Filters
total: 8021
-
Catalog
- Publications 4824 available results
- Journals 96 available results
- Conferences 77 available results
- People 157 available results
- Inventions 12 available results
- Projects 8 available results
- Laboratories 4 available results
- Research Teams 2 available results
- e-Learning Courses 207 available results
- Events 33 available results
- Open Research Data 2601 available results
displaying 1000 best results Help
Search results for: NMEA DATA
-
Real-time web-based gis for analysis, visualization, and integration of marine environment data
PublicationWizaulizacja i integracja przestrzennych danych morskich zbieranych przez różnego rodzaju sensory i pochodzących z różnych źródeł stanowi istotny aspekt monitorowania środowiska morskiego. Ta praca przedstawia system GIS powstały na Katedrze Systemów Geoinformatycznych na Politechnice Gdańskiej. System umożliwia integrecję i wizualizację różnego rodzaju danych morskich, w szczególności pochodzących z sensorów akustycznych takich,...
-
Drawing conclusions about reliability of power systems from small number of statistical data
PublicationW artykule podjęto próbę udzielenia odpowiedzi na pytanie, czy możliwe jest wyciągnięcie przydatnych w praktyce wniosków o niezawodności elementów technicznych, wchodzących w skład systemów energetycznych, mając do dyspozycji nieliczne dane statystyczne. W opinii autora jest to możliwe. Wskazano dwie drogi postępowania. Pierwsza opiera się na wykorzystaniu metod statystycznych. Druga wykorzystuje elementy teorii zbiorów rozmytych.
-
Data Partitioning and Task Management in the Clustered Server Layer of the Volunteer-based Computation System
PublicationWhile the typical volunteer-based distributed computing system focus on the computing performance, the Comcute system was designed especially to keep alive in the emergency situations. This means that designers had to take into account not only performance, but the safety of calculations as well. Quadruple-layered architecture was proposed to separate the untrusted components from the core of the system. The main layer (W) consists...
-
Using Principal Component Analysis and Canonical Discriminant Analysis for multibeam seafloor characterisation data
PublicationThe paper presents the seafloor characterisation based on multibeam sonar data. It relies on using the integrated model and description of three types of multibeam data obtained during seafloor sensing: 1) the grey-level sonar images (echograms) of seabed, 2) the 3D model of the seabed surface which consists of bathymetric data, 3) the set of time domain bottom echo envelopes received in the consecutive sonar beams. The classification...
-
Interactive visualization of marine pollution monitoring and forecasting data via a Web-based GIS
PublicationArtykuł prezentuje zastosowanie sieciowego Systemu Informacji Geograficznej do monitoringu i prezentacji wyników modelowania plam ropy na morzu. Omawiany system wykorzystuje technologie ESRI ArcIMS (Arc Internet Map Server) oraz Open Source GeoServer z biblioteką klienta OpenLayers w celu wizualizacji i mapowania rozprzestrzeniania się wycieku ropy w dwóch wybranych obszarach Morza Egejskiego w Grecji. Przedstawiony GIS stanowi...
-
Monitoring Parkinson's disease patients employing biometric sensors and rule-based data processing
PublicationArtykuł prezentuje automatyczny system wykrywania pogorszenia zdrowia pacjentów z chorobą Parkinsona opracowany w ramach projektu PERFORM.The paper presents how rule-based processing can be applied to automatically evaluate the motor state of Parkinson's Disease patients. Automatic monitoring of patients by using biometric sensors can provide assessment of the Parkinson's Disease symptoms. All data on PD patients' state are compared...
-
Game theory-based virtual machine migration for energy sustainability in cloud data centers
PublicationAs the demand for cloud computing services increases, optimizing resource allocation and energy consumption has become a key factor in achieving sustainability in cloud environments. This paper presents a novel approach to address these challenges through an optimized virtual machine (VM) migration strategy that employs a game-theoretic approach based on particle swarm optimization (PSO) (PSO-GTA). The proposed approach leverages...
-
Reversible data hiding in encrypted DICOM images using sorted binary sequences of pixels
PublicationIn this paper, a novel reversible data hiding method for encrypted DICOM images is proposed. The method utilizes binary decomposition of the input data paired with a sorting process of the obtained binary sequences to ensure efficient data embedding in each predefined data block for specific most significant bit (MSB) planes while exploiting the properties of run-length encoding. The proposed scheme is lossless, and based on the...
-
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....
-
Towards High-Value Datasets Determination for Data-Driven Development: A Systematic Literature Review
PublicationOpen government data (OGD) is seen as a political and socio-economic phenomenon that promises to promote civic engagement and stimulate public sector innovations in various areas of public life. To bring the expected benefits, data must be reused and transformed into value-added products or services. This, in turn, sets another precondition for data that are expected to not only be available and comply with open data principles,...
