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Wyniki wyszukiwania dla: model predictive control
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Magnetic Signature Description of Ellipsoid-Shape Vessel Using 3D Multi-Dipole Model Fitted on Cardinal Directions
PublikacjaThe 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
PublikacjaDue 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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CUTTING POWER FORECASTING WHILE WOOD SAWING: FRACTURE MECHANICS APPROACH AND AXELSSON’S MODEL COMPARISON
PublikacjaIn 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
PublikacjaFactors 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
PublikacjaAs the Internet of Things technology is developing rapidly, companies have an ability to observe the health of engine components and constructed systems through collecting signals from sensors. According to output of IoT sensors, companies can build systems to predict the conditions of components. Practically the components are required to be maintained or replaced before the end of life in performing their assigned task. Predicting...
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Application of a hybrid mechanistic/machine learning model for prediction of nitrous oxide (N2O) production in a nitrifying sequencing batch reactor
PublikacjaNitrous 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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Survey on fuzzy logic methods in control systems of electromechanical plants
PublikacjaРассмотрены 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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Cost-Efficient Surrogate Modeling of High-Frequency Structures Using Nested Kriging with Automated Adjustment of Model Domain Lateral Dimensions
PublikacjaSurrogate 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
PublikacjaSurrogate 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
PublikacjaWhen 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
PublikacjaGender 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
PublikacjaBackground. 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
PublikacjaBackground: 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
PublikacjaThis 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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Using Long-Short term Memory networks with Genetic Algorithm to predict engine condition
PublikacjaPredictive 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
PublikacjaThis 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
PublikacjaW 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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Uniform sampling in constrained domains for low-cost surrogate modeling of antenna input characteristics
PublikacjaIn 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
PublikacjaW 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
PublikacjaThe 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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Reduced-Cost Microwave Modeling Using Constrained Domains and Dimensionality Reduction
PublikacjaDevelopment 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.
PublikacjaUsing 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
PublikacjaWhen 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
PublikacjaDesign 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
PublikacjaW 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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Variable‐fidelity modeling of antenna input characteristics using domain confinement and two‐stage Gaussian process regression surrogates
PublikacjaThe 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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On the use of the cumulative strain energy density for fatigue life assessment in advanced high-strength steels
PublikacjaIn 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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THE ROLE OF INFERENCE IN MOBILE MEDICAL APPLICATION DESIGN
PublikacjaIn 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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Low-cost data-driven modelling of microwave components using domain confinement and PCA-based dimensionality reduction
PublikacjaFast 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...
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Forewarned Is Forearmed: Machine Learning Algorithms for the Prediction of Catheter-Induced Coronary and Aortic Injuries
PublikacjaCatheter-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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Model organizacji ruchu na sieci kolejowej z uwzględnieniem rekuperacji energii
PublikacjaNa wstępie przeanalizowano aktualny stan wiedzy z zakresu metod wykorzystywania energii z rekuperacji oraz istniejących modeli optymalizujących ich efektywność. Na tej podstawie za główny cel pracy wyznaczono opracowanie metody modyfikacji kolejowego rozkładu jazdy, która doprowadzi do zwiększenia efektywności wykorzystania energii pochodzącej z rekuperacji. W związku z powyższym postawiono tezę, że możliwe jest zwiększenie efektywności...
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Prediction of metal deformation due to line heating; an alternative method of mechanical bending, based on artificial neural network approach
PublikacjaLine 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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Projekt systemu sterowania dwukołowym robotem balansującym
PublikacjaW niniejszym artykule rozważony został problem sterowania dwukołowym robotem balansującym. Celem zaprezentowanych prac było zaprojektowanie systemu sterowania tego typu obiektem z wykorzystaniem metod nowoczesnej teorii sterowania. W ramach syntezy, bazując na wyprowadzonym w oparciu o zasady dynamiki Newtona modelu, dobrana została struktura systemu sterowania w postaci regulatora wykorzystującego sprzężenie zwrotne od stanu oraz...
