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Search results for: separable algorithm
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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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Piotr Sypek dr inż.
PeoplePiotr Sypek received the M.S.E.E. and Ph.D. degrees (with hons.) in microwave engineering from the Gdańsk University of Technology, Gdańsk, Poland, in 2003 and 2012, respectively. He was involved in the design and implementation of parallel algorithms for the formulation and solution of electromagnetic problems executed on CPUs (workstations and clusters) and GPUs. His current research interests include parallel processing in computational...
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The Quick Measure of a Nurbs Surface Curvature for Accurate Triangular Meshing
PublicationNURBS 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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Predicting the impact of traffic–induced vibrations on buildings using artificial neural networks
PublicationTraffic–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
PublicationThe 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
PublicationAuthors 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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Impact of Low Switching-to-Fundamental Frequency Ratio on Predictive Current Control of PMSM: A simulation study
PublicationPredictive 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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Advancing Solar Energy: Machine Learning Approaches for Predicting Photovoltaic Power Output
PublicationThis 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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0-step K-means for clustering Wikipedia search results
PublicationThis article describes an improvement for K-means algorithm and its application in the form of a system that clusters search results retrieved from Wikipedia. The proposed algorithm eliminates K-means isadvantages and allows one to create a cluster hierarchy. The main contributions of this paper include the ollowing: (1) The concept of an improved K-means algorithm and its application for hierarchical clustering....
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Poprawa jakości klasyfikacji głębokich sieci neuronowych poprzez optymalizację ich struktury i dwuetapowy proces uczenia
PublicationW 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...
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Algoritmically improved microwave radar monitors breathing more acurrate than sensorized belt
PublicationThis paper describes a novel way to measure, process, analyze, and compare respiratory signals acquired by two types of devices: a wearable sensorized belt and a microwave radar-based sensor. Both devices provide breathing rate readouts. First, the background research is presented. Then, the underlying principles and working parameters of the microwave radar-based sensor, a contactless device for monitoring breathing, are described....
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Elimination of clicks from archive speech signals using sparse autoregressive modeling
PublicationThis paper presents a new approach to elimination of impulsivedisturbances from archive speech signals. The proposedsparse autoregressive (SAR) signal representation is given ina factorized form - the model is a cascade of the so-called formantfilter and pitch filter. Such a technique has been widelyused in code-excited linear prediction (CELP) systems, as itguarantees model stability. After detection of noise pulses usinglinear...
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Separability in terms of a single entanglement witness
PublicationThe separability problem is formulated in terms of a characterization of a single entanglement witness. More specifically, we show that any (in general multipartite) state rho is separable if and only if a specially constructed entanglement witness W-rho is weakly optimal, i.e., its expectation value vanishes on at least one product vector. Interestingly, the witness can always be chosen to be decomposable. Our result changes the...
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Broadcast copies reveal the quantumness of correlations
PublicationWe study the quantumness of bipartite correlations by proposing a quantity that combines a measure of total correlations-mutual information-with the notion of broadcast copies-i.e., generally nonfactorized copies-of bipartite states. By analyzing how our quantity increases with the number of broadcast copies, we are able to classify classical, separable, and entangled states. This motivates the definition of the broadcast regularization...
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OCHRONA PRYWATNOŚCI W SYSTEMACH MONITORINGU WIZYJNEGO, PRZEGLĄD OPRACOWANYCH ARCHITEKTUR I ALGORYTMÓW
PublicationNieustannie rozwijające się technologie informacyjne związane z inteligentnym monitoringiem wizyjnym stwarzają ryzyko niewłaściwego wykorzystywania danych osobowych. W celu zapewnienia prawidłowej ochrony materiału wizyjnego, w ramach projektów realizowanych w Katedrze Systemów Multimedialnych WETI PG, opracowany został szereg architektur i algorytmów, które ułatwiają ochronę danych wrażliwych, takich jak: wizerunki osób, numery...
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Silence/noise detection for speech and music signals
PublicationThis paper introduces a novel off-line algorithm for silence/noise detection in noisy signals. The main concept of the proposed algorithm is to provide noise patterns for further signals processing i.e. noise reduction for speech enhancement. The algorithm is based on frequency domain characteristics of signals. The examples of different types of noisy signals are presented.
