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Search results for: DATA ACQUISITION SYSTEMS
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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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Identification of continuous systems - Practical issues of insensitivity to perturbations
PublicationIn this paper the issue of continuous systems estimation, insensitive to certain perturbations, is discussed. Such an approach has rational advantages, especially when robust schemes are used to assist a target system responsible for industrial diagnostics. This requires that estimated model parameters are generated on-line, and their values are reliable and to a great extent accurate. Practical hints are suggested to challenge...
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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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Analysis of Transformation Methods of Hydroacoustic and Optoelectronic Data Based on the Tombolo Measurement Campaign in Sopot
PublicationMeasurements in the coastal zone are carried out using various methods, including Global Navigation Satellite Systems (GNSS), hydroacoustic and optoelectronic methods. Therefore, it is necessary to develop coordinate transformation models that will enable the conversion of data from the land and marine parts to one coordinate system. The article presents selected issues related to the integration of geodetic and hydrographic data....
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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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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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Systematics of intelligent transport systems services
PublicationRecent years have seen a more intensified deployment of Intelligent Transport Systems (ITS) in Polish cities. Work is also underway on the implementation of ITS on the national roads within the National Traffic Management System (KSZR). The research project RID-4D (part of Road Innovations), is designed to fill the gap, which is the lack of systematics of ITS services in Poland. The paper presents a proposal of ITS services systematics,...
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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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Weather Routing System Architecture Using Onboard Data Collection and Route Optimisation
PublicationThis paper describes the architecture of a weather routing system consisting of two key elements: onboard monitoring and route optimiser sub-systems. The former is responsible for collecting various onboard measurements, such as current ship position or ship motion variables. These data, when gathered and processed, are then used for fine-tuning a ship model. The model, together with weather forecasts, is utilised by a multi-objective...
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Adaptive Dynamical Systems Modelling of Transformational Organizational Change with Focus on Organizational Culture and Organizational Learning
PublicationTransformative Organizational Change becomes more and more significant both practically and academically, especially in the context of organizational culture and learning. However computational modeling and a formalization of organizational change and learning processes are still largely unexplored. This paper aims to provide an adaptive network model of transformative organizational change and translate a selection of organizational...
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Solving the Problem of Dynamic Adaptability of Artificial Intelligence Systems that Control Dynamic Technical Objects
PublicationThis paper investigates the increase in the response speed and stability of artificial intelligence systems that control dynamic technical objects. The problem of calculating the optimal time of switching an artificial intelligence system between software classes by the criterion of the rigidity degree of the model of a control object is considered. The solution of this problem is proposed for the general case of the control object...
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Assessment of Road Restraint Systems in Polish Conditions
PublicationKey to understanding the needs and tools of road infrastructure management is identifying the hazards and their sources involved in having no or faulty road restraint systems. Clarity is also needed on why the systems are wrongly designed, constructed, built and operated. To ensure that the problem is adequately understood, research and site observations were conducted and...
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Designing Control and Protection Systems with Regard to Integrated Functional Safety and Cybersecurity Aspects
PublicationThis article addresses current problems of risk analysis and probabilistic modelling for functional safety management in the life cycle of safety-related systems. Two main stages in the lifecycle of these systems are distinguished, namely the design and operation. The risk analysis and probabilistic modelling differ in these stages in view of available knowledge and data. Due to the complexity and uncertainty involved, both qualitative...
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Application of Maximum-Length Sequences to impulse response measurement of hydroacoustic communications systems
PublicationThere is a growing interest in digital transmission of telemetry data on ultrasonic waves. The dependence of signal attenuation on squared frequency, specific to the hy-droacoustic systems, induces problems that do not exist in monochromatic, narrowband radio communications systems. For adapting the transmission parameters to current propagation conditions, a precise knowledge of instantaneous changes of channel performances is...
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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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Optimization of Data Assignment for Parallel Processing in a Hybrid Heterogeneous Environment Using Integer Linear Programming
PublicationIn the paper we investigate a practical approach to application of integer linear programming for optimization of data assignment to compute units in a multi-level heterogeneous environment with various compute devices, including CPUs, GPUs and Intel Xeon Phis. The model considers an application that processes a large number of data chunks in parallel on various compute units and takes into account computations, communication including...
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On noncausal weighted least squares identification of nonstationary stochastic systems
PublicationIn this paper, we consider the problem of noncausal identification of nonstationary, linear stochastic systems, i.e., identification based on prerecorded input/output data. We show how several competing weighted (windowed) least squares parameter smoothers, differing in memory settings, can be combined together to yield a better and more reliable smoothing algorithm. The resulting parallel estimation scheme automatically adjusts...
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Approximation of Fractional Order Dynamic Systems Using Elman, GRU and LSTM Neural Networks
PublicationIn the paper, authors explore the possibility of using the recurrent neural networks (RNN) - Elman, GRU and LSTM - for an approximation of the solution of the fractional-orders differential equations. The RNN network parameters are estimated via optimisation with the second order L-BFGS algorithm. It is done based on data from four systems: simple first and second fractional order LTI systems, a system of fractional-order point...
