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Wyniki wyszukiwania dla: NEURAL NETWORKS, SURROGATE-BASED OPTIMIZATION, HYPERPARAMETER OPTIMIZATION, SEQUENTIAL SAMPLING
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Problems in toxicity analysis - application of fuzzy neural networks
PublikacjaPraca 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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Artificial Neural Networks in Microwave Components and Circuits Modeling
PublikacjaArtykuł dotyczy wykorzystania sztucznych sieci neuronowych (SNN) w projektowaniu i optymalizacji układów mikrofalowych.Zaprezentowano podstawowe zasady i założenia modelowania z użyciem SNN. Możliwości opisywanej metody opisano wykorzystując przykładowyprojekt anteny łatowej. Przedstawiono różne strategie modelowania układów, które wykorzystują możliwości opisywanej metody w połączeniu zwiedzą mikrofalową. Porównano również dokładność...
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Neural networks in the diagnostics of induction motor rotor cages.
PublikacjaW 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
PublikacjaOmówiono 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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Analysis of circular polarization antenna design trade‐offs using low‐cost EM‐driven multiobjective optimization
PublikacjaCircular polarization (CP) antennas are vital components of modern communication systems. Their design involves handling several requirements such as low reflection and axial ratio (AR) within the frequency range of interest. Small size is an important criterion for antenna mobility which is normally achieved as a by‐product of performance‐oriented modifications of the structure topology. In this work, multiobjective optimization...
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Recent advances in rapid multiobjective optimization of expensive simulation models in microwave and antenna engineering by Pareto front exploration
PublikacjaPractical engineering design problems are inherently multiobjective, that is, require simultaneous control of several (and often conflicting) criteria. In many situations, genuine multiobjective optimization is required to acquire comprehensive information about the system of interest. The most popular solution techniques are populationbased metaheuristics, however, they are not practical for handling expensive electromagnetic...
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Fast multi-objective design optimization of microwave and antenna structures using data-driven surrogates and domain segmentation
PublikacjaPurpose Strategies and algorithms for expedited design optimization of microwave and antenna structures in multi-objective setup are investigated. Design/methodology/approach Formulation of the multi-objective design problem oriented towards execution of the population-based metaheuristic algorithm within the segmented search space is investigated. Described algorithmic framework exploit variable fidelity modeling, physics- and...
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Fast surrogate-assisted simulation-driven design of compact microwave hybrid couplers
PublikacjaThis work presents a robust methodology for expedited simulation-driven design optimization of compact microwave hybrid couplers. The technique relies on problem decomposition, and a bot-tom–up design strategy, starting from the level of basic building blocks of the coupler, and finishing with a tuning procedure that exploits a fast surrogate model of the entire structure. The latter is constructed by cascading local response surface...
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The Neural Knowledge DNA Based Smart Internet of Things
PublikacjaABSTRACT The Internet of Things (IoT) has gained significant attention from industry as well as academia during the past decade. Smartness, however, remains a substantial challenge for IoT applications. Recent advances in networked sensor technologies, computing, and machine learning have made it possible for building new smart IoT applications. In this paper, we propose a novel approach: the Neural Knowledge DNA based Smart Internet...
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Controlling nodal displacement of pantographic structures using matrix condensation and interior-point optimization: A numerical and experimental study
PublikacjaThis study presents an innovative approach for the precise control of nodal displacements in pantographic structures. The method is founded on the Matrix Condensation of Force Method, seamlessly integrated with an Interior Point Optimization algorithm. This combination offers a unique advantage by allowing users to manipulate displaced nodes within a defined coordination domain. Furthermore, this approach introduces the Interior...
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Optimization of electrochemical doping approach resulting in highly photoactive iodine-doped titania nanotubes
PublikacjaThe paper focuses on the optimization procedure concerning the synthesis method resulting in highly ordered titania nanotubes doped with iodine atoms. The doping process was based on the electrochemical treatment of a titania nanotube layer immersed in a potassium iodide (KI) solution acting as an iodine precursor. A number of endeavors were undertaken in order to optimize the doping conditions. Electrolyte concentration, reaction...
