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Wyniki wyszukiwania dla: final prediction error
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Akaike's final prediction error criterion revisited
PublikacjaWhen local identification of a nonstationary ARX system is carried out, two important decisions must be taken. First, one should decide upon the number of estimated parameters, i.e., on the model order. Second, one should choose the appropriate estimation bandwidth, related to the (effective) number of input-output data samples that will be used for identification/ tracking purposes. Failure to make the right decisions results...
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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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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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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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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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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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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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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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Closer Look at the Uncertainty Estimation in Semantic Segmentation under Distributional Shift
PublikacjaWhile recent computer vision algorithms achieve impressive performance on many benchmarks, they lack robustness - presented with an image from a different distribution, (e.g. weather or lighting conditions not considered during training), they may produce an erroneous prediction. Therefore, it is desired that such a model will be able to reliably predict its confidence measure. In this work, uncertainty estimation for the task...
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On adaptive covariance and spectrum estimation of locally stationary multivariate processes
PublikacjaWhen estimating the correlation/spectral structure of a locally stationary process, one has to make two important decisions. First, one should choose the so-called estimation bandwidth, inversely proportional to the effective width of the local analysis window, in the way that complies with the degree of signal nonstationarity. Too small bandwidth may result in an excessive estimation bias, while too large bandwidth may cause excessive...
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RECSYS CHALLENGE 2015: a BUY EVENT PREDICTION IN THE E-COMMERCE DOMAIN
PublikacjaIn this paper we present our approach to RecSys Challenge 2015. Given a set of e-commerce events, the task is to predict whether a user will buy something in the current session and, if yes, which of the item will be bought. We show that the data preparation and enrichment are very important in finding the solution for the challenge and that simple ideas and intuitions could lead to satisfactory results. We also show that simple...
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Robust Parameter Estimation and Output Prediction for Reactive Carrier-Load Nonlinear Dynamic Networks
PublikacjaIn this paper an extension of on-line model simplification technique for a class of networked systems, namely reactive carrier-load nonlinear dynamic networked system (RCLNDNS), kept within point-parametric model (PPM) framework is addressed. The PPM is utilised to acquire a piece wise constant time-varying parameter linear structure for the RCLNDNS suitable for the on-line one step ahead prediction that may be applied to monitoring...
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Comparative study on total nitrogen prediction in wastewater treatment 1 plant and effect of various feature selection methods on machine learning algorithms performance
PublikacjaWastewater characteristics prediction in wastewater treatment plants (WWTPs) is valuable and can reduce the number of sampling, energy, and cost. Feature Selection (FS) methods are used in the pre-processing section for enhancing the model performance. This study aims to evaluate the effect of seven different FS methods (filter, wrapper, and embedded methods) on enhancing the prediction accuracy for total nitrogen (TN) in the WWTP...
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Prediction of energy consumption and evaluation of affecting factors in a full-scale WWTP using a machine learning approach
PublikacjaTreatment of municipal wastewater to meet the stringent effluent quality standards is an energy-intensive process and the main contributor to the costs of wastewater treatment plants (WWTPs). Analysis and prediction of energy consumption (EC) are essential in designing and operating sustainable energy-saving WWTPs. In this study, the effect of wastewater, hydraulic, and climate-based parameters on the daily consumption of EC by...
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Effective Air Quality Prediction Using Reinforced Swarm Optimization and Bi-Directional Gated Recurrent Unit
PublikacjaIn the present scenario, air quality prediction (AQP) is a complex task due to high variability, volatility, and dynamic nature in space and time of particulates and pollutants. Recently, several nations have had poor air quality due to the high emission of particulate matter (PM2.5) that affects human health conditions, especially in urban areas. In this research, a new optimization-based regression model was implemented for effective...
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Sampling-based novel heterogeneous multi-layer stacking ensemble method for telecom customer churn prediction
PublikacjaIn recent times, customer churn has become one of the most significant issues in business-oriented sectors with telecommunication being no exception. Maintaining current customers is particularly valuable due to the high degree of rivalry among telecommunication companies and the costs of acquiring new ones. The early prediction of churned customers may help telecommunication companies to identify the causes of churn and design...
