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Search results for: DATA-DRIVEN MODELLING, MICROWAVE DESIGN, SURROGATE MODELLING, ARTIFICIAL NEURAL NETWORKS, DEEP LEARNING
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Method for Clustering of Brain Activity Data Derived from EEG Signals
PublicationA method for assessing separability of EEG signals associated with three classes of brain activity is proposed. The EEG signals are acquired from 23 subjects, gathered from a headset consisting of 14 electrodes. Data are processed by applying Discrete Wavelet Transform (DWT) for the signal analysis and an autoencoder neural network for the brain activity separation. Processing involves 74 wavelets from 3 DWT families: Coiflets,...
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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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Prediction of maximum tensile stress in plain-weave composite laminates with interacting holes via stacked machine learning algorithms: A comparative study
PublicationPlain 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...
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Results and models for Novel high frequency components with non-conventional shape employing smooth geometry deformation of 3D solid with FFD
Open Research DataThe project aims to investigate the possibility of developing and manufacturing novel high frequency devices having non-standard geometries, allowing for improved electromagnetic performance over what is achievable with currently available design tools. The non-conventional geometry will be obtained by employing the free-form shape deformation technique...
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Expedited Re-Design of Multi-Band Passive Microwave Circuits Using Orthogonal Scaling Directions and Gradient-Based Tuning
PublicationGeometry scaling of microwave circuits is an essential but challenging task. In particular, the employment of a given passive structure in a different application area often requires re-adjustment of the operating frequencies/bands while maintaining top performance. Achieving this necessitates utilization of numerical optimization methods. Nonetheless, if the intended frequencies are distant from the ones at the starting point,...
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Advances in Architectures, Big Data, and Machine Learning Techniques for Complex Internet of Things Systems
PublicationTe feld of Big Data is rapidly developing with a lot of ongoing research, which will likely continue to expand in the future. A crucial part of this is Knowledge Discovery from Data (KDD), also known as the Knowledge Discovery Process (KDP). Tis process is a very complex procedure, and for that reason it is essential to divide it into several steps (Figure 1). Some authors use fve steps to describe this procedure, whereas others...
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Blockchain based Secure Data Exchange between Cloud Networks and Smart Hand-held Devices for use in Smart Cities
PublicationIn relation to smart city planning and management, processing huge amounts of generated data and execution of non-lightweight cryptographic algorithms on resource constraint devices at disposal, is the primary focus of researchers today. To enable secure exchange of data between cloud networks and mobile devices, in particular smart hand held devices, this paper presents Blockchain based approach that disperses a public/free key...
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Krzysztof Goczyła prof. dr hab. inż.
PeopleKrzysztof Goczyła, full professor of Gdańsk University of Technology, computer scientist, a specialist in software engineering, knowledge engineering and databases. He graduated from the Faculty of Electronics Technical University of Gdansk in 1976 with a degree in electronic engineering, specializing in automation. Since then he has been working at Gdańsk University of Technology. In 1982 he obtained a doctorate in computer science...
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Social learning in cluster initiatives
PublicationPurpose – The purpose of the paper is to portray social learning in cluster initiatives (CIs), namely: 1) to explore, with the lens of the communities of practice (CoPs) theory, in what ways social learning occurs in CIs; 2) to discover how various CoPs emerge and evolve in CIs to facilitate a collective journey in their learning process. Subsequently, the authors address the research questions: In what ways does social learning...
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Application of artificial intelligence into/for control of flexible manufacturing cell
PublicationThe application of artificial intelligence in technological processes control is usually limited. One problem is how to respond to changes in the environment of manufacturing system. A way to overcome the above shortcoming is to use fuzzy logic for representation of the inexact information. In this paper fundamentals of artificial intelligence and fuzzy logic are introduced from a theoretical point of view. Still more the fuzzy...
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Fast EM-driven optimization using variable-fidelity EM models and adjoint sensitivities
PublicationA robust and computationally efficient technique for microwave design optimization is presented. Our approach exploits variable-fidelity electromagnetic (EM) simulation models and adjoint sensitivities. The low-fidelity EM model correction is realized by means of space mapping (SM). In the optimization process, the SM parameters are optimized together with the design itself, which allows us to keep the number...
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Designing RBF Networks Using the Agent-Based Population Learning Algorithm
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Machine Learning and Electronic Noses for Medical Diagnostics
PublicationThe need for noninvasive, easy-to-use, and inexpensive methods for point-of-care diagnostics of a variety of ailments motivates researchers to develop methods for analyzing complex biological samples, in particular human breath, that could aid in screening and early diagnosis. There are hopes that electronic noses, that is, devices based on arrays of semiselective or nonselective chemical sensors, can fill this niche. Electronic...
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Prioritising national healthcare service issues from free text feedback – A computational text analysis & predictive modelling approach
PublicationPatient experience surveys have become a key source of evidence for supporting decision-making and continuous quality improvement within healthcare services. To harness free-text feedback collected as part of these surveys for additional insights, text analytics methods are increasingly employed when the data collected is not amenable to traditional qualitative analysis due to volume. However, while text analytics techniques offer...
