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Search results for: DEEP REINFORCEMENT LEARNING
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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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Scent emitting multimodal computer interface for learning enhancement
PublicationKomputerowy interfejs aromatyczny stanowi ważne uzupełnienie procesu stymulacji polisensorycznej. Stymulacja ta odgrywa kluczową rolę w terapii i kształceniu dzieci z zaburzeniami rozwoju (np. w przypadku autyzmu czy ADHD). Opracowany interfejs może stać się elementem wyposażenia tzw. sal doświadczania świata, ale może być także stosowany niezależnie stanowiąc znaczące wzbogacenie komputerowych programów edukacyjnych. Dzięki możliwości...
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Machine learning applied to bi-heterocyclic drugs recognition
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Learning from examples with data reduction and stacked generalization
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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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Learning from the often-forgotten Jan Heweliusz disaster
PublicationPrzedstawiono konieczność przeprowadzenia badań nad zatonięciem promu Jan Heweliusz, którego katastrofa - w odróżnieniu od innych promów - została przemilczana i nie wywołała żadnych badań naukowych.
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IEEE 802.11 LAN capacity: incentives and incentive learning
PublicationPrzedstawiono matematyczny model zgodności motywacyjnej dla gier niekooperacyjnych wywiązujących się przy autonomicznym ustawianiu parametrów mechanizmu dostępu do medium transmisyjnego. Zaproponowano koncepcję przewidywania wyniku gry w zależności od stopnia wyrafinowania strategii terminala oraz jego możliwości energetycznych. Analiza symulacyjna potwierdziła dobrą wynikową wydajność sieci przy niewielu terminalach silnie uzależnionych...
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Using similar classification tasks in feature extractor learning
PublicationThe article presents and experimentally verify the idea of automatic construction of feature extractors in classification problems. The extractors are created by genetic programming techniques using classification examples taken from other problems then the problem under consideration.
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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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Transfer learning in imagined speech EEG-based BCIs
PublicationThe Brain–Computer Interfaces (BCI) based on electroencephalograms (EEG) are systems which aim is to provide a communication channel to any person with a computer, initially it was proposed to aid people with disabilities, but actually wider applications have been proposed. These devices allow to send messages or to control devices using the brain signals. There are different neuro-paradigms which evoke brain signals of interest...
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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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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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E-learning course "International comparative studies on SMEs"
PublicationProjekt Leonardo da Vinci "International comparative studies and course development on SMEs" został zainspirowany poprzednim projektem LdV "A European Diploma in SME Management". Bazując na poprzednich doświadczeniach projektowych zaproponowano opracowanie struktur dla opisania narodowych systemów małych i średnich przedsiębiorstw (ang. SME Small Media Enterprises) przy wykorzystaniu dostępnych krajowych danych. Udowodniono, że...
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Release Kinetics Studies of Early-Stage Volatile Secondary Oxidation Products of Rapeseed Oil Emitted during the Deep-Frying Process
PublicationThe research concerns the use of proton transfer reaction mass spectrometer to track real-time emissions of volatile secondary oxidation products released from rapeseed oil as a result of deep-frying of potato cubes. Therefore, it was possible to observe a sudden increase of volatile organic compound (VOC) emissions caused by immersion of the food, accompanied by a sudden release of steam from a potato cube and a decrease of the...
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Solubility of Carbon Dioxide in Deep Eutectic Solvents Based on 3-Amino-1-Propanol and Tetraalkylammonium Salts at Low Pressure
PublicationDeep eutectic solvents (DESs) became an object of a great interest as an alternative to ionic liquids (ILs) and commonly used in CO2 capture amine solutions. In the present study, five different DESs based on 3-amino-1-propanol as physical-chemical CO2 absorbents were used. The composition was chosen in order to estimate the effects of hydrogen bond acceptor:hydrogen bond donor (HBA:HBD) molar ratio, anion type and length of alkyl...
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An air-assisted dispersive liquid phase microextraction method based on a hydrophobic magnetic deep eutectic solvent for the extraction and preconcentration of melamine from milk and milk-based products
PublicationIn the current research, a fast and sustainable air-assisted hydrophobic magnetic deep eutectic solvent-based dispersive liquid phase microextraction followed by UV–Vis spectrophotometry measurements was optimized for the extraction and determination of melamine in milk and milk-based products. The central composite design was applied for the optimization of factors affecting the recovery of melamine. Quantitative extraction of...
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Prediction of fracture toughness in fibre-reinforced concrete, mortar, and rocks using various Machine learning techniques
PublicationMachine Learning (ML) method is widely used in engineering applications such as fracture mechanics. In this study, twenty different ML algorithms were employed and compared for the prediction of the fracture toughness and fracture load in modes I, II, and mixed-mode (I-II) of various materials, including fibre-reinforced concrete, cement mortar, sandstone, white travertine, marble, and granite. A set of 401 specimens of “Brazilian...
