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Wyniki wyszukiwania dla: MACHINE OLFACTION
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Current status of toxoplasmosis vaccine development
PublikacjaToksoplazmoza, choroba wywoływana przez wewnątrzkomórkowego pasożyta Toxoplasma gondii jest szeroko rozpowszechniona na całym świecie. Zarażenie tym pasożytem stanowi bardzo poważny problem medyczny i weterynaryjny, ponieważ jest przyczyną ciężkiej wrodzonej postaci choroby (tzw. toksoplazmozy wrodzonej) oraz poronień, które dotyczą zarówno ludzi jak i zwierząt domowych. Toksoplazmoza może mieć także ciężki przebieg u osób upośledzoną...
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Therapeutic Potential of Multifunctional Tacrine Analogues
PublikacjaTacrine is a potent inhibitor of cholinesterases (acetylcholinesterase and butyrylcholinesterase) that shows limiting clinical application by liver toxicity. In spite of this, analogues of tacrine are considered as a model inhibitor of cholinesterases in the therapy of Alzheimer’s disease. The interest in these compounds is mainly related to a high variety of their structure and biological properties. In the present review, we...
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Identification and non-integer order modelling of synchronous machines operating as generator
PublikacjaThis paper presents an original mathematical model of a synchronous generator using derivatives of fractional order. In contrast to classical models composed of a large number of R-L ladders, it comprises half-order impedances, which enable the accurate description of the electromagnetic induction phenomena in a wide frequency range, while minimizing the order and number of model parameters. The proposed model takes into account...
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Machined Surface Roughness Including Cutter Displacements in Milling of Hardened Teel
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Energy-Saving Inertial Drive for Dual-Frequency Excitation of Vibrating Machines
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Non-Linear Control of Electrical Machines Using Non-Linear Feedback
PublikacjaPrzedstawiono zasady nieliniowego sterowania oraz zastosowanie nielinowego sprzężenia zwrotnego do maszyn elektrycznych. Opisano nieliniowe sterowanie obcowzbudnym silnikiem prądu stałego. Zaprezentowano multiskalarne modele maszyn prądu przemiennego. Maszynę indukcyjną zamodelowano z wykorzystaniem strumienia wirnika oraz z wykorzystaniem strumienia stojana. MMultiskalarne modele maszyny indukcyjnej wykorzystano do nieliniowego...
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Calculations of labyrinth seals with and without diagnostic extraction in fluid-flow machines
PublikacjaLabyrinth seals are essential components of steam turbine unit constructions. Two types of labyrinth seals can be named, the first of which is the seal without diagnostic steam extraction, and the second – with extraction. The distribution of flow parameters along the packing is affected remarkably by the average seal clearance. The presence of diagnostic extraction leads to the equation system which is determinable and can be...
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Scheduling with Complete Multipartite Incompatibility Graph on Parallel Machines: Complexity and Algorithms
PublikacjaIn this paper, the problem of scheduling on parallel machines with a presence of incompatibilities between jobs is considered. The incompatibility relation can be modeled as a complete multipartite graph in which each edge denotes a pair of jobs that cannot be scheduled on the same machine. The paper provides several results concerning schedules, optimal or approximate with respect to the two most popular criteria of optimality:...
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Influence of Honing Parameters on the Quality of the Machined Parts and Innovations in Honing Processes
PublikacjaThe article presents a literature review dealing with the effect of the honing parameters on the quality of the machined parts, as well as with the recent innovations in honing processes. First, an overview about the honing and the plateau-honing processes is presented, considering the main parameters that can be varied during machining. Then, the influence of the honing parameters on surface finish, shape deviation and material...
