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Search results for: data stewardship
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Journal of Direct, Data and Digital Marketing Practice
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International Journal of Business Intelligence and Data Mining
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International Journal of Data Analysis Techniques and Strategies
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International Journal of Information Management Data Insights
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Sampling Theory, Signal Processing, and Data Analysis
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Research Data Journal for the Humanities and Social Sciences
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<title>Synchronous optical transmission data link integrated with FPGA for TESLA FEL SIMCON system: long data vector optical transceiver module tests</title>
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Using Isolation Forest and Alternative Data Products to Overcome Ground Truth Data Scarcity for Improved Deep Learning-based Agricultural Land Use Classification Models
PublicationHigh-quality labelled datasets represent a cornerstone in the development of deep learning models for land use classification. The high cost of data collection, the inherent errors introduced during data mapping efforts, the lack of local knowledge, and the spatial variability of the data hinder the development of accurate and spatially-transferable deep learning models in the context of agriculture. In this paper, we investigate...
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Review and comparison of smoothing algorithms for one-dimensional data noise reduction
PublicationThe paper considers the choice of parameters of smoothing algorithms for data denoising. The impact of the window size on smoothing accuracy was analyzed. The parameters of denoising filters were selected with respect to the meansquare error between the computed linear regression and the noisy signal. Finally, we have compared mean, median, SavitzkyGolay, Kalman and Gaussian filter algorithms for the data from the digital sensor....
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Assessing Highway Travel Time Reliability using Probe Vehicle Data
PublicationProbe vehicle data (also known as “floating car data”) can be used to analyze travel time reliability of an existing road corridor in order to determine where, when, and how often traffic congestion occurs at particular road segments. The aim of the study is to find the best reliability performance measures for assessing congestion frequency and severity based on probe data. Pilot surveys conducted on A2 motorway in Poland confirm...
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Multibaem Sonar Records Data Decimation Using Hierarchical Spline Interpolation
PublicationMultibeam sonar records feature high vertical and horizontal resolution. Interpolating and approximating, eventually displaying of of high volume scattered 3D raster data leads to some difficulties related to a computer processing power. The paper presents some advantages of using hierarchical splines in the context. Such an approach facilitates real time 3D MBS data rendering.
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Harmony Search to Self-Configuration of Fault-Tolerant Grids for Big Data
PublicationIn this paper, harmony search algorithms have been proposed to self-configuration of fault-tolerant grids for big data processing. Some tasks related to big data processing have been considered. Moreover, two criteria have been applied to evaluate quality of grids. The first criterion is a probability that all tasks meet their deadlines and the second one is grid reliability. Furthermore, some intelligent agents based on harmony...
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Using Rule-Based System for Monitoring Marine Navigation Data Processing
PublicationProcessing marine navigational data requires sophisticated software solutions. Typically, specialized tools called processors are analyzing raw data from different sensors. It becomes important to create the monitoring software that is able to validate and verify processing components integrated into the final system. Drools®business rule management platform provides a core business rules engine, web authoring and rules management...
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Collective citizens' behavior modelling with support of the Internet of Things and Big Data
PublicationIn this paper, collective human behaviors are modelled by a development of Big Data mining related to the Internet of Things. Some studies under MapReduce architectures have been carried out to improve an efficiency of Big Data mining. Intelligent agents in data mining have been analyzed for smart city systems, as well as data mining has been described by genetic programming. Furthermore, artificial neural networks have been discussed...
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Reconstruction Methods for 3D Underwater Objects Using Point Cloud Data
PublicationExisting methods for visualizing underwater objects in three dimensions are usually based on displaying the imaged objects either as unorganised point sets or in the form of edges connecting the points in a trivial way. To allow the researcher to recognise more details and characteristic features of an investigated object, the visualization quality may be improved by transforming the unordered point clouds into higher order structures....
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URBANIZATION OF METROPOLITAN AREAS – THE IMPORTANCE OF NEW SPATIAL DATA ANALYSIS TOOLS
PublicationNowadays, a rapid development of metropolises is connected with the pressure on urbanizing, which leads to a sharp increase in developed areas as well as urbanized areas. As this trend becomes more dynamic, cities sprawl beyond their administrative boundaries, causing spatial disintegration and hindering sustainable development of a given area. Increased dispersion of residential area results in extensive and chaotic spatial development,...
