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Search results for: DATA
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Different philosophical approaches to estimating missing data in AHP frameworks for uncertainty representation in risk assessments
PublicationAHP (ang. Analytic Hierarchy Process) jest jedną z metod szeroko stosowaną w wieloatrybutowym podejmowaniu decyzji. Zwykle ekspert lub grupa ekspertów jest proszona o wyrażenie swojej subiektywnej opinii o każdej z par wariantów decyzyjnych. Na tej podstawie tworzone są tzw. macierze ocen. Zdarza się często, że macierze takie są niekompletne i wtedy występuje problem brakujących danych. Referat dotyczy wybranych metod ich uzupełnienia.
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Evaluation of water turbine hydrodynamic thrust bearing performance on the basis of thermoelastohydrodynamic calculations and operational data.
PublicationW pracy przedstawiono analizę konstrukcji łożyska wzdłużnego turbiny wodnej. Łożysko zostało skonstruowane około 50 lat temu, a jego konstrukcja przewiduje kompensację termicznych odkształceń klocków. W analizie uwzględniono odkształcenia łożyska i wymianę ciepła w filmie smarowym i klockach łożyskowych. Poza obecną konstrukcją łożyska przeprowadzono również studium wpływu podstawowych parametrów konstrukcyjnych: grubości klocka...
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Global Value Chains and Wages: Multi-Country Evidence from Linked Worker-Industry Data
PublicationThis paper uses a multi-country microeconomic setting to contribute to the literature on the nexus between production fragmentation and wages. Exploiting a rich dataset on over 110,000 workers from nine Eastern and Western European countries and the United States, we study the relationship between individual workers’ wages and industry ties into global value chains (GVCs). We find an inverse (but weak) relationship between the...
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Determinants of COVID-19 Impact on the Private Sector: A Multi-Country Analysis Based on Survey Data
PublicationOur paper aims to investigate the impact of COVID‐19 on private sector companies in terms of sales, production, finance and employment. We check whether the country and industry in which companies operate, government financial support and loan access matter to the behaviour and performances of companies during the pandemic. We use a microdata set from a worldwide survey of more than 15,729 companies conducted between April and...
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IV Pomorska Konferencja Open Science - udostępnianie danych badawczych (sharing research data)
EventsTematyka Otwartej Nauki jest coraz bardziej rozpowszechniona. Zarówno udostępnianie wyników badań w postaci publikacji jak i danych badawczych jest coraz częściej wymogiem instytucji i agencji finansujących badania naukowe. Tworzone są liczne rekomendacje, dobre praktyki i polityki w zakresie wprowadzania otwartego dostępu. Celem konferencji jest zebranie...
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ACM Journal of Data and Information Quality
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Advances in Modelling and Analysis B: Signals, Information, Data, Patterns
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The Central European GNSS Research Network (CEGRN) dataset
PublicationThe Central European GNSS Research Network (CEGRN) collects GNSS data since 1994 from contributors which today include 42 Institutions in 33 Countries. CEGRN returns a dataset of coordinates and velocities computed according to international standards and the most recent processing procedures and recommendations. We provide a dataset of 1229 positions and velocities resulting from 3 or more repetitions of coordinate measurements...
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High resolution optical and acoustic remote sensing datasets of the Puck Lagoon
PublicationThe very shallow marine basin of Puck Lagoon in the southern Baltic Sea, on the Northern coast of Poland, hosts valuable benthic habitats and cultural heritage sites. These include, among others, protected Zostera marina meadows, one of the Baltic’s major medieval harbours, a ship graveyard, and likely other submerged features that are yet to be discovered. Prior to this project, no comprehensive high-resolution remote sensing...
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Data Mining Path
e-Learning CoursesWithin this path, various issues regarding data mining and their practical application in various systems are discussed. 4 semestr specjalności ISI i ZAD
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Reversible Data Hiding in Encrypted DICOM Images Using Cyclic Binary Golay (23, 12) Code
PublicationIn this paper, a novel reversible data hiding method for encrypted images (RDHEI) is proposed. An efficient coding scheme based on cyclic binary Golay (23, 12) code is designed to embed additional data into the least significant bits (LSBs) of the encrypted image. The most significant bits (MSBs) are used to ensure the reversibility of the embedding process. The proposed scheme is lossless, and based on the receiver’s privileges,...
