Results 51 to 60 of about 5,207,763 (284)

Biometric systems based on ECG using ensemble empirical mode decomposition and Variational Mode decomposition [PDF]

Journal of Applied Engineering Science, 2020
Electrocardiogram (ECG) based biometric is challenging to be developed with the aim of high-security access. This biometric system is more difficult to falsify, compared to the conventional biometric systems. From previous proposed studies, there is still a gap to improve the accuracy of the system.
Sugondo Hadiyoso, Inung Wijayanto, Achmad Rizal, Suci Aulia   +3 more
openaire   +1 more source

Inverse Design of Nanoparticulate Materials

Advanced Materials, EarlyView.
Inverse design shifts nanomaterial development from empirical trial‐and‐error to predictive model‐driven strategies. It can rely on knowledge‐based, data‐based, or hybrid process and property functions. This perspective article provides a practical framework for applying inverse design based on instructive examples. It discusses which modeling approach
Nabi Etienne Traoré, Annika Mauch, Michelle Berthold, Lukas Pflug, Wolfgang Peukert, Nicolas Vogel   +5 more
wiley   +1 more source

Enhanced hybrid CEEMDAN-GMDH regression model for forewarning sucking pests in cotton crops of Coimbatore, Tamil Nadu

Journal of Agrometeorology
Effective pest management relies on early and accurate forecasting, yet current models struggle to capture regional specific complex relationship between weather conditions and pest incidence.
N. NARANAMMAL, S. R. KRISHNA PRIYA, NAVEENA. K.   +2 more
doaj   +1 more source

Fault Diagnosis of Rotating Machinery Based on Adaptive Stochastic Resonance and AMD-EEMD

Shock and Vibration, 2016
An adaptive stochastic resonance and analytical mode decomposition-ensemble empirical mode decomposition (AMD-EEMD) method is proposed for fault diagnosis of rotating machinery in this paper.
Peiming Shi, Cuijiao Su, Dongying Han
doaj   +1 more source

Remaining Useful Life Prediction Based on the Bayesian Regularized Radial Basis Function Neural Network for an External Gear Pump

IEEE Access, 2020
A remaining useful life (RUL) prediction method for an external gear pump is proposed by Bayesian regularized radial basis function neural network (Trainbr-RBFNN).
Rui Guo, Yongtao Li, Lijiang Zhao, Jingyi Zhao, Dianrong Gao   +4 more
doaj   +1 more source

Sustainable Materials Design With Multi‐Modal Artificial Intelligence

Advanced Science, EarlyView.
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu, Tianshuo Wei, Yan Ge, Bo Peng, Yue Li, Maolin Wang, Peng Wen, Chao Yang, Ye Wei   +8 more
wiley   +1 more source

Soil moisture forecasting by a hybrid machine learning technique: ELM integrated with ensemble empirical mode decomposition

, 2018
Soil moisture (SM) is an essential component of the environmental and the agricultural system. Continuous monitoring and forecasting of soil moisture is a desirable strategy to understand the soil dynamics for proactive planning and decision-making ...
Deo, Ravinesh C., Prasad, Ramendra, Ravinesh C. Deo, Tek Maraseni, Li, Yan, Maraseni, Tek, Ramendra Prasad, Yan Li   +7 more
core   +1 more source

Data‐Driven Modeling of Composition–Processing–Microstructure Relations for Recycled Aluminum Cast Alloys

Advanced Science, EarlyView.
Interpretable machine learning reveals how composition and processing govern the formation and microstructural burden of Fe‐rich intermetallic compounds in recycled Al–Si–Fe–Mn alloys. By separating morphology selection from morphology‐conditioned burden partitioning, this framework shows that identical Fe contents can yield different intermetallic ...
Jaemin Wang, Waleed Mohammed, Dierk Raabe   +2 more
wiley   +1 more source

Arrhythmia ECG Noise Reduction by Ensemble Empirical Mode Decomposition [PDF]

, 2012
[[abstract]]A novel noise filtering algorithm based on ensemble empirical mode decomposition (EEMD) is proposed to remove artifacts in electrocardiogram (ECG) traces.
張剛鳴;Chang, Kang-Ming
core  

Physics‐Constrained Constitutive Learning of Rate‐Limiting Timescales for Efficient Hydrogen‐Based Direct Reduction for Green Steel Making

Advanced Science, EarlyView.
A conversion‐resolved constitutive framework is developed for the hydrogen‐based direct reduction of iron oxide pellets. Effective reaction and transport timescales are inferred directly from measured trajectories and mapped against operating conditions, pellet architecture, and composition. The analysis reveals how late‐stage transport control emerges
Anurag Bajpai, Barak Ratzker, Pasquale Cavaliere, Dierk Raabe   +3 more
wiley   +1 more source