Search results for: SURROGATE-MODEL-ASSISTED EVOLUTIONARY ALGORITHM
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Towards application of uncertainty quantification procedure combined with experimental procedure for assessment of the accuracy of the DEM approach dedicated for granular flow modeling
PublicationThere is a high demand for accurate and fast numerical models for dense granular flows found in many industrial applications. Nevertheless, before numerical model can be used its need to be always validated against experimental data. During the validation, it is important to consider how the measurement data sets, as well as the numerical models, are affected by errors and uncertainties. In this study, the uncertainty quantification...
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Proportional-Derivative and Model-based Controllers used for a Serial Type Manipulator in case of a Variable Mass Payload
PublicationIn the paper, numerical analysis of dynamics of a variable mass system is considered. Its reference example is a serial-like manipulator composed of revolute joints and rigid bodies. Payload of its gripper is considered as its variable mass element (mass and inertia irregularly between subsequent payloads). For the rest of the system, inertia parameters are considered as known (precisely identified during the assembling process)....
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The distributed model predictive controller for the nuclear power plant turbo-generator set
PublicationTypically there are two main control loops with PI controllers operating at each turbo-generator set. In this paper a distributed model predictive controller DMPC, with local QDMC controllers for the turbine generator, is proposed instead of a typical PI controllers. The local QDMC controllers utilize step-response models for the controlled system components. These models parameters are determined based on the proposed black-box...
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Simulation-Driven Antenna Modeling by Means of Response Features and Confined Domains of Reduced Dimensionality
PublicationIn recent years, the employment of full-wave electromagnetic (EM) simulation tools has become imperative in the antenna design mainly for reliability reasons. While the CPU cost of a single simulation is rarely an issue, the computational overhead associated with EM-driven tasks that require massive EM analyses may become a serious bottleneck. A widely used approach to lessen this cost is the employment of surrogate models, especially...
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Ionic liquid as morphology-directing agent of two-dimensional Bi2WO6: New insight into photocatalytic and antibacterial activity
PublicationAn efficient and durable utilization of light to drive photocatalytic reactions still requires the overcoming of barriers. Herein, two-dimensional (2D) ultrathin IL_Bi2WO6 (IL_BWO) photocatalysts were prepared for the first time via ionic liquid-assisted hydrothermal route by adjusting the amount of tetrabutylammonium chloride [TBA][Cl], synthesis temperature and duration. IL played the role of morphology-directing agent given...
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Phenolic compounds from Nerium oleander leaves: microwave assisted extraction, characterization, antiproliferative and cytotoxic activities
PublicationA microwave-assisted extraction (MAE) method was used for the extraction of phenolic compounds from Nerium oleander leaves. The influence of variables such as ethanol concentration, microwave power, irradiation time and liquid/solid ratio on polyphenol extraction was modelled using a second-order regression equation based on response surface methodology (RSM). The optimal conditions for MAE were: extraction solvent 35% ethanol...
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Sano-Tachiya-Noolandi-Hong, Onsager and Braun models vs Monte Carlo simulation of charge photogeneration in organic solids
PublicationThe Sano-Tachiya-Noolandi-Hong (STNH), Onsager, and Braun models as well as Monte Carlo (MC) simulations of charge recombination/separation have been applied for the first time to reproduce the results of the electromodulated photoluminescence measurements in vacuum-evaporated films of fluorescent materials commonly used in optoelectronic devices. The values of the electron-hole pair final recombination speed in the monomer emitters:...
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ANALIZA I PROJEKTOWANIE UKŁADÓW STEROWANIA STERAMI STRUMIENIOWYMI STATKÓW Z ZASTOSOWANIEM SYSTEMU Z BAZĄ WIEDZY
PublicationŚwiatowa literatura dostarcza przykładów wskazujących na aktualność tematyki związanej z wykorzystaniem elementów sztucznej inteligencji w zastosowaniach morskich. Komisja Europejska finansuje projekty mające na celu poprawę konkurencyjności przemysłu okrętowego. W rozprawie podjęto tematykę związaną ze wspomaganiem projektowania podsystemów elektroenergetycznych statków. W rozprawie udowodniono przyjętą na wstępie tezę pracy:...
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Online sound restoration system for digital library applications.
PublicationAudio signal processing algorithms were introduced to the new online non-commercial service for audio restoration intended to enhance the content of digitized audio repositories. Missing or distorted audio samples are predicted using neural networks and a specific implementation of the Jannsen interpolation method based on the autoregressive model (AR) combined with the iterative restoring of missing signal samples. Since the distortion...
