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Search results for: MACHINE LEARNING, 3D-PRINTED FIBER REINFORCED CONCRETE, MODEL INTERPRETABILITY, COMPRESSIVE STRENGTH
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Cost-Efficient Measurement Platform and Machine-Learning-Based Sensor Calibration for Precise NO2 Pollution Monitoring
PublicationAir quality significantly impacts human health, the environment, and the economy. Precise real-time monitoring of air pollution is crucial for managing associated risks and developing appropriate short- and long-term measures. Nitrogen dioxide (NO2) stands as a common pollutant, with elevated levels posing risks to the human respiratory tract, exacerbating respiratory infections and asthma, and potentially leading to chronic lung...
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Latest Achievements in Concrete Structures Three-Dimensional Printing
PublicationWe can hear about three-dimensional printed concrete structures for several years, up to date solutions in this technology allow entire printing settlements of tiny concrete houses. Due to technical limitations, these houses are still small and not very durable, but undoubtedly, this technology is developing. Home printed in three-dimensional technology can be an alternative to modular container buildings implemented in areas affected...
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Experimental and numerical investigations of size effects in reinforced concrete beams with steel or basalt bars.
PublicationW artykule przedstawiono wyniki obliczeń efektów skali w belkach betonowych zbrojonych prętami stalowymi i bazaltowymi podczas zginania. Zastosowano model sprężysto-plastyczny z nielokalnym osłabieniem. Rozkład wytrzymałości na rozciąganie był stochastyczny – przestrzennie skorelowany. Belki były geometrycznie podobne. Wyniki porównano z modelem efektu skali Bazanta
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BEHAVIOR OF REINFORCED CONCRETE BEAMS CONTAINING LIGHTWEIGHT AGGREGATE IN THE TENSILE ZONE
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Experimental investigations of size effect in reinforced concrete beams failing by shear
PublicationW artykule omówiono wyniki doświadczalne efektu skali w zbrojonych betonowych belkach niszczących się przez ścinanie. Doświadczenia wykonano dla belek o różnych wymiarach ze zbrojeniem stalowym i bazaltowym. Podczas doświadczeń pomierzono siłę oraz szerokości lokalizacji i rys. Wyniki porównano z modelem skali wg Bazanta.
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Numerical analysis of behaviour of reinforced concrete elements under eccentric compression
PublicationPrzedstawiono wyniki modelowania nośności elementów żelbetowych stosując metodę elementów skończonych. Do opisu betonu zastosowano sprężysto-plastyczne prawo materiałowe wg Druckera-Pragera. Do modelowania stali zbrojeniowej zastosowano sprężysto-plastyczne prawo materiałowe według von Misesa. Obliczenia wykonano dla ścian żelbetowych.
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Driver’s Condition Detection System Using Multimodal Imaging and Machine Learning Algorithms
PublicationTo this day, driver fatigue remains one of the most significant causes of road accidents. In this paper, a novel way of detecting and monitoring a driver’s physical state has been proposed. The goal of the system was to make use of multimodal imaging from RGB and thermal cameras working simultaneously to monitor the driver’s current condition. A custom dataset was created consisting of thermal and RGB video samples. Acquired data...
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Numerical and experimental study on effect of boundary conditions during testing of stiffened plates subjected to compressive loads
PublicationThis study analyses the effect of boundary conditions during testing on the structural behaviour stiffened plates with different thicknesses subjected to compressive loads. The goal of the compressive tests is to analyse the ultimate strength of a stiffened plate. During the test, relevant physical quantities are measured and investigated. The supporting structure's behaviour is investigated by analysing the force-displacements...
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Playback detection using machine learning with spectrogram features approach
PublicationThis paper presents 2D image processing approach to playback detection in automatic speaker verification (ASV) systems using spectrograms as speech signal representation. Three feature extraction and classification methods: histograms of oriented gradients (HOG) with support vector machines (SVM), HAAR wavelets with AdaBoost classifier and deep convolutional neural networks (CNN) were compared on different data partitions in respect...
