Search
Filters
total: 8347
-
Catalog
- Publications 5056 available results
- Journals 113 available results
- Conferences 127 available results
- People 121 available results
- Inventions 1 available results
- Projects 5 available results
- Laboratories 1 available results
- Research Teams 1 available results
- e-Learning Courses 188 available results
- Events 23 available results
- Open Research Data 2711 available results
displaying 1000 best results Help
Search results for: DISTRIBUTED REPRESENTATION OF DATA
-
An INSPIRE-Based Vocabulary for the Publication of Agricultural Linked Data
Publication -
Energy-Optimal Data Aggregation and Dissemination for the Internet of Things
Publication -
Learning from examples with data reduction and stacked generalization
Publication -
An Agent-Based Simulated Annealing Algorithm for Data Reduction
Publication -
Agent-Based Data Reduction Using Ensemble Technique
Publication -
Bi-criteria Data Reduction for Instance-Based Classification
Publication -
Stacking-Based Integrated Machine Learning with Data Reduction
Publication -
passive spice networks from non-passive data
PublicationArtykuł przestawia technike generacji schematow zastepczych w formacie SPICE dla pasywnych układów mikrofalowych. Wynikowy schemat zastepczy ma zagwarantowana pasywnosc. Schematy zastepcze powstaja na podstawie symulacji lub pomiarow w dziedzinie czestotliwosci i moga byc wykorzystane do symulacji w dziedzinie czasu.
-
3d imaging software tools for multibeam sonar data
PublicationArtykuł porusza problem trójwymiarowej wizualizacji dna morskiego na podstawie danych pochodzących z systemu wielowiązkowego. W prezentowanym systemie wykorzystano trzy technologie programistyczne do wytwarzania grafiki 3D (C++ OpenGL, Java 3D, Java OpenGL). W artykule przedstawiono problemy, na które natknięto się podczas tworzenia systemu coraz omówiono sposoby ich rozwiązywania.
-
Data transmission optical link for RF-GUN project
Publication -
Consumer Bankruptcy Prediction Using Balanced and Imbalanced Data
PublicationThis paper examines the usefulness of logit regression in forecasting the consumer bankruptcy of households using an imbalanced dataset. The research on consumer bankruptcy prediction is of paramount importance as it aims to build statistical models that can identify consumers in a difficult financial situation that may lead to consumer bankruptcy. In the face of the current global pandemic crisis, the future of household finances...
-
K-means clustering for SAT-AIS data analysis
Publication -
Manganese Distribution in CdMnTeSe Crystals. EXAFS Data Analysis
Publication -
VALIDATION OF A THREE-DIMENSIONAL HEAD PHANTOM FOR IMAGING DATA
Publication -
Realistic visualization of real terrain based on GIS Data.
PublicationArtykuł prezentuje projekt realistycznej wizualizacji terenu rzeczywistego na podstawie danych pochodzących z Geograficznych Systemów Informacyjnych (GIS). Opisano w nim koncepcję projektu, wskazano trudności w jego realizacji i wskazano drogi ich przezwyciężenia.
-
Detection of Face Position and Orientation Using Depth Data
PublicationIn this paper an original approach is presented for real-time detection of user's face position and orientation based only on depth channel from a Microsoft Kinect sensor which can be used in facial analysis on scenes with poor lighting conditions where traditional algorithms based on optical channel may have failed. Thus the proposed approach can support, or even replace, algorithms based on optical channel or based on skeleton...
-
Consumer Bankruptcy Prediction Using Balanced and Imbalanced Data
PublicationThis paper examines the usefulness of logit regression in forecasting the consumer bankruptcy of households using an imbalanced dataset. The research on consumer bankruptcy prediction is of paramount importance as it aims to build statistical models that can identify consumers in a difficult financial situation that may lead to consumer bankruptcy. In the face of the current global pandemic crisis, the future of household finances...
