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Search results for: sparse autoregressive models
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Sparse autoregressive modeling
PublicationIn the paper the comparison of the popular pitch determination (PD) algorithms for thepurpose of elimination of clicks from archive audio signals using sparse autoregressive (SAR)modeling is presented. The SAR signal representation has been widely used in code-excitedlinear prediction (CELP) systems. The appropriate construction of the SAR model is requiredto guarantee model stability. For this reason the signal representation...
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RENOVATION OF ARCHIVE AUDIO RECORDINGS USING SPARSE AUTOREGRESSIVE MODELING AND BIDIRECTIONAL PROCESSING
PublicationThe paper presents a new approach to elimination of broadband noise and impulsive disturbances from archive audio recordings. The proposed adaptive Kalman-like algorithm, based on a sparse autoregressive model of the audio signal, simultaneously detects noise pulses, interpolates the irrevocably distorted samples and performs signal smoothing. It is shown that bidirectional (forward-backward) processing of the archive signal improves...
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Elimination of clicks from archive speech signals using sparse autoregressive modeling
PublicationThis paper presents a new approach to elimination of impulsivedisturbances from archive speech signals. The proposedsparse autoregressive (SAR) signal representation is given ina factorized form - the model is a cascade of the so-called formantfilter and pitch filter. Such a technique has been widelyused in code-excited linear prediction (CELP) systems, as itguarantees model stability. After detection of noise pulses usinglinear...
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Sparse vector autoregressive modeling of audio signals and its application to the elimination of impulsive disturbances
PublicationArchive audio files are often corrupted by impulsive disturbances, such as clicks, pops and record scratches. This paper presents a new method for elimination of impulsive disturbances from stereo audio signals. The proposed approach is based on a sparse vector autoregressive signal model, made up of two components: one taking care of short-term signal correlations, and the other one taking care of long-term correlations. The method...
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Low order autoregressive (AR) models for FDTD analysis of microwave filters.
PublicationArtykuł opisuje zastosowanie modeli AR w celu poprawy efektywności analizy struktur filtrujących metodą różnic skończonych w dziedzinie czasu (FD-TD). Opisanych jest szereg kryteriów pozwalających na automatyczne tworzenie modeli AR sygnałów czasowych, w tym wybór fragmentu odpowiedzi układu stanowiący podstawę ekstrakcji współczynników modelu, współczynnika decymacji oraz rzędu modelu. Skuteczność wprowadzonych kryteriów...
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A Cost-Effective Method for Reconstructing City-Building 3D Models from Sparse Lidar Point Clouds
PublicationThe recent popularization of airborne lidar scanners has provided a steady source of point cloud datasets containing the altitudes of bare earth surface and vegetation features as well as man-made structures. In contrast to terrestrial lidar, which produces dense point clouds of small areas, airborne laser sensors usually deliver sparse datasets that cover large municipalities. The latter are very useful in constructing digital...
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Variable-Fidelity Simulation Models and Sparse Gradient Updates for Cost-Efficient Optimization of Compact Antenna Input Characteristics
PublicationDesign of antennas for the Internet of Things (IoT) applications requires taking into account several performance figures, both electrical (e.g., impedance matching) and field (gain, radiation pattern), but also physical constraints, primarily concerning size limitation. Fulfillment of stringent specifications necessitates the development of topologically complex structures described by a large number of geometry parameters that...
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Prognozowanie ostrzegawcze w małej firmie
PublicationW artykule pokazano możliwości zastosowania prostych metod prognostycznych do ostrzegania w małej firmie przed niekorzystnymi zjawiskami. Przedmiotem badań jest sprzedaż, a ze względu na występowanie w szeregu czasowym sezonowości, w celu wyznaczenia sygnałów ostrzegawczych dokonano porównań trendów prognozowanych i rzeczywistych w okresach jednoimiennych za pomocą pierwszych różnic. Do prognozowania sprzedaży wykorzystano proste...
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On Adaptive Spectrum Estimation of Multivariate Autoregressive Locally Stationary Processes
PublicationAutoregressive modeling is a widespread parametricspectrum estimation method. It is well known that, in the caseof stationary processes with unknown order, its accuracy canbe improved by averaging models of different complexity usingsuitably chosen weights. The paper proposes an extension of thistechnique to the case of multivariate locally stationary processes.The proposed solution is based on local autoregressive...
