Search results for: SPECTRAL ESTIMATION, MULTIVARIATE AUTOREGRESSIVEPROCESS, MODEL AVERAGING, FINAL PREDICTION ERROR
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Analiza właściwości rozszerzonego obserwatora prędkości maszyny indukcyjnej
PublicationRozszerzony obserwator prędkości został zaproponowany przez prof. Krzemińskiego i jest oparty na rozszerzonym modelu maszyny indukcyjnej, gdzie wprowadzona został nowa zmienna ζ. Jest to nowe podejście do estymacji zmiennych stanu maszyny indukcyjnej i nie wszystkie problemy zostały do tej pory rozwiązane. Zaproponowano wykorzystanie algorytmów ewolucyjnych do doboru wzmocnień obserwatora. W celu redukcji nakładów obliczeniowych...
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Quality Assurance and Quality Control in the Analytical Chemical Laboratory. A practical approach : Second edition
PublicationThe second edition defines the tools used in QA/QC, especially the application of statistical tools during analytical data treatment. Clearly written and logically organized, it takes a generic approach applicable to any field of analysis. The authors begin with the theory behind quality control systems, then detail validation parameter measurements, the use of statistical tests, counting the margin of error, uncertainty estimation,...
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Discrete-time estimation of nonlinear continuous-time stochastic systems
PublicationIn this paper we consider the problem of state estimation of a dynamic system whose evolution is described by a nonlinear continuous-time stochastic model. We also assume that the system is observed by a sensor in discrete-time moments. To perform state estimation using uncertain discrete-time data, the system model needs to be discretized. We compare two methods of discretization. The first method uses the classical forward Euler...
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Discrete-time estimation of nonlinear continuous-time stochastic systems
PublicationIn this paper we consider the problem of state estimation of a dynamic system whose evolution is described by a nonlinear continuous-time stochastic model. We also assume that the system is observed by a sensor in discrete-time moments. To perform state estimation using uncertain discrete-time data, the system model needs to be discretized. We compare two methods of discretization. The first method uses the classical forward Euler...
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Constrained aerodynamic shape optimization using neural networks and sequential sampling
PublicationAerodynamic shape optimization (ASO) involves computational fluid dynamics (CFD)-based search for an optimal aerodynamic shape such as airfoils and wings. Gradient-based optimization (GBO) with adjoints can be used efficiently to solve ASO problems with many design variables, but problems with many constraints can still be challenging. The recently created efficient global optimization algorithm with neural network (NN)-based prediction...
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Acoustic heating produced in resonators filled by a newtonian fluid
PublicationAcoustic heating in resonators is studied. The governing equation of acoustic heating is derived by means of the special linear combination of conservation equations in differential form, allowing the reduction of all acoustic terms in the linear part of the final equation, but preserving terms belonging to the thermal mode responsible for heating. This equation is instantaneous and includes nonlinear acoustic terms that form a...
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New First - Path Detector for LTE Positioning Reference Signals
PublicationIn today's world, where positioning applications reached a huge popularity and became virtually ubiquitous, there is a strong need for determining a device location as accurately as possible. A particularly important role in positioning play cellular networks, such as Long Term Evolution (LTE). In the LTE Observed Time Difference of Arrival (OTDOA) positioning method, precision of device location estimation depends on accuracy...
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Advanced Lithium-Ion Battery Model for Power System Performance Analysis
PublicationThe paper describes a novel approach in battery storage system modelling. Different types of lithium-ion batteries exhibit differences in performance due to the battery anode and cathode materials being the determining factors in the storage system performance. Because of this, the influence of model parameters on the model accuracy can be different for different battery types. These models are used in battery management system...
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Effective Permeability of Multi Air Gap Ferrite Core 3-Phase Medium Frequency Transformer in Isolated DC-DC Converters
PublicationThe magnetizing inductance of the medium frequency transformer (MFT) impacts the performance of the isolated dc-dc power converters. The ferrite material is considered for high power transformers but it requires an assembly of type “I” cores resulting in a multi air gap structure of the magnetic core. The authors claim that the multiple air gaps are randomly distributed and that the average air gap length is unpredictable at the...
