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Search results for: multiphase machine
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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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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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Organotin compounds in marine sediments
PublicationZwiązki 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
PublicationZnaczna 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.
PublicationPrzedstawiono 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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The Influence of Permanent Magnet Length and Magnet Type on Flux-control of Axial Flux Hybrid Excited Electrical Machine
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Molecular Simulations Using Boltzmann’s Thermally Activated Diffusion - Implementation on ARUZ – Massively-parallel FPGA-based Machine
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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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Presentation of Novel Architecture for Diagnosis and Identifying Breast Cancer Location Based on Ultrasound Images Using Machine Learning
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Development of advanced machine learning for prognostic analysis of drying parameters for banana slices using indirect solar dryer
PublicationIn this study, eXtreme Gradient Boosting (XGBoost) and Light Gradient Boosting (LightGBM) algorithms were used to model-predict the drying characteristics of banana slices with an indirect solar drier. The relationships between independent variables (temperature, moisture, product type, water flow rate, and mass of product) and dependent variables (energy consumption and size reduction) were established. For energy consumption,...
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Machine Learning-Based Wetland Vulnerability Assessment in the Sindh Province Ramsar Site Using Remote Sensing Data
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Improving the prediction of biochar production from various biomass sources through the implementation of eXplainable machine learning approaches
PublicationExamining 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
PublicationRubbers 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
PublicationDesigning 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-Based Wetland Vulnerability Assessment in the Sindh Province Ramsar Site Using Remote Sensing Data
PublicationWetlands provide vital ecological and socioeconomic services but face escalating pressures worldwide. This study undertakes an integrated spatiotemporal assessment of the multifaceted vulnerabilities shaping Khinjhir Lake, an ecologically significant wetland ecosystem in Pakistan, using advanced geospatial and machine learning techniques. Multi-temporal optical remote sensing data from 2000 to 2020 was analyzed through spectral...
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Improving platelet‐RNA‐based diagnostics: a comparative analysis of machine learning models for cancer detection and multiclass classification
PublicationLiquid biopsy demonstrates excellent potential in patient management by providing a minimally invasive and cost-effective approach to detecting and monitoring cancer, even at its early stages. Due to the complexity of liquid biopsy data, machine-learning techniques are increasingly gaining attention in sample analysis, especially for multidimensional data such as RNA expression profiles. Yet, there is no agreement in the community...
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A Computationally Efficient Model for Predicting Successful Memory Encoding Using Machine-Learning-based EEG Channel Selection
PublicationComputational 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
PublicationThe 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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A pilot study to assess manufacturing processes using selected point measures of vibroacoustic signals generated on a multitasking machine
PublicationThe 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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1 kapitola: Status report on frame sawing machines for narrow-kerf sawing
PublicationW opracowaniu przedstawiono genezę pilarek ramowych oraz przecinania drewna cienkimi piłami. Omówiono ekonomiczne i ekologiczne zalety tego typu obróbki. Zaprezentowano kinematykę współczesnych pilarek dostępnych na rynkach światowych: Orbit, Mamuth oraz DSG Sonic. Szczegółowo opisano układ napędowy pilarek DTPX-30 i PRW15 z hybrydowym napędem głównym i całkowitym wyrównoważeniem dynamicznym układu.
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A graph coloring approach to scheduling of multiprocessor tasks on dedicated machines with availability constraints
PublicationWe address a generalization of the classical 1- and 2-processor unit execution time scheduling problem on dedicated machines. In our chromatic model of scheduling machines have non-simultaneous availability times and tasks have arbitrary release times and due dates. Also, the versatility of our approach makes it possible to generalize all known classical criteria of optimality. Under these stipulations we show that the problem...
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Makespan minimization of multi-slot just-in-time scheduling on single and parallel machines
PublicationArtykuł podejmuje problem szeregowania zadań przy założeniu podziału czasu na sloty jednakowej długości, gdzie każde z zadań ma ustaloną długość oraz czas jego zakończenia, który jest relatywny do końca slotu. Problem znalezienia uszeregowania polega na dokonaniu przydziału zadań do poszczególnych slotów, przy czym w ogólności długość zadania może wymuszać sytuację, w której zadańie jest realizowane nie tylko w slocie, w którym...
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Hybrid Process Equipment: Improving the Efficiency of the Integrated Metalworking Machines Initial Designing
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An overview of torque meters and new devices development for condition monitoring of mining machines
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Dynamic Analysis of an Enhanced Multi-Frequency Inertial Exciter for Industrial Vibrating Machines
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Cogging torque analysis based on energy approach in surface-mounted PM machines
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Scheduling of unit-length jobs with bipartite incompatibility graphs on four uniform machines
PublicationThe problem of scheduling n identical jobs on 4 uniform machines with speeds s1>=s2>=s3>=s4 is considered.The aim is to find a schedule with minimum possible length. We assume that jobs are subject to mutual exclusion constraints modeled by a bipartite incompatibility graph of degree delta. We show that the general problem is NP-hard even if s1=s2=s3. If, however, delta<5 and s1>12s2 s2=s3=s4, then the problem can be solved to...
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Scheduling of identical jobs with bipartite incompatibility graphs on uniform machines. Computational experiments
PublicationWe consider the problem of scheduling unit-length jobs on three or four uniform parallel machines to minimize the schedule length or total completion time. We assume that the jobs are subject to some types of mutual exclusion constraints, modeled by a bipartite graph of a bounded degree. The edges of the graph correspond to the pairs of jobs that cannot be processed on the same machine. Although the problem is generally NP-hard,...
