wyświetlamy 1000 najlepszych wyników Pomoc
Wyniki wyszukiwania dla: IDENTIFICATION OF NONSTATIONARY PROCESSES, SELECTION OF MODEL ORDER, SELECTION OF ESTIMATION MEMORY
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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
PublikacjaThe 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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On joint order and bandwidth selection for identification of nonstationary autoregressive processes
PublikacjaWhen 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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On Noncausal Identification of Nonstationary Multivariate Autoregressive Processes
PublikacjaThe 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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Regularized Local Basis Function Approach to Identification of Nonstationary Processes
PublikacjaThe problem of identification of nonstationary stochastic processes (systems or signals) is considered and a new class of identification algorithms, combining the basis functions approach with local estimation technique, is described. Unlike the classical basis function estimation schemes, the proposed regularized local basis function estimators are not used to obtain interval approximations of the parameter trajectory, but provide...
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Generalized Savitzky–Golay filters for identification of nonstationary systems
PublikacjaThe problem of identification of nonstationary systems using noncausal estimation schemes is consid-ered and a new class of identification algorithms, combining the basis functions approach with localestimationtechnique,isdescribed.Unliketheclassicalbasisfunctionestimationschemes,theproposedlocal basis function estimators are not used to obtain interval approximations of the parametertrajectory, but provide a sequence of point...
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Zdzisław Kowalczuk prof. dr hab. inż.
OsobyW 1978 ukończył studia w zakresie automatyki i informatyki na Wydziale Elektroniki Politechniki Gdańskiej, następnie rozpoczął pracę na macierzystej uczelni. W 1986 obronił pracę doktorską, w 1993 habilitował się na Politechnice Śląskiej na podstawie pracy Dyskretne modele w projektowaniu układów sterowania. W 1996 mianowany profesorem nadzwyczajnym, w 2003 otrzymał tytuł profesora nauk technicznych. W 2006 założył i od tego czasu...
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On adaptive covariance and spectrum estimation of locally stationary multivariate processes
PublikacjaWhen estimating the correlation/spectral structure of a locally stationary process, one has to make two important decisions. First, one should choose the so-called estimation bandwidth, inversely proportional to the effective width of the local analysis window, in the way that complies with the degree of signal nonstationarity. Too small bandwidth may result in an excessive estimation bias, while too large bandwidth may cause excessive...
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Locally Adaptive Cooperative Kalman Smoothing and Its Application to Identification of Nonstationary Stochastic Systems
PublikacjaOne of the central problems of the stochastic approximation theory is the proper adjustment of the smoothing algorithm to the unknown, and possibly time-varying, rate and mode of variation of the estimated signals/parameters. In this paper we propose a novel locally adaptive parallel estimation scheme which can be used to solve the problem of fixed-interval Kalman smoothing in the presence of model uncertainty. The proposed solution...
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New results on estimation bandwidth adaptation
PublikacjaThe problem of identification of a nonstationary autoregressive signal using non-causal estimation schemes is considered. Noncausal estimators can be used in applications that are not time-critical, i.e., do not require real-time processing. A new adaptive estimation bandwidth selection rule based on evaluation of pseudoprediction errors is proposed, allowing one to adjust tracking characteristics of noncausal estimators to unknown...
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A Computationally Efficient Model for Predicting Successful Memory Encoding Using Machine-Learning-based EEG Channel Selection
PublikacjaComputational cost is an important consideration for memory encoding prediction models that use data from dozens of implanted electrodes. We propose a method to reduce computational expense by selecting a subset of all the electrodes to build the prediction model. The electrodes were selected based on their likelihood of measuring brain activity useful for predicting memory encoding better than chance (in terms of AUC). A logistic...
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Identification of nonstationary processes using noncausal bidirectional lattice filtering
PublikacjaThe problem of off-line identification of a nonstationary autoregressive process with a time-varying order and a time-varying degree of nonstationarity is considered and solved using the parallel estimation approach. The proposed parallel estimation scheme is made up of several bidirectional (noncausal) exponentially weighted lattice algorithms with different estimation memory and order settings. It is shown that optimization of...
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Emilia Miszewska dr inż.
OsobyEmilia Miszewska urodziła się w 1986 roku w Gdańsku. Ukończyła Szkołę Podstawową nr 17 w Gdańsku z klasami sportowymi o profilu pływanie oraz Liceum Sportowe nr 11 im. Janusza Kusocińskiego w Gdańsku. W 2005 roku rozpoczęła jednolite studia magisterskie na Wydziale Inżynierii Lądowej i Środowiska, które ukończyła w roku 2011, broniąc pracę dyplomową pt. „Analiza i opracowanie wytycznych zabezpieczenia pożarowego oraz planu...
