Wyniki wyszukiwania dla: STRUCTURE PREDICTION
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TOWARDS EXPLAINABLE CLASSIFIERS USING THE COUNTERFACTUAL APPROACH - GLOBAL EXPLANATIONS FOR DISCOVERING BIAS IN DATA
PublikacjaThe paper proposes summarized attribution-based post-hoc explanations for the detection and identification of bias in data. A global explanation is proposed, and a step-by-step framework on how to detect and test bias is introduced. Since removing unwanted bias is often a complicated and tremendous task, it is automatically inserted, instead. Then, the bias is evaluated with the proposed counterfactual approach. The obtained results...
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Machine learning-based seismic response and performance assessment of reinforced concrete buildings
PublikacjaComplexity and unpredictability nature of earthquakes makes them unique external loads that there is no unique formula used for the prediction of seismic responses. Hence, this research aims to implement the most well-known Machine Learning (ML) methods in Python software to propose a prediction model for seismic response and performance assessment of Reinforced Concrete Moment-Resisting Frames (RC MRFs). To prepare 92,400 data...
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An algorithm for selecting a machine learning method for predicting nitrous oxide emissions in municipal wastewater treatment plants
PublikacjaThis study presents an advanced algorithm for selecting machine learning (ML) models for nitrous oxide (N2O) emission prediction in wastewater treatment plants (WWTPs) employing the activated sludge process. The examined ML models comprised multivariate adaptive regression spline (MARS), support vector machines (SVM), and extreme gradient boosting (XGboost). The study explores the concept that involves new criteria to select the...
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Computational collective intelligence for enterprise information systems
PublikacjaCollective intelligence is most often understood as a kind of intelligence which arises on the basis of a group (collective) of autonomous unites (people, systems) which is taskoriented. There are two important aspects of an intelligent collective: The cooperation aspect and the competition aspect (Levy 1997). The first of them means the possibility for integrating the decisions made by the collective members for creating the decision of...
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Aerodynamic shape optimization by variable-fidelity computational fluid dynamics models: a review of recent progress
PublikacjaA brief review of some recent variable-fidelity aerodynamic shape optimization methods is presented.We discuss three techniques that—by exploiting information embedded in low-fidelity computationalfluid dynamics (CFD) models—are able to yield a satisfactory design at a low computational cost, usu-ally corresponding to a few evaluations of the original, high-fidelity CFD model to be optimized. Thespecific techniques considered here...
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ADAPTIVE PREDICTIONS OF THE EURO/ZŁOTY CURRENCY EXCHANGE RATE USING STATE SPACE WAVELET NETWORKS AND FORECAST COMBINATIONS
PublikacjaThe paper considers the forecasting of the euro/Polish złoty (EUR/PLN) spot exchange rate by applying state space wavelet network and econometric forecast combination models. Both prediction methods are applied to produce one-trading-day- ahead forecasts of the EUR/PLN exchange rate. The paper presents the general state space wavelet network and forecast combination models as well as their underlying principles. The state space...
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Multi-Criteria Knowledge-Based Recommender System for Decision Support in Complex Business Processes
PublikacjaIn this paper, we present a concept of a multi-criteria knowledge-based Recommender System (RS) designed to provide decision support in complex business process (BP) scenarios. The developed approach is based on the knowledge aspects of Stylistic Patterns, Business Sentiment and Decision-Making Logic extracted from the BP unstructured texts. This knowledge serves as an input for a multi-criteria RS algorithm. The output is prediction...
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Chained machine learning model for predicting load capacity and ductility of steel fiber–reinforced concrete beams
PublikacjaOne of the main issues associated with steel fiber–reinforced concrete (SFRC) beams is the ability to anticipate their flexural response. With a comprehensive grid search, several stacked models (i.e., chained, parallel) consisting of various machine learning (ML) algorithms and artificial neural networks (ANNs) were developed to predict the flexural response of SFRC beams. The flexural performance of SFRC beams under bending was...
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On joint order and bandwidth selection for identification of nonstationary autoregressive processes
PublikacjaWhen identifying a nonstationary autoregressive process, e.g. for the purpose of signal prediction or parametric spectrum estimation, two important decisions must be taken. First, one should choose the appropriate order of the autoregressive model, i.e., the number of autoregressive coefficients that will be estimated. Second, if identification is carried out using the local estimation technique, such as the localized version of...