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Exploration of the Solubility Hyperspace of Selected Active Pharmaceutical Ingredients in Choline- and Betaine-Based Deep Eutectic Solvents: Machine Learning Modeling and Experimental Validation
PublicationDeep eutectic solvents (DESs) are popular green media used for various industrial, pharmaceutical, and biomedical applications. However, the possible compositions of eutectic systems are so numerous that it is impossible to study all of them experimentally. To remedy this limitation, the solubility landscape of selected active pharmaceutical ingredients (APIs) in choline chloride- and betaine-based deep eutectic solvents was...
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Deep Learning
PublicationDeep learning (DL) is a rising star of machine learning (ML) and artificial intelligence (AI) domains. Until 2006, many researchers had attempted to build deep neural networks (DNN), but most of them failed. In 2006, it was proven that deep neural networks are one of the most crucial inventions for the 21st century. Nowadays, DNN are being used as a key technology for many different domains: self-driven vehicles, smart cities,...
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Machinability investigation in electric discharge machining of carbon fiber reinforced composites for aerospace applications
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Tuning Ferulic Acid Solubility in Choline-Chloride- and Betaine-Based Deep Eutectic Solvents: Experimental Determination and Machine Learning Modeling
PublicationDeep eutectic solvents (DES) represent a promising class of green solvents, offering particular utility in the extraction and development of new formulations of natural compounds such as ferulic acid (FA). The experimental phase of the study undertook a systematic investigation of the solubility of FA in DES, comprising choline chloride or betaine as hydrogen bond acceptors and six different polyols as hydrogen bond donors....
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The role of electrolysis and enzymatic hydrolysis treatment in the enhancement of the electrochemical properties of 3D-printed carbon black/poly(lactic acid) structures
PublicationAdditive manufacturing, also known as 3D printing, is beginning to play an unprecedented role in developing many applications for industrial or personalized products. The conductive composite structures require additional treatment to achieve an electroactive surface useful for electrochemical devices. In this paper, the surfaces of carbon black/poly(lactic acid) CB-PLA printouts were activated by electrolysis or enzymatic digestion...
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User satisfaction model
PublicationRaport techniczny - opis metody ''User Satisfaction Methods'' wykorzystywanej w projektowaniu komunikacji człowiek-komputer oraz doskonaleniu interfejsu użytkownika.
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Application of Artificial Neural Networks to Predict Insulation Properties of Lightweight Concrete
PublicationPredicting the properties of concrete before its design and application process allows for refining and optimizing its composition. However, the properties of lightweight concrete are much harder to predict than those of normal weight concrete, especially if the forecast concerns the insulating properties of concrete with artificial lightweight aggregate (LWA). It is possible to use porous aggregates and precisely modify the composition...
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Solubility Characteristics of Acetaminophen and Phenacetin in Binary Mixtures of Aqueous Organic Solvents: Experimental and Deep Machine Learning Screening of Green Dissolution Media
PublicationThe solubility of active pharmaceutical ingredients is a mandatory physicochemical characteristic in pharmaceutical practice. However, the number of potential solvents and their mixtures prevents direct measurements of all possible combinations for finding environmentally friendly, operational and cost-effective solubilizers. That is why support from theoretical screening seems to be valuable. Here, a collection of acetaminophen...
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Machine learning-based prediction of residual drift and seismic risk assessment of steel moment-resisting frames considering soil-structure interaction
PublicationNowadays, due to improvements in seismic codes and computational devices, retrofitting buildings is an important topic, in which, permanent deformation of buildings, known as Residual Interstory Drift Ratio (RIDR), plays a crucial role. To provide an accurate yet reliable prediction model, 32 improved Machine Learning (ML) algorithms were considered using the Python software to investigate the best method for estimating Maximum...
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Numerical simulation of hardening of concrete plate
PublicationThe paper presents a theoretical formulation of concrete curing in order to predict temperature evolution and strength development. The model of heat flow is based on a well-known Fourier equation. The numerical solution is implemented by means of the Finite Difference Method. In order to verify the model, the in situ temperature measurements at the top plate of a road bridge were carried out. A high agreement between numerical...