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Design-oriented modeling of antenna structures by means of two-level kriging with explicit dimensionality reduction
PublikacjaThe employment of full-wave electromagnetic (EM) analysis is a practical necessity in the design of contemporary antenna structures. This is because simpler models are generally not available or of limited accuracy. At the same time, EM-based design is computationally expensive. Consequently, the ways of accelerating tasks such as parametric optimization or uncertainty quantification have to be sought. A possible workaround that...
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Unmasking the COVID-19 Pandemic Prevention Gains: Excess Mortality Reversal in 2022
PublikacjaObjectives: The purpose of this study was to assess the long-term effectiveness of COVID-19 pandemic prevention measures in saving lives after European governments began to lift restrictions. Study design: Excess mortality interrupted time series.Methods: Country-level weekly data on deaths were fitted to the Poisson mixed linear model to estimate excess deaths. Based on this estimate, the percentage of excess deaths...
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Reduced model of gyroscopic system
PublikacjaThe paper presents the method of model reduction for the system with gyroscopic interactions. Two methods were used to obtain the approximate discrete models of the continuous structure: the modal decomposition method and the rigid finite element method. The first approach is used for this part of a system for which it is easy to formulate orthogonality conditions, meanwhile the second one is used for other part. The method enables...
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Improving methods to calculate the loss of ecosystem services provided by urban trees using LiDAR and aerial orthophotos
PublikacjaIn this paper we propose a methodology for combining remotely sensed data with field measurements to assess selected tree parameters (diameter at breast height (DBH) and tree species) required by the i-Tree Eco model to estimate ecosystem services (ES) provided by urban trees. We determined values of ES provided by trees in 2017 in Racibórz (a city in South Poland) and estimated the loss of ES from January 1, 2017 to March 5, 2017,...
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Pomiędzy kontrolą i zaufaniem – jakich liderów potrzebują wirtualne zespoły projektowe
PublikacjaArtykuł dotyczy zarządzania zespołem wirtualnym, które jest szczególnym wyzwaniem ze względu na rozproszenie geograficzne członków zespołu oraz porozumiewanie się za pośrednictwem technologii informacyjnej. Skoncentrowano się na utrzymywaniu odpowiedniej proporcji pomiędzy zaufaniem i kontrolą zespołu i opracowano listę rekomendacji dla liderów zespołów wirtualnych, dotyczących budowania zaufania i koordynacji pracy. Do realizacji...
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Platelet RNA Sequencing Data Through the Lens of Machine Learning
PublikacjaLiquid biopsies offer minimally invasive diagnosis and monitoring of cancer disease. This biosource is often analyzed using sequencing, which generates highly complex data that can be used using machine learning tools. Nevertheless, validating the clinical applications of such methods is challenging. It requires: (a) using data from many patients; (b) verifying potential bias concerning sample collection; and (c) adding interpretability...
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Modelowanie reorganizacji ruchu w transporcie szynowym zwiększające efektywne wykorzystanie energii z hamowania odzyskowego
PublikacjaWe wstępie artykułu przedstawiono metody wykorzystania energii elektrycznej odzyskanej w procesie hamowania elektrodynamicznego. Szczególną uwagę zwrócono na metodę zwrotu odzyskanej energii do sieci jezdnej i wykorzystania jej przez inne pojazdy szynowe, której efektywne zastosowanie niejednokrotnie wymaga reorganizacji ruchu. W pracy przeanalizowano opisany w literaturze model organizacji ruchu w transporcie szynowym, który uwzględnia...
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Permeability of sandy soils estimated from particle size distribution and field measurements
PublikacjaAccurate estimation of soil permeability is crucial in many geotechnical applications. Empirical and theoretical equations based on soil particle size distribution (PSD) offer a fast and cheap way for preliminary estimation of permeability in granular soils, however the results obtained from various formulas available in the literature often show significant discrepancies. While several comparative studies on this topic have been...