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Prediction of metal deformation due to line heating; an alternative method of mechanical bending, based on artificial neural network approach
PublikacjaLine heating is one of the alternative methods of forming metals and this kind of forming uses the heating torch as a source of heat input. During the process, many parameters are considered like the size of the substrate, thickness, cooling method, source power intensity, the travel speed of the power source, the sequence of heating, and so on. It is important to analyze the factors affecting the...
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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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Global Surrogate Modeling by Neural Network-Based Model Uncertainty
PublikacjaThis work proposes a novel adaptive global surrogate modeling algorithm which uses two neural networks, one for prediction and the other for the model uncertainty. Specifically, the algorithm proceeds in cycles and adaptively enhances the neural network-based surrogate model by selecting the next sampling points guided by an auxiliary neural network approximation of the spatial error. The proposed algorithm is tested numerically...
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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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Formowanie napięć wyjściowych trójfazowego przekształtnika sieciowego
PublikacjaW artykule przedstawiono kompensację dwu zasadniczych zjawisk powodujących zniekształcenia prądów fazowych przekształtnika sieciowego. Pierwszym z nich są zniekształcenia napięcia sieci. W celu ich eliminacji zaproponowano uśrednianie za okres podstawowej harmonicznej uchybu regulatora napięcia obwodu pośredniczącego oraz predykcję napięcia sieci. Drugim natomiast są zniekształcenia napięć wyjściowych przekształtnika sieciowego....
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Computational Complexity and Its Influence on Predictive Capabilities of Machine Learning Models for Concrete Mix Design
PublikacjaThe design of concrete mixtures is crucial in concrete technology, aiming to produce concrete that meets specific quality and performance criteria. Modern standards require not only strength but also eco-friendliness and production efficiency. Based on the Three Equation Method, conventional mix design methods involve analytical and laboratory procedures but are insufficient for contemporary concrete technology, leading to overengineering...
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Quality of Analytical Results: Classifiying Errors and Estimating Measurement Uncertainty
PublikacjaThe most important parameter of each analytical result is its reliability. An analytical result is not a constant value; each result has two properties, error and uncertainty. The sources of both these parameters have to be known and their values determined (estimated). All analytical results are obtained by applying an appropriate measuring procedure. The need for reliable results requires application of reliable analytical procedures,...
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FFT analysis of temperature modulated semiconductor gas sensor response for the prediction of ammonia concentration under humidity interference
PublikacjaThe increasing environmental contamination forces the need to design reliable devices for detecting of the volatile compounds present in the air. For this purpose semiconductor gas sensors, which have been widely used for years, are often utilized. Although they have many advantages such as low price and quite long life time, they still lack of long term stability and selectivity. Namely, environmental conditions have significant...
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Predicting seismic response of SMRFs founded on different soil types using machine learning techniques
PublikacjaPredicting the Maximum Interstory Drift Ratio (M-IDR) of Steel Moment-Resisting Frames (SMRFs) is a useful tool for designers to approximately evaluate the vulnerability of SMRFs. This study aims to explore supervised Machine Learning (ML) algorithms to build a surrogate prediction model for SMRFs to reduce the need for complex modeling. For this purpose, twenty well-known ML algorithms implemented in Python software are trained...
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Analiza bibliometryczna w badaniach dotyczących prognozowania upadłości przedsiębiorstw w Polsce
PublikacjaCelem opracowania jest ukazanie obrazu piśmiennictwa poświęconego zagadnieniom prognozowania upadłości przedsiębiorstw w Polsce. Jako metodę badawczą zastosowano analizę bibliometryczną. Do analizy wykorzystano bazę Google Scholar oraz narzędzie Publish or Perish 7. Okresem badań objęto lata 1995– 2019. Jako frazy do wyszukiwania publikacji zastosowano: „prognozowanie upadłości”, „prognozowanie zagrożenia finansowego”, „systemy...
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The spontaneous electron emission and rotational predissociation lifetimes of the diatomic silver anion
Dane BadawczeThe process of a two-channel decay of the diatomic silver anion (Ag2-), namely the spontaneous electron ejection giving Ag2 + e- and the dissociation leading to Ag- + Ag is theoretically studied. The ground state potential energy curves (PECs) of the neutral silver dimer and anionic silver diatomic molecule are calculated using the single reference...