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Wykorzystanie algorytmów ewolucyjnych do doboru wzmocnień rozszerzonego obserwatora prędkości maszyny indukcyjnej
PublikacjaW pracy opisano sposób doboru wzmocnień rozszerzonego obserwatora prędkości maszyny indukcyjnej przy wykorzystaniu algorytmów ewolucyjnych. Zaproponowano funkcję celu opartą na rozkładzie biegunów obserwatora. Ze względu na wpływ prędkości maszyny na dynamikę obserwatora zaproponowano dobór wzmocnień obserwatora dla różnych przedziałów prędkości. Dla poszczególnych przedziałów zaprezentowano wyniki doboru wzmocnień w postaci tabel...
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The Optimal Location of Ground-Based GNSS Augmentation Transceivers
PublikacjaModern Global Navigation Satellite Systems (GNSS) allow for positioning with accuracies ranging from tens of meters to single millimeters depending on user requirements and available equipment. A major disadvantage of these systems is their unavailability or limited availability when the sky is obstructed. One solution is to use additional range measurements from ground-based nodes located in the vicinity of the receiver. The highest...
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Balanced Spider Monkey Optimization with Bi-LSTM for Sustainable Air Quality Prediction
PublikacjaA reliable air quality prediction model is required for pollution control, human health monitoring, and sustainability. The existing air quality prediction models lack efficiency due to overfitting in prediction model and local optima trap in feature selection. This study proposes the Balanced Spider Monkey Optimization (BSMO) technique for effective feature selection to overcome the local optima trap and overfitting problems....
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STRATEGIA DOBORU PROCESU PRODUKCYJNEGO WG. REAKCJI NA ZAMÓWIENIA KLIENTA
PublikacjaW opracowaniu poruszono zagadnienie doboru strategii wytwarzania w zakresie procesu produkcyjnego. W ramach tego zagadnienia dokonano podziału procesów produkcyjnych wg różnych kryteriów. Skupiano się na podziale procesów wg. reakcji na zamówienia klienta. Przedstawiono pokrótce najistotniejsze cechy charakteryzujące tego typu procesy. By móc określić strategię w zakresie procesu produkcyjnego zestawiono kryteria wyboru procesu...
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Analiza właściwości rozszerzonego obserwatora prędkości maszyny indukcyjnej
PublikacjaRozszerzony obserwator prędkości został zaproponowany przez prof. Krzemińskiego i jest oparty na rozszerzonym modelu maszyny indukcyjnej, gdzie wprowadzona został nowa zmienna ζ. Jest to nowe podejście do estymacji zmiennych stanu maszyny indukcyjnej i nie wszystkie problemy zostały do tej pory rozwiązane. Zaproponowano wykorzystanie algorytmów ewolucyjnych do doboru wzmocnień obserwatora. W celu redukcji nakładów obliczeniowych...
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On adaptive selection of estimation bandwidth for analysis of locally stationary multivariate processes
PublikacjaWhen estimating the correlation/spectral structure of a locally stationary process, one should choose the so-called estimation bandwidth, related to the effective width of the local analysis window. The choice should comply with the degree of signal nonstationarity. Too small bandwidth may result in an excessive estimation bias, while too large bandwidth may cause excessive estimation variance. The paper presents a novel method...
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Automated Reduced Model Order Selection
PublikacjaThis letter proposes to automate generation of reduced-order models used for accelerated -parameter computation by applying a posteriori model error estimators. So far,a posteriori error estimators were used in Reduced Basis Method (RBM) and Proper Orthogonal Decomposition (POD) to select frequency points at which basis vectors are generated. This letter shows how a posteriori error estimators can be applied to automatically select...
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Neural Approximators for Variable-Order Fractional Calculus Operators (VO-FC)
PublikacjaThe paper presents research on the approximation of variable-order fractional operators by recurrent neural networks. The research focuses on two basic variable-order fractional operators, i.e., integrator and differentiator. The study includes variations of the order of each fractional operator. The recurrent neural network architecture based on GRU (Gated Recurrent Unit) cells functioned as a neural approximation for selected...
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OOA-modified Bi-LSTM network: An effective intrusion detection framework for IoT systems
PublikacjaCurrently, the Internet of Things (IoT) generates a huge amount of traffic data in communication and information technology. The diversification and integration of IoT applications and terminals make IoT vulnerable to intrusion attacks. Therefore, it is necessary to develop an efficient Intrusion Detection System (IDS) that guarantees the reliability, integrity, and security of IoT systems. The detection of intrusion is considered...
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Automatic Reduction-Order Selection for Finite-Element Macromodels
PublikacjaAn automatic reduction-order selection algorithm for macromodels in finite-element analysis is presented. The algorithm is based on a goal-oriented a posteriori error estimator that operates on low-order reduced blocks of matrices, and hence, it can be evaluated extremely quickly.
