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Search results for: NEURAL NETWORKS, SURROGATE-BASED OPTIMIZATION, HYPERPARAMETER OPTIMIZATION, SEQUENTIAL SAMPLING
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Application of Box–Behnken design in the optimization of a simple graphene oxide/zinc oxide nanocomposite-based pipette tip micro-solid phase extraction for the determination of Rhodamine B and Malachite green in seawater samples by spectrophotometry
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Mutual Coupling Reduction in Antenna Arrays Using Artificial Intelligence Approach and Inverse Neural Network Surrogates
PublicationThis paper presents a novel approach to reduce undesirable coupling in antenna arrays using custom-designed resonators and inverse surrogate modeling. To illustrate the concept, two stand-ard patch antenna cells with 0.07λ edge-to-edge distance are designed and fabricated to operate at 2.45 GHz. A stepped-impedance resonator is applied between the antennas to suppress their mutual coupling. For the first time, the optimum values...
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EM-Driven Multi-Objective Design of Impedance Transformers By Pareto Ranking Bisection Algorithm
PublicationIn the paper, the problem of fast multi-objective optimization of compact impedance matching transformers is addressed by utilizing a novel Pareto ranking bisection algorithm. It approximates the Pareto front by dividing line segments connecting the designs found in the previous iterations, and refining the obtained candidate solutions by means of poll-type search involving Pareto ranking. The final Pareto set is obtained using...
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SIAM Conference on Optimization
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Optimization: Techniques And Applications
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Krzysztof Lipiński dr hab. inż.
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Formation of Protein Networks between Mucins: Molecular Dynamics Study Based on the Interaction Energy of the System
PublicationMolecular dynamics simulations have been performed for a model aqueous solution of mucin. As mucin is a central part of lubricin, a key component of synovial fluid, we investigate its ability to form cross-linked networks. Such network formation could be of major importance for the viscoelastic properties of the soft-matter system and crucial for understanding the lubrication mechanism in articular cartilage. Thus,the inter- and...
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A novel class-based protection algorithm providing fast service recovery in IP/WDM networks
PublicationW artykule rozważa się warstwową strukturę sieci IP-MPLS/WDM. Węzły sieci mają funkcjonalność zarówno optycznych krotnic transferowych (OXC), jak i routerów IP. Dowolne dwa routery IP mogą być ze sobą połączone poprzez logiczne łącze IP realizowane przez ścieżkę optyczną WDM. Zaproponowano metodę klasową doboru tras przeżywalnych zapewniającą szybkie odtwarzanie uszkodzonych strumieni ruchu zarówno w warstwie WDM jak i IP-MPLS....
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Evidence-Based Risk Management for Civil Engineering Projects Using Bayesian Belief Networks (BBN)
PublicationThe authors are seeking new methods for improving the efficiency of the investments associated with the maintenance and operation of existing civil engineering structures. It is demonstrated how the knowledge about the elements of construction and operation phases and their relationships, combined with monitoring data can be used for more effective management of the risks associated with civil engineering projects. The methodology...
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Jacek Tomków dr hab. inż.
PeopleEducation:1. 2018 - Ph.D. of Technical Sciencesin field of Materials Engineeringthesis: Influence of underwater welding conditions on cold cracking of high strength low alloy steel 2. 2012 - Master of Science Engineer, Gdansk University of Technologyin the field of: Mechanical Engineeringwith specialization in: Manufacturing Engineering and Computer Aided Manufacturing Processesthesis: Non-destructive testing of welding joints...
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Local-Global Space Mapping for Rapid EM-Driven Design of Compact RF Structures
PublicationIn this work, we introduce a robust and efficient technique for rapid design of compact RF circuits. Our approach exploits two-level space mapping (SM) correction of an equivalent circuit model of the structure under design. The first SM layer (local correction) is utilized to ensure good matching between the equivalent circuit and the electromagnetic model at the component level. On the other hand, the global correction allows...