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On autoregressive spectrum estimation using the model averaging technique
PublicationThe problem of estimating spectral density of a nonstationary process satisfying local stationarity conditions is considered. The proposed solution is a two step procedure based on local autoregressive (AR) modeling. In the first step Bayesian-like averaging of AR models, differing in order, is performed. The main contribution of the paper is development of a new final-prediction-error-like statistic, which can be used to select...
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On Noncausal Identification of Nonstationary Multivariate Autoregressive Processes
PublicationThe problem of identification of nonstationary multivariate autoregressive processes using noncausal local estimation schemes is considered and a new approach to joint selection of the model order and the estimation bandwidth is proposed. The new selection rule, based on evaluation of pseudoprediction errors, is compared with the previously proposed one, based on the modified Akaike’s final prediction error criterion.
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On joint order and bandwidth selection for identification of nonstationary autoregressive processes
PublicationWhen identifying a nonstationary autoregressive process, e.g. for the purpose of signal prediction or parametric spectrum estimation, two important decisions must be taken. First, one should choose the appropriate order of the autoregressive model, i.e., the number of autoregressive coefficients that will be estimated. Second, if identification is carried out using the local estimation technique, such as the localized version of...
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A memory efficient and fast sparse matrix vector product on a Gpu
PublicationThis paper proposes a new sparse matrix storage format which allows an efficient implementation of a sparse matrix vector product on a Fermi Graphics Processing Unit (GPU). Unlike previous formats it has both low memory footprint and good throughput. The new format, which we call Sliced ELLR-T has been designed specifically for accelerating the iterative solution of a large sparse and complex-valued system of linear equations arising...
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A Task-Scheduling Approach for Efficient Sparse Symmetric Matrix-Vector Multiplication on a GPU
PublicationIn this paper, a task-scheduling approach to efficiently calculating sparse symmetric matrix-vector products and designed to run on Graphics Processing Units (GPUs) is presented. The main premise is that, for many sparse symmetric matrices occurring in common applications, it is possible to obtain significant reductions in memory usage and improvements in performance when the matrix is prepared in certain ways prior to computation....
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Lattice filter based autoregressive spectrum estimation with joint model order and estimation bandwidth adaptation
PublicationThe problem of parametric, autoregressive model based estimation of a time-varying spectral density function of a nonstationary process is considered. It is shown that estimation results can be considerably improved if identification of the autoregressive model is carried out using the two-sided doubly exponentially weighted lattice algorithm which combines results yielded by two one-sided lattice algorithms running forward in...
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Models in spatial development
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Estimation of the amplitude of the signal for the active optical gesture sensor with sparse detectors
PublicationIn this paper we deal with the problem of precise gesture recognition for the active optical proximity sensor with sparse 8 photodiodes. We particularly focus on developing the method of estimating the real, usually not observable, maximum signal value representing maximum intensity of light reflected from an obstacle present in the front of the sensor. Different configurations of the fingers were used as an obstacle. The Monte Carlo...
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Lattice filter based multivariate autoregressive spectral estimation with joint model order and estimation bandwidth adaptation
PublicationThe problem of parametric, autoregressive model based estimation of a time-varying spectral density function of a multivariate nonstationary process is considered. It is shown that estimation results can be considerably improved if identification of the autoregressive model is carried out using the two-sided doubly exponentially weighted lattice algorithm which combines results yielded by two one-sided lattice algorithms running...
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Two-Stage Identification of Locally Stationary Autoregressive Processes and its Application to the Parametric Spectrum Estimation
PublicationThe problem of identification of a nonstationary autoregressive process with unknown, and possibly time-varying, rate of parameter changes, is considered and solved using the parallel estimation approach. The proposed two-stage estimation scheme, which combines the local estimation approach with the basis function one, offers both quantitative and qualitative improvements compared with the currently used single-stage methods.
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Expedited Gradient-Based Design Closure of Antennas Using Variable-Resolution Simulations and Sparse Sensitivity Updates
PublicationNumerical optimization has been playing an increasingly important role in the design of contemporary antenna systems. Due to the shortage of design-ready theoretical models, optimization is mainly based on electromagnetic (EM) analysis, which tends to be costly. Numerous techniques have evolved to abate this cost, including surrogate-assisted frameworks for global optimization, or sparse sensitivity updates for speeding up local...
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Signal Reconstruction from Sparse Measurements Using Compressive Sensing Technique
PublicationThe paper presents the possibility of applying a new class ofmathematical methods, known as Compressive Sensing (CS) for recovering thesignal from a small set of measured samples. CS allows the faithful recon-struction of the original signal back from fewer random measurements bymaking use of some non-linear reconstruction techniques. Since of all thesefeatures, CSfinds its applications especially in the areas where, sensing is...
