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Page 230 of Energy Research Abstracts Vol. 15, Issue 23 [page]

1990 Energy Research Abstracts  
For Cs-135 we present in a comprehensive sensitivity analysis the impact of non-linear (Freundlich) sorption isotherm on break-through curves.  ...  Out of these flowpaths nuclides diffuse into stagnant pore water of a spatially limited, adjacent zone (matrix diffusion). Sorption on rock surfaces is described by a non-linear isotherm.  ... 

CasGCN: Predicting future cascade growth based on information diffusion graph [article]

Zhixuan Xu, Minghui Qian, Xiaowei Huang, Jie Meng
2020 arXiv   pre-print
End-to-end deep learning models, such as recurrent neural networks, are not suitable to work with graphical inputs directly and cannot handle structural information that is embedded in the cascade graphs  ...  input, followed by the application of the attention mechanism on both the extracted features and the temporal information before conducting cascade size prediction.  ...  On the other hand, linear models are unable to handle the non-linear effects (e.g., time effect) of factors sufficiently.  ... 
arXiv:2009.05152v1 fatcat:oiye3s555re43lw3ij3xvuftre

Neuronal Network Inference and Membrane Potential Model using Multivariate Hawkes Processes [article]

Anna Bonnet
2021 arXiv   pre-print
The first step of the procedure is to select a subnetwork of neurons impacting the central neuron: we use a multivariate Hawkes process to model the spike trains of all neurons and compare two sparse inference  ...  Our approach relies on two types of data: extracellular recordings of multiple spikes trains and intracellular recordings of the membrane potential of a central neuron.  ...  Acknowledgments The authors thank Rune Berg for many advice on the neuronal data and Patricia Reynaud-Bouret for fruitful discussions, particularly on the goodness-of-fit part of this work.  ... 
arXiv:2108.00758v1 fatcat:hecsetwvk5cshkwgem5mon7lqm

MAF-GNN: Multi-adaptive Spatiotemporal-flow Graph Neural Network for Traffic Speed Forecasting [article]

Yaobin Xu, Weitang Liu, Zhongyi Jiang, Zixuan Xu, Tingyun Mao, Lili Chen, Mingwei Zhou
2021 arXiv   pre-print
MAF-GNN achieves better performance than other models on two real-world datasets of public traffic network, METR-LA and PeMS-Bay, demonstrating the effectiveness of the proposed approach.  ...  Approaches based on graph neural networks have been widely used in this task to effectively capture spatial and temporal dependencies of road networks.  ...  With the rapid development in computational power and growth in traffic data volume in recent years, models capable of modeling highly non-linear temporal dependencies are required for traffic forecasting  ... 
arXiv:2108.03594v1 fatcat:k5m6ijgmfrevtkpckmzzv6gmxm

A Comprehensive Model for Real Gas Transport in Shale Formations with Complex Non-planar Fracture Networks

Ruiyue Yang, Zhongwei Huang, Wei Yu, Gensheng Li, Wenxi Ren, Lihua Zuo, Xiaosi Tan, Kamy Sepehrnoori, Shouceng Tian, Mao Sheng
2016 Scientific Reports  
However, it is still challenging to predict the impacts of various gas transport mechanisms on well performance with arbitrary fracture geometry in a computationally efficient manner.  ...  Numerous efforts have been made to model the flow behavior of such fracture networks.  ...  Lashgari (The University of Texas at Austin) for his helpful suggestions and ideas to the work.  ... 
doi:10.1038/srep36673 pmid:27819349 pmcid:PMC5098178 fatcat:7m3xu2f2mbbpdiokb2m4nzjzqi

In vivo MR imaging of brain networks: illusion or revolution?

Ewald Moser, Jean-Philippe Ranjeva
2010 Magnetic Resonance Materials in Physics, Biology and Medicine  
Finer traffic routes may also have an important impact on some functional networks.  ...  However, we are still at an early stage in brain network analysis and most of the current techniques do not account for non-linear dynamics of brain functions.  ... 
doi:10.1007/s10334-010-0231-x pmid:21136136 fatcat:eoujtz6nyrcmriokqznafq24fu

Optimizing Graph Structure for Targeted Diffusion [article]

Sixie Yu, Leonardo Torres, Scott Alfeld, Tina Eliassi-Rad, Yevgeniy Vorobeychik
2021 arXiv   pre-print
However, in many applications, such as cybersecurity, an attacker may want to attack a targeted subgraph of a network, while limiting the impact on the rest of the network in order to remain undetected  ...  The problem of diffusion control on networks has been extensively studied, with applications ranging from marketing to controlling infectious disease.  ...  The authors would like to thank the anonymous reviewers and Chloe Wohlgemuth for their helpful comments.  ... 
arXiv:2008.05589v4 fatcat:fmbjr4fwhbgrteihrizpnaguhy

Grey-Box Modeling for Photo-Voltaic Power Systems Using Dynamic Neural-Networks

Naji Al-Messabi, Cindy Goh, Yun Li
2017 2017 Ninth Annual IEEE Green Technologies Conference (GreenTech)  
The two directions of modeling pose a number of drawbacks.  ...  To benefit from both worlds, this paper proposes a novel method where clear-box model is extended to a grey-box model by modeling uncertainities using focused time-delay neural network models.  ...  The intermittent and non-linear characteristics of PV data is due to an interplay of various factors such as the variability in sunrise and the amount of sunshine, sudden changes in atmospheric conditions  ... 
doi:10.1109/greentech.2017.45 fatcat:lf24fkxxxvhwbdhlivffgrcqpi

