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Wyniki wyszukiwania dla: MICROWAVE DESIGN, MULTI-OBJECTIVE OPTIMIZATION, DESIGN AUTOMATION, MACHINE LEARNING, NEURAL NETWORKS
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Machine Learning Applied to Aspirated and Non-Aspirated Allophone Classification—An Approach Based on Audio "Fingerprinting"
PublikacjaThe purpose of this study is to involve both Convolutional Neural Networks and a typical learning algorithm in the allophone classification process. A list of words including aspirated and non-aspirated allophones pronounced by native and non-native English speakers is recorded and then edited and analyzed. Allophones extracted from English speakers’ recordings are presented in the form of two-dimensional spectrogram images and...
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Model Correction and Optimization Framework for Expedited EM-Driven Surrogate-Assisted Design of Compact Antennas
PublikacjaDesign of compact antennas is a numerically challenging process that heavily relies on electromagnetic (EM) simulations and numerical optimization algorithms. For reliability of simulation results, EM models of small radiators often include connectors which—despite being components with fixed dimensions—significantly contribute to evaluation cost. In this letter, a response correction method for antenna models without connector,...
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Analysis of electrical patterns activity in artificial multi-stable neural networks
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AGENT-BASED APPROACH TO THE DESIGN OF RBF NETWORKS
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Predicting emotion from color present in images and video excerpts by machine learning
PublikacjaThis work aims at predicting emotion based on the colors present in images and video excerpts using a machine-learning approach. The purpose of this paper is threefold: (a) to develop a machine-learning algorithm that classifies emotions based on the color present in an image, (b) to select the best-performing algorithm from the first phase and apply it to film excerpt emotion analysis based on colors, (c) to design an online survey...
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Key success factors for small design offices in the bidding process
PublikacjaCompetition in the design office market is high, therefore it is important to be aware of the conditions determining the competitive advantage, thus increasing the bidding effectiveness. For this reason, the aim of the article is to identify key success factors (KSF) increasing successful bidding of a small design office. The factors were identified and then analysed based on a literature review, expert interviews and using Group...
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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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TR-Based Antenna Design with Forward FD: The Effects of Step Size on the Optimization Performance
PublikacjaNumerical methods are important tools for design of modern antennas. Trust-region (TR) methods coupled with data-efficient surrogates based on finite differentiation (FD) represent a popular class of antenna design algorithms. However, TR performance is subject to FD setup, which is normally determined a priori based on rules-of-thumb. In this work, the effect of FD perturbations on the performance of TR-based design is evaluated...
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Towards automated full-wave design of microwave structures
PublikacjaArtykuł przedstawia problematykę automatycznego projektowania układów mikrofalowych i jego znaczenie. przedstawia stan rynku narzędzi projektowania, pojawiąjące się rozwiązania i przyszłe trendy.
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Conditional Value-at-Risk Vs. Value-at-Risk to Multi-Objective Portfolio Optimization
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Extended Hopfield models of neural networks for combinatorial multiobjective optimization problems
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Optimization of a three-bed adsorption chiller by genetic algorithms and neural networks
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Simulation-driven design of compact ultra-wideband antenna structures
PublikacjaPurpose–The purpose of this paper is to investigate strategies and algorithms for expedited designoptimization and explicit size reduction of compact ultra-wideband (UWB) antennas.Design/methodology/approach–Formulation of the compact antenna design problem aiming atexplicit size reduction while maintaining acceptable electrical performance is presented. Algorithmicframeworks are described suitable for handling various design situations...
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Design. Metodology outline and practice
PublikacjaNa tle - uznawanego za typowy - schematu prac składających się na proces projektowania, pokazano przykładowe tworzenie inicjatywy sprawczej oraz rozwój koncepcji dotyczących sformułowania konkretnego zadania projektowego w dziedzinie budowy maszyn.Temat dotyczył obszaru projektowania turbin wodnych.The origin of project initiative, as well as concept development related to formulating a specific design goal, are presented in the...
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A new approach to design of weather disruption-tolerant wireless mesh networks
PublikacjaWireless Mesh Networks, offering transmission rates of 1–10 Gb/s per a millimeter-wave link (utilizing the 71–86 GHz band) seem to be a promising alternative to fiber optic backbone metropolitan area networks because of significantly lower costs of deployment and maintenance. However, despite providing high transmission rates in good weather conditions, high-frequency wireless links are very susceptible to weather disruptions....
