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- Publikacje 3312 wyników po odfiltrowaniu
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- Osoby 51 wyników po odfiltrowaniu
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- Projekty 2 wyników po odfiltrowaniu
- Kursy Online 41 wyników po odfiltrowaniu
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- Dane Badawcze 188 wyników po odfiltrowaniu
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Metoda diagnostyki cieplno-przepływowej turbin parowych wykorzystująca elementy algorytmów genetycznych
PublikacjaRozprawa doktorska poświęcona jest opisowi budowania metody diagnostyki cieplno-przepływowej z wykorzystaniem elementów algorytmów genetycznych. Do tworzenia założeń i algorytmów metody posłużono się przykładem funkcjonowania bloku elektrowni kondensacyjnej ze szczególnym uwzględnieniem układu łopatkowego turbiny parowej. Celem pracy jest zbudowanie metody diagnostyki cieplno-przepływowej. Zadaniem metody jest przeprowadzenie procesu...
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Output voltage, current and DC-link voltages under SVPWM, experimental results
Dane BadawczeThe dataset contains the experimental results of the project: A universal algorithm of space vector pulse width modulation for three-level three and multi-phase NPC inverters with DC-link voltage balancing. The output line-to-line voltage, output current and DC-link voltages were included. The comparison studies between proposed Space Vector Pulse-Width...
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Output voltage, current and DC-link voltages under SPWM, experimental results
Dane BadawczeThe dataset contains the experimental results of the project: A universal algorithm of space vector pulse width modulation for three-level three and multi-phase NPC inverters with DC-link voltage balancing. The output line-to-line voltage, output current and DC-link voltages were included. The Carrier-Based Pulse-Width Modulation (CBPWM) technique was...
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RANS-based design optimization of dual-rotor wind turbines
PublikacjaPurpose An improvement in the energy efficiency of wind turbines can be achieved using dual rotors. Because of complex flow physics, the design of dual-rotor wind turbines (DRWTs) requires repetitive evaluations of computationally expensive partial differential equation (PDE) simulation models. Approaches for solving design optimization of DRWTs constrained by PDE simulations are investigated. The purpose of this study is to determine...
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Expert systems in quality control of manufacturing processes
PublikacjaThe paper deals with quality control in conditions of computer integrated manufacturing (CIM). It shows that quality of material stream items have to be analyzed on every stage of manufacturing process. Collecting and analyzing quantity of data with usage of expert systems make it possible to create a system for coordination of cell's work. The system contains error recovery algorithm and adaptive control subsystem based on fuzzy...
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Discovering patterns of Web Page Visits from Associaton Rules Viewpoint
PublikacjaThe popularity of the Internet results from the almost unlimited resources of information stored in it. At the same time, Internet portals have become a widespread source of information and note very large number of visits. The list of web pages opened by users is stored in web servers' log files. Extraction of knowledge on the navigation paths of users has become carefully analyzed problem. Currently, there are a number of algorithms...
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SONIC - Self-optimizing narrowband interference canceler: comparison of two frequency tracking strategies
PublikacjaThis paper presents a new approach to rejection of complex-valued sinusoidal disturbances acting at the output of a discrete-time linear stable plant with unknown and possibly time-varying dynamics. It is assumed that both the instantaneous frequency of the sinusoidal disturbance and its amplitude may be slowly varying with time and that the output signal is contaminated with wideband measurement noise. The proposed disturbance...
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Facial emotion recognition using depth data
PublikacjaIn this paper an original approach is presented for facial expression and emotion recognition based only on depth channel from Microsoft Kinect sensor. The emotional user model contains nine emotions including the neutral one. The proposed recognition algorithm uses local movements detection within the face area in order to recognize actual facial expression. This approach has been validated on Facial Expressions and Emotions Database...
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Decisional DNA and Optimization Problem
PublikacjaMany researchers have proved that Decisional DNA (DDNA) and Set of Experience Knowledge Structure (SOEKS or SOE) is a technology capable of gathering information and converting it into knowledge to help decision-makers to make precise decisions in many ways. These techniques have a feature to combine with different tools, such as data mining techniques and web crawlers, helping organization collect information from different sources...
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Dynamic Signal Strength Mapping and Analysis by Means of Mobile Geographic Information System
PublikacjaBluetooth beacons are becoming increasingly popular for various applications such as marketing or indoor navigation. However, designing a proper beacon installation requires knowledge of the possible sources of interference in the target environment. While theoretically beacon signal strength should decay linearly with log distance, on-site measurements usually reveal that noise from objects such as Wi-Fi networks operating in...
