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Search results for: MACHINE LEARNING, DEEP NEURAL NETWORKS, CEREBRAL MICROBLEEDS, CMB DETECTION, MR IMAGES
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Detection of roles of actors in social networks using the properties of actors' neighborhood structure.
PublicationArtykuł opisuje metodę identyfikacji ról aktorów sieci społecznej. Metoda ta może być szczególnie przydatna w sieciach społecznych, o których posiadamy ograniczoną wiedzę, głównie zawężoną do lokalnych powiązań pomiędzy aktorami. Przedstawiona w artykule metoda korzysta z grafu relacji społecznych, algorytmu identyfikacji ról oraz zbioru grafów wzorców relacji. Rozwiązanie zostało przetestowane w społeczności użytkowników serwisu...
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Comparison of edge detection algorithms for electric wire recognition
PublicationEdge detection is the preliminary step in image processing for object detection and recognition procedure. It allows to remove useless information and reduce amount of data before further analysis. The paper contains the comparison of edge detection algorithms optimized for detection of horizontal edges. For comparison purposes the algorithms were implemented in the developed application dedicated to detection of electric line...
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Fault diagnosis of marine 4-stroke diesel engines using a one-vs-one extreme learning ensemble
PublicationThis paper proposes a novel approach for intelligent fault diagnosis for stroke Diesel marine engines, which are commonly used in on-road and marine transportation. The safety and reliability of a ship's work rely strongly on the performance of such an engine; therefore, early detection of any type of failure that affects the engine is of crucial importance. Automatic diagnostic systems are of special importance because they can...
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Application of deep eutectic solvents in atomic absorption spectrometry
PublicationAtomic absorption spectrometry (AAS) is a widely applied technique for metal quantification due to its practicality, easy use and low cost. However, to improve the metrological characteristics of AAS, in particular the sensitivity and the detection limit, sample pretreatment is commonly used before the detection step itself. In consideration of the principles of Green Analytical Chemistry, new solvents are being introduced into...
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Load effect impact on the exploitation of concrete machine foundations used in the gas and oil industry
PublicationMachine foundations is a critical topic in the gas and oil industry, which design and exploitation require extensive technical knowledge. Machine foundations are the constructions which are intended for mounting on it a specific type of machine. The foundation has to transfer dynamic and static load from machine to the ground. The primary difference between machine foundations and building foundations is that the machine foundations...
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Respiratory Rate Estimation Based on Detected Mask Area in Thermal Images
PublicationThe popularity of non-contact methods of measuring vital signs, particularly respiratory rate, has increased during the SARS-COV-2 pandemic. Breathing parameters can be estimated by analysis of temperature changes observed in thermal images of nostrils or mouth regions. However, wearing virus-protection face masks prevents direct detection of such face regions. In this work, we propose to use an automatic mask detection approach...
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Experimental tests of reinforced concrete deep-beams
PublicationThe paper presents results of experimental research of the reinforced concrete deep beam with a spatial arrangement. Tested structural elements consist of the cantilever deep beam loaded on the height and transverse deep beam with hanging on it another one. The analysis includes crack morphology, effort of steel and load distribution. The article verified effectiveness of two different kind of reinforcement in both tested deep...
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Photos and rendered images of LEGO bricks
PublicationThe paper describes a collection of datasets containing both LEGO brick renders and real photos. The datasets contain around 155,000 photos and nearly 1,500,000 renders. The renders aim to simulate real-life photos of LEGO bricks allowing faster creation of extensive datasets. The datasets are publicly available via the Gdansk University of Technology “Most Wiedzy” institutional repository. The source files of all tools used during...
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Double Fed Induction Machine Drives
PublicationContents 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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Experimental investigations and prediction of WEDMed surface of nitinol SMA using SinGAN and DenseNet deep learning model
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Neural Approximators for Variable-Order Fractional Calculus Operators (VO-FC)
PublicationThe paper presents research on the approximation of variable-order fractional operators by recurrent neural networks. The research focuses on two basic variable-order fractional operators, i.e., integrator and differentiator. The study includes variations of the order of each fractional operator. The recurrent neural network architecture based on GRU (Gated Recurrent Unit) cells functioned as a neural approximation for selected...
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Social learning in cluster initiatives
PublicationPurpose – The purpose of the paper is to portray social learning in cluster initiatives (CIs), namely: 1) to explore, with the lens of the communities of practice (CoPs) theory, in what ways social learning occurs in CIs; 2) to discover how various CoPs emerge and evolve in CIs to facilitate a collective journey in their learning process. Subsequently, the authors address the research questions: In what ways does social learning...