-
COVID-19 severity forecast based on machine learning and complete blood count data
PublicationProper triage of COVID-19 patients is a key factor in eective case management, especially with limited and insucient resources. In this paper, we propose a machine-aided diagnostic system to predict how badly a patient with COVID-19 will develop disease. The prognosis of this type is based on the parameters of commonly used complete blood count tests, which makes it possible to obtain data from a wide range of patients.We chose...
-
COVID-19 severity forecast based on machine learning and complete blood count data
PublicationProper triage of COVID-19 patients is a key factor in eective case management, especially with limited and insucient resources. In this paper, we propose a machine-aided diagnostic system to predict how badly a patient with COVID-19 will develop disease. The prognosis of this type is based on the parameters of commonly used complete blood count tests, which makes it possible to obtain data from a wide range of patients.We chose...
-
Buried Object Characterization by Data-Driven Surrogates and Regression-Enabled Hyperbolic Signature Extraction
PublicationThis work addresses artificial-intelligence-based buried object characterization using FDTD-based electromagnetic simulation toolbox of a Ground Penetrating Radar (GPR) to generate B-scan data. In data collection, FDTD-based simulation tool, gprMax is used. The task is to estimate geophysical parameters of a cylindrical shape object of various radii, buried at different positions in the dry soil medium simultaneously and independently...
-
Operational Enhancement of Numerical Weather Prediction with Data from Real-time Satellite Images
PublicationNumerical weather prediction (NWP) is a rapidly expanding field of science, which is related to meteorology, remote sensing and computer science. Authors present methods of enhancing WRF EMS (Weather Research and Forecast Environmental Modeling System) weather prediction system using data from satellites equipped with AMSU sensor (Advanced Microwave Sounding Unit). The data is acquired with Department of Geoinformatics’ ground...
-
Digitalization Process and Its Impact on Economic Growth A Panel Data Study for Developing Countries
PublicationThis book analyses the impact of Information and Communication Technologies (ICTs) on economic development. It contains theoretical and empirical studies, including panel studies on various issues facing developing countries, such as education, corruption, economic growth, government expenditure, financial inclusion, foreign direct investment, infrastructure, economic and social welfare, and inequality. Each chapter offers a well-conceived...
-
Reduction of measurement data before Digital Terrain Model generation vs. DTM generalisation
PublicationModern data acquisition technologies provide large datasets that are not always necessary in its entirety to properly accomplish the goal of the study. In addition, such datasets are often cumbersome for rational processing, and their processing is time and labour consuming. Therefore, methods that enable to reduce the size of the measurement dataset, such as the generalization of the Digital Terrain Model (DTM) or the reduction...
-
Application of multisensoral remote sensing data in the mapping of alkaline fens Natura 2000 habitat
PublicationThe Biebrza River valley (NE Poland) is distinguished by largely intact, highly natural vegetation patterns and very good conservation status of wetland ecosystems. In 20132014, studies were conducted in the upper Biebrza River basin to develop a remote sensing method for alkaline fen classification a protected Natura 2000 habitat (code 7230) using remote sensing technologies. High resolution airborne true colour (RGB) and...
-
Impact of AI-Based Tools and Urban Big Data Analytics on the Design and Planning of Cities
PublicationWide access to large volumes of urban big data and artificial intelligence (AI)-based tools allow performing new analyses that were previously impossible due to the lack of data or their high aggregation. This paper aims to assess the possibilities of the use of urban big data analytics based on AI-related tools to support the design and planning of cities. To this end, the author introduces a conceptual framework to assess the...
-
Advances in Architectures, Big Data, and Machine Learning Techniques for Complex Internet of Things Systems
PublicationTe feld of Big Data is rapidly developing with a lot of ongoing research, which will likely continue to expand in the future. A crucial part of this is Knowledge Discovery from Data (KDD), also known as the Knowledge Discovery Process (KDP). Tis process is a very complex procedure, and for that reason it is essential to divide it into several steps (Figure 1). Some authors use fve steps to describe this procedure, whereas others...
-
Influence of YARN Schedulers on Power Consumption and Processing Time for Various Big Data Benchmarks
PublicationClimate change caused by human activities can influence the lives of everybody onthe planet. The environmental concerns must be taken into consideration by all fields of studyincludingICT. Green Computing aims to reduce negative effects of IT on the environment while,at the same time, maintaining all of the possible benefits it provides. Several Big Data platformslike Apache Spark orYARNhave become widely used in analytics and...
