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Wyniki wyszukiwania dla: SURROGATE MODELING , ANTENNA DESIGN , DOMAIN CONFINEMENT , NESTED KRIGING , DEEP NEURAL NETWORKS
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Design and modeling of the piezoelectric motor based on three resonance actuators
PublikacjaThis paper describes a piezoelectric motor which combines advantages from two existing piezoelectric motors topologies. The research work presents the design, simulations and measurements of the piezoelectric motor with three rotation-mode actuators. The aim of the project was to obtain the high speed piezoelectric motor. Other advantages of this conception are blocking torque, short response times, the ability to work in a hostile...
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Zdzisław Kowalczuk prof. dr hab. inż.
OsobyW 1978 ukończył studia w zakresie automatyki i informatyki na Wydziale Elektroniki Politechniki Gdańskiej, następnie rozpoczął pracę na macierzystej uczelni. W 1986 obronił pracę doktorską, w 1993 habilitował się na Politechnice Śląskiej na podstawie pracy Dyskretne modele w projektowaniu układów sterowania. W 1996 mianowany profesorem nadzwyczajnym, w 2003 otrzymał tytuł profesora nauk technicznych. W 2006 założył i od tego czasu...
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Robust design in delta domain for SISO plants: PI and PID controllers
PublikacjaW pracy przedstawiono zunifikowaną metodę numerycznie odpornej syntezy sterowników (regulatorów) działających w dyskretnym czasie w układach sterowania skalarnymi obiektami czasu ciągłego. Wykorzystano dyskretnoczasowe modele takich obiektów, oparte na tak zwanym operatorze delta, charakteryzującym się korzystnymi odpornościowymi cechami w przypadku stosowania dostatecznie małych wartości okresu próbkowania przetwarzanych sygnałów....
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Introductory modeling for decision-making using AMPL
Kursy OnlineIntroductory modeling for decision-making using AMPL
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Modeling projects for decision-making using AMPL
Kursy OnlineModeling projects for decision-making using AMPL
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OmicSelector: automatic feature selection and deep learning modeling for omic experiments
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Ultracapacitor modeling and control with discrete fractional order artificial neural network
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Accidental wow evaluation based on sinusoidal modeling and neural nets prediction
PublikacjaReferat przedstawia opis algorytmu do określenia charakterystyki zniekształcenia kołysania dźwięku. Prezentowane podejście wykorzystuje sinusoidalną analizę dźwięku bazującą zarówno na amplitudowym jak i fazowym widmie sygnału fonicznego. Trajektorie poszczególnych składowych tonalnych, obrazujące zniekształcenie kołysania, określane są na podstawie analizy ich chwilowych amplitud, częstotliwości i faz. Dodatkowo referat przedstawia...
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Modelling of residential sales price with kriging using different distance metrics in different correlation functions
PublikacjaThe modelling and estimation of sales prices based on economical conditions are important for housing sector especially in developing countries. Analysts are focused on the subject to analyze price movements and estimate the future trend of the sales prices for housing sector. In this study, we tried to generate a robust and efficient model related to the subject. Firstly, we investigated economic variables affecting housing sales...
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Variable Data Structures and Customized Deep Learning Surrogates for Computationally Efficient and Reliable Characterization of Buried Objects
PublikacjaIn this study, in order to characterize the buried object via deep-learning-based surrogate modeling approach, 3-D full-wave electromagnetic simulations of a GPR model has been used. The task is to predict simultaneously and independent of each characteristic parameters of a buried object of several radii at different positions (depth and lateral position) in various dispersive subsurface media. This study has analyzed variable...
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Modeling of Wireless Traffic Load in Next Generation Wireless Networks
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Numerical modeling of force and contact networks in fragmented sea ice
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Interpretable Deep Learning Model for the Detection and Reconstruction of Dysarthric Speech
PublikacjaWe present a novel deep learning model for the detection and reconstruction of dysarthric speech. We train the model with a multi-task learning technique to jointly solve dysarthria detection and speech reconstruction tasks. The model key feature is a low-dimensional latent space that is meant to encode the properties of dysarthric speech. It is commonly believed that neural networks are black boxes that solve problems but do not...
