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Klasyfikacja sygnału EKG przy użyciu konwolucyjnych sieci neuronowych
PublikacjaAutomation 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
PublikacjaAutomation 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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GNSS INVENTORY OF HISTORIC NARROW-GAUGE RAILWAY LINE IN KOSZALIN UNDER EXTREMELY UNFAVORABLE MEASUREMENTS CONDITIONS FROM THE POINT OF VIEW OF SATELLITE SIGNALS AVAILABILITY
PublikacjaA team of academic researchers from the Gdańsk University of Technology, Gdynia Maritime University and the Polish Naval Academy have been working since 2009 on the methodology of using active GNSS geodetic networks for geodetic inventory of railways and on adapting this measurement technique for designing geometric layouts of railway and tram lines. Over the years, the team tested a variety of configurations of receivers and settings...
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Simulation of unsteady flow over floodplain using the diffusive wave equation and the modified finite element method
PublikacjaWe consider solution of 2D nonlinear diffusive wave equation in a domain temporarily covered by a layer of water. A modified finite element method with triangular elements and linear shape functions is used for spatial discretization. The proposed modification refers to the procedure of spatial integration and leads to a more general algorithm involving a weighting parameter. The standard finite element method and the finite difference...
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Improved Empirical Coefficients for Estimating Water Vapor Weighted Mean Temperature over Europe for GNSS Applications
PublikacjaDevelopment of the so-called global navigation satellite system (GNSS) meteorology is based on the possibility of determining a precipitable water vapor (PWV) from a GNSS zenith wet delay (ZWD). Conversion of ZWD to the PWV requires application of water vapor weighted mean temperature (Tm) measurements, which can be done using a surface temperature (Ts) and its linear dependency to the Tm. In this study we analyzed up to 24 years...
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Polynomial Chaos Expansion in Bio- and Structural Mechanics
PublikacjaThis thesis presents a probabilistic approach to modelling the mechanics of materials and structures where the modelled performance is influenced by uncertainty in the input parameters. The work is interdisciplinary and the methods described are applied to medical and civil engineering problems. The motivation for this work was the necessity of mechanics-based approaches in the modelling and simulation of implants used in the repair...
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Dynamic Bayesian Networks for Symbolic Polyphonic Pitch Modeling
PublikacjaSymbolic pitch modeling is a way of incorporating knowledge about relations between pitches into the process of an- alyzing musical information or signals. In this paper, we propose a family of probabilistic symbolic polyphonic pitch models, which account for both the “horizontal” and the “vertical” pitch struc- ture. These models are formulated as linear or log-linear interpo- lations of up to fi ve sub-models, each of which is...
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A System for Heart Sounds Classification
PublikacjaThe future of quick and efficient disease diagnosis lays in the development of reliable non-invasive methods. As for the cardiac diseases – one of the major causes of death around the globe – a concept of an electronic stethoscope equipped with an automatic heart tone identification system appears to be the best solution. Thanks to the advancement in technology, the quality of phonocardiography signals is no longer an issue. However,...
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Polynomial Chaos Expansion in Bio-and Structural Mechanics
PublikacjaThis monograph presents a probabilistic approach to modelling the mechanics of materials and structures where the modelled performance is influenced by uncertainty in the input parameters. The work is interdisciplinary and the methods described are applied to medical and civil engineering problems. The motivation for this work was the necessity of mechanics-based approaches in the modelling and simulation of implants used in the...
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Degradation of Kinematic PPP of GNSS Stations in Central Europe Caused by Medium-Scale Traveling Ionospheric Disturbances During the St. Patrick’s Day 2015 Geomagnetic Storm
PublikacjaIn solar cycle 24, the strongest geomagnetic storm took place on March 17, 2015, when the geomagnetic activity index was as high as -223 nT. To verify the impact that the storm had on the Global Navigation Satellite System (GNSS)’s positioning accuracy and precision, we used 30-s observations from 15 reference stations located in Central Europe. For each of them, we applied kinematic precise point positioning (PPP) using gLAB software...
