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Hybrid evaluation of the industrial global impact on Mexican aquifers under uncertain criteria evaluations
Flores Casamayor, H.; Carpitella, Silvia; Izquierdo, J.; Mora-Rodríguez, J.; Delgado-Galván, X.
2022 - anglický
The present paper proposes an integrated methodological approach to address the problem of managing five aquifers of Guanajuato state, Mexico, according to such relevant criteria as environmental, social, economic and hydrological aspects. The goal of this research consists in formalizing a structured framework to first evaluate the various degrees of importance of criteria and to secondly get a classification of aquifers by minimizing uncertainty of evaluations. To such an aim, the Analytic Hierarchy Process (AHP) is used for calculating the vector of criteria weights, while the Fuzzy Logic (FL) theory supports in deriving quantitative evaluations of aquifers under each selected criterion. The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is then proposed to formalize the final ranking of aquifers, something that will be helpful to understand which alternative matches all the differently weighted criteria in the most suitable way at a practical level. In such a way, getting a comprehensive and strategic overview about the problem of interest will be possible.
Klíčová slova:
Analytic Hierarchy Process (AHP); Fuzzy Logic (FL) theory; Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS)
Dokument je dostupný na externích webových stránkách.
Hybrid evaluation of the industrial global impact on Mexican aquifers under uncertain criteria evaluations
The present paper proposes an integrated methodological approach to address the problem of managing five aquifers of Guanajuato state, Mexico, according to such relevant criteria as environmental, ...
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Zitová, Barbara; Šorel, Michal
2022 - český
Přednáška si klade za cíl seznámit odbornou veřejnost s aktivitami oddělení Zpracování obrazové informace ÚTIA AV ČR v.v.i. v oblasti analýz dat projektu Copernicus. Oddělení se dlouhodobě zabývá vývojem metod digitálního zpracování obrazu a hlubokého učení. Během posledních dvou let vzniklo několik demonstračních studentských prací ve spolupráci s MFF UK a FJFI ČVUT využívajících data z družic Sentinel, jako například rozpoznávání typů plodin z časových řad snímků ze satelitu Sentinel-2, automatická segmentace oblastí podle způsobu využití či typu povrchu pomocí metod strojového učení, přesnější detekce mraků v datech ze Sentinel-2, ve spolupráci s Ústavem pro hydrodynamiku AV ČR postupy pro odhad vlhkosti povrchové vrstvy krajiny z dat družice Sentinel-2 a zvyšování rozlišení tepelných dat Sentinel-3 pomocí metod hlubokého učení. V druhé části budou přiblíženy možnosti aplikace metod vyvinutých pro jiné oblasti (separace zdrojů \ninformace) v DPZ. The lecture aims to introduce the activities of the Image Processing Department of the Institute of Image Information of the CAS in the field of Copernicus data analysis to the professional public. The department has long been involved in the development of digital image processing and deep learning methods. During the last two years, in cooperation with the MFF UK and FJFI CTU, several student demonstration projects using data from Sentinel satellites have been finished, such as crop type recognition from Sentinel-2 time-series images, automatic segmentation of areas by land use or surface type using machine learning methods learning, more accurate cloud detection in Sentinel-2 data, in collaboration with the Institute of Hydrodynamics of the CAS Czech Republic, procedures for estimating landscape surface moisture from Sentinel-2 data and increasing the resolution of Sentinel-3 thermal data using deep learning methods. The second part will present the application of developed methods for other areas in remote sensing.
Klíčová slova:
remote sensing; satellite imaging; machine learning
Dokument je dostupný na externích webových stránkách.
Jak to v těch datech najít?
Přednáška si klade za cíl seznámit odbornou veřejnost s aktivitami oddělení Zpracování obrazové informace ÚTIA AV ČR v.v.i. v oblasti analýz dat projektu Copernicus. Oddělení se dlouhodobě zabývá ...