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A Novel Spatio–Temporal Deep Learning Vehicle Turns Detection Scheme Using GPS-Only Data
PublicationWhether the computer is driving your car or you are, advanced driver assistance systems (ADAS) come into play on all levels, from weather monitoring to safety. These modern-day ADASs use various assisting tools for drivers to keep the journey safe; these sophisticated tools provide early signals of numerous events, such as road conditions, emerging traffic scenarios, and weather warnings. Many urban applications, such as car-sharing...
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A model, design, and implementation of an efficient multithreaded workflow execution engine with data streaming, caching, and storage constraints
PublicationThe paper proposes a model, design, and implementation of an efficient multithreaded engine for execution of distributed service-based workflows with data streaming defined on a per task basis. The implementation takes into account capacity constraints of the servers on which services are installed and the workflow data footprint if needed. Furthermore, it also considers storage space of the workflow execution engine and its cost....
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Big Data 2023
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Data quality assurance
e-Learning CoursesThe first lecture: 22.02.2021 at 8:15 on Teams Pierwszy wykład: 22.02.2021 o 8:15 w Teams ---------------------------------------------- Kierunek: Inżynieria danych (WETI) Studia I stopnia - inżynierskie, stacjonarne, semestr 6
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Variable Data Structures and Customized Deep Learning Surrogates for Computationally Efficient and Reliable Characterization of Buried Objects
PublicationIn this study, in order to characterize the buried object via deep-learning-based surrogate modeling approach, 3-D full-wave electromagnetic simulations of a GPR model has been used. The task is to predict simultaneously and independent of each characteristic parameters of a buried object of several radii at different positions (depth and lateral position) in various dispersive subsurface media. This study has analyzed variable...
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Big Data from Sensor Network via Internet of Things to Edge Deep Learning for Smart City
PublicationData from a physical world is sampled by sensor networks, and then streams of Big Data are sent to cloud hosts to support decision making by deep learning software. In a smart city, some tasks may be assigned to smart devices of the Internet of Things for performing edge computing. Besides, a part of workload of calculations can be transferred to the cloud hosts. This paper proposes benchmarks for division tasks between an edge...
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Investigation of Parallel Data Processing Using Hybrid High Performance CPU + GPU Systems and CUDA Streams
PublicationThe paper investigates parallel data processing in a hybrid CPU+GPU(s) system using multiple CUDA streams for overlapping communication and computations. This is crucial for efficient processing of data, in particular incoming data stream processing that would naturally be forwarded using multiple CUDA streams to GPUs. Performance is evaluated for various compute time to host-device communication time ratios, numbers of CUDA streams,...
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Wave Method for Structural Health Monitoring: Testing Using Full-Scale Shake Table Experiment Data
PublicationAn algorithm of the wave method for structural health monitoring (SHM) is tested and calibrated using shake table experiment data of a full-scale, seven-story, reinforced-concrete building slice. The method is based on monitoring changes in the velocity of waves propagating vertically through the structure, identified by least-squares (LSQ) fit of beam models. The experiment was conducted by a team from the University of California,...
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Ontological Modeling for Contextual Data Describing Signals Obtained from Electrodermal Activity for Emotion Recognition and Analysis
PublicationMost of the research in the field of emotion recognition is based on datasets that contain data obtained during affective computing experiments. However, each dataset is described by different metadata, stored in various structures and formats. This research can be counted among those whose aim is to provide a structural and semantic pattern for affective computing datasets, which is an important step to solve the problem of data...
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Application of COSMO-RS-DARE as a Tool for Testing Consistency of Solubility Data: Case of Coumarin in Neat Alcohols
PublicationCoumarin is a naturally occurring lactone-type benzopyrone with various applications in the pharmaceutical, food, perfume, and cosmetics industries. This hydrophobic compound is poorly soluble in water but dissolves well in protic organic solvents such as alcohols. Despite the extensive use of coumarin, there are only a few reports documenting its solubility in organic solvents, and some reported data are incongruent, which...
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A Fail-Safe NVRAM Based Mechanism for Efficient Creation and Recovery of Data Copies in Parallel MPI Applications
PublicationThe paper presents a fail-safe NVRAM based mechanism for creation and recovery of data copies during parallel MPI application runtime. Specifically, we target a cluster environment in which each node has an NVRAM installed in it. Our previously developed extension to the MPI I/O API can take advantage of NVRAM regions in order to provide an NVRAM based cache like mechanism to significantly speed up I/O operations and allow to preload...
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Researching Digital Society: Using Data-Mining to Identify Relevant Themes from an Open Access Journal
PublicationOpen Access scholarly literature is scientific output free from economic barriers and copyright restrictions. Using a case study approach, data mining methods and qualitative analysis, the scholarly output and the meta-data of the Open Access eJournal of e-Democracy and Open Government during the time interval 2009–2020 was analysed. Our study was able to identify the most prominent research topics (defined as thematic clusters)...
