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Search results for: NEURAL NETWORKS, SURROGATE-BASED OPTIMIZATION, HYPERPARAMETER OPTIMIZATION, SEQUENTIAL SAMPLING
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Numerically Efficient Miniaturization-Oriented Optimization of an Ultra-Wideband Spline-Parameterized Antenna
PublicationDesign of ultra-wideband radiators for modern handheld applications is a challenging task that involves not only selection of an appropriate topology, but also its tuning oriented towards balancing the electrical performance and size. In this work, a low-cost design of a compact, broadband, spline-parameterized monopole antenna has been considered. The framework used for the structure design implements trust-region-based methods,...
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Optimization algorithm and filtration using the adaptive TIN model at the stage of initial processing of the ALS point cloud
PublicationAirborne laser scanning (ALS) provides survey results in the form of a point cloud. The ALS point cloud is a source of data used primarily for constructing a digital terrain model (DTM). To generate a DTM, the set of ALS observations must be first subjected to the point cloud processing methodology. A standard methodology is composed of the following stages: acquisition of the ALS data, initial processing (including filtration),...
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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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Results of implementation of Feed Forward Neural Networks for modeling of heat transfer coefficient during flow condensation for low and high values of saturation temperature
Open Research DataThis database present results of implementation of Feed Forward Neural Networks for modeling of heat transfer coefficient during flow condensation for low and high values of saturation temperature. Databse contain one table and 7 figures.
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Neural Networks and the Evolution of Environmental Change
PublicationZmiany środowiskowe na Ziemii są odwieczne i liczą około 4 miliardy lat. Homo sapiens wpłynął na każdy aspekt środowiska ziemskiego w wyniku rozwoju ludzkości na przestrzeni ostatnich milionów lat. Ale nic tak nie wpłynęło na wzrost i szybkość zmian na Ziemi jak ludzka aktywność w ciągu ostatnich dwóch stuleci. Po raz pierwszy zmiany ekosystemów były tak intensywne i zachodziły na tka wielką skalę i z taką szybkością jak nigdy...
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Artificial Neural Networks for Comparative Navigation
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Designing of Track Axis Alignment with the Use of Satellite Measurements and Particle Swarm Optimization
PublicationDesigning of the track’s alignment is a key issue from the point of view of maintaining of proper geometries. The paper presents a design method for sections of railway line located in the horizontal arch. The method is adapted to the technique of mobile satellite measurements. The general principles of this measurement method have been described in the article. A project's solution has been presented using mathematical notation...
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Optimization of river network representation data models for web-based systems
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Global Optimization-Based Method for Deriving Intermolecular Potential Parameters for Crystals
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An automated microwave planar filter design based on space mapping optimization
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Optimization of chip removing system operation in circular sawing machine
PublicationThe paper presents the optimization of the wood chips removing system in the sliding table saw. Chips are generated during the cutting of the material. The attention was focused on the upper casing of mentioned system. The methodical experimental studies of the pressure distribution inside the casing during the wood chip removing operation for the selected rotational speed of saw blade with a diameter of 300 mm and 450 mm were...
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Optimization of Nuclear Power Share in the Structure of Electricity Production in Poland in Time Perspective by 2060
PublicationThe author of this paper presented the results of a system analysis using MARKAL model, aiming at the optimization of nuclear power share in power generation structure in Poland in time perspective by 2060. Optimization criterion is the minimization of the objective function, i.e. the total cost of energy system, taking into account constraints related to CO2, SOx and NOx emissions and obligatory shares of electricity from renewable...
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Balanced Spider Monkey Optimization with Bi-LSTM for Sustainable Air Quality Prediction
PublicationA reliable air quality prediction model is required for pollution control, human health monitoring, and sustainability. The existing air quality prediction models lack efficiency due to overfitting in prediction model and local optima trap in feature selection. This study proposes the Balanced Spider Monkey Optimization (BSMO) technique for effective feature selection to overcome the local optima trap and overfitting problems....
