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Wyniki wyszukiwania dla: DATA-DRIVEN MODELLING
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Improved Uniform Sampling in Constrained Domains for Data-Driven Modelling of Antennas
PublikacjaData-driven surrogate modelling of antenna structures is an attractive way of accelerating the design process, in particular, parametric optimization. In practice, construction of surrogates is hindered by curse of dimensionality as well as wide ranges of geometry parameters that need to be covered in order to make the model useful. These difficulties can be alleviated by constrained performance-driven modelling with the surrogate...
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Low-cost data-driven modelling of microwave components using domain confinement and PCA-based dimensionality reduction
PublikacjaFast data-driven surrogate models can be employed as replacements of computationally demanding full-wave electromagnetic simulations to facilitate the microwave design procedures. Unfortunately, practical application of surrogate modelling is often hindered by the curse of dimensionality and/or considerable nonlinearity of the component characteristics. This paper proposes a simple yet reliable approach to cost-efficient modelling...
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Fundamentals of Data-Driven Surrogate Modeling
PublikacjaThe primary topic of the book is surrogate modeling and surrogate-based design of high-frequency structures. The purpose of the first two chapters is to provide the reader with an overview of the two most important classes of modeling methods, data-driven (or approx-imation), as well as physics-based ones. These are covered in Chap-ters 1 and 2, respectively. The remaining parts of the book give an exposition of the specific aspects...
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Dis/Trust and data-driven technologies
PublikacjaThis concept paper contextualises, defines, and systematises the concepts of trust and distrust (and their interrelations), providing a critical review of existing literature so as to identify gaps, disjuncture, and continuities in the use of these concepts across the social sciences and in the context of the consolidation of the digital society. Firstly, the development of the concept of trust is explored by looking at its use...
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Multilevel pharmacokinetics-driven modeling of metabolomics data
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Enhanced uniform data sampling for constrained data‐driven modeling of antenna input characteristics
PublikacjaData-driven surrogates are the most popular replacement models utilized in many fields of engineering and science, including design of microwave and antenna structures. The primary practical issue is a curse of dimensionality which limits the number of independent parameters that can be accounted for in the modelling process. Recently, a performance-driven modelling technique has been proposed where the constrained domain of the...
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3D MODELLING OF CYLINDRICAL-SHAPED OBJECTS FROM LIDAR DATA - AN ASSESSMENT BASED ON THEORETICAL MODELLING AND EXPERIMENTAL DATA
PublikacjaDespite the increasing availability of measured laser scanning data and their widespread use, there is still the problem of rapid and correct numerical interpretation of results. This is due to the large number of observations that carry similar information. Therefore, it is necessary to extract from the results only the essential features of the modelled objects. Usually, it is based on a process using filtration, followed by...
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Book review: Simulation-Driven Design Optimisation and Modelling for Microwave Engineering
PublikacjaCelem książki jest przedstawienie aktualnego stanu badań dotyczących projektowania układów mikrofalowych poprzez modelowanie i optymalizacje wspomagane symulacjami elektromagnetycznymi. Grupa międzynarodowych ekspertów zajmujących się rożnymi aspektami komputerowo wspomaganego projektowania układów mikrofalowych, podsumowuje i dokonuje przeglądu ostatnich osiągnięć w tej dziedzinie oraz przedstawia szereg praktycznych zastosowań....
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Sensor data fusion techniques for environment modelling
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Application of mechanistic and data-driven models for nitrogen removal in wastewater treatment systems
PublikacjaIn this dissertation, the application of mechanistic and data-driven models in nitrogen removal systems including nitrification and deammonification processes was evaluated. In particular, the influential parameters on the activity of the Nitrospira activity were assessed using response surface methodology (RSM). Various long-term biomass washout experiments were operated in two parallel sequencing batch reactor (SBR) with a different...
