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Search results for: alternative fuels co-gasification dual-fuel engine machine learning renewable energy optimization
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Small Scale Gasification of Biomass and Municipal Wastes for Heat and Electricity Production using HTAG Technology
PublicationCombustion 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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Is it too late now to say we’re sorry? Examining anxiety contagion and crisis communication strategies using machine learning
PublicationIn this paper, we explore the role of perceived emotions and crisis communication strategies via organizational computer-mediated communication in predicting public anxiety, the default crisis emotion. We use a machine-learning approach to detect and predict anxiety scores in organizational crisis announcements on social media and the public’s responses to these posts. We also control for emotional and language tones in organizational...
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Mitigating the Energy Consumption and the Carbon Emission in the Building Structures by Optimization of the Construction Processes
PublicationFor decades, among other industries, the construction sector has accounted for high energy consumption and emissions. As the energy crisis and climate change have become a growing concern, mitigating energy usage is a significant issue. The operational and end of life phases are all included in the building life cycle stages. Although the operation stage accounts for more energy consumption with higher carbon emissions, the...
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ANALYSIS AND OPTIMIZATION OF ELECTRIC VEHICLE CHARGING PROCESSES IN TRANSACTIVE ENERGY SYSTEMS
PublicationThe implementation of smart charging of electric vehicles allows operators of local power networks and electricity suppliers to implement new business models for the interaction of electric vehicles with the network. In addition to the optimal selection of Microgrid capacities when charging electric vehicles, it is also important to use different charging methods. To satisfy the interests of all participants of local systems from...
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A semi-Markov model of fuel combustion process in a Diesel engine
PublicationW 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...
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Influence of the use of ethanol fuel on selected parameters of the gasoline engine
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The influence of fuel type on heat balance of medium-speed engine
PublicationW artykule zaprezentowano analizę wpływu rodzaju zastosowanego paliwa na bilans cieplny silników średnioobrotowych stosowanych w energetyce stacjonarnej. Przedmiotem analizy są silniki ZS i ZI zasilane gazem ziemnym oraz silniki ZS zasilane olejem napędowym. Dodatkowo analizę uzupełniono o wyniki obliczeń wykonanych dla silników dwupaliwowych, tzn. silników, w których zapłon mieszanki paliwowo gazowej realizowany jest przez pilotażowy...
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The possibilities of using of the engine multidimensional charakteristics in fuel consumption prediction
PublicationDokument przedstawia możliwości prognozowania zużycia paliwa z wykorzystaniem wielowymiarowej charakterystyki zużycia silnika. Zdefiniowane zostały charakterystyki wielowymiarowe silnika.
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Infiltration - an alternative method to prepare composites for Solid Oxide Fuel Cells
PublicationPrzedstawiono różne techniki nasączania pozwalające na uzyskanie materiałów o mieszanym przewodnictwie jonowo-elektronowym do zastosowań w tlenkowych ogniwach paliwowych
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Key issues in modeling and optimization of lignocellulosic biomass fermentative conversion to gaseous biofuels
PublicationThe industrial-scale production of lignocellulosic-based biofuels from biomass is expected to benefit society and the environment. The main pathways of residues processing include advanced hydrolysis and fermentation, pyrolysis, gasification, chemical synthesis and biological processes. The products of such treatment are second generation biofuels. The degree of fermentation of organic substances depends primarily on their composition...
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The concept of research on ecological, energy and reliability effects of modified marine fuel oils application to supply compression-ignition engines in real conditions
PublicationWithin the article, basic assumptions of the research project financed by Regional Fund for Environmental Protection and Water in Gdansk were described. The project concerns the experimental investigations carried out on laboratory compression-ignition engine in conditions of its supply with a non-standard marine fuel oil. Configuration and measuring capability of laboratory test bed presently being constructed were introduced....
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Deep eutectic solvents based highly efficient extractive desulfurization of fuels – Eco-friendly approach
PublicationThe developed process is based on alternative, green and cheap solvents for efficient desulfurization of fuels. Several deep eutectic solvents (DESs) were successfully synthesized and studied as extraction solvents for desulfurization of model fuel containing thiophene (T), benzothiophene (BT) and dibenzothiophene (DBT). The most important extraction parameters (i.e. kind of DES, DES: fuel volume ratio, hydrogen bond acceptor:...
