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Wyniki wyszukiwania dla: CONCRETE, DATA MINING, FAILURE OCCURRENCE PREDICTION, MACHINE CONCRETE FOUNDATIONS, MACHINE LEARNING
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Structural Concrete
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Machine Learning- and Artificial Intelligence-Derived Prediction for Home Smart Energy Systems with PV Installation and Battery Energy Storage
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Numerical simulation of hardening of concrete plate
PublikacjaThe 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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A Data Driven Model for Predicting RNA-Protein Interactions based on Gradient Boosting Machine
PublikacjaRNA protein interactions (RPI) play a pivotal role in the regulation of various biological processes. Experimental validation of RPI has been time-consuming, paving the way for computational prediction methods. The major limiting factor of these methods has been the accuracy and confidence of the predictions, and our in-house experiments show that they fail to accurately predict RPI involving short RNA sequences such as TERRA RNA....
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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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International Journal of Machine Learning and Cybernetics
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International Journal of Machine Learning and Computing
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Machine-learning-based precise cost-efficient NO2 sensor calibration by means of time series matching and global data pre-processing
PublikacjaAir pollution remains a considerable contemporary challenge affecting life quality, the environment, and economic well-being. It encompasses an array of pollutants—gases, particulate matter, biological molecules—emanating from sources such as vehicle emissions, industrial activities, agriculture, and natural occurrences. Nitrogen dioxide (NO2), a harmful gas, is particularly abundant in densely populated urban areas. Given its...
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Acoustic emission signals in concrete beams under 3-point bending (beams #1, #2, #3)
Dane BadawczeThe DataSet contains the results of the mechanical behaviour of concrete beams with dimensions 40 x 40 x 160 cm3under the 3-point bending. The beams were made of concrete with the following ingredients: cement CEM I 42.5R (330 kg/m3), aggregate 0/2 mm (710 kg/m3), aggregate 2/8 mm (664 kg/m3), aggregate 8/16 mm (500 kg/m3), water (165 kg/m3) and super-plasticizer...
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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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Finger Vein Presentation Attack Detection Method Using a Hybridized Gray-Level Co-Occurrence Matrix Feature with Light-Gradient Boosting Machine Model
PublikacjaPresentation Attack Detection (PAD) is crucial in biometric finger vein recognition. The susceptibility of these systems to forged finger vein images is a significant challenge. Existing approaches to mitigate presentation attacks have computational complexity limitations and limited data availability. This study proposed a novel method for identifying presentation attacks in finger vein biometric systems. We have used optimal...
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Machine-Learning-Powered EM-Based Framework for Efficient and Reliable Design of Low Scattering Metasurfaces
PublikacjaPopularity 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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Machine Learning-Based Wetland Vulnerability Assessment in the Sindh Province Ramsar Site Using Remote Sensing Data
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Selected Problems of Machine Dynamics
Kursy OnlineThe following set of lectures is performed: 1. LECTURE No.1 - INTRODUCTION TO SELECTED PROBLEMS OF MACHINE DYNAMICS. STRUCTURES and MACHINES 2. LECTURE No.2 - ENVIRONMENT, LOADS ON STRUCTURES and MACHINES 3. LECTURE No.3 - DYNAMICS of STRUCTURES and MACHINES 4. LECTURE No.4 - STRENGTH of STRUCTURES and MACHINES 5. LECTURE No.5 - SPECIAL PROBLEMS ASSOCIATED with DYNAMICS and STRENGTH of STRUCTURES and MACHINES
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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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A Computationally Efficient Model for Predicting Successful Memory Encoding Using Machine-Learning-based EEG Channel Selection
PublikacjaComputational cost is an important consideration for memory encoding prediction models that use data from dozens of implanted electrodes. We propose a method to reduce computational expense by selecting a subset of all the electrodes to build the prediction model. The electrodes were selected based on their likelihood of measuring brain activity useful for predicting memory encoding better than chance (in terms of AUC). A logistic...
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CEMENT & CONCRETE COMPOSITES
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CEMENT CONCRETE AND AGGREGATES
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Advances in Concrete Construction
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Nordic Concrete Research
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Systemy z Uczeniem Maszynowym / Systems with Machine Learning 2022/2023
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Measurements of the heat of hydration released by concrete specimens cured under adiabatic conditions
Dane BadawczeThe DataSet contains measurements of heat of hydartion of concrete cubes (150 x 150 x 150 mm) cured under adiabatic conditions. The specimens were moulded from six types of concrete mixtures produced in the laboratory conditions. Mix #1: Portland cement CEM I 42.5R and gravel aggregate, mix #2: CEM I 42.5R and basalt aggregate, mix#3: Portland-composite...