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Design thinking (DT) for the design and planning education of engineer-architects
PublikacjaEngineers are facing new challenges connected with globalisation, digitisation and the increased complexity of the design process. This calls for new, more interdisciplinary and user-oriented approaches to problem- solving. In this article, the authors analyse design thinking (DT) as a method to support the education of engineers specialising in architecture and urban planning. Identified in this study are the opportunities this...
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Machine Learning and Text Analysis in an Artificial Intelligent System for the Training of Air Traffic Controllers
PublikacjaThis chapter presents the application of new information technology in education for the training of air traffic controllers (ATCs). Machine learning, multi-criteria decision analysis, and text analysis as the methods of artificial intelligence for ATCs training have been described. The authors have made an analysis of the International Civil Aviation Organization documents for modern principles of ATCs education. The prototype...
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Design, Realization and Measurements of Enhanced Performance 2.4 GHz ESPAR Antenna for Localization in Wireless Sensor Networks
PublikacjaThis paper presents the design, realization and measurements of an Electronically Steerable Parasitic Array Radiator (ESPAR) antenna with enhanced performance of estimating the incoming signal direction. Designed antenna is dedicated for 2.4 GHz ISM applications with emphasis on Wireless Sensor Networks (WSN). Proposed antenna provides different radiation patterns by proper configuration of the parasitic elements. Thus, several...
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An Automated Method for Biometric Handwritten Signature Authentication Employing Neural Networks
PublikacjaHandwriting biometrics applications in e-Security and e-Health are addressed in the course of the conducted research. An automated graphomotor analysis method for the dynamic electronic representation of the handwritten signature authentication was researched. The developed algorithms are based on dynamic analysis of electronically handwritten signatures employing neural networks. The signatures were acquired with the use of the...
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A Selection of Starting Points for Iterative Position Estimation Algorithms Using Feedforward Neural Networks
PublikacjaThis article proposes the use of a feedforward neural network (FNN) to select the starting point for the first iteration in well-known iterative location estimation algorithms, with the research objective of finding the minimum size of a neural network that allows iterative position estimation algorithms to converge in an example positioning network. The selected algorithms for iterative position estimation, the structure of the...
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Expedited Globalized Antenna Optimization by Principal Components and Variable-Fidelity EM Simulations: Application to Microstrip Antenna Design
PublikacjaParameter optimization, also referred to as design closure, is imperative in the development of modern antennas. Theoretical considerations along with rough dimension adjustment through supervised parameter sweeping can only yield initial designs that need to be further tuned to boost the antenna performance. The major challenges include handling of multi-dimensional parameter spaces while accounting for several objectives and...
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Process of Medical Dataset Construction for Machine Learning-Multifield Study and Guidelines
PublikacjaThe acquisition of high-quality data and annotations is essential for the training of efficient machine learning algorithms, while being an expensive and time-consuming process. Although the process of data processing and training and testing of machine learning models is well studied and considered in the literature, the actual procedures of obtaining data and their annotations in collaboration with physicians are in most cases...
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Constrained optimization for generating gain-bandwidth design trade-offs of wideband unidirectional antennas
PublikacjaBroadband unidirectional antennas realised in microstrip technology find applications in many wireless communication systems. One of their design challenges is the necessity of handling multiple performance figures which is difficult when using traditional design methods, largely based on parameter sweeping. This work presents a simple optimisation-based framework that permits generation of gain-bandwidth trade-off designs for...
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Design of dimensionally stable composites using efficient global optimization method
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Frequency-Variant Double-Zero Single-Pole Reactive Coupling Networks for Coupled-Resonator Microwave Bandpass Filters
PublikacjaIn this work, a family of frequency-variant reactive coupling (FVRC) networks is introduced and discussed as new building blocks for the synthesis of coupled-resonator bandpass filters with real or complex transmission zeros (TZs). The FVRC is a type of nonideal frequency-dependent inverter that has nonzero elements on the diagonal of the impedance matrix, along with a nonlinear frequency-variation profile of its transimpedance...
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Miniaturization-Oriented Design of Spline-Parameterized UWB Antenna for In-Door Positioning Applications
PublikacjaDesign of ultra-wideband antennas for in-door localization applications is a challenging task. It involves development of geometry that maintains appropriate balance between the size and performance. In this work, a topologically-flexible monopole has been generated using a stratified framework which embeds a gradient-based trust-region (TR) optimization algorithm in a meta-loop that gradually increases the structure dimensionality....