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Data-driven, probabilistic model for attainable speed for ships approaching Gdańsk harbour
PublikacjaThe growing demand for maritime transportation leads to increased traffic in ports. From this arises the need to observe the consequences of the specific speed ships reach when approaching seaports. However, usually the analyzed cases refer only to the statistical evaluation of the studied phenomenon or to the empirical modelling, ignoring the mutual influence of variables such as ship type, length or weather conditions. In this...
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International Journal of Data Mining Modelling and Management
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Low-Cost Data-Driven Surrogate Modeling of Antenna Structures by Constrained Sampling
PublikacjaFull-wave electromagnetic (EM) analysis has become one of the major design tools for contemporary antenna structures. Although reliable, it is computationally expensive which makes automated simulation-driven antenna design (e.g., parametric optimization) difficult. This difficulty can be alleviated by utilization of fast and accurate replacement models (surrogates). Unfortunately, conventional data-driven modeling of antennas...
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Data-Driven Modeling of Mechanical Properties of Fiber-Reinforced Concrete: A Critical Review
PublikacjaFiber-reinforced concrete (FRC) is extensively used in diverse structural engineering applications, and its mechanical properties are crucial for designing and evaluating its performance. The compressive, flexural, splitting tensile, and shear strengths of FRCs are among the most important attributes, which have been discussed more extensively than other properties. The accurate prediction of these properties, which are required...
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Urban Freight Transport Demand Modelling and Data Availability Constraints
PublikacjaThe paper provides a review of urban freight transport demand modelling approaches confronted with constrains regarding adequate data provision from a perspective of the local authorities. Demand estimation models has been selected as a reference because they are the most representative in terms of inclusion of urban freight indicators which can be transformed into a decision-support tool for evaluation of freight measures. The...
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Low-cost performance-driven modelling of compact microwave components with two-layer surrogates and gradient kriging
PublikacjaUtilization of electromagnetic (EM) simulation tools has become indispensable for reliable evaluation of microwave components. As the cost of an individual analysis may already be considerable, the computational overhead associated with EM-driven tasks that require massive simulations (e.g., optimization) may turn prohibitive. One of mitigation methods is the employment of equivalent network models. Yet, they are incapable of accounting...
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Data-Driven Surrogate-Assisted Optimization of Metamaterial-Based Filtenna Using Deep Learning
PublikacjaIn this work, a computationally efficient method based on data driven surrogate models is pro-posed for the design optimization procedure of a Frequency Selective Surface (FSS)-based filtering antenna (Filtenna). A Filtenna acts as a as module that simultaneously pre-filters unwanted sig-nals, and enhances the desired signals at the operating frequency. However, due to a typically large number of design variables of FSS unit elements,...
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A Data Driven Model for Predicting RNA-Protein Interactions based on Gradient Boosting Machine
PublikacjaRNA protein interactions (RPI) play a pivotal role in the regulation of various biological processes. Experimental validation of RPI has been time-consuming, paving the way for computational prediction methods. The major limiting factor of these methods has been the accuracy and confidence of the predictions, and our in-house experiments show that they fail to accurately predict RPI involving short RNA sequences such as TERRA RNA....
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Buried Object Characterization by Data-Driven Surrogates and Regression-Enabled Hyperbolic Signature Extraction
PublikacjaThis work addresses artificial-intelligence-based buried object characterization using FDTD-based electromagnetic simulation toolbox of a Ground Penetrating Radar (GPR) to generate B-scan data. In data collection, FDTD-based simulation tool, gprMax is used. The task is to estimate geophysical parameters of a cylindrical shape object of various radii, buried at different positions in the dry soil medium simultaneously and independently...
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Towards High-Value Datasets Determination for Data-Driven Development: A Systematic Literature Review
PublikacjaOpen government data (OGD) is seen as a political and socio-economic phenomenon that promises to promote civic engagement and stimulate public sector innovations in various areas of public life. To bring the expected benefits, data must be reused and transformed into value-added products or services. This, in turn, sets another precondition for data that are expected to not only be available and comply with open data principles,...
