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Search results for: benchmark
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Relative product diversification in the course of economic development: import-export analysis.
PublicationThis paper contributes to trade diversification literature by comparing changes in relative (i.e. assessed in comparison with world patterns) heterogeneity of import and export structures in the process of economic development. In particular, by focusing on the diversification of imports, we add a missing piece to already analysed export trends. We use highly disaggregated trade statistics (4963 product lines) for 163 countries...
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Gender approaches to evolutionary multi-objective optimization using pre-selection of criteria
PublicationA novel idea to perform evolutionary computations (ECs) for solving highly dimensional multi-objective optimization (MOO) problems is proposed. Following the general idea of evolution, it is proposed that information about gender is used to distinguish between various groups of objectives and identify the (aggregate) nature of optimality of individuals (solutions). This identification is drawn out of the fitness of individuals...
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Characterizing the Scalability of Graph Convolutional Networks on Intel® PIUMA
PublicationLarge-scale Graph Convolutional Network (GCN) inference on traditional CPU/GPU systems is challenging due to a large memory footprint, sparse computational patterns, and irregular memory accesses with poor locality. Intel’s Programmable Integrated Unffied Memory Architecture (PIUMA) is designed to address these challenges for graph analytics. In this paper, a detailed characterization of GCNs is presented using the Open-Graph Benchmark...
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Expedited optimization of antenna input characteristics with adaptive Broyden updates
PublicationSimulation-driven adjustment of geometry and/or material parameters is a necessary step in the design of contemporary antenna structures. Due to their topological complexity, other means, such as supervised parameter sweeping, does not usually lead to satisfactory results. On the other hand, rigorous numerical optimization is computationally expensive due to a high cost of underlying full-wave electromagnetic (EM) analyses, otherwise...
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Power System Dynamics. Stability and Control. 3rd edition
PublicationComprehensive, state-of-the-art review of information on the electric power system dynamics and stability. It places the emphasis first on understanding the underlying physical principles before proceeding to more complex models and algorithms. The book explores the influence of classical sources of energy, wind farms and virtual power plants, power plants inertia and control strategy on power system stability. The book cover...
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W-dominance: Tradeoff-inspired dominance relation for preference-based evolutionary multi-objective optimization
PublicationThe 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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A new multi-process collaborative architecture for time series classification
PublicationTime series classification (TSC) is the problem of categorizing time series data by using machine learning techniques. Its applications vary from cybersecurity and health care to remote sensing and human activity recognition. In this paper, we propose a novel multi-process collaborative architecture for TSC. The propositioned method amalgamates multi-head convolutional neural networks and capsule mechanism. In addition to the discovery...
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Modelling of FloodWave Propagation with Wet-dry Front by One-dimensional Diffusive Wave Equation
PublicationA full dynamic model in the form of the shallow water equations (SWE) is often useful for reproducing the unsteady flow in open channels, as well as over a floodplain. However, most of the numerical algorithms applied to the solution of the SWE fail when flood wave propagation over an initially dry area is simulated. The main problems are related to the very small or negative values of water depths occurring in the vicinity of...
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Dynamic model of nuclear power plant turbine
PublicationThe paper presents the dynamic multivariable model of Nuclear Power Plant steam turbine. Nature of the processes occurring in a steam turbine causes a task of modeling it very difficult, especially when this model is intended to be used for on-line optimal process control (model based) over wide range of operating conditions caused by changing power demand. Particular property of developed model is that it enables calculations...
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Particle shape dependence in 2D granular media
PublicationParticle shape is a key to the space-filling and strength properties of granular matter. We consider a shape parameter eta describing the degree of distortion from a perfectly spherical shape. Encompassing most specific shape characteristics such as elongation, angularity and non-convexity, eta is a low-order but generic parameter that we used in a numerical benchmark test for a systematic investigation of shape dependence in sheared...
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A new anisotropic bending model for nonlinear shells: Comparison with existing models and isogeometric finite element implementation
PublicationA new nonlinear hyperelastic bending model for shells formulated directly in surface form is presented, and compared to four existing prominent bending models. Through an essential set of elementary nonlinear bending test cases, the membrane and bending stresses of each model are examined analytically. Only the proposed bending model passes all the test cases, while the other bending models either fail or only pass the test cases for...