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On noncausal identification of nonstationary stochastic systems
PublikacjaIn this paper we consider the problem of noncausal identification of nonstationary,linear stochastic systems, i.e., identification based on prerecorded input/output data. We show how several competing weighted least squares parameter smoothers, differing in memory settings, can be combined together to yield a better and more reliable smoothing algorithm. The resulting parallel estimation scheme automatically adjusts its smoothing...
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Multiplicative Long Short-Term Memory with Improved Mayfly Optimization for LULC Classification
PublikacjaLand Use and Land Cover (LULC) monitoring is crucial for global transformation, sustainable land control, urban planning, urban growth prediction, and the establishment of climate regulations for long-term development. Remote sensing images have become increasingly important in many environmental planning and land use surveys in recent times. LULC is evaluated in this research using the Sat 4, Sat 6, and Eurosat datasets. Various...
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Lattice filter based autoregressive spectrum estimation with joint model order and estimation bandwidth adaptation
PublikacjaThe 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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Lattice filter based multivariate autoregressive spectral estimation with joint model order and estimation bandwidth adaptation
PublikacjaThe 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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Intracranial hemorrhage detection in 3D computed tomography images using a bi-directional long short-term memory network-based modified genetic algorithm
PublikacjaIntroduction: 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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Selection of Visual Descriptors for the Purpose of Multi-camera Object Re-identification
PublikacjaA comparative analysis of various visual descriptors is presented in this chapter. The descriptors utilize many aspects of image data: colour, texture, gradient, and statistical moments. The descriptor list is supplemented with local features calculated in close vicinity of key points found automatically in the image. The goal of the analysis is to find descriptors that are best suited for particular task, i.e. re-identification...
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On noncausal weighted least squares identification of nonstationary stochastic systems
PublikacjaIn this paper, we consider the problem of noncausal identification of nonstationary, linear stochastic systems, i.e., identification based on prerecorded input/output data. We show how several competing weighted (windowed) least squares parameter smoothers, differing in memory settings, can be combined together to yield a better and more reliable smoothing algorithm. The resulting parallel estimation scheme automatically adjusts...
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Towards Robust Identification of Nonstationary Systems
PublikacjaThe article proposes a fast, two-stage method for the identification of nonstationary systems. The method uses iterative reweighting to robustify the identification process against the outliers in the measurement noise and against the numerical errors that may occur at the first stage of identification. We also propose an adaptive algorithm to optimize the values of the hyperparameters that are crucial for this new method.
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Estimation of the size of informal employment based on administrative records with non‐ignorable selection mechanism
PublikacjaIn 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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Two-Stage Identification of Locally Stationary Autoregressive Processes and its Application to the Parametric Spectrum Estimation
PublikacjaThe 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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On the preestimation technique and its application to identification of nonstationary systems
PublikacjaThe problem of noncausal identification of a nonstationary stochastic FIR (finite impulse response) sys- tem is reformulated, and solved, as a problem of smoothing of preestimated parameter trajectories. Three approaches to preestimation are critically analyzed and compared. It is shown that optimization of the smoothing operation can be performed adaptively using the parallel estimation technique. The new approach is computationally...
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A Universal Gains Selection Method for Speed Observers of Induction Machine
PublikacjaProperties of state observers depend on proper gains selection. Each method of state estimation may require the implementation of specific techniques of finding those gains. The aim of this study is to propose a universal method of automatic gains selection and perform its verification on an induction machine speed observer. The method utilizes a genetic algorithm with fitness function which is directly based on the impulse response...
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IDENTYFIKACJA CZYNNIKÓW WPŁYWAJĄCYCH NA BEZPIECZEŃSTWO EKSPLOATACJI STATKU NA ŚRÓDLĄDOWEJ DRODZE WODNEJ W DELCIE WISŁY
PublikacjaKażdego roku w Polsce, na śródlądowych drogach wodnych rejestrowane są przez Urzędy Żeglugi Śródlądowej, Państwową Straż Pożarną i Policję wypadki i incydenty, prowadzące zarówno do uszkodzenia infrastruktury jak i uszczerbku na zdrowiu. Poprawa poziomu bezpieczeństwa wymaga dogłębnej analizy i wyciągania wniosków z zaistniałych sytuacji awaryjnych. Istotną rzeczą jest identyfikacja i usystematyzowanie zagrożeń występujących w...
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Comparison and Analysis of Service Selection Algorithms
PublikacjaIn Service Oriented Architecture, applications are developed by integration of existing services in order to reduce development cost and time. The approach, however, requires algorithms that select appropriate services out of available, alternative ones. The selection process may consider both optimalization requirements, such as maximalization of performance, and constraint requirements, such minimal security or maximum development...