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Universal Predictors of Dental Students’ Attitudes towards COVID-19 Vaccination: Machine Learning-Based Approach
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Prediction of Wastewater Quality at a Wastewater Treatment Plant Inlet Using a System Based on Machine Learning Methods
PublicationOne 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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Morphometric evaluation of the delayed cerebral arteries response to acetazolamide test in patients with chronic carotid artery stenosis using computed tomography angiography
PublicationBackground: The evidence accumulates that the response to acetazolamide test is delayed on the ipsilateral side to stenosis. However, the effect of acetazolamide beyond 30 minutes after acetazolamide administration remains unknown. The aim of this study was to assess the diameters of: anterior cerebral arteries (ACAs), middle cerebral arteries (MCAs) and posterior cerebral arteries (PCAs) before and 60 minutes after the acetazolamide...
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Neural Modelling of Steam Turbine Control Stage
PublicationThe paper describes possibility of steam turbine control stage neural model creation. It is of great importance because wider application of green energy causes severe conditions for control of energy generation systems operation Results of chosen steam turbine of 200 MW power measurements are applied as an example showing way of neural model creation. They serve as training and testing data of such neural model. Relatively simple...
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An Approach to the Detection of Bank Robbery Acts Employing Thermal Image Analysis
PublicationA novel approach to the detection of selected security-related events in bank monitoring systems is presented. Thermal camera images are used for the detection of people in difficult lighting conditions. Next, the algorithm analyses movement of objects detected in thermal or standard monitoring cameras using a method evolved from the motion history images algorithm. At the same time, thermal images are analyzed in order to detect...
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Histogram of Gradients with Cell Average Intensity for Human Detection
PublicationThe modification of the descriptor in human detector using Histogram of Oriented Gradients and support vector machine is presented. The proposed modification requires inserting the average cell intensitiesresulting with the increase of the length of the descriptor from 3780 to 4200 values, but it is easy to compute and instantly gives 14-26% of miss rate improvement at 10^-4 False Positives Per Window (FPPW). The modification...
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Data-driven models for fault detection using kernel pca:a water distribution system case study
PublicationKernel Principal Component Analysis (KPCA), an example of machine learning, can be considered a non-linear extension of the PCA method. While various applications of KPCA are known, this paper explores the possibility to use it for building a data-driven model of a non-linear system-the water distribution system of the Chojnice town (Poland). This model is utilised for fault detection with the emphasis on water leakage detection....
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Feature Reduction Using Similarity Measure in Object Detector Learning with Haar-like Features
PublicationThis paper presents two methods of training complexity reduction by additional selection of features to check in object detector training task by AdaBoost training algorithm. In the first method, the features with weak performance at first weak classifier building process are reduced based on a list of features sorted by minimum weighted error. In the second method the feature similarity measures are used to throw away that features...
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Statistical Data Pre-Processing and Time Series Incorporation for High-Efficacy Calibration of Low-Cost NO2 Sensor Using Machine Learning
PublicationAir 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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EXPERIMENTAL AND THEORETICAL FLOW OF THE FORCES IN DEEP BEAMS WITH CANTILEVAR
PublicationThis article presents the results of experimental research carried out on deep beams with cantilever which was loaded throughout the depth. The main deep beam was directly simply supported on the one side. On the other side the deep beam was suspended in another deep member situated at right angles. All deep beams created a spatial arrangement. The paper is focused on the analysis of the cracks morphology and flow of the internal...
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Comparison of selected clustering algorithms of raw data obtained by interferometric methods using artificial neural networks
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Emotion Recognition from Physiological Channels Using Graph Neural Network
PublicationIn recent years, a number of new research papers have emerged on the application of neural networks in affective computing. One of the newest trends observed is the utilization of graph neural networks (GNNs) to recognize emotions. The study presented in the paper follows this trend. Within the work, GraphSleepNet (a GNN for classifying the stages of sleep) was adjusted for emotion recognition and validated for this purpose. The...
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Evaluation the effectiveness of virtual machine integrated with CPU
PublicationIn 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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MultiRegional PCA for leakage detection and localisation in DWDS - approach
PublicationMonitoring is one of the most important parts in advanced control of complex dynamic systems. Information about systems behavior, including failures indicating, enables for efficient control. The chapter describes an approach to detection and localisation of pipe leakage in Drinking Water Distribution Systems (DWDS) representing complex and distributed dynamic system of large scale. Proposed MultiRegional Principal Component Analysis...
