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Search results for: GAUSSIAN RANDOM VECTOR
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The Effect of the Selection of Three-Dimensional Random Numerical Soil Models on Strip Foundation Settlements
PublicationThis paper delivers a probabilistic attempt to prove that the selection of a random three-dimensional finite element (FE) model of a subsoil affects the computed settlements. Parametricanalysis of a random soil block is conducted, assuming a variable subsoil Young’s modulus inparticular finite elements. The modulus is represented by a random field or different-sized setsof random variables; in both cases, the same truncated...
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Note on the multidimensional Gebelein inequality
PublicationWe generalize the Gebelein inequality for Gaussian random vectors in R^d.
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An automatic system for identification of random telegraph signal (RTS) noise in noise signals
PublicationIn the paper the automatic and universal system for identification of Random Telegraph Signal (RTS) noise as a non-Gaussian component of the inherent noise signal of semiconductor devices is presented. The system for data acquisition and processing is described. Histograms of the instantaneous values of the noise signals are calculated as the basis for analysis of the noise signal to determine the number of local maxima of histograms...
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An improved frequency estimator for an adaptive active noise control scheme
PublicationAn improved frequency tracker is proposed for the recently introduced self optimizing narrowband interference canceller (SONIC). The scheme is designed for disturbances with quasi-linear frequency modulation and, under second-order Gaussian random-walk assumption, can be shown to be statistically efficient. One real-world experiment and several simulations show that a considerable improvement in disturbance rejection may be achieved...
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A method of RTS noise identification in noise signals of semiconductor devices in the time domain
PublicationIn the paper a new method of Random Telegraph Signal (RTS) noise identification is presented. The method is based on a standardized histogram of instantaneous noise values and processing by Gram-Charlier series. To find a device generating RTS noise by the presented method one should count the number of significant coefficients of the Gram-Charlier series. This would allow to recognize the type of noise. There is always one (first)...
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Statistics 2022_23
e-Learning Courses1.Elements of probability. The axioms of the probability theory 2. Random variables and their distributions. Discrete and continuous random variables 3. Parameters of random variables: expected value, moments 4. Selected distributions of random variables (Bernoulli, Poison, Gaussian) 5.The distribution in the sample. Visualisation by histograms 6. Measures of statistical location: arithmetic mean, median, quantiles. 7. Measures...
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Self-tuning adaptive frequency tracker
PublicationAn automatic gain tuning algorithm is proposed for a recently introduced adaptive notch filter. Theoretical analysis and simulations show that, under Gaussian random-walk type assumptions, the proposed extension is capable of adjusting adaptation gains of the filter so as to minimize the mean-squared frequency tracking error without prior knowledge of the true frequency trajectory. A simplified one degree of freedom version of...
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Identification of Optocoupler Devices with RTS Noise
PublicationThe results of noise measurements in low frequency range for CNY 17 type optocouplers are presented. The research were carried out on devices with different values of Current Transfer Ratio (CTR). The methods for identification of Random Telegraph Signal (RTS) in noise signal of optocouplers were proposed. It was found that the Noise Scattering Pattern method (NSP method) enables to identify RTS noise as non-Gaussian component...
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Histogram of Gradients with Cell Average Intensity for Human Detection
PublicationThe modification of the descriptor in human detector using Histogram of Oriented Gradients and support vector machine is presented. The proposed modification requires inserting the average cell intensitiesresulting with the increase of the length of the descriptor from 3780 to 4200 values, but it is easy to compute and instantly gives 14-26% of miss rate improvement at 10^-4 False Positives Per Window (FPPW). The modification...
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A novel hybrid adaptive framework for support vector machine-based reliability analysis: A comparative study
PublicationThis study presents an innovative hybrid Adaptive Support Vector Machine - Monte Carlo Simulation (ASVM-MCS) framework for reliability analysis in complex engineering structures. These structures often involve highly nonlinear implicit functions, making traditional gradient-based first or second order reliability algorithms and Monte Carlo Simulation (MCS) time-consuming. The application of surrogate models has proven effective...
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FE investigations of the effect of fluctuating local tensile strength on coupled energetic-statistical size effect in concrete beams
PublicationThe effect of fluctuating local tensile strength on a coupled energetic-statistical size effect in plain concrete beams under bending was numerically investigated. First, the influence of varying autocorrelation length of the random field describing a spatial variation of local tensile strength was studied. Next, the influence of the coefficient of variation of local tensile strength was analyzed. The numerical FE investigations...
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Histogram of Oriented Gradients with Cell Average Brightness for Human Detection
PublicationA modification of the descriptor in a human detector using Histogram of Oriented Gradients (HOG) and Support Vector Machine (SVM) is presented. The proposed modification requires inserting the values of average cell brightness resulting in the increase of the descriptor length from 3780 to 3908 values, but it is easy to compute and instantly gives ≈ 25% improvement of the miss rate at 10‒4 False Positives Per Window (FPPW). The...
