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Wyniki wyszukiwania dla: equivariant gradient maps
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Surrogate-Assisted Design of Checkerboard Metasurface for Broadband Radar Cross-Section Reduction
PublikacjaMetasurfaces have been extensively exploited in stealth applications to reduce radar cross section (RCS). They rely on the manipulation of backward scattering of electromagnetic (EM) waves into various oblique angles. However, arbitrary control of the scattering properties poses a significant challenge as a design task. Yet it is a principal requirement for making RCS reduction possible. This article introduces a surrogate-based...
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Expedited Trust-Region-Based Design Closure of Antennas by Variable-Resolution EM Simulations
PublikacjaThe observed growth in the complexity of modern antenna topologies fostered a widespread employment of numerical optimization methods as the primary tools for final adjustment of the system parameters. This is mainly caused by insufficiency of traditional design closure approaches, largely based on parameter sweeping. Reliable evaluation of complex antenna structures requires full-wave electromagnetic (EM) analysis. Yet, EM-driven...
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Molecular mechanism of proton-coupled ligand translocation by the bacterial efflux pump EmrE
PublikacjaThe current surge in bacterial multi-drug resistance (MDR) is one of the largest challenges to public health, threatening to render ineffective many therapies we rely on for treatment of serious infections. Understanding different factors that contribute to MDR is hence crucial from the global “one health” perspective. In this contribution, we focus on the prototypical broad-selectivity proton-coupled antiporter EmrE, one of the...
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Prediction of energy consumption and evaluation of affecting factors in a full-scale WWTP using a machine learning approach
PublikacjaTreatment of municipal wastewater to meet the stringent effluent quality standards is an energy-intensive process and the main contributor to the costs of wastewater treatment plants (WWTPs). Analysis and prediction of energy consumption (EC) are essential in designing and operating sustainable energy-saving WWTPs. In this study, the effect of wastewater, hydraulic, and climate-based parameters on the daily consumption of EC by...
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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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User experience and user interface (UX/UI) design of Greencoin mobile application.
PublikacjaThe aim of the Greencoin mobile application is to encourage its users to change their behavior and to act pro-ecologically. The pilot version of the application will operate within the city of Gdańsk. To keep the app’s user base as large as possible, the graphical user interface should be attractive to the broadest possible audience, and the application itself should be easy and fun to use. This work is a continuation of studies...
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Retained features of embryonic metabolism in the adult MRL mouse
PublikacjaThe MRL mouse is an inbred laboratory strain that was derived by selective breeding in 1960 from the rapidly growing LG/J (Large) strain. MRL mice grow to nearly twice the size of other commonly used mouse strains, display uncommonly robust healing and regeneration properties, and express later onset autoimmune traits similar to Systemic Lupus Erythematosis. The regeneration trait (heal) in the MRL mouse maps to 14-20 quantitative...
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Modeling of TEC Variations Based on Signals from Near Zenith GNSS Satellite Observed by Dense Regional Network
PublikacjaCurrently the substantial successes in high-resolution ionospheric mapping is declared in many publications. Nevertheless, up to now there are no examples of dynamic visualization of TEC disturbances on regional scale with as high resolution as tropospheric models. Over the years, ionosphere has been modeling basing on the simple assumption, that it is a thin layer, which surrounds the Earth at some arbitrary height. However, the...
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Flood Modelling and Risk Analysis of Cinan Feizuo Flood Protection Area, Huaihe River Basin
PublikacjaThis study evaluated multiple aspects of flood risks and effects on the Cinan Feizuo flood protection area in the Huaihe River basin. Flooding remains a leading problem for infrastructure, especially in urban, residential areas of the region. Effective flood modeling for urbanized floodplains is challenging, but MIKE (ID-2D) is paramount for analyzing and quantifying the risk in the vulnerable region. The Saint-Venant equation...
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Współczesne zmiany klimatyczne i ich wpływ na funkcjonowanie systemów miejskich (na przykładzie miast strefy nadmorskiej Polski)
PublikacjaThe purpose of this article is to present contemporary climatic changes in their actual scale, and to assess their impact on functioning of urban areas situated on the Polish coast. The results of the analysis of variability of hydro-climatic conditions that occurred in the last 65 years (1951-2015) in the area of the Polish coast suggest that important changes were concerning: (1) temperature of the air, and thickness and length...