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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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In silico modelling for predicting the cationic hydrophobicity and cytotoxicity of ionic liquids towards the Leukemia rat cell line, Vibrio fischeri and Scenedesmus vacuolatus based on molecular interaction potentials of ions
PublikacjaIn this study we present prediction models for estimating in silico the cationic hydrophobicity and the cytotoxicity (log [1/EC50]) of ionic liquids (ILs) towards the Leukemia rat cell line (IPC-81), the marine bacterium Vibrio fischeri and the limnic green algae Scenedesmus vacuolatus using linear free energy relationship (LFER) descriptors computed by COSMO calculations. The LFER descriptors used for the prediction model (i.e....
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Evaluation of Response Amplitude Operator of Ship Roll Motions Based on the Experiments in White Noise Waves
PublikacjaEvaluation of the response amplitude operator (RAO) function for ship wave frequency motions by means of scale model tests in regular waves is a standard procedure conducted by hydrodynamic model testing institutions. The resulting RAO function allows for evaluating sufficiently reliable seakeeping predictions for low to moderate sea states. However, for standard hull forms, correct prediction of roll motion in irregular wave (and...
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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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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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Polychlorinated Biphenyls (PCBs) and Polycyclic Aromatic Hydrocarbons (PAHs): Sediments and Water Analysis
PublikacjaUnfavorable side effects of different forms of anthropogenic activities can be found anywhere in the world. One of the basic characteristics of pollutants entering marine and ocean waters is their spread and movement in the global ocean. A portion of the substances entering the marine environment is rapidly degraded by chemical processes occurring in the air, sediments, and water, thereby losing their toxic properties. The biggest...
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Installation of GNSS receivers on a mobile railway platform – methodology and measurement aspects
PublikacjaDetermining the course of a railway track axis using satellite methods relies on ensuring the precise assembly of GNSS receivers in dedicated measuring devices. Depending on the number of receivers, solutions that are based on placing the apparatus directly above the railway track axis (as well as in eccentric positions) are used to indirectly obtain data to form the basis of the desired results. This publication describes the...
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Application of a hybrid mechanistic/machine learning model for prediction of nitrous oxide (N2O) production in a nitrifying sequencing batch reactor
PublikacjaNitrous oxide (N2O) is a key parameter for evaluating the greenhouse gas emissions from wastewater treatment plants. In this study, a new method for predicting liquid N2O production during nitrification was developed based on a mechanistic model and machine learning (ML) algorithm. The mechanistic model was first used for simulation of two 15-day experimental trials in a nitrifying sequencing batch reactor. Then, model predictions...
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Application of gas chromatographic data and 2D molecular descriptors for accurate global mobility potential prediction
PublikacjaMobility is a key feature affecting the environmental fate, which is of particular importance in the case of persistent organic pollutants (POPs) and emerging pollutants (EPs). In this study, the global mobility classification artificial neural networks-based models employing GC retention times (RT) and 2D molecular descriptors were constructed and validated. The high usability of RT was confirmed based on the feature selection...
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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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Determination of Odour Interactions of Three-Component Gas Mixtures Using an Electronic Nose
PublikacjaThe 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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Experimental investigations on adiabatic frictional pressure drops of R134a during flow in 5mm diameter channel
PublikacjaThe article presents detailed two-phase adiabatic pressure drops data for refrigerant R134a at a saturation pressure of 5.5 bar corresponding to the saturation temperature of 19.4 °C. Study cases have been set for a mass flux varying from 100 to 500 kg/m2 s. The frictional pressure drop was characterized for the refrigerant R134a, for vapor qualities ranging from 0 to 1. Long-time thermal stability of test facility allowed to gather...
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The Dynamics of Trade Relations between Ukraine and Romania: Modelling and Forecasting
PublikacjaThe 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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Driver’s Condition Detection System Using Multimodal Imaging and Machine Learning Algorithms
PublikacjaTo 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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Local variability in snow concentrations of chlorinated persistent organic pollutants as a source of large uncertainty in interpreting spatial patterns at all scales
PublikacjaSingle point sampling, a widespread practice in snow studies in remote areas, due to logistical constraints, can present an unquantified error to the final study results. The low concentrations of studied chemicals, such as chlorinated persistent organic pollutants, contribute to the uncertainty. We conducted a field experiment in the Arctic to estimate the error stemming from differences in the composition of snow at short distances...
