Efficient Simulations for Contamination of Groundwater Aquifers under Uncerta...Alexander Litvinenko
1. Solved time-dependent density driven flow problem with uncertain porosity and permeability in 2D and 3D
2. Computed propagation of uncertainties in porosity into the mass fraction.
3. Computed the mean, variance, exceedance probabilities, quantiles, risks.
4. Such QoIs as the number of fingers, their size, shape, propagation time can be unstable
5. For moderate perturbations, our gPCE surrogate results are similar to qMC results.
6. Used highly scalable solver on up to 800 computing nodes,
Response Surface in Tensor Train format for Uncertainty QuantificationAlexander Litvinenko
We apply low-rank Tensor Train format to solve PDEs with uncertain coefficients. First, we approximate uncertain permeability coefficient in TT format, then the operator and then apply iterations to solve stochastic Galerkin system.
Mx/G(a,b)/1 With Modified Vacation, Variant Arrival Rate With Restricted Admi...IJRES Journal
In this paper, a bulk arrival general bulk service queuing system with modified M-vacation policy, variant arrival rate under a restricted admissibility policy of arriving batches and close down time is considered. During the server is in non- vacation, the arrivals are admitted with probability with ' α ' whereas, with probability 'β' they are admitted when the server is in vacation. The server starts the service only if at least ‘a’ customers are waiting in the queue, and renders the service according to the general bulk service rule with minimum of ‘a’ customers and maximum of ‘b’ customers. At the completion of service, if the number of waiting customers in the queue is less than ‘𝑎’ then the server performs closedown work , then the server will avail of multiple vacations till the queue length reaches a consecutively avail of M number of vacations, After completing the Mth vacation, if the queue length is still less than a then the server remains idle till it reaches a. The server starts the service only if the queue length b ≥ a. It is considered that the variant arrival rate dependent on the state of the server.
Propagation of Uncertainties in Density Driven Groundwater FlowAlexander Litvinenko
Major Goal: estimate risks of the pollution in a subsurface flow.
How?: we solve density-driven groundwater flow with uncertain porosity and permeability.
We set up density-driven groundwater flow problem,
review stochastic modeling and stochastic methods, use UG4 framework (https://gcsc.uni-frankfurt.de/simulation-and-modelling/ug4),
model uncertainty in porosity and permeability,
2D and 3D numerical experiments.
Major Goal: estimate risks of the pollution in a subsurface flow.
How? We solve density-driven groundwater flow with uncertain porosity and permeability.
1. We set up density-driven groundwater flow problem
2. Review stochastic modeling and stochastic methods
3. Modeling of uncertainty in porosity and permeability
4. Numerical methods to solve deterministic problem
5. 2D and 3D examples with 0.5-8 Millions mesh points.
Efficient Simulations for Contamination of Groundwater Aquifers under Uncerta...Alexander Litvinenko
1. Solved time-dependent density driven flow problem with uncertain porosity and permeability in 2D and 3D
2. Computed propagation of uncertainties in porosity into the mass fraction.
3. Computed the mean, variance, exceedance probabilities, quantiles, risks.
4. Such QoIs as the number of fingers, their size, shape, propagation time can be unstable
5. For moderate perturbations, our gPCE surrogate results are similar to qMC results.
6. Used highly scalable solver on up to 800 computing nodes,
Response Surface in Tensor Train format for Uncertainty QuantificationAlexander Litvinenko
We apply low-rank Tensor Train format to solve PDEs with uncertain coefficients. First, we approximate uncertain permeability coefficient in TT format, then the operator and then apply iterations to solve stochastic Galerkin system.
Mx/G(a,b)/1 With Modified Vacation, Variant Arrival Rate With Restricted Admi...IJRES Journal
In this paper, a bulk arrival general bulk service queuing system with modified M-vacation policy, variant arrival rate under a restricted admissibility policy of arriving batches and close down time is considered. During the server is in non- vacation, the arrivals are admitted with probability with ' α ' whereas, with probability 'β' they are admitted when the server is in vacation. The server starts the service only if at least ‘a’ customers are waiting in the queue, and renders the service according to the general bulk service rule with minimum of ‘a’ customers and maximum of ‘b’ customers. At the completion of service, if the number of waiting customers in the queue is less than ‘𝑎’ then the server performs closedown work , then the server will avail of multiple vacations till the queue length reaches a consecutively avail of M number of vacations, After completing the Mth vacation, if the queue length is still less than a then the server remains idle till it reaches a. The server starts the service only if the queue length b ≥ a. It is considered that the variant arrival rate dependent on the state of the server.