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MEASUREMENT AND ANALYSIS OF A FLOOD WAVE PROPAGATION ON THE KACZA RIVER IN GDYNIA IN NORTHERN POLAND
PublikacjaKacza river is located in northern Poland in the neighborhood of the Gulf of Gdansk and the Baltic Sea. A Kacza having length of 15 km and catchment area of 53 km2 collects the water into the Gulf mostly from inhabited and forested areas within the administrative boundaries of the city of Gdynia. On the 14th and 15th of July 2016 in northern Poland on the large area of Tri-City agglomeration (Gdynia, Gdansk and Sopot) total daily...
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Nondestructive methods complemented by FEM calculations in diagnostics of cracks in bridge approach pavement
PublikacjaNondestructive methods of road pavement diagnostics are an alternative to traditional approach to pavement failure investigation. The article presents a detailed multidisciplinary inspection carried out using ground-penetrating radar (GPR), laser scanning technology and finite element method (FEM) calculations. It was done in order to assess the factors that contributed to occurrence of premature cracks of a bridge approach pavement....
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The image of the City on social media: A comparative study using “Big Data” and “Small Data” methods in the Tri-City Region in Poland
Publikacja“The Image of the City” by Kevin Lynch is a landmark planning theory of lasting influence; its scientific rigor and relevance in the digital age were in dispute. The rise of social media and other digital technologies offers new opportunities to study the perception of urban environments. Questions remain as to whether social media analytics can provide a reliable measure of perceived city images? If yes, what implication does...
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Intermolecular Interactions as a Measure of Dapsone Solubility in Neat Solvents and Binary Solvent Mixtures
PublikacjaDapsone is an effective antibacterial drug used to treat a variety of conditions. However, the aqueous solubility of this drug is limited, as is its permeability. This study expands the available solubility data pool for dapsone by measuring its solubility in several pure organic solvents: N-methyl-2-pyrrolidone (CAS: 872-50-4), dimethyl sulfoxide (CAS: 67-68-5), 4-formylmorpholine (CAS: 4394-85-8), tetraethylene pentamine (CAS:...
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Experimental investigation and process parameter optimization of sheet metal bending by line heating method
PublikacjaThe present study is concerned with the experimental investigation of sheet metal deforming by line heating method that incorporates the combined effect of traverse speed of the torch, thickness of the sheet metal, and the number of passes of the torch. For the numerical analysis of metal bending by line heating, the
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Determination of high-intensity sweeteners in beverages by high-performance liquid chromatography with mass spectrometry detection.
PublikacjaThe objective of the present study was to measure the concentration of nine high intensity sweeteners (acesulfame-K, aspartame, alitame, cyclamate, dulcin, neohesperidin dihydrochalcon, neotame, saccharin and sucralose) in different types of beverages available on the polish market. The proposed methodology reported here consists of a extraction with buffer composed of formic acid and N,N-diisopropylethylamine (pH 4.5) followed...
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An automated learning model for twitter sentiment analysis using Ranger AdaBelief optimizer based Bidirectional Long Short Term Memory
PublikacjaSentiment analysis is an automated approach which is utilized in process of analysing textual data to describe public opinion. The sentiment analysis has major role in creating impact in the day-to-day life of individuals. However, a precise interpretation of text still relies as a major concern in classifying sentiment. So, this research introduced Bidirectional Long Short Term Memory with Ranger AdaBelief Optimizer (Bi-LSTM RAO)...
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Machine-Learning-Based Global Optimization of Microwave Passives with Variable-Fidelity EM Models and Response Features
PublikacjaMaximizing microwave passive component performance demands precise parameter tuning, particularly as modern circuits grow increasingly intricate. Yet, achieving this often requires a comprehensive approach due to their complex geometries and miniaturized structures. However, the computational burden of optimizing these components via full-wave electromagnetic (EM) simulations is substantial. EM analysis remains crucial for circuit...
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A novel hybrid adaptive framework for support vector machine-based reliability analysis: A comparative study
PublikacjaThis study presents an innovative hybrid Adaptive Support Vector Machine - Monte Carlo Simulation (ASVM-MCS) framework for reliability analysis in complex engineering structures. These structures often involve highly nonlinear implicit functions, making traditional gradient-based first or second order reliability algorithms and Monte Carlo Simulation (MCS) time-consuming. The application of surrogate models has proven effective...
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Computationally Efficient Design Optimization of Compact Microwave and Antenna Structures
PublikacjaMiniaturization is one of the important concerns of contemporary wireless communication systems, especially regarding their passive microwave components, such as filters, couplers, power dividers, etc., as well as antennas. It is also very challenging, because adequate performance evaluation of such components requires full-wave electromagnetic (EM) simulation, which is computationally expensive. Although high-fidelity EM analysis...
