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Search results for: MISSING DATA PREDICTION
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Missing Verification of Source Data in Hypertension Research: The HYGIA PROJECT in Perspective
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Chemometric exploration of sea water chemical component data sets with missing elements
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Different philosophical approaches to estimating missing data in AHP frameworks for uncertainty representation in risk assessments
PublicationAHP (ang. Analytic Hierarchy Process) jest jedną z metod szeroko stosowaną w wieloatrybutowym podejmowaniu decyzji. Zwykle ekspert lub grupa ekspertów jest proszona o wyrażenie swojej subiektywnej opinii o każdej z par wariantów decyzyjnych. Na tej podstawie tworzone są tzw. macierze ocen. Zdarza się często, że macierze takie są niekompletne i wtedy występuje problem brakujących danych. Referat dotyczy wybranych metod ich uzupełnienia.
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Algorithms for Ship Movement Prediction for Location Data Compression
PublicationDue to safety reasons, the movement of ships on the sea, especially near the coast should be tracked, recorded and stored. However, the amount of vessels which trajectories should be tracked by authorized institutions, often in real time, is usually huge. What is more, many sources of vessels position data (radars, AIS) produces thousands of records describing route of each tracked object, but lots of that records are correlated...
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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...
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Numerical weather prediction - data fusion to GIS systems and potential applications
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Data Sampling-Based Feature Selection Framework for Software Defect Prediction
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Preeclampsia Risk Prediction Using Machine Learning Methods Trained on Synthetic Data
PublicationThis paper describes a research study that investigates the use of machine learning algorithms on synthetic data to classify the risk of developing preeclampsia by pregnant women. Synthetic datasets were generated based on parameter distributions from three real patient studies. Four models were compared: XGBoost, Support Vector Machine (SVM), Random Forest, and Explainable Boosting Machines (EBM). The study found that the XGBoost...
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Prediction of flow boiling heat transfer data for R134a, R600a and R290 in minichannels
PublicationIn the paper presented is the analysis of the results of calculations using a model to predict flow boiling of refrigerants such as R134a, R600a and R290. The latter two fluids were not used in development of model semiempirical correction. For that reason the model was verified with present experimental data. The experimental research was conducted for a full range of quality variation and a relatively wide range of mass velocity....
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The Influence of Input Data Standardization Method on Prediction Accuracy of Artificial Neural Networks
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Cavitation based cleaner technologies for biodiesel production and processing of hydrocarbon streams: A perspective on key fundamentals, missing process data and economic feasibility – A review
PublicationThe present review emphasizes the role of hydrodynamic cavitation (HC) and acoustic cavitation in clean and green technologies for selected fuels (of hydrocarbon origins such as gasoline, naphtha, diesel, heavy oil, and crude oil) processing applications including biodiesel production. Herein, the role of cavitation reactors, their geometrical parameters, physicochemical properties of liquid media, liquid oxidants, catalyst loading,...
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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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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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ADAPTATION OF ENGINEERING FEA-BASED ALGORITHMS TO LCF FAILURE AND MATERIAL DATA PREDICTION IN OFFSHORE DESIGN
PublicationThere is an ever growing industrial demand for quantitative assessment of fatigue endurance of critical structural details. Although FEA-based calculations have become a standard in engineering design, problems involving the Low-To-Medium cycle range (101-104) remain challenging. This paper presents an attempt to optimally choose material data, meshing density and other algorithm settings in the context of recent design of the...
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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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Personalized prediction of the secondary oocytes number after ovarian stimulation: A machine learning model based on clinical and genetic data
PublicationControlled ovarian stimulation is tailored to the patient based on clinical parameters but estimating the number of retrieved metaphase II (MII) oocytes is a challenge. Here, we have developed a model that takes advantage of the patient’s genetic and clinical characteristics simultaneously for predicting the stimulation outcome. Sequence variants in reproduction-related genes identified by next-generation sequencing were matched...
