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Search results for: SECOND GRADIENT
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Optimization of the distance between the vertical plates in the convective air heat exchanger
PublicationThis paper examines the influence of the distance between vertical plates on the intensity of free convective heat transfer along with the optimization of this distance. Experimental tests were carried out for one model channel of such an heat exchanger with widths , 0.085 and 0.18 m. This channel, open at the top and sides, was formed by two isothermal symmetrically heated parallel vertical plates of dimensions m and m. The influence...
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Molecular mechanism of proton-coupled ligand translocation by the bacterial efflux pump EmrE
PublicationThe 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
PublicationTreatment 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
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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Intermolecular Interactions as a Measure of Dapsone Solubility in Neat Solvents and Binary Solvent Mixtures
PublicationDapsone 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
PublicationThe 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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Reduced-Cost Design Optimization of High-Frequency Structures Using Adaptive Jacobian Updates
PublicationElectromagnetic (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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Computationally efficient two-objective optimization of compact microwave couplers through corrected domain patching
PublicationFinding 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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Computationally Efficient Design Optimization of Compact Microwave and Antenna Structures
PublicationMiniaturization 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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Expedited Acquisition of Database Designs for Reduced-Cost Performance-Driven Modeling and Rapid Dimension Scaling of Antenna Structures
PublicationFast 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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Charge Distribution and Hyperfine Interactions in GdBa2Cu3O7 from First Principles
PublicationW 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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Determination of high-intensity sweeteners in beverages by high-performance liquid chromatography with mass spectrometry detection.
PublicationThe 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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Fast Low-fidelity Wing Aerodynamics Model for Surrogate-Based Shape Optimization
PublicationVariable-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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Quantitative study of free convective heat losses from thermodynamic partitions using Thermal Imaging
PublicationThe 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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Intracranial hemorrhage detection in 3D computed tomography images using a bi-directional long short-term memory network-based modified genetic algorithm
PublicationIntroduction: 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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Study on a polish peat bog “Rucianka” as a source of yeast strains capable of effective phenol biodegradation
PublicationPhenol 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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Simultaneous Determination of Indolic Compounds in Plant Extracts by Solid-Phase Extraction and High-Performance Liquid Chromatography with UV and Fluorescence Detection
PublicationA 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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An automated learning model for twitter sentiment analysis using Ranger AdaBelief optimizer based Bidirectional Long Short Term Memory
PublicationSentiment 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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On Unsupervised Artificial-Intelligence-Assisted Design of Antennas for High-Performance Planar Devices
PublicationDesign 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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Machine-Learning-Based Global Optimization of Microwave Passives with Variable-Fidelity EM Models and Response Features
PublicationMaximizing 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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Global Design Optimization of Microwave Circuits Using Response Feature Inverse Surrogates
PublicationModern 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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Comparative study on total nitrogen prediction in wastewater treatment 1 plant and effect of various feature selection methods on machine learning algorithms performance
PublicationWastewater 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
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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Pulsed Laser Deposition of Bismuth Vanadate Thin Films—The Effect of Oxygen Pressure on the Morphology, Composition, and Photoelectrochemical Performance
PublicationThin layers of bismuth vanadate were deposited using the pulsed laser deposition technique on commercially available FTO (fluorine-doped tin oxide) substrates. Films were sputtered from a sintered, monoclinic BiVO4 pellet, acting as the target, under various oxygen pressures (from 0.1 to 2 mbar), while the laser beam was perpendicular to the target surface and parallel to the FTO substrate. The oxygen pressure strongly affects...
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Low-cost performance-driven modelling of compact microwave components with two-layer surrogates and gradient kriging
PublicationUtilization of electromagnetic (EM) simulation tools has become indispensable for reliable evaluation of microwave components. As the cost of an individual analysis may already be considerable, the computational overhead associated with EM-driven tasks that require massive simulations (e.g., optimization) may turn prohibitive. One of mitigation methods is the employment of equivalent network models. Yet, they are incapable of accounting...
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Fast and reliable knowledge-based design closure of antennas by means of iterative prediction-correction scheme
PublicationA novel framework for expedited antenna optimization with an iterative prediction-correction scheme is proposed. The methodology is comprehensively validated using three real-world antenna structures: narrow-band, dual-band and wideband, optimized under various design scenarios. The keystone of the proposed approach is to reuse designs pre-optimized for various sets of performance specifications and to encode them into metamodels...
