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Wyniki wyszukiwania dla: TURBINE LINEAR REGRESSION MACHINE LEARNING OPTIMIZATION ORC
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SZACOWANIE ZAWARTOŚCI BENZO(a)PIRENU W PYLE ZAWIESZONYM PM10 W AGLOMERACJI TRÓJMIEJSKIEJ ZA POMOCĄ WIELOWYMIAROWEJ REGRESJI LINIOWEJ=ESTIMATION OF BENZO(A)PYRENE CONTENT IN SUSPENDED DUST PM10 IN TRI-CITY AGGLOMERATION USING MULTIDIMENSIONAL LINEAR REGRESSION
PublikacjaW pracy przedstawiono próbę oszacowania przy pomocy wielowymiarowej regresji liniowej modelu empirycznego opisującego czynniki wpływające na zawartość B(a)P w pyle zawieszonym PM10 w Aglomeracji Trójmiejskiej w latach 2008-2011. Na przestrzeni tych lat średnioroczne stężenie B(a)P w PM10 wzrosło ponad dwukrotnie i ponad trzykrotnie przewyższa poziom docelowy. Z przeprowadzonych analiz wynika, że główną przyczyną wzrostu stężenia...
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Multi-criteria Differential Evolution for Optimization of Virtual Machine Resources in Smart City Cloud
PublikacjaIn 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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Machine Learning Applied to Aspirated and Non-Aspirated Allophone Classification—An Approach Based on Audio "Fingerprinting"
PublikacjaThe purpose of this study is to involve both Convolutional Neural Networks and a typical learning algorithm in the allophone classification process. A list of words including aspirated and non-aspirated allophones pronounced by native and non-native English speakers is recorded and then edited and analyzed. Allophones extracted from English speakers’ recordings are presented in the form of two-dimensional spectrogram images and...
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Perception of Pathologists in Poland of Artificial Intelligence and Machine Learning in Medical Diagnosis—A Cross-Sectional Study
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Universal Predictors of Dental Students’ Attitudes towards COVID-19 Vaccination: Machine Learning-Based Approach
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Detection of Cystic Fibrosis Symptoms Based on X-Ray Images Using Machine Learning- Pilot Study
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Efficient Calibration of Cost-Efficient Particulate Matter Sensors Using Machine Learning and Time-Series Alignment
PublikacjaAtmospheric particulate matter (PM) poses a significant threat to human health, infiltrating the lungs and brain and leading to severe issues such as heart and lung diseases, cancer, and premature death. The main sources of PM pollution are vehicular and industrial emissions, construction and agricultural activities, and natural phenomena such as wildfires. Research underscores the absence of a safe threshold for particulate exposure,...
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Prediction of Wastewater Quality at a Wastewater Treatment Plant Inlet Using a System Based on Machine Learning Methods
PublikacjaOne of the important factors determining the biochemical processes in bioreactors is the quality of the wastewater inflow to the wastewater treatment plant (WWTP). Information on the quality of wastewater, sufficiently in advance, makes it possible to properly select bioreactor settings to obtain optimal process conditions. This paper presents the use of classification models to predict the variability of wastewater quality at...
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Guest editorial: learning, scheduling, resource optimization, and evolution in smart artificial systems: challenges and support
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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
PublikacjaIn 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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A Computationally Efficient Model for Predicting Successful Memory Encoding Using Machine-Learning-based EEG Channel Selection
PublikacjaComputational cost is an important consideration for memory encoding prediction models that use data from dozens of implanted electrodes. We propose a method to reduce computational expense by selecting a subset of all the electrodes to build the prediction model. The electrodes were selected based on their likelihood of measuring brain activity useful for predicting memory encoding better than chance (in terms of AUC). A logistic...
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Machine Learning- and Artificial Intelligence-Derived Prediction for Home Smart Energy Systems with PV Installation and Battery Energy Storage
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Machine Learning Algorithm-Based Tool and Digital Framework for Substituting Daylight Simulations In Early- Stage Architectural Design Evaluation
PublikacjaThe aim of this paper is to examine the new method of obtaining the simulation-based results using backpropagation of errors artificial neural networks. The primary motivation to conduct the research was to determine an alternative, more efficient and less timeconsuming method which would serve to achieve the results of daylight simulations. Three daylight metrics: Daylight Factor, Daylight Autonomy and Daylight Glare Probability have...
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Personalized prediction of the secondary oocytes number after ovarian stimulation: A machine learning model based on clinical and genetic data
PublikacjaControlled ovarian stimulation is tailored to the patient based on clinical parameters but estimating the number of retrieved metaphase II (MII) oocytes is a challenge. Here, we have developed a model that takes advantage of the patient’s genetic and clinical characteristics simultaneously for predicting the stimulation outcome. Sequence variants in reproduction-related genes identified by next-generation sequencing were matched...