-
Floodplain inundation Mapping using SAR Scattering Coefficient Thresholding and Observed Discharge Data
PublicationInundation area time series are important for wetlands monitoring and hydrological model validation. This study is conducted in Biebrza floodplain, which is a natural wetland with complex inundation generation processes. In order to map 2014-2018 series of inundation in the floodplain we test our automatic thresholding method on Sentinel 1 data. The threshold value is optimized using correlation of the inundation area with observed...
-
Evaluation of the efficiency of the duty cycle of refuse collection vehicle based on real-world data
PublicationIn this paper a method of the efficiency evaluation of the duty cycle of Refuse Collection Vehicle is presented. Using real world data, two representative duty cycles were analysed. Total cycle efficiency was calculated, as well as the efficiency of particular cycle phases. Then, energy needed to collect and compact the waste and energy from fuel were compared. Measured and calculated values were shown on the diagrams illustrating...
-
Energetic model of hydraulic system of refuse collection vehicle based on simulation and experimental data
PublicationThis paper presents an energetic model of hydraulic system of a refuse collection vehicle. First, benefits resulting from implementation of an energetic model in the industry and operation of a Refuse Collection Vehicle are briefly explained. Then, components of the energy consumption in hydraulic circuits of compactor and lifting device are described and combined into a comprehensive model that can be evaluated using basic measurement...
-
Novel Fault Identification for Electromechanical Systems via Spectral Technique and Electrical Data Processing
PublicationIt is proposed, developed, investigated, and validated by experiments and modelling for the first time in worldwide terms new data processing technologies, higher order spectral multiple correlation technologies for fault identification for electromechanical systems via electrical data processing. Investigation of the higher order spectral triple correlation technology via modelling has shown that the proposed data processing technology...
-
A Data Driven Model for Predicting RNA-Protein Interactions based on Gradient Boosting Machine
PublicationRNA protein interactions (RPI) play a pivotal role in the regulation of various biological processes. Experimental validation of RPI has been time-consuming, paving the way for computational prediction methods. The major limiting factor of these methods has been the accuracy and confidence of the predictions, and our in-house experiments show that they fail to accurately predict RPI involving short RNA sequences such as TERRA RNA....
-
TOWARDS EXPLAINABLE CLASSIFIERS USING THE COUNTERFACTUAL APPROACH - GLOBAL EXPLANATIONS FOR DISCOVERING BIAS IN DATA
PublicationThe paper proposes summarized attribution-based post-hoc explanations for the detection and identification of bias in data. A global explanation is proposed, and a step-by-step framework on how to detect and test bias is introduced. Since removing unwanted bias is often a complicated and tremendous task, it is automatically inserted, instead. Then, the bias is evaluated with the proposed counterfactual approach. The obtained results...
-
Use of Data from Satellite Navigation System in Operational and Strategic Management of Transport in Cities
PublicationThe article presents the possibilities of using data from the Global Positioning System for the development of traffic models and examples of use this data in the transport management. Traffic models are useful tools in planning and evaluation of transport solutions, but also can be used for current, operational transport management.
-
Using LSTM networks to predict engine condition on large scale data processing framework
PublicationAs the Internet of Things technology is developing rapidly, companies have an ability to observe the health of engine components and constructed systems through collecting signals from sensors. According to output of IoT sensors, companies can build systems to predict the conditions of components. Practically the components are required to be maintained or replaced before the end of life in performing their assigned task. Predicting...
-
Detection of Lexical Stress Errors in Non-Native (L2) English with Data Augmentation and Attention
PublicationThis paper describes two novel complementary techniques that improve the detection of lexical stress errors in non-native (L2) English speech: attention-based feature extraction and data augmentation based on Neural Text-To-Speech (TTS). In a classical approach, audio features are usually extracted from fixed regions of speech such as the syllable nucleus. We propose an attention-based deep learning model that automatically de...
-
Data-Driven Surrogate-Assisted Optimization of Metamaterial-Based Filtenna Using Deep Learning
PublicationIn this work, a computationally efficient method based on data driven surrogate models is pro-posed for the design optimization procedure of a Frequency Selective Surface (FSS)-based filtering antenna (Filtenna). A Filtenna acts as a as module that simultaneously pre-filters unwanted sig-nals, and enhances the desired signals at the operating frequency. However, due to a typically large number of design variables of FSS unit elements,...
-
A Comparison between MD and EXAFS extracted Structural Data for TernaryRbBr(1-x)Ix.
PublicationStrukturę trójskładnikowych soli poddano analizie za pomocą metody EXAFS i symulacji M-D. Przedyskutowano przydatność używanego w symulacjach potencjału oddziaływań międzyatomowych.
