Results 71 to 80 of about 307,816 (329)
This work investigates the Nernst effect in the Kagome magnet ErMn6Sn6 which exhibits both topological and anomalous Nernst effects with the anomalous Nernst coefficient reaching 1.71 µV K⁻¹ at 300 K. This value surpasses that of most canted antiferromagnetic materials, making ErMn6Sn6 a promising candidate for advancing thermoelectric devices based on
Olajumoke Oluwatobiloba Emmanuel+2 more
wiley +1 more source
A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data
In data analysis, recognizing unusual patterns (outliers’ analysis or anomaly detection) plays a crucial role in identifying critical events. Because of its widespread use in many applications, it remains an important and extensive research brand in data
Syahirah Suboh+4 more
doaj +1 more source
Surface anomaly detection on island-based PV panels using edge neural networks
Surface anomaly detection on photovoltaic (PV) panels is crucial for their operation and maintenance, especially in island environments where challenges such as small anomaly sizes and minimal color differences are prevalent. Due to the poor accuracy and
ZHANG Yinxian, ZHANG Zhanyao, ZHANG Xiya
doaj +1 more source
Cross correlation anomaly detection system [PDF]
This invention provides a method for automatically inspecting the surface of an object, such as an integrated circuit chip, whereby the data obtained by the light reflected from the surface, caused by a scanning light beam, is automatically compared with
Micka, E. Z.
core +1 more source
Control of Ferromagnetism of Vanadium Oxide Thin Films by Oxidation States
The nonstoichiometric VOx exhibits a distinct ferromagnetic hysteresis loop and demonstrates a high magnetic susceptibility (χ=dMdH$ = \frac{{dM}}{{dH}}\;$∼10). Micromagnetic simulations show the results of the “partial volume fraction ferromagnetic phase model” for VOx/Co/Pt structure.
Kwonjin Park+9 more
wiley +1 more source
UniFlow: Unified Normalizing Flow for Unsupervised Multi-Class Anomaly Detection
Multi-class anomaly detection is more efficient and less resource-consuming in industrial anomaly detection scenes that involve multiple categories or exhibit large intra-class diversity.
Jianmei Zhong, Yanzhi Song
doaj +1 more source
ASAD: Adaptive Seasonality Anomaly Detection Algorithm under Intricate KPI Profiles
Anomaly detection is the foundation of intelligent operation and maintenance (O&M), and detection objects are evaluated by key performance indicators (KPIs). For almost all computer O&M systems, KPIs are usually the machine-level operating data. Moreover,
Hao Wang+8 more
doaj +1 more source
A lack of standard approaches for testing and reporting the performance of metal halide perovskites and organic semiconductor radiation detectors has resulted in inconsistent interpretation of performance parameters, impeding progress in the field. This Perspective recommends key metrics and experimental details, which are suggested for reporting in ...
Jessie A. Posar+8 more
wiley +1 more source
Lifelong Continual Learning for Anomaly Detection: New Challenges, Perspectives, and Insights
Anomaly detection is of paramount importance in many real-world domains characterized by evolving behavior, such as monitoring cyber-physical systems, human conditions and network traffic.
Kamil Faber+3 more
doaj +1 more source
The orbital‐current‐induced torque is investigated as an efficient method for controlling magnetization direction. By introducing Ti as an orbital current source in Ti/Ta (or Pt)/CoFeB/MgO structures, the switching current is reduced by ∼25% compared to a conventional spin‐orbit torque structure of Ta/CoFeB/MgO.
So y. Shin+3 more
wiley +1 more source