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Prediction of protein structure with the coarse-grained UNRES force field assisted by small X-ray scattering data and knowledge-based information
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Cytokine TGFβ Gene Polymorphism in Asthma: TGF-Related SNP Analysis Enhances the Prediction of Disease Diagnosis (A Case-Control Study With Multivariable Data-Mining Model Development)
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Balanced Spider Monkey Optimization with Bi-LSTM for Sustainable Air Quality Prediction
PublicationA reliable air quality prediction model is required for pollution control, human health monitoring, and sustainability. The existing air quality prediction models lack efficiency due to overfitting in prediction model and local optima trap in feature selection. This study proposes the Balanced Spider Monkey Optimization (BSMO) technique for effective feature selection to overcome the local optima trap and overfitting problems....
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Piotr Paradowski dr
PeopleDr Piotr Paradowski's areas of expertise in quantitative social science methods include truncated and censored models, quantile regressions, survival analysis, panel data models, discrete regressions and qualitative choice models, instrumental variable estimation, and hierarchical modeling. He is also an expert in statistical matching and statistical methods to handle missing data. In addition, he conducts research on income and...
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Chemometrics for Selection, Prediction, and Classification of Sustainable Solutions for Green Chemistry—A Review
PublicationIn this review, we present the applications of chemometric techniques for green and sustainable chemistry. The techniques, such as cluster analysis, principal component analysis, artificial neural networks, and multivariate ranking techniques, are applied for dealing with missing data, grouping or classification purposes, selection of green material, or processes. The areas of application are mainly finding sustainable solutions...
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Identification of category associations using a multilabel classifier
PublicationDescription of the data using categories allows one to describe it on a higher abstraction level. In this way, we can operate on aggregated groups of the information, allowing one to see relationships that do not appear explicit when we analyze the individual objects separately. In this paper we present automatic identification of the associations between categories used for organization of the textual data. As experimental data...
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Zdzisław Kowalczuk prof. dr hab. inż.
PeopleZdzislaw Kowalczuk received his M.Sc. degree in 1978 and Ph.D. degree in 1986, both in Automatic Control from Technical University of Gdańsk (TUG), Gdańsk, Poland. In 1993 he received his D.Sc. degree (Dr Habilitus) in Automatic Control from Silesian Technical University, Gliwice, Poland, and the title of Professor from the President of Poland in 2003. Since 1978 he has been with Faculty of Electronics, Telecommunications and Informatics...
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Evaluating the risk of endometriosis based on patients’ self-assessment questionnaires
PublicationBackground Endometriosis is a condition that significantly affects the quality of life of about 10 % of reproductive-aged women. It is characterized by the presence of tissue similar to the uterine lining (endometrium) outside the uterus, which can lead lead scarring, adhesions, pain, and fertility issues. While numerous factors associated with endometriosis are documented, a wide range of symptoms may still be undiscovered. Methods In...
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Online sound restoration system for digital library applications
PublicationAudio signal processing algorithms were introduced to the new online non-commercial service for audio restoration intended to enhance the content of digitized audio repositories. Missing or distorted audio samples are predicted using neural networks and a specific implementation of the Jannsen interpolation method based on the autoregressive model (AR) combined with the iterative restoring of missing signal samples. Since the distortion...
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Online sound restoration system for digital library applications.
PublicationAudio signal processing algorithms were introduced to the new online non-commercial service for audio restoration intended to enhance the content of digitized audio repositories. Missing or distorted audio samples are predicted using neural networks and a specific implementation of the Jannsen interpolation method based on the autoregressive model (AR) combined with the iterative restoring of missing signal samples. Since the distortion...
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Andrzej Chybicki dr inż.
PeopleA graduate of the Faculty of Electronics, Telecommunications and Informatics at the Gdańsk University of Technology, PhD in technical sciences in the field of IT specializing in distributed data processing in IT . Aimed at exploiting the achievements and knowledge in the field of industrial research. He cooperated with a number of companies including OpeGieka Elbląg, Reson Inc., Powel Sp. z o. o., Wasat, Better Solutions, the European...
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Expectation-Maximization Model for Substitution of Missing Values Characterizing Greenness of Organic Solvents
PublicationOrganic solvents are ubiquitous in chemical laboratories and the Green Chemistry trend forces their detailed assessments in terms of greenness. Unfortunately, some of them are not fully characterized, especially in terms of toxicological endpoints that are time consuming and expensive to be determined. Missing values in the datasets are serious obstacles, as they prevent the full greenness characterization of chemicals. A featured...