-
Parametric versus nonparametric modelling of dynamic susceptibility contrast enhanced MRI based data
PublicationDynamic tracking of a bolus of a paramagnetic agent (dynamic susceptibility contract - DSC) in MRI (magnetic resonance imaging) measurements is successfully used for assessment of the tissue perfusion and the other features and functions of the brain (i.e. cerebral blood flow - CBF, cerebral blood volume - CBV, mean transit time - MTT). The parametric and nonparametric approaches to the identification of MRI models are presented...
-
Wide-band modulation and adaptive equalization techniques for fast and reliable underwater data transmission.
PublicationSzybkość transmisji w płytkim kanale podwodnym jest ograniczona ze względu na wielokrotne odbicia fal dźwiękowych oraz niestacjonarność kanału. Dla zapewnienia szybkiej i niezawodnej transmisji danych w systemach komunikacji stosowane są złożone techniki modulacji oraz equalizacji kanału. W artykule zaproponowano zastosowanie modulacji OFDM oraz equalizacji adaptacyjnej w systemie komunikacji podwodnej. Modulacja OFDM stosowana...
-
Perception-based data processing in acoustics. Applications to music information retrieval and psychophysiology of hearing.
PublicationTematyka książki obejmuje w pierwszej kolejności opis mechanizmów kognitywnych leżących u podstaw percepcji muzyki. Przedstawione zostały również zagadnienia automatycznego rozpoznawania dźwięków instrumentów muzycznych i muzyki, zastosowanie nowych metod z dziedziny sztucznej inteligencji w szeroko rozumianej inżynierii dźwięku oraz komputerowych metod badania słuchu.
-
Activation of Metabotropic Glutamate Receptor (mGlu2) and Muscarinic Receptors (M1, M4, and M5), Alone or in Combination, and Its Impact on the Acquisition and Retention of Learning in the Morris Water Maze, NMDA Expression and cGMP Synthesis
PublicationThe Morris water maze (MWM) is regarded as one of the most popular tests for detecting spatial memory in rodents. Long-term potentiation and cGMP synthesis seem to be among the crucial factors involved in this type of learning. Muscarinic (M1, M4, and M5 receptors) and metabotropic glutamate (mGlu) receptors are important targets in the search for antipsychotic drugs with the potency to treat cognitive disabilities associated with...
-
Paweł Czarnul dr hab. inż.
PeoplePaweł Czarnul obtained a D.Sc. degree in computer science in 2015, a Ph.D. in computer science granted by a council at the Faculty of Electronics, Telecommunications and Informatics, Gdansk University of Technology in 2003. His research interests include:parallel and distributed processing including clusters, accelerators, coprocessors; distributed information systems; architectures of distributed systems; programming mobile devices....
-
Lipophilicity data for some preservatives estimated by reversed-phase liquid chromatography and different copmutation methods
PublicationW pracy przedstawiono wyniki badań właściwości chromatograficznych wybranych 12 związków z grupy kopnserwantów. Lipofilowy charakter tych związków był oceniany na podtsawie różnych parametrów retencyjnych (log Kw, log K i inne. Zastosowano narzędzie chemometryczne do zbadania korelacji występujących pomiędzy tymi parametrami retencji chromatogfraficznej.
-
Predictive Capacity of Rainfall Data to Estimate the Water Needs of Fruit Plants in Water Deficit Areas
Publication -
Kidney function in the very elderly with hypertension: data from the hypertension in the very elderly (HYVET) trial
Publication -
Transcriptomics in Toxicogenomics, Part I: Experimental Design, Technologies, Publicly Available Data, and Regulatory Aspects
Publication -
Mean Shift Segmentation Assessment for Individual Forest Tree Delineation from Airborne Lidar Data
Publication -
Application of physicochemical data for water-quality assessment of watercourses in the Gdansk Municipality (South Baltic coast)
Publication -
BatchI: Batch effect Identification in high-throughput screening data using a dynamic programming algorithm
Publication -
Count Data Modeling About Relationship Between Dubai Housing Sales Transactions and Financial Indicators
Publication -
Occurrence and variability of River Habitat Survey features across Europe and the consequences for data collection and evaluation
Publication -
Seeking genetic signature of radiosensitivity - a novel method for data analysis in case of small sample sizes
Publication -
The effect of a unique halide-stabilizing residue on the catalytic properties of haloalkane dehalogenase DatA fromAgrobacterium tumefaciensC58
Publication -
Application of hidden Markov models to eye tracking data analysis of visual quality inspection operations
Publication -
The Use of Satellite Data to Determine the Changes of Hydrodynamic Parameters in the Gulf of Gdańsk via EcoFish Model
Publication -
Quality of Life Surveys as a Method of Obtaining Data for Sustainable City Development—Results of Empirical Research
Publication