Search results for: automatic control
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Theory versus experiment for vacuum Rabi oscillations in lossy cavities. II. Direct test of uniqueness of vacuum
PublicationThe paper continues the analysis of vacuum Rabi oscillations we started in part I [Phys. Rev. A 79, 033836 (2009)]. Here we concentrate on experimental consequences for cavity QED of two different classes of representations of harmonic-oscillator Lie algebras. The zero-temperature master equation, derived in part I for irreducible representations of the algebra, is reformulated in a reducible representation that models electromagnetic...
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KernelHive: a new workflow-based framework for multilevel high performance computing using clusters and workstations with CPUs and GPUs
PublicationThe paper presents a new open-source framework called KernelHive for multilevel parallelization of computations among various clusters, cluster nodes, and finally, among both CPUs and GPUs for a particular application. An application is modeled as an acyclic directed graph with a possibility to run nodes in parallel and automatic expansion of nodes (called node unrolling) depending on the number of computation units available....
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THE RESEARCH ON EGNOS SYSTEM IN CONTEXT OF THE ABILITY TO DETERMINE THE SHIP’S HULL SPATIAL ORIENTATION
PublicationThe European Geostationary Navigation Overlay Service (EGNOS) thanks to geostationary satellites covers an area of whole Europe, including Baltic and North Sea. It allows to fix the coordinates of object position with typical absolute accuracy of 1,5 m. Previous research have shown that relative accuracy is usually higher than absolute one [Nowak A., 2010, Nowak A., 2011], so probably it could be possible to use EGNOS to determine...
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The Influence of Selecting Regions from Endoscopic Video Frames on The Efficiency of Large Bowel Disease Recognition Algorithms
PublicationThe article presents our research in the field of the automatic diagnosis of large intestine diseases on endoscopic video. It focuses on the methods of selecting regions of interest from endoscopic video frames for further analysis by specialized disease recognition algorithms. Four methods of selecting regions of interest have been discussed: a. trivial, b. with the deletion of characteristic, endoscope specific additions to the...
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Integration, Processing and Dissemination of LiDAR Data in a 3D Web-GIS
PublicationThe rapid increase in applications of Light Detection and Ranging (LiDAR) scanners, followed by the development of various methods that are dedicated for survey data processing, visualization, and dissemination constituted the need of new open standards for storage and online distribution of collected three-dimensional data. However, over a decade of research in the area has resulted in a number of incompatible solutions that offer...
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MRI-Derived Subcutaneous and Visceral Adipose Tissue Reference Values for Children Aged 6 to Under 18 Years
PublicationThe assessment of body composition in pediatric population is essential for proper nutritional support during hospitalization. However, currently available methods have limitations. This study aims to propose a novel approach for nutrition status assessment and introduce magnetic resonance imaging (MRI)-derived subcutaneous and visceral fat normative reference values. A total of 262 healthy subjects aged from 6 to 18 years underwent...
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Neural Approximators for Variable-Order Fractional Calculus Operators (VO-FC)
PublicationThe paper presents research on the approximation of variable-order fractional operators by recurrent neural networks. The research focuses on two basic variable-order fractional operators, i.e., integrator and differentiator. The study includes variations of the order of each fractional operator. The recurrent neural network architecture based on GRU (Gated Recurrent Unit) cells functioned as a neural approximation for selected...
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THE EFFECT OF LOG SORTING STRATEGY ON THE FORECASTED LUMBER VALUE AFTER SAWING PINE WOOD
PublicationThe optimal transformation path for the resource is determined by the quality of a log combined with its dimension. The commercial value of derived products is also closely connected with the size and extent of containing wood deficiencies. The results of studies with three diverse strategies for log sorting are presented in the paper. Resource assessment by a worker without extensive experience in sorting logs, the certified grading...
