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Search results for: missing data prediction
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Methods of data extraction from sub-bottom profiler's signal
PublicationData obtain during sounding Gdansk Bay with SES-2000 Standard parametric sub-bottom profiler has two types of information: envelope and pure signal. First is used to plot echograms in real time and contain envelope of echo. The second one is stored during sounding and can be processed after recording data. Comparison of results will be shown and discussed. First step in investigation was proper configuration of small measurement...
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Cache service for maps presentation in distributed information data exchange system
PublicationThe paper presents the proposition of caches implementation for map presentation in distributed information data exchange system. The concept of cache service is described in the context of distributed information data exchange system elements which control and present on maps positions and other identification data of vessels and other suspicious objects on the territorial sea, sea-coast and the internal sea-waters. The proposed...
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Automatic Clustering of EEG-Based Data Associated with Brain Activity
PublicationThe aim of this paper is to present a system for automatic assigning electroencephalographic (EEG) signals to appropriate classes associated with brain activity. The EEG signals are acquired from a headset consisting of 14 electrodes placed on skull. Data gathered are first processed by the Independent Component Analysis algorithm to obtain estimates of signals generated by primary sources reflecting the activity of the brain....
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Assessing the failure of Open Government Data initiatives in Brazil
PublicationWhile assessing the potential of a particular digital innovation initiative, especially when it has implications for a range of societal stakeholders, it becomes pertinent to understand the possible bottlenecks in its acceptability as well. In this regard, the present study seeks to understand how the Open Government Data (OGD) initiatives in Brazil are being confronted with bottlenecks in terms of their execution and acceptability....
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Graph Neural Networks and Structural Information on Ionic Liquids: A Cheminformatics Study on Molecular Physicochemical Property Prediction
PublicationIonic liquids (ILs) provide a promising solution in many industrial applications, such as solvents, absorbents, electrolytes, catalysts, lubricants, and many others. However, due to the enormous variety of their structures, uncovering or designing those with optimal attributes requires expensive and exhaustive simulations and experiments. For these reasons, searching for an efficient theoretical tool for finding the relationship...
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Multibeam Sonar Characterisation of Seafloor in the Context of Visualisation and Dissemination of Marine Data
PublicationThe paper presents the seafloor characterisation method based on multibeam sonar data. it relies on using three types of multibeam seafloor sensing data: 1) the grey-level sonar images (echograms) of seabed, 2) the 3D model of the seabed surface which consists of high resolution bathymetric data, 3) the set of time domain bottom echo envelopes received in the consecutive sonar beams. The classification is performed by utilisation...
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Early Oceanographical Data Collected by the Institute of Oceanography, University of Gdańsk
PublicationThree data sets entitled Water currents in Głębinka Passage in late spring of 1975, Hydrometeorological and hydrochemical conditions in the Gulf of Gdańsk in the vicinity of Vistula river mouth in July of 1977, and Gulf of Gdańsk monitoring conducted by the Institute of Oceanography, University of Gdańsk, in 1981–1994 contain archival field measurement results from the Gulf of Gdańsk (the southern Baltic). The data can be used...
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Data augmentation for improving deep learning in image classification problem
PublicationThese days deep learning is the fastest-growing field in the field of Machine Learning (ML) and Deep Neural Networks (DNN). Among many of DNN structures, the Convolutional Neural Networks (CNN) are currently the main tool used for the image analysis and classification purposes. Although great achievements and perspectives, deep neural networks and accompanying learning algorithms have some relevant challenges to tackle. In this...
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Model of an Integration Bus of Data and Ontologies of Smart Cities Processes
PublicationThis paper presents a model of an integration bus used in the design of Smart Cities system architectures. The model of such a bus becomes necessary when designing high-level architectures, within which the silo processes of the organization should be seen from the perspective of its ontology. For such a bus to be used by any city, a generic solution was proposed which can be implemented as a whole or in part depending on the requirements...