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Parallel Background Subtraction in Video Streams Using OpenCL on GPU Platforms
PublicationImplementation of the background subtraction algorithm using OpenCL platform is presented. The algorithm processes live stream of video frames from the surveillance camera in on-line mode. Processing is performed using a host machine and a parallel computing device. The work focuses on optimizing an OpenCL algorithm implementation for GPU devices by taking into account specific features of the GPU architecture, such as memory access,...
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A Robust Random Forest Model for Classifying the Severity of Partial Discharges in Dielectrics
PublicationPartial Discharges (PDs) are a common source of degradation in electrical assets. It is essential that the extent of the deterioration level of insulating medium is correctly identified, to optimize maintenance schedules and prevent abrupt power outages. Temporal PD signals received from damaged insulation, collected through the IEC-60270 method is the gold standard for PD detection. Temporal signals may be transformed to the frequency...
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Fast Real-Time RDFT- and GDFT-Based Direct Fault Diagnosis of Induction Motor Drive
PublicationThis paper presents the theoretical analysis and experimental verification of a direct fault harmonic identification approach in a converter-fed electric drive for automated diagnosis purposes. On the basis of the analytical model of the proposed real-time direct fault diagnosis, the fault-related harmonic component is calculated using recursive DFT (RDFT) and Goertzel DFT (GDFT), applied instead of the full spectrum calculations...
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Advanced Control With PLC—Code Generator for aMPC Controller Implementation and Cooperation With External Computational Server for Dealing With Multidimensionality, Constraints and LMI Based Robustness
PublicationThe manufacturers of Programmable Logic Controllers (PLC) usually equip their products with extremely simple control algorithms, such as PID and on-off regulators. However, modern PLCs have much more efficient processors and extensive memory, which enables implementing more sophisticated controllers. The paper discusses issues related to the implementation of matrix operations, time limitations for code execution within one PLC...
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Janusz Cieśliński prof. dr hab. inż.
PeopleHe was born on April 15, 1954 in Slupsk. He graduated from the Faculty of Mechanical Engineering at Gdańsk University of Technology (1978). In 1986 he received the title of Doctor, in 1997 he obtained the title of Ph.D. with habilitation, and in 2006 he received the title of Professor. He worked as head of department and vice-dean for Education at the Faculty of Mechanical Engineering for two terms (2002-2008). His research interests...
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A non-uniform real-time speech time-scale stretching method
PublicationAn algorithm for non-uniform real-time speech stretching is presented. It provides a combination of typical SOLA algorithm (Synchronous Overlap and Add ) with the vowels, consonants and silence detectors. Based on the information about the content and the estimated value of the rate of speech (ROS), the algorithm adapts the scaling factor value. The ability of real-time speech stretching and the resultant quality of voice were...
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A low complexity double-talk detector based on the signal envelope
PublicationA new algorithm for double-talk detection, intended for use in the acoustic echo canceller for voice communication applications, is proposed. The communication system developed by the authors required the use of a double-talk detection algorithm with low complexity and good accuracy. The authors propose an approach to doubletalk detection based on the signal envelopes. For each of three signals: the far-end speech, the microphone...
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Labeler-hot Detection of EEG Epileptic Transients
PublicationPreventing early progression of epilepsy and sothe severity of seizures requires effective diagnosis. Epileptictransients indicate the ability to develop seizures but humansoverlook such brief events in an electroencephalogram (EEG)what compromises patient treatment. Traditionally, trainingof the EEG event detection algorithms has relied on groundtruth labels, obtained from the consensus...
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Visual Data Encryption for Privacy Enhancement in Surveillance Systems
PublicationIn this paper a methodology for employing reversible visual encryption of data is proposed. The developed algorithms are focused on privacy enhancement in distributed surveillance architectures. First, motivation of the study performed and a short review of preexisting methods of privacy enhancement are presented. The algorithmic background, system architecture along with a solution for anonymization of sensitive regions of interest...
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IPMSM rotor position estimator based on analysis of phase current derivatives
PublicationThis paper describes an algorithm for estimation of IPMSM angular rotor position. The algorithm uses derivatives of motor phase currents resulting from PWM modulation to obtain the rotor position. The presented method is designed for medium- and high-speed range, since it is based on determination of the EMF vector. Algorithm is characterised by a very simple formulae. The calculation of rotor position is performed in every PWM...