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Identification of Unstable Reference Points and Estimation of Displacements Using Squared Msplit Estimation
PublicationThe article presents a new version of the method for estimating parameters in a split functional model, which enables the determination of displacements of geodetic network points with constrained datum. The main aim of the study is to present theoretical foundations of Msplit CD estimation and its basic properties and possible applications. Particular attention was paid to the efficacy of the method in the context of geodetic...
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Non-Adaptive Speed and Position Estimation of Doubly-Fed Induction Generator in Grid-Connected Operations
PublicationThe nonadaptive speed and position estimation scheme for a doubly-fed induction generator (DFIG) is presented in this article. The observer structure is based on the extension of the mathematical model of DFIG to the introduced H vector. Based on the defined H vector, the nonadaptive position and speed estimation is proposed. The Lyapunov method is extended to the practical stability theorem to stabilize the structure. The classic...
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Factors affecting the conclusion of an arrangement in restructuring proceedings: evidence from Poland
PublicationThe EU Restructuring Directive (2019/1023) requires Member States to provide a preventive restructuring framework for financially distressed entities that remain viable or are likely to readily restore economic viability. The first step to a successful restructuring is the approval of an arrangement between the debtor and creditors. The main research objective of the article is to identify factors affecting the conclusion of an...
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Effect of waviness and roughness components on transverse profiles of turned surfaces
PublicationThis paper presents the authors method of simultaneous analysis of roughness and waviness irregularity components, with the aim of better defining the key qualities and characteristics.Periodical surface machining traces may be analyzed spectrally, with the irregularity's peaks and troughs being used to define the wave's amplitude.In this work the standard composition for filtering waviness and roughness components of a surface...
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Seven Different Lighting Conditions in Photogrammetric Studies of a 3D Urban Mock-Up
PublicationOne of the most important elements during photogrammetric studies is the appropriate lighting of the object or area under investigation. Nevertheless, the concept of “adequate lighting” is relative. Therefore, we have attempted, based on experimental proof of concept (technology readiness level—TRL3), to verify the impact of various types of lighting emitted by LED light sources for scene illumination and their direct influence...
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Numerical solution of threshold problems in epidemics and population dynamics
PublicationA new algorithm is proposed for the numerical solution of threshold problems in epidemics and population dynamics. These problems are modeled by the delay-differential equations, where the delay function is unknown and has to be determined from the threshold conditions. The new algorithm is based on embedded pair of continuous Runge–Kutta method of order p = 4 and discrete Runge–Kutta method of order q = 3 which is used for the...
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Evaluation of Facial Pulse Signals Using Deep Neural Net Models
PublicationThe reliable measurement of the pulse rate using remote photoplethysmography (PPG) is very important for many medical applications. In this paper we present how deep neural networks (DNNs) models can be used in the problem of PPG signal classification and pulse rate estimation. In particular, we show that the DNN-based classification results correspond to parameters describing the PPG signals (e.g. peak energy in the frequency...
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High quality speech codec employing sines+noise+transients model
PublicationA method of high quality wideband speech signal representation employing sines+transients+noise model is presented. The need for a wideband speech coding approach as well as various methods for analysis and synthesis of sines, residual and transient states of speech signal is discussed. The perceptual criterion is applied in the proposed approach during encoding of sines amplitudes in order to reduce bandwidth requirements and...
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Improved model of isothermal and incompressible fluid flow in pipelines versus the Darcy–Weisbach equation and the issue of friction factor
PublicationIn this article, we consider the modelling of stationary incompressible and isothermal one-dimensional fluid flow through a long pipeline. The approximation of the average pressure in the developed model by the arithmetic mean of inlet and outlet pressures leads to the known empirical Darcy–Weisbach equation. Most importantly, we also present another improved approach that is more accurate because the average pressure is estimated...
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Application 2D Descriptors and Artificial Neural Networks for Beta-Glucosidase Inhibitors Screening
PublicationBeta-glucosidase inhibitors play important medical and biological roles. In this study, simple two-variable artificial neural network (ANN) classification models were developed for beta-glucosidase inhibitors screening. All bioassay data were obtained from the ChEMBL database. The classifiers were generated using 2D molecular descriptors and the data miner tool available in the STATISTICA package (STATISTICA Automated Neural...