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Researching Digital Society: Using Data-Mining to Identify Relevant Themes from an Open Access Journal
PublicationOpen Access scholarly literature is scientific output free from economic barriers and copyright restrictions. Using a case study approach, data mining methods and qualitative analysis, the scholarly output and the meta-data of the Open Access eJournal of e-Democracy and Open Government during the time interval 2009–2020 was analysed. Our study was able to identify the most prominent research topics (defined as thematic clusters)...
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Heavy Duty Vehicle Fuel Consumption Modelling Based on Exploitation Data by Using Artificial Neural Networks
PublicationOne of the ways to improve the fuel economy of heavy duty trucks is to operate the combustion engine in its most efficient operating points. To do that, a mathematical model of the engine is required, which shows the relations between engine speed, torque and fuel consumption in transient states. In this paper, easy accessible exploitation data collected via CAN bus of the heavy duty truck were used to obtain a model of a diesel...
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MATCHED FILTER APPROACH FOR MICROSEISMIC SIGNAL PROCESSING OF REAL DATA FROM EAST POMERANIA SHALE GAS
PublicationThe microseismic monitoring is a method of monitoring of fracture propagation during hydraulic fracturing (HF)process. An array of several hundred geophones is placed on the surface to record little ground tremors induced by fracturing process. Filtration and summation of signals from geophones is essential to identify and locate fracturing events from underground. Authors propose a method of matched filtering, that is usually...
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Reliable OFDM Data Transmission with Pilot Tones and Error-Correction Coding in Shallow Underwater Acoustic Channel
PublicationThe performance of Underwater Acoustic Communication (UAC) systems are strongly related to the specific propagation conditions of the underwater channel. Horizontal, shallow-water channels are characterised by extremely disadvantageous transmission properties, due to strong multipath propagation and refraction phenomena. The paper presents the results of communication tests performed during a shallow, inland-water experiment with...
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Application of data driven methods in diagnostic of selected process faults of nuclear power plant steam turbine
PublicationArticle presents a comparison of process anomaly detection in nuclear power plant steam turbine using combination of data driven methods. Three types of faults are considered: water hammering, fouling and thermocouple fault. As a virtual plant a nonlinear, dynamic, mathe- matical steam turbine model is used. Two approaches for fault detection using one class and two class classiers are tested and compared.
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Seafloor characterisation using multibeam data: sonar image properties, seabed surface properties and echo properties
PublicationIn the paper, the approach to seafloor characterisation is presented. The multibeam sonars, besides their well verified and widely used applications like high resolution bathymetry and underwater object detection and imaging, are also the promising tool in seafloor characterization and classification, having several advantages over conventional single beam echosounders. The proposed approach relies on the combined, concurrent use...
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Data-driven models for fault detection using kernel pca:a water distribution system case study
PublicationKernel Principal Component Analysis (KPCA), an example of machine learning, can be considered a non-linear extension of the PCA method. While various applications of KPCA are known, this paper explores the possibility to use it for building a data-driven model of a non-linear system-the water distribution system of the Chojnice town (Poland). This model is utilised for fault detection with the emphasis on water leakage detection....
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High Resolution Sea Ice Floe Size and Shape Data from Knox Coast, East Antarctica
PublicationThis dataset contains floe size distribution data from a very high resolution (pixel size: 0.3 m) optical satellite image of sea ice, acquired on 16 Feb. 2019 off the Knox Coast (East Antarctica). The image shows relatively small ice floes produced by wave-induced breakup of landfast ice between Mill Island and Bowman Island. The ice floes are characterised by a narrow size distribution and angular, polygonal shapes, typical...
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Reliable data-driven modeling of high-frequency structures by means of nested kriging with enhanced design of experiments
PublicationData-driven (or approximation) surrogate models have been gaining popularity in many areas of engineering and science, including high-frequency electronics. They are attractive as a way of alleviating the difficulties pertinent to high computational cost of evaluating full-wave electromagnetic (EM) simulation models of microwave, antenna, and integrated photonic components and devices. Carrying out design tasks that involve massive...
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Application of Msplit method for filtering airborne laser scanning data sets to estimate digital terrain models
PublicationALS point cloud filtering involves the separation of observations representing the physical terrain surface from those representing terrain details. A digital terrain model (DTM) is created from a subset of points representing the ground surface. The accuracy of the generated DTM is influenced by several factors, including the survey method used, the accuracy of the source data, the applied DTM generation algorithm, and the survey...
