Search results for: PREDICTION
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Road noise mapping in the city area: measurements compared to model-based estimations
PublicationThe paper presents an approach to the verification of noise prediction models in selected localization in the city of Gdansk. The experiments described include a comparison between environmentalmeasurement results performed in the terrain and the noise level prediction results. The NMPB-96 (Nouvelle Méthode de Prévision du Bruit) and Harmonoise models outcomes provide the subject ofthe analysis. The proposed solution of continuous...
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Evaluation of Response Amplitude Operator of Ship Roll Motions Based on the Experiments in White Noise Waves
PublicationEvaluation 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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Detection of impulsive disturbances in archive audio signals
PublicationIn this paper the problem of detection of impulsive disturbances in archive audio signals is considered. It is shown that semi-causal/noncausal solutions based on joint evaluation of signal prediction errors and leave-one-out signal interpolation errors, allow one to noticeably improve detection results compared to the prediction-only based solutions. The proposed approaches are evaluated on a set of clean audio signals contaminated...
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Impact of Low Switching-to-Fundamental Frequency Ratio on Predictive Current Control of PMSM: A simulation study
PublicationPredictive current control algorithms for permanent magnet synchronous (PMSM) drives rely on an assumption that within short intervals motor currents can be approximated with linear functions. This approximation may result either from discretizing the motor model or from simplifications applied to the continuous-time model. As the linear current approximation has been recognized as inaccurate in case when the drive operates with...
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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
PublicationIn 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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Analiza bibliometryczna w badaniach dotyczących prognozowania upadłości przedsiębiorstw w Polsce
PublicationCelem 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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Identification of ship’s hull mathematical model with numerical methods
PublicationThe modern maritime industry is moving toward the development of technology that will allow for full or partial autonomy of ship operation. This innovation places high demands on ship performance prediction techniques at the design stage. The researchwork presented in the article is related to the design stage of the ship and concerns methods for prognosis and evaluation of the specific operational condition of the ship, namely...
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Wireless intelligent audio-video surveillance prototyping system
PublicationThe presented system is based on the Virtex6 FPGA and several supporting devices like a fast DDR3 memory, small HD camera, microphone with A/D converter, WiFi radio communication module, etc. The system is controlled by the Linux operating system. The Linux drivers for devices implemented in the system have been prepared. The system has been successfully verified in a H.264 compression accelerator prototype in which the most demanding...
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Elimination of impulsive disturbances from archive audio files – comparison of three noise pulse detection schemes
PublicationThe problem of elimination of impulsive disturbances (such as clicks, pops, ticks, crackles, and record scratches) from archive audio recordings is considered and solved using autoregressive modeling. Three classical noise pulse detection schemes are examined and compared: the approach based on open-loop multi-step-ahead signal prediction, the approach based on decision-feedback signal prediction, and the double threshold approach,...
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Efficient uncertainty quantification using sequential sampling-based neural networks
PublicationUncertainty quantification (UQ) of an engineered system involves the identification of uncertainties, modeling of the uncertainties, and the forward propagation of the uncertainties through a system analysis model. In this work, a novel surrogate-based forward propagation algorithm for UQ is proposed. The proposed algorithm is a new and unique extension of the recent efficient global optimization using neural network (NN)-based...
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On ship roll resonance frequency
PublicationThe paper deals with the problem of modeling of rolling motion under a variety of excitation parameters. Special emphasis is put on the analysis and prediction of the frequency of the resonant mode of rolling, since it is often an essential issue in terms of motion of a ship related to her safety against capsizing or excessive amplitudes of roll. The research is performed for both free rolling and excited rolling and it is based...
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Elimination of clicks from archive speech signals using sparse autoregressive modeling
PublicationThis paper presents a new approach to elimination of impulsivedisturbances from archive speech signals. The proposedsparse autoregressive (SAR) signal representation is given ina factorized form - the model is a cascade of the so-called formantfilter and pitch filter. Such a technique has been widelyused in code-excited linear prediction (CELP) systems, as itguarantees model stability. After detection of noise pulses usinglinear...
