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Search results for: MACHINE SYNCHRONE
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Game theory-based virtual machine migration for energy sustainability in cloud data centers
PublicationAs 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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Machine Learning and Text Analysis in an Artificial Intelligent System for the Training of Air Traffic Controllers
PublicationThis 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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A Data Driven Model for Predicting RNA-Protein Interactions based on Gradient Boosting Machine
PublicationRNA protein interactions (RPI) play a pivotal role in the regulation of various biological processes. Experimental validation of RPI has been time-consuming, paving the way for computational prediction methods. The major limiting factor of these methods has been the accuracy and confidence of the predictions, and our in-house experiments show that they fail to accurately predict RPI involving short RNA sequences such as TERRA RNA....
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Forewarned Is Forearmed: Machine Learning Algorithms for the Prediction of Catheter-Induced Coronary and Aortic Injuries
PublicationCatheter-induced dissections (CID) of coronary arteries and/or the aorta are among the most dangerous complications of percutaneous coronary procedures, yet the data on their risk factors are anecdotal. Logistic regression and five more advanced machine learning techniques were applied to determine the most significant predictors of dissection. Model performance comparison and feature importance ranking were evaluated. We identified...
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Road traffic can be predicted by machine learning equally effectively as by complex microscopic model
PublicationSince high-quality real data acquired from selected road sections are not always available, a traffic control solution can use data from software traffic simulators working offline. The results show that in contrast to microscopic traffic simulation, the algorithms employing neural networks can work in real-time, so they can be used, among others, to determine the speed displayed on variable message road signs. This paper describes...
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Polymeric Bearings as a new base isolation system suitable for mitigating machine-induced vibrations
PublicationThe present paper summarizes the preliminary results of the experimental shaking table investigation conducted in order to verify the effectiveness of a new base isolation system consisting of Polymeric Bearings in reducing strong horizontal machine-induced vibrations. Polymeric Bearing considered in the present study is a prototype base isolation system, which was constructed with the use of a specially prepared flexible polymer...
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Load effect impact on the exploitation of concrete machine foundations used in the gas and oil industry
PublicationMachine foundations is a critical topic in the gas and oil industry, which design and exploitation require extensive technical knowledge. Machine foundations are the constructions which are intended for mounting on it a specific type of machine. The foundation has to transfer dynamic and static load from machine to the ground. The primary difference between machine foundations and building foundations is that the machine foundations...
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Advances in Architectures, Big Data, and Machine Learning Techniques for Complex Internet of Things Systems
PublicationTe feld of Big Data is rapidly developing with a lot of ongoing research, which will likely continue to expand in the future. A crucial part of this is Knowledge Discovery from Data (KDD), also known as the Knowledge Discovery Process (KDP). Tis process is a very complex procedure, and for that reason it is essential to divide it into several steps (Figure 1). Some authors use fve steps to describe this procedure, whereas others...
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Performance Analysis of Machine Learning Methods with Class Imbalance Problem in Android Malware Detection
PublicationDue 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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Problems associated with the up of actuating system of a single-disc lapping machine for flat surfaces
PublicationPrzedstawiono wyniki badań nagrzewania się podstawowych elementów układu wykonawczego docierarki jednotarczowej o standardowej kinematyce do obróbki powierzchni płaskich. Analizowano przyrost temperatury zespołu napędowego, rolek i pierścieni prowadzących separatory oraz tarczy docierającej i obrabianych elementów. Badano nagrzewanie się układu obróbkowego podczas wyrównywania żeliwnego narzędzia i docierania powierzchni płaskich....
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Non-Adaptive Rotor Speed Estimation of Induction Machine in an Adaptive Full-Order Observer
PublicationIn the sensorless control system of an induction machine, the rotor speed value is not measured but reconstructed by an observer structure. The rotor speed value can be reconstructed by the classical adaptive law with the integrator. The second approach, which is the main contribution of this paper, is the non-adaptive structure without an integrator. The proposed method of the rotor speed reconstruction is based on an algebraic...
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Multi-criteria Differential Evolution for Optimization of Virtual Machine Resources in Smart City Cloud
PublicationIn a smart city, artificial intelligence tools support citizens and urban services. From the user point of view, smart applications should bring computing to the edge of the cloud, closer to citizens with short latency. However, from the cloud designer point of view, the trade-off between cost, energy and time criteria requires the Pareto solutions. Therefore, the proposed multi-criteria differential evolution can optimize virtual...
