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Search results for: artificial neural network, modelling,ship speed, engine fuel consumption
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Mathematical modelling of the overhead contact line for the purpose of diagnostics of pantographs
PublicationThe overhead contact line (OCL) is the most effective way for supplying railway electric vehicles. The increase of the speed of the vehicles increases power consumption and requires ensuring proper cooperation of pantographs with OCL. The paper describes the novel mathematical model of the OCL system and the simulation results. The primary objective is a more accurate analysis to increase the reliability of the evaluation of monitoring...
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Analysis of Properties of an Active Linear Gesture Sensor
PublicationBasic gesture sensors can play a significant role as input units in mobile smart devices. However, they have to handle a wide variety of gestures while preserving the advantages of basic sensors. In this paper a user-determined approach to the design of a sparse optical gesture sensor is proposed. The statistical research on a study group of individuals includes the measurement of user-related parameters like the speed of a performed...
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The searchlight problem for road networks
PublicationWe consider the problem of searching for a mobile intruder hiding in a road network given as the union of two or more lines, or two or more line segments, in the plane. Some of the intersections of the road network are occupied by stationary guards equipped with a number of searchlights, each of which can emit a single ray of light in any direction along the lines (or line segments) it is on. The goal is to detect the intruder,...
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Modelling of wastewater treatment plant for monitoring and control purposes by state - space wavelet networks
PublicationMost 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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Approximation of Fractional Order Dynamic Systems Using Elman, GRU and LSTM Neural Networks
PublicationIn the paper, authors explore the possibility of using the recurrent neural networks (RNN) - Elman, GRU and LSTM - for an approximation of the solution of the fractional-orders differential equations. The RNN network parameters are estimated via optimisation with the second order L-BFGS algorithm. It is done based on data from four systems: simple first and second fractional order LTI systems, a system of fractional-order point...
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Deep learning approach on surface EEG based Brain Computer Interface
PublicationIn this work we analysed the application of con-volutional neural networks in motor imagery classification for the Brain Computer Interface (BCI) purposes. To increase the accuracy of classification we proposed the solution that combines the Common Spatial Pattern (CSP) with convolutional network (ConvNet). The electroencephalography (EEG) is one of the modalities we try to use for controlling the prosthetic arm. Therefor in this...
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Simulations of wave propagation and attenuation in fields of colliding ice floes
Open Research DataThis dataset contains results of numerical smulations of sea ice-wave interactions, corresponding to laboratory experiments conducted at the Large Ice Model Basin (LIMB) at the Hamburg Ship Model Basin (HSVA) as part of the LS-WICE ("Loads on Structure and Waves in Ice"; https://zenodo.org/record/1067170#.XrLt_dhpxhE) project. THe simulations were conducted...
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The influence of screw configuration and screw speed of co-rotating twin screw extruder on the properties of products obtained by thermomechanical reclaiming of ground tire rubber
PublicationThe results of our investigations on the process of continuous thermomechanical reclaiming of ground tire rubber (GTR) carried out using a twin screw extruder are presented.We used a co-rotating twin screw extruder with a special configuration of plasticizing unit, enabling generation of considerable shear forces. The influence of screw configuration and screw speed on breaking of chemical crosslink bonds contained in ground tire...
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Spatiotemporal Assessment of Satellite Image Time Series for Land Cover Classification Using Deep Learning Techniques: A Case Study of Reunion Island, France
PublicationCurrent Earth observation systems generate massive amounts of satellite image time series to keep track of geographical areas over time to monitor and identify environmental and climate change. Efficiently analyzing such data remains an unresolved issue in remote sensing. In classifying land cover, utilizing SITS rather than one image might benefit differentiating across classes because of their varied temporal patterns. The aim...
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A new quaternion-based encryption method for DICOM images
PublicationIn this paper, a new quaternion-based lossless encryption technique for digital image and communication on medicine (DICOM) images is proposed. We have scrutinized and slightly modified the concept of the DICOM network to point out the best location for the proposed encryption scheme, which significantly improves speed of DICOM images encryption in comparison with those originally embedded into DICOM advanced encryption standard...
