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Wyniki wyszukiwania dla: deep learning, genetic algorithm, artificial neural networks, predictive maintenance, cost efficient maintenance
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Rapid Surrogate-Aided Multi-Criterial Optimization of Compact Microwave Passives Employing Machine Learning and ANNs
PublikacjaThis article introduces an innovative method for achieving low-cost and reliable multi-objective optimization (MO) of microwave passive circuits. The technique capitalizes on the attributes of surrogate models, specifically artificial neural networks (ANNs), and multi-resolution electromagnetic (EM) analysis. We integrate the search process into a machine learning (ML) framework, where each iteration produces multiple infill points...
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Data Reduction Algorithm for Machine Learning and Data Mining
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COMPREHENSIVE MODELLING OF THE COST EFFECTIVNESS OF RAILWAY LINE ELECTRIFICATION
PublikacjaSubject of this paper is the mathematical model estimating the Economical threshold between usage of combustion engine traction and electrical traction for new and modernized railway passenger communication lines. Currently available models do not coincide with the whole complexity of the problem. The proposed model was implemented into Matlab and then validated on “Pomorska Kolej Metropolitalna” investment time-frame and its cost...
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On Computationally-Efficient Reference Design Acquisition for Reduced-Cost Constrained Modeling and Re-Design of Compact Microwave Passives
PublikacjaFull-wave electromagnetic (EM) analysis has been playing a major role in the design of microwave components for the last few decades. In particular, EM tools allow for accurate evaluation of electrical performance of miniaturized structures where strong cross-coupling effects cannot be adequately quantified using equivalent network models. However, EM-based design procedures (parametric optimization, statistical analysis) generate...
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Toward Intelligent Recommendations Using the Neural Knowledge DNA
PublikacjaIn this paper we propose a novel recommendation approach using past news click data and the Neural Knowledge DNA (NK-DNA). The Neural Knowledge DNA is a novel knowledge representation method designed to support discovering, storing, reusing, improving, and sharing knowledge among machines and computing systems. We examine our approach for news recommendation tasks on the MIND benchmark dataset. By taking advantages of NK-DNA, deep...
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A New Heuristic Algorithm for Effective Preemption in MPLS Networks
PublikacjaW artykule opisano nowy algorytm wywłaszczania przeznaczony dla sieci MPLS. Umożliwia on alokację zasobów sieci dla nowej ścieżki uwzględniając koszt usuniętych jednej lub wielu istniejących już ścieżek. Proponowany heurystyczny algorytm wybiera ścieżki do wywłaszczenia wykorzystując informację o topologii sieci. Używa funkcji optymalizacji minimalizującej stratę pasma na poziomie sieci. Przedstawiono i omówiono wyniki badań symulacyjnych...
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Energy-Efficient Neural Network Inference with Microcavity Exciton Polaritons
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Artificial-Neural-Network-Based Sensorless Nonlinear Control of Induction Motors
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Ultracapacitor modeling and control with discrete fractional order artificial neural network
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Artificial neural network controller for underwater ship hull operation robot.
PublikacjaZaproponowano model matematyczny pojazdu podwodnego, który w uproszczonej wersji spełnia warunki dynamiki odpowiadające głowicy roboczej podwodnego robota. Uwzględniono niektóre czynniki oddziałujące na ruch podwodnej głowicy roboczej, jak np. gęstość wody oraz siły odśrodkowe i wypornościowe. Przedstawiono układ sterowania, w którym zastosowano regulator oparty na bazie sieci neuronowych, za pomocą którego można sterować...
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On thermal and Flow Expert Systems Based on Artificial Neural Network (ANN)
PublikacjaZaprezentowano możliwość realizacji jednego z zadań systemów eksperckich, polegającego na określaniu rozmiaru eksploatacyjnej degradacji parametrów geometrycznych układów łopatkowych turbin. Dyskusję przeprowadzono w oparciu o zastosowanie wybranego typu sztucznej sieci neuronowej (SSN). Badano jakość i dokładność polegającą na dobrej identyfikacji rozmiaru degradacji przez tę wybraną SSN wykrywającą rozmiar degradacji geometrycznej....