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Development and validation of a model that includes two ultrasound parameters and the plasma D-dimer level for predicting malignancy in adnexal masses: an observational study
PublicationBackground: Pre-operative discrimination of malignant from benign adnexal masses is crucial for planning additional imaging, preparation, surgery and postoperative care. This study aimed to define key ultrasound and clinical variables and develop a predictive model for calculating preoperative ovarian tumor malignancy risk in a gynecologic oncology referral center. We compared our model to a subjective ultrasound assessment (SUA)...
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Application of the ISE Optimized Proportional Control of the Wave Maker in a Towing Tank
PublicationThis paper presents the improvement of the wave maker control system. The wave maker is a facility widely used in hydromechanics laboratories to generate waves in towing tanks. It is equipped with an electrohydraulic drive and an actuator submerged into water. The waves are generated to model the environmental conditions for physical experiments, performed on reduced-scale models of maritime objects. The physical experiments allow...
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Assessing the attractiveness of human face based on machine learning
PublicationThe attractiveness of the face plays an important role in everyday life, especially in the modern world where social media and the Internet surround us. In this study, an attempt to assess the attractiveness of a face by machine learning is shown. Attractiveness is determined by three deep models whose sum of predictions is the final score. Two annotated datasets available in the literature are employed for training and testing...
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SPECTRAL-BASED MODAL PARAMETERS IDENTIFICATION WITH MULTIPLE PARTICLE SWARMS OPTIMIZATION
PublicationThe paper presents usage of a Particle Swarm Optimization [1] based algorithm for spectral-based modal parameters identification. The main algorithm consists of two groups of swarms, namely, scouts and helpers. For the first group additional penalizing process is provided to force separation of scouting swarms in frequency space. The swarms have an ability to communicate with each other. At first stage, each swarm focuses on a...
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Robust output prediction of differential – algebraic systems – application to drinking water distribution system
PublicationThe paper presents the recursive robust output variable prediction algorithm, applicable for systems described in the form of nonlinear algebraic-differential equations. The algorithm bases on the uncertainty interval description, the system model, and the measurements. To improve the algorithm efficiency, nonlinear system models are linearised along the nominal trajectory. The effectiveness of the algorithm is demonstrated on...
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Network oscillations modulate interictal epileptiform spike rate during human memory
PublicationEleven patients being evaluated with intracranial electroencephalography for medically resistant temporal lobe epilepsy participated in a visual recognition memory task. Interictal epileptiform spikes were manually marked and their rate of occurrence compared between baseline and three 2 s periods spanning a 6 s viewing period. During successful, but not unsuccessful, encoding of the images there was a significant reduction in...
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Influence of addition of carbon nanotubes on rheological properties of selected liquid lubricants - a computer simulation study
PublicationThis work is motivated by the improvement of anti-friction properties of lubricants by addition of CNTs proved experimentally in literature. In particular, a methodology is developed to compute the shear viscosity of liquid lubricants (Propylene Glycol) based on Molecular Dynamics simulation. Non-Equilibrium molecular dynamics (NEMD) approach is used with a reactive force field ReaxFF implemented in LAMMPS. The simulations are...
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The loop impedance measurement
Open Research DataThe loop impedance measurement
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ARIMA vs LSTM on NASDAQ stock exchange data
PublicationThis study compares the results of two completely different models: statistical one (ARIMA) and deep learning one (LSTM) based on a chosen set of NASDAQ data. Both models are used to predict daily or monthly average prices of chosen companies listed on the NASDAQ stock exchange. Research shows which model performs better in terms of the chosen input data, parameters and number of features. The chosen models were compared using...
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Conceptual fuzzy model of the polish internet mortgage market
PublicationThe aim of this paper is to present the conceptual structure of basic fuzzy model representing Polish Internet mortgage market. The paper starts with introduction describing the market complexities and challenges, and description of previously created rule based model. Then the steps of the process of proposed model fuzzyfication are presented. Final part of the paper consists of conclusions and directions for future research.
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Ship Resistance Prediction with Artificial Neural Networks
PublicationThe paper is dedicated to a new method of ship’s resistance prediction using Artificial Neural Network (ANN). In the initial stage selected ships parameters are prepared to be used as a training and validation sets. Next step is to verify several network structures and to determine parameters with the highest influence on the result resistance. Finally, other parameters expected to impact the resistance are proposed. The research utilizes...
