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Search results for: PLIKI CLDATA
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Using LSTM networks to predict engine condition on large scale data processing framework
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A Data Driven Model for Predicting RNA-Protein Interactions based on Gradient Boosting Machine
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A Regular Expression Matching Application with Configurable Data Intensity for Testing Heterogeneous HPC Systems
PublicationModern High Performance Computing (HPC) systems are becoming increasingly heterogeneous in terms of utilized hardware, as well as software solutions. The problems, that we wish to efficiently solve using those systems have different complexity, not only considering magnitude, but also the type of complexity: computation, data or communication intensity. Developing new mechanisms for dealing with those complexities or choosing an...
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Multivariate analysis of impedance data obtained for coating systems of varying thickness applied on steel
PublicationElectrochemical impedance spectroscopy (EIS) has proven to be a valuable test method for the electrochemical characterization of protective coatings on metals. The common way of analysis in impedance spectroscopy is to model the impedance spectrum by means of an equivalent circuit and to extract the quantity of interest using optimization techniques. A model, corresponding to the behavior of the sample under testing, is important...
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Application of multisensoral remote sensing data in the mapping of alkaline fens Natura 2000 habitat
PublicationThe Biebrza River valley (NE Poland) is distinguished by largely intact, highly natural vegetation patterns and very good conservation status of wetland ecosystems. In 20132014, studies were conducted in the upper Biebrza River basin to develop a remote sensing method for alkaline fen classification a protected Natura 2000 habitat (code 7230) using remote sensing technologies. High resolution airborne true colour (RGB) and...
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Advances in Architectures, Big Data, and Machine Learning Techniques for Complex Internet of Things Systems
PublicationTe feld of Big Data is rapidly developing with a lot of ongoing research, which will likely continue to expand in the future. A crucial part of this is Knowledge Discovery from Data (KDD), also known as the Knowledge Discovery Process (KDP). Tis process is a very complex procedure, and for that reason it is essential to divide it into several steps (Figure 1). Some authors use fve steps to describe this procedure, whereas others...
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Influence of YARN Schedulers on Power Consumption and Processing Time for Various Big Data Benchmarks
PublicationClimate change caused by human activities can influence the lives of everybody onthe planet. The environmental concerns must be taken into consideration by all fields of studyincludingICT. Green Computing aims to reduce negative effects of IT on the environment while,at the same time, maintaining all of the possible benefits it provides. Several Big Data platformslike Apache Spark orYARNhave become widely used in analytics and...
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Floodplain inundation Mapping using SAR Scattering Coefficient Thresholding and Observed Discharge Data
PublicationInundation area time series are important for wetlands monitoring and hydrological model validation. This study is conducted in Biebrza floodplain, which is a natural wetland with complex inundation generation processes. In order to map 2014-2018 series of inundation in the floodplain we test our automatic thresholding method on Sentinel 1 data. The threshold value is optimized using correlation of the inundation area with observed...
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Fast synchronous distribution network of data streams for RPC Muon Trigger in CMS experiment
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Changes in the addiction prevalence in Polish population between 1990-2019: Review of available data
PublicationThe 1989 collapse of the socialist political system in Poland initiated an avalanche of modifications regarding healthcare policy resulting with new institutions and programs dedicated to monitoring and preventing addiction. In the current article, we look at the available data allowing to track changes in (1) the prevalence of exposure to addictive substances and behaviors, and (2) changes of addictions prevalence in Poland...
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The application of Local Indicators for Categorical Data (LICD) to explore spatial dependence in archaeological spaces
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MAPSERVER – INFORMATION FLOW MANAGEMENT SOFTWARE FOR THE BORDER GUARD DISTRIBUTED DATA EXCHANGE SYSTEM
PublicationIn this paper the architecture of the software designed for management of position and identification data of floating and flying objects in Maritime areas controlled by Polish Border Guard is presented. The software was designed for managing information stored in a distributed system with two variants of the software, one for a mobile device installed on a vessel, an airplane or a car and second for a central server. The details...