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Reduced-cost electromagnetic-driven optimisation of antenna structures by means of trust-region gradient-search with sparse Jacobian updates
PublicationNumerical optimisation plays more and more important role in the antenna design. Because of lack of design-ready theoretical models, electromagnetic (EM)-simulation-driven adjustment of geometry parameters is a necessary step of the design process. At the same time, traditional parameter sweeping cannot handle complex topologies and large number of design variables. On the other hand, high computational cost of the conventional...
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GRAPHICAL MODELS
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STOCHASTIC MODELS
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Elimination of Impulsive Disturbances From Stereo Audio Recordings Using Vector Autoregressive Modeling and Variable-order Kalman Filtering
PublicationThis paper presents a new approach to elimination of impulsive disturbances from stereo audio recordings. The proposed solution is based on vector autoregressive modeling of audio signals. Online tracking of signal model parameters is performed using the exponential ly weighted least squares algo- rithm. Detection of noise pulses an d model-based interpolation of the irrevocably distorted sampl es is realized using an adaptive, variable-order...
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Adaptive identification of sparse underwater acoustic channels with a mix of static and time-varying parameters
PublicationWe consider identification of sparse linear systems with a mix of static and time-varying parameters. Such systems are typical in underwater acoustics (UWA), for instance, in applications requiring identi- fication of the acoustic channel, such as UWA communications, navigation and continuous-wave sonar. The recently proposed fast local basis function (fLBF) algorithm provides high performance when identi- fying time-varying systems....
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A GPU Solver for Sparse Generalized Eigenvalue Problems with Symmetric Complex-Valued Matrices Obtained Using Higher-Order FEM
PublicationThe paper discusses a fast implementation of the stabilized locally optimal block preconditioned conjugate gradient (sLOBPCG) method, using a hierarchical multilevel preconditioner to solve nonHermitian sparse generalized eigenvalue problems with large symmetric complex-valued matrices obtained using the higher-order finite-element method (FEM), applied to the analysis of a microwave resonator. The resonant frequencies of the low-order...
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Identification of nonstationary multivariate autoregressive processes– Comparison of competitive and collaborative strategies for joint selection of estimation bandwidth and model order
PublicationThe problem of identification of multivariate autoregressive processes (systems or signals) with unknown and possibly time-varying model order and time-varying rate of parameter variation is considered and solved using parallel estimation approach. Under this approach, several local estimation algorithms, with different order and bandwidth settings, are run simultaneously and compared based on their predictive performance. First,...
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[AEiE] Selected topics of electrical engineering - models of electrical machines
e-Learning Courses{mlang pl} Dyscyplina: automatyka, elektronika i elektrotechnika Zajęcia fakultatywne dla doktorantów II roku Prowadzący: dr hab. inż. Andrzej Wilk, prof. PG, prof. dr hab. inż. Zbigniew Krzemiński Liczba godzin: 15 Forma zajęć: wykład {mlang} {mlang en} Discipline: control, electronic and electrical engineering Facultative course for 2nd-year PhD students Academic teachers: dr hab. inż. Andrzej Wilk, prof. PG, prof....
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Disease Models & Mechanisms
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Kinetic and Related Models
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Language Models in Speech Recognition
PublicationThis chapter describes language models used in speech recognition, It starts by indicating the role and the place of language models in speech recognition. Mesures used to compare language models follow. An overview of n-gram, syntactic, semantic, and neural models is given. It is accompanied by a list of popular software.
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Models of Structures in Didactics
PublicationThe final aim of teaching students subjects, such as structural mechanics, reinforced concrete, and steel structures is to teach them how structures work in a given building as well as to provide them with skills enabling them to calculate and design structures. The behavioral model of the structure, contrary to the architectural model, which focuses mainly on the external form of the building, shows workings from both the static...
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Bridging the gap between business process models and use-case models
PublicationToday's software development methodologies are equipped with a plethora of methods and techniques for business process engineering and Requirements Engineering. However, heavy investments in IT have not brought forth expected results. What seems to be lacking is a systematic approach that consolidates both disciplines to gain a synergistic effect. To address this challenge we extend Use-Case Driven Approach (UCDA) by binding use...
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Comparison of technology adoption models
PublicationThere are several technology adoption models, that try to explain, how and why the technologies are adopted and used. Among those, that are widely used to explain, how the older adults accept technologies, there are some general models and models specific to the group of older users. Among the general ones I would recommend paying attention to the following models: Technology Acceptance Model (TAM) proposed by Davis...
