Filtry
wszystkich: 9711
wybranych: 7900
-
Katalog
- Publikacje 7900 wyników po odfiltrowaniu
- Czasopisma 484 wyników po odfiltrowaniu
- Konferencje 170 wyników po odfiltrowaniu
- Osoby 385 wyników po odfiltrowaniu
- Projekty 26 wyników po odfiltrowaniu
- Laboratoria 2 wyników po odfiltrowaniu
- Kursy Online 363 wyników po odfiltrowaniu
- Wydarzenia 14 wyników po odfiltrowaniu
- Dane Badawcze 367 wyników po odfiltrowaniu
Filtry wybranego katalogu
wyświetlamy 1000 najlepszych wyników Pomoc
Wyniki wyszukiwania dla: MICROWAVE DESIGN, MULTI-OBJECTIVE OPTIMIZATION, DESIGN AUTOMATION, MACHINE LEARNING, NEURAL NETWORKS
-
Low-cost multiband compact branch-line coupler design using response features and automated EM model fidelity adjustment
PublikacjaDesign closure of compact microwave components is a challenging problem because of significant electromagnetic (EM) cross-couplings in densely arranged layouts. A separate issue is a large number of designable parameters resulting from replacement of conventional transmission line sections by compact microstrip resonant cells. This increases complexity of the design optimization problem and requires employment of expensive high-fidelity...
-
Book review: Simulation-Driven Design Optimisation and Modelling for Microwave Engineering
PublikacjaCelem książki jest przedstawienie aktualnego stanu badań dotyczących projektowania układów mikrofalowych poprzez modelowanie i optymalizacje wspomagane symulacjami elektromagnetycznymi. Grupa międzynarodowych ekspertów zajmujących się rożnymi aspektami komputerowo wspomaganego projektowania układów mikrofalowych, podsumowuje i dokonuje przeglądu ostatnich osiągnięć w tej dziedzinie oraz przedstawia szereg praktycznych zastosowań....
-
Design of a SiC based triple active bridge ceil for a multi-megawatt DC-DC converter
PublikacjaThe paper describes the design methodology of a novel Triple Active Bridge cell used as the building block for modular DC-DC converters. The intended application is for Medium Voltage Direct Current grids, such as the DC collector for offshore wind farms. The latest generation of SiC MOSFET semiconductors is utilized to operate in the medium frequency range while optimizing the efficiency. The dimensioning of the main cell components,...
-
Function and Frustration of Multi-Drug ABC Exporter Protein and Design of Model Proteins for Drug Delivery Using Protein Hydration Thermodynamics
Publikacja -
A Proposed Machine Learning Model for Forecasting Impact of Traffic-Induced Vibrations on Buildings
PublikacjaTraffic-induced vibrations may cause various damages to buildings located near the road, including cracking of plaster, cracks in load-bearing elements or even collapse of the whole structure. Measurements of vibrations of real buildings are costly and laborious. Therefore the aim of the research is to propose the original numerical algorithm which allows us to predict, with high probability, the nega-tive dynamic impact of traffic-induced...
-
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...
-
Prediction of energy consumption and evaluation of affecting factors in a full-scale WWTP using a machine learning approach
PublikacjaTreatment of municipal wastewater to meet the stringent effluent quality standards is an energy-intensive process and the main contributor to the costs of wastewater treatment plants (WWTPs). Analysis and prediction of energy consumption (EC) are essential in designing and operating sustainable energy-saving WWTPs. In this study, the effect of wastewater, hydraulic, and climate-based parameters on the daily consumption of EC by...
-
Expedited Yield Optimization of Narrow- and Multi-Band Antennas Using Performance-Driven Surrogates
PublikacjaUncertainty quantification is an important aspect of engineering design, also pertaining to the development and performance evaluation of antenna systems. Manufacturing tolerances as well as other types of uncertainties, related to material parameters (e.g., substrate permittivity) or operating conditions (e.g., bending) may affect the antenna characteristics. In the case of narrow- or multi-band antennas, this usually leads to...
