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Wyniki wyszukiwania dla: POLYPHASE MACHINE - INDUCTION MACHINE - MULTISCALAR MODEL - OBSERVER - CONTROL SYSTEM
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Detection of circulating tumor cells by means of machine learning using Smart-Seq2 sequencing
PublikacjaCirculating tumor cells (CTCs) are tumor cells that separate from the solid tumor and enter the bloodstream, which can cause metastasis. Detection and enumeration of CTCs show promising potential as a predictor for prognosis in cancer patients. Furthermore, single-cells sequencing is a technique that provides genetic information from individual cells and allows to classify them precisely and reliably. Sequencing data typically...
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Game theory-based virtual machine migration for energy sustainability in cloud data centers
PublikacjaAs the demand for cloud computing services increases, optimizing resource allocation and energy consumption has become a key factor in achieving sustainability in cloud environments. This paper presents a novel approach to address these challenges through an optimized virtual machine (VM) migration strategy that employs a game-theoretic approach based on particle swarm optimization (PSO) (PSO-GTA). The proposed approach leverages...
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Unsupervised machine-learning classification of electrophysiologically active electrodes during human cognitive task performance
PublikacjaIdentification of active electrodes that record task-relevant neurophysiological activity is needed for clinical and industrial applications as well as for investigating brain functions. We developed an unsupervised, fully automated approach to classify active electrodes showing event-related intracranial EEG (iEEG) responses from 115 patients performing a free recall verbal memory task. Our approach employed new interpretable...
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A new approach to designing control of dissolved oxygen and aeration system in sequencing batch reactor by applied backstepping control algorithm
PublikacjaThe Wastewater Treatment Plant (WWTP) is a very complex system, due to its nonlinearity, time-variance, and multiple time scales in its dynamics among others. The most important control parameter in a WWTP is the Dissolved Oxygen (DO) concentration. The tracking problem of the DO concentration is one of the most fundamental issues in biological wastewater treatment. Proper DO concentration control is necessary to achieve adequate...
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Active Annotation in Evaluating the Credibility of Web-Based Medical Information: Guidelines for Creating Training Data Sets for Machine Learning
PublikacjaMethods Results Discussion References Abbreviations Copyright Abstract Background: The spread of false medical information on the web is rapidly accelerating. Establishing the credibility of web-based medical information has become a pressing necessity. Machine learning offers a solution that, when properly deployed, can be an effective tool in fighting medical misinformation on the web. Objective: The aim of this study is to...
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Model of control plane of ASON/GMPLS network
PublikacjaASON (Automatic Switched Optical Network) is a concept of optical network recommended in G.8080/Y.1304 by ITU-T. Control Plane of this network could be based on GMPLS (Generalized Multi-Protocol Label Switching) protocols. This solution, an ASON control plane built on GMPLS protocols is named ASON/GMPLS. In the paper, we decompose the control plane problem and show the main concepts of ASON network. We propose a hierarchical architecture...
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Cost-Efficient Multi-Objective Design of Miniaturized Microwave Circuits Using Machine Learning and Artificial Neural Network
PublikacjaDesigning microwave components involves managing multiple objectives such as center frequencies, impedance matching, and size reduction for miniaturized structures. Traditional multi-objective optimization (MO) approaches heavily rely on computationally expensive population-based methods, especially when exe-cuted with full-wave electromagnetic (EM) analysis to guarantee reliability. This paper introduces a novel and cost-effective...
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Machine-Learning Methods for Estimating Performance of Structural Concrete Members Reinforced with Fiber-Reinforced Polymers
PublikacjaIn recent years, fiber-reinforced polymers (FRP) in reinforced concrete (RC) members have gained significant attention due to their exceptional properties, including lightweight construction, high specific strength, and stiffness. These attributes have found application in structures, infrastructures, wind power equipment, and various advanced civil products. However, the production process and the extensive testing required for...
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An Automatic Self-Tuning Control System Design for an Inverted Pendulum
PublikacjaA control problem of an inverted pendulum in the presence of parametric uncertainty has been investigated in this paper. In particular, synthesis and implementation of an automatic self-tuning regulator for a real inverted pendulum have been given. The main cores of the control system are a swing-up control method and a stabilisation regulator. The first one is based on the energy of an inverted pendulum, whereas the second one...
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Performance Analysis of Machine Learning Methods with Class Imbalance Problem in Android Malware Detection
PublikacjaDue to the exponential rise of mobile technology, a slew of new mobile security concerns has surfaced recently. To address the hazards connected with malware, many approaches have been developed. Signature-based detection is the most widely used approach for detecting Android malware. This approach has the disadvantage of being unable to identify unknown malware. As a result of this issue, machine learning (ML) for detecting malware...
