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Wyniki wyszukiwania dla: IMAGE COLOR ANALYSIS, MACHINE LEARNING, LESIONS, IMAGE CLASSIFICATION, NEURAL NETWORKS, CANCER, TASK ANALYSIS
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Machine-Learning Methods for Estimating Performance of Structural Concrete Members Reinforced with Fiber-Reinforced Polymers
PublikacjaIn recent years, fiber-reinforced polymers (FRP) in reinforced concrete (RC) members have gained significant attention due to their exceptional properties, including lightweight construction, high specific strength, and stiffness. These attributes have found application in structures, infrastructures, wind power equipment, and various advanced civil products. However, the production process and the extensive testing required for...
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Sensing Direction of Human Motion Using Single-Input-Single-Output (SISO) Channel Model and Neural Networks
PublikacjaObject detection Through-the-Walls enables localization and identification of hidden objects behind the walls. While numerous studies have exploited Channel State Information of Multiple Input Multiple Output (MIMO) WiFi and radar devices in association with Artificial Intelligence based algorithms (AI) to detect and localize objects behind walls, this study proposes a novel non-invasive Through-the-Walls human motion direction...
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An Improved Convolutional Neural Network for Steganalysis in the Scenario of Reuse of the Stego-Key
PublikacjaThe topic of this paper is the use of deep learning techniques, more specifically convolutional neural networks, for steganalysis of digital images. The steganalysis scenario of the repeated use of the stego-key is considered. Firstly, a study of the influence of the depth and width of the convolution layers on the effectiveness of classification was conducted. Next, a study on the influence of depth and width of fully connected...
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Computational Complexity and Its Influence on Predictive Capabilities of Machine Learning Models for Concrete Mix Design
PublikacjaThe design of concrete mixtures is crucial in concrete technology, aiming to produce concrete that meets specific quality and performance criteria. Modern standards require not only strength but also eco-friendliness and production efficiency. Based on the Three Equation Method, conventional mix design methods involve analytical and laboratory procedures but are insufficient for contemporary concrete technology, leading to overengineering...
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Dynamically positioned ship steering making use of backstepping method and artificial neural networks
PublikacjaThe article discusses the issue of designing a dynamic ship positioning system making use of the adaptive vectorial backstepping method and RBF type arti cial neural networks. In the article, the backstepping controller is used to determine control laws and neural network weight adaptation laws. e arti cial neural network is applied at each time instant to approximate nonlinear functions containing parametric uncertainties....
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Neural Graph Collaborative Filtering: Analysis of Possibilities on Diverse Datasets
PublikacjaThis paper continues the work by Wang et al. [17]. Its goal is to verify the robustness of the NGCF (Neural Graph Collaborative Filtering) technique by assessing its ability to generalize across different datasets. To achieve this, we first replicated the experiments conducted by Wang et al. [17] to ensure that their replication package is functional. We received sligthly better results for ndcg@20 and somewhat poorer results for...
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Foundations of Capital Market Analysis
Kursy Online -
Foundations of Capital Market Analysis
Kursy Online -
Non-destructive testing of industrial structures with the use of multi-camera Digital Image Correlation method
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Active Annotation in Evaluating the Credibility of Web-Based Medical Information: Guidelines for Creating Training Data Sets for Machine Learning
PublikacjaMethods 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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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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Analysis of the objects images on the sea using Dempster-Shafer Theory
PublikacjaThe paper presents the concept of using aerial and satellite imagery or images coming from the marine radar to identify and track vessels at sea. The acquired data were subjected to a highly advanced image analysis. The development of remote sensing techniques allows to gain a huge amount of data. These data are useful information source however usually we have to use different data mining methods to gain interested information....
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Failure characterisation of sandwich beams using integrated acoustic emission and digital image correlation techniques
PublikacjaThe paper presents the experimental study of the failure behaviour of sandwich beams subjected to bending. The samples examined are sandwich beams made of polyethylene terephthalate foam core and glass fibre-reinforced polymer laminate face sheets. In a series of experiments, it has been proposed to integrate diagnostic techniques with acoustic emission and digital image correlation to accurately track the cracking process on the...
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Chained machine learning model for predicting load capacity and ductility of steel fiber–reinforced concrete beams
PublikacjaOne of the main issues associated with steel fiber–reinforced concrete (SFRC) beams is the ability to anticipate their flexural response. With a comprehensive grid search, several stacked models (i.e., chained, parallel) consisting of various machine learning (ML) algorithms and artificial neural networks (ANNs) were developed to predict the flexural response of SFRC beams. The flexural performance of SFRC beams under bending was...
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Image projection in Immersive 3D Visualization Laboratory
PublikacjaIn recent years, many centers in the world attempted to build a virtual reality laboratory. The main idea of such laboratory is to allow the user to “immerse” into and move in a computer-generated virtual world. In the paper, the underlying principles of the system of virtual reality (VR) are described. The selected implementations constructed by the research centers of the world are also presented. The cave automatic virtual environment...