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New generation of analytical tests based on the assessment of enzymatic and nuclear receptor activity changes induced by environmental pollutants
PublikacjaAnalytical methods show great potential in biological tests. The analysis of biological response that results from environmental pollutant exposure allows: (i) prediction of the risk of toxic effects and (ii) provision of the background for the development of markers of the toxicants presence. Bioanalytical tests based on changes in enzymatic activity and nuclear receptor action provide extremely high specificity and sensitivity....
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Performance of Noise Map Service Working in Cloud Computing Environment
PublikacjaIn the paper a noise map service designated for the user interested in environmental noise subject is presented. It is based on cloud computing. Noise prediction algorithm and source model, developed for creating acoustic maps, are working in cloud computing environment. In the study issues related to noise modeling of sound propagation in urban spaces are discussed with a special focus on road noise. Examples of results obtained...
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Mathematical Modeling of Ice Dynamics as a Decision Support Tool in River Engineering
PublikacjaThe prediction of winter flooding is a complicated task since it is affected by many meteorological and hydraulic factors. Typically, information on river ice conditions is based on historical observations, which are usually incomplete. Recently, data have been supplemented by information extracted from satellite images. All the above mentioned factors provide a good background of the characteristics of ice processes, but are not...
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The Use of Artificial Neural Networks and Decision Trees to Predict the Degree of Odor Nuisance of Post-Digestion Sludge in the Sewage Treatment Plant Process
PublikacjaThis paper presents the application of artificial neural networks and decision trees for the prediction of odor properties of post-fermentation sludge from a biological-mechanical wastewater treatment plant. The input parameters were concentrations of popular compounds present in the sludge, such as toluene, p-xylene, and p-cresol, and process parameters including the concentration of volatile fatty acids, pH, and alkalinity in...
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Implementation of Extended Kalman Filter with Optimized Execution Time for Sensorless Control of a PMSM Using ARM Cortex-M3 Microcontroller
PublikacjaThis paper addresses the implementation and optimization of an Extended Kalman Filter (EKF) for the Permanent Magnet Synchronous Motor (PMSM) sensorless control using an ARM Cortex-M3 microcontroller. A various optimization levels based on arithmetic calculation reduction was implemented in ARM Cortex-M3 microcontroller. The execution time of EKF estimator was reduced from 260.4 μs to 37.7 μs without loss of accuracy. To further...
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On Noncausal Identification of Nonstationary Multivariate Autoregressive Processes
PublikacjaThe problem of identification of nonstationary multivariate autoregressive processes using noncausal local estimation schemes is considered and a new approach to joint selection of the model order and the estimation bandwidth is proposed. The new selection rule, based on evaluation of pseudoprediction errors, is compared with the previously proposed one, based on the modified Akaike’s final prediction error criterion.
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Survival time prognosis under a Markov model of cancer development
PublikacjaIn this study we look at a breast cancer data set of women from Pomerania region collected in year 1987-1992 in the Medical University of Gdańsk. We analyze the clinical risk factors in conjunction with Markov model of cancer development. We evaluate Artificial Neural Network (ANN) survival time prediction via a simulation study.
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Long-term hindcast simulation of sea level in the Baltic Sea
Dane BadawczeThe dataset contains the results of numerical modelling of sea level fluctuations 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). The hydrodynamic model...
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Things You Might Not Know about the k-Nearest Neighbors Algorithm
PublikacjaRecommender Systems aim at suggesting potentially interesting items to a user. The most common kind of Recommender Systems is Collaborative Filtering which follows an intuition that users who liked the same things in the past, are more likely to be interested in the same things in the future. One of Collaborative Filtering methods is the k Nearest Neighbors algorithm which finds k users who are the most similar to an active user...
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An Ontology-based Contextual Pre-filtering Technique for Recommender Systems
PublikacjaContext-aware Recommender Systems aim to provide users with the most adequate recommendations for their current situation. However, an exact context obtained from a user could be too specific and may not have enough data for accurate rating prediction. This is known as the data sparsity problem. Moreover, often user preference representation depends on the domain or the specific recommendation approach used. Therefore, a big effort...
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Pose-Invariant Face Detection by Replacing Deep Neurons with Capsules for Thermal Imagery in Telemedicine
PublikacjaAbstract— The aim of this work was to examine the potential of thermal imaging as a cost-effective tool for convenient, non- intrusive remote monitoring of elderly people in different possible head orientations, without imposing specific behavior on users, e.g. looking toward the camera. Illumination and pose invariant head tracking is important for many medical applications as it can provide information, e.g. about vital signs, sensory...
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The analysis of soil resistance during screw displacement pile installation
PublikacjaThe analysis of soil resistances during screw displacement pile installation based on model and field tests. The investigations were carried out as a part of research project, financed by the Polish Ministry of Science and Higher Education. A proposal of empirical method for prediction of rotation resistance (torque) during screw auger penetration in non-cohesive subsoil based on CPT result.
