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Wyniki wyszukiwania dla: MACHINE LEARNING, COMPATIBILITY TESTING, NEW PRODUCT DEVELOPMENT, SMART PRODUCTS
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Szymon Zaporowski mgr inż.
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International Journal of Machine Learning and Cybernetics
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International Journal of Machine Learning and Computing
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The chemistry, properties and performance of flame-retardant rubber composites: Collecting, analyzing, categorizing, machine learning modeling, and visualizing
PublikacjaRubbers combine the flexibility with mechanical strength, supporting myriad applications, but suffer from inherent flammability. Formulation and production of flame-retardant rubber composites (FRRCs) have intensively been practiced over years, but not comprehensively reviewed. This necessity has outlined collecting, analyzing, screening, classifying, and interpreting the literature with the aim of classifying the FRRCs. We quantified...
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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
PublikacjaPlain 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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Optimization-based stacked machine-learning method for seismic probability and risk assessment of reinforced concrete shear walls
PublikacjaEfficient seismic risk assessment aids decision-makers in formulating citywide risk mitigation plans, providing insights into building performance and retrofitting costs. The complexity of modeling, analysis, and post-processing of the results makes it hard to fast-track the seismic probabilities, and there is a need to optimize the computational time. This research addresses seismic probability and risk assessment of reinforced...
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Development and Learning in Organizations
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Language Learning and Development
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Journal of Learning for Development
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Exchange-traded products in Germany: development and substitution of exchange-traded funds, exchange-traded commodities and exchange-traded notes.
PublikacjaResearch background: Exchange-traded products (ETPs) are one of the most rapidly growing categories of financial products. Their fast development has been boosted by innovative features. Three main categories of ETPs are exchange-traded funds (ETFs), exchange-traded commodities (ETCs) and exchange-traded notes (ETNs). ETCs and ETNs remain least known, even though their number on some stock exchanges is high. In Europe, Germany...
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Development of the New Polish Method for Capacity Analysis of Motorways and Expressways
PublikacjaThe paper presents development of the new Polish method for performing capacity analysis of basic segments of dual carriageway roads (motorways and expressways). The method is based on field traffic surveys conducted at 30 motorway and expressway sites (class A and S roads) in Poland. Traffic flows, composition and travel times were observed in 15-min intervals at each site using ANPR filming method. These data were used to calibrate...
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Expedited Machine-Learning-Based Global Design Optimization of Antenna Systems Using Response Features and Multi-Fidelity EM Analysis
PublikacjaThe 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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Efficient sampling of high-energy states by machine learning force fields
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Modular machine learning system for training object detection algorithms on a supercomputer
PublikacjaW 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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Evaluation of aspiration problems in L2 English pronunciation employing machine learning
PublikacjaThe 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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POPULATION-BASED MULTI-AGENT APPROACH TO SOLVING MACHINE LEARNING PROBLEMS
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Magdalena Szuflita-Żurawska
OsobyMagdalena Szuflita-Żurawska jest kierownikiem Sekcji Informacji Naukowo-Technicznej na Politechnice Gdańskiej oraz Liderem Centrum Kompetencji Otwartej Nauki przy Bibliotece Politechniki Gdańskiej. Jej główne zainteresowania badawcze koncentrują się w obszarze komunikacji naukowej oraz otwartych danych badawczych, a także motywacji i produktywności naukowej. Jest odpowiedzialna między innymi za prowadzenie szkoleń dla pracowników...
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Methods for Elucidation of DNA-Anticancer Drug Interactions and Their Applications in the Development of New Drugs
PublikacjaDNA damaging agents including anthracyclines, camptothecins and platinum drugs are among most frequently used drugs in the chemotherapeutic routine. Due to their relatively low selectivity for cancer cells, administration is associated with adverse side effects, whereas the inherent genotoxicity of these drugs is associated with risk of developing secondary cancers. Development of new drugs, which could be spared of these drawbacks...
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Searching for new development in areas of the city
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Rediscovering Automatic Detection of Stuttering and Its Subclasses through Machine Learning—The Impact of Changing Deep Model Architecture and Amount of Data in the Training Set
PublikacjaThis work deals with automatically detecting stuttering and its subclasses. An effective classification of stuttering along with its subclasses could find wide application in determining the severity of stuttering by speech therapists, preliminary patient diagnosis, and enabling communication with the previously mentioned voice assistants. The first part of this work provides an overview of examples of classical and deep learning...
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Machine learning-based prediction of seismic limit-state capacity of steel moment-resisting frames considering soil-structure interaction
PublikacjaRegarding 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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A modern solid waste management strategy – the generation of new by-products
PublikacjaTo benefit the environment and society, EU legislation has introduced a ‘zero waste’ strategy, in which waste material should be converted to resources. Such legislation is supported by the solid waste hierarchy concept, which is a set of priorities in waste management. Under this concept, municipal solid waste plants (MSWPs) should be equipped with sorting and recycling facilities, composting/incineration units and landfill prisms...
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METHODOLOGICAL IDENTIFICATION OF OPPORTUNITIES FOR DEVELOPMENT OF SMART SPECIALISATION IN POMERANIAN VOIVODESHIP IN POLAND
PublikacjaThe subject of the presented research was projects co financed with European Union funds realised in years 2007–2013 in small towns of Pomeranian Voivodship. Projects which were included belong to 3 programmes: Innovative Economy Programme, Infrastructure and Environment Programme and Regional Operational Programme. The aim of the researches was study of the structure of projects according to its kind and town division. The other...
