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Search results for: MICROWAVE ENGINEERING, COMPUTER-AIDED DESIGN, MULTI-CRITERIAL OPTIMIZATION, MACHINE LEARNING, NEURAL NETWORKS
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Selection of circuit geometry for miniaturized microwave components based on concurrent optimization of performance and layout area
PublicationThe paper presents a framework for automated EM-driven circuit geometry selection of miniaturized microwave components. Selection of a particular layout is based directly on miniaturization rates achieved for a set of candidate circuit geometries. Size reduction of the considered structures is obtained by replacing their main building blocks (i.e., conventional transmission lines) with slow-wave composite cells and meander lines....
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Accurate Modeling of Antenna Structures by Means of Domain Confinement and Pyramidal Deep Neural Networks
PublicationThe importance of surrogate modeling techniques has been gradually increasing in the design of antenna structures over the recent years. Perhaps the most important reason is a high cost of full-wave electromagnetic (EM) analysis of antenna systems. Although imperative in ensuring evaluation reliability, it entails considerable computational expenses. These are especially pronounced when carrying out EM-driven design tasks such...
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Design and Optimization of a Compact Planar Radiator for UWB Applications and Beyond
PublicationA compact monopole antenna for ultra-wideband (UWB) and beyond applications has been proposed. The radiator is based on the monopole topology. The super-wideband behavior has been achieved using a combination of spline-based modifications applied to the driven element, as well as utilization of a tapered feed and a slot-modified ground plane. The electrical performance of the structure has been tuned using a numerical optimization...
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Expedited EM-driven multi-objective antenna design in highly-dimensional parameter spaces
PublicationA technique for low-cost multi-objective optimization of antennas in highly-dimensional parameter spaces is presented. The optimization procedure is expedited by exploiting fast surrogate models, including coarse-discretization EM antenna simulations and response surface approximations (RSA). The latter is utilized to yield an initial set of Pareto non-dominated designs which are further refined using response correction methods....
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The use of fast molecular descriptors and artificial neural networks approach in organochlorine compounds electron ionization mass spectra classification
PublicationDeveloping of theoretical tools can be very helpful for supporting new pollutant detection. Nowadays, a combination of mass spectrometry and chromatographic techniques are the most basic environmental monitoring methods. In this paper, two organochlorine compound mass spectra classification systems were proposed. The classification models were developed within the framework of artificial neural networks (ANNs) and fast 1D and...
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Statistical analysis and robust design of circularly polarized antennas using sequential approximate optimization
PublicationIn 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 Use of Artificial Neural Networks and Decision Trees to Predict the Degree of Odor Nuisance of Post-Digestion Sludge in the Sewage Treatment Plant Process
PublicationThis paper presents the application of artificial neural networks and decision trees for the prediction of odor properties of post-fermentation sludge from a biological-mechanical wastewater treatment plant. The input parameters were concentrations of popular compounds present in the sludge, such as toluene, p-xylene, and p-cresol, and process parameters including the concentration of volatile fatty acids, pH, and alkalinity in...
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Breast MRI segmentation by deep learning: key gaps and challenges
PublicationBreast MRI segmentation plays a vital role in early diagnosis and treatment planning of breast anomalies. Convolutional neural networks with deep learning have indicated promise in automating this process, but significant gaps and challenges remain to address. This PubMed-based review provides a comprehensive literature overview of the latest deep learning models used for breast segmentation. The article categorizes the literature...
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Driver’s Condition Detection System Using Multimodal Imaging and Machine Learning Algorithms
PublicationTo this day, driver fatigue remains one of the most significant causes of road accidents. In this paper, a novel way of detecting and monitoring a driver’s physical state has been proposed. The goal of the system was to make use of multimodal imaging from RGB and thermal cameras working simultaneously to monitor the driver’s current condition. A custom dataset was created consisting of thermal and RGB video samples. Acquired data...
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Neural Network Subgraphs Correlation with Trained Model Accuracy
PublicationNeural Architecture Search (NAS) is a computationally demanding process of finding optimal neural network architecture for a given task. Conceptually, NAS comprises applying a search strategy on a predefined search space accompanied by a performance evaluation method. The design of search space alone is expected to substantially impact NAS efficiency. We consider neural networks as graphs and find a correlation between the presence...