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Analyses of static displacements of a spindle apllied in typical circular sawing machines
PublikacjaW pracy przedstawiono analizę właściwości statycznych wrzeciona stosowanego w typowych pilarkach tarczowych. Zdefiniowano umowną oś obrotu wrzeciona pilarki tarczowej, która odpowiada geometrycznemu środkowi otworu piły tarczowej. W obliczeniach wyznaczono przemieszczenia umownej osi obrotu wrzeciona, wskaźnik sztywności wrzeciona oraz przemieszczenie poprzeczne piły.
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Modelling electrical machines using bond graphs for mechatronics system applications.
PublikacjaW artykule przedstawiono modelowanie maszyn elektrycznych metodą grafów wiązań dla potrzeb mechatroniki. Omówiono ogólne założenia modelowania maszyn elektrycznych w ujęciu grafów wiązań, bazującego na modelach wzorcowego sprzężenia transformatorowego i elektromechanicznego. Wykorzystując modele tych sprzężeń przedstawiono w ujęciu grafów wiązań model maszyny indukcyjnej w układzie współrzędnych naturalnych stojana. Model opracowano...
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GIS for remote sensing, analysis and visualisation of marine pollution and other marine ecosystem components
PublikacjaW artykule przedstawiono koncepcję oraz prototyp morskiego systemu GIS do zdalnego monitorowania w czasie rzeczywistym zanieczyszczeń środowiska morskiego. System pozwala na gromadzenie i integrowanie danych z różnego rodzaju sensorów, takich jak echosondy jednowiązkowe, sonary boczne i echosondy wielowiązkowe.
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Chip suction system in circular sawing machine: empirical research and computational fluid dynamics numerical simulations
PublikacjaThe experimental analysis of the wood chip removing system during its redesigning in the existing sliding table circular saw and computational fluid dynamic (CFD) numerical simulations of the air flow process is presented in the paper. The attention was focused on the extraction hood and the bottom shelter of the actual existing system. The main aim was to perform experimental research on the pressure distribution inside the...
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Detection of Cystic Fibrosis Symptoms Based on X-Ray Images Using Machine Learning- Pilot Study
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Influence of geometry of iron poles on the cogging torque of a field control axial flux permanent magnet machine
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Control of induction machine supplied by a current source inverter using the multi-scalar transformation and backstepping approach
PublikacjaThe paper describes the voltage control technique of squire-cage induction machines supplied by a current source inverter. The control system is based on new transformation of the electric drive system (machine and inverter) state variables to the multi-scalar variables form. The backstepping approach is used to obtain the feedback control law. The control system contains the structure of the observer...
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Universal Predictors of Dental Students’ Attitudes towards COVID-19 Vaccination: Machine Learning-Based Approach
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Prediction of energy consumption and evaluation of affecting factors in a full-scale WWTP using a machine learning approach
PublikacjaTreatment of municipal wastewater to meet the stringent effluent quality standards is an energy-intensive process and the main contributor to the costs of wastewater treatment plants (WWTPs). Analysis and prediction of energy consumption (EC) are essential in designing and operating sustainable energy-saving WWTPs. In this study, the effect of wastewater, hydraulic, and climate-based parameters on the daily consumption of EC by...
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Prediction of Wastewater Quality at a Wastewater Treatment Plant Inlet Using a System Based on Machine Learning Methods
PublikacjaOne of the important factors determining the biochemical processes in bioreactors is the quality of the wastewater inflow to the wastewater treatment plant (WWTP). Information on the quality of wastewater, sufficiently in advance, makes it possible to properly select bioreactor settings to obtain optimal process conditions. This paper presents the use of classification models to predict the variability of wastewater quality at...
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Control Strategy of a Five-Phase Induction Machine Supplied by the Current Source Inverter With the Third Harmonic Injection
PublikacjaIn the five-phase induction machine (IM), it is possible to better use the electromagnetic circuit than in the three-phase IM. This requires the use of an adequate converter system which will be supplied by an induction machine. The electric drive system described, in this article, includes the five-phase induction machine supplied by the current source inverter (CSI). The proposed novelty—not presented previously—is the control...
