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Search results for: prediction
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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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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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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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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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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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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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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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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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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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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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The Smith-Watson-Topper parameter and fracture surface topography relationship for additively manufactured 18Ni300 steel subjected to uniaxial variable-amplitude loading
PublicationIn this paper, the association between Smith-Watson-Topper (SWT) parameter and fracture surface topography is studied in additively manufactured maraging steel exposed to variable-amplitude fatigue loading. The post-failure fracture surfaces were examined using a non-contact 3D surface topography measuring system and the entire fracture surface method. The focal point is on the correspondence between fatigue characteristics, articulate...
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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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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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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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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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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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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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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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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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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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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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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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e-Learning CoursesTreści przedmiotu: > koncepcja napędu żaglowego <> rozwój napędu żaglowego <> środowisko pracy żagli - powietrze i natura wiatru <> systematyka napędu żaglowego <> nomenklatura przedmiotu <> siły generowane na pędniku żaglowym <> teoria płata nośnego - matematyczne modele (wiry związane, wiry swobodne, prędkości indukowane, rozkład cyrkulacji i rozkład ciśnień na powierzchni żagla) <> ...
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Experimental and Machine-Learning-Assisted Design of Pharmaceutically Acceptable Deep Eutectic Solvents for the Solubility Improvement of Non-Selective COX Inhibitors Ibuprofen and Ketoprofen
PublicationDeep eutectic solvents (DESs) are commonly used in pharmaceutical applications as excellent solubilizers of active substances. This study investigated the tuning of ibuprofen and ketoprofen solubility utilizing DESs containing choline chloride or betaine as hydrogen bond acceptors and various polyols (ethylene glycol, diethylene glycol, triethylene glycol, glycerol, 1,2-propanediol, 1,3-butanediol) as hydrogen bond donors. Experimental...
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Experimental and Machine-Learning-Assisted Design of Pharmaceutically Acceptable Deep Eutectic Solvents for the Solubility Improvement of Non-Selective COX Inhibitors Ibuprofen and Ketoprofen
PublicationDeep eutectic solvents (DESs) are commonly used in pharmaceutical applications as excellent solubilizers of active substances. This study investigated the tuning of ibuprofen and ketoprofen solubility utilizing DESs containing choline chloride or betaine as hydrogen bond acceptors and various polyols (ethylene glycol, diethylene glycol, triethylene glycol, glycerol, 1,2-propanediol, 1,3-butanediol) as hydrogen bond donors. Experimental...
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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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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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Navier number and transition to turbulence
PublicationThe motivation behind this article is to explain a role of the Navier number (Na -dimensionless slip-length) in prediction of closures for laminar to turbulent transition undergoing via eddies detachment from the slip layer in nano-cannals. Additionally the role of the Navier number Na in universal modeling of phenomenon of enhanced mass flow rate reported in micro- and nano-channels has been explained. The Na number should be...
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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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Early warning models against bankruptcy risk for Central European and Latin American enterprises
PublicationThis article is devoted to the issue of forecasting the bankruptcy risk of enterprises in Latin America and Central Europe. The author has used statistical and soft computing methods to program the prediction models. It compares the effectiveness of twelve different early warningmodels for forecasting the bankruptcy risk of companies. In the research conducted, the author used data on 185 companies listed on the Warsaw Stock Exchange...
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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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Time Domain Modeling of Propeller Forces due to Ventilation in Static and Dynamic Conditions
PublicationThis paper presents experimental and theoretical studies on the dynamic effect on the propeller loading due to ventilation by using a simulation model that generates a time domain solution for propeller forces in varying operational conditions. For ventilation modeling, the simulation model applies a formula based on the idea that the change in lift coefficient due to ventilation computes the change in the thrust coefficient. It...
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Interventions reducing car usage: Systematic review and meta-analysis
PublicationThis systematic literature review aimed to investigate the extent to which transport-related interventions induced a reduction in car use. Both qualitative synthesis and meta-analysis were employed. The synthesis included 31 original studies, while the meta-analysis included 21. Of the qualitatively synthesised studies, 74 % demonstrated that interventions were effective in reducing car use. The pooled estimates of the effects...