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Global Value Chains and Wages: International Evidence from Linked Worker-Industry Data
PublicationUsing a rich dataset on over 110,000 workers from nine European countries and the USA we study the wage response to industry dependence on foreign value added. We estimate a Mincerian wage model augmented with an input-output interindustry linkages measure accounting for task heterogeneity across workers. Low and mediumeducated workers and those performing routine tasks experience (little) wage decline due to major dependency of...
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The structure of the data flow in integrated urban traffic management systems – the case of TRISTAR system
PublicationThe purpose of the article is to offer some insight into the data flow architecture in the Tri-City’s integrated traffic management system called TRISTAR. To that end selected elements of TRISTAR are identified and described as well as the structure for collecting and exchanging data within different sub-systems. Finally, the article highlights how the TRISTAR system can be extended by adding new elements and modules.
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Interactive visualization of marine pollution monitoring and forecasting data via a Web-based GIS
PublicationArtykuł prezentuje zastosowanie sieciowego Systemu Informacji Geograficznej do monitoringu i prezentacji wyników modelowania plam ropy na morzu. Omawiany system wykorzystuje technologie ESRI ArcIMS (Arc Internet Map Server) oraz Open Source GeoServer z biblioteką klienta OpenLayers w celu wizualizacji i mapowania rozprzestrzeniania się wycieku ropy w dwóch wybranych obszarach Morza Egejskiego w Grecji. Przedstawiony GIS stanowi...
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Monitoring Parkinson's disease patients employing biometric sensors and rule-based data processing
PublicationArtykuł prezentuje automatyczny system wykrywania pogorszenia zdrowia pacjentów z chorobą Parkinsona opracowany w ramach projektu PERFORM.The paper presents how rule-based processing can be applied to automatically evaluate the motor state of Parkinson's Disease patients. Automatic monitoring of patients by using biometric sensors can provide assessment of the Parkinson's Disease symptoms. All data on PD patients' state are compared...
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3D seafloor reconstruction using data from side scan and synthetic aperture sonar
PublicationSide scan and synthetic aperture sonars are widely used imaging systems in the underwater environment. They are relatively cheap and easy to deploy, in comparison with more powerful sensors, like multibeam echosounders. Although side scan and synthetic aperture sonars does not provide seafloor bathymetry directly, their records are finally related to seafloor images. Moreover, the analysis of such images performed by human eye...
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Reduction of measurement data before Digital Terrain Model generation vs. DTM generalisation
PublicationModern data acquisition technologies provide large datasets that are not always necessary in its entirety to properly accomplish the goal of the study. In addition, such datasets are often cumbersome for rational processing, and their processing is time and labour consuming. Therefore, methods that enable to reduce the size of the measurement dataset, such as the generalization of the Digital Terrain Model (DTM) or the reduction...
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Evaluation of the efficiency of the duty cycle of refuse collection vehicle based on real-world data
PublicationIn this paper a method of the efficiency evaluation of the duty cycle of Refuse Collection Vehicle is presented. Using real world data, two representative duty cycles were analysed. Total cycle efficiency was calculated, as well as the efficiency of particular cycle phases. Then, energy needed to collect and compact the waste and energy from fuel were compared. Measured and calculated values were shown on the diagrams illustrating...
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Energetic model of hydraulic system of refuse collection vehicle based on simulation and experimental data
PublicationThis paper presents an energetic model of hydraulic system of a refuse collection vehicle. First, benefits resulting from implementation of an energetic model in the industry and operation of a Refuse Collection Vehicle are briefly explained. Then, components of the energy consumption in hydraulic circuits of compactor and lifting device are described and combined into a comprehensive model that can be evaluated using basic measurement...
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Deduplication of Position Data and Global Identification of Objects Tracked in Distributed Vessel Monitoring System
PublicationVessel monitoring systems (VMS) play a very important role in safety navigation. In most cases, their structure is distributed and they are based on two data sources, namely Automatic Identification System (AIS) and Automatic Radar Plotting Aids (ARPA). Such approach results in several objects identification and position data duplication problems, which need to be solved in order to ensure the correct performance of a given VMS....