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Analiza właściwości rozszerzonego obserwatora prędkości maszyny indukcyjnej
PublicationRozszerzony obserwator prędkości został zaproponowany przez prof. Krzemińskiego i jest oparty na rozszerzonym modelu maszyny indukcyjnej, gdzie wprowadzona został nowa zmienna ζ. Jest to nowe podejście do estymacji zmiennych stanu maszyny indukcyjnej i nie wszystkie problemy zostały do tej pory rozwiązane. Zaproponowano wykorzystanie algorytmów ewolucyjnych do doboru wzmocnień obserwatora. W celu redukcji nakładów obliczeniowych...
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PROJEKTOWANIE WIELOWYMIAROWEGO REGULATORA BACKSTEPPING W UKŁADZIE DYNAMICZNEGO POZYCJONOWANIA STATKU
PublicationW komercyjnych systemach dynamicznego pozycjonowania statku, pomimo znacznego wzrostu poziomu automatyzacji, wykorzystywane jest nadal sterowanie typu PID. Poprawę jakości procesu pozycjonowania może umożliwić wykorzystanie bardziej efektywnych algorytmów, oferujących zaawansowane nieliniowe techniki sterowania. W artykule przedstawiono zagadnienie projektowania regulatora pozycji i kursu dla układu dynamicznego pozycjonowania...
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Optimally regularized local basis function approach to identification of time-varying systems
PublicationAccurate identification of stochastic systems with fast-varying parameters is a challenging task which cannot be accomplished using model-free estimation methods, such as weighted least squares, which assume only that system coefficients can be regarded as locally constant. The current state of the art solutions are based on the assumption that system parameters can be locally approximated by a linear combination of appropriately...
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Optimising approach to designing kernel PCA model for diagnosis purposes with and without a priori known data reflecting faulty states
PublicationFault detection plays an important role in advanced control of complex dynamic systems since precise information about system condition enables efficient control. Data driven methods of fault detection give the chance to monitor the plant state purely based on gathered measurements. However, they especially nonlinear, still suffer from a lack of efficient and effective learning methods. In this paper we propose the two stages learning...
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Material Parameters Identification of Historic Lighthouse Based on Operational Modal Analysis
PublicationIn the present paper, the identification of the material parameters of a masonry lighthouse is discussed. A fully non-invasive method was selected, in which the material properties were determined via numerical model validation applied to the first pair of natural frequencies and their related mode shapes, determined experimentally. The exact structural model was built by means of the finite element method. To obtain experimental...
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Impact of AlphaFold on structure prediction of protein complexes: The CASP15‐CAPRI experiment
PublicationWe present the results for CAPRI Round 54, the 5th joint CASP-CAPRI protein assembly prediction challenge. The Round offered 37 targets, including 14 homodimers, 3 homo-trimers, 13 heterodimers including 3 antibody–antigen complexes, and 7 large assemblies. On average 70 CASP and CAPRI predictor groups, including more than 20 automatics servers, submitted models for each target. A total of 21 941 models submitted by these groups...
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Optimization-Based Robustness Enhancement of Compact Microwave Component Designs with Response Feature Regression Surrogates
PublicationThe ability to evaluate the effects of fabrication tolerances and other types of uncertainties is a critical part of microwave design process. Improving the immunity of the device to parameter deviations is equally important, especially when the performance specifications are stringent and can barely be met even assuming a perfect manufacturing process. In the case of modern miniaturized microwave components of complex topologies,...
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Stochastic optimisation algorithm for optimisation of controller parameters for control of dissolved oxygen in wastewater treatment plant
PublicationWastewater treatment plants (WWTPs) are very important facilities for mankind. They enable the removal and neutralisation of man-made pollutants. Therefore, it is important for wastewater treatment plants to operate as efficiently as possible so that the level of pollutants in the treated wastewater meets specific requirements. This paper concerns the design of a hierarchical nonlinear adaptive control system for dissolved oxygen...
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The OptD-multi method in LiDAR processing
PublicationNew and constantly developing technology for acquiring spatial data, such as LiDAR (light detection and ranging), is a source for large volume of data. However, such amount of data is not always needed for developing the most popular LiDAR products: digital terrain model (DTM) or digital surface model. Therefore, in many cases, the number of contained points are reduced in the pre-processing stage. The degree of reduction is determined...