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Artificial Neural Network-Based Sensorless Nonlinear Control Of Induction Motors
PublikacjaW niniejszym artykule przedstawiono strukturę sztucznej sieci neuronowej służącej do korygowania działania układu estymacji prędkości kątowej wirnika. Odtworzona prędkość kątowa wirnika zostały wykorzystane w bezczujnikowym układzie sterowania silnikiem indukcyjnym pracującym w zamkniętej pętli sprzężenia prędkościowego.Przedstawiono wyniki badań eksperymentalnych z silnikiem o mocy 1,1kW.
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Machine Learning Techniques in Concrete Mix Design
PublikacjaConcrete mix design is a complex and multistage process in which we try to find the best composition of ingredients to create good performing concrete. In contemporary literature, as well as in state-of-the-art corporate practice, there are some methods of concrete mix design, from which the most popular are methods derived from The Three Equation Method. One of the most important features of concrete is compressive strength, which...
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Hierarchical Estimation of Human Upper Body Based on 2D Observation Utilizing Evolutionary Programming and 'Genetic Memory'
PublikacjaNew method of the human body pose estimation based on single camera 2D observation is presented. It employs 3D model of the human body, and genetic algorithm combined with annealed particle filter for searching the global optimum of model state, best matching the object's 2D observation. Additionally, motion cost metric is employed, considering current pose and history of the body movement, favouring the estimates with the lowest...
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Free-standing TiO2 nanotubes decorated with spherical nickel nanoparticles as a cost-efficient electrocatalyst for oxygen evolution reaction
PublikacjaHere, we report significant activity towards the oxygen evolution reaction (OER) of spherical nickel nanoparticles (NPs) electrodeposited onto free-standing TiO2 nanotubes (TNT) via cyclic voltammetry. It has been shown that simple manipulation of processing parameters, including scan rate and number of cycles, allows for formation of the NPs in various diameters and amounts. The polarization data with respect to transmission electron...
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Shape Optimisation of Kaplan Turbine Blades Using Genetic Algorithms
PublikacjaThis monograph is a comprehensive guide to a method of blade profile optimisation for Kaplan-type turbines. This method is based on modelling the interaction between rotor and stator blades. Additionally, the shape of the draft tube is investigated. The influence of the periodic boundary condition vs. full geometry is also discussed. Evolutionary algorithms (EA) are used as an optimisation method together with artificial neural...
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Single-agent MOR208 salvage and maintenance therapy in a patient with refractory/relapsing diffuse large B-cell lymphoma: a case report
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Data governance: Organizing data for trustworthy Artificial Intelligence
PublikacjaThe rise of Big, Open and Linked Data (BOLD) enables Big Data Algorithmic Systems (BDAS) which are often based on machine learning, neural networks and other forms of Artificial Intelligence (AI). As such systems are increasingly requested to make decisions that are consequential to individuals, communities and society at large, their failures cannot be tolerated, and they are subject to stringent regulatory and ethical requirements....
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Cost-Efficient Bi-Layer Modeling of Antenna Input Characteristics Using Gradient Kriging Surrogates
PublikacjaOver the recent years, surrogate modeling has been playing an increasing role in the design of antenna structures. The main incentive is to mitigate the issues related to high cost of electromagnetic (EM)-based procedures. Among the various techniques, approximation surrogates are the most popular ones due to their flexibility and easy access. Notwithstanding, data-driven modeling of antenna characteristics is associated with serious...
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The use of a genetic algorithm in the process of optimizing the shape of a three-dimensional periodic beam
PublikacjaMechanical periodic structures exhibit unusual dynamic behavior thanks to the periodicity of their structures, which can be attributed to their cellular arrangement. The source of this periodicity may result from periodic variations of material properties within their cells and/or variations in the cell geometry. The authors present the results of their studies on the optimization of physical parameters of a three-dimensional axisymetrical...
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Evolving gene regulatory networks controlling foraging strategies of prey and predators in an artificial ecosystem
PublikacjaCo-evolution of predators and prey is an example of an evolutionary arms race, leading in nature to selective pressures in positive feedback. We introduce here an artificial life ecosystem in which such positive feedback can emerge. This ecosystem consists of a 2-dimensional liquid environment and animats controlled by evolving artificial gene regulatory networks encoded in linear genomes. The genes in the genome encode chemical...
