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Search results for: MISSING DATA PREDICTION
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EVALUATION OF THE NO2CONCENTRATION PREDICTION POSSIBILITYBASED ON STATIC AND DYNAMIC RESPONSES OF TGS SENSORSAT CHANGING HUMIDITY LEVELS
PublicationThe commercially available metal-oxide TGS sensors are widely used in many applications due to thefact that they are inexpensive and considered to be reliable. However, they are partially selective and theirresponses are influenced by various factors,e.g. temperature or humidity level. Therefore, it is importanttodesign a proper analysis system of the sensor responses. In this paper, the results of examinations of eightcommercial...
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Prediction of manoeuvring abilities of 10000 DWT pod-driven coastal tanker
PublicationThis paper aims to present a new approach in the prediction of manoeuvring abilities of pod-driven ships. A new mathematical model of motions based on MMG methodology was developed and a new type of description of forces acting on azimuth drives is presented. Captive model tests of medium-size coastal tanker and pod open water tests were carried out in CTO S.A. (Ship Design and Research Centre S.A.) to obtain hull hydrodynamic derivatives...
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Anna Wałek dr
PeopleDr Anna Wałek, President of IATUL – International Association of University Libraries, director of the Gdańsk University of Technology Library. An experienced library manager, an expert in the field of Open Science, and organization and management of a scientific library. She conducts scientific research in data management in various scientific disciplines, metadata for research data, and data management support services - incl....
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DATA JOURNALS AND DATA PAPERS IN VARIOUS RESEARCH AREAS AND SCIENTIFIC DISCIPLINES – BIBLIOMETRIC ANALYSIS BASED ON INCITES
PublicationThe main aim of this work is to provide insight into a bibliometric analysis of Data Journals and Data Papers in terms of research areas, disciplines, publication year and country. In particular, we calculated many bibliometric indicators, especially: the number of publications and citations. Furthermore, this work also investigated the top 20 journals in which scientists published the largest number of Data Papers. It was found...
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Forewarned Is Forearmed: Machine Learning Algorithms for the Prediction of Catheter-Induced Coronary and Aortic Injuries
PublicationCatheter-induced dissections (CID) of coronary arteries and/or the aorta are among the most dangerous complications of percutaneous coronary procedures, yet the data on their risk factors are anecdotal. Logistic regression and five more advanced machine learning techniques were applied to determine the most significant predictors of dissection. Model performance comparison and feature importance ranking were evaluated. We identified...
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Robust output prediction of differential – algebraic systems – application to drinking water distribution system
PublicationThe paper presents the recursive robust output variable prediction algorithm, applicable for systems described in the form of nonlinear algebraic-differential equations. The algorithm bases on the uncertainty interval description, the system model, and the measurements. To improve the algorithm efficiency, nonlinear system models are linearised along the nominal trajectory. The effectiveness of the algorithm is demonstrated on...
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Rapid antenna design optimization using shape-preserving response prediction
PublicationAn approach to rapid optimization of antennas using the shape-preserving response-prediction (SPRP) technique and coarsediscretization electromagnetic (EM) simulations (as a low-fidelity model) is presented. SPRP allows us to estimate the response of the high-fidelity EM antenna model, e.g., its reflection coefficient versus frequency, using the properly selected set of so-called characteristic points of the low-fidelity model...
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Mining Knowledge of Respiratory Rate Quantification and Abnormal Pattern Prediction
PublicationThe described application of granular computing is motivated because cardiovascular disease (CVD) remains a major killer globally. There is increasing evidence that abnormal respiratory patterns might contribute to the development and progression of CVD. Consequently, a method that would support a physician in respiratory pattern evaluation should be developed. Group decision-making, tri-way reasoning, and rough set–based analysis...
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Data Mining Applications and Methods in Medicine
PublicationIn this paper we describe the research area of data mining and its applications in medicine. The origins of data mining and its crucial features are shortly presented. We discuss the specificity of medicine as an application area for computer systems. Characteristic features of the medical data are investigated. Common problems in the area are also presented as well as the strengths and capabilities of the data mining methods....
