|
|
|
|
|
Ufuk Beyaztas and Hanlin Shang
We propose a functional time series method to obtain accurate multi-step-ahead forecasts for age-specific mortality rates. The dynamic functional principal component analysis method is used to decompose the mortality curves into dynamic functional princi...
ver más
|
|
|
|
|
|
|
|
|
|
|
Weidong Wang, Xiangshui Li, Kai Zhang, Juan Shi, Wentao Shi and Wasiq Ali
To minimize the major decline in direction of arrival (DOA) estimation performance for an acoustic vector sensor array (AVSA) with the coexistence of axial deviation and non-uniform noise, a two-step iterative minimization (TSIM) method is proposed in th...
ver más
|
|
|
|
|
|
|
|
|
|
|
Asra Nusrat, Yaan Li, Chunyan Cheng, Hafeezullah Qazi and Lingji Xu
This paper considers the problem of tracking a uniform moving source using noisy bearing measurements obtained from a distant observer. Observer trajectory optimization plays a central role in this problem, with the objective to minimize the estimation e...
ver más
|
|
|
|
|
|
|
|
|
|
|
Lin Ang, Mi Hong Yim, Jun-Hyeong Do and Sanghun Lee
Hypertension has been a crucial public health challenge among adults. This study aimed to develop a novel method for non-contact prediction of hypertension using facial characteristics such as facial features and facial color. The data of 1099 subjects (...
ver más
|
|
|
|
|
|
|
|
|
|
|
Mirka Mobilia and Antonia Longobardi
Evapotranspiration is the major component of the water cycle, so a correct estimate of this variable is fundamental. The purpose of the present research is to assess the monthly scale accuracy of six meteorological data-based models in the prediction of ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Ang Su, Liang Zhang, Xuefeng Zhang, Shaoqing Zhang, Zhao Liu, Caili Liu and Anmin Zhang
Due to the model and sampling errors of the finite ensemble, the background ensemble spread becomes small and the error covariance is underestimated during filtering for data assimilation. Because of the constraint of computational resources, it is diffi...
ver más
|
|
|
|
|
|
|
|
|
|
|
Minjeong Kim, Daseon Hong and Sungsu Park
This paper presents two amplitude comparison monopulse algorithms and their covariance prediction equation. The proposed algorithms are based on the iterated least-squares estimation method and include the conventional monopulse algorithm as a special ca...
ver más
|
|
|
|
|
|
|
|
|
|
|
Vladimir Zalesny, Valeriy Agoshkov, Victor Shutyaev, Eugene Parmuzin and Natalia Zakharova
The technology is presented for modeling and prediction of marine hydrophysical fields based on the 4D variational data assimilation technique developed at the Marchuk Institute of Numerical Mathematics, Russian Academy of Sciences (INM RAS). The technol...
ver más
|
|
|
|
|
|
|
|
|
|
|
Rasoul Shafipour and Gonzalo Mateos
We develop online graph learning algorithms from streaming network data. Our goal is to track the (possibly) time-varying network topology, and affect memory and computational savings by processing the data on-the-fly as they are acquired. The setup enta...
ver más
|
|
|
|
|
|
|
|
|
|
|
Jean-Michel Roger, Silvia Mas Garcia, Mireille Cambert and Corinne Rondeau-Mouro
This work presents a novel and rapid approach to predict fat content in butter products based on nuclear magnetic resonance longitudinal (T1) relaxation measurements and multi-block chemometric methods. The potential of using simultaneously liquid (T1L) ...
ver más
|
|
|
|
|
|