-
Improving Effectiveness of SVM Classifier for Large Scale Data
PublicationThe paper presents our approach to SVM implementation in parallel environment. We describe how classification learning and prediction phases were pararellised. We also propose a method for limiting the number of necessary computations during classifier construction. Our method, named one-vs-near, is an extension of typical one-vs-all approach that is used for binary classifiers to work with multiclass problems. We perform experiments...
-
Recent Developments in Data-Assisted Modeling of Flexible Proteins
PublicationMany proteins can fold into well-defined conformations. However, intrinsically-disordered proteins (IDPs) do not possess a defined structure. Moreover, folded multi-domain proteins often digress into alternative conformations. Collectively, the conformational dynamics enables these proteins to fulfill specific functions. Thus, most experimental observables are averaged over the conformations that constitute an ensemble. In this...
-
Reliable OFDM Data Transmission with Pilot Tones and Error-Correction Coding in Shallow Underwater Acoustic Channel
PublicationThe performance of Underwater Acoustic Communication (UAC) systems are strongly related to the specific propagation conditions of the underwater channel. Horizontal, shallow-water channels are characterised by extremely disadvantageous transmission properties, due to strong multipath propagation and refraction phenomena. The paper presents the results of communication tests performed during a shallow, inland-water experiment with...
-
Optimising approach to designing kernel PCA model for diagnosis purposes with and without a priori known data reflecting faulty states
PublicationFault detection plays an important role in advanced control of complex dynamic systems since precise information about system condition enables efficient control. Data driven methods of fault detection give the chance to monitor the plant state purely based on gathered measurements. However, they especially nonlinear, still suffer from a lack of efficient and effective learning methods. In this paper we propose the two stages learning...
-
Multivariate analysis of impedance data obtained for coating systems of varying thickness applied on steel
PublicationElectrochemical 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...
-
Remote command and control capabilities for data acquisition systems provided by delay-tolerant network mechanisms
PublicationThe paper presents an assessment of a remote device reconfiguration service employing a Delay Tolerant Network (DTN) mechanisms. This service has been implemented as a part of a communication appliance dedicated to marine data transfer in off-shore and open sea areas. The service has been successfully deployed and validation test have been completed. The practical use-case has been defined as remote access to the equipment operating...
-
Low-cost data-driven modelling of microwave components using domain confinement and PCA-based dimensionality reduction
PublicationFast data-driven surrogate models can be employed as replacements of computationally demanding full-wave electromagnetic simulations to facilitate the microwave design procedures. Unfortunately, practical application of surrogate modelling is often hindered by the curse of dimensionality and/or considerable nonlinearity of the component characteristics. This paper proposes a simple yet reliable approach to cost-efficient modelling...
-
Application of data driven methods in diagnostic of selected process faults of nuclear power plant steam turbine
PublicationArticle presents a comparison of process anomaly detection in nuclear power plant steam turbine using combination of data driven methods. Three types of faults are considered: water hammering, fouling and thermocouple fault. As a virtual plant a nonlinear, dynamic, mathe- matical steam turbine model is used. Two approaches for fault detection using one class and two class classiers are tested and compared.
-
Data from the Survey on Entrepreneurs’ Opinions on Factors Determining the Employment of the Gdańsk University of Technology Graduates
PublicationThe dataset includes data from a survey on factors determining the employment of the Gdańsk University of Technology (Gdańsk Tech) graduates’ in the opinion of entrepreneurs. The survey was conducted in 2017. The research sample included 102 respondents representing various firms from the Pomeranian Voivodeship, Poland. The study concerned i.a. factors determining the decision to hire a candidate, methods of recruiting employees,...
-
Microseismic Monitoring of Hydraulic Fracturing - Data Interpretation Methodology With an Example from Pomerania
PublicationMicroseismic monitoring is a method for localizing fractures induced by hydraulic fracturing in search for shell gas. The data is collected from an array of geophones deployed on the surface or underground. Ground vibrations are recorded and analysed for fracture location, magnitude and breakage mechanism. For successful microseismic monitoring one need a velocity model of underlying formations. The model is further tuned with...
