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Number of found documents:
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Spatio-Spectral EEG Patterns in the Source-Reconstructed Space and Relation to Resting-State Networks: An EEG-fMRI Study
Jiříček, Stanislav; Koudelka, V.; Mantini, D.; Mareček, R.; Hlinka, Jaroslav
2022 - English
In this work, we present and evaluate a novel EEG-fMRI integration approach combining a spatio-spectral decomposition method and a reliable source localization technique. On the large 72 subjects resting- state hdEEG-fMRI data set we tested the stability of the proposed method in terms of both extracted spatio-spectral patterns(SSPs) as well as their correspondence to the BOLD signal. We also compared the proposed method with the spatio-spectral decomposition in the electrode space as well as well-known occipital alpha correlate in terms of the explained variance of BOLD signal. We showed that the proposed method is stable in terms of extracted patterns and where they correlate with the BOLD signal. Furthermore, we show that the proposed method explains a very similar level of the BOLD signal with the other methods and that the BOLD signal in areas of typical BOLD functional networks is explained significantly more than by a chance. Nevertheless, we didn’t observe a significant relation between our source-space SSPs and the BOLD ICs when spatio-temporally comparing them. Finally, we report several the most stable source space EEG-fMRI patterns together with their interpretation and comparison to the electrode space patterns.
Keywords:
EEG-fMRI Integration; EEG-informed fMRI; Spatio-spectral Decomposition; Electrical Source Imaging; Independent Component Analysis; Resting State Networks
Available in digital repository of the ASCR
Spatio-Spectral EEG Patterns in the Source-Reconstructed Space and Relation to Resting-State Networks: An EEG-fMRI Study
In this work, we present and evaluate a novel EEG-fMRI integration approach combining a spatio-spectral decomposition method and a reliable source localization technique. On the large 72 subjects ...
Final Report of the Centre of Excellence for Nonlinear Dynamic Behaviour of Advanced Materials in Engineering
Parma, Slavomír; Gabriel, Dušan
2022 - English
This final report presents the CeNDYNMAT Center of Excellence, which was established at the Institute of Thermomechanics of the Czech Academy of Sciences in 2016 and ended in 2022. The report summarizes the most important scientific results of the center. It also gives an overview of the main outcomes and developments of the project, including budgeting, purchasing instrumentation, international cooperation and organization of conferences and summer courses.
Keywords:
nonlinear dynamic behavior; advanced materials; metal plasticity
Available at various institutes of the ASCR
Final Report of the Centre of Excellence for Nonlinear Dynamic Behaviour of Advanced Materials in Engineering
This final report presents the CeNDYNMAT Center of Excellence, which was established at the Institute of Thermomechanics of the Czech Academy of Sciences in 2016 and ended in 2022. The report ...
Diffusion Kalman filtering under unknown process and measurement noise covariance matrices
Vlk, T.; Dedecius, Kamil
2022 - English
The state-of-the-art algorithms for Kalman filtering in agent networks with information diffusion impose the requirement of well-defined state-space models. In particular, they assume that both the process and measurement noise covariance matrices are known and properly set. This is a relatively strong assumption in the signal processing domain. By design, the Kalman filters are rather sensitive to its violation, which may potentially lead to their divergence. In this paper, we propose a novel distributed filtering algorithm with increased robustness under unknown process and measurement noise covariance matrices. It is formulated as a Bayesian variational message passing procedure for simultaneous analytically tractable inference of states and measurement noise covariance matrices.
Keywords:
Collaborative estimation; State estimation; Variational Bayesian methods
Fulltext is available at external website.
Diffusion Kalman filtering under unknown process and measurement noise covariance matrices
The state-of-the-art algorithms for Kalman filtering in agent networks with information diffusion impose the requirement of well-defined state-space models. In particular, they assume that both the ...
Aerodynamic Measurements on Transonic Compressor Blade Cascades KR-D-5 and KR-D-6
Šimurda, David; Hála, Jindřich; Luxa, Martin
2022 - English
This report contains results and evaluation of aerodynamic measurements conducted on two variant transonic compressor blade cascades with MCA profile (KR-D-5) and DCA profile (KR-D-6).
Keywords:
compressor blade cascade; experiment; transonic flow; MCA profile; DCA profile
Available at various institutes of the ASCR
Aerodynamic Measurements on Transonic Compressor Blade Cascades KR-D-5 and KR-D-6
This report contains results and evaluation of aerodynamic measurements conducted on two variant transonic compressor blade cascades with MCA profile (KR-D-5) and DCA profile (KR-D-6).
Recursive mixture estimation with univariate multimodal Poisson variable
Uglickich, Evženie; Nagy, Ivan
2022 - English
Analysis of count variables described by the Poisson distribution is required in many application fields. Examples of the count variables observed per a time unit can be, e.g., number of customers, passengers, road accidents, Internet traffic packet arrivals, bankruptcies, virus attacks, etc. If the behavior of such a variable exhibits a multimodal character, the problem of clustering and classification of incoming count data arises. This issue can touch, for instance, detecting clusters of the different behavior of drivers in traffic flow analysis as well as cyclists or pedestrians. This work focuses on the model-based clustering of Poisson-distributed count data with the help of the recursive Bayesian estimation of the mixture of Poisson components. The aim of the work is to explain the methodology in details with an illustrative simple example, so that the work is limited to the univariate case and static pointer.