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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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Chained machine learning model for predicting load capacity and ductility of steel fiber–reinforced concrete beams
PublikacjaOne of the main issues associated with steel fiber–reinforced concrete (SFRC) beams is the ability to anticipate their flexural response. With a comprehensive grid search, several stacked models (i.e., chained, parallel) consisting of various machine learning (ML) algorithms and artificial neural networks (ANNs) were developed to predict the flexural response of SFRC beams. The flexural performance of SFRC beams under bending was...
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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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Efficient Calibration of Cost-Efficient Particulate Matter Sensors Using Machine Learning and Time-Series Alignment
PublikacjaAtmospheric particulate matter (PM) poses a significant threat to human health, infiltrating the lungs and brain and leading to severe issues such as heart and lung diseases, cancer, and premature death. The main sources of PM pollution are vehicular and industrial emissions, construction and agricultural activities, and natural phenomena such as wildfires. Research underscores the absence of a safe threshold for particulate exposure,...
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Development of an emulation platform for synchronous machine power generation system using a nonlinear functional level model
PublikacjaThe article presents the Power Hardware in the Loop (PHIL) approach for an autonomous power system analysis based on the synchronous generator model incorporating magnetic saturation effects. The model was prepared in the MATLAB/Simulink environment and then compiled into the C language for the PHIL platform implementation. The 150 kVA bidirectional DC/AC commercial-grade converter was used to emulate the synchronous generator....
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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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Machine-Learning-Based Global Optimization of Microwave Passives with Variable-Fidelity EM Models and Response Features
PublikacjaMaximizing microwave passive component performance demands precise parameter tuning, particularly as modern circuits grow increasingly intricate. Yet, achieving this often requires a comprehensive approach due to their complex geometries and miniaturized structures. However, the computational burden of optimizing these components via full-wave electromagnetic (EM) simulations is substantial. EM analysis remains crucial for circuit...
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Ecology In Tribology: Selected Problems of Eliminating Natural Oil-Based Lubricants from Machine Friction Couples
PublikacjaThe elimination of mineral oil-based lubricants from machines has multiple beneficial effects on the natural environment. Firstly – these lubricants are a direct threat to the environment in the event of leaks; secondly – their elimination reduces the demand for crude oil from which they are obtained. In addition, in many cases, e.g. when replacing traditional lubricants with water, friction losses in the bearings can also be reduced...
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Application of fiber optic sensors using Machine Learning algorithms for temperature measurement of lithium-ion batteries
PublikacjaOptical fiber sensorsusing low-coherence interferometry require processing ofthe output spectrum or interferogramto quickly and accurately determine the instantaneous value of the measured quantity, such as temperature.Methods based on machine learning are a good candidate for this application. The application of four such methods in an optical fiber temperature sensoris demonstrated.Using aZnO-coated...
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An algorithm for selecting a machine learning method for predicting nitrous oxide emissions in municipal wastewater treatment plants
PublikacjaThis study presents an advanced algorithm for selecting machine learning (ML) models for nitrous oxide (N2O) emission prediction in wastewater treatment plants (WWTPs) employing the activated sludge process. The examined ML models comprised multivariate adaptive regression spline (MARS), support vector machines (SVM), and extreme gradient boosting (XGboost). The study explores the concept that involves new criteria to select the...
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IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
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Organotin compounds in marine sediments
PublikacjaZwiązki cynoorganiczne są szeroko wykorzystywane w różnych sektorach gospodarki. Farby zawierające czynniki przeciwporostowe (biocydy), były wykorzystywane w ochronie przeciwkorozyjnej kadłubów statków i okrętów, są głównym źródłem emisji trójbutylo- i trójfenylocyny do środowiska morskiego.Międzynarodowa Organizacja Morska (IMO) wprowadziła w roku 2001 powszechny zakaz stosowania tych związków jako biocydów w powłokach malarskich....
