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Search results for: data driven planning
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General concept of reduction process for big data obtained by interferometric methods
PublicationInterferometric sonar systems apply the phase content of the sonar signal to measure the angle of a wave front returned from the seafloor or from a target. It collect a big data – datasets that are so large or complex that traditional data processing application software is inadequate to deal with them. The recording a large number of data is associated with the difficulty of their efficient use. So data have to be reduced. The main...
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Combining Road Network Data from OpenStreetMap with an Authoritative Database
PublicationComputer modeling of road networks requires detailed and up-to-date dataset. This paper proposes a method of combining authoritative databases with OpenStreetMap (OSM) system. The complete route is established by finding paths in the graph constructed from partial data obtained from OSM. In order to correlate data from both sources, a method of coordinate conversion is proposed. The algorithm queries road data from OSM and provides...
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Analysis of GNSS, Hydroacoustic and Optoelectronic Data Integration Methods Used in Hydrography
PublicationThe integration of geospatial data in hydrography, performed using different measurement systems, involves combining several study results to provide a comprehensive analysis. Each of the hydroacoustic and optoelectronic systems is characterised by a different spatial reference system and the method for technical implementation of the measurement. Therefore, the integration of hydrographic data requires that problems in selected...
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Artysta i analityk. Big data w przestrzeni kultury
PublicationTekst rozważa rolę Big Data - ogromnych zbiorów danych - w badaniu kultury oraz w jej tworzeniu. Przedmiotem analiz jest również wpływ tej technologii na twórczość artystyczną, w tym na współczesną architekturę i urbanistykę. Przedstawione zostały scenariusze potencjalnej przyszłej roli Big Data w społeczeństwie.
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Multibeam Sonar Data Processing for Seafloor Classification
PublicationDespite many years of the development of methodology for sensing the seafloor by means of underwater acoustics, the currently used techniques are still not mature enough and not ready to be utilised in numerous different (i.e. with respect to a water region character, used equipment type etc.) tasks. Therefore the hydroacoustic methods, both utilising vertical observations (e.g. by singlebeam echosounders), as well as those relying...
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Platelet RNA Sequencing Data Through the Lens of Machine Learning
PublicationLiquid biopsies offer minimally invasive diagnosis and monitoring of cancer disease. This biosource is often analyzed using sequencing, which generates highly complex data that can be used using machine learning tools. Nevertheless, validating the clinical applications of such methods is challenging. It requires: (a) using data from many patients; (b) verifying potential bias concerning sample collection; and (c) adding interpretability...
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Music Data Processing and Mining in Large Databases for Active Media
PublicationThe aim of this paper was to investigate the problem of music data processing and mining in large databases. Tests were performed on a large data-base that included approximately 30000 audio files divided into 11 classes cor-responding to music genres with different cardinalities. Every audio file was de-scribed by a 173-element feature vector. To reduce the dimensionality of data the Principal Component Analysis (PCA) with variable...
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Visualization of events using various kinds of synchronized data for the Border Guard
PublicationSTRADAR project is dedicated to streaming real-time data in a distributed dispatcher and teleinfor-mation system of the Border Guard. The Events Visualization Post is a software designed for simultaneous visualization of data of different types in BG headquarters. The software allows the operator to visualize files, images, SMS, SDS, video, audio, and current or archival data on naval situation on digital maps. All the visualized...
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Evaluation of position estimation based on accelerometer data
PublicationThe paper concerns the problem of integrating data from accelerometers. A suitable model of a MEMS accelerometer is presented which is a part of inertial measurement units (IMU). Such units allow to measure orientation as well as to localize systems. They also appear to be applicable for systems positioning. The main purpose of the paper is to discuss conditions that must be satisfied to calculate the location of the sensor by...
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Planning, Configuration and Usefulness of Microseismic Monitoring on Eastern-Europe Platform – Example from East Pomerania
PublicationThe microseismic monitoring is a method of monitoring of fracture propagation during hydraulic fracturing process. The method uses array of geophones to localize micro tremors induced by liquid pumped underground at high rate and pressure. The acquired information helps to optimize fracturing process and prevents fracture growth to aquifer levels. It proved to be useful on several unconventional hydrocarbon reservoirs in the USA....
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Big Data and the Internet of Things in Edge Computing for Smart City
PublicationRequests expressing collective human expectations and outcomes from city service tasks can be partially satisfied by processing Big Data provided to a city cloud via the Internet of Things. To improve the efficiency of the city clouds an edge computing has been introduced regarding Big Data mining. This intelligent and efficient distributed system can be developed for citizens that are supposed to be informed and educated by the...
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Analysis of data fusion algorithms for the vessel with the dynamic positioning system
PublicationThe dynamic positioning (DP) system on the vessel is operated to control the position and heading of the vessel with the use of propellers and thrusters installed on the board. On DP vessels redundant measurement systems of position, heading and the magnitude and direction of environmental forces are required for safety at sea. In this case, a fusion of data is needed from individual measurement devices. The article proposes a...
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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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ARIMA vs LSTM on NASDAQ stock exchange data
PublicationThis study compares the results of two completely different models: statistical one (ARIMA) and deep learning one (LSTM) based on a chosen set of NASDAQ data. Both models are used to predict daily or monthly average prices of chosen companies listed on the NASDAQ stock exchange. Research shows which model performs better in terms of the chosen input data, parameters and number of features. The chosen models were compared using...