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Transfer learning in imagined speech EEG-based BCIs
PublikacjaThe Brain–Computer Interfaces (BCI) based on electroencephalograms (EEG) are systems which aim is to provide a communication channel to any person with a computer, initially it was proposed to aid people with disabilities, but actually wider applications have been proposed. These devices allow to send messages or to control devices using the brain signals. There are different neuro-paradigms which evoke brain signals of interest...
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Predicting emotion from color present in images and video excerpts by machine learning
PublikacjaThis work aims at predicting emotion based on the colors present in images and video excerpts using a machine-learning approach. The purpose of this paper is threefold: (a) to develop a machine-learning algorithm that classifies emotions based on the color present in an image, (b) to select the best-performing algorithm from the first phase and apply it to film excerpt emotion analysis based on colors, (c) to design an online survey...
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Projekt badawczy BRIK: Opracowanie innowacyjnej metody wyznaczania precyzyjnej trajektorii pojazdu szynowego
PublikacjaW artykule przedstawiono podstawowe informacje dotyczące projektu badawczego realizowanego na zlecenie Narodowego Centrum Badań i Rozwoju oraz Spółki PKP Polskie Linie Kolejowe S. A. przez Konsorcjum Politechniki Gdańskiej i Uniwersytetu Morskiego w Gdyni. Projekt obejmuje wykorzystanie nowoczesnych metod pomiarowych, takich jak techniki pozycjonowania satelitarnego GNSS, pomiary inercyjne INS oraz skaning laserowy LS, w procesie...
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Deep convolutional neural network for predicting kidney tumour malignancy
PublikacjaPurpose: According to the statistics, up to 15-20% of removed solid kidney tumors turn out to be benign in postoperative histopathological examination, despite having been identified as malignant by a radiologist. The aim of the research was to limit the number of unnecessary nephrectomies of benign tumors. Methods or Background: We propose a machine-aided diagnostic system for kidney...
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Port-Based Modelling of Distributed-Lumped Parameter Systems
PublikacjaThere in the paper is presented an uniform, port-based approach to modelling of both lumped and distributed parameter systems. Port-based model of the distributed system has been defined by application of bond graph methodology and distributed transfer function method (DTFM). The approach proposed combines versatility of port-based modelling and accuracy of distributed transfer function method. The concise representation of lumped-distributed...
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Ship Dynamic Positioning Based on Nonlinear Model Predictive Control
PublikacjaThe presented work explores the simulation test results of using nonlinear model predictive control algorithm for ship dynamic positioning. In the optimization task, a goal function with a penalty was proposed with a variable prediction step. The results of the proposed control algorithm were compared with backstepping and PID. The effect of estimation accuracy on the control quality with the implemented algorithms was investigated....
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Real and imaginary motion classification based on rough set analysis of EEG signals for multimedia applications
PublikacjaRough set-based approach to the classification of EEG signals of real and imaginary motion is presented. The pre-processing and signal parametrization procedures are described, the rough set theory is briefly introduced, and several classification scenarios and parameters selection methods are proposed. Classification results are provided and discussed with their potential utilization for multimedia applications controlled by the...
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Reliability assessment of truss towers using Monte Carlo Method, PEM and RSM
PublikacjaThe paper discusses reliability assessment of simple random truss structures using three different probabilistic methodologies: the Monte Carlo Method (MCM), the Point Estimate Method (PEM) and the Response Surface Method (RSM). A benchmark truss structure and a simplified full–size engineering tower are both analyzed. A set of ultimate load numerical calculations is performed and the results are taken as the basis of advanced...
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A telemedical and an outpatient thoracic impedance measurements - a validation algorithm of the electrodes placement
PublikacjaThis paper presents the algorithm for validation of electrodes locations for the thoracic impedance measurements. In particular the presented algorithm was designed to perform the telemetric sleep apnea monitoring. One of the problems, during the clinical tests of a developed device, was to preserve the repeatability of measurements. It strongly depended on the appropriate electrodes placement on the examined person’s thorax. It...
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Zero phase shift digital filtering for assessment of exposure to non-sinusoidal magnetic fields
PublikacjaAccuracy of assessment of human body exposure to magnetic fields is affected by several uncertainty sources. One of them is estimation of the total exposure to non-sinusoidal fields. Standard methods can be implemented using analogue or digital filters that introduce a phase shift that affect the result of total exposure level estimation. The paper presents a new method that allows performing more precise assessment of exposure...