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Creating a radiological database for automatic liver segmentation using artificial intelligence.
PublikacjaImaging in medicine is an irreplaceable stage in the diagnosis and treatment of cancer. The subsequent therapeutic effect depends on the quality of the imaging tests performed. In recent years we have been observing the evolution of 2D to 3D imaging for many medical fields, including oncological surgery. The aim of the study is to present a method of selection of radiological imaging tests for learning neural networks.
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Cost-Efficient Two-Level Modeling of Microwave Passives Using Feature-Based Surrogates and Domain Confinement
PublikacjaA variety of surrogate modelling techniques has been utilized in high-frequency design over the last two decades. Yet, the curse of dimensionality still poses a serious challenge in setting up re-liable design-ready surrogates of modern microwave components. The difficulty of the model-ing task is only aggravated by nonlinearity of circuit responses. Consequently, constructing a practically usable surrogate model, valid across...
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Employing Subjective Tests and Deep Learning for Discovering the Relationship between Personality Types and Preferred Music Genres
PublikacjaThe purpose of this research is two-fold: (a) to explore the relationship between the listeners’ personality trait, i.e., extraverts and introverts and their preferred music genres, and (b) to predict the personality trait of potential listeners on the basis of a musical excerpt by employing several classification algorithms. We assume that this may help match songs according to the listener’s personality in social music networks....
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Model Predictive Super-Twisting Sliding Mode Control for An Autonomous Surface Vehicle
PublikacjaThis paper presents a new robust Model Predictive Control (MPC) algorithm for trajectory tracking of an Autonomous Surface Vehicle (ASV) in presence of the time-varying external disturbances including winds, waves and ocean currents as well as dynamical uncertainties. For fulfilling the robustness property, a sliding mode control-based procedure for designing of MPC and a super-twisting term are adopted. The MPC algorithm has been...
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Ship Dynamic Positioning Based on Nonlinear Model Predictive Control
PublikacjaThe presented work explores the simulation test results of using nonlinear model predictive control algorithm for ship dynamic positioning. In the optimization task, a goal function with a penalty was proposed with a variable prediction step. The results of the proposed control algorithm were compared with backstepping and PID. The effect of estimation accuracy on the control quality with the implemented algorithms was investigated....
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Deep learning-based waste detection in natural and urban environments
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Generation of microbial colonies dataset with deep learning style transfer
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DentalSegmentator: robust deep learning-based CBCT image segmentation
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Cost-Efficient Globalized Parameter Optimization of Microwave Components through Response-Feature Surrogates and Nature-Inspired Metaheuristics
PublikacjaDesign of contemporary microwave devices predominantly utilizes computational models, including both circuit simulators, and full-wave electromagnetic (EM) evaluation. The latter constitutes the sole generic way of rendering accurate assessment of the system outputs that considers phenomena such as cross-coupling or radiation and dielectric losses. Consequently, for reliability reasons, the final tuning of microwave device parameters...
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Artificial Intelligence Aided Architectural Design
PublikacjaTools and methods used by architects always had an impact on the way building were designed. With the change in design methods and new approaches towards creation process, they became more than ever before crucial elements of the creation process. The automation of architects work has started with computational functions that were introduced to traditional computer-aided design tools. Nowadays architects tend to use specified tools...
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Speed sensorless induction motor drive with predictive current controller
PublikacjaToday, speed sensorless modes of operation are becoming standard solutions in the area of electric drives. This paper presents a speed sensorless control system of an induction motor with a predictive current controller. A closed-loop estimation system with robustness against motor parameter variation is used for the control approach. The proposed algorithm has been implemented using field-programmable gate arrays (FPGAs) and a...