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Cost-Efficient Multi-Objective Design of Miniaturized Microwave Circuits Using Machine Learning and Artificial Neural Network
PublicationDesigning microwave components involves managing multiple objectives such as center frequencies, impedance matching, and size reduction for miniaturized structures. Traditional multi-objective optimization (MO) approaches heavily rely on computationally expensive population-based methods, especially when exe-cuted with full-wave electromagnetic (EM) analysis to guarantee reliability. This paper introduces a novel and cost-effective...
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Patryk Ziółkowski dr inż.
PeoplePatryk Ziolkowski is a graduate of the Faculty of Civil and Environmental Engineering at the Gdansk University of Technology, specializing in Building and Engineering Structures. He works as an Assistant Professor at the Department of Engineering Structures. He participated in international projects, including projects for the Ministry of Transportation of the State of Alabama (2015), he is also the winner of a grant from the Kosciuszko...
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Curve Curvature Analysis of a Grain Trajectories in Variable Honing of Cylindrical Holes of Thin Wall Cylinder Liners as a Honing Process Optimization Strategy
PublicationThe main problem of honing of thin wall cylinder liners is a thermal distortion of honed holes. The higher the value of the temperature of the honed workpiece, the greater its holes deformation. The paper presents a method of reducing the temperature occurring in the honing process as a result of the application of a variable honing kinematics conditions with particular emphasis on the analysis of the effect of the value of the...
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Determination of mercury in mosses by novel cold vapor generation atmospheric pressure glow microdischarge optical emission spectrometry after multivariate optimization
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Optimization of the UNRES Force Field by Hierarchical Design of the Potential-Energy Landscape. 1. Tests of the Approach Using Simple Lattice Protein Models
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Example of Using Particle Swarm Optimization Algorithm with Nelder–Mead Method for Flow Improvement in Axial Last Stage of Gas–Steam Turbine
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Unlocking the biosynthetic potential of Penicillium roqueforti for hyperproduction of the immunosuppressant mycophenolic acid: Gamma radiation mutagenesis and response surface optimization of fermentation medium
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Process Optimization for Acid Hydrolysis and Characterization of Bioethanol from Leftover Injera Waste by Using Response Surface Methodology: Central Composite Design
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Novel Versatile Topologies and Design Optimization of Wide-Bandstop Frequency Selective Surfaces for X-Band, Ku-Band and Millimeter-Wave Applications
PublicationNovel designs of frequency selective surface (FSS) are presented for wideband applications in X, Ku and mmWave (millimeter Wave) bands. Two identical metallic layers of FSS are imprinted on both sides of the RO4003 substrate. The geometry parameters are optimized to maximize the bandstop at the specified in-band maximum transmission level of –10 dB; satisfaction of the latter condition is enforced through appropriate formulation...
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Strategies for computationally feasible multi-objective simulation-driven design of compact RF/microwave components
PublicationMulti-objective optimization is indispensable when possible trade-offs between various (and usually conflicting) design objectives are to be found. Identification of such design alternatives becomes very challenging when performance evaluation of the structure/system at hand is computationally expensive. Compact RF and microwave components are representative examples of such a situation: due to highly compressed layouts and considerable...
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Novel structure and size-reduction-oriented design of microstrip compact rat-race coupler
PublicationIn this paper, a novel structure of a miniaturized microstrip rat-race coupler has been proposed. Surrogate-based optimization procedures are applied to explicitly reduce the coupler size while maintaining equal power split at the operating frequency of 1 GHz and sufficient bandwidth for return loss and isolation characteristics. The optimization is performed using the objective function with four penalty components. The footprint...
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Fast Fading Influence on the Deep Learning-Based LOS and NLOS Identificationin Wireless Body Area Networks
PublicationIn the article, the fast fading influence on the proposed DL (Deep Learning) approach for LOS (Line-of-Sight) and NLOS (Non-Line-of-Sight) conditions identification in Wireless Body Area Networks is investigated. The research was conducted on the basis of the off-body communication measurements using the developed mobile measurement stand, in an indoor environment for both static and dynamic scenarios. The measurements involved...
