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Search results for: bayesian compressive sensing
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Compressive Sensing Approach to Harmonics Detection in the Ship Electrical Network
PublicationThe contribution of this paper is to show the opportunities for using the compressive sensing (CS) technique for detecting harmonics in a frequency sparse signal. The signal in a ship’s electrical network, polluted by harmonic distortions, can be modeled as a superposition of a small number of sinusoids and the discrete Fourier transform (DFT) basis forms its sparse domain. According to the theory of CS, a signal may be reconstructed...
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Signal Reconstruction from Sparse Measurements Using Compressive Sensing Technique
PublicationThe paper presents the possibility of applying a new class ofmathematical methods, known as Compressive Sensing (CS) for recovering thesignal from a small set of measured samples. CS allows the faithful recon-struction of the original signal back from fewer random measurements bymaking use of some non-linear reconstruction techniques. Since of all thesefeatures, CSfinds its applications especially in the areas where, sensing is...
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Direct spectrum detection based on Bayesian approach
PublicationThe paper investigates the Bayesian framework's performance for a direct detection of spectrum parameters from the compressive measurements. The reconstruction signal stage is eliminated in by the Bayesian Compressive Sensing algorithm, which causes that the computational complexity and processing time are extremely reduced. The computational efficiency of the presented procedure is significantly...
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Rzadka reprezentacja sygnału niestacjonarnego w technice oszczędnego próbkowania
PublicationPrzedstawiono zastosowanie techniki oszczędnego próbkowania do rekonstrukcji sygnału niestacjonarnego na podstawie skompresowanych próbek w dziedzinie czas-częstotliwość. Zastosowano nadmiarowy algorytm z różnymi słownikami aby znaleźć rzadką reprezentację sygnału. Wyniki symulacji potwierdzają, że zastosowanie oszczędnego próbkowania pozwala na rekonstrukcję sygnału niestacjonarnego z małej liczby losowo pobranych próbek, z niewielką...
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Acoustic Sensing Analytics Applied to Speech in Reverberation Conditions
PublicationThe paper aims to discuss a case study of sensing analytics and technology in acoustics when applied to reverberation conditions. Reverberation is one of the issues that makes speech in indoor spaces challenging to understand. This problem is particularly critical in large spaces with few absorbing or diffusing surfaces. One of the natural remedies to improve speech intelligibility in such conditions may be achieved through speaking...
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Szybka identyfikacja harmonicznych na podstawie oszczędnego próbkowania
PublicationW pracy przedstawiono implementację szybkiego algorytmu rekonstrukcji sygnału, opartego na teorii oszczędnego próbkowania, który może wykrywać harmoniczne w sygnale wejściowym. Zagadnienie rekonstrukcji sygnału jest problemem optymalizacyjnym rozwiązywanym za pomocą algorytmu programowania liniowego. Dodatkowo, aby przyspieszyć zbieżność rozwiązania zastosowano w rzadkiej dziedzinie sygnału filtr typu K-rank-order. Przeprowadzona...
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Remote Sensing
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An adaptive-noise Augmented Kalman Filter approach for input-state estimation in structural dynamics
PublicationThe establishment of a Digital Twin of an operating engineered system can increase the potency of Structural Health Monitoring (SHM) tools, which are then bestowed with enhanced predictive capabilities. This is particularly relevant for wind energy infrastructures, where the definition of remaining useful life is a main driver for assessing the efficacy of these systems. In order to ensure a proper representation of the physical...
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Magdalena Apollo dr inż.
People2017 - PhD in Civil Engineering, thesis: Risk management in construction investments related to urban regeneration projects, Gdansk University of Technology IX 2012–VI 2013 - Postgraduate Studies at Gdynia Maritime University: Research Project Management (IPMA D Certificate) 2010 – MSc in Management and Marketing, Gdansk University of Technology 2007 – MSc in Civil Engineering, Gdansk University of Technology 2007-2010 - structural...
