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- Publikacje 7127 wyników po odfiltrowaniu
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Wyniki wyszukiwania dla: alternative fuels co-gasification dual-fuel engine machine learning renewable energy optimization
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Solubility of dapsone in deep eutectic solvents: Experimental analysis, molecular insights and machine learning predictions
PublikacjaBackground. 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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Impact of Renewable and Non-Renewable Energy Consumption on the Production of the Agricultural Sector in the European Union
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Impact of Renewable and Non-Renewable Energy Consumption on the Production of the Agricultural Sector in the European Union
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Forewarned Is Forearmed: Machine Learning Algorithms for the Prediction of Catheter-Induced Coronary and Aortic Injuries
PublikacjaCatheter-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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Expert system against machine learning approaches as a virtual sensor for ventricular arrhythmia risk level estimation
PublikacjaRecent advancements in machine learning have opened new avenues for preventing fatal ventricular arrhythmia by accurately measuring and analyzing QT intervals. This paper presents virtual sensor based on an expert system designed to prevent the risk of fatal ventricular arrhythmias associated with QT-prolonging treatments. The expert system categorizes patients into three risk levels based on their electrocardiogram-derived QT...
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Assessment Of the Relevance of Best Practices in The Development of Medical R&D Projects Based on Machine Learning
PublikacjaMachine learning has emerged as a fundamental tool for numerous endeavors within health informatics, bioinformatics, and medicine. However, novices among biomedical researchers and IT developers frequently lack the requisite experience to effectively execute a machine learning project, thereby increasing the likelihood of adopting erroneous practices that may result in common pitfalls or overly optimistic predictions. The paper...
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Power and heat from renewable energy sources on energy market in Poland
PublikacjaPrzedstawiono aktualne uwarunkowania rynków energii w Polsce w odniesieniu do źródeł odnawialnych. Przedstawiono perspektywy rozwojowe. Omówiono wyniki opłacalności budowy małego bloku skojarzonego opalanego słomą.
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Proximal primal–dual best approximation algorithm with memory
PublikacjaWe propose a new modified primal–dual proximal best approximation method for solving convex not necessarily differentiable optimization problems. The novelty of the method relies on introducing memory by taking into account iterates computed in previous steps in the formulas defining current iterate. To this end we consider projections onto intersections of halfspaces generated on the basis of the current as well as the previous...
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Asphalt pavement structure optimization with alternative materials
PublikacjaThe paper briefly describes modern method assessment of the pavement structure based on the simplified viscoelastic continuum damage (S-VECD) model. The method was used to compare two types of pavement structures. There were analysed classical cstructures with asphalt concretes with neat bitumen and innovative one- or two layered structures with SMA 16 with highly polymer modified bitumen (HiMA). Pavement structures using SMA 16...
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Reinforcement Learning Algorithm and FDTD-based Simulation Applied to Schroeder Diffuser Design Optimization
PublikacjaThe aim of this paper is to propose a novel approach to the algorithmic design of Schroeder acoustic diffusers employing a deep learning optimization algorithm and a fitness function based on a computer simulation of the propagation of acoustic waves. The deep learning method employed for the research is a deep policy gradient algorithm. It is used as a tool for carrying out a sequential optimization process the goal of which is...
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OPTIMIZATION OF ENERGY CONVERSION IN GOLD NANOPARTICLES IRRADIATED BY LIGHT FOR SUSTAINABLE ENERGY APPLICATIONED BY LIGHT FOR SUSTAINABLE ENERGY APPLICATION
PublikacjaThis study investigates the optimization of light-to-heat conversion in gold nanoparticles under irradiation by continuous- and pulsed-wave laser sources. The conversion process relies on the absorption of electromagnetic energy and the subsequent generation of heat, a phenomenon that is integral to a variety of applications. The photothermal conversion model is based on the Rayleigh-Drude approximation, facilitating predictions...
