scholarly journals Multifocal Electroretinography in the Presence of Temporal and Spatial Correlations and Eye Movements

Vision ◽  
2016 ◽  
Vol 1 (1) ◽  
pp. 3 ◽  
Author(s):  
Alan Saul ◽  
Amber Still
Keyword(s):  
Eye Movements ◽  
Multifocal Electroretinography ◽  
Spatial Correlations ◽  
Temporal And Spatial

scholarly journals Integration Capability Evaluation of Wind and Photovoltaic Generation in Power Systems Based on Temporal and Spatial Correlations

Energies ◽  
2019 ◽  
Vol 12 (1) ◽  
pp. 171 ◽  
Author(s):  
Hua Zhou ◽  
Huahua Wu ◽  
Chengjin Ye ◽  
Shijie Xiao ◽  
Jun Zhang ◽  
...  
Keyword(s):  
Power Generation ◽  
Renewable Energy ◽  
Power Systems ◽  
Wind Power ◽  
Energy Generation ◽  
Copula Model ◽  
Spatial Correlations ◽  
Temporal And Spatial ◽  
Renewable Energy Generation ◽  
Pv Power Generation

With the rapid growth of renewable energy generation, it has become essential to give a comprehensive evaluation of renewable energy integration capability in power systems to reduce renewable generation curtailment. Existing research has not considered the correlations between wind power and photovoltaic (PV) power. In this paper, temporal and spatial correlations among different renewable generations are utilized to evaluate the integration capability of power systems based on the copula model. Firstly, the temporal and spatial correlation between wind and PV power generation is analyzed. Secondly, the temporal and spatial distribution model of both wind and PV power generation output is formulated based on the copula model. Thirdly, aggregated generation output scenarios of wind and PV power are generated. Fourthly, wind and PV power scenarios are utilized in an optimal power flow calculation model of power systems. Lastly, the integration capacity of wind power and PV power is shown to be able to be evaluated by satisfying the reliability of power system operation. Simulation results of a modified IEEE RTS-24 bus system indicate that the integration capability of renewable energy generation in power systems can be comprehensively evaluated based on the temporal and spatial correlations of renewable energy generation.

scholarly journals Embracing the uncertainty: the evolution of SOFI into a diverse family of fluctuation-based super-resolution microscopy methods

2021 ◽  
Author(s):  
Monika Pawlowska ◽  
Ron Tenne ◽  
Bohnishikha Ghosh ◽  
Adrian Makowski ◽  
Radek Lapkiewicz
Keyword(s):  
3D Imaging ◽  
Deep Neural Networks ◽  
Fluorescent Proteins ◽  
Super Resolution ◽  
Significant Progress ◽  
Spatial Correlations ◽  
Order Of Magnitude ◽  
Temporal And Spatial ◽  
Microscopy Techniques ◽  
Super Resolution Microscopy

Abstract Super-resolution microscopy techniques have pushed the limits of resolution in optical imaging by more than an order of magnitude. However, these methods often require long acquisition times as well as complex setups and sample preparation protocols. Super-resolution Optical Fluctuation Imaging (SOFI) emerged over ten years ago as an approach that exploits temporal and spatial correlations within the acquired images to obtain increased resolution with less strict requirements. This review follows the progress of SOFI from its first demonstration to the development of a branch of methods that treat fluctuations as a source of contrast, rather than noise. Among others, we highlight the implementation of SOFI with standard fluorescent proteins as well as the microscope modification that facilitate 3D imaging and the application of modern cameras. Going beyond the classical framework of SOFI, we explore different innovative concepts from deep neural networks all the way to a quantum analogue of SOFI, antibunching microscopy. While SOFI has not reached the same level of ubiquity as other super-resolution methods, our overview finds significant progress and substantial potential for the concept of leveraging fluorescence fluctuations to obtain super-resolved images.

Dealing with temporal and spatial correlations to classify outliers in geophysical data streams

2014 ◽  
Vol 285 ◽  
pp. 162-180 ◽  
Author(s):  
Annalisa Appice ◽  
Pietro Guccione ◽  
Donato Malerba ◽  
Anna Ciampi
Keyword(s):  
Data Streams ◽  
Geophysical Data ◽  
Spatial Correlations ◽  
Temporal And Spatial

Neural Coding by Temporal and Spatial Correlations

2003 ◽  
pp. 673-680
Author(s):  
Allan Kardec Barros ◽  
Andrzej Cichocki ◽  
Noboru Ohnishi
Keyword(s):  
Neural Coding ◽  
Spatial Correlations ◽  
Temporal And Spatial

Detecting temporal and spatial correlations in pseudoperiodic time series

2007 ◽  
Vol 75 (1) ◽  
Author(s):  
Jie Zhang ◽  
Xiaodong Luo ◽  
Tomomichi Nakamura ◽  
Junfeng Sun ◽  
Michael Small
Keyword(s):  
Time Series ◽  
Spatial Correlations ◽  
Temporal And Spatial

Structure of Round, Fully Developed, Buoyant Turbulent Plumes

1994 ◽  
Vol 116 (2) ◽  
pp. 409-417 ◽  
Author(s):  
Z. Dai ◽  
L.-K. Tseng ◽  
G. M. Faeth
Keyword(s):  
Carbon Dioxide ◽  
Experimental Study ◽  
Sulfur Hexafluoride ◽  
Mixture Fraction ◽  
Power Spectra ◽  
Probability Density Functions ◽  
Density Functions ◽  
Spatial Correlations ◽  
Integral Scales ◽  
Temporal And Spatial

An experimental study of the structure of round buoyant turbulent plumes was carried out, emphasizing conditions in the fully developed (self-preserving) portion of the flow. Plume conditions were simulated using dense gas sources (carbon) dioxide and sulfur hexafluoride) in a still air environment. Mean and fluctuating mixture fraction properties were measured using single-and two-point laser-induced iodine fluorescence. The present measurements extended farther from the source (up to 151 source diameters) than most earlier measurements (up to 62 source diameters) and indicated that self-preserving turbulent plumes are narrower, with larger mean and fluctuating mixture fractions (when appropriately scaled) near the axis, than previously thought. Other mixture fraction measurements reported include probability density functions, temporal power spectra, radial spatial correlations and temporal and spatial integral scales.

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