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On organic coatings in marine applications
PublikacjaZnaczna liczba konstrukcji eksploatowanych w warunkach morskich ulega zniszczeniu wskutek zmęczeniowego oddziaływania cyklicznych naprężeń mechanicznych. Również w przypadku powłok organicznych chroniących wspomniane konstrukcje obserwuje się przedwczesną degradację zmęczeniową. W poniższym artykule autorzy przedstawiają metodologię oceny wpływu cyklicznych naprężeń mechanicznych na trwałość ochronnych układów powłokowych. Badaniu...
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Determination of tributyltin in marine sediment.
PublikacjaPrzedstawiono wyniki badań międzynarodowego porównawczego, międzylaboratoryjnego oznaczania zawartości tributylocyny w osadzie morskim. Badania były organizowane przez Comite Consultatif pour la Quantite de Matiere (CCQM) pilot study P-18 international intercomparison i była to ich pierwsza część - badania pilotażowe. W badaniach uczestniczyło 11 laboratoriów. Uzyskano zadowalająco zgodne wyniki oznaczeń tributylocyny.
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INTERNATIONAL JOURNAL OF MACHINE TOOLS & MANUFACTURE
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JOURNAL OF MARINE SYSTEMS
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BIOINFO Vaccine Sciences
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Pediatric Infection and Vaccine
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Machinery and Production Engineering
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Machine Learning-Based Wetland Vulnerability Assessment in the Sindh Province Ramsar Site Using Remote Sensing Data
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Integrated Processing: Quality Assurance Procedure of the Surface Layer of Machine Parts during the Manufacturing Step "Diamond Smoothing"
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The Influence of Permanent Magnet Length and Magnet Type on Flux-control of Axial Flux Hybrid Excited Electrical Machine
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Presentation of Novel Architecture for Diagnosis and Identifying Breast Cancer Location Based on Ultrasound Images Using Machine Learning
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Molecular Simulations Using Boltzmann’s Thermally Activated Diffusion - Implementation on ARUZ – Massively-parallel FPGA-based Machine
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A pilot study to assess manufacturing processes using selected point measures of vibroacoustic signals generated on a multitasking machine
PublikacjaThe article presents the method for the evaluation of selected manufacturing processes using the analysis of vibration and sound signals. This method is based on the use of sensors installed outside the machining zone, allowing to be used quickly and reliably in real production conditions. The article contains a developed measurement methodology based on the specific location of microphones and vibration transducers mounted on...
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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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THE EFFECT OF WOOD DRYING METHOD ON THE GRANULARITY OF SAWDUST OBTAINED DURING THE SAWING PROCESS USING THE FRAME SAWING MACHINE
PublikacjaThe experimental results of the study focused on the effect of drying processes of warm air drying at the temperature of 6580°C and warm air-steam mixture drying at the temperature of 105°C of pine and beech wood to the size of sawdust grains created by cutting using RPW 15M frame saw is presented in the paper. Particle size analysis of dry sawdust was performed using two methods - screening method and optical method based on...
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Improving the prediction of biochar production from various biomass sources through the implementation of eXplainable machine learning approaches
PublikacjaExamining the game-changing possibilities of explainable machine learning techniques, this study explores the fast-growing area of biochar production prediction. The paper demonstrates how recent advances in sensitivity analysis methodology, optimization of training hyperparameters, and state-of-the-art ensemble techniques have greatly simplified and enhanced the forecasting of biochar output and composition from various biomass...
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The chemistry, properties and performance of flame-retardant rubber composites: Collecting, analyzing, categorizing, machine learning modeling, and visualizing
PublikacjaRubbers combine the flexibility with mechanical strength, supporting myriad applications, but suffer from inherent flammability. Formulation and production of flame-retardant rubber composites (FRRCs) have intensively been practiced over years, but not comprehensively reviewed. This necessity has outlined collecting, analyzing, screening, classifying, and interpreting the literature with the aim of classifying the FRRCs. We quantified...
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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...