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Examining Classifiers Applied to Static Hand Gesture Recognition in Novel Sound Mixing System
PublicationThe main objective of the chapter is to present the methodology and results of examining various classifiers (Nearest Neighbor-like algorithm with non-nested generalization (NNge), Naive Bayes, C4.5 (J48), Random Tree, Random Forests, Artificial Neural Networks (Multilayer Perceptron), Support Vector Machine (SVM) used for static gesture recognition. A problem of effective gesture recognition is outlined in the context of the system...
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Plasma models, contribution matrix for detector setup and generated projections for plasma emissivity reconstruction in fusion devices
Open Research DataThe original plasma models for fusion devices, together with the complementary detector setup in the form of a contribution matrix and generated projections. Samples are packed inside a Plasma Tomography Format (PTF) files which is a part of the Plasma Tomography in Fusion Devices Python package, and inside the general JSON format. The constructed dataset...
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AUTOMATIC OPTIMIZATION OF ADAPTIVE NOTCH FILTER’S FREQUEN CY TRACKING
PublicationEstimation of instantaneous frequency of narrowband com- plex sinusoids is often performed using lightweight algo- rithms called adaptive notch filters. However, to reach high performance, these algorithms require careful tuning. The paper proposes a novel self-tuning layer for a recently intr o- ducedadaptive notch filtering algorithm. Analysis shows th at, under Gaussian random-walk type assumptions, the resultin g solution converges...
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Automatic Optimization Of Adaptive Notch Filter’s Frequency Tracking
PublicationEstimation of instantaneous frequency of narrowband com- plex sinusoids is often performed using lightweight algo- rithms called adaptive notch filters. However, to reach high performance, these algorithms require careful tuning. The paper proposes a novel self-tuning layer for a recently intr o- ducedadaptive notch filtering algorithm. Analysis shows th at, under Gaussian random-walk type assumptions, the resultin g solution converges...
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Statistically efficient smoothing algorithm for time-varying frequency estimation
PublicationThe problem of extraction/elimination of a nonstationary sinusoidal signal from noisy measurements is considered. This problem is usually solved using adaptive notch filtering (ANF) algorithms. It is shown that the accuracy of frequency estimates can be significantly increased if the results obtained from ANF are backward-time filtered by an appropriately designed lowpass filter. The resulting adaptive notch smoothing (ANS) algorithm...
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Estimation of the size of informal employment based on administrative records with non‐ignorable selection mechanism
PublicationIn this study, we used company level administrative data from the National Labour Inspectorate and The Polish Social Insurance Institution in order to estimate the prevalence of informal employment in Poland in 2016. Since the selection mechanism is non‐ignorable, we employed a generalization of Heckman’s sample selection model assuming non‐Gaussian correlation of errors and clustering by incorporation of random effects. We found...
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Moments of Hermite-Gaussian functionals
PublicationMoments of finite products of Hermite-Gaussian functionals are expressed by covariances of Gaussian sequence.
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From the multiple frequency tracker to the multiple frequency smoother
PublicationThe problem of extraction/elimination of nonstationary sinusoidalsignals from noisy measurements is considered. This problem is usually solved using adaptive notch filtering (ANF)algorithms. It is shown that the accuracy of frequency estimates can be significantly increased if the results obtained from ANF are backward-time filtered by an appropriately designed lowpass filter. The resulting adaptive notch smoothing (ANS)algorithm...
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Generic appearance of objective results in quantum measurements
PublicationMeasurement is of central interest in quantum mechanics as it provides the link between the quantum world and the world of everyday experience. One of the features of everyday experience is its robust, objective character, contrasting the delicate nature of quantum systems. Here we analyze in a completely model-independent way the celebrated von Neumann measurement process, using recent techniques of information flow, studied in...
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Convex set of quantum states with positive partial transpose analysed by hit and run algorithm
PublicationThe convex set of quantum states of a composite K×K system with positive partial transpose is analysed. A version of the hit and run algorithm is used to generate a sequence of random points covering this set uniformly and an estimation for the convergence speed of the algorithm is derived. For K >3 or K=3 this algorithm works faster than sampling over the entire set of states and verifying whether the partial transpose is positive....
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Buried Object Characterization Using Ground Penetrating Radar Assisted by Data-Driven Surrogate-Models
PublicationThis 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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Computer-Aided Diagnosis of COVID-19 from Chest X-ray Images Using Hybrid-Features and Random Forest Classifier
PublicationIn recent years, a lot of attention has been paid to using radiology imaging to automatically find COVID-19. (1) Background: There are now a number of computer-aided diagnostic schemes that help radiologists and doctors perform diagnostic COVID-19 tests quickly, accurately, and consistently. (2) Methods: Using chest X-ray images, this study proposed a cutting-edge scheme for the automatic recognition of COVID-19 and pneumonia....
