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Wyniki wyszukiwania dla: MARKDOWN, BOOKDOWN, R-EXAMS, TUTORIALS, MOODLE, E- LEARNING, WEBEXERCISES, GITHUB, DATA ANALYSIS.
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Business Analysis Winter 2023/24
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Versatile prototyping platform for Data Processing Boards for CBM experiment
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Improving the prediction of biochar production from various biomass sources through the implementation of eXplainable machine learning approaches
PublikacjaExamining 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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Czy należy bać się E?
PublikacjaW ciągu ostatnich lat nastąpił gwałtowny rozwój rynku żywnościowego. Producenci chcąc utrzymać się na rynku dopasowują się do nowych wymagań i rosnących potrzeb konsumenta. Duża konkurencja w branży żywnościowej zmusza wytwórców do ciągłego obniżania kosztów produkcji przy jednoczesnym zachowaniu atrakcyjności wyrobu. Obecnie można kupić niemal wszystko: kilka rodzajów chleba, masła, serów, wędlin i... czego tylko dusza zapragnie....
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Machine learning-based seismic fragility and seismic vulnerability assessment of reinforced concrete structures
PublikacjaMany 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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Machine learning-based prediction of preplaced aggregate concrete characteristics
PublikacjaPreplaced-Aggregate Concrete (PAC) is a type of preplaced concrete where coarse aggregate is placed in the mold and a Portland cement-sand grout with admixtures is injected to fill the voids. Due to the complex nature of PAC, many studies were conducted to determine the effects of admixtures and the compressive and tensile strengths of PAC. Considering that a prediction tool is needed to estimate the compressive and tensile...
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Machine learning-based prediction of preplaced aggregate concrete characteristics
PublikacjaPreplaced-Aggregate Concrete (PAC) is a type of preplaced concrete where coarse aggregate is placed in the mold and a Portland cement-sand grout with admixtures is injected to fill the voids. Due to the complex nature of PAC, many studies were conducted to determine the effects of admixtures and the compressive and tensile strengths of PAC. Considering that a prediction tool is needed to estimate the compressive and tensile strengths...
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International Journal of Research in E-learning
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Primary role identification in e-mail networks using pattern subgraphs and sequence diagrams
PublikacjaSocial networks often forms very complex structures that additionally change over time. Description of actors' roles in such structures requires to take into account this dynamics reflecting behavioral characteristics of the actors. A role can be defined as a sequence of different types of activities. Various types of activities are modeled by pattern subgraphs, whereas sequences of these activities are modeled by sequence diagrams....
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Anomaly Detection in Railway Sensor Data Environments: State-of-the-Art Methods and Empirical Performance Evaluation
PublikacjaTo date, significant progress has been made in the field of railway anomaly detection using technologies such as real-time data analytics, the Internet of Things, and machine learning. As technology continues to evolve, the ability to detect and respond to anomalies in railway systems is once again in the spotlight. However, railway anomaly detection faces challenges related to the vast infrastructure, dynamic conditions, aging...
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Thermogravimetric analysis (TGA ) and derivative thermogravimetry (DTG) results for potassium citrate
Dane BadawczeThese data contains thermogravimetric analysis (TGA ) and derivative thermogravimetry (DTG) results for thermal decomposition of potassium citrate.
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Recognition of two-phase flow patterns with the use of dynamic image analysis
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DNAffinity: a machine-learning approach to predict DNA binding affinities of transcription factors
PublikacjaWe present a physics-based machine learning approach to predict in vitro transcription factor binding affinities from structural and mechanical DNA properties directly derived from atomistic molecular dynamics simulations. The method is able to predict affinities obtained with techniques as different as uPBM, gcPBM and HT-SELEX with an excellent performance, much better than existing algorithms. Due to its nature, the method can...
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Improving Effectiveness of SVM Classifier for Large Scale Data
PublikacjaThe paper presents our approach to SVM implementation in parallel environment. We describe how classification learning and prediction phases were pararellised. We also propose a method for limiting the number of necessary computations during classifier construction. Our method, named one-vs-near, is an extension of typical one-vs-all approach that is used for binary classifiers to work with multiclass problems. We perform experiments...
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Gdansk 2020, Obroncow Wybrzeza - pedestrian crossing (E) street - video data - pedestrian, bicycles, vehicles
Dane BadawczeThe data contain video traffic data (pedestrian, cyclists, vehicles) registered at Obroncow Wybrzeza street. Date 12.08.2020, 6:00-20:00. The video camera was installed around pedestrian crossings. Camera was mounted on 7-meter-high mast.
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Machine-Learning-Based Global Optimization of Microwave Passives with Variable-Fidelity EM Models and Response Features
PublikacjaMaximizing microwave passive component performance demands precise parameter tuning, particularly as modern circuits grow increasingly intricate. Yet, achieving this often requires a comprehensive approach due to their complex geometries and miniaturized structures. However, the computational burden of optimizing these components via full-wave electromagnetic (EM) simulations is substantial. EM analysis remains crucial for circuit...
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Intra-subject class-incremental deep learning approach for EEG-based imagined speech recognition
PublikacjaBrain–computer interfaces (BCIs) aim to decode brain signals and transform them into commands for device operation. The present study aimed to decode the brain activity during imagined speech. The BCI must identify imagined words within a given vocabulary and thus perform the requested action. A possible scenario when using this approach is the gradual addition of new words to the vocabulary using incremental learning methods....