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Kriging Models for Microwave Filters
PublicationSurrogate modeling of microwave filters’ response is discussed. In particular, kriging is used to model either the scattering parameters of the filter or the rational representation of the filter’s characteristics. Surrogate models for these two variants of kriging are validated in solving a microwave filter optimization problem. A clear advantage of surrogate models based on the rational representation over the models based on scattering...
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Multibody models for gait analysis
PublicationThe aim of this study was to create multibody biomechanical models to analyze a normal gait of the human. Proposed models can be used to identify joint moments of the lower limbs during normal gait in the single and double support phases. Applying Newton-Euler formulation, following planar models were developed: 1) a mathematical 6DOF model describing a gait in the sagittal plane of the body for single support phase and double...
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Efficient list cost coloring of vertices and/or edges of some sparse graphs
PublicationRozważane jest kolorowanie wierzchołków i krawędzi grafów w modelach klasycznym, totalnym i pseudototalnym z uwzględnieniem dodatkowego ograniczenia w postaci list dostępnych kolorów. Proponujemy wielomianowy algorytm oparty na paradygmacie programowania dynamicznego dla grafów o strukturze drzewa. Wynik ten można uogólnić na grafy o liczbie cyklomatycznej ograniczonej z góry przez dowolnie wybraną stała.
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Efficient List Cost Coloring of Vertices and∕or Edges of Some Sparse Graphs
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Data Compression in Ultrasonic Network Communication via Sparse Signal Processing
PublicationThis document presents the approach of using compressed sensing in signal encoding and information transferring within a guided wave sensor network, comprised of specially designed frequency steerable acoustic transducers (FSATs). Wave propagation in a damaged plate was simulated using commercial FEM-based software COMSOL. Guided waves were excited by means of FSATs, characterized by the special shape of its electrodes, and modeled...
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Physical models in the education of architectural history
PublicationIn this article, the authors present the long tradition and common use of physical models in the process of teaching the history of architecture in higher education institutions. The research described in the article is focused on the use of physical models and mock-ups as stimulants during architectural history classes to support lectures and increase the learning capabilities of students. The authors also cover the general use...
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Sophistication assessment of existing FEM models of orbital blowout trauma: Is models valuation justified?
PublicationAfter a thorough study of the work entitled “Development and validation of an optimized finite element model of the human orbit”, some doubts aroused concerning the sophistication assessment of the existing finite element method (FEM) models of orbital blow-out. Although the work was unquestionably innovative, and the results were not only fascinating but also invaluable, the authors stated that their model was the most sophisticated...
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Rapid Variable-Resolution Parameter Tuning of Antenna Structures Using Frequency-Based Regularization and Sparse Sensitivity Updates
PublicationGeometry parameter tuning is an inherent part of antenna design process. While most often performed in a local sense, it still entails considerable computational expenses when carried out at the level of full-wave electromagnetic (EM) simulation models. Moreover, the optimization outcome may be impaired if good initial design is not available. This paper proposes a novel approach to fast and improved-reliability gradient-based...
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Single and Dual-GPU Generalized Sparse Eigenvalue Solvers for Finding a Few Low-Order Resonances of a Microwave Cavity Using the Finite-Element Method
PublicationThis paper presents two fast generalized eigenvalue solvers for sparse symmetric matrices that arise when electromagnetic cavity resonances are investigated using the higher-order finite element method (FEM). To find a few loworder resonances, the locally optimal block preconditioned conjugate gradient (LOBPCG) algorithm with null-space deflation is applied. The computations are expedited by using one or two graphical processing...
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Fast EM-Driven Parameter Tuning of Microwave Circuits with Sparse Sensitivity Updates via Principal Directions
PublicationNumerical optimization has become more important than ever in the design of microwave components and systems, primarily as a consequence of increasing performance demands and growing complexity of the circuits. As the parameter tuning is more and more often executed using full-wave electromagnetic (EM) models, the CPU cost of the overall process tends to be excessive even for local optimization. Some ways of alleviating these issues...
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COMPARISON OF INFINITE ELEMENT MODELS
PublicationThe main objective of this paper is to show the comparison of two models of infinite ab- sorbing layer with increasing damping in numerical investigations of elastic wave prop- agation in unbounded structures. This has been achieved by the Authors by a careful in- vestigation of two different engineering structures characterised by gradually increasing geometrical and mathematical description complexities. The analysis included...
