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Search results for: prediction
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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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Adam Inglot dr inż.
PeopleAdam Inglot (born October 3, 1984), studied Environmental Engineering and Geodesy and Cartography at the Faculty of Mine Surveying and Environmental Engineering of AGH University of Science and Technology in Krakow. He graduated in 2011 as a M.Sc. in Environmental Engineering, defending his thesis "Verification of usefulness of GeoMod model for prediction of the urbanization process in Cracow agglomeration" under the guidance of...
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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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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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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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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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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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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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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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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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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...
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Can Web Search Queries Predict Prices Change on the Real Estate Market?
PublicationThis study aims to explore whether the intensity of internet searches, according to the Google Trends search volume index (SVI), is a predictor of changes in real estate prices. The motivation of this study is the possibility to extend the understanding of the extra predictive power of Google search engine query volume of future housing price change (shift direction) by (i) the introduction of a research approach that combines...
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Long-term hindcast simulation of water temperature and salinity in the Baltic Sea
Open Research DataThe 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
Open Research DataThe 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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Fundamenty palowe, obliczenia z zastosowaniem zasad Eurokodu 7 i doświadczeń krajowych
PublicationPrzedstawiono zagadnienia obliczania fundamentów palowych w nawiązaniu do zaleceń Eurokodu 7. Zwrócono uwagę, że zgodnie z założeniami Eurokodu 7, projektant i inżynier ma swobodę w wyborze metod obliczeniowych.Przytoczono i zarekomendowano metody i propozycje miedzy innymi obliczania statycznego układów palowych, określania nośności pali, prognozowania osiadań fundamentów palowych oraz charakterystyk obciążenie-osiadanie pali...
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Predicting Ice Phenomena in a River Using the Artificial Neural Network and Extreme Gradient Boosting
PublicationForecasting 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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ANALYSIS OF POSSIBILITIES FOR THE USE OF VOLUME-DELAY FUNCTIONS IN THE PLANNING MODULE OF THE TRISTAR SYSTEM
PublicationTravel 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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Syntetyczne wskaźniki oceny stanu toru
PublicationJakość geometryczna toru analizowana jest w różnych celach, a dane podlegają różnemu stopniowi agregacji. Pojedyncze nierówności toru analizowane są zazwyczaj z uwagi na bezpieczeństwo i służą do planowanie napraw w krótkich terminach. Natomiast agregacja pomierzonych parametrów pozwala na planowanie robót w terminach średniookresowych i budowę modeli predykcji. W artykule przedstawiono zagregowane wskaźniki jakości geometrycznej...
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A new quantum-inspired approach to reduce the blocking probability of demands in resource-constrained path computation scenarios
PublicationThis 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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GIS Solution for Weather Forecast Data Analysis
PublicationIn 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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Optimized Deep Learning Model for Flood Detection Using Satellite Images
PublicationThe 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
PublicationRNA 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
PublicationComprehensive 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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The Concept of Geodetic Analyses of the Measurement Results Obtained by Hydrostatic Leveling
PublicationThe 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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The Analysis of Patients' Airflow with Respect to Early Detection of Sleep Apnea
PublicationThe 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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Dynamic fracture of brittle shells in a space-time adaptive isogeometric phase field framework
PublicationPhase 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
PublicationThe 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 approach to railway noise modeling employing Genetic Algorithms
PublicationMain 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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Application of Majority Voting Protocols to Supporting Trading Decisions
PublicationA 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
PublicationA 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 type T-Source inverter
PublicationThis 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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Protokół głosowania większościowego w narzędziu wsparcia decyzji handlowych
PublicationIstnieje szerokie spektrum narzędzi i metod wspierających decyzje handlowe, lecz brakuj jasnych reguł ich stosowania. Zaproponowano samoorganizujacy się system agentowy do wspierania decyzji handlowych. System bazując na glosowaniu z dynamicznymi wagami, wskazuje efektywne indykatory na podstawie ich poprzednich osiągnięć. Przedstawiono analizę formalną i wyniki weryfikacji, potwierdzającej cechy rozwiązania.
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Explainable machine learning for diffraction patterns
PublicationSerial 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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Verification of the new viscoelastic method of thermal stress calculation in asphalt layers of pavements
PublicationThe 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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Ship Dynamic Positioning Based on Nonlinear Model Predictive Control
PublicationThe 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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A predictive estimation based control strategy for a quasi-resonant dc-link inverter
PublicationIn 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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Sensorless predictive control of three-phase parallel active filter
PublicationThe 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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New results on estimation bandwidth adaptation
PublicationThe 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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Full scale measurements of pressure field induced on the quay wall by bow thrusters – indirect method for seabed velocities monitoring
PublicationThe 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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News that Moves the Market: DSEX-News Dataset for Forecasting DSE Using BERT
PublicationStock market is a complex and dynamic industry that has always presented challenges for stakeholders and investors due to its unpredictable nature. This unpredictability motivates the need for more accurate prediction models. Traditional prediction models have limitations in handling the dynamic nature of the stock market. Additionally, previous methods have used less relevant data, leading to suboptimal performance. This study...