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Wyniki wyszukiwania dla: CONCRETE, DATA MINING, FAILURE OCCURRENCE PREDICTION, MACHINE CONCRETE FOUNDATIONS, MACHINE LEARNING
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Machine Learning Methods in Damage Prediction of Masonry Development Exposed to the Industrial Environment of Mines
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Speed estimation of a car at impact with a W-beam guardrail using numerical simulations and machine learning
PublikacjaThis paper aimed at developing a new method of estimating the impact speed of a passenger car at the moment of a crash into a W-beam road safety barrier. The determination of such a speed based on the accident outcomes is demanding, because often there is no access to full accident data. However, accurate determination of the impact speed is one of the key elements in the reconstruction of road accidents. A machine learning algorithm...
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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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An algorithm for selecting a machine learning method for predicting nitrous oxide emissions in municipal wastewater treatment plants
PublikacjaThis study presents an advanced algorithm for selecting machine learning (ML) models for nitrous oxide (N2O) emission prediction in wastewater treatment plants (WWTPs) employing the activated sludge process. The examined ML models comprised multivariate adaptive regression spline (MARS), support vector machines (SVM), and extreme gradient boosting (XGboost). The study explores the concept that involves new criteria to select the...
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Overcoming “Big Data” Barriers in Machine Learning Techniques for the Real-Life Applications
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Predicting seismic response of SMRFs founded on different soil types using machine learning techniques
PublikacjaPredicting 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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Experiments and calibration of a bond-slip relation and efficiency factors for textile reinforcement in concrete
PublikacjaTextile reinforcement yarns consist of many filaments, which can slip relative each other. At modelling of the global structural behaviour, interfilament slip in the yarns, and slip between the yarns and the concrete can be considered by efficiency factors for the stiffness and strength of the yarns, and by applying a bond-slip relation between yarns and concrete. In this work, an effective and robust method for calibration of...
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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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MP3vec: A Reusable Machine-Constructed Feature Representation for Protein Sequences
Publikacja—Machine Learning (ML) methods have been used with varying degrees of success on protein prediction tasks, with two inherent limitations. First, prediction performance often depends upon the features extracted from the proteins. Second, experimental data may be insufficient to construct reliable ML models. Here we introduce MP3vec, a transferable representation for protein sequences that is designed to be used specifically for sequence-to-sequence...
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Experimental and Machine-Learning-Assisted Design of Pharmaceutically Acceptable Deep Eutectic Solvents for the Solubility Improvement of Non-Selective COX Inhibitors Ibuprofen and Ketoprofen
PublikacjaDeep eutectic solvents (DESs) are commonly used in pharmaceutical applications as excellent solubilizers of active substances. This study investigated the tuning of ibuprofen and ketoprofen solubility utilizing DESs containing choline chloride or betaine as hydrogen bond acceptors and various polyols (ethylene glycol, diethylene glycol, triethylene glycol, glycerol, 1,2-propanediol, 1,3-butanediol) as hydrogen bond donors. Experimental...
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Experimental and Machine-Learning-Assisted Design of Pharmaceutically Acceptable Deep Eutectic Solvents for the Solubility Improvement of Non-Selective COX Inhibitors Ibuprofen and Ketoprofen
PublikacjaDeep eutectic solvents (DESs) are commonly used in pharmaceutical applications as excellent solubilizers of active substances. This study investigated the tuning of ibuprofen and ketoprofen solubility utilizing DESs containing choline chloride or betaine as hydrogen bond acceptors and various polyols (ethylene glycol, diethylene glycol, triethylene glycol, glycerol, 1,2-propanediol, 1,3-butanediol) as hydrogen bond donors. Experimental...
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Machine-to-Machine communication and data processing approach in Future Internet applications
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Detection of circulating tumor cells by means of machine learning using Smart-Seq2 sequencing
PublikacjaCirculating 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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Evaluation of Mechanical Properties of Two-Stage Concrete and Conventional Concrete Using Nondestructive Tests
PublikacjaDifferent types of concrete mixtures are used as building materials. The manufacturing process of two-stage concrete (TSC) differs from that of conventional concrete. This study investigated conventional mechanical properties derive empirical relations for estimation of the mechanical parameters of TSC and conventional concrete mixtures. TSC was used to prepare 216 specimens and conventional concrete was used to prepare 108 specimens...
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Harmony Search for Data Mining with Big Data
PublikacjaIn this paper, some harmony search algorithms have been proposed for data mining with big data. Three areas of big data processing have been studied to apply new metaheuristics. The first problem is related to MapReduce architecture that can be supported by a team of harmony search agents in grid infrastructure. The second dilemma involves development of harmony search in preprocessing of data series before data mining. Moreover,...
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Simple empirical formula to estimate the main geomechanical parameters of preplaced aggregate concrete and conventional concrete
PublikacjaPreplaced aggregate concrete (PAC) or two-stage concrete is a specific type of concrete successfully employed in many projects including underwater concrete structures, massive concrete structures, structures made of reinforced concrete, and improvement of concrete structures. PAC is significantly different than the conventional concrete. In this type of concrete, aggregates are initially poured into the mold, the voids between...
