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Search results for: prediction
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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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Accuracy of Pretreatment Ultrasonography Assessment of Intra-Abdominal Spread in Epithelial Ovarian Cancer: A Prospective Study
PublicationThe aim of this study was to test the accuracy of ultrasonography performed by gynecological oncologists for the preoperative assessment of epithelial ovarian cancer (EOC) spread in the pelvis and abdominal cavity. A prospective, observational cohort study was performed at a single tertiary cancer care unit. Patients with suspected EOC were recruited and underwent comprehensive transvaginal and abdominal ultrasonography performed...
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Zbigniew Łubniewski dr hab. inż.
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Long-term hindcast simulation of sea ice in the Baltic Sea
Open Research DataThe data set contains the results of numerical modeling of sea ice over a period of 50 years (1958-2007) in the Baltic Sea. A long-term hindcast simulation was performed using a three-dimensional hydrodynamic model PM3D (Kowalewski and Kowalewska-Kalkowska, 2017), a new version of the M3D model (Kowalewski, 1997). A numerical dynamic-thermodynamic model...
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Estimation of Housing Demand with Adaptive Neuro-Fuzzy Inference Systems (ANFIS)
PublicationIt has always been important to anticipate the demand for a product. To determine the demand for any product, the parameters such as the economic situation and the demands of the rival products are used generally. Especially in the housing sector, which is the locomotive sector for emerging countries, it is critical to anticipate housing demand and its relationship with economic variables. Because of that, economists, real estate...
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Identification of nonstationary multivariate autoregressive processes– Comparison of competitive and collaborative strategies for joint selection of estimation bandwidth and model order
PublicationThe problem of identification of multivariate autoregressive processes (systems or signals) with unknown and possibly time-varying model order and time-varying rate of parameter variation is considered and solved using parallel estimation approach. Under this approach, several local estimation algorithms, with different order and bandwidth settings, are run simultaneously and compared based on their predictive performance. First,...
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Investigation of the road noise source employing an automatic noise monitoring station
PublicationThe paper presents a pilot investigation of noise source models in two selected localizations in the context of future dynamic noise map creation. The experiments were carried out using the automatic noise monitoring station engineered at the Multimedia Systems Departmentof the Gda´nsk University of Technology. The results of the noise measurements employing monitoring stations and its comparison to the reference values are depicted....
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Viscoplastic damage analysis of structures subjected to impact loading. Plate and shell structures. - Ł. Pyrzowski.
PublicationThe work presents the investigation in the response of plate-shell structures subjected to impact loading (gas mixture explosions). This phenomenon is studied in the context of its mechanical aspects, mainly the ductile fracture prediction. The work starts with the literature review and the description of theories, which are nowadays the most popular in the damage and failure modelling. After selecting the theoretical models and...
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DO WE NEED NAVIER NUMBER? – FURTHER REMARKS AND COMPARISON WITH ANOTHER DIMENSIONLESS NUMBERS
PublicationThis paper presents a role of the Navier number (Na-dimensionless slip-length) in universal modelling of flow reported in micro- and nano-channels like: capillary biological flows, fuel cell systems, micro-electro-mechanical systems and nano-electro-mechanical systems. Similar to another bulk-like and surface-like dimensionless numbers, the Na number should be treated as a ratio of internal viscous to external viscous momentum...
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COMPARISON OF TWO MODELS OF CONDENSATION
PublicationIn the low-pressure part of steam turbine, the state path usually crosses the saturation line in penultimate stages. At least last two stages of this part of turbines operate in two –phase region. The liquid phase in this region in mainly created in the process of homogeneous and heterogeneous condensation. Several observations confirm however, that condensation often occurs earlier than it is predicted by theory i.e. before the...
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Remarks on steam condensation modeling related to steam turbine large output
PublicationIn the paper numerical simulations have been performed to predict the performance of the diferent steam models. All of the considered models of steam condensation have been validated on the base of benchmark experiment employing expansion in nozzle and next on the low pressure part of the steam turbine equipped with the so-called Baumann stage. For numerical analysis three models have been finally used - the ideal steam model without...