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Sharing research data across disciplines
PublicationThis monograph is a collection of experiences gathered by the team implementing the Bridge of Data project. However, it is not just a simple summary of the project implementation. It shows and systematizes the substantive and technical works performed by the teams and several issues related to data management itself in various disciplines, represented by members of the scientific team and other researchers from partner universities.The...
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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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Machine learning-based prediction of seismic limit-state capacity of steel moment-resisting frames considering soil-structure interaction
PublicationRegarding the unpredictable and complex nature of seismic excitations, there is a need for vulnerability assessment of newly constructed or existing structures. Predicting the seismic limit-state capacity of steel Moment-Resisting Frames (MRFs) can help designers to have a preliminary estimation and improve their views about the seismic performance of the designed structure. This study improved data-driven decision techniques in...
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Surrogate Modeling and Optimization Using Shape-Preserving Response Prediction: A Review
PublicationComputer simulation models are ubiquitous in modern engineering design. In many cases, they are the only way to evaluate a given design with sufficient fidelity. Unfortunately, an added computa-tional expense is associated with higher fidelity models. Moreover, the systems being considered are often highly nonlinear and may feature a large number of designable parameters. Therefore, it may be impractical to solve the design problem...
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Time window based features extraction from temperature modulated gas sensors for prediction of ammonia concentration
PublicationElectronic gas recognition systems, in literature commonly referred as electronic noses, enable the recognition of a type and a concentration of various volatile compounds. Typical electronic gas-analyzing device consists of four main elements, namely, gas delivery subsystem, an array of gas sensors, data acquisition and power supply circuits and data analysis software. The commercially available metal-oxide TGS sensors are widely...
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Improving the prediction of biochar production from various biomass sources through the implementation of eXplainable machine learning approaches
PublicationExamining the game-changing possibilities of explainable machine learning techniques, this study explores the fast-growing area of biochar production prediction. The paper demonstrates how recent advances in sensitivity analysis methodology, optimization of training hyperparameters, and state-of-the-art ensemble techniques have greatly simplified and enhanced the forecasting of biochar output and composition from various biomass...
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Radar data fusion in the STRADAR system
PublicationThe main task of the Polish Border Guard is protection of the country’s border which requires utilization of multimedia surveillance systems automatically gathering, processing and sharing various data. The paper presents such a system developed for the Maritime Division of the Polish Border Guard within the STRADAR project and the problem of fusion of radar data in this system. The system, apart from providing communication means,...
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Sampling-based novel heterogeneous multi-layer stacking ensemble method for telecom customer churn prediction
PublicationIn recent times, customer churn has become one of the most significant issues in business-oriented sectors with telecommunication being no exception. Maintaining current customers is particularly valuable due to the high degree of rivalry among telecommunication companies and the costs of acquiring new ones. The early prediction of churned customers may help telecommunication companies to identify the causes of churn and design...
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Olgun Aydin dr
PeopleOlgun Aydin finished his PhD by publishing a thesis about Deep Neural Networks. He works as a Principal Machine Learning Engineer in Nike, and works as Assistant Professor in Gdansk University of Technology in Poland. Dr. Aydin is part of editorial board of "Journal of Artificial Intelligence and Data Science" Dr. Aydin served as Vice-Chairman of Why R? Foundation and is member of Polish Artificial Intelligence Society. Olgun is...
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Application of the Heavy-Atom Effect for (Sub)microsecond Thermally Activated Delayed Fluorescence and an All-Organic Light-Emitting Device with Low-Efficiency Roll-off
PublicationThefeatureof abundantandenvironmentallyfriendlyheavyatoms(HAs)like bromineto acceleratespin-forbiddentransitionsin organicmoleculeshas beenknownforyears.In combinationwiththe easinessof incorporation,brominederivativesof organicemittersshowingthermallyactivateddelayedfluorescence(TADF)emergeas a cheapand efficientsolutionforthe slowreverseintersystemcrossing(rISC)problemin suchemittersand strongefficiencyroll-offof all-organiclight-emittingdiodes(OLEDs).Here,we...
