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Search results for: DEEP LEARNING, ROBOTICS
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PERFORMANCE AND ORGANIZATIONAL LEARNING CAPABILITY IN POLISH COMPANIES
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Designing learning-skills towards industry 4.0
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The Use of Photographs in the Teaching/Learning of Descriptive Geometry
PublicationThe article presents the concept of enriching the Descriptive Geometry course with photographs and several simplified real-life engineering tasks. The photographic images used for the exercises are tightly linked to engineering structures, the given specialization and the surrounding world. The photo image as a record of central projection of a real space can be useful for presentation and analysis of the properties of perspective....
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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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Improving the prediction of biochar production from various biomass sources through the implementation of eXplainable machine learning approaches
PublicationExamining the game-changing possibilities of explainable machine learning techniques, this study explores the fast-growing area of biochar production prediction. The paper demonstrates how recent advances in sensitivity analysis methodology, optimization of training hyperparameters, and state-of-the-art ensemble techniques have greatly simplified and enhanced the forecasting of biochar output and composition from various biomass...
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Journal of Mechanisms and Robotics-Transactions of the ASME
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Journal of Robotics Networking and Artificial Life
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International Journal of Intelligent Robotics and Applications
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Journal of Institute of Control, Robotics and Systems
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International Journal of Computational Vision and Robotics
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IEEE Transactions on Medical Robotics and Bionics
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Extractive detoxification of feedstocks for the production of biofuels using new hydrophobic deep eutectic solvents – Experimental and theoretical studies
PublicationThe paper presents a synthesis of novel hydrophobic deep eutectic solvents (DESs) composed of natural components, which were used for removal of furfural (FF) and 5-hydroxymethylfurfural (HMF) from lignocellulosic hydrolysates. The main physicochemical properties of DESs were determined, followed by explanation of the DES formation mechanism, using 1H NMR, 13C NMR and FT-IR analysis and density functional theory (DFT). The most...
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Magnetic deep eutectic solvents as efficient media for extraction of furfural and 5-hydroxymethylfurfural from aqueous samples
PublicationThe extraction of furfural (FF) and 5-hydroxymethylfurfural (HMF) from hydrolysates is currently one of the main challenges in bio-refinery. In this work, the separation of FF and HMF from the aqueous phase was carried out using a new type of green solvents – Magnetic Deep Eutectic Solvents (MDES). A conductor-like screening model for realistic solvents (COSMO-RS) was used for the preselection of 400 MDES. MDES which exhibit the...
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Deep eutectic solvent based method for analysis of Niclosamide in pharmaceutical and wastewater samples – A green analytical chemistry approach
PublicationThe paper presents a simple, but very effective and sensitive spectrophotometric method for trace analysis of Niclosamide based on liquid–liquid microextraction using deep eutectic solvents (DESs) prior to its quantification. Here, different DES systems, such as Choline chloride (ChCl) + Urea, ChCl + Citric acid, ChCl + Ethylene glycol and ChCl + Phenol, were synthesized and evaluated at different molar ratios, selecting ChCl + Phenol...
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GPU Power Capping for Energy-Performance Trade-Offs in Training of Deep Convolutional Neural Networks for Image Recognition
PublicationIn the paper we present performance-energy trade-off investigation of training Deep Convolutional Neural Networks for image recognition. Several representative and widely adopted network models, such as Alexnet, VGG-19, Inception V3, Inception V4, Resnet50 and Resnet152 were tested using systems with Nvidia Quadro RTX 6000 as well as Nvidia V100 GPUs. Using GPU power capping we found other than default configurations minimizing...
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Machine learning-based seismic fragility and seismic vulnerability assessment of reinforced concrete structures
PublicationMany studies have been performed to put quantifying uncertainties into the seismic risk assessment of reinforced concrete (RC) buildings. This paper provides a risk-assessment support tool for purpose of retrofitting and potential design strategies of RC buildings. Machine Learning (ML) algorithms were developed in Python software by innovative methods of hyperparameter optimization, such as halving search, grid search, random...
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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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Unsupervised Learning for Biomechanical Data Using Self-organising Maps, an Approach for Temporomandibular Joint Analysis
PublicationWe proposed to apply a specific machine learning technique called Self-Organising Maps (SOM) to identify similarities in the performance of muscles around human temporomandibular joint (TMJ). The performance was assessed by measuring muscle activation with the use of surface electromyography (sEMG). SOM algorithm used in the study was able to find clusters of data in sEMG test results. The SOM analysis was based on processed sEMG...
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Multimodal learning application with interactive animated character. [Multimodalna aplikacja edukacyjna wykorzystująca interaktywną animowaną postać]
PublicationThe aim of this study is to design a computer application that may assist teachers and therapists in multimodal manner in their work with impaired or disabled children. The application can be operated in many different ways, giving to a child with special educational needs a possibility to learn and train many skills or treat speech disorders. The main stress in this research is on the creation of animated character that will serve...
