A Novel Edge Detection Method for Multi-Temporal PolSAR Images Based on the SIRV Model and a SDAN-Based 3D Gaussian-like Kernel by Xiaolong Zheng, Dongdong Guan, Bangjie Li, Zhengsheng Chen, Lefei Pan

“…The spherically invariant random vector (SIRV) and span-driven adaptive neighborhood (SDAN) improve the estimation accuracy of the average covariance matrix (ACM) in terms of data representation and spatial support, respectively. …”
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Highly efficient hypothesis testing methods for regression-type tests with correlated observations and heterogeneous variance structure by Yun Zhang, Gautam Bandyopadhyay, David J. Topham, Ann R. Falsey, Xing Qiu

“…The PB-transformed data will have a scalar variance-covariance matrix. 2. The original H-T problem will be reduced to an equivalent one-sample H-T problem. …”
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Tailored graphical lasso for data integration in gene network reconstruction by Camilla Lingjærde, Tonje G. Lien, Ørnulf Borgan, Helga Bergholtz, Ingrid K. Glad

“…Assuming a Gaussian graphical model, a gene association network may be estimated from multiomic data based on the non-zero entries of the inverse covariance matrix. Inferring such biological networks is challenging because of the high dimensionality of the problem, making traditional estimators unsuitable. …”
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Optimizing the Sowing Date to Improve Water Management and Wheat Yield in a Large Irrigation Scheme, through a Remote Sensing and an Evolution Strategy-Based Approach by Salwa Belaqziz, Saïd Khabba, Mohamed Hakim Kharrou, El Houssaine Bouras, Salah Er-Raki, Abdelghani Chehbouni

“…For that, a scenario-based simulation approach based on the covariance matrix adaptation–evolution strategy (CMA-ES) was proposed to optimize both the spatiotemporal distribution of sowing dates and the irrigation schedules, and then evaluate wheat crop using the 2011–2012 growing season dataset. …”
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Assimilating aerosol optical properties related to size and absorption from POLDER/PARASOL with an ensemble data assimilation system by A. Tsikerdekis, A. Tsikerdekis, N. A. J. Schutgens, O. P. Hasekamp

“…Additionally, sensitivity experiments reveal the benefits of assimilating AE over AOD at a second wavelength or SSA over AAOD, possibly due to a simpler observation covariance matrix in the present data assimilation framework. …”
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Design of Generalized Sinusoidal Frequency Modulated Pulse Train Waveform to Improve Tracking Performance of High Duty Cycle Sonar Systems by Geunhwan Kim, Seokjin Lee, Kyungsik Yoon, Changsoo Ryu, Minseuk Park, Youngmin Choo

“…In the framework, the detection probability and measurement noise covariance matrix of the Kalman filter are calculated based on the designed GSFM pulse train waveform. …”
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MixMobileNet: A Mixed Mobile Network for Edge Vision Applications by Yanju Meng, Peng Wu, Jian Feng, Xiaoming Zhang

“…For <i>global</i>, we propose the global-feature aggregation encoder (GFAE), which employs a pooling strategy and computes the covariance matrix between channels instead of the spatial dimensions, changing the computational complexity from quadratic to linear, and this accelerates the inference of the model. …”
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Scalable phylogenetic Gaussian process models improve the detectability of environmental signals on local extinctions for many Red List species by Misako Matsuba, Keita Fukasawa, Satoshi Aoki, Munemitsu Akasaka, Fumiko Ishihama

“…However, modelling many species with the Gaussian process (GP), which underlies the evolutionary process of phylogenetic random effects, remains a challenge owing to the computational burden in estimating the large variance–covariance matrix. Here, we applied a phylogenetic generalised mixed model with random slopes and random intercepts to 1010 endangered vascular plant taxa in Japan following phylogenetic GPs implemented by nearest neighbour GP (NNGP) approximation. …”
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Coastal observing and forecasting system for the German Bight &ndash; estimates of hydrophysical states by W. Petersen, J. Seemann, S. Grayek, J. Staneva, J. Schulz-Stellenfleth, E. V. Stanev

“…Assimilation of FerryBox data based on an optimal interpolation approach using a Kalman filter with a stationary background covariance matrix derived from a preliminary model run which was validated against remote sensing and in situ data demonstrated the capabilities of the pre-operational system. …”
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Remdesivir Strongly Binds to RNA-Dependent RNA Polymerase, Membrane Protein, and Main Protease of SARS-CoV-2: Indication From Molecular Modeling and Simulations by Faez Iqbal Khan, Tongzhou Kang, Haider Ali, Dakun Lai

“…Furthermore, the eigenvalues and the trace of the covariance matrix were found to be low in case of Mprotease–remdesivir, Mprotein–remdesivir, and RDRP–remdesivir. …”
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Diffuse Large B-cell Lymphoma of the Uterus: A Propensity Score Matched Analysis of the Texas Cancer Registry by A. Ensor, J. Ensor, K. Anand