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Predicting seismic response of SMRFs founded on different soil types using machine learning techniques
PublicationPredicting the Maximum Interstory Drift Ratio (M-IDR) of Steel Moment-Resisting Frames (SMRFs) is a useful tool for designers to approximately evaluate the vulnerability of SMRFs. This study aims to explore supervised Machine Learning (ML) algorithms to build a surrogate prediction model for SMRFs to reduce the need for complex modeling. For this purpose, twenty well-known ML algorithms implemented in Python software are trained...
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Deep Data Analysis of a Large Microarray Collection for Leukemia Biomarker Identification
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Deep sea habitats in the chemical warfare dumping areas of the Baltic Sea
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Simulation of backup rolls quenching with experimental study of deep cryogenic treatment
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Influence of parameters of deep grinding on nanohardness and surface roughness of C45 steel
PublicationPrzedstawiono wyniki badań wpływu głębokości współbieżnego szlifowania powierzchni płaskich na chropowatość i nanotwardość warstwy wierzchniej stali C45 o strukturze ferrytyczno-perlitycznej i średniej wielkości ziarna 20 μm. Dla wszystkich wartości głębokości szlifowania uzyskano znaczny wzrost twardości warstwy wierzchniej przedmiotu obrabianego.
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Deep Features Class Activation Map for Thermal Face Detection and Tracking
PublicationRecently, capabilities of many computer vision tasks have significantly improved due to advances in Convolutional Neural Networks. In our research, we demonstrate that it can be also used for face detection from low resolution thermal images, acquired with a portable camera. The physical size of the camera used in our research allows for embedding it in a wearable device or indoor remote monitoring solution for elderly and disabled...
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Removal of phenolic inhibitor compounds from hydrolysates and post-fermentation broths by using a Hydrophobic Magnetic Deep Eutectic Solvent
PublicationHydroxymethylfurfural (HMF), furfural (FF), hydroquinone (HQ), and vanillin (VAN) are among the main inhibitors generated during most of biomass pre-treatments prior to fermentation processes. They are recognized as toxic to several fermentative microorganisms and therefore cause a decrease in biohydrogen or biofuel production (after hydrolysis). Moreover, if they are released into aqueous solutions (after fermentation), they can...
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Sample preparation procedure using extraction and derivatization of carboxylic acids from aqueous samples by means of deep eutectic solvents for gas chromatographic-mass spectrometric analysis
PublicationThe paper presents a new procedure for the determination of organic acids in a complex aqueous matrixusing ultrasound-assisted dispersive liquid–liquid microextraction followed by injection port derivati-zation and GC–MS analysis. A deep eutectic solvent (choline chloride: 4-methylphenol in a 1:2 mol ratio)was used both as an extracting solvent and as a derivatizing agent to yield ion pairs which were next con-verted to methyl...
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Satellite Image Classification Using a Hierarchical Ensemble Learning and Correlation Coefficient-Based Gravitational Search Algorithm
PublicationSatellite image classification is widely used in various real-time applications, such as the military, geospatial surveys, surveillance and environmental monitoring. Therefore, the effective classification of satellite images is required to improve classification accuracy. In this paper, the combination of Hierarchical Framework and Ensemble Learning (HFEL) and optimal feature selection is proposed for the precise identification...
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FE analysis of size effects in reinforced concrete beams without shear reinforcement based on stochastic elasto-plasticity with non-local softening.
PublicationW artykule przedstawiono wyniki analizy MES dotyczącej deterministycznego i statystycznego efektu skali w żelbetowych belkach bez zbrojenia na ścinanie. W analizie zastosowano prawo sprężysto-plastyczne z nielokalnym osłabieniem. Wyniki analizy porównano z doświadczeniami i modelem skali Bazanta.
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Machine-Learning-Powered EM-Based Framework for Efficient and Reliable Design of Low Scattering Metasurfaces
PublicationPopularity 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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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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Prediction of energy consumption and evaluation of affecting factors in a full-scale WWTP using a machine learning approach
PublicationTreatment of municipal wastewater to meet the stringent effluent quality standards is an energy-intensive process and the main contributor to the costs of wastewater treatment plants (WWTPs). Analysis and prediction of energy consumption (EC) are essential in designing and operating sustainable energy-saving WWTPs. In this study, the effect of wastewater, hydraulic, and climate-based parameters on the daily consumption of EC by...
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Anita Maria Dąbrowicz-Tlałka dr
PeopleAnita Dąbrowicz-Tlałka graduated from the Faculty of Mathematics and Physics at the University of Gdańsk with an outstanding grade, having written her thesis in the field of geometric topology. She concurrently obtained a diploma in Postgraduate Studies in the Basics of Computer Science at the University of Gdańsk. In 2001 she received a Ph.D. degree in mathematical studies at the Poznań University of Technology after defending...
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Polychlorinated biphenyls (PCBs) and polychlorodibenzo-p-dioxins (PCDDs) determination in disposable baby diapers with the application of natural deep eutectic solvent
PublicationIn this work a new method involving solvent extraction of porous membrane-packed solid samples (SE-PMSS) coupled to gas chromatography-mass spectrometry (GC–MS) has been developed for the determination of six polychlorinated biphenyls (PCBs) and five polychlorodibenzo-p-dioxines (PCDDs) in disposable baby diapers. In that aim, a terpenoid-based natural deep eutectic solvent (NADES) composed of carvone and camphor in a 1:1 M ratio...
