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Wyniki wyszukiwania dla: DATA-DRIVEN MODELING
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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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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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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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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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Multilevel pharmacokinetics-driven modeling of metabolomics data
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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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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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Performance-Driven Surrogate Modeling of High-Frequency Structures
PublikacjaThe development of modern high-frequency structures, including microwave and antenna components, heavily relies on full-wave electromagnetic (EM) simulation models. Notwithstanding, EM-driven design entails considerable computational expenses. This is especially troublesome when solving tasks that require massive EM analyzes, parametric optimization and uncertainty quantification be-ing representative examples. The employment of...
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Knowledge-based performance-driven modeling of antenna structures
PublikacjaThe importance of surrogate modeling techniques in the design of modern antenna systems has been continuously growing over the recent years. This phenomenon is a matter of practical necessity rather than simply a fashion. On the one hand, antenna design procedures rely on full-wave electromagnetic (EM) simulation tools. On the other hand, the computational costs incurred by repetitive EM analyses involved in solving common tasks...
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Performance‐driven modeling of compact couplers in restricted domains
PublikacjaFast surrogate models can play an important role in reducing the cost of EM-driven design closure of miniaturized microwave components. Unfortunately, construction of such models is challenging due to curse of dimensionality and wide range of geometry parameters that need to be included in order to make it practically useful. In this letter, a novel approach to design-oriented modeling of compact couplers is presented. Our method...
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Accurate simulation-driven modeling and design optimization of compact microwave structures
PublikacjaCost efficient design optimization of microwave structures requires availability of fast yet reliable replacement models so that multiple evaluations of the structure at hand can be executed in reasonable timeframe. Direct utilization of full-wave electromagnetic (EM) simulations is often prohibitive. On the other hand, accurate data-driven modeling normally requires a very large number of training points and it is virtually infeasible...
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Recent Advances in Performance-Driven Surrogate Modeling of High-Frequency Structures
PublikacjaDesign of high‐frequency structures, including microwave and antenna components, heavily relies on full‐wave electromagnetic (EM) simulation models. Their reliability comes at a price of a considerable computational cost. This may lead to practical issues whenever numerous EM analyses are to be executed, e.g., in the case of parametric optimization. The difficulties entailed by massive simulations may be mitigated by the use of...
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Performance-Driven Inverse/Forward Modeling of Antennas in Variable-Thickness Domains
PublikacjaDesign of contemporary antenna systems is a challenging endeavor. The difficulties are partially rooted in stringent specifications imposed on both electrical and field characteristics, demands concerning various functionalities, but also constraints imposed upon the physical size of the radiators. Furthermore, conducting the design process at the level of full-wave electromagnetic (EM) simulations, otherwise dictated by reliability,...
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Rapid EM-driven antenna dimension scaling through inverse modeling
PublikacjaIn this letter, a computationally feasible technique for dimension scaling of antenna structures is introduced. The proposed methodology is based on inverse surrogate modeling where the geometry parameters of the antenna structure of interest are explicitly related to the operating frequency. The surrogate model is identified based on a few antenna designs optimized for selected reference frequencies. For the sake of computational...
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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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Simulation-Driven Antenna Modeling by Means of Response Features and Confined Domains of Reduced Dimensionality
PublikacjaIn recent years, the employment of full-wave electromagnetic (EM) simulation tools has become imperative in the antenna design mainly for reliability reasons. While the CPU cost of a single simulation is rarely an issue, the computational overhead associated with EM-driven tasks that require massive EM analyses may become a serious bottleneck. A widely used approach to lessen this cost is the employment of surrogate models, especially...
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Improved Modeling of Microwave Structures Using Performance-Driven Fully-Connected Regression Surrogate
PublikacjaFast replacement models (or surrogates) have been widely applied in the recent years to accelerate simulation-driven design procedures in microwave engineering. The fundamental reason is a considerable—and often prohibitive—CPU cost of massive full-wave electromagnetic (EM) analyses related to solving common tasks such as parametric optimization or uncertainty quantification. The most popular class of surrogates are data-driven...
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On Inadequacy of Sequential Design of Experiments for Performance-Driven Surrogate Modeling of Antenna Input Characteristics
PublikacjaDesign of contemporary antennas necessarily involves electromagnetic (EM) simulation tools. Their employment is imperative to ensure evaluation reliability but also to carry out the design process itself, especially, the adjustment of antenna dimensions. For the latter, traditionally used parameter sweeping is more and more often replaced by rigorous numerical optimization, which entails considerable computational expenses, sometimes...
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Recent Developments in Data-Assisted Modeling of Flexible Proteins
PublikacjaMany proteins can fold into well-defined conformations. However, intrinsically-disordered proteins (IDPs) do not possess a defined structure. Moreover, folded multi-domain proteins often digress into alternative conformations. Collectively, the conformational dynamics enables these proteins to fulfill specific functions. Thus, most experimental observables are averaged over the conformations that constitute an ensemble. In this...