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Experimental tuning of AuAg nanoalloy plasmon resonances assisted by machine learning method
PublikacjaPlasmonic nanostructures based on AuAg nanoalloys were fabricated by thermal annealing of metallic films in an argon atmosphere. The nanoalloys were chosen because they can extend the wavelength range in which plasmon resonance occurs and thus allow the design of plasmonic platforms with the desired parameters. The influence of initial fabrication parameters and experimental conditions on the formation of nanostructures was investigated....
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Modelling of reinforced concrete beams under mixed shear-tension failure with different continuous FE approaches
PublikacjaW artykule omówiono wyniki modelowania numerycznego MES zachowania się wysokich belek żelbetowych podczas zniszczenia mieszanego ścinanie-rozciąganie. Obliczenia wykonano stosując różne modele dla betonu rozszerzone o długość charakterystyczną mikrostruktury w oparciu o teorie nielokalna. Otrzymano dobrą zgodność z wynikami doświadczalnymi.
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Machine Learning and Text Analysis in an Artificial Intelligent System for the Training of Air Traffic Controllers
PublikacjaThis chapter presents the application of new information technology in education for the training of air traffic controllers (ATCs). Machine learning, multi-criteria decision analysis, and text analysis as the methods of artificial intelligence for ATCs training have been described. The authors have made an analysis of the International Civil Aviation Organization documents for modern principles of ATCs education. The prototype...
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Exploring the Solubility Limits of Edaravone in Neat Solvents and Binary Mixtures: Experimental and Machine Learning Study
PublikacjaThis study explores the edaravone solubility space encompassing both neat and binary dissolution media. Efforts were made to reveal the inherent concentration limits of common pure and mixed solvents. For this purpose, the published solubility data of the title drug were scrupulously inspected and cured, which made the dataset consistent and coherent. However, the lack of some important types of solvents in the collection called...
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Data Mining Applications and Methods in Medicine
PublikacjaIn this paper we describe the research area of data mining and its applications in medicine. The origins of data mining and its crucial features are shortly presented. We discuss the specificity of medicine as an application area for computer systems. Characteristic features of the medical data are investigated. Common problems in the area are also presented as well as the strengths and capabilities of the data mining methods....
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Application of fiber optic sensors using Machine Learning algorithms for temperature measurement of lithium-ion batteries
PublikacjaOptical fiber sensorsusing low-coherence interferometry require processing ofthe output spectrum or interferogramto quickly and accurately determine the instantaneous value of the measured quantity, such as temperature.Methods based on machine learning are a good candidate for this application. The application of four such methods in an optical fiber temperature sensoris demonstrated.Using aZnO-coated...
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Energy consumption optimization in wastewater treatment plants: Machine learning for monitoring incineration of sewage sludge
PublikacjaBiomass 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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Machine Learning Assisted Interactive Multi-objectives Optimization Framework: A Proposed Formulation and Method for Overtime Planning in Software Development Projects
PublikacjaMachine Learning Assisted Interactive Multi-objectives Optimization Framework: A Proposed Formulation and Method for Overtime Planning in Software Development Projects Hammed A. Mojeed & Rafal Szlapczynski Conference paper First Online: 14 September 2023 161 Accesses Part of the Lecture Notes in Computer Science book series (LNAI,volume 14125) Abstract Software development project requires proper planning to mitigate risk and...
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Performance Analysis of Machine Learning Methods with Class Imbalance Problem in Android Malware Detection
PublikacjaDue 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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Prediction of Wastewater Quality at a Wastewater Treatment Plant Inlet Using a System Based on Machine Learning Methods
PublikacjaOne of the important factors determining the biochemical processes in bioreactors is the quality of the wastewater inflow to the wastewater treatment plant (WWTP). Information on the quality of wastewater, sufficiently in advance, makes it possible to properly select bioreactor settings to obtain optimal process conditions. This paper presents the use of classification models to predict the variability of wastewater quality at...
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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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Double Fed Induction Machine Drives
PublikacjaContents of the Chapter 22:Machine model.Properties of the DFM.Steady state machine operation.Control rules and decoupled control.Decoupling based on MM machine model.Decoupling based on vector model.Decoupling based on rotor current equation.Overall control system.Control system based on MM model.Control system based on vector model.Estimation of variables.Calculation of the angle between stator and rotor.Remarks about digital...
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Prediction of cast-in-place concrete strength of the extradosed bridge deck based on temperature monitoring and numerical simulations
PublikacjaThe work is devoted to the implementation of a monitoring system for high performance concrete embedded in the span of an extradosed bridge deck using a modified maturity method augmented by numerical simulations conducted by the authors’ FEM code. The paper presents all research stages of bridge construction and considers the conclusions drawn from the results of laboratory tests, field measurements, and numerical calculations....