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Effectiveness of the robust PSS design
PublikacjaThe paper discusses optimal PSS of synchronous generator synthesis. The optimal controller is an Hinf controller, what means that minimises Hinf norm of transfer function between the exogenous signals such as reference inputs and disturbances, and the error signals which are to be minimised to meet the control objective. The dynamic properties of the plant are shaped by choosing appropriate weighting function applied to the plant...
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Deep Learning
PublikacjaDeep learning (DL) is a rising star of machine learning (ML) and artificial intelligence (AI) domains. Until 2006, many researchers had attempted to build deep neural networks (DNN), but most of them failed. In 2006, it was proven that deep neural networks are one of the most crucial inventions for the 21st century. Nowadays, DNN are being used as a key technology for many different domains: self-driven vehicles, smart cities,...
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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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A decision-making module for aiding ship system automation design; A knowledge-based approach
PublikacjaZastosowanie elementów sztucznej inteligencji, w tym systemów z bazą wiedzy staje się coraz bardziej powszechne przy komputerowo wspomaganym projektowaniu. Proces projektowy związany jest z wieloma problemami decyzyjnymi, jak: wybór struktury podsystemu, podzespołów czy też elementów składowych. Z tego względu zdecydowano się opracować system z bazą wiedzy z modułem wspirającym proces podejmowania decyzji.W artykule przedstawiono...
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CBR methodology application in an expert system for aided design ship's engine room automation
PublikacjaW artykule przedstawiono metody obliczania podobieństwa na podstawie przypadków, zastosowane w opracowanym systemie ekspertowym do wspomagania projektowania siłowni okrętowej. Do realizacji metody na przykładzie automatyki napędu głównego zastosowano oprogramowanie bazy danych i system ekspertowy. Uzyskane wyniki wyszukiwania w bazie danych statków podobnych zostały porównane i przeanalizowane. Do weryfikacji zastosowanych w bazie...
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Reduced-cost surrogate modeling of input characteristics and design optimization of dual-band antennas using response features
PublikacjaIn this article, a procedure for low-cost surrogate modeling of input characteristics of dual-band antennas has been discussed. The number of training data required for construction of an accurate model has been reduced by representing the antenna reflection response to the level of suitably defined feature points. The points are allocated to capture the critical features of the reflection characteristic, such as the frequencies...
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The CDIO model in architectural education and research by design
PublikacjaArchitectural education has always been related to experimentation: that is, defining concepts, drawing sketches, working on models, then testing and modifying them. This activity mirrors the CDIO learning methods and objectives. Despite this, research studies into the applicability of the CDIO model in architectural curricula are scarce. In the discipline of architecture, hands-on experiences are associated not only with one of...
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Optimization of Wireless Networks for Resilience to Adverse Weather Conditions
PublikacjaIn this chapter, we consider how adverse weather conditions such as rain or fog affect the performance of wireless networks, and how to optimize these networks so as to make them robust to these conditions. We first show how to analyze the weather conditions in order to make them useful for network optimization modelling. Using an example realistic network, we show how to optimize two types of wireless networks: free-space optical...
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An Intelligent Approach to Short-Term Wind Power Prediction Using Deep Neural Networks
PublikacjaIn this paper, an intelligent approach to the Short-Term Wind Power Prediction (STWPP) problem is considered, with the use of various types of Deep Neural Networks (DNNs). The impact of the prediction time horizon length on accuracy, and the influence of temperature on prediction effectiveness have been analyzed. Three types of DNNs have been implemented and tested, including: CNN (Convolutional Neural Networks), GRU (Gated Recurrent...
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Automated Design of Linear Phase Filters
PublikacjaThis paper presents a fast technique for an automated design of microwave filters with linear phase. The proposed method exploits the cost function defined using the location of complex zeros and poles of the filter’s transfer and reflection function. The effectiveness of the proposed technique is presented with two illustrative examples.
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Integrating Experience-Based Knowledge Representation and Machine Learning for Efficient Virtual Engineering Object Performance
PublikacjaMachine learning and Artificial Intelligence have grown significant attention from industry and academia during the past decade. The key reason behind interest is such technologies capabilities to revolutionize human life since they seamlessly integrate classical networks, networked objects and people to create more efficient environments. In this paper, the Knowledge Representation technique of Set of Experience...
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Rapid Design Centering of Multi-Band Antennas Using Knowledge-Based Inverse Models and Response Features
PublikacjaAccounting for manufacturing tolerances as well as uncertainties concerning operating conditions and material parameters is one of the important yet often neglected aspects of antenna development. Appropriate quantification of uncertainties allows for estimating the fabrication yield but also to carry out robust design (e.g., yield maximization). For reliability reasons, statistical analysis should be executed at the accuracy level...