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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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A video monitoring system using ontology-driven identification of threats
PublicationIn this paper, we present a video monitoring systemthat leverages image recognition and ontological reasoningabout threats. In the solution, an image processing subsystemuses video recording of a monitored area and recognizesknown concepts in scenes. Then, a reasoning subsystem uses anontological description of security conditions and informationfrom image recognition to check if a violation of a conditionhas occurred. If a threat...
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Hybridization-driven gap in U3Bi4Ni3: A 209Bi NMR/NQR study
PublicationZostały przeprowadzone badania jądrowego rezonansu magnetycznego (na jądrach 209Bi) na kryształach U3Bi4Ni3. U3Ni4Bi3 jest tzw. izolatorem typu Kondo.
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Development of Generalized Distribution Utility Index in Consumer-Driven Logistics
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Test limitations induced by fault-driven instability of analog circuits.
PublicationCelem pracy jest ocena ograniczeń testowania uszkodzeń parametrycznych wynikajacych z utraty stabilności przez testowany układ analogowy. Zastosowano metody zapożyczone z teorii sterowania: liniową transformacje frakcyjną i analizę metodą strukturalnych wartości szczególnych. Przykładowej analizie poddano filtr typu leapfrog. Do obliczeń wykorzystano środowisko Matlab/Simulink. Wyniki obliczeń wykazały dużą podatność testowanego...
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Visual GQM approach to quality driven development of electronic documents.
PublicationJednym z celów projektu europejskiego MEORIAL jest opracowanie nowej technologii wytwarzania webowych systemów informacyjnych wykorzystujących interaktywne dokumenty cyfrowe wytworzone z papierowych oryginałów z zastosowaniem zaawansowanych technik przetwarzania i rozpoznania obrazów. Wieloelementowy model cyklu życia dokumentu cyfrowego przedstawiony w artykule stanowi postawę opracowanej technologii.
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Axial piston pumps with cam driven commutation unit. z.
PublicationPrzedstawiono wyniki badań i podstawowe dane techniczne typowego szeregu pomp wielotłoczkowych osiowych wdrażanych do produkcji seryjnej.
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Simulation-driven design of compact ultra-wideband antenna structures
PublicationPurpose–The purpose of this paper is to investigate strategies and algorithms for expedited designoptimization and explicit size reduction of compact ultra-wideband (UWB) antennas.Design/methodology/approach–Formulation of the compact antenna design problem aiming atexplicit size reduction while maintaining acceptable electrical performance is presented. Algorithmicframeworks are described suitable for handling various design situations...
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Experience-Driven Model of Decision-Making Processes in Project Teams
PublicationThis article presents a model of decision-making processes in project teams. Project teams constitute a specific type of organization appointed to implement a project. Decisions made by project teams result from the methods of project management and best management practices. The authors have undertaken the task of formalizing these processes using the classical method of constructing decision trees. It has been established that...
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Endothelial Dysfunction Driven by Hypoxia—The Influence of Oxygen Deficiency on NO Bioavailability
PublicationCardiovascular diseases (CVDs) are the leading cause of death worldwide. The initial stage of CVDs is characterized by endothelial dysfunction, defined as the limited bioavailability of nitric oxide (NO). Thus, any factors that interfere with the synthesis or metabolism of NO in endothelial cells are involved in CVD pathogenesis. It is well established that hypoxia is both the triggering factor as well as the accompanying factor...
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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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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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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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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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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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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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DATA MINING STAC 2022/2023
e-Learning CoursesSTAC
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Advanced Data Mining 2022/23
e-Learning Courses -
Numerical Methods - Data Engineering - 2023
e-Learning Coursesstudia inżynierskie, informatyka i inżynieria danych
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Analiza danych typu Big Data
e-Learning Courses -
Numerical Methods - Data Engineering - 2024
e-Learning CoursesInżynieria danych
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Business Data Analytics-2023 /2024
e-Learning Courses -
Inżynieria Danych Data Science 2024
e-Learning Courses -
Advanced Data Mining 2023/24
e-Learning Courses -
T cell Activation Is Driven by an ADP-Dependent Glukosinase Linking Enhanced Glycolysis with Mitochondrial Reactive Oxygen Species Generation
PublicationMitochondria-originating reactive oxygen species control T cell receptor (TCR)-induced gene expression. Here, we show that TCR-triggered activation of ADP-dependent glucokinase (ADPGK), an alternative, glycolytic enzyme typical for Archaea, mediates generation of the oxidative signal. We also show that ADPGK is localized in the endoplasmic reticulum and suggest that its active site protrudes toward the cytosol. The ADPGK-driven...
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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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Ireneusz Czarnowski Prof.
PeopleIRENEUSZ CZARNOWSKI is a graduate of the Faculty of Electrical Engineering at Gdynia Maritime University. He gained a doctoral degree in the field of computer science at Poznan University of Technology and a postdoctoral degree in the field of computer science at Wroclaw University of Science and Technology. Since 1998 is associated with Gdynia Maritime University, currently is a professor of computer science in the Department...
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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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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,...