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3D Monitoring - Identification of measurement problems at larger movements of the tracked points
PublikacjaAuthors identified the problems associated with the determination of the controlled points coordinates by use of automated Total Station placed behind transparent barrier. Important thing in the mentioned analysis was a large change of controlled points position and not stable Total Station’s stand (because of stand’s thermal drift). This two elements, combined with measurement made through glass plate determine the need for impact...
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Isotope-labeled substances in analysis of persistent organicpollutants in environmental samples
PublikacjaUltratrace analysis of persistent organic pollutants (POPs) in environmental samples requires very sophisticated methods for both sample preparation and instrumental analysis. The complex matrix requires a multi-stage procedure. Each stage is a potential source of error, as a consequence of which the final result of analysis could be a source of misinformation rather than information. The individual stages and the procedure as...
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Simplified, multiregional fuzzy model of a nuclear power plant steam turbine
PublikacjaPower systems, including steam turbines and synchronous generators, are complex nonlinear systems with parameters varying over time. The paper presents the developed simplified, multiregional fuzzy model of the steam turbine of a nuclear power plant turbine generator set and compares the results with a full nonlinear model and commonly used linear input-output model of a steam turbine. The proposed model consist of series of linear...
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Deep learning for ultra-fast and high precision screening of energy materials
PublikacjaSemiconductor materials for energy storage are the core and foundation of modern information society and play important roles in photovoltaic system, integrated circuit, spacecraft technology, lighting applications, and other fields. Unfortunately, due to the long experiment period and high calculation cost, the high-precision band gap (the basic characteristic parameter) of semiconductor is difficult to obtain, which hinders the...
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Comparison of different techniques for extracting Polychlorinated Biphenyls from bottom sediment samples using Isotope Dilution Mass Spectrometry
PublikacjaIn this work, problems that may occur during determination of trace levels of polychlorinated biphenyls in sediment samples are described. The main error sources are connected with extraction of analytes prior to final determination. During model studies, polychlorinated biphenyls have been extracted from sediment reference material (METRANAL 2) with the use of different solvents (dichloromethane, hexane, and toluene); the process...
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Autocorrelation function for the chosen effective potential of the diatomic silver anion
Dane BadawczeThe process of a two-channel decay of the diatomic silver anion (Ag2-), namely the spontaneous electron ejection giving Ag2 + e- and the dissociation leading to Ag- + Ag is theoretically studied. The ground state potential energy curves (PECs) of the neutral silver dimer and anionic silver diatomic molecule are calculated using the single reference...
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Non-adiabatic coupling elements between the diatomic silver anion and neutral silver dimer plus continuum electron
Dane BadawczeThe process of a two-channel decay of the diatomic silver anion (Ag2-), namely the spontaneous electron ejection giving Ag2 + e- and the dissociation leading to Ag- + Ag is theoretically studied. The ground state potential energy curves (PECs) of the neutral silver dimer and anionic silver diatomic molecule are calculated using the single reference...
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Novel Complementary Multiple Concentric Split Ring Resonator for Reliable Characterization of Dielectric Substrates with High Sensitivity
PublikacjaAccurate characterization of dielectric substrates with high sensitivity remains an important challenge in a variety of industrial applications. This paper proposes an innovative strategy to address this challenge by developing and optimizing a unique Complementary Multiple Concentric Split Ring Resonator (CMC-SRR). The major goal is to propose a sensor design with increased sensitivity and reliability for dielectric characterization....
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An adaptive-noise Augmented Kalman Filter approach for input-state estimation in structural dynamics
PublikacjaThe 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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Application 2D Descriptors and Artificial Neural Networks for Beta-Glucosidase Inhibitors Screening
PublikacjaBeta-glucosidase inhibitors play important medical and biological roles. In this study, simple two-variable artificial neural network (ANN) classification models were developed for beta-glucosidase inhibitors screening. All bioassay data were obtained from the ChEMBL database. The classifiers were generated using 2D molecular descriptors and the data miner tool available in the STATISTICA package (STATISTICA Automated Neural...
