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Search results for: buckling-restrained braced frame machine-learning algorithm residual interstory drift seismic retrofit seismic performance curve seismic failure probability
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Probabilistic assessment of SMRFs with infill masonry walls incorporating nonlinear soil-structure interaction
PublicationInfill Masonry Walls (IMWs) are used in the perimeter of a building to separate the inner and outer space. IMWs may affect the lateral behavior of buildings, while they are different from those partition walls that separate two inner spaces. This study focused on the seismic vulnerability assessment of Steel Moment-Resisting Frames (SMRFs) assuming different placement of IMWs incorporating nonlinear Soil-Structure Interaction (SSI)....
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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
PublicationDue 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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Experimental tuning of AuAg nanoalloy plasmon resonances assisted by machine learning method
PublicationPlasmonic 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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Prediction of energy consumption and evaluation of affecting factors in a full-scale WWTP using a machine learning approach
PublicationTreatment of municipal wastewater to meet the stringent effluent quality standards is an energy-intensive process and the main contributor to the costs of wastewater treatment plants (WWTPs). Analysis and prediction of energy consumption (EC) are essential in designing and operating sustainable energy-saving WWTPs. In this study, the effect of wastewater, hydraulic, and climate-based parameters on the daily consumption of EC by...
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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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THE EFFECT OF WOOD DRYING METHOD ON THE GRANULARITY OF SAWDUST OBTAINED DURING THE SAWING PROCESS USING THE FRAME SAWING MACHINE
PublicationThe experimental results of the study focused on the effect of drying processes of warm air drying at the temperature of 6580°C and warm air-steam mixture drying at the temperature of 105°C of pine and beech wood to the size of sawdust grains created by cutting using RPW 15M frame saw is presented in the paper. Particle size analysis of dry sawdust was performed using two methods - screening method and optical method based on...
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Machine Learning and Text Analysis in an Artificial Intelligent System for the Training of Air Traffic Controllers
PublicationThis 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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Detection of People Swimming in Water Reservoirs with the Use of Multimodal Imaging and Machine Learning
PublicationEvery year in many countries, there are fatal unintentional drownings in different water reservoirs like swimming pools, lakes, seas, or oceans. The existing threats of this type require creating a method that could automatically supervise such places to increase the safety of bathers. This work aimed to create methods and prototype solutions for detecting people bathing in water reservoirs using a multimodal imaging system and...
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Self-Supervised Learning to Increase the Performance of Skin Lesion Classification
PublicationTo successfully train a deep neural network, a large amount of human-labeled data is required. Unfortunately, in many areas, collecting and labeling data is a difficult and tedious task. Several ways have been developed to mitigate the problem associated with the shortage of data, the most common of which is transfer learning. However, in many cases, the use of transfer learning as the only remedy is insufficient. In this study,...
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Air flow phenomena in the model of the blind drift
PublicationIn the presented paper, Particle Image Velocimetry (PIV) has been used to investigate flow pattern and turbulent structure in the model of blind drift. The presented model exist in mining, and has been analyzed to resolve ventilation issues. Blind region is particularly susceptible to unsafe methane accumulation. The measurement system allows us to evaluate all components of the velocity vector in channel cross-section simultaneously....
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Cost-Efficient Multi-Objective Design of Miniaturized Microwave Circuits Using Machine Learning and Artificial Neural Network
PublicationDesigning microwave components involves managing multiple objectives such as center frequencies, impedance matching, and size reduction for miniaturized structures. Traditional multi-objective optimization (MO) approaches heavily rely on computationally expensive population-based methods, especially when exe-cuted with full-wave electromagnetic (EM) analysis to guarantee reliability. This paper introduces a novel and cost-effective...
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MACHINE LEARNING–BASED ANALYSIS OF ENGLISH LATERAL ALLOPHONES
PublicationAutomatic 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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Genetic Algorithm Approach for Gains Selection of Induction Machine Extended Speed Observer
PublicationThe subject of this paper is gains selection of an extended induction machine speed observer. A high number of gains makes manual gains selection difficult and due to nonlinear equations of the observer, well-known methods of gains selection for linear systems cannot be applied. A method based on genetic algorithms has been proposed instead. Such an approach requires multiple fitness function calls; therefore, using a quality index...
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Determinants of anxiety levels among young males in a threat of experiencing military conflict–Applying a machine-learning algorithm in a psychosociological study
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Influence of frame sawing machine´s kinematics on saw blade tooth wear.
PublicationW pracy przedstawiono wpływ kinematyki pilarki ramowej na zużycie ostrzy piłtrakowych.
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Torsional buckling and post-buckling of columns made of aluminium alloy
PublicationThe paper concerns torsional buckling and the initial post-buckling of axially compressed thin-walled aluminium alloy columns with bisymmetrical cross-section. It is assumed that the column material behaviour is described by the Ramberg–Osgood constitutive equation in non-linear elastic range. The stationary total energy principle is used to derive the governing non-linear differential equation. An approximate solution of the equation...