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Model szkolenia "Blended learning" z wykorzystaniem platformy Oracle I-learning.
PublicationW artykule zaproponowano modele organizacyjne szkoleń "blended learning", które pokazują możliwości współpracy firm prywatnych z instytucjami edukacyjnymi w dziedzinie e-learningu. W ramach wspólnego eksperymentu firm Oracle, Incenti S.A., WiedzaNet Sp. z o.o. oraz Centrum Edukacji Niestacjonarnej Politechniki Gdańskiej w semestrze letnim roku akademickiego 2003/2004 udostępniony będzie kurs dla studentów Wydziału Inzynierii Lądowej...
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Grade of service determination methodology in IP networks with SIP protocol
PublicationAlthough Grade of Service is very important in VoIP providers evaluation, We wasn't able to find any paper regarding the topic of measuring GoS variables for IP networks utilizing SIP, which are defined like for PSTN/ISDN/GSM networks (post-selection delay, answering delay, release delay, or probability of end-to-end blocking). Due to the lack of research in this field, it was necessary to start from defining measures and cover...
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From evil demiurge to caring hero: Images of geneticists in the movies
PublicationAlthough images of science and scientists depicted in popular culture have been criticized as an exaggeration and fear mongering, the cinema is an important resource that influences individuals’ beliefs about science. Because popular depictions of science play a crucial role in constructing the public’s ‘scientific imaginary’ they constitute an inherent dimension of the social understanding of science and are as important for...
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E-learning versus traditional learning - Polish case
PublicationE-learning jest współczesnym fenomenem, który pozwala na dostęp do kształcenia i treści edukacyjnych, niezależnie od czasu i miejsca, dla każdego użytkownika. E-learnig tworzy ogromne możliwości dla uczelni akademickich, organizacji, instytucji komercyjnych i szkoleniowych, dostarczając na żądanie kształcenia i szkoleń w wirtualnym środowisku. Student może stworzyć własny plan kształcenia, dostosowując go do swojej pracy i sytuacji...
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A Closed Bipolar Electrochemical Cell for the Interrogation of BDD Single Particles: Electrochemical Advanced Oxidation
PublicationA closed bipolar electrochemical cell containing two conductive boron-doped diamond (BDD) particles of size 250 – 350 m, produced by high-pressure high-temperature (HPHT) synthesis, has been used to demonstrate the applicability of single BDD particles for electrochemical oxidative degradation of the dye, methylene blue (MB). The cell is fabricated using stereolithography 3D printing and the BDD particles are located at either...
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Neural network simulator's application to reference performance determination of turbine blading in the heat-flow diagnostics.
PublicationIn the paper, the possibility of application of artificial neural networks to perform the fluid flow calculations through both damaged and undamaged turbine blading was investigated. Preliminary results are presented and show the potentiality of further development of the method for the purpose of heat-flow diagnostics.
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Merging Images from Parallel Depth Cameras
PublicationIn this paper a problem of simultaneous information acquisition from multiple depth cameras is investigated, aiming at obtaining single overall picture containing information from all cameras. The experiments are carried out on Microsoft Kinect devices. A methodology for merging images from multiple positioned in a line cameras is proposed. The method is based on the concept of simulating a view of an imaginary camera covering...
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Merging Images From Parallel Depth Cameras
PublicationIn this paper a problem of simultaneous information acquisition from multiple depth cameras is investigated, aiming at obtaining single overall picture containing information from all cameras. The experiments are carried out on Microsoft Kinect devices. A methodology for merging images from multiple positioned in a line cameras is proposed. The method is based on the concept of simulating a view of an imaginary camera covering...
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Machine Learning-Based Wetland Vulnerability Assessment in the Sindh Province Ramsar Site Using Remote Sensing Data
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A Computationally Efficient Model for Predicting Successful Memory Encoding Using Machine-Learning-based EEG Channel Selection
PublicationComputational 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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Adding Interpretability to Neural Knowledge DNA
PublicationThis paper proposes a novel approach that adds the interpretability to Neural Knowledge DNA (NK-DNA) via generating a decision tree. The NK-DNA is a promising knowledge representation approach for acquiring, storing, sharing, and reusing knowledge among machines and computing systems. We introduce the decision tree-based generative method for knowledge extraction and representation to make the NK-DNA more explainable. We examine...