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Machine learning-based seismic fragility and seismic vulnerability assessment of reinforced concrete structures
PublikacjaMany studies have been performed to put quantifying uncertainties into the seismic risk assessment of reinforced concrete (RC) buildings. This paper provides a risk-assessment support tool for purpose of retrofitting and potential design strategies of RC buildings. Machine Learning (ML) algorithms were developed in Python software by innovative methods of hyperparameter optimization, such as halving search, grid search, random...
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A machine learning approach to classifying New York Heart Association (NYHA) heart failure
PublikacjaAccording to the European Society of Cardiology, globally the number of patients with heart failure nearly doubled from 33.5 million in 1990 to 64.3 million in 2017, and is further projected to increase dramatically in this decade, still remaining a leading cause of morbidity and mortality. One of the most frequently applied heart failure classification systems that physicians use is the New York Heart Association (NYHA) Functional...
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Modeling and optimization of chemical-treated torrefaction of wheat straw to improve energy density by response surface methodology
PublikacjaToday, torrefaction is important technique for extending the potential of biomass for improvement of energy density. The independent variables investigated for torrefaction study were temperature, retention time, acid concentration, and particle size. The experiment was designed by central composite design (CCD) method using design expert (version 11). The three dependent variables were higher heating value (HHV), energy enhancement...
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Clean energy in the European Union: Transition or evolution?
PublikacjaIn this paper, we analyse two phenomena. First, the relationship between greenhouse gases emission and effectiveness of the European Union energy policies and second the transition from the fossil fuels to renewable energy sources. We run two-step data analysis concerning 25 European Union member states in the period from 1990 to 2018. We use information on greenhouse gases emission, introduction of new energy policies, source...
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COVID-19 severity forecast based on machine learning and complete blood count data
PublikacjaProper triage of COVID-19 patients is a key factor in eective case management, especially with limited and insucient resources. In this paper, we propose a machine-aided diagnostic system to predict how badly a patient with COVID-19 will develop disease. The prognosis of this type is based on the parameters of commonly used complete blood count tests, which makes it possible to obtain data from a wide range of patients.We chose...
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COVID-19 severity forecast based on machine learning and complete blood count data
PublikacjaProper triage of COVID-19 patients is a key factor in eective case management, especially with limited and insucient resources. In this paper, we propose a machine-aided diagnostic system to predict how badly a patient with COVID-19 will develop disease. The prognosis of this type is based on the parameters of commonly used complete blood count tests, which makes it possible to obtain data from a wide range of patients.We chose...
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Renewable Resources for Polyurethanes and Polyurethane Composites: A Review
PublikacjaEach year, more than two million tons of polyurethane is produced in the EU by reacting isocyanates with polyols made from fossil fuel. In addition, there are appreciable quantities of petroleum based functional additives applied in the industry nowadays for both polyols and polyurethane materials. It is therefore of key importance to develop sustainable economically viable polyols with enhanced functionalities, and thereby reducing...
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Forecast of basic fuel prices in imports to Poland (constant prices in USD in 2007)
Dane BadawczeThis dataset presents price growth forecasts for conventional energy sources. It should be noted that the Ministry of Economy forecasts a more than two-fold increase in oil prices (although these forecasts may be greatly underestimated) over 23 years, an almost two-fold increase in natural gas prices and a 40% increase in coal prices.
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Exergy analysis of a negative CO2 emission gas power plant based on water oxy-combustion of syngas from sewage sludge gasification and CCS
PublikacjaA power cycle with water-injected oxy-combustion (water cycle) is investigated by exergy analysis. It is fueled with syngas (aka. producer gas) from gasification of sewage sludge. The cycle is equipped with a spray-ejector condenser (SEC). CO2 is separated and compressed for transportation and storage. The net delivered electric power is 31% of the fuel exergy. The task efficiency is 39% when the flue gas bleed to gasification...
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Optimization of the efficiency of braking energy recovery in rail transport by changing arrival time
PublikacjaThe article refers to the previous work of the authors, in which the model of traffic organization of cooperating trains including the optimization of the use of energy returned to the catenary was presented. In the presented article, the model was modified by changing the main control variable, which affects the efficient use of energy. Departure time was changed for the arrival time of the train to the stop or station. The optimization...
