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Wyniki wyszukiwania dla: data stewardship
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The structure of the data flow in integrated urban traffic management systems – the case of TRISTAR system
PublikacjaThe purpose of the article is to offer some insight into the data flow architecture in the Tri-City’s integrated traffic management system called TRISTAR. To that end selected elements of TRISTAR are identified and described as well as the structure for collecting and exchanging data within different sub-systems. Finally, the article highlights how the TRISTAR system can be extended by adding new elements and modules.
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Trade differentiation and the characteristics of new imported and exported products - international panel data analysis
PublikacjaDrawing on o large panel of international economies we have shown how the set of imported and exported products evolves in economic growth process. Strong activity at the extensive margin, manifested through the rise in the number of active export and import lines, is typical for early stages of development. Trade diversification tendency, typical for a predominant mass of observations in our panel, is associated with changes in...
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TOWARDS EXPLAINABLE CLASSIFIERS USING THE COUNTERFACTUAL APPROACH - GLOBAL EXPLANATIONS FOR DISCOVERING BIAS IN DATA
PublikacjaThe 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
PublikacjaThis 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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Floodplain inundation Mapping using SAR Scattering Coefficient Thresholding and Observed Discharge Data
PublikacjaInundation 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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Use of Data from Satellite Navigation System in Operational and Strategic Management of Transport in Cities
PublikacjaThe 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.
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Using LSTM networks to predict engine condition on large scale data processing framework
PublikacjaAs 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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Novel Fault Identification for Electromechanical Systems via Spectral Technique and Electrical Data Processing
PublikacjaIt 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
PublikacjaRNA 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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Impact of AI-Based Tools and Urban Big Data Analytics on the Design and Planning of Cities
PublikacjaWide 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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Research and Analysis of High-Speed Data Transmission Radio Link Designed for Maritime Environment
PublikacjaIn 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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Using Principal Component Analysis and Canonical Discriminant Analysis for multibeam seafloor characterisation data
PublikacjaThe 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...
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Buried Object Characterization by Data-Driven Surrogates and Regression-Enabled Hyperbolic Signature Extraction
PublikacjaThis 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...
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A Regular Expression Matching Application with Configurable Data Intensity for Testing Heterogeneous HPC Systems
PublikacjaModern High Performance Computing (HPC) systems are becoming increasingly heterogeneous in terms of utilized hardware, as well as software solutions. The problems, that we wish to efficiently solve using those systems have different complexity, not only considering magnitude, but also the type of complexity: computation, data or communication intensity. Developing new mechanisms for dealing with those complexities or choosing an...
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Multivariate analysis of impedance data obtained for coating systems of varying thickness applied on steel
PublikacjaElectrochemical impedance spectroscopy (EIS) has proven to be a valuable test method for the electrochemical characterization of protective coatings on metals. The common way of analysis in impedance spectroscopy is to model the impedance spectrum by means of an equivalent circuit and to extract the quantity of interest using optimization techniques. A model, corresponding to the behavior of the sample under testing, is important...
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Application of multisensoral remote sensing data in the mapping of alkaline fens Natura 2000 habitat
PublikacjaThe 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...
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A strategy for GPS data processing in a precise local network during high solar activity
PublikacjaThis 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
PublikacjaIn 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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Digitalization Process and Its Impact on Economic Growth A Panel Data Study for Developing Countries
PublikacjaThis 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
PublikacjaIn 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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Data-Driven Surrogate-Assisted Optimization of Metamaterial-Based Filtenna Using Deep Learning
PublikacjaIn 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
PublikacjaOpen 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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A Comparison between MD and EXAFS extracted Structural Data for TernaryRbBr(1-x)Ix.
PublikacjaStrukturę 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
PublikacjaDynamic 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.
PublikacjaTematyka 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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Wide-band modulation and adaptive equalization techniques for fast and reliable underwater data transmission.
PublikacjaSzybkość 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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Nicole Nawrot dr inż.
OsobyDr inż. Nicole Nawrot jest zatrudniona w Katedrze Inżynierii Sanitarnej od 2016 roku. W 2021 uzyskała tytuł naukowy doktora z wyróżnieniem w dziedzinie nauk inżynieryjno-technicznych w dyscyplinie inżynieria środowiska, górnictwo i energetyka. Pracę doktorską pt. „Heavy metals in urban retention tanks bottom sediments: distribution, source tracking, and evaluation of phytostabilisation adaptability and performance of P. australis...
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INFLUENCE OF DATA NORMALIZATION ON THE EFFECTIVENESS OF NEURAL NETWORKS APPLIED TO CLASSIFICATION OF PAVEMENT CONDITIONS – CASE STUDY
PublikacjaIn recent years automatic classification employing machine learning seems to be in high demand for tele-informatic-based solutions. An example of such solutions are intelligent transportation systems (ITS), in which various factors are taken into account. The subject of the study presented is the impact of data pre-processing and normalization on the accuracy and training effectiveness of artificial neural networks in the case...