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3D MODELLING OF CYLINDRICAL-SHAPED OBJECTS FROM LIDAR DATA - AN ASSESSMENT BASED ON THEORETICAL MODELLING AND EXPERIMENTAL DATA
PublicationDespite the increasing availability of measured laser scanning data and their widespread use, there is still the problem of rapid and correct numerical interpretation of results. This is due to the large number of observations that carry similar information. Therefore, it is necessary to extract from the results only the essential features of the modelled objects. Usually, it is based on a process using filtration, followed by...
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GIS three-dimensional Modelling with geo-informatics techniques
PublicationThe integration issue of virtual models and geo-referenced database have a very broad spectrum of potential applications. Before the integration issue was on the cusp, it was quite problematic to combine three-dimensional models with the geo-referenced database. An integrated database contains a variety of data including such as object orientated data model and raster data. Within this paper, authors present an integration process...
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Clothes Detection and Classification Using Convolutional Neural Networks
PublicationIn this paper we describe development of a computer vision system for accurate detection and classification of clothes for e-commerce images. We present a set of experiments on well established architectures of convolutional neural networks, including Residual networks, SqueezeNet and Single Shot MultiBox Detector (SSD). The clothes detection network was trained and tested on DeepFashion dataset, which contains box annotations...
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Modeling of luminance distribution in CAVE-type virtual reality systems
PublicationAt present, one of the most advanced virtual reality systems are CAVE-type (Cave Automatic Virtual Environment) installations. Such systems are usually consisted of four, five or six projection screens and in case of six screens arranged in form of a cube. Providing the user with a high level of immersion feeling in such systems is largely dependent of optical properties of the system. The modeling of physical phenomena plays nowadays...
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Computed aided system for separation and classification of the abnormal erythrocytes in human blood
PublicationThe human peripheral blood consists of cells (red cells, white cells, and platelets) suspended in plasma. In the following research the team assessed an influence of nanodiamond particles on blood elements over various periods of time. The material used in the study consisted of samples taken from ten healthy humans of various age, different blood types and both sexes. The markings were leaded by adding to the blood unmodified...
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The Effect of Fly Ash Microspheres on the Pore Structure of Concrete
PublicationThe fly ash microspheres (FAMs) formed during the mineral transformation stage in coal combustion are hollow spherical particles with a density less than water. This paper presents the results of X‐ray micro‐computed tomography and an automatic image analysis system of the porosity in the structure of hardened concrete with microspheres. Concrete mixtures with ordinary Portland cement and two substitution rates of cement by microspheres—5%...
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Geoscience Methods in Real Estate Market Analyses Subjectivity Decrease
PublicationReal estate management, including real estate market analysis, is part of a so-called geosystem. In recent years, the popularity of creating various types of systems and automatic solutions in real estate management, including those related to property classification and valuation, has been growing in the world, mainly to reduce the impact of human subjectivity, to increase the scope of analyses and reduce research time. A very...
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Deep Instance Segmentation of Laboratory Animals in Thermal Images
PublicationIn this paper we focus on the role of deep instance segmentation of laboratory rodents in thermal images. Thermal imaging is very suitable to observe the behaviour of laboratory animals, especially in low light conditions. It is an non-intrusive method allowing to monitor the activity of animals and potentially observe some physiological changes expressed in dynamic thermal patterns. The analysis of the recorded sequence of thermal...
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Applying the Lombard Effect to Speech-in-Noise Communication
PublicationThis study explored how the Lombard effect, a natural or artificial increase in speech loudness in noisy environments, can improve speech-in-noise communication. This study consisted of several experiments that measured the impact of different types of noise on synthesizing the Lombard effect. The main steps were as follows: first, a dataset of speech samples with and without the Lombard effect was collected in a controlled setting;...
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Maritime traffic situation awareness analysis via high-fidelity ship imaging trajectory
PublicationSituation awareness provides crucial yet instant information to maritime traffic participants, and significant attentions are paid to implement traffic situation awareness task via various maritime data source (e.g., automatic identification system, maritime surveillance video, radar, etc.). The study aims to analyze traffic situation with the support of ship imaging trajectory. First, we employ the dark channel prior model to...