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Architectural Heritage Virtual Models in Conservation Practice
PublicationThe article presents the issues concerning architectural heritage digital models’ applications in conservation practice. These considerations are discussed in the context of the commencement of creating virtual models regarding no-longer existing historical buildings in the first half of the 1980s. Such models’ applications and possible uses are analyzed within the adopted criteria that distinguish the following model types....
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Non-monotone graph searching models
PublicationGraph searching encompasses a variety of different models, many of which share a property that in optimal strategies fugitive can never access once searched regions. Monotonicity, as it is called, is vital in many established results in the field however its absence significantly impedes the analysis of a given problem. This survey attempts to gather non-monotone models, that are less researched in effort of summarizing the results...
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Melody Harmonization with Interpolated Probabilistic Models
PublicationMost melody harmonization systems use the generative hidden Markov model (HMM), which model the relation between the hidden chords and the observed melody. Relations to other variables, such as the tonality or the metric structure, are handled by training multiple HMMs or are ignored. In this paper, we propose a discriminative means of combining multiple probabilistic models of various musical variables by means of model interpolation....
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Advanced Mathematical Models and Applications
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Animal Models and Experimental Medicine
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Advances in Continuous and Discrete Models
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Periodicity Matters: Grating or lattice resonances in the scattering by sparse arrays of subwavelength strips and wires.
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Derivation of Executable Test Models From Embedded System Models using Model Driven Architecture Artefacts - Automotive Domain
PublicationThe approach towards system engineering compliant to Model-Driven Architecture (MDA) implies an increased need for research on the automation of the model-based test generation. This applies especially to embedded real-time system development where safety critical requirements must be met by a system. The following paper presents a methodology to derive basic Simulink test models from Simulink system models so as to execute them...
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Symbolic multibody models for digital-twin applications
PublicationSymbolic generation of multibody systems equations of motion appeared in the 1980s. In addition to their computational advantage over their numerical counterparts, symbolic models can be very easily and straightforwardly interfaced with a wide range of software environments and hardware devices. These two features place this approach in a pole position to participate and intervene in the design of digital twins for systems such...
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Differential models versus neural models in optimisation
PublicationW pracy porównano zastosowanie modeli różniczkowych i modeli neuronowych dla celów optymalizacji.
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Flow Process Models for Pipeline Diagnosis
PublicationThis chapter examines the problem of modeling and parameterization of the transmission pipeline flow process. First, the base model for discrete time is presented, which is a reference for other developed models. Then, the diagonal approximation (AMDA) method is proposed, in which the tridiagonal sub-matrices of the recombination matrix are approximated by their diagonal counterparts, which allows for a simple determination of...
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COMPARISON OF TWO MODELS OF CONDENSATION
PublicationIn the low-pressure part of steam turbine, the state path usually crosses the saturation line in penultimate stages. At least last two stages of this part of turbines operate in two –phase region. The liquid phase in this region in mainly created in the process of homogeneous and heterogeneous condensation. Several observations confirm however, that condensation often occurs earlier than it is predicted by theory i.e. before the...
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A Review of Hyperelastic Constitutive Models for Dielectric Elastomers
PublicationDielectric elastomers are smart materials that are essential components in soft systems and structures. The core element of a dielectric elastomer is soft matter, which is mainly rubber-like and elastomeric. These soft materials show a nonlinear behaviour and have a nonlinear strain-stress curve. The best candidates for modelling the nonlinear behaviour of such materials are hyperelastic strain energy functions. Hyperelastic functions...
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A review on analytical models of brushless permanent magnet machines
PublicationThis study provides an in-depth investigation of the use of analytical and numerical methods in analyzing electrical machines. Although numerical models such as the finite-element method (FEM) can handle complex geometries and saturation effects, they have significant computational burdens, are time-consuming, and are inflexible when it comes to changing machine geometries or input values. Analytical models based on magnetic equivalent...
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Diagnostic Models and Estimators for LDI in Transmission Pipelines
PublicationThis article considers and compares four analytical models of the pipeline flow process for leak detection and location tasks. The synthesis of these models is briefly outlined. Next, the methodology for generating data and diagnosing pipes is described, as well as experimental settings, assumptions and implemented scenarios. Finally, the quality of model-based diagnostic estimators has been evaluated for their bias, standard deviations...
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The role of traditional architectural models in the first stages of education.
PublicationThe oldest architectural models discovered by scientists date from the Middle Ages, while models or 1:1 scale prototypes were used in ancient times. Architectural miniatures quickly evolved into an indispensable tool for designers that enabled them to creatively express their thoughts and ideas. Mock-ups became a way of helping a designer communicate a concept, and their educational value was also recognised. The method of modelling,...