Development and optimization of the IPM MM5 GPS slant path 4DVAR system

Florian Zus, Matthias Grzeschik, Hans-Stefan Bauer, Volker Wulfmeyer, Galina Dick, Michael Bender
2008 Meteorologische Zeitschrift  
A set of modifications to the existing non linear, tangent linear and adjoint model is presented.  ...  We demonstrate that the model minus observation statistics of STD data crucially depends on the convection scheme and the implementation of horizontal diffusion.  ...  Acknowledgments We appreciate the access to the ECMWF analysis and the radar data provided by DWD. The author wants to thank T. SCHWITALLA for helpful tips regarding the graphics.  ... 
doi:10.1127/0941-2948/2008/0339 fatcat:zuwy4qtpnnct3kekjf2tm4zqp4

Multiple Kernel Learning Model for Relating Structural and Functional Connectivity in the Brain

Sriniwas Govinda Surampudi, Shruti Naik, Raju Bapi Surampudi, Viktor K. Jirsa, Avinash Sharma, Dipanjan Roy
2018 Scientific Reports  
This linear diffusion model considers brain dynamics, the diffusing quantity, firing rate of the neuronal population, undergoing random walk on the SC graph.  ...  On the other hand, static FC enables investigation of the analytical properties of network behavior 8 .  ...  Data availability statement. The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.  ... 
doi:10.1038/s41598-018-21456-0 pmid:29459634 pmcid:PMC5818607 fatcat:2rnipnrbuzawtbvspb2zedvg7u

Machine Learning Based PV Power Generation Forecasting in Alice Springs

Khizir Mahmud, Sami Azam, Asif Karim, Sm Zobaed, Bharanidharan Shanmugam, Deepika Mathur
2021 IEEE Access  
The impact of data normalization on forecasting performance is also analyzed using multiple performance metrics.  ...  The study has chosen Alice Springs, one of the geographically solar energy-rich areas in Australia, and considered various environmental parameters.  ...  Random forest regression performs well on diversified problems with the potentiality of handling non-linear relationships.  ... 
doi:10.1109/access.2021.3066494 fatcat:ezpuw3iobjejdfv76vz4rzmzhi

Page 515 of Energy Research Abstracts Vol. 19, Issue 6 [page]

1994 Energy Research Abstracts  
Under some assumptions on different ability of the probability measure functions, simple algo- rithms to solve some PAC learning problems are proposed based on networks of non-polynomial units (e.g. artificial  ...  The code handles binary, but not Knudsen, diffusion in the gas phase and capillary and phase adsorption effects for the liquid phase.  ... 

A roadmap of brain recovery in a mouse model of concussion: insights from neuroimaging

Xuan Vinh To, Fatima A. Nasrallah
2021 Acta Neuropathologica Communications  
Our results demonstrate the capabilities of advanced MRI in detecting the effects of a single concussive impact in the brain, and highlight a mismatch in the onset and temporal evolution of behaviour,  ...  These results have significant translational impact in developing methods for the detection of human concussion and the time course of brain recovery.  ...  We acknowledge the support from the Queensland NMR Network and the National Imaging Facility (a National Collaborative Research Infrastructure Strategy capability) for the operation of 9.4T MRI and utilisation  ... 
doi:10.1186/s40478-020-01098-y pmid:33407949 pmcid:PMC7789702 fatcat:bhkt6y4afbazpiazxtz3a76wvi

The Transient Flow Analysis of Fluid in a Fractal, Double-Porosity Reservoir

Yuedong Yao, Yu-Shu Wu, Ronglei Zhang
2012 Transport in Porous Media  
Because of the small compressibility of formation fluid, the quadratic term of pressure gradient is always ignored to linearize the non-linear diffusion equation.  ...  This may result in significant errors in model prediction, especially at large time scale. In order to solve this problem, it may be necessary to keep the quadratic term in the non-linear equations.  ...  The authors would also like to acknowledge the support from the Energy Modeling Group (EMG) at Colorado School of Mines.  ... 
doi:10.1007/s11242-012-9995-y fatcat:qkgmgojm3ncadaw64cldw3ydmu

Forecasting the success of telecommunication services in the presence of network effects

Detlef Schoder
2000 Information Economics and Policy  
This paper reviews the role played by network effects for the adoption of telecommunication services, which lead to diffusion phenomena including critical mass, lock-in, path dependency, and inefficiency  ...  To improve forecasting practices, we propose the master equation approach as an appropriate modelling technique incorporating network effects.  ...  Rogers at the workshop ''Diffusion and Innovation'', 1994, Bonn, and at the ''Scientific Symposium 1996'' at Schloß Thurnau, Germany, and detailed comments by David Allen, also by two anonymous reviewers  ... 
doi:10.1016/s0167-6245(00)00006-8 fatcat:vypk23ovnzbzxk4jmc4klvhn2u
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