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An Intelligent Approach to Short-Term Wind Power Prediction Using Deep Neural Networks
PublicationIn this paper, an intelligent approach to the Short-Term Wind Power Prediction (STWPP) problem is considered, with the use of various types of Deep Neural Networks (DNNs). The impact of the prediction time horizon length on accuracy, and the influence of temperature on prediction effectiveness have been analyzed. Three types of DNNs have been implemented and tested, including: CNN (Convolutional Neural Networks), GRU (Gated Recurrent...
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Electromagnetic interference frequencies prediction model of flyback converter for snubber design
PublicationSnubber design for flyback converters usually requires experimental prototype measurements or simulation based on accurate and complex models. In this study simplified circuit modelling of a flyback converter has been described to dimension snubbers in early stage of design process. Simulation based prediction of the transistor and diode ringing frequencies has been validated by measurements in a prototype setup. In that way obtained...
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Analysis of energy efficiency of suburban railway transport network
PublicationRising numbers of agglomeration residents cause increased need for people movement on daily basis. Because of congestion of local roads, air pollution and limited parking space, providing mass transit based on electric traction is reasonable. While the electric rail vehicles are considered highly efficient in themselves, they need to be analyzed as a part of a transport network, because energy consumption depends on operating conditions...
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Collision‐Aware Routing Using Multi‐Objective Seagull Optimization Algorithm for WSN‐Based IoT
PublicationIn recent trends, wireless sensor networks (WSNs) have become popular because of their cost, simple structure, reliability, and developments in the communication field. The Internet of Things (IoT) refers to the interconnection of everyday objects and sharing of information through the Internet. Congestion in networks leads to transmission delays and packet loss and causes wastage of time and energy on recovery. The routing protocols...
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NetBaltic System-Heterogenous Wireless Network for Maritime Communications
PublicationIn case of maritime communications, we observe a growing interest in deployment of multitask satellite-based solutions and development of new maritime-specific systems intended for improvements in safety of e-navigation. Analysis of different types of currently used maritime communication systems leads, however, to a conclusion that neither global and still very expensive satellite systems nor cheaper, but short-ranged transmission...
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Measurement Campaign and Mathematical Model Construction for the Ship Zodiak Magnetic Signature Reproduction
PublicationThe paper presents the partial work done within the framework of the EDA Siramis II project focused on magnetic signature reproduction of ships. Reproduction is understood here as the ability to determine the magnetic anomaly of the local Earth magnetic field in any direction and at any measurement depth due to the presence of the analysed object. The B-91 type hydrographic ship Zodiak was selected as the real case study. The work...
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Features of load and wear of main propulsion devices on sea-going ships with piston combustion engines and their impact on changes in technical states of the systems
PublicationThe paper presents the specificity of operation of propulsion systems of seagoing ships which causes the need to control the load on them, especially on their engines called main engines. The characteristics of the load on the propulsion systems, especially on the main engines as well as on the shaft lines and propellers driven by the engines, along with the process of wear in tribological joints (sliding tribological systems)...
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Early warning models against bankruptcy risk for Central European and Latin American enterprises
PublicationThis article is devoted to the issue of forecasting the bankruptcy risk of enterprises in Latin America and Central Europe. The author has used statistical and soft computing methods to program the prediction models. It compares the effectiveness of twelve different early warningmodels for forecasting the bankruptcy risk of companies. In the research conducted, the author used data on 185 companies listed on the Warsaw Stock Exchange...
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Automatic Rhythm Retrieval from Musical Files
PublicationThis paper presents a comparison of the effectiveness of two computational intelligence approaches applied to the task of retrieving rhythmic structure from musical files. The method proposed by the authors of this paper generates rhythmic levels first, and then uses these levels to compose rhythmic hypotheses. Three phases: creating periods, creating simplified hypotheses and creating full hypotheses are examined within this study....
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Poprawa jakości klasyfikacji głębokich sieci neuronowych poprzez optymalizację ich struktury i dwuetapowy proces uczenia
PublicationW pracy doktorskiej podjęto problem realizacji algorytmów głębokiego uczenia w warunkach deficytu danych uczących. Głównym celem było opracowanie podejścia optymalizującego strukturę sieci neuronowej oraz zastosowanie uczeniu dwuetapowym, w celu uzyskania mniejszych struktur, zachowując przy tym dokładności. Proponowane rozwiązania poddano testom na zadaniu klasyfikacji znamion skórnych na znamiona złośliwe i łagodne. W pierwszym...