“…The survival difference between the two cohorts was investigated using a Cox proportional hazards model based on the robust sandwich estimate for the covariance matrix to account for the dependent nature of the matching process. …”
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Space Target Tracking with the HRRP Characteristic-Aided Filter via Space-Based Radar by Shuyu Zheng, Libing Jiang, Qingwei Yang, Yingjian Zhao, Zhuang Wang

“…Additionally, a modified spatial spectrum method with a novel covariance matrix is designed to improve the scattering parameter estimation accuracy. …”
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A comparison of optimisation algorithms for high-dimensional particle and astrophysics applications by The DarkMachines High Dimensional Sampling Group, Csaba Balázs, Melissa van Beekveld, Sascha Caron, Barry M. Dillon, Ben Farmer, Andrew Fowlie, Eduardo C. Garrido-Merchán, Will Handley, Luc Hendriks, Guðlaugur Jóhannesson, Adam Leinweber, Judita Mamužić, Gregory D. Martinez, Sydney Otten, Roberto Ruiz de Austri, Pat Scott, Zachary Searle, Bob Stienen, Joaquin Vanschoren, Martin White

“…Although the best algorithm to use depends on the function being investigated, we are able to present general conclusions about the relative merits of random sampling, Differential Evolution, Particle Swarm Optimisation, the Covariance Matrix Adaptation Evolution Strategy, Bayesian Optimisation, Grey Wolf Optimisation, and the PyGMO Artificial Bee Colony, Gaussian Particle Filter and Adaptive Memory Programming for Global Optimisation algorithms.…”
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Repeatability and genotypic stability in intraspecific hybrids of Paspalum notatum Flügge by Roberto Luis Weiler, Diógenes Cecchin Silveira, André Pich Brunes, Carine Simioni, Annamaria Mills, Júlia Longhi, Marcos Vinicius Schiavoni Corrêa, Carla Nauderer, Arthur Valentini, Weliton Menezes dos Santos, Miguel Dall'Agnol

“…The repeatability coefficients estimates obtained for the eight characteristics evaluated with the ANOVA I and II methods were almost always lower than those obtained by PCA and structural analysis methods. Based on the covariance matrix, the principal component method generated higher estimates than those produced by ANOVA or structural analysis. …”
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Calibrating a global three-dimensional biogeochemical ocean model (MOPS-1.0) by I. Kriest, V. Sauerland, S. Khatiwala, A. Srivastav, A. Oschlies

“…The framework combines an offline approach for transport of biogeochemical tracers with an estimation of distribution algorithm (Covariance Matrix Adaption Evolution Strategy, CMA-ES). …”
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Potential risk factors associated with human encephalitis: application of canonical correlation analysis by Crowcroft Natasha S, Meaney Christopher, Hamid Jemila S, Granerod Julia, Beyene Joseph

“…Data consists of 208 confirmed cases of encephalitis from a prospective multicenter study conducted in the United Kingdom. We used a covariance matrix based on Gini's measure of similarity and used permutation based approaches to test significance of canonical variates.…”
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Machine Learning Methods for Inferring the Number of UAV Emitters via Massive MIMO Receive Array by Yifan Li, Feng Shu, Jinsong Hu, Shihao Yan, Haiwei Song, Weiqiang Zhu, Da Tian, Yaoliang Song, Jiangzhou Wang

“…Therefore, we perform feature extraction on the the eigenvalue sequence of a sample covariance matrix to construct a feature vector and innovatively propose a multi-layer neural network (ML-NN). …”
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Development and validation of uncertainty neutron transport calculations at an industrial scale by Gaillet Julien, Bonaccorsi Thomas, Noguere Gilles, Truchet Guillaume

“…For the purpose of the tests, dedicated covariance matrix have been created by condensation from 49 to 4 groups of the COMAC matrix. …”
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Non-isotropic noise correlation in PET data reconstructed by FBP but not by OSEM demonstrated using auto-correlation function by Schneider Harald, Lubberink Mark, Razifar Pasha, Långström Bengt, Bengtsson Ewert, Bergström Mats

“…In synthetic images we compared the ACF results with those from covariance matrix. The results were illustrated as 1D profiles and also visualized as 2D ACF images.…”
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Signal Subspace Reconstruction for DOA Detection Using Quantum-Behaved Particle Swarm Optimization by Rui Zhang, Kaijie Xu, Yinghui Quan, Shengqi Zhu, Mengdao Xing

“…In the developed scheme, according to received data, a noise subspace is established through performing an eigen-decomposition operation on a sampling covariance matrix. Then, a collection of angles randomly selected from the observation space are used to build a potential signal subspace on the basis of the steering matrix of the array. …”
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