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Flexible Knowledge–Vision–Integration Platform for Personal Protective Equipment Detection and Classification Using Hierarchical Convolutional Neural Networks and Active Leaning
PublikacjaThis 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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Artificial Intelligence
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Artificial intelligence
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Towards neural knowledge DNA
PublikacjaIn this paper, we propose the Neural Knowledge DNA, a framework that tailors the ideas underlying the success of neural networks to the scope of knowledge representation. Knowledge representation is a fundamental field that dedicates to representing information about the world in a form that computer systems can utilize to solve complex tasks. The proposed Neural Knowledge DNA is designed to support discovering, storing, reusing,...
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Autonomous port management based AGV path planning and optimization via an ensemble reinforcement learning framework
PublikacjaThe rapid development of shipping trade pushes automated container terminals toward the direction of intelligence, safety and efficiency. In particular, the formulation of AGV scheduling tasks and the safety and stability of transportation path is an important part of port operation and management, and it is one of the basic tasks to build an intelligent port. Existing research mainly focuses on collaborative operation between...
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Efficient list cost coloring of vertices and/or edges of bounded cyclicity graphs
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Efficient List Cost Coloring of Vertices and∕or Edges of Some Sparse Graphs
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Efficient list cost coloring of vertices and/or edges of bounded cyclicity graphs
PublikacjaW artykule rozważamy listowo-kosztowe kolorowanie wierzchołków i krawędzi grafu w modelu wierzchołkowym, krawędziowym, totalnym i pseudototalnym. Stosujemy programowanie dynamiczne w celu otrzymania algorytmów wielomianowych dla drzew. Następnie uogólniamy to podejście na dowolne grafy z ograniczonymi liczbami cyklomatycznymi i na ich multikolorowania.
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Efficient list cost coloring of vertices and/or edges of some sparse graphs
PublikacjaRozważane jest kolorowanie wierzchołków i krawędzi grafów w modelach klasycznym, totalnym i pseudototalnym z uwzględnieniem dodatkowego ograniczenia w postaci list dostępnych kolorów. Proponujemy wielomianowy algorytm oparty na paradygmacie programowania dynamicznego dla grafów o strukturze drzewa. Wynik ten można uogólnić na grafy o liczbie cyklomatycznej ograniczonej z góry przez dowolnie wybraną stała.
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Machine-Learning-Powered EM-Based Framework for Efficient and Reliable Design of Low Scattering Metasurfaces
PublikacjaPopularity of metasurfaces has been continuously growing due to their attractive properties including the ability to effectively manipulate electromagnetic (EM) waves. Metasurfaces comprise optimized geometries of unit cells arranged as a periodic lattice to obtain a desired EM response. One of their emerging application areas is the stealth technology, in particular, realization of radar cross section (RCS) reduction. Despite...
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Cost Accounting 2024 winter
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Practical issues for the implementation of survivability and recovery techniques in optical networks
PublikacjaFailures in optical networks are inevitable. They may occur during work being done for the maintenance of other infrastructures, or on a larger scale as the result of an attack or large-scale disaster. As a result, service availability, an important aspect of Quality of Service (QoS), is often degraded. Appropriate fault recovery techniques are thus crucial to meet the requirements set by the Service Level Agreements (SLAs) between...
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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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Using neural networks to examine trending keywords in Inventory Control
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Neural networks based NARX models in nonlinear adaptive control
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Application of neural networks for description of pressure distribution in slide bearing.
PublikacjaBadano rozkład ciśnienia hydrodynamicznego w łożysku ślizgowym dla wybranych wariantów łożyska. Wykazano, że zastosowanie sieci neuronowych umożliwia opis rozkładu ciśnienia hydrodynamicznego z uwzględnieniem zmian geometrycznych (bezwymiarowa długość - L) i mechanicznych (mimośrodowość względem H) łożyska.
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Identification of slide bearing main parameters using neural networks.
PublikacjaWykazano, że sieci neuronowe jak najbardziej nadają się do identyfikacji głównych parametrów geometrycznych i ruchowych hydrodynamicznych łożysk ślizgowych.
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Estimation the rhythmic salience of sound with association rules and neural networks
PublikacjaW referacie przedstawiono eksperymenty mające na celu automatyczne wyszukiwanie wartości rytmicznych we frazie muzycznej. W tym celu wykorzystano metody data mining i sztuczne sieci neuronowe.