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New semi-causal and noncausal techniques for detection of impulsive disturbances in multivariate signals with audio applications
PublicationThis paper deals with the problem of localization of impulsive disturbances in nonstationary multivariate signals. Both unidirectional and bidirectional (noncausal) detection schemes are proposed. It is shown that the strengthened pulse detection rule, which combines analysis of one-step-ahead signal prediction errors with critical evaluation of leave-one-out signal interpolation errors, allows one to noticeably improve detection results...
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Trim Optimisation - Theory and Practice
PublicationForce Technology has been working intensively with trim optimisation tests for almost last 10 years. Focus has primarily been put on the possible power savings and exhaust gases reduction. This paper describes the trim optimisation process for a large cargo vessel. The physics behind changed propulsive power is described and the analyses in order to elaborate the optimum trimmed conditions are presented. Different methods for prediction...
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Global Surrogate Modeling by Neural Network-Based Model Uncertainty
PublicationThis 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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Chemistry and Nanochemistry 2022.
e-Learning CoursesThe course consists of lectures (15 x 2 hours) and laboratories (5 x 3 hours).The goal of this course is to teach general chemistry and adequately apply it to nano-size systems, their synthesis and analysis. An emphasis is laid on an analysis of electronic structure of molecules and prediction of resulting properties and reasons of consequent behaviour in chemical reactions. The course also encloses laboratory classes, where the...
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Traffic Noise Analysis Applied to Automatic Vehicle Counting and Classification
PublicationProblems related to determining traffic noise characteristics are discussed in the context of automatic dynamic noise analysis based on noise level measurements and traffic prediction models. The obtained analytical results provide the second goal of the study, namely automatic vehicle counting and classification. Several traffic prediction models are presented and compared to the results of in-situ noise level measurements. Synchronized...
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TOWARDS EXPLAINABLE CLASSIFIERS USING THE COUNTERFACTUAL APPROACH - GLOBAL EXPLANATIONS FOR DISCOVERING BIAS IN DATA
PublicationThe 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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An algorithm for selecting a machine learning method for predicting nitrous oxide emissions in municipal wastewater treatment plants
PublicationThis 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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Machine learning-based seismic response and performance assessment of reinforced concrete buildings
PublicationComplexity 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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Andrzej Chybicki dr inż.
PeopleA graduate of the Faculty of Electronics, Telecommunications and Informatics at the Gdańsk University of Technology, PhD in technical sciences in the field of IT specializing in distributed data processing in IT . Aimed at exploiting the achievements and knowledge in the field of industrial research. He cooperated with a number of companies including OpeGieka Elbląg, Reson Inc., Powel Sp. z o. o., Wasat, Better Solutions, the European...
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Computational collective intelligence for enterprise information systems
PublicationCollective 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
PublicationA 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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Multi-Criteria Knowledge-Based Recommender System for Decision Support in Complex Business Processes
PublicationIn 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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Akcelerator predykcji wewnątrzramkowej H.264 do kompresji obrazu w sensorach wizyjnych
PublicationW komunikacie przedstawiono konfigurowalny cyfrowy akcelerator predykcji wewnątrzramkowej przeznaczony dla enkodera wideo standardu H.264. Akcelerator realizuje predykcję typu „intra” dla makrobloków luminancji o wymiarach 4x4 i 16x16. Akcelerator wstępnie zaimplementowano w układzie FPGA, gdzie został on pomyślnie zweryfikowany, a następnie zaimplementowano go w układzie ASIC w technologii UMC 90 nm. Szczegółowe wyniki testów...
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Akcelerator predykcji wewnątrzramkowej H.264 do kompresji obrazu w sensorach wizyjnych
PublicationW artykule przedstawiono konfigurowalny cyfrowy akcelerator predykcji wewnątrzramkowej przeznaczony dla enkodera wideo standardu H.264. Akcelerator realizuje predykcję typu „intra” dla makrobloków luminancji o wymiarach 4x4 i 16x16. Akcelerator wstępnie zaimplementowano w układzie FPGA, gdzie został on pomyślnie zweryfikowany, a następnie zaimplementowano go w układzie ASIC w technologii UMC 90 nm. Szczegółowe wyniki testów akceleratora...