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Ultrasound-Assisted Dispersive Liquid-Liquid Microextraction Using Deep Eutectic Solvents (DESs) for Neutral Red Dye Spectrophotometric Determination
PublicationDeep eutectic solvents (DES), which have low toxicity and are low cost, biodegradable, and easily synthesized, were used for the extraction of neutral red (NR) dye before its spectrophotometric analysis. DES, containing choline chloride as a hydrogen bond acceptor and phenol as a hydrogen bond donor with a molar ratio of 1:2, was used for the extraction of NR dye from aqueous media. The possible interaction of different DESs with...
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Thermal Instability of Choline Chloride-Based Deep Eutectic Solvents and Its Influence on Their Toxicity─Important Limitations of DESs as Sustainable Materials
PublicationDeep eutectic solvents (DESs) have become a hot topic in many branches of science due to their remarkable properties. They have been studied in a wide variety of applications. In particular, choline chloride (ChCl)-based DESs are one of the most commonly used representatives of these fluids. Nevertheless, in order to apply DESs in some fields, it is essential to guarantee their stability, reusability, and biocompatibility. In this...
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Seismic response and performance prediction of steel buckling-restrained braced frames using machine-learning methods
PublicationNowadays, Buckling-Restrained Brace Frames (BRBFs) have been used as lateral force-resisting systems for low-, to mid-rise buildings. Residual Interstory Drift (RID) of BRBFs plays a key role in deciding to retrofit buildings after seismic excitation; however, existing formulas have limitations and cannot effectively help civil engineers, e.g., FEMA P-58, which is a conservative estimation method. Therefore, there is a need to...
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Assessment of Failure Occurrence Rate for Concrete Machine Foundations Used in Gas and Oil Industry by Machine Learning
PublicationConcrete machine foundations are structures that transfer loads from machines in operation to the ground. The design of such foundations requires a careful analysis of the static and dynamic effects caused by machine exploitation. There are also other substantial differences between ordinary concrete foundations and machine foundations, of which the main one is that machine foundations are separated from the building structure....
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Energy consumption optimization in wastewater treatment plants: Machine learning for monitoring incineration of sewage sludge
PublicationBiomass management in terms of energy consumption optimization has become a recent challenge for developed countries. Nevertheless, the multiplicity of materials and operating parameters controlling energy consumption in wastewater treatment plants necessitates the need for sophisticated well-organized disciplines in order to minimize energy consumption and dissipation. Sewage sludge (SS) disposal management is the key stage of...
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The detection of Alternaria solani infection on tomatoes using ensemble learning
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Scheduling Repetitive Construction Processes Using the Learning-Forgetting Theory
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Becoming a Learning Organization Through Dynamic Business Process Management
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Digital competence learning in secondary adult education in Finland and Poland
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Didaktische simulationsmodelle fur E-learning in der IK-ausbildung.
PublicationPrzedstawiono dydaktyczne modele symulacyjne wykorzystywane w zdalnym kształceniu z zakresu informatyki i technik komunikacyjnych. Pokazano na przykładach zbudowanych symulatorów, w jaki sposób zrealizować lub dostosować modele symulacyjne do zdalnego nauczania. Opisano doświadczenia autorów w wykorzystaniu modeli symulacyjnych w zdalnym nauczaniu.
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Meta-Design and the Triple Learning Organization in Architectural Design Process
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Building the Learning Environment for Sustainable Development: a Co-creation approach
PublicationEducation for sustainable development supports the improvement of knowledge, skills, attitudes and behaviors related to global challenges such as climate change, global warming and environmental degradation, among others. It is increasingly taking place through projects based on information and communication technologies. The effectiveness of the actions taken depends not only on the quality of the project activities or the...
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Agent-Based Population Learning Algorithm for RBF Network Tuning
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An A-Team Approach to Learning Classifiers from Distributed Data Sources
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An A-Team approach to learning classifiers from distributed data sources
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Employing a biofeedback method based on hemispheric synchronization in effective learning
PublicationIn this paper an approach to build a brain computer-based hemispheric synchronization system is presented. The concept utilizes the wireless EEG signal registration and acquisition as well as advanced pre-processing methods. The influence of various filtration techniques of EOG artifacts on brain state recognition is examined. The emphasis is put on brain state recognition using band pass filtration for separation of individual...
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Cost-Efficient Multi-Objective Design of Miniaturized Microwave Circuits Using Machine Learning and Artificial Neural Network
PublicationDesigning microwave components involves managing multiple objectives such as center frequencies, impedance matching, and size reduction for miniaturized structures. Traditional multi-objective optimization (MO) approaches heavily rely on computationally expensive population-based methods, especially when exe-cuted with full-wave electromagnetic (EM) analysis to guarantee reliability. This paper introduces a novel and cost-effective...