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Optimisation of turbine shaft heating process under steam turbine run-up conditions
PublicationAn important operational task for thermal turbines during run-up and run-down is to keep the stresses in the structural elements at a right level. This applies not only to their instantaneous values, but also to the impact of them on the engine lifetime. The turbine shaft is a particularly important element. The distribution of stresses depends on geometric characteristics of the shaft and its specific locations. This means a groove manufactured...
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Adaptive Hounsfield Scale Windowing in Computed Tomography Liver Segmentation
PublicationIn computed tomography (CT) imaging, the Hounsfield Unit (HU) scale quantifies radiodensity, but its nonlinear nature across organs and lesions complicates machine learning analysis. This paper introduces an automated method for adaptive HU scale windowing in deep learning-based CT liver segmentation. We propose a new neural network layer that optimizes HU scale window parameters during training. Experiments on the Liver Tumor...
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Intelligent Autonomous Robot Supporting Small Pets in Domestic Environment
PublicationIn this contribution, we present preliminary results of the student project aimed at the development of an intelligent autonomous robot supporting small pets in a domestic environment. The main task of this robot is to protect a freely moving small pets against accidental stepping on them by home residents. For this purpose, we have developed the mobile robot which follows a pet and makes an alarm signal when a human is approaching....
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TensorHive: Management of Exclusive GPU Access for Distributed Machine Learning Workloads
PublicationTensorHive is a tool for organizing work of research and engineering teams that use servers with GPUs for machine learning workloads. In a comprehensive web interface, it supports reservation of GPUs for exclusive usage, hardware monitoring, as well as configuring, executing and queuing distributed computational jobs. Focusing on easy installation and simple configuration, the tool automatically detects the available computing...
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Architektury klasyfikatorów obrazów
PublicationKlasyfikacja obrazów jest zagadnieniem z dziedziny widzenia komputerowego. Polega na całościowej analizie obrazu i przypisaniu go do jednej lub wielu kategorii (klas). Współczesne rozwiązania tego problemu są w znacznej części realizowane z wykorzystaniem konwolucyjnych głębokich sieci neuronowych (convolutional neural network, CNN). W tym rozdziale opisano przełomowe architektury CNN oraz ewolucję state-of-the-art w klasyfikacji...
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CONTROL OF THE WAVES IN A TOWING TANK WITH THE USE OF A BLACK-BOX MODEL
PublicationThe paper describes an adaptive control system of the waves, implemented in the Ship Design and Research Centre, CTO S.A. The purpose of generating the waves in the towing tank is the modelling of the environmental conditions during hydrodynamic model tests. The tests are performed on scale models of towed or free running ships, anchored structures like oil rigs or bottommounted structures, e.g. wind turbines. In the towing tank...
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Simplified approach to assess the dynamic response of a container ship subjected to bow slamming load
PublicationSimplified approach to assess the dynamic response of a container ship subjected to the bow slamming load, resulting in a transient vibratory response, typically called a 'whip-ping', is presented. The accurate numerical modelling is very complex and involves cou-pling of the hydrodynamic and structural solution at every time step, leading to huge com-putational and workload cost. Thus, the one-way coupling methodology is adopted,...
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PROPELLER INVESTIGATIONS BY MEANS OF NUMERICAL SIMULATION
PublicationThe analyses of hydroacoustics are of high interest at the moment due to strong impact of hydroacoustic phenomena on marine environment; the noises, generated e.g. by marine traffic, may be harmful for sea life. The analyses presented here are focused on one of main sources of noises generated by ships, i.e. cavitating propeller. The goal of the work is the assessment of the cavitation phenomenon, carried out with the standard...
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Real-Time Basic Principles Nuclear Reactor Simulator Based on Client-Server Network Architecture with WebBrowser as User Interface
PublicationThe real-time simulator of nuclear reactor basic processes (neutron kinetics, heat generation and its exchange, poisoning and burn- ing up fuel) build in a network environment is presented in this paper. The client-server architecture was introduced, where the server is a pow- erful computing unit and the web browser application is a client for user interface purposes. The challenge was to develop an application running under the...