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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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Wireless Systems of Threats Monitoring
PublicationThe concept of wireless system of threats monitoring with self-organizing network of multipurpose data transfer nodes are presented. Two practical applications of this system are also presented. The first of these is the Global Wireless Monitoring System for Containers, and the second is the Mobile Monitoring System for Gas Air Pollution Measurements. Presented practical applications of the wireless threats monitoring system is...
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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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Innovative Research Into Road Restraint Systems
PublicationKey to understanding the needs and building road infrastructure management tools to prevent and mitigate run-off-road accidents is to identify hazards and their sources which are a result of wrong design, construction, installation and maintenance of road restraint systems [1]. Building such tools requires advanced studies with field tests, simulations and models to demonstrate the effects of selected parameters on road user safety...
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A Concept of Modeling and Optimization of Applications in Large Scale Systems
PublicationThe chapter presents the idea that includes modeling and subsequent optimization of application execution on large scale parallel and distributed systems. The model considers performance, reliability and power consumption. It should allow easy modeling of various classes of applications while reflecting key parameters of both the applications and two classes of target systems: clusters and volunteer based systems. The chapter presents...
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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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Clarke duality for Hamiltonian systems with nonstandard growth
PublicationWe consider the existence of periodic solutions to Hamiltonian systems with growth conditions involving G-function. We introduce the notion of symplectic G-function and provide relation for the growth of Hamiltonian in terms of certain constant CG associated to symplectic G-function G. We discuss an optimality of this constant for some special cases. We also provide applications to the Φ-laplacian type systems.
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Optimum Control of Gyroscopic Systems
PublicationThe problem of optimum control of transverse rotor vibrations with gyroscopic interactions has been described and solved in the paper. An integral performance index has been defined for such system in order to minimize vibration level of a chosen rotor point. For this reason, an efficient way of finding the weight coefficients of integral performance index for multi-degrees-of-freedom system with gyroscopic interactions has been...
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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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Anomaly Detection in Railway Sensor Data Environments: State-of-the-Art Methods and Empirical Performance Evaluation
PublicationTo date, significant progress has been made in the field of railway anomaly detection using technologies such as real-time data analytics, the Internet of Things, and machine learning. As technology continues to evolve, the ability to detect and respond to anomalies in railway systems is once again in the spotlight. However, railway anomaly detection faces challenges related to the vast infrastructure, dynamic conditions, aging...
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Smart Embedded Systems with Decisional DNA Knowledge Representation
PublicationEmbedded systems have been in use since the 1970s. For most of their history embedded systems were seen simply as small computers designed to accomplish one or a few dedicated functions; and they were usually working under limited resources i.e. limited computing power, limited memories, and limited energy sources. As such, embedded systems have not drawn much attention from researchers, especially from those in the artificial...
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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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Kamila Kokot-Kanikuła mgr
PeopleKamila Kokot-Kanikuła is a digital media senior librarian at Gdańsk University of Technology (GUT) Library. She works in Digital Archive and Multimedia Creation Department and her main areas of interests include early printed books, digital libraries, Open Access and Open Science. In the Pomeranian Digital Library (PDL) Project she is responsible for creating annual digital plans, transferring files on digital platform, and promoting...
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Losses and energy efficiency of drive motors and systems
PublicationLosses and energy efficiency of every drive motor must be presented as functions of physical quantities independent of losses in the motor. Such quantities are speed and load required by the machine or device driven by the motor, changing in the drive operating field. Speed and load of the motor decide of the instantaneous useful power of the motor and also in a differentiated way of kinds and values of losses occurring in the...
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Losses and energy efficiency of drive motors and systems
PublicationLosses and energy efficiency of every drive motor must be presented as functions of physical quantities independent of losses in the motor. Such quantities are speed and load required by the machine or device driven by the motor, changing in the drive operating field. Speed and load of the motor decide of the instantaneous useful power of the motor and also in a differentiated way of kinds and values of losses occurring in the...
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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 -
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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Propagation Loss and Interference Analysis for 5G Systems in the Context of C-ITS System Implementation
PublicationThe article presents the concept of implementing subsequent phases of services for the C-ITS system (the Cooperative Intelligent Transport Systems), based on the European Parliament resolution of March 2018. Next, the 5G systems, in the context of their possible cooperation with C-ITS systems, were discussed. Numerical propagation analysis was performed for V2V and V2I type communication based on two different propagation models....
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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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Autoencoder application for anomaly detection in power consumption of lighting systems
PublicationDetecting energy consumption anomalies is a popular topic of industrial research, but there is a noticeable lack of research reported in the literature on energy consumption anomalies for road lighting systems. However, there is a need for such research because the lighting system, a key element of the Smart City concept, creates new monitoring opportunities and challenges. This paper examines algorithms based on the deep learning...