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Wyniki wyszukiwania dla: algorithms
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Accelerated multi-objective design of miniaturized microwave components by means of nested kriging surrogates
PublikacjaDesign of microwave components is an inherently multiobjective task. Often, the objectives are at least partially conflicting and the designer has to work out a suitable compromise. In practice, generating the best possible trade‐off designs requires multiobjective optimization, which is a computationally demanding task. If the structure of interest is evaluated through full‐wave electromagnetic (EM) analysis, the employment of...
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Bibliometric analysis of artificial intelligence in wastewater treatment: Current status, research progress, and future prospects
PublikacjaWastewater treatment is an important topic for improving water quality and environmental protection, and artificial intelligence has become a powerful tool for wastewater treatment. This work provides research progress and a literature review of artificial intelligence applied to wastewater treatment based on the visualization of bibliometric tools. A total of 3460 publications from 2000 to 2023 were obtained from the Web of Science...
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Modelling of wastewater treatment plant for monitoring and control purposes by state - space wavelet networks
PublikacjaMost of industrial processes are nonlinear, not stationary, and dynamical with at least few different time scales in their internal dynamics and hardly measured states. A biological wastewater treatment plant falls into this category. The paper considers modelling such processes for monitorning and control purposes by using State - Space Wavelet Neural Networks (SSWN). The modelling method is illustrated based on bioreactors of...
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Efficient Simulation-Based Global Antenna Optimization Using Characteristic Point Method and Nature-Inspired Metaheuristics
PublikacjaAntenna structures are designed nowadays to fulfil rigorous demands, including multi-band operation, where the center frequencies need to be precisely allocated at the assumed targets while improving other features, such as impedance matching. Achieving this requires simultaneous optimization of antenna geometry parameters. When considering multimodal problems or if a reasonable initial design is not at hand, one needs to rely...
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An optimized system for sensor ontology meta-matching using swarm intelligent algorithm
PublikacjaIt is beneficial to annotate sensor data with distinct sensor ontologies in order to facilitate interoperability among different sensor systems. However, for this interoperability to be possible, comparable sensor ontologies are required since it is essential to make meaningful links between relevant sensor data. Swarm Intelligent Algorithms (SIAs), namely the Beetle Swarm Optimisation Algorithm (BSO), present a possible answer...
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Condition-Based Monitoring of DC Motors Performed with Autoencoders
PublikacjaThis paper describes a condition-based monitoring system estimating DC motor degradation with the use of an autoencoder. Two methods of training the autoencoder are evaluated, namely backpropagation and extreme learning machines. The root mean square (RMS) error in the reconstruction of successive fragments of the measured DC motor angular-frequency signal, which is fed to the input of autoencoder, is used to determine the health...
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Blockchain based Secure Data Exchange between Cloud Networks and Smart Hand-held Devices for use in Smart Cities
PublikacjaIn 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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Improved Design Closure of Compact Microwave Circuits by Means of Performance Requirement Adaptation
PublikacjaNumerical optimization procedures have been widely used in the design of microwave components and systems. Most often, optimization algorithms are applied at the later stages of the design process to tune the geometry and/or material parameter values. To ensure sufficient accuracy, parameter adjustment is realized at the level of full-wave electromagnetic (EM) analysis, which creates perhaps the most important bottleneck due to...
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Evaluation of aspiration problems in L2 English pronunciation employing machine learning
PublikacjaThe approach proposed in this study includes methods specifically dedicated to the detection of allophonic variation in English. This study aims to find an efficient method for automatic evaluation of aspiration in the case of Polish second-language (L2) English speakers’ pronunciation when whole words are analyzed instead of particular allophones extracted from words. Sample words including aspirated and unaspirated allophones...
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Human Feedback and Knowledge Discovery: Towards Cognitive Systems Optimization
PublikacjaCurrent computer vision systems, especially those using machine learning techniques are data-hungry and frequently only perform well when dealing with patterns they have seen before. As an alternative, cognitive systems have become a focus of attention for applications that involve complex visual scenes, and in which conditions may vary. In theory, cognitive applications uses current machine learning algorithms, such as deep learning,...
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Low-Cost Unattended Design of Miniaturized 4 × 4 Butler Matrices with Nonstandard Phase Differences
PublikacjaDesign of Butler matrices dedicated to Internet of Things and 5th generation (5G) mobile systems—where small size and high performance are of primary concern—is a challenging task that often exceeds capabilities of conventional techniques. Lack of appropriate, unified design approaches is a serious bottleneck for the development of Butler structures for contemporary applications. In this work, a low-cost bottom-up procedure for...