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Basic evaluation of limb exercises based on electromyography and classification methods
PublicationSymptoms caused by cerebral palsy or stroke deprive a person partially or even completely of his ability to move. Nowadays we can observe more technologically advanced rehabilitation devices which incorporate biofeedback into the process of rehabilitation of such people. However, there is still a lack of devices that would analyse, assess, and control (independently or with limited support) specialised movement exercises. Here...
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Preeclampsia Risk Prediction Using Machine Learning Methods Trained on Synthetic Data
PublicationThis paper describes a research study that investigates the use of machine learning algorithms on synthetic data to classify the risk of developing preeclampsia by pregnant women. Synthetic datasets were generated based on parameter distributions from three real patient studies. Four models were compared: XGBoost, Support Vector Machine (SVM), Random Forest, and Explainable Boosting Machines (EBM). The study found that the XGBoost...
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Improved Uniform Sampling in Constrained Domains for Data-Driven Modelling of Antennas
PublicationData-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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The Suzuki model of the multipath fading channel
Open Research DataThe dataset contains the results of simulations that are part of the research on modelling the multipath fading in the communication channel. The Suzuki fading envelope is generated using the Monte-Carlo simulation (MCS) in the LabVIEW programming environment.
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Soft Sensor Application in Identification of the Activated Sludge Bulking Considering the Technological and Economical Aspects of Smart Systems Functioning
PublicationThe paper presented the methodology for the construction of a soft sensor used for activated sludge bulking identification. Devising such solutions fits within the current trends and development of a smart system and infrastructure within smart cities. In order to optimize the selection of the data-mining method depending on the data collected within a wastewater treatment plant (WWTP), a number of methods were considered, including:...
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Noise sources in Raman spectroscopy of biological objects
PublicationWe present an overview of noise sources deteriorating the quality of the recorded biological Raman spectra and the ability to determine the specimen composition. The acquired Raman spectra exhibit intense additive noise components or drifts because of low intensity of the scattered light. Therefore we have to apply expensive or bulky measurement setups to limit their inherent noise or to apply additional signal processing to reduce...
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Automatic labeling of traffic sound recordings using autoencoder-derived features
PublicationAn approach to detection of events occurring in road traffic using autoencoders is presented. Extensions of existing algorithms of acoustic road events detection employing Mel Frequency Cepstral Coefficients combined with classifiers based on k nearest neighbors, Support Vector Machines, and random forests are used. In our research, the acoustic signal gathered from the microphone placed near the road is split into frames and converted...
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Compressive Sensing Approach to Harmonics Detection in the Ship Electrical Network
PublicationThe contribution of this paper is to show the opportunities for using the compressive sensing (CS) technique for detecting harmonics in a frequency sparse signal. The signal in a ship’s electrical network, polluted by harmonic distortions, can be modeled as a superposition of a small number of sinusoids and the discrete Fourier transform (DFT) basis forms its sparse domain. According to the theory of CS, a signal may be reconstructed...
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Application of autoencoder to traffic noise analysis
PublicationThe aim of an autoencoder neural network is to transform the input data into a lower-dimensional code and then to reconstruct the output from this code representation. Applications of autoencoders to classifying sound events in the road traffic have not been found in the literature. The presented research aims to determine whether such an unsupervised learning method may be used for deploying classification algorithms applied to...
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Random Processes 2022/2023
e-Learning CoursesThe e-learning course page for the purpose of the remote or hybrid learning for Random Processes.
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Random Processes 2023/2024
e-Learning CoursesThe e-learning course page for the purpose of the remote or hybrid learning for Random Processes.
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Note on the variance of the sum of gaussian functonals
PublicationDowodzi się oszacowania wariancji sum funkcjonałów losowych, konstruowanych dla zależnego ciągu gaussowskiego.Let (Xi; i = 1; 2; : : :) be a Gaussian sequence with Xi 2 N(0; 1) for each i and suppose its correlation matrix R = (ij)i;j1 is the matrix of some linear operator R : l2 ! l2. Then for fi 2 L 2(), i = 1; 2; : : : ; where is the standard normal distribution, we estimate the variation of the sum of the Gaussian functionals...
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SOME CONVERGENCE PROPERTIES OF THE SUM OF GAUSSIAN FUNCTIONALS
PublicationIn the paper, some aspects of the convergence of series of dependent Gaussian sequences problem are solved. The necessary and sufficient conditions for the convergence of series of centered dependent indicators are obtained. Some strong convergence results for weighted sums of Gaussian functionals are discussed.