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Performance improvement of NN based RTLS by customization of NN structure - heuristic approach
PublikacjaThe purpose of this research is to improve performance of the Hybrid Scene Analysis – Neural Network indoor localization algorithm applied in Real-time Locating System, RTLS. A properly customized structure of Neural Network and training algorithms for specific operating environment will enhance the system’s performance in terms of localization accuracy and precision. Due to nonlinearity and model complexity, a heuristic analysis...
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Generalized regression neural network and fitness dependent optimization: Application to energy harvesting of centralized TEG systems
PublikacjaThe thermoelectric generator (TEG) system has attracted extensive attention because of its applications in centralized solar heat utilization and recoverable heat energy. The operating efficiency of the TEG system is highly affected by operating conditions. In a series-parallel structure, due to diverse temperature differences, the TEG modules show non-linear performance. Due to the non-uniform temperature distribution (NUTD) condition,...
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International Conference on Probabilistic, Combinatorial, and Asymptotic Methods in the Analysis of Algorithms (Conference on Analysis of Algorithms)
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Discrete and Algorithmic Geometry
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Algorithmic Learning Theory
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Human awareness versus Autonomous Vehicles view: comparison of reaction times during emergencies
PublikacjaHuman safety is one of the most critical factors when a new technology is introduced to the everyday use. It was no different in the case of Autonomous Vehicles (AV), designed to replace generally available Conventional Vehicles (CV) in the future. AV rules, from the start, focus on guaranteeing safety for passengers and other road users, and these assumptions usually work during normal traffic conditions. However, there is still...
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Ex-situ XRD (X-ray Diffraction) results for electrodes under different charge/discharge states
Dane BadawczeEx-situ XRD was employed to analyze the energy storage mechanism of CPMD in ZICs system. The ZICs were firstly charged to 1.8 V from the open circuit voltage (at around 1.3 V), then discharge to 1.0 V and 0.2 V, and finally recharged to 1.0 V and 1.8 V. Sample abbreviations (CPMD) are in agreement with the markings used in the linked publication.
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Performance evaluation of parallel background subtraction on GPU platforms
PublikacjaImplementation of the background subtraction algorithm on parallel GPUs is presented. The algorithm processes video streams and extracts foreground pixels. The work focuses on optimizing parallel algorithm implementation by taking into account specific features of the GPU architecture, such as memory access, data transfers and work group organization. The algorithm is implemented in both OpenCL and CUDA. Various optimizations of...
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Gas Detection Using Resistive Gas Sensors And Radial Basis Function Neural Networks
PublikacjaWe present a use of Radial Basis Function (RBF) neural networks and Fluctuation Enhanced Sensing (FES) method in gas detection system utilizing a prototype resistive WO3 gas sensing layer with gold nanoparticles. We investigated accuracy of gas detection for three different preprocessing methods: no preprocessing, Principal Component Analysis (PCA) and wavelet transformation. Low frequency noise voltage observed in resistive gas...
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Algorytmy równoległe i rozproszone/Parallel and distributed >> algorithms
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Efficient uncertainty quantification using sequential sampling-based neural networks
PublikacjaUncertainty quantification (UQ) of an engineered system involves the identification of uncertainties, modeling of the uncertainties, and the forward propagation of the uncertainties through a system analysis model. In this work, a novel surrogate-based forward propagation algorithm for UQ is proposed. The proposed algorithm is a new and unique extension of the recent efficient global optimization using neural network (NN)-based...
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Sterowanie predykcyjne i fuzja danych w systemie dynamicznego pozycjonowania statku
PublikacjaRozprawa doktorska poświęcona jest badaniu zastosowania fuzji danych oraz sterowania predykcyjnego w systemie dynamicznego pozycjonowania statku. W pierwszej części pracy przedstawiono historię rozwoju systemów dynamicznego pozycjonowania, różne metody estymacji położenia statku, metody sterowania oraz cel i tezę pracy. Następnie zaprezentowano model matematyczny statku, kinematykę oraz dynamikę. W kolejnej części przedstawiono...
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Andrzej Chybicki dr inż.
OsobyZ wykształcenia informatyk, absolwent Wydziału Elektroniki, Telekomunikacji i Informatyki Politechniki Gdańskiej, doktor nauk technicznych w dziedzinie informatyka specjalizujący się w przetwarzaniau danych przestrzennych w rozproszonych systemach informatycznych. Ukierunkowany na wykorzystywanie osiągnięć i wiedzy zakresu prowadzonych badań w przemyśle. Współpracował z szeregiem podmiotów przemysłu informatycznego, geodezyjnego...
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Przemysław Kalitowski dr inż.