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Scheduling of unit-length jobs with cubic incompatibility graphs on three uniform machines
PublicationWe consider the problem of scheduling n identical jobs on 3 uniform machines with speeds s1, s2, and s3 to minimize the schedule length. We assume that jobs are subject to some kind of mutual exclusion constraints, modeled by a cubic incompatibility graph. We how that if the graph is 2-chromatic then the problem can be solved in O(n^2) time. If the graph is 3-chromatic, the problem becomes NP-hard even if s1>s2=s3.
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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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Energy Loss Coefficients ki in a Displacement Pump and Hydraulic Motor used in Hydrostatic Drives
PublicationThe article aims at defining and analysing the energy loss coefficients in design solutions of rotating displacement machines, with a piston machine as an example. The energy losses observed in these machines include mechanical loss, volumetric loss, and pressure loss. The scale and relations between these losses in different machines depend on machine design and manufacturing quality, and on operating parameters. The operating...
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Parametric optimization of hybrid metalworking machinery quality
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Analysing media coverage of India's vaccine diplomacy
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On a matching distance between rooted phylogenetic trees
PublicationThe Robinson–Foulds (RF) distance is the most popular method of evaluating the dissimilarity between phylogenetic trees. In this paper, we define and explore in detail properties of the Matching Cluster (MC) distance, which can be regarded as a refinement of the RF metric for rooted trees. Similarly to RF, MC operates on clusters of compared trees, but the distance evaluation is more complex. Using the graph theoretic approach...
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Current Source Inverter Fed Drive
PublicationThis book covers three-phase and multiphase (more than three-phase) motor drives including their control and practical problems faced in the field (e.g., adding LC filters in the output of a feeding converter), are considered. The new edition contains links to Matlab®/Simulink models and PowerPoint slides ideal for teaching and understanding the material contained within the book. Readers will also benefit from the inclusion of: A...
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Gas turbine: advanced marine propulsion.
PublicationPrzedstawiono rys historyczny rozwoju okrętowych turbin gazowych. Omówiono główne problemy zastosowania turbiny gazowej jako głównego silnika okrętowego i współczesne tendencje rozwoju tego napędu.
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Marine and Cosmic Inspirations for AI Algorithms
PublicationArtificial Intelligence (AI) is a scientific area that currently sees an enormous growth. Various new algorithms and methods are developed and many of them meets practical, successful applications. Authors of new algorithms draw different inspirations. Probably the most common one is the nature. For example, Artificial Neural Networks were inspired by the structure of human brain and nervous system while the classic Genetic Algorithm...
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Toward mechanosynthesis of diamondoid structures: V. Silicon as the material of choice for preliminary implementation of intermediate generation of nano-machine systems
PublicationStosując ostatnio wprowadzony przez Drexlera ''moduł skalowany stałą sieciową'' KLM, porównano dwa potencjalne nano-materiały, krzem i diament. Szczegółowe porównanie właściwości fizycznych i chemicznych wykazuje, że krzem może być rozważany jako materiał z wyboru dla pierwotnej implementacji pośredniej generacji nano-systemów.
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Modeling of small molecule's affinity to phospholipids using IAM-HPLC and QSRR approach enhanced by similarity-based machine algorithms
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Prediction of Stress and Deformation Caused by Magnetic Attraction Force in Modulation Elements in a Magnetically Geared Machine Using Subdomain Modeling
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Machine Learning- and Artificial Intelligence-Derived Prediction for Home Smart Energy Systems with PV Installation and Battery Energy Storage
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Sawdust size distribution analysis of thermally modified and unmodified oak wood sawed on the frame sawing machine PRW15-M
PublicationW pracy przedstawiono wyniki analizy granulometrycznej składu wiórów drewna dębowego niemodyfikowanego i modyfikowanego termicznie uzyskanych podczas piłowania na pilarce ramowej PRW15-M z prędkością posuwu 1.67 mmin-1. Otrzymane trociny termicznie modyfikowanego drewna dębowego składają się z wiórów o ziarnistości w przedziale od 44.7 mm do 4.6 mm, podczas gdy dla drewna niemodyfikowanego zaobserwowano zmiany ziarnistości w granicach...
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STUDY IN MECHANICAL FAULT ELEMENT THERMOGRAPHY THROUGH THE MACHINE: The case of deep groove ball bearings of a career without screen.
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Modeling flatness deviation in face milling considering angular movement of the machine tool system components and tool flank wear
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Solvent Screening for Solubility Enhancement of Theophylline in Neat, Binary and Ternary NADES Solvents: New Measurements and Ensemble Machine Learning
PublicationTheophylline, 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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Forecasting energy consumption and carbon dioxide emission of Vietnam by prognostic models based on explainable machine learning and time series
PublicationThis 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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Optical method supported by machine learning for dynamics of C‐reactive protein concentrations changes detection in biological matrix samples
PublicationIn this article we present the novel spectroscopy method supported with machine learning for real-time detection of infectious agents in wastewater. In the case of infectious diseases, wastewater monitoring can be used to detect the presence of inflammation biomarkers, such as the proposed C-reactive protein, for monitoring inflammatory conditions and mass screening during epidemics for early detection in communities of concern,...