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Influence of stirrups in a concrete shell on strengthening reinforced concrete column
PublikacjaTwelve concrete columns, with a 150x150mm square section and three columns with a circular section (d=200mm), are tested to investigate the effect of strengthening by RC jacket. Based on a confined concrete model for axial static loading, an analytical methods, reported in the literature are proposed to predict the behavior of columns with RC jacket. The results support the conception that the effect of strengthening depends...
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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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Unsupervised machine-learning classification of electrophysiologically active electrodes during human cognitive task performance
PublikacjaIdentification 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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Failure analysis of a high-speed induction machine driven by a SiC-inverter and operating on a common shaft with a high-speed generator
PublikacjaDue to ongoing research work, a prototype test rig for testing high-speed motors/generators has been developed. Its design is quite unique as the two high- speed machines share a single shaft with no support bearings between them. A very high maximum operating speed, up to 80,000 rpm, was required. Because of the need to minimise vibration during operation at very high rotational speeds, rolling bearings were used. To eliminate...
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Shear resistance of low height precast concrete lintels
PublikacjaThe scope of the paper is to investigate analytically and determine experimentally the shear resistance of low height reinforced precast concrete lintels. The chosen procedures included in national and international standards applied for the design of structural concrete elements to an estimation of shear behaviour of reinforced concrete elements are described. The characteristic and designed shear strength of precast concrete...
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Evaluation the effectiveness of virtual machine integrated with CPU
PublikacjaIn the paper effectiveness of example CPU with integrated virtual machine is presented. The idea and implementation of virtual machine is shown. In next sections reference CPU and sample virtual machine is described. Finally optimality of the translation process is analysed.
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Size effect in concrete under splitting tension
PublikacjaThe size effect is a fundamental phenomenon in concrete materials. It denotes that both the nominal structural strength and material ductility always decrease with increasing element size under tension. In the paper splitting tensile tests on cylindrical concrete specimens with the different diameter were carried out. Two types of the loading strip (plywood board and steel cylinder) were used. The concrete strength and ductility...
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The lethal effect of hydrotechnical concrete on freshwater Bivalvia
PublikacjaMost hydrotechnical buildings under construction demand the concrete mixture to be set directly under water. The main reason for such a procedure is to limit the washing away of the the concrete binding mixture and to increase the efficiency of organisation of work so as to ensure continuity in concreting. The impact on the aquatic environment of recent developments in concrete technology and the use of new components has not yet...
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An Approach to Data Reduction and Integrated Machine Classification
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PERFORMANCE COMPARISON OF MACHINE LEARNING ALGORITHMS FOR PREDICTIVE MAINTENANCE
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Machine Learning for Sensorless Temperature Estimation of a BLDC Motor
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Machine learning applied to bi-heterocyclic drugs recognition
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Machine Learning Modelling and Feature Engineering in Seismology Experiment
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MACHINE LEARNING–BASED ANALYSIS OF ENGLISH LATERAL ALLOPHONES
PublikacjaAutomatic 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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MACHINE LEARNING SYSTEM FOR AUTOMATED BLOOD SMEAR ANALYSIS
PublikacjaIn 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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The use of machine learning for face regions detection in thermograms
PublikacjaThe 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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Playback detection using machine learning with spectrogram features approach
PublikacjaThis paper presents 2D image processing approach to playback detection in automatic speaker verification (ASV) systems using spectrograms as speech signal representation. Three feature extraction and classification methods: histograms of oriented gradients (HOG) with support vector machines (SVM), HAAR wavelets with AdaBoost classifier and deep convolutional neural networks (CNN) were compared on different data partitions in respect...
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Reinforced concrete thin wall dome after eighty years of operation in maritime climate environment
PublikacjaThe paper presents a description of the construction elements of the Gdynia Seaport main hall dome. Firstly, it provides information about the technical condition of the dome’s structure. Secondly, it examines the strength analysis of the thin-walled reinforced concrete dome covering. Throughout the last 80 years the building has been exposed to an unfavourable marine climate. The analysis of the state of stress and deformations...
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Standard and modified falling mass impact tests on preplaced aggregatefibrous concrete and slurry infiltrated fibrous concrete
PublikacjaAlthough several studies have been conducted to evaluate the impact response of concrete using theAmerican Concrete Institute (ACI) 544-2R falling mass impact test, the variations in test results are themain drawback of this testing method. This study aims to reduce the variations in experimental impacttest results by introducing two simple test setup modifications; (1) using coarse or fine aggregate bed-ding as an alternative...
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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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A concept of heterogeneous numerical model of concrete for GPR simulations
PublikacjaThe Ground Penetrating Radar (GPR) method, which is increasingly being used in the non-destructive diagnostics of reinforced concrete structures, often needs more accurate interpretation tools for analysis of experimental data. Recently, there has been growing interest in developing of various numerical models for exhaustive understanding of GPR data. This paper presents the concept of a heterogeneous numerical model of concrete,...