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Love your mistakes!—they help you adapt to change. How do knowledge, collaboration and learning cultures foster organizational intelligence?
PublikacjaPurpose: The study aims to determine how the acceptance of mistakes is related to adaptability to change in a broad organizational context. Therefore it explores how knowledge, collaboration, and learning culture (including “acceptance of mistakes”) might help organizations overcome their resistance to change. Methodology: The study uses two sample groups: students aged 18–24 (330 cases) and employees aged >24 (326 cases) who work...
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Learning & Memory
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Adult Learning
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Open Learning
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For the Learning of Mathematics
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Teaching & Learning
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Vocations and Learning
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LEARNing Landscapes
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Action Learning
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Support for Learning
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Ubiquitous Learning
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Learning Disabilities
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Online Learning
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LEARNING & MEMORY
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MACHINE LEARNING
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LEARNING & BEHAVIOR
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LANGUAGE LEARNING
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Learning and Instruction
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MANAGEMENT LEARNING
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LEARNING AND MOTIVATION
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Metacognition and Learning
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Multibeam data processing for 3D object shape reconstruction
PublikacjaThe technology of hydroacoustic scanning offers an efficient and widely-used source of geospatial information regarding underwater environments, providing measurement data which usually have the structure of irregular groups of points known as point clouds. Since this data model has known disadvantages, a different form of representation based on representing surfaces with simple geometric structures, such as edges and facets,...
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Active management of equipment cooling in hoteling data centers
PublikacjaHoteling data centers are designated for housing computing and storage units of many, usually small customers, as opposed to traditional data centers supporting own computing and storage resources of a bigger company. One of the services to be provided to consumer’s equipment is cooling. Cooling in data centers is prevalently achieved by circulating air in computer room. Efficient cooling requires delivering cold air from central...
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Przetwarzanie emocjonalne i scenariusze jego zastosowania w edukacji i e-edukacji
PublikacjaW pracy zbadano możliwości i celowość zastosowania mechanizmów i narzędzi przetwarzania emocjonalnego w e-edukacji. Wyróżniono i opisano szereg scenariuszy użycia technik afektywnych, zarówno w zastosowaniu komputerów do wspomagania tradycyjnych procesów edukacyjnych, jak i do nauczania za pośrednictwem środków elektronicznych. Jedne z najciekawszych zastosowań dotyczą poszukiwania optymalnej afektywnej przestrzeni uczenia się,...
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Use of LIDAR Data in the 3D/4D Analyses of the Krakow Fortress Objects
PublikacjaThe article presents partial results of studies within the framework of the international project "Cultural Heritage Through Time" (CHT2). The subject of the study were forts of the Krakow Fortress, which had been built by the Austrians between 1849-1914 in order to provide defence against the Russians. Research works were aimed at identifying architectural changes occurring in different time periods in relation to selected...
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Fundamentals of Data-Driven Surrogate Modeling
PublikacjaThe primary topic of the book is surrogate modeling and surrogate-based design of high-frequency structures. The purpose of the first two chapters is to provide the reader with an overview of the two most important classes of modeling methods, data-driven (or approx-imation), as well as physics-based ones. These are covered in Chap-ters 1 and 2, respectively. The remaining parts of the book give an exposition of the specific aspects...
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Split-Beam Echosounder Data from Puck Bay
PublikacjaThe acoustic data was collected in 2018–2019 in the Bay of Puck in the seasons: autumn, winter, spring. The data was collected during the day and night using three split-beam echosounders with frequencies of 38 kHz, 120 kHz and 333 kHz at a designated study area not far from the city of Hel, while the ship was sailing. To ensure data quality, the echosounders were calibrated and passive noise was measured.
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Enhanced susceptibility of SARS-CoV-2 spike RBD protein assay targeted by cellular receptors ACE2 and CD147: Multivariate data analysis of multisine impedimetric response
PublikacjaSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) enters the cells through the binding of spike protein to the host cell surface-expressing angiotensin-converting enzyme 2 (ACE2) or by endocytosis mediated by extracellular matrix metalloproteinase inducer (CD147). We present extended statistical studies of the multisine dynamic electrochemical impedance spectroscopy (DEIS) revealing interactions between Spike RBD and...
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Reversible data hiding in encrypted DICOM images using sorted binary sequences of pixels
PublikacjaIn this paper, a novel reversible data hiding method for encrypted DICOM images is proposed. The method utilizes binary decomposition of the input data paired with a sorting process of the obtained binary sequences to ensure efficient data embedding in each predefined data block for specific most significant bit (MSB) planes while exploiting the properties of run-length encoding. The proposed scheme is lossless, and based on the...
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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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A Workflow Application for Parallel Processing of Big Data from an Internet Portal
PublikacjaThe paper presents a workflow application for efficient parallel processing of data downloaded from an Internet portal. The workflow partitions input files into subdirectories which are further split for parallel processing by services installed on distinct computer nodes. This way, analysis of the first ready subdirectories can start fast and is handled by services implemented as parallel multithreaded applications using multiple...
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INVESTIGATION OF THE LOMBARD EFFECT BASED ON A MACHINE LEARNING APPROACH
PublikacjaThe 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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Predicting the Purchase of Electricity Prices for Renewable Energy Sources Based on Polish Power Grids Data Using Deep Learning Models for Controlling Small Hybrid PV Microinstallations
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