Research on the Combined Detection of Magnetic Anomaly and Shaft‐Rate Magnetic Field Signals
IET Radar, Sonar & NavigationDue to the stable propagation of magnetic signals in ocean and air, magnetic detection technology has become an effective means for nonacoustic detection.
Honglei Wang +2 more
doaj +1 more source
Advanced Engineering Materials, EarlyView.Disordered (Fe50Co50)1−xPtx thin films exhibit a pronounced anomalous Nernst effect (ANE) with a strong composition dependence on both rigid and flexible substrates. The transverse thermoelectric response peaks near 22.5 at.% Pt, accompanied by enhanced αxy/σxy scaling, thermal transport, and ANE sensitivity.
Mojtaba Mohammadi +2 more
wiley +1 more source
Joint Sub-component Level Segmentation and Classification for Anomaly Detection within Dual-Energy X-Ray Security Imagery [PDF]
, 2022 Neelanjan Bhowmik, Toby P. Breckon
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Collaborative Anomaly Detection
, 2022 In recommendation systems, items are likely to be exposed to various users and we would like to learn about the familiarity of a new user with an existing item. This can be formulated as an anomaly detection (AD) problem distinguishing between "common users" (nominal) and "fresh users" (anomalous). Considering the sheer volume of items and the sparsity
Bai, Ke +5 more
openaire +2 more sources
A Knowledge‐Based Approach for Understanding and Managing Additive Manufacturing Data
Advanced Engineering Materials, EarlyView.Additive manufacturing processes generate a large amount of data. Effectively managing, understanding, and retrieving information from this data remains a major challenge. Therefore, we propose an ontology‐based approach to integrate heterogeneous data, enable semantic queries, and support decision‐making.
Mina Abd Nikooie Pour +5 more
wiley +1 more source
Enhancing Time Series Anomaly Detection: A Knowledge Distillation Approach with Image Transformation
SensorsAnomaly detection is critical in safety-sensitive fields, but faces challenges from scarce abnormal data and costly expert labeling. Time series anomaly detection is relatively challenging due to its reliance on sequential data, which imposes high ...
Haiwoong Park, Hyeryung Jang
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SNAP Framework: Linked Prediction Based Anomaly Prevention With Suspicious Nodes on Social Network Graph [PDF]
Journal of Universal Computer ScienceIn previous studies, the focus has predominantly been on anomaly detection, with minimal attention given to anomaly prevention. However, anomaly prevention holds greater significance than anomaly detection.
Vahide Nida Kılıç, Esra Saraç Eşsiz
doaj +3 more sources
Enhancing Security in Cloud Computing with Anomaly Detection Using Machine Learning
, 2023 Mayank Namdev, Jayasundar S., Muhammad Babur, Deepak A. Vidhate, Santosh Yerasuri
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Multimodal Data‐Driven Microstructure Characterization
Advanced Engineering Materials, EarlyView.A self‐consistent autonomous workflow for EBSP‐based microstructure segmentation by integrating PCA, GMM clustering, and cNMF with information‐theoretic parameter selection, requiring no user input. An optimal ROI size related to characteristic grain size is identified.
Qi Zhang +4 more
wiley +1 more source
A Lightweight Procedural Layer for Hybrid Experimental–Computational Workflows in Materials Science
Advanced Engineering Materials, EarlyView.We unveil a prototype hybrid‐workflow framework that fuses automatedcomputation with hands‐on experiments. Built atop pyiron, a lightweight, parameterized layer translates procedure descriptions into executable manual steps, syncing instrument settings, human interventions, and data capture in real‐time today.
Steffen Brinckmann +8 more
wiley +1 more source