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Properties of Composite Modified with Limestone Powder for 3D Concrete Printing
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Prediction of maximum tensile stress in plain-weave composite laminates with interacting holes via stacked machine learning algorithms: A comparative study
PublicationPlain weave composite is a long-lasting type of fabric composite that is stable enough when being handled. Open-hole composites have been widely used in industry, though they have weak structural performance and complex design processes. An extensive number of material/geometry parameters have been utilized for designing these composites, thereby an efficient computational tool is essential for that purpose. Different Machine Learning...
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Sperm segmentation and abnormalities detection during the ICSI procedure using machine learning algorithms
Publication(1) About 15-20% of couples struggle with the problem of infertility. 30 to 40% of these cases are caused by abnormalities in the structure and motility of sperm. Sometimes the only possibility for such people is to use the procedure of artificial insemination. CASA systems are used to increase the efficiency of this procedure by selecting the appropriate sperm cell. (2) This paper presents an approach to the sperm classification...
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Expedited Machine-Learning-Based Global Design Optimization of Antenna Systems Using Response Features and Multi-Fidelity EM Analysis
PublicationThe design of antenna systems poses a significant challenge due to stringent per-formance requirements dictated by contemporary applications and the high com-putational costs associated with models, particularly full-wave electromagnetic (EM) analysis. Presently, EM simulation plays a crucial role in all design phases, encompassing topology development, parametric studies, and the final adjustment of antenna dimensions. The latter...
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Machine learning-based prediction of seismic limit-state capacity of steel moment-resisting frames considering soil-structure interaction
PublicationRegarding the unpredictable and complex nature of seismic excitations, there is a need for vulnerability assessment of newly constructed or existing structures. Predicting the seismic limit-state capacity of steel Moment-Resisting Frames (MRFs) can help designers to have a preliminary estimation and improve their views about the seismic performance of the designed structure. This study improved data-driven decision techniques in...
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Zastosowanie elementów "węzłowych" do budowy modelu 3D cewki giętkiej w programie polowym OPERA 3D = Application of "nodal" elements for creation of a 3D model of a flexible coil in the program Opera 3D
PublicationNiniejsza praca jest kontynuacją serii artykułów dotyczących modelowania 3D uzwojenia maszyn elektrycznych z cewkami giętkimi. Istotnym problemem dotyczącym modelowania takiego uzwojenia jest zmienność kształtu przekroju poprzecznego zwłaszcza w części czołowej. Powoduje to problemy w utworzeniu uzwojenia bez konfliktów wymiarowych (nie przenikanie się wierzchołków, przyleganie boków cewek, odpowiednie położenie). Niektóre programy...
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Computational simulations of concrete behaviour under dynamic conditions using elasto-visco-plastic model with non-local softening.
PublicationW artykule przedstawiono wyniki obliczeniowych symulacji zachowania betonu w warunkach dynamicznych stosując sprężysto-lepko-plastyczny model z nielokalnym osłabieniem. Wykonano obliczenia dla ściskania jednoosiowego, rozciągania jednoosiowego i zginania. Dla dużych prędkości obciążenia uwzględniono fragmentację materiału. Wyniki porównano z doswiadczeniami.
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Stress–strain model of lower corroded steel plates of normal strength for fitness-for-purpose analyses
PublicationThis study investigates the mechanical properties of specimens made of normal strength steel subjected to lower marine immersed corrosion degradation levels (below 25 %). The specimens were corroded in laboratory conditions, and only natural factors were controlled to raise the corrosion rate (reaching the level of 1 mm/year). Three different thicknesses of plates made of normal strength of shipbuilding steel are investigated (between...
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A simple model of circular hydraulic pump
PublicationRozpatrzono warunki powstawania osiowosymetrycznego uskoku hydraulicznego. Przedstawiono model, w którym rozpatrzono obecność dodatkowych strat w równaniu Bernoulliego. Przyczyniają się one do powstawania dodatkowego wiru w miejscu uskoku. Porównanie z wynikami badań eksperymentalnych potwierdza słuszność przyjętych tez.
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Integrating Statistical and Machine‐Learning Approach for Meta‐Analysis of Bisphenol A‐Exposure Datasets Reveals Effects on Mouse Gene Expression within Pathways of Apoptosis and Cell Survival
PublicationBisphenols are important environmental pollutants that are extensively studied due to different detrimental effects, while the molecular mechanisms behind these effects are less well understood. Like other environmental pollutants, bisphenols are being tested in various experimental models, creating large expression datasets found in open access storage. The meta‐analysis of such datasets is, however, very complicated for various...