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Fast Design Closure of Compact Microwave Components by Means of Feature-Based Metamodels
PublikacjaPrecise tuning of geometry parameters is an important consideration in the design of modern microwave passive components. It is mandatory due to limitations of theoretical design methods unable to quantify certain phenomena that are important for the operation and performance of the devices (e.g., strong cross-coupling effects in miniaturized layouts). Consequently, the initial designs obtained using analytical or equivalent network...
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Detection of anomalies in bee colony using transitioning state and contrastive autoencoders
PublikacjaHoneybees plays vital role for the environmental sustainability and overall agricultural economy. Assisting bee colonies within their proper functioning brings the attention of researchers around the world. Electronics systems and machine learning algorithms are being developed for classifying specific undesirable bee behaviors in order to alert about upcoming substantial losses. However, classifiers could be impaired when used...
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The Proposal to “Snapshot” Raim Method for Gnss Vessel Receivers Working in Poor Space Segment Geometry
PublikacjaNowadays, we can observe an increase in research on the use of small unmanned autonomous vessel (SUAV) to patrol and guiding critical areas including harbours. The proposal to “snapshot” RAIM (Receiver Autonomous Integrity Monitoring) method for GNSS receivers mounted on SUAV operating in poor space segment geometry is presented in the paper. Existing “snapshot” RAIM methods and algorithms which are used in practical applications...
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Application of autoencoder to traffic noise analysis
PublikacjaThe aim of an autoencoder neural network is to transform the input data into a lower-dimensional code and then to reconstruct the output from this code representation. Applications of autoencoders to classifying sound events in the road traffic have not been found in the literature. The presented research aims to determine whether such an unsupervised learning method may be used for deploying classification algorithms applied to...
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Machine Learning Techniques in Concrete Mix Design
PublikacjaConcrete mix design is a complex and multistage process in which we try to find the best composition of ingredients to create good performing concrete. In contemporary literature, as well as in state-of-the-art corporate practice, there are some methods of concrete mix design, from which the most popular are methods derived from The Three Equation Method. One of the most important features of concrete is compressive strength, which...
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Optimal selection of input features and an acompanying neural network structure for the classification purposes - skin lesions case study
PublikacjaMalignant melanomas are the most deadly type of skin cancers however detected early enough give a high chances for successful treatment. The last years saw the dynamic growth of interest of automatic computer-aided skin cancer diagnosis. Every month brings new research results on new approaches to this problem, new methods of preprocessing, new classifiers, new ideas to follow etc. In particular, the rapid development of dermatoscopy,...
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Economical methods for measuring road surface roughness
PublikacjaTwo low-cost methods of estimating the road surface condition are presented in the paper, the first one based on the use of accelerometers and the other on the analysis of images acquired from cameras installed in a vehicle. In the first method, miniature positioning and accelerometer sensors are used for evaluation of the road surface roughness. The device designed for installation in vehicles is composed of a GPS receiver and...
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Interictal high-frequency oscillations in focal human epilepsy
PublikacjaPURPOSE OF REVIEW: Localization of focal epileptic brain is critical for successful epilepsy surgery and focal brain stimulation. Despite significant progress, roughly half of all patients undergoing focal surgical resection, and most patients receiving focal electrical stimulation, are not seizure free. There is intense interest in high-frequency oscillations (HFOs) recorded with intracranial electroencephalography as potential...
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Performance evaluation of unified memory and dynamic parallelism for selected parallel CUDA applications
PublikacjaThe aim of this paper is to evaluate performance of new CUDA mechanisms—unified memory and dynamic parallelism for real parallel applications compared to standard CUDA API versions. In order to gain insight into performance of these mechanisms, we decided to implement three applications with control and data flow typical of SPMD, geometric SPMD and divide-and-conquer schemes, which were then used for tests and experiments. Specifically,...
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Analysis of IMS/NGN Call Processing Performance Using Phase-Type Distributions Based on Experimental Histograms
PublikacjaThe paper describes our further research done with the proposed analytical and simulation traffic models of the Next Generation Network (NGN), which is standardized for delivering multimedia services with strict quality and includes elements of the IP Multimedia Subsystem (IMS). The aim of our models of a single IMS/NGN domain is to evaluate two standardized call processing performance parameters, which appropriate values are very...