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Accelerated Gradient-Based Optimization of Antenna Structures Using Multi-Fidelity Simulations and Convergence-Based Model Management Scheme
PublicationThe importance of numerical optimization has been steadily growing in the design of contemporary antenna structures. The primary reason is the increasing complexity of antenna topologies, [ a typically large number of adjustable parameters that have to be simultaneously tuned. Design closure is no longer possible using traditional methods, including theoretical models or supervised parameter sweeping. To ensure reliability, optimization...
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Determination of trace levels of eleven bisphenol A analogues in human blood serum by high performance liquid chromatography–tandem mass spectrometry
PublicationChemicals showing structural or functional similarity to bisphenol A (BPA), commonly called BPA analogues, have recently drawn scientific attention due to their common industrial and commercial application as a substitute for BPA. In the European Union, the use of BPA has been severely restricted by law due to its endocrine disrupting properties. Unfortunately, it seems that all BPA analogues show comparable biological activity,...
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An algorithm for selecting a machine learning method for predicting nitrous oxide emissions in municipal wastewater treatment plants
PublicationThis 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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Globalized Simulation-Driven Miniaturization of Microwave Circuits by Means of Dimensionality-Reduced Constrained Surrogates
PublicationSmall size has become a crucial prerequisite in the design of modern microwave components. Miniaturized devices are essential for a number of application areas, including wireless communications, 5G/6G technology, wearable devices, or the internet of things. Notwithstanding, size reduction generally degrades the electrical performance of microwave systems. Therefore, trade-off solutions have to be sought that represent acceptable...
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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
PublicationPlain 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
PublicationRe-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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Machine learning-based seismic response and performance assessment of reinforced concrete buildings
PublicationComplexity 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...
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User Authentication by Eye Movement Features Employing SVM and XGBoost Classifiers
PublicationDevices 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
PublicationSmart 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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On Improved-Reliability Design Optimization of High-Frequency Structures Using Local Search Algorithms
PublicationThe role of numerical optimization has been continuously growing in the design of high-frequency structures, including microwave and antenna components. At the same time, accurate evaluation of electrical characteristics necessitates full-wave electromagnetic (EM) analysis, which is CPU intensive, especially for complex systems. As rigorous optimization routines involve repetitive EM simulations, the associated cost may be significant....
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Overview of planar antenna loading metamaterials for gain performance enhancement: the two decades of progress
PublicationMetamaterials (MTMs) are artificially engineered materials with unique electromagnetic properties not occurring in natural materials. MTMs have gained considerable attention owing to their exotic electromagnetic characteristics such as negative permittivity and permeability, thereby a negative refraction index. These extraordinary properties enable many practical applications such as super-lenses, and cloaking technology, and are...
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Applications of Tensor Analysis in Continuum Mechanics
PublicationA tensor field is a tensor-valued function of position in space. The use of tensor fields allows us to present physical laws in a clear, compact form. A byproduct is a set of simple and clear rules for the representation of vector differential operators such as gradient, divergence, and Laplacian in curvilinear coordinate systems. The tensorial nature of a quantity permits us to formulate transformation rules for its components...
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Blowing Kinetics, Pressure Resistance, Thermal Stability, and Relaxation of the Amorphous Phase of the PET Container in the SBM Process with Hot and Cold Mold. Part II: Statistical Analysis and Interpretation of Tests
PublicationThe technology of filling drinks without preservatives (such as fresh juices, iced tea drinks, and vitaminized drinks) is carried out using hot filling. Mainly due to the production costs and lower carbon footprint, polyethylene terephthalate (PET) bottles are increasingly used in this technology. In this paper, the main aim is to describe and interpret the results of statistical analysis of the influence of the temperature of...
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Blowing Kinetics, Pressure Resistance, Thermal Stability, and Relaxation of the Amorphous Phase of the PET Container in the SBM Process with Hot and Cold Mold. Part I: Research Methodology and Results
PublicationThe technology of filling drinks without preservatives (such as fresh juices, iced tea drinks, vitaminized drinks) is carried out using hot filling. Mainly due to the production costs and lower carbon footprint, polyethylene terephthalate bottles, commonly called PET, are increasingly used in this technology. In this paper, the main aim is to describe the statistical analysis methodology of the influence of the temperature of the...
