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Search results for: ARTIFICIAL NEURAL NETWORK, MODELLING,SHIP SPEED, ENGINE FUEL CONSUMPTION
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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...
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Driver fatigue detection method based on facial image analysis
PublicationNowadays, ensuring road safety is a crucial issue that demands continuous development and measures to minimize the risk of accidents. This paper presents the development of a driver fatigue detection method based on the analysis of facial images. To monitor the driver's condition in real-time, a video camera was used. The method of detection is based on analyzing facial features related to the mouth area and eyes, such as...
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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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Application of semi-Markov processes for evaluation of diesel engines reliability with regards to diagnostics
PublicationThe paper presents semi-Markov models of technical state transitions for diesel engines, useful for determination of their reliability, as a result of the conducted statistical empirical studies. Interpretation of technical states provided for this sort of engines refers to ship main engines, i.e. engines employed in propulsion systems of sea-going ships. The considerations recognize diesel engine as a diagnosed system (SDN), of...
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Adaptive dynamic control allocation for dynamic positioning of marine vessel based on backstepping method and sequential quadratic programming
PublicationIt is generally assumed in dynamic positioning of over-actuated marine vessels that the control effectiveness matrix (input matrix) is known and constant, or, in case of fault information, it is estimated by the fault detection and diagnosis system. The purpose of the study is to develop the adaptive dynamic positioning control system for an over-actuated marine vessel in the presence of uncertainties and with emphasis on limited...
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Intracranial hemorrhage detection in 3D computed tomography images using a bi-directional long short-term memory network-based modified genetic algorithm
PublicationIntroduction: Intracranial hemorrhage detection in 3D Computed Tomography (CT) brain images has gained more attention in the research community. The major issue to deal with the 3D CT brain images is scarce and hard to obtain the labelled data with better recognition results. Methods: To overcome the aforementioned problem, a new model has been implemented in this research manuscript. After acquiring the images from the Radiological...
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Regulacja napięcia w sieci nN z rozproszonymi źródłami energii
PublicationPodłączanie rozproszonych źródeł energii do sieci energetycznych niskiego napięcia powoduje powstawanie problemów zmienności i niesymetrii napięcia, zwłaszcza w przypadku dużych odległości od transformatora zasilającego. W skrajnych przypadkach zachodzi konieczność redukcji mocy generowanej przez źródło podczas oddawaniu energii do sieci. Rozwiązaniem tego problemu jest zastosowanie energoelektronicznego regulatora napięcia składającego...
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Algorithms for Ship Movement Prediction for Location Data Compression
PublicationDue to safety reasons, the movement of ships on the sea, especially near the coast should be tracked, recorded and stored. However, the amount of vessels which trajectories should be tracked by authorized institutions, often in real time, is usually huge. What is more, many sources of vessels position data (radars, AIS) produces thousands of records describing route of each tracked object, but lots of that records are correlated...
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Automated hearing loss type classification based on pure tone audiometry data
PublicationHearing problems are commonly diagnosed with the use of tonal audiometry, which measures a patient’s hearing threshold in both air and bone conduction at various frequencies. Results of audiometry tests, usually represented graphically in the form of an audiogram, need to be interpreted by a professional audiologist in order to determine the exact type of hearing loss and administer proper treatment. However, the small number of...
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Impact of the Manufacturing Sector on the Export Competitiveness of European Countries – a Spatial Panel Analysis
PublicationThe purpose of this paper is to determine how changes in the export competitiveness of the EU economy (measured by exports and net exports) depend on changes in the competitiveness of processing industries, on the basis of manufacturing data from 19 EU countries over years 1995-2009 and using a spatial panel data model. The determinants of export competitiveness are selected in the light of predictions from international trade...
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Optimisation of cooperation of hybrid renewable energy sources with hydrogen energy storage toward the lowest net present cost
PublicationThe paper presents the results of a technical and economic analysis of the power supply for a model industrial facility based on intermittent renewable energy sources in the form of wind turbines and photovoltaic modules, supplemented with hydrogen energy storage. The adopted power supply strategy assumed the maximisation of self-consumption of self-produced electricity. Six variants were considered, including two with an energy...
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A comparative analysis of the effectiveness of corporate bankruptcy prediction models based on financial ratios: Evidence from Colombia, 2008 to 2015
PublicationLogit and discriminant analyses have been used for corporate bankruptcy prediction in several studies since the last century. In recent years there have been dozens of studies comparing the several models available, including the ones mentioned above and also probit, artificial neural networks, support vector machines, among others. For the first time for Colombia, this paper presents a comparative analysis of the effectiveness...
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Soft Sensor Application in Identification of the Activated Sludge Bulking Considering the Technological and Economical Aspects of Smart Systems Functioning
PublicationThe paper presented the methodology for the construction of a soft sensor used for activated sludge bulking identification. Devising such solutions fits within the current trends and development of a smart system and infrastructure within smart cities. In order to optimize the selection of the data-mining method depending on the data collected within a wastewater treatment plant (WWTP), a number of methods were considered, including:...