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Rating by detection: an artifact detection protocol for rating EEG quality with average event duration
PublikacjaQuantitative evaluation protocols are critical for the development of algorithms that remove artifacts from real EEG optimally. However, visually inspecting the real EEG to select the top-performing artifact removal pipeline is infeasible while hand-crafted EEG data allow assessing artifact removal configurations only in a simulated environment. This study proposes a novel, principled approach for quantitatively evaluating algorithmically...
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Speed estimation of a car at impact with a W-beam guardrail using numerical simulations and machine learning
PublikacjaThis paper aimed at developing a new method of estimating the impact speed of a passenger car at the moment of a crash into a W-beam road safety barrier. The determination of such a speed based on the accident outcomes is demanding, because often there is no access to full accident data. However, accurate determination of the impact speed is one of the key elements in the reconstruction of road accidents. A machine learning algorithm...
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Zintegrowane sterowanie systemami zaopatrzenia w wodę pitną
PublikacjaOptymalne ekonomicznie zaspokojenie w miastach bieżącego zapotrzebowania na wodę pitną tak, aby spełnione były wymagania jakości dostaw oraz jakości samej wody jest złożonym zadaniem. Zarówno aspekty aplikacyjne jak i teoretyczne tego problemu są przedmiotem intensywnych prac prowadzanych w sektorach naukowych i przemysłowych na całym świecie. Prace te finansowane są przez przemysł, komitety naukowe oraz Programy Ramowe Unii Europejskiej....
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Analiza i badania transformatora hybrydowego z przekształtnikiem AC/DC/AC współdziałającym z przełącznikiem zaczepów
PublikacjaRozprawa dotyczy badań nad układem transformatora hybrydowego, który oprócz możliwości regulacji ciągłej napięcia za pomocą przekształtnika energoelektronicznego, posiada układ regulacji skokowej w postaci przełącznika zaczepów. Badane urządzenie przeznaczone jest do stabilizacji napięcia w dystrybucyjnej sieci niskiego napięcia. Dzięki skoordynowanej pracy układów (ciągłego i skokowego) uzyskana zostaje tzw. Wielostrefowa Regulacja...
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Event driven MPC for networked control systems
PublikacjaBecause of variable delays and stochastic data packets loss networked control systems require suitable algorithms to ensure stability of the control system and guarantee desired control performance. This paper presents the idea of an event driven approach with MPC controller. In opposition to network compensation, where standard regulators are used, the presented solution integrates network with plant. A MPC based controller is...
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Multi-core processing system for real-time image processing in embedded computer vision applications
PublikacjaW artykule opisano architekturę wielordzeniowego programowalnego systemu do przetwarzania obrazów w czasie rzeczywistym. Dane obrazu są przetwarzane równocześnie przez wszystkie procesory. System umożliwia niskopoziomowe przetwarzanie obrazów,np. odejmowanie tła, wykrywanie obiektów ruchomych, transformacje geometryczne, indeksowanie wykrytych obiektów, ocena ich kształtu oraz podstawowa analiza trajektorii ruchu. Ang:This paper...
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Digital structures for high-speed signal processing
PublikacjaThe work covers several issues of realization of digital structures for pipelined processing of real and complex signals with the use of binary arithmetic and residue arithmetic. Basic rules of performing operations in residue arithmetic are presented along with selected residue number systems for processing of complex signals and computation of convolution. Subsequently, methods of conversion of numbers from weighted systems to...
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Pose-Configurable Generic Tracking of Elongated Objects
PublikacjaElongated objects have various shapes and can shift, rotate, change scale, and be rigid or deform by flexing, articulating, and vibrating, with examples as varied as a glass bottle, a robotic arm, a surgical suture, a finger pair, a tram, and a guitar string. This generally makes tracking of poses of elongated objects very challenging. We describe a unified, configurable framework for tracking the pose of elongated objects, which...
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Impact of optimization of ALS point cloud on classification
PublikacjaAirborne laser scanning (ALS) is one of the LIDAR technologies (Light Detection and Ranging). It provides information about the terrain in form of a point cloud. During measurement is acquired: spatial data (object’s coordinates X, Y, Z) and collateral data such as intensity of reflected signal. The obtained point cloud is typically applied for generating a digital terrain model (DTM) and a digital surface model (DSM). For DTM...