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Estimating the Average Speed of Public Transport Vehicles Based on Traffic Control System Data
PublicationIntelligent Transport Systems are a valuable source of traffic information, covering both private and public vehicles. The main problem, however, is that very few studies are conducted to determine the speed of buses, trams and trolleys in urban networks in relation to traffic conditions. The paper investigates how ITS systems data could be used to model the speed of Public Transport vehicles. This is now possible thanks to the...
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Deduplication of Tracked Objects Position Data at Single Observation Point of a Vessel Monitoring System
PublicationVessel Monitoring System (VMS) play a major role in safety navigation. In most cases they are based on two data sources, namely Automatic Identification System (AIS) and Automatic Radar Plotting Aids (ARPA). Integration of data obtained from these sources is an important problem, which needs to be solved in order to ensure the correct performance of a given VMS. In this paper basic functions which should be implemented in a tracked...
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Analysis of Transformation Methods of Hydroacoustic and Optoelectronic Data Based on the Tombolo Measurement Campaign in Sopot
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SCRAMBLE’N’GAMBLE: a tool for fast and facile generation of random data for statistical evaluation of QSAR models
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Documenting the de-identification process of clinical and imaging data for AI for health imaging projects
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New implementation of data standards for AI research in precision oncology. Experience from EuCanImage
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A Comparison between MD and EXAFS extracted Structural Data for TernaryRbBr(1-x)Ix.
PublicationStrukturę trójskładnikowych soli poddano analizie za pomocą metody EXAFS i symulacji M-D. Przedyskutowano przydatność używanego w symulacjach potencjału oddziaływań międzyatomowych.
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Ensemble Online Classifier Based on the One-Class Base Classifiers for Mining Data Streams
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Improved calculation of damage due creep by more accurate time to rupture data representation
PublicationReguła Robinsona (Linear Life Fraction Damage Rule) jest stosunkowo łatwa w użyciu dla różnorodnych warunków obciążenia. Z tego powodu jest ona powszechnie akceptowana i używana. Potencjalne możliwości poprawy dokładności obliczeń tą metodą daje zastosowanie specjalnych funkcji do aproksymacji wyników badań wytrzymałości czasowej. W pracy zaproponowano zastosowanie funkcji typu Spline oraz bardzo elastycznej funkcji Spline3D do...
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Condition monitoring and fault detection in wind turbines based on cointegration analysis of SCADA data
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On Cointegration Analysis for Condition Monitoring and Fault Detection of Wind Turbines Using SCADA Data
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Condition monitoring of wind turbines based on cointegration analysis of gearbox and generator temperature data
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Impact of the Time Window Length on the Ship Trajectory Reconstruction Based on AIS Data Clustering
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Environmental Factors and the Risk of Developing Type 1 Diabetes—Old Disease and New Data
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Issue of quality and reliability of spatial records information in the context of data concerning boundary points
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Parametric versus nonparametric modelling of dynamic susceptibility contrast enhanced MRI based data
PublicationDynamic tracking of a bolus of a paramagnetic agent (dynamic susceptibility contract - DSC) in MRI (magnetic resonance imaging) measurements is successfully used for assessment of the tissue perfusion and the other features and functions of the brain (i.e. cerebral blood flow - CBF, cerebral blood volume - CBV, mean transit time - MTT). The parametric and nonparametric approaches to the identification of MRI models are presented...
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Perception-based data processing in acoustics. Applications to music information retrieval and psychophysiology of hearing.
PublicationTematyka książki obejmuje w pierwszej kolejności opis mechanizmów kognitywnych leżących u podstaw percepcji muzyki. Przedstawione zostały również zagadnienia automatycznego rozpoznawania dźwięków instrumentów muzycznych i muzyki, zastosowanie nowych metod z dziedziny sztucznej inteligencji w szeroko rozumianej inżynierii dźwięku oraz komputerowych metod badania słuchu.