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Quaternion Encryption Method for Image and Video Transmission
PublikacjaQuaternions are hyper-complex numbers of rank 4. They are often applied to mechanics in 3D space and are considered to be one of the best ways of representing rotations. In this paper a quaternion encryption method, based on algorithm by Nagase et al. (2004) has been proposed. According to a computer-based simulation the results of the performed research yield a high level of security, which is additionally strengthened by the...
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Fractional Derivatives Application to Image Fusion Problems
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A New Quaternion Encryption Scheme for Image Transmission
PublikacjaQuaternions are hypercomplex number of rank 4. They are often applied to mechanics in three-dimensional space and considered as one of the best ways to represent rotations. In this paper a new encryption scheme, based on the rotation of data vector in three-dimensional space around another quaternion (key) is proposed. A computer-based simulation was created to analyze the potential of the proposed encryption technique.
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Image content description methods for a retrieval system.
PublikacjaArtykuł przedstawia metody opisu treści obrazu dla potrzeb systemu wyszukiwania. Omówiono deskryptory opisu treści obrazu oraz ich realizację w Systemie Wyszukiwania Obrazów.
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Gas Detection Using Resistive Gas Sensors And Radial Basis Function Neural Networks
PublikacjaWe present a use of Radial Basis Function (RBF) neural networks and Fluctuation Enhanced Sensing (FES) method in gas detection system utilizing a prototype resistive WO3 gas sensing layer with gold nanoparticles. We investigated accuracy of gas detection for three different preprocessing methods: no preprocessing, Principal Component Analysis (PCA) and wavelet transformation. Low frequency noise voltage observed in resistive gas...
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Real and imaginary motion classification based on rough set analysis of EEG signals for multimedia applications
PublikacjaRough set-based approach to the classification of EEG signals of real and imaginary motion is presented. The pre-processing and signal parametrization procedures are described, the rough set theory is briefly introduced, and several classification scenarios and parameters selection methods are proposed. Classification results are provided and discussed with their potential utilization for multimedia applications controlled by the...
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IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
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Deep Learning-Based Intrusion System for Vehicular Ad Hoc Networks
PublikacjaThe increasing use of the Internet with vehicles has made travel more convenient. However, hackers can attack intelligent vehicles through various technical loopholes, resulting in a range of security issues. Due to these security issues, the safety protection technology of the in-vehicle system has become a focus of research. Using the advanced autoencoder network and recurrent neural network in deep learning, we investigated...
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USING ARTIFICIAL NEURAL NETWORKS FOR PREDICTING SHIP FUEL CONSUMPTION
PublikacjaIn marine vessel operations, fuel costs are major operating costs which affect the overall profitability of the maritime transport industry. The effective enhancement of using ship fuel will increase ship operation efficiency. Since ship fuel consumption depends on different factors, such as weather, cruising condition, cargo load, and engine condition, it is difficult to assess the fuel consumption pattern for various types...
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Authentication of whisky due to its botanical origin and way of production by instrumental analysis and multivariate classification methods
PublikacjaHeadspacemass-spectrometry (HS-MS), mid infrared (MIR) and UV–vis spectroscopywere used to authenticate whisky samples from different origins and ways of production ((Irish, Spanish, Bourbon, TennesseeWhisky and Scotch). The collected spectra were processed with partial least-squares discriminant analysis (PLS-DA) to build the classification models. In all cases the five groups ofwhiskieswere distinguished, but the best resultswere...
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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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Analysis of urinary nucleosides as potential cancer markers determined using LC–MS technique
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Sensory analysis of confectionery products.
Dane BadawczeThe data set presents the results of the sensory analysis of confectionery products, which was carried out by the sensory profiling analysis method based on the PN-ISO 11035: 1999 standard – “Sensory analysis - Identification and selection of descriptors for determining the sensory profile using multivariate methods”. The method was used to evaluate...
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The Analysis and Solutions to the Problems of IPv6 Configuration Migration of Small Networks
PublikacjaThe paper analyzes the problems of IPv4 to IPv6 migration processes and indicates the areas in which migration can be done without expensive replacement of hardware, software and organizational changes. This paper presents the migration tools developed for the SOHO network administrators. The tools provide theoretical knowledge and practical advices on migrating to IPv6 and enable automation of the migration process. The article...
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Machine Learning-Based Wetland Vulnerability Assessment in the Sindh Province Ramsar Site Using Remote Sensing Data
PublikacjaWetlands 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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Classification of Covid-19 using Differential Evolution Chaotic Whale Optimization based Convolutional Neural Network
PublikacjaCOVID-19, also known as the Coronavirus disease-2019, is an transferrable disease that spreads rapidly, affecting countless individuals and leading to fatalities in this worldwide pandemic. The precise and swift detection of COVID-19 plays a crucial role in managing the pandemic's dissemination. Additionally, it is necessary to recognize COVID-19 quickly and accurately by investigating chest x-ray images. This paper proposed a...
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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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Characterization of fracture process in polyolefin fibre-reinforced concrete using ultrasonic waves and digital image correlation
PublikacjaThis study explores the monitoring of the fracture process in concrete beams and aims to characterize the evolution of damage in polyolefin fibre-reinforced concrete beams by utilizing the integrated application of two measurement techniques, digital image correlation and ultrasonic testing. The interpretation of registered wave time histories data was provided by the calculation of the magnitude-phase-composite metrics. An efficient...