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An Attempt to Develop a Model Selection Algorithm of Computer Simulation during the Design Process of Mechanical Response of Any Mechanical Body
PublikacjaIn the literature, there are algorithms associated with the design of simulations of technological processes, in which the material model has always been defined previously. However, in none of the studies of computer simulation modelling of technological processes known to the authors of this article, is there a detailed description of how the algorithm, or the selection of plastic model used, is subject to this process. This...
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An attempt to develop a model selection algorithm of computer simulation during the design process of mechanical response of any mechanical body
Publikacjan the literature, there are algorithms associated with the design of simulations of technological processes, in which the material model has always been defined previously. However, in none of the studies of computer simulation modelling of technological processes known to the authors of this article, is there a detailed description of how the algorithm, or the selection of plastic model used, is subject to this process. This article...
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GENETICS SELECTION EVOLUTION
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Hydrauliczna wiarygodność wyników pomiarów terenowych stosowanych do identyfikacji oporności hydraulicznej przewymiarowanych sieci wodociągowych
PublikacjaPublikacja zawiera zalecenia metodyczne dotyczące identyfikacji oporności hydraulicznej w przewymiarowanych sieciach wodociągowych na tle spotykanych nieprawidłowości. Krytycznie oceniono wyniki pomiarów terenowych, które zastosowano do tarowania komputerowych modeli przepływów (KMP) pomimo, że nie spełniały kryterium hydraulicznej wiarygodności. Ponadto zaproponowano spadek hydrauliczny jako obiektywny wskaźnik wiarygodności pomiarów,...
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Fast Basis Function Estimators for Identification of Nonstationary Stochastic Processes
PublikacjaThe problem of identification of a linear nonsta-tionary stochastic process is considered and solved using theapproach based on functional series approximation of time-varying parameter trajectories. The proposed fast basis func-tion estimators are computationally attractive and yield resultsthat are better than those provided by the local least squaresalgorithms. It is shown that two...
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Interoperability Constraints in Service Selection Algorithms
PublikacjaIn Service Oriented Architecture, composite applications are developed by integration of existing, atomic services that may be available in alternative versions realizing the same functionality but having different Quality of Service (QoS) attributes. The development process requires effective service selection algorithms that balance profits and constraints of QoS attributes. Additionally, services operate in a heterogeneous environment,...
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Local basis function estimators for identification of nonstationary systems
PublikacjaThe problem of identification of a nonstationary stochastic system is considered and solved using local basis function approximation of system parameter trajectories. Unlike the classical basis function approach, which yields parameter estimates in the entire analysis interval, the proposed new identification procedure is operated in a sliding window mode and provides a sequence of point (rather than interval) estimates. It is...
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Extending Service Selection Algorithms with Interoperability Analysis
PublikacjaApplication development by integration of existing, atomic services reduces development cost and time by extensive reuse of service components. In Service Oriented Architecture, there exist alternative versions of services supplying the same functionality but differing in Quality of Service (QoS) attributes, which enables developers to select services with optimal QoS. Existing algorithms of service selection focus on the formal...
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Selection Pressure in the Evolutionary Path Planning Problem
PublikacjaThis article compares an impact of using various post-selection methods on the selection pressure and the quality of the solution for the problem of planning the path for a moving object using the evolutionary method. The concept of selection pressure and different methods of post-selection are presented. Article analyses behaviour of post-selection for four options of evolutionary algorithms. Based on the results achieved, waveform...
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Smart Karyotyping Image Selection Based on Commonsense Knowledge Reasoning
PublikacjaKaryotyping requires chromosome instances to be segmented and classified from the metaphase images. One of the difficulties in chromosome segmentation is that the chromosomes are randomly positioned in the image, and there is a great chance for chromosomes to be touched or overlap with others. It is always much easier for operators and automatic programs to tackle images without overlapping chromosomes than ones with largely overlapped...
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Wydajność przetwarzania żądań usług uwarunkowanych czasowo realizowanych w sieci IMS/NGN
PublikacjaW rozprawie dokonano przeglądu stanu implementacji koncepcji IMS/NGN, a także modeli systemów obsługi z oczekiwaniem pod kątem zastosowania dla serwerów i łączy w modelu analitycznym wielodomenowej sieci IMS/NGN. Przedstawiono założenia dla tego modelu oraz metodologię obliczeń i analizy wyników: średnich czasów E(CSD) zestawiania i E(CDD) rozłączenia połączenia dla scenariuszy połączeń zakończonych sukcesem. Opisano założenia,...
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Clonal selection algorithm for vehicle routing
PublikacjaOver the years several successful computing techniques have been inspired by biological mechanisms. Studies of the mechanisms that allow the immune systems of vertebratesto adapt and learn have resulted in a class of algorithms called artificial immune systems. Clonal selection is a process that allows lymphocytes to launch a quick response to known pathogens and to adapt to new, previously unencountered ones. This paper presents...