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Fast Low-fidelity Wing Aerodynamics Model for Surrogate-Based Shape Optimization
PublikacjaVariable-fidelity optimization (VFO) can be efficient in terms of the computational cost when compared with traditional approaches, such as gradient-based methods with adjoint sensitivity information. In variable-fidelity methods, the directoptimization of the expensive high-fidelity model is replaced by iterative re-optimization of a physics-based surrogate model, which is constructed from a corrected low-fidelity model. The success...
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Simultaneous Determination of Indolic Compounds in Plant Extracts by Solid-Phase Extraction and High-Performance Liquid Chromatography with UV and Fluorescence Detection
PublikacjaA high-performance liquid chromatographic method with UV and fluorescence detection (HPLC-DAD-FLD) was developed for simultaneous determination of indolic compounds in plant material. Indole-3-carbinol (I3C), indole-3-acetic acid (I3AA), indole-3-acetonitrile (I3ACN), and 3,3′-diindolylmethane (DIM) were used as representative compounds that cover a wide spectrum of indole structures occurring in nature. For concentration and purification...
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Charge Distribution and Hyperfine Interactions in GdBa2Cu3O7 from First Principles
PublikacjaW rozdziale przedstawiono wyniki obliczeń "z zasad pierwszych" (''ab initio'') struktury elektronowej, rozkładu ładunku i struktury nadsubtelnej, w szczególności gradientu pola elektrycznego (EFG) i składnika kontaktowego pola nadsubtelnego (HFF), nadprzewodnika wysokotemperaturowego o wzorze GdBa2Cu3O7 (Gd123). Do obliczeń wykorzystano metodę FP-LAPW (full-potential linearized augmented plane wave). Efekty związane z oddziaływaniami...
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Variable Resolution Machine Learning Optimization of Antennas Using Global Sensitivity Analysis
PublikacjaThe significance of rigorous optimization techniques in antenna engineering has grown significantly in recent years. For many design tasks, parameter tuning must be conducted globally, presenting a challenge due to associated computational costs. The popular bio-inspired routines often necessitate thousands of merit function calls to converge, generating prohibitive expenses whenever the design process relies on electromagnetic...
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Fast Machine-Learning-Enabled Size Reduction of Microwave Components Using Response Features
PublikacjaAchieving compact size has emerged as a key consideration in modern microwave design. While structural miniaturization can be accomplished through judicious circuit architecture selection, precise parameter tuning is equally vital to minimize physical dimensions while meeting stringent performance requirements for electrical characteristics. Due to the intricate nature of compact structures, global optimization is recommended,...
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Intracranial hemorrhage detection in 3D computed tomography images using a bi-directional long short-term memory network-based modified genetic algorithm
PublikacjaIntroduction: Intracranial hemorrhage detection in 3D Computed Tomography (CT) brain images has gained more attention in the research community. The major issue to deal with the 3D CT brain images is scarce and hard to obtain the labelled data with better recognition results. Methods: To overcome the aforementioned problem, a new model has been implemented in this research manuscript. After acquiring the images from the Radiological...
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Optimization-based stacked machine-learning method for seismic probability and risk assessment of reinforced concrete shear walls
PublikacjaEfficient seismic risk assessment aids decision-makers in formulating citywide risk mitigation plans, providing insights into building performance and retrofitting costs. The complexity of modeling, analysis, and post-processing of the results makes it hard to fast-track the seismic probabilities, and there is a need to optimize the computational time. This research addresses seismic probability and risk assessment of reinforced...
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On Unsupervised Artificial-Intelligence-Assisted Design of Antennas for High-Performance Planar Devices
PublikacjaDesign of modern antenna structures is a challenging endeavor. It is laborious, and heavily reliant on engineering insight and experience, especially at the initial stages oriented towards the devel-opment of a suitable antenna architecture. Due to its interactive nature and hands-on procedures (mainly parametric studies) for validating suitability of particular geometric setups, typical antenna development requires many weeks...
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Pantographic metamaterials: an example of mathematically driven design and of its technological challenges
PublikacjaIn this paper, we account for the research efforts that have been started, for some among us, already since 2003, and aimed to the design of a class of exotic architectured, optimized (meta) materials. At the first stage of these efforts, as it often happens, the research was based on the results of mathematical investigations. The problem to be solved was stated as follows: determine the material (micro)structure governed by those...