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Towards the 4th industrial revolution: networks, virtuality, experience based collective computational intelligence, and deep learning
PublicationQuo vadis, Intelligent Enterprise? Where are you going? The authors of this paper aim at providing some answers to this fascinating question addressing emerging challenges related to the concept of semantically enhanced knowledge-based cyber-physical systems – the fourth industrial revolution named Industry 4.0.
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International Journal of Energy Optimization and Engineering
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ACM Transactions on Architecture and Code Optimization
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Anna Sobieraj-Żłobińska dr inż.
PeopleAnna Sobieraj-Żłobińska (born in 1977 in Przasnysz) graduated from the National Education Commission High School in Przasnysz. From 1996 she continued her studies at the Faculty of Geodesy and Spatial Management at the University of Agriculture and Technology Michał Oczapowski in Olsztyn. In 2001, she obtained a master's degree in engineering at the University of Warmia and Mazury in Olsztyn (thesis topic "Determining a multiple...
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Optimization of adsorption of methyl orange from aqueous solution by magnetic CoFe2O4/ZnAl-layered double hydroxide composite using response surface methodology
PublicationThe CoFe2O4/ZnAl-layered double hydroxide (LDH) composite was successfully developed through a facile co-precipitation method, characterized, and applied as an effective adsorbent for the removal of methyl orange (MO) dye from aqueous solutions. The central composite design (CCD) of the response surface methodology (RSM) was employed to estimate and optimize process variables such as initial MO concentrations, solution pH, adsorbent...
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Synthesis, characterization and application of cross-linked functional terpolymer through epoxy group as sorbent for extraction of cadmium from waters and foods: Multivariate optimization
PublicationThe purpose of this study was to develop a selective sorbent for cadmium ions (Cd(II)) enrichment in orbital shaker assisted solid phase microextraction (OS-SPME) from different aqueous and food samples. A maleic anhydride-styrene-glycidyl methacrylate (MA-St-GMA) terpolymer was synthesized and characterized in detail. Experimental variables of sample preparation step were optimized using a central composite design (CCD). The final...
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Machine learning-based seismic fragility and seismic vulnerability assessment of reinforced concrete structures
PublicationMany studies have been performed to put quantifying uncertainties into the seismic risk assessment of reinforced concrete (RC) buildings. This paper provides a risk-assessment support tool for purpose of retrofitting and potential design strategies of RC buildings. Machine Learning (ML) algorithms were developed in Python software by innovative methods of hyperparameter optimization, such as halving search, grid search, random...
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Prediction of metal deformation due to line heating; an alternative method of mechanical bending, based on artificial neural network approach
PublicationLine 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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A new analyzer based on pellistor sensor with neural network data postprocessing for measurement of hydrocarbons in lower explosive limit range
PublicationW pracy przedstawiono rezultaty pierwszego etapu badań nad nowym typem analizatora do oznaczania stężenia wodoru i lotnych węglowodorów w zakresie dolnej granicy wybuchowości. Analizator ten zbudowano w oparciu o pojedynczy czujnik pelistorowy z układem przetwarzania danych wykorzystującym sztuczną sieć neuronową.
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Improved Modeling of Microwave Structures Using Performance-Driven Fully-Connected Regression Surrogate
PublicationFast replacement models (or surrogates) have been widely applied in the recent years to accelerate simulation-driven design procedures in microwave engineering. The fundamental reason is a considerable—and often prohibitive—CPU cost of massive full-wave electromagnetic (EM) analyses related to solving common tasks such as parametric optimization or uncertainty quantification. The most popular class of surrogates are data-driven...