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Improved-Efficacy EM-Driven Optimization of Antenna Structures Using Adaptive Design Specifications and Variable-Resolution Models
PublicationOptimization-driven parameter tuning is an essential step in the design of antenna systems. Although in many cases it is still conducted through parametric studies, rigorous numerical methods become a necessity if truly optimum designs are sought for, and the problem intricacies (number of variables, multiple goals, constraints) make the interactive approaches insufficient. The two practical considerations of electromagnetic (EM)-driven...
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Computer-assisted pronunciation training—Speech synthesis is almost all you need
PublicationThe research community has long studied computer-assisted pronunciation training (CAPT) methods in non-native speech. Researchers focused on studying various model architectures, such as Bayesian networks and deep learning methods, as well as on the analysis of different representations of the speech signal. Despite significant progress in recent years, existing CAPT methods are not able to detect pronunciation errors with high...
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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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Switching Regulation in the Control of 5-Phase Permanent Magnet Synchronous Motor Fed by 3×5 Direct Matrix Converter
PublicationMatrix converter is an AC-AC direct power converter comprising of an array of bi- directional switches. It does not require an intermediate DC-link and allows sinusoidal output waveforms with varying amplitudes and frequencies. The configuration of these bi- directional switches decides the number of inputs and outputs...
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Effective Air Quality Prediction Using Reinforced Swarm Optimization and Bi-Directional Gated Recurrent Unit
PublicationIn the present scenario, air quality prediction (AQP) is a complex task due to high variability, volatility, and dynamic nature in space and time of particulates and pollutants. Recently, several nations have had poor air quality due to the high emission of particulate matter (PM2.5) that affects human health conditions, especially in urban areas. In this research, a new optimization-based regression model was implemented for effective...
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Modeling and control of a redundantly actuated variable mass 3RRR planar manipulator controlled by a model-based feedforward and a model-based-proportional-derivative feedforward–feedback controller
PublicationIn the paper, dynamics of a complex mechatronics system is considered. A redundantly actuated planar manipulator is the base of the mechanical part of it. It is a 3RRR 1 platform based parallel manipulator. To control its trajectory, a model-based feedforward controller is employed. Three aspects are fundamental in the presented investigations. The first focus is on development of an accurate numerical model used to solve the inverse...
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Variable-fidelity shape optimization of dual-rotor wind turbines
PublicationPurpose Dual-rotor wind turbines (DRWTs) are a novel type of wind turbines that can capture more power than their single-rotor counterparts. Because their surrounding flow fields are complex, evaluating a DRWT design requires accurate predictive simulations, which incur high computational costs. Currently, there does not exist a design optimization framework for DRWTs. Since the design optimization of DRWTs requires numerous model...
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Reduced-cost optimization-based miniaturization of microwave passives by multi-resolution EM simulations for internet of things and space-limited applications
PublicationStringent performance specifications along with constraints imposed on physical dimensions, make the design of contemporary microwave components a truly onerous task. In recent years, the latter demand has been growing in importance, with the innovative application areas such as Internet of Things coming into play. The need to employ full-wave electromagnetic (EM) simu-lations for response evaluation, reliable yet CPU heavy, only...
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Predicting the peak structural displacement preventing pounding of buildings during earthquakes
PublicationThe aim of the present paper is to verify the effectiveness of the artificial neural network (ANN) in predicting the peak lateral displacement of multi-story building during earthquakes, based on the peak ground acceleration (PGA) and building parameters. For the purpose of the study, the lumped-mass multi-degree-of-freedom structural model and different earthquake records have been considered. Firstly, values of stories mass and...
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Discrete identification of continuous non-linear and non-stationary dynamical systems that is insensitive to noise correlation and measurement outliers
PublicationThe paper uses specific parameter estimation methods to identify the coefficients of continuous-time models represented by linear and non-linear ordinary differential equations. The necessary approximation of such systems in discrete time in the form of utility models is achieved by the use of properly tuned `integrating filters' of the FIR type. The resulting discrete-time descriptions retain the original continuous parameterization...
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Analiza działania rozszerzonego obserwatora prędkości w szerokim zakresie zmian prędkości maszyny indukcyjnej
PublicationW artykule przedstawiono zagadnienia związane z odtwarzaniem zmiennych stanu maszyny indukcyjnej. Wykorzystano obserwator oparty na modelu matematycznym maszyny z dodatkowymi zmiennymi. Przedstawiono macierz stanu zlinearyzowanych równań błędu odtwarzania. Opisano sposób definiowania wyznacznika jakości na podstawie rozkładu biegunów obserwatora. Zaproponowano metodę korekcji wzmocnień wraz ze zmianą warunków pracy maszyny. Wykazano...