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Automatic Detection of Nerves in Confocal Corneal Images with Orientation-Based Edge Merging
PublicationThe paper presents an algorithm for improving results of automatic nerve detections in confocal microscopy images of human corneal. The method is designed as a postprocessing step of regular detection. After the nerves are initially detected, the algorithms attempts to improve the results by filling unde-sired gaps between single nerves detections in order to correctly mark the entire nerve instead of only parts of it. This approach...
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Dobór parametrów silnika indukcyjnego dużej mocy
PublicationW artykule przedstawiono trzy typy statycznych modeli matematycznych silników klatkowych oraz metodę estymacji parametrów, przy wykorzystaniu algorytmów genetycznych. Korzystając z kryteriów: suma kwadratów, suma wartości bez-względnych oraz całkowego, oceniono przydatność badanych modeli. Opracowane modele matematyczne zostały wykorzystane przy doborze algorytmów sterownia sterów strumieniowych. Po-kazano metodykę doboru parametrów...
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Multimodal system for diagnosis and polysensory stimulation of subjects with communication disorders
PublicationAn experimental multimodal system, designed for polysensory diagnosis and stimulation of persons with impaired communication skills or even non-communicative subjects is presented. The user interface includes an eye tracking device and the EEG monitoring of the subject. Furthermore, the system consists of a device for objective hearing testing and an autostereoscopic projection system designed to stimulate subjects through their...
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Collective Uncertainty Entanglement Test
PublicationFor a given pure state of a composite quantum system we analyze the product of its projections onto aset of locally orthogonal separable pure states. We derive a bound for this product analogous to theentropic uncertainty relations. For bipartite systems the bound is saturated for maximally entangled statesand it allows us to construct a family of entanglement measures, we shall call collectibility. As thesequantities are experimentally...
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Autonomous port management based AGV path planning and optimization via an ensemble reinforcement learning framework
PublicationThe rapid development of shipping trade pushes automated container terminals toward the direction of intelligence, safety and efficiency. In particular, the formulation of AGV scheduling tasks and the safety and stability of transportation path is an important part of port operation and management, and it is one of the basic tasks to build an intelligent port. Existing research mainly focuses on collaborative operation between...
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Study of various machine learning approaches for Sentinel-2 derived bathymetry
PublicationIn recent years precise and up-to-date information regarding seabed depth has become more and more important for companies and institutions that operate on coastlines. While direct, in-situ measurements are performed regularly, they are expensive, time-consuming and impractical to be performed in short time intervals. At the same time, an ever-increasing amount of satellite imaging data becomes available. With these images, it...
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Domain segmentation for low-cost surrogate-assisted multi-objective design optimisation of antennas
PublicationAbstract: Information regarding the best possible design trade-offs of an antenna structure can be obtained through multiobjective optimisation (MO). Unfortunately, MO is extremely challenging if full-wave electromagnetic (EM) simulation models are used for performance evaluation. Yet, for the majority of contemporary antennas, EM analysis is the only tool that ensures reliability. This study introduces a procedure for accelerated...
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Accelerated multi-objective design optimization of antennas by surrogate modeling and domain segmentation
PublicationMulti-objective optimization yields indispensable information about the best possible design trade-offs of an antenna structure, yet it is challenging if full-wave electromagnetic (EM) analysis is utilized for performance evaluation. The latter is a necessity for majority of contemporary antennas as it is the only way of achieving acceptable modeling accuracy. In this paper, a procedure for accelerated multi-objective design of...
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Determining the optimal filling of the surface with a linker with Universal Force Field and Reax Force Field
Open Research DataThe DataSet contains the atomic slabs of diamond surfaces with ATP molecules in water. The calculated data includes different sized surfaces from 90 Angstrom^2 to 691 Angstrom^2. Structures were relaxed using the Reax Force Field method with the Limited Memory Broyden–Fletcher–Goldfarb–Shanno algorithm. Structures were calculated with a convergence...
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Fast multi-objective design optimization of microwave and antenna structures using data-driven surrogates and domain segmentation
PublicationPurpose Strategies and algorithms for expedited design optimization of microwave and antenna structures in multi-objective setup are investigated. Design/methodology/approach Formulation of the multi-objective design problem oriented towards execution of the population-based metaheuristic algorithm within the segmented search space is investigated. Described algorithmic framework exploit variable fidelity modeling, physics- and...