-
Active Learning on Ensemble Machine-Learning Model to Retrofit Buildings Under Seismic Mainshock-Aftershock Sequence
PublikacjaThis research presents an efficient computational method for retrofitting of buildings by employing an active learning-based ensemble machine learning (AL-Ensemble ML) approach developed in OpenSees, Python and MATLAB. The results of the study shows that the AL-Ensemble ML model provides the most accurate estimations of interstory drift (ID) and residual interstory drift (RID) for steel structures using a dataset of 2-, to 9-story...
-
VARIANT DESIGNING IN the PRELIMINARY SMALL SHIP DESIGN PROCESS
PublikacjaShip designing is a complex process, as the ship itself is a complex, technical multi-level object which operates in the air/water boundary environment and is exposed to the action of many different external and internal factors resulting from the adopted technical solutions, type of operation, and environmental conditions. A traditional ship design process consists of a series of subsequent multistage iterations, which gradually...
-
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...
-
Recycled rubber wastes-based polymer composites with flame retardancy and electrical conductivity: Rational design, modeling and optimization
PublikacjaPolymer recycling techniques experience a maturity period of design and application. Rubbers comprise a high proportion of polymer wastes, highly flammable and impossible to re-melt. Polymer composites based on ground tire rubber (GTR) and ethylene-vinyl acetate copolymer (EVA) containing carbon black (CB) (1–50 phr), with variable EVA/GTR weight composition (10/90, 25/75, 50/50, 75/25 and 90/10), and processing temperature (Low:...
-
Zero-Pole Electromagnetic Optimization
PublikacjaA fast technique for the full-wave optimization of transmission or reflection properties of general linear timeinvariant high-frequency components is proposed. The method is based on the zeros and poles of the rational function representing the scattering parameters of the device being designed and it is the generalization of the technique developed for the design by optimization of microwave filters. The performance of the proposed...
-
A structure and design of a novel compact UWB MIMO antenna
PublikacjaIn the paper, a concept and design procedure of a novel compact MIMO slot antenna is presented. In order to achieve a better filling of available space, individual antennas are constrained to a triangular shape and optimized for a reduced size. The MIMO structure is then assembled using the two of previously designed antennas in orthogonal arrangement. Surrogate-assisted numerical optimization involving variable-fidelity electromagnetic...
-
DESIGN AND THEORETICAL ANALYSIS OF A PROTOTYPE TILTING-PAD RADIAL BEARING WITH ADJUSTABLE CLEARANCE
PublikacjaThe article introduces a design and analysis results of a prototype ORC (organic Rankine cycle) turbo generator rotor assembly of 300kW power, supported by tilting-pad bearings of original design. The calculations were performed for a prototype turbo generator rotor. The shaft of this machine is supported with two radial bearings, lubricated with an unusual lubricant – a low-boiling-point agent. The main objective of the presented...
-
MACHINE LEARNING–BASED ANALYSIS OF ENGLISH LATERAL ALLOPHONES
PublikacjaAutomatic classification methods, such as artificial neural networks (ANNs), the k-nearest neighbor (kNN) and selforganizing maps (SOMs), are applied to allophone analysis based on recorded speech. A list of 650 words was created for that purpose, containing positionally and/or contextually conditioned allophones. For each word, a group of 16 native and non-native speakers were audio-video recorded, from which seven native speakers’...
-
On geometry parameterization for simulation-driven design closure of antenna structures
PublikacjaFull-wave electromagnetic (EM) simulation tools have become ubiquitous in antenna design, especially final tuning of geometry parameters. From the reliability standpoint, the recommended realization of EM-driven design is through rigorous numerical optimization. It is a challenging endeavor with the major issues related to the high computational cost of the process, but also the necessity of handling several objectives and constraints...
-
MULTI-CRITERIA ASSESSMENT SYSTEM FOR ARCHITECTURAL DESIGN IN PRACTICE AND TEACHING
Publikacja -
Simulation-Driven Design of Microstrip Antenna Subarrays
PublikacjaA methodology for computationally efficient simulation-driven design of microstrip antenna subarrays is presented. Our approach takes into account the effect of the feed (e.g., a corporate network) on the subarray side lobe level and allows adjusting both radiation and reflection responses of the structure under design within a single automated process. This process is realized as surrogate-based optimization that produces designs...