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A Data Driven Model for Predicting RNA-Protein Interactions based on Gradient Boosting Machine
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Modelling of Capillary Pressure-driven Water Flow in Unsaturated Concrete Using Coupled DEM/CFD Approach.
PublikacjaSformułowano nowatorskie, połączone podejście do modelowania dwufazowego przepływu wody napędzanego kapilarami w nienasyconym betonie. Dzięki połączeniu metody elementów dyskretnych (DEM) z obliczeniową dynamiką płynów (CFD) w warunkach izotermicznych proces został zbadany numerycznie w mezoskali w warunkach dwuwymiarowych. Niewielkie próbki betonu o uproszczonej mezostrukturze cząstek poddano w pełni sprzężonym hydromechanicznym...
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Collective citizens' behavior modelling with support of the Internet of Things and Big Data
PublikacjaIn this paper, collective human behaviors are modelled by a development of Big Data mining related to the Internet of Things. Some studies under MapReduce architectures have been carried out to improve an efficiency of Big Data mining. Intelligent agents in data mining have been analyzed for smart city systems, as well as data mining has been described by genetic programming. Furthermore, artificial neural networks have been discussed...
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Buried Object Characterization Using Ground Penetrating Radar Assisted by Data-Driven Surrogate-Models
PublikacjaThis work addresses artificial-intelligence-based buried object characterization using 3-D full-wave electromagnetic simulations of a ground penetrating radar (GPR). The task is to characterize cylindrical shape, perfectly electric conductor (PEC) object buried in various dispersive soil media, and in different positions. The main contributions of this work are (i) development of a fast and accurate data driven surrogate modeling...
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Fast multi-objective optimization of antenna structures by means of data-driven surrogates and dimensionality reduction
PublikacjaDesign of contemporary antenna structures needs to account for several and often conflicting objectives. These are pertinent to both electrical and field properties of the antenna but also its geometry (e.g., footprint minimization). For practical reasons, especially to facilitate efficient optimization, single-objective formulations are most often employed, through either a priori preference articulation, objective aggregation,...
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Cost‐efficient performance‐driven modelling of multi‐band antennas by variable‐fidelity electromagnetic simulations and customized space mapping
PublikacjaElectromagnetic (EM) simulations have become an indispensable tool in the design of contemporary antennas. EM‐driven tasks, for example, parametric optimization, entail considerable computational efforts, which may be reduced by employing surrogate models. Yet, data‐driven modelling of antenna characteristics is largely hindered by the curse of dimensionality. This may be addressed using the recently reported domain‐confinement...
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Brain perfusion imaging with the use of parametric modelling basing on DSC-MRI data
PublikacjaW pracy do estymacji parametrów perfuzji mózgu: przepływu krwi mózgowej (cerebral blood flow, CBF), objętości krwi mózgowej (cerebral blood volume, CBV) oraz średniego czasu przejścia (mean transit time, MTT) wykorzystano pomiary DSC-MRI (Dynamic Susceptibility Contrast Magnetic Resonance Imaging). W modelowaniu danych MRI zastoswoano model trzykompartmentowy. Przedstawiono i porównano dwa podejścia do identyfikacji modelu różniące...
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Application of data driven methods in diagnostic of selected process faults of nuclear power plant steam turbine
PublikacjaArticle presents a comparison of process anomaly detection in nuclear power plant steam turbine using combination of data driven methods. Three types of faults are considered: water hammering, fouling and thermocouple fault. As a virtual plant a nonlinear, dynamic, mathe- matical steam turbine model is used. Two approaches for fault detection using one class and two class classiers are tested and compared.
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Data-driven models for fault detection using kernel pca:a water distribution system case study
PublikacjaKernel Principal Component Analysis (KPCA), an example of machine learning, can be considered a non-linear extension of the PCA method. While various applications of KPCA are known, this paper explores the possibility to use it for building a data-driven model of a non-linear system-the water distribution system of the Chojnice town (Poland). This model is utilised for fault detection with the emphasis on water leakage detection....