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Ontology-based text convolution neural network (TextCNN) for prediction of construction accidents
PublicationThe construction industry suffers from workplace accidents, including injuries and fatalities, which represent a significant economic and social burden for employers, workers, and society as a whole.The existing research on construction accidents heavily relies on expert evaluations,which often suffer from issues such as low efficiency, insufficient intelligence, and subjectivity.However, expert opinions provided in construction...
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The lognormal model of the multipath fading channel
Open Research DataThe dataset contains the results of simulations that are part of the research on modelling the multipath fading in the communication channel. The lognormal fading envelope is generated using the Monte-Carlo simulation (MCS) in the LabVIEW programming environment.
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Intermolecular Interactions as a Measure of Dapsone Solubility in Neat Solvents and Binary Solvent Mixtures
PublicationDapsone is an effective antibacterial drug used to treat a variety of conditions. However, the aqueous solubility of this drug is limited, as is its permeability. This study expands the available solubility data pool for dapsone by measuring its solubility in several pure organic solvents: N-methyl-2-pyrrolidone (CAS: 872-50-4), dimethyl sulfoxide (CAS: 67-68-5), 4-formylmorpholine (CAS: 4394-85-8), tetraethylene pentamine (CAS:...
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Employing Subjective Tests and Deep Learning for Discovering the Relationship between Personality Types and Preferred Music Genres
PublicationThe purpose of this research is two-fold: (a) to explore the relationship between the listeners’ personality trait, i.e., extraverts and introverts and their preferred music genres, and (b) to predict the personality trait of potential listeners on the basis of a musical excerpt by employing several classification algorithms. We assume that this may help match songs according to the listener’s personality in social music networks....
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Application of a hybrid mechanistic/machine learning model for prediction of nitrous oxide (N2O) production in a nitrifying sequencing batch reactor
PublicationNitrous oxide (N2O) is a key parameter for evaluating the greenhouse gas emissions from wastewater treatment plants. In this study, a new method for predicting liquid N2O production during nitrification was developed based on a mechanistic model and machine learning (ML) algorithm. The mechanistic model was first used for simulation of two 15-day experimental trials in a nitrifying sequencing batch reactor. Then, model predictions...
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Intracranial hemorrhage detection in 3D computed tomography images using a bi-directional long short-term memory network-based modified genetic algorithm
PublicationIntroduction: Intracranial hemorrhage detection in 3D Computed Tomography (CT) brain images has gained more attention in the research community. The major issue to deal with the 3D CT brain images is scarce and hard to obtain the labelled data with better recognition results. Methods: To overcome the aforementioned problem, a new model has been implemented in this research manuscript. After acquiring the images from the Radiological...
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Constructive Controllability for Incompressible Vector Fields
PublicationWe give a constructive proof of a global controllability result for an autonomous system of ODEs guided by bounded locally Lipschitz and divergence free (i.e. incompressible) vector field, when the phase space is the whole Euclidean space and the vector field satisfies so-called vanishing mean drift condition. For the case when the ODE is defined over some smooth compact connected Riemannian manifold, we significantly strengthen...
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Convergence to equilibrium under a random Hamiltonian
PublicationWe analyze equilibration times of subsystems of a larger system under a random total Hamiltonian, in which the basis of the Hamiltonian is drawn from the Haar measure. We obtain that the time of equilibration is of the order of the inverse of the arithmetic average of the Bohr frequencies. To compute the average over a random basis, we compute the inverse of a matrix of overlaps of operators which permute four systems. We first...
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Anomaly Detection in Railway Sensor Data Environments: State-of-the-Art Methods and Empirical Performance Evaluation
PublicationTo date, significant progress has been made in the field of railway anomaly detection using technologies such as real-time data analytics, the Internet of Things, and machine learning. As technology continues to evolve, the ability to detect and respond to anomalies in railway systems is once again in the spotlight. However, railway anomaly detection faces challenges related to the vast infrastructure, dynamic conditions, aging...
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The law of the Iterated Logarithm for random interval homeomorphisms
PublicationA proof of the law of the iterated logarithm for random homeomorphisms of the interval is given.
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Estimation of blood pressure parameters using ex-Gaussian model
PublicationThe paper presents an example of model-based estimation of blood pressure parameters (onset, systolic and diastolic pressure) from continuous measurements. First, the signal was low pass filtered and its quality was estimated. Good quality periods were divided into beats using an electrocardiogram. Next, the beginning of each beat of the blood pressure signal was approximated basing on the function created from the sum of two independent...
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Random field model of foundations at the example of continuous footing
PublicationThe purpose of the paper is to indicate an efficient method of foundation settlement analysis taking into account the variability of soil properties. The impact of the random variable distribution (Gauss or Lognormal) describing soil stiffness on foundation deposits was assessed. The Monte Carlo simulation method was applied in the computations. The settlements of the strip foundation with the subsoil described by a single random...