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Data on LEGO sets release dates and worldwide retail prices combined with aftermarket transaction prices in Poland between June 2018 and June 2023
PublikacjaThe dataset contains LEGO bricks sets item count and pricing history for AI-based set pricing prediction. The data spans the timeframe from June 2018 to June 2023. The data was obtained from three sources: Brickset.com (LEGO sets retail prices, release dates, and IDs), Lego.com official web page (ID number of each set that was released by Lego, its retail prices, the current status of the set) and promoklocki.pl web page (the retail...
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Sensing Direction of Human Motion Using Single-Input-Single-Output (SISO) Channel Model and Neural Networks
PublikacjaObject detection Through-the-Walls enables localization and identification of hidden objects behind the walls. While numerous studies have exploited Channel State Information of Multiple Input Multiple Output (MIMO) WiFi and radar devices in association with Artificial Intelligence based algorithms (AI) to detect and localize objects behind walls, this study proposes a novel non-invasive Through-the-Walls human motion direction...
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Study on the accuracy of axle load spectra used for pavement design
PublikacjaWeigh-in-Motion (WIM) systems are used in order to reduce the number of overloaded vehicles. Data collected from WIM provide characteristics of vehicle axle loads that are crucial for pavement design as well as for the development of pavement distress prediction models. The inaccuracy of WIM data lead to erroneous estimation of traffic loads and in consequence inaccurate prediction of pavement distress process. The objective of...
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Edgewise Compressive Behavior of Composite Structural Insulated Panels with Magnesium Oxide Board Facings
PublikacjaEdgewise compression response of a composite structural insulated panel (CSIP) with magnesium oxide board facings was investigated. The discussed CSIP is a novel multifunctional sandwich panel introduced to the housing industry as a part of the wall, floor, and roof assemblies. The study aims to propose a computational tool for reliable prediction of failure modes of CSIPs subjected to concentric and eccentric axial loads. An advanced...
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ANALYSIS OF POSSIBILITIES FOR THE USE OF VOLUME-DELAY FUNCTIONS IN THE PLANNING MODULE OF THE TRISTAR SYSTEM
PublikacjaTravel time is a measure commonly used for traffic flow modelling and traffic control. It also helps to evaluate the quality of traffic control systems in urban areas. Traffic control systems that use traffic models to predict changes and disruptions in vehicle flows have to use vehicle speed-prediction models. Travel time estimation studies the effects of traffic volumes on a street section at an average speed. The TRISTAR Integrated...
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Predicting Ice Phenomena in a River Using the Artificial Neural Network and Extreme Gradient Boosting
PublikacjaForecasting ice phenomena in river systems is of great importance because these phenomena are a fundamental part of the hydrological regime. Due to the stochasticity of ice phenomena, their prediction is a difficult process, especially when data sets are sparse or incomplete. In this study, two machine learning models—Multilayer Perceptron Neural Network (MLPNN) and Extreme Gradient Boosting (XGBoost)—were developed to predict...
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Long-term hindcast simulation of water temperature and salinity in the Baltic Sea
Dane BadawczeThe dataset contains the results of numerical modelling of water temperature and salinity 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). The hydrodynamic...
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Long-term hindcast simulation of currents in the Baltic Sea
Dane BadawczeThe dataset contains the results of numerical modelling of currents 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). The hydrodynamic model was coupled...
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GIS Solution for Weather Forecast Data Analysis
PublikacjaIn this paper authors present the GIS system for the analysis of the numerical weather prediction data. This kind of data has multidimensional character (three dimensions and time) and its analysis should consider all the available factors. Proposed GIS system consists of RASDAMAN application with implemented OLAP cube mechanism, which enables the user to process data in the spatial-time domain. It also simplifies the meteorological...
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A new quantum-inspired approach to reduce the blocking probability of demands in resource-constrained path computation scenarios
PublikacjaThis article presents a new approach related with end-to-end routing, which, owing to quantum-inspired mecha-nisms of prediction of availability of network resources, results in improved blocking probability of incoming requests to establish transmission paths. The proposed scheme has been analyzed for three network topologies and several scenarios of network load. Obtained results show a significant (even twofold) reduction of...
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Optimized Deep Learning Model for Flood Detection Using Satellite Images
PublikacjaThe increasing amount of rain produces a number of issues in Kerala, particularly in urban regions where the drainage system is frequently unable to handle a significant amount of water in such a short duration. Meanwhile, standard flood detection results are inaccurate for complex phenomena and cannot handle enormous quantities of data. In order to overcome those drawbacks and enhance the outcomes of conventional flood detection...