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Resistant to correlated noise and outliers discrete identification of continuous non-linear non-stationary dynamic objects
PublicationIn this article, specific methods of parameter estimation were used to identify the coefficients of continuous models represented by linear and nonlinear differential equations. The necessary discrete-time approximation of the base model is achieved by appropriately tuned FIR linear integral filters. The resulting discrete descriptions, which retain the original continuous parameterization, can then be identified using the classical...
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Resistant to correlated noise and outliers discrete identification of continuous non-linear non-stationary dynamic objects
PublicationIn this study, dedicated methods of parameter estimation were used to identify the coefficients of continuous models represented by linear and nonlinear differential equations. The necessary discrete-time approximation of the base model is achieved by appropriately tuned FIR linear integral filters. The resulting discrete descriptions, which retain the original continuous parameterization, can then be identified using the classical...
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Classification of Sea Going Vessels Properties Using SAR Satellite Images
PublicationThe aim of the project was to analyze the possibility of using machine learning and computer vision to identify (indicate the location) of all sea-going vessels located in the selected area of the open sea and to classify the main attributes of the vessel. The key elements of the project were to download data from the Sentinel-1 satellite [1], download data on the sea vessels [2], then automatically tag data and develop a detection...
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MSIS sonar image segmentation method based on underwater viewshed analysis and high-density seabed model
PublicationHigh resolution images of Mechanically Scanned Imaging Sonars can bring detailed representation of underwater area if favorable conditions for acoustic signal to propagate are provided. However to properly asses underwater situation based solely on such data can be challenging for less than proficient interpreter. In this paper we propose a method to enhance interpretative potential of MSIS image by dividing it in to subareas depending...
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Prospects in elongation of railway transition curves
PublicationThe paper presents an analysis of the elongation of transition curves in relation to railway track alignment correction and modernisation. The analysis is based on numerical computations for a wide range of parameters describing a typical railway geometrical layout with transition curves. The differences between the horizontal ordinates of the existing layout and the layout with the elongated transition curves are evaluated and...
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SONIC - Self-optimizing narrowband interference canceler: comparison of two frequency tracking strategies
PublicationThis paper presents a new approach to rejection of complex-valued sinusoidal disturbances acting at the output of a discrete-time linear stable plant with unknown and possibly time-varying dynamics. It is assumed that both the instantaneous frequency of the sinusoidal disturbance and its amplitude may be slowly varying with time and that the output signal is contaminated with wideband measurement noise. The proposed disturbance...
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Facial emotion recognition using depth data
PublicationIn this paper an original approach is presented for facial expression and emotion recognition based only on depth channel from Microsoft Kinect sensor. The emotional user model contains nine emotions including the neutral one. The proposed recognition algorithm uses local movements detection within the face area in order to recognize actual facial expression. This approach has been validated on Facial Expressions and Emotions Database...
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Performance improvement of NN based RTLS by customization of NN structure - heuristic approach
PublicationThe purpose of this research is to improve performance of the Hybrid Scene Analysis – Neural Network indoor localization algorithm applied in Real-time Locating System, RTLS. A properly customized structure of Neural Network and training algorithms for specific operating environment will enhance the system’s performance in terms of localization accuracy and precision. Due to nonlinearity and model complexity, a heuristic analysis...
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Rating Prediction with Contextual Conditional Preferences
PublicationExploiting contextual information is considered a good solution to improve the quality of recommendations, aiming at suggesting more relevant items for a specific context. On the other hand, recommender systems research still strive for solving the cold-start problem, namely where not enough information about users and their ratings is available. In this paper we propose a new rating prediction algorithm to face the cold-start...
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Stable indirect adaptive control based on discrete-time T-S fuzzy model
PublicationThis paper presents an indirect adaptive fuzzy control scheme for uncertain nonlinear asymptotically stable plants.A discrete-time T-S fuzzy input-output model is employed to approximate the unknown plant dynamics. The T-S fuzzy model is fed with its own states, which are indeed its past outputs, rather than the measurements from the plants. Entirely based on this model, a feedback linearization control law is designed by using...
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Stable indirect adaptive control based on discrete-time T-S fuzzy model
PublicationThis paper presents an indirect adaptive fuzzy control scheme for uncertain nonlinear asymptotically stable plants.A discrete-time T-S fuzzy input-output model is employed to approximate the unknown plant dynamics. The T-S fuzzy model is fed with its own states, which are indeed its past outputs, rather than the measurements from the plants. Entirely based on this model, a feedback linearization control law is designed by using...