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The use of machine learning for face regions detection in thermograms
PublicationThe aim of this study is to analyse the methods of detecting characteristic points of the face in thermographic images. As part of the implementation an extensive analysis of scientific publications covering similar issues both for the analysis of images made in visible light and thermographic images was carried out. On the basis of this analysis, 3 models were selected and then they were implemented and tested on the basis of...
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PERFORMANCE COMPARISON OF MACHINE LEARNING ALGORITHMS FOR PREDICTIVE MAINTENANCE
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Machine Learning for Sensorless Temperature Estimation of a BLDC Motor
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Machine learning applied to bi-heterocyclic drugs recognition
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Machine learning system for estimating the rhythmic salience of sounds.
PublicationW artykule przedstawiono badania dotyczące wyszukiwania danych rytmicznych w muzyce. W pracy przedstawiono postać funkcji rankingujacej poszczególnych dźwięków frazy muzycznej. Opracowano metodę tworzenia wszystkich możliwych hierarchicznych struktur rytmicznych, zwanych hipotezami rytmicznymi. Otrzymane hipotezy są następnie porządkowane w kolejności malejącej wartości funkcji rankingującej, aby ustalić, która ze znalezionych...
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Personal bankruptcy prediction using machine learning techniques
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Stacking-Based Integrated Machine Learning with Data Reduction
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Data Reduction Algorithm for Machine Learning and Data Mining
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Design and Implementation of Multi-Band Reflectarray Metasurface for 5G Millimeter Wave Coverage Enhancement
PublicationA compact low-profile multi-band millimeter-wave (mm-wave) reflectarray metasurface design is presented for coverage enhancement in 5G and beyond cellular communication. The proposed single-layer metasurface exhibits a stable reflection response under oblique incidence angles of up to 60o at 24 and 38 GHz, and transmission response at 30 GHz, effectively covering the desired 5G mm-wave frequency bands. The proposed reflectarray...
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Application of neural networks for turbine rotor trajectory investigation.
PublicationW pracy przedstawiono rezultaty badań sieci neuronowych przewidujących trajektorię wirnika turbinowego uzyskanych ze stanowiska turbiny modelowej. Badania wykazały, iż sieci neuronowe wydają się być z powodzeniem zastosowane do przewidywania trajektorii ruchu wirnika turbiny. Najważniejszym zadaniem wydaje się poprawne określenie wektorów sygnałów wejściowych oraz wyjściowych jak również prawidłowe stworzenie sieci neuronowej....
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Problems in toxicity analysis - application of fuzzy neural networks
PublicationPraca dotyczy zastosowania sztucznych sieci neuronowych do przygotowywania danych do szacowania toksyczności (wody powierzchniowe). Przygotowanie to polega na sztucznym zagęszczaniu zbioru danych, które następnie mogą być wykorzystane do szacowania/modelowania wartości toksyczności na ich podstawie.
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Neural networks in the diagnostics of induction motor rotor cages.
PublicationW środowisku Lab VIEW została stworzona aplikacja służąca do pomiaru, prezentacji i zapisu przebiegów widma prądu stojana z uwzględnieniem potrzeb pomiarowych występujących podczas badania wirników silników indukcyjnych przy użyciu sieci neuronowych. Utworzona na bazie zbioru uczącego sieć Kohonena z powodzeniem rozwiązała stawiany przed nią problem klasyfikacji widm prądu stojana, a co za tym idzie również diagnozy stanu...
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Applications of neural networks and perceptual masking to audio restoration
PublicationOmówiono zastosowania algorytmów uczących się w dziedzinie rekonstruowania nagrań fonicznych. Szczególną uwagę zwrócono na zastosowanie sztucznych sieci neuronowych do usuwania zakłócających impulsów. Ponadto opisano zastosowanie inteligentnego algorytmu decyzyjnego do sterowania maskowaniem perceptualnym w celu redukowania szumu.
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Fusion-based Representation Learning Model for Multimode User-generated Social Network Content
PublicationAs mobile networks and APPs are developed, user-generated content (UGC), which includes multi-source heterogeneous data like user reviews, tags, scores, images, and videos, has become an essential basis for improving the quality of personalized services. Due to the multi-source heterogeneous nature of the data, big data fusion offers both promise and drawbacks. With the rise of mobile networks and applications, UGC, which includes...