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A Data Driven Model for Predicting RNA-Protein Interactions based on Gradient Boosting Machine
PublikacjaRNA protein interactions (RPI) play a pivotal role in the regulation of various biological processes. Experimental validation of RPI has been time-consuming, paving the way for computational prediction methods. The major limiting factor of these methods has been the accuracy and confidence of the predictions, and our in-house experiments show that they fail to accurately predict RPI involving short RNA sequences such as TERRA RNA....
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Cost assessment of computer security activities
PublikacjaComprehensive cost-benefit analysis plays a crucial role in the decision-making process when it comes to investments in information security solutions. The cost of breaches needs to be analysed in the context of spending on protection measures. However, no methods exist that facilitate the quick and rough prediction of true expenditures on security protection systems. Rafal Leszczyna of Gdansk University of Technology presents...
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Application of Majority Voting Protocols to Supporting Trading Decisions
PublikacjaA broad spectrum of analysis and prediction indicators and methods exists to support trading decisions, but no hard knowledge exist to tell in advance which of them will fit best in a given timeframe. To support trading decisions, a multi-agent self-organizing system has been proposed. The system is based on history based dynamic weight voting and selects the right indicators based on their past performance. The formal analysis...
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APPLICATION OF MAJORITY VOTING PROTOCOLS TO SUPPORTING TRADING DECISIONS
PublikacjaA broad spectrum of analysis and prediction indicators and methods exists to support trading decisions, but no hard knowledge exist to tell in advance which of them will fit best in a given timeframe. To support trading decisions, a multi-agent self-organizing system has been proposed. The system is based on history based dynamic weight voting and selects the right indicators based on their past performance. The formal analysis...
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New approach to railway noise modeling employing Genetic Algorithms
PublikacjaMain goal of this paper was to describe an innovative method of noise prediction based on Genetic Algorithms. First part of the paper addresses the problem of growing noise, mainly in the context of a unified method for measuring noise. Further, Genetic Algorithms are described with regards to their fundamental features. Further a description is provided as to how Genetic Algorithms were used in the area of noise modeling. Next...
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The Analysis of Patients' Airflow with Respect to Early Detection of Sleep Apnea
PublikacjaThe paper discusses the analysis of the respiratory events of sleep apnea patients. The analysis was carried out on the basis of the patient's airflow. As a result of the conducted analysis we proposed an algorithm which establishes an individual respiratory pattern for each subject. The algorithm could be implemented in the measurement - control system which manages the prosthetic device applying positive airway pressure. Its...
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The Concept of Geodetic Analyses of the Measurement Results Obtained by Hydrostatic Leveling
PublikacjaThe article discusses the issue of hydrostatic leveling. Its application is presented in structural health monitoring systems in order to determine vertical displacements of controlled points. Moreover, the article includes a complete computation scheme that utilizes the estimation from observation differences, allowing the elimination of the influence of individual sensors’ systematic errors. The authors suggest two concepts of...
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Dynamic fracture of brittle shells in a space-time adaptive isogeometric phase field framework
PublikacjaPhase field models for fracture prediction gained popularity as the formulation does not require the specification of ad-hoc criteria and no discontinuities are inserted in the body. This work focuses on dynamic crack evolution of brittle shell structures considering large deformations. The energy contributions from in-plane and out-of-plane deformations are separately split into tensile and compressive components and the resulting...
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Non-Contact Temperature Measurements Dataset
PublikacjaThe dataset titled The influence of the distance of the pyrometer from the surface of the radiating object on the accuracy of measurements contains temperature measurements using a selection of four commercially available pyrometers (CHY 314P, TM-F03B, TFA 31.1125 and AB-8855) as a function of the measuring distance. The dataset allows a comparison of the accuracy and measuring precision of the devices, which are very important...
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New type T-Source inverter
PublikacjaThis paper presents different topologies of voltage inverters with alternative input LC networks. The basic topology is known in the literature as a Z-source inverter (ZSI). Alternative passive networks were named by the authors as T-sources. T-source inverter has fewer reactive components in comparison to conventional Z-source inverter. The most significant advantage of the T-source inverter (TSI) is its use of a common voltage...
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Verification of the new viscoelastic method of thermal stress calculation in asphalt layers of pavements
PublikacjaThe new viscoelastic method of thermal stress calculations in asphalt layers has been developed and published recently by the author. This paper presents verification of this method. The verification is based on the comparison of the results of calculations with results of testing of thermal stresses in Thermal Stress Restrained Specimen Test. The calculations of thermal stresses according to the new method were based on rheological...