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Machine learning-based seismic response and performance assessment of reinforced concrete buildings
PublicationComplexity and unpredictability nature of earthquakes makes them unique external loads that there is no unique formula used for the prediction of seismic responses. Hence, this research aims to implement the most well-known Machine Learning (ML) methods in Python software to propose a prediction model for seismic response and performance assessment of Reinforced Concrete Moment-Resisting Frames (RC MRFs). To prepare 92,400 data...
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Active Annotation in Evaluating the Credibility of Web-Based Medical Information: Guidelines for Creating Training Data Sets for Machine Learning
PublicationMethods Results Discussion References Abbreviations Copyright Abstract Background: The spread of false medical information on the web is rapidly accelerating. Establishing the credibility of web-based medical information has become a pressing necessity. Machine learning offers a solution that, when properly deployed, can be an effective tool in fighting medical misinformation on the web. Objective: The aim of this study is to...
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Optimization of chip removing system operation in circular sawing machine
PublicationThe paper presents the optimization of the wood chips removing system in the sliding table saw. Chips are generated during the cutting of the material. The attention was focused on the upper casing of mentioned system. The methodical experimental studies of the pressure distribution inside the casing during the wood chip removing operation for the selected rotational speed of saw blade with a diameter of 300 mm and 450 mm were...
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Data-Driven Surrogate-Assisted Optimization of Metamaterial-Based Filtenna Using Deep Learning
PublicationIn this work, a computationally efficient method based on data driven surrogate models is pro-posed for the design optimization procedure of a Frequency Selective Surface (FSS)-based filtering antenna (Filtenna). A Filtenna acts as a as module that simultaneously pre-filters unwanted sig-nals, and enhances the desired signals at the operating frequency. However, due to a typically large number of design variables of FSS unit elements,...
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Thermochemical Conversion of Biomass and Municipal Waste into Useful Energy Using Advanced HiTAG/HiTSG Technology
PublicationAn advanced thermal conversion system involving high-temperature gasification of biomass and municipal waste into biofuel, syngas or hydrogen-rich gas is presented in this paper. The decomposition of solid biomass and wastes by gasification is carried out experimentally with a modern and innovative regenerator and updraft continuous gasifier, among others. A ceramic high-cycle regenerator provides extra energy for the thermal conversion...
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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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Multi-criteria Differential Evolution for Optimization of Virtual Machine Resources in Smart City Cloud
PublicationIn a smart city, artificial intelligence tools support citizens and urban services. From the user point of view, smart applications should bring computing to the edge of the cloud, closer to citizens with short latency. However, from the cloud designer point of view, the trade-off between cost, energy and time criteria requires the Pareto solutions. Therefore, the proposed multi-criteria differential evolution can optimize virtual...
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A Decision Support System for the Planning of Hybrid Renewable Energy Technologies
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Sustainability: myth, reality, future–planning and renewable energy management
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Small hydro-power as a source of renewable energy in the European Union
PublicationW pracy przedstawiono udział odnawialnych źródeł energii w produkcji energii elektrycznej w 25 krajach Unii Europejskiej w roku 1997 i przewidywanu udział w roku 2010. Omówiono krótką historię rozwoju małych elektrownii wodnych w UE i dokonano przeglądu małych elektrowni wodnych w krajach UE oraz w wybranych krajach Europy, nie należących do UE. Przedstawiono także możliwy rozwój małej energetyki wodnej w okresie perspektywicznym...
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Geometry optimization of steroid sulfatase inhibitors - the influence on the free binding energy with STS
PublicationIn the paper we review the application of two techniques (molecular mechanics and quantum mechanics) to study the influence of geometry optimization of the steroid sulfatase inhibitors on the values of descriptors coded their chemical structure and their free binding energy with the STS protein. We selected 22 STS-inhibitors and compared their structures optimized with MM+, PM7 and DFT B3LYP/6–31++G* approaches considering separately...