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Cost-Efficient EM-Driven Size Reduction of Antenna Structures by Multi-Fidelity Simulation Models
PublicationDesign of antenna systems for emerging application areas such as the Internet of Things (IoT), fifth generation wireless communications (5G), or remote sensing, is a challenging endeavor. In addition to meeting stringent performance specifications concerning electrical and field properties, the structure has to maintain small physical dimensions. The latter normally requires searching for trade-off solutions because miniaturization...
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Rapid design optimization of antennas using variable-fidelity EM models and adjoint sensitivities
PublicationPurpose – Development of techniques for expedited design optimization of complex and numerically expensive electromagnetic (EM) simulation models of antenna structures validated both numerically and experimentally. The paper aims to discuss these issues. Design/methodology/approach – The optimization task is performed using a technique that combines gradient search with adjoint sensitivities, trust region framework, as well as...
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EM-Driven Size Reduction and Multi-Criterial Optimization of Broadband Circularly-Polarized Antennas Using Pareto Front Traversing and Design Extrapolation
PublicationMaintaining small size has become an important consideration in the design of contemporary antenna structures. In the case of broadband circularly polarized (CP) antennas, miniaturization is a challenging process due to the necessity of simultaneous handling of electrical and field properties (reflection, axial ratio, gain), as well as ensuring sufficient frequency range of operation, especially at the lower edge of the antenna...
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Direct Constraint Control for EM-Based Miniaturization of Microwave Passives
PublicationHandling constraints imposed on physical dimensions of microwave circuits has become an important design consideration over the recent years. It is primarily fostered by the needs of emerging application areas such as 5G mobile communications, internet of things, or wearable/implantable devices. The size of conventional passive components is determined by the guided wavelength, and its reduction requires topological modifications,...
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Multiplicative Long Short-Term Memory with Improved Mayfly Optimization for LULC Classification
PublicationLand Use and Land Cover (LULC) monitoring is crucial for global transformation, sustainable land control, urban planning, urban growth prediction, and the establishment of climate regulations for long-term development. Remote sensing images have become increasingly important in many environmental planning and land use surveys in recent times. LULC is evaluated in this research using the Sat 4, Sat 6, and Eurosat datasets. Various...
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Marine and Cosmic Inspirations for AI Algorithms
PublicationArtificial Intelligence (AI) is a scientific area that currently sees an enormous growth. Various new algorithms and methods are developed and many of them meets practical, successful applications. Authors of new algorithms draw different inspirations. Probably the most common one is the nature. For example, Artificial Neural Networks were inspired by the structure of human brain and nervous system while the classic Genetic Algorithm...
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High-Efficacy Global Optimization of Antenna Structures by Means of Simplex-Based Predictors
PublicationDesign of modern antenna systems has become highly dependent on computational tools, especially full-wave electromagnetic (EM) simulation models. EM analysis is capable of yielding accurate representation of antenna characteristics at the expense of considerable evaluation time. Consequently, execution of simulation-driven design procedures (optimization, statistical analysis, multi-criterial design) is severely hindered by the...
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Designing acoustic scattering elements using machine learning methods
PublicationIn the process of the design and correction of room acoustic properties, it is often necessary to select the appropriate type of acoustic treatment devices and make decisions regarding their size, geometry, and location of the devices inside the room under the treatment process. The goal of this doctoral dissertation is to develop and validate a mathematical model that allows predicting the effects of the application of the scattering...
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Study of Multi-Class Classification Algorithms’ Performance on Highly Imbalanced Network Intrusion Datasets
PublicationThis paper is devoted to the problem of class imbalance in machine learning, focusing on the intrusion detection of rare classes in computer networks. The problem of class imbalance occurs when one class heavily outnumbers examples from the other classes. In this paper, we are particularly interested in classifiers, as pattern recognition and anomaly detection could be solved as a classification problem. As still a major part of...
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Determination of nine high-intensity sweeteners in various foods by high-performance liquid chromatography with mass spectrometric detection
PublicationAn analytical procedure involving solid-phase extraction (SPE) and high-performance liquid chromatography-mass spectrometry has been developed for the determination of nine high-intensity sweeteners authorised in the EU; acesulfame-K (ACS-K), aspartame (ASP), alitame (ALI), cyclamate (CYC), dulcin (DUL), neohesperidin dihydrochalcone (NHDC), neotame (NEO), saccharin (SAC) and sucralose (SCL) in a variety of food samples (i.e. beverages,...