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A new look at the statistical identification of nonstationary systems
PublikacjaThe paper presents a new, two-stage approach to identification of linear time-varying stochastic systems, based on the concepts of preestimation and postfiltering. The proposed preestimated parameter trajectories are unbiased but have large variability. Hence, to obtain reliable estimates of system parameters, the preestimated trajectories must be further filtered (postfiltered). It is shown how one can design and optimize such...
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Local Texture Pattern Selection for Efficient Face Recognition and Tracking
PublikacjaThis paper describes the research aimed at finding the optimal configuration of the face recognition algorithm based on local texture descriptors (binary and ternary patterns). Since the identification module was supposed to be a part of the face tracking system developed for interactive wearable computer, proper feature selection, allowing for real-time operation, became particularly important. Our experiments showed that it is...
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Deep Learning Optimization for Edge Devices: Analysis of Training Quantization Parameters
PublikacjaThis paper focuses on convolution neural network quantization problem. The quantization has a distinct stage of data conversion from floating-point into integer-point numbers. In general, the process of quantization is associated with the reduction of the matrix dimension via limited precision of the numbers. However, the training and inference stages of deep learning neural network are limited by the space of the memory and a...
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An automatic selection of optimal recurrent neural network architecture for processes dynamics modelling purposes
PublikacjaA problem related to the development of algorithms designed to find the structure of artificial neural network used for behavioural (black-box) modelling of selected dynamic processes has been addressed in this paper. The research has included four original proposals of algorithms dedicated to neural network architecture search. Algorithms have been based on well-known optimisation techniques such as evolutionary algorithms and...
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INTERNATIONAL JOURNAL OF SELECTION AND ASSESSMENT
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EVALUATION OF THE SEMIVARIOGRAM SELECTION ON THE KRIGING INTERPOLATION
PublikacjaThe aim of the paper is to present the possibilities of geostatistical interpolation kriging method using in the process of generating digital terrain models (DTM). The source of data is a direct measurements realized with a precision GNSS positioning kinematic measurement technique RTN. Kriging algorithm was analysed, especially in the meaning of a semivariogram every step. Theoretical semivariogram selection influence on the...
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Learning and memory processes in autonomous agents using an intelligent system of decision-making
PublikacjaThis paper analyzes functions and structures of the memory that is an indispensable part of an Intelligent System of Decision-making (ISD), developed as a universal engine for autonomous robotics. A simplified way of processing and coding information in human cognitive processes is modelled and adopted for the use in autonomous systems. Based on such a knowledge structure, an artificial model of reality representation and a model...
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Learning and memory processes in autonomous agents using an intelligent system of decision-making
PublikacjaThis paper analyzes functions and structures of the memory that is an indispensable part of an Intelligent System of Decision-making (ISD), developed as a universal engine for autonomous robotics. A simplified way of processing and coding information in human cognitive processes is modelled and adopted for the use in autonomous systems. Based on such a knowledge structure, an artificial model of reality representation and a model...
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Frequencies selection for accelerated cnls parameter identification of anticorrosion coatings
PublikacjaArtykuł przedstawia zmodyfikowaną metodę CNLS dopasowywania widma impedancyjnego dla identyfikacji parametrów obiektów technicznych. Liczba częstotliwości pomiarowych została ograniczona do liczby identyfikowanych parametrów, a ich wartości są dobierane w oparciu o różne kryteria. Jako obiekt testowy wybrano model powłoki antykorozyjnej. Wyniki symulowanej identyfikacji przeanalizowano pod kątem dokładności i zmniejszenia czasu...
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Selection of Relevant Features for Text Classification with K-NN
PublikacjaIn this paper, we describe five features selection techniques used for a text classification. An information gain, independent significance feature test, chi-squared test, odds ratio test, and frequency filtering have been compared according to the text benchmarks based on Wikipedia. For each method we present the results of classification quality obtained on the test datasets using K-NN based approach. A main advantage of evaluated...
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Criteria for evaluation and selection of the best offer for the Contract Engineer service
PublikacjaThe purpose of the legal regulations regarding public procurement in EU countries is to ensure effective funds' spending. When assessing and selecting the best offer, the contracting entities have at their disposal many different criteria, including non-price criteria. Their proper selection and application is necessary to ensure the high quality of the ordered product, delivery or service. Making an order for intellectual services,...
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A solvent selection guide based on chemometrics and multicriteria decision analysis
PublikacjaThe selection of suitable solvents is a crucially important subject in a wide range of chemical processes. This study presents a solvent selection guide where 151 solvents were assessed, including a significant number of recently reported bio-based solvents. The assessment procedure involves grouping of solvents according to their physicochemical parameters and ranking within clusters according to their toxicological and hazard...