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Pre-analytical aspects in metabolomics of human biofluids – sample collection, handling, transport, and storage
PublikacjaMetabolomics is the field of omics research that offers valuable insights into the complex composition of biological samples. It has found wide application in clinical diagnostics, disease investigation, therapy prediction, monitoring of treatment efficiency, drug discovery, or in-depth analysis of sample composition. A suitable study design constitutes the fundamental requirements to ensure robust and reliable results from the...
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The rovibrational energy levels of the diatomic silver anion and neutral silver dimer
Dane BadawczeThe process of a two-channel decay of the diatomic silver anion (Ag2-), namely the spontaneous electron ejection giving Ag2 + e- and the dissociation leading to Ag- + Ag is theoretically studied. The ground state potential energy curves (PECs) of the neutral silver dimer and anionic silver diatomic molecule are calculated using the single reference...
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Selection of effective cocrystals former for dissolution rate improvement of active pharmaceutical ingredients based on lipoaffinity index
PublikacjaNew theoretical screening procedure was proposed for appropriate selection of potential cocrystal formers possessing the ability of enhancing dissolution rates of drugs. The procedure relies on the training set comprising 102 positive and 17 negative cases of cocrystals found in the literature. Despite the fact that the only available data were of qualitative character, performed statistical analysis using binary classification...
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Assessment of the Accuracy of Determining the Angular Position of the Unmanned Bathymetric Surveying Vehicle Based on the Sea Horizon Image
PublikacjaThe paper presents the results of research on assessing the accuracy of angular position measurement relative to the sea horizon using a camera mounted on an unmanned bathymetric surveying vehicle of the Unmanned Surface Vehicle (USV) or Unmanned Aerial Vehicle (UAV) type. The first part of the article presents the essence of the problem. The rules of taking the angular position of the vehicle into account in bathymetric surveys...
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Application of Feed Forward Neural Networks for Modeling of Heat Transfer Coefficient During Flow Condensation for Low and High Values of Saturation Temperatur
PublikacjaMost of the literature models for condensation heat transfer prediction are based on specific experimental parameters and are not general in nature for applications to fluids and non-experimental thermodynamic conditions. Nearly all correlations are created to predict data in normal HVAC conditions below 40°C. High temperature heat pumps operate at much higher parameters. This paper aims to create a general model for the calculation...
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Final Project BiM
Kursy OnlineThis course pertains to the final thesis that you students prepare and defend to obtain the bachelor's degree.
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ROBOT TYPU QUADROCOPTER STEROWANY MIKROKONTROLERAMI O NIEWIELKIEJ MOCY OBLICZENIOWEJ
PublikacjaWspółczesna robotyka rozwija się bardzo dynamicznie. Coraz więcej osób prywatnych i inżynierów konstruuje różnego rodzaju pojazdy mobilne. Dlatego autorzy niniejszego referatu postawili sobie następującą tezę: możliwa jest budowa latającego robota mobilnego na bazie kontrolera o niskiej mocy obliczeniowej oraz prostego regulatora, i podjęli się jej udowodnienia.
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Reliable EM-driven size reduction of antenna structures by means of adaptive penalty factors
PublikacjaMiniaturization has become of paramount importance in the design of modern antenna systems. In particular, compact size is essential for emerging application areas such as internet of things, wearable and implantable devices, 5G technology, or medical imaging. On the other hand, reduction of physical dimensions generally has a detrimental effect on antenna performance. From the perspective of numerical optimization, miniaturization...
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Speed estimation of a car at impact with a W-beam guardrail using numerical simulations and machine learning
PublikacjaThis paper aimed at developing a new method of estimating the impact speed of a passenger car at the moment of a crash into a W-beam road safety barrier. The determination of such a speed based on the accident outcomes is demanding, because often there is no access to full accident data. However, accurate determination of the impact speed is one of the key elements in the reconstruction of road accidents. A machine learning algorithm...
