Results 21 to 30 of about 30,371 (174)

A hybrid crude oil price forecasting framework: Modified ensemble empirical mode decomposition and hidden Markov regression

Energy Science & Engineering
AbstractThe considerable influence of crude oil prices on the international economy has motivated numerous scholars to develop various prediction models. Two difficulties are encountered in forecasting. One is that the time series of crude oil prices show massive jumps in high frequency.
Muyangzi Lin, Haonan Xie, Cai Yang
openaire   +2 more sources

EMD-based filtering (EMDF) of low-frequency noise for speech enhancement [PDF]

, 2012
An Empirical Mode Decomposition based filtering (EMDF) approach is presented as a post-processing stage for speech enhancement. This method is particularly effective in low frequency noise environments.
Chatlani, Navin, Soraghan, John J.
core   +1 more source

Universal Electronic‐Structure Relationship Governing Intrinsic Magnetic Properties in Permanent Magnets

Advanced Functional Materials, EarlyView.
Permanent magnets derive their extraordinary strength from deep, universal electronic‐structure principles that control magnetization, anisotropy, and intrinsic performance. This work uncovers those governing rules, examines modern modeling and AI‐driven discovery methods, identifies critical bottlenecks, and reveals electronic fingerprints shared ...
Prashant Singh
wiley   +1 more source

Tourism forecasting using hybrid modified empirical mode decomposition and neural network [PDF]

, 2017
Due to the dynamically increasing importance of the tourism industry worldwide, new approaches for tourism demand forecasting are constantly being explored especially in this Big Data era.
Samsudin, Ruhaidah, Shabri, Ani, Yahya, Nurhaziyatul Adawiyah   +2 more
core  

Electrocatalytic Reduction of CO2 to Ethylene: Catalyst Design and Synchrotron‐Based Characterizations

Advanced Functional Materials, EarlyView.
This review evaluates strategies for electrochemical CO2 reduction to ethylene, focusing on copper‐based catalyst design and microenvironment modulation to achieve industrial‐grade performance. By leveraging operando synchrotron‐based characterizations, we provide a multiscale understanding of dynamic structural transformations and key reaction ...
Meng Zhang, Zuolong Chen, Yimin A. Wu
wiley   +1 more source

Properties of 42 Solar-type Kepler Targets from the Asteroseismic Modeling Portal

, 2014
Recently the number of main-sequence and subgiant stars exhibiting solar-like oscillations that are resolved into individual mode frequencies has increased dramatically.
Aksoy, C., Bedding, T. R., Benomar, O., Brown, B. P., Buzasi, D. L., Campante, T. L., Chaplin, W. J., Christensen-Dalsgaard, J., Creevey, O. L., Cunha, M. S., Davies, G. R., Deheuvels, S., Derekas, A., Di Mauro, M. P., Doğan, G., Elsworth, Y., García, R. A., Gruberbauer, M., Guenther, D. B., Guzik, J. A., Howe, R., Karoff, C., Lebreton, Y., licki, M., MacGregor, K. B., Mathur, S., Mazumdar, A., Metcalfe, T. S., Molaverdikhani, K., Montalbán, J., Monteiro, M. J. P. F. G., Pricopi, D., Salabert, D., Serenelli, A., Simoniello, R., Ste&șacute, Stello, D., Suran, M. D., Trampedach, R., White, T. R., Xu, H., Yıldız, M., Çelik, Z.   +42 more
core   +3 more sources

Beyond Presumptions: Toward Mechanistic Clarity in Metal‐Free Carbon Catalysts for Electrochemical H2O2 Production via Data Science

Advanced Materials, EarlyView.
Metal‐free carbon catalysts enable the sustainable synthesis of hydrogen peroxide via two‐electron oxygen reduction; however, active site complexity continues to hinder reliable interpretation. This review critiques correlation‐based approaches and highlights the importance of orthogonal experimental designs, standardized catalyst passports ...
Dayu Zhu, Hsi‐wen Wu, Xiao Wang, Jie Zhang   +3 more
wiley   +1 more source

Characterization of Droplet Formation in Ultrasonic Spray Coating: Influence of Ink Formulation Using Phase Doppler Anemometry and Machine Learning

Advanced Materials Technologies, EarlyView.
This study explores how machine learning models, trained on small experimental datasets obtained via Phase Doppler Anemometry (PDA), can accurately predict droplet size (D32) in ultrasonic spray coating (USSC). By capturing the influence of ink complexity (solvent, polymer, nanoparticles), power, and flow rate, the model enables precise droplet control
Pieter Verding, Danny E. P. Vanpoucke, Yunus T. Aksoy, Tobias Corthouts, Maria R. Vetrano, Wim Deferme   +5 more
wiley   +1 more source

Power System Parameters Forecasting Using Hilbert-Huang Transform and Machine Learning [PDF]

, 2014
A novel hybrid data-driven approach is developed for forecasting power system parameters with the goal of increasing the efficiency of short-term forecasting studies for non-stationary time-series. The proposed approach is based on mode decomposition and
Kurbatsky, Victor, Leahy, Paul, Sidorov, Denis, Spiryaev, Vadim, Tomin, Nikita, Zhukov, Alexei   +5 more
core   +2 more sources

Accelerating Luminescence in Nanostructures: Exploring the Physical Limits and Impact of Ultrafast Emission in Nanoscale Materials

Advanced Photonics Research, EarlyView.
This review highlights recent advances in accelerating luminescence in nanostructures through cooperative emission, resonator coupling, and nonlocal light–matter interactions. By unifying concepts such as excitonic superradiance, superfluorescence, and the plasmonic Purcell effect, it reveals physical limits of ultrafast emission and their potential ...
Masaaki Ashida, Koichi Okamoto, Takuya Matsuda, Hajime Ishihara   +3 more
wiley   +1 more source