-
Architecture of security and application layer structure of radio system for monitoring and acquisition of data from traffic enforcement cameras
PublicationThe study presents architecture of security and application layer structure of Radio System for Monitoring and Acquisition of Data from Traffic Enforcement Cameras. It also provides general assumptions concerning the range of the system as well as its modules and application components.
-
Seafloor characterisation using multibeam data: sonar image properties, seabed surface properties and echo properties
PublicationIn the paper, the approach to seafloor characterisation is presented. The multibeam sonars, besides their well verified and widely used applications like high resolution bathymetry and underwater object detection and imaging, are also the promising tool in seafloor characterization and classification, having several advantages over conventional single beam echosounders. The proposed approach relies on the combined, concurrent use...
-
Health System Efficiency in European Countries: Network Data Envelopment Analysis Approach
PublicationPurpose: The article's main aim is to investigate the effectiveness of health systems in European countries based on EUROSTAT data. A comparative analysis of the health systems' effectiveness in different countries is based on their improvement (reform), using the best practices approach. Design/Methodology/Approach: The network DEA model and a slack-based model (NDEA – SBM) are used. A non-oriented model is used. The research...
-
WETI - Data Engineering - Mathematics 2024/25 (E.Kozłowska-Walania)
e-Learning Courses -
WETI (Data Engineering) - Mathematics 2023/24 (E.Kozłowska-Walania)
e-Learning Courses -
Utilizing UAV and orthophoto data with bathymetric LiDAR in google earth engine for coastal cliff degradation assessment
PublicationThis study introduces a novel methodology for estimating and analysing coastal cliff degradation, using machine learning and remote sensing data. Degradation refers to both natural abrasive processes and damage to coastal reinforcement structures caused by natural events. We utilized orthophotos and LiDAR data in green and near-infrared wavelengths to identify zones impacted by storms and extreme weather events that initiated mass...
-
3D seafloor reconstruction using data from side scan and synthetic aperture sonar
PublicationSide scan and synthetic aperture sonars are widely used imaging systems in the underwater environment. They are relatively cheap and easy to deploy, in comparison with more powerful sensors, like multibeam echosounders. Although side scan and synthetic aperture sonars does not provide seafloor bathymetry directly, their records are finally related to seafloor images. Moreover, the analysis of such images performed by human eye...
-
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,...
-
Application of the Msplitmethod for filtering airborne laser scanning data-sets to estimate digital terrain models
PublicationALS point cloud filtering involves the separation of observations representing the physical terrain surface from those representing terrain details. A digital terrain model (DTM) is created from a subset of points representing the ground surface. The accuracy of the generated DTM is influenced by several factors, including the survey method used, the accuracy of the source data, the applied DTM generation algorithm, and the survey...
-
Fast multi-objective optimization of antenna structures by means of data-driven surrogates and dimensionality reduction
PublicationDesign of contemporary antenna structures needs to account for several and often conflicting objectives. These are pertinent to both electrical and field properties of the antenna but also its geometry (e.g., footprint minimization). For practical reasons, especially to facilitate efficient optimization, single-objective formulations are most often employed, through either a priori preference articulation, objective aggregation,...
-
Data-driven models for fault detection using kernel pca:a water distribution system case study
PublicationKernel Principal Component Analysis (KPCA), an example of machine learning, can be considered a non-linear extension of the PCA method. While various applications of KPCA are known, this paper explores the possibility to use it for building a data-driven model of a non-linear system-the water distribution system of the Chojnice town (Poland). This model is utilised for fault detection with the emphasis on water leakage detection....
-
High Resolution Sea Ice Floe Size and Shape Data from Knox Coast, East Antarctica
PublicationThis dataset contains floe size distribution data from a very high resolution (pixel size: 0.3 m) optical satellite image of sea ice, acquired on 16 Feb. 2019 off the Knox Coast (East Antarctica). The image shows relatively small ice floes produced by wave-induced breakup of landfast ice between Mill Island and Bowman Island. The ice floes are characterised by a narrow size distribution and angular, polygonal shapes, typical...