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Fast Design Optimization of Waveguide Filters Applying Shape Deformation Techniques
PublicationThis paper presents an efficient design of microwave filters by means of geometry optimization using shape deformation techniques. This design procedure allows for modelling complex 3D geometries which can be fabricated by additive manufacturing (AM). Shape deforming operations are based on radial basis function (RBF) interpolation and are integrated into an electromagnetic field simulator based on the 3D finiteelement method (FEM)....
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Robust and Efficient Machine Learning Algorithms for Visual Recognition
PublicationIn visual recognition, the task is to identify and localize all objects of interest in the input image. With the ubiquitous presence of visual data in modern days, the role of object recognition algorithms is becoming more significant than ever and ranges from autonomous driving to computer-aided diagnosis in medicine. Current models for visual recognition are dominated by models based on Convolutional Neural Networks (CNNs), which...
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Review of the Complexity of Managing Big Data of the Internet of Things
PublicationTere is a growing awareness that the complexity of managing Big Data is one of the main challenges in the developing feld of the Internet of Tings (IoT). Complexity arises from several aspects of the Big Data life cycle, such as gathering data, storing them onto cloud servers, cleaning and integrating the data, a process involving the last advances in ontologies, such as Extensible Markup Language (XML) and Resource Description...
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Predictions of cervical cancer identification by photonic method combined with machine learning
PublicationCervical cancer is one of the most commonly appearing cancers, which early diagnosis is of greatest importance. Unfortunately, many diagnoses are based on subjective opinions of doctors—to date, there is no general measurement method with a calibrated standard. The problem can be solved with the measurement system being a fusion of an optoelectronic sensor and machine learning algorithm to provide reliable assistance for doctors...
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Comparison of the exponential thermal transient parameterization methods with the SMTP method in the unipedicled DIEP flap computer modelling and simulation
PublicationThe aim of this paper is to compare the spatial contrast of the image descriptors obtained via three different thermal transient parameterization methods in Active Dynamic Thermography. The thermal constants and amplitude values of the one- and two- exponential parametrization are compared to the Simplified Magnitude-Temporal Parametrization method (SMTP). The comparison is performed using the data obtained by simulating the cold...
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Evolution of Animats Following a Moving Target in an Artificial Ecosystem
PublicationMany biological animals, even microscopically small, are able to track moving sources of food. In this paper, we investigate the emergence of such behavior in artificial animals (animats) in a 2-dimensional simulated liquid environment. These "predators" are controlled by evolving artificial gene regulatory networks encoded in linear genomes. The fate of the predators is determined only by their ability to gather food and reproduce—no...
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An A-Team Approach to Learning Classifiers from Distributed Data Sources
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An A-Team approach to learning classifiers from distributed data sources
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Brain-Inspired Deep Networks for Facial Expression Recognition. Frontiers in Biomedical Technologies
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Playback detection using machine learning with spectrogram features approach
PublicationThis 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...
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Study of various machine learning approaches for Sentinel-2 derived bathymetry
PublicationIn recent years precise and up-to-date information regarding seabed depth has become more and more important for companies and institutions that operate on coastlines. While direct, in-situ measurements are performed regularly, they are expensive, time-consuming and impractical to be performed in short time intervals. At the same time, an ever-increasing amount of satellite imaging data becomes available. With these images, it...
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Turbulence model evaluation for numerical modelling of turbulent flow and heat transfer of nanofluids
PublicationIn this work, Nusselt number and friction factor are calculated numerically for turbulent pipe flow (Reynolds number between 6000 and 12000) with constant heat flux boundary condition using nanofluids. The nanofluid is modelled with the single-phase approach and the simulation results are compared with experimental data. Ethylene glycol and water, 60:40 EG/W mass ratio, as base fluid and SiO2 nanoparticles are used as nanofluid...
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Central European Journal of Economic Modelling and Econometrics
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International Journal of Engineering Systems Modelling and SImulation
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International Journal of Vehicle Systems Modelling and Testing
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Journal of Mathematical Modelling and Algorithms in Operations Research
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RUSSIAN JOURNAL OF NUMERICAL ANALYSIS AND MATHEMATICAL MODELLING
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EXPERIMENTAL AND THEORETICAL FLOW OF THE FORCES IN DEEP BEAMS WITH CANTILEVAR
PublicationThis 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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Surrogate Modeling and Optimization Using Shape-Preserving Response Prediction: A Review
PublicationComputer simulation models are ubiquitous in modern engineering design. In many cases, they are the only way to evaluate a given design with sufficient fidelity. Unfortunately, an added computa-tional expense is associated with higher fidelity models. Moreover, the systems being considered are often highly nonlinear and may feature a large number of designable parameters. Therefore, it may be impractical to solve the design problem...