OsobyPrzemyslaw Kalitowski (born 26 July 1991) currently works at the Gdansk University of Technology in Gdansk, Poland. He acts as the Professor's Assistant at the Department of Rail Transportation and Bridges. In 2015 he started PhD studies at the Department of Rail Transportation and Bridges. He has over 4 years experience in static and dynamic analysis of structures - primarily with FEM programs. The scope of analysis are mainly...
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Automatic assessment of the motor state of the Parkinson's disease patient --a case study
PublikacjaThis paper presents a novel methodology in which the Unified Parkinson's Disease Rating Scale (UPDRS) data processed with a rule-based decision algorithm is used to predict the state of the Parkinson's Disease patients. The research was carried out to investigate whether the advancement of the Parkinson's Disease can be automatically assessed. For this purpose, past and current UPDRS data from 47 subjects were examined. The results...
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Robust output prediction of differential – algebraic systems – application to drinking water distribution system
PublikacjaThe paper presents the recursive robust output variable prediction algorithm, applicable for systems described in the form of nonlinear algebraic-differential equations. The algorithm bases on the uncertainty interval description, the system model, and the measurements. To improve the algorithm efficiency, nonlinear system models are linearised along the nominal trajectory. The effectiveness of the algorithm is demonstrated on...
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Piotr Szczuko dr hab. inż.
OsobyDr hab. inż. Piotr Szczuko w 2002 roku ukończył studia na Wydziale Elektroniki, Telekomunikacji i Informatyki Politechniki Gdańskiej zdobywając tytuł magistra inżyniera. Tematem pracy dyplomowej było badanie zjawisk jednoczesnej percepcji obrazu cyfrowego i dźwięku dookólnego. W roku 2008 obronił rozprawę doktorską zatytułowaną "Zastosowanie reguł rozmytych w komputerowej animacji postaci", za którą otrzymał nagrodę Prezesa Rady...
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Fuzzy soft modeling of environmental data. A study of the impact of a Phosphatic Fertilizer Plant on the adjacent environment in Gdańsk
PublikacjaAnaliza podobieństwa obejmuje nie tylko zastosowanie logiki rozmytej, ale również wiele innych podejść matematycznych. Opracowano wiele algorytmów, których celem jest wyodrębnienie wyraźnych skupień (hard clusters) z danego zbioru danych. Prawdopodobnie najczęściej stosowanymi algorytmami są tzw. algorytmy c-średnie (c-means algorithms). Twarde c-średnie (hard c-means) służy do ostrej klasyfikacji, podczas której obiekt jest przypisany...
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Computer vision techniques applied for reconstruction of seafloor 3D images from side scan and synthetic aperture sonars data
PublikacjaThe Side Scan Sonar and Synthetic Aperture Sonar are well known echo signal processing technologies that produce 2D images of the seafloor. Both systems combines a number of acoustic pings to form a high resolution image of seafloor. It was shown in numerous papers that 2D images acquired by such systems can be transformed into 3D models of seafloor surface by algorithmic approach using intensity information, contained in a grayscaled...
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Minimising the Churn Out of the Service by Using a Fairness Mechanism
PublikacjaThe paper proposes an algorithm of bandwidth distribution, ensuring fairness to end-users in computer networks. The proposed algorithm divides users into satisfied and unsatisfied users. It provides fairness in terms of quality of experience (QoE) for satisfied users and quality of service (QoS) for unsatisfied users. In this paper, we present detailed comparisons relevant to service providers to show the advantages of the proposed...
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Data-driven, probabilistic model for attainable speed for ships approaching Gdańsk harbour
PublikacjaThe growing demand for maritime transportation leads to increased traffic in ports. From this arises the need to observe the consequences of the specific speed ships reach when approaching seaports. However, usually the analyzed cases refer only to the statistical evaluation of the studied phenomenon or to the empirical modelling, ignoring the mutual influence of variables such as ship type, length or weather conditions. In this...
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The Experimental Determination of Bearings Dynamic Coefficients in a Wide Range of Rotational Speeds, Taking into Account the Resonance and Hydrodynamic Instability
PublikacjaMethods for the experimental determination of dynamic coefficients are commonly used for the analysis of various types of bearings, including hydrodynamic, aerodynamic and foil bearings. There are currently several algorithms that allow estimating bearing dynamic coefficients. Such algorithms usually use various excitation techniques applied to rotor–bearings systems. So far only a small number of scientific publications show how...
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Impact of optimization of ALS point cloud on classification
PublikacjaAirborne laser scanning (ALS) is one of the LIDAR technologies (Light Detection and Ranging). It provides information about the terrain in form of a point cloud. During measurement is acquired: spatial data (object’s coordinates X, Y, Z) and collateral data such as intensity of reflected signal. The obtained point cloud is typically applied for generating a digital terrain model (DTM) and a digital surface model (DSM). For DTM...
