Publications

The information comes from the university database V3S.

Authors:
Ing. Zuzana Purkrábková; Ing. Martin Langr, Ph.D.; doc. Ing. Pavel Hrubeš, Ph.D.; Ing. Marek Brabec, Ph.D.
Published:
2024, Neural Network World, 34 (4), p. 203-218), ISSN 1210-0552
Annotation:
The primary objective of the presented research is to enhance an existing data quality control application by integrating advanced anomaly detection mechanisms based on generalized additive models. This approach targets time- series traffic data, where traditional methods may fall short in identifying complex, non-linear patterns of anomalies. In collaboration with Simplity s.r.o., we are extending their current data quality assessment tool to incorporate generalized additive models, providing a more robust and dynamic solution for monitoring and ensuring the reliability of traffic datasets. The integration of these models aims to improve the accuracy of anomaly detection, leading to more effective data management in transport systems and contributing to higher standards of data quality in the field of traffic informatics.
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Authors:
Miron, L.; Chiriac, R.; Ing. Marek Brabec, Ph.D.; Badescu, V.
Published:
2021, Energy Reports, 7, p. 5483-5494), ISSN 2352-4847
Annotation:
The ignition delay is an important parameter which characterizes the initiation of combustion process and consequently its development in Diesel engines. This parameter mainly depends on chemical factors which are related to the fuel structure and its properties and also on physical factors which are related to the engine operating conditions. The need for alternative fuels usage in Diesel engines determined by the depletion of petroleum resources and by the regulations imposed on pollutant emissions have enforced the researches on renewable biofuels. Among these new fuels, biodiesel B7, actually in use, and biodiesel B20, in prospective, have received a particular interest. In this sense, an experimental and theoretical study was performed on a tractor Diesel engine aiming to determine the ignition delay of the rapeseed biodiesel B7 and B20 and to compare them with the ignition delay of pure Diesel fuel for full load and different engine speeds as tested operating conditions. This present study represents an extension of the previously mentioned research having now as objectives: to review what are the methods used for the ignition delay evaluation, to perform a comparison between several commonly Arrhenius type relationships used for the assessment of ignition delay and the ignition delay experimentally determined, and to offer a better understanding of the influences induced by the ignition delay respectively by the fuel reactivity on performance, efficiency and emissions of compression ignited engines operating with different Diesel-biodiesel fuels. The novelty of this work consists in the statistical approach to probability density of ignition delay which leads to better estimation of this crucial parameter and consequently to better control of the combustion process. (C) 2021 The Authors. Published by Elsevier Ltd.
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Authors:
Ing. Marek Brabec, Ph.D.; Konár, O.; Kasanický, I.; Malý, M.; Pelikán, E.
Published:
2020, APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY, 36 (1), p. 184-194), ISSN 1524-1904
Annotation:
Household consumption of natural gas is usually considered to be quite stable as cooking, space, and water heating belong to basic needs. The improvement of technologies together with possibilities of switching to alternative sources can, however, lead to a decreasing consumption trend. Knowing more about such trend, especially of its spatial distribution, can be useful for strategic planning. In this paper, we describe a general statistical methodology allowing to study the spatiotemporal behavior of consumption. It is based on semiparametric modeling. Formalized error and sensitivity analyses are part of the methodology. Presented methods are illustrated on large-scale data from the Czech Republic.
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Authors:
Broz, J.; Ing. Marek Brabec, Ph.D.; Kvapil, M.; Polak, J.
Published:
2018, Frontiers in Endocrinology, 9, ISSN 1664-2392
Annotation:
Bergmark et al. published a study dealing with the relationship of cardiovascular (CV) risks and adiponectin levels (1). The paper analyses the plasma levels of adiponectin in acute coronary syndrome type 2 diabetes patients (ACS) enrolled in the study EXAMINE (alogliptin vs. placebo, adiponectin sampled at study baseline) where they were monitored for CV outcomes (but not adiponectin) for a period of 18 months (2). Bergmark et al. conclude that adiponectin concentration was independently positively associated with increased risk of death from CV causes, all-cause mortality, and hospitalization for heart failure. In the introduction and the discussion, the authors mention that the relation between the adiponectin level and CV outcomes has been investigated in several studies, nevertheless with heterogeneous results: in some of them, adiponectin is associated with an increased CV risk, while others conclude that it is a protective factor. This study results rank adiponectin among factors that may increase CV risk in ACS type 2 diabetes patients.
