Results 71 to 80 of about 352,249 (316)

Machine learning for Internet of things anomaly detection under low-quality data

International Journal of Distributed Sensor Networks, 2022
With the popularization of Internet of things, its network security has aroused widespread concern. Anomaly detection is one of the important technologies to protect network security.
Shangbin Han, Qianhong Wu, Yang Yang
doaj   +1 more source

Recurrent Hypothermia and Autonomic Dysfunction Secondary to Shapiro Syndrome

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT A 44‐year‐old man presented with recurrent hypothermia, diaphoresis and hypertension. Extensive investigation for infectious, inflammatory, metabolic and endocrine aetiologies was negative. MR scan of the brain demonstrated no lesions but revealed callosal dysgenesis, consistent with Shapiro syndrome.
Naveen Kumar, Jeremy Johnson, Susanne Watkins, Eoin Mulroy   +3 more
wiley   +1 more source

Hyperspectral anomaly detection: a performance comparison of existing techniques

International Journal of Digital Earth, 2022
Anomaly detection in Hyperspectral Imagery (HSI) has received considerable attention because of its potential application in several areas. Numerous anomaly detection algorithms for HSI have been proposed in the literature; however, due to the use of ...
Noman Raza Shah, Abdur Rahman M. Maud, Farrukh Aziz Bhatti, Muhammad Khizer Ali, Khurram Khurshid, Moazam Maqsood, Muhammad Amin   +6 more
doaj   +1 more source

Building a Framework for Sexual and Reproductive Health Care in the Rheumatology Context: Content and Approaches

Arthritis Care &Research, EarlyView.
People with systemic autoimmune and rheumatic diseases (SARDs) are at higher risk than the general population of experiencing adverse pregnancy and perinatal outcomes such as preeclampsia, intrauterine growth restriction, and maternal and/or fetal death.
Mehret Birru Talabi, Sonya Borrero
wiley   +1 more source

Hyperspectral Anomaly Detection Based on Intrinsic Image Decomposition and Background Subtraction

IEEE Access
Hyperspectral anomaly detection is a detection of abnormal targets in a region based on spectral and spatial information under the premise of no prior knowledge of the target, which is a very important research topic in the field of remote sensing.
Jiao Jiao, Longlong Xiao, Chonglei Wang
doaj   +1 more source

An Adaptive Human Pilot Model With Reaction Time Delay for Enhanced Adaptive Control in Piloted Systems

International Journal of Adaptive Control and Signal Processing, EarlyView.
This work introduces an adaptive human pilot model that captures pilot time‐delay effects in adaptive control systems. The model enables the prediction of pilot–controller interactions, facilitating safer integration and improved design of adaptive controllers for piloted applications.
Abdullah Habboush, Yildiray Yildiz
wiley   +1 more source

Characterization of Defect Distribution in an Additively Manufactured AlSi10Mg as a Function of Processing Parameters and Correlations with Extreme Value Statistics

Advanced Engineering Materials, EarlyView.
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt, Varma Kvvssn, Hossein Laieghi, Zia Uddin, Peyman Ansari, E. Kıvanç Sadak, Can Barış Toprak, Hüseyin Kızıl, Enrico Salvati   +8 more
wiley   +1 more source

JointNet: Multitask Learning Framework for Denoising and Detecting Anomalies in Hyperspectral Remote Sensing

Remote Sensing
One of the significant challenges with traditional single-task learning-based anomaly detection using noisy hyperspectral images (HSIs) is the loss of anomaly targets during denoising, especially when the noise and anomaly targets are similar. This issue
Yingzhao Shao, Shuhan Li, Pengfei Yang, Fei Cheng, Yueli Ding, Jianguo Sun   +5 more
doaj   +1 more source

Elinvar Materials: Recent Progress and Challenges

Advanced Engineering Materials, EarlyView.
Elinvar materials, exhibiting temperature‐invariant elastic modulus, are critical for precision instruments and emerging technologies. This article reviews recent progress in the field, with a focus on the anomalous thermoelastic behavior observed in key material systems.
Wenjie Li, Yang Ren
wiley   +1 more source

Prediction of Surface Topography Parameters in Direct Laser Interference Patterning of Stainless Steel Using Infrared Monitoring and Convolutional Neural Networks

Advanced Engineering Materials, EarlyView.
This study presents an infrared monitoring approach for direct laser interference patterning (DLIP) combined with a convolutional neural network (CNN). Thermal emission data captured during structuring are used to predict surface topography parameters.
Lukas Olawsky, Marcelo Sallese, Leander Kläber, Clemens Kuhn, Keming Du, Andrés Fabián Lasagni   +5 more
wiley   +1 more source