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Position Estimation in Mixed Indoor-Outdoor Environment Using Signals of Opportunity and Deep Learning Approach
PublicationTo improve the user's localization estimation in indoor and outdoor environment a novel radiolocalization system using deep learning dedicated to work both in indoor and outdoor environment is proposed. It is based on the radio signatures using radio signals of opportunity from LTE an WiFi networks. The measurements of channel state estimators from LTE network and from WiFi network are taken by using the developed application....
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Approximate Cramér–Rao bound on Doppler error in correlation-processing relatively narrowband noise radar
PublicationThe paper studies limitations on accuracy of Doppler estimation in continuous-wave noise radar with correlation processing. Second order properties of output of the correlation receiver are evaluated and an approximate Cram´er-Rao bound on errors of Doppler measurement is derived. The accuracy of Doppler measurements is found to be affected by the following factors: power spectral density of noise signal, frequency response of the...
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BADANIE EFEKTYWNOŚCI WYKRYWANIA ANOMALII PROCESOWYCH W DZIAŁANIU TURBINY PAROWEJ ELEKTROWNI JĄDROWEJ PRZY POMOCY METOD WIELOWYMIAROWEJ ANALIZY STATYSTYCZNEJ
PublicationW artykule przedstawiono analizę możliwości wykrywania anomalii procesowych w działaniu turbiny parowej elektrowni jądrowej przy pomocy metod wielowymiarowej analizy statystycznej. Zasymulowano symptomy dwóch rodzajów uszkodzeń turbiny parowej tj. uderzenie wodne oraz, wyciek pary z zaworu części niskoprężnej. Jako narzędzie diagnostyczne wykorzystano Metodę Składników Podstawowych PCA (z ang. Principal Component Analysis). Jako...
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Adaptive estimation of the transformer stray capacitances for DC–DC converter modelling
PublicationNew low cost and accurate estimation method of transformer stray capacitances for wide band DC–DC converter modelling and design is proposed. The Wiener filter (WF) method is applied to estimate the transformer impedance – referred to the selected transformer winding configurations. Laboratory tests are used to adapt the filter, that is to find optimal impedance which minimises mean square error between measured, noise perturbed...
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PREDICTION OF SHIP MOTIONS IN IRREGULAR WAVES BASED ON RESPONSE AMPLITUDE OPERATORS EVALUATED EXPERIMENTALLY IN NOISE WAVES
PublicationThe most common methods for predicting ship roll motions in a specified sea state are direct measurements of motions in a representative irregular wave realisation (time domain) or calculations of motions from response amplitude operators (RAOs) in the frequency domain. The result of the first method is valid only for the tested sea state, whilst the second method is more flexible but less accurate. RAO-based predictions are calculated...
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Flood Routing by the Non-Linear Muskingum Model: Conservation of Mass and Momentum
PublicationIn this paper, the conservative properties of the Muskingum equation, commonly applied to solve river flood routing, are analysed. The aim of this analysis is to explain the causes ofthe mass balance error, which is observed in the numerical solutions of its non-linear form. The linear Muskingum model has been considered as a semi-discrete form of the kinematic wave equation and therefore it was possible to derive its two non-linear...
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Measurements of radiation emission of a portable power bank with a capacity of 5200 mAh
Open Research DataThe dataset contains the emission measurement results that are part of comprehensive tests carried out for portable power banks with different capacities. The measurements were performed in the frequency range from 30 MHz to 3 GHz using a Gigahertz Transverse Electromagnetic (GTEM) cell. The test setup was configured to measure a portable power bank...
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Measurements of radiation emission of a portable power bank with a capacity of 2600 mAh
Open Research DataThe dataset contains the emission measurement results that are part of comprehensive tests carried out for portable power banks with different capacities. The measurements were performed in the frequency range from 30 MHz to 3 GHz using a Gigahertz Transverse Electromagnetic (GTEM) cell. The test setup was configured to measure a portable power bank...
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Identification of ship’s hull mathematical model with numerical methods
PublicationThe modern maritime industry is moving toward the development of technology that will allow for full or partial autonomy of ship operation. This innovation places high demands on ship performance prediction techniques at the design stage. The researchwork presented in the article is related to the design stage of the ship and concerns methods for prognosis and evaluation of the specific operational condition of the ship, namely...