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The Proposition of an Automated Honing Cell with Advanced Monitoring
PublicationHoning of holes allows for small shape deviation and a low value of a roughness profile parameter, e.g., Ra parameter. The honing process heats the workpiece and raises its temperature. The increase in temperature causes thermal deformations of the honed holes. The article proposes the construction of a honing cell, containing in addition to CNC honing machine: thermographic camera, sound intensity meter, and software for collecting...
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Sustainable Use of the Catenary by Trolleybuses with Auxiliary Power Sources on the Example of Gdynia
PublicationThe current developments in onboard power source technology, in particular, traction batteries, open up new potential in trolleybus transport and also make it possible to introduce electric buses. Thus far, trolleybus transport has required the presence of overhead lines (OHL). Introducing trolleybuses with onboard batteries makes it possible to grow the zero-emissions transport network in places with limited power supply capabilities...
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How high-tech solutions support the fight against IUU and ghost fishing: a review of innovative approaches, methods, and trends
PublicationIllegal, Unreported, and Unregulated fishing is a major threat to human food supply and marine ecosystem health. Not only is it a cause of significant economic loss but also its effects have serious long-term environmental implications, such as overfishing and ocean pollution. The beginning of the fight against this problem dates since the early 2000s. From that time, a number of approaches and methods have been developed and reported....
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Detection of Anomalies in the Operation of a Road Lighting System Based on Data from Smart Electricity Meters
PublicationSmart meters in road lighting systems create new opportunities for automatic diagnostics of undesirable phenomena such as lamp failures, schedule deviations, or energy theft from the power grid. Such a solution fits into the smart cities concept, where an adaptive lighting system creates new challenges with respect to the monitoring function. This article presents research results indicating the practical feasibility of real‐time...
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Selection of an artificial pre-training neural network for the classification of inland vessels based on their images
PublicationArtificial neural networks (ANN) are the most commonly used algorithms for image classification problems. An image classifier takes an image or video as input and classifies it into one of the possible categories that it was trained to identify. They are applied in various areas such as security, defense, healthcare, biology, forensics, communication, etc. There is no need to create one’s own ANN because there are several pre-trained...
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Design of reverse curves adapted to the satellite measurements
PublicationThe paper presents a new method for designing railway route in the direction change area adapted to the Mobile Satellite Measurements technique. The method may be particularly useful in the situations when both tangents cannot be connected in an elementary way using a circular arc with transition curves. Thus, the only solution would be the application of two circular arcs of opposite curvature signs, that is, the use of an inverse...
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Efficiency of Artificial Intelligence Methods for Hearing Loss Type Classification: an Evaluation
PublicationThe evaluation of hearing loss is primarily conducted by pure tone audiometry testing, which is often regarded as golden standard for assessing auditory function. If the presence of hearing loss is determined, it is possible to differentiate between three types of hearing loss: sensorineural, conductive, and mixed. This study presents a comprehensive comparison of a variety of AI classification models, performed on 4007 pure tone...
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A Semiautomatic Experience-Based Tool for Solving Product Innovation Problem
PublicationIn this paper we present the idea of Smart Innovation Engineering (SIE) System and its implementation methodology. The SIE system is semi-automatic system that helps in carrying the process of product innovation. It collects the experiential knowledge from the formal decisional events. This experiential knowledge is collected from the group of similar products having some common functions and features. The SIE system behaves like...
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Minimizing Distribution and Data Loading Overheads in Parallel Training of DNN Acoustic Models with Frequent Parameter Averaging
PublicationIn the paper we investigate the performance of parallel deep neural network training with parameter averaging for acoustic modeling in Kaldi, a popular automatic speech recognition toolkit. We describe experiments based on training a recurrent neural network with 4 layers of 800 LSTM hidden states on a 100-hour corpora of annotated Polish speech data. We propose a MPI-based modification of the training program which minimizes the...