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Rapid multi-objective design optimisation of compact microwave couplers by means of physics-based surrogates
PublikacjaThe authors introduce a methodology for fast multi-objective design optimisation of miniaturised microwave couplers. The approach exploits the surrogate-based optimisation paradigm with an underlying low-fidelity model constructed from an equivalent circuit of the structure under consideration, corrected through implicit and frequency space mapping. A fast prediction tool obtained this way is subsequently optimised by a multi-objective...
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On Fast Multi-objective Optimization of Antenna Structures Using Pareto Front Triangulation and Inverse Surrogates
PublikacjaDesign of contemporary antenna systems is a challenging endeavor, where conceptual developments and initial parametric studies, interleaved with topology evolution, are followed by a meticulous adjustment of the structure dimensions. The latter is necessary to boost the antenna performance as much as possible, and often requires handling several and often conflicting objectives, pertinent to both electrical and field properties...
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Expedited antenna optimization with numerical derivatives and gradient change tracking
PublikacjaDesign automation has been playing an increasing role in the development of novel antenna structures for various applications. One of its aspects is electromagnetic (EM)-driven design closure, typically applied upon establishing the antenna topology, and aiming at adjustment of geometry parameters to boost the performance figures as much as possible. Parametric optimization is often realized using local methods given usually reasonable...
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Numerical Modeling of Hydrosystems 2023/2024
Kursy OnlineKurs do przedmiotu NUMERICAL MODELING OF HYDROSYSTEMS Specjalność: Environmental Engineering (WILiŚ), II stopnia, stacjonarne dr hab. inż. Michał Szydłowski, prof. PG
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Brain-Inspired Deep Networks for Facial Expression Recognition. Frontiers in Biomedical Technologies
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Design and Analysis of Artificial Neural Network (ANN) Models for Achieving Self-Sustainability in Sanitation
PublikacjaThe present study investigates the potential of using fecal ash as an adsorbent and demonstrates a self-sustaining, optimized approach for urea recovery from wastewater streams. Fecal ash was prepared by heating synthetic feces to 500 °C and then processing it as an adsorbent for urea adsorption from synthetic urine. Since this adsorption approach based on fecal ash is a promising alternative for wastewater treatment, it increases...
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Self-organizing Artificial Neural Networks into Hydrographic Big Data Reduction Process
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Adsorption chiller in a combined heating and cooling system: simulation and optimization by neural networks
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Aerodynamic excitations generated in turbine shroud clearance determined bymeans of neural networks
PublikacjaSiły aerodynamiczne generowane w uszczelnieniach turbinowych z reguły opisywane są modelem liniowym. Przy dużych drganiach wirnika sposób ten daje niezbyt dokładne wyniki. Zaproponowano wykorzystanie sieci neuronowych do określania sił ciśnieniowych powstających w uszczelnieniu. Wyniki porównano z badaniami eksperymentalnymi.
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Artificial Neural Networks in Classification of Steel Grades Based on Non-Destructive Tests
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Designing the Composition of Cement Stabilized Rammed Earth Using Artificial Neural Networks
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The Influence of Input Data Standardization Method on Prediction Accuracy of Artificial Neural Networks
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Compact antenna array comprising fractal-shaped microstripradiators
PublikacjaA design method of antenna array consisting of eight microstrip patches modified with Sierpinski fractal curves has been presented andexperimentally validated in this paper. Method proposed has enabled the achievement of considerable miniaturization of array length (26%),together with multi-band behavior of the antenna, which proves the attractiveness of presented design methodology and its ability to be implemented in more complex...
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EXPERIMENTAL AND THEORETICAL FLOW OF THE FORCES IN DEEP BEAMS WITH CANTILEVAR
PublikacjaThis article presents the results of experimental research carried out on deep beams with cantilever which was loaded throughout the depth. The main deep beam was directly simply supported on the one side. On the other side the deep beam was suspended in another deep member situated at right angles. All deep beams created a spatial arrangement. The paper is focused on the analysis of the cracks morphology and flow of the internal...