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Authors:
Brož, J.; Holubová, A.; Vlasáková, M.; Mužík, J.; Ing. Marek Brabec, Ph.D.; Rahelić, D.
Published:
2018, Frontiers in Endocrinology, 9 (10.3389), ISSN 1664-2392
Annotation:
See the article "Glucose Self-monitoring in Non–Insulin-Treated Patients With Type 2 Diabetes in Primary Care Settings" in JAMA Intern Med, volume 177 on page 920. The articles published by Young et al. (1, 2) have presented the results and protocol of their Monitor Trial Study, comparing three approaches to self-monitoring of blood glucose (SMBG) to the subsequent outcome of their HbA1c metabolic control, by investigating 3 groups of type 2 diabetes mellitus (T2DM) patients treated with non-insulin antidiabetics, i.e., “no SMBG,” “once daily SMBG,” and “once daily SMBG with enhanced patient feedback” groups.
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Authors:
Broz, J.; Zd'arska, D.; Urbanova, J.; Ing. Marek Brabec, Ph.D.; Doničová, V.; Štěpánková, R.; Martinka, E.; Kvapil, M.
Published:
2018, Diabetes therapy : research, treatment and education of diabetes and related disorders, 9 (5), p. 1897-1906), ISSN 1869-6953
Annotation:
The aim of the study was to determine the level of metabolic control in type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM) patients in the Czech and Slovak Republics. A non-interventional prospective (observational) study was conducted from January 2015 until April 2016 in routine clinical practice settings at 141 centers in the Czech and Slovak Republics. Data were analyzed from a total of 425 patients with T1DM and 1034 patients with T2DM, proportionally corresponding to the number of patients in both countries. The primary objective of the study was to determine the percentage of patients with HbA1c < 7% (53 mmol/mol).
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Authors:
Broz, J.; Ing. Marek Brabec, Ph.D.; Lukac, O.; Zd'arska, D.; Kvapil, M.
Published:
2018, Primary Care Diabetes Europe, 12 (1), p. 92-92), ISSN 1751-9918
Annotation:
We read with interest the article by Rautio et al. which has been recently published online in the journal Primary Care Diabetes [1]. This article objectively quantifies the relationship between varying exposure to unemployment and impaired glucose metabolism, suggesting a relation of unemployment and type 2 diabetes in men. In our recent work [2] we have, through a different type of data (extensive population data from official registers, without a longitudinal structure), detected a relationship between unemployment and the incidence of diabetes in the Czech Republic.
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Authors:
Paulescu, M.; Badescu, V.; Ing. Marek Brabec, Ph.D.
Published:
2018, Theoretical and Applied Climatology Theoretical and Applied Climatology, 133 (1-2), p. 437-446), ISSN 0177-798X
Annotation:
Clouds play a key role in establishing the Earth's climate. Real cloud fields are very different and very complex in both morphological and microphysical senses. Consequently, the numerical description of the cloud field is a critical task for accurate climate modeling. This study explores the feasibility of retrieving the effective cloud field parameters (namely the cloud aspect ratio and cloud factor) from systematic radiometric measurements at high frequency (measurement is taken every 15 s). Two different procedures are proposed, evaluated, and discussed with respect to both physical and numerical restrictions. None of the procedures is classified as best; therefore, the specific advantages and weaknesses are discussed. It is shown that the relationship between the cloud shade and point cloudiness computed using the estimated cloud field parameters recovers the typical relationship derived from measurements.
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Authors:
Hunova, I.; Ing. Marek Brabec, Ph.D.; Malý, M.; Valerianova, A.