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Examining Quality of Hand Segmentation Based on Gaussian Mixture Models
PublicationResults of examination of various implementations of Gaussian mix-ture models are presented in the paper. Two of the implementations belonged to the Intel’s OpenCV 2.4.3 library and utilized Background Subtractor MOG and Background Subtractor MOG2 classes. The third implementation presented in the paper was created by the authors and extended Background Subtractor MOG2 with the possibility of operating on the scaled version of...
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Tuning matrix-vector multiplication on GPU
PublicationA matrix times vector multiplication (matvec) is a cornerstone operation in iterative methods of solving large sparse systems of equations such as the conjugate gradients method (cg), the minimal residual method (minres), the generalized residual method (gmres) and exerts an influence on overall performance of those methods. An implementation of matvec is particularly demanding when one executes computations on a GPU (Graphics...
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Limits Theorems for Random Walks on Homeo(S1)
PublicationThe central limit theorem and law of the iterated logarithm for Markov chains corresponding to random walks on the space Homeo(S1) of circle homeomorphisms for centered Lipschitz functions and every starting point are proved.
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Application of Barycentric Coordinates in Space Vector PWM Computations
PublicationThis paper proposes the use of barycentric coordinates in the development and implementationof space-vector pulse-width modulation (SVPWM) methods, especially for inverters with deformed space-vector diagrams. The proposed approach is capable of explicit calculation of vector duty cycles, independentof whether they assume ideal positions or are displaced due to the DC-link voltage imbalance. The use ofbarycentric coordinates also...
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Underground Water Level Prediction in Remote Sensing Images Using Improved Hydro Index Value with Ensemble Classifier
PublicationThe economic sustainability of aquifers across the world relies on accurate and rapid estimates of groundwater storage changes, but this becomes difficult due to the absence of insitu groundwater surveys in most areas. By closing the water balance, hydrologic remote sensing measures offer a possible method for quantifying changes in groundwater storage. However, it is uncertain to what extent remote sensing data can provide an...
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Global Optimization for Recovery of Clipped Signals Corrupted With Poisson-Gaussian Noise
PublicationWe study a variational formulation for reconstructing nonlinearly distorted signals corrupted with a Poisson-Gaussian noise. In this situation, the data fidelity term consists of a sum of a weighted least squares term and a logarithmic one. Both of them are precomposed by a nonlinearity, modelling a clipping effect, which is assumed to be rational. A regularization term, being a piecewise rational approximation of the ℓ0 function...
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Quantum superadditivity in linear optics networks: Sending bits via multiple-access Gaussian channels
PublicationSuperadditivity effects of communication capacities are known in the case of discrete variable quantum channels. We describe the continuous variable analog of one of these effects in the framework of Gaussian multiple access channels (MACs). Classically, superadditivity-type effects are strongly restricted: For example, adding resources to one sender is never advantageous to other senders in sending their respective information...
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Edge and Pair Queries-Random Graphs and Complexity
PublicationWe investigate two types of query games played on a graph, pair queries and edge queries. We concentrate on investigating the two associated graph parameters for binomial random graphs, and showing that determining any of the two parameters is NP-hard for bounded degree graphs.
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The Hopf theorem for gradient local vector fields on manifolds
PublicationWe prove the Hopf theorem for gradient local vector fields on manifolds, i.e., we show that there is a natural bijection between the set of gradient otopy classes of gradient local vector fields and the integers if the manifold is connected Riemannian without boundary.
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Uncertainty estimation of loop impedance measurement determined by the vector method
PublicationThis article presents a detailed analysis of uncertainty estimation of loop impedance measurement determined by the vector method. The analysis includes the following estimates: resistance variance, voltage variance and time measurement variance. This paper presents a methodology for estimating the combined standard uncertainty of loop impedance by the vector method. The vector method allows to determine loop impedance based on...
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A remark on singular sets of vector bundle morphisms
PublicationIf characteristic classes for two vector bundles over the same base space do not coincide, then the bundles are not isomorphic. We give under rather common assumptions a lower bound on the topological dimension of the set of all points in the base over which a morphism between such bundles is not bijective. Moreover, we show that this set is topologically non-trivial.
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Concept of managing quality in baking industry, in vector representation
PublicationThe author introduced an innovative metrisable method of describing a manufacturing process. The idea of vector structure of a manufacturing process allows to formulate quantitative relations between the activity of input streams, elements of product quality, and measurable effects of losses. The structure was basis for the formulation of the concept of the process of managing product quality in the baking industry in a vector...