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Explainable machine learning for diffraction patterns
PublikacjaSerial crystallography experiments at X-ray free-electron laser facilities produce massive amounts of data but only a fraction of these data are useful for downstream analysis. Thus, it is essential to differentiate between acceptable and unacceptable data, generally known as ‘hit’ and ‘miss’, respectively. Image classification methods from artificial intelligence, or more specifically convolutional neural networks (CNNs), classify...
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A predictive estimation based control strategy for a quasi-resonant dc-link inverter
PublikacjaIn this paper the predictive estimation based control strategy for a quasi-resonant dc link inverter (PQRDCLI) is developed. Instead of direct measurement of dc link input inverter current – its estimation with one step prediction is applied. The PQRDCLI fed induction motor, controlled with a predictive current estimation stabilized inverter output voltage slopes independently of load. Moreover, reduction of overvoltage spikes...
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Full scale measurements of pressure field induced on the quay wall by bow thrusters – indirect method for seabed velocities monitoring
PublikacjaThe paper presents the results of full-scale experimental investigation of loads generated on the quay wall by bow thrusters during unberthing of a self-manoeuvring vessel. The presented research allowed for the comparison of the measurements results with generally accepted empirical prediction methods and confirmed the utility of the developed measuring setup for the on-line monitoring of jet induced loads. The conclusions from the...
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New results on estimation bandwidth adaptation
PublikacjaThe problem of identification of a nonstationary autoregressive signal using non-causal estimation schemes is considered. Noncausal estimators can be used in applications that are not time-critical, i.e., do not require real-time processing. A new adaptive estimation bandwidth selection rule based on evaluation of pseudoprediction errors is proposed, allowing one to adjust tracking characteristics of noncausal estimators to unknown...
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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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Sensorless predictive control of three-phase parallel active filter
PublikacjaThe paper presents the control system of parallel active power filter (APF) with predictive reference current calculation and model based predictive current control. The novel estimator and predictor of grid emf is proposed for AC voltage sensorless operation of APF, regardless of distortion of this voltage. Proposed control system provides control of APF current with high precision and dynamics limited only by filter circuit parameters....
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FEM modelling of screw displacement pile interaction with subsoil
PublikacjaPredicting the-settlement characteristics of piles is an important element in the designing of pile foundations. The most reliable method in evaluating pile-soil interaction is the static load test, preferably performed with instrumentation for measuring shaft and pile base resistances. This, however, is a mostly post-implementation test. In the design phase, prediction methods are needed, in which numerical simulations play an...
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Simplified AutoDock force field for hydrated binding sites
Publikacjahas been extracted from the Protein Data Bank and used to test and recalibrate AutoDock force field. Since for some binding sites water molecules are crucial for bridging the receptor-ligand interactions, they have to be included in the analysis. To simplify the process of incorporating water molecules into the binding sites and make it less ambiguous, new simple water model was created. After recalibration of the force field on...
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Numerical modelling and experimental verification of compressible squeeze film pressure
PublikacjaThe validity of using the Reynolds equation for compressible squeeze film pressure was tested with computational fluid dynamics (CFD). A squeeze film air bearing was instrumented with pressure sensors and non-contacting displacement probes to provide transient measurements of film thickness and pressure. The film thickness measurements also provided input parameters to the numerical prediction. However, numerical results showed...
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Residence time distribution in rapid multiphase reactors
PublikacjaResidence time distribution (RTD) provides information about average hydraulic residence time and the distribution of material in the reactor. A method for determining RTD for reactors with very short hydraulic residence times is deconvolution based on extraction of real RTD by the analysis of a non-ideal input signal. The mean residence time and dispersion were determined for the spinning fluids reactor (SFR). For the first time...
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Modeling of Performance, Reliability and Energy Efficiency in Large-Scale Computational Environment
PublikacjaLarge scale of complexity of distributed computational systems imposes special challanges for prediction of quality in such systems.Existing quality models for lower-scale systems include functionality,performance,reliability,flexibility and usability.Among these attributes,performance and reliability have a particular significance to the large-scale systems computing quality modeling due to their strong dependence on the system...
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Lattice filter based autoregressive spectrum estimation with joint model order and estimation bandwidth adaptation
PublikacjaThe problem of parametric, autoregressive model based estimation of a time-varying spectral density function of a nonstationary process is considered. It is shown that estimation results can be considerably improved if identification of the autoregressive model is carried out using the two-sided doubly exponentially weighted lattice algorithm which combines results yielded by two one-sided lattice algorithms running forward in...