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Magdalena Szuflita-Żurawska
PeopleHead of the Scientific and Technical Information Services at the Gdansk University of Technology Library and the Leader of the Open Science Competence Center. She is also a Plenipotentiary of the Rector of the Gdańsk University of Technology for open science. She is a PhD Candidate. Her main areas of research and interests include research productivity, motivation, management of HEs, Open Access, Open Research Data, information...
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Syntetyczne wskaźniki oceny stanu toru
PublicationJakość geometryczna toru analizowana jest w różnych celach, a dane podlegają różnemu stopniowi agregacji. Pojedyncze nierówności toru analizowane są zazwyczaj z uwagi na bezpieczeństwo i służą do planowanie napraw w krótkich terminach. Natomiast agregacja pomierzonych parametrów pozwala na planowanie robót w terminach średniookresowych i budowę modeli predykcji. W artykule przedstawiono zagregowane wskaźniki jakości geometrycznej...
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Rating Prediction with Contextual Conditional Preferences
PublicationExploiting contextual information is considered a good solution to improve the quality of recommendations, aiming at suggesting more relevant items for a specific context. On the other hand, recommender systems research still strive for solving the cold-start problem, namely where not enough information about users and their ratings is available. In this paper we propose a new rating prediction algorithm to face the cold-start...
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Client-side versus server-side geographic data processing performance comparison: Data and code
PublicationThe data and code presented in this article are related to the research article entitled “Analysis of Server-side and Client-side Web-GIS data processing methods on the example of JTS and JSTS using open data from OSM and Geoportal” (Kulawiak et al., 2019). The provided 12 datasets include multi-point and multi-polygon data of different scales and volumes, representing real-world geographic features. The datasets cover the area...
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Badanie i analiza efektywności alokacji strumieni danych w heterogenicznej sieci WBAN
PublicationW niniejszej dysertacji doktorskiej poddano dyskusji efektywność alokacji strumieni danych w heterogenicznej radiowej sieci WBAN (Wireless Body Area Networks). Biorąc pod uwagę dynamiczny rozwój nowoczesnych sieci radiokomunikacyjnych piątej generacji (5G), którego część stanowią radiowe sieci działające w obrębie ciała człowieka, bardzo ważnym aspektem są metody maksymalizujące wykorzystanie dostępnych zasobów czasowo –częstotliwościowych...
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Data on LEGO sets release dates and worldwide retail prices combined with aftermarket transaction prices in Poland between June 2018 and June 2023
PublicationThe dataset contains LEGO bricks sets item count and pricing history for AI-based set pricing prediction. The data spans the timeframe from June 2018 to June 2023. The data was obtained from three sources: Brickset.com (LEGO sets retail prices, release dates, and IDs), Lego.com official web page (ID number of each set that was released by Lego, its retail prices, the current status of the set) and promoklocki.pl web page (the retail...
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Participatory Budgeting in Poland – Missing Link in Urban Regeneration Process
PublicationIn last thirty years Poland has gone a long way toward democracy and decentralization. Role of public participation in planning is increasing rapidly and recently many new instruments of empowering the community is being introduced, participatory budgeting is one of the most important. On the other hand, urban regeneration is one of the most important challenges of polish cities are facing. Technical and transport infrastructure...
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Big Data i 5V – nowe wyzwania w świecie danych (Big Data and 5V – New Challenges in the World of Data)
PublicationRodzaje danych, składające się na zbiory typu Big Data, to m.in. dane generowane przez użytkowników portali internetowych, dane opisujące transakcje dokonywane poprzez Internet, dane naukowe (biologiczne, astronomiczne, pomiary fizyczne itp.), dane generowane przez roboty w wyniku automatycznego przeszukiwania przez nie Internetu (Web mining, Web crawling), dane grafowe obrazujące powiązania pomiędzy stronami WWW itd. Zazwyczaj,...
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An Intelligent Approach to Short-Term Wind Power Prediction Using Deep Neural Networks
PublicationIn this paper, an intelligent approach to the Short-Term Wind Power Prediction (STWPP) problem is considered, with the use of various types of Deep Neural Networks (DNNs). The impact of the prediction time horizon length on accuracy, and the influence of temperature on prediction effectiveness have been analyzed. Three types of DNNs have been implemented and tested, including: CNN (Convolutional Neural Networks), GRU (Gated Recurrent...