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Identification of High-Value Dataset determinants: is there a silver bullet for efficient sustainability-oriented data-driven development?
PublikacjaOpen Government Data (OGD) are seen as one of the trends that has the potential to benefit the economy, improve the quality, efficiency, and transparency of public administration, and change the lives of citizens, and the society as a whole facilitating efficient sustainability-oriented data-driven services. However, the quick achievement of these benefits is closely related to the “value” of the OGD, i.e., how useful, and reusable...
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Reliable data-driven modeling of high-frequency structures by means of nested kriging with enhanced design of experiments
PublikacjaData-driven (or approximation) surrogate models have been gaining popularity in many areas of engineering and science, including high-frequency electronics. They are attractive as a way of alleviating the difficulties pertinent to high computational cost of evaluating full-wave electromagnetic (EM) simulation models of microwave, antenna, and integrated photonic components and devices. Carrying out design tasks that involve massive...
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Data-driven models for fault detection using kernel PCA: A water distribution system case study
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O-43 Data-driven selection of active iEEG channels during verbal memory task performance
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Influence of input data on airflow network accuracy in residential buildings with natural wind - and stack - driven ventilation.
PublikacjaW artykule omówiono wpływ danych wejściowych na dokładność modelu przepływu sieciowego powietrza w budynkach mieszkalnych z naturalną i kominową wentylacją. Zastosowano połączony model AFN-BES. Wyniki numeryczne omówiono dla 8 różnych przypadków z różnymi danymi ciśnienia wiatru. Wyniki pokazały, że ogromny wpływ danych wejściowych dotyczących ciśnienia wiatru na wyniki numeryczne.
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Advances in Modelling and Analysis B: Signals, Information, Data, Patterns
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Parametric versus nonparametric modelling of dynamic susceptibility contrast enhanced MRI based data
PublikacjaDynamic tracking of a bolus of a paramagnetic agent (dynamic susceptibility contract - DSC) in MRI (magnetic resonance imaging) measurements is successfully used for assessment of the tissue perfusion and the other features and functions of the brain (i.e. cerebral blood flow - CBF, cerebral blood volume - CBV, mean transit time - MTT). The parametric and nonparametric approaches to the identification of MRI models are presented...
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N-way modelling of sediment monitoring data from Mar Menor lagoon, Spain
PublikacjaW artykule przedstawiono zastosowanie modelowania typu Tucker3 dla danych pochodzących z monitorowania chemizmu osadów obszaru laguny Mar Menor w Hiszpanii. Celem badania jest modelowanie i interpretacja frakcjonowania metali ciężkich w materii zawieszonej i frakcjach osadów wynikających z procesów sedymentacyjnych. Modelowanie ma na celu oszacowanie ryzyka środowiskowego ponieważ działalność ludzka ma znaczny wpływ na stan laguny....
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Fast multi-objective design optimization of microwave and antenna structures using data-driven surrogates and domain segmentation
PublikacjaPurpose Strategies and algorithms for expedited design optimization of microwave and antenna structures in multi-objective setup are investigated. Design/methodology/approach Formulation of the multi-objective design problem oriented towards execution of the population-based metaheuristic algorithm within the segmented search space is investigated. Described algorithmic framework exploit variable fidelity modeling, physics- and...
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Modelling hydraulic and capillary-driven two-phase fluid flow in unsaturated concretes at the meso-scale with a unique coupled DEM-CFD technique
PublikacjaThe goal of the research was to demonstrate the impact of thin porous interfacial transition zones (ITZs) between aggregates and cement matrix on fluid flow in unsaturated concrete caused by hydraulic/capillary pressure. To demonstrate this impact, a novel coupled approach to simulate the two-phase (water and moist air) flow of hydraulically and capillary-driven fluid in unsaturated concrete was developed. By merging the discrete...