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Prediction of metal deformation due to line heating; an alternative method of mechanical bending, based on artificial neural network approach
PublicationLine heating is one of the alternative methods of forming metals and this kind of forming uses the heating torch as a source of heat input. During the process, many parameters are considered like the size of the substrate, thickness, cooling method, source power intensity, the travel speed of the power source, the sequence of heating, and so on. It is important to analyze the factors affecting the...
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Review of Selected Methods for Prediction of Added Resistance in Following Waves
PublicationThe added resistance in waves is a mean value of non-linear, second order reaction of a ship to incoming waves. In the beginning of the 20th century, the experimental methods for investigation of ship hydrodynamics at model scale were developed. They allowed the evaluation of added resistance by measurements in irregular waves (directly) or by measurements in regular waves (in-direct method). The main goal was to find more precise...
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Big Data in Regenerative Urban Design
PublicationWhy the use of Big Data in regenerative planning matters? The aim of this chapter is to study under what conditions Big Data can be integrated into regenerative design and sustainable planning? Authors seek to answer how – when related to the ecosystem and to human activities – Big Data can be used to: • both shape policies that support the development of regenerative human settlements, • support restorative design for practitioners...
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The Use of Big Data in Regenerative Planning
PublicationWith the increasing significance of Big Data sources and their reliability for studying current urban development processes, new possibilities have appeared for analyzing the urban planning of contemporary cities. At the same time, the new urban development paradigm related to regenerative sustainability requires a new approach and hence a better understanding of the processes changing cities today, which will allow more efficient...
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Analiza danych typu Big Data 2023/24 KOPIA
e-Learning CoursesThe aim of the course is to familiarize students with the methods of storing and analysis of big data. Practical tools for these tasks are presented.
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Validating data acquired with experimental multimodal biometric system installed in bank branches
PublicationAn experimental system was engineered and implemented in 100 copies inside a real banking environment comprising: dynamic handwritten signature verification, face recognition, bank client voice recognition and hand vein distribution verification. The main purpose of the presented research was to analyze questionnaire responses reflecting user opinions on: comfort, ergonomics, intuitiveness and other aspects of the biometric enrollment...
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CPLFD-GDPT5: High-resolution gridded daily precipitation and temperature data set for two largest Polish river basins
PublicationThe CHASE-PL (Climate change impact assessment for selected sectors in Poland) Forcing Data–Gridded Daily Precipitation & Temperature Dataset–5 km (CPLFD-GDPT5) consists of 1951–2013 daily minimum and maximum air temperatures and precipitation totals interpolated onto a 5 km grid based on daily meteorological observations from the Institute of Meteorology and Water Management (IMGW-PIB; Polish stations), Deutscher Wetterdienst...
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Accurate modelling of microwave structures using shape-preserving response prediction
PublicationArtykuł prezentuje metodologię dokładnego modelowania struktur mikrofalowych. Jest to zmodyfikowana wersja techniki opartej na procedurze przewidywania odpowiedzi z zachowaniem kształtu (shape-preserving response prediction, SPRP), która oszacowuje odpowiedź struktury mikrofalowej otrzymanej poprzez kosztowną obliczeniowo symulację elektromagnetyczną za pomocą taniego obliczeniowo modelu tejże struktury. Modyfikacja polega na wykorzystaniu...
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Integration and verification of meteorological observations and NWP model data for the local GNSS tomography
PublicationGNSS meteorology applies the Global Navigation Satellite Systems (GNSS) to derive information about the state of the atmosphere (particularly troposphere). The tomography is one of the methods used in GNSS meteorology. The input data of GNSS tomography are the signal troposphere delays, results of GNSS data processing and additionally meteorological observations and Numerical Weather Prediction (NWP) models data. Different types...