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Numerical modelling of 3D printout using line (1D) elements
PublicationA proposition of some numerical modelling of the 3D printout is presented in the paper. The proposed model is composed of some 1D elements. The resulting numerical model of the infill consist of beam, spring and rigid elements. Obtained results confirm correctness of the proposed modelling method. Two methods of estimation of the spring parameters are proposed in the paper. In the first method, mechanical properties of the connecting...
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The Mechanism of a Retro-Diels–Alder Fragmentation of Luteolin: Theoretical Studies Supported by Electrospray Ionization Tandem Mass Spectrometry Results
PublicationThe mechanisms of retro-Diels–Alder fragmentation of luteolin are studied theoretically using the Density Functional Theory method (B3LYP hybrid functional) together with the 6-311++G(d,p) basis set and supported by electrospray ionization tandem mass spectrometry (ESI-MS) results. The reaction paths leading to the formation of 1,3A and 1,3B fragment ions observed as the main spectral features in the ESI-MS spectrum are described...
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Advancing Solar Energy: Machine Learning Approaches for Predicting Photovoltaic Power Output
PublicationThis research is primarily concentrated on predicting the output of photovoitaic power, an essential field in the study of renewable energy. The paper comprehensively reviews various forecasting methodologies, transitioning from conventional physical and statistical methods to advanced machine learning (ML) techniques. A significant shift has been observed from traditional point forecasting to machine learning-based forecasting...
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Greedy Multipoint Model-Order Reduction Technique for Fast Computation of Scattering Parameters of Electromagnetic Systems
PublicationThis paper attempts to develop a new automated multipoint model-order reduction (MOR) technique, based on matching moments of the system input–output function, which would be suited for fast and accurate computation of scattering parameters for electromagnetic (EM) systems over a wide frequency band. To this end, two questions are addressed. Firstly, the cost of the wideband reduced model generation is optimized by automating a...
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Hybrid Model of Axially Moving Continua
PublicationThe paper introduces the method of the model reduction of systems that experience a Coriolis acceleration component. It causes that system equations are non-self-adjoined. To avoid such problem modal, reduced model is built up for the system without Coriolis acceleration terms which are next included by application of any lumping technique. Hence, the final reduced model is a hybrid one, obtained by both lumping and modal methods...
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Spectrum-based modal parameters identification with Particle Swarm Optimization
PublicationThe paper presents the new method of the natural frequencies and damping identification based on the Artificial Intelligence (AI) Particle Swarm Optimization (PSO) algorithm. The identification is performed in the frequency domain. The algorithm performs two PSO-based steps and introduces some modifications in order to achieve quick convergence and low estimation error of the identified parameters’ values for multi-mode systems....
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Ryszard Katulski prof. dr hab. inż.
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Mathematical Modeling of Ice Dynamics as a Decision Support Tool in River Engineering
PublicationThe prediction of winter flooding is a complicated task since it is affected by many meteorological and hydraulic factors. Typically, information on river ice conditions is based on historical observations, which are usually incomplete. Recently, data have been supplemented by information extracted from satellite images. All the above mentioned factors provide a good background of the characteristics of ice processes, but are not...
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On the Handling of Outliers in the GNSS Time Series by Means of the Noise and Probability Analysis
PublicationThe data pre-analysis plays a significant role in the noise determination. The most important issue is to find an optimum criterion for outliers removal, since their existence can affect any further analysis. The noises in the GNSS time series are characterized by spectral index and amplitudes that can be determined with a few different methods. In this research, the Maximum Likelihood Estimation (MLE) was used. The noise amplitudes...
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Hybrid model of moving or rotating continua
PublicationThe paper introduces the method of the model reduction of systems that experience a Coriolis acceleration or gyroscopic effect component. In such causes that corresponding system equations are non-self-adjoined. Modal reduced model is built up for the system without Coriolis or gyroscopic effect terms. These phenomena are next included by application of any lumping technique. Hence, the final reduced model is a hybrid one, obtained...
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Machine learning-based seismic response and performance assessment of reinforced concrete buildings
PublicationComplexity and unpredictability nature of earthquakes makes them unique external loads that there is no unique formula used for the prediction of seismic responses. Hence, this research aims to implement the most well-known Machine Learning (ML) methods in Python software to propose a prediction model for seismic response and performance assessment of Reinforced Concrete Moment-Resisting Frames (RC MRFs). To prepare 92,400 data...