Some modifications of the limited-memory variable metric optimization methods
Vlček, Jan; Lukšan, Ladislav
2023 - English Several modifications of the limited-memory variable metric (or quasi-Newton) line search methods for large scale unconstrained optimization are investigated. First the block version of the symmetric rank-one (SR1) update formula is derived in a similar way as for the block BFGS update in Vlˇcek and Lukˇsan (Numerical Algorithms 2019). The block SR1 formula is then modified to obtain an update which can reduce the required number of arithmetic operations per iteration. Since it usually violates the corresponding secant conditions, this update is combined with the shifting investigated in Vlˇcek and Lukˇsan (J. Comput. Appl. Math. 2006). Moreover, a new efficient way how to realize the limited-memory shifted BFGS method is proposed. For a class of methods based on the generalized shifted economy BFGS update, global convergence is established. A numerical comparison with the standard L-BFGS and BNS methods is given. Keywords: unconstrained minimization; variable metric methods; limited-memory methods; variationally derived methods; arithmetic operations reduction; global convergence Available in a digital repository NRGL Some modifications of the limited-memory variable metric optimization methods

Several modifications of the limited-memory variable metric (or quasi-Newton) line search methods for large scale unconstrained optimization are investigated. First the block version of the symmetric ...

Vlček, Jan; Lukšan, Ladislav
Ústav informatiky, 2023

GA 19-07635S: Outputs and Results
Rehák, Branislav
2023 - English This manuscript aims to deliver a survey of results obtained during the solution of the project No. GA19-07635S of the Czech Science Foundation. The timespan dedicated to the work on this project was 1.3.2019 - 30.6.2022. The main area dealt with were\nnonlinear multi-agent systems and their synchronization, further, attention was paid to some auxiliary results in the area of nonlinear observers. This Report briefly introduces the Project, provides a summary of the results obtained and also sketches an outline how these results will be applied and extended in future. Keywords: multi-agent systems; nonlinear multi-agent systems; synchronization Fulltext is available at external website. GA 19-07635S: Outputs and Results

This manuscript aims to deliver a survey of results obtained during the solution of the project No. GA19-07635S of the Czech Science Foundation. The timespan dedicated to the work on this project was ...

Rehák, Branislav
Ústav teorie informace a automatizace, 2023

Drivers of Private Equity Activity across Europe: An East-West Comparison
Kočenda, Evžen; Shivendra, R.
2023 - English We investigate the key macroeconomic and institutional determinants of fundraising and investment activities and compare them across Europe, covering 13 Central and Eastern European (CEE) and 16 Western European (WE) countries. Five macroeconomic variables and nineteen institutional variables are selected. These variables are studied using panel data analysis with fixed effects and random effects models over an eleven-year observation period (2010–2020). Bayesian Model Averaging (BMA) is applied to select the key variables. Our results suggest that macroeconomic variables have no significant impact on fundraising and investment activity in either region. Investment activity is a significant driver of fundraising across Europe. Similarly, fundraising and divestment activity are significant drivers of investments across Europe. Institutional variables, however, affect fundraising and investment activity differently. While investment freedom has a significant effect on funds raised in the WE and CEE countries, government integrity and trade freedom are both significant determinants of investments in both European regions. In addition, the results demonstrate that, in contrast to the WE region, fundraising in the CEE region is not country specific. We investigate the key macroeconomic and institutional determinants of fundraising and investment activities and compare them across Europe, covering 13 Central and Eastern European (CEE) and 16 Western European (WE) countries. Five macroeconomic variables and nineteen institutional variables are selected. These variables are studied using panel data analysis with fixed effects and random effects models over an eleven-year observation period (2010–2020). Bayesian Model Averaging (BMA) is applied to select the key variables. Our results suggest that macroeconomic variables have no significant impact on fundraising and investment activity in either region. Investment activity is a significant driver of fundraising across Europe. Similarly, fundraising and divestment activity are significant drivers of investments across Europe. Institutional variables, however, affect fundraising and investment activity differently. While investment freedom has a significant effect on funds raised in the WE and CEE countries, government integrity and trade freedom are both significant determinants of investments in both European regions. In addition, the results demonstrate that, in contrast to the WE region, fundraising in the CEE region is not country specific. Keywords: Private equity; Fundraising; Investment Fulltext is available at external website. Drivers of Private Equity Activity across Europe: An East-West Comparison