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Thermoplastic elastomer filaments and their application In 3D printig
PublicationThe paper provides an overview on the materials used in the 3D printing technology (the Polish and foreign market) with a particular focus on flexible filaments and their possible application in the industry. There are described the techniques of 3D printing and modern filaments available on the market. There is observed the increase of interest in the production of products from filaments based on thermoplastic elastomers (TPE),...
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Experimental investigations on the mechanical properties and damage detection of carbon nanotubes modified crumb rubber concrete
PublicationThis study presents a modified crumb rubber (MCR) concrete design mix reinforced with multi-walled carbon nanotubes (MWCNTs), mechanical characterization, and cracking monitoring using the acoustic emission (AE) technique. The results showed that the bridging effect of MWCNTs and MCR in the concrete mix mitigated the shortcomings of MWCNT-MCR concrete and improved the flexural and compressive strengths by 18.3% and 26.5%, respectively,...
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Comparative study on total nitrogen prediction in wastewater treatment 1 plant and effect of various feature selection methods on machine learning algorithms performance
PublicationWastewater characteristics prediction in wastewater treatment plants (WWTPs) is valuable and can reduce the number of sampling, energy, and cost. Feature Selection (FS) methods are used in the pre-processing section for enhancing the model performance. This study aims to evaluate the effect of seven different FS methods (filter, wrapper, and embedded methods) on enhancing the prediction accuracy for total nitrogen (TN) in the WWTP...
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Deep Learning: A Case Study for Image Recognition Using Transfer Learning
PublicationDeep learning (DL) is a rising star of machine learning (ML) and artificial intelligence (AI) domains. Until 2006, many researchers had attempted to build deep neural networks (DNN), but most of them failed. In 2006, it was proven that deep neural networks are one of the most crucial inventions for the 21st century. Nowadays, DNN are being used as a key technology for many different domains: self-driven vehicles, smart cities,...
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Fusion-based Representation Learning Model for Multimode User-generated Social Network Content
PublicationAs mobile networks and APPs are developed, user-generated content (UGC), which includes multi-source heterogeneous data like user reviews, tags, scores, images, and videos, has become an essential basis for improving the quality of personalized services. Due to the multi-source heterogeneous nature of the data, big data fusion offers both promise and drawbacks. With the rise of mobile networks and applications, UGC, which includes...
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Optimized Deep Learning Model for Flood Detection Using Satellite Images
PublicationThe increasing amount of rain produces a number of issues in Kerala, particularly in urban regions where the drainage system is frequently unable to handle a significant amount of water in such a short duration. Meanwhile, standard flood detection results are inaccurate for complex phenomena and cannot handle enormous quantities of data. In order to overcome those drawbacks and enhance the outcomes of conventional flood detection...
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Experimental Study and Finite Element Modeling of Reinforced Concrete Column Having an Opening
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Effect of a characteristic length on crack spacing in a reinforced concrete bar under tension
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Experimental study of corrosion in reinforced concrete by acoustic emission and electrochemical noise techniques
PublicationTechnika emisji akustycznej jest znaną metodą badań korozji zbrojenia żelbetu. Źródłem aktywności akustycznej są zawsze zjawiska o naturze mechanicznej. Przedstawiono wynik badań akustycznych zbrojonego betonu w warunkach polaryzacji anodowej, przyspieszającej procesy korozyjne. Symultanicznie prowadzona była rejestracja szumu elektrochemicznego. Dla umożliwienia korelacji wyników, uzyskanych obiema technikami, wykonana została...
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Electrochemical investigations of conductive coatings applied as anodes in cathodic protection of reinforced concrete.
PublicationW pracy przedstawiono rezultaty badań elektrochemicznych polimerów przewodzących z pigmentem grafitowym. Wyznaczono parametry elektrochemiczne badanych powłok w trakcie długotrwałej polaryzacji zbrojonego betonu. W oparciu o pomiary impedancyjne wyznaczono parametry elektrochemiczne powłok przewodzących. Wykazano, że badane powłoki mogą być stosowane w ochronie katodowej żelbetu. Badania wykazały, że optymalne stężenie grafitu...