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Predicting seismic response of SMRFs founded on different soil types using machine learning techniques
PublikacjaPredicting the Maximum Interstory Drift Ratio (M-IDR) of Steel Moment-Resisting Frames (SMRFs) is a useful tool for designers to approximately evaluate the vulnerability of SMRFs. This study aims to explore supervised Machine Learning (ML) algorithms to build a surrogate prediction model for SMRFs to reduce the need for complex modeling. For this purpose, twenty well-known ML algorithms implemented in Python software are trained...
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A Computationally Efficient Model for Predicting Successful Memory Encoding Using Machine-Learning-based EEG Channel Selection
PublikacjaComputational cost is an important consideration for memory encoding prediction models that use data from dozens of implanted electrodes. We propose a method to reduce computational expense by selecting a subset of all the electrodes to build the prediction model. The electrodes were selected based on their likelihood of measuring brain activity useful for predicting memory encoding better than chance (in terms of AUC). A logistic...
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Two-Level Multivariable Control System of Dissolved Oxygen Tracking and Aeration System for Activated Sludge Processes
PublikacjaThe problem of tracking dissolved oxygen is one of the most complex and fundamental issues related to biological processes. The dissolved oxygen level in aerobic tanks has significant influence on behaviour and activity of microorganism inhabiting the plant. Aerated tanks are supplied with air from an aeration system (blowers, pipes, throttling valves, diffusers). It is a complex dynamic system governed by nonlinear hybrid dynamics....
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Greenhouse control system design
PublikacjaCoraz większa populacja i zmniejszające się tereny uprawne wymusza efektywniejsze metody uprawy roślin. Zaradzić temu mogą układu hydroponiczne, które dzięki rozwojowi techniki są w stanie osiągać znacznie większe oraz bardziej jednorodne plony. Jest to możliwe dzięki zaawansowanym systemom opartym na dokładnych urządzeniach pomiarowych, sterowaniu w zamkniętej pętli oraz mikrokontrolerom umożliwiającym...
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Softly switched model predictive control for control of integratedwastewater treatment system at medium time scale.
PublikacjaW przypadku gdy system jest sterowany za pomocą jednej, uniwersalnej strategii sterowania w pełnym zakresie jego obciążeń, powstają poważne trudności w znalezieniu optymalnego sterowania. W celu jak najlepszego dopasowania strategii sterowania do panujący warunków, zdefiniowano trzy stany operacyjne: normalny, zakłóceniowy oraz awaryjny. Dla tych stanów zaprojektowano odpowiednie strategie sterowania. W związku z tym pojawia się...
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Voltage control in a power system with renewable sources of energy
PublikacjaIntensive development of distributed generation in power systems, caused by the European Union energy policy, gives possibility for improving safety in power delivery as well as optimizing the costs of the systems functioning. In this context, distributed generation can be used for voltage control in power systems – it can be performed by the control of reactive power of each source of energy or a group of energy sources. This...
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Microgrinding of flat surfaces on a single-disc lapping machine
PublikacjaW referacie przedstawiono wyniki badań eksperymentalnych mikroszlifowania z kinematyką docierania jednotarczowego. Przedstawiono propozycję narzędzia z wkładkami ściernymi z ziarnem diamentowym D3/2 i spoiwem żywicznym. Omówiono kinematykę docierania jednotarczowego i sposób oceny krzywizny rys obróbkowych.
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Microgrinding of flat surfaces on single-disk lapping machine
PublikacjaW pracy przedstawiono wyniki badań mikroszlifowania z kinematyką docierania w układzie jednotarczowym z wykorzystaniem nowego narzędzia wykonanego z pastylek ściernych z ziarnem diamentowym (D3/2) i spoiwem żywicznym. Zakres pracy obejmował przeprowadzenie badań eksperymentalnych i modelowych związanych z analizą promienia krzywizny rys obróbkowych.
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Machine Learning Modelling and Feature Engineering in Seismology Experiment
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Microgrinding of flat surfaces on single-disc lapping machine
PublikacjaW pracy przedstawiono możliwości zastosowania specjalnych narzędzi do mikroszlifowania na docierarce jednotarczowej. Jedno z zastosowanych narzędzi posiada warstwę ścierniwa diamentowego (D64) nałożoną metodą galwaniczną. Drugie przetestowane narzędzie zbudowane zostało z diamentowych pastylek ściernych (D3/2). Przedstawiono analizę kinematyczną i wyniki ubytku materiałowego oraz osiągnięte parametry chropowatości.
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Hybrid excited electric machine with axial flux bridges
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Machine learning applied to bi-heterocyclic drugs recognition
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Stacking-Based Integrated Machine Learning with Data Reduction
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Data Reduction Algorithm for Machine Learning and Data Mining
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Synthesis of irregular motion mechanisms for production machine drives
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The use of machine learning for face regions detection in thermograms
PublikacjaThe aim of this study is to analyse the methods of detecting characteristic points of the face in thermographic images. As part of the implementation an extensive analysis of scientific publications covering similar issues both for the analysis of images made in visible light and thermographic images was carried out. On the basis of this analysis, 3 models were selected and then they were implemented and tested on the basis of...