On a class of biped underactuated robot models with upper body: Sensitivity analysis of the walking performance
Papáček, Štěpán; Polach, P.; Prokýšek, R.; Anderle, Milan
2022 - anglický
Biped underactuated robots with an upper body (being a torso) form a subclass of legged robots. This study deals with the walking performance of such class of legged robot models and has been motivated by the need to implement of the previously developed sensor and control algorithms for the real-time movement of the laboratory walking robot, designed and built at the Department of Control Theory of the Institute of Information Theory and Automation (UTIA) of the Czech Academy of Sciences, see Fig. 1 (left). A detailed description of this underactuated walking-like mechanical system (called further UTIA Walking Robot – UWR) is provided in [2] and [5]. The simplest underactuated walking robot hypothetically able to walk is the so-called Compass gait biped walker, alternatively called the Acrobot, see Fig. 1 (right). For a review of underactuated mechanical systems, i.e. systems with fewer actuators than degrees of freedom, which encounter many applications in different fields (e.g., in robotics, in aeronautical and spatial systems, in marine and underwater systems, and in-flexible and mobile systems), see [3]. As follows, we examine the walking performance of parametrized models for different walking regimes and different values of model parameters. More specifically, the sensitivity analysis (i.e., parameter study) of the walking performance with respect to certain design variables (model parameters) is carried out using the software package alaska/MultibodyDynamics. The main attention is attracted to the role of the upper body mass m3 and position lc3, see Fig. 1 (right). Last but not least, having surveyed the mechanics of planar biped robots, our subsequent goal is the analysis of a 3D biped model where lateral balance is either controlled, suppressed or compensated.
Klíčová slova:
Walking robot; ALASCA; Simulation
Dokument je dostupný na externích webových stránkách.
On a class of biped underactuated robot models with upper body: Sensitivity analysis of the walking performance
Biped underactuated robots with an upper body (being a torso) form a subclass of legged robots. This study deals with the walking performance of such class of legged robot models and has been ...
Recursive mixture estimation with univariate multimodal Poisson variable
Uglickich, Evženie; Nagy, Ivan
2022 - anglický
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.
Klíčová slova:
recursive mixture estimation; mixture of Poisson distributions; clustering and classification
Dokument je dostupný na externích webových stránkách.
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, ...
Macroeconomic Responses of Emerging Market Economies to Oil Price Shocks: Analysis by Region and Resource Profile
Togonidze, S.; Kočenda, Evžen
2022 - anglický
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
Klíčová slova:
Emerging market economies; Oil shocks; GDP; Markov-switching; Exchange rate; Oil exporters; Metal exporters
Dokument je dostupný na externích webových stránkách.
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 ...
Probabilistic representation of spatial fuzzy sets
Soukup, Lubomír
2022 - anglický
Membership function of a given fuzzy set is expressed by probability that a point belongs in the fuzzy set. Such a membership function is derived from probability distribution of points on the boundary of the fuzzy set. Polygonal boundary is considered. Spatial operations (conjunction, disjunction, complement) are defined accordingly. Several application areas are mentioned, namely classification of land cover, cadastral mapping, material quality analysis, interferometric monitoring of bridges.
Klíčová slova:
fuzzy set theory; probability theory; uncertainty; geographic information system
Dokument je dostupný na externích webových stránkách.
Probabilistic representation of spatial fuzzy sets
Membership function of a given fuzzy set is expressed by probability that a point belongs in the fuzzy set. Such a membership function is derived from probability distribution of points on the ...
Yield Curve Dynamics and Fiscal Policy Shocks
Kučera, A.; Kočenda, Evžen; Maršál, Aleš
2022 - anglický
We show that government spending does play a role in shaping the yield curve which has important consequences for the cost of private and government financing. We combine government spending shock identification strategies from the fiscal macro literature with recent advancements in no-arbitrage affine term structure modeling, where we account for time-varying macroeconomic trends in inflation and the equilibrium real interest rate. We stress in our empirical macro-finance framework the importance of timing in the response of yields to government spending. We find that the yield curve responds positively but mildly to a surprise in government spending shocks where the rise in risk-neutral yields is compensated by a drop in nominal term premia. The news shock in expectations about future expenditures decreases yields across all maturities. Complementarily, we also analyze the effect of fiscal policy uncertainty where higher fiscal uncertainty lowers yields.