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Investigation of optical properties of Infitec and Active Stereo stereoscopic techniques for CAVE-type virtual reality systems
PublicationIn recent years, many scientific and industrial centres in the world developed virtual reality systems or laboratories. At present, among the most advanced virtual reality systems are CAVE-type (Cave Automatic Virtual Environment) installations. Such systems usually consist of four, five, or six projection screens arranged in the form of a closed or hemi-closed space. The basic task of such systems is to ensure the effect of user...
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Investigating Feature Spaces for Isolated Word Recognition
PublicationMuch attention is given by researchers to the speech processing task in automatic speech recognition (ASR) over the past decades. The study addresses the issue related to the investigation of the appropriateness of a two-dimensional representation of speech feature spaces for speech recognition tasks based on deep learning techniques. The approach combines Convolutional Neural Networks (CNNs) and timefrequency signal representation...
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Properties of New Composite Materials Based on Hydroxyapatite Ceramic and Cross-Linked Gelatin for Biomedical Applications
PublicationThe main aim of the research was to develop a new biocompatible and injectable composite with the potential for application as a bone-to-implant bonding material or as a bone substitute. A composite based on hydroxyapatite, gelatin, and two various types of commercially available transglutaminase (TgBDF/TgSNF), as a cross-linking agent, was proposed. To evaluate the impacts of composite content and processing parameters on various...
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Optimizing Medical Personnel Speech Recognition Models Using Speech Synthesis and Reinforcement Learning
PublicationText-to-Speech synthesis (TTS) can be used to generate training data for building Automatic Speech Recognition models (ASR). Access to medical speech data is because it is sensitive data that is difficult to obtain for privacy reasons; TTS can help expand the data set. Speech can be synthesized by mimicking different accents, dialects, and speaking styles that may occur in a medical language. Reinforcement Learning (RL), in the...
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Offshore benthic habitat mapping based on object-based image analysis and geomorphometric approach. A case study from the Slupsk Bank, Southern Baltic Sea
PublicationBenthic habitat mapping is a rapidly growing field of underwater remote sensing studies. This study provides the first insight for high-resolution hydroacoustic surveys in the Slupsk Bank Natura 2000 site, one of the most valuable sites in the Polish Exclusive Zone of the Southern Baltic. This study developed a quick and transparent, automatic classification workflow based on multibeam echosounder and side-scan sonar surveys to...
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Identification of acoustic event of selected noise sources in a long-term environmental monitoring systems
PublicationABSTRACT Undertaking long-term acoustic measurements on sites located near an airport is related to a problem of large quantities of recorded data, which very often represents information not related to flight operations. In such areas, usually defined as zone of limited use, often other sources of noise exist, such as roads or railway lines treated is such context as acoustic background. Manual verification of such recorded data...
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A System for Heart Sounds Classification
PublicationThe future of quick and efficient disease diagnosis lays in the development of reliable non-invasive methods. As for the cardiac diseases – one of the major causes of death around the globe – a concept of an electronic stethoscope equipped with an automatic heart tone identification system appears to be the best solution. Thanks to the advancement in technology, the quality of phonocardiography signals is no longer an issue. However,...
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MicroGal Gravity Measurements with MGS-6 Micro-g LaCoste Gravimeter
PublicationKnowing the exact number of fruit and trees helps growers to make better decisions about how to manage their production in the orchard and prevent plant diseases. The current practice of yield estimation is to manually count fruit or flowers (before harvesting), which is a very time-consuming and costly process. Moreover it’s not practical for large orchards. It also doesn’t allow to make predictions of plant development in a more...
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Relationship between album cover design and music genres.
PublicationThe aim of the study is to find out whether there exists a relationship between typographic, compositional and coloristic elements of the music album cover design and music contained in the album. The research study involves basic statistical analysis of the manually extracted data coming from the worldwide album covers. The samples represent 34 different music genres, coming from nine countries from around the world. There are...