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PERFORMANCE COMPARISON OF MACHINE LEARNING ALGORITHMS FOR PREDICTIVE MAINTENANCE
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Machine Learning for Sensorless Temperature Estimation of a BLDC Motor
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Digital measurements in monitoring of position and velocity of machine subassambly
PublikacjaReferat dotyczy zastosowania enkoderów z sygnałem wyjściowym kwadraturowym współdziałających z odpowiednim systemem DAQ do monitorowania przebiegu ruchu podzespołów maszyn technologicznych. Przedyskutowano podstawowe zasady konstrukcji układów do cyfrowych pomiarów prędkości i przemieszczeń.Porównano wady, zalety i ograniczenia rozdzielczości pomiaru prędkości dwoma znanymi sposobami. Omówiono własne rozwiązania zastosowane w układach...
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Finishing of Ceramics in a Single-Disk Lapping Machine Configuration
PublikacjaPrzedstawiono metodę obróbki ceramiki technicznej na zmodifikowanej docierarce jednotarczowej z niezależnym napędem pierścienia prowadzącego. Omówiono przebieg obróbki z wykorzystaniem nowych narzędzi i zastosowaniem ziarna wiązanego.
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Geometric working volume of a satellite positive displacement machine
PublikacjaThis article describes a method for determining the geometric working volume of satellite positive displacement machines (pump and motor). The working mechanism of these machines is satellite mechanism consisting of two non-circular gears (rotor and curvature) and circular gears (satellites). Two variants of the satellite mechanism are presented. In the first mechanism, the rolling line of the rotor is a sinusoid "wrapped" around...
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MACHINE LEARNING–BASED ANALYSIS OF ENGLISH LATERAL ALLOPHONES
PublikacjaAutomatic classification methods, such as artificial neural networks (ANNs), the k-nearest neighbor (kNN) and selforganizing maps (SOMs), are applied to allophone analysis based on recorded speech. A list of 650 words was created for that purpose, containing positionally and/or contextually conditioned allophones. For each word, a group of 16 native and non-native speakers were audio-video recorded, from which seven native speakers’...
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INVESTIGATION OF THE LOMBARD EFFECT BASED ON A MACHINE LEARNING APPROACH
PublikacjaThe Lombard effect is an involuntary increase in the speaker’s pitch, intensity, and duration in the presence of noise. It makes it possible to communicate in noisy environments more effectively. This study aims to investigate an efficient method for detecting the Lombard effect in uttered speech. The influence of interfering noise, room type, and the gender of the person on the detection process is examined. First, acoustic parameters...
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Employment of a Nonlinear Adaptive Control System for Improved Control of Dissolved Oxygen in Sequencing Batch Reactor
PublikacjaA proper control in a complex system, such as Wastewater Treatment Plant (WWTP) with each year is becoming increasingly important. High quality control can minimize an environmental impact as well as reduce operational costs of the WWTP. One of the core issues is providing adequate dissolved oxygen (DO) concetration for microorganisms used in a treatment process. An aeration process of the wastewater realised by an system consisting...
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Seismic response and performance prediction of steel buckling-restrained braced frames using machine-learning methods
PublikacjaNowadays, Buckling-Restrained Brace Frames (BRBFs) have been used as lateral force-resisting systems for low-, to mid-rise buildings. Residual Interstory Drift (RID) of BRBFs plays a key role in deciding to retrofit buildings after seismic excitation; however, existing formulas have limitations and cannot effectively help civil engineers, e.g., FEMA P-58, which is a conservative estimation method. Therefore, there is a need to...
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Deep slot effect in the squirrel-cage induction motors with scalar (V/F) control
PublikacjaQualitative characteristics of the electrical drive considerably depend on identification accuracy of math model parameters. In particular, it is depend on detection accuracy of stator active resistance r1 that is used in calculation of flux linkages, rotary speed in sensorless control systems. Paper provides analysis of influence of stator deep slot effect to stator active resistance value
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Robust identification of quadrocopter model for control purposes
PublikacjaThe paper addresses a problem of quadrotor unmanned aerial vehicle (so-called X4-flyer or quadrocopter) utility model identification for control design purposes. To that goal the quadrotor model is assumed to be composed of two abstracted subsystems, namely a rigid body (plant) and four motors equipped with blades (actuators). The model of the former is acquired based on a well-established dynamic equations of motion while the...