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High temperature corrosion evaluation and lifetime prediction of porous Fe22Cr stainless steel in air in temperature range 700–900 °C
PublicationThis work describes a high temperature corrosion kinetics study of ~30% porous Fe22Cr alloys. The surface area of the alloy (~0.02 m2 g-1) has been determined by tomographic microscopy. The weight gain of the alloys was studied by isothermal thermogravimetry in the air for 100 hours at 700 - 900 °C. Breakaway oxidation was observed after oxidation at 850 °C (~100 hours) and 900 °C (~30 hours). The lifetime prediction shows the...
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Prediction of the fatigue lifetime of PUR structural elements using a combined experimental-numerical approach
PublicationThis paper presents a method for estimating the fatigue life of polyurethane elastomeric components. A rubber replacement - polyurethane of hardness 80ShA commonly used in vibration damping systems, for example, in motor vehicle suspensions, was used for the study. A metal-rubber bushing component was selected for analysis, and numerical analysis was carried out along with a fatigue model proposal based on a modification of the...
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EvOLAP Graph – Evolution and OLAP-Aware Graph Data Model
PublicationThe objective of this paper is to propose a graph model that would be suitable for providing OLAP features on graph databases. The included features allow for a multidimensional and multilevel view on data and support analytical queries on operational and historical graph data. In contrast to many existing approaches tailored for static graphs, the paper addresses the issue for the changing graph schema. The model, named Evolution...
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The image of the City on social media: A comparative study using “Big Data” and “Small Data” methods in the Tri-City Region in Poland
Publication“The Image of the City” by Kevin Lynch is a landmark planning theory of lasting influence; its scientific rigor and relevance in the digital age were in dispute. The rise of social media and other digital technologies offers new opportunities to study the perception of urban environments. Questions remain as to whether social media analytics can provide a reliable measure of perceived city images? If yes, what implication does...
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Big Data Processing by Volunteer Computing Supported by Intelligent Agents
PublicationIn this paper, volunteer computing systems have been proposed for big data processing. Moreover, intelligent agents have been developed to efficiency improvement of a grid middleware layer. In consequence, an intelligent volunteer grid has been equipped with agents that belong to five sets. The first one consists of some user tasks. Furthermore, two kinds of semi-intelligent tasks have been introduced to implement a middleware...
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Emulator and simulator of Terma SCANTER and ARPA radar data server
PublicationThe software solutions presented in this paper generate real-time data compatible with ARPA radar standard as well as Terma SCANTER 2001 radar cooperating with Video Distribution and Tracking (VDT) server. Two different approaches to this problem are considered: emulation based on the data captured from real devices and simulation of objects on the sea. For both of them architecture, implementation details and functional test results...
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Improving css-KNN Classification Performance by Shifts in Training Data
PublicationThis paper presents a new approach to improve the performance of a css-k-NN classifier for categorization of text documents. The css-k-NN classifier (i.e., a threshold-based variation of a standard k-NN classifier we proposed in [1]) is a lazy-learning instance-based classifier. It does not have parameters associated with features and/or classes of objects, that would be optimized during off-line learning. In this paper we propose...
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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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Synteza algorytmu detekcji pęknięcia szyby metodą ''data fission - data fusion''
PublicationPrzedstawiono założenia projektowe oraz proces syntezy algorytmu detekcyjnego akustycznego detektora pęknięcia szyby. W konstrukcji algorytmu użyto techniki rozszczepiania i syntezy danych. Przedstawiono użyte narzędzia badawcze, opracowany model pęknięcia szyby oraz wynki testowania finalnego algorytmu detekcyjnego. Metoda znalazła zastosowanie w konstrukcji akustycznego detektora pęknięcia szyby stosowanego w systemach alarmowych.