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Computationally efficient two-objective optimization of compact microwave couplers through corrected domain patching
PublikacjaFinding an acceptable compromise between various objectives is a necessity in the design of contemporary microwave components and circuits. A primary reason is that most objectives are at least partially conflicting. For compact microwave structures, the design trade-offs are normally related to the circuit size and its electrical performance. In order to obtain comprehensive information about the best possible trade-offs, multi-objective...
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Study on a polish peat bog “Rucianka” as a source of yeast strains capable of effective phenol biodegradation
PublikacjaPhenol is one of the most widely distributed environmental pollutants which can be found in wastewaters and industrial effluents. Due to its toxicity and resistance to self-degradation, it could become even lethal for humans and animals. The treatment of this toxic compound is focused on psychical–chemical methods, although biological treatment of phenol is preferable for economic aspects related to relatively...
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Quantitative study of free convective heat losses from thermodynamic partitions using Thermal Imaging
PublikacjaThe following paper presents a simple method of determining the presence, distribution and values of heat losses from external building walls as thermodynamic partitions using a Thermal Imaging Camera (TIC). According to Fourier's equation, the value of heat loss is proportional to the temperature gradient ∂t/∂y|y=0 in air in the y direction perpendicular to the heated surface. Unfortunately, air temperature cannot be measured...
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Reduced-Cost Design Optimization of High-Frequency Structures Using Adaptive Jacobian Updates
PublikacjaElectromagnetic (EM) analysis is the primary tool utilized in the design of high-frequency structures. In vast majority of cases, simpler models (e.g., equivalent networks or analytical ones) are either not available or lack accuracy: they can only be used to yield initial designs that need to be further tuned. Consequently, EM-driven adjustment of geometry and/or material parameters of microwave and antenna components is a necessary...
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Comparative study on total nitrogen prediction in wastewater treatment 1 plant and effect of various feature selection methods on machine learning algorithms performance
PublikacjaWastewater characteristics prediction in wastewater treatment plants (WWTPs) is valuable and can reduce the number of sampling, energy, and cost. Feature Selection (FS) methods are used in the pre-processing section for enhancing the model performance. This study aims to evaluate the effect of seven different FS methods (filter, wrapper, and embedded methods) on enhancing the prediction accuracy for total nitrogen (TN) in the WWTP...
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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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Global Design Optimization of Microwave Circuits Using Response Feature Inverse Surrogates
PublikacjaModern microwave design has become heavily reliant on full-wave electromagnetic (EM) simulation tools, which are necessary for accurate evaluation of microwave components. Consequently, it is also indispensable for their development, especially the adjustment of geometry parameters, oriented towards performance improvement. However, EM-driven optimization procedures incur considerable computational expenses, which may become impractical...
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Expedited Acquisition of Database Designs for Reduced-Cost Performance-Driven Modeling and Rapid Dimension Scaling of Antenna Structures
PublikacjaFast replacement models have been playing an increasing role in high-frequency electronics, including the design of antenna structures. Their role is to improve computational efficiency of the procedures that normally entail large numbers of expensive full-wave electromagnetic (EM) simulations, e.g., parametric optimization or uncertainty quantification. Recently introduced performance-driven modeling methods, such as the nested...
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Measurements of raising of 160EC pantograph type
Dane BadawczeIn this description the results of the experiment and also simulation performed on the total assembly of the 160 EC pantograph type is given. Multibody dynamics of pantograph rising due to external torque and forces are measured for parameter validation of the pantograph model.
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Chemical composition of water from roof in Gdańsk, Poland
PublikacjaThis study deals with the assessment of roof runoff waters from the region of Gdansk collected during the winter season (2007/2008). The chemical analysis includes 16 chemical variables: major ions, PAHs and PCBs measured at 3 sampling sites for 6-14 rain events. Although the data set is of limited volume the statistical data treatment using self-organizing maps (SOM) reveals the main factors controlling roof runoff water quality...
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CMGNet: Context-aware middle-layer guidance network for salient object detection
PublikacjaSalient object detection (SOD) is a critical task in computer vision that involves accurately identifying and segmenting visually significant objects in an image. To address the challenges of gridding issues and feature...
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Two-body dissociation of isoxazole following double photoionization – an experimental PEPIPICO and theoretical DFT and MP2 study
PublikacjaThe dissociative double photoionization of isoxazole molecules has been investigated experimentally and theoretically. The experiment has been carried out in the 27.5–36 eV photon energy range using vacuum ultraviolet (VUV) synchrotron radiation excitation combined with ion time-of-flight (TOF) spectrometry and photoelectron–photoion–photoion coincidence (PEPIPICO) technique. Five wellresolved two-body dissociation channels have...