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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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Beata Krawczyk-Bryłka dr
OsobyPsycholog, doktor nauk humanistycznych w dziedzinie zarządzania, adiunkt w Katedrze przedsiębiorczości. 2018 - 2021: Kierownik projektu NCN: „Efektuacyjny model zespołu przedsiębiorczego. Jak działają przedsiębiorcze zespoły odnoszące sukces" od 2016: Quality Standards Lead filaru People management & personal development na studiach MBA Politechniki Gdańskiej 2008 – 2012: Prodziekan ds kształcenia Wzydziału Zarządzania i Ekonomii...
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Light-Powered Starter for Micro-Power Boost DC–DC Converter for CMOS Image Sensors
PublikacjaThe design of a starter for a low-voltage, micro-power boost DC–DC converter intended for powering CMOS image sensors is presented. A unique feature of the starter is extremely low current, below 1 nA, supplying its control circuit. Therefore, a high-voltage (1.3 V) configuration of series-connected photovoltaic diodes available in a standard CMOS process or a small external LED working in photovoltaic mode can be used as an auxiliary...
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Entropy analysis of surface EMG for classification of face movements
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Comparative study of neural networks used in modeling and control of dynamic systems
PublikacjaIn this paper, a diagonal recurrent neural network that contains two recurrent weights in the hidden layer is proposed for the designing of a synchronous generator control system. To demonstrate the superiority of the proposed neural network, a comparative study of performances, with two other neural network (1_DRNN) and the proposed second-order diagonal recurrent neural network (2_DRNN). Moreover, to confirm the superiority...
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The application of neural networks in forecasting the influence of traffic-induced vibrations on residential buildings
PublikacjaTraffic-induced vibrations may cause the cracking of plaster, damage to structural elements and, in extreme cases, may even lead to the structural collapse of residential buildings. The aim of this article is to analyse the effectiveness of a method of forecasting the impact of vibrations on residential buildings using the concept of artificial intelligence. The article presents several alternative forecasting systems for which...
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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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Application of Particle Image Velocimetry method for monitoring the volume changes during silo flow on the basis of X-radiographs
PublikacjaW artykule przedstawiono wyniki badań nad zastosowaniem techniki pomiarowej PIV (Particle Image Velocimetry) do analizy zmian objętościowych zachodzących w materiale sypkim w czasie opróżniania silosu prostokątnego. Jako mateirły do analizy wykorzystano cyfrowe radiografy uzyskane z kontynualnej rejestracji z użyciem systemu tomografii promieni X. Szcególny nacisk położono na analizę zmian objętościowych zachodzącyh w kanale przepływu.
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Forewarned Is Forearmed: Machine Learning Algorithms for the Prediction of Catheter-Induced Coronary and Aortic Injuries
PublikacjaCatheter-induced dissections (CID) of coronary arteries and/or the aorta are among the most dangerous complications of percutaneous coronary procedures, yet the data on their risk factors are anecdotal. Logistic regression and five more advanced machine learning techniques were applied to determine the most significant predictors of dissection. Model performance comparison and feature importance ranking were evaluated. We identified...
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Efficient uncertainty quantification using sequential sampling-based neural networks
PublikacjaUncertainty quantification (UQ) of an engineered system involves the identification of uncertainties, modeling of the uncertainties, and the forward propagation of the uncertainties through a system analysis model. In this work, a novel surrogate-based forward propagation algorithm for UQ is proposed. The proposed algorithm is a new and unique extension of the recent efficient global optimization using neural network (NN)-based...
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Optimized Deep Learning Model for Flood Detection Using Satellite Images
PublikacjaThe increasing amount of rain produces a number of issues in Kerala, particularly in urban regions where the drainage system is frequently unable to handle a significant amount of water in such a short duration. Meanwhile, standard flood detection results are inaccurate for complex phenomena and cannot handle enormous quantities of data. In order to overcome those drawbacks and enhance the outcomes of conventional flood detection...
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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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COMPARATIVE ANALYSIS OF ACTIVE GEODETIC NETWORKS IN POLAND
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Modelling of wastewater treatment plant for monitoring and control purposes by state - space wavelet networks
PublikacjaMost of industrial processes are nonlinear, not stationary, and dynamical with at least few different time scales in their internal dynamics and hardly measured states. A biological wastewater treatment plant falls into this category. The paper considers modelling such processes for monitorning and control purposes by using State - Space Wavelet Neural Networks (SSWN). The modelling method is illustrated based on bioreactors of...
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Evaluation of Facial Pulse Signals Using Deep Neural Net Models
PublikacjaThe reliable measurement of the pulse rate using remote photoplethysmography (PPG) is very important for many medical applications. In this paper we present how deep neural networks (DNNs) models can be used in the problem of PPG signal classification and pulse rate estimation. In particular, we show that the DNN-based classification results correspond to parameters describing the PPG signals (e.g. peak energy in the frequency...
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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...