Keywords:
recursive mixture estimation; mixture of Poisson distributions; clustering and classification
Fulltext is available at external website.
Recursive mixture estimation with univariate multimodal Poisson variable
Analysis of count variables described by the Poisson distribution is required in many application fields. Examples of the count variables observed per a time unit can be, e.g., number of customers, ...
Survey of the use of propane as refrigerant R290 in cooling circuits and heat pumps
Aminian, Ali; Prokopová, Olga; Vinš, Václav
2022 - English
The technical report presents a review on the application of propane as refrigerant R290 in cooling circuits and heat pumps (HVAC). Safety risks of R290 used in HVAC are addressed according to ANSI/ASHRAE and EN standards. Comparison of thermophysical properties of propane with other refrigerants, solubility and miscibility of propane in compressor oils and heat transfer in condenser and evaporator are discussed. The main aim of the study is to provide an overview about the potential use of propane in the cooling circuit and heat pump for the hydrogen bus developed by the SOR Libchavy company.
Keywords:
cooling circuit; heat pump; hydrogen bus; refrigerant
Available at various institutes of the ASCR
Survey of the use of propane as refrigerant R290 in cooling circuits and heat pumps
The technical report presents a review on the application of propane as refrigerant R290 in cooling circuits and heat pumps (HVAC). Safety risks of R290 used in HVAC are addressed according to ...
A Measure of Variability WIthin Parametric Families of Continuous Distributions
Fabián, Zdeněk
2022 - English
A continuous probability measure on an open interval of the real line induces in it a unique geometry, "center of gravity" of which is the typical value of the distribution. In the paper is identified a score variance as a finite measure of variability of distributions with respect to the typical value and discussed its properties and methods of estimation. Itroducing a generalized Rao distance in the sample space one can appraise the precision of the estimate of the typical value.
Keywords:
scalar-valued score; score mean; score variance; distance in the sample space
Available at various institutes of the ASCR
A Measure of Variability WIthin Parametric Families of Continuous Distributions
A continuous probability measure on an open interval of the real line induces in it a unique geometry, "center of gravity" of which is the typical value of the distribution. In the paper is identified ...
Macroeconomic Responses of Emerging Market Economies to Oil Price Shocks: Analysis by Region and Resource Profile
Togonidze, S.; Kočenda, Evžen
2022 - English
This study employs a vector autoregressive (VAR) model to analyse how oil price shocks affect macroeconomic fundamentals in emerging economies. Findings from existing literature remain inconclusive how macroeconomic variables fare towards shocks, especially in emerging economies. The objective of our study is to uncover if analysis by region (Latin America and the Caribbean, East Asia and the Pacific, Europe, and Central Asia) and resource intensity of economies (oil exporters, oil importers, minerals exporters, and less resource intensive). Our unique approach forms part of our contribution to the literature. We find that Latin America and the Caribbean are least affected by oil price shocks, while in East Asia and the Pacific the response of inflation and interest rate to oil price shocks is positive, and output growth is negative. Our analysis by resource endowment fails to show oil price shocks’ ability to explain huge variations in macroeconomic variables in oil importing economies. Further sensitivity analysis using US interest rates as an alternative source of external shocks to emerging economies establishes a significant response of interest rate responses to US interest rate in Europe and Central Asia, and in inflation in Latin America and the Caribbean. We also find that regardless of resource endowment, the response of output growth and capital to a positive US interest rate shock is negative and significant in EMs. Our results are persuasive that resource intensity and regional factors impact the responsiveness of emerging economies to oil price shocks, thus laying a basis for policy debate.\n
Keywords:
Emerging market economies; Oil shocks; GDP; Markov-switching; Exchange rate; Oil exporters; Metal exporters
Fulltext is available at external website.
Macroeconomic Responses of Emerging Market Economies to Oil Price Shocks: Analysis by Region and Resource Profile
This study employs a vector autoregressive (VAR) model to analyse how oil price shocks affect macroeconomic fundamentals in emerging economies. Findings from existing literature remain inconclusive ...
Score correlation for skewed distributions
Fabián, Zdeněk
2022 - English
Based on the new concept of the scalar-valued score function of continuous distributions we introduce the score correlation coefficient ”tai-lored” to the assumed probabilistic model and study its properties by means of simulation experiments. It appeared that the new correlation method is useful for enormously skewed distributions.
Keywords:
Scalar-valued score; score coefficient of variation; Monte Carlo
Available at various institutes of the ASCR
Score correlation for skewed distributions
Based on the new concept of the scalar-valued score function of continuous distributions we introduce the score correlation coefficient ”tai-lored” to the assumed probabilistic model and study its ...
Introduction to statistical inference based on scalar-valued scores
Fabián, Zdeněk
2022 - English
In the report we maintain consistently the following point of view: Given a continuous model, there are not the observed values, which are to be used in probabilistic and statistical considerations, but their ”treated forms”,the values of the scalar-valued score function corresponding to the model. Based on this modified concept of the score function, we develop theory of score random variables, study their geometry and define their new characteristics, finite even in cases of heavy-tailed models. A generalization for parametric families provides a new approach to parametric point estimation.
Keywords:
continuous distributions; score mean; score variance; score moment estimation method; score distance
Available at various institutes of the ASCR
Introduction to statistical inference based on scalar-valued scores
In the report we maintain consistently the following point of view: Given a continuous model, there are not the observed values, which are to be used in probabilistic and statistical considerations, ...
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