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Mathematical Models in Design Process of Ship Bow Thrusters
PublicationThe paper describes an application of simulation models for computer-aided design of ship bow thrusters. Generation of simulation models of ship bow thruster requires development and verifying of mathematical models of system component elements. Using the results of simulation the expert system is able to determine, that the rules of classification societies are met. Design procedures and mathematical models are part of an expert...
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Mathematical Models in Design Process of Ship Bow Thrusters
PublicationThe presentation is about an application of simulation models for computer-aided design of ship bow thrusters. Generation of simulation models of ship bow thruster requires development and verifying of mathematical models of system component elements. Using the results of simulation the expert system is able to determine, that the rules of classification societies are met. Design procedures and mathematical models are part of an...
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Overview of new product development strategies and models
PublicationMotivation: The motivation for the overview presented in this article is to provide a starting point for considering whether existing new product development methodology and its level of detail allows product teams to develop high-quality and business-effective product concepts. Aim: The aim of this article is recognise the current state of research into new product development methodology and to present the strategies and models...
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Modeling of medium flow processes in transportation pipelines - the synthesis of their state-space models and the analysis of the mathematical properties of the models for leak detection purposes
PublicationThe dissertation concerns the issue of modeling the pipeline flow process under incompressible and isothermal conditions, with a target application to the leak detection and isolation systems. First, an introduction to the model-based process diagnostics is provided, where its basic terminology, tools, and methods are described. In the following chapter, a review of the state of the art in the field of leak detection and isolation...
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Overview of new product development strategies and models
PublicationMotivation: The motivation for the overview presented in this article is to provide a starting point for considering whether existing new product development methodology and its level of detail allows product teams to develop high-quality and business-effective product concepts. Aim: The aim of this article is recognise the current state of research into new product development methodology and to present the strategies...
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Intelligent Decision Forest Models for Customer Churn Prediction
PublicationCustomer churn is a critical issue impacting enterprises and organizations, particularly in the emerging and highly competitive telecommunications industry. It is important to researchers and industry analysts interested in projecting customer behavior to separate churn from non‐churn consumers. The fundamental incentive is a firm’s intent desire to keep current consumers, along with the exorbitant expense of gaining new ones....
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Comparative testing of numerical models of river ice jams
PublicationIce processes in general, and ice jams in particular, play a dominant role in the hydrologic regime of Canadian rivers, often causing extreme floods and affecting the life cycle of many aquatic, terrestrial, and avian species. Various numerical models have been developed to help simulate the formation and consequences of these very dynamic and often destructive jam events. To test and compare the performance of existing models,...
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Rothe’s method for physiologically structured models with diffusion
PublicationWe consider structured population models with diffusion and dynamic boundary conditions. The respective approximation, called Rothe’s method, produces positive and exponentially bounded solutions. Its solutions converge to the exact solution of the original PDE.
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Integrate-and-fire models with an almost periodic input function
PublicationWe investigate leaky integrate-and-fire models (LIF models for short) driven by Stepanov and μ-almost periodic functions. Special attention is paid to the properties of the firing map and its displacement, which give information about the spiking behavior of the considered system. We provide conditions under which such maps are well-defined and are uniformly continuous. We show that the LIF models with Stepanov almost periodic...
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Identification of models and signals robust to occasional outliers
PublicationIn this paper estimation algorithms derived in the sense of the least sum of absolute errors are considered for the purpose of identification of models and signals. In particular, off-line and approximate on-line estimation schemes discussed in the work are aimed at both assessing the coefficients of discrete-time stationary models and tracking the evolution of time-variant characteristics of monitored signals. What is interesting,...
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Identification of models and signals robust to occasional outliers
PublicationIn this paper estimation algorithms derived in the sense of the least sum of absolute errors are considered for the purpose of identification of models and signals. In particular, off-line and approximate on-line estimation schemes discussed in the work are aimed at both assessing the coefficients of discrete-time stationary models and tracking the evolution of time-variant characteristics of monitored signals. What is interesting,...
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Dynamic Bankruptcy Prediction Models for European Enterprises
PublicationThis manuscript is devoted to the issue of forecasting corporate bankruptcy. Determining a firm’s bankruptcy risk is one of the most interesting topics for investors and decision-makers. The aim of the paper is to develop and to evaluate dynamic bankruptcy prediction models for European enterprises. To conduct this objective, four forecasting models are developed with the use of four different methods—fuzzy sets, recurrent and...