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Wykorzystanie algorytmów ewolucyjnych do doboru wzmocnień rozszerzonego obserwatora prędkości maszyny indukcyjnej
PublikacjaW pracy opisano sposób doboru wzmocnień rozszerzonego obserwatora prędkości maszyny indukcyjnej przy wykorzystaniu algorytmów ewolucyjnych. Zaproponowano funkcję celu opartą na rozkładzie biegunów obserwatora. Ze względu na wpływ prędkości maszyny na dynamikę obserwatora zaproponowano dobór wzmocnień obserwatora dla różnych przedziałów prędkości. Dla poszczególnych przedziałów zaprezentowano wyniki doboru wzmocnień w postaci tabel...
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Application of the ISE Optimized Proportional Control of the Wave Maker in a Towing Tank
PublikacjaThis paper presents the improvement of the wave maker control system. The wave maker is a facility widely used in hydromechanics laboratories to generate waves in towing tanks. It is equipped with an electrohydraulic drive and an actuator submerged into water. The waves are generated to model the environmental conditions for physical experiments, performed on reduced-scale models of maritime objects. The physical experiments allow...
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Assessing the attractiveness of human face based on machine learning
PublikacjaThe attractiveness of the face plays an important role in everyday life, especially in the modern world where social media and the Internet surround us. In this study, an attempt to assess the attractiveness of a face by machine learning is shown. Attractiveness is determined by three deep models whose sum of predictions is the final score. Two annotated datasets available in the literature are employed for training and testing...
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Potential energy curves and spectroscopic parameters of the diatomic silver anion and neutral silver dimer
Dane BadawczeThe process of a two-channel decay of the diatomic silver anion (Ag2-), namely the spontaneous electron ejection giving Ag2 + e- and the dissociation leading to Ag- + Ag is theoretically studied. The ground state potential energy curves (PECs) of the neutral silver dimer and anionic silver diatomic molecule are calculated using the single reference...
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On zero-error codes produced by greedy algorithms
PublikacjaWe present two greedy algorithms that determine zero-error codes and lower bounds on the zero-error capacity. These algorithms have many advantages, e.g., they do not store a whole product graph in a computer memory and they use the so-called distributions in all dimensions to get better approximations of the zero-error capacity. We also show an additional application of our algorithms.
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An Approximation of the Zero Error Capacity by a Greedy Algorithm.
PublikacjaWe present a greedy algorithm that determines a lower bound on the zero error capacity. The algorithm has many new advantages, e.g., it does not store a whole product graph in a computer memory and it uses the so-called distributions in all dimensions to get a better approximation of the zero error capacity. We also show an additional application of our algorithm.
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An Approximation of the Zero Error Capacity by a Greedy Algorithm
PublikacjaWe present a greedy algorithm that determines a lower bound on the zero error capacity. The algorithm has many new advantages, e.g., it does not store a whole product graph in a computer memory and it uses the so-called distributions in all dimensions to get a better approximation of the zero error capacity. We also show an additional application of our algorithm.
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Computationally efficient two-objective optimization of compact microwave couplers through corrected domain patching
PublikacjaFinding an acceptable compromise between various objectives is a necessity in the design of contemporary microwave components and circuits. A primary reason is that most objectives are at least partially conflicting. For compact microwave structures, the design trade-offs are normally related to the circuit size and its electrical performance. In order to obtain comprehensive information about the best possible trade-offs, multi-objective...
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Accurate Modeling of Frequency Selective Surfaces Using Fully-Connected Regression Model with Automated Architecture Determination and Parameter Selection Based on Bayesian Optimization
PublikacjaSurrogate modeling has become an important tool in the design of high-frequency structures. Although full-wave electromagnetic (EM) simulation tools provide an accurate account for the circuit characteristics and performance, they entail considerable computational expenditures. Replacing EM analysis by fast surrogates provides a way to accelerate the design procedures. Unfortunately, modeling of microwave passives is a challenging...
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A Simple Neural Network for Collision Detection of Collaborative Robots
PublikacjaDue to the epidemic threat, more and more companies decide to automate their production lines. Given the lack of adequate security or space, in most cases, such companies cannot use classic production robots. The solution to this problem is the use of collaborative robots (cobots). However, the required equipment (force sensors) or alternative methods of detecting a threat to humans are usually quite expensive. The article presents...
