- Úvod
- Ústav
- Lidé
- Výzkum
- Aplikace
- Semináře a akce
- Knihovna
- Doktorské studium
- Kariéra
Ústav informatiky
Akademie věd České republiky
Akademie věd České republiky
"Jednoduchost je velká ctnost, ale vyžaduje mnoho práce, aby jí bylo dosaženo, a vzdělání, aby byla oceněna. A co je horší: složitost se lépe prodává." - E. W. Dijkstra
Vybrané publikace
Computational Aspects of Psychometric Methods With R.
CRC Press (Taylor & Francis Group, LLC), 2023,
This book covers the computational aspects of psychometric methods involved in developing measurement instruments and analyzing measurement data in social sciences. It covers the main topics of psychometrics such as validity, reliability, item analysis, item response theory models, and computerized adaptive testing. The computational aspects comprise the statistical theory and models, comparison of estimation methods and algorithms, as well as an implementation with practical data examples in R and also in an interactive ShinyItemAnalysis application.
Validation of the PALM model system 6.0 in a real urban environment: a case study in Dejvice, Prague, the Czech Republic.
In Geoscientific Model Development, ročník 14, svazek č. 8, strana 4797-4842 , 2021, ISSN 1991-959X.
In recent years, the PALM 6.0 modelling system has been rapidly developing its capability to simulate physical processes within urban environments. Some examples in this regard are energy-balance solvers for building and land surfaces, a radiative transfer model to account for multiple reflections and shading, a plant-canopy model to consider the effects of plants on flow (thermo)dynamics, and a chemistry transport model to enable simulation of air quality. This study provides a thorough evaluation of modelled meteorological, air chemistry, and ground and wall-surface quantities against dedicated in situ measurements taken in an urban environment in Dejvice, Prague, the Czech Republic. Measurements included monitoring of air quality and meteorology in street canyons, surface temperature scanning with infrared cameras, and monitoring of wall heat fluxes. Large-eddy simulations (LES) using the PALM model driven by boundary conditions obtained from a mesoscale model were performed for multiple days within two summer and three winter episodes characterized by different atmospheric conditions. For the simulated episodes, the resulting temperature, wind speed, and chemical compound concentrations within street canyons show a realistic representation of the observed state, except that the LES did not adequately capture night-time cooling near the surface for certain meteorological conditions. In some situations, insufficient turbulent mixing was modelled, resulting in higher near-surface concentrations. At most of the evaluation points, the simulated surface temperature reproduces the observed surface temperature reasonably well for both absolute and daily amplitude values. However, especially for the winter episodes and for modern buildings with multilayer walls, the heat transfer through walls is not well captured in some cases, leading to discrepancies between the modelled and observed wall-surface temperature. Furthermore, the study corroborates model dependency on the accuracy of the input data. In particular, the temperatures of surfaces affected by nearby trees strongly depend on the spatial distribution of the leaf area density, land surface temperatures at grass surfaces strongly depend on the initial soil moisture, wall-surface temperatures depend on the correct setting of wall material parameters, and concentrations depend on detailed information on spatial distribution of emissions, all of which are often unavailable at sufficient accuracy. The study also points out some current model limitations, particularly the implications of representing topography and complex heterogeneous facades on a discrete Cartesian grid, and glass facades that are not fully represented in terms of radiative processes. Our findings are able to validate the representation of physical processes in PALM while also pointing out specific shortcomings. This will help to build a baseline for future developments of the model and improvements of simulations of physical processes in an urban environment.
Logic and Implication: An introduction to the General Algebraic Study of Non-classical Logics.
Springer, 2021,
This monograph presents a general theory of weakly implicative logics, a family covering a vast number of non-classical logics studied in the literature, concentrating mainly on the abstract study of the relationship between logics and their algebraic semantics. It can also serve as an introduction to (abstract) algebraic logic, both propositional and first-order, with special attention paid to the role of implication, lattice and residuated connectives, and generalized disjunctions. Based on their recent work, the authors develop a powerful uniform framework for the study of non-classical logics. In a self-contained and didactic style, starting from very elementary notions, they build a general theory with a substantial number of abstract results. The theory is then applied to obtain numerous results for prominent families of logics and their algebraic counterparts, in particular for superintuitionistic, modal, substructural, fuzzy, and relevant logics. The book may be of interest to a wide audience, especially students and scholars in the fields of mathematics, philosophy, computer science, or related areas, looking for an introduction to a general theory of non-classical logics and their algebraic semantics.
Is academic tracking related to gains in learning competence? Using propensity score matching and differential item change functioning analysis for better understanding of tracking implications.
In Learning and Instruction, ročník 66, svazek April 2020 , 2020, ISSN 0959-4752.
This study analyzes gains in cognitive components of learning competence with respect to cohorts based on ability tracking in a Czech longitudinal study. Propensity score matching is used to form parallelized samples of academic and non-academic track students and to eliminate the effect of selective school intake. We applied regression models on the total scores to test for the overall track effect. Furthermore, we analyze scores and gains on the subscores and check for differential item functioning in Grade 6 and in change to Grade 9. While after 3 years, no significant difference between the two tracks was apparent in the total learning competence score, we did, however, find significant differences in some subscores and in the functioning of some items. We argue that item-level analysis is important for deeper understanding of the tracking implications and may provide the basis for more precise evidence-based decisions regarding the tracking policy.
Generalized Spectrum of Second Order Differential Operators.
In SIAM Journal on Numerical Analysis, ročník 58, svazek č. 4, strana 2193-2211 , 2020, ISSN 0036-1429.
