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Search results for: model predictive control
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The Predictive Role of Positive Mental Health for Attitudes Towards Suicide and Suicide Prevention: Is the Well-Being of Students of the Helping Professions a Worthwhile Goal for Suicide Prevention?
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Lack of control over work and organizational citizenship behavior: overwork climate as a suppressor variable
Open Research DataThis study investigates a suppressor effect in the relationship between lack of control over work and organizational citizenship behavior (OCB). Suppressor effects operate when the addition of a predictor (in our study it is an overwork climate) increases the predictive power of another variable (lack of control over work) in predicting an outcome variable...
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Predykcyjne sterowanie równoległym filtrem aktywnym ze sprzężeniem od prądu zasilającego
PublicationArtykuł przedstawia nowatorską strategię predykcyjnego sterowania równoległym energetycznym filtrem aktywnym (EFA). Proponowane sterowanie zawiera sprzężenie zwrotne od prądu zasilającego i wiąże zalety sterowania w układzie otwartym oraz zamkniętym – szybkość reakcji na zmianę prądu odbioru i bardzo wysoką skuteczność kompensacji. Wysoka jakość prądu kompensacyjnego wynika również z zastosowania w sterowaniu algorytmów predykcyjnych,...
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Can Web Search Queries Predict Prices Change on the Real Estate Market?
PublicationThis study aims to explore whether the intensity of internet searches, according to the Google Trends search volume index (SVI), is a predictor of changes in real estate prices. The motivation of this study is the possibility to extend the understanding of the extra predictive power of Google search engine query volume of future housing price change (shift direction) by (i) the introduction of a research approach that combines...
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A fuzzy logic model for forecasting exchange rates
PublicationThis article is devoted to the issue of forecasting exchange rates. The objective of the conducted research is to develop a predictive model with the use of an innovative methodology - fuzzy logic theory - and to evaluate its effectiveness in times of prosperity and during the financial crisis. The model is based on sets of rules written by the author in the form of IF-THEN, where expert knowledge is stored. This model is the result...
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Identification of nonstationary multivariate autoregressive processes– Comparison of competitive and collaborative strategies for joint selection of estimation bandwidth and model order
PublicationThe problem of identification of multivariate autoregressive processes (systems or signals) with unknown and possibly time-varying model order and time-varying rate of parameter variation is considered and solved using parallel estimation approach. Under this approach, several local estimation algorithms, with different order and bandwidth settings, are run simultaneously and compared based on their predictive performance. First,...
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Rule-Based Model for Selecting Integration Technologies for Smart Cities Systems
PublicationThe aim of this article is to present the stages of development for an information technology integration model for the design of systems for smart cities. The Introduction explains the need for integration technologies and presents a model for selecting integration technologies and the conditions for its use in designing smart cities systems. Then two verification stages of the presented model are discussed. In the first stage,...
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Innovations in Wastewater Treatment: Harnessing Mathematical Modeling and Computer Simulations with Cutting-Edge Technologies and Advanced Control Systems
PublicationThe wastewater treatment landscape in Central Europe, particularly in Poland, has undergone a profound transformation due to European Union (EU) integration. Fueled by EU funding and rapid technological advancements, wastewater treatment plants (WWTPs) have adopted cutting-edge control methods to adhere to EU Water Framework Directive mandates. WWTPs contend with complexities such as variable flow rates, temperature fluctuations,...
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Michał Czubenko dr inż.
PeopleMichał Czubenko is a distinguished 2009 graduate of the Faculty of Electronics, Telecommunications, and Informatics at Gdańsk University of Technology, specializing in the discipline of automatic control and robotics. Currently, he serves as an adjunct in the Department of Robotics and Decision Systems at the same institution. In 2012, he embarked on a three-month internship at Kingston University London, broadening his horizons...
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CoRBAC – kontekstowo zorientowany model bezpieczeństwa
PublicationZaproponowano uogólniony model kontroli dostępu do usługowych systemów internetowych uwzględniający różne kategorie kontekstu. Określono wpływ kontekstu na model jak i architekturę systemu bezpieczeństwa. Podano przykład implementacji modelu i architektury bezpieczeństwa dla zestawu usług dotyczących e-uczelni i wstępnie oszacowano zalety takiego rozwiązania.