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Comment on "Measurements without probabilities in the final state proposal"
PublikacjaThe final state proposal [G.T. Horowitz and J.M. Maldacena, J. High Energy Phys.2004(2),8 (2004)] is an attempt to relax the apparent tension betweenstring theory and semiclassicalarguments regarding the unitarity of black hole evaporation. The authors of [R. Bousso and D.Stanford, Phys. Rev. D89, 044038 (2014)] analyze thought experiments where an infalling observerfirst verifies the entanglement between early and late Hawking...
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AHURI Final Report
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Badanie i analiza efektywności alokacji strumieni danych w heterogenicznej sieci WBAN
PublikacjaW niniejszej dysertacji doktorskiej poddano dyskusji efektywność alokacji strumieni danych w heterogenicznej radiowej sieci WBAN (Wireless Body Area Networks). Biorąc pod uwagę dynamiczny rozwój nowoczesnych sieci radiokomunikacyjnych piątej generacji (5G), którego część stanowią radiowe sieci działające w obrębie ciała człowieka, bardzo ważnym aspektem są metody maksymalizujące wykorzystanie dostępnych zasobów czasowo –częstotliwościowych...
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Evaluating the risk of endometriosis based on patients’ self-assessment questionnaires
PublikacjaBackground Endometriosis is a condition that significantly affects the quality of life of about 10 % of reproductive-aged women. It is characterized by the presence of tissue similar to the uterine lining (endometrium) outside the uterus, which can lead lead scarring, adhesions, pain, and fertility issues. While numerous factors associated with endometriosis are documented, a wide range of symptoms may still be undiscovered. Methods In...
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Final report on noise and rolling resistance
PublikacjaWork Package 6 deals with environmental impacts of PERS use, including noise and rolling resistance. This report covers preliminary noise tests performed in the laboratory and at the road test sites. The obtained results indicate that PERS material reduce noise considerably - up to 12 dB in comparison to SMA16 reference surface. Noise reduction properties are especially visible in the case of factory produced PERS slabs supplied...
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Final Farewell to Alberto Zanchetti MD
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Hourly GNSS-derived integrated moisture in the global tropics for the years 2001-2018
Dane BadawczeGlobal tropics are essential in formulating weather patterns and climate across various latitudes through atmospheric teleconnections. Since water vapour is an essential parameter in atmospheric convection and, thus, latent heat release, its tropical variability on different time scales is crucial in understanding weather and climate changes. The provided...
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A Goal-Oriented Error Estimator for Reduced Basis Method Modeling of Microwave Devices
PublikacjaThis letter proposes a novel a-posteriori error estimator suitable for the reduced order modeling of microwave circuits. Unlike the existing error estimators based on impedance function residuals, the new one exploits the residual error associated with the computation of the scattering matrix. The estimator can be effectively used in the Reduced Basis Method (RBM) to automatically generate reduced-order models. The results of numerical...
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Study of Multi-Class Classification Algorithms’ Performance on Highly Imbalanced Network Intrusion Datasets
PublikacjaThis paper is devoted to the problem of class imbalance in machine learning, focusing on the intrusion detection of rare classes in computer networks. The problem of class imbalance occurs when one class heavily outnumbers examples from the other classes. In this paper, we are particularly interested in classifiers, as pattern recognition and anomaly detection could be solved as a classification problem. As still a major part of...
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Linearized CMOS OTA using Active-Error Feedforward technique.
PublikacjaW pracy przedstawiono koncepcję układową operacyjnego wzmacniacza transkonduktancyjnego CMOS OTA oraz metodę linearyzacji jego charakterystyki przejściowej typu ''active-error feedforward''. Badania symulacyjne przy pomocy programu SPICE wykazały, że linearyzowany układ jest dostosowany do pracy z napięciem zasilania ± 1,25 V i dla sygnału harmonicznego o częstotliwości 1MHz (0,8 Vp-p) zapewnia poziom zniekształceń harmonicznych...
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Final dissertation preparation
Kursy Online -
Final Exam KF
Kursy Online -
Fixed final time and free final state optimal control problem for fractional dynamic systems – linear quadratic discrete-time case
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The impacts of final demands changes on the total outputs of Japanese industrial sectors: A further study
PublikacjaThe purpose of the current study is to expand the previous studies which analyze the impacts of final demands changes on the total outputs of industrial sectors of a specific country. More specifically, the study conducts the analysis regarding the impacts on the total outputs of Japanese industries. The study employs a demand-pull Input-Output (IO) quantity model, one of the calculation tools in the IO analysis. The study focuses...