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M-Split Estimation in Laser Scanning Data Modeling
PublikacjaPublikacja traktuje o wykorzystaniu estymacji M-Split do modelowania danych pozyskanych w wyniku skaningu laserowego. Autorzy prezentują rozwiązanie w oparciu o detekcję krawędzi dwóch płaszczyzn.
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Weather Hazard Avoidance in Modeling Safety of Motor-Driven Ship for Multicriteria Weather Routing
PublikacjaWeather routing methods find the most suitable ocean?s route for a vessel, taking into account changeable weather conditions and navigational constraints. In the multicriteria approach based on the evolutionary SPEA algorithm one is able to consider a few constrained criteria simultaneously. The approach applied for a ship with hybrid propulsions has already been presented by one of the authors on previous TransNav?2009. This time...
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Nonlinear planar modeling of massive taut strings travelled by a force-driven point-mass
PublikacjaThe planar response of horizontal massive taut strings, travelled by a heavy point-mass, either driven by an assigned force, or moving with an assigned law, is studied. A kinematically exact model is derived for the free boundary problem via a variational approach, accounting for the singularity in the slope of the deflected string. Reactive forces exchanged between the point-mass and the string are taken into account via Lagrange...
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Weather Hazard Avoidance in Modeling Safety of Motor-driven Ship for Multicriteria Weather Routing
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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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A Data-Driven Comparative Analysis of Machine-Learning Models for Familial Hypercholesterolemia Detection
PublikacjaThis study presents an assessment of familial hypercholesterolemia (FH) probability using different algorithms (CatBoost, XGBoost, Random Forest, SVM) and its ensembles, leveraging electronic health record data. The primary objective is to explore an enhanced method for estimating FH probability, surpassing the currently recommended Dutch Lipid Clinic Network (DLCN) Score. The models were trained using the largest Polish cohort...
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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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Open Data Capability Architecture - An Interpretive Structural Modeling Approach
PublikacjaDespite of increasing availability of open data as a vital organizational resource, large numbers of startups and organizations fail when it comes to utilizing open data effectively. This shortcoming is attributable to the poor understanding of what types of capabilities are required to successfully conduct data related activities. At the same time, research on open data capabilities and how they relate to one another remains sparse....
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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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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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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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A coarse‐grained approach to NMR ‐data‐assisted modeling of protein structures
PublikacjaThe ESCASA algorithm for analytical estimation of proton positions from coarse-grained geometry developed in our recent work has been implemented in modeling protein structures with the highly coarse-grained UNRES model of polypeptide chains (two sites per residue) and nuclear magnetic resonance (NMR) data. A penalty function with the shape of intersecting gorges was applied to treat ambiguous distance restraints, which automatically...
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Expedited Acquisition of Database Designs for Reduced-Cost Performance-Driven Modeling and Rapid Dimension Scaling of Antenna Structures
PublikacjaFast replacement models have been playing an increasing role in high-frequency electronics, including the design of antenna structures. Their role is to improve computational efficiency of the procedures that normally entail large numbers of expensive full-wave electromagnetic (EM) simulations, e.g., parametric optimization or uncertainty quantification. Recently introduced performance-driven modeling methods, such as the nested...
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Analysis of Isocratic-Chromatographic-Retention Data using Bayesian Multilevel 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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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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Modeling of Imaging Mass Spectrometry Data and Testing by Permutation for Biomarkers Discovery in Tissues
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O-43 Data-driven selection of active iEEG channels during verbal memory task performance
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Data-driven models for fault detection using kernel PCA: A water distribution system case study
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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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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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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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Rigid Finite Element Modeling for Identification of Vibrations in Elastic in Elastic Rod Driven by a DC-motor Suplied from a Thyristor Rectifier
PublikacjaRozdział dotyczy analizy numerycznej układu elektromechanicznego. Układ składa się z silnika zasilanego z jednopołówkowego prostownika tysystorowego i napędzanego tym silnikiem wirującego pręta. Celem obliczeń jest określenie postaci i wielkości drgań pręta, jeśli uwzględniamy jego elastyczność. Dyskretna struktura modelu to łańcuch wielomasowy ciał - sztywnych ciał połączonych bezmasowymi węzłami. Autorzy obliczyli zachowanie...
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Data set generation at novel test-rig for validation of numerical models for modeling granular flows
PublikacjaSignificant effort has been exerted on developing fast and reliable numerical models for modeling particulate flow; this is challenging owing to the complexity of such flows. To achieve this, reliable and high-quality experimental data are required for model development and validation. This study presents the design of a novel test-rig that allows the visualization and measurement of particle flow patterns during the collision...
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Count Data Modeling About Relationship Between Dubai Housing Sales Transactions and Financial Indicators
PublikacjaIn this study, illustrating and comparing the performances of count data models such as Poisson, negative binomial (NB), Hurdle and zero-inflated models for the determination of factors affected housing sales in Dubai. Model comparisons are made via Akaike’s information criterion (AIC), the Vuong test and examining the residuals. Main purpose of this study is building reliable statistical model for relationship between Dubai housing...
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Count Data Modeling About Relationship Between Dubai Housing Sales Transactions and Financial Indicators
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