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ADAPTATION OF ENGINEERING FEA-BASED ALGORITHMS TO LCF FAILURE AND MATERIAL DATA PREDICTION IN OFFSHORE DESIGN
PublikacjaThere is an ever growing industrial demand for quantitative assessment of fatigue endurance of critical structural details. Although FEA-based calculations have become a standard in engineering design, problems involving the Low-To-Medium cycle range (101-104) remain challenging. This paper presents an attempt to optimally choose material data, meshing density and other algorithm settings in the context of recent design of the...
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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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Debonding Detection in Reinforced Concrete Beams with the Use of Guided Wave Propagation
PublikacjaOne of the most frequent damage of the reinforced concrete structures is debonding between steel bar and concrete cover. In the case of debonding occurrence not only the strength of the structure decreases, but also it is more vulnerable to corrosion damages. For this reason fast and effective methods of debonding detection in an early stage of its development need a significant boost. The paper presents analytical and experimental...
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Data, Information, Knowledge, Wisdom Pyramid Concept Revisited in the Context of Deep Learning
PublikacjaIn this paper, the data, information, knowledge, and wisdom (DIKW) pyramid is revisited in the context of deep learning applied to machine learningbased audio signal processing. A discussion on the DIKW schema is carried out, resulting in a proposal that may supplement the original concept. Parallels between DIWK pertaining to audio processing are presented based on examples of the case studies performed by the author and her collaborators....
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Szymon Zaporowski mgr inż.
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Forecasting energy consumption and carbon dioxide emission of Vietnam by prognostic models based on explainable machine learning and time series
PublikacjaThis study assessed the usefulness of algorithms in estimating energy consumption and carbon dioxide emissions in Viet- nam, in which the training dataset was used to train the models linear regression, random forest, XGBoost, and AdaBoost, allowing them to comprehend the patterns and relationships between population, GDP, and carbon dioxide emissions, energy consumption. The results revealed that random forest, XGBoost, and AdaBoost...
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Statistical Data Pre-Processing and Time Series Incorporation for High-Efficacy Calibration of Low-Cost NO2 Sensor Using Machine Learning
PublikacjaAir pollution stands as a significant modern-day challenge impacting life quality, the environment, and the economy. It comprises various pollutants like gases, particulate matter, biological molecules, and more, stemming from sources such as vehicle emissions, industrial operations, agriculture, and natural events. Nitrogen dioxide (NO2), among these harmful gases, is notably prevalent in densely populated urban regions. Given...
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Broken Rotor Symptons in the Sensorless Control of Induction Machine
PublikacjaInverter fed sensorless controlled variable speed drives with induction machine are widely used in the industry applications, also in wind power generation and electric vehicles. On-line self diagnostic systems implementation is needed for early stage fault detection and avoiding a critical fault. Diagnostic algorithms in modern DSP-based controllers can operate simultaneously with control system functions. In the closed-loop controlled...
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Anna Baj-Rogowska dr
OsobyAnna Baj-Rogowska zatrudniona jest na stanowisku adiunkta w Katedrze Informatyki w Zarządzaniu (Politechnika Gdańska, Wydział Zarządzania i Ekonomii). Jej wyższa edukacja związana jest z Uniwersytetem Gdańskim, gdzie ukończyła magisterskie studia informatyczne, studia doktoranckie i następnie uzyskała stopień naukowy doktora nauk ekonomicznych w zakresie nauk o zarządzaniu (Katedra Informatyki Ekonomicznej na Wydziale Zarządzania...
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Evaluation of the resistance of steel–concrete adhesive connection in reinforced concrete beams using guided wave propagation
PublikacjaThe development of the nondestructive diagnostic methods is of significant importance in the last decades. A special attention is paid to diagnostics of reinforced concrete structures, which are very popular in the civil engineering field. A possible use of the guided waves in the estimation of the resistance of steel–concrete adhesive connection is studied in the following paper. The relationships relating adhesive connection...
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Damage of a post-tensioned concrete bridge – Unwanted cracks of the girders
PublikacjaThe cracking of a post-tensioned T-beam superstructure, which was built using the incremental launching method, is analyzed in the paper. The problem is studied in detail, as specific damage was observed in the form of longitudinal cracks, especially in the mid-height zone of the girder at the interface of two assembly sections. The paper is a case study. A detailed inspection is done and non-destructive testing results of the...
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Numerical simulation of the influence of the selected factors on the performance of a concrete road barrier H2/W5/B
PublikacjaThis paper discuss the influence of selected factors on the performance of a concrete road barrier H2/W5/B. Modelling techniques of a concrete road safety system were briefly discussed. Comparison to the full scale crash test results has been shown. The concrete road safety barrier has been investigated for evaluation of the overall damage after collision under various initial conditions. The failure assessment criterion has been...