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Design of Optical Wireless Networks with Fair Traffic Flows
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Design of Weather Disruption-Tolerant Wireless Mesh Networks
PublikacjaZ uwagi na wysoki koszt realizacji sieci teleinformatycznych wykorzystujących przewodową transmisję światłowodową, bezprzewodowe sieci kratowe (WMN) oferujące transmisję rzędu 1-10 Gb/s (przy wykorzystaniu pasma millimeter-wave - 71-86 GHz), wydają się być obiecującą alternatywą dla przewodowych sieci MAN. Jednakże z uwagi na właściwości transmisji bezprzewodowej w oparciu o łącza wysokiej częstotliwości, łącza te są bardzo wrażliwe...
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Compact Dual-Polarized Corrugated Horn Antenna for Satellite Communications
PublikacjaIn this paper, a structure and design procedure of a novel compact dual-polarized corrugated horn antenna with high gain and a stable phase center for satellite communication is presented. The antenna incorporates an Ortho-Mode Transducer (OMT), a mode converter, and a corrugated structure. The compact OMT section is designed to be fed by standard WR-75 waveguides. The proposed compact design utilizes only ten corrugated slots...
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Two- and three-dimensional elastic networks with rigid junctions: modeling within the theory of micropolar shells and solids
PublikacjaFor two- and three-dimensional elastic structures made of families of flexible elastic fibers undergoing finite deformations, we propose homogenized models within the micropolar elasticity. Here we restrict ourselves to networks with rigid connections between fibers. In other words, we assume that the fibers keep their orthogonality during deformation. Starting from a fiber as the basic structured element modeled by the Cosserat...
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Statistical analysis and robust design of circularly polarized antennas using sequential approximate optimization
PublikacjaIn the paper, reliable yield estimation and tolerance-aware design optimization of circular polarization (CP) antennas is discussed. We exploit auxiliary kriging interpolation models established in the vicinity of the nominal design in order to speed up the process of statistical analysis of the antenna structure at hand. Sequential approximate optimization is then applied to carry out robust design of the antenna, here, oriented...
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THE ROLE OF INFERENCE IN MOBILE MEDICAL APPLICATION DESIGN
PublikacjaIn the early 21st century, artificial intelligence began to be used to process medical information. However, before this happened, predictive models used in healthcare could only consider a limited number of variables, and only in properly structured and organised medical data. Today, advanced tools based on machine learning techniques - which, using artificial neural networks, can explore extremely complex relationships - and...
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Extraction of antenna pattern from near field antenna measurements distorted by undesired emission
PublikacjaIn this paper authors present experimental correction of antenna pattern obtained from near field measurements when they are distorted by determined electromagnetic emission. Such situation may be met e.g. when feeding or supply subsystem interacts with antenna radiation pattern due to self-emission. Presented results of experiments show effectiveness of extraction of antenna pattern utilizing near field antenna measurements.
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Deep Learning w Keras
Kursy OnlineKurs przeznaczony dla słuchaczy studiów podyplomowych Sztuczna inteligencja i automatyzacja procesów biznesowych w ujęciu praktycznym - edycja biznesowa.
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Multi-Beam Antenna for Ka-Band CubeSat Connectivity Using 3-D Printed Lens and Antenna Array
PublikacjaIn this paper, the design of a passive multi-beam lens antenna is proposed for the CubeSat space communication system as an alternative application of a 2-D microstrip antenna array that has originally been designed for a 39 GHz 5 G MU-MIMO system. The half-ellipsoid lens is 3-D printed using stereolithography (SLA) technology. The antenna prototype is capable of selecting the main beam between 16 different directions with a gain...
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Position Estimation in Mixed Indoor-Outdoor Environment Using Signals of Opportunity and Deep Learning Approach
PublikacjaTo improve the user's localization estimation in indoor and outdoor environment a novel radiolocalization system using deep learning dedicated to work both in indoor and outdoor environment is proposed. It is based on the radio signatures using radio signals of opportunity from LTE an WiFi networks. The measurements of channel state estimators from LTE network and from WiFi network are taken by using the developed application....
