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High Temperature Air/Steam Conversion of Biomass and Wastes Into Fuel Gas for Heat and Electricity Production
PublicationPaper present principle of high temperature air/staem gasification as well as some results of research using this technology for conversion of biomass and wastes into fuel gas.
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A Comprehensive Analysis of Deep Neural-Based Cerebral Microbleeds Detection System
PublicationMachine learning-based systems are gaining interest in the field of medicine, mostly in medical imaging and diagnosis. In this paper, we address the problem of automatic cerebral microbleeds (CMB) detection in magnetic resonance images. It is challenging due to difficulty in distinguishing a true CMB from its mimics, however, if successfully solved it would streamline the radiologists work. To deal with this complex three-dimensional...
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International Conference on Language and Automata Theory and Applications
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The Innovative Faculty for Innovative Technologies
PublicationA leaflet describing Faculty of Electronics, Telecommunications and Informatics, Gdańsk University of Technology. Multimedia Systems Department described laboratories and prototypes of: Auditory-visual attention stimulator, Automatic video event detection, Object re-identification application for multi-camera surveillance systems, Object Tracking and Automatic Master-Slave PTZ Camera Positioning System, Passive Acoustic Radar,...
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Corrosion monitoring by harmonic analysis in aqueous environments
PublicationThis paper presents tests concerning the rate of corrosion in non-alloy steel (type S235JR) in an aqueous environment, with an additive of sodium chloride by means of polarization resistance measurements and harmonic analysis. The tests have been carried out for steel samples exposed to the testing environment for six weeks, in order to obtain a constant rate of corrosion in the function of time. The measurements have aimed at...
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Parameters optimization in medicine supporting image recognition algorithms
PublicationIn this paper, a procedure of automatic set up of image recognition algorithms' parameters is proposed, for the purpose of reducing the time needed for algorithms' development. The procedure is presented on two medicine supporting algorithms, performing bleeding detection in endoscopic images. Since the algorithms contain multiple parameters which must be specified, empirical testing is usually required to optimise the algorithm's...
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Klasyfikacja sygnału EKG przy użyciu konwolucyjnych sieci neuronowych
PublicationAutomation and improvement of diagnostic process is a vital element of medicine development and patient’s condition self-control. For a long time different ECG signal classification methods exist and are successfully applied, nevertheless their accuracy is not always satisfying enough. The lack of identification of an existing abnormality, which is very similar to a normal heartbeat is the biggest issue - for example premature...
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Klasyfikacja sygnału EKG przy użyciu konwolucyjnych sieci neuronowych
PublicationAutomation and improvement of diagnostic process is a vital element of medicine development and patient’s condition self-control. For a long time different ECG signal classification methods exist and are successfully applied, nevertheless their accuracy is not always satisfying enough. The lack of identification of an existing abnormality, which is very similar to a normal heartbeat is the biggest issue - for example premature...
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Marek Sylwester Tatara dr inż.
PeopleMarek Tatara achieved his master's degree in the field of Automatic Control and Robotics with specialization Intelligent Decision-making Systems in 2014 at Faculty of Electronics, Telecommunications and Informatics of Gdańsk University of Technology. Earlier this year achieved bachelor's degree in the field of Technical Physics with Nanotechnology specialization. In 2014 started job as lecturer in the Department of Robotics and...
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Using similar classification tasks in feature extractor learning
PublicationThe article presents and experimentally verify the idea of automatic construction of feature extractors in classification problems. The extractors are created by genetic programming techniques using classification examples taken from other problems then the problem under consideration.
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Systemy wbudowane w automatyce i robotyce - 22/23
e-Learning CoursesSystemy wbudowane w automatyce i robotyce - kurs uzupełniający.
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Performance evaluation of the parallel object tracking algorithm employing the particle filter
PublicationAn algorithm based on particle filters is employed to track moving objects in video streams from fixed and non-fixed cameras. Particle weighting is based on color histograms computed in the iHLS color space. Particle computations are parallelized with CUDA framework. The algorithm was tested on various GPU devices: a desktop GPU card, a mobile chipset and two embedded GPU platforms. The processing speed depending on the number...
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Automation of Business Processes_2023
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Soxhlet Extraction and New Developments Such as Soxtec in: Comprehansive Sampling and Sample Preparation
PublicationSoxhlet extraction is one of the most popular techniques for extraction of analytes from solid materials. Since its discovery in 1879, the standard Soxhlet technique has been routinely applied in almost every analytical laboratory. Up to this day, Soxhlet extraction technique remains a standard technique to which the performance of modern extraction techniques is compared.Over the years, an intensive research on different modifications...