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On autoregressive spectrum estimation using the model averaging technique
PublikacjaThe problem of estimating spectral density of a nonstationary process satisfying local stationarity conditions is considered. The proposed solution is a two step procedure based on local autoregressive (AR) modeling. In the first step Bayesian-like averaging of AR models, differing in order, is performed. The main contribution of the paper is development of a new final-prediction-error-like statistic, which can be used to select...
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Progressive failure analysis of laminates in the framework of 6-field nonlinear shell theory
PublikacjaThe paper presents the model of progressive failure analysis of laminates incorporated into the 6-field non-linear shell theory with non-symmetrical strain measures of Cosserat type. Such a theory is specially recommended in the analysis of shells with intersections due to its specific kinematics including the so-called drilling rotation. As a consequence of asymmetry of strain measures, modified laminates failure criteria must...
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A history of the physical and chemical stability of pharmaceuticals : a review
Publikacja: There is a great need for a broad range review of stability tests of active pharmaceutical ingredients (APIs) in comparison with current requirements contained in the pharmacopoeia. This review focuses on a pharmaceutical history of physical and chemical stability determination. Traditional knowledge must be considered in the context of physical stability, while new knowledge must be applied and acquired in terms of identification...
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Geo-engineering computer simulation seems attractive but is it the real world?
PublikacjaCorrect formulation of the differential equation system for equilibriom conditions of subsoil, especially in terms of controlled numerical calculation, is discussed. The problem of solution stability is also considered. The solution of problems, which are ill-posed, have no practical value in the majority of cases and is this way the engineering prognosis can lead to real disaster. The object of this paper is quite relevant if...
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Modeling of Performance, Reliability and Energy Efficiency in Large-Scale Computational Environments
PublikacjaLarge scale of complexity of distributed computational systems imposes special challenges for prediction of quality in such systems. Existing quality models for lower-scale systems include functionality, performance, reliability, flexibility and usability. Among these attributes, performance and reliability have a particular significance to the large-scale systems computing quality modeling due to their strong dependence on the...
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Wideband Modeling of DC-DC Buck Converter with GaN Transistors
PublikacjaThe general wideband modeling method of the power converter is presented on the example of DC-DC buck converter with GaN High Electron Mobility Transistors (HEMT). The models of all basic and parasitic components are briefly described. The two methods of Printed Circuit Board (PCB) layout parameter extraction are presented. The results of simulation in Saber@Sketch simulation software and measurements are compared. Next, the model...
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Lattice filter based multivariate autoregressive spectral estimation with joint model order and estimation bandwidth adaptation
PublikacjaThe problem of parametric, autoregressive model based estimation of a time-varying spectral density function of a multivariate nonstationary process is considered. It is shown that estimation results can be considerably improved if identification of the autoregressive model is carried out using the two-sided doubly exponentially weighted lattice algorithm which combines results yielded by two one-sided lattice algorithms running...
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Assessment of Trajectories of Non-bankrupt and Bankrupt Enterprises
PublikacjaThe aim of this study is to show how long-term trajectories of enterprises can be used to increase the forecasting horizon of bankruptcy prediction models. The author used seven popular forecasting models (two from Europe, two from Asia, two from North America and one from Latin America). These models (five multivariate discriminant analysis models and two logit models) were used to develop 17-year trajectories separately for non-bankrupt...
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Improving Effectiveness of SVM Classifier for Large Scale Data
PublikacjaThe paper presents our approach to SVM implementation in parallel environment. We describe how classification learning and prediction phases were pararellised. We also propose a method for limiting the number of necessary computations during classifier construction. Our method, named one-vs-near, is an extension of typical one-vs-all approach that is used for binary classifiers to work with multiclass problems. We perform experiments...
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Decisional-DNA-Based Digital Twin Implementation Architecture for Virtual Engineering Objects
PublikacjaDigital twin (DT) is an enabling technology that integrates cyber and physical spaces. It is well-fitted for manufacturing setup since it can support digitalized assets and data analytics for product and process control. Conventional manufacturing setups are still widely used all around the world for the fabrication of large-scale production. This article proposes a general DT implementation architecture for engineering objects/artifacts...
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MODELLING OF TRANSIENT FLOW IN STORM SEWERS
PublikacjaThe paper focuses on the assessment of second-order explicit numerical scheme for unsteady flows in sewers. In order to simulate the pressurized flow the 'Preissmann slot' concept is implemented. For simulation of the transcritical flow the original and improved McCormack scheme is used. The calculated results are compared with numerical solutions and laboratory measurements published in the technical literature. Moreover, the...