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A new method of wind farm active power curve estimation based on statistical approach
PublikacjaThe purpose of this paper is to solve the wind farm active power estimation problem, introducing the method which is based on a statistical approach and robust fitting. The proposed algorithm uses a statistical approach and compared to existing ones- includes a wind direction as well as the influence of turbine start-up procedure on the estimation. The results show that additional estimation inputs i.e. the wind direction and the...
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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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Towards Emotion Acquisition in IT Usability Evaluation Context
PublikacjaThe paper concerns extension of IT usability studies with automatic analysis of the emotional state of a user. Affect recognition methods and emotion representation models are reviewed and evaluated for applicability in usability testing procedures. Accuracy of emotion recognition, susceptibility to disturbances, independence on human will and interference with usability testing procedures are...
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Model Order Reduction for Problems With Dispersive Surface Boundary Conditions
PublikacjaThis letter proposes a new scheme for reduced-order finite-element modeling of electromagnetic structures with nonlinear, dispersive surface boundary conditions, which optimally exploits the numerically stable and efficient MOR framework for second-order systems provided by SAPOR method. The presented results of numerical experiments for an example of a waveguide filter demonstrate the superior accuracy of the resulting reduced models...
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Feature Weighted Attention-Bidirectional Long Short Term Memory Model for Change Detection in Remote Sensing Images
PublikacjaIn remote sensing images, change detection (CD) is required in many applications, such as: resource management, urban expansion research, land management, and disaster assessment. Various deep learning-based methods were applied to satellite image analysis for change detection, yet many of them have limitations, including the overfitting problem. This research proposes the Feature Weighted Attention (FWA) in Bidirectional Long...
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Detecting type of hearing loss with different AI classification methods: a performance review
PublikacjaHearing is one of the most crucial senses for all humans. It allows people to hear and connect with the environment, the people they can meet and the knowledge they need to live their lives to the fullest. Hearing loss can have a detrimental impact on a person's quality of life in a variety of ways, ranging from fewer educational and job opportunities due to impaired communication to social withdrawal in severe situations. Early...
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Kriging-assisted hybrid reliability design and optimization of offshore wind turbine support structure based on a portfolio allocation strategy
PublikacjaIn recent years, offshore wind power generation technology has developed rapidly around the world, making important contributions to the further development of renewable energy. When designing an Offshore Wind Turbine (OWT) system, the uncertainties in parameters and different types of constraints need to be considered to find the optimal design of these systems. Therefore, the Reliability-Based Design Optimization (RBDO) method...
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Machine learning-based prediction of preplaced aggregate concrete characteristics
PublikacjaPreplaced-Aggregate Concrete (PAC) is a type of preplaced concrete where coarse aggregate is placed in the mold and a Portland cement-sand grout with admixtures is injected to fill the voids. Due to the complex nature of PAC, many studies were conducted to determine the effects of admixtures and the compressive and tensile strengths of PAC. Considering that a prediction tool is needed to estimate the compressive and tensile...
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Visual measurement system for chosen parameters of current collectors
PublikacjaA current collector is an element in a traction vehicle, used for movable, contact con-nection between the main circuit of this vehicle and the contact line. Bad technical condi-tion of these important elements in the main circuit of the vehicle result in its incorrect cooperation with contact line. Periodic control of technical condition of current collectors ensures infallible current collection. The pantograph diagnostics consists...
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Novel approach to modeling spectral-domain optical coherence tomography with Monte Carlo method
PublikacjaNumerical modeling Optical Coherence Tomography (OCT) systems is needed for optical setup optimization, development of new signal processing methods and assessment of impact of different physical phenomena inside the sample on OCT signal. The Monte Carlo method has been often used for modeling Optical Coherence Tomography, as it is a well established tool for simulating light propagation in scattering media. However, in this method...
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Large hydrodynamic thrust bearing: Comparison of the calculations and measurements
PublikacjaHydrodynamic thrust bearings, used to carry axial loads in heavily loaded shafts of water power plants hydro turbines, can reach outer diameters even exceeding 5 m. In such large objects scale effect could be observed. According to this, allowable bearing specific load assuring safe operation of the bearings has to be decreased, which increases thrust bearing dimensions. This effect is caused by excessive thermal deflections of...