Propagation of Uncertainties in Density Driven Groundwater FlowAlexander Litvinenko
Major Goal: estimate risks of the pollution in a subsurface flow.
How?: we solve density-driven groundwater flow with uncertain porosity and permeability.
We set up density-driven groundwater flow problem,
review stochastic modeling and stochastic methods, use UG4 framework (https://gcsc.uni-frankfurt.de/simulation-and-modelling/ug4),
model uncertainty in porosity and permeability,
2D and 3D numerical experiments.
Major Goal: estimate risks of the pollution in a subsurface flow.
How? We solve density-driven groundwater flow with uncertain porosity and permeability.
1. We set up density-driven groundwater flow problem
2. Review stochastic modeling and stochastic methods
3. Modeling of uncertainty in porosity and permeability
4. Numerical methods to solve deterministic problem
5. 2D and 3D examples with 0.5-8 Millions mesh points.
Presented at Evolution 2013, June 24; describes an approach to teaching populations genetics at the upper undergraduate/beginning graduate level, using simulations based in R and incorporating available large genomic data sets.
Kazushi Okamoto: Families of Triangular Norm Based Kernel Function and Its Application to Kernel k-means, Joint 8th International Conference on Soft Computing and Intelligent Systems and 17th International Symposium on Advanced Intelligent Systems (SCIS-ISIS2016), 2016.08.25
Epidemic processes on switching networksNaoki Masuda
Presentation slides for the following two papers:
- Leo Speidel, Konstantin Klemm, Víctor M. Eguíluz, Naoki Masuda.
New Journal of Physics, 18, 073013 (2016).
- Tomokatsu Onaga, James P. Gleeson, Naoki Masuda.
Physical Review Letters, 119, 108301 (2017).
Slides: On the Chi Square and Higher-Order Chi Distances for Approximating f-...Frank Nielsen
Slides for the paper:
On the Chi Square and Higher-Order Chi Distances for Approximating f-Divergences
published in IEEE SPL:
http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6654274
An Introduction into Anomaly Detection Using CUSUMDominik Dahlem
A gentle introduction into anomaly detection using the cumulative sum (CUSUM) algorithm. Extensive visuals are used to exemplify the inner workings of the algorithm. CUSUM relies on stationarity assumptions of the underlying process.
International Journal of Mathematics and Statistics Invention (IJMSI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJMSI publishes research articles and reviews within the whole field Mathematics and Statistics, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
ON APPROACH TO DECREASE DIMENSIONS OF FIELD-EFFECT TRANSISTORS FRAMEWORK ELEM...ijfcstjournal
In this paper we consider manufacturing of elements SRAM with increased density of field-effect transistors
consisting these elements. The approach based on manufacturing of the elements in heterostructure with
specific configuration. We consider doping of several required areas of the heterostructure by diffusion or
by ion implantation. After that dopant and radiation defects have been annealed framework optimized
scheme.
Presented at Evolution 2013, June 24; describes an approach to teaching populations genetics at the upper undergraduate/beginning graduate level, using simulations based in R and incorporating available large genomic data sets.
Kazushi Okamoto: Families of Triangular Norm Based Kernel Function and Its Application to Kernel k-means, Joint 8th International Conference on Soft Computing and Intelligent Systems and 17th International Symposium on Advanced Intelligent Systems (SCIS-ISIS2016), 2016.08.25
Epidemic processes on switching networksNaoki Masuda
Presentation slides for the following two papers:
- Leo Speidel, Konstantin Klemm, Víctor M. Eguíluz, Naoki Masuda.
New Journal of Physics, 18, 073013 (2016).
- Tomokatsu Onaga, James P. Gleeson, Naoki Masuda.
Physical Review Letters, 119, 108301 (2017).
Slides: On the Chi Square and Higher-Order Chi Distances for Approximating f-...Frank Nielsen
Slides for the paper:
On the Chi Square and Higher-Order Chi Distances for Approximating f-Divergences
published in IEEE SPL:
http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6654274
An Introduction into Anomaly Detection Using CUSUMDominik Dahlem
A gentle introduction into anomaly detection using the cumulative sum (CUSUM) algorithm. Extensive visuals are used to exemplify the inner workings of the algorithm. CUSUM relies on stationarity assumptions of the underlying process.