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Analysis of pedestrian activity before and during COVID-19 lockdown, using webcam time-lapse from Cracow and machine learning
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Determinants of anxiety levels among young males in a threat of experiencing military conflict–Applying a machine-learning algorithm in a psychosociological study
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Machine-learning-based precise cost-efficient NO2 sensor calibration by means of time series matching and global data pre-processing
PublikacjaAir pollution remains a considerable contemporary challenge affecting life quality, the environment, and economic well-being. It encompasses an array of pollutants—gases, particulate matter, biological molecules—emanating from sources such as vehicle emissions, industrial activities, agriculture, and natural occurrences. Nitrogen dioxide (NO2), a harmful gas, is particularly abundant in densely populated urban areas. Given its...
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Statistical Data Pre-Processing and Time Series Incorporation for High-Efficacy Calibration of Low-Cost NO2 Sensor Using Machine Learning
PublikacjaAir pollution stands as a significant modern-day challenge impacting life quality, the environment, and the economy. It comprises various pollutants like gases, particulate matter, biological molecules, and more, stemming from sources such as vehicle emissions, industrial operations, agriculture, and natural events. Nitrogen dioxide (NO2), among these harmful gases, is notably prevalent in densely populated urban regions. Given...
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Example of Using Particle Swarm Optimization Algorithm with Nelder–Mead Method for Flow Improvement in Axial Last Stage of Gas–Steam Turbine
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The dynamic performance analysis of the Micro-turbine's rotor supparted on slide and roling element bearings
PublikacjaThis article presents the results of investigations of dynamic characteristics of a small-dimension rotor with slide and rolling element bearings. The object of investigations was the rotor-bearing system designed for the ORC based low-power steam micro-turbine. The investigations were performed using MESWIR series programs, as well as commercial FEA software ABAQUS and MADYN 2000. The results of modal analysis of the micro-rotor...
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Looking for a minimum exergy destruction in hierarchical cycle
PublikacjaThe paper presents results of energy analysis, complemented with an exergy balance, of hierarchical thermodynamic cycle. Proposed cycle is a binary vapour cycle based on a model of real supercritical steam power plant. Energy analysis is used to preliminary optimization of the cycle and the exergy losses analysis is proposed to perform optimization of heat transfer processes, which are essential for hierarchical cycles. Proposed...
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Management of low-temperature heat source by ORC aided by additional heat source
PublikacjaThe presented work is aimed at utilisation of waste heat in the manner to produce electricity in ORC installation. Therefore the precondition of the study was to use the waste heat available in the form of a stream of hot water at 90°C. Such low enthalpy heat source is rather insufficient to produce a good quality vapour to feed the ORC turbine. That was the incentive to search for the ways of increasing the temperature of the...
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Combined operation of 900MW power plant with the ORC through the bleed steam extraction point and CO2 recovery system
PublikacjaThe work presented here is aimed at utylisation of waste heat in the reference supercritical power plant in the manner to produce electricity in ORC installation. The waste heat is available in the form of a stream of hot water at 90 C, recovered from the exhaust gases in the amount of 200MW. Such low enthalpy heat source is rather insufficient to produce a good quality vapour to feed the ORC turbine. Therefore an original approach...
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A commercial gas boiler fitted with the ORC module as perspective solution for households
PublikacjaIn this paper the applicability of the commercial gas boiler (De Dietrich DTG X23N) coupled with the laboratory prototype micro ORC setup was experimentally studied. The main objective was to determine the working fluid capability to obtain required temperatures of vapour prior to the turbine, attainable heat rates and efficiencies of the whole system. The boiler thermal power was 25 kW. Tests were carried out with a single stage...
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Organic Supercritical Thermodynamic Cycles with Isothermal Turbine
PublikacjaOrganic Rankine cycles (ORC) are quite popular, but the overall efficiencies of these plants are rather very low. Numerous studies have been conducted in many scientific centers and research centers to improve the efficiency of such cycles. The research concerns both the modification of the cycle and the increase in the parameters of the medium at the inlet to the turbine. However, the efficiency of even these modified cycles rarely...
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Method of selecting the LS-SVM algorithm parameters in gas detection process
PublikacjaIn this paper we showed the method of resistive gas sensors data processing. The UV irradiation and temperature modulation was applied to improve gas sensors’ selectivity and sensitivity. Noise voltage across the sensor’s terminals (proportional to its resistance fluctuations) was recorded to estimate power spectral density. This function was an input data vector for LS-SVM (least squares – support vector machine) algorithm, which...