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Speed Observer Structure of Induction Machine Based on Sliding Super-Twisting and Backstepping Techniques
PublicationThis paper presents an analysis of the two speed observer structures which are based on the backstepping and sliding super twisting approach. The observer stabilizing functions result from the Lyapunov theorem. To obtain the observer tuning gains the observer structure is linearized near the equilibrium point. The rotor angular speed is obtained from non-adaptive dependence. In the sensorless control system structure the classical...
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Speed observer of induction machine based on backstepping and sliding mode for low‐speed operation
PublicationThis paper presents a speed observer design based on backstepping and slidingmode approaches. The inputs to the observer are the stator current and thevoltage vector components. This observer structure is extended to the integra-tors. The observer stabilizing functions contain the appropriate sliding surfaceswhich result from the Lyapunov function. The rotor angular speed is obtainedfrom the non‐adaptive formula with a sliding...
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Sperm segmentation and abnormalities detection during the ICSI procedure using machine learning algorithms
Publication(1) About 15-20% of couples struggle with the problem of infertility. 30 to 40% of these cases are caused by abnormalities in the structure and motility of sperm. Sometimes the only possibility for such people is to use the procedure of artificial insemination. CASA systems are used to increase the efficiency of this procedure by selecting the appropriate sperm cell. (2) This paper presents an approach to the sperm classification...
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Szymon Racewicz dr inż.
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Machinery for severe climate conditions
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Modes of Failure Analysis in Reinforced Concrete Beam Using Laser Scanning and Synchro-Photogrammetry - How to apply optical technologies in the diagnosis of reinforced concrete elements?
PublicationThe following paper reveal the limitations and possibilities of terrestrial laser scanning technology adaptation in diagnostics of reinforced concrete beams. In this paper, authors present potential spectrum of TLS use in modes of failure analysis of R-C beams and determines under which conditions the laser technologies might be applied. Research was carried out at the Regional Laboratory of Structural Engineering at Gdansk University...
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MECHANISM AND MACHINE THEORY
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Monitoring of Velocity of Manufacturing Machines Subassamblieas by Means of a DAQ System
PublicationArtykuł dotyczy dokładnych cyfrowych pomiarów prędkości ruchu podzespołów maszyn, realizowanych za pomocą enkoderów kwadraturowych, kart licznikowych DAQ oraz dedykowanych aplikacji pomiarowych DAQ. Przedstawiono koncepcje trzech różnych sposobów takiego pomiaru. W pierwszym sposobie, nazywanym ''częstotliwościowym'', pomiar odbywa się poprzez bramkowane zliczanie impulsów enkodera. Drugi sposób nazywany ''czasowym'' polega na...
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The issues of quantum in empirical research on machines and other power systems
PublicationW pracy uzasadniono, że w badaniach naukowych systemów empirycznych, zwłaszcza maszyn jak również i innych urządzeń energetycznych, należy uwzględnić istniejącą w ich eksploatacji przypadkowość i nieprzewidywalność zdarzeń. Nawiązano do osiągnięć mechaniki kwantowej wskazując na wynikający z nich postulat, że wielkości nazywane komplementarnymi, mają istotną własność, która polega na tym, że niemożliwy jest jednoczesny i zarazem...
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Modelling of energy flow in electrical machines. A bond graph approach
PublicationPrzedstawiono w ujęcia grafów wiązań model przepływu energii/mocy w maszynach elektrycznych pracujących w hybrydowych systemach przetwarzania energii. Jako przykład do rozważań przyjęto system napędu trakcyjnego pojazdów hybrydowych.
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Chemical Theory of Machines, basic principles of strength with examples of calculations
PublicationThis book encompasses the essential range of information on technical aspects of mechanical design. It was written primarily for the students and staff of chemistry faculties of technical universities, yet it may also be utilized by everyone, who ether would like to try or already enjoys designing, but cannot take advantage of typical stress & machine construction handbooks. These handbooks often require familiarity with the concepts...
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Vibration surveillance in modern milling machines by the spindle speed control.