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Integrated monitoring, control and security of Critical Infrastructure Systems
PublikacjaModern societies have reached a point where everyday life relies heavily on desired operation of critical infrastructures, in spite of accidental failures and/or deliberate attacks. The issue of desired performance operation of CIS at high security level receives considerable attention worldwide. The pioneering generic methodologies and methods are presented in the paper project for designing systems capable of achieving these...
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Novel approach to modeling spectral-domain optical coherence tomography with Monte Carlo method
PublikacjaNumerical modeling Optical Coherence Tomography (OCT) systems is needed for optical setup optimization, development of new signal processing methods and assessment of impact of different physical phenomena inside the sample on OCT signal. The Monte Carlo method has been often used for modeling Optical Coherence Tomography, as it is a well established tool for simulating light propagation in scattering media. However, in this method...
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Comparative Analysis of Text Representation Methods Using Classification
PublikacjaIn our work, we review and empirically evaluate five different raw methods of text representation that allow automatic processing of Wikipedia articles. The main contribution of the article—evaluation of approaches to text representation for machine learning tasks—indicates that the text representation is fundamental for achieving good categorization results. The analysis of the representation methods creates a baseline that cannot...
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Visual Features for Endoscopic Bleeding Detection
PublikacjaAims: To define a set of high-level visual features of endoscopic bleeding and evaluate their capabilities for potential use in automatic bleeding detection. Study Design: Experimental study. Place and Duration of Study: Department of Computer Architecture, Faculty of Electronics, Telecommunications and Informatics, Gdansk University of Technology, between March 2014 and May 2014. Methodology: The features have...
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Error analysis of calculating average d-q current components using Regular Sampling and Park transformation in FOC drives
PublikacjaIn electric drives using voltage source inverters, motor currents contain ripple component resulting from pulse-width modulated (PWM) voltage. The frequency range of the ripples is much higher than the bandwidth of current control. Therefore the control is performed on the basis of a fundamental current component, i.e. average value with the averaging time being the PWM period. In majority of cases the average current is measured...
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Analysis of metals in air particles from Gdańsk and London with EDX/EDS detectors in electron microscope
PublikacjaElectron microscopy with energy dispersive X-ray spectrometry (EDX/EDS) is the example of non-destructive analytical method for surface elemental analysis, with a potential detection limit of 0.1-0.5 wt.% for most elements. A spatial resolution <10 nm can be achieved using this technique, which provides a basis for the generation of quantitative and qualitative elemental data for individual particles. In order to obtain quantitative...
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Development of advanced machine learning for prognostic analysis of drying parameters for banana slices using indirect solar dryer
PublikacjaIn this study, eXtreme Gradient Boosting (XGBoost) and Light Gradient Boosting (LightGBM) algorithms were used to model-predict the drying characteristics of banana slices with an indirect solar drier. The relationships between independent variables (temperature, moisture, product type, water flow rate, and mass of product) and dependent variables (energy consumption and size reduction) were established. For energy consumption,...
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Nonlinear material identification of heterogeneous isogeometric Kirchhoff–Love shells
PublikacjaThis work presents a Finite Element Model Updating inverse methodology for reconstructing heterogeneous materialdistributions based on an efficient isogeometric shell formulation. It uses nonlinear hyperelastic material models suitable fordescribing incompressible material behavior as well as initially curved shells. The material distribution is discretized by bilinearelements such that the nodal values...
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Know your safety indicator – A determination of merchant vessels Bow Crossing Range based on big data analytics
PublikacjaEven in the era of automatization maritime safety constantly needs improvements. Regardless of the presence of crew members on board, both manned and autonomous ships should follow clear guidelines (no matter as bridge procedures or algorithms). To date, many safety indicators, especially in collision avoidance have been proposed. One of such parameters commonly used in day-to-day navigation but usually omitted by researchers is...
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Low-Cost Automated Design of Compact Branch-Line Couplers
PublikacjaBranch-line couplers (BLCs) are important components of wireless communication systems. Conventional BLCs are often characterized by large footprints which make miniaturization an important prerequisite for their application in modern devices. State-of-the-art approaches to design of compact BLCs are largely based on the use of high-permittivity substrates and multi-layer topologies. Alternative methods involve replacement of transmission-line...