We investigate the key macroeconomic and institutional determinants of fundraising and investment activities and compare them across Europe, covering 13 Central and Eastern European (CEE) and 16 ...

Kočenda, Evžen; Shivendra, R.
Ústav teorie informace a automatizace, 2023

Vývoj nástrojů pro minimalizaci rizik kontaminace ovzduší respirabilními azbestovými vlákny uvolňovanými lidskou činností z horninového prostředí – souhrnná výzkumná zpráva o průběhu a výsledcích řešení projektu
Vavro, Leona; Vavro, Martin; Daněk, T.; Kajzar, Vlastimil; Drozdová, J.; Raclavský, K.; Kubina, Lukáš
2023 - Czech Souhrnná výzkumná zpráva přináší zhodnocení postupu a výsledků projektu SS01010257 - Vývoj nástrojů pro minimalizaci rizika kontaminace ovzduší respirabilními azbestovými vlákny uvolňovanými lidskou činností z horninového prostředí (AZROCK). Řešený projekt měl dva hlavní cíle. Prvním bylo vytvoření dvou metodických návodů, a to jednak pro odběr vzorků hornin a kameniva s možným obsahem přirozeně se vyskytujících azbestů a jednak pro následnou analýzu přítomnosti azbestových vláken v odebraných vzorcích. Dále si projekt stanovil za cíl tvorbu specializované mapy rizika výskytu azbestu v horninovém prostředí v České republice a internetového znalostního portálu azbestů. Podstatná část řešení projektu byla založena na odběru vzorků hornin a kameniva na téměř stovce vytipovaných lokalit po celé České republice a jejich následném vyhodnocení zvoleným a ověřeným souborem analytických metod. Podobné informace o výskytu azbestu v horninovém prostředí České republiky nebyly dosud zájemcům z řad odborné i laické veřejnosti k dispozici. The summary research report provides an evaluation of the procedure and results of the project SS01010257 - Development of tools to minimise the risks of air contamination by respirable asbestos fibres released from the rock environment by human activities (AZROCK). The solved project had two main objectives. The first one was the creation of two methodical instructions, both for the rock and aggregate sampling with a possible naturally occurring asbestos content and for the subsequent analysis of the presence of asbestos fibers in the samples taken. Furthermore, the project set itself the goal of creating: (1) a specialized map of the risk of asbestos occurrence in the rock environment in the Czech Republic and (2) a web knowledge portal of asbestos. A substantial part of the project solution was based on the collection of samples of rocks and aggregates at almost a hundred selected sites throughout the Czech Republic and their subsequent evaluation using a selected and verified set of analytical methods. Similar information on the occurrence of asbestos in the rock environment of the Czech Republic has not yet been available to interested professionals and the non-specialist public. Keywords: naturally occuring asbestos; rocks; aggregate; sampling; analysis; Czech Republic Fulltext is available at external website. Vývoj nástrojů pro minimalizaci rizik kontaminace ovzduší respirabilními azbestovými vlákny uvolňovanými lidskou činností z horninového prostředí – souhrnná výzkumná zpráva o průběhu a výsledcích řešení projektu

Souhrnná výzkumná zpráva přináší zhodnocení postupu a výsledků projektu SS01010257 - Vývoj nástrojů pro minimalizaci rizika kontaminace ovzduší respirabilními azbestovými vlákny uvolňovanými lidskou ...