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Finite State Machine Based Modelling of Discrete Control Algorithm in LAD Diagram Language With Use of New Generation Engineering Software
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Power System Dynamics. Stability and Control. 3rd edition
PublikacjaComprehensive, state-of-the-art review of information on the electric power system dynamics and stability. It places the emphasis first on understanding the underlying physical principles before proceeding to more complex models and algorithms. The book explores the influence of classical sources of energy, wind farms and virtual power plants, power plants inertia and control strategy on power system stability. The book cover...
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Optimizing control by robustly feasible model predictive control and application to drinking water distribution systems
PublikacjaThe paper considers optimizing Model Predictive Control (MPC) for nonlinear plants with output constraints under uncertainties. Although the MPC technology can handle the constraints in the model by solving constraint model based optimization task, satisfying the plant output constraints under the model uncertainty still remains a challenge. The paper proposes Robustly Feasible MPC (RFMPC), which achieves feasibility of the outputs...
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Forecasting energy consumption and carbon dioxide emission of Vietnam by prognostic models based on explainable machine learning and time series
PublikacjaThis study assessed the usefulness of algorithms in estimating energy consumption and carbon dioxide emissions in Viet- nam, in which the training dataset was used to train the models linear regression, random forest, XGBoost, and AdaBoost, allowing them to comprehend the patterns and relationships between population, GDP, and carbon dioxide emissions, energy consumption. The results revealed that random forest, XGBoost, and AdaBoost...
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The structure of the control system for a dynamically positioned ship
PublikacjaThe article discusses functions and tasks of dynamic positioning (DP) systems for ships. The analysed issues include ship steering, in particular stabilisation of ship position and direction of motion (real course) at low manoeuvring speeds, and commonly used DP ship models. Requirements imposed by classification societies on DP ships are quoted. A multi-layer structure of the DP control system is presented, with special attention...
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Prediction of fracture toughness in fibre-reinforced concrete, mortar, and rocks using various Machine learning techniques
PublikacjaMachine Learning (ML) method is widely used in engineering applications such as fracture mechanics. In this study, twenty different ML algorithms were employed and compared for the prediction of the fracture toughness and fracture load in modes I, II, and mixed-mode (I-II) of various materials, including fibre-reinforced concrete, cement mortar, sandstone, white travertine, marble, and granite. A set of 401 specimens of “Brazilian...
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Designing control strategies of aeration system in biological WWTP
PublikacjaThe paper presents the complete design processes of a novel aeration control systems in the SBR (Sequencing Batch Reactor) wastewater treatment plant (WWTP). Due to large energy expense and high influence on biological processes, the aeration system plays a key role in WWTP operation. The paper considers the aeration system for a biological WWTP located in the northeast of Poland. This system consists of blowers, the main collector...
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Marine autonomous surface ship - control system configuration
PublikacjaThis paper addresses the problem of marine autonomous surface ship (MASS) control. The contribution of the paper is the development of a control system configuration, done assuming fully autonomous MASS operation under distinct operational conditions. The overview of hardware and software selection is included.
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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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Solvent Screening for Solubility Enhancement of Theophylline in Neat, Binary and Ternary NADES Solvents: New Measurements and Ensemble Machine Learning
PublikacjaTheophylline, a typical representative of active pharmaceutical ingredients, was selected to study the characteristics of experimental and theoretical solubility measured at 25 °C in a broad range of solvents, including neat, binary mixtures and ternary natural deep eutectics (NADES) prepared with choline chloride, polyols and water. There was a strong synergistic effect of organic solvents mixed with water, and among the experimentally...
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Cost-Efficient Measurement Platform and Machine-Learning-Based Sensor Calibration for Precise NO2 Pollution Monitoring
PublikacjaAir quality significantly impacts human health, the environment, and the economy. Precise real-time monitoring of air pollution is crucial for managing associated risks and developing appropriate short- and long-term measures. Nitrogen dioxide (NO2) stands as a common pollutant, with elevated levels posing risks to the human respiratory tract, exacerbating respiratory infections and asthma, and potentially leading to chronic lung...
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Factors determining selection of production planning and control system
PublikacjaThe article contains a comparative characteristics of selected systems of production planning and control, such as: MRP, kanban/JiT, DBR/TOC. The results of the performed analyses served as a basis for determining key market factors related to production planning and control functions, which determine the choice of an appropriate system.
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Comparative study on total nitrogen prediction in wastewater treatment 1 plant and effect of various feature selection methods on machine learning algorithms performance
PublikacjaWastewater characteristics prediction in wastewater treatment plants (WWTPs) is valuable and can reduce the number of sampling, energy, and cost. Feature Selection (FS) methods are used in the pre-processing section for enhancing the model performance. This study aims to evaluate the effect of seven different FS methods (filter, wrapper, and embedded methods) on enhancing the prediction accuracy for total nitrogen (TN) in the WWTP...