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Data Analytics Meeting
EventsData Analytics Meeting Konferencja studentów i doktorantów
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Akaike's final prediction error criterion revisited
PublicationWhen local identification of a nonstationary ARX system is carried out, two important decisions must be taken. First, one should decide upon the number of estimated parameters, i.e., on the model order. Second, one should choose the appropriate estimation bandwidth, related to the (effective) number of input-output data samples that will be used for identification/ tracking purposes. Failure to make the right decisions results...
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Integrated Sectors - Diversified Earnings: The (Missing) Impact of Offshoring on Wages and Wage Convergence in the EU27
PublicationThis paper assesses the impact of international outsourcing/offshoring practices on the process of wage equalization across manufacturing sectors in a sample of EU27 economies (1995-2009). We discriminate between heterogeneous wage effects on different skill categories of workers (low, medium and high skill). The main focus is on the labour market outcomes of vertical integration, so we augment a model of conditional wage convergence...
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ATOMIC DATA AND NUCLEAR DATA TABLES
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Tool Wear Prediction in Single-Sided Lapping Process
PublicationSingle-sided lapping is one of the most effective planarization technologies. The process has relatively complex kinematics and it is determined by a number of inputs parameters. It has been noted that prediction of the tool wear during the process is critical for product quality control. To determine the profile wear of the lapping plate, a computer model which simulates abrasive grains trajectories was developed in MATLAB. Moreover,...
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Missing Puzzle Pieces in Dementia Research: HCN Channels and Theta Oscillations
PublicationIncreasing evidence indicates a role of hyperpolarization activated cation (HCN) channels in controlling the resting membrane potential, pacemaker activity, memory formation, sleep, and arousal. Their disfunction may be associated with the development of epilepsy and age-related memory decline. Neuronal hyperexcitability involved in epileptogenesis and EEG desynchronization occur in the course of dementia in human Alzheimer’s Disease...
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A Perspective on Missing Aspects in Ongoing Purification Research towards Melissa officinalis
PublicationMelissa officinalis L. is a medicinal plant used worldwide for ethno-medical purposes. Today, it is grown everywhere; while it is known to originate from Southern Europe, it is now found around the world, from North America to New Zealand. The biological properties of this medicinal plant are mainly related to its high content of phytochemical (bioactive) compounds, such as flavonoids, polyphenolic compounds, aldehydes, glycosides...
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Data Warehouses 2023/2024
e-Learning CoursesThe aim of the course is to familiarize students with the development process of data warehouses for BI systems. The course is prepared for students of Data Engineering.
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Ship Resistance Prediction with Artificial Neural Networks
PublicationThe paper is dedicated to a new method of ship’s resistance prediction using Artificial Neural Network (ANN). In the initial stage selected ships parameters are prepared to be used as a training and validation sets. Next step is to verify several network structures and to determine parameters with the highest influence on the result resistance. Finally, other parameters expected to impact the resistance are proposed. The research utilizes...
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Data in Brief
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Data Analysis in Bridge of Data
PublicationThe chapter presents the data analysis aspects of the Bridge of Data project. The software framework used, Jupyter, and its configuration are presented. The solution’s architecture, including the TRYTON supercomputer as the underlying infrastructure, is described. The use case templates provided by the Stat-reducer application are presented, including data analysis related to spatial points’ cloud-, audio- and wind-related research.
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Multicomponent ionic liquid CMC prediction
PublicationWe created a model to predict CMC of ILs based on 704 experimental values published in 43 publications since 2000. Our model was able to predict CMC of variety of ILs in binary or ternary system in a presence of salt or alcohol. The molecular volume of IL (Vm), solvent-accessible surface (Sˆ), solvation enthalpy (DsolvGN), concentration of salt (Cs) or alcohol (Ca) and their molecular volumes (Vms and Vma, respectively) were chosen...
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GIS Solution for Weather Forecast Data Analysis
PublicationIn this paper authors present the GIS system for the analysis of the numerical weather prediction data. This kind of data has multidimensional character (three dimensions and time) and its analysis should consider all the available factors. Proposed GIS system consists of RASDAMAN application with implemented OLAP cube mechanism, which enables the user to process data in the spatial-time domain. It also simplifies the meteorological...