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Game theory-based virtual machine migration for energy sustainability in cloud data centers
PublicationAs the demand for cloud computing services increases, optimizing resource allocation and energy consumption has become a key factor in achieving sustainability in cloud environments. This paper presents a novel approach to address these challenges through an optimized virtual machine (VM) migration strategy that employs a game-theoretic approach based on particle swarm optimization (PSO) (PSO-GTA). The proposed approach leverages...
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A strategy for GPS data processing in a precise local network during high solar activity
PublicationThis paper presents the analyses connected with reduction of errors from ionospheric refraction using GPS data from local satellite networks. This is particularly essential during rising solar activity. The Bernese GPS Software v. 4.2 was used, as an analytical tool. The test data included measurements from a geodynamic network SUDETES situated in the Sudety Mountains across the border between the Czech Republic and Poland. A local...
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Research and analysis of high-speed data transmission radio link designed for maritime environment
PublicationIn these article the realization of digital radio link for high-speed data transmission was presented. Its concept and practical realization, using USRP devices from National Instruments, were described. Developed software for generation and reception of digital signals in baseband, including description of modulation types, and time and frequency synchronization mechanisms, was presented. Moreover, an operation of designed radio...
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Research and Analysis of High-Speed Data Transmission Radio Link Designed for Maritime Environment
PublicationIn these article, the realization of digital radio link for high-speed data transmission was presented. Its concept and practical realization, using USRP devices from National Instruments, were described. Developed software for generation and reception of digital signals in baseband, including description of modulation types, and time and frequency synchronization mechanisms, was presented. Moreover, an operation of designed radio...
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Data-Driven Surrogate-Assisted Optimization of Metamaterial-Based Filtenna Using Deep Learning
PublicationIn this work, a computationally efficient method based on data driven surrogate models is pro-posed for the design optimization procedure of a Frequency Selective Surface (FSS)-based filtering antenna (Filtenna). A Filtenna acts as a as module that simultaneously pre-filters unwanted sig-nals, and enhances the desired signals at the operating frequency. However, due to a typically large number of design variables of FSS unit elements,...
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Towards High-Value Datasets Determination for Data-Driven Development: A Systematic Literature Review
PublicationOpen government data (OGD) is seen as a political and socio-economic phenomenon that promises to promote civic engagement and stimulate public sector innovations in various areas of public life. To bring the expected benefits, data must be reused and transformed into value-added products or services. This, in turn, sets another precondition for data that are expected to not only be available and comply with open data principles,...
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Wyróżnienie HR dla PG od Komisji Europejskiej na następne trzy lata
PublicationArtykuł powstał, by poinformować o wyróżnienie HR Excellence in Research, które Komisja Europejska przyznała Politechnice Gdańskiej na kolejne trzy lata - do 2026 r. oraz działaniach podejmowanych w ramach Strategii HR4R PG 2022-2025. Prawo do posługiwania się Logo HR przyznawane jest instytucjom, które działają na rzecz zwiększania atrakcyjności warunków pracy i rozwoju kariery pracowników naukowych.
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Novel Fault Identification for Electromechanical Systems via Spectral Technique and Electrical Data Processing
PublicationIt is proposed, developed, investigated, and validated by experiments and modelling for the first time in worldwide terms new data processing technologies, higher order spectral multiple correlation technologies for fault identification for electromechanical systems via electrical data processing. Investigation of the higher order spectral triple correlation technology via modelling has shown that the proposed data processing technology...
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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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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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COVID-19 severity forecast based on machine learning and complete blood count data
PublicationProper triage of COVID-19 patients is a key factor in eective case management, especially with limited and insucient resources. In this paper, we propose a machine-aided diagnostic system to predict how badly a patient with COVID-19 will develop disease. The prognosis of this type is based on the parameters of commonly used complete blood count tests, which makes it possible to obtain data from a wide range of patients.We chose...
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COVID-19 severity forecast based on machine learning and complete blood count data
PublicationProper triage of COVID-19 patients is a key factor in eective case management, especially with limited and insucient resources. In this paper, we propose a machine-aided diagnostic system to predict how badly a patient with COVID-19 will develop disease. The prognosis of this type is based on the parameters of commonly used complete blood count tests, which makes it possible to obtain data from a wide range of patients.We chose...