Vavro, Leona; Vavro, Martin; Daněk, T.; Kajzar, Vlastimil; Drozdová, J.; Raclavský, K.; Kubina, Lukáš
Ústav geoniky, 2023

Good vs. Bad Volatility in Major Cryptocurrencies: The Dichotomy and Drivers of Connectedness
Šíla, Jan; Kočenda, Evžen; Kukačka, Jiří; Krištoufek, Ladislav
2023 - English Cryptocurrencies exhibit unique statistical and dynamic properties compared to those of traditional financial assets, making the study of their volatility crucial for portfolio managers and traders. We investigate the volatility connectedness dynamics of a representative set of eight major crypto assets. Methodologically, we decompose the measured volatility into positive and negative components and employ the time-varying parameters vector autoregression (TVP-VAR) framework to show distinct dynamics associated with market booms and downturns. The results suggest that crypto connectedness reflects important events and exhibits more variable and cyclical dynamics than those of traditional financial markets. Periods of extremely high or low connectedness are clearly linked to specific events in the crypto market and macroeconomic or monetary history. Furthermore, existing asymmetry from good and bad volatility indicates that information about market downturns spills over substantially faster than news about comparable market surges. Overall, the connectedness dynamics are predominantly driven by fundamental crypto factors, while the asymmetry measure also depends on macro factors such as the VIX index and the expected inflation. Keywords: Volatility; Dynamic connectedness; Asymmetric effects; Cryptocurrency Fulltext is available at external website. Good vs. Bad Volatility in Major Cryptocurrencies: The Dichotomy and Drivers of Connectedness

Cryptocurrencies exhibit unique statistical and dynamic properties compared to those of traditional financial assets, making the study of their volatility crucial for portfolio managers and traders. ...

Šíla, Jan; Kočenda, Evžen; Kukačka, Jiří; Krištoufek, Ladislav
Ústav teorie informace a automatizace, 2023

Determinants of Financial Inclusion in Africa and OECD Countries
Kočenda, Evžen; Eshun, S. F.
2023 - English Sub-Saharan Africa (SSA) has been identified as one of the least financially inclusive regions in the world with a huge disparity in comparison to highly financially inclusive regions. Using a dynamic panel data analysis, we explore the factors influencing financial inclusion in Sub-Saharan Africa (SSA) using countries belonging to the Organisation for Economic Co-operation and Development (OECD) as a benchmark. We employ the System Generalized Method of Moments (GMM) estimator and assess 31 SSA and 38 OECD countries from 2000-2021. We show that the differences in trade openness, banks' efficiency, income, and remittances are some macro-level factors that explain the variation in financial inclusion levels. We highlight the importance of quality literacy policies, trade improvement with restrictions on cross-border capital flows, and a more efficient financial system to promote financial inclusion. Keywords: Financial Inclusion; Financial Inclusion Index; Sub-Saharan Africa Fulltext is available at external website. Determinants of Financial Inclusion in Africa and OECD Countries

Sub-Saharan Africa (SSA) has been identified as one of the least financially inclusive regions in the world with a huge disparity in comparison to highly financially inclusive regions. Using a dynamic ...

Kočenda, Evžen; Eshun, S. F.
Ústav teorie informace a automatizace, 2023

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 ...

Jiříček, Stanislav; Koudelka, V.; Mantini, D.; Mareček, R.; Hlinka, Jaroslav
Ústav informatiky, 2022

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 ...

Vlk, T.; Dedecius, Kamil
Ústav teorie informace a automatizace, 2022

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, ...

Uglickich, Evženie; Nagy, Ivan
Ústav teorie informace a automatizace, 2022

Tisková zpráva - měření tepelného komfortu
Geletič, Jan; Lehnert, M.
2022 - Czech Fulltext is available at external website. Tisková zpráva - měření tepelného komfortu

Geletič, Jan; Lehnert, M.
Ústav informatiky, 2022