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Modelling study of flow boiling heat transfer of perspective fluids for refrigeration technology
PublicationThere is a gap of knowledge on flow boiling at high saturation temperatures and higher values of reduced pressure. Thus far, the in-house developed semi-empirical model for flow boiling and flow condensation showed a satisfactory accuracy for calculations for various refrigeration fluids for a wide scope of reduced pressures. This study presents results of calculations of heat transfer coefficient of perspective refrigeration fluids,...
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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
PublicationSiły 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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Design of Optical Wireless Networks with Fair Traffic Flows
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Design of Weather Disruption-Tolerant Wireless Mesh Networks
PublicationZ 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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Predicting the Purchase of Electricity Prices for Renewable Energy Sources Based on Polish Power Grids Data Using Deep Learning Models for Controlling Small Hybrid PV Microinstallations
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Performance-driven yield optimization of high-frequency structures by kriging surrogates
PublicationUncertainty quantification is an important aspect of engineering design, as manufacturing toler-ances may affect the characteristics of the structure. Therefore, quantification of these effects is in-dispensable for adequate assessment of the design quality. Toward this end, statistical analysis is performed, for reliability reasons, using full-wave electromagnetic (EM) simulations. Still, the computational expenditures associated...
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Deep Data Analysis of a Large Microarray Collection for Leukemia Biomarker Identification
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Reliable Microwave Modeling By Means of Variable-Fidelity Response Features
PublicationIn this work, methodologies for low-cost and reliable microwave modeling are presented using variable-fidelity response features. The two key components of our approach are: (i) a realization of the modeling process at the level of suitably selected feature points of the responses (e.g., S-parameters vs. frequency) of the structure at hand, and (ii) the exploitation of variable-fidelity EM simulation data, also for the response...
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A Generalized SDP Multi-Objective Optimization Method for EM-Based Microwave Device Design
PublicationIn this article, a generalized sequential domain patching (GSDP) method for efficient multi-objective optimization based on electromagnetics (EM) simulation is proposed. The GSDP method allowing fast searching for Pareto fronts for two and three objectives is elaborated in detail in this paper. The GSDP method is compared with the NSGA-II method using multi-objective problems in the DTLZ series, and the results show the GSDP method...
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Natalia Sokół dr inż.
PeopleBACKGROUND Master of Science in Light and Lighting (2008-2009/11) The UCL Bartlett School of Graduate Studies, Faculty of the Built Environment, London, UK, www.bartlett.ucl.ac.uk MA Degree in Interior Architecture (1999-2004), The Academy of Fine Arts, Poznan, Poland, www.uap.edu.pl MA Degree in Art Education (1997-2002), Academy of Fine Arts, Poznan, Poland, www.uap.edu.pl MAIN RESEARCH AREAS · ...
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e-Learning - user's guide for students
e-Learning Coursese-Learning - user's guide for students
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Globalized parametric optimization of microwave components by means of response features and inverse metamodels
PublicationSimulation-based optimization of geometry parameters is an inherent and important stage of microwave design process. To ensure reliability, the optimization process is normally carried out using full-wave electromagnetic (EM) simulation tools, which entails significant computational overhead. This becomes a serious bottleneck especially if global search is required (e.g., design of miniaturized structures, dimension scaling over...
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3-D finite-difference time-domain modelling of ground penetrating radar for identification of rebars in complex reinforced concrete structures
PublicationThis paper presents numerical and experimental investigations to identify reinforcing bars using the ground penetrating radar (GPR) method. A novel element of the paper is the inspection of different arrangements of reinforcement bars. Two particular problems, i.e. detection of few adjacent transverse bars and detection of a longitudinal bar located over or under transverse reinforcement, have been raised. An attention was also...
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Cost-Efficient Design Methodology for Compact Rat-Race Couplers
PublicationIn this article, a reliable and low-cost design methodology for simulation-driven optimization of miniaturized rat-race couplers (RRCs) is presented. We exploit a two-stage design approach, where a composite structure (a basic building block of the RRC structure) is first optimized using a pattern search algorithm, and, subsequently, the entire coupler is tuned by means of surrogate-based optimization (SBO) procedure. SBO is executed...
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ADAPTATION OF ENGINEERING FEA-BASED ALGORITHMS TO LCF FAILURE AND MATERIAL DATA PREDICTION IN OFFSHORE DESIGN
PublicationThere is an ever growing industrial demand for quantitative assessment of fatigue endurance of critical structural details. Although FEA-based calculations have become a standard in engineering design, problems involving the Low-To-Medium cycle range (101-104) remain challenging. This paper presents an attempt to optimally choose material data, meshing density and other algorithm settings in the context of recent design of the...
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Expedited Optimization of Passive Microwave Devices Using Gradient Search and Principal Directions
PublicationOver the recent years, utilization of numerical optimization techniques has become ubiquitous in the design of high-frequency systems, including microwave passive components. The primary reason is that the circuits become increasingly complex to meet ever growing performance demands concerning their electrical performance, additional functionalities, as well as miniaturization. Nonetheless, as reliable evaluation of microwave device...