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User satisfaction model
PublikacjaRaport techniczny - opis metody ''User Satisfaction Methods'' wykorzystywanej w projektowaniu komunikacji człowiek-komputer oraz doskonaleniu interfejsu użytkownika.
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Optymalizacja efektywności hamowania odzyskowego w transporcie szynowym przez sterowanie czasem przyjazdu na stację
PublikacjaArtykuł nawiązuje do poprzednich prac autorów, w których przedstawiono model organizacji ruchu kooperujących pociągów z uwzględnieniem optymalizacji wykorzystania energii zwracanej do sieci jezdnej. W przedstawionej pracy zmodyfikowano model zmieniając główną zmienną sterującą, mającą wpływ na efektywne wykorzystanie energii, z czasu odjazdu na czas przyjazdu pociągu na stację lub przystanek. Optymalizacja dokonywana jest przez...
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ZARZADZANIE ORGANIZACJĄ TYPU SMART
PublikacjaZaprezentowano organizacji, w której charakterystykę wpisano następujące cechy: strategiczne uwarunkowanie, maksymalną innowacyjność, atrakcyjność dla interesariuszy, rozwijanie osobowości pracowników oraz twórczość w działaniu. Te atrybuty, tworzą koncepcję organizacji SMART (akronim od pierwszych liter powyższych cech), która wyróżnia się dodatkowo strukturą opartą o dynamicznie kreowane zespoły oraz skutecznym wspomaganiem...
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Towards Rational Biosurfactant Design—Predicting Solubilization in Rhamnolipid Solutions
PublikacjaThe efficiency of micellar solubilization is dictated inter alia by the properties of the solubilizate, the type of surfactant, and environmental conditions of the process. We, therefore, hypothesized that using the descriptors of the aforementioned features we can predict the solubilization efficiency, expressed as molar solubilization ratio (MSR). In other words, we aimed at creating a model to find the optimal surfactant and...
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A simple model of circular hydraulic pump
PublikacjaRozpatrzono warunki powstawania osiowosymetrycznego uskoku hydraulicznego. Przedstawiono model, w którym rozpatrzono obecność dodatkowych strat w równaniu Bernoulliego. Przyczyniają się one do powstawania dodatkowego wiru w miejscu uskoku. Porównanie z wynikami badań eksperymentalnych potwierdza słuszność przyjętych tez.
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On Nature-Inspired Design Optimization of Antenna Structures Using Variable-Resolution EM Models
PublikacjaNumerical optimization has been ubiquitous in antenna design for over a decade or so. It is indispensable in handling of multiple geometry/material parameters, performance goals, and constraints. It is also challenging as it incurs significant CPU expenses, especially when the underlying computational model involves full-wave electromagnetic (EM) analysis. In most practical cases, the latter is imperative to ensure evaluation reliability....
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Spirometry measurement model - the diagnostic purpose support
Publikacjathe paper presents a new model of respiratory mechanism based on the spirometry measurements. the spirometry test assesses the efficiency of the lung ventilation. the respiratory system functioning is based on the ventilation mechanism. thus the quality of the lung depends on the quality of lung ventilation. modelling of the respiratory system supports a diagnostic process. the model parameter estimates are obtained on the basis...
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Solvent Screening for Solubility Enhancement of Theophylline in Neat, Binary and Ternary NADES Solvents: New Measurements and Ensemble Machine Learning
PublikacjaTheophylline, a typical representative of active pharmaceutical ingredients, was selected to study the characteristics of experimental and theoretical solubility measured at 25 °C in a broad range of solvents, including neat, binary mixtures and ternary natural deep eutectics (NADES) prepared with choline chloride, polyols and water. There was a strong synergistic effect of organic solvents mixed with water, and among the experimentally...
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Consumer Bankruptcy Prediction Using Balanced and Imbalanced Data
PublikacjaThis 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...