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Post processing and selecting data obtain with parametric sub-bottom profiler SES-2000 Standard during sounding the Gulf of Gdansk
PublikacjaThe main goal of the paper is to describe the results of sounding the Gulf of Gdansk seabed using a parametric sub-bottom profiler SES-2000 Standard. Quality of obtained during trials data depends inter alia on proper location of antenna to reduce influence of pitch, roll, heave and ship noise (bubbles from propeller and a hull flow, vibration from main engine and peripheral devices). Furthermore calibration of complementary units...
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Scoreboard Architectural Pattern and Integration of Emotion Recognition Results
PublikacjaThis paper proposes a new design pattern, named Scoreboard , dedicated for applications solving complex, multi-stage, non-deterministic problems. The pattern provides a computational framework for the design and implementation of systems that integrate a large number of diverse specialized modules that may vary in accuracy, solution level, and modality. The Scoreboard is an extension of Blackboard design pattern and comes under...
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A three-dimensional periodic beam for vibroacoustic isolation purposes
PublikacjaThis paper presents results of investigations on a three-dimensional (3-D) isotropic periodic beam. The beam can represent a vibroacoustic isolator of optimised dynamic characteristics in the case of its longitudinal, flexural and torsional behaviour. The optimisation process concerned both the widths as well as the positions of particular frequency band gaps that are present in the frequency spectrum of the beam. Since the dynamic...
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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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Deep CNN based decision support system for detection and assessing the stage of diabetic retinopathy
PublikacjaThe diabetic retinopathy is a disease caused by long-standing diabetes. Lack of effective treatment can lead to vision impairment and even irreversible blindness. The disease can be diagnosed by examining digital color fundus photographs of retina. In this paper we propose deep learning approach to automated diabetic retinopathy screening. Deep convolutional neural networks (CNN) - the most popular kind of deep learning algorithms...
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Low Cost Hexacopter Autonomous Platform for Testing and Developing Photogrammetry Technologies and Intelligent Navigation Systems
PublikacjaLow-cost solutions for autonomous aerial platforms are being intensively developed and used within geodetic community. Unmanned aerial vehicles are becoming very popular and widely used for photogrammetry and remote sensing applications. Today’s market offers an affordable price components for unmanned solution with significant quality and accuracy growth. Every year market offers a new solutions for autonomous platforms with better...
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Modeling of lapping plate wear and conditioning in single-sided lapping
PublikacjaIn order to achieve higher quality on worked surfaces with lower roughness, very high accuracy of shape and dimensions it is crucial to improve conventional finishing technologies and to develop new working principles. Single-sided lapping is one of the most effective planarization technologies and it is determined by a number of factors and boundary conditions. The most significant influence over a dimensional and profile accuracy,...
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Determination of rectification corrections for semi gantry crane rail axes in the local 3D coordinate system
PublikacjaElectronic tacheometers are currently the standard instruments used in geodetic work, including also geodetic engineering measurements. The main advantage connected with this equipment is among others high accuracy of the measurement and thus high accuracy of the final determinations represented for example by the points’ coordinates. One of many applications of the tacheometers is the measurement of crane rail axes. This measurement...
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Surface and Trapping Energies as Predictors for the Photocatalytic Degradation of Aromatic Organic Pollutants
PublikacjaIn this study, anatase samples enclosed by the majority of three different crystal facets {0 0 1}, {1 0 0}, and {1 0 1} were successfully synthesized. These materials were further studied toward photocatalytic degradation of phenol and toluene as model organic pollutants in water and gas phases. The obtained results were analyzed concerning their surface structure, reaction type, and surface development. Moreover, the regression...
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Flooding Extent Mapping for Synthetic Aperture Radar Time Series Using River Gauge Observations
PublikacjaThe flooding extent area in a river valley is related to river gauge observations such as discharge and water elevations. The higher the water elevations, or discharge, the larger the flooding area. Flooding extent maps are often derived from synthetic aperture radar (SAR) images using thresholding methods. The thresholding methods vary in complexity and number of required parameters. We proposed a simple thresholding method that...