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Detection of circulating tumor cells by means of machine learning using Smart-Seq2 sequencing
PublicationCirculating tumor cells (CTCs) are tumor cells that separate from the solid tumor and enter the bloodstream, which can cause metastasis. Detection and enumeration of CTCs show promising potential as a predictor for prognosis in cancer patients. Furthermore, single-cells sequencing is a technique that provides genetic information from individual cells and allows to classify them precisely and reliably. Sequencing data typically...
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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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Reduced-cost surrogate modeling of input characteristics and design optimization of dual-band antennas using response features
PublicationIn this article, a procedure for low-cost surrogate modeling of input characteristics of dual-band antennas has been discussed. The number of training data required for construction of an accurate model has been reduced by representing the antenna reflection response to the level of suitably defined feature points. The points are allocated to capture the critical features of the reflection characteristic, such as the frequencies...
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Machine-Learning Methods for Estimating Performance of Structural Concrete Members Reinforced with Fiber-Reinforced Polymers
PublicationIn recent years, fiber-reinforced polymers (FRP) in reinforced concrete (RC) members have gained significant attention due to their exceptional properties, including lightweight construction, high specific strength, and stiffness. These attributes have found application in structures, infrastructures, wind power equipment, and various advanced civil products. However, the production process and the extensive testing required for...
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Using Isolation Forest and Alternative Data Products to Overcome Ground Truth Data Scarcity for Improved Deep Learning-based Agricultural Land Use Classification Models
PublicationHigh-quality labelled datasets represent a cornerstone in the development of deep learning models for land use classification. The high cost of data collection, the inherent errors introduced during data mapping efforts, the lack of local knowledge, and the spatial variability of the data hinder the development of accurate and spatially-transferable deep learning models in the context of agriculture. In this paper, we investigate...
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Performance Analysis of Machine Learning Methods with Class Imbalance Problem in Android Malware Detection
PublicationDue to the exponential rise of mobile technology, a slew of new mobile security concerns has surfaced recently. To address the hazards connected with malware, many approaches have been developed. Signature-based detection is the most widely used approach for detecting Android malware. This approach has the disadvantage of being unable to identify unknown malware. As a result of this issue, machine learning (ML) for detecting malware...
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Dual fuelling of truck CI engine with diesel oil and mixture of propane and butane
PublicationW artykule przedstawiono zasadę działania dwupaliwowego zasilania jednocześnie olejem napędowym i odparowanym LPG silnika samochodu ciężarowego. Pokazano korzyści wynikające ze zużycia tańszego paliwa zbadane doświadczalnie.
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Dimensionless Analysis of Stirling Engine using of Optimization Methods
PublicationW pracy zaprezetowano wyniki analizy wpływu parametrów konstrukcyjnych silnika Stirlinga na jego wskaźniki jakości.Analizę przeprowadzono na modelu bezwymiarowym wykorzystując metody optymalizacji parametrycznej.
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TEST FOR ASSESSING THE ENERGY EFFICIENCY OF VEHICLES WITH INTERNAL COMBUSTION ENGINES
PublicationThe most popular method for assessing the energy efficiency of vehicles is to compare the fuel consumption achieved in the conditions of selected approval test. Operating conditions are defined using the speed profiles, usually for only two categories: urban and extra-urban driving. Assessing the energy efficiency of vehicles should be performed using a more detailed classification of conditions. Presented results of comparison...
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Review of Methods for Diagnosing the Degradation Process in Power Units Cooperating with Renewable Energy Sources Using Artificial Intelligence
PublicationThis work is based on a literature review (191). It mainly refers to two diagnostic methods based on artificial intelligence. This review presents new possibilities for using genetic algorithms (GAs) for diagnostic purposes in power plants transitioning to cooperation with renewable energy sources (RESs). The genetic method is rarely used directly in the modeling of thermal-flow analysis. However, this assignment proves that the...