International Journal of Mathematics and Statistics Invention (IJMSI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJMSI publishes research articles and reviews within the whole field Mathematics and Statistics, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
ON APPROACH TO DECREASE DIMENSIONS OF FIELD-EFFECT TRANSISTORS FRAMEWORK ELEM...ijfcstjournal
In this paper we consider manufacturing of elements SRAM with increased density of field-effect transistors
consisting these elements. The approach based on manufacturing of the elements in heterostructure with
specific configuration. We consider doping of several required areas of the heterostructure by diffusion or
by ion implantation. After that dopant and radiation defects have been annealed framework optimized
scheme.
Listen to Positive Affirmation by specific topic here http://www.positivemindhub.com
Connect us on Social Media:
♥ #Twitter : http://www.twitter.com/Positivemindhub
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REUNIÓN ANUAL DE LA SECCIÓN DE RIESGO VASCULAR Y REHABILITACIÓN CARDIACA DE LA S.E.C.
Sede: Hotel Catalonia Plaza
9 - 10 de mayo de 2014
www.riesgo-vascular.com
ÚLTIMAS NOVEDADES SOBRE ANTICOAGULACIÓN EN FIBRILACIÓN AURICULAR
Dificultades en la implementación de los nuevos anticoagulantes y cómo superarlas.
Dr. Gonzalo Barón Esquivias · H.U. Virgen de Rocío. Sevilla
Quantum Annealing for Dirichlet Process Mixture Models with Applications to N...Shu Tanaka
Our paper entitled “Quantum Annealing for Dirichlet Process Mixture Models with Applications to Network Clustering" was published in Neurocomputing. This work was done in collaboration with Dr. Issei Sato (Univ. of Tokyo), Dr. Kenichi Kurihara (Google), Professor Seiji Miyashita (Univ. of Tokyo), and Prof. Hiroshi Nakagawa (Univ. of Tokyo).
http://www.sciencedirect.com/science/article/pii/S0925231213005535
The preprint version is available:
http://arxiv.org/abs/1305.4325
佐藤一誠さん(東京大学)、栗原賢一さん(Google)、宮下精二教授(東京大学)、中川裕志教授(東京大学)との共同研究論文 “Quantum Annealing for Dirichlet Process Mixture Models with Applications to Network Clustering" が Neurocomputing に掲載されました。
http://www.sciencedirect.com/science/article/pii/S0925231213005535
プレプリントバージョンは
http://arxiv.org/abs/1305.4325
からご覧いただけます。
Analysis of large scale spiking networks dynamics with spatio-temporal constr...Hassan Nasser
Recent experimental advances have made it possible to record up to several hundreds of neurons simultaneously in the cortex or in the retina. Analysing such data requires mathematical and numerical methods to describe the spatio-temporal correlations in population activity. This can be done thanks to Maximum Entropy method. Here, a crucial parameter is the product NxR where N is the number of neurons and R the memory depth of correlations (how far in the past does the spike activity affects the current state). Standard statistical mechanics methods are limited to spatial correlation structure with
R = 1 (e.g. Ising model) whereas methods based on transfer matrices, allowing the analysis of spatio-temporal correlations, are limited to NR = 20.
In the first part of the thesis we propose a modified version of the transfer matrix method, based on the parallel version of the Montecarlo algorithm, allowing us to go to NR = 100.
In the second part we present EnaS, a C++ library with a Graphical User Interface developed for neuroscientists. EnaS offers highly interactive tools that allow users to manage data, perform empirical statistics, modeling and visualizing results.
Finally, in a third part, we test our method on synthetic and real data sets. Real data set correspond to retina data provided by neuroscientists partners. Our non extensive analysis shows the advantages of considering spatio-temporal correlations for the analysis of retina spike trains, but it also outlines the limits of Maximum Entropy methods.
For more information about the software that I co-developed with my colleagues, please visit this page:
https://enas.inria.fr/
For more information about the publications, please visit this page:
https://scholar.google.fr/citations?user=L97ZODwAAAAJ
For the thesis, please visit this link:
https://www.theses.fr/178166669
(SAC2020 SVT-2) Constrained Detecting Arrays for Fault Localization in Combin...Hao Jin
Authors:
Hao Jin, Osaka University
Ce Shi, Shanghai Lixin University of Accounting and Finance
Tatsuhiro Tsuchiya, Osaka University
Abstract:
Detecting Arrays (DAs) are mathematical objects that enable fault localization in combinatorial interaction testing. Each row of a DA serves as a test case, whereas a whole DA is treated as a test suite. In real-world testing problems, it is often the case that some constraints exist among test parameters. In this paper, we show that it may be impossible to construct a DA using only constraint-satisfying test cases. The reason for this is that a set of some faulty interactions may always mask the effect of other faulty interactions in the presence of constraints. Based on this observation, we propose the notion of Constrained Detecting Arrays (CDAs) to adapt DAs to practical situations. The definition of CDAs requires that all rows of a CDA must satisfy the constraints and the same fault localization capability as the DA must hold except for such inherently undetectable faults. We then propose a computational method for constructing CDAs. Experimental results obtained by using a program that implements the method show that the method was able to produce CDAs within a reasonable time for practical problem instances.