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Local response surface approximations and variable-fidelity electromagnetic simulations for computationally efficient microwave design optimisation
PublicationIn this study, the authors propose a robust and computationally efficient algorithm for simulation-driven design optimisation of microwave structures. Our technique exploits variable-fidelity electromagnetic models of the structure under consideration. The low-fidelity model is optimised using its local response surface approximation surrogates. The high-fidelity model is refined by space mapping with polynomial interpolation of...
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Use of Neural Networks in Diagnostics of Rolling-Element Bearing of the Induction Motor
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Exploring the Solubility Limits of Edaravone in Neat Solvents and Binary Mixtures: Experimental and Machine Learning Study
PublicationThis study explores the edaravone solubility space encompassing both neat and binary dissolution media. Efforts were made to reveal the inherent concentration limits of common pure and mixed solvents. For this purpose, the published solubility data of the title drug were scrupulously inspected and cured, which made the dataset consistent and coherent. However, the lack of some important types of solvents in the collection called...
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Generalized regression neural network and fitness dependent optimization: Application to energy harvesting of centralized TEG systems
PublicationThe thermoelectric generator (TEG) system has attracted extensive attention because of its applications in centralized solar heat utilization and recoverable heat energy. The operating efficiency of the TEG system is highly affected by operating conditions. In a series-parallel structure, due to diverse temperature differences, the TEG modules show non-linear performance. Due to the non-uniform temperature distribution (NUTD) condition,...
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Cleaner energy for sustainable future using hybrid photovoltaics-thermoelectric generators system under non-static conditions using machine learning based control technique
PublicationIn addition to the load demand, the temperature difference between the hot and cold sides of the thermoelectric generator (TEG) module determines the output power for thermoelectric generator systems. Maximum power point tracking (MPPT) control is needed to track the optimal global power point as operating conditions change. The growing use of electricity and the decline in the use of fossil fuels have sparked interest in photovoltaic-TEG...
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THE ROLE OF INFERENCE IN MOBILE MEDICAL APPLICATION DESIGN
PublicationIn 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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Maximization of multicast periodic traffic throughput in multi-hop wireless networks with broadcast transmissions
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Technology-Enhanced Environmental Learning: Co-design of Educational Mobile Application Case
PublicationThe process of co-creating an educational mobile application to support environmentally friendly behavior is presented in this paper. The research material consisted of quantitative data collected on the application during the first testing phase by early adopters. The results suggest that the most frequently used features of the app were related to transport and educational activities. While women tended to split their time between...
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Kriging Models for Microwave Filters
PublicationSurrogate modeling of microwave filters’ response is discussed. In particular, kriging is used to model either the scattering parameters of the filter or the rational representation of the filter’s characteristics. Surrogate models for these two variants of kriging are validated in solving a microwave filter optimization problem. A clear advantage of surrogate models based on the rational representation over the models based on scattering...
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Design of Microwave Lossy Filter Based on Substrate Integrated Waveguide (SIW)
PublicationIn this letter, we propose a lossy three-pole Chebyshev filter centered at 5.15 GHz, based on the substrate integrated waveguide (SIW) with scattering characteristics shifted down by 5.68 dB. The filter is composed of three directly coupled SIW cavities with three lossy couplings between nonadjacent resonators. These additional couplings are realized using mixed coupled slot and microstrip lines connected with metal electrode leadless...
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Interpretable Deep Learning Model for the Detection and Reconstruction of Dysarthric Speech
PublicationWe 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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Application possibilities of LBN for civil engineering issues
PublicationBayesian Networks (BN) are efficient to represent knowledge and for the reasoning in uncertainty. However the classic BN requires manual definition of the network structure by an expert, who also defines the values entered into the conditional probability tables. In practice, it can be time-consuming, hence the article proposes the use of Learning Bayesian Networks (LBN). The aim of the study is not only to present LBN, which can...
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Computer aided registration of current pulses in polyethylene insulation during the first stage of electrical treeing.
PublicationW referacie przedstawiono aplikację w programie Labview do automatycznej rejestracji impulsów prądowych zjawisku drzewienia elektrycznego w izolacji polietylenowej.