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When Neural Networks Meet Decisional DNA: A Promising New Perspective for Knowledge Representation and Sharing
PublikacjaABSTRACT In this article, we introduce a novel concept combining neural network technology and Decisional DNA for knowledge representation and sharing. Instead of using traditional machine learning and knowledge discovery methods, this approach explores the way of knowledge extraction through deep learning processes based on a domain’s past decisional events captured by Decisional DNA. We compare our approach with kNN (k-nearest...
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Assessment, optimisation and working fluid comparison of organic rankine cycle combined with negative CO2 gas power plant system
PublikacjaThis study aims to investigate the application of the Organic Rankine Cycle (ORC) as an alternative to low-pressure expansion in the negative CO2 power plant (nCO2PP). The reason for this study is that a detailed analysis of nCO2PP indicates a certain amount of waste heat present in the exhaust gas from the high-to-intermediate pressure gas turbine. Some of this energy can be used by the application of the expansion in a low-pressure...
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Organic Rankine as bottoming cycle to a combined Brayton and Clausius-Rankine cycle
PublikacjaThis paper presents an enhanced approach, as it will be considered here that the ORC installation could be extra-heated with the bleed steam, a concept presented by the authors. In such way the efficiency of the bottoming cycle can be increased and an amount of electricity generated increases. A thermodynamic analysis and a comparative study of the cycle efficiency for a simplified steam cycle cooperating with ORC cycle will be...
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Computing methods for fast and precise body surface area estimation of selected body parts
PublikacjaCurrently used body surface area (BSA) formulas give satisfactory results only for individuals with typical physique, while for elderly, obese or anorectic people accurate results cannot be expected. Particularly noteworthy are the results for individuals with severe obesity (body-mass index greater than 35 kg/m2), for which BSA estimation errors reached 80%. The main goal of our study is the development of precise BSA models for...
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Operation of the 900 MW power plant with the ORC supplied from three heat sources
PublikacjaThe chapter is aimed at utilisation of waste heat in the reference supercritical power plant in the manner to produce electricity in ORC installation. The waste heat is available in the form of a stream of hot water at 90°C, recovered from the exhaust gases in the amount of 200MW. Such low enthalpy heat source is rather insufficient to produce a good quality vapour to feed the ORC turbine. Therefore an original approach to increase...
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Buried Object Characterization Using Ground Penetrating Radar Assisted by Data-Driven Surrogate-Models
PublikacjaThis work addresses artificial-intelligence-based buried object characterization using 3-D full-wave electromagnetic simulations of a ground penetrating radar (GPR). The task is to characterize cylindrical shape, perfectly electric conductor (PEC) object buried in various dispersive soil media, and in different positions. The main contributions of this work are (i) development of a fast and accurate data driven surrogate modeling...
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Selected aspects of performance of organic Rankine cycles incorporated into bioenergy with carbon capture and storage using gasification of sewage sludge
PublikacjaThe study aims to investigate the application of the Organic Rankine Cycle (ORC) in the bioenergy with carbon capture and storage (BECCS) using gasification of sewage sludge. The tool used in the investigation is the Aspen Plus software with REFPROP property methods for calculating fluid properties. The reason for this study is that a detailed analysis of the proposed BECCS process flow diagram indicates that a certain amount of...
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Increase of power and efficiency of the 900 MW supercritical power plant through incorporation of the ORC
PublikacjaThe objective of the paper is to analyse thermodynamical and operational parameters of the supercritical power plant with reference conditions as well as following the introduction of the hybrid system incorporating ORC. In ORC the upper heat source is a stream of hot water from the system of heat recovery having temperature of 90 °C, which is additionally aided by heat from the bleeds of the steam turbine. Thermodynamical analysis...
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Subcritical Thermodynamic Cycles with Organic Medium and Isothermal Expansion
PublikacjaThe efffciencies of the Organic Rankine Cycle (ORC) are not very high and only very seldom do they exceed 20%. The increase and optimization of initial parameters and certain modifications of the thermodynamic cycle make it possible to overcome these drawbacks. A new modified cycle has been described and analyzed in detail in the paper. Similarly to the Ericsson cycle for gas turbines, isothermal expansion in the turbine is suggested...
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Data-driven models for fault detection using kernel pca:a water distribution system case study
PublikacjaKernel Principal Component Analysis (KPCA), an example of machine learning, can be considered a non-linear extension of the PCA method. While various applications of KPCA are known, this paper explores the possibility to use it for building a data-driven model of a non-linear system-the water distribution system of the Chojnice town (Poland). This model is utilised for fault detection with the emphasis on water leakage detection....
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From Linear Classifier to Convolutional Neural Network for Hand Pose Recognition
PublikacjaRecently gathered image datasets and the new capabilities of high-performance computing systems have allowed developing new artificial neural network models and training algorithms. Using the new machine learning models, computer vision tasks can be accomplished based on the raw values of image pixels instead of specific features. The principle of operation of deep neural networks resembles more and more what we believe to be happening...