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4D Models in World Wide Web
PublicationThe paper presents some results of research curried out within the framework of the European project named "Cultural Heritage Through Time" (CHT2). One of the main project aims were to develop a methodology for sharing multi-temporal information via the Internet (webGIS) for remote analysis of structures and landscapes over time. Reported in this paper results are focused on testing two technologies (Hexagon and Esri) for online...
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Aleksandra Parteka dr hab. inż.
PeopleAbout me: I am an associate professor and head of doctoral studies at the Faculty of Management and Economics, Gdansk University of Technology (GdanskTech, Poland). I got my MSc degree in Economics from Gdansk University of Technology (2003) and Universita’ Politecnica delle Marche (2005), as well as MA degree in Contemporary European Studies from Sussex University (2006, with distinction). I received my PhD in Economics...
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Towards New Mappings between Emotion Representation Models
PublicationThere are several models for representing emotions in affect-aware applications, and available emotion recognition solutions provide results using diverse emotion models. As multimodal fusion is beneficial in terms of both accuracy and reliability of emotion recognition, one of the challenges is mapping between the models of affect representation. This paper addresses this issue by: proposing a procedure to elaborate new mappings,...
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Uniform Model Interface for Assurance Case Integration with System Models
PublicationAssurance cases are developed and maintained in parallel with corresponding system models and therefore need to reference each other. Managing the correctness and consistency of interrelated safety argument and system models is essential for system dependability and is a nontrivial task. The model interface presented in this paper enables a uniform process of establishing and managing assurance case references to various types...
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Models of using the Internet by young Poles and their social capital.
PublicationHighlights • Study examining Polish youth on internet usage styles. • Online communication is the most common form of spending time on the Internet. •...
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Evaluation of Lombard Speech Models in the Context of Speech in Noise Enhancement
PublicationThe Lombard effect is one of the most well-known effects of noise on speech production. Speech with the Lombard effect is more easily recognizable in noisy environments than normal natural speech. Our previous investigations showed that speech synthesis models might retain Lombard-effect characteristics. In this study, we investigate several speech models, such as harmonic, source-filter, and sinusoidal, applied to Lombard speech...
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Looking for Social Enterprise Models in Poland: institutional and historical context
PublicationThe paper is an attempt at identification of key social enterprise models in Poland. The authors recognize three models: entrepreneurial non-profit organizations, cooperatives as well as social integration clubs and centres. Their social and institutional background is presented together with institutional trajectories of social enterprise development.
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Fuzzy Methods and Models for a Team-Building Process
PublicationThis chapter contains an introduction to fuzzy-logic model-based approaches for a team-building process. Such appraches allow extending typical recruiting practice and selection processes to enable a wider and more precise assessment of a new team and/or existing team members, taking into account both their hard and soft skills. Moreover, as effectiveness of teams depends on the interpersonal skills and emotional intelligence...
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The Comparison of the Web GIS Applications Relevant for 4D Models Sharing
PublicationThe paper presents results of the project: Cultural Heritage Through Time (CHT 2, http://cht2-project.eu) realized accomplished within the framework of the “Joint Programming Initiative in Cultural Heritage” JPI-CH (http://www.jpi-culturalheritage.eu) by an international consortium: Politecnico di Milano (IT), Newcastle University (UK), Salamanca University (ES), and Stanislaw Staszic Scientific Association SSSA (a non-profit...
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A Hyperdense Semantic Domain for Discontinuous Behavior in Physical System Models
PublicationMultiple time models have been proposed for the formalization of hybrid dynamic system behavior. The superdense notion of time is a well-known time model for describing event-based systems where several events can occur simultaneously. Hyperreals provide a domain for defining the semantics of hybrid models that is elegantly aligned with first principles in physics. This paper discusses the value of both time models and shows how...
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Online brand communities’ contribution to digital business models
PublicationAbstract Purpose – There is limited research examining social drivers and mediators of online brand community identification in the context of business models development. This study aims to identify them behind the social mechanisms and present essential factors which should be applied in business models to foster value co-creation. Design/methodology/approach – Data were collected from a convenience sample of 712 cases gathered among...
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Training of Deep Learning Models Using Synthetic Datasets
PublicationIn order to solve increasingly complex problems, the complexity of Deep Neural Networks also needs to be constantly increased, and therefore training such networks requires more and more data. Unfortunately, obtaining such massive real world training data to optimize neural networks parameters is a challenging and time-consuming task. To solve this problem, we propose an easy-touse and general approach to training deep learning...