An Improved Adaptive Multi-Objective Particle Swarm Optimization for Disassem...IJRESJOURNAL
With the development of productivity and the fast growth of the economy, environmental pollution, resource utilization and low product recovery rate have emerged subsequently, so more and more attention has been paid to the recycling and reuse of products. However, since the complexity of disassembly line balancing problem (DLBP) increases with the number of parts in the product, finding the optimal balance is computationally intensive. In order to improve the computational ability of particle swarm optimization (PSO) algorithm in solving DLBP, this paper proposed an improved adaptive multi-objective particle swarm optimization (IAMOPSO) algorithm. Firstly, the evolution factor parameter is introduced to judge the state of evolution using the idea of fuzzy classification and then the feedback information from evolutionary environment is served in adjusting inertia weight, acceleration coefficients dynamically. Finally, a dimensional learning strategy based on information entropy is used in which each learning object is uncertain. The results from testing in using series of instances with different size verify the effect of proposed algorithm.
The treatment of large structural systems may be simplified by dividing the system into
smaller systems called components. The components are related through the
displacement, and force conditions at their junction points. Each component is represented
by mode shapes (or functions).
When models are defined implicitly as systems of differential equations with no closed form solution, the choice of discretization grid for their approximation represents a trade-off between accuracy of the estimated solution and computational resources. We apply principles of statistical design to a class of sequential probability based models of discretization uncertainty for selecting the optimal discretization grid adaptively. Our proposal is compared to other approaches in the literature.
This presentation slides will help to make bridge with knowledge and reality in traffic flow modelling based on real understanding of mathematical terms in modelling equations. I hope it will make good contribution to improve our knowledge level for performing simulation of any model based on numerical method e.g., finite difference scheme.
All the best.
Nikhil Chandra Sarkar
Similar to Modeling Big Count Data: An IRLS Framework for COM-Poisson Regression and GAM (20)
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
Data Centers - Striving Within A Narrow Range - Research Report - MCG - May 2...pchutichetpong
M Capital Group (“MCG”) expects to see demand and the changing evolution of supply, facilitated through institutional investment rotation out of offices and into work from home (“WFH”), while the ever-expanding need for data storage as global internet usage expands, with experts predicting 5.3 billion users by 2023. These market factors will be underpinned by technological changes, such as progressing cloud services and edge sites, allowing the industry to see strong expected annual growth of 13% over the next 4 years.
Whilst competitive headwinds remain, represented through the recent second bankruptcy filing of Sungard, which blames “COVID-19 and other macroeconomic trends including delayed customer spending decisions, insourcing and reductions in IT spending, energy inflation and reduction in demand for certain services”, the industry has seen key adjustments, where MCG believes that engineering cost management and technological innovation will be paramount to success.
MCG reports that the more favorable market conditions expected over the next few years, helped by the winding down of pandemic restrictions and a hybrid working environment will be driving market momentum forward. The continuous injection of capital by alternative investment firms, as well as the growing infrastructural investment from cloud service providers and social media companies, whose revenues are expected to grow over 3.6x larger by value in 2026, will likely help propel center provision and innovation. These factors paint a promising picture for the industry players that offset rising input costs and adapt to new technologies.
According to M Capital Group: “Specifically, the long-term cost-saving opportunities available from the rise of remote managing will likely aid value growth for the industry. Through margin optimization and further availability of capital for reinvestment, strong players will maintain their competitive foothold, while weaker players exit the market to balance supply and demand.”