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Rapid optimization of compact microwave passives using kriging surrogates and iterative correction
PublikacjaDesign of contemporary microwave components is—in a large part—based on full-wave electromagnetic (EM) simulation tools. The primary reasons for this include reliability and versatility of EM analysis. In fact, for many microwave structures, notably compact components, EM-driven parameter tuning is virtually imperative because traditional models (analytical or network equivalents) are unable to account for the cross-coupling effects,...
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The Simulation of Activated Sludge System for Optimization of Predictive Aeration at Large WWTP
PublikacjaEffective use of biodegradable substrates as an internal carbon sources (ICS) for denitrification and EBPR and predicting performance of aeration systems during nitrification in activated sludge bioreactors, may be useful in realization the sustainable development by potentially saving energy consumption at WWTPs. A large number of WWTPs use activated sludge systems with an integrated removal of carbon, nitrogen and phosphorus...
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Optimization of the UNRES Force Field by Hierarchical Design of the Potential-Energy Landscape. 3. Use of Many Proteins in Optimization
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Design and optimization of IIR digital filters with non-standard characteristics using continuous ant colony optimization algorithm
PublikacjaW pracy przedstawiono metodę projektowania i optymalizacji stabilnych filtrów cyfrowych IIR o niestandardowych charakterystykach amplitudowych, przy zastosowaniu ''mrówkowego'' algorytmu optymalizującego ACO. W proponowanej metodzie (nazwanej ACO-IIRFD), wprowadzono dynamiczne zmiany parametrów. Dzięki tym zmianom parametrów filtru cyfrowego możliwe jest uzyskanie małych odchyłek charakterystyk między założonymi i aktualnymi....
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The use of fast molecular descriptors and artificial neural networks approach in organochlorine compounds electron ionization mass spectra classification
PublikacjaDeveloping 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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Intensification of catechin extraction from the bark of Syzygium cumini using ultrasonication: Optimization, characterization, degradation analysis and kinetic studies
PublikacjaCatechin is a prominent polyphenolic component that possesses various medicinal properties. Present work communicates the intensification and optimization of catechin extraction from the bark of Syzygium cumini tree using stirred reactor, soxhlet, ultrasonic bath, and ultrasonic horn technique. The optimization of several parameters such as type of solvent, solid to solvent ratio (1:100 w/v), speed of agitation (300 RPM), extraction...
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Multiplicative Long Short-Term Memory with Improved Mayfly Optimization for LULC Classification
PublikacjaLand Use and Land Cover (LULC) monitoring is crucial for global transformation, sustainable land control, urban planning, urban growth prediction, and the establishment of climate regulations for long-term development. Remote sensing images have become increasingly important in many environmental planning and land use surveys in recent times. LULC is evaluated in this research using the Sat 4, Sat 6, and Eurosat datasets. Various...
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Optimization of biocorrosion resistance and mechanical properties of PM Ti–XAl–2Fe–3Cu alloys by response surface methodology
PublikacjaIn the current study, the biocorrosion resistance and mechanical properties of the Ti–XAl–2Fe–3Cu (wt%) (X = 6, 4, 2 wt%) alloy produced by powder compact extrusion of blended elemental powders were optimized by using the response surface methodology in order to gain the best combination of processing parameters. To run the optimization process, central composite design with three equal levels of oxygen, hydrogen and aluminum was...
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Corrosion degradation monitoring of ship stiffened plates using guided wave phase velocity and constrained convex optimization method
PublikacjaThe study presents an experimental investigation on the corrosion degradation level assessment using nondestructive wave-based methods. The degradation level of ship structural elements has been assessed in two different ways. The first one is based on the spectral decomposition and zero-crossing incorporated reconstruction of the dispersion curve approach of the antisymmetric Lamb wave mode and the best matching of the theoretical...
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Determination of Odour Interactions in Gaseous Mixtures Using Electronic Nose Methods with Artificial Neural Networks
PublikacjaThis paper presents application of an electronic nose prototype comprised of eight sensors, five TGS-type sensors, two electrochemical sensors and one PID-type sensor, to identify odour interaction phenomenon in two-, three-, four- and five-component odorous mixtures. Typical chemical compounds, such as toluene, acetone, triethylamine, α-pinene and n-butanol, present near municipal landfills and sewage treatment plants were subjected...