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The impacts of final demands changes on the total outputs of Japanese industrial sectors: A further study
PublikacjaThe purpose of the current study is to expand the previous studies which analyze the impacts of final demands changes on the total outputs of industrial sectors of a specific country. More specifically, the study conducts the analysis regarding the impacts on the total outputs of Japanese industries. The study employs a demand-pull Input-Output (IO) quantity model, one of the calculation tools in the IO analysis. The study focuses...
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Final state of thermal evolution of Jupiter-type planet
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Rating Prediction with Contextual Conditional Preferences
PublikacjaExploiting contextual information is considered a good solution to improve the quality of recommendations, aiming at suggesting more relevant items for a specific context. On the other hand, recommender systems research still strive for solving the cold-start problem, namely where not enough information about users and their ratings is available. In this paper we propose a new rating prediction algorithm to face the cold-start...
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Rhamnolipid CMC Prediction
PublikacjaRelationships between the purity, pH, hydrophobicity (log Kow) of the carbon substrate, and the critical micelle concentration (CMC) of rhamnolipid type biosurfactants (RL) were investigated using a quantitative structure–property relationship (QSPR) approach and are presented here for the first time. Measured and literature CMC values of 97 RLs, representing biosurfactants at different stages of purification, were considered....
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The asymptotic formula for the error in orthogonal projection
PublikacjaW pracy podano formułę asymptotyczną błędu aproksymacji dla rzutów ortogonalnych w normie L^p.
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Asymptotic formulas for the error in linear interpolation
PublikacjaWyznaczono asymptotyczny wzór dla błędu w liniowej interpolacji z dowolnymi węzłami.
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Error analysis for European IGS stations
PublikacjaEach of the GPS time series that describes the changes of topocentric components consists of a deterministic and a stochastic part, whose character influences the errors of the deterministic parameters. As to the uncertainties of reliable velocities of permanent satellite station systems, surveys that estimate and take into account any dependencies that may affect subsequent operational efficiency are very important. For this analysis,...
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Ship Resistance Prediction with Artificial Neural Networks
PublikacjaThe paper is dedicated to a new method of ship’s resistance prediction using Artificial Neural Network (ANN). In the initial stage selected ships parameters are prepared to be used as a training and validation sets. Next step is to verify several network structures and to determine parameters with the highest influence on the result resistance. Finally, other parameters expected to impact the resistance are proposed. The research utilizes...
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The dying medium temperature impact on the final moisture content of pine wood at constant drying time
PublikacjaThe results of final moisture content of pine wood (Pinus sylvestris L.) after drying process are presented. The wood in the experiments was taken from the northern part of Pomeranian region in Poland. The drying process was performed in the experimental chamber equipped with the micro-jet heat exchanger. The air at temperatures of 40°C, 60°C, 80°C, 100°C and 120°C with relative humidity about 60% and atmospheric pressure was the...
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Comparison of different extraction techniques of polychlorinated biphenyls from sediments samples.
PublikacjaIn this work, problems that may occur during determination of trace levels of polychlorinated biphenyls in sediment samples are described. Main error sources are connected with extraction of analytes prior to final determination. During model studies, polychlorinated biphenyls have been extracted from sedimentreference material (METRANAL 2) with the use of different solvents (dichloromethane, hexsane, and toluene); the process...
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The Recent Past and Possible Futures of Citizen Science: Final Remarks
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The final answer to the complexity of a basic problem in resilient network design
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Final Project Seminar_Natalia Przybylska_2021
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Intelligent Decision Forest Models for Customer Churn Prediction
PublikacjaCustomer churn is a critical issue impacting enterprises and organizations, particularly in the emerging and highly competitive telecommunications industry. It is important to researchers and industry analysts interested in projecting customer behavior to separate churn from non‐churn consumers. The fundamental incentive is a firm’s intent desire to keep current consumers, along with the exorbitant expense of gaining new ones....
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Asymptotic error expansions for Schoenberg type operators.
PublikacjaW pracy wyprowadzono rozwinięcie asymptotyczne dla błędu w L2 operatorówSchoenberga.