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Optimization of using recuperative braking energy on a double-track railway line
PublikacjaIn the introduction, possible ways of reusing energy from recuperation are presented. Next, the paper investigates the possibility of using regenerative braking in the range allowed by the detailed timetable by adopting the method of transferring the recovered electric energy directly to the catenary and immediate use of this energy by another train at the same power section. In the main part of the work, it is shown, that the...
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Modeling of entrained flow steam gasification of sewage sludge
PublikacjaProper management of sewage sludge becomes increasingly problematic due to legal requirements aiming at diminishing environmental impact, as well as rationalizing the utilization from the point of view of logistics. Steam gasification of sewage sludge can result in very good quality of the producer gas. So far, the works have been focused on the gasification in fixed bed gasifiers. However, this does not allow to take full advantage...
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Optical method supported by machine learning for dynamics of C‐reactive protein concentrations changes detection in biological matrix samples
PublikacjaIn 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,...
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Impact of Renewable and Non-Renewable Energy Consumption and CO2 Emissions on Economic Growth in the Visegrad Countries
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Impact on Economic Growth in the Visegrad Countries of Renewable and Non-Renewable Energy Consumption and CO2 Emissions
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Improving platelet‐RNA‐based diagnostics: a comparative analysis of machine learning models for cancer detection and multiclass classification
PublikacjaLiquid 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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Systemy z Uczeniem Maszynowym / Systems with Machine Learning
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Energy Versus Throughput Optimisation for Machine-to-Machine Communication
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Speed estimation of a car at impact with a W-beam guardrail using numerical simulations and machine learning
PublikacjaThis 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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Road traffic can be predicted by machine learning equally effectively as by complex microscopic model
PublikacjaSince 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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Thermodynamic Cycles of Air Microturbine Power Plants Working on Biomass Fuels
PublikacjaThe gas turbine engine is modified to work as an air turbine set which consists, in the simplest arrangement, of a compressor, a heat exchanger and a turbine. Air is a working medium for both: the compressor and the turbine. This kind of air turbine set can be applied in power plants working on biomass fuels. In this solution we can burn fuels of varying parameters in the external combustion chamber without any harmful effects...
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Cost-Efficient Multi-Objective Design of Miniaturized Microwave Circuits Using Machine Learning and Artificial Neural Network
PublikacjaDesigning microwave components involves managing multiple objectives such as center frequencies, impedance matching, and size reduction for miniaturized structures. Traditional multi-objective optimization (MO) approaches heavily rely on computationally expensive population-based methods, especially when exe-cuted with full-wave electromagnetic (EM) analysis to guarantee reliability. This paper introduces a novel and cost-effective...
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Machine-Learning-Powered EM-Based Framework for Efficient and Reliable Design of Low Scattering Metasurfaces
PublikacjaPopularity of metasurfaces has been continuously growing due to their attractive properties including the ability to effectively manipulate electromagnetic (EM) waves. Metasurfaces comprise optimized geometries of unit cells arranged as a periodic lattice to obtain a desired EM response. One of their emerging application areas is the stealth technology, in particular, realization of radar cross section (RCS) reduction. Despite...
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Machine-learning methods for estimating compressive strength of high-performance alkali-activated concrete
PublikacjaHigh-performance alkali-activated concrete (HP-AAC) is acknowledged as a cementless and environmentally friendly material. It has recently received a substantial amount of interest not only due to the potential it has for being used instead of ordinary concrete but also owing to the concerns associated with climate change, sustainability, reduction of CO2 emissions, and energy consumption. The characteristics and amounts of the...
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Microprocessor system for controlling the operation of renewable energy resources
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Machine learning approach to packaging compatibility testing in the new product development process
PublikacjaThe paper compares the effectiveness of selected machine learning methods as modelling tools supporting the selection of a packaging type in new product development process. The main goal of the developed model is to reduce the risk of failure in compatibility tests which are preformed to ensure safety, durability, and efficacy of the finished product for the entire period of its shelf life and consumer use. This kind of testing...