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Bayesian Analysis
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On Bayesian Tracking and Prediction of Radar Cross Section
PublicationWe consider the problem of Bayesian tracking of radar cross section. The adopted observation model employs the gamma family, which covers all Swerling cases in a unified framework. State dynamics are modeled using a nonstationary autoregressive gamma process. The principal component of the proposed solution is a nontrivial gamma approximation, applied during the time update recursion. The superior performance of the proposed approach...
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Optimizing Construction Engineering Management Using Metaheuristic Methods and Bayesian Networks
PublicationThe construction of buildings invariably involves time and costs, and disruptions impact ongoing construction projects. Crisis situations in management strategies, structural confusion, and finan-cial miscalculations often arise due to misguided decision-making. This article proposes a method that combines the learning of Bayesian Networks and heuristic techniques to optimize deci-sion-making processes in construction scheduling....
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Fluctuation-Enhanced Sensing (FES): A Promising Sensing Technique
PublicationFluctuation-enhanced sensing (FES) is a very powerful odor and gas sensing technique and as such it can play a fundamental role in the control of environments and, therefore, in the protection of health. For this reason, we conduct a comprehensive survey on the state-of-the-art of the FES technique, highlighting potentials and limits. Particular attention is paid to the dedicated instrumentation necessary for the application of...
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Observation Value Analysis – Integral Part of Bayesian Diagnostics
PublicationThe decision making process, in general, is understood as a process of selecting one of the available solutions to the problem. One of possible approaches supporting the process is Bayesian statistical decision theory providing a mathematical model to make decisions of a technical nature in conditions of uncertainty. Regarding above, a detailed subject of the research is to analyze the value of the observation, which is a part...
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Bayesian Optimization for solving high-frequency passive component design problems
PublicationIn this paper, the performance of the Bayesian Optimization (BO) technique applied to various problems of microwave engineering is studied. Bayesian optimization is a novel, non-deterministic, global optimization scheme that uses machine learning to solve complex optimization problems. However, each new optimization scheme needs to be evaluated to find its best application niche, as there is no universal technique that suits all...
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Sharp transitions in low-number quantum dots Bayesian magnetometry
PublicationWe consider Bayesian estimate of static magnetic field, characterized by a prior Gaussian probability distribution, in systems of a few electron quantum dot spins interacting with infinite temperature spin environment via hyperfine interaction. Sudden transitions among optimal states and measurements are observed. Usefulness of measuring occupation levels is shown for all times of the evolution, together with the role of entanglement...
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Ultimate compressive strength assessment of uncleaned and cleaned corroded plates with locked crack
PublicationThe work presented here investigates the structural response of cleaned corroded plates, subjected to compressive load in the presence of a locked crack, where the change of mechanical properties as a result of corrosion development and the cleaning process is also accounted for. A Finite Element model for assessing the compressive strength, considering geometric and material nonlinearities, is developed, and the analysed plates...
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Analysis of ultimate compressive strength of cracked plates with the use of DOE techniques
PublicationThe objective of this work is to investigate the structural compressive response of plates with locked cracks accounting for all relevant factors and correlation between them. The nonlinear FE model considering both geometric and material nonlinearities is employed herein, and the FE model of the structural response of intact plates is validated with the available experimental data. In the common studies, based on One Factor at...
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A Bayesian regularization-backpropagation neural network model for peeling computations
PublicationA Bayesian regularization-backpropagation neural network (BRBPNN) model is employed to predict some aspects of the gecko spatula peeling, viz. the variation of the maximum normal and tangential pull-off forces and the resultant force angle at detachment with the peeling angle. K-fold cross validation is used to improve the effectiveness of the model. The input data is taken from finite element (FE) peeling results. The neural network...
