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Wyniki wyszukiwania dla: NEURAL NETWORKS, SURROGATE-BASED OPTIMIZATION, HYPERPARAMETER OPTIMIZATION, SEQUENTIAL SAMPLING
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Fast Fading Influence on the Deep Learning-Based LOS and NLOS Identificationin Wireless Body Area Networks
PublikacjaIn 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
PublikacjaQuo 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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Optimization of adsorption of methyl orange from aqueous solution by magnetic CoFe2O4/ZnAl-layered double hydroxide composite using response surface methodology
PublikacjaThe 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
PublikacjaThe 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
PublikacjaMany 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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A new analyzer based on pellistor sensor with neural network data postprocessing for measurement of hydrocarbons in lower explosive limit range
PublikacjaW 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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Prediction of metal deformation due to line heating; an alternative method of mechanical bending, based on artificial neural network approach
PublikacjaLine heating is one of the alternative methods of forming metals and this kind of forming uses the heating torch as a source of heat input. During the process, many parameters are considered like the size of the substrate, thickness, cooling method, source power intensity, the travel speed of the power source, the sequence of heating, and so on. It is important to analyze the factors affecting the...
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Improved Modeling of Microwave Structures Using Performance-Driven Fully-Connected Regression Surrogate
PublikacjaFast 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
PublikacjaTwo 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
PublikacjaCoding 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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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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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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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
PublikacjaW 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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Partial dominated schedules and minimizing the total completion time of deteriorating jobs
PublikacjaA 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
PublikacjaTabu 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
PublikacjaAlong 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...
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Marine and Cosmic Inspirations for AI Algorithms
PublikacjaArtificial 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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Expedited Gradient-Based Design Closure of Antennas Using Variable-Resolution Simulations and Sparse Sensitivity Updates
PublikacjaNumerical optimization has been playing an increasingly important role in the design of contemporary antenna systems. Due to the shortage of design-ready theoretical models, optimization is mainly based on electromagnetic (EM) analysis, which tends to be costly. Numerous techniques have evolved to abate this cost, including surrogate-assisted frameworks for global optimization, or sparse sensitivity updates for speeding up local...
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Pareto Ranking Bisection Algorithm for EM-Driven Multi-Objective Design of Antennas in Highly-Dimensional Parameter Spaces
PublikacjaA deterministic technique for fast surrogate-assisted multi-objective design optimization of antennas in highly-dimensional parameters spaces has been discussed. In this two-stage approach, the initial approximation of the Pareto set representing the best compromise between conflicting objectives is obtained using a bisection algorithm which finds new Pareto-optimal designs by dividing the line segments interconnecting previously...
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Reduced-Cost Microwave Design Closure by Multi-Resolution EM Simulations and Knowledge-Based Model Management
PublikacjaParameter adjustment through numerical optimization has become a commonplace of contemporary microwave engineering. Although circuit theory methods are ubiquitous in the development of microwave components, the initial designs obtained with such tools have to be further tuned to improve the system performance. This is particularly pertinent to miniaturized structures, where the cross-coupling effects cannot be adequately accounted...
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Adsorption of lead (Pb-II) using CaO-NPs synthesized by solgel process from hen eggshell: Response surface methodology for modeling, optimization and kinetic studies
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Optimization of submerged fermentation conditions for immunosuppressant mycophenolic acid production by Penicillium roqueforti isolated from blue-molded cheeses: enhanced production by ultraviolet and gamma irradiation
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Exploiting the exceptional biosynthetic potency of the endophytic Aspergillus terreus in enhancing production of Co3O4, CuO, Fe3O4, NiO, and ZnO nanoparticles using bioprocess optimization and gamma irradiation
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Mutual Interaction between Temperature and DO Set Point on AOB and NOB Activity during Shortcut Nitrification in a Sequencing Batch Reactor in Terms of Energy Consumption Optimization
PublikacjaRecently, many wastewater treatment plants (WWTPs) have had to deal with serious problems related to the restrictive requirements regarding the euent quality, as well as significant energy consumption associated with it. In this situation, mainstream deammonification and/or shortened nitrification-denitrification via nitrite (so-called “nitrite shunt”) is a new promising strategy. This study shows the mechanisms and operating conditions...