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Mykola Lukianov mgr
PeopleMykola Lukianov received a B.Sc. and M.Sc degree in Electronics and Communications from the National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute” in 2018 and 2020 respectively. He is currently a PhD student at the Gdansk University of Technology, Poland and a researcher group member in project SMARTGYsum “Research and Training Network for Smart and Green Energy Systems and Business Models”. His research...
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Detection of vehicles stopping in restricted zones in video from surveillance cameras
PublicationAn algorithm for detection of vehicles that stop in restricted areas, e.g. excluded by traffic rules, is proposed. Classic approaches based on object tracking are inefficient in high traffic scenes because of tracking errors caused by frequent object merging and splitting. The proposed algorithm uses the background subtraction results for detection of moving objects, then pixels belonging to moving objects are tested for stability....
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Model Predictive Super-Twisting Sliding Mode Control for An Autonomous Surface Vehicle
PublicationThis paper presents a new robust Model Predictive Control (MPC) algorithm for trajectory tracking of an Autonomous Surface Vehicle (ASV) in presence of the time-varying external disturbances including winds, waves and ocean currents as well as dynamical uncertainties. For fulfilling the robustness property, a sliding mode control-based procedure for designing of MPC and a super-twisting term are adopted. The MPC algorithm has been...
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Wykorzystanie klasyfikacji funkcjonalnej usług do efektywnego zarządzania zasobami chmurowymi
PublicationWykazano jak istotnym problemem jest zarzadzanie chmurą obliczeniową, w tym alokacja zasobów do wykonania usług (workloadów) zgłoszonych przez użytkownika. Przeanalizowano problem podziału usług wdrażanych w środowiskach chmurowych na klasy określające ich funkcjonalność. Zaproponowano oryginalną metodę alokacji workloadów wykorzystującą wprowadzoną klasyfikację funkcjonalną oraz identyfikację tych klas na podstawie wielkości generowanego...
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Real-Time Facial Features Detection from Low Resolution Thermal Images with Deep Classification Models
PublicationDeep networks have already shown a spectacular success for object classification and detection for various applications from everyday use cases to advanced medical problems. The main advantage of the classification models over the detection models is less time and effort needed for dataset preparation, because classification networks do not require bounding box annotations, but labels at the image level only. Yet, after passing...
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Application of the finite element methods in long-term simulation of the multi-physics systems with large transient response differences
PublicationApplication of the Finite Element Method (FEM) and the Multibody Dynamics Method allows analyzing of complex physical systems. Complexity of the system could be related both to the geometry and the physical description of phenomenon. The metod is the excellent tool for analyzing statics or dynamics of the mechanical systems, and permits tracking of Multi Body System (MBS) transient response for the long-term simulations and application...
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Application of a hybrid mechanistic/machine learning model for prediction of nitrous oxide (N2O) production in a nitrifying sequencing batch reactor
PublicationNitrous oxide (N2O) is a key parameter for evaluating the greenhouse gas emissions from wastewater treatment plants. In this study, a new method for predicting liquid N2O production during nitrification was developed based on a mechanistic model and machine learning (ML) algorithm. The mechanistic model was first used for simulation of two 15-day experimental trials in a nitrifying sequencing batch reactor. Then, model predictions...
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Discrete identification of continuous non-linear and non-stationary dynamical systems that is insensitive to noise correlation and measurement outliers
PublicationThe paper uses specific parameter estimation methods to identify the coefficients of continuous-time models represented by linear and non-linear ordinary differential equations. The necessary approximation of such systems in discrete time in the form of utility models is achieved by the use of properly tuned `integrating filters' of the FIR type. The resulting discrete-time descriptions retain the original continuous parameterization...
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Modal parameters identification with Particle Swarm Optimization
PublicationThe paper presents method of the modal parameters identification based on the Particle Swarm Optimization (PSO) algorithm [1]. The basic PSO algorithm is modified in order to achieve fast convergence and low estimation error of identified parameters values. The procedure of identification as well as algorithm modifications are presented and some simple examples for the SISO systems are provided. Results are compared with the results...