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Data-driven, probabilistic model for attainable speed for ships approaching Gdańsk harbour
PublicationThe growing demand for maritime transportation leads to increased traffic in ports. From this arises the need to observe the consequences of the specific speed ships reach when approaching seaports. However, usually the analyzed cases refer only to the statistical evaluation of the studied phenomenon or to the empirical modelling, ignoring the mutual influence of variables such as ship type, length or weather conditions. In this...
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Magnetic Signature Description of Ellipsoid-Shape Vessel Using 3D Multi-Dipole Model Fitted on Cardinal Directions
PublicationThe article presents a continuation of the research on the 3D multi-dipole model applied to the reproduction of magnetic signatures of ferromagnetic objects. The model structure has been modified to improve its flexibility - model parameters determined by optimization can now be located in the cuboid contour representing the object's hull. To stiffen the model, the training dataset was expanded to data collected from all four cardinal...
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High-resolution fire danger forecast for Poland based on the Weather Research and Forecasting Model
PublicationDue to climate change and associated longer and more frequent droughts, the risk of forest fires increases. To address this, the Institute of Meteorology and Water Management implemented a system for forecasting fire weather in Poland. The Fire Weather Index (FWI) system, developed in Canada, has been adapted to work with meteorological fields derived from the high-resolution (2.5 km) Weather Research and Forecasting (WRF) model....
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Krzysztof Jan Kaliński prof. dr hab. inż.
PeopleKrzysztof J. Kaliński completed his MSc study at Gdańsk University of Technology (GUT) Faculty of Production Engineering (1980, result – get a first). He obtained PhD at GUT Faculty of Machine Building (1988, result – get a first), DSc at GUT Faculty of Mechanical Engineering (ME) (2002, result – get a first), and professor’s title – w 2013 r. In 2015 r. he became full professor, and since 2019 - professor.His research area includes:...
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How personality traits, sports anxiety, and general imagery could influence the physiological response measured by SCL to imagined situations in sports?
Open Research DataThe data were collected to understand how individual differences in personality (e.g. neuroticism), general imagery, and situational sports anxiety are linked to arousal measuring with skin conductance level (SCL) in situational imagery (as scripted for sport-related scenes). Thirty persons participated in the study, aged between 14 and 42 years, with...
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CUTTING POWER FORECASTING WHILE WOOD SAWING: FRACTURE MECHANICS APPROACH AND AXELSSON’S MODEL COMPARISON
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. On the other hand, cutting forces (power) could be considered from a point of view of modern fracture mechanics. Another way is to forecast cutting power consumption on...
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Toward a unified model of mobile Business Intelligence (m-BI) acceptance and use
PublicationFactors affecting mobile business intelligence (m-BI) acceptance and use have become an increasingly important topic in practice due to the growing complexity of organizations, and their underlying information systems (IS). Since, one can notice considerable interest in m-BI, however, to the best of our knowledge few studies (if any) aim to synthesize the existing body of knowledge with regards to the factors affecting m-BI acceptance...
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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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Survey on fuzzy logic methods in control systems of electromechanical plants
PublicationРассмотрены алгоритмы управления электромеханическими системами с использованием теории нечеткой логики, приводятся основные положения их синтеза, рассматриваются методы анализа их устойчивости на основе нечетких функций Ляпунова. Эти алгоритмы чаще всего реализуются в виде различных регуляторов, применение которых целесообразно в системах, математическая модель которых не известна, не детерминирована или является строго нелинейной,...
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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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Cost-Efficient Surrogate Modeling of High-Frequency Structures Using Nested Kriging with Automated Adjustment of Model Domain Lateral Dimensions
PublicationSurrogate models are becoming popular tools of choice in mitigating issues related to the excessive cost of electromagnetic (EM)-driven design of high-frequency structures. Among available techniques, approximation modeling is by far the most popular due to its versatility. In particular, the surrogates are exclusively based on the sampled simulation data with no need to involve engineering insight or problem-specific knowledge....