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Comparison of Selection Schemes in Evolutionary Method of Path Planning
PublikacjaThis article compares an impact of using various selection schemes on the quality of the solution for the problem of planning the path for a moving object using the evolutionary method. In study case problem of avoiding collisions at sea is analyzed. The modelled environment includes static constraints (lands, canals, etc.) and dynamic objects (moving ships). Article analyses behaviour of selection schemes in two similar environments...
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Criteria for selection of working fluid in low-temperature ORC
PublikacjaThe economics of an ORC system is strictly linked to thermodynamic properties of the working fluid. A bad choice of working fluid could lead to a less efficient and expensive plant/generation unit. Some selection criteria have been put forward by various authors, incorporating thermodynamic properties, provided in literature but these do not have a general character. In the paper a simple analysis has been carried out which resulted...
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Embedded gas sensing setup for air samples analysis
PublikacjaThis paper describes a measurement setup (eNose) designed to analyze air samples containing various volatile organic compounds (VOCs). The setup utilizes a set of resistive gas sensors of divergent gas selectivity and sensitivity. Some of the applied sensors are commercially available and were proposed recently to reduce their consumed energy. The sensors detect various VOCs at sensitivities determined by metal oxide sensors’ technology...
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Computer experiments with a parallel clonal selection algorithm for the graph coloring problem
PublikacjaArtificial immune systems (AIS) are algorithms that are based on the structure and mechanisms of the vertebrate immune system. Clonal selection is a process that allows lymphocytes to launch a quick response to known pathogens and to adapt to new, previously unencountered ones. This paper presents a parallel island model algorithm based on the clonal selection principles for solving the Graph Coloring Problem. The performance of...
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The Selection of Anchoring System for Floating Houses by Means of AHP Method
PublikacjaThis paper indicates and analyses the use of anchoring systems, such as mooring piles, booms, mooring cables, and deadweight anchors with additional elastic connectors, which are the most frequently applied by the producers of floating houses. The selection of the most advantageous anchoring system is complicated and requires the application of quantitative and qualitative data and methods. This publication presents the results...
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A Clustering-Based Methodology for Selection of Fault Tolerance Techniques
PublikacjaDevelopment of dependable applications requires selection of appropriate fault tolerance techniques that balance efficiency in fault handling and resulting consequences, such as increased development cost or performance degradation. This paper describes an advisory system that recommends fault tolerance techniques considering specified development and runtime application attributes. In the selection process, we use the K-means...
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Selection of DES for biotrickling filtration of air polluted with hexane and cyclohexane
Dane BadawczeDataset covers selected data collected during selection of deep eutectic solvent (DES) additive to mineral salt medium (MSM) as a liquid phase during biotrickling filtration of air polluted with hexane and cyclohexane.
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Selection of Features for Multimodal Vocalic Segments Classification
PublikacjaEnglish speech recognition experiments are presented employing both: audio signal and Facial Motion Capture (FMC) recordings. The principal aim of the study was to evaluate the influence of feature vector dimension reduction for the accuracy of vocalic segments classification employing neural networks. Several parameter reduction strategies were adopted, namely: Extremely Randomized Trees, Principal Component Analysis and Recursive...
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Prediction based on integration of Decisional DNA and a feature selection algorithm Relief-F
PublikacjaThe paper presents prediction model based on Decisional DNA and Set of experienced integrated with Relief_F algorithm for feature selection
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Chemometrics for Selection, Prediction, and Classification of Sustainable Solutions for Green Chemistry—A Review
PublikacjaIn this review, we present the applications of chemometric techniques for green and sustainable chemistry. The techniques, such as cluster analysis, principal component analysis, artificial neural networks, and multivariate ranking techniques, are applied for dealing with missing data, grouping or classification purposes, selection of green material, or processes. The areas of application are mainly finding sustainable solutions...
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Selection of derivatisation agents for chlorophenols determination with multicriteria decision analysis
PublikacjaThe paper shows very systematic method of selection of derivatisation agents for a given group of analytes. In this study 8 derivatisation agents are assessed for their capability to derivatise 8 chlorophenols. Multicriteria decision analysis is used to combine many objectives of derivatisation agents selection into single, easy to be interpreted numerical value. Three basic analyses were performed to obtain rankings with the aims...
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Design and material selection for a patient transport device in field hospitals
PublikacjaACKGROUND: A major cause of patient and hospital worker injuries occurs transferring patients between two planes. The main aim of this paper was to propose a design of patient’s lift and transfer apparatus for use in field hospitals. The assumption was to design lightweight, durable and ergonomic device using innovative material. The authors concentrated on partial elimination of manual lifting in order to device could work both...