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Flexural buckling and post-buckling of columns made of aluminium alloy
PublicationThe paper concerns flexural buckling and initial post-buckling of axially compressed columns made of aluminium alloy described by the Ramberg-Osgood relationship. The non-linear differential equation of the problem is derived using the stationary total energy principle and the assumptions of classical beam theory within a finite range. The approximate analytical solution of the equation leading to the buckling loads and initial...
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Deep Learning Basics 2023/24
e-Learning CoursesA course about the basics of deep learning intended for students of Computer Science. It includes an introduction to supervised machine learning, the architecture of basic artificial neural networks and their training algorithms, as well as more advanced architectures (convolutional networks, recurrent networks, transformers) and regularization and optimization techniques.
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Active Annotation in Evaluating the Credibility of Web-Based Medical Information: Guidelines for Creating Training Data Sets for Machine Learning
PublicationMethods Results Discussion References Abbreviations Copyright Abstract Background: The spread of false medical information on the web is rapidly accelerating. Establishing the credibility of web-based medical information has become a pressing necessity. Machine learning offers a solution that, when properly deployed, can be an effective tool in fighting medical misinformation on the web. Objective: The aim of this study is to...
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Impact of probability distribution on the uncertainty of resistance measurement
PublicationThe paper presents studies on the influence of probability distributions on the expanded uncertainty of the resistance measurement. Choosing the correct probability distribution is very important to estimate of measurement uncertainty. The paper presents the results of analysis of the resistance measurement uncertainty using the technical method of resistance: 100 G. The analysis of the uncertainty...
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Modeling of generator performance of BLDC machine using mathematica software
PublicationW artykule porównano trzy modele maszyny bezszczotkowej prądu stałego z magnesami trwałymi(BLDC) w przypadku pracy prądnicowej. Najprostszy model qd0 sprowadzono do dwóch osi prostopadłychzwiązanych z wirnikiem [3]. Zakłada on sinusoidalny rozkład pola w szczelinie. Model opisany wosiach naturalnych wyprowadzono w oparciu o formalizm Lagrnage'a [4] i moŜe uwzględniać dowolnyrozkład pola wzbudzonego przez magnesy trwałe. Model pośredni...
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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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Foundations and Trends in Machine Learning
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Machine Learning and Knowledge Extraction
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Machine Learning-Science and Technology
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Performance of Watermarking-based DTD Algorithm Under Time-varying Echo Path Conditions
PublicationA novel double-talk detection (DTD) algorithm based on techniques similar to those used for audio signal watermarking was introduced by the authors. The application of the described DTD algorithm within acoustic echo cancellation system is presented. The problem of DTD robustness to time-varying conditions of acoustic echo path is discussed and explanation as to why such conditions occur in practical situations is provided. The...
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Robust-adaptive dynamic programming-based time-delay control of autonomous ships under stochastic disturbances using an actor-critic learning algorithm
PublicationThis paper proposes a hybrid robust-adaptive learning-based control scheme based on Approximate Dynamic Programming (ADP) for the tracking control of autonomous ship maneuvering. We adopt a Time-Delay Control (TDC) approach, which is known as a simple, practical, model free and roughly robust strategy, combined with an Actor-Critic Approximate Dynamic Programming (ACADP) algorithm as an adaptive part in the proposed hybrid control...
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New transition curve adapted to railway operational requirements
PublicationThe paper points to the limited possibilities of improving the existing situation in the area of transition curves used in geometrical layouts of the railway track. Difficulties in the practical implementation and maintenance of very small horizontal ordinates of the transition curve and the ordinates of the gradient due to cant in the initial section, appearing on smooth transition curves, were indicated. The main reason for this...
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An investigation on residual stress and fatigue life assessment of T-shape welded joints
PublicationThis paper aims to quantitatively evaluate the residual stress and fatigue life of T-type welded joints with a multi-pass weld in different direction. The main research objectives of the experimental test were to test the residual stress by changing direction along with multiple wielding passes and determine the fatigue life of the welded joints. The result shows that compressive residual stress increases in the sample gradually...
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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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Driver’s Condition Detection System Using Multimodal Imaging and Machine Learning Algorithms
PublicationTo 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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Experimental evaluation of estimator mean square error curve for cognitive tracking radar
PublicationTo make decisions, cognitive radar must rely on predictions of its own performance. In the literature, these predictions are usually based on some form of Cram\'er-Rao lower bound. This approach is scientifically sound, but it also brings a possibility of the cognitive controller overestimating radar performance. It therefore makes sense to back theoretical predictions with careful experiments which will verify their applicability....