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W-dominance: Tradeoff-inspired dominance relation for preference-based evolutionary multi-objective optimization
PublikacjaThe paper presents a method of incorporating decision maker preferences into multi-objective meta-heuristics. It is based on tradeoffcoefficients and extends their applicability from bi-objective to multi-objective. The method assumes that a decision maker specifies a priori each objective’s importance as a weight interval. Based on this, w-dominance relation is introduced, which extends Pareto dominance. By replacing reference...
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Modeling, run-time optimization and execution of distributed workflow applications in the JEE-based BeesyCluster environment
PublikacjaArtykuł prezentuje kompletne rozwiązanie do modelowania naukowych i biznesowych scenariuszy. statycznego i dynamicznego wyboru usług z uwzględnieniem parametrów jakościowych oraz wykonanie scenariuszy w rzeczywistym środowisku. Scenariusz jest modelowany jako acykliczny graf skierowany, w którym węzły reprezentują zadania zaś krawędzie zależności pomiędzy zadaniami. Warstwa pośrednia BeesyCluster jest wykorzystana do umożliwienia...
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Vessel Scheduling Optimization Model Based on Variable Speed in a Seaport with One-Way Navigation Channel
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Selection of circuit geometry for miniaturized microwave components based on concurrent optimization of performance and layout area
PublikacjaThe 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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Feedline Alterations for Optimization-Based Design of Compact Super-Wideband MIMO Antennas in Parallel Configuration
PublikacjaThis letter presents a technique for size reduction of wideband multiple-input-multiple-output (MIMO) antennas. Our approach is a two-stage procedure. At the first stage, the antenna structure is modified to improve its impedance matching. This is achieved through incorporation of an n-section tapered feedline, followed by reoptimization of geometry parameters. Reducing the maximum in-band reflection well beyond the acceptance...
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Optymalizacja zasad koegzystencji sieci standardów Bluetooth i IEEE 802.11 = Optimization of Bluetooth and IEEE 802.11 networks co-existence
PublikacjaZ uwagi na rosnącą popularność standardów Bluetooth (BT) i IEEE 802.11b (Wi-Fi ) można się z nimi spotkać praktycznie wszędzie. Gwałtowny wzrost liczby urządzeń różnych technologii ma także swoje negatywne strony. Stosowanie coraz większej liczby urządzeń różnych systemów radiokomunikacyjnych powoduje wzrost poziomu zaburzeń elektromagnetycznych. W konsekwencji działanie różnych sieci bezprzewodowych pracujących w bliskim zasięgu...
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Multicriteria Optimization Approach to Design and Operation of District Heating Supply System over its Life Cycle
PublikacjaDistrict Heating (DH) systems are commonly supplied using local heat sources. Nowadays, modern insulation materials allow for effective and economically viable heat transportation over long distances (over 20 km). In the paper a method for optimized selection of design and operating parameters of long distance Heat Transportation System (HTS) is proposed. The method allows for evaluation of feasibility and effectivity of heat transportation...
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Multi-response optimization on the effect of wet and eco-friendly cryogenic turning of D2 steel using Taguchi-based grey relational analysis
PublikacjaMaterial removal processes, including turning and milling, are still commonly used operations for manufacturing most of mechanical components in modern industry. Apart from the cutting parameters, the cooling method has the great impact on the technological efects and, above all, on the environmental friendliness of production. In this study, multi-response optimization on the efect of wet and cryogenic machining is performed during...
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Towards Designing an Innovative Industrial Fan: Developing Regression and Neural Models Based on Remote Mass Measurements
PublikacjaThis article presents the process of the construction and testing a remote, fully autonomous system for measuring the operational parameters of fans. The measurement results obtained made it possible to create and verify mathematical models using linear regression and neural networks. The process was implemented as part of the first stage of an innovative project. The article presents detailed steps of constructing a system to...