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Przygotowanie, realizacja i ocena pomiarów terenowych do identyfikacji oporności hydraulicznej sieci wodociągowej
PublikacjaW procesie tworzenia komputerowego modelu przepływów (KMP) jednym z wiodących zadań jest przygotowanie i realizacja pomiarów terenowych w celu identyfikacji oporności hydraulicznej czynnej sieci wodociągowej. Motywacją autora do przedstawienia zasad postępowania w tym zakresie jest narastająca niefrasobliwość twórców KMP, którzy w nieuprawniony sposób używają paramodeli do rozwiązywania problemów inżynierskich. W pracy zdefiniowano...
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Wpływ przechyłki na zjawisko postępowania zużycia bocznego szyn kolejowych w łukach poziomych
PublikacjaDegradacja elementów nawierzchni kolejowej jest zagadnieniem bardzo złożonym, w które uwikłane jest wiele czynników związanych między innymi z układem geometrycznym toru kolejowego, właściwościami trybologicznymi poszczególnych elementów nawierzchni, jak również z parametrami podłoża gruntowego, a także z właściwościami samych pojazdów szynowych. W artykule omówiono jeden z powyższych problemów, tj. wpływ ukształtowania toru kolejowego...
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Wiktoria Wojnicz dr hab. inż.
OsobyDSc in Mechanics (in the field of Biomechanics) - Lodz Univeristy of Technology, 2019 PhD in Mechanics (in the field of Biomechanics) - Lodz Univeristy of Technology, 2009 (with distinction) Publikacje z listy MNiSW (2009 - ) Wojnicz W., Wittbrodt E., Analysis of muscles' behaviour. Part I. The computational model of muscle. Acta of Bioengineering and Biomechanics, Vol. 11, No.4, 2009, p. 15-21 Wojnicz W., Wittbrodt E., Analysis...
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Prediction of maximum tensile stress in plain-weave composite laminates with interacting holes via stacked machine learning algorithms: A comparative study
PublikacjaPlain weave composite is a long-lasting type of fabric composite that is stable enough when being handled. Open-hole composites have been widely used in industry, though they have weak structural performance and complex design processes. An extensive number of material/geometry parameters have been utilized for designing these composites, thereby an efficient computational tool is essential for that purpose. Different Machine Learning...
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Rapid and Reliable Re-Design of Miniaturized Microwave Passives by Means of Concurrent Parameter Scaling and Intermittent Local Tuning
PublikacjaRe-design of microwave passive components for the assumed operating frequencies or substrate parameters is an important yet a tedious process. It requires simultaneous tuning of relevant circuit variables, often over broad ranges thereof, to ensure satisfactory performance of the system. If the operating conditions at the available design are distant from the intended ones, local optimization is typically insufficient, whereas...
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An algorithm for selecting a machine learning method for predicting nitrous oxide emissions in municipal wastewater treatment plants
PublikacjaThis study presents an advanced algorithm for selecting machine learning (ML) models for nitrous oxide (N2O) emission prediction in wastewater treatment plants (WWTPs) employing the activated sludge process. The examined ML models comprised multivariate adaptive regression spline (MARS), support vector machines (SVM), and extreme gradient boosting (XGboost). The study explores the concept that involves new criteria to select the...
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User Authentication by Eye Movement Features Employing SVM and XGBoost Classifiers
PublikacjaDevices capable of tracking the user’s gaze have become significantly more affordable over the past few years, thus broadening their application, including in-home and office computers and various customer service equipment. Although such devices have comparatively low operating frequencies and limited resolution, they are sufficient to supplement or replace classic input interfaces, such as the keyboard and mouse. The biometric...
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On a 3D material modelling of smart nanocomposite structures
PublikacjaSmart composites (SCs) are utilized in electro-mechanical systems such as actuators and energy harvesters. Typically, thin-walled components such as beams, plates, and shells are employed as structural elements to achieve the mechanical behavior desired in these composites. SCs exhibit various advanced properties, ranging from lower order phenomena like piezoelectricity and piezomagneticity, to higher order effects including flexoelectricity...
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Machine learning-based seismic response and performance assessment of reinforced concrete buildings
PublikacjaComplexity and unpredictability nature of earthquakes makes them unique external loads that there is no unique formula used for the prediction of seismic responses. Hence, this research aims to implement the most well-known Machine Learning (ML) methods in Python software to propose a prediction model for seismic response and performance assessment of Reinforced Concrete Moment-Resisting Frames (RC MRFs). To prepare 92,400 data...