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Rapid EM-Driven Design of Compact RF Circuits By Means of Nested Space Mapping
PublikacjaA methodology for rapid design of RF circuits constituted by compact microstrip resonant-cells (CMRCs) is presented. Our approach exploits nested space mapping (NSM) technology, where the inner SM layer is used to correct the equivalent circuit model at the CMRC level, whereas the outer layer enhances the coarse model of the entire structure under design. We demonstrate that NSM dramatically improves performance of surrogate-based...
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Cost-efficient simulation-driven design of compact impedance matching transformers
PublikacjaIn this paper, an algorithmic framework for cost-efficient design optimization of miniaturized impedance matching transformers has been presented. Our approach exploits a bottom-up design that involves translating the overall design specifications for the circuit at hand to its elementary building blocks (here, compact microstrip resonant cells, CMRCs), as well as fast surrogate-assisted optimization of the cells followed by simulation-based...
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Using Deep Neural Network Methods for Forecasting Energy Productivity Based on Comparison of Simulation and DNN Results for Central Poland—Swietokrzyskie Voivodeship
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Using Deep Neural Network Methods for Forecasting Energy Productivity Based on Comparison of Simulation and DNN Results for Central Poland – Swietokrzyskie Voivodeship
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Optymalizacja procedur dyskryminacyjnych w procesie weryfikacji mówców - metodyka doboru wag parametrów = Optimization of discriminative procedures in speaker verification process - a method for selecting parameter weights
PublikacjaPoddano testowaniu system weryfikacji mówców, działający w sposób zależny od tekstu, oparty na parametrach cepstralnych. Wstępnie przyjęto wagi wyrównane przypisane do zdefiniowanego w ten sposób wektora wag, właściwego dla obranego systemu parametryzacyjnego. Uzyskane wyniki przedstawiono w postaci macierzy pomyłek (''confusion matrix''). Dobór wartości wektora wag odbywał się w oparciu o część treningową bazy danych przy użyciu...
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Ionic liquid-assisted sol-gel synthesis of Fe2O3-TiO2 for enhanced photocatalytic degradation of bisphenol a under UV illumination: Modeling and optimization using response surface methodology
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Solar light driven degradation of textile dye contaminants for wastewater treatment – studies of novel polycationic selenide photocatalyst and process optimization by response surface methodology desirability factor
PublikacjaThe unplanned anthropogenic activities and raced industrial revolution detrimentally causes serious threat to terrestrial and aquatic life. A high discharge of wastewater from industries using dyes affects living organisms and the environment. This paper presents studies on polycationic selenides (PCS) synthesized by hydrothermal methods for photocatalytic degradation of dyes. The synthesized PCS were confirmed by various characterization...
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Optimization of a Fabric Phase Sorptive Extraction protocol for the isolation of six bisphenols from juice pouches to be analysed by high performance liquid chromatography coupled with diode array detector
PublikacjaFabric Phase Sorptive Extraction (FPSE) combined with high pressure liquid chromatography using to diode array detection (HPLC-DAD) was applied for the simultaneous determination of bisphenols (BPA, BPB, BPC, BPE, BPF, BPS) in juice pouches. The FPSE procedure was optimized with regards to the critical parameters that affect the performance of the method including the selection of the FPSE membrane type and size, adsorption time,...
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Application and optimization of headspace solid-phase microextraction (HS-SPME) coupled with gas chromatography - flame-ionization detector (GC-FID) to determine products of the petroleum industry in aqueous samples
PublikacjaA simple and solvent-free analytical method has been optimized for the determination of hydrocarbons (C6 - C20) from products of the petroleum industry in aqueous samples. Extraction and analysis was carried out using headspace solid-phase microextraction (HS-SPME) and gas chromatography coupled with flame-ionization detector (GC-FID). A ZB-5 capillary column (30 m × 0.25 mm inner diameter, 0.25 µm film thickness) was used for...
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Application of gas flow headspace liquid phase micro extraction coupled with gas chromatography-mass spectrometry for determination of 4-methylimidazole in food samples employing experimental design optimization
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Fast Design Closure of Compact Microwave Components by Means of Feature-Based Metamodels
PublikacjaPrecise tuning of geometry parameters is an important consideration in the design of modern microwave passive components. It is mandatory due to limitations of theoretical design methods unable to quantify certain phenomena that are important for the operation and performance of the devices (e.g., strong cross-coupling effects in miniaturized layouts). Consequently, the initial designs obtained using analytical or equivalent network...
