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Search results for: STRAIN-GRADIENT ELASTICITY
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Pantographic metamaterials: an example of mathematically driven design and of its technological challenges
PublicationIn 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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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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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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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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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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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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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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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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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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Optimization-based stacked machine-learning method for seismic probability and risk assessment of reinforced concrete shear walls
PublicationEfficient 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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Fast Machine-Learning-Enabled Size Reduction of Microwave Components Using Response Features
PublicationAchieving 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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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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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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A novel hybrid adaptive framework for support vector machine-based reliability analysis: A comparative study
PublicationThis 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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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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Variable Resolution Machine Learning Optimization of Antennas Using Global Sensitivity Analysis
PublicationThe 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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Global Miniaturization of Broadband Antennas by Prescreening and Machine Learning
PublicationThe development of contemporary electronic components, particularly antennas, places significant emphasis on miniaturization. This trend is driven by the emergence of technologies such as mobile communications, the internet of things, radio-frequency identification, and implantable devices. The need for small size is accompanied by heightened demands on electrical and field properties, posing a considerable challenge for antenna...
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RAGN-R: A multi-subject ensemble machine-learning method for estimating mechanical properties of advanced structural materials
PublicationThe utilization of advanced structural materials, such as preplaced aggregate concrete (PAC), fiber-reinforced concrete (FRC), and FRC beams has revolutionized the field of civil engineering. These materials exhibit enhanced mechanical properties compared to traditional construction materials, offering engineers unprecedented opportunities to optimize the design, construction, and performance of structures and infrastructures....
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Grey wolf optimizer integrated within boosting algorithm: Application in mechanical properties prediction of ultra high-performance concrete including carbon nanotubes
PublicationNowadays, the construction industry has increasingly recognized the superior performance characteristics of ultra high-performance concrete (UHPC). Known for its exceptional durability and high tensile strength, UHPC material is revolutionizing structure standards subjected to extreme environmental conditions and heavy loads. This paper explores the enhancement of UHPC with nano- and micromaterials, employing advanced machine-learning...
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Przygotowanie, realizacja i ocena pomiarów terenowych do identyfikacji oporności hydraulicznej sieci wodociągowej
PublicationW 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
PublicationDegradacja 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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Enzymes of the lysine biosynthetic pathway as targets for antifungals ?
PublicationSystemic infections caused by human pathogenic fungi in immunocompromized patients continue to be one of the important clinical problems. Limited availability of safe and efficacious antifungal chemotherapeutics and emerging resistance to existing drugs stimulates search for novel molecular targets for antifungals. The α-aminoadipate pathway (AAP) of L-lysine biosynthesis is unique in fungi and thus has been so far considered...
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The New LM-PCR/Shifter Method for the Genotyping of Microorganism
PublicationTechniques relies on the ligation of appropriates adapters (LM-PCR) as AFLP, PCR MP and ADSRRS are successfully used for epidemiological studies for prokaryotic and eukaryotic microorganisms. In this study we propose a new method, called the LM-PCR/Shifter, based on the use of a Class IIS restriction enzyme giving restriction fragments with different 4 base 5' overhangs (Shifter) and the ligation of appropriate oligonucleotide...
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Phenotypic consequences of the LYS4 gene disruption in Candida albicans
PublicationThe main scientific purpose of our studies was to verify the hypothesis that homoaconitase (HA) from Candida albicans, an enzyme catalyzing a second step of the α-aminoadipate pathway (AAP) of L-Lys biosynthesis may become a new target for antifungal chemotherapy. Previous studies indicated that the A. fumigatus mutant lacking the functional lysF gene, encoding HA, exhibited attenuated virulence in a low-dose mouse infection model...
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Modes of Failure Analysis in Reinforced Concrete Beam Using Laser Scanning and Synchro-Photogrammetry - How to apply optical technologies in the diagnosis of reinforced concrete elements?
PublicationThe following paper reveal the limitations and possibilities of terrestrial laser scanning technology adaptation in diagnostics of reinforced concrete beams. In this paper, authors present potential spectrum of TLS use in modes of failure analysis of R-C beams and determines under which conditions the laser technologies might be applied. Research was carried out at the Regional Laboratory of Structural Engineering at Gdansk University...
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Modes of Failure Analysis in Reinforced Concrete Beam Using Laser Scanning and Synchro-Photogrammetry
PublicationThe following paper reveal the limitations and possibilities of terrestrial laser scanning technology adaptation in diagnostics of reinforced concrete beams. In this paper, authors present potential spectrum of TLS use in modes of failure analysis of R-C beams and determines under which conditions the laser technologies might be applied. Research was carried out at the Regional Laboratory of Structural Engineering at Gdansk University...
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Identification of antigen Ag43 in uropathogenic Escherichia coli Dr+ strains and defining its role in the pathogenesis of urinary tract infections
PublicationUrinary tract infections (UTIs) caused by uropathogenic Escherichia coli (UPEC) are among the most common bacterial infectious diseases in the developed world. The urovirulence of UPEC is mainly associated with the surface-exposed fimbrial adhesins and adhesins of the autotransporter (AT) family. The best studied of theses proteins is antigen 43 (Ag43) mediating cell aggregation, adhesion and biofilm development as the causes of...