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Categorization of emotions in dog behavior based on the deep neural network
PublicationThe aim of this article is to present a neural system based on stock architecture for recognizing emotional behavior in dogs. Our considerations are inspired by the original work of Franzoni et al. on recognizing dog emotions. An appropriate set of photographic data has been compiled taking into account five classes of emotional behavior in dogs of one breed, including joy, anger, licking, yawning, and sleeping. Focusing on a particular...
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Optimization of vortex-assisted supramolecular solvent-based liquid liquid microextraction for the determination of mercury in real water and food samples
PublicationA novel method was developed for sample preparation for spectrophotometric determination of Hg(II) in water and food samples. The method was based on vortex-assisted supramolecular solvent-assisted liquid-liquid microextraction (VA-SUPRASs-LLME). Analytical parameters such as pH, chelating agent, solvent type and volume, vortex time and salting out effect were optimized. Surface and normal probability plots were drawn for the variables...
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Prediction of Early Childhood Caries Based on Single Nucleotide Polymorphisms Using Neural Networks
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Spectral measurement of birefringence using particle swarm optimization analysis
PublicationThe measurement of birefringence is useful for the examination of both technical and biological objects. One of the main problems is that the polarization state of light in birefringent media changes periodically. Without the knowledge of the period number, the birefringence of a given medium cannot be determined reliably. We propose to analyse the spectrum of light in order to determine the birefringence. We use a Particle Swarm...
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Rapid Yield Optimization of Miniaturized Microwave Passives by Response Features and Variable-Fidelity EM Simulations
PublicationThe operation of high-frequency devices, including microwave passive components, can be impaired by fabrication tolerances but also incomplete knowledge concerning operating conditions (temperature, input power levels) and material parameters (e.g., substrate permittivity). Although the accuracy of manufacturing processes is always limited, the effects of parameter deviations can be accounted for in advance at the design phase...
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Convolutional Neural Networks for C. Elegans Muscle Age Classification Using Only Self-Learned Features
PublicationNematodes Caenorhabditis elegans (C. elegans) have been used as model organisms in a wide variety of biological studies, especially those intended to obtain a better understanding of aging and age-associated diseases. This paper focuses on automating the analysis of C. elegans imagery to classify the muscle age of nematodes based on the known and well established IICBU dataset. Unlike many modern classification methods, the proposed...
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Reduction of Tire Rolling Resistance by Optimization of Road Surfaces and Tires
PublicationDuring interaction between tire and road surface three very important phenomena are always in effect. One of them (very desirable) is friction that is important for traction, braking and cornering. Two other phenomena are not desirable at all, that is rolling resistance and noise. This paper discusses relations between road surface and tire parameters versus tire rolling resistance. Road surface texture, porosity, impedance, strength...
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Fast Multi-Objective Optimization of Narrow-Band Antennas Using RSA Models and Design Space Reduction
PublicationComputationally efficient technique for multi-objective design optimization of narrow-band antennas is presented. In our approach, the corrected low-fidelity antenna model (obtained through coarse-discretization EM simulations) is enhanced using frequency scaling and response correction, sampled, and utilized to obtain a fast response surface approximation (RSA) antenna surrogate. The RSA model is constructed in the reduced design space....
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The Way One Defines Specification Matters: On the Performance Criteria for Efficient Antenna Optimization in Aggregated Bi-Objective Setups
PublicationDesign of antenna structures for real-world applications is a challenging task that often involves addressing multiple design requirements at a time. Popular solution approaches to this class of problems include utilization of composite objectives. Although configuration of such functions has a significant effect on the cost and performance of the optimization, their specific structure is normally determined based on engineering...
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ANALYSIS AND OPTIMIZATION OF ELECTRIC VEHICLE CHARGING PROCESSES IN TRANSACTIVE ENERGY SYSTEMS
PublicationThe implementation of smart charging of electric vehicles allows operators of local power networks and electricity suppliers to implement new business models for the interaction of electric vehicles with the network. In addition to the optimal selection of Microgrid capacities when charging electric vehicles, it is also important to use different charging methods. To satisfy the interests of all participants of local systems from...