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Sparse autoregressive modeling
PublicationIn the paper the comparison of the popular pitch determination (PD) algorithms for thepurpose of elimination of clicks from archive audio signals using sparse autoregressive (SAR)modeling is presented. The SAR signal representation has been widely used in code-excitedlinear prediction (CELP) systems. The appropriate construction of the SAR model is requiredto guarantee model stability. For this reason the signal representation...
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Decisional DNA and Optimization Problem
PublicationMany 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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Modeling the Structure, Dynamics, and Transformations of Proteins with the UNRES Force Field
PublicationThe physics-based united-residue (UNRES) model of proteins ( www.unres.pl ) has been designed to carry out large-scale simulations of protein folding. The force field has been derived and parameterized based on the principles of statistical-mechanics, which makes it independent of structural databases and applicable to treat nonstandard situations such as, proteins that contain D-amino-acid residues. Powered by Langevin dynamics...
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INFLUENCE OF THE HULL SHAPE ON THE ENERGY DEMAND OF A SMALL INLAND VESSEL WITH HYBRID PROPULSION
PublicationRecently, there has been a significant development of ecological propulsion systems, which is in line with the general trend of environmentally friendly “green shipping”. The main aim is to build a safe, low-energy passenger ship with a highly efficient, emission-free propulsion system. This can be achieved in a variety of ways. The article presents the main problems encountered by designers and constructors already at the stage...
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Introduction to the special issue on machine learning in acoustics
PublicationWhen we started our Call for Papers for a Special Issue on “Machine Learning in Acoustics” in the Journal of the Acoustical Society of America, our ambition was to invite papers in which machine learning was applied to all acoustics areas. They were listed, but not limited to, as follows: • Music and synthesis analysis • Music sentiment analysis • Music perception • Intelligent music recognition • Musical source separation • Singing...
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AVHRR Level1CD covering Baltic Sea area year 2006
Open Research DataThe product level is the NOAA AVHRR Level 1C that is result of processing the AVHRR data from the HRPT stream based on ancillary information like sensing geometry and calibration data. Then converted into geophysical variables: top-of-the atmosphere (TOA) albedo or brightness temperature. Additionally, information like geolocation has been added. Other...
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AVHRR Level1CD covering Baltic Sea area year 2010
Open Research DataThe product level is the NOAA AVHRR Level 1C that is result of processing the AVHRR data from the HRPT stream based on ancillary information like sensing geometry and calibration data. Then converted into geophysical variables: top-of-the atmosphere (TOA) albedo or brightness temperature. Additionally, information like geolocation has been added. Other...
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AVHRR Level1CD covering Baltic Sea area year 2007
Open Research DataThe product level is the NOAA AVHRR Level 1C that is result of processing the AVHRR data from the HRPT stream based on ancillary information like sensing geometry and calibration data. Then converted into geophysical variables: top-of-the atmosphere (TOA) albedo or brightness temperature. Additionally, information like geolocation has been added. Other...
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AVHRR Level1CD covering Baltic Sea area year 2011
Open Research DataThe product level is the NOAA AVHRR Level 1C that is result of processing the AVHRR data from the HRPT stream based on ancillary information like sensing geometry and calibration data. Then converted into geophysical variables: top-of-the atmosphere (TOA) albedo or brightness temperature. Additionally, information like geolocation has been added. Other...
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AVHRR Level1CD covering Baltic Sea area year 2012
Open Research DataThe product level is the NOAA AVHRR Level 1C that is result of processing the AVHRR data from the HRPT stream based on ancillary information like sensing geometry and calibration data. Then converted into geophysical variables: top-of-the atmosphere (TOA) albedo or brightness temperature. Additionally, information like geolocation has been added. Other...
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AVHRR Level1CD covering Baltic Sea area year 2008
Open Research DataThe product level is the NOAA AVHRR Level 1C that is result of processing the AVHRR data from the HRPT stream based on ancillary information like sensing geometry and calibration data. Then converted into geophysical variables: top-of-the atmosphere (TOA) albedo or brightness temperature. Additionally, information like geolocation has been added. Other...
