, even with all its amazing features.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!