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Application of multicriteria decision analysis in solvent type optimization for chlorophenols determination with a dispersive liquid–liquid microextraction
PublicationThis study presents a novel support tool for the optimization and development of analytical methods. The tool is based on multi-criteria decision analysis (MCDA), namely the Technique for Order of Preference by Similarity to the Ideal Solution (TOPSIS), that allows users to rank possible solutions according to their requirements. In this study, we performed rankings of pairs of eight extraction and three dispersive solvents used...
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Design specification management with automated decision-making for reliable optimization of miniaturized microwave components
PublicationThe employment of numerical optimization techniques for parameter tuning of microwave components has nowadays become a commonplace. In pursuit of reliability, it is most often carried out at the level of full-wave electromagnetic (EM) simulation models, incurring considerable computational expenses. In the case of miniaturized microstrip circuits, densely arranged layouts with strong cross-coupling effects make EM-driven tuning...
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Optimization of the Hardware Layer for IoT Systems using a Trust Region Method with Adaptive Forward Finite Differences
PublicationTrust-region (TR) algorithms represent a popular class of local optimization methods. Owing to straightforward setup and low computational cost, TR routines based on linear models determined using forward finite differences (FD) are often utilized for performance tuning of microwave and antenna components incorporated within the Internet of Things systems. Despite usefulness for design of complex structures, performance of TR methods...
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Applying artificial neural networks for modelling ship speed and fuel consumption
PublicationThis paper deals with modelling ship speed and fuel consumption using artificial neural network (ANN) techniques. These tools allowed us to develop ANN models that can be used for predicting both the fuel consumption and the travel time to the destination for commanded outputs (the ship driveline shaft speed and the propeller pitch) selected by the ship operator. In these cases, due to variable environmental conditions, making...
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Recycled rubber wastes-based polymer composites with flame retardancy and electrical conductivity: Rational design, modeling and optimization
PublicationPolymer recycling techniques experience a maturity period of design and application. Rubbers comprise a high proportion of polymer wastes, highly flammable and impossible to re-melt. Polymer composites based on ground tire rubber (GTR) and ethylene-vinyl acetate copolymer (EVA) containing carbon black (CB) (1–50 phr), with variable EVA/GTR weight composition (10/90, 25/75, 50/50, 75/25 and 90/10), and processing temperature (Low:...
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Low-Cost Multi-Objective Optimization of Antennas By Means Of Generalized Pareto Ranking Bisection Algorithm
PublicationThis paper introduces a generalized Pareto ranking bisection algorithm for low-cost multi-objective design optimization of antenna structures. The algorithm allows for identifying a set of Pareto optimal sets of parameters (that represent the best trade-offs between considered objectives) by iterative partitioning of the intervals connecting previously found designs and executing a Pareto-ranking-based poll search. The initial...
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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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Testing Stability of Digital Filters Using Multimodal Particle Swarm Optimization with Phase Analysis
PublicationIn this paper, a novel meta-heuristic method for evaluation of digital filter stability is presented. The proposed method is very general because it allows one to evaluate stability of systems whose characteristic equations are not based on polynomials. The method combines an efficient evolutionary algorithm represented by the particle swarm optimization and the phase analysis of a complex function in the characteristic equation....
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EM-Driven Multi-Objective Optimization of a Generic Monopole Antenna by Means of a Nested Trust-Region Algorithm
PublicationAntenna structures for modern applications are characterized by complex and unintuitive topologies that are difficult to develop when conventional experience-driven techniques are of use. In this work, a method for automatic generation of antenna geometries in a multi-objective setup has been proposed. The approach involves optimization of a generic spline-based radiator with adjustable number of parameters using a nested trust-region-based...