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Cost minimisation in unbounded multi-interface networks
PublicationW pracy badano problem odłączania niektórych urządzeń komunikacyjnych w wielointerfejsowych sieciach bezprzewodowych w taki sposób, by zapewnić realizację wymaganego grafu połączeń przy jednoczesnej minimalizacji zużycia energii. Sformułowano problem optymalizacyjny, podano wyniki dotyczące jego trudności i zaproponowano algorytmy optymalizacyjne dla wariantu, w którym liczba interfejsów komunikacyjnych jest potencjalnie nieograniczona...
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Task Assignments in Logistics by Adaptive Multi-Criterion Evolutionary Algorithm with Elitist Selection
PublicationAn evolutionary algorithm with elitist selection has been developed for finding Pareto-optimal task assignments in logistics. A multi-criterion optimization problem has been formulated for finding a set of Pareto- optimal solutions. Three criteria have been applied for evaluation of task assignment: the workload of a bottleneck machine, the cost of machines, and the numerical performance of system. The machine constraints have...
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Reducing the Environmental Impact of the Public Water Transportation Systems by Parametric Design and Optimization of Vessels’ Hulls. Study of the Gdańsk’s Electric Passenger Ferry (2015-2016).
PublicationThe paper presents the potential and risks of utilizing Rhinoceros and Grasshopper software for parametric design and multi-varietal optimization of the hull of a small sustainable ferry. The sustainability criteria, parametric design flowchart and optimizing methods are described. As the result, the advantages and disadvantages of this approach obtained in the research-by-design process conducted by an intercollegiate team at...
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Patch size setup and performance/cost trade-offs in multi-objective antenna optimization using domain patching technique
PublicationA numerical study concerning multi-objective optimization of antenna structures using sequential domain patching (SDP) technique has been presented. We investigate the effect of various setups of the patch size on the operation of the SDP algorithm and possible trade-offs concerning the quality of the Pareto set found by SDP and the computational cost of the optimization process. Our considerations are illustrated using a UWB monopole...
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Design of a Planar UWB Dipole Antenna with an Integrated Balun Using Surrogate-Based Optimization
PublicationA design of an ultra-wideband (UWB) antenna with an integrated balun is presented. A fully planar balun configuration interfacing the microstrip input of the structure to the coplanar stripline (CPS) input of the dipole antenna is introduced. The electromagnetic (EM) model of the structure of interest includes the dipole, the balun, and the microstrip input to account for coupling and radiation effects over the UWB band. The EM...
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Applying artificial intelligence for cellular networks optimization
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Mathematical Models in Design Process of Ship Bow Thrusters
PublicationThe paper describes an application of simulation models for computer-aided design of ship bow thrusters. Generation of simulation models of ship bow thruster requires development and verifying of mathematical models of system component elements. Using the results of simulation the expert system is able to determine, that the rules of classification societies are met. Design procedures and mathematical models are part of an expert...
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Mathematical Models in Design Process of Ship Bow Thrusters
PublicationThe presentation is about an application of simulation models for computer-aided design of ship bow thrusters. Generation of simulation models of ship bow thruster requires development and verifying of mathematical models of system component elements. Using the results of simulation the expert system is able to determine, that the rules of classification societies are met. Design procedures and mathematical models are part of an...
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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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Simulation-driven size-reduction-oriented design of multi-band antennas by means of response features
PublicationThis study addresses the problem of explicit size reduction of multi-band antennas by means of simulation-driven optimisation. The principal difficulty of electromagnetic (EM)-based miniaturisation of multi-band antennas is that several resonances have to be controlled independently (both in terms of their frequency allocation and depth) while attempting to reduce physical dimensions of the structure at hand. The design method...
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Machine learning techniques combined with dose profiles indicate radiation response biomarkers
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MACHINE VISION DETECTION OF THE CIRCULAR SAW VIBRATIONS
PublicationDynamical properties of rotating circular saw blades are crucial for both production quality and personnel safety. This paper presents a novel method for monitoring circular saw vibrations and deviations. A machine vision system uses a camera and a laser line projected on the saw’s surface to estimate vibration range. Changes of the dynamic behaviour of the saw were measured as a function of the rotational speed. The critical rotational...
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The Influence of Input Data Standardization Method on Prediction Accuracy of Artificial Neural Networks
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