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Optimized Deep Learning Model for Flood Detection Using Satellite Images
PublikacjaThe increasing amount of rain produces a number of issues in Kerala, particularly in urban regions where the drainage system is frequently unable to handle a significant amount of water in such a short duration. Meanwhile, standard flood detection results are inaccurate for complex phenomena and cannot handle enormous quantities of data. In order to overcome those drawbacks and enhance the outcomes of conventional flood detection...
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Nested Space Mapping Technology for Expedite EM-driven Design of Compact RF/microwave Components
PublikacjaA robust simulation-driven methodology for rapid and reliable design of RF/microwave circuits comprising compact microstrip resonant cells (CMRCs) is presented. We introduce a nested space mapping (NSM) technology, in which the inner space mapping layer is utilized to improve the generalization capabilities of the equivalent circuit model corresponding to a constitutive element of the circuit under consideration. The outer layer...
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Expedited Design Closure of Antennas By Means Of Trust-Region-Based Adaptive Response Scaling
PublikacjaIn the letter, a reliable procedure for expedited design optimization of antenna structures by means of trust-region adaptive response scaling (TR-ARS) is proposed. The presented approach exploits two-level electromagnetic (EM) simulation models. A predicted high-fidelity model response is obtained by applying nonlinear frequency and amplitude correction to the low-fidelity model. The surrogate created this way is iteratively rebuilt...
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Reply to “Comment on ‘Crystal Structure Prediction by Global Optimization as a Tool for Evaluating Potentials: Role of the Dipole Moment Correction Term in Successful Predictions'” by B. P. van Eijck and J. Kroon
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Separation and determination of ciprofloxacin in seawater, human blood plasma and tablet samples using molecularly imprinted polymer pipette‐tip solid phase extraction and its optimization by response surface methodology
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Structure and computationally-efficient simulation-driven design of compact UWB monopole antenna
PublikacjaIn this letter, a structure of a small ultra-wideband (UWB) monopole antenna, its design optimization procedure as well as experimental validation are presented. According to our approach, antenna compactness is achieved by means of a meander line for current path enlargement as well as the two parameterized slits providing additional degrees of freedom that help to ensure good impedance matching. For the sake of reliability, the...
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Electromagnetic Simulation with 3D FEM for Design Automation in 5G Era
PublikacjaElectromagnetic simulation and electronic design automation (EDA) play an important role in the design of 5G antennas and radio chips. The simulation challenges include electromagnetic effects and long simulation time and this paper focuses on simulation software based on finite-element method (FEM). The state-of-the-art EDA software using novel computational techniques based on FEM can not only accelerate numerical analysis, but...
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Computationally Efficient Surrogate-Assisted Design of Pyramidal-Shaped 3D Reflectarray Antennas
PublikacjaReflectarrays (RAs) have been attracting considerable interest in the recent years due to their appealing features, in particular, a possibility of realizing pencil-beam radiation patterns, as in the phased arrays, but without the necessity of incorporating the feeding networks. These characteristics make them attractive solutions, among others, for satellite communications or mobile radar antennas. Notwithstanding, available microstrip...
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Implicit Space Mapping for Variable-Fidelity EM-Driven Design of Compact Circuits
PublikacjaSpace mapping (SM) belongs to the most successful surrogate-based optimization (SBO) methods in microwave engineering. Among available SM variations, implicit SM (ISM) is particularly attractive due to its simplicity and separation of extractable surrogate model parameters and design variables of the circuit/system at hand. Unlike other SM approaches, ISM exploits a set of preassigned parameters to align the surrogate with the...
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Reduced-cost constrained miniaturization of wideband antennas using improved trust-region gradient search with repair step
PublikacjaIn the letter, an improved algorithm for electromagnetic (EM)-driven size reduction of wideband antennas is proposed. Our methodology utilizes variable-fidelity EM simulation models, auxiliary polynomial regression surrogates, as well as multi-point response correction. The constraint handling is implicit, using penalty functions. The core optimization algorithm is a trust-region gradient search with a repair step added in order...
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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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Globalized Simulation-Driven Miniaturization of Microwave Circuits by Means of Dimensionality-Reduced Constrained Surrogates
PublikacjaSmall 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...