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Driving Performance Indicators of Electric Bus Driving Technique: Naturalistic Driving Data Multicriterial Analysis
PublikacjaThe issue of electric energy saving in public transport is becoming the key area of interest. By improving of driving techniques and the implementation of eco-driving, it is possible to save electric energy. Systems that help to decrease energy consumption and to reduce fuel emissions are becoming popular in vehicles powered by diesel engines. However, these methods have not yet gained popularity in electric vehicles. Therefore,...
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3D Object Shape Reconstruction from Underwater Multibeam Data and Over Ground Lidar Scanning
PublikacjaThe technologies of sonar and laser scanning are an efficient and widely used source of spatial information with regards to underwater and over ground environment respectively. The measurement data are usually available in the form of groups of separate points located irregularly in three-dimensional space, known as point clouds. This data model has known disadvantages, therefore in many applications a different form of representation,...
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Speaker Recognition Using Convolutional Neural Network with Minimal Training Data for Smart Home Solutions
PublikacjaWith the technology advancements in smart home sector, voice control and automation are key components that can make a real difference in people's lives. The voice recognition technology market continues to involve rapidly as almost all smart home devices are providing speaker recognition capability today. However, most of them provide cloud-based solutions or use very deep Neural Networks for speaker recognition task, which are...
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Is data management a new “digitisation”? A change of the role of librarians in the context of changing academic libraries’ tasks
PublikacjaAcademic libraries’ tasks have been evolving over the years. The changes have been stimulated by appearing of electronic resources, automated library systems, digital libraries and Open Access (OA) repositories. Librarians’ tasks and responsibilities in the academic environment have been evolving in accordance with new tasks they were expected to assume. A few years ago there was a discussion during which an attempt was made to...
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Anomaly Detection in Railway Sensor Data Environments: State-of-the-Art Methods and Empirical Performance Evaluation
PublikacjaTo 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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Application Of Generative Adversarial Network for Data Augmentation and Multiplication to Automated Cell Segmentation of the Corneal Endothelium
PublikacjaConsidering the automatic segmentation of the endothelial layer, the available data of the corneal endothelium is still limited to a few datasets, typically containing an average of only about 30 images. To fill this gap, this paper introduces the use of Generative Adversarial Networks (GANs) to augment and multiply data. By using the ``Alizarine'' dataset, we train a model to generate a new synthetic dataset with over 513k images....
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Integration Data Model of the Bathymetric Monitoring System for Shallow Waterbodies Using UAV and USV Platforms
PublikacjaChanges in the seafloor relief are particularly noticeable in shallow waterbodies (at depths up to several metres), where they are of significance for human safety and environmental protection, as well as for which the highest measurement accuracy is required. The aim of this publication is to present the integration data model of the bathymetric monitoring system for shallow waterbodies using Unmanned Aerial Vehicles (UAV) and...
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Which Curve Fits Best: Fitting ROC Curve Models to Empirical Credit-Scoring Data
PublikacjaIn the practice of credit-risk management, the models for receiver operating characteristic (ROC) curves are helpful in describing the shape of an ROC curve, estimating the discriminatory power of a scorecard, and generating ROC curves without underlying data. The primary purpose of this study is to review the ROC curve models proposed in the literature, primarily in biostatistics, and to fit them to actual credit-scoring ROC data...
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Unsupervised Learning for Biomechanical Data Using Self-organising Maps, an Approach for Temporomandibular Joint Analysis
PublikacjaWe proposed to apply a specific machine learning technique called Self-Organising Maps (SOM) to identify similarities in the performance of muscles around human temporomandibular joint (TMJ). The performance was assessed by measuring muscle activation with the use of surface electromyography (sEMG). SOM algorithm used in the study was able to find clusters of data in sEMG test results. The SOM analysis was based on processed sEMG...
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Are creative users more apt in reusing and adopting Open Government Data (OGD)? Gender differences
PublikacjaOpen Government Data (OGD) has been considered as a potent instrument for value creation and innovation by a range of stakeholders. Given that individual ingenuity is a function of individual and environmental factors, it is important to understand how the OGD adoption and usage is a factor of creative performance behaviors (CPB), viz., Problem Identification (PI), Information Search (IS), Idea Generation (IG) and Idea Promotion...
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Simulation of Direct-Sequence Spread Spectrum Data Transmission System for Reliable Underwater Acoustic Communications
PublikacjaUnderwater acoustic communication (UAC) system designers tend to transmit as much information as possible, per unit of time, at as low as possible error rate. It is a particularly difficult task in a shallow underwater channel in which the signal suffers from strong time dispersion due to multipath propagation and refraction phenomena. The direct-sequence spread spectrum technique (DSSS) applied successfully in the latest standards...
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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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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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Application of gas chromatographic data and 2D molecular descriptors for accurate global mobility potential prediction
PublikacjaMobility 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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