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Accurate Modeling of Frequency Selective Surfaces Using Fully-Connected Regression Model with Automated Architecture Determination and Parameter Selection Based on Bayesian Optimization
PublicationSurrogate modeling has become an important tool in the design of high-frequency structures. Although full-wave electromagnetic (EM) simulation tools provide an accurate account for the circuit characteristics and performance, they entail considerable computational expenditures. Replacing EM analysis by fast surrogates provides a way to accelerate the design procedures. Unfortunately, modeling of microwave passives is a challenging...
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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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Gender-Related Differences in Trimethylamine and Oxidative Blood Biomarkers in Cardiovascular Disease Patients
PublicationGender differences in the burden of cardiovascular disease (CVD) have been observed worldwide. In this study, plasmatic levels of trimethylamine (TMA) and blood oxidative biomarkers have been evaluated in 358 men (89 controls and 269 CVD patients) and 189 women (64 control and 125 CVD patients). The fluorescence technique was applied to determine erythrocyte membrane fluidity using 1,6-diphenyl-1,3,5-hexatriene (DPH) and Laurdan,...
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Physics augmented classification of fNIRS signals
PublicationBackground. Predictive classification favours performance over semantics. In traditional predictive classification pipelines, feature engineering is often oblivious to the underlying phenomena. Hypothesis. In applied domains such as functional Near Infrared Spectroscopy (fNIRS), the exploitation of physical knowledge may improve the discriminative quality of our observation set. Aims. Give exemplary evidence that intervening the...
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Development and validation of a model that includes two ultrasound parameters and the plasma D-dimer level for predicting malignancy in adnexal masses: an observational study
PublicationBackground: Pre-operative discrimination of malignant from benign adnexal masses is crucial for planning additional imaging, preparation, surgery and postoperative care. This study aimed to define key ultrasound and clinical variables and develop a predictive model for calculating preoperative ovarian tumor malignancy risk in a gynecologic oncology referral center. We compared our model to a subjective ultrasound assessment (SUA)...
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The Implementation of Fuzzy Logic in Forecasting Financial Ratios
PublicationThis paper is devoted to the issue of forecasting financial ratios. The objective of the conducted research is to develop a predictive model with the use of an innovative methodology, i.e., fuzzy logic theory, and to evaluate its effectiveness. Fuzzy logic has been widely used in machinery, robotics and industrial engineering. This paper introduces the use of fuzzy logic for the financial analysis of enterprises. While many current...
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Computer Controlled Systems Lab - 2023/2024
e-Learning CoursesComputer Controlled Systems Lab The course includes 5 individual projects and their laboratory implementation. The topics:- Job analysis and tuning digital servo- Usage of a PC computer and MatLab package for controlling the dynamic object as a model of the tethered helicopter- Use of C language and the PC to control the plant in real time- Use of assembly language, and a microcontroller to control the plant in real time- Use...
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Computer Controlled Systems Lab - Nowy - Nowy
e-Learning CoursesComputer Controlled Systems Lab The course includes 5 individual projects and their laboratory implementation. The topics:- Job analysis and tuning digital servo- Usage of a PC computer and MatLab package for controlling the dynamic object as a model of the tethered helicopter- Use of C language and the PC to control the plant in real time- Use of assembly language, and a microcontroller to control the plant in real time- Use...
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A Machine Learning Approach for Estimating Overtime Allocation in Software Development Projects
PublicationOvertime planning in software projects has traditionally been approached with search-based multi-objective optimization algorithms. However, the explicit solutions produced by these algorithms often lack applicability and acceptance in the software industry due to their disregard for project managers' intuitive knowledge. This study presents a machine learning model that learns the preferred overtime allocation patterns from solutions...
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Using Long-Short term Memory networks with Genetic Algorithm to predict engine condition
PublicationPredictive maintenance (PdM) is a type of approach for maintenance processes, allowing maintenance actions to be managed depending on the machine's current condition. Maintenance is therefore carried out before failures occur. The approach doesn’t only help avoid abrupt failures but also helps lower maintenance cost and provides possibilities to manufacturers to manage maintenance budgets in a more efficient way. A new deep neural...