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Residual Current Devices: Selection, Operation, and Testing
PublicationIn this book, the idea for residual current protection has been presented. The evolution in construction types of residual current devices, which has taken place over decades, is discussed. Types and functional properties of the contemporary residual current devices are described. The main parameters of these devices, from the point of view of their selection and application, are indicated. Special constructions of the protective...
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Trees with equal restrained domination and total restrained domination numbers
PublicationW publikacji scharakteryzowano wszystkie drzewa, w których liczby dominowania powściągniętego oraz podwójnie totalnego są sobie równe.
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Efficient algorithm for blinking LED detection dedicated to embedded systems equipped with high performance cameras
PublicationThis paper presents the concept and implementation of an efficient algorithm for detection of blinking LED or similar signal sources. Algorithm is designed for embedded devices equipped with high performance cameras being a part of an indoor positioning embedded system. An algorithm to be implemented in such a system should be efficient in terms of computational power what is hard to be achieved when large amount of data from camera...
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Energy consumption optimization in wastewater treatment plants: Machine learning for monitoring incineration of sewage sludge
PublicationBiomass 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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Stability and load bearing capacity of a braced truss under upward wind loading
PublicationThe paper is focused on the numerical and experimental investigation of stability of a steel truss under upward wind loading. The structure was stiffened by elastic braces situated at the top and bottom chord. Usually the lateral (translational) brace stiffness is considered. However, the rotational stiffness of braces caused by interaction between torsional stiffness of the truss top chord and bending stiffness of the roof elements...
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Stability and load bearing capacity of a braced truss under upward wind loading
PublicationThe paper is focused on the numerical and experimental investigation of stability of a steel truss under upward wind loading. The structure was stiffened by elastic braces situated at the top and bottom chord. Usually the lateral (translational) brace stiffness is considered. However, the rotational stiffness of braces caused by interaction between torsional stiffness of the truss top chord and bending stiffness of the roof elements...
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Performance of isotropic constitutive laws in simulating failure mechanisms in scaled RC beams
PublicationResults of numerical calculations of reinforced concrete (RC) beams are presented. Based on experimental results on longitudinally reinforced specimens of different sizes and shapes are investigated. Four different continuum constitutive laws with isotropic softening are used: one defined within continuum damage mechanics, an elasto-plastic with the Rankine criterion in tension and the Drucker-Prager criterion in compression, a...
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Torsion of restrained thin-walled bars of open constant bisymmetric cross-section
PublicationElastic and geometric stiffness matrices were derived using Castigliano's first theorem, for the case of torsion of restrained thin-walled bars of open constant bisymmetric cross-section. Functions which describe the angles of torsion were adopted from the solutions of thedifferential equation for restrained torsion. The exact solutions were simplified by expanding them in a power series. Numerical examples were taken from Kujawa...
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On instabilities and post-buckling of piezomagnetic and flexomagnetic nanostructures
PublicationWe focus on the mechanical strength of piezomagnetic beam-like nanosize sensors during post-buckling. An effective flexomagnetic property is also taken into account. The modelled sensor is selected to be a Euler-Bernoulli type beam. Long-range interactions between atoms result in a mathematical model based on the nonlocal strain gradient elasticity approach (NSGT). Due to possible large deformations within a post-buckling phenomenon,...
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Multiple reference frame theory in the synchronous generator model considering harmonic distortions caused by nonuniform pole shoe saturation
PublicationThe paper describes a synchronous generator model developed based on the multiple reference frame theory. The main physical phenomena included in the model are the machine armature non-sinusoidal voltage waveform and the influence of armature current in load conditions on the armature voltage waveform higher harmonic components. The modified multiple reference frame theory model is proposed. In this modified theory model the field...
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The shape of an ROC curve in the evaluation of credit scoring models
PublicationThe AUC, i.e. the area under the receiver operating characteristic (ROC) curve, or its scaled version, the Gini coefficient, are the standard measures of the discriminatory power of credit scoring. Using binormal ROC curve models, we show how the shape of the curves affects the economic benefits of using scoring models with the same AUC. Based on the results, we propose that the shape parameter of the fitted ROC curve is reported...
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Application of Multiplicative Drift Correction and Component Correction methods on simulated gas sensor array responses
PublicationSensor response drift is one of the most challenging problems in gas-analyzing systems. Such systems, commonly called electronic noses, are expected to be reliable and reproducible in the long term. Due to the drift phenomena, electronic noses usability is limited to the relatively short period of time, and frequent recalibrations of device are required. Because it is very hard to fabricate sensors without drift, this phenomenon...
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Machine learning applied to bi-heterocyclic drugs recognition
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Stacking-Based Integrated Machine Learning with Data Reduction
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Machine Learning Modelling and Feature Engineering in Seismology Experiment
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Machine Learning for Sensorless Temperature Estimation of a BLDC Motor
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MACHINE LEARNING SYSTEM FOR AUTOMATED BLOOD SMEAR ANALYSIS
PublicationIn 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
PublicationThe 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...