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Processing and structure–property relationships of natural rubber/wheat bran biocomposites
PublicationIn this work, wheat bran was used as cellulosic filler in biocomposites based on natural rubber. The impact of wheat bran content [ranging from 10 to 50 parts per hundred rubber (phr)] on processing, structure, dynamic mechanical properties, thermal properties, physico-mechanical properties and morphology of resulting biocomposites was investigated. For better characterization of interfacial interactions between natural rubber...
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Development and validation of lumbar spine finite element model
PublicationThe functional biomechanics of the lumbar spine have been better understood by finite element method (FEM) simulations. However, there are still areas where the behavior of soft tissues can be better modeled or described in a different way. The purpose of this research is to develop and validate a lumbar spine section intended for biomechanical research. A FE model of the 50th percentile adult male (AM) Total Human Model for Safety...
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Experimental Study on the Effectiveness of Polyurethane Flexible Adhesive in Reduction of Structural Vibrations
PublicationThe aim of the present study is to consider the idea of using polyurethane flexible adhesive in to reduce the vibrations in structures exposed to dynamic loads and evaluate their damping properties in relation to large deformations. Firstly, two aluminium cantilever beams, simulating structural elements (without and with polyurethane layer in the form of tape), were analysed, in order to check the damping of the unconstrained polymer...
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Highly Dissipative Materials for Damage Protection against Earthquake-Induced Structural Pounding
PublicationIt is a common situation that seismic excitations may lead to collisions between adjacent civil engineering structures. This phenomenon, called earthquake-induced structural pounding, may result in serious damage or even the total collapse of the colliding structures. Filling the gap between two buildings erected close to one another by using visco-elastic materials can be considered to be one of the most effective methods to avoid...
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A Novel Cryptic Clostridial Peptide That Kills Bacteria by a Cell Membrane Permeabilization Mechanism
PublicationThis work reports detailed characteristics of the antimicrobial peptide Intestinalin (P30), which is derived from the LysC enzyme of Clostridium intestinale strain URNW. The peptide shows a broader antibacterial spectrum than the parental enzyme, showing potent antimicrobial activity against clinical strains of Gram-positive staphylococci and Gram-negative pathogens and causing between 3.04 ± 0.12 log kill for Pseudomonas aeruginosa...
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Hyperelastic Microcantilever AFM: Efficient Detection Mechanism Based on Principal Parametric Resonance
PublicationThe impetus of writing this paper is to propose an efficient detection mechanism to scan the surface profile of a micro-sample using cantilever-based atomic force microscopy (AFM), operating in non-contact mode. In order to implement this scheme, the principal parametric resonance characteristics of the resonator are employed, benefiting from the bifurcation-based sensing mechanism. It is assumed that the microcantilever is made...
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Bee Pollen and Bee Bread as a Source of Bacteria Producing Antimicrobials
PublicationThe principal objective of the study was the isolation and identification of bacteria that are present in mature bee bread (BB) and dried (ready for selling and consumption) bee pollen (BP). Obtained isolates were screened for their potential to inhibit select human pathogenic bacteria and their ability to produce enzymes of particular industrial importance. Four and five samples of BP and BB, respectively, were used for the study....
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Discrimination of hospital isolates of Acinetobacter baumannii using repeated sequences and whole genome alignment differential analysis
PublicationAn optimized method for bacterial strain differentiation, based on combination of Repeated Sequences and Whole Genome Alignment Differential Analysis (RS&WGADA), is presented in this report. In this analysis, 51 Acinetobacter baumannii multidrug-resistance strains from one hospital environment and patients from 14 hospital wards were classified on the basis of polymorphisms of repeated sequences located in CRISPR region, variation...
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Creep rupture study of dissimilar welded joints of P92 and 304L steels
PublicationThe present work investigates the high-temperature tensile and creep properties of the dissimilar metal weld joints of 304L austenitic stainless steel (SS) and P92 creep strength-enhanced ferritic-martensitic (CSEF/M) steel under diferent testing condition. Thermanit MTS 616 fller rod (P92 fller) and the multi-pass tungsten inert gas (TIG) welding process were used to create the dissimilar weld connection. The ultimate tensile...
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Whole-genome sequencing and antimicrobial potential of bacteria isolated from Polish honey
PublicationThe aim of this study was the whole-genome analysis and assessment of the antimicrobial potential of bacterial isolates from honey harvested in one geographical location—the north of Poland. In total, 132 strains were derived from three honey samples, and the antimicrobial activity of CFAM (cell-free after-culture medium) was used as a criterion for strain selection and detailed genomic investigation. Two of the tested isolates...
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Preconditioners with Low Memory Requirements for Higher-Order Finite-Element Method Applied to Solving Maxwell’s Equations on Multicore CPUs and GPUs
PublicationThis paper discusses two fast implementations of the conjugate gradient iterative method using a hierarchical multilevel preconditioner to solve the complex-valued, sparse systems obtained using the higher order finite-element method applied to the solution of the time-harmonic Maxwell equations. In the first implementation, denoted PCG-V, a classical V-cycle is applied and the system of equations on the lowest level is solved...
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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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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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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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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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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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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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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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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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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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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...