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Analysis of effect of overloaded vehicles on fatigue life of flexible pavements based on weigh in motion (WIM) data
PublicationOverloaded vehicles have a significant impact on pavement fatigue life and distress. As the studies show, the phenomena intensify when the control of traffic is poor. The paper presents the results of the research including analysis of weigh in motion data from eight stations and analysis of asphalt pavement fatigue caused by mixed traffic. Distributions of vehicles axles load including the multiple axles effects are presented....
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Investigation of the 16-year and 18-year ZTD Time Series Derived from GPS Data Processing
PublicationThe GPS system can play an important role in activities related to the monitoring of climate. Long time series, coherent strategy, and very high quality of tropospheric parameter Zenith Tropospheric Delay (ZTD) estimated on the basis of GPS data analysis allows to investigate its usefulness for climate research as a direct GPS product. This paper presents results of analysis of 16-year time series derived from EUREF Permanent Network...
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NLITED - New Level of Integrated Techniques for Daylighting Education: Preliminary Data on the Use of an E-learning Platform
PublicationProject NLITED – New Level of Integrated Techniques for Daylighting Education - is an educational project for students and professionals. The project's objective is to create and develop an online eLearning platform with 32 eModules dedicated to daylight knowledge. The project also offers e-learners two summer school training where the theory is put into practice. The platform was launched on January 31, 2022. The paper...
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TRANSPORT POSSIBILITY FOR MPEG-4/AVC- AND MPEG-2-ENCODED VIDEO DATA IN IPTV: A COMPARISON STUDY
PublicationIPTV (Television over IP) is a modern service with a great potential to expand. It uses the IP transport platform, that is already in worldwide operation. At the time of writing, two techniques are used to transport the video and audio data of IPTV: MPEG-2 TS and Native RTP. The two techniques quite definitely have an influence on both quality of service (QoS) and quality of experience (QoE). This paper sets out to demonstrate...
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Minimizing Distribution and Data Loading Overheads in Parallel Training of DNN Acoustic Models with Frequent Parameter Averaging
PublicationIn the paper we investigate the performance of parallel deep neural network training with parameter averaging for acoustic modeling in Kaldi, a popular automatic speech recognition toolkit. We describe experiments based on training a recurrent neural network with 4 layers of 800 LSTM hidden states on a 100-hour corpora of annotated Polish speech data. We propose a MPI-based modification of the training program which minimizes the...
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<title>Data quality management system (DQMS) for BAC detector in the ZEUS experiment at the HERA accelerator</title>
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Comparison of selected clustering algorithms of raw data obtained by interferometric methods using artificial neural networks
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Methotrexate Decreases the Level of PCSK9—A Novel Indicator of the Risk of Proatherogenic Lipid Profile in Psoriasis. The Preliminary Data
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Investigating impacts of asphalt mixture properties on pavement performance using LTPP data through random forests
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Spatial and Temporal Variability of Moisture Condition in Soil-Plant Environmet using Spectral Data and GIS Tools
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Ephemeral wetland communities of Isoëto-Nano-Juncetea class – new data from south-eastern Poland
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Comprehensive Analysis of MILE Gene Expression Data Set Advances Discovery of Leukaemia Type and Subtype Biomarkers
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Instrumented end notched flexure - Crack propagation and process zonemonitoring Part II: Data reduction and experimental
PublicationA mode II instrumented end notched flexure three point bending (ENF) adhesion test is described. The adhesive joint consists of two aluminium alloy (AW7075-T6) plates bonded with a structural epoxy adhesive (Hysol EA 9395™). Strain gauges are attached to the outer surface (backface) of the substrates in the lengthwise direction to measure local surface strain during crack propagation. Simultaneously, load/displacement measurements...
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Data-Centric Dempster-Shafer Theory-Based Selfishness Thwarting via Trust Evaluation in MANETs and WSNs
PublicationPrzedstawiono ramy wymiany informacji reputacyjnej pomiędzy terminalami sieci mobilnej ad hoc lub sensorowej, prowadzące do efektywnej lokalizacji terminali egoistycznych i jednocześnie zapobiegające skutkom fałszywych rekomendacji. Integrację miar zaufania i rekomendacji reputacyjnych oparto na teorii Dempstera-Shafera.
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Determinants of inward FDI into Visegrad countries: empirical evidence based on panel data for the years 2000–2012
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Data-driven models for fault detection using kernel PCA: A water distribution system case study
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O-43 Data-driven selection of active iEEG channels during verbal memory task performance
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