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Application of the Optimization Methods to the Search of Marine Propulsion Shafting Global Equilibrium in Running Condition
PublikacjaFull film hydrodynamic lubrication of marine propulsion shafting journal bearings in running condition is discussed. Considerable computational difficulties in non-linear determining the quasi-static equilibrium of the shafting are highlighted. The approach using two optimization methods (the particle swarm method and the interior point method) in combination with the specially developed relaxation technique is proposed to overcome...
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Low-Cost Quasi-Global Optimization of Expensive Electromagnetic Simulation Models by Inverse Surrogates and Response Features
PublikacjaConceptual design of contemporary high-frequency structures is typically followed by a careful tuning of their parameters, predominantly the geometry ones. The process aims at improving the relevant performance figures, and may be quite expensive. The reason is that conventional design methods, e.g., based on analytical or equivalent network models, often only yield rough initial designs. This is especially the case for miniaturized...
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Predicting Performance of Lightweight Concrete with Granulated Expanded Glass and Ash Aggregate by Means of Using Artificial Neural Networks
PublikacjaLightweight concrete (LWC) is a group of cement composites of the defined physical, mechanical, and chemical performance. The methods of designing the composition of LWC with the assumed density and compressive strength are used most commonly. The purpose of using LWC is the reduction of the structure’s weight, as well as the reduction of thermal conductivity index. The highest possible strength, durability and low thermal conductivity...
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DIAGNOSIS OF MALIGNANT MELANOMA BY NEURAL NETWORK ENSEMBLE-BASED SYSTEM UTILISING HAND-CRAFTED SKIN LESION FEATURES
PublikacjaMalignant melanomas are the most deadly type of skin cancer but detected early have high chances for successful treatment. In the last twenty years, the interest of automated melanoma recognition detection and classification dynamically increased partially because of public datasets appearing with dermatoscopic images of skin lesions. Automated computer-aided skin cancer detection in dermatoscopic images is a very challenging task...
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Optimization of Data Assignment for Parallel Processing in a Hybrid Heterogeneous Environment Using Integer Linear Programming
PublikacjaIn the paper we investigate a practical approach to application of integer linear programming for optimization of data assignment to compute units in a multi-level heterogeneous environment with various compute devices, including CPUs, GPUs and Intel Xeon Phis. The model considers an application that processes a large number of data chunks in parallel on various compute units and takes into account computations, communication including...
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Recurrent Neural Network Based Adaptive Variable-Order Fractional PID Controller for Small Modular Reactor Thermal Power Control
PublikacjaThis paper presents the synthesis of an adaptive PID type controller in which the variable-order fractional operators are used. Due to the implementation difficulties of fractional order operators, both with a fixed and variable order, on digital control platforms caused by the requirement of infinite memory resources, the fractional operators that are part of the discussed controller were approximated by recurrent neural networks...
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GPU Power Capping for Energy-Performance Trade-Offs in Training of Deep Convolutional Neural Networks for Image Recognition
PublikacjaIn the paper we present performance-energy trade-off investigation of training Deep Convolutional Neural Networks for image recognition. Several representative and widely adopted network models, such as Alexnet, VGG-19, Inception V3, Inception V4, Resnet50 and Resnet152 were tested using systems with Nvidia Quadro RTX 6000 as well as Nvidia V100 GPUs. Using GPU power capping we found other than default configurations minimizing...
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Application of neural networks for description of pressure distribution in slide bearing.
PublikacjaBadano rozkład ciśnienia hydrodynamicznego w łożysku ślizgowym dla wybranych wariantów łożyska. Wykazano, że zastosowanie sieci neuronowych umożliwia opis rozkładu ciśnienia hydrodynamicznego z uwzględnieniem zmian geometrycznych (bezwymiarowa długość - L) i mechanicznych (mimośrodowość względem H) łożyska.
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Identification of slide bearing main parameters using neural networks.
PublikacjaWykazano, że sieci neuronowe jak najbardziej nadają się do identyfikacji głównych parametrów geometrycznych i ruchowych hydrodynamicznych łożysk ślizgowych.
