Results 81 to 90 of about 26,074 (306)
Advanced Materials, EarlyView.A deep learning inverse‐design framework is established to create versatile reconfigurable terahertz metadevices. By synergizing deep learning with phase‐change materials, this approach enables on‐demand customization of multidimensional electromagnetic responses.
Yisheng Dong +11 more
wiley +1 more source
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 +5 more
wiley +1 more source
The Relationship between the Beveridge-Nelson Decomposition andUnobserved Component Models with Correlated Shocks [PDF]
Many researchers believe that the Beveridge-Nelson decomposition leads to permanent and transitory components whose shocks are perfectly negatively correlated. Indeed, some even consider it to be a property of the decomposition.
Eric Zivot, Drew Creal, Kum Hwa Oh
core
An analysis of land prices: A structural time‐series approach
International Journal of Strategic Property Management, 2005 This paper analyses spatio‐temporal variation of land prices in two single localities by means of structural time series modelling formalism that combines the flexibility of a time series model with that of the interpretation of a regression analysis ...
Marko Hannonen
doaj +1 more source
Do Unobserved Components Models Forecast Inflation in Russia? [PDF]
SSRN Electronic Journal, 2013 I apply the model with unobserved components and stochastic volatility (UC-SV) to forecast the Russian consumer price index. I extend the model which was previously suggested as a model for inflation forecasting in the USA to take into account a possible difference in model parameters and seasonal factor.
openaire +1 more source
Recent Advances of Slip Sensors for Smart Robotics
Advanced Materials Technologies, EarlyView.This review summarizes recent progress in robotic slip sensors across mechanical, electrical, thermal, optical, magnetic, and acoustic mechanisms, offering a comprehensive reference for the selection of slip sensors in robotic applications. In addition, current challenges and emerging trends are identified to advance the development of robust, adaptive,
Xingyu Zhang +8 more
wiley +1 more source
Prediction intervals in conditionally heteroscedastic time series with stochastic components. [PDF]
Differencing is a very popular stationary transformation for series with stochastic trends. Moreover, when the differenced series is heteroscedastic, authors commonly model it using an ARMA-GARCH model. The corresponding ARIMA-GARCH model is then used to
Ruiz, Esther +2 more
core
State Space Modeling Using SAS
Journal of Statistical Software, 2011 This article provides a brief introduction to the state space modeling capabilities in SAS, a well-known statistical software system. SAS provides state space modeling in a few different settings.
Rajesh Selukar
doaj
At Home Detection of Ovarian Health Biomarker in Menstruation Blood
Advanced Materials Technologies, EarlyView.A lateral flow assay enables the detection of anti‐Müllerian hormone directly in unprocessed menstrual blood using silica‐gold nanoshells and smartphone‐assisted machine learning analysis. The platform supports decentralized, user‐operated testing in wearable and dipstick formats, highlighting the potential of menstrual blood as a non‐invasive matrix ...
Lucas Dosnon +3 more
wiley +1 more source
Data‐Efficient Electromagnetic Surrogate Solver Through Dissipative Relaxation Transfer Learning
Advanced Optical Materials, EarlyView.Dissipative relaxation transfer learning (DIRTL) enables data‐efficient training of electromagnetic surrogate solvers by pretraining data generated with artificial material loss before fine‐tuning on target lossless data. The framework suppresses resonant outlier effects during early training, allowing effective adaptation to high‐amplitude resonances ...
Sunghyun Nam +2 more
wiley +1 more source