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OCENA PRZYDATNOŚCI WIELOWYMIAROWYCH MODELI DYSKRYMINACYJNYCH DO PROGNOZOWANIA UPADŁOŚCI PRZEDSIĘBIORSTW HANDLOWYCH
PublicationCelem badań była ocena przydatności użycia modeli opartych na wielowymiarowej analizie dyskryminacyjnej do prognozowania upadłości polskich przedsiębiorstw handlowych oraz próba zwiększenia ich sprawności poprzez zmianę wartości ich punktów granicznych. Badaniu poddano modele: E. I. Altmana „B”, D. Hadasik, A. Hołdy oraz M. Hamrola, B. Czajki i M. Piechockiego. Do oceny modeli wykorzystano iloraz szans oraz macierz klasyfikacji...
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System do prototypowania bezprzewodowych inteligentnych urządzeń monitoringu audio-video
PublicationW komunikacie przedstawiono system prototypowania bezprzewodowych urządzeń do monitoringu audio-video. System bazuje na układach FPGA Virtex6 i wielu dodatkowych wspierających urządzeniach jak: szybka pamięć DDR3, mała kamera HD, mikrofon z konwerterem A/C, moduł radiowy WiFi, itp. Funkcjonalność systemu została szczegółowo opisana w komunikacie. System został zoptymalizowany do pracy pod kontrolą systemu operacyjnego Linux, zostały...
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Chained machine learning model for predicting load capacity and ductility of steel fiber–reinforced concrete beams
PublicationOne 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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Performance of Noise Map Service Working in Cloud Computing Environment
PublicationIn 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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On joint order and bandwidth selection for identification of nonstationary autoregressive processes
PublicationWhen 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
PublicationAnalytical 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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Predicting bankruptcy with the use of macroeconomic variables
PublicationRegarding the current global financial crisis, the firms can expect the increased uncertainty of their existence. The relevant literature includes extensive studies on bankruptcy prediction. Studies show that the most popular method used for prediction of firms' failures are discriminant analyses (30,3% of all models), then logit and probit models (21,3%), which all three are parametric models. The nature, the structure of the...
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Mathematical Modeling of Ice Dynamics as a Decision Support Tool in River Engineering
PublicationThe 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
PublicationThis 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
PublicationThis 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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Long-term hindcast simulation of sea level in the Baltic Sea
Open Research DataThe 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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On Noncausal Identification of Nonstationary Multivariate Autoregressive Processes
PublicationThe 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
PublicationIn 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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An Ontology-based Contextual Pre-filtering Technique for Recommender Systems
PublicationContext-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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Things You Might Not Know about the k-Nearest Neighbors Algorithm
PublicationRecommender 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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Pose-Invariant Face Detection by Replacing Deep Neurons with Capsules for Thermal Imagery in Telemedicine
PublicationAbstract— 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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Predicting seismic response of SMRFs founded on different soil types using machine learning techniques
PublicationPredicting 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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The analysis of soil resistance during screw displacement pile installation
PublicationThe 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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Formowanie napięć wyjściowych trójfazowego przekształtnika sieciowego
PublicationW 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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Data on LEGO sets release dates and worldwide retail prices combined with aftermarket transaction prices in Poland between June 2018 and June 2023
PublicationThe 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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Towards a reliable method for extrapolation of propulsion performance for vessels with twin-crp-pod system
PublicationThe study presents power performance prediction of an Ultra Large Container Ship (ULCS) with hybrid twin-crp-pod propulsion system. Twin crp-pod propulsion system is a combination of three concepts: twin screw, contra-rotating propellers (crp) and conventional shaft propellers with pod propulsors behind. The presented study shows the current extrapolation method for crp propulsion systems and tries to point out its weaknesses....
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Study on the accuracy of axle load spectra used for pavement design
PublicationWeigh-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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Sensing Direction of Human Motion Using Single-Input-Single-Output (SISO) Channel Model and Neural Networks
PublicationObject 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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Edgewise Compressive Behavior of Composite Structural Insulated Panels with Magnesium Oxide Board Facings
PublicationEdgewise 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...