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STUDY IN MECHANICAL FAULT ELEMENT THERMOGRAPHY THROUGH THE MACHINE: The case of deep groove ball bearings of a career without screen.
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A compact smart sensor based on a neural classifier for objects modeled by Beaunier's model
PublicationA new solution of a smart microcontroller sensor based on a simple direct sensor-microcontroller interface for technical objects modeled by two-terminal networks and by the Beaunier’s model of anticorrosion coating is proposed. The tested object is stimulated by a square pulse and its time voltage response is sampled four times by the internal ADC of microcontroller. A neural classifier based on measurement data classifies the...
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Discovering Rule-Based Learning Systems for the Purpose of Music Analysis
PublicationMusic analysis and processing aims at understanding information retrieved from music (Music Information Retrieval). For the purpose of music data mining, machine learning (ML) methods or statistical approach are employed. Their primary task is recognition of musical instrument sounds, music genre or emotion contained in music, identification of audio, assessment of audio content, etc. In terms of computational approach, music databases...
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An Analysis of Neural Word Representations for Wikipedia Articles Classification
PublicationOne of the current popular methods of generating word representations is an approach based on the analysis of large document collections with neural networks. It creates so-called word-embeddings that attempt to learn relationships between words and encode this information in the form of a low-dimensional vector. The goal of this paper is to examine the differences between the most popular embedding models and the typical bag-of-words...
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Application of Shape From Shading Technique for Side Scan Sonar Images
PublicationSide scan sonar (SSS) is one of the most widely used imaging systems in the underwater environment. It is relatively cheap and easy to deploy in comparison with more powerful sensors like multibeam echosounder or synthetic aperture sonar. Although, the SSS does not provide directly the seafloor bathymetry measurements. Its outputs are usually in a form of grey level acoustic images of seafloor. However, the analysis of such images...
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Resilient Routing in Communication Networks
PublicationThis important text/reference addresses the latest issues in end-to-end resilient routing in communication networks. The work highlights the main causes of failures of network nodes and links, and presents an overview of resilient routing mechanisms, covering issues related to the Future Internet (FI), wireless mesh networks (WMNs), and vehicular ad-hoc networks (VANETs). For each of these network architectures, a selection of...
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Predicting Ice Phenomena in a River Using the Artificial Neural Network and Extreme Gradient Boosting
PublicationForecasting ice phenomena in river systems is of great importance because these phenomena are a fundamental part of the hydrological regime. Due to the stochasticity of ice phenomena, their prediction is a difficult process, especially when data sets are sparse or incomplete. In this study, two machine learning models—Multilayer Perceptron Neural Network (MLPNN) and Extreme Gradient Boosting (XGBoost)—were developed to predict...
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Practical issues for the implementation of survivability and recovery techniques in optical networks
PublicationFailures in optical networks are inevitable. They may occur during work being done for the maintenance of other infrastructures, or on a larger scale as the result of an attack or large-scale disaster. As a result, service availability, an important aspect of Quality of Service (QoS), is often degraded. Appropriate fault recovery techniques are thus crucial to meet the requirements set by the Service Level Agreements (SLAs) between...
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Topology recognition and leader election in colored networks
PublicationTopology recognition and leader election are fundamental tasks in distributed computing in networks. The first of them requires each node to find a labeled isomorphic copy of the network, while the result of the second one consists in a single node adopting the label 1 (leader), with all other nodes adopting the label 0 and learning a path to the leader. We consider both these problems in networks whose nodes are equipped with...
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Deep slot effect in the squirrel-cage induction motors with scalar (V/F) control
PublicationQualitative characteristics of the electrical drive considerably depend on identification accuracy of math model parameters. In particular, it is depend on detection accuracy of stator active resistance r1 that is used in calculation of flux linkages, rotary speed in sensorless control systems. Paper provides analysis of influence of stator deep slot effect to stator active resistance value
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Digital Fingerprinting Based on Quaternion Encryption Scheme for Gray-Tone Images
PublicationIn this paper a new idea of digital images fingerprinting is proposed. The method is based on quaternion encryption in the Cipher Block Chaining (CBC) mode. Quaternion sare hyper-complex numbers of rank 4 and thus often applied to mechanics in three-dimensional space. The encryption algorithm described in the paper is designed for gray-tone images but can easily be adopted for color ones. For the encryption purpose, the algorithm...
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Modelling relation between oxidation resistance and tribological properties of non-toxic lubricants with the use of artificial neural networks
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Long Short-Term Memory (LSTM) neural networks in predicting fair price level in the road construction industry
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