PublicationPraca poświęcona jest nadzorowaniu drgań wirujących narzędzi w nowo-czesnych frezarkach. Polega ono na zastosowaniu sterowania programo-wego w układach niestacjonarnych. Dotyczy to zamkniętych układów obra-biarek, kiedy to istotną rolę odgrywają drgania samowzbudne typu chat-ter. Sygnałem sterującym jest chwilowa zmiana prędkości obrotowej. Rozważano frezowanie czołowe smukłym frezem trzpieniowym na pionowym centrum frezarskim....
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Mechatronic design for improve current performences of machines : Chapter 3
PublicationPrzedstawiono wybrane zagadnienia z zakresu projektowania mechatronicznego w zastosowaniu do maszyn służących do transpoetu wibracyjnego w procesie suszenia i do przecinarek ściernicowych. Opisano układy sterowania i optymalizację parametrów technologicznych.
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Reliability of production machines in the bakery industry – theoretical and practical issues
PublicationThe aim of the article is to present probabilistic models, which were then used to analyze the reliability of production machines in the baking industry. The author conducted research in the period from January 2, 2016 to December 31, 2018 regarding the measurement of reliability of a traditional production system based on a probabilistic concept. Due to the limited scope of the article, reliability calculations for a set of thermo-oil...
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Mechines Technologies Materials
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Hybrid Processing: the Impact of Mechanical and Surface Thermal Treatment Integration onto the Machine Parts Quality
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Investigations of methods to measure longitudinal forces in continuous welded rail tracks using the tamping machine.
PublicationPraca przedstawia w sposób poglądowy próby znalezienia efektywnej metody określania sił podłużnych w szynach toru bezstykowego. Szczególną uwagę poświęcono metodzie wymuszonych przemieszczeń poprzecznych. Podstawowym stwierdzeniem z przeprowadzonych własnych badań była konieczność odejścia od podnoszenia odłączonego od podkładów odcinka szyny i skoncentrowanie się na przemieszczeniach poprzecznych; doprowadziło to koncepcji zastosowania...
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Exploring the Solubility Limits of Edaravone in Neat Solvents and Binary Mixtures: Experimental and Machine Learning Study
PublicationThis study explores the edaravone solubility space encompassing both neat and binary dissolution media. Efforts were made to reveal the inherent concentration limits of common pure and mixed solvents. For this purpose, the published solubility data of the title drug were scrupulously inspected and cured, which made the dataset consistent and coherent. However, the lack of some important types of solvents in the collection called...
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Solubility of dapsone in deep eutectic solvents: Experimental analysis, molecular insights and machine learning predictions
PublicationBackground. Dapsone (DAP) is an anti-inflammatory and antimicrobial active pharmaceutical ingredient used to treat, e.g., AIDS-related diseases. However, low solubility is a feature hampering its efficient use. Objectives. First, deep eutectic solvents...
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Perception of Pathologists in Poland of Artificial Intelligence and Machine Learning in Medical Diagnosis—A Cross-Sectional Study
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Modelling of First- and Second-order Chemical Reactions on ARUZ – Massively-parallel FPGA-based Machine
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A novel hybrid adaptive framework for support vector machine-based reliability analysis: A comparative study
PublicationThis study presents an innovative hybrid Adaptive Support Vector Machine - Monte Carlo Simulation (ASVM-MCS) framework for reliability analysis in complex engineering structures. These structures often involve highly nonlinear implicit functions, making traditional gradient-based first or second order reliability algorithms and Monte Carlo Simulation (MCS) time-consuming. The application of surrogate models has proven effective...
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Machine-Learning Methods for Estimating Performance of Structural Concrete Members Reinforced with Fiber-Reinforced Polymers
PublicationIn 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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Predicting seismic response of SMRFs founded on different soil types using machine learning techniques
PublicationPredicting 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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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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Integrating Experience-Based Knowledge Representation and Machine Learning for Efficient Virtual Engineering Object Performance
PublicationMachine 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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Decisional DNA (DDNA) Based Machine Monitoring and Total Productive Maintenance in Industry 4.0 Framework
PublicationThe entire manufacturing spectrum is transforming with the advent of Industry 4.0. The features of Set of Experience Knowledge Structure (SOEKS) and Decisional DNA (DDNA) were utilized for developing Virtual Engineering Objects (VEO), Virtual Engineering Process (VEP) and Virtual Engineering Factory (VEF), which in turn facilitate the creation of smart factories. In this study, DDNA based Machine Monitoring for Total Maintenance...