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REVERSE MODELLING OF MICROSEISMIC WAVES PROPAGATION FOR THE INTERPRETATION OF THE DATA FROM HYDRAULIC FRACTURING MONITORING IN POLAND
PublikacjaA hydraulic fracturing job was performed to stimulate gas flow from a horizontal wellbore located in Poland. The whole operation was overseen by means of microseismic monitoring. For this purpose, an array of 12000 geophones was deployed on ground in form of patches distributed unevenly in a region of 4km from the wellbore. The array was constantly recording seismic signals during whole fracturing processed. Such recorded signals...
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Performance and Emission Modelling and Simulation of Marine Diesel Engines using Publicly Available Engine Data
PublikacjaTo analyse the behaviour of marine diesel engines in unsteady states for different purposes, for example to determine the fuel consumption or emissions level, to adjust the control strategy, to manage the maintenance, etc., a goal-based mathematical model that can be easily implemented for simulation is necessary. Such a model usually requires a wide range of operating data, measured on a test stand. This is a time-consuming process...
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Heavy Duty Vehicle Fuel Consumption Modelling Based on Exploitation Data by Using Artificial Neural Networks
PublikacjaOne of the ways to improve the fuel economy of heavy duty trucks is to operate the combustion engine in its most efficient operating points. To do that, a mathematical model of the engine is required, which shows the relations between engine speed, torque and fuel consumption in transient states. In this paper, easy accessible exploitation data collected via CAN bus of the heavy duty truck were used to obtain a model of a diesel...
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Deterministic versus stochastic modelling of unsaturated flow in a sandy field soil based on dual tracer breakthrough data
PublikacjaThe 216 km2 Neuenhagen Millcreeck catchment can be characterized as a drought sensitive landscape in NE Germany. It is therefore a fundamental human interest to understand how water that fell as precipitation moves through the unsaturated soils and recharges groundwater. Additionally, a better knowledge of nutrient transport from soil to groundwater is important also, especially in landscapes with light sandy soils. For a better...
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Least square spline modelling along with tin decimation for 3D seafloor mapping from multibeam sonar data.
PublikacjaPrzedstawiono wyniki prac związane z zastosowaniem algorytmu aproksymacyjnego minimalnokwadratowego do wizualizacji danych wysokorozdzielczych pochodzących z sonaru wielowiązkowego. Metoda pozwala na redukcję danych oraz łatwą ich modyfikację.
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Data accompanying the paper: Zarach and Parteka (2023), Export diversification and dependence on natural resources , Economic Modelling (Elsevier), 126 (2023) 106436.
Dane BadawczeThe folder contains the data and codes used in the analysis described in the paper: Zarach Z.H., Parteka A. (2023). Export diversification and dependence on natural resources. Economic Modelling Volume 126, September 2023, 106436.
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International Conference on Informatics & Data-Driven Medicine
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International Workshop on Domain Driven Data Mining
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International Workshop on Modelling and Visualization of XML and Semantic Web Data
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Knowledge management driven leadership, culture and innovation success – an integrative model
PublikacjaPurpose – This article examines the relation between knowledge management (KM) driven leadership, culture and innovation success of knowledge-intensive small and medium sized companies. By building on the previously reported research on leadership, culture, innovation, and knowledge management, we synergistically integrated KM-driven leadership and innovation success while exploring the meditational role of culture in that. Design/methodology/approach...
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A probabilistic-driven framework for enhanced corrosion estimation of ship structural components
PublikacjaThe work proposes a probabilistic-driven framework for enhanced corrosion estimation of ship structural components using Bayesian inference and limited measurement data. The new approach for modelling measurement uncertainty is proposed based on the results of previous corrosion tests that incorporate the non-uniform character of the corroded surface of structural components. The proposed framework's basic features are outlined,...