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Tworzenie miejskości po 1990r., Geneza niemieckiej urbanistyki współczesnych założeń mieszkaniowych
PublicationArtykuł jest przyczyną do przypomnienia genezy współczesnej formy niemieckich miejskich struktur mieszkaniowych w kontekście zmian rozumienia ich wymiaru miejskości. Niemiecka myśl urbanistyczna łączy w sobie dwie wyraziste tradycje dwudziestego wieku - Gründerzeit i KlassischeModerne. Pozostaje jednak silnie otwarta na innowację generowaną nie tylko dzięki postępowi technicznemu, ale przede wszystkim poprzez planowanie interdyscyplinarne...
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Analiza skuteczności wybranych strategii kontrariańskich na warszawskiej GPW w latach 2014–2018
PublicationCapital multiplication is the main goal of investors and for many years they have been looking for methods and strategies that would enable them to achieve it to the greatest possible extent. Due to the fact that the expectations and characteristics of investors, including those concerning the investment period, are diverse, multiple strategies have emerged. One of such strategies, mainly long-term in nature, is the so-called...
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Computationally-efficient design optimisation of antennas by accelerated gradient search with sensitivity and design change monitoring
PublicationElectromagnetic (EM) simulation tools are of primary importance in the design of contemporary antennas. The necessity of accurate performance evaluation of complex structures is a reason why the final tuning of antenna dimensions, aimed at improvement of electrical and field characteristics, needs to be based on EM analysis. Design automation is highly desirable and can be achieved by coupling EM solvers with numerical optimisation...
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How can HSR promote inter-city collaborative innovation across regional borders?
PublicationMany studies have shown that high-speed rail (HSR) can reshape the spatial pattern of economic geography. However, there needs to be more logical argumentation and rigorous empirical design on the paths and mechanisms involved. This paper considers the impact of the border effect on HSR links and innovation clusters from the perspective of inter-regional collaborative innovation. It provides a logical and compact theoretical...
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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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Cost-Efficient Multi-Objective Design of Miniaturized Microwave Circuits Using Machine Learning and Artificial Neural Network
PublicationDesigning microwave components involves managing multiple objectives such as center frequencies, impedance matching, and size reduction for miniaturized structures. Traditional multi-objective optimization (MO) approaches heavily rely on computationally expensive population-based methods, especially when exe-cuted with full-wave electromagnetic (EM) analysis to guarantee reliability. This paper introduces a novel and cost-effective...
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Creating new voices using normalizing flows
PublicationCreating realistic and natural-sounding synthetic speech remains a big challenge for voice identities unseen during training. As there is growing interest in synthesizing voices of new speakers, here we investigate the ability of normalizing flows in text-to-speech (TTS) and voice conversion (VC) modes to extrapolate from speakers observed during training to create unseen speaker identities. Firstly, we create an approach for TTS...
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Trust and Distrust in e-Democracy
PublicationIn the digital government research literature, the concept of trust is typically used as a precondition for the adoption of digital technology in the public sector or an outcome of a roadmap leading up to such adoption. The concept plays a central role in many decisions linked to the planning, adoption and management of the public sector technology. In contrast, the concept of distrust is almost neglected in such literature but,...
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Client-side versus server-side geographic data processing performance comparison: Data and code
PublicationThe data and code presented in this article are related to the research article entitled “Analysis of Server-side and Client-side Web-GIS data processing methods on the example of JTS and JSTS using open data from OSM and Geoportal” (Kulawiak et al., 2019). The provided 12 datasets include multi-point and multi-polygon data of different scales and volumes, representing real-world geographic features. The datasets cover the area...
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Fast EM-Driven Parameter Tuning of Microwave Circuits with Sparse Sensitivity Updates via Principal Directions
PublicationNumerical optimization has become more important than ever in the design of microwave components and systems, primarily as a consequence of increasing performance demands and growing complexity of the circuits. As the parameter tuning is more and more often executed using full-wave electromagnetic (EM) models, the CPU cost of the overall process tends to be excessive even for local optimization. Some ways of alleviating these issues...
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A Surrogate-Assisted Measurement Correction Method for Accurate and Low-Cost Monitoring of Particulate Matter Pollutants
PublicationAir pollution involves multiple health and economic challenges. Its accurate and low-cost monitoring is important for developing services dedicated to reduce the exposure of living beings to the pollution. Particulate matter (PM) measurement sensors belong to the key components that support operation of these systems. In this work, a modular, mobile Internet of Things sensor for PM measurements has been proposed. Due to a limited...