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The role of governance to support smart community development: a systematic literature review
PublikacjaThis paper studies the interaction between the smart community and smart governance concepts to elaborate on the role of governance to support local governments in developing smart communities’ strategies and solutions. We perform a systematic literature review to analyse how the concept of smart community has advanced in terms of its definitions, context, benefits, challenges, and enablers and propose a unified term with a focus...
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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
PublikacjaWastewater 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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Further development of the poroelastic road surface within the new Polish project SEPOR
PublikacjaRoad surfaces have a direct impact on noise generated by rolling tyres, the main and dominant source of noise of moving vehicles. Road surface texture, porosity and stiffness/elasticity govern the pavement contribution to tyre/road noise the most. An experimental PoroElastic Road Surface (PERS) is a wearing course with a high content of interconnected voids (pores) and with an elastic behavior due to the use of small particles...
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Machine Learning and data mining tools applied for databases of low number of records
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Multivariate Features Extraction and Effective Decision Making Using Machine Learning Approaches
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Machine learning techniques combined with dose profiles indicate radiation response biomarkers
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Driver’s Condition Detection System Using Multimodal Imaging and Machine Learning Algorithms
PublikacjaTo 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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Analyzing the Effectiveness of the Brain–Computer Interface for Task Discerning Based on Machine Learning
PublikacjaThe aim of the study is to compare electroencephalographic (EEG) signal feature extraction methods in the context of the effectiveness of the classification of brain activities. For classification, electroencephalographic signals were obtained using an EEG device from 17 subjects in three mental states (relaxation, excitation, and solving logical task). Blind source separation employing independent component analysis (ICA) was...
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Overcoming “Big Data” Barriers in Machine Learning Techniques for the Real-Life Applications
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Machine learning-based prediction of residual drift and seismic risk assessment of steel moment-resisting frames considering soil-structure interaction
PublikacjaNowadays, 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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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
PublikacjaBisphenols 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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Building the Learning Environment for Sustainable Development: a Co-creation approach
PublikacjaEducation 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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New Directions for Teaching and Learning
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Lead-free bismuth-based perovskites coupled with g–C3N4: A machine learning based novel approach for visible light induced degradation of pollutants
PublikacjaThe use of metal halide perovskites in photocatalytic processes has been attempted because of their unique optical properties. In this work, for the first time, Pb-free Bi-based perovskites of the Cs3Bi2X9 type (X = Cl, Br, I, Cl/Br, Cl/I, Br/I) were synthesized and subjected to comprehensive morphological, structural, and surface analyses, and photocatalytic properties in the phenol degradation reaction were examined. Furthermore,...
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High-Performance Machine-Learning-Based Calibration of Low-Cost Nitrogen Dioxide Sensor Using Environmental Parameter Differentials and Global Data Scaling
PublikacjaAccurate tracking of harmful gas concentrations is essential to swiftly and effectively execute measures that mitigate the risks linked to air pollution, specifically in reducing its impact on living conditions, the environment, and the economy. One such prevalent pollutant in urban settings is nitrogen dioxide (NO2), generated from the combustion of fossil fuels in car engines, commercial manufacturing, and food processing. Its...
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Smart Pen - new multimodal computer control tool for graphomotorical therapy
PublikacjaW sytuacji, gdy około 15% populacji uczniów wykazuje cechy dyslektyczne, koniecznością staje się wyposażenie szkół w efektywne narzędzia do diagnozy i terapii tego rodzaju zaburzeń. Dzięki wykorzystaniu tabletu i specjalnie skonstruowanego długopisu wyposażonego w czujniki nacisku uzyskano możliwość monitorowania wielu parametrów, które do tej pory były dla terapeutów całkowicie niedostępne (np. pomiar nacisku na podłoże czy ścisku...
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New technologies and diffusion of innovative financial products: Evidence on exchange-traded funds in selected emerging and developed economies
PublikacjaExchange-traded funds (ETFs) are one of the most rapidly-expanding categories of innovative financial products that have been introduced on many financial markets, in both emerging and developed economies. Our research contributes to the present state of knowledge by examining factors, including information and communication technologies (ICTs), influencing the diffusion of ETFs. In our research, we consider also the impact of...
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Machine Learning for Control Systems Security of Industrial Robots: a Post-covid-19 Overview
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Likelihood of Transformation to Green Infrastructure Using Ensemble Machine Learning Techniques in Jinan, China
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Advances in Architectures, Big Data, and Machine Learning Techniques for Complex Internet of Things Systems
PublikacjaTe feld of Big Data is rapidly developing with a lot of ongoing research, which will likely continue to expand in the future. A crucial part of this is Knowledge Discovery from Data (KDD), also known as the Knowledge Discovery Process (KDP). Tis process is a very complex procedure, and for that reason it is essential to divide it into several steps (Figure 1). Some authors use fve steps to describe this procedure, whereas others...
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Machine learning goes global: Cross-sectional return predictability in international stock markets
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Sperm segmentation and abnormalities detection during the ICSI procedure using machine learning algorithms
Publikacja(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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Edyta Gołąb-Andrzejak dr hab.
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Guest editorial: learning, scheduling, resource optimization, and evolution in smart artificial systems: challenges and support
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Journal of Motor Learning and Development
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Testing of the longest span soil-steel bridge in Europe – new quality in measurements
PublikacjaThe article describes interdisciplinary and comprehensive diagnostic tests of final bridge inspection and acceptance proposed for a soil – steel bridge made of corrugated sheets, being the European span length record holder (25.74 m). As an effect of an original concept a detailed and precise information about the structure response was collected. The load test design was based on the nonlinear numerical simulations performed by...