Published:
2018, The Science of the Total Environment, 636, p. 1490-1499), ISSN 0048-9697
Annotation:
We examined observation-based fog occurrence at three Czech monitoring sites: Praha 4 - Libus, Kosetice and Churanov, representing different environments - urban, rural and mountain - over a time span of 27 years (1989-2015). We searched for a simple model describing fog occurrence fitting the observed air pollution and meteorological data. For our analysis we used a generalized additive model, GAM, with (penalized) spline components to capture possible nonlinear and a priori unknown functional relationships. In order to cope with the binary nature of the data (indicators of fog presence on individual days), we employed a logistic regression GAM model fitted by a maximizing penalized likelihood (where the penalty coefficients were estimated via cross-validation). After testing several physically motivated models, being guided by AIC and physical interpretation of the components, we arrived at a model which uses the following explanatory variables: relative humidity, ambient SO2 concentrations, ambient NOx concentrations, air temperature and seasonality. All associations between the response and the analysed explanatory variables were highly significant. According to our results, the most important explanatory variables modelling the fog probability were relative humidity and air pollutants. Interestingly, we observed an increasing trend in fog occurrence at all three sites under review starting around the mid 2000s.
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Authors:
Mala, S.; Potockova, V.; Hoskovcova, L.; Pithova, P.; Ing. Marek Brabec, Ph.D.
Published:
2017, DIABETES RESEARCH AND CLINICAL PRACTICE, 134, p. 139-144), ISSN 0168-8227
Annotation:
Aims: Cardiac autonomic neuropathy (CAN) is a frequent and severe complication of type 1 diabetes mellitus (T1DM). CAN diagnosis is associated with increased cardiovascular morbidity and mortality, often due to progressive atherosclerosis. Carotid intima media thickness (CIMT) is a surrogate marker of the atherosclerosis. The aim of our study was to evaluate the relationship between CIMT and CAN in T1DM patients.
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Authors:
Aldhaidhawi, M.; Ing. Marek Brabec, Ph.D.; Lucian, M.; Chiriac, R.
Published:
2017, IOP Conference Series-Materials Science and Engineering - CAR2017 International Congress of Automotive and Transport Engineering - Mobility Engineering and Environment, Madeira, IOPscience), ISSN 1757-8981
Annotation:
The ignition delay period for a compression ignition engine fueled alternatively with pure diesel and with biodiesel B20 has been experimentally and numerically investigated. The engine was operated under full load conditions for two speeds, 1400 rpm speed for maximum brake torque and 2400 rpm speed for maximum brake power. Different parameters suggested as important to define the start of combustion have been considered before the acceptance of a certain evaluation technique of ignition delay. Correlations between these parameters were analyzed and concluded about the best method to identify the start of combustion. The experimental results were further compared with the ignition delay predicted by some correlations. The results showed that the determined ignition delays are in good agreement with those of the Arrhenius type expressions for pure diesel fuel, while for biodiesel B20 the correlation results are significantly different than the experimental results.
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Authors:
Hunova, I.; Ing. Marek Brabec, Ph.D.; Maly, M.; Knobova, V.
Published:
2017, Air Quality, Atmosphere & Health, 10 (2), p. 183-194), ISSN 1873-9318
Annotation:
We have investigated the association between heat waves and mortality and hospital admissions for Prague inhabitants for the summer heat waves of August 2003 and July 2006. The effect of heat waves was investigated using negative binomial regression in a generalized additive model. We used a linear model on a logarithmic scale, having 1-day lagged temperature differences from the long-term average, 1-day lagged ambient O-3 and PM10 concentration, relative humidity, simple "heat wave" indicator, and smooth seasonal effect as explanatory variables. We found a small increase in daily mortality for the examined period. This increase can be attributed to PM10 concentrations in most cases, and in fewer instances, to air temperature and O-3 concentrations. The "heat wave" indicator did not significantly increase the relative risk; the same held for the relative humidity. For the general unstratified population, the highest increase in relative risk of 1.072 (95% CI 1.001-1.147) was observed for cardiovascular mortality and was associated with an increase in temperature of 10 A degrees C, followed by an increase in relative risk of 1.056 (95% CI 1.025-1.087) for respiratory mortality associated with an increase in O-3 concentrations by 10 mu g.m(-3). A higher risk in most cases was found for women. A significant increase of relative risk of 1.013 (95 % CI 1.002-1.024) due to PM10 was found for hospital admissions for cardiovascular causes. This issue should be studied further in view of the anticipated increase in meteorological extremes, including heat waves, in the future, to prepare prevention plans for eliminating their negative effects as far as possible.