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On Adaptive Spectrum Estimation of Multivariate Autoregressive Locally Stationary Processes
PublikacjaAutoregressive 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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Application of TOPSIS for Selection and Assessment of Analytical Procedures for Ibuprofen Determination in Wastewater
PublikacjaThis paper describes the possible implementation of the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) as green analytical chemistry metrics tools. TOPSIS is one of the multi-criteria decision analysis (MCDA) tools that is applied in the selection of the best alternative from many possible. In this case we have applied it to assess the nineteen analytical procedures for ibuprofen determination in wastewater...
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Parameter selection of an adaptive PI state observer for an induction motor
PublikacjaThe paper discusses problems connected with the parameters selection of the proportional-integral observer, designed for recon- struction of magnetic fluxes and angular speed of an induction motor. The selection is performed in several stages that are focused on different criteria. The first stage consists in selecting observer’s gains and provides desired dynamical properties, taking into consideration immunity to disturbances and...
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Selection of main engines for hopper suction dredgers with the use oobability models
PublikacjaThis paper presents a new original method of selection of main engines for hopper suction dredgers with regard to probabilistic models. It was proposed to use the normal distribution to describe the operational loads of the main receivers. The principles for determination of parameters of load distribution and design power of the main engines were formulated. Lastly, the principles of selection of the size and number of main engines...
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COMPOSITE MATERIAL SELECTION FOR A PATIENT TRANSFER ASSIST DEVICE
PublikacjaLaminates - layered composites containing at least two elements (matrix and reinforcement) widely used in industry have also found their usage in medicine. Their main feature is the ability to modify the material in order to obtain the required properties. Depending on the needs, we can modify reinforcement, type of resin or the method of bonding substrates. Commonly used fibers are: carbon fiber, glass and aramid fibers; resins...
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Spiral Search Grasshopper Features Selection with VGG19-ResNet50 for Remote Sensing Object Detection
PublikacjaRemote sensing object detection plays a major role in satellite imaging and is required in various scenarios such as transportation, forestry, and the ocean. Deep learning techniques provide efficient performance in remote sensing object detection. The existing techniques have the limitations of data imbalance, overfitting, and lower efficiency in detecting small objects. This research proposes the spiral search grasshopper (SSG)...
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Auditory-model based robust feature selection for speech recognition
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Residual Current Devices: Selection, Operation, and Testing
PublikacjaIn this book, the idea for residual current protection has been presented. The evolution in construction types of residual current devices, which has taken place over decades, is discussed. Types and functional properties of the contemporary residual current devices are described. The main parameters of these devices, from the point of view of their selection and application, are indicated. Special constructions of the protective...
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PROTEIN ENGINEERING DESIGN & SELECTION
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Heuristic Method of Safe Manoeuvre Selection Based on Collision Threat Parameters Areas
PublikacjaThis paper is a continuation of papers dedicated to a radar-based CTPA (Collision Threat Parameters Area) display designed to support safe manoeuvre selection. The display visualizes all the ships in an encounter and presents situational overview from the own ship’s point of view. It calculates and displays information on unsafe or unrealistic own ship’s course & speed allowing a user to select a safe manoeuvre. So far only the...
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A Framework for Enhancing Supplier Selection Process by Using SOEKS and Decisional DNA
PublikacjaAbstract. Supplier selection process is one of the significant stages in supply chain management for industrial manufactured products. It plays an integral role in the success of any manufacturing organization and is an important part starting right from selecting raw material to dispatch of finished products. This paper contributes to enhance the supplier selection process by proposing a multi-criteria decision making framework...
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Genetic Algorithm Approach for Gains Selection of Induction Machine Extended Speed Observer
PublikacjaThe subject of this paper is gains selection of an extended induction machine speed observer. A high number of gains makes manual gains selection difficult and due to nonlinear equations of the observer, well-known methods of gains selection for linear systems cannot be applied. A method based on genetic algorithms has been proposed instead. Such an approach requires multiple fitness function calls; therefore, using a quality index...
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Ontology Oriented Approach to Service Selection and Invocation in Complex Context Analysis
PublikacjaContext-aware applications running in the intelligent space are taken into account and their execution in the service oriented environment is considered. It has been presented where and how SOA services can be utilized during their execution: to analyze current context of the application and to support execution of strictly determined actions suitable for that context. The proposed mechanism of context-aware service selection and...
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Materials Selection (DaPE; 1st grade; 6th semester) 21/22 PG_00053711
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O-43 Data-driven selection of active iEEG channels during verbal memory task performance
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Information retrieval with semantic memory model
PublikacjaPsycholinguistic theories of semantic memory form the basis of understanding of natural language concepts. These theories are used here as an inspiration for implementing a computational model of semantic memory in the form of semantic network. Combining this network with a vector-based object-relation-feature value representation of concepts that includes also weights for confidence and support, allows for recognition of concepts...