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Impact of information systems (IS) infusion on Open Government Data (OGD) adoption
PublicationPurpose – This study aims to underline the possible influence of the moderator, information systems (IS) infusion, on Open Government Data (OGD) adoption and usage. Design/methodology/approach – Using the partial least squares-structural equation modeling methodological approach, the adapted unified theory of acceptance and use of technology (UTAUT) model has been used for understanding the role of themoderating variable, namely,...
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Mobilenet-V2 Enhanced Parkinson's Disease Prediction with Hybrid Data Integration
PublicationThis study investigates the role of deep learning models, particularly MobileNet-v2, in Parkinson's Disease (PD) detection through handwriting spiral analysis. Handwriting difficulties often signal early signs of PD, necessitating early detection tools due to potential impacts on patients' work capacities. The study utilizes a three-fold approach, including data augmentation, algorithm development for simulated PD image datasets,...
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Data from the Survey on Gdańsk University of Technology Graduates’ Professional Careers
PublicationThe dataset titled Data from the survey on Gdańsk University of Technology graduates’ professional careers includes data from a survey of Gdańsk University of Technology (Gdańsk Tech) graduates’ professional careers. The survey was conducted in 2017, two years after the respondents obtained graduate status. The research sample included 2553 respondents. The study concerned, i.a. the percentage of people working among graduates...
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A coarse‐grained approach to NMR ‐data‐assisted modeling of protein structures
PublicationThe ESCASA algorithm for analytical estimation of proton positions from coarse-grained geometry developed in our recent work has been implemented in modeling protein structures with the highly coarse-grained UNRES model of polypeptide chains (two sites per residue) and nuclear magnetic resonance (NMR) data. A penalty function with the shape of intersecting gorges was applied to treat ambiguous distance restraints, which automatically...
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Testing the Effect of Bathymetric Data Reduction on the Shape of the Digital Bottom Model
PublicationDepth data and the digital bottom model created from it are very important in the inland and coastal water zones studies and research. The paper undertakes the subject of bathymetric data processing using reduction methods and examines the impact of data reduction according to the resulting representations of the bottom surface in the form of numerical bottom models. Data reduction is an approach that is meant to reduce the size...
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Identification of the Vistula Mounting tower model using measured modal data
PublicationW pracy przedstawiono problem identyfikacji pięcioparametrowego modelu zabytkowej wieży twierdzy Wisłoujście. Poszukiwane parametry wyznaczono jako rozwiązanie problemu minimalizacji błędu średniokwadratowego pomierzonych dwóch pierwszych częstości i pierwszej postaci drgań własnych. Do tego celu wykorzystano hierarchiczną procedurę minimalizacji przy zastosowaniu analizy wrażliwości. Analiza numeryczna potwierdziła efektywność...
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Processing data on sea bottom structure obtained by means of the parametric sounding
PublicationThe aim of the paper is to analyze data obtained during sounding the Gdansk Bay sea bed by means of the parametric echo-sounder. The accuracy of the sea bottom structure investigation needs correct configuration of research equipment and proper calibration of peripheral devices (GPS, heading sensor, MRU-Z motion sensor and navigation instruments which provide necessary data to bathymetrical measurement system, enabling its work...
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System for characterisation and multidimensional imaging of seafloor using multibeam sonar data
PublicationMultibeam sonars are widely used in applications like high resolution bathymetry measurements, underwater object detection and imaging, etc. Also, they are the promising tool in seafloor characterisation and classification, having several advantages over conventional single beam echosounders. The proposed approach to seafloor classification relies on the combined use of three different techniques. In each of them, a set of descriptors...
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Methodology for Processing of 3D Multibeam Sonar Big Data for Comparative Navigation
PublicationAutonomous navigation is an important task for unmanned vehicles operating both on the surface and underwater. A sophisticated solution for autonomous non-global navigational satellite system navigation is comparative (terrain reference) navigation. We present a method for fast processing of 3D multibeam sonar data to make depth area comparable with depth areas from bathymetric electronic navigational charts as source maps during...