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Seismic damage diagnosis in adjacent steel and RC MRFs considering pounding effects through improved wavelet-based damage-sensitive feature
PublicationThis paper aims to propose complex Morlet (cmorfb-fc) wavelet-based refined damage-sensitive feature (rDSF) as a new and more precise damage indicator to diagnose seismic damages in adjacent steel and Reinforced Concrete (RC) Moment Resisting Frames (MRFs) assuming pounding conditions using acceleration responses. The considered structures include 6- and 9-story steel and 4- and 8-story RC benchmark MRFs that are assumed to have...
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Deep eutectic solvents – Ideal solution for clean air or hidden danger?
PublicationThe industrial sector is one of the fastest-growing sources of greenhouse gases, due to its excessive energy consumption to meet the rapidly growing demand for energy-intensive products. The use of deep eutectic solvents (DESs) has been studied extensively in order to cope with these harmful gases, but their usage can be an issue in respect to ecological reasons. Do deep eutectic solvents harm the atmosphere? Yes, these solvents...
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USING ARTIFICIAL NEURAL NETWORKS FOR PREDICTING SHIP FUEL CONSUMPTION
PublicationIn marine vessel operations, fuel costs are major operating costs which affect the overall profitability of the maritime transport industry. The effective enhancement of using ship fuel will increase ship operation efficiency. Since ship fuel consumption depends on different factors, such as weather, cruising condition, cargo load, and engine condition, it is difficult to assess the fuel consumption pattern for various types...
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Reduced-cost electromagnetic-driven optimisation of antenna structures by means of trust-region gradient-search with sparse Jacobian updates
PublicationNumerical optimisation plays more and more important role in the antenna design. Because of lack of design-ready theoretical models, electromagnetic (EM)-simulation-driven adjustment of geometry parameters is a necessary step of the design process. At the same time, traditional parameter sweeping cannot handle complex topologies and large number of design variables. On the other hand, high computational cost of the conventional...
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Improving Accuracy of Contactless Respiratory Rate Estimation by Enhancing Thermal Sequences with Deep Neural Networks
PublicationEstimation of vital signs using image processing techniques have already been proved to have a potential for supporting remote medical diagnostics and replacing traditional measurements that usually require special hardware and electrodes placed on a body. In this paper, we further extend studies on contactless Respiratory Rate (RR) estimation from extremely low resolution thermal imagery by enhancing acquired sequences using Deep...
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Identification of Parameters Influencing the Accuracy of the Solution of the Nonlinear Muskingum Equation
PublicationTwo nonlinear versions of the Muskingum equation are considered. The difference between both equations relates to the exponent parameter. In the first version, commonly used in hydrology, this parameter is considered as free, while in the second version, it takes a value resulting from the kinematic wave theory. Consequently, the first version of the equation is dimensionally inconsistent, whereas the proposed second one is consistent. It...
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Selected Technical Issues of Deep Neural Networks for Image Classification Purposes
PublicationIn recent years, deep learning and especially Deep Neural Networks (DNN) have obtained amazing performance on a variety of problems, in particular in classification or pattern recognition. Among many kinds of DNNs, the Convolutional Neural Networks (CNN) are most commonly used. However, due to their complexity, there are many problems related but not limited to optimizing network parameters, avoiding overfitting and ensuring good...
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Trust and Distrust in e-Democracy
PublicationIn the digital government research literature, the concept of trust is typically used as a precondition for the adoption of digital technology in the public sector or an outcome of a roadmap leading up to such adoption. The concept plays a central role in many decisions linked to the planning, adoption and management of the public sector technology. In contrast, the concept of...
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Filter-Hilbert Method for Automatic Correction of Non-Anechoic Antenna Measurements with Embedded Self-Calibration Mechanism
PublicationOne of the most important steps in the process of antenna development involves measurements of its prototype. Far-field performance of radiators is normally characterized in strictly controlled environments such as anechoic chambers which can ensure certification-grade accuracy. Unfortunately, they are also characterized by high construction costs which might not be justified for low-budget research and/or teaching-related activities....