-
Validating the Rules of Government Automation
PublikacjaThere is growing evidence on the benefits and risks of government automation, and how should government organizations proceed with automation when the benefits outweigh the risks. This evidence was recently consolidated into the "rules of government automation", part of the project funded by the Inter-American Development Bank. The project uncovered that the combined nature of government work and its transformation into digital...
-
Use of the AHP Method for Preference Determination in Yacht Design
PublikacjaA sailing yacht is a human-centred product, the design of which revolves primarily around the wants and desires of the future owner. In most cases, these preferences are not measurable, such as a personal aesthetic feeling, or a need for comfort, speed, safety etc. The aims of this paper are to demonstrate that these preferences can be classified and represented numerically, and to show that they are correlated with the type of...
-
Use of the AHP Method for Preference Determination in Yacht Design
PublikacjaA sailing yacht is a human-centred product, the design of which revolves primarily around the wants and desires of the future owner. In most cases, these preferences are not measurable, such as a personal aesthetic feeling, or a need for comfort, speed, safety etc. The aims of this paper are to demonstrate that these preferences can be classified and represented numerically, and to show that they are correlated with the type...
-
From Linear Classifier to Convolutional Neural Network for Hand Pose Recognition
PublikacjaRecently gathered image datasets and the new capabilities of high-performance computing systems have allowed developing new artificial neural network models and training algorithms. Using the new machine learning models, computer vision tasks can be accomplished based on the raw values of image pixels instead of specific features. The principle of operation of deep neural networks resembles more and more what we believe to be happening...
-
Design Optimization of an Anisotropic Magnetoresistance Sensor for Detection of Magnetic Nanoparticles
Publikacja -
On the complexity of resilient network design
Publikacja -
Gesture Recognition With the Linear Optical Sensor and Recurrent Neural Networks
PublikacjaIn this paper, the optical linear sensor, a representative of low-resolution sensors, was investigated in the multiclass recognition of near-field hand gestures. The recurrent neural network (RNN) with a gated recurrent unit (GRU) memory cell was utilized as a gestures classifier. A set of 27 gestures was collected from a group of volunteers. The 27 000 sequences obtained were divided into training, validation, and test subsets....
-
Prediction of maximum tensile stress in plain-weave composite laminates with interacting holes via stacked machine learning algorithms: A comparative study
PublikacjaPlain weave composite is a long-lasting type of fabric composite that is stable enough when being handled. Open-hole composites have been widely used in industry, though they have weak structural performance and complex design processes. An extensive number of material/geometry parameters have been utilized for designing these composites, thereby an efficient computational tool is essential for that purpose. Different Machine Learning...
-
Prototype and design of six axis robotic manipulator
PublikacjaThe paper presents a design of six axis manipulator. The design consists of specially designed solutions for housing, planetary gearboxes and electronics. The manipulator is controlled by a supervisory control system. The use of a series of measuring elements allows to track the current position of each axis and use this to create a cascade control loop with velocity and acceleration feed-forward. The implemented control algorithm...
-
Inline Microwave Filters With N+1 Transmission Zeros Generated by Frequency-Variant Couplings: Coupling-Matrix-Based Synthesis and Design
PublikacjaA general coupling-matrix-based synthesis methodology for inline Nth-order microwave bandpass filters (BPFs) with frequency-variant reactive-type couplings that generate N+1 transmission zeros (TZs) is presented in this brief. The proposed approach exploits the formulation of the synthesis problem as three inverse nonlinear eigenvalue problems (INEVPs) so that the coupling matrix is built from their sets of eigenvalues. For this...
-
Design process as complex system
Publikacja -
Playback detection using machine learning with spectrogram features approach
PublikacjaThis paper presents 2D image processing approach to playback detection in automatic speaker verification (ASV) systems using spectrograms as speech signal representation. Three feature extraction and classification methods: histograms of oriented gradients (HOG) with support vector machines (SVM), HAAR wavelets with AdaBoost classifier and deep convolutional neural networks (CNN) were compared on different data partitions in respect...