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Authors:
Ing. Marek Brabec, Ph.D.; Paulescu, M.; Badescu, V.
Published:
2017, Solar Energy, 153, p. 508-518), ISSN 0038-092X
Annotation:
The focus of this study is on the properties of consecutive intervals consisting of pairs of clear periods (the Sun is shining) and dark periods (the Sun is obscured by clouds). Namely, the distribution of the duration length of clear and dark periods is studied and illustrated with results obtained for the climatic regime of Timisoara (Romania, Eastern Europe). Usual simple moment-based characteristics such as means and variances cannot be unambiguously estimated due to censoring. Seasonal changes in the length distributions have been studied through the (nonparametric) Kaplan-Meier estimates. Both dark and clear duration distributions are different among months. The correlation between clear and dark periods within one dark-clear pair is of substantial interest. Therefore, a rigorous approach based on Spearman's rank correlation coefficient is used instead. The dependence of duration distribution upon covariates is studied using the Cox regression model, which fits the hazard ratio incurred by a unit change in the explanatory variables. It is shown that increasing the extraterrestrial irradiance on horizontal surface and the clearness index during dark/clear periods increases significantly the dark/clear period end risk. The Cox regression model enables more complicated analyses, such as the non-additive effects (i.e. interactions) of several covariates. The clearness index of a dark period (CID) has a much stronger effect than the extraterrestrial irradiance on horizontal surface of a dark period (EID) and the CID-EID interaction is still significant after the interactions when the months are included.
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Authors:
Paulescu, M.; Ing. Marek Brabec, Ph.D.; Boata, R.; Badescu, V.
Published:
2017, Energy, 121, p. 792-802), ISSN 0360-5442
Annotation:
Two advanced models for forecasting the output power of photovoltaic plants are discussed in details: a black-box Takagi-Sugeno fuzzy model and a physically inspired, semiparametric statistical model (Generalized Additive Model, GAM) based on smoothing splines. The structure of the two models, their strengths and weaknesses, are presented. The models performance is thoroughly compared with the performance of a simple linear model tested under the frame of the European Cooperation in Science and Technology (COST) Action "Weather Intelligence for Renewable Energies", as a benchmark used also in the forecasting exercise reported in Sperati et al. Energies 8 (2015) 9594. The models are used to forecasting the output power at time horizons of 1-72 h ahead. The data used during the COST competition are used here as input. The present study extends beyond the traditional evaluation of overall model accuracy. Detailed influences of seasonal effects, sun elevation angle and solar irradiance level upon the models performance are assessed. While the accuracy of the simple linear model is not entirely bad, it differs in important details from the two advanced forecasting models. The results show that a moderate, carefully chosen increase in model structure complexity can improve the predictive performance. Suitable penalty on model complexity can help both to enforce parsimony and improve practical forecasting abilities, to a certain extent. The physically inspired GAM comes out as the best performing model.
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Authors:
Vančura, V.; Wichterle, D.; Ulč, I.; Šmíd, J.; Ing. Marek Brabec, Ph.D.; Zárybnická, M.; Rokyta, R.
Published:
2017, Europace, 19 (4), p. 636-643), ISSN 1099-5129
Annotation:
Previous studies have demonstrated substantial variability in manual assessment of QRS complex duration (QRSd). Disagreements in QRSd measurements were also found in several automated algorithms tested on digitized electrocardiogram (ECG) recordings. The aim of our study was to investigate the variability of automated QRSd measurements performed by two commercially available electrocardiographs.
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