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AVHRR Level1CD covering Baltic Sea area year 2009
Open Research DataThe product level is the NOAA AVHRR Level 1C that is result of processing the AVHRR data from the HRPT stream based on ancillary information like sensing geometry and calibration data. Then converted into geophysical variables: top-of-the atmosphere (TOA) albedo or brightness temperature. Additionally, information like geolocation has been added. Other...
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Framework for Integration Decentralized and Untrusted Multi-vendor IoMT Environments
PublicationLack of standardization is highly visible while we use historical data sets or compare our model with others that use IoMT devices from different vendors. The problem also concerns the trust in highly decentralized and anonymous environments where sensitive data are transferred through the Internet and then are analyzed by third-party companies. In our research we propose a standard that has been implemented in the form of framework...
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Optical method supported by machine learning for dynamics of C‐reactive protein concentrations changes detection in biological matrix samples
PublicationIn this article we present the novel spectroscopy method supported with machine learning for real-time detection of infectious agents in wastewater. In the case of infectious diseases, wastewater monitoring can be used to detect the presence of inflammation biomarkers, such as the proposed C-reactive protein, for monitoring inflammatory conditions and mass screening during epidemics for early detection in communities of concern,...
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Autonomous Ship Utility Model Parameter Estimation Utilising Extended Kalman Filter
PublicationIn this paper, a problem of autonomous ship utility model identification for control purposes is considered. In particular, the problem is formulated in terms of model parameter estimation (one-step-ahead prediction). This is a complex task due to lack of measurements of the parameter values, their time-variability and structural uncertainty introduced by the available models. In this work, authors consider and compare two utility...
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Improving Clairvoyant: reduction algorithm resilient to imbalanced process arrival patterns
PublicationThe Clairvoyant algorithm proposed in “A novel MPI reduction algorithm resilient to imbalances in process arrival times” was analyzed, commented and improved. The comments concern handling certain edge cases in the original pseudocode and description, i.e., adding another state of a process, improved cache friendliness more precise complexity estimations and some other issues improving the robustness of the algorithm implementation....
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A novel approach exploiting properties of convolutional neural networks for vessel movement anomaly detection and classification
PublicationThe article concerns the automation of vessel movement anomaly detection for maritime and coastal traffic safety services. Deep Learning techniques, specifically Convolutional Neural Networks (CNNs), were used to solve this problem. Three variants of the datasets, containing samples of vessel traffic routes in relation to the prohibited area in the form of a grayscale image, were generated. 1458 convolutional neural networks with...
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Analysis of the Capability of Deep Learning Algorithms for EEG-based Brain-Computer Interface Implementation
PublicationMachine learning models have received significant attention for their exceptional performance in classifying electroencephalography (EEG) data. They have proven to be highly effective in extracting intricate patterns and features from the raw signal data, thereby contributing to their success in EEG classification tasks. In this study, we explore the possibilities of utilizing contemporary machine learning algorithms in decoding...
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Driver’s Condition Detection System Using Multimodal Imaging and Machine Learning Algorithms
PublicationTo this day, driver fatigue remains one of the most significant causes of road accidents. In this paper, a novel way of detecting and monitoring a driver’s physical state has been proposed. The goal of the system was to make use of multimodal imaging from RGB and thermal cameras working simultaneously to monitor the driver’s current condition. A custom dataset was created consisting of thermal and RGB video samples. Acquired data...
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Positron scattering on molecular hydrogen: Analysis of experimental and theoretical uncertainties
PublicationExperiments performed in recent years on positron scattering from molecular hydrogen indicated a rise of the total cross section in the limit of zero energy, but essentially disagree on the amplitude of this rise. Mitroy and collaborators [J.-Y. Zhang et al., Phys. Rev. Lett. 103, 223202 (2009)] predicted a scattering length somewhat different from values deduced experimentally. Using a Markov chain Monte Carlo modified effective...
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Application Isssues of the Semi-Markov Reliability Model
PublicationPredicting the reliability of marine internal combustion engines, for instance, is of particular importance, as it makes it possible to predict their future reliability states based on the information on the past states. Correct reliability prediction is a complex process which consists in processing empirical results obtained from operating practice, complemented by analytical considerations. The process of technical state changes...
