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Search results for: cnc machines
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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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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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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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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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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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Generative Process Planning with Reasoning based on Geometrical Product Specification
PublicationThe focus of this paper is on computer aided process planning for parts manufacture in systems of definite process capabilities, involving the use of multi-axis machining centers for parts shaping and grinding machines for finishing. It presents in particular a decision making scheme for setup determination as a part of generative process planning. The planning procedurę consists of two stages. The first stage is associated with...
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A method of Functional Test interval selection with regards to Machinery and Economical aspects
PublicationThis paper discusses the problem of choosing the optimal frequency of functional test, including the reliability calculations and production efficiency, but also the effect of company risk management. The proof test as a part of the functional test interval is well described for the process industry. Unfortunately, this situation is not the case for the machinery safety functions with low demand mode. Afterwards, it is presented...
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Budowa rurociągu ciśnieniowego przy użyciu nowych rur CC-GRP
PublicationAnaliza zastosowań rur GRP do budowy przewodów ciśnieniowych. Przydatność duroplastów do budowy kanalizacji tłocznej i sieci wodociągowych. Przyklady rozwiązań.
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Effect of the Relative Position of the Face Milling Tool towards the Workpiece on Machined Surface Roughness and Milling Dynamics
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Analysis of specific cutting resistance while cutting frozen pine blocks with narrow-kerf stellite tipped saws on frame sawing machines.
PublicationPrzedstawiono wyniki analizy oporów skrawania drewna zmrożonego podczas przecierania pryzm sosnowych na pilarce ramowej za pomocą cienkich pił. Badania prowadzono dla temperatur drewna -5 st. C, -20 st. C oraz dla porównania w temperaturze +18 st. C. Wilgotność drewna wynosiła 30%. Zaobserwowano znaczacy wzrost oporów skrawania wraz ze spadkiem jego temperatury.
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Hydrostatic drives as safe and energy saving machines. The drive investigation method compatible diagram of power increase opposite to the direction of power flow
PublicationProjektanci i producenci napędu hydrostatycznego nie dysponują możliwością dokładnego określania jego sprawności energetycznej zmieniającej się szeroko w polu pracy napędzanego urządzenia a więc w pełnym zakresie zmiany prędkości i obciążenia silnika hydraulicznego oraz lepkości zastosowanego czynnika roboczego. Dotyczy to zarówno określania strat i sprawności maszyn wyporowych (pompy i silnika hydraulicznego) zastosowanych w układzie...
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An assessment of regulated emissions and CO2 emissions from a European light-duty CNG-fueled vehicle in the context of Euro 6 emissions regulations
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Detection of Cystic Fibrosis Symptoms Based on X-Ray Images Using Machine Learning- Pilot Study
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Machine-Learning-Based Global Optimization of Microwave Passives with Variable-Fidelity EM Models and Response Features
PublicationMaximizing 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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Efficient Calibration of Cost-Efficient Particulate Matter Sensors Using Machine Learning and Time-Series Alignment
PublicationAtmospheric 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
PublicationThe 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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Chained machine learning model for predicting load capacity and ductility of steel fiber–reinforced concrete beams
PublicationOne 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
PublicationAir 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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Application of fiber optic sensors using Machine Learning algorithms for temperature measurement of lithium-ion batteries
PublicationOptical 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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Seismic response and performance prediction of steel buckling-restrained braced frames using machine-learning methods
PublicationNowadays, 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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Influence of geometry of iron poles on the cogging torque of a field control axial flux permanent magnet machine
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Universal Predictors of Dental Students’ Attitudes towards COVID-19 Vaccination: Machine Learning-Based Approach
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Control of induction machine supplied by a current source inverter using the multi-scalar transformation and backstepping approach
PublicationThe 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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Control Strategy of a Five-Phase Induction Machine Supplied by the Current Source Inverter With the Third Harmonic Injection
PublicationIn 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
PublicationMachine 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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Prediction of energy consumption and evaluation of affecting factors in a full-scale WWTP using a machine learning approach
PublicationTreatment 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
PublicationOne 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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Chip suction system in circular sawing machine: empirical research and computational fluid dynamics numerical simulations
PublicationThe 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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Ecology In Tribology: Selected Problems of Eliminating Natural Oil-Based Lubricants from Machine Friction Couples
PublicationThe 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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An algorithm for selecting a machine learning method for predicting nitrous oxide emissions in municipal wastewater treatment plants
PublicationThis 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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Prediction of Overall In Vitro Microsomal Stability of Drug Candidates Based on Molecular Modeling and Support Vector Machines. Case Study of Novel Arylpiperazines Derivatives
PublicationOther than efficacy of interaction with the molecular target, metabolic stability is the primary factor responsible for the failure or success of a compound in the drug development pipeline. The ideal drug candidate should be stable enough to reach its therapeutic site of action. Despite many recent excellent achievements in the field of computational methods supporting drug metabolism studies, a well-recognized procedure to model...