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Investigation of tracking systems properties in CAVE-type virtual reality systems
PublicationIn recent years, many scientific and industrial centers in the world developed a virtual reality systems or laboratories. One of the most advanced solutions are Immersive 3D Visualization Lab (I3DVL), a CAVE-type (Cave Automatic Virtual Environment) laboratory. It contains two CAVE-type installations: six-screen installation arranged in a form of a cube, and four-screen installation, a simplified version of the previous one. The...
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Application of autoencoder to traffic noise analysis
PublicationThe 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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Optimal selection of input features and an acompanying neural network structure for the classification purposes - skin lesions case study
PublicationMalignant 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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Data-driven, probabilistic model for attainable speed for ships approaching Gdańsk harbour
PublicationThe growing demand for maritime transportation leads to increased traffic in ports. From this arises the need to observe the consequences of the specific speed ships reach when approaching seaports. However, usually the analyzed cases refer only to the statistical evaluation of the studied phenomenon or to the empirical modelling, ignoring the mutual influence of variables such as ship type, length or weather conditions. In this...
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Development of the System Assurance Reference Model for Generating Modular Assurance Cases
PublicationAssurance cases are structured arguments used to demonstrate specific system properties such as safety or security. They are used in many industrial sectors including automotive, aviation and medical devices. Larger assurance cases are usually divided into modules to manage the complexity and distribute the work. Each of the modules is developed to address specific goals allocated to the specific objects i.e. components of the...
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Modeling and Accuracy Assessment of Determining the Coastline Course Using Geodetic, Photogrammetric and Satellite Measurement Methods: Case Study in Gdynia Beach in Poland
PublicationThe coastal environment represents a resource from both a natural and economic point of view, but it is subject to continuous transformations due to climate change, human activities, and natural risks. Remote sensing techniques have enormous potential in monitoring coastal areas. However, one of the main tasks is accurately identifying the boundary between waterbodies such as oceans, seas, lakes or rivers, and the land surface....
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Evaluation of aspiration problems in L2 English pronunciation employing machine learning
PublicationThe 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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Creating Dynamic Maps of Noise Threat Using PL-Grid Infrastructure
PublicationThe paper presents functionality and operation results of a system for creating dynamic maps of acoustic noise employing the PL-Grid infrastructure extended with a distributed sensor network. The work presented provides a demonstration of the services being prepared within the PLGrid Plus project for measuring, modeling and rendering data related to noise level distribution in city agglomerations. Specific computational environments,...
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The geodetic monitoring of the engineering structure – a practical solution of the problem in 3D space
PublicationThe study raises the issues concerning the automatic system designed for the monitoring of movement of controlled points, located on the roof covering of the Forest Opera in Sopot. It presents the calculation algorithm proposed by authors. It takes into account the specific design and location of the test object. High forest stand makes it difficult to use distant reference points. Hence the reference points used to study the stability...
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Quality of graphical markers for the needs of eyewear devices
Publicationin this paper we propose to cast the problem of identification of people, objects or places into an application for smart glasses that decodes information from graphical markers. We focus on analyzing different factors that can have influence on the processes of the automatic recognition of information from a code. The research we present aims at reviewing recognition performances in function of: size of a marker, distance from/to...
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Extraction of stable foreground image regions for unattended luggage detection
PublicationA novel approach to detection of stationary objects in the video stream is presented. Stationary objects are these separated from the static background, but remaining motionless for a prolonged time. Extraction of stationary objects from images is useful in automatic detection of unattended luggage. The proposed algorithm is based on detection of image regions containing foreground image pixels having stable values in time and...
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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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Know your safety indicator – A determination of merchant vessels Bow Crossing Range based on big data analytics
PublicationEven 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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Cost-Efficient Surrogate Modeling of High-Frequency Structures Using Nested Kriging with Automated Adjustment of Model Domain Lateral Dimensions
PublicationSurrogate models are becoming popular tools of choice in mitigating issues related to the excessive cost of electromagnetic (EM)-driven design of high-frequency structures. Among available techniques, approximation modeling is by far the most popular due to its versatility. In particular, the surrogates are exclusively based on the sampled simulation data with no need to involve engineering insight or problem-specific knowledge....