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Platelet RNA Sequencing Data Through the Lens of Machine Learning
PublikacjaLiquid biopsies offer minimally invasive diagnosis and monitoring of cancer disease. This biosource is often analyzed using sequencing, which generates highly complex data that can be used using machine learning tools. Nevertheless, validating the clinical applications of such methods is challenging. It requires: (a) using data from many patients; (b) verifying potential bias concerning sample collection; and (c) adding interpretability...
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Chained machine learning model for predicting load capacity and ductility of steel fiber–reinforced concrete beams
PublikacjaOne of the main issues associated with steel fiber–reinforced concrete (SFRC) beams is the ability to anticipate their flexural response. With a comprehensive grid search, several stacked models (i.e., chained, parallel) consisting of various machine learning (ML) algorithms and artificial neural networks (ANNs) were developed to predict the flexural response of SFRC beams. The flexural performance of SFRC beams under bending was...
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Detection of circulating tumor cells by means of machine learning using Smart-Seq2 sequencing
PublikacjaCirculating tumor cells (CTCs) are tumor cells that separate from the solid tumor and enter the bloodstream, which can cause metastasis. Detection and enumeration of CTCs show promising potential as a predictor for prognosis in cancer patients. Furthermore, single-cells sequencing is a technique that provides genetic information from individual cells and allows to classify them precisely and reliably. Sequencing data typically...
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Graph Neural Networks and Structural Information on Ionic Liquids: A Cheminformatics Study on Molecular Physicochemical Property Prediction
PublikacjaIonic liquids (ILs) provide a promising solution in many industrial applications, such as solvents, absorbents, electrolytes, catalysts, lubricants, and many others. However, due to the enormous variety of their structures, uncovering or designing those with optimal attributes requires expensive and exhaustive simulations and experiments. For these reasons, searching for an efficient theoretical tool for finding the relationship...
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Optimum number of actuators to minimize the cross-sectional area of prestressable cable and truss structures
PublikacjaThis paper describes a new computational method for determining the optimum number of actuators to design the optimal and economic cross-sectional area of pin-jointed assemblies based on the conventional force method. The most active members are selected to be prestressed to redistribute stress in the whole structure, resulting in regulating the internal force of bars that face high stress. Reducing stress in critical members allows...
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AI-powered Digital Transformation: Tools, Benefits and Challenges for Marketers – Case Study of LPP
PublikacjaThe article aims to show the role (benefits and challenges) of AI-powered digital marketing tools for marketers in the age of digital transformation. The considerations were related to the Polish market and a case study of LPP, a Polish clothing retailer. The starting point for this study was the analysis of the literature on the concept of artificial intelligence (AI) with reference to digital marketing. In the next steps, the...
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Dynamic Route Discovery Using Modified Grasshopper Optimization Algorithm in Wireless Ad-Hoc Visible Light Communication Network
PublikacjaIn recent times, visible light communication is an emerging technology that supports high speed data communication for wireless communication systems. However, the performance of the visible light communication system is impaired by inter symbol interference, the time dispersive nature of the channel, and nonlinear features of the light emitting diode that significantly reduces the bit error rate performance. To address these problems,...
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Expedited Trust-Region-Based Design Closure of Antennas by Variable-Resolution EM Simulations
PublikacjaThe observed growth in the complexity of modern antenna topologies fostered a widespread employment of numerical optimization methods as the primary tools for final adjustment of the system parameters. This is mainly caused by insufficiency of traditional design closure approaches, largely based on parameter sweeping. Reliable evaluation of complex antenna structures requires full-wave electromagnetic (EM) analysis. Yet, EM-driven...
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Rigorous numerics for critical orbits in the quadratic family
PublikacjaWe develop algorithms and techniques to compute rigorous bounds for finite pieces of orbits of the critical points, for intervals of parameter values, in the quadratic family of one-dimensional maps fa(x)=a−x2. We illustrate the effectiveness of our approach by constructing a dynamically defined partition P of the parameter interval Ω=[1.4,2] into almost 4 million subintervals, for each of which we compute to high precision the...
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How ethics combine with big data: a bibliometric analysis
PublikacjaThe term Big Data is becoming increasingly widespread throughout the world, and its use is no longer limited to the IT industry, quantitative scientific research, and entrepreneurship, but entered as well everyday media and conversations. The prevalence of Big Data is simply a result of its usefulness in searching, downloading, collecting and processing massive datasets. It is therefore not surprising that the number of scientific...