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The forecasted values of cutting power for sawing on band sawing machines for Polish Scots pine wood (Pinus sylvestris L.) in a function of its provenance.
PublicationIn this paper the predicted values of cutting power for band sawing machine (EB 1800, f. EWD), which is used in the Polish sawmills, were showed. The values of cutting power were forecasted for Scots pine (Pinus sylvestris L.) wood of five provenances from Poland. These values were determined using an innovative method of predicting the cutting power, which takes into account of elements of fracture mechanics. The resulting predictions...
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A Comparison of Ammonia Emission Factors from Light-Duty Vehicles Operating on Gasoline, Liquefied Petroleum Gas (LPG) and Compressed Natural Gas (CNG)
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Regulated and Unregulated Exhaust Emissions from CNG Fueled Vehicles in Light of Euro 6 Regulations and the New WLTP/GTR 15 Test Procedure
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Modelling of SO2 and NOx Emissions from Coal and Biomass Combustion in Air-Firing, Oxyfuel, iG-CLC, and CLOU Conditions by Fuzzy Logic Approach
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Liposomal cytarabine in the prophylaxis and treatment of CNS lymphoma: toxicity analysis in a retrospective case series study conducted at Polish Lymphoma Research Group Centers
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Kapilarna chromatografia gazowa fazy nad-powierzchniowej – HS-CGC w badaniach składu lotnych produktów hydrolizy biomasy ligno-celulozowej – BMLC
PublicationW pracy przedstawiono sposoby obróbki biomasy ligno-celulozowej, których celem jest rozpulchnienie struktury surowca i zwiększenie dostępności struktur dla czynników hydrolizujących. Na podstawie przeglądu literatury wskazano na możliwe do zidentyfikowania związki obecne w hydrolizatach z biomasy ligno-celulozowej. Opracowano metodykę oraz zbadano możliwość oznaczania lotnych produktów hydrolizy chemicznej z wykorzystaniem techniki...
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Toxicity of the New Psychoactive Substance (NPS) Clephedrone (4-Chloromethcathinone, 4-CMC): Prediction of Toxicity Using In Silico Methods for Clinical and Forensic Purposes
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The Perception and Attitudes toward COVID-19 Vaccines: A Cross-Sectional Study in Poland
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Cost minimization of locating construction machinery park with the use of simulation and optimization algorithms
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Active Control of Highly Autocorrelated Machinery Noise in Multivariate Nonminimum Phase Systems
PublicationIn this paper, a novel multivariate active noise control scheme, designed to attenuate disturbances with high autocorrelation characteristics and preserve background signals, is proposed. The algorithm belongs to the class of feedback controllers and, unlike the popular feedforward FX-LMS approach, does not require availability of a reference signal. The proposed approach draws its inspiration from the iterative learning control...
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Maritime Communication and Sea Safety of the Future - Machnine-type 5G Communication Concept
PublicationThe article presents the concept of a system based on 5G network and M2M communication increasing maritime safety. Generally, the focus was on presenting a proposal for a hierarchical, hybrid, cooperative system with M2M communication coordinated with BAN networks. The possi-ble applications of M2M communication at sea were also presented.
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HCI-Based Wireless System for Measuring the Concentration of Mining Machinery and Equipment Operators
PublicationMaintaining stable and reliable working conditions is a matter of vital importance for various companies, especially those involving heavy machinery. Due to human exhaustion, as well as unpredicted hazards and dangerous situations, the personnel has to take actions and wisely plan each move. This paper presents a human–computer interaction (HCI)-based system that uses a concentration level measurement function to increase the safety...
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Selected problems of planning machinery and devices location in a ship´s engine room.
PublicationPrzedstawiono podstawowe zasady rozplanowania maszyn i urządzeń w przedziale maszynowym na statku. Podano warunki i kryteria wpływające na proces projektowania rozmieszczenia maszyn i urządzeń w siłowni. Przedstawiono główne warunki i zasady dotyczące rozplanowania głównego układu napędowego, elektrowni, kotłowni pomocniczych oraz innych instalacji siłownianych.
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Formation of CN (B2Σ+) radicals in the vacuum-ultraviolet photodissociation of pyridine and pyrimidine molecules
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Formation of CN (B2∑+) radicals in the vacuum-ultraviolet photodissociation of pyridine and pyrimidine molecules
PublicationFormation of the excited CN(B2∑+) free radicals in the photodissociation of pyridine (C5H5N) and pyrimidine (C4H4N2) molecules was investigated over the energy ranges 16–27 and 14.7–25 eV, respectively. Photon-induced fluorescence spectroscopy was applied to detect the vibrationally and rotationally excited CN radicals by recording the B2∑+→X2∑+ emission bands (violet system). The measured dissociation yield curves demonstrate...