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A Selection of Starting Points for Iterative Position Estimation Algorithms Using Feedforward Neural Networks
PublikacjaThis article proposes the use of a feedforward neural network (FNN) to select the starting point for the first iteration in well-known iterative location estimation algorithms, with the research objective of finding the minimum size of a neural network that allows iterative position estimation algorithms to converge in an example positioning network. The selected algorithms for iterative position estimation, the structure of the...
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Role patterns in IT projects teams - design of a selection module using fuzzy logic techniques
PublikacjaPresented paper introduces an approach based on usage of role patterns and modelling by the use of fuzzy logic tool for selection process with limitation to the area of IT projects environment. The article shows a concept of role patterns structures and their further usage in process of forming a fuzzy model dedicated to candidate assessment process support
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Hard Lessons Learned: A Model that Facilitates the Selection of Methods of IT Project Management
PublikacjaThe article presents the results of research conducted in an international enterprise responsible for IT project implementation. The carried out analysis of the case study with the use of surveys and data synthesis allowed the major factors causing problems connected with project management to be identified. The identified factors were aggregated and then, by using four key variables, a rhomboidal model adaptation was proposed...
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Impact of R/X ratio of distribution network on selection and control of energy storage units
PublikacjaThe interest in energy storage is still increasing. Energy storage units are installed in high voltage networks, medium voltage networks and low voltage distribution networks as well. These units are often used to improve power quality. One of the criteria for improving power quality is reducing voltage deviations. Depending on the type of network and specifying its R/X ratio, this criterion can be fulfilled by control of active...
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Scaling of numbers in residue arithmetic with the flexible selection of scaling factor
PublikacjaA scaling technique of numbers in resudue arithmetic with the flexible selection of the scaling factor is presented. The required scaling factor can be selected from the set of moduli products of the Residue Number System (RNS) base. By permutation of moduli of the number system base it is possible to create many auxilliary Mixed-Radix Systems associated with the given RNS with respect to the base, but they have different sets...
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The Effect of the Selection of Three-Dimensional Random Numerical Soil Models on Strip Foundation Settlements
PublikacjaThis 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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Accurate Modeling of Frequency Selective Surfaces Using Fully-Connected Regression Model with Automated Architecture Determination and Parameter Selection Based on Bayesian Optimization
PublikacjaSurrogate modeling has become an important tool in the design of high-frequency structures. Although full-wave electromagnetic (EM) simulation tools provide an accurate account for the circuit characteristics and performance, they entail considerable computational expenditures. Replacing EM analysis by fast surrogates provides a way to accelerate the design procedures. Unfortunately, modeling of microwave passives is a challenging...
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New Approach to Noncasual Identification of Nonstationary Stochastic FIR Systems Subject to Both Smooth and Abrupt Parameter Changes
PublikacjaIn this technical note, we consider the problem of finite-interval parameter smoothing for a class of nonstationary linear stochastic systems subject to both smooth and abrupt parameter changes. The proposed parallel estimation scheme combines the estimates yielded by several exponentially weighted basis function algorithms. The resulting smoother automatically adjusts its smoothing bandwidth to the type and rate of nonstationarity...
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ANALYSIS OF BONE WEDGE DIMENSIONS SELECTION METHODS IN HIGH TIBIAL OSTEOTOMY
PublikacjaThe article presents the analysis of methods for selecting dimensions of bone wedge for high tibial osteotomy. The existing methods are described along with the procedure. In the following paragraphs, deficiencies in the selection of bone wedge dimensions and global trends in this field have been demonstrated. Based on the numerical analysis, the problem appearing in the wrong choice of bone wedge imensions was illustrated.
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Genetic Programming with Negative Selection for Volunteer Computing System Optimization
PublikacjaVolunteer computing systems like BOINC or Comcute are strongly supported by a great number of volunteers who contribute resources of their computers via the Web. So, the high efficiency of such grid system is required, and that is why we have formulated a multi-criterion optimization problem for a volunteer grid system design. In that dilemma, both the cost of the host system and workload of a bottleneck host are minimized. On...
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Reduced order models in computational electromagnetics (in memory of Ruediger Vahldieck)
PublikacjaThis paper reviews research of Ruediger Vahldieck's group and the group at the Gdansk University of Technology in the area of model order reduction techniques for accelerating full-wave simulations. The applications of reduced order models to filter design as well as of local and nested(multilevel) macromodels for solving 3D wave equations and wave-guiding problems using finite difference and finite element methods are discussed.
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On autoregressive spectrum estimation using the model averaging technique
PublikacjaThe 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...