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Estimation the rhythmic salience of sound with association rules and neural networks
PublikacjaW referacie przedstawiono eksperymenty mające na celu automatyczne wyszukiwanie wartości rytmicznych we frazie muzycznej. W tym celu wykorzystano metody data mining i sztuczne sieci neuronowe.
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Forecasting of currency exchange rates using artificial neural networks
PublikacjaW rozdziale tym autor przedstawił wyniki swoich badań nad wykorzystaniem sztucznych sieci neuronowych do prognozowania kursu walut (na przykładzie pary walutowej PLN-USD).Głównym celem badań było porównanie skuteczności przewidywania kursu złotówki w latach 1997 - 2005 przy pomocy różnych rodzajów sieci neuronowych.
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Application of Artificial Neural Networks in Investigations of Steam Turbine Cascades
PublikacjaZaprezentowano wyniki badań numerycznych zastosowania sieci neuronowych przy obliczeniach przepływów w palisadach turbin parowych. Na podstawie uzyskanych wyników wykazano, że sieci neuronowe mogą być używane do szacowania przestrzennego rozkładu parametrów przepływu, takich jak entalpia, entropia, ciśnienie czy prędkość czynnika w kanale przepływowym. Omówiono również zastosowania tego typu metod przy projektowaniu palisad, stopni...
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Automatic singing quality recognition employing artificial neural networks
PublikacjaCelem artykułu jest udowodnienie możliwości automatycznej oceny jakości technicznej głosów śpiewaczych. Pokrótce zaprezentowano w nim stworzoną bazę danych głosów śpiewaczych oraz zaimplementowane parametry. Przy pomocy sztucznych sieci neuronowych zaprojektowano system decyzyjny, który oceniono w pięciostopniowej skali jakość techniczną głosu. Przy pomocy metod statystycznych udowodniono, że wyniki generowane przez ten system...
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Prediction of antimicrobial activity of imidazole derivatives by artificial neural networks
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Using neural networks to examine trending keywords in Inventory Control
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Automatic Breath Analysis System Using Convolutional Neural Networks
PublikacjaDiseases related to the human respiratory system have always been a burden for the entire society. The situation has become particularly difficult now after the outbreak of the COVID-19 pandemic. Even now, however, it is common for people to consult their doctor too late, after the disease has developed. To protect patients from severe disease, it is recommended that any symptoms disturbing the respiratory system be detected as...
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Automatic Breath Analysis System Using Convolutional Neural Networks
PublikacjaDiseases related to the human respiratory system have always been a burden for the entire society. The situation has become particularly difficult now after the outbreak of the COVID-19 pandemic. Even now, however, it is not uncommon for people to consult their doctor too late, after the disease has developed. To protect patients from severe disease, it is recommended that any symptoms disturbing the respiratory system be detected...
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Deep Learning-Based LOS and NLOS Identification in Wireless Body Area Networks
PublikacjaIn this article, the usage of deep learning (DL) in ultra-wideband (UWB) Wireless Body Area Networks (WBANs) is presented. The developed approach, using channel impulse response, allows higher efficiency in identifying the direct visibility conditions between nodes in off-body communication with comparison to the methods described in the literature. The effectiveness of the proposed deep feedforward neural network was checked on...
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EM-Driven Size Reduction and Multi-Criterial Optimization of Broadband Circularly-Polarized Antennas Using Pareto Front Traversing and Design Extrapolation
PublikacjaMaintaining small size has become an important consideration in the design of contemporary antenna structures. In the case of broadband circularly polarized (CP) antennas, miniaturization is a challenging process due to the necessity of simultaneous handling of electrical and field properties (reflection, axial ratio, gain), as well as ensuring sufficient frequency range of operation, especially at the lower edge of the antenna...
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Improving the energy balance in wastewater treatment plants by optimization of aeration control and application of new technologies
PublikacjaThe methods to improve the energy balance of a wastewater treatment plant (WWTP) by optimization of aeration process control and application of innovative nitrogen removal technologies were overviewed in the study. The control of aeration based on the ABAC (Ammonia-Based Aeration Control) system allows not only for significant savings in electricity consumption, but it can also increase the efficiency of the denitrification process....