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Sensing Direction of Human Motion Using Single-Input-Single-Output (SISO) Channel Model and Neural Networks
PublikacjaObject detection Through-the-Walls enables localization and identification of hidden objects behind the walls. While numerous studies have exploited Channel State Information of Multiple Input Multiple Output (MIMO) WiFi and radar devices in association with Artificial Intelligence based algorithms (AI) to detect and localize objects behind walls, this study proposes a novel non-invasive Through-the-Walls human motion direction...
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Deep-Learning-Based Precise Characterization of Microwave Transistors Using Fully-Automated Regression Surrogates
PublikacjaAccurate models of scattering and noise parameters of transistors are instrumental in facilitating design procedures of microwave devices such as low-noise amplifiers. Yet, data-driven modeling of transistors is a challenging endeavor due to complex relationships between transistor characteristics and its designable parameters, biasing conditions, and frequency. Artificial neural network (ANN)-based methods, including deep learning...
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Toward Intelligent Recommendations Using the Neural Knowledge DNA
PublikacjaIn this paper we propose a novel recommendation approach using past news click data and the Neural Knowledge DNA (NK-DNA). The Neural Knowledge DNA is a novel knowledge representation method designed to support discovering, storing, reusing, improving, and sharing knowledge among machines and computing systems. We examine our approach for news recommendation tasks on the MIND benchmark dataset. By taking advantages of NK-DNA, deep...
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Low-Cost Multi-Objective Optimization Yagi-Uda Antenna in Multi-Dimensional Parameter Space
PublikacjaA surrogate-based technique for fast multi-objective optimization of a multi-parameter planar Yagi-Uda antenna structure is presented. The proposed method utilizes response surface approximation (RSA) models constructed using training samples obtained from evaluation of the low-fidelity antenna model. Utilization of the RSA models allowsfor fast determination of the best possible trade-offs between conflicting objectives in multi-objective...
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Grand Challenges on the Theory of Modeling and Simulation
PublikacjaModeling & Simulation (M&S) is used in many different fields and has made many significant contributions. As a field in its own right, there have been many advances in methodologies and technologies. In 2002 a workshop was held in Dagstuhl, Germany, to reflect on the grand challenges facing M&S. Ten years on, a series of M& S Grand Challenge activities are marking a decade of progress and are providing an opportunity to reflect...
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Field Calibration of Low-Cost Particulate Matter Sensors Using Artificial Neural Networks and Affine Response Correction
PublikacjaDue to detrimental effects of atmospheric particulate matter (PM), its accurate monitoring is of paramount importance, especially in densely populated urban areas. However, precise measurement of PM levels requires expensive and sophisticated equipment. Although low-cost alternatives are gaining popularity, their reliability is questionable, attributed to sensitivity to environmental conditions, inherent instability, and manufacturing...
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OBTAINING FLUID FLOW PATTERN FOR TURBINE STAGE WITH NEURAL MODEL.
PublikacjaIn the paper possibility of applying neural model to obtaining patterns of proper operation for fluid flow in turbine stage for fluid-flow diagnostics is discussed. Main differences between Computational Fluid Dynamics (CFD) solvers and neural model is given, also limitations and advantages of both are considered. Time of calculations of both methods was given, also possibilities of shortening that time with preserving the accuracy...
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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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Measurements of electrically small antenna radiation patterns in non-anechoic environments using TGM
Dane BadawczeThe dataset contains raw and processed measurements of radiation pattern characteristics performed in non-anechoic regime for four antenna structures: a spline-parameterized Vivaldi structure, a compact spline-based monopole, super-ultrawideband antenna, and a quasi-Yagi component. The responses have been obtained at the selected frequencies of interest...
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Expedited optimization of antenna input characteristics with adaptive Broyden updates
PublikacjaSimulation-driven adjustment of geometry and/or material parameters is a necessary step in the design of contemporary antenna structures. Due to their topological complexity, other means, such as supervised parameter sweeping, does not usually lead to satisfactory results. On the other hand, rigorous numerical optimization is computationally expensive due to a high cost of underlying full-wave electromagnetic (EM) analyses, otherwise...
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EFFECTS OF BOUNDARY CONDITION EVALUATION ON DESIGN WAVE MODELING
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Design and modeling of switched reluctance motor for scooter application
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A dynamical model for plasma confinement transitions
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