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Design of synchronous generator two inputs regulator based on hinf control theory.
PublicationThe power system is highly nonlinear system, its dynamics depends on system network configuration, system loading… etc. To overcome the above mentioned difficulties and fulfill the performance requirements the different control methods are considered and tested for design of synchronous generator control system. Application of the H optimization method to synchronous generator regulator based on measurement of generator voltage...
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Examining Influence of Distance to Microphone on Accuracy of Speech Recognition
PublicationThe problem of controlling a machine by the distant-talking speaker without a necessity of handheld or body-worn equipment usage is considered. A laboratory setup is introduced for examination of performance of the developed automatic speech recognition system fed by direct and by distant speech acquired by microphones placed at three different distances from the speaker (0.5 m to 1.5 m). For feature extraction from the voice signal...
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Systemy wizyjne w automatyce 2023/2024
e-Learning CoursesKurs "Wizyjnych Systemów w Automatyce" - materiały i platforma komunikacji
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System of monitoring of the Forest Opera in Sopot structure and roofing
PublicationThe authors present a solution realized in Forest Opera (name in Polish: Opera Leśna) in Sopot (Poland) in connection with the modernization and construction of a new roof. The complicated structure of the roof of the facility and the used covering in form of membrane made of technical fabric required (for security reasons) to install the unit of devices allowing for the continuous geodetic monitoring of the facility. Monitoring...
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Stanisław Galla dr inż.
PeopleStanisław Galla was born in 1970 in Gdańsk. He graduated from the Secondary Technical School of Mechanical and Electrical Engineering in Gdansk (1990). He studied at the Faculty of Electrical Engineering at Gdansk University of Technology (graduated in 1996). His PhD thesis entitled "Methodology for increasing the accuracy of low frequency measurements of periodic disturbance indicators in low voltage networks" was defended in...
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Installation of Compensators in the Power System Transmission Grid
PublicationThe article discusses issues of reactive power compensation in transmission grids, with particular focus on the selection of compensator locations and basic parameters. Attention was focused on modern power electronics systems that ensure full automatic compensator adjustment to voltage or power criteria.
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International Conference on Intelligent Data Engineering and Automated Learning
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International Conference on Computational Intelligence for Modelling, Control and Automation
Conferences -
Monitoring Parkinson's disease patients employing biometric sensors and rule-based data processing
PublicationArtykuł prezentuje automatyczny system wykrywania pogorszenia zdrowia pacjentów z chorobą Parkinsona opracowany w ramach projektu PERFORM.The paper presents how rule-based processing can be applied to automatically evaluate the motor state of Parkinson's Disease patients. Automatic monitoring of patients by using biometric sensors can provide assessment of the Parkinson's Disease symptoms. All data on PD patients' state are compared...
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Exploring Stock Traders’ Cognitive Biases: Research Design and Simulator Framework
PublicationCognitive bias is a phenomenon that has been extensively studied in stock trading and many other fields. This paper presents a framework for a Mobile Stock Trading Simulator (MSTS) that facilitates automatic investment in stocks with minimal human influence, by investigating the behavioral patterns and cognitive errors of stock market investors. The paper aims to determine whether investors’ investment strategies can be improved...
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Spectral measurement of birefringence using particle swarm optimization analysis
PublicationThe measurement of birefringence is useful for the examination of both technical and biological objects. One of the main problems is that the polarization state of light in birefringent media changes periodically. Without the knowledge of the period number, the birefringence of a given medium cannot be determined reliably. We propose to analyse the spectrum of light in order to determine the birefringence. We use a Particle Swarm...
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A Framework of A Ship Domain-Based Near-Miss Detection Method Using Mamdani Neuro-Fuzzy Classification
PublicationSafety analysis of navigation over a given area may cover application of various risk measures for ship collisions. One of them is percentage of the so called near- miss situations (potential collision situations). In this article a method of automatic detection of such situations based on the data from Automatic Identification System (AIS), is proposed. The method utilizes input parameters such as: collision risk measure based...
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Mispronunciation Detection in Non-Native (L2) English with Uncertainty Modeling
PublicationA common approach to the automatic detection of mispronunciation in language learning is to recognize the phonemes produced by a student and compare it to the expected pronunciation of a native speaker. This approach makes two simplifying assumptions: a) phonemes can be recognized from speech with high accuracy, b) there is a single correct way for a sentence to be pronounced. These assumptions do not always hold, which can result...