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The Dynamics of Trade Relations between Ukraine and Romania: Modelling and Forecasting
PublicationThe article examines the monthly dynamics of exports, imports and balance of trade between Ukraine and Romania in the period from 2005 to 2021. Time series from 2015 to 2021 were used for modelling and forecasting (since the date the European Union–Ukraine Association Agreement took effect). Adequate models of the dynamics series of the Box-Jenkins methodology were built: additive models with seasonal component ARIMA (Autoregressive...
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Virtual Whiteboard: A gesture-controlled pen-free tool emulating school whiteboard
PublicationIn the paper the so-called Virtual Whiteboard is presented which may be an alternative solution for modern electronic whiteboards based on electronic pens and sensors. The presented tool enables the user to write, draw and handle whiteboard contents using his/her hands only. An additional equipment such as infrared diodes, infrared cameras or cyber gloves is not needed. The user's interaction with the Virtual Whiteboard computer...
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The influence of global climate change on the environmental fate of anthropogenic pollution released from the permafrost
PublicationThis article presents a review of information related to the influence of potential permafrost degradation on the environmental fate of chemical species which are relased and stored, classified as potential influence in future Antarctic environment. Considering all data regarding climate change prediction, this topic may prove important issue for the future state of the Antarctic environment. A detailed survey on soil and permafrost...
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Effective Gap Size Index for Determination of Optimum Separation Distance Preventing Pounding between Buildings during Earthquakes
PublicationSeismic excitations may lead to collisions between adjacent civil engineering structures causing major damage. In this paper, an effective equation for calculating the gap size index is proposed so as to provide the optimum separation distance preventing structural pounding during different earthquakes. Evaluation of the best prediction of the required separation distance between two adjacent buildings was carried out by using...
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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...
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FEM and experimental investigations of concrete temperature field in the massive stemwall of the bridge abutment
PublicationThe paper deals with the prediction of early-age concrete temperature of cast-in-place stemwall of the bridge abutment. The considered object is an arch bridge located in Gda´nsk. In the case of massive structures, it is particularly important to not exceed the temperature difference between the core and the concrete surface. Too high temperature gradient generates an increase in thermal stresses, what could be the reason of exceeding...
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Modeling SARS‐CoV‐2 proteins in the CASP‐commons experiment
PublicationCritical Assessment of Structure Prediction (CASP) is an organization aimed at advancing the state of the art in computing protein structure from sequence. In the spring of 2020, CASP launched a community project to compute the structures of the most structurally challenging proteins coded for in the SARS-CoV-2 genome. Forty-seven research groups submitted over 3000 three-dimensional models and 700 sets of accuracy estimates on...
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AVHRR Level1CD covering Baltic Sea area year 2001
Open Research DataThe dataset contains data derived from recordings of the AVHRR/3 radiometer operating on board the NOAA POES (Polar Orbiting Environmental Satellites) Series - 5th Generation Satellites covering the Baltic Sea area. The satellite data was recorded in the years 2000-2012 directly by the HRPT station installed at the University of Gdańsk. The registration...
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Using LSTM networks to predict engine condition on large scale data processing framework
PublicationAs the Internet of Things technology is developing rapidly, companies have an ability to observe the health of engine components and constructed systems through collecting signals from sensors. According to output of IoT sensors, companies can build systems to predict the conditions of components. Practically the components are required to be maintained or replaced before the end of life in performing their assigned task. Predicting...
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Adaptive Sampling for Non-intrusive Reduced Order Models Using Multi-Task Variance
PublicationNon-intrusive reduced order modeling methods (ROMs) have become increasingly popular for science and engineering applications such as predicting the field-based solutions for aerodynamic flows. A large sample size is, however, required to train the models for global accuracy. In this paper, a novel adaptive sampling strategy is introduced for these models that uses field-based uncertainty as a sampling metric. The strategy uses...
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Genre-Based Music Language Modeling with Latent Hierarchical Pitman-Yor Process Allocation
PublicationIn this work we present a new Bayesian topic model: latent hierarchical Pitman-Yor process allocation (LHPYA), which uses hierarchical Pitman-Yor pr ocess priors for both word and topic distributions, and generalizes a few of the existing topic models, including the latent Dirichlet allocation (LDA), the bi- gram topic model and the hierarchical Pitman-Yor topic model. Using such priors allows for integration of -grams with a topic model,...