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Advancing Urban Transit: Gepard and CAR projects - Innovations in Trolleybus Technology
PublicationThe Gepard project in Gdynia, Poland, revolutionized the city's trolleybus network with the introduction of “Trolleybus 2.0” vehicles and an innovative charging system. “Trolleybus 2.0” vehicles combine features of traditional trolleybuses and electric buses boasting traction batteries for autonomous driving and dual legal approval. Statistical analysis of energy consumption informed the development of a hybrid charging concept,...
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Smart Approach for Glioma Segmentation in Magnetic Resonance Imaging using Modified Convolutional Network Architecture (U-NET)
PublicationSegmentation of a brain tumor from magnetic resonance multimodal images is a challenging task in the field of medical imaging. The vast diversity in potential target regions, appearance and multifarious intensity threshold levels of various tumor types are few of the major factors that affect segmentation results. An accurate diagnosis and its treatment demand strict delineation of the tumor affected tissues. Herein, we focus on...
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Improving Social Justice, Environmental Integrity, and Geopolitical Resilience in EU Electric Mobility Transition
PublicationWe recommend improving social justice, environmental integrity, and geopolitical resilience in electric mobility transition. To achieve this policy recommendation, we propose the following: (1) Increase societal acceptance and justice of climate policies by engaging local stakeholders; (2) Prioritize sustainable mobility practices over replacement of internal combustion engine vehicle (ICEV) with battery electric vehicle (BEV);...
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Machine-learning-based precise cost-efficient NO2 sensor calibration by means of time series matching and global data pre-processing
PublicationAir pollution remains a considerable contemporary challenge affecting life quality, the environment, and economic well-being. It encompasses an array of pollutants—gases, particulate matter, biological molecules—emanating from sources such as vehicle emissions, industrial activities, agriculture, and natural occurrences. Nitrogen dioxide (NO2), a harmful gas, is particularly abundant in densely populated urban areas. Given its...
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Comparison of Absorbed and Intercepted Fractions of PAR for Individual Trees Based on Radiative Transfer Model Simulations
PublicationThe fraction of absorbed photosynthetically active radiation (fAPAR) is a key parameter for estimating the gross primary production (GPP) of trees. For continuous, dense forest canopies, fAPAR, is often equated with the intercepted fraction, fIPAR. This assumption is not valid for individual trees in urban environments or parkland settings where the canopy is sparse and there are well-defined tree crown boundaries. Here, the distinction...
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Multi-objective optimization of tool wear, surface roughness, and material removal rate in finishing honing processes using adaptive neural fuzzy inference systems
PublicationHoning processes are usually employed to manufacture combustion engine cylinders and hydraulic cylinders. A crosshatch pattern is obtained that favors the oil flow. In this paper, Adaptive Neural Fuzzy Inference System (ANFIS) models were obtained for tool wear, average roughness Ra, cylindricity and material removal rate in finish honing processes. In addition, multi-objective optimization with the desirability function method...
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Multi-nodal PWR reactor model — Methodology proposition for power distribution coefficients calculation
PublicationIn the paper the multi-nodal Pressurized Water Reactor (PWR) model called Mann’s model is presented. This models is used for modelling purposes of the heat transfer from fuel to coolant in reactor core. The authors expand widely used in literature approach by defining additional coefficients for the heat transfer model. These parameters approximate the power generation distribution in the PWR reactor core according to the to the...
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Application of gas chromatographic data and 2D molecular descriptors for accurate global mobility potential prediction
PublicationMobility is a key feature affecting the environmental fate, which is of particular importance in the case of persistent organic pollutants (POPs) and emerging pollutants (EPs). In this study, the global mobility classification artificial neural networks-based models employing GC retention times (RT) and 2D molecular descriptors were constructed and validated. The high usability of RT was confirmed based on the feature selection...
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Endoscopic image processing and analysis of pistons' service failures of marine diesel engines
PublicationThe paper deals with diagnostic issues concerning endoscopic examinations of working spaces within marine diesel engines. In the beginning, endoscopy apparatus being on laboratory equipment of the Department of Ship Power Plants of Gdansk University of Technology has been characterized. The endoscopy considerations have been focused on theoretical bases of a digital image processing and especially - on the "Shadow" measurement...
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Assessment of under power ed propulsion machinery in electrically driven small inland waterway passenger ships from classification society point of view
PublicationPaper presents short operat ional a nd engineering analysis of underpowered propulsion in small electrically propelled small inland passenger ships. There is evidence that in certain weather conditions the phenomena of added aerodynamic resistance of small water crafts may have seriou s influence on their speed and manoeuvrability. Existing regulations like class societies rules for ship classification and construction or EU Directive 2006/87/EC do...