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Concrete Compressive Strength Under Changing Environmental Conditions During Placement Processes
PublicationThe technological process of concrete production consists of several parts, including concrete mix design, concrete mix production, transportation of fresh concrete mix to a construction site, placement in concrete framework, and curing. Proper execution of these steps provides good quality concrete. Some factors can disturb the technological process, mainly temperature and excessive precipitation. Changing daily temperature and...
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FE analysis of support-specimen interaction of compressive experimental test
PublicationThe objective of this work is to investigate the support-specimen interaction during the compressive experimental testing of stiffened plates. The interaction is analyzed employing the nonlinear Finite Element Method using the commercial software ANSYS. The connection between the stiffened plate and testing supports is modelled with the use of contact elements, where several possible interaction scenarios are investigated, and...
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Fluctuation-Enhanced Sensing
PublicationFluctuation-enhanced sensing (FES) is an exciting and relatively new research field that promises to extend the range of information that can be extracted from a single sensor. In FES, the stochastic fluctuations of the sensor signal, rather than its average value, are recorded and analyzed. Typical components of such fluctuations are due to interactions at the microscopic level. Proper statistical analysis provides optimum sensory...
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Machine-learning methods for estimating compressive strength of high-performance alkali-activated concrete
PublicationHigh-performance alkali-activated concrete (HP-AAC) is acknowledged as a cementless and environmentally friendly material. It has recently received a substantial amount of interest not only due to the potential it has for being used instead of ordinary concrete but also owing to the concerns associated with climate change, sustainability, reduction of CO2 emissions, and energy consumption. The characteristics and amounts of the...
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Advanced Bayesian study on inland navigational risk of remotely controlled autonomous ship
PublicationThe arise of autonomous ships has necessitated the development of new risk assessment techniques and methods. This study proposes a new framework for navigational risk assessment of remotely controlled Maritime Autonomous Surface Ships (MASS). This framework establishes a set of risk influencing factors affecting safety of navigation of a remotely-controlled MASS. Next, model parameters are defined based on the risk factors, and...
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Underground Water Level Prediction in Remote Sensing Images Using Improved Hydro Index Value with Ensemble Classifier
PublicationThe economic sustainability of aquifers across the world relies on accurate and rapid estimates of groundwater storage changes, but this becomes difficult due to the absence of insitu groundwater surveys in most areas. By closing the water balance, hydrologic remote sensing measures offer a possible method for quantifying changes in groundwater storage. However, it is uncertain to what extent remote sensing data can provide an...
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Spiral Search Grasshopper Features Selection with VGG19-ResNet50 for Remote Sensing Object Detection
PublicationRemote sensing object detection plays a major role in satellite imaging and is required in various scenarios such as transportation, forestry, and the ocean. Deep learning techniques provide efficient performance in remote sensing object detection. The existing techniques have the limitations of data imbalance, overfitting, and lower efficiency in detecting small objects. This research proposes the spiral search grasshopper (SSG)...
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Remote Sensing in Vessel Detection and Navigation
PublicationThe Special Issue (SI) “Remote Sensing in Vessel Detection and Navigation” highlighted a variety of topics related to remote sensing with navigational sensors. The sequence of articles included in this Special Issue is in line with the latest scientific trends. The latest developments in science, including artificial intelligence, were used. The 15 papers (from 23 submitted) were published.
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Compressive strength data of cementitous material with biochar and recycled fines
Open Research DataCompressive strength data of cementitous material with biochar and recycled fines using Controls UTM250.
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Advanced numerical modelling for predicting residual compressive strength of corroded stiffened plates
PublicationAn advanced methodology for predicting the residual compressive strength of corroded stiffened plates is developed here using the non-linear finite element method. The non-uniform loss of a plate thickness is accounted for on a macro-scale. In contrast, mechanical properties are changed using the constitutive model to reflect the corrosion degradation impact on a micro-scale. Three different stiffened plate thicknesses are considered,...
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Jakub Szulwic dr inż.