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Method for Clustering of Brain Activity Data Derived from EEG Signals
PublicationA method for assessing separability of EEG signals associated with three classes of brain activity is proposed. The EEG signals are acquired from 23 subjects, gathered from a headset consisting of 14 electrodes. Data are processed by applying Discrete Wavelet Transform (DWT) for the signal analysis and an autoencoder neural network for the brain activity separation. Processing involves 74 wavelets from 3 DWT families: Coiflets,...
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Proposition of the methodology for Data Acquisition, Analysis and Visualization in support of Industry 4.0
PublicationIndustry 4.0 offers a comprehensive, interlinked, and holistic approach to manufacturing. It connects physical with digital and allows for better collaboration and access across departments, partners, vendors, product, and people. Consequently, it involves complex designing of highly specialized state of the art technologies. Thus, companies face formidable challenges in the adoption of these new technologies....
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Daily Radiation Budget of the Baltic Sea Surface from Satellite Data
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Use of Satellite Data in Monitoring of Hydrophysical Parameters of the Baltic Sea Environment
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Comparison of Selected Reduction Methods of Bathymetric Data Obtained by Multibeam Echosounder
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Deep Data Analysis of a Large Microarray Collection for Leukemia Biomarker Identification
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Optimization of river network representation data models for web-based systems
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Structural Model of the Bilitranslocase Transmembrane Domain Supported by NMR and FRET Data
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Analysis of Isocratic-Chromatographic-Retention Data using Bayesian Multilevel Modeling
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An Approach to Imbalanced Data Classification Based on Instance Selection and Over-Sampling
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Learning from Imbalanced Data Using Over-Sampling and the Firefly Algorithm
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Impact of Clustering on a Synthetic Instance Generation in Imbalanced Data Streams Classification
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A Comprehensive Framework for Measuring Governments’ Digital Initiatives Including Open Data
PublicationDigital innovation and digital initiatives are generally recognized and considered to be the driving forces behind firm survival and success in the market. This is not the case in the public sector, where digital initiatives have suffered not only from a lack of research trying to explain them but also from a major lack of recognition of their importance. The government’s eagerness to introduce more digital initiatives for better...
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Ecotoxicity and chemical sediment data classification by the useof self-organising maps
PublicationArtykuł dotyczy przedstawiania nowej interpretacji szacowania jakości osadów. To oryginalne podejście bada powiązania między parametrami ekotoksyczności (ostrej i chronicznej) i składnikami chemicznymi (zanieczyszczenia takie jak polichlorowane bifenyle, pestycydy, wielopierścieniowe węglowodory aromatyczne, metale ciężkie) próbek osadów Jeziora Turawskiego (Polska) poprzez zastosowanie samoorganizujących się map (SOM) wobec badanego...
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Data Sampling-Based Feature Selection Framework for Software Defect Prediction
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CMS data processing workflows during an extended cosmic ray run
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<title>Data acquisition module implemented on PCI mezzanine card</title>
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Selection of SOM parameters for the needs of clusterization of data obtained by interferometric methods
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A probabilistic model of ship performance in ice based on full-scale data
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Use of LIDAR Data in the 3D/4D Analyses of the Krakow Fortress Objects
PublicationThe article presents partial results of studies within the framework of the international project "Cultural Heritage Through Time" (CHT2). The subject of the study were forts of the Krakow Fortress, which had been built by the Austrians between 1849-1914 in order to provide defence against the Russians. Research works were aimed at identifying architectural changes occurring in different time periods in relation to selected...
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Considerations and consequences of allowing DNA sequence data as types of fungal taxa
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Disk space allocation schemes for real-time data gathering applications
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Low-Level Aerial Photogrammetry as a Source of Supplementary Data for ALS Measurements
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A Comparison Study of Strategies for Combining Classifiers from Distributed Data Sources
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Stacking and rotation-based technique for machine learning classification with data reduction
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