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Personal Branding and Brand Loyalty, Social Network Users Brand Identification: Polish-French Model
PublicationSocial network brand sites are increasingly attracting the attention of scientists and managers intrigued by their potential application for brand value creation. The aim of this research, based on a multinational sample, is to fill the gap in understanding how users choose among social networking sites as an act of brand identification. The authors of the paper point to the fact that creating a personal brand is becoming more...
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Hardware-Software Implementation of Basic Principles Simulator of Nuclear Reactor Processes
PublicationThe paper presents implementation process of basic principle simulators of a nuclear reactor processes. Simulators are based on point-models of processes: kinetics of neutrons, heat generation and exchange, poisoning and burning-up nuclear fuel. Reference simulator was developed in MATLAB/Simulink without taking into account real-time operation. Second simulator was built using the toolbox xPC with hard real-time requirements....
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Poroelastic Low Noise Road Surfaces
PublicationNoise is one of the most important problems related to road traffic. During the last decades, noise emitted by engine and powertrain of vehicles was greatly reduced and tyres became a clearly dominant noise source. The paper describes the concept of low noise poroelastic road surfaces that are composed with mineral and rubber aggregate bound by polyurethane resin. Those surfaces have a porous structure and are much more flexible...
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MODEL OF MULTILEVEL STOCHASTIC ANALYSIS OF ROAD SAFETY ON REGIONAL LEVEL
PublicationIn this paper multilevel approach to the issue of road safety level on the road network of European regions, classified as NUTS 2 in statistical databases of the European Union, has been presented. Following the pattern of many publications on road safety it has been assumed that the risk calculated as the number of death casualties in road accidents per 100,000 inhabitants of a given region has Poisson distribution. Therefore,...
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Smooth start for strategry game development supported by XNA framework
PublicationTo attract young and casual game developers, Microsoft created a set of libraries oriented towards easier game development and end-product management. The aim of XNA Framework is to provide a unified software development environment for creating games for both PC's and dedicated platforms like XBOX consoles or mobile phones capable of 3D acceleration. The use of modern, object oriented languages available for the .NET platform...
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MARSTRUCT benchmark study on nonlinear FE simulation of an experiment of an indenter impact with a ship side-shell structure
PublicationThis paper presents a benchmark study on collision simulations that was initiated by the MARSTRUCT Virtual Institute. The objective was to compare assumptions, finite element models, modelling techniques and experiences between established researchers within the field. Fifteen research groups world-wide participated in the study. An experiment involving a rigid indenter penetrating a ship-like side structure was used as the case...
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Towards bees detection on images: study of different color models for neural networks
PublicationThis paper presents an approach to bee detection in videostreams using a neural network classifier. We describe the motivationfor our research and the methodology of data acquisition. The maincontribution to this work is a comparison of different color models usedas an input format for a feedforward convolutional architecture appliedto bee detection. The detection process has is based on a neural...
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Instance segmentation of stack composed of unknown objects
PublicationThe article reviews neural network architectures designed for the segmentation task. It focuses mainly on instance segmentation of stacked objects. The main assumption is that segmentation is based on a color image with an additional depth layer. The paper also introduces the Stacked Bricks Dataset based on three cameras: RealSense L515, ZED2, and a synthetic one. Selected architectures: DeepLab, Mask RCNN, DEtection TRansformer,...
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Deep learning for recommending subscription-limited documents
PublicationDocuments recommendation for a commercial, subscription-based online platform is important due to the difficulty in navigation through a large volume and diversity of content available to clients. However, this is also a challenging task due to the number of new documents added every day and decreasing relevance of older contents. To solve this problem, we propose deep neural network architecture that combines autoencoder with...
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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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Towards Cancer Patients Classification Using Liquid Biopsy
PublicationLiquid biopsy is a useful, minimally invasive diagnostic and monitoring tool for cancer disease. Yet, developing accurate methods, given the potentially large number of input features, and usually small datasets size remains very challenging. Recently, a novel feature parameterization based on the RNA-sequenced platelet data which uses the biological knowledge from the Kyoto Encyclopedia of Genes and Genomes, combined with a classifier...