-
User Orientation Detection in Relation to Antenna Geometry in Ultra-Wideband Wireless Body Area Networks Using Deep Learning
PublikacjaIn this paper, the issue of detecting a user’s position in relation to the antenna geometry in ultra-wideband (UWB) off-body wireless body area network (WBAN) communication using deep learning methods is presented. To measure the impulse response of the channel, a measurement stand consisting of EVB1000 devices and DW1000 radio modules was developed and indoor static measurement scenarios were performed. It was proven that for...
-
Specification-Oriented Automatic Design of Topologically Agnostic Antenna Structure
PublikacjaDesign of antennas for modern applications is a challenging task that combines cognition-driven development of topology intertwined with tuning of its parameters using rigorous numerical optimization. However, the process can be streamlined by neglecting the engineering insight in favor of automatic de-termination of structure geometry. In this work, a specification-oriented design of topologically agnostic antenna is considered....
-
Kriging metamodels and design re‐utilization for fast parameter tuning of antenna structures
PublikacjaThe paper addresses the problem of computationally efficient electromagnetic (EM)‐driven design closure of antenna structures. The foundations of the presented approach are fast kriging interpolation metamodels, utilized for two purposes: (a) producing a good starting point for further parameter tuning, and (b) yielding a reasonable Jacobian matrix estimate to jump‐start the optimization procedure. The models are rendered using...
-
Dynamically positioned ship steering making use of backstepping method and artificial neural networks
PublikacjaThe article discusses the issue of designing a dynamic ship positioning system making use of the adaptive vectorial backstepping method and RBF type arti cial neural networks. In the article, the backstepping controller is used to determine control laws and neural network weight adaptation laws. e arti cial neural network is applied at each time instant to approximate nonlinear functions containing parametric uncertainties....
-
Space Mission Risk, Sustainability and Supply Chain: Review, Multi-Objective Optimization Model and Practical Approach
Publikacja -
Evaluation of Machine Learning Methods for the Experimental Classification and Clustering of Higher Education Institutions
PublikacjaHigher education institutions have a big impact on the future of skills supplied on the labour market. It means that depending on the changes in labour market, higher education institutions are making changes to fields of study or adding new ones to fulfil the demand on labour market. The significant changes on labour market caused by digital transformation, resulted in new jobs and new skills. Because of the necessity of computer...
-
Hybrid of Neural Networks and Hidden Markov Models as a modern approach to speech recognition systems
PublikacjaThe aim of this paper is to present a hybrid algorithm that combines the advantages ofartificial neural networks and hidden Markov models in speech recognition for control purpos-es. The scope of the paper includes review of currently used solutions, description and analysis of implementation of selected artificial neural network (NN) structures and hidden Markov mod-els (HMM). The main part of the paper consists of a description...
-
Interaction Design in Agile IT Projects
PublikacjaIn recent years, interactive systems, such as various types of software, online services or mobile applications, have become an integral part of everyday life. Interactive systems and digital services should be easy to use and provide a positive User Experience (UX). For this reason, interaction design has recently emerged as a distinct professional area of information technology (IT). Easy interaction and user experience (UX)...
-
Classification of objects in the LIDAR point clouds using Deep Neural Networks based on the PointNet model
PublikacjaThis work attempts to meet the challenges associated with the classification of LIDAR point clouds by means of deep learning. In addition to achieving high accuracy, the designed system should allow the classification of point clouds covering an area of several dozen square kilometers within a reasonable time interval. Therefore, it must be characterized by fast processing and efficient use of memory. Thus, the most popular approaches...
-
Convolutional Neural Networks for C. Elegans Muscle Age Classification Using Only Self-Learned Features
PublikacjaNematodes Caenorhabditis elegans (C. elegans) have been used as model organisms in a wide variety of biological studies, especially those intended to obtain a better understanding of aging and age-associated diseases. This paper focuses on automating the analysis of C. elegans imagery to classify the muscle age of nematodes based on the known and well established IICBU dataset. Unlike many modern classification methods, the proposed...