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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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Application of Web-GIS for Dissemination and 3D Visualization of Large-Volume LiDAR Data
PublicationThe increasing number of digital data sources, which allow for semi-automatic collection and storage of information regarding various aspects of life has recently granted a considerable rise in popularity to the term “Big data”. As far as geospatial data is concerned, one of the major sources of Big data are Light Detection And Ranging (LiDAR) scanners, which produce high resolution three-dimensional data on a local scale. The...
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PREDICTION OF SHIP MOTIONS IN IRREGULAR WAVES BASED ON RESPONSE AMPLITUDE OPERATORS EVALUATED EXPERIMENTALLY IN NOISE WAVES
PublicationThe most common methods for predicting ship roll motions in a specified sea state are direct measurements of motions in a representative irregular wave realisation (time domain) or calculations of motions from response amplitude operators (RAOs) in the frequency domain. The result of the first method is valid only for the tested sea state, whilst the second method is more flexible but less accurate. RAO-based predictions are calculated...
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Towards a Framework for Context Awareness Based on Textual Process Data
PublicationContext awareness is critical for the successful execution of processes. In the abundance of business process management (BPM) research, frameworks exclusively devoted to extracting context from textual process data are scarce. With the deluge of textual data and its increasing value for organizations, it be-comes essential to employ relevant text analytics techniques to increase the awareness of business process (BP) workers,...
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Coastal zone monitoring using Sentinel-1 SAR polarymetry data
PublicationIn recent years the role of the surveillance and security of Polish boundaries has significantly increased. Polish coastal zone monitoring requires various approaches using various technological means in order to ensure the protection of Polish boundaries. In this paper, the authors discuss and present alternatives to underwater surveillance methods of coastal area analysis and monitoring using data retrieved from the newly developed...
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Study of data scheduling methods in the WiMAX Mobile metropolitan area networks
PublicationThe paper discusses basic assumptions of the WiMAX Mobile system. It also presents and analyses the results of simulation tests run for selected data scheduling methods and subcarrier allocation. Based on the test results, the authors have prepared a comparative analysis of two popular data scheduling methods, i.e. WRR and PF, and their own method CDFQ which uses information about the current channel situation for the queuing processes...
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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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Description logic based generator of data-centric applications
PublicationThe knowledge stored in Ontology Management Systems (OMS) that originally has the form of expressions, can be seen as a user application specification or as knowledge provided by an expert. The generator of applications discussed in this paper is defined as a program that automatically generates an application that meets a certain specification stored in OMS. It is shown that it is possible to build a user interface for data management...
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Description logic based generator of data-centric applications
PublicationThe knowledge stored in Ontology Management Systems (OMS) that originally has the form of expressions, can be seen as a user application specification or as knowledge provided by an expert. The generator of applications discussed in this paper is defined as a program that automatically generates an application that meets a certain specification stored in OMS. It is shown that it is possible to build a user interface for data management...
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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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Processing data on sea bottom structure obtained by means of the parametric sounding
PublicationThe aim of the paper is to analyze data obtain during sounding of the Gdansk Bay by means of the parametric sonar. The accuracy of the sea bottom structure investigation needs the correct configuration of research equipment and the proper calibration of peripheral devices (GPS, heading sensor, motion sensor MRU-Z and navigation units) which provide necessary data to bathymetrical measurement system enabling its work with whole...
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Integration of inertial sensors and GPS system data for underwater navigation
PublicationThe Inertial Navigation System (INS) is usually employed to determine the position of an underwater vehicles, like Remotely Operated Vehicles (ROV) and, more recently, Autonomous Underwater Vehicle (AUV). The accuracy of the position provided by the INS, which uses accelerometers and gyroscopes, deteriorates with time. An external aiding sources such as the Global Positioning System (GPS) can be employed to reduce the error growth...
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Prediction of flow boiling heat transfer coefficient for carbon dioxide in minichannels and conventional channels
PublicationIn the paper presented are the results of calculations using authors own model to predict heat transfer coefficient during flow boiling of carbon dioxide. The experimental data from various resea rches were collected. Calculations were conducted for a full range of quality variation and a wide range of mass velocity. The aim of the study was to test the sensitivity of the in-house model. The results show the importance of taking into...