Modeling Big Count Data: An IRLS Framework for COM-Poisson Regression and GAM
1. Modeling Big Count Data
An IRLS framework for COM-Poisson regression and GAM
Suneel Chatla
Galit Shmueli
November 12, 2016
Institute of Service Science
National Tsing Hua University, Taiwan (R.O.C)
2. Table of contents
1. Speed Dating Experiment- Count data models
2. Motivation
3. An IRLS framework
4. Simulation Study-Comparison of IRLS with MLE
5. A CMP Generalized Additive Model
6. Results & Conclusions
1
4. Speed dating experiment
Fisman et al. (2006) conducted a speed dating experiment to
evaluate the gender differences in mate selection 1
.
Total sessions 14
Decision 1 or 0
Attractiveness 1-10
Intelligence 1-10
Ambition 1-10
...
...
Control variables
1https://www.kaggle.com/annavictoria/speed-dating-experiment
2
5. Outcome/Count variables
Matches : When both persons decide Yes
Tot.Yes : Total number of Yes for each subject in a particular session
3
10. CMP Regression
CMP regression models can be formulated as follows:
log(λ) = Xβ (1)
log(ν) = Zγ (2)
Maximizing the log-likelihood w.r.t the parameters β and γ will yield
the following normal equations Sellers and Shmueli (2010):
U =
∂logL
∂β
= XT
(y − E(y)) (3)
V =
∂logL
∂γ
= νZT
(−log(y!) + E(log(y!))) (4)
8
13. More flexibility?
Generalized Additive Models
• Smoothing Splines
• Penalized Splines
Both implementations are dependent upon the Iterative Reweighted
Least Squares (IRLS) estimation framework.
At present, there is no IRLS framework available for CMP !!
10
20. Study design
We compare our IRLS algorithm with the existing implementation
which is based on maximizing the likelihood function (through optim
in R).
(a) Set sample size n = 100
(b) Generate x1 ∼ U(0, 1) and x2 ∼ N(0, 1)
(c) Calculate x3 = 0.2x1 + U(0, 0.3) and x4 = 0.3x2 + N(0, 0.1) (to
create correlated variables)
(d) Generate
y ∼ CMP(log(λ) = 0.05 + 0.5x1 − 0.5x2 + 0.25x3 − 0.25x4, ν)
where ν = {0.5, 2, 5}
15
21. Results
q
q
q
q
IR MLE IR MLE IR MLE
−0.50.00.51.01.5
x1
q q
q
q
q
q
q
q
IR MLE IR MLE IR MLE
−2.0−1.5−1.0−0.50.00.5
x2
q
q
q
IR MLE IR MLE IR MLE
−4−20246
x3
q
q
q
q
q
q
q
q
qq
IR MLE IR MLE IR MLE
−4−2024
x4
q
q
q
IR MLE IR MLE IR MLE
−2−101234
log(ν)
ν=0.5
ν=2
ν=5
16
27. Comparison of Additive Models on Tot.Yes
Dependent variable:
Tot.Yes
CMP(Chi.Sq) Poisson(Chi.Sq)
s(sinc) 7.16 11.53∗∗
s(func) 7.51 11.40∗∗
s(sinc_o) 13.96∗∗
29.30∗∗∗
s(intel_o) 14.06∗∗
13.26∗∗∗
ν 0.56
AIC 2737.03 2804.77
Note: ∗
p<0.1; ∗∗
p<0.05; ∗∗∗
p<0.01
It’s more about the behavior of opposite person that guide us to
select her/him.
20
28. Summary
• The IRLS framework is far more efficient than the existing
likelihood based method and provides more flexibility.
• Since CMP is computationally heavier than the other GLMs we
could parallelize some matrix computations inorder to increase
the speed.
• The IRLS framework allows CMP to have other modeling
extensions such as LASSO etc.
Full paper available from https://arxiv.org/abs/1610.08244
and the source code is available from
https://github.com/SuneelChatla/cmp
21
30. References
Fisman, R., Iyengar, S. S., Kamenica, E., and Simonson, I. (2006).
Gender differences in mate selection: Evidence from a speed
dating experiment. The Quarterly Journal of Economics, pages
673–697.
Hastie, T. J. and Tibshirani, R. J. (1990). Generalized additive models,
volume 43. CRC Press.
Sellers, K. F. and Shmueli, G. (2010). A flexible regression model for
count data. Annals of Applied Statistics, 4(2):943–961.
Shmueli, G., Minka, T. P., Kadane, J. B., Borle, S., and Boatwright, P.
(2005). A useful distribution for fitting discrete data: revival of the
conway–maxwell–poisson distribution. Journal of the Royal
Statistical Society: Series C (Applied Statistics), 54(1):127–142.
31. Wood, S. (2006). Generalized additive models: an introduction with R.
CRC press.