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Price convergence in the European Union and in the new member states
PublicationThis paper examines price dispersion in the European Union (EU15) and in three New Member States (Poland, Hungary and the Czech Republic) between 1995 and 2006. The analysis utilizes both disaggregate and aggregate price data, including the prices of 157 products and two indices constructed using two different weighting procedures. For each category of goods the price dispersion is lower in EU15 than EU15 plus 3 NMS. Sigma convergence...
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The differential impact of a density of Polish pine wood on cutting forces with its origin region taken into consideration
PublicationIn the article the dependence of cutting forces in a function the density of wood with regard to the wood origin are presented. Samples used in experiment were with Scotch pine (Pinus sylvestris L.) originating from four provenances in Poland (Figure 1). Wood density was measured by two methods: stereometric method (global density) and radiometric method (local density). Stereometric method consists in measurements the volume...
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Objects classification based on their physical sizes for detection of events in camera images
PublicationIn the paper, a method of estimation of the physical sizes of the objects tracked in the video surveillance system, and a simple module for object classification based on the estimated physical sizes, are presented. The results of object classification are then used for automatic detection of various types of events in the camera image.
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Aestheticization of Flowcharts
PublicationOne of the important issues of diagrams is their aesthetics. In this paper a method of its formalization for freehand drawn flowcharts is proposed. In order to formalize the evaluation of flowcharts' aesthetics a criterion consisting of several measures is proposed. Based on this criterion the algorithms for automatic optimization of flowcharts' appearance are proposed.
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Emotion Recognition for Affect Aware Video Games
PublicationIn this paper the idea of affect aware video games is presented. A brief review of automatic multimodal affect recognition of facial expressions and emotions is given. The first result of emotions recognition using depth data as well as prototype affect aware video game are presented
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Oddziaływanie wybranych elementów przekształtnika energoelektronicznego nagenerację zaburzeń przewodzonych.**2002, 134 s. 125 rys. bibliogr. 102 poz. Rozprawa doktorska /17.12.2002/. PG, Wydz. Elektrotech. Automat. Promotor: dr hab. inż. Piotr J. Chrzan, prof. nadzw. PG
PublicationW rozprawie przedstawiono sposób obliczania generowanych zaburzeń elektroma-gnetycznych przewodzonych z układu przekształtnika do sieci zasilającej. Ce-lem pracy było opracowanie, w oparciu o symulację komputerową i badania eks-perymentalne, modeli wybranych elementów układu przekształtnika energoelek-tronicznego, pozwalających na określanie poziomów zaburzeń elektromagnetycz-nych przewodzonych w układach symulacyjnych. Zakres...
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EXPERIMENTAL RESEARCH ON INFLUENCE OF THE FUEL NOZZLE GEOMETRY ON THE FUEL CONSUMPTION OF THE MARINE 4-STROKE DIESEL ENGINE
PublicationThe article presents experimental research that has been carried out on a marine, 4-stroke, 3-cylinder, turbocharged engine. During testing, the engine operated at a constant rotational speed of 750 rpm and a load from 0 kW to 280 kW. The engine was fuelled by diesel oil of known specification and loaded by electric generator with water resistance. The fuel consumption was measured during the engine operation with fuel nozzles...
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Acoustic radar employing particle velocity sensors
PublicationA concept, practical realization and applications of a passive acoustic radar to automatic localization, tracking of sound sources were presented in the paper. The device consist of the new kind of multichannel miniature sound intensity sensors and a group of digital signal processing algorithms. Contrary to active radars, it does not emit the scanning beam but after receiving surroundings sounds it provide information about the...
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MACHINE LEARNING–BASED ANALYSIS OF ENGLISH LATERAL ALLOPHONES
PublicationAutomatic classification methods, such as artificial neural networks (ANNs), the k-nearest neighbor (kNN) and selforganizing maps (SOMs), are applied to allophone analysis based on recorded speech. A list of 650 words was created for that purpose, containing positionally and/or contextually conditioned allophones. For each word, a group of 16 native and non-native speakers were audio-video recorded, from which seven native speakers’...
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Segmentation-Based BI-RADS ensemble classification of breast tumours in ultrasound images
PublicationBackground: The development of computer-aided diagnosis systems in breast cancer imaging is exponential. Since 2016, 81 papers have described the automated segmentation of breast lesions in ultrasound images using arti- ficial intelligence. However, only two papers have dealt with complex BI-RADS classifications. Purpose: This study addresses the automatic classification of breast lesions into binary classes (benign vs. ma- lignant)...