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Finding the Right Solvent: A Novel Screening Protocol for Identifying Environmentally Friendly and Cost-Effective Options for Benzenesulfonamide
PublicationThis study investigated the solubility of benzenesulfonamide (BSA) as a model compound using experimental and computational methods. New experimental solubility data were collected in the solvents DMSO, DMF, 4FM, and their binary mixtures with water. The predictive model was constructed based on the best-performing regression models trained on available experimental data, and their hyperparameters were optimized using a newly...
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Analiza wpływu transmisji danych na jakość działania rozproszonych systemów sterowania
PublicationW artykule przedstawiono zagadnienia związane z transmisją danych w rozproszonych systemach sterowania. Opisano cechy charakterystyczne przemysłowych sieci i protokołów informatycznych. Utworzono model rozproszonego systemu sterowania poziomem cieczy w zbiorniku, w którym komunikacja oparta została na protokole Modbus RTU. Na podstawie zmian parametrów transmisji danych wykazano, że poprawna komunikacja pomiędzy elementami systemu...
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Tomasz Zubowicz dr inż.
PeopleTomasz Zubowicz has received his M.Sc. Eng. degree in Control Engineering from the Faculty of Electrical and Control Engineering at the Gda{\'n}sk University of Technology (GUT) in $2008$. He received his Ph.D. Eng. (Hons.) in the field of Control Engineering from the same faculty in $2019$. In $2012$ he became a permanent staff member at the Department of Intelligent Control and Decision Support Systems at GUT and a member of...
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Uniform sampling in constrained domains for low-cost surrogate modeling of antenna input characteristics
PublicationIn this letter, a design of experiments technique that permits uniform sampling in constrained domains is proposed. The discussed method is applied to generate training data for construction of fast replacement models (surrogates) of antenna input characteristics. The modeling process is design-oriented with the surrogate domain spanned by a set of reference designs optimized with respect to the performance figures and/or operating...
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Wieloobszarowa rozmyta regulacja PID mocy reaktora jądrowego
PublicationW artykule przedstawiono wieloobszarowy regulator rozmyty z lokalnymi regulatorami PID dla sterowania mocą reaktora jądrowego typu PWR. Wykorzystano model matematyczny o parametrach skupionych reaktora PWR obejmujący procesy generacji i wymiany ciepła oraz efektów reaktywnościowych. Nastawy lokalnych regulatorów PID zostały dobrane w sposób optymalny, minimalizując całkowy wskaźnik jakości ISE. Na przykładzie pokazano że zastosowane...
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Predicting Value of Binding Constants of Organic Ligands to Beta-Cyclodextrin: Application of MARSplines and Descriptors Encoded in SMILES String
PublicationThe quantitative structure–activity relationship (QSPR) model was formulated to quantify values of the binding constant (lnK) of a series of ligands to beta–cyclodextrin (β-CD). For this purpose, the multivariate adaptive regression splines (MARSplines) methodology was adopted with molecular descriptors derived from the simplified molecular input line entry specification (SMILES) strings. This approach allows discovery of regression...
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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...
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Reduced-Cost Microwave Modeling Using Constrained Domains and Dimensionality Reduction
PublicationDevelopment of modern microwave devices largely exploits full-wave electromagnetic (EM) simulations. Yet, simulation-driven design may be problematic due to the incurred CPU expenses. Addressing the high-cost issues stimulated the development of surrogate modeling methods. Among them, data-driven techniques seem to be the most widespread owing to their flexibility and accessibility. Nonetheless, applicability of approximation-based...
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Retention modeling of some saccharides separated on an amino column.
PublicationUsing an amino column (Supelcosil LC-NH2) and different mixtures of acetonitrile-water, quantitative structure-retention relationship models are discussed. These models are based on computed molecular descriptors representing numerically structured features of some saccharides. The obtained results are underlining the lipophilicity/hydrophilicity balance, and how this is controlling the separation of the saccharides. The resulting...