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Non-Gaussian Resistance Fluctuations in Gold-Nanoparticle-Based Gas Sensors: An Appraisal of Different Evaluation Techniques
PublicationVolatile organic compounds, such as formaldehyde, can be used as biomarkers in human exhaled breath in order to non-invasively detect various diseases, and the same compounds are of much interest also in the context of environmental monitoring and protection. Here, we report on a recently-developed gas sensor, based on surface-functionalized gold nanoparticles, which is able to generate voltage noise with a distinctly non-Gaussian...
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Fault detection and diagnostics of complex dynamic systems using Gaussian Process Models - nuclear power plant case study
PublicationThe article examines the use of Gaussian Process Models to simulate the dynamic processes of a Pressurized Water nuclear Reactor for fault detection and diagnostics. The paper illustrates the potential of Gaussian Process Models as a tool for monitoring and predicting various fault conditions in Pressurized Water nuclear Reactor power plants, including reactor coolant flow and temperature variations, deviations from nominal working...
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Connected components of the space of proper gradient vector fields
PublicationWe show that there exist two proper gradient vector fields on Rn which are homotopic in the category of proper maps but not homotopic in the category of proper gradient maps.
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Empirical analysis of tree-based classification models for customer churn prediction
PublicationCustomer churn is a vital and reoccurring problem facing most business industries, particularly the telecommunications industry. Considering the fierce competition among telecommunications firms and the high expenses of attracting and gaining new subscribers, keeping existing loyal subscribers becomes crucial. Early prediction of disgruntled subscribers can assist telecommunications firms in identifying the reasons for churn and...
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RANDOM STRUCTURES & ALGORITHMS
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Formulation of Time-Fractional Electrodynamics Based on Riemann-Silberstein Vector
PublicationIn this paper, the formulation of time-fractional (TF) electrodynamics is derived based on the Riemann-Silberstein (RS) vector. With the use of this vector and fractional-order derivatives, one can write TF Maxwell’s equations in a compact form, which allows for modelling of energy dissipation and dynamics of electromagnetic systems with memory. Therefore, we formulate TF Maxwell’s equations using the RS vector and analyse their...
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The homotopy type of the space of gradient vector fields on the two-dimensional disc
PublicationWe prove that the inclusion of the space of gradient vector fields into the space of all vector fields on D^2 non-vanishing in S^1 is a homotopy equivalence
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Effectiveness of Random Field Approach in Serviceability Limit State Analysis of Strip Foundation
PublicationThis work conducts a probabilistic inquiry on how the variability of the parameter defining soil deformability affects the settlement of the foundation located on the soil. The analysis addresses the random foundation model to relevantly estimate the probability of allowable deflection exceedance. The constitutive model parameter is based either on a single random variable or a random field. The computations incorporate direct...
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Generation of random fields to reflect material and geometric imperfections of plates and shells
PublicationThe paper covers two patterns of random field generation: conditional acceptance – rejection method and Karhunen – Loève expansion. The generation of two-dimensional random fields is essential in plates and shells analysis, allowing for a relevant limit and critical state assessment of geometrically and ma-terially imperfect structures. The features of both generation methods dedicate them to selected problems.
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A random signal generation method for microcontrollers with DACs
PublicationA new method of noise generation based on software implementation of a 7-bit LFSR based on a common polynomial PRBS7 using microcontrollers equipped with internal ADCs and DACs and a microcontroller noise generator structure are proposed in the paper. Two software applications implementing the method: written in ANSI C and based on the LUT technique and written in AVR Assembler are also proposed. In the method the ADC results are...
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Metrisable assessment of the course of stream‑systemic processes in vector form in industry 4.0
PublicationThe goal of this paper is to present an innovative conception how to use metrisable vector structure of a manufacturing process, based on quantitative relations between the activity of input streams, features of the product, and effect of losses; all of which are excellent practical solution for Industry 4.0, and in turn intelligent factories. This solution can be a usefull way in the process of building sustainable organization....
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Discrete random variables in reliability calculations of a reticulated shell
PublicationImplementation of the Point Estimation Method (PEM) in the reliability analysis of a three-dimensional truss structure is presented in the paper. The influence of geometric and material random parameters on the truss load-carrying capacity was investigated. The analysis was performed for different combinations of basic variables. Symmetric and asymmetric cases of snow load were taken to assess the structural reliability. Sensitivity...
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Computations of critical load value of composite shell with random geometric imperfections
PublicationThe work presents the numerical analysis of composite shell with geometric imperfections subjected to compression along its generatrix. The imperfections are described as single indentations and random fields with random parameters of shape and correlation. The fields are generated with the use of the authors made program. Using the authors’ FEM software as well as commercial package Femap with NX Nastran, the critical load values...