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Optimal and suboptimal algorithms for identification of time-varying systems with randomly drifting parameters
PublicationNoncausal estimation algorithms, which involve smoothing, can be used for off-line identification of nonstationary systems. Since smoothingis based on both past and future data, it offers increased accuracy compared to causal (tracking) estimation schemes, incorporating past data only. It is shown that efficient smoothing variants of the popular exponentially weighted least squares and Kalman filter-based parameter trackers can...
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On ''cheap smoothing'' opportunities in identification of time-varying systems
PublicationIn certain applications of nonstationary system identification the model-based decisions can be postponed, i.e. executed with a delay. This allows one to incorporate into the identification process not only the currently available information, but also a number of ''future'' data points. The resulting estimation schemes, which involve smoothing, are not causal. Despite the possible performance improvements, the existing smoothing...
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On the lower smoothing bound in identification of time-varying systems
PublicationIn certain applications of nonstationary system identification the model-based decisions can be postponed, i.e. executed with a delay. This allows one to incorporate in the identification process not only the currently available information, but also a number of ''future'' data points. The resulting estimation schemes, which involve smoothing, are not causal. Assuming that the infinite observation history is available, the paper...
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Self-optimizing generalized adaptive notch filters - comparison of three optimization strategies
PublicationThe paper provides comparison of three different approaches to on-line tuning of generalized adaptive notch filters (GANFs) the algorithms used for identification/tracking of quasi-periodically varying dynamic systems. Tuning is needed to adjust adaptation gains, which control tracking performance of ANF algorithms, to the unknown and/or time time-varying rate of system nonstationarity. Two out ofthree compared approaches are classical...
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Generalized adaptive notch filters with frequency debiasing for tracking of polynomial phase systems
PublicationGeneralized adaptive notch filters are used for identification/tracking of quasi-periodically varying dynamic systems and can be considered an extension, to the system case, of classical adaptive notch filters. For general patterns of frequency variation the generalized adaptive notch filtering algorithms yield biased frequency estimates. We show that when system frequencies change slowly in a smooth way, the estimation bias can...
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Easy recipes for cooperative smoothing
PublicationIn this paper we suggest how several competing signal smoothers, differing in design parameters, or even in design principles, can be combined together to yield a better and more reliable smoothing algorithm. The proposed heuristic, but statistically well motivated, fusion mechanism allows one to combine practically all kinds of smoothers, from simple local averaging or order statistic filters, to parametric smoothers designed...
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A J-lossless coprime factorisation approach to H control in delta domain
PublicationPraca dotyczy sterowania wielowymiarowym obiektem dynamicznym czasu ciągłego opisanym dyskretnoczasowym modelem w przestrzeni stanu, przy założeniu, że wskaźnik jakości sterowania oparty jest na normie H-inf. Odpowiednie zadanie optymalizacji tego wskaźnika rozwiązuje się, stosując tak zwaną względnie pierwszą J-bezstratną faktoryzację modelu sterowanego. Pokazano, że synteza optymalnego sterownika, wymagająca rozwiązania dwóch...
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On noncausal weighted least squares identification of nonstationary stochastic systems
PublicationIn 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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On adaptive covariance and spectrum estimation of locally stationary multivariate processes
PublicationWhen 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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Generalized Savitzky–Golay filters for identification of nonstationary systems
PublicationThe 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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A new look at the statistical identification of nonstationary systems
PublicationThe 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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Application of regularized Savitzky–Golay filters to identification of time-varying systems
PublicationSavitzky–Golay (SG) filtering is a classical signal smoothing technique based on the local least squares approximation of the analyzed signal by a linear combination of known functions of time (originally — powers of time, which corresponds to polynomial approximation). It is shown that the regularized version of the SG algorithm can be successfully applied to identification of time-varying finite impulse response (FIR) systems....
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Generalized adaptive comb filters/smoothers and their application to the identification of quasi-periodically varying systems and signals
PublicationThe problem of both causal and noncausal identification of linear stochastic systems with quasiharmonically varying parameters is considered. The quasi-harmonic description allows one to model nonsinusoidal quasi-periodic parameter changes. The proposed identification algorithms are called generalized adaptive comb filters/smoothers because in the special signal case they reduce down to adaptive comb algorithms used to enhance...