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Accurate modeling of quasi-resonant inverter fed IM drive
PublicationIn this paper wide-band modeling methodology of a parallel quasi-resonant dc link inverter (PQRDCLI) fed induction machine (IM) is presented. The modeling objective is early-design stage prediction of conductive electromagnetic interference (EMI) emissions of the considered converter fed IM drive system. Operation principles of the selected topology of PQRDCLI feeding IM drive are given. Modeling of the converter drive system is...
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Automatic recognition of therapy progress among children with autism
PublicationThe article presents a research study on recognizing therapy progress among children with autism spectrum disorder. The progress is recognized on the basis of behavioural data gathered via five specially designed tablet games. Over 180 distinct parameters are calculated on the basis of raw data delivered via the game flow and tablet sensors - i.e. touch screen, accelerometer and gyroscope. The results obtained confirm the possibility...
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Qualitative and Quantitative Analysis of Selected Tonic Waters by Potentiometric Taste Sensor With All-Solid-State Electrodes
PublicationTaste sensor with five all-solid-state electrodes (ASSE) III (third version) was used for qualitative and quantitative analysis of selected tonic waters (J.Gasco, Kinley, Jurajski, Jurajski with citrus flavor, Carrefour, Schweppes Indian Tonic, and Schweppes Bitter Lemon). The results obtained by this taste sensor analyzed with principal component analysis, agglomerative hierarchical clustering methods show that this sensor can...
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Rapid multi-objective design optimisation of compact microwave couplers by means of physics-based surrogates
PublicationThe authors introduce a methodology for fast multi-objective design optimisation of miniaturised microwave couplers. The approach exploits the surrogate-based optimisation paradigm with an underlying low-fidelity model constructed from an equivalent circuit of the structure under consideration, corrected through implicit and frequency space mapping. A fast prediction tool obtained this way is subsequently optimised by a multi-objective...
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Evaluation of the Electronic Nose Used for Monitoring Environmental Pollution
PublicationAir pollution is a one of the major concern of civilized world, which has a significant impact on human health and the environment. Recent studies highlight that the exposure to polluted air can increase the incidence of diseases and deteriorate the quality of life. Hence, it is necessary to develop tools for real-time air quality monitoring. Electronic-nose systems based on sensors are an interesting and promising technology in...
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Ligand-Modified Boron-Doped Diamond Surface: DFT Insights into the Electronic Properties of Biofunctionalization
PublicationWith the increasing power of computation systems, theoretical calculations provide a means for quick determination of material properties, laying out a research plan, and lowering material development costs. One of the most common is Density Functional Theory (DFT), which allows us to simulate the structure of chemical molecules or crystals and their interaction. In developing a new generation of biosensors, understanding the nature...
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IFE: NN-aided Instantaneous Pitch Estimation
PublicationPitch estimation is still an open issue in contemporary signal processing research. Nowadays, growing momentum of machine learning techniques application in the data-driven society allows for tackling this problem from a new perspective. This work leverages such an opportunity to propose a refined Instantaneous Frequency and power based pitch Estimator method called IFE. It incorporates deep neural network based pitch estimation...
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Towards Improving Optimised Ship Weather Routing
PublicationThe aim of the paper is to outline a project focusing on the development of a new type of ship weather routing solution with improved uncertainty handling, through better estimation of ship performance and responses to sea conditions. Ensemble forecasting is considered to take into account the uncertainty levels that are typical of operations in a stochastic environment. Increased accuracy of weather prediction is achieved through...
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Isothermal Calorimetry and Compressive Strength Tests of Mortar Specimens for Determination of Apparent Activation Energy
PublicationThe hydration process of cementitious materials involves a thermally activated reaction that depends on the composition of the mixture and the curing temperature. The main parameter affecting the temperature variation of cast-in-place concrete is the apparent activation energy, which can be used for the efficient prediction of the temperature evolution and maturity index of hardening concrete. This paper discusses two methods to...