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Fast Real-Time RDFT- and GDFT-Based Direct Fault Diagnosis of Induction Motor Drive
PublicationThis paper presents the theoretical analysis and experimental verification of a direct fault harmonic identification approach in a converter-fed electric drive for automated diagnosis purposes. On the basis of the analytical model of the proposed real-time direct fault diagnosis, the fault-related harmonic component is calculated using recursive DFT (RDFT) and Goertzel DFT (GDFT), applied instead of the full spectrum calculations...
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Novel approach to modeling spectral-domain optical coherence tomography with Monte Carlo method
PublicationNumerical modeling Optical Coherence Tomography (OCT) systems is needed for optical setup optimization, development of new signal processing methods and assessment of impact of different physical phenomena inside the sample on OCT signal. The Monte Carlo method has been often used for modeling Optical Coherence Tomography, as it is a well established tool for simulating light propagation in scattering media. However, in this method...
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Performance-Driven Surrogate Modeling of High-Frequency Structures
PublicationThe development of modern high-frequency structures, including microwave and antenna components, heavily relies on full-wave electromagnetic (EM) simulation models. Notwithstanding, EM-driven design entails considerable computational expenses. This is especially troublesome when solving tasks that require massive EM analyzes, parametric optimization and uncertainty quantification be-ing representative examples. The employment of...
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Noise profiling for speech enhancement employing machine learning models
PublicationThis paper aims to propose a noise profiling method that can be performed in near real-time based on machine learning (ML). To address challenges related to noise profiling effectively, we start with a critical review of the literature background. Then, we outline the experiment performed consisting of two parts. The first part concerns the noise recognition model built upon several baseline classifiers and noise signal features...
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Modelling of FloodWave Propagation with Wet-dry Front by One-dimensional Diffusive Wave Equation
PublicationA full dynamic model in the form of the shallow water equations (SWE) is often useful for reproducing the unsteady flow in open channels, as well as over a floodplain. However, most of the numerical algorithms applied to the solution of the SWE fail when flood wave propagation over an initially dry area is simulated. The main problems are related to the very small or negative values of water depths occurring in the vicinity of...
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Modelowanie procesu wrzenia i kondensacji w rozszerzonym zakresie ciśnień zredukowanych
PublicationNiniejsza rozprawa doktorska ma na celu pokazanie wpływu uwzględnienia ciśnienia zredukowanego w analizowanym modelu opisują-cym współczynnik przejmowania ciepła na zbieżność z danymi eksperymentalnymi.Przedmiotem analizy jest półempiryczny model Mikielewicza w zastosowaniu do danych eksperymentalnych w kanałach konwencjonalnych i o małej średnicy płynów uznanych za perspektywiczne.W ramach realizowanych prac badawczych pozyskano...
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Cu( II ) ions removal from wastewater using starch nanoparticles ( SNPs ): An Eco‐sustainable approach
PublicationThe complex structured starch particles were reduced to the nanoscale size range through hydrolysis utilizing low concentration acid assisted with ultrasound irradiation. The synthesized starch nanoparticles (SNPs) were characterized by TEM, FTIR, and XRD techniques. The synthesized SNPs possessed surface activated entities, as many cationic functional groups were confirmed through the FTIR spectrum. Also, these SNPs were effectively...
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Development of a new green analytical methodology for the determination of phthalates in single-use babies diapers using ultrasound-assisted extraction and polypropylene porous membrane
PublicationA green extraction strategy was developed and utilized for the extraction and determination of phthalates. The extraction is based on ultrasound-assisted extraction and a polypropylene porous membrane. The Box-Behnken model was performed to optimize the extraction condition. The optimal extraction conditions are 5.5 mL of ethyl acetate, 10 min of extraction time and 55 C for extraction temperature. The developed green extraction...
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Energy efficient indoor localisation for narrowband internet of things
PublicationThere are an increasing number of Narrow Band IoT devices being manufactured as the technology behind them develops quickly. The high co-channel interference and signal attenuation was seen in edge Narrow Band IoT devices make it challenging to guarantee the service quality of these devices. To maximize the data rate fairness of Narrow Band IoT devices, a multi-dimensional indoor localization model is devised, consisting of...
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Predicting the impact of traffic–induced vibrations on buildings using artificial neural networks
PublicationTraffic–induced vibrations may constitute a considerable load to a building, cause cracking of plaster, cracks in load–bearing elements or even a global structural collapse of the whole structure [1-4]. Vibrations measurements of real structures are costly and laborious, not justified in all cases. The aim of the paper is to create an original algorithm, to predict the negative dynamic impact on the examined residential building...