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A Text as a Set of Research Data. A Number of Aspects of Data Acquisition and Creation of Datasets in Neo-Latin Studies
PublicationIn this paper, the authors, who specialise in part in neo-Latin studies and the his-tory of early modern education, share their experiences of collecting sources for Open Research Data sets under the Bridge of Data project. On the basis of inscription texts from St. Mary’s Church in Gdańsk, they created 29 Open Research Data sets. In turn, the text of the lectures of the Gdańsk scholar Michael Christoph Hanow, Praecepta de arte...
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Application of a hybrid mechanistic/machine learning model for prediction of nitrous oxide (N2O) production in a nitrifying sequencing batch reactor
PublicationNitrous oxide (N2O) is a key parameter for evaluating the greenhouse gas emissions from wastewater treatment plants. In this study, a new method for predicting liquid N2O production during nitrification was developed based on a mechanistic model and machine learning (ML) algorithm. The mechanistic model was first used for simulation of two 15-day experimental trials in a nitrifying sequencing batch reactor. Then, model predictions...
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Big Data 2023
e-Learning Courses -
Data quality assurance
e-Learning CoursesThe first lecture: 22.02.2021 at 8:15 on Teams Pierwszy wykład: 22.02.2021 o 8:15 w Teams ---------------------------------------------- Kierunek: Inżynieria danych (WETI) Studia I stopnia - inżynierskie, stacjonarne, semestr 6
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Advanced data mining
e-Learning Courses -
Collaborative Data Acquisition and Learning Support
PublicationWith the constant development of neural networks, traditional algorithms relying on data structures lose their significance as more and more solutions are using AI rather than traditional algorithms. This in turn requires a lot of correctly annotated and informative data samples. In this paper, we propose a crowdsourcing based approach for data acquisition and tagging with support for Active Learning where the system acts as an...
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Performance Modeling and Prediction of Real Application Workload in a Volunteer-based System
PublicationThe goal of this paper is to present a model that predicts the real workload placed on a volunteer based system by an application, with incorporation of not only performance but also availability of volunteers. The application consists of multiple data packets that need to be processed. Knowing the computational workload demand of a single data packet we show how to estimate the application workload in a volunteer based system. Furthermore,...
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Quality prediction of foil capacitors by acoustic emission signals
PublicationJakość i trwałość kondensatorów foliowych jest zależna od ich warunków pracy (np. nadmiarowego napięcia pracy, temperatury, wilgotności) oraz od potencjalnych defektów wprowadzonych na różnych etapach wytwarzania kondensatorów. Nieustanny nacisk na wzrost jakości wytwarzanych elementów przy jednoczesnej redukcji kosztów wytwarzania oznacza, że nowe, tanie i szybkie metody predykcji jakości tych elementów są mocno poszukiwane. W...
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Active Learning Based on Crowdsourced Data
PublicationThe paper proposes a crowdsourcing-based approach for annotated data acquisition and means to support Active Learning training approach. In the proposed solution, aimed at data engineers, the knowledge of the crowd serves as an oracle that is able to judge whether the given sample is informative or not. The proposed solution reduces the amount of work needed to annotate large sets of data. Furthermore, it allows a perpetual increase...
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Effective Air Quality Prediction Using Reinforced Swarm Optimization and Bi-Directional Gated Recurrent Unit
PublicationIn the present scenario, air quality prediction (AQP) is a complex task due to high variability, volatility, and dynamic nature in space and time of particulates and pollutants. Recently, several nations have had poor air quality due to the high emission of particulate matter (PM2.5) that affects human health conditions, especially in urban areas. In this research, a new optimization-based regression model was implemented for effective...