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Computationally-efficient design optimisation of antennas by accelerated gradient search with sensitivity and design change monitoring
PublikacjaElectromagnetic (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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Editorial for the special issue on advances in forward and inverse surrogate modeling for high-frequency design
PublikacjaThe design of modern‐day high‐frequency devices and circuits, including microwave/RF, antenna and photonic components, historically has relied on full‐wave electromagnetic (EM) simulation tools. Initially used for design verification, EM simulations are nowadays used in the design process itself, for example, for finding optimum values of geometry and/or material parameters of the structures of interest. In a growing number of...
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Novel structure and design of compact UWB slot antenna
PublikacjaIn this paper, a novel structure of a compact UWB slot antenna is presented along with a simulation-driven design optimization algorithm for adjusting geometry parameters of the device. Our primary objective is to obtain small footprint of the structure while maintaining its acceptable electrical performance. It is achieved by introducing sufficiently large number of geometry degrees of freedom, including increased number of parameterized...
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Human Resource Management Digitalisation in Multidisciplinary Ship Design Companies
PublikacjaThe digitalisation in the ship design sector is currently applied to the design process itself and is well defined, partially standardised and practically implemented by both independent design companies and the design departments of shipyards. The situation is similar in other sectors of engineering. However, the requirements for the digitalisation of other processes in design and engineering companies have not previously been...
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Network lifetime maximization in wireless mesh networks for machine-to-machine communication
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Novel structure and design of enhanced-bandwidth hybrid quadrature patch coupler
PublikacjaA novel structure and design optimization procedure of an enhanced-bandwidth hybrid quadrature patch coupler is proposed. Improved performance of the circuit has been obtained by parameterizing the coupler sections using splines, which introduces additional degrees of freedom. Due to computational complexity of the parameter adjustment problem, a sequential design procedure is applied. In each iteration, a selected number of spline...
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Deep Learning: A Case Study for Image Recognition Using Transfer Learning
PublikacjaDeep learning (DL) is a rising star of machine learning (ML) and artificial intelligence (AI) domains. Until 2006, many researchers had attempted to build deep neural networks (DNN), but most of them failed. In 2006, it was proven that deep neural networks are one of the most crucial inventions for the 21st century. Nowadays, DNN are being used as a key technology for many different domains: self-driven vehicles, smart cities,...
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Design and Experimental Validation of a Metamaterial-Based Sensor for Microwave Imaging in Breast, Lung, and Brain Cancer Detection
PublikacjaThis study proposes an innovative geometry of a microstrip sensor for high-resolution microwave imaging (MWI). The main intended application of the sensor is early detection of breast, lung, and brain cancer. The proposed design consists of a microstrip patch antenna fed by a coplanar waveguide with a metamaterial layer-based lens implemented on the back side, and an artificial magnetic conductor (AMC) realized on as a separate...
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Adsorption chiller in a combined heating and cooling system: simulation and optimization by neural networks
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Inverse and forward surrogate models for expedited design optimization of unequal-power-split patch couplers
PublikacjaIn the paper, a procedure for precise and expedited design optimization of unequal power split patchcouplers is proposed. Our methodology aims at identifying the coupler dimensions that correspond to thecircuit operating at the requested frequency and featuring a required power split. At the same time, thedesign process is supposed to be computationally efficient. The proposed methodology involves two typesof auxiliary models (surrogates):...
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Machine learning for the management of biochar yield and properties of biomass sources for sustainable energy
PublikacjaBiochar is emerging as a potential solution for biomass conversion to meet the ever increasing demand for sustainable energy. Efficient management systems are needed in order to exploit fully the potential of biochar. Modern machine learning (ML) techniques, and in particular ensemble approaches and explainable AI methods, are valuable for forecasting the properties and efficiency of biochar properly. Machine-learning-based forecasts,...
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Design of Weather Disruption-Tolerant Wireless Mesh Networks
PublikacjaZ uwagi na wysoki koszt realizacji sieci teleinformatycznych wykorzystujących przewodową transmisję światłowodową, bezprzewodowe sieci kratowe (WMN) oferujące transmisję rzędu 1-10 Gb/s (przy wykorzystaniu pasma millimeter-wave - 71-86 GHz), wydają się być obiecującą alternatywą dla przewodowych sieci MAN. Jednakże z uwagi na właściwości transmisji bezprzewodowej w oparciu o łącza wysokiej częstotliwości, łącza te są bardzo wrażliwe...