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Support Vector Machine Applied to Road Traffic Event Classification
PublicationThe aim of this paper is to present results of road traffic event signal recognition. First, several types of systems for road traffic monitoring, including Intelligent Transport System (ITS) are shortly described. Then, assumptions of creating a database of vehicle signals recorded in different weather and road conditions are outlined. Registered signals were edited as single vehicle pass by. Using the Matlab-based application...
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Probabilistic Analysis of Structure Models using Target Random Sampling (TRS)
PublicationThe work presents testing methods of sensitivity and reliability of mechanical or structural systems. All computations concerned the case of Zigler column, a simple model of a compressed column involving two random variables only. A conclusion was drawn that the standard Monte Carlo method, its reduction variants and the response surface method allow to assess the sensitivity of structural response to the variation of random structural...
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Complementarity between entanglement-assisted and quantum distributed random access code
PublicationCollaborative communication tasks such as random access codes (RACs) employing quantum resources have manifested great potential in enhancing information processing capabilities beyond the classical limitations. The two quantum variants of RACs, namely, quantum random access code (QRAC) and the entanglement-assisted random access code (EARAC), have demonstrated equal prowess for a number of tasks. However, there do exist specific...
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Aggregated conducted interferences generated by group of asynchronous drives with deterministic and random modulation
PublicationThis paper addresses problems linked with electromagnetic interferences generated by group of three adjustable speed drives fed by frequency converters with deterministic and random modulation. Based on the experimental results it has been shown that decreasing of the conducted interferences in a case of random modulation is measuring phenomenon linked with selectivity of the EMI receiver.
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JOURNAL OF VECTOR ECOLOGY
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Determination of the Vehicles Speed Using Acoustic Vector Sensor
PublicationThe method for determining the speed of vehicles using acoustic vector sensor and sound intensity measurement technique was presented in the paper. First, the theoretical basis of the proposed method was explained. Next, the details of the developed algorithm of sound intensity processing both in time domain and in frequency domain were described. Optimization process of the method was also presented. Finally, the proposed measurement...
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Random field modelling of mechanical behaviour of corroded thin steel plate specimens
PublicationThe objective of this work is to explore the possibility of corrosion degradation modelling of thin steel plate specimens with the use of random field approach. The mechanical properties are obtained via the nonlinear Finite Element Analysis with the use of an explicit dynamic solver. The fully nonlinear material model is adopted to obtain the proper stress-strain response. Sensitivity analysis considering the main statistical...
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Data obtained by computation for X-ray focusing using oriented Gaussian beams
Open Research DataThe propagation of X-ray waves through an optical system consisting of several X-ray refractive lenses is considered. Gaussian beams are exact solutions of the paraxial equation. The Helmholtz equation describes the propagation of a monochromatic electromagnetic wave. Since the widths of the beams are much larger than the wavelength of X-rays, Gaussian...
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Detection and segmentation of moving vehicles and trains using Gaussian mixtures, shadow detection and morphological processing
PublicationSolution presented in this paper combines background modelling, shadow detection and morphological and temporal processing into one system responsible for detection and segmentation of moving objects recorded with a static camera. Vehicles and trains are detected based on their pixellevel difference from the continually updated background model utilizing a Gaussian mixture calculated separately for every pixel. The shadow detection...
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Measurement and visualization of sound intensity vector distribution in proximity of acoustic diffusers
PublicationIn this work, we would like to present analyses and visualizations of sound intensity distribution measured in proximity of an acoustic diffuser. Such distribution may be used for estimation of basic acoustic parameters of a diffuser. Measurement is performed with the use of a logarithmic sine sweep which allows for the analysis of waves scattered by the diffuser and rejecting the direct sound signal component. Pressure and sound...
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Oriented Gaussian beams for high-accuracy computation with accuracy control of X-ray propagation through a multi-lens system
PublicationA highly accurate method for calculating X-ray propagation is developed. Within this approach, the propagating wave is represented as a superposition of oriented Gaussian beams. The direction of wave propagation in each Gaussian beam agrees with the local direction of propagation of the X-ray wavefront. When calculating the propagation of X-ray waves through lenses, the thin lens approximation is applied. In this approximation,...
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Connections between Mutually Unbiased Bases and Quantum Random Access Codes
PublicationWe present a new quantum communication complexity protocol, the promise--Quantum Random Access Code, which allows us to introduce a new measure of unbiasedness for bases of Hilbert spaces. The proposed measure possesses a clear operational meaning and can be used to investigate whether a specific number of mutually unbiased bases exist in a given dimension by employing Semi--Definite Programming techniques.
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Counting and tracking vehicles using acoustic vector sensors
PublicationA method is presented for counting vehicles and for determining their movement direction by means of acoustic vector sensor application. The assumptions of the method employing spatial distribution of sound intensity determined with the help of an integrated 3D intensity probe are discussed. The intensity probe developed by the authors was used for the experiments. The mode of operation of the algorithm is presented in conjunction...