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FE-analysis of failure behaviour of reinforced concrete columns under eccentric compression
PublicationArtykuł omawia obliczanie słupów żelbetowych poddanych ściskaniu mimośrodowemu z uwzględnieniem lokalizacji odkształceń. Obliczenia wykonano przy zastosowaniu MES i sprężysto-plastycznego prawa konstytutywnego rozszerzonego o długość charakterystyczną mikrostruktury za pomocą teorii nielokalnej.
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Effect of a characteristic length on crack spacing in a reinforced concrete bar under tension.
PublicationW artykule przedstawiono wyniki numerycznej obliczenia rozstawu rys w pręcie żelbetowym poddanemu rozciąganiu. Obliczenia wykonano przy zastosowaniu sprężysto-plastycznego modelu rozszerzonego o długość charakterystyczna mikrostruktury przy pomocy teorii nielokalnej.
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Tests of bond between concrete and steel bars – literature background and program of own research
PublicationThis article deals with the issue of the bond between concrete and reinforcement. The bond is crucial for reinforced concrete elements because it is possible to transfer forces (stresses) from concrete to the reinforcement. Basic information related to the cooperation of concrete and rebars was recalled in the article. Selected issues concerning theoretical and numerical analysis as well as experiments of the bond phenomenon were...
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Nanolayers in Fiber-Optic Biosensing
PublicationIn this chapter, fiber-optic sensors based on nanolayers or thin films and their ability to perform biophotonic measurements is presented. In the last decade, fiber-optic sensors have gained popularity as biosensing devices. This has been made possible because of the design and the integration of new materials in fiber-optic technology. Nanolayers and thin films made from various materials such as nanodiamond (NCD), boron-doped...
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Spirometry measurement model - the diagnostic purpose support
Publicationthe paper presents a new model of respiratory mechanism based on the spirometry measurements. the spirometry test assesses the efficiency of the lung ventilation. the respiratory system functioning is based on the ventilation mechanism. thus the quality of the lung depends on the quality of lung ventilation. modelling of the respiratory system supports a diagnostic process. the model parameter estimates are obtained on the basis...
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Comparison of classical Winter's bracing requirements of compressedtruss chord with stability analysis of 3D truss-model
PublicationMost code requirements concerning bracing are based on principles developed by Winter. The present research is devoted tostudy a lateral buckling of truss with linear elastic side supports. The classical Winter's model of truss chord in the case ofout of the truss plane buckling is compared with nonlinear analysis of 3D truss model. Full bracing condition, that permitsthe truss chord to support load level corresponding to an unbraced...
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Reliability of Corroded Stiffened Plate Subjected to Uniaxial Compressive Loading
PublicationThe work is focused on the reliability of corroded stiffened plates subjected to compressive uniaxial load based on the progressive collapse approach as stipulated by the Common Structural Rules for Bulk Carriers and Oil Tankers, employing the limit state design. Two different cases have been investigated. In the first model, the corrosion degradation led to uniform thickness loss, whereas the mechanical properties were unchanged,...
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Modular machine learning system for training object detection algorithms on a supercomputer
PublicationW pracy zaprezentowano architekturę systemu służącego do tworzenia algorytmów wykorzystujących metodę AdaBoost i służących do wykrywania obiektów (np. twarzy) na obrazach. System został podzielony na wyspecjalizowane moduły w celu umożliwienia łatwej rozbudowy i efektywnego zrównoleglenia implementacji przeznaczonej dla superkomputera. Na przykład, system może być rozszerzony o nowe cechy i algorytmy ich ekstrakcji bez konieczności...
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Efficient sampling of high-energy states by machine learning force fields
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Evaluation of aspiration problems in L2 English pronunciation employing machine learning
PublicationThe approach proposed in this study includes methods specifically dedicated to the detection of allophonic variation in English. This study aims to find an efficient method for automatic evaluation of aspiration in the case of Polish second-language (L2) English speakers’ pronunciation when whole words are analyzed instead of particular allophones extracted from words. Sample words including aspirated and unaspirated allophones...
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Stacking and rotation-based technique for machine learning classification with data reduction
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