-
Improved-Efficacy EM-Based Antenna Miniaturization by Multi-Fidelity Simulations and Objective Function Adaptation
PublikacjaThe growing demands for integration of surface mount design (SMD) antennas into miniatur-ized electronic devices have been continuously imposing limitations on the structure dimen-sions. Examples include embedded antennas in applications such as on-board devices, picosatel-lites, 5G communications, or implantable and wearable devices. The demands for size reduction while ensuring a satisfactory level of the electrical and field...
-
Machine-Learning Methods for Estimating Performance of Structural Concrete Members Reinforced with Fiber-Reinforced Polymers
PublikacjaIn recent years, fiber-reinforced polymers (FRP) in reinforced concrete (RC) members have gained significant attention due to their exceptional properties, including lightweight construction, high specific strength, and stiffness. These attributes have found application in structures, infrastructures, wind power equipment, and various advanced civil products. However, the production process and the extensive testing required for...
-
Efficient uncertainty quantification using sequential sampling-based neural networks
PublikacjaUncertainty quantification (UQ) of an engineered system involves the identification of uncertainties, modeling of the uncertainties, and the forward propagation of the uncertainties through a system analysis model. In this work, a novel surrogate-based forward propagation algorithm for UQ is proposed. The proposed algorithm is a new and unique extension of the recent efficient global optimization using neural network (NN)-based...
-
Optical method supported by machine learning for urinary tract infection detection and urosepsis risk assessment
PublikacjaThe study presents an optical method supported by machine learning for discriminating urinary tract infections from an infection capable of causing urosepsis. The method comprises spectra of spectroscopy measurement of artificial urine samples with bacteria from solid cultures of clinical E. coli strains. To provide a reliable classification of results assistance of 27 algorithms was tested. We proved that is possible to obtain...
-
Preeclampsia Risk Prediction Using Machine Learning Methods Trained on Synthetic Data
PublikacjaThis paper describes a research study that investigates the use of machine learning algorithms on synthetic data to classify the risk of developing preeclampsia by pregnant women. Synthetic datasets were generated based on parameter distributions from three real patient studies. Four models were compared: XGBoost, Support Vector Machine (SVM), Random Forest, and Explainable Boosting Machines (EBM). The study found that the XGBoost...
-
Optimal Design of Transmitarray Antennas via Low-Cost Surrogate Modelling
PublikacjaOver the recent years, reflectarrays and transmitarrays have been drawing a considerable attention due to their attractive features, including a possibility of realizing high gain and pencil-like radiation patterns without the employment of complex feeding networks. Among the two, transmitarrays seem to be superior over reflectarrays in terms of achieving high radiation efficiency without the feed blockage. Notwithstanding, the...
-
A structure and simulation-driven design of compact CPW-fed UWB antenna
PublikacjaIn this letter, a structure of a miniaturized ultra-wideband CPW-fed antenna and its design proce-dure are presented. The antenna is a modified version of the design previously proposed in the literature, with additional degrees of freedom introduced in order to improve the structure flexibility. The small size is achieved by executing a rigorous optimization procedure that consists of two stages: (i) smart random search carried...
-
Analysis of the design development of the sliding table saw spindles
PublikacjaProducers of sliding table saws constantly strive for improvement in sawing accuracy. One of the method is an upswing in a spindle behavior, since, it affects to a large degree sawing effects. The design development of sliding table saw spindles during the last quarter-century is presented. The spindle system of the modernized spindle of the sawing machine Fx550 is described.
-
Active Annotation in Evaluating the Credibility of Web-Based Medical Information: Guidelines for Creating Training Data Sets for Machine Learning
PublikacjaMethods Results Discussion References Abbreviations Copyright Abstract Background: The spread of false medical information on the web is rapidly accelerating. Establishing the credibility of web-based medical information has become a pressing necessity. Machine learning offers a solution that, when properly deployed, can be an effective tool in fighting medical misinformation on the web. Objective: The aim of this study is to...