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Streaming Real-time Data in Distributed Dispatcher and Teleinformation Systems for Visualization of Multimedia Data of the Border Guard
PublicationSurveillance of the sea borders is a very important task for the Border Guard. Monitoring of country maritime border is an important task of the Border Guard. This task can be facilitated with the use of the technology enabling gathering information from distributed sources and its supervision and visualization. This task can be accomplished using a technology that allows to collect information from distributed sensors of different...
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On the impact of Big Data and Cloud Computing on a scalable multimedia archiving system
PublicationMultimedia Archiver (MA) is a system build upon the promise and fascination of the possibilities emerging from cloud computing and big data. We aim to present and describe how the Multimedia Archiving system works for us to record, put in context and allow a swift access to large amounts of data. We introduce the architecture, identified goals and needs taken into account while designing a system processing data with Big Data...
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Big Data Analytics for ICT Monitoring and Development
PublicationThe expanded growth of information and communication technology has opened new era of digitization which is proving to be a great challenge for researchers and scientists around the globe. The utmost paradigm is to handle and process the explosion of data with minimal cost and discover relevant hidden information in the least amount of time. The buzz word “BIG DATA” is a widely anticipated term with the potential to handle heterogeneous,...
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Ontology-based text convolution neural network (TextCNN) for prediction of construction accidents
PublicationThe construction industry suffers from workplace accidents, including injuries and fatalities, which represent a significant economic and social burden for employers, workers, and society as a whole.The existing research on construction accidents heavily relies on expert evaluations,which often suffer from issues such as low efficiency, insufficient intelligence, and subjectivity.However, expert opinions provided in construction...
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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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3D MODELLING OF CYLINDRICAL-SHAPED OBJECTS FROM LIDAR DATA - AN ASSESSMENT BASED ON THEORETICAL MODELLING AND EXPERIMENTAL DATA
PublicationDespite the increasing availability of measured laser scanning data and their widespread use, there is still the problem of rapid and correct numerical interpretation of results. This is due to the large number of observations that carry similar information. Therefore, it is necessary to extract from the results only the essential features of the modelled objects. Usually, it is based on a process using filtration, followed by...
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Linking music data in executable documents
PublicationThis paper presents the application of Interactive Open Document Architecture (IODA) to music and video data. This architecture was design to create multilayer documents which consist of many files. The paper shows the method of creating media documents on the basis of IODA. These kind of documents were called IODA Media Documents (IMD). IMD have links that connect many different kinds of files containing music and video data....
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AN INNOVATIVE APPROACH TO PREDICTION ENERGETIC EFFECTS OF WOOD CUTTING PROCESS WITH CIRCULAR-SAW BLADES
PublicationIn the classical approach, energetic effects (cutting forces and cutting power) of wood sawing process are generally calculated on the basis of the specific cutting resistance, which is in the case of wood cutting the function of more or less important factors. The aim of the paper is to present a new calculating model using the application of modern fracture mechanics and to compare cutting parameters of native beech, Bendywood...
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Data reduction and stacking for imbalanced data classification
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numerical prediction of vortex generated by hydrofoil
PublicationW pracy przedstawiono wyniki obliczeń programami Fluent i Comet dla płata śruby napędowej. Pola prędkości oraz wirowość za płatem porównano z wynikami pomiarów (LDA- Laser Doppler Anemometry) w tunelu kawitacyjnym Centrum Techik Okrętowych (CTO). Przedstawiono wpływ adaptacji siatki wg różnych kryteriów (lokalnej wirowości lub prędkości) na zgodność wyników obliczeń z danymi eksperymentalnymi.
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Toward Prediction of Environmental Arctic Change
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Bankruptcy Prediction - History, Present and Future.
PublicationW artykule przedstawiono krótką wzmiankę dotyczącą dotychczasowych badań w obszarze zagrożenia przedsiębiorstw upadłością, techniki wykorzystywane do budowy modeli prognozowania upadłości przedsiębiorstw oraz metody stosowane w analizie porównawczej tego typu modeli.