PeopleJakub Szulwic (born 23 December 1974 in Bydgoszcz, Poland) – is an experienced, licensed Land Surveyor, specialized in construction monitoring by the use of photogrammetric methods and laser scanning technology. His specialization are geomatics and geoinformatics. He is an author about 100 publications including 50 indexed in Web of Science (H-index = 15) In 1993, He graduated from Secondary School in Tuchola, Poland on physics...
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Recognition and sensing of anions
PublicationMolecular ion recognition is one of the most intensively studied areas of supramolecular technology. The reason for this is the essential role that ions play in many biological as well as industrial processes. On the other hand, however, it has been proved that ions can have a negative impact on human health and the environment. For these reasons, it is extremly important to develop rapid and simple methods allowing the determination...
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Quantum dots in gas sensing a review
PublicationAir pollution becomes an increasing problem in the recent years. There is a need to develop more sensitive gas sensors. Much effort has been performed to develop different types of gas sensors, such as electrochemical sensors or polymer sensors. One of the most promising approaches to improve sensors performance is the application of the nanostructures as sensing materials. State of the art of quantum...
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Correlation between Compressive Strength and Heat of Hydration of Cement Mortars with Siliceous Fly Ash
PublicationThis paper presents the results of calorimetric and strength tests of mortars with ordinary Portland cement and two substitution rates (10 and 20%) of cement by siliceous fly ash. The prepared samples were cured under isothermal conditions at four different temperatures: 23, 33, 43 and 53 °C. Heat of hydration was measured using an isothermal calorimeter dedicated to monitor the hydration process of cementitious composites such...
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Cascade Object Detection and Remote Sensing Object Detection Method Based on Trainable Activation Function
PublicationObject detection is an important process in surveillance system to locate objects and it is considered as major application in computer vision. The Convolution Neural Network (CNN) based models have been developed by many researchers for object detection to achieve higher performance. However, existing models have some limitations such as overfitting problem and lower efficiency in small object detection. Object detection in remote...
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Analysis of compressive forces in CFGFT cylindrical pillars and their coatings using laboratory tests and metric spaces
PublicationThe article discusses compressive forces tests in composite-concrete pillars with the use of laboratory active experiment including the factors and properties of materials which have a significant impact on the test results and their repeatability. A polymer composite based on glass fiber reinforced resin with different fiber beam angles (20, 55 and 85) was used as a buffer/coat of the pole. Due to the problems with direct comparison...
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Feature Weighted Attention-Bidirectional Long Short Term Memory Model for Change Detection in Remote Sensing Images
PublicationIn 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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Reliability of Corroded Stiffened Plate Subjected to Uniaxial Compressive Loading
PublicationThe work is focused on the reliability of corroded stiffened plates subjected to compressive uniaxial load based on the progressive collapse approach as stipulated by the Common Structural Rules for Bulk Carriers and Oil Tankers, employing the limit state design. Two different cases have been investigated. In the first model, the corrosion degradation led to uniform thickness loss, whereas the mechanical properties were unchanged,...
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Satellite remote sensing - EMSS - 2022
e-Learning CoursesThis course is designed for M.Sc. students of Space and Satellite Technologies, including HSB specialries Computer Science and Aerospace Technologies, within the specialty Engineering and Management of Space Systems (EMSS).
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Satellite remote sensing - EMSS - 2023
e-Learning CoursesThis course is designed for M.Sc. students of Space and Satellite Technologies, including HSB specialries Computer Science and Aerospace Technologies, within the specialty Engineering and Management of Space Systems (EMSS).
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Sensing and Bio-Sensing Research
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The Idea of Using Bayesian Networks in Forecasting Impact of Traffic-Induced Vibrations Transmitted through the Ground on Residential Buildings
PublicationTraffic–induced vibrations may constitute a considerable load to buildings. In this paper, vibrations transmitted through the ground caused by wheeled vehicles are considered. This phenomenon may cause cracking of plaster, cracks in load-bearing elements or even, in extreme cases, collapse of the whole structure. Measurements of vibrations of real structures are costly and laborious. Therefore, the aim of the present paper is to...