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FUEL
Czasopisma -
Generalized regression neural network and fitness dependent optimization: Application to energy harvesting of centralized TEG systems
PublikacjaThe thermoelectric generator (TEG) system has attracted extensive attention because of its applications in centralized solar heat utilization and recoverable heat energy. The operating efficiency of the TEG system is highly affected by operating conditions. In a series-parallel structure, due to diverse temperature differences, the TEG modules show non-linear performance. Due to the non-uniform temperature distribution (NUTD) condition,...
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Machine Learning and Text Analysis in an Artificial Intelligent System for the Training of Air Traffic Controllers
PublikacjaThis 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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Renewable energy sources (Archiwizowany 2023-11-02)
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Computational Complexity and Its Influence on Predictive Capabilities of Machine Learning Models for Concrete Mix Design
PublikacjaThe 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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Detection of People Swimming in Water Reservoirs with the Use of Multimodal Imaging and Machine Learning
PublikacjaEvery year in many countries, there are fatal unintentional drownings in different water reservoirs like swimming pools, lakes, seas, or oceans. The existing threats of this type require creating a method that could automatically supervise such places to increase the safety of bathers. This work aimed to create methods and prototype solutions for detecting people bathing in water reservoirs using a multimodal imaging system and...
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Experimental determination of general characteristic of internal combustion engine using mobile test bench connected via Power Take-Off unit
PublikacjaThe general characteristics of the engine include information about the regions of the engine's operating area that are most efficient, where specific fuel consumption reaches the smallest values. Economic operation based on those characteristics can contribute to a significant reduction of fuel consumption and consequently less pollutant emissions and lower costs. The paper presents an experimental method of determination of general...
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A Case Study of Electric Vehicles Load Forecasting in Residential Sector Using Machine Learning Techniques
PublikacjaElectric vehicles (EVs) have been widely adopted to prevent global warming in recent years. The higher installation of Level-1 and Level-2 chargers in residential areas soon poses challenges to the distributed network. However, such challenges can be mitigated through the adoption of smart charging or controlled charging schemes. To facilitate the implementation of smart charging, accurate forecasting of EV charging demand in residential...
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Small Scale Gasification of Biomass and Municipal Wastes for Heat and Electricity Production using HTAG Technology
PublikacjaCombustion and gasification technology utilizing high-cycle regenerative air/steam preheater has drawn increased attention in many application areas. The process is to be realized at temperature level above ash melting point using highly preheated agent. The use of highly preheated media above 900degC provides additional energy to conversion processes and results in considerable...
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Reducing Air Pollutant Emissions from the Residential Sector by Switching to Alternative Energy Sources in Single-Family Homes
PublikacjaThe paper discusses a scenario for adapting residential buildings to the requirements of the EU climate and energy package. It analyzes the option of reducing pollutant emissions to ambient air by switching to alternative energy sources in a typical single-family residential building. The most common sources of energy in central heating and ventilation systems and water heating systems were compared, and the analyzed energy carriers...
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The possibilities of using of the engine multidimensional charakteristics in fuel consumption prediction
PublikacjaDokument przedstawia możliwości prognozowania zużycia paliwa z wykorzystaniem wielowymiarowej charakterystyki zużycia silnika. Zdefiniowane zostały charakterystyki wielowymiarowe silnika.
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Influence of the use of ethanol fuel on selected parameters of the gasoline engine
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A semi-Markov model of fuel combustion process in a Diesel engine
PublikacjaW artykule przedstawiono czterostanowy model procesu spalania w przestrzeniach roboczych (cylindrach) silników o zapłonie samoczynnym w formie procesu semimarkowskiego, dyskretnego w stanach i ciągłego w czasie. Wartościami tego procesu są stany odpowiadające powszechnie akceptowanym rodzajom spalania w tego rodzaju silnikach a mianowicie takie stany procesu jak: spalanie pełne (całkowite i zupełne), spalanie niezupełne, spalanie...