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Multi-Objective Design Optimization of Compact Quasi-Isotropic Dielectric Resonator Antenna
PublicationMulti-objective optimization of a quasi-isotropic dielectric resonator antenna (DRA) is presented. Utilization of variable-fidelity electromagnetic (EM) DRA models, response surface approximations, and response correction techniques, allows us to obtain—at a low computational cost—a set of alternative antenna designs representing the best possible trade-offs between three conflicting objectives: antenna size, its reflection response,...
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Global Optimization for Recovery of Clipped Signals Corrupted With Poisson-Gaussian Noise
PublicationWe study a variational formulation for reconstructing nonlinearly distorted signals corrupted with a Poisson-Gaussian noise. In this situation, the data fidelity term consists of a sum of a weighted least squares term and a logarithmic one. Both of them are precomposed by a nonlinearity, modelling a clipping effect, which is assumed to be rational. A regularization term, being a piecewise rational approximation of the ℓ0 function...
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Low-Cost Design Optimization of Microwave Passives Using Multi-Fidelity EM Simulations and Selective Broyden Updates
PublicationGeometry parameters of contemporary microwave passives have to be carefully tuned in the final stages of their design process to ensure the best possible performance. For reliability reasons, the tuning has to be to be carried out at the level of full-wave electromagnetic (EM) simulations. This is because traditional modeling methods are incapable of quantifying certain phenomena that may affect operation and performance of these...
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Optimization of the distance between the vertical plates in the convective air heat exchanger
PublicationThis paper examines the influence of the distance between vertical plates on the intensity of free convective heat transfer along with the optimization of this distance. Experimental tests were carried out for one model channel of such an heat exchanger with widths , 0.085 and 0.18 m. This channel, open at the top and sides, was formed by two isothermal symmetrically heated parallel vertical plates of dimensions m and m. The influence...
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Reduced-cost optimization-based miniaturization of microwave passives by multi-resolution EM simulations for internet of things and space-limited applications
PublicationStringent performance specifications along with constraints imposed on physical dimensions, make the design of contemporary microwave components a truly onerous task. In recent years, the latter demand has been growing in importance, with the innovative application areas such as Internet of Things coming into play. The need to employ full-wave electromagnetic (EM) simu-lations for response evaluation, reliable yet CPU heavy, only...
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Maximizing SDN resilience to node‐targeted attacks through joint optimization of the primary and backup controllers placements
PublicationIn Software Defined Networks (SDN) packet data switches are configured by a limited number of SDN controllers, which respond to queries for packet forwarding decisions from the switches. To enable optimal control of switches in real time the placement of controllers at network nodes must guarantee that the controller-to-controller and switch-to-controller communications delays are bounded. Apart from the primary controllers that...
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DEEP CONVOLUTIONAL NEURAL NETWORKS AS A DECISION SUPPORT TOOL IN MEDICAL PROBLEMS – MALIGNANT MELANOMA CASE STUDY
PublicationThe paper presents utilization of one of the latest tool from the group of Machine learning techniques, namely Deep Convolutional Neural Networks (CNN), in process of decision making in selected medical problems. After the survey of the most successful applications of CNN in solving medical problems, the paper focuses on the very difficult problem of automatic analyses of the skin lesions. The authors propose the CNN structure...
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Fast Full-Wave Multilevel Zero-Pole Optimization of Microwave Filters
PublicationA new concept is proposed for the full-wave computer-aided design of microwave filters. The method consists of two stages and operates on the zeros and poles of the transfer function and their derivatives. These quantities are evaluated from the response computed by a full-wave electromagnetic solver with two levels of accuracy. The two stages make use of different models that are optimized using a low-accuracy electromagnetic...
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Energy consumption optimization in wastewater treatment plants: Machine learning for monitoring incineration of sewage sludge
PublicationBiomass management in terms of energy consumption optimization has become a recent challenge for developed countries. Nevertheless, the multiplicity of materials and operating parameters controlling energy consumption in wastewater treatment plants necessitates the need for sophisticated well-organized disciplines in order to minimize energy consumption and dissipation. Sewage sludge (SS) disposal management is the key stage of...