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Optical method supported by machine learning for urinary tract infection detection and urosepsis risk assessment
PublicationThe study presents an optical method supported by machine learning for discriminating urinary tract infections from an infection capable of causing urosepsis. The method comprises spectra of spectroscopy measurement of artificial urine samples with bacteria from solid cultures of clinical E. coli strains. To provide a reliable classification of results assistance of 27 algorithms was tested. We proved that is possible to obtain...
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Speed estimation of a car at impact with a W-beam guardrail using numerical simulations and machine learning
PublicationThis paper aimed at developing a new method of estimating the impact speed of a passenger car at the moment of a crash into a W-beam road safety barrier. The determination of such a speed based on the accident outcomes is demanding, because often there is no access to full accident data. However, accurate determination of the impact speed is one of the key elements in the reconstruction of road accidents. A machine learning algorithm...
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Computational Complexity and Its Influence on Predictive Capabilities of Machine Learning Models for Concrete Mix Design
PublicationThe design of concrete mixtures is crucial in concrete technology, aiming to produce concrete that meets specific quality and performance criteria. Modern standards require not only strength but also eco-friendliness and production efficiency. Based on the Three Equation Method, conventional mix design methods involve analytical and laboratory procedures but are insufficient for contemporary concrete technology, leading to overengineering...
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Analysis of surface roughness of chemically impregnated Scots pine processed using frame-sawing machine
PublicationThe objective of this work was to evaluate the effect of the impregnation process of pine wood (Pinus sylvestris L.) on roughness parameters of the surface processed on a frame sawing. The samples weredried and impregnated using a commercial procedure by a local company. The touch method withthe use of measuring stylus (pin) was employed to determine of surface roughness of the samplesconsidering parameters, namely, arithmetical...
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Machining process sequencing and machine assignment in generative feature-based CAPP for mill-turn parts
PublicationProcess selection and sequencing, as one of the most complex issues when evaluated from a mathematical point of view and crucial in CAPP, still attract research attention. For the current trend of intelligent manufacturing, machining features (MFs) are the information carriers for workpiece geometry and topology representation. They are basically derived from CAD models and are used by downstream engineering applications. A feature-based...
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Forecasting values of cutting power for the sawing process of impregnated pine wood on band sawing machine
PublicationW artykule przedstawiono prognozowane wartości mocy skrawania dla pilarki taśmowej (ST100R firmy STENNER), które są stosowane w polskich tartakach. Wartości mocy skrawania oszacowano dla drewna sosny zwyczajnej (Pinus sylvestris L.), które zostało poddane impregnacji. Dla porównania wyznaczono również wartości mocy skrawania dla drewna niezaimpregnowanego. Wartości te określono za pomocą innowacyjnej metody prognozowania sił skrawania,...
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Machine Learning Applied to Aspirated and Non-Aspirated Allophone Classification—An Approach Based on Audio "Fingerprinting"
PublicationThe 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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Numerical analysis of chip removing system operation in circular sawing machine using CFD software
PublicationPaper presents the analysis of the results of numerical simulations of the air flow process of wood chips removing system in the circular sawing machine. The attention is focused on the upper cover and bottom shelter of the chip removing system. Within the framework of the work a systematic numerical modeling of the air flow distribution in the cover and shelter during operation of the selected rotational speed of saw blade with...
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The methodology of design of axial clearances compensation unit in hydraulic satellite displacement machine and their experimental verification
PublicationA new methodology of calculating the dimensions of the axial clearance compensation unit in the hydraulic satellite displacement machine is described in this paper. The methods of shaping the compensation unit were also proposed and described. These methods were used to calculate the geometrical dimensions of the compensation field in an innovative prototype of a satellite hydraulic motor. This motor is characterized by the fact...
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Unsupervised machine-learning classification of electrophysiologically active electrodes during human cognitive task performance
PublicationIdentification 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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Machine-Learning-Powered EM-Based Framework for Efficient and Reliable Design of Low Scattering Metasurfaces
PublicationPopularity 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...