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Concrete mix design using machine learning
PublikacjaDesigning a concrete mix is a process of synthesizing many components, it is not a simple process and requires extensive technical knowledge. The design process itself focuses on obtaining the required strength of concrete. Very often designing a concrete mix takes into account the need to maintain the proper water-demand and frost-resistance features. The parameters that influence the concrete class most significantly are the...
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Proceedings of the fib Symposium 2019: Concrete - Innovations in Materials, Design and Structures 2019
PublikacjaDesigning a concrete mix is a process of synthesizing many components, it is not a simple process and requires extensive technical knowledge. The design process itself focuses on obtaining the required strength of concrete. Very often designing a concrete mix takes into account the need to maintain the proper water-demand and frost-resistance features. The parameters that influence the concrete class most significantly are the...
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Combination of instrumental and qualitative descriptive analysis for evaluation of selected tonic waters quality features
PublikacjaThe combination of sensory and instrumental analysis was applied for quality assurance of selected tonic waters. The Quantitative Descriptive Analysis (QDA) in terms of fourteen sensory attributes (aroma, astringency, bite, burn, numbing, tongue heaviness, carbonation, mouth coating, sweet taste, sour taste, bitter taste, sweet aftertaste, sour aftertaste, bitter aftertaste) of selected tonic waters was performed by sensory experts....
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Localization of impulsive disturbances in archive audio signals using predictive matched filtering
PublikacjaThe problem of elimination of impulsive disturbances from archive audio signals is considered and its new solution, called predictive matched filtering, is proposed. The new approach is based on the observation that a large percentage of noise pulses corrupting archive audio recordings have highly repetitive shapes that match several typical “patterns”, called click templates. To localize noise pulses, click templates can be correlated...
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A city and a wind farm. Landscape perspective
PublikacjaThe aim of the paper is to present the problems of the location of the wind farms in close neighbourhood to the historical cities, and the ways to minimize the potential landscape threats. The production of clean energy is obligatory in EU. In spite of how positive to the environment the wind energy production is, it may cause negative effects. The results of landscape studies of two towns in Poland prove that the location of such...
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Estimation of the steam condensation flow via CFD methods
PublikacjaThe results of numerical simulations to predict the performance of different steam models have been presented. 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 stage. For numerical analysis three models have been finally used – the ideal steam model without condensation, an equilibrium steam...
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MESOSCALE FUNCTIONS OF GPS SLANT DELAY
PublikacjaThe paper presents a computer module for GPS slant delay determination using data from COAMPS (Coupled Ocean/Atmosphere Mesoscale Prediction System) mesoscale non-hydrostatic model of the atmosphere which is run on IA64 Feniks computer cluster in the Department of Civil Engineering and Geodesy of the Military University of Technology. The slant delay is the result of integrating the ray (eikonal) equation for the spatial function...
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Robustness Analysis of a Distributed MPC Control System of a Turbo-Generator Set of a Nuclear Plant – Disturbance Issues
PublikacjaTypically, there are two main control loops with PI controllers operating at each turbo-generator set. In this paper, a distributed model predictive controller with local quadratic model predictive controllers for the turbine generator is proposed instead of a set of classical PI controllers. The local quadratic predictive controllers utilize step-response models for the controlled system components. The parameters of these models...
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Safety assurance strategies for autonomous vehicles
PublikacjaAssuring safety of autonomous vehicles requires that the vehicle control system can perceive the situation in the environment and react to actions of other entities. One approach to vehicle safety assurance is based on the assumption that hazardous sequences of events should be identified during hazard analysis and then some means of hazard avoidance and mitigation, like barriers, should be designed and implemented. Another approach...
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Ultrawideband transmission in physical channels: a broadband interference view
PublikacjaThe superposition of multipath components (MPC) of an emitted wave, formed by reflections from limiting surfaces and obstacles in the propagation area, strongly affects communication signals. In the case of modern wideband systems, the effect should be seen as a broadband counterpart of classical interference which is the cause of fading in narrowband systems. This paper shows that in wideband communications, the time- and frequency-domain...
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Study of Noise Propagation for Small Vessels
PublikacjaThe paper presents the results of the noise propagation analysis in ship structures tested in a number of AHTS (Anchor Handling Tug Supply) vessels. Statistical Energy Analysis (SEA) based on numerical model developed specially for the purpose of this numerical investigation were conducted. This numerical model enabled the analysis of both the structural elements and the acoustic spaces. For the detailed studies 47 points fixed...