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Gas Detection Using Resistive Gas Sensors And Radial Basis Function Neural Networks
PublicationWe present a use of Radial Basis Function (RBF) neural networks and Fluctuation Enhanced Sensing (FES) method in gas detection system utilizing a prototype resistive WO3 gas sensing layer with gold nanoparticles. We investigated accuracy of gas detection for three different preprocessing methods: no preprocessing, Principal Component Analysis (PCA) and wavelet transformation. Low frequency noise voltage observed in resistive gas...
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Improved-Efficacy EM-Driven Optimization of Antenna Structures Using Adaptive Design Specifications and Variable-Resolution Models
PublicationOptimization-driven parameter tuning is an essential step in the design of antenna systems. Although in many cases it is still conducted through parametric studies, rigorous numerical methods become a necessity if truly optimum designs are sought for, and the problem intricacies (number of variables, multiple goals, constraints) make the interactive approaches insufficient. The two practical considerations of electromagnetic (EM)-driven...
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Traffic Modeling in IMS-based NGN Networks
PublicationIn the modern world the need for accurate and quickly delivered information is becoming more and more essential. In order to fulfill these requirements, next generation telecommunication networks should be fast introduced and correctly dimensioned. For this reason proper traffic models must be identified, which is the subject of this paper. In the paper standardization of IMS (IP Multimedia Subsystem) concept and IMS-based NGN...
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Comparison of Optimization Techniques for Coupling Matrix Synthesis Using Eigenvalue Based Approach
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Multiscalar Control Based Airgap Flux Optimization of Induction Motor for Loss Minimization
PublicationBased on the induction motor model, considering the core loss resistance that accounts for magnetic characteristic saturation, a speed control approach is devised with an adaptive full-order (AFO) speed observer. The induction motor model analysis is done sincerely in a stationary reference frame. The control approach incorporates a flux reference generator designed to meet optimal operational circumstances and a nonlinear speed...
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GPU-Accelerated 3D Mesh Deformation for Optimization Based on the Finite Element Method
PublicationThis paper discusses a strategy for speeding up the mesh deformation process in the design-byoptimization of high-frequency components involving electromagnetic field simulations using the 3D finite element method (FEM). The mesh deformation is assumed to be described by a linear elasticity model of a rigid body; therefore, each time the shape of the device is changed, an auxiliary elasticity finite-element problem must be solved....
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Design and Optimization of Metamaterial-Based 5G Millimeter Wave Antenna for Gain Enhancement
PublicationIn this brief, a low profile, broadband, high-gain antenna array based on optimized metamaterials (MMs) with dual-beam radiation is reported for 5G millimeters wave (mm-wave) applications. The design is a simple bow tie operating at a 5G band of 28 GHz. It consists of two bow ties with substrate integrated waveguide (SIW)-based power splitter. A broad impedance bandwidth of 26.3−29.8 GHz is obtained by appropriately combining the...
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Flexible Knowledge–Vision–Integration Platform for Personal Protective Equipment Detection and Classification Using Hierarchical Convolutional Neural Networks and Active Leaning
PublicationThis work is part of an effort to develop of a Knowledge-Vision Integration Platform for Hazard Control (KVIP-HC) in industrial workplaces, adaptable to a wide range of industrial environments. The paper focuses on hazards resulted from the non-use of personal protective equipment (PPE). The objective is to test the capability of the platform to adapt to different industrial environments by simulating the process of randomly selecting...
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OPTIMIZATION OF THE LAST STAGE OF GAS-STEAM TURBINE USING A HYBRID METHOD
PublicationThis paper relates to the CFD calculation of a new turbine type which is in the phase of theoretical analysis, because the working fluid is a mixture of steam and gas generated in wet combustion chamber. At first, this article concentrates on a possibility of streamlining the flow efficiency of a last stage of axial turbine working on gas-steam mixture using a hybrid of the particle swarm optimization algorithm with the Nelder-Mead...