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Bayesian Optimization for solving high-frequency passive component design problems
PublikacjaIn this paper, the performance of the Bayesian Optimization (BO) technique applied to various problems of microwave engineering is studied. Bayesian optimization is a novel, non-deterministic, global optimization scheme that uses machine learning to solve complex optimization problems. However, each new optimization scheme needs to be evaluated to find its best application niche, as there is no universal technique that suits all...
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Management of low-temperature heat source by ORC aided by additional heat source
PublikacjaIn the paper presented is a concept to utilize waste heat from the power plant with the aid of the low-temperature ORC cycle. The ORC system is heated from two heat sources, the first one being the flow rate of waste heat obtained from the exhaust gases. Subsequently, the working fluid in the cycle is additionally heated by the condensing steam from the low pressure turbine extraction points increasing in such way the level of...
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Utilisation of waste heat from the power plant by use of the ORC aided with bleed steam and extra source of heat
PublikacjaUtilization of waste heat recovered from the exhaust gases of the power generation unit by means of ORC (organic Rankine cycles) installation is considered. The waste heat is available in the form of a stream of hot water having temperature of 90 stC in the amount of 200 MWt. To increase evaporation temperaturę of ORC working fluid the heat of steam from the extraction points from the low-pressure part of steam turbine is used....
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Buried Object Characterization by Data-Driven Surrogates and Regression-Enabled Hyperbolic Signature Extraction
PublikacjaThis work addresses artificial-intelligence-based buried object characterization using FDTD-based electromagnetic simulation toolbox of a Ground Penetrating Radar (GPR) to generate B-scan data. In data collection, FDTD-based simulation tool, gprMax is used. The task is to estimate geophysical parameters of a cylindrical shape object of various radii, buried at different positions in the dry soil medium simultaneously and independently...
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Introduction to the ONDM 2022 special issue
PublikacjaThis JOCN special issue contains extended versions of selected papers presented at the 26th International Conference on Optical Network Design and Modeling (ONDM 2022), which took place 16–19 May 2022 at Warsaw University of Technology, Warsaw, Poland. The topics covered by the papers represent trends in optical networking research: application of machine learning to network management, cross-layer network performance optimization,...
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Dynamic state assessment of the water turbine with the power of 600 kW
PublikacjaThe article discusses the results of experimental studies to assess the dynamic state of the turbine set with the Kaplan turbine. The dynamic assessment was made on the basis of appropriate standards, based on the measurement results of selected parameters of vibration, which have been measured for several states of the machine load. In addition, we attempted to identify the causes of the increased vibration levels based on the...
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Possibilities of Increasing the Overall Efficiency of Gas-steam CHP Microplant
PublikacjaThe paper presents ways to increase the efficiency of a gas-steam micro power plant by modifying the cycle combination. The modification consists in partial release of the fluid downstream of the gas turbine and using it for ORC fluid overheating and evaporation. Advantages of this solution over the simplest gas and steam cycles’ combination are demonstrated.
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Advanced Turbine Cycles with Organic Media
PublikacjaOrganic Rankine Cycle (ORC) power plants have become very popular and have found their applications in systems with renewable sources of energy. So far their overall efficiencies are not very impressive and only for the upper temperature of about 300 °C do they exceed 20%. A drawback of these cycles is the limitation of the cycle upper temperature due to the heat exchanger technology and the materials used. However, it is possible...
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Organic Rankine cycle as bottoming cycle to a combined Brayton and Clausius - Rankine cycle
PublikacjaA preliminary evaluation has been made of a possibility of bottoming of a conventional Brayton cycle cooperating with the CHP power plant with the organic Rankine cycle installation. Such solution contributes to the possibility of annual operation of that power plant, except of operation only in periods when there is a demand for the heat. Additional benefit would be the fact that an optimized backpressure steam cycle has the advantage...
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Globalized Parametric Optimization of Microwave Passive Components Using Simplex-Based Surrogates
PublikacjaOptimization-based parameter adjustment involving full-wave electromagnetic (EM) simulation models is a crucial stage of present-day microwave design process. In fact, rigorous optimization is the only reliable mean permitting to simultaneously handle multiple geometry/material parameters, objectives, and constraints. Unfortunately, EM-driven design is a computationally intensive endeavor. While local tuning is usually manageable,...
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Design analysis of ORC micro-turbines making use of thermal energy of oceans
PublikacjaThe article presents the results of the analysis of energy conversion cycles making use of thermal energy of oceans. The objects of analysis were two cases of closed Organic Rankine Cycle (ORC) power plants, which were: the cycle in which the vapour of the working medium was produced by warm oceanic water in the circum-equatorial zone, and the so-called “arctic” cycle in which this vapour was produced by non-frozen water in the circumpolar...