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Search results for: data-rasterization
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A strategy for GPS data processing in a precise local network during high solar activity
PublicationThis paper presents the analyses connected with reduction of errors from ionospheric refraction using GPS data from local satellite networks. This is particularly essential during rising solar activity. The Bernese GPS Software v. 4.2 was used, as an analytical tool. The test data included measurements from a geodynamic network SUDETES situated in the Sudety Mountains across the border between the Czech Republic and Poland. A local...
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Research and analysis of high-speed data transmission radio link designed for maritime environment
PublicationIn these article the realization of digital radio link for high-speed data transmission was presented. Its concept and practical realization, using USRP devices from National Instruments, were described. Developed software for generation and reception of digital signals in baseband, including description of modulation types, and time and frequency synchronization mechanisms, was presented. Moreover, an operation of designed radio...
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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...
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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...
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Deduplication of Position Data and Global Identification of Objects Tracked in Distributed Vessel Monitoring System
PublicationVessel monitoring systems (VMS) play a very important role in safety navigation. In most cases, their structure is distributed and they are based on two data sources, namely Automatic Identification System (AIS) and Automatic Radar Plotting Aids (ARPA). Such approach results in several objects identification and position data duplication problems, which need to be solved in order to ensure the correct performance of a given VMS....
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Estimating the Average Speed of Public Transport Vehicles Based on Traffic Control System Data
PublicationIntelligent Transport Systems are a valuable source of traffic information, covering both private and public vehicles. The main problem, however, is that very few studies are conducted to determine the speed of buses, trams and trolleys in urban networks in relation to traffic conditions. The paper investigates how ITS systems data could be used to model the speed of Public Transport vehicles. This is now possible thanks to the...
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Deduplication of Tracked Objects Position Data at Single Observation Point of a Vessel Monitoring System
PublicationVessel Monitoring System (VMS) play a major role in safety navigation. In most cases they are based on two data sources, namely Automatic Identification System (AIS) and Automatic Radar Plotting Aids (ARPA). Integration of data obtained from these sources is an important problem, which needs to be solved in order to ensure the correct performance of a given VMS. In this paper basic functions which should be implemented in a tracked...
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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...
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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...
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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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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...
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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...
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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,...
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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,...
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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...
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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....
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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...
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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...
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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...
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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...
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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...
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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...
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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.
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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...
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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.
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Nicole Nawrot dr inż.
PeopleDr. Eng. Nicole Nawrot has been employed at the Department of Sanitary Engineering since 2016. In 2021, she obtained a PhD in the field of engineering and technical sciences in the discipline of environmental engineering, mining and energy. Doctoral thesis entitled "Heavy metals in urban retention tanks bottom sediments: distribution, source tracking, and evaluation of phytostabilization adaptability and performance of P. australis...
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Application of gas chromatographic data and 2D molecular descriptors for accurate global mobility potential prediction
PublicationMobility is a key feature affecting the environmental fate, which is of particular importance in the case of persistent organic pollutants (POPs) and emerging pollutants (EPs). In this study, the global mobility classification artificial neural networks-based models employing GC retention times (RT) and 2D molecular descriptors were constructed and validated. The high usability of RT was confirmed based on the feature selection...
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Quality of Life Surveys as a Method of Obtaining Data for Sustainable City Development—Results of Empirical Research
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Condition monitoring and fault diagnosis of wind turbines based on structural break detection in SCADA data
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Process Monitoring in Heavy Duty Drilling Rigs—Data Acquisition System and Cycle Identification Algorithms
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Prediction of NOx Emission Based on Data of LHD On-Board Monitoring System in a Deep Underground Mine
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Measurement of idlers rotation speed in belt conveyors based on image data analysis for diagnostic purposes
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Predictive Capacity of Rainfall Data to Estimate the Water Needs of Fruit Plants in Water Deficit Areas
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Kidney function in the very elderly with hypertension: data from the hypertension in the very elderly (HYVET) trial
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Transcriptomics in Toxicogenomics, Part I: Experimental Design, Technologies, Publicly Available Data, and Regulatory Aspects
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Mean Shift Segmentation Assessment for Individual Forest Tree Delineation from Airborne Lidar Data
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Application of physicochemical data for water-quality assessment of watercourses in the Gdansk Municipality (South Baltic coast)
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BatchI: Batch effect Identification in high-throughput screening data using a dynamic programming algorithm
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Count Data Modeling About Relationship Between Dubai Housing Sales Transactions and Financial Indicators
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Occurrence and variability of River Habitat Survey features across Europe and the consequences for data collection and evaluation
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Seeking genetic signature of radiosensitivity - a novel method for data analysis in case of small sample sizes
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Application of a modified evolutionary algorithm for the optimization of data acquisition to improve the accuracy of a video-polarimetric system
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Multiservice Optical Fibre Local Area Networks For Data Transmission And Telemetry In The Electric Power Industry
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PLS-Based and Regularization-Based Methods for the Selection of Relevant Variables in Non-targeted Metabolomics Data
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Increasing conclusiveness of metabonomic studies by cheminformatic preprocessing of capillary electrophoretic data on urinary nucleoside profiles
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Circulating MAdCAM-1 and ITGB7 in Patients with Plaque Psoriasis and Eruptive Lichen Planus—Preliminary Data
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The effect of a unique halide-stabilizing residue on the catalytic properties of haloalkane dehalogenase DatA fromAgrobacterium tumefaciensC58
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Application of hidden Markov models to eye tracking data analysis of visual quality inspection operations
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The Use of Satellite Data to Determine the Changes of Hydrodynamic Parameters in the Gulf of Gdańsk via EcoFish Model
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Landsat 8 Data as a Source of High Resolution Sea Surface Temperature Maps in the Baltic Sea
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