Klíčová slova:
Government Expenditures; Fiscal policy; U.S. Treasury Yield Curve; Affine Term Structure Model
Dokument je dostupný na externích webových stránkách.
Yield Curve Dynamics and Fiscal Policy Shocks
We show that government spending does play a role in shaping the yield curve which has important consequences for the cost of private and government financing. We combine government spending shock ...
Characterizing Uncertainty In Decision-Making Models For Maintenance In Industry 4.0
Ahmed, U.; Carpitella, Silvia; Certa, A.
2022 - anglický
Decision-making involves our daily life at any level, something that entails uncertainty and potential occurrence of risks of varied nature. When dealing with industrial engineering systems, effective decisions are fundamental in terms of maintenance planning and implementation. Specifically, several forms of uncertainty may affect decision-making procedures, for which adopting suitable techniques seems to be a good strategy to attain the main maintenance goals by taking into account system criticality along with decision-maker(s) opinions. A wide variety of factors contributes to uncertainty, being some of them greatly important while other ones less significant. However, all of these factors in synergy can impact the functioning of systems in a positive, neutral, or negative way. In this case, the question is whether obtaining a complete picture of such uncertainty can improve decision-making capabilities and mitigate both through-life costs and unforeseen problems. The fundamental issues include dealing with ambiguity in the maintenance decision-making process by employing numerous evaluation criteria and dealing with real-world scenarios in the maintenance environment. In this study, the Multi-Criteria Decision-Making (MCDM) approach is analysed, with particular reference to the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS), technique capable to effectively rank alternatives while dealing with uncertainty for maintenance decision-making. A final case study is developed to demonstrate the applicability of the method to the field of maintenance in industry 4.0. The proposed study may be useful in supporting intelligent and efficient decisions resulting in favorable maintenance outcomes.
Klíčová slova:
Decision-Making; Uncertainty; Industry 4.0
Dokument je dostupný na externích webových stránkách.
Characterizing Uncertainty In Decision-Making Models For Maintenance In Industry 4.0
Decision-making involves our daily life at any level, something that entails uncertainty and potential occurrence of risks of varied nature. When dealing with industrial engineering systems, effective ...
Computing the Decomposable Entropy of Graphical Belief Function Models
Jiroušek, Radim; Kratochvíl, Václav; Shenoy, P. P.
2022 - anglický
In 2018, Jiroušek and Shenoy proposed a definition of entropy for Dempster-Shafer (D-S) belief functions called decomposable entropy. Here, we provide an algorithm for computing the decomposable entropy of directed graphical D-S belief function models. For undirected graphical belief function models, assuming that each belief function in the model is non-informative to the others, no algorithm is necessary. We compute the entropy of each belief function and add them together to get the decomposable entropy of the model. Finally, the decomposable entropy generalizes Shannon’s entropy not only for the probability of a single random variable but also for multinomial distributions expressed as directed acyclic graphical models called Bayesian networks.
Klíčová slova:
Decomposable Entropy; DempsterShafer belief functions; Bayesian networks
Dokument je dostupný na externích webových stránkách.
Computing the Decomposable Entropy of Graphical Belief Function Models
In 2018, Jiroušek and Shenoy proposed a definition of entropy for Dempster-Shafer (D-S) belief functions called decomposable entropy. Here, we provide an algorithm for computing the decomposable ...
Classes of Conflictness / Non-Conflictness of Belief Functions
Daniel, Milan; Kratochvíl, Václav
2022 - anglický
Theoretic, descriptive and experimental analysis and description of classes of conflictness, non-conflictness and of conflict hiddeness of belief functions. Theoretic extension of theory of hidden conflicts. Idea of catalogue of belief structures.
Klíčová slova:
belief functions; theory of hidden conflicts; classes of conflictness
Dokument je dostupný na externích webových stránkách.
Classes of Conflictness / Non-Conflictness of Belief Functions
Theoretic, descriptive and experimental analysis and description of classes of conflictness, non-conflictness and of conflict hiddeness of belief functions. Theoretic extension of theory of hidden ...
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