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Localization of sound sources with dual acoustic vector sensor
PublicationThe aim of the work is to estimate the position of sound sources. The proposed method uses a setup of two acoustic vector sensors (AVS). The intersection of azimuth rays from each AVS should indicate the position of a source. In practice, the result of position estimation using this method is an area rather than a point. This is a result of inaccuracy of the individual sensors, but more importantly, of the influence of a source...
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Detection of Water on Road Surface with Acoustic Vector Sensor
PublicationThis paper presents a new approach to detecting the presence of water on a road surface, employing an acoustic vector sensor. The proposed method is based on sound intensity analysis in the frequency domain. Acoustic events, representing road vehicles, are detected in the sound intensity signals. The direction of the incoming sound is calculated for the individual spectral components of the intensity signal, and the components...
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Anisotropic Orlicz–Sobolev spaces of vector valued functions and Lagrange equations
PublicationIn this paper we study some properties of anisotropic Orlicz and Orlicz–Sobolev spaces of vector valued functions for a special class of G-functions. We introduce a variational setting for a class of Lagrangian Systems. We give conditions which ensure that the principal part of variational functional is finitely defined and continuously differentiable on Orlicz–Sobolev space.
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Random Processes and Stochastic Control - project
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Bearing capacity for random subsoil.
PublicationW pracy zaproponowano modyfikację metody charakterystyk bazującej na stochastycznej metodzie różnic skończonych. Podejście takie pozwoliło na uwzględnienie przestrzennej zmienności podłoża gruntowego przy ocenie nośności granicznej ławy fundamentowej posadowionej na losowym podłożu. Przeprowadzono analizę wpływu dyskretyzacji ośrodka gruntowego na rozwiązanie oraz rozpatrzono jego zbieżności.
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Optimal asynchronous estimation of 2D Gaussian-Markov processes
PublicationW artykule rozważa się problem estymacji trajektorii dwuwymiarowych ciągłoczasowych procesów Gaussa-Markowa na podstawie zaszumionych pomiarów wykonywanych w nierównomiernie rozłożonych chwilach czasu. W przypadku takiego problemu, w każdym cyklu pracy algorytmu należy dokonać dyskretnoczasowej predykcji (analogicznie jak w przypadku filtru Kalmana). Niestety zadanie to może być złożone obliczeniowo. Aby rozwiązać ten problem,...
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Gaussian mixture decomposition in the analysis of MALDI-TOF spectra
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Estimation and Prediction of Vertical Deformations of Random Surfaces, Applying the Total Least Squares Collocation Method
PublicationThis paper proposes a method for determining the vertical deformations treated as random fields. It is assumed that the monitored surfaces are subject not only to deterministic deformations, but also to random fluctuations. Furthermore, the existence of random noise coming from surface’s vibrations is also assumed. Such noise disturbs the deformation’s functional models. Surface monitoring with the use of the geodetic levelling...
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RSS-Based DoA Estimation for ESPAR Antennas Using Support Vector Machine
PublicationIn this letter, it is shown how direction-of-arrival (DoA) estimation for electronically steerable parasitic array radiator (ESPAR) antennas, which are designed to be integrated within wireless sensor network nodes, can be improved by applying support vector classification approach to received signal strength (RSS) values recorded at an antenna's output port. The proposed method relies on ESPAR antenna's radiation patterns measured...
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Dangerous sound event recognition using Support Vector Machine classifiers
PublicationA method of recognizing events connected to danger based on their acoustic representation through Support Vector Machine classification is presented. The method proposed is particularly useful in an automatic surveillance system. The set of 28 parameters used in the classifier consists of dedicated parameters and MPEG-7 features. Methods for parameter calculation are presented, as well as a design of SVM model used for classification....
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Neural Networks, Support Vector Machine and Genetic Algorithms for Autonomous Underwater Robot Support
PublicationIn this paper, artificial neural networks, a classification technique called support vector machine and meta-heuristics genetic algorithm have been considered for development in autonomous underwater robots. Artificial neural networks have been used for seabed modelling as well as support vector machine has been applied for the obstacles classification to avoid some collision problems. Moreover, genetic algorithm has been applied...
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Macromodeling of multiport systems using a fast implementation of the vector fitting method
PublicationMakromodelowanie układów wieloportowych przy użyciu vector fittingu jest czasochłonne oraz wymaga dużych zasobów obliczeniowych w przypadku gdy wszystkie elementy macierzy systemowej dzielą wspólne bieguny. Artykuł prezentuje stabilne rozwiązanie, które usuwa problem rzadkości macierzy poprzez zastosowanie bezpośrednie dekompozycje QR. Jako przykład przedstawiony został 60 portowy układ, który ilustruje oszczędność czasu potrzebnego...
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Waves in Random and Complex Media
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