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Relationship between wages, labour productivity and unemployment rate in new EU member countries
PublicationThe main aim of this article is to find out the extent to which relative labour productivity and relative unemployment rate changes determine relative wage changes. We use average annual macro-data for the period 2002-2013 for Poland and other 5 new EU members: Estonia, Hungary, Slovak, Czech Republic and Slovenia. Using Poland as benchmark, rst we examine the correlation between wage, productivity and unemployment rate changes...
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Nieliniowa statyka 6-parametrowych powłok sprężysto plastycznych. Efektywne obliczenia MES
PublicationGłównym zagadnieniem omawianym w monografii jest sformułowanie sprężysto-plastycznego prawa konstytutywnego w nieliniowej 6-parametrowej teorii powłok. Wyróżnikiem tej teorii jest występujący w niej w naturalny sposób tzw. stopień 6 swobody, czyli owinięcie (drilling rotation). Podstawowe założenie pracy to przyjęcie płaskiego stanu naprężenia uogólnionego na ośrodek typu Cosseratów. Takie podejście stanowi oryginalny aspekt opracowania....
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Fully Automated AI-powered Contactless Cough Detection based on Pixel Value Dynamics Occurring within Facial Regions
PublicationIncreased interest in non-contact evaluation of the health state has led to higher expectations for delivering automated and reliable solutions that can be conveniently used during daily activities. Although some solutions for cough detection exist, they suffer from a series of limitations. Some of them rely on gesture or body pose recognition, which might not be possible in cases of occlusions, closer camera distances or impediments...
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Neural Architecture Search for Skin Lesion Classification
PublicationDeep neural networks have achieved great success in many domains. However, successful deployment of such systems is determined by proper manual selection of the neural architecture. This is a tedious and time-consuming process that requires expert knowledge. Different tasks need very different architectures to obtain satisfactory results. The group of methods called the neural architecture search (NAS) helps to find effective architecture...
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Evaluation of ChatGPT Applicability to Learning Quantum Physics
PublicationChatGPT is an application that uses a large language model. Its purpose is to generate answers to various questions as well as provide information, help solve problems and participate in conversations on a wide range of topics. This application is also widely used by students for the purposes of learning or cheating (e.g., writing essays or programming codes). Therefore, in this contribution, we evaluate the ability of ChatGPT...
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Non-ergodic fragmentation upon collision-induced activation of cysteine–water cluster cations
PublicationCysteine–water cluster cations Cys(H2O)3,6 + and Cys(H2O)3,6H+ are assembled in He droplets and probed by tandem mass spectrometry with collision-induced activation. Benchmark experimental data for this biologically important system are complemented with theory to elucidate the details of the collisioninduced activation process. Experimental energy thresholds for successive release of water are compared to water dissociation energies...
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Reliable computationally-efficient behavioral modeling of microwave passives using deep learning surrogates in confined domains
PublicationThe importance of surrogate modeling techniques has been steadily growing over the recent years in high-frequency electronics, including microwave engineering. Fast metamodels are employed to speedup design processes, especially those conducted at the level of full-wave electromagnetic (EM) simulations. The surrogates enable massive system evaluations at nearly EM accuracy and negligible costs, which is invaluable in parameter...
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Deep learning-based waste detection in natural and urban environments
PublicationWaste pollution is one of the most significant environmental issues in the modern world. The importance of recycling is well known, both for economic and ecological reasons, and the industry demands high efficiency. Current studies towards automatic waste detection are hardly comparable due to the lack of benchmarks and widely accepted standards regarding the used metrics and data. Those problems are addressed in this article by...
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Reduction of exceeding the guaranteed service time for external trucks at the DCT Gdańsk container terminal using a six sigma framework
PublicationPurpose The purpose of this research was to investigate ways to reduce the average amount of exceeded guaranteed service time for external trucks at Deepwater Container Terminal Gdańsk Sp z o.o. (DCT Gdańsk) via dosing the gate activities, in particular IN-Gate entry process of trucks carrying import/export/transit containers. Design/methodology/approach A Six Sigma methodology with the DMAIC methods along with the SIPOC chart,...
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Constrained multi-objective optimization of compact microwave circuits by design triangulation and pareto front interpolation
PublicationDevelopment of microwave components is an inherently multi-objective task. This is especially pertinent to the design closure stage, i.e., final adjustment of geometry and/or material parameters carried out to improve the electrical performance of the system. The design goals are often conflicting so that the improvement of one normally leads to a degradation of others. Compact microwave passives constitute a representative case:...