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Evidence-Based Risk Management for Civil Engineering Projects Using Bayesian Belief Networks (BBN)
PublicationThe authors are seeking new methods for improving the efficiency of the investments associated with the maintenance and operation of existing civil engineering structures. It is demonstrated how the knowledge about the elements of construction and operation phases and their relationships, combined with monitoring data can be used for more effective management of the risks associated with civil engineering projects. The methodology...
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Impact of Tensile and Compressive Stress on Classical and Acoustic Barkhausen Effects in Grain-Oriented Electrical Steel
PublicationIn this paper, we present the results of the investigation of impact of tensile and compressive stress on the classical Barkhausen effect, magnetoacoustic emission (MAE) signal properties, and B(H) hysteresis loops for grain-oriented (GO) electrical steel. Samples have been glued to a nonmagnetic steel bar and stressed within elastic range (±800 μdef) by means of four-point bending method. The samples were cut out in two directions...
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Compressive strength and density of cement pastes containing iron oxide (Fe3O4) nanoparticles (nanomagnetite)
Open Research Data*.ODS - open-data source spreadsheet - Dataset presenting:
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Perspectives of Fluctuation-Enhanced Gas Sensing by Two-Dimensional Materials
PublicationWe present the results of gas sensing using the fluctuation-enhanced sensing method in selected two-dimensional materials (2DMs). We claim that gas sensing selectivity can be improved further by considering semiconducting two-dimensional materials doped by noble metal nanoparticles. The 2DMs' structures exhibit some imperfections defined by their structure, occurring repeatedly there. These imperfections are adsorption-desorption...
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Korzyści z zastosowania układów Load Sensing
PublicationW artykule porównano układy Load Sensing I i II rodzaju z układem z dwudrogowym regulatorem przepływu. Dokonano oceny mocy traconych oraz korzyści stosowania układów LS w stosunku do tradycyjnych rozwiązań
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On reliability assessment of ship machinery system in different autonomy degree; A Bayesian-based approach
PublicationAnalyzing the reliability of autonomous ships has recently attracted attention mainly due to epistemic uncertainty (lack of knowledge) integrated with automatic operations in the maritime sector. The advent of new random failures with unrecognized failure patterns in autonomous ship operations requires a comprehensive reliability assessment specifically aiming at estimating the time in which the ship can be trusted to be left unattended....
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Numerical and experimental study on effect of boundary conditions during testing of stiffened plates subjected to compressive loads
PublicationThis study analyses the effect of boundary conditions during testing on the structural behaviour stiffened plates with different thicknesses subjected to compressive loads. The goal of the compressive tests is to analyse the ultimate strength of a stiffened plate. During the test, relevant physical quantities are measured and investigated. The supporting structure's behaviour is investigated by analysing the force-displacements...
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Nitrogen dioxide sensing properties of PEDOT polymer films
PublicationThis work presents a simple and fully electrochemical route for the polymerization of poly(3,4-ethylenedioxytiophene) (PEDOT) films for fabricating a NO2 gas sensor prepared by electropolymerization of 3,4-Ethylenedioxythiophene (EDOT) monomer in lithium perchlorate/acetonitrile solution. The main aim of this study is to determine the sensing properties of conductive polymer at elevated temperatures. The effects of the humidity,...
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Application of Bayesian Networks in risk diagnostics arising from the degree of urban regeneration area degradation
PublicationUrban regeneration as a complex project, generates many extremely specific threats affecting the increase of investment risk. Its unique nature causes that probability parameter, normally applied in the process of risk quantification, is extremely difficult to estimate. Due to lack of historical data urban regeneration related activities are therefore associated with uncertainty. According to the authors, a useful tool for resolving...