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Analysis of the Influence of Fuel Sulphur Content on Diesel Engine Particulate Emissions
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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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Low temperature rotary Stirling engine: conceptual design and theoretical analysis
PublicationThe use of low-temperature energy sources for electricity generation demands a dual focus: a substantial enhancement in the efficiency of energy conversion devices and a reduction in system production costs. Particularly in scenarios where low-temperature energy sources are scarce, this factor can be pivotal in facilitating widespread adoption of such technologies. The Stirling engine emerges as a promising solution capable of...
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Analyzing Wind Energy Potential Using Efficient Global Optimization: A Case Study for the City Gdańsk in Poland
PublicationWind energy (WE), which is one of the renewable energy (RE) sources for generating electricity, has been making a significant contribution to obtaining clean and green energy in recent years. Fitting an appropriate statistical distribution to the wind speed (WS) data is crucial in analyzing and estimating WE potential. Once the best suitable statistical distribution for WS data is determined, WE potential and potential yield could...
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MACHINE LEARNING–BASED ANALYSIS OF ENGLISH LATERAL ALLOPHONES
PublicationAutomatic classification methods, such as artificial neural networks (ANNs), the k-nearest neighbor (kNN) and selforganizing maps (SOMs), are applied to allophone analysis based on recorded speech. A list of 650 words was created for that purpose, containing positionally and/or contextually conditioned allophones. For each word, a group of 16 native and non-native speakers were audio-video recorded, from which seven native speakers’...
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MACHINE LEARNING SYSTEM FOR AUTOMATED BLOOD SMEAR ANALYSIS
PublicationIn this paper the authors propose a decision support system for automatic blood smear analysis based on microscopic images. The images are pre-processed in order to remove irrelevant elements and to enhance the most important ones - the healthy blood cells (erythrocytes) and the pathologic (echinocytes). The separated blood cells are analyzed in terms of their most important features by the eigenfaces method. The features are the...
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Machine Learning Modelling and Feature Engineering in Seismology Experiment
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PERFORMANCE COMPARISON OF MACHINE LEARNING ALGORITHMS FOR PREDICTIVE MAINTENANCE
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Machine Learning for Sensorless Temperature Estimation of a BLDC Motor
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Machine learning applied to bi-heterocyclic drugs recognition
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Stacking-Based Integrated Machine Learning with Data Reduction
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Data Reduction Algorithm for Machine Learning and Data Mining
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Personal bankruptcy prediction using machine learning techniques
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Machine learning system for estimating the rhythmic salience of sounds.
PublicationW artykule przedstawiono badania dotyczące wyszukiwania danych rytmicznych w muzyce. W pracy przedstawiono postać funkcji rankingujacej poszczególnych dźwięków frazy muzycznej. Opracowano metodę tworzenia wszystkich możliwych hierarchicznych struktur rytmicznych, zwanych hipotezami rytmicznymi. Otrzymane hipotezy są następnie porządkowane w kolejności malejącej wartości funkcji rankingującej, aby ustalić, która ze znalezionych...
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INVESTIGATION OF THE LOMBARD EFFECT BASED ON A MACHINE LEARNING APPROACH
PublicationThe Lombard effect is an involuntary increase in the speaker’s pitch, intensity, and duration in the presence of noise. It makes it possible to communicate in noisy environments more effectively. This study aims to investigate an efficient method for detecting the Lombard effect in uttered speech. The influence of interfering noise, room type, and the gender of the person on the detection process is examined. First, acoustic parameters...
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The use of machine learning for face regions detection in thermograms
PublicationThe aim of this study is to analyse the methods of detecting characteristic points of the face in thermographic images. As part of the implementation an extensive analysis of scientific publications covering similar issues both for the analysis of images made in visible light and thermographic images was carried out. On the basis of this analysis, 3 models were selected and then they were implemented and tested on the basis of...
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Exploring the Solubility Limits of Edaravone in Neat Solvents and Binary Mixtures: Experimental and Machine Learning Study
PublicationThis study explores the edaravone solubility space encompassing both neat and binary dissolution media. Efforts were made to reveal the inherent concentration limits of common pure and mixed solvents. For this purpose, the published solubility data of the title drug were scrupulously inspected and cured, which made the dataset consistent and coherent. However, the lack of some important types of solvents in the collection called...