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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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Prediction of Pile Shaft Capacity in Tension Based on Some Direct CPT Methods—Vistula Marshland Test Site
PublicationThis paper presents different CPT methodologies for the prediction of the pile shaft resistance in tension on the example of three reference screw piles of the Jazowa test site in Poland. The shaft capacity was estimated based on the cone resistance, sleeve friction and CPT excess pore water pressure. Three piles with diameter 0.4 m and the length varied from 8 m to 14.6 m were subjected to static load tests in tension. Their...
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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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Network-aware Data Prefetching Optimization of Computations in a Heterogeneous HPC Framework
PublicationRapid development of diverse computer architectures and hardware accelerators caused that designing parallel systems faces new problems resulting from their heterogeneity. Our implementation of a parallel system called KernelHive allows to efficiently run applications in a heterogeneous environment consisting of multiple collections of nodes with different types of computing devices. The execution engine of the system is open for...
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Distributed Detection of Selected Features in Data Streams Using Grid-class Systems
PublicationThis chapter describes basic methodology of distributed digital signal processing. A choice of distributed methods of detection of selected features in data streams using grid-class systems is discussed. Problems related to distribution of data for processing are addressed. A mitigating method for data distribution and result merging is described.
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Prediction of pile shaft capacity in tension based on some direct CPT methods – Vistula Marshland test site
PublicationThis paper presents different CPT methodologies for the prediction of the pile shaft resistance in tension on the example of three reference screw piles of the Jazowa test site in Poland. The shaft capacity was estimated based on the cone resistance, sleeve friction and CPT excess pore water pressure. Three piles with a diameter of 0.4 m and the length...
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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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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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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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Distributed measurement system with data transmission secured using XXTEA algorithm
PublicationThe paper deals with wireless data transmission security in the distributed measurement and control system. An overview of cryptographic algorithms was presented paying special attention to the algorithm dedicated to units with low processing power, which is important due to minimization of energy consumption. Measurement modules equipped with simple microcontrollers send data wirelessly to the central unit. The transmission was...
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Visual Data Encryption for Privacy Enhancement in Surveillance Systems
PublicationIn this paper a methodology for employing reversible visual encryption of data is proposed. The developed algorithms are focused on privacy enhancement in distributed surveillance architectures. First, motivation of the study performed and a short review of preexisting methods of privacy enhancement are presented. The algorithmic background, system architecture along with a solution for anonymization of sensitive regions of interest...
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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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EXPERIMENTAL VERIFICATION OF THE METHOD OF FLOW BOILING AND FLOW CONDENSATION HEAT TRANSFER PREDICTION FOR SELECTED FLUIDS
PublicationIn the paper presented are the results of calculations using authors own model to predict heat transfer coefficient during flow boiling of different refrigerants. The experimental data from various research studies from literature were collected. Calculations were conducted for a full range of quality variation and a wide range of mass velocity. The aim of the study was to test the sensitivity of the in- house developed model....
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From the pills to environment – Prediction and tracking of non-steroidal anti-inflammatory drug concentrations in wastewater
PublicationThe extend of environment pollution by pharmaceuticals is in a stage that required more automatic and integrated solutions. The non-steroidal anti-inflammatory drugs (NSAIDs) are one of the most popular pharmaceutical in the world and emerging pollutants of natural waters. The aim of the paper was to check the correlation of the sales data of selected NSAIDs (ibuprofen, naproxen, diclofenac) and their concentration in the WWTP...
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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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Towards explainable motion prediction using heterogeneous graph representations
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Prediction of antimicrobial activity of imidazole derivatives by artificial neural networks
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Prediction of the properties of PVD/CVD coatings with the use of FEM analysis
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Towards probabilistic models for the prediction of a ship performance in dynamic ice
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