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Mixed integer nonlinear optimization of biological processes in wastewater sequencing batch reactor
PublikacjaWastewater treatment plays a key role for humanity. The waste entering lakes, rivers, and seas deteriorates daily quality of life. Therefore, it is very important to improve the efficiency of wastewater treatment. From a control point of view, a biological wastewater treatment plant is a complex, non-linear, multidimensional, hybrid control system. The paper presents the design of the optimizing hierarchical control system applied...
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Dual drive control under SVPWM, experimental results
Dane BadawczeThe dataset contains the experimental results of the project: A universal algorithm of space vector pulse width modulation for three-level three and multi-phase NPC inverters with DC-link voltage balancing. The analysis includes the behaviour of the drive system, examining the dynamic system response to speed and angle changes, and encompassing data...
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Computability in Europe: Logic and Theory of Algorithms
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Symposium of Asian Association for Algorithms and Computation
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Tools and Algorithms for Construction and Analysis of Systems
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Symposium on Stochastic Algorithms, Foundations and Applications
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Conference on Algorithms and Hardware for Parallel Processing
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International Conference and Workshop on Algorithms and Computation
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ACM/SIAM Symposium on Discrete Algorithms
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Workshop on Algorithms And Models For The Web Graph
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The Quick Measure of a Nurbs Surface Curvature for Accurate Triangular Meshing
PublikacjaNURBS surfaces are the most widely used surfaces for three-dimensional models in CAD/CAE programs. As a model for FEM calculation is prepared with a CAD program it is inevitable to mesh it finally. There are many algorithms for meshing planar regions. Some of them may be used for meshing surfaces but it is necessary to take the curvature of the surface under consideration to avoid poor quality mesh. The mesh must be denser in the...
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Advancing Solar Energy: Machine Learning Approaches for Predicting Photovoltaic Power Output
PublikacjaThis research is primarily concentrated on predicting the output of photovoitaic power, an essential field in the study of renewable energy. The paper comprehensively reviews various forecasting methodologies, transitioning from conventional physical and statistical methods to advanced machine learning (ML) techniques. A significant shift has been observed from traditional point forecasting to machine learning-based forecasting...
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Impact of Low Switching-to-Fundamental Frequency Ratio on Predictive Current Control of PMSM: A simulation study
PublikacjaPredictive current control algorithms for permanent magnet synchronous (PMSM) drives rely on an assumption that within short intervals motor currents can be approximated with linear functions. This approximation may result either from discretizing the motor model or from simplifications applied to the continuous-time model. As the linear current approximation has been recognized as inaccurate in case when the drive operates with...
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Predicting the impact of traffic–induced vibrations on buildings using artificial neural networks
PublikacjaTraffic–induced vibrations may constitute a considerable load to a building, cause cracking of plaster, cracks in load–bearing elements or even a global structural collapse of the whole structure [1-4]. Vibrations measurements of real structures are costly and laborious, not justified in all cases. The aim of the paper is to create an original algorithm, to predict the negative dynamic impact on the examined residential building...
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Crowdsourcing-Based Evaluation of Automatic References Between WordNet and Wikipedia
PublikacjaThe paper presents an approach to build references (also called mappings) between WordNet and Wikipedia. We propose four algorithms used for automatic construction of the references. Then, based on an aggregation algorithm, we produce an initial set of mappings that has been evaluated in a cooperative way. For that purpose, we implement a system for the distribution of evaluation tasks, that have been solved by the user community....
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Improving SBR Performance Alongside with Cost Reduction through Optimizing Biological Processes and Dissolved Oxygen Concentration Trajectory
PublikacjaAuthors of this paper take under investigation the optimization of biological processes during the wastewater treatment in sequencing batch reactor (SBR) plant. A designed optimizing supervisory controller generates the dissolved oxygen (DO) trajectory for the lower level parts of the hierarchical control system. Proper adjustment of this element has an essential impact on the efficiency of the wastewater treatment process as well...
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Poprawa jakości klasyfikacji głębokich sieci neuronowych poprzez optymalizację ich struktury i dwuetapowy proces uczenia
PublikacjaW pracy doktorskiej podjęto problem realizacji algorytmów głębokiego uczenia w warunkach deficytu danych uczących. Głównym celem było opracowanie podejścia optymalizującego strukturę sieci neuronowej oraz zastosowanie uczeniu dwuetapowym, w celu uzyskania mniejszych struktur, zachowując przy tym dokładności. Proponowane rozwiązania poddano testom na zadaniu klasyfikacji znamion skórnych na znamiona złośliwe i łagodne. W pierwszym...