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Two Stage SVM and kNN Text Documents Classifier
PublikacjaThe paper presents an approach to the large scale text documents classification problem in parallel environments. A two stage classifier is proposed, based on a combination of k-nearest neighbors and support vector machines classification methods. The details of the classifier and the parallelisation of classification, learning and prediction phases are described. The classifier makes use of our method named one-vs-near. It is...
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Developing Prognostic Models of Organization Evolution
PublikacjaThe work focuses on the problem of measuring evolution of IT organizations. Changes in business influence functioning of the IT organization. IT departments or companies must ensure that the needs of their parent company/customers will be met. Therefore they must constantly evolve. Following question can be raised: is it possible to support process of changes the IT organization to run it smoother, faster, easier but with reduced...
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Calibration of precipitation estimation algorithm with particular emphasis on the Pomeranian region using high performance computing
PublikacjaFast and accurate precipitation estimation is an important element of remote atmosphere monitoring, as it allows, for example, to correct short-term weather forecasts and the prediction of several types of meteorological threats. The paper presents methodology for calibrating precipitation estimation algorithm based on MSG SEVIRI sensor data, and Optimal Cloud Analysis product available via EumetCast transmission. Calibration is...
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Influence of pitting corrosion on fatigue and corrosion fatigue of ship and offshore structures. Part II: Load - pit crack interaction
PublikacjaIn the paper has been discussed influence of stresses on general corrosion rate and corrosion pit nucleation and growth rate, whose presence has been questioned by some authors but accepted by most of them. Influence of pit walls roughness on fatigue life of a plate suffering pit corrosion and presence of so called "non damaging" pits which never lead to initiation of fatigue crack, has been presented. Possibility of prediction...
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Natural ventilation performance of family building in cold climate during windy days
PublikacjaAdequately designed natural ventilation is the cheapest and easiest way to effectively remove indoor pollutants and keep the fresh air inside a building. A prediction of performance and effectiveness of ventilation in order to determine the design of a ventilation system can provide real and long term cost savings. The paper presents results of performance (air change rate ACH) and effectiveness (CO2 concentration in the breathing...
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Outlier detection method by using deep neural networks
PublikacjaDetecting outliers in the data set is quite important for building effective predictive models. Consistent prediction can not be made through models created with data sets containing outliers, or robust models can not be created. In such cases, it may be possible to exclude observations that are determined to be outlier from the data set, or to assign less weight to these points of observation than to other points of observation....
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Ionosphere variability I: Advances in observational, monitoring and detection capabilities
PublikacjaThe paper aims to review recent advances regarding the observational and monitoring capabilities of the ionization conditions in the Earth's upper atmosphere. The analysis spans both ground and space-based experiments, seeking for new installations and/or missions, new or upgraded instrumentation and/or observational network establishments as means for advancing current understanding and prediction ability of the ionosphere variability....
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Road traffic can be predicted by machine learning equally effectively as by complex microscopic model
PublikacjaSince high-quality real data acquired from selected road sections are not always available, a traffic control solution can use data from software traffic simulators working offline. The results show that in contrast to microscopic traffic simulation, the algorithms employing neural networks can work in real-time, so they can be used, among others, to determine the speed displayed on variable message road signs. This paper describes...
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Accuracy of Pretreatment Ultrasonography Assessment of Intra-Abdominal Spread in Epithelial Ovarian Cancer: A Prospective Study
PublikacjaThe 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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Investigation of the road noise source employing an automatic noise monitoring station
PublikacjaThe 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.
PublikacjaThe 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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Remarks on steam condensation modeling related to steam turbine large output
PublikacjaIn 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
PublikacjaIn 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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COMPARISON OF TWO MODELS OF CONDENSATION
PublikacjaIn 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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DO WE NEED NAVIER NUMBER? – FURTHER REMARKS AND COMPARISON WITH ANOTHER DIMENSIONLESS NUMBERS
PublikacjaThis 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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Estimation of Housing Demand with Adaptive Neuro-Fuzzy Inference Systems (ANFIS)
PublikacjaIt 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
PublikacjaThe 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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Introduction to the special issue on machine learning in acoustics
PublikacjaWhen 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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INFLUENCE OF THE HULL SHAPE ON THE ENERGY DEMAND OF A SMALL INLAND VESSEL WITH HYBRID PROPULSION
PublikacjaRecently, 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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Long-term hindcast simulation of sea ice in the Baltic Sea
Dane BadawczeThe 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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AVHRR Level1CD covering Baltic Sea area year 2006
Dane BadawczeThe 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
Dane BadawczeThe 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
Dane BadawczeThe 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...