We analyze the spectrum of the operator Delta(-1)[Delta . (K del u)], where Delta denotes the Laplacian and K = K(x, y) is a symmetric tensor. Our main result shows that this spectrum can be derived from the spectral decomposition K = Q Lambda Q(T), where Q = Q(x, y) is an orthogonal matrix and Lambda = Lambda(x, y) is a diagonal matrix. More precisely, provided that K is continuous, the spectrum equals the convex hull of the ranges of the diagonal function entries of A. The involved domain is assumed to be bounded and Lipschitz, and both homogeneous Dirichlet and homogeneous Neumann boundary conditions are considered. We study operators defined on infinite dimensional Sobolev spaces. Our theoretical investigations are illuminated by numerical experiments, using discretized problems. The results presented in this paper extend previous analyses which have addressed elliptic differential operators with scalar coefficient functions. Our investigation is motivated by both preconditioning issues (efficient numerical computations) and the need to further develop the spectral theory of second order PDEs (core analysis).
Krylov Methods for Nonsymmetric Linear Systems - From Theory to Computations.
Springer, 2020,
Zásadní událostí v Oddělení výpočetní matematiky bylo vydání knihy „Krylovovy metody pro nesymetrické lineární systémy“, kterou napsal Jurjen Duintjer Tebbens spolu s významným francouzským vědcem Gérardem Meurantem, který je po mnoho let jednou z vedoucích osobností v oblasti numerické lineární algebry. Řešení soustav algebraických lineárních rovnic je jedním ze základních problémů numerické analýzy. Tvoří základ téměř každého algoritmu ve vědeckých výpočtech s aplikacemi v mnoha oborech, jako je fyzika, inženýrství, chemie, biologie a mnoha dalších. Krylovovy metody se ukázaly jako vysoce efektivní iterační metody, kterou jsou navíc velmi robustní pro řešení velkých lineárních systémů rovnic. Tato kniha poskytuje nejen přehled nejmodernějších iterativních metod založených na Krylovských podprostorech pro řešení nesymetrických systémů algebraických lineárních rovnic, ale také prezentuje řadu současných výsledků obou autorů. Dalším vynikajícím rysem knihy je to, že sjednocuje z literatury známe metody v obecném rámci a předkládá jak jejich teoretické základy, tak algoritmické otázky pro praktickou implementaci.
Critical slowing down as a biomarker for seizure susceptibility.
In Nature Communications, ročník 11, svazek č. 1 , 2020, ISSN 2041-1723.
The human brain has the capacity to rapidly change state, and in epilepsy these state changes can be catastrophic, resulting in loss of consciousness, injury and even death. Theoretical interpretations considering the brain as a dynamical system suggest that prior to a seizure, recorded brain signals may exhibit critical slowing down, a warning signal preceding many critical transitions in dynamical systems. Using long-term intracranial electroencephalography (iEEG) recordings from fourteen patients with focal epilepsy, we monitored key signatures of critical slowing down prior to seizures. The metrics used to detect critical slowing down fluctuated over temporally long scales (hours to days), longer than would be detectable in standard clinical evaluation settings. Seizure risk was associated with a combination of these signals together with epileptiform discharges. These results provide strong validation of theoretical models and demonstrate that critical slowing down is a reliable indicator that could be used in seizure forecasting algorithms.
Overview of the PALM Model System 6.0.
In Geoscientific Model Development, ročník 13, svazek č. 3, strana 1335-1372 , 2020, ISSN 1991-959X.
Článek popisuje modelový systém PALM v.6.0. PALM je rozšířený mikroměřítkový atmosferický model založený na LES přístupu. Tento model je optimalizován pro běh na masívně paralelních počítačových architekturách. V průběhu posledních let byl model výrazně rozšířen a nyní nabízí množství nových komponent. Velké úsilí bylo speciálně věnováno rozšíření modelu o komponenty potřebné pro aplikace v městském prostředí, jako například plně interaktivní model povrchu země a budov, modelování interakcí radiace v komplexním prostředí, chemický model a model vnitřního prostředí budov. Tento článek je součástí speciálního čísla časopisu GMD věnovaného modelu PALM v.6.0 a slouží jako základní přehledový článek o modelu a jeho komponentách pro městské aplikace. Podrobný popis jednotlivých komponent stejně jako popis validačních studií a záležitostí spojených se vstupními daty modelu jsou popsány a diskutovány v řadě doprovodných článků tohoto speciálního čísla.
Long-term trends in fog occurrence in the Czech Republic, Central Europe.
In Science of the Total Environment, ročník 711, svazek April 1 , 2020, ISSN 0048-9697.
Fog is a very important and complex atmospheric phenomenon of the utmost importance for the environment and for human society. For practical reasons, fog occurrence is observed regularly at meteorological stations worldwide. Decreasing trends in fog frequency reported from numerous regions have been often associated with either decreasing pollution or climate change, including increasing temperature and changes in atmospheric circulation. We have examined the data on fog occurrence from twelve Czech sites representing different environments (urban, rural, mountain), geographical areas, and altitudes across the country. For our analysis we used long-term records from the time period of 1961–2018, covering both the ambient air’s heavily polluted periods of the 1970s and 1980s and the cleaner period, following the adoption of new, more stringent legislation and effective countermeasures after the 1990s. We applied a generalised additive model (GAM) framework as a flexible, semiparametric regression approach to address nonlinear trend shapes in a formalised and unified way. In particular, we employed a penalised spline approach with cross-validated penalty coefficient estimation. Our study confirmed non-linear behaviour for both year-to-year trends and annual seasonality. Our results showed further that over the analysed, almost sixty-year period, fog occurrence has decreased significantly at all the examined sites, though the pattern of the long-term change differed among individual sites. Moreover, we have found significant seasonality in fog occurrence, though it is different at individual sites. Furthermore, apart from the overall annual fog probability change over the years, at some sites the fog’s seasonal profile has also deformed substantially over the long term.