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A novel hybrid adaptive framework for support vector machine-based reliability analysis: A comparative study
PublikacjaThis study presents an innovative hybrid Adaptive Support Vector Machine - Monte Carlo Simulation (ASVM-MCS) framework for reliability analysis in complex engineering structures. These structures often involve highly nonlinear implicit functions, making traditional gradient-based first or second order reliability algorithms and Monte Carlo Simulation (MCS) time-consuming. The application of surrogate models has proven effective...
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A novel heterogeneous model of concrete for numerical modelling of ground penetrating radar
PublikacjaThe ground penetrating radar (GPR) method has increasingly been applied in the non-destructive testing of reinforced concrete structures. The most common approach to the modelling of radar waves is to consider concrete as a homogeneous material. This paper proposes a novel, heterogeneous, numerical model of concrete for exhaustive interpretation of GPR data. An algorithm for determining the substitute values of the material constants...
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Data augmentation for improving deep learning in image classification problem
PublikacjaThese days deep learning is the fastest-growing field in the field of Machine Learning (ML) and Deep Neural Networks (DNN). Among many of DNN structures, the Convolutional Neural Networks (CNN) are currently the main tool used for the image analysis and classification purposes. Although great achievements and perspectives, deep neural networks and accompanying learning algorithms have some relevant challenges to tackle. In this...
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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
PublikacjaThe 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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Adiabatic calorimetry results for fresh concrete mixes M0 and M100
Dane BadawczeAdiabatic calorimetry results for fresh 3D printed concrete mixes (M0 and M100) determined using Controls S.p.A., Italy calorimeter
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Concrete temperature measurements of cubic specimens cured under isothermal and semi-adiabatic conditions
Dane BadawczeThe DataSet contains temperature measurements of concrete cubes (150 x 150 x 150 mm) cured under isothermal and semi-adiabatic conditions. The specimens were moulded from six types of concrete mixtures produced in the laboratory conditions. Mix #1: Portland cement CEM I 42.5R and gravel aggregate, mix #2: CEM I 42.5R and basalt aggregate, mix#3: Portland-composite...
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Ultrasound monitoring for evaluation of damage in reinforced concrete
PublikacjaThe paper deals with automated monitoring of damage evolution in concrete elements subjected to three-point bending tests. The monitoring is based on the nonlinear interactions of traveling ultrasonic waves with micro-crack zones inside the concrete specimens and surface-breaking cracks. The developed procedure assumes semi-continuous ultrasonic testing during the element full loading cycle and generation of the power spectral...
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Machine Learning Applied to Aspirated and Non-Aspirated Allophone Classification—An Approach Based on Audio "Fingerprinting"
PublikacjaThe purpose of this study is to involve both Convolutional Neural Networks and a typical learning algorithm in the allophone classification process. A list of words including aspirated and non-aspirated allophones pronounced by native and non-native English speakers is recorded and then edited and analyzed. Allophones extracted from English speakers’ recordings are presented in the form of two-dimensional spectrogram images and...
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The Effect of Fly Ash Microspheres on the Pore Structure of Concrete
PublikacjaThe fly ash microspheres (FAMs) formed during the mineral transformation stage in coal combustion are hollow spherical particles with a density less than water. This paper presents the results of X‐ray micro‐computed tomography and an automatic image analysis system of the porosity in the structure of hardened concrete with microspheres. Concrete mixtures with ordinary Portland cement and two substitution rates of cement by microspheres—5%...
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Self-compacting grout to produce two-stage concrete
PublikacjaTraditional concrete (TC) is primarily composed of a mixture of cement, fine and coarse aggregates, and water. TC is made by mixing together all the components before placing them. Using non-traditional concrete (two-stage concrete) to solve and to eliminate the problem of the aggregate segregation which appears in TC and in the self-compacting concrete. Two-stage concrete (TSC) consists of two main components, namely the grout...
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Influence of selected additives and admixtures on underwater concrete and the environment
PublikacjaThe intensive civilization development has an influence on searching for new possibilities connected with extension of city agglomerations, both the areas of flat building and the industrial areas. One of the most interesting solution is to use water reservoirs, rivers and sea areas. The extension of buildings has an influence on building materials, especially hydrotechnical, which means development of production of hydrotechnical...
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Application of gpr method in diagnostics of reinforced concrete structures
PublikacjaThis paper presents an application of the ground penetration method (GPR) for diagnostics of reinforced concrete structures. In situ measurements were conducted for three civil engineering structures: the ground floor structure, the abutment of the railway viaduct and the concrete well. The dual polarized ground penetrating radar with the antenna operating at a center frequency of 2 GHz was used for GPR surveys. Three different...
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Machine Design PG_00059691
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Efficient sampling of high-energy states by machine learning force fields
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POPULATION-BASED MULTI-AGENT APPROACH TO SOLVING MACHINE LEARNING PROBLEMS
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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...