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Reduced-Cost Design Optimization of High-Frequency Structures Using Adaptive Jacobian Updates
PublicationElectromagnetic (EM) analysis is the primary tool utilized in the design of high-frequency structures. In vast majority of cases, simpler models (e.g., equivalent networks or analytical ones) are either not available or lack accuracy: they can only be used to yield initial designs that need to be further tuned. Consequently, EM-driven adjustment of geometry and/or material parameters of microwave and antenna components is a necessary...
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Machine-Learning-Based Global Optimization of Microwave Passives with Variable-Fidelity EM Models and Response Features
PublicationMaximizing microwave passive component performance demands precise parameter tuning, particularly as modern circuits grow increasingly intricate. Yet, achieving this often requires a comprehensive approach due to their complex geometries and miniaturized structures. However, the computational burden of optimizing these components via full-wave electromagnetic (EM) simulations is substantial. EM analysis remains crucial for circuit...
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Screening stability, thermochemistry, and chemical kinetics of 3-hydroxybutanoic acid as a bifunctional biodiesel additive
PublicationThe thermo-kinetic aspects of 3-hydroxybutyric acid (3-HBA) pyrolysis in the gas phase were investigated using density functional theory (DFT), specifically the M06-2X theoretical level in conjunction with the cc-pVTZ basis set. The obtained data were compared with benchmark CBS-QB3 results. The degradation mechanism was divided into 16 pathways, comprising 6 complex fissions and 10 barrierless reactions. Energy profiles were calculated...
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Bi-GRU-APSO: Bi-Directional Gated Recurrent Unit with Adaptive Particle Swarm Optimization Algorithm for Sales Forecasting in Multi-Channel Retail
PublicationIn the present scenario, retail sales forecasting has a great significance in E-commerce companies. The precise retail sales forecasting enhances the business decision making, storage management, and product sales. Inaccurate retail sales forecasting can decrease customer satisfaction, inventory shortages, product backlog, and unsatisfied customer demands. In order to obtain a better retail sales forecasting, deep learning models...
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The role of microbial coagulants on the physicochemical, proteolysis, microstructure and sensory properties of low-fat Edam cheese manufactured from ultrafiltered buffalo milk
PublicationThis work investigates the influence of using microbial coagulants, including Rhizomucor miehei (MCR) protease and Cryphonectria parasitica (MCC) protease, on the quality characteristics of low-fat Edam cheese made from ultrafiltered buffalo milk (LFUE). Concurrently, a benchmark with calf rennet (CR) has been also performed. Throughout a 90-day ripening period, the cheeses were assessed for their physicochemical features, proteolysis,...
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Melanoma skin cancer detection using mask-RCNN with modified GRU model
PublicationIntroduction: Melanoma Skin Cancer (MSC) is a type of cancer in the human body; therefore, early disease diagnosis is essential for reducing the mortality rate. However, dermoscopic image analysis poses challenges due to factors such as color illumination, light reflections, and the varying sizes and shapes of lesions. To overcome these challenges, an automated framework is proposed in this manuscript. Methods: Initially, dermoscopic...
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Low-Cost Yield-Driven Design of Antenna Structures Using Response-Variability Essential Directions and Parameter Space Reduction
PublicationQuantifying the effects of fabrication tolerances and uncertainties of other types is fundamental to improve antenna design immunity to limited accuracy of manufacturing procedures and technological spread of material parameters. This is of paramount importance especially for antenna design in the industrial context. Degradation of electrical and field properties due to geometry parameter deviations often manifests itself as, e.g.,...
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Low-Cost and Highly-Accurate Behavioral Modeling of Antenna Structures by Means of Knowledge-Based Domain-Constrained Deep Learning Surrogates
PublicationThe awareness and practical benefits of behavioral modeling methods have been steadily growing in the antenna engineering community over the last decade or so. Undoubtedly, the most important advantage thereof is a possibility of a dramatic reduction of computational expenses associated with computer-aided design procedures, especially those relying on full-wave electromagnetic (EM) simulations. In particular, the employment of...
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Real-time simulation in non real-time environment
PublicationSimulation in real-time is a very useful tool because of didactical and practical benefits. Very important benefit of real-time simulation is a fact that operator’s decision can be taken into account in the same time scale as the real system would work. This enables construction of simulators, and opportunity to test control algorithms in Hardware in The Loop scheme using target industrial equipment. Professional real-time environments...