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Injury Prediction Models for Onshore Road Network Development
PublicationIntegrating different modes of transport (road, rail, air and water) is important for port cities. To accommodate this need, new transport hubs must be built such as airports or sea ports. If ports are to grow, they must be accessible, a feature which is best achieved by building new roads, including fast roads. Poland must develop a network of fast roads that will provide good access to ports. What is equally important is to upgrade...
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Comparative analysis of different numerical models of a steel radial gate
PublicationHydrotechnical structures are important components in water management system and general flooding safety. Their reliability should be ensured since potential damage might lead to catastrophic consequences. Weir gates are considered to be highly vulnerable elements of each hydro power plant, with regard to its dynamic resistance. The aim of the paper is to compare different numerical models and their influence on the results of...
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Local hidden–variable models for entangled quantum states
PublicationWhile entanglement and violation of Bell inequalities were initially thought to be equivalent quantum phenomena, we now have different examples of entangled states whose correlations can be described by local hidden-variable models and, therefore, do not violate any of the Bell inequalities. We provide an up-to-date overview of the existing literature regarding local hidden-variable models for entangled quantum states, in both...
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Numerical simulation of asphalt mixtures fracture using continuum models
PublicationThe paper considers numerical models of fracture processes of semi-circular asphalt mixture specimens subjected to three-point bending. Parameter calibration of the asphalt mixture constitutive models requires advanced, complex experimental test procedures. The highly non-homogeneous material is numerically modelled by a quasicontinuum model. The computational parameters are averaged data of the components, i.e. asphalt, aggregate...
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Equivalent single-layer models in deformation analysis of laminated multilayered plates
PublicationThe performance of selected Equivalent Single-Layer (ESL) models is evaluated within several classical benchmark tests for linear static analysis of multi-layered plates. The authors elaborated their own Finite Element software based on the first-order shear deformation theory (FOSD) with some modifications incorporated including a correction of the transverse shear stiffness and an application of zig-zag type functions. Seven...
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Review of ship safety domains: Models and applications
PublicationShip safety domain is a term which is widely used in research on collision avoidance and traffic engineering among others. Classic ship domains have been compared in multiple reports. However, up till now there has been no work summing up contemporary research in this field. The paper offers a systematic and critical review of the newer ship domain models and related research. It discusses multiple differences in approach to ship...
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Polymodal Method of Improving the Quality of Photogrammetric Images and Models
PublicationPhotogrammetry using unmanned aerial vehicles has become very popular and is already commonly used. The most frequent photogrammetry products are an orthoimage, digital terrain model and a 3D object model. When executing measurement flights, it may happen that there are unsuitable lighting conditions, and the flight itself is fast and not very stable. As a result, noise and blur appear on the images, and the images themselves can...
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Naturally-derived hydrogels for 3D pancreatic tumor models: A short review
PublicationStatistics suggest a high proportion of mortality rate by pancreatic cancer, which is a solid tumor characterized by high heterogeneity and the presence of a complex extracellular matrix. The very low effectiveness of pancreatic cancer treatment roots in the high metastatic potential and drug resistance of this tumor. Therefore, the quest for efficient cellular models enabling precise mimicking in vivo conditions, and anticancer...
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Improvement of Task Management with Process Models in Small and Medium Software Companies
PublicationSmall and medium software companies exhibit many special features that give reason for a dedicated approach to process improvement. They often cannot afford implementing maturity models or quality standards both in terms of time and money. Instead, they expect simpler solutions that can allow to run projects in more systematic and repeatable way, increase quality and knowledge management. In this paper, we present a method focused...
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Selected Propagation Models Modification for Application in Container Terminal
PublicationIt is particularly important to look for any propagation model that could be useful for designing mobile radio systems in container terminal environment. The selected propagation models have been investigated. The applied research methodology has been described too. Results of the statistical adjustment in terms of signal loss determination in such environment have been analysed. The analysis have proved effectiveness of adjustment...
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Drug Discovery Today: Disease Models
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APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY
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MATHEMATICAL MODELS & METHODS IN APPLIED SCIENCES
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The first International Comparative Social Enterprise Models Working Paper: Poland
PublicationIn this paper, social enterprise models: entrepreneurial nonprofit organizations, cooperatives and vocational enterprises for the disabled are presented. Their emergence and institutionalization in the Polish social enterprise organizations landscape is provided and analysed. Also, the authors point to the convergences and divergences between these three models. Additionally historical background and institutional trajectories...