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All-gather Algorithms Resilient to Imbalanced Process Arrival Patterns
PublicationTwo novel algorithms for the all-gather operation resilient to imbalanced process arrival patterns (PATs) are presented. The first one, Background Disseminated Ring (BDR), is based on the regular parallel ring algorithm often supplied in MPI implementations and exploits an auxiliary background thread for early data exchange from faster processes to accelerate the performed all-gather operation. The other algorithm, Background Sorted...
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Modeling and optimizing the removal of cadmium by Sinapis alba L. from contaminated soil via Response Surface Methodology and Artificial Neural Networks during assisted phytoremediation with sewage sludge
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A new fuzzy model of multi-criteria decision support based on Bayesian networks for the urban areas' decarbonization planning
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Supervised-learning-based development of multi-bit RCS-reduced coding metasurfaces
PublicationCoding metasurfaces have been introduced as efficient tools allowing meticulous control over the electromagnetic (EM) scattering. One of their relevant application areas is radar cross section (RCS) reduction, which principally relies on the diffusion of impinging EM waves. Despite its significance, careful control of the scattering properties poses a serious challenge at the level of practical realization. This article is concerned...
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Analysis and Optimization of Dimensional Accuracy and Porosity of High Impact Polystyrene Material Printed by FDM Process: PSO, JAYA, Rao, and Bald Eagle Search Algorithms
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Bioprocess optimization using response surface methodology for production of the anticancer drug paclitaxel by Aspergillus fumigatus and Alternaria tenuissima: Enhanced production by ultraviolet and gamma irradiation
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MHD darcy-forchheimer nanofluid flow and entropy optimization in an odd-shaped enclosure filled with a (MWCNT-Fe3O4/water) using galerkin finite element analysis
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ESTYMACJA WSPÓŁCZYNNIKÓW SZTYWNOŚCI ZAMOCOWANIA PODATNEGO PRZEDMIOTU OBRABIANEGO NA STOLE FREZARKI
PublicationW pracy przedstawiono metodę estymacji współczynników sztywności Elementów Sprężystych (ES) modelujących zamocowanie podatnego wielkogabarytowego przedmiotu obrabianego na stole frezarki. Proponowana metoda bazuje na algorytmie optymizacji za pomocą roju cząstek (ang. Particle Swarm Optimization), który pozwala na uzyskanie dobrej zgodności (aktualizacji) modelu Metody Elementów Skończonych (MES) z modelem pochodzącym z identyfikacji...
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European Chapter on Combinatorial Optimization
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SIGOPT - International Conference on Optimization
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International Workshop on Global Optimization
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Modelling and Optimization: Theory and Applications
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International Network Optimization Conference
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Conference on Combinatorial Optimization and Applications
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Partial dominated schedules and minimizing the total completion time of deteriorating jobs
PublicationA problem of scheduling deteriorating jobs on a single processor is considered. The processing time of a job is given by a function pi=ai+bisi, where si is the starting time of the job, ai>=0, bi>=0, for i=1,...,n. Jobs are non-preemptive and independent and there are neither ready times nor deadlines. The goal is to minimize the total weighted completion time. We show how to employ the concept of non-dominated schedules to construct...
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Parallel tabu search for graph coloring problem
PublicationTabu search is a simple, yet powerful meta-heuristic based on local search that has been often used to solve combinatorial optimization problems like the graph coloring problem. This paper presents current taxonomy of patallel tabu search algorithms and compares three parallelization techniques applied to Tabucol, a sequential TS algorithm for graph coloring. The experimental results are based on graphs available from the DIMACS...
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Neural network training with limited precision and asymmetric exponent
PublicationAlong with an extremely increasing number of mobile devices, sensors and other smart utilities, an unprecedented growth of data can be observed in today’s world. In order to address multiple challenges facing the big data domain, machine learning techniques are often leveraged for data analysis, filtering and classification. Wide usage of artificial intelligence with large amounts of data creates growing demand not only for storage...