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On joint order and bandwidth selection for identification of nonstationary autoregressive processes
PublicationWhen identifying a nonstationary autoregressive process, e.g. for the purpose of signal prediction or parametric spectrum estimation, two important decisions must be taken. First, one should choose the appropriate order of the autoregressive model, i.e., the number of autoregressive coefficients that will be estimated. Second, if identification is carried out using the local estimation technique, such as the localized version of...
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Triangulation-based Constrained Surrogate Modeling of Antennas
PublicationDesign of contemporary antenna structures is heavily based on full-wave electromagnetic (EM) simulation tools. They provide accuracy but are CPU-intensive. Reduction of EM-driven design procedure cost can be achieved by using fast replacement models (surrogates). Unfortunately, standard modeling techniques are unable to ensure sufficient predictive power for real-world antenna structures (multiple parameters, wide parameter ranges,...
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PROJEKTOWANIE WIELOWYMIAROWEGO REGULATORA BACKSTEPPING W UKŁADZIE DYNAMICZNEGO POZYCJONOWANIA STATKU
PublicationW komercyjnych systemach dynamicznego pozycjonowania statku, pomimo znacznego wzrostu poziomu automatyzacji, wykorzystywane jest nadal sterowanie typu PID. Poprawę jakości procesu pozycjonowania może umożliwić wykorzystanie bardziej efektywnych algorytmów, oferujących zaawansowane nieliniowe techniki sterowania. W artykule przedstawiono zagadnienie projektowania regulatora pozycji i kursu dla układu dynamicznego pozycjonowania...
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Improved Efficacy Behavioral Modeling of Microwave Circuits through Dimensionality Reduction and Fast Global Sensitivity Analysis
PublicationBehavioral models have garnered significant interest in the realm of high-frequency electronics. Their primary function is to substitute costly computational tools, notably electromagnetic (EM) analysis, for repetitive evaluations of the structure under consideration. These evaluations are often necessary for tasks like parameter tuning, statistical analysis, or multi-criterial design. However, constructing reliable surrogate models...
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Numerical methods in heat and fluid flow, PG_00057408
e-Learning CoursesReiteration of information on thermodynamic cycles and extension of information on their modelling using commercial software tools. Presentation of balances, constitutive equations, how to set up conditions in CFD type codes. Equipment regulation and control in the context of heat exchangers.Presentation of the computational capabilities of the CFD calculation code ANSYS Fluent. Mass, momentum and energy balances in 0D and 3D terms.Analysis...
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Variable‐fidelity modeling of antenna input characteristics using domain confinement and two‐stage Gaussian process regression surrogates
PublicationThe major bottleneck of electromagnetic (EM)-driven antenna design is the high CPU cost of massive simulations required by parametric optimization, uncertainty quantification, or robust design procedures. Fast surrogate models may be employed to mitigate this issue to a certain extent. Unfortunately, the curse of dimensionality is a serious limiting factor, hindering the construction of conventional data-driven models valid over...
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THE ROLE OF INFERENCE IN MOBILE MEDICAL APPLICATION DESIGN
PublicationIn the early 21st century, artificial intelligence began to be used to process medical information. However, before this happened, predictive models used in healthcare could only consider a limited number of variables, and only in properly structured and organised medical data. Today, advanced tools based on machine learning techniques - which, using artificial neural networks, can explore extremely complex relationships - and...
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On the use of the cumulative strain energy density for fatigue life assessment in advanced high-strength steels
PublicationIn this paper, the applicability of the cumulative strain energy density is explored as a fatigue indicator parameter for advanced high-strength steels subjected to strain-controlled conditions. Firstly, the cyclic stress-strain responses of nine steels, selected from three multiphase families, encompassing different elemental compositions and different heat treatment routes, were studied. Then, the predictive capabilities of the...
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Rafał Leszczyna dr hab. inż.
PeopleDr hab. Rafal Leszczyna is an associate professor at Gdansk University of Technology, Faculty of Management and Economics. He holds the M.Sc. degrees of Computer Science and Business Management. In December, 2006 he earned a Ph.D. in Computer Science, specialisation - Computer Security at the Faculty of Electronics, Telecommunications and Informatics of Gdansk University of Technology. Between 2004 and 2008 he worked in the European...
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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...