-
Post processing and selecting data obtain with parametric sub-bottom profiler SES-2000 Standard during sounding the Gulf of Gdansk
PublicationThe main goal of the paper is to describe the results of sounding the Gulf of Gdansk seabed using a parametric sub-bottom profiler SES-2000 Standard. Quality of obtained during trials data depends inter alia on proper location of antenna to reduce influence of pitch, roll, heave and ship noise (bubbles from propeller and a hull flow, vibration from main engine and peripheral devices). Furthermore calibration of complementary units...
-
Reliable data-driven modeling of high-frequency structures by means of nested kriging with enhanced design of experiments
PublicationData-driven (or approximation) surrogate models have been gaining popularity in many areas of engineering and science, including high-frequency electronics. They are attractive as a way of alleviating the difficulties pertinent to high computational cost of evaluating full-wave electromagnetic (EM) simulation models of microwave, antenna, and integrated photonic components and devices. Carrying out design tasks that involve massive...
-
Are creative users more apt in reusing and adopting Open Government Data (OGD)? Gender differences
PublicationOpen 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...
-
Mathematical analysis of the lasing eigenvalue problem for the optical modes in a layered dielectric cavity with a quantum well and distributed Bragg reflectors
Publication -
From Data to Decision: Interpretable Machine Learning for Predicting Flood Susceptibility in Gdańsk, Poland
PublicationFlood susceptibility prediction is complex due to the multifaceted interactions among hydrological, meteorological, and urbanisation factors, further exacerbated by climate change. This study addresses these complexities by investigating flood susceptibility in rapidly urbanising regions prone to extreme weather events, focusing on Gdańsk, Poland. Three popular ML techniques, Support Vector Machine (SVM), Random Forest (RF), and...
-
Fast multi-objective design optimization of microwave and antenna structures using data-driven surrogates and domain segmentation
PublicationPurpose Strategies and algorithms for expedited design optimization of microwave and antenna structures in multi-objective setup are investigated. Design/methodology/approach Formulation of the multi-objective design problem oriented towards execution of the population-based metaheuristic algorithm within the segmented search space is investigated. Described algorithmic framework exploit variable fidelity modeling, physics- and...
-
Buried Object Characterization Using Ground Penetrating Radar Assisted by Data-Driven Surrogate-Models
PublicationThis work addresses artificial-intelligence-based buried object characterization using 3-D full-wave electromagnetic simulations of a ground penetrating radar (GPR). The task is to characterize cylindrical shape, perfectly electric conductor (PEC) object buried in various dispersive soil media, and in different positions. The main contributions of this work are (i) development of a fast and accurate data driven surrogate modeling...
-
Genetic and Proteomic data
Open Research DataGenetic and Proteomic data (shotgun proteomics) for Uroseptic and UTI E. coli strains.
-
Sierakowice 2020- video data
Open Research DataSierakowice 2020- video data
-
Automated Valuation Model based on fuzzy and rough set theory for real estate market with insufficient source data
PublicationObjective monitoring of the real estate value is a requirement to maintain balance, increase security and minimize the risk of a crisis in the financial and economic sector of every country. The valuation of real estate is usually considered from two points of view, i.e. individual valuation and mass appraisal. It is commonly believed that Automated Valuation Models (AVM) should be devoted to mass appraisal, which requires a large...
-
The role and importance of WIMAX mobile system as a high-performance data transfer technology in wireless sensor networks for wide area monitoring applications
PublicationThe study discuses basic features and functional design of WiMAX Mobile system, based on the IEEE 802.16e (Release 1.5 Rev. 2.0) standard. The analysis has been made in terms of ability to use this system to transmit video stream related to monitoringof large agglomeration areas. What is more, the study includes comparison of technical parameters of WiMAX Mobile system with competitive systems such as: HSPA+ and UMTS-LTE, which...