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Burnout Investigation of Small Diameter Tubes Immersed in Nanofluids
PublicationThis paper deals with research into pool boiling critical heat flux (CHF) of water–Al2O3, water–TiO2 and water–Cu nanofluids on horizontal stainless steel tubes. The experiments were conducted under atmospheric pressure. Nanoparticles were tested at concentrations of 0.001%, 0.01%, 0.1% and 1% by weight. Ultrasonic vibration was used in order to stabilize the dispersion of the nanoparticles. Although dispersants were not used to...
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Determination of Odour Interactions of Three-Component Gas Mixtures Using an Electronic Nose
PublicationThe paper presents an application of an electronic nose prototype comprised of six TGS-type sensors and one PID-type sensor to identify odour interaction phenomena in odorous three-component mixtures. The investigation encompassed eight odorous mixtures—toluene-acetone-triethylamine and formaldehyde-butyric acid-pinene — characterized by different odour intensity and hedonic tone. A principal component regression (PCR) calibration...
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Uczenie maszynowe do samoorganizacji systemów rozproszonych w zastosowaniach gospodarczych
PublicationW pracy omówiono uczenie maszynowe do samoorganizacji systemów rozproszonych w zastosowaniach gospodarczych ze szczególnym uwzględnieniem sieci neuronowych do predykcji finansowych oraz szacowania ratingu przedsiębiorstw. Oprócz sieci neuronowych, istotną rolę w przygotowaniu i testowaniu informatycznych systemów finansowych może pełnić programowanie genetyczne. Z tego powodu omówiono uczenie maszynowe w aplikacjach konstruowanych...
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Application of a stochastic compartmental model to approach the spread of environmental events with climatic bias
PublicationWildfires have significant impacts on both environment and economy, so understanding their behaviour is crucial for the planning and allocation of firefighting resources. Since forest fire management is of great concern, there has been an increasing demand for computationally efficient and accurate prediction models. In order to address this challenge, this work proposes applying a parameterised stochastic model to study the propagation...
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Towards hand grip force assessment by using EMG estimators
PublicationThe purpose of this study was to propose a method to assess individual regression (calibration) curves to establish a relationship between an isometric grip force and surface electromyography (EMG) estimator. In this study 18 healthy volunteers (12 male (23.0 ± 2.0 years) and 6 female (23.2 ± 0.7 years)) had been examined. Ten EMG estimators (mean absolute value, root mean square, entropy, energy, turns per second, mean of zero...
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The green waterfront of a city. Where are the limits of good planning? Gdansk case
PublicationThe aim of the article is to present the role of green public areas of waterfronts in shaping the image of cities, and the threats to such landscape which may be caused by wrong planning decisions. The case study of Gdansk sea-shore area in Poland is presented as an example to illustrate the values and potential of the waterfront landscape which can be easily destroyed by inadequate spatial development. Some theoretical studies...
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Assessment of under power ed propulsion machinery in electrically driven small inland waterway passenger ships from classification society point of view
PublicationPaper presents short operat ional a nd engineering analysis of underpowered propulsion in small electrically propelled small inland passenger ships. There is evidence that in certain weather conditions the phenomena of added aerodynamic resistance of small water crafts may have seriou s influence on their speed and manoeuvrability. Existing regulations like class societies rules for ship classification and construction or EU Directive 2006/87/EC do...
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ASSESSMENT OF UNDERPOWER ED PROPULSION MACHINERY IN ELECTRICALLY DRIVEN SMALL INLAND WATERWAY PASSENGER SHIPS FROM CLASSIFICATION SOCIETY POINT OF View
PublicationPaper presents short operat ional a nd engineering analysis of underpowered propulsion in small electrically propelled small inland passenger ships. There is evidence that in certain weather conditions the phenomena of added aerodynamic resistance of small water crafts may have serious influence on their speed and manoeuvrability. Existing regulations like class societies rules for ship classification and construction or EU Directive 2006/87/EC do...
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Investigating Feature Spaces for Isolated Word Recognition
PublicationThe study addresses the issues related to the appropriateness of a two-dimensional representation of speech signal for speech recognition tasks based on deep learning techniques. The approach combines Convolutional Neural Networks (CNNs) and time-frequency signal representation converted to the investigated feature spaces. In particular, waveforms and fractal dimension features of the signal were chosen for the time domain, and...