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Starch plasticization with choline dihydrogencitrate-based deep eutectic system
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Deep brain stimulation: new possibilities for the treatment of mental disorders
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The Impact of Dredging Deep Pits on Organic Matter Decomposition in Sediments
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Problem of selection of reference plane with deep and wide valleys analysis
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Efficiency of deep bed filtration in treatment of swimming pool water
PublicationPrzebadano efektywność filtracji wody w filtrach ze złożem żwirowo-piaskowym w instalacji basenu rehabilitacyjnego. Obok analizy instrumentalnej wody, w badaniach uwzględniono rozkład wielkości cząstek i analizę termiczną osadu zgromadzonego w złożu piaskowym filtrów wgłębnych i usuwanego podczas płukania.
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Deep eutectic solvent (DES) with silver nanoparticles (Ag-NPs) based assay for analysis of lead (II) in edible oils
PublicationThis paper presents an application of silver nanoparticles impregnated by Deep Eutectic Solvents (DES) as ultrasonication aided microextraction system for lead (II) determination in edible oils. The paper presents a systematic optimization of method parameters and examples of its application for analysis of real samples. Maximum recovery for lead (II) extraction was obtained for choline chloride and phenol with a 1:2 molar ratio....
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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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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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Machine-learning methods for estimating compressive strength of high-performance alkali-activated concrete
PublicationHigh-performance alkali-activated concrete (HP-AAC) is acknowledged as a cementless and environmentally friendly material. It has recently received a substantial amount of interest not only due to the potential it has for being used instead of ordinary concrete but also owing to the concerns associated with climate change, sustainability, reduction of CO2 emissions, and energy consumption. The characteristics and amounts of the...
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Learning Communities-International Journal of Learning in Social Contexts
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Marek Sylwester Tatara dr inż.
PeopleMarek Tatara achieved his master's degree in the field of Automatic Control and Robotics with specialization Intelligent Decision-making Systems in 2014 at Faculty of Electronics, Telecommunications and Informatics of Gdańsk University of Technology. Earlier this year achieved bachelor's degree in the field of Technical Physics with Nanotechnology specialization. In 2014 started job as lecturer in the Department of Robotics and...
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Novel binary mixtures of alkanolamine based deep eutectic solvents with water - thermodynamic calculation and correlation of crucial physicochemical properties
PublicationThis paper demonstrates the assessment of physicochemical and thermodynamic properties of aqueous solutions of novel deep eutectic solvent (DES) built of tetrabutylammonium chloride and 3-amino-1-propanol or tetrabutylammonium bromide and 3-amino-1-propanol or 2-(methylamino)ethanol or 2-(butylamino)ethanol. Densities, speeds of sound, refractive indices, and viscosities for both pure and aqueous mixtures of DES were investigated...
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Novel Binary Mixtures of Alkanolamine Based Deep Eutectic Solvents with Water—Thermodynamic Calculation and Correlation of Crucial Physicochemical Properties
PublicationThis paper demonstrates the assessment of physicochemical and thermodynamic properties of aqueous solutions of novel deep eutectic solvent (DES) built of tetrabutylammonium chloride and 3-amino-1-propanol or tetrabutylammonium bromide and 3-amino-1-propanol or 2-(methylamino)ethanol or 2-(butylamino)ethanol. Densities, speeds of sound, refractive indices, and viscosities for both pure and aqueous mixtures of DES were investigated...
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Molecularly imprinted polymers based on deep eutectic solvents as a greenest materials for selective extraction of emerging contaminants from complex samples
PublicationSome of the reagents applied in the synthesis of molecularly imprinted polymers (MIPs) may impact on health and the environment. Thus, a new generation of promising green chemicals are nowadays introduced and investigated, including deep eutectic solvents (DESs). DESs seems to be a reasonable choice as they are characterized as non-toxic, low cost, easy to prepare and biodegradable chemicals. This review presents the information...
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Project-Based Learning as a Method for Interdisciplinary Adaptation to Climate Change—Reda Valley Case Study
PublicationThe challenges of the global labour market require university authorities to extend traditional forms of education into more innovative and effective solutions. Project-based learning (PjBL) is one of highly effective methods for acquiring knowledge and teaching “soft” skills to future employees. This article describes an experimental use of PjBL at a university with a long history of teaching based on traditional methods—the Gdansk...
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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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Iterative learning approach to active noise control of highly autocorrelated signals with applications to machinery noise
PublicationThis paper discusses the design and application of iterative learning control (ILC) and repetitive control (RC) for high modal density systems. Typical examples of these systems are structural and acoustical systems considered in active structural acoustic control (ASAC) and active noise control (ANC) applications. The application of traditional ILC and RC design techniques, which are based on a parametric system model, on systems...
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Mathematical Thinking and Learning
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Animal Learning and Behavior
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Learning Environments Research
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Development and Learning in Organizations
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Journal of Workplace Learning
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Information and Learning Science
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Learning Media and Technology
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Journal of Learning Styles
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Journal of Teaching and Learning
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Language Learning and Development
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Journal of Learning Design
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Journal of Peer Learning
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International Journal of Learning
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