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Characterization of Defects Inside the Cable Dielectric With Partial Discharge Modeling
PublikacjaThe continuous monitoring of power system devices is an important step toward keeping such capital assets safe. Partial discharge (PD)-based measurement tools provide a reliable and accurate condition assessment of power system insulations. It is very common that voids or cavities exist in every solid dielectric insulation medium. In this article, different voids are modeled and analyzed using an advanced finite element (FE)-based...
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Comparative study on the effectiveness of various types of road traffic intensity detectors
PublikacjaVehicle detection and speed measurements are crucial tasks in traffic monitoring systems. In this work, we focus on several types of electronic sensors, operating on different physical principles in order to compare their effectiveness in real traffic conditions. Commercial solutions are based on road tubes, microwave sensors, LiDARs, and video cameras. Distributed traffic monitoring systems require a high number of monitoring...
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Machine learning-based prediction of preplaced aggregate concrete characteristics
PublikacjaPreplaced-Aggregate Concrete (PAC) is a type of preplaced concrete where coarse aggregate is placed in the mold and a Portland cement-sand grout with admixtures is injected to fill the voids. Due to the complex nature of PAC, many studies were conducted to determine the effects of admixtures and the compressive and tensile strengths of PAC. Considering that a prediction tool is needed to estimate the compressive and tensile strengths...
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Performance Analysis and Quantification of BeiDou Navigation Satellite System (BDS-3)
PublikacjaPositioning, Navigation, and Timing (PNT) information play a vital role in everyday life of common persons. People greatly rely on Global Navigation Satellite System (GNSS)-enabled applications for navigation to reach their desired destination. However, GNSS navigation performance is highly degraded in urban environments due to the high probability of signal interruption, multipath (MP), and/or non-line-of-sight (NLOS) signal...
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KEMR-Net: A Knowledge-Enhanced Mask Refinement Network for Chromosome Instance Segmentation
PublikacjaThis article proposes a mask refinement method for chromosome instance segmentation. The proposed method exploits the knowledge representation capability of Neural Knowledge DNA (NK-DNA) to capture the semantics of the chromosome’s shape, texture, and key points, and then it uses the captured knowledge to improve the accuracy and smoothness of the masks. We validate the method’s effectiveness on our latest high-resolution chromosome...
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Ab-initio study of electrical and optical properties of allylamine
PublikacjaThe Density functional theory is one of most promising methodology in fast and accurate calculations of electrical and optical properties from the atomic basis. In this paper, we calculate electrical and optical properties of allylamine (2-propen 1- amine) in terms of accuracy and speed of calculations obtained by selection of DFT-1/2 method with ultrasoft Vanderbilt pseudopotentials. Comparison of density of states between...
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Enhanced voice user interface employing spatial filtration of signals from acoustic vector sensor
PublikacjaSpatial filtration of sound is introduced to enhance speech recognition accuracy in noisy conditions. An acoustic vector sensor (AVS) is employed. The signals from the AVS probe are processed in order to attenuate the surrounding noise. As a result the signal to noise ratio is increased. An experiment is featured in which speech signals are disturbed by babble noise. The signals before and after spatial filtration are processed...
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Computational complexity and length of recorded data for fluctuation enhanced sensing method in resistive gas sensors
PublikacjaThis paper considers complexity and accuracy of data processing for gas detection using resistance fluctuation data observed in resistance gas sensors. A few selected methods were considered (Principal Component Analysis – PCA, Support Vector Machine – SVM). Functions like power spectral density or histogram were used to create input data vector for these algorithms from the observed resistance fluctuations. The presented considerations...
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Elimination of impulsive disturbances from archive audio files – comparison of three noise pulse detection schemes
PublikacjaThe problem of elimination of impulsive disturbances (such as clicks, pops, ticks, crackles, and record scratches) from archive audio recordings is considered and solved using autoregressive modeling. Three classical noise pulse detection schemes are examined and compared: the approach based on open-loop multi-step-ahead signal prediction, the approach based on decision-feedback signal prediction, and the double threshold approach,...