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Rapid Surrogate-Aided Multi-Criterial Optimization of Compact Microwave Passives Employing Machine Learning and ANNs
PublicationThis article introduces an innovative method for achieving low-cost and reliable multi-objective optimization (MO) of microwave passive circuits. The technique capitalizes on the attributes of surrogate models, specifically artificial neural networks (ANNs), and multi-resolution electromagnetic (EM) analysis. We integrate the search process into a machine learning (ML) framework, where each iteration produces multiple infill points...
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Selection of excitation signals for high-impedance spectroscopy
PublicationA method of fast impedance spectroscopy of technical objects with high impedance (|Zx| > 1 GOhm) is evaluated in this paper. An object is excited with a signal generated by a digital-to-analog converter (DAC) located on the U2531A DAQ module. Response signals proportional to current flowing through and voltage across the measured object are sampled by analog-to-digital converters (ADC) in the DAQ module. The object impedance spectrum...
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Deep Video Multi-task Learning Towards Generalized Visual Scene Enhancement and Understanding
PublicationThe goal of this thesis was to develop efficient video multi-task convolutional architectures for a range of diverse vision tasks, on RGB scenes, leveraging i) task relationships and ii) motion information to improve multi-task performance. The approach we take starts from the integration of diverse tasks within video multi-task learning networks. We present the first two datasets of their kind in the existing literature, featuring...
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Training of Deep Learning Models Using Synthetic Datasets
PublicationIn order to solve increasingly complex problems, the complexity of Deep Neural Networks also needs to be constantly increased, and therefore training such networks requires more and more data. Unfortunately, obtaining such massive real world training data to optimize neural networks parameters is a challenging and time-consuming task. To solve this problem, we propose an easy-touse and general approach to training deep learning...
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Using Convolutional Neural Networks for Corneal Arcus Detection Towards Familial Hypercholesterolemia Screening
PublicationFamilial hypercholesterolemia (FH) is a highly undiagnosed disease. Among FH patients, the onset of premature coronary artery disease is 13 times higher than in the general population. Early diagnosis and treatment is essential to prevent cardiovascular diseases and their complications, and to prolong life. One of the clinical criteria of FH is the occurrence of a corneal arcus (CA) among patients, especially those under 45 years...
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Prognozowanie wpływu drgań komunikacyjnych na budynki mieszkalne za pomocą sztucznych sieci neuronowych i maszyn wektorów wspierających
PublicationDrgania komunikacyjne mogą stanowić duże obciążenie eksploatacyjne budynku, powodując zarysowania i spękania tynków, odpadanie wypraw, zarysowania konstrukcji, pękanie elementów konstrukcji lub nawet zawalenie się budynku. Pomiary drgań na rzeczywistych konstrukcjach są pracochłonne i kosztowne, a co ważne nie w każdym przypadku są one uzasadnione. Celem pracy jest analiza autorskiego algorytmu, dzięki któremu z dużym prawdopodobieństwem...
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Hardware-Software Implementation of a Sensor Network for CityTraffic Monitoring Using the FPGA- and ASIC-Based Sensor Nodes
PublicationArtykuł opisuje prototypową sieć sensorową do monitorowania ruchu pojazdów w mieście. Węzły sieci sensorowej, wyposażone w kamerę o niskiej rozdzielczości, obserwują ulice i wykrywają poruszające się obiekty. Detekcja obiektów jest realizowana w oparciu o własny algorytm segmentacji obrazów, wykorzystujący podwójne odejmowanie tła, wykrywanie krawędzi i cieni, działający na dedykowanym systemie mikroelektronicznym typu ''System...
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Evolutionary Sets of Cooperating Ship Trajectories: COLREGS Compliance
PublicationThe paper presents a newly designed improvement to the method of solving multi-ship encounter situations. In general, the method combines some of the assumptions of game theory with evolutionary programming and aims to find optimal set of cooperating trajectories of all ships involved in an encounter situation. The improvement presented here is a new way of modelling some of the COLREGS rules. Due to this change, the method is...
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Modelling the loss of time caused by traffic incidents on motorways
PublicationFor each road incident important factors like location, capacity reduction, traffic management, duration of road incidents and amount of traffic should be defined. All performer operations and effects of incidents affect the capacity of the road, average speed, time loss, vehicle queues and traffic jams. In the article road incidents were divided into planned and unexpected. Statistical analysis prepared using the database of traffic...
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THE VIBRATION BASED DIAGNOSTICS OF SHIP PROPULSION SYSTEMS
PublicationThe article has been worked out on the basis of the report devoted to the conducted diagnostic investigations of the ship main propulsion unit’s mechanical system. Gdansk University of Technology has been ordered with such investigations by the repair Shipyard carrying out the ship’s overhaul. Diagnostic tests involved measurements and analyses of the vibration signals generated in selected constructional kinematic pairs of the...
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Predicting a passenger ship's response during evasive maneuvers using Bayesian Learning
PublicationThe rapidly advancing automation of the maritime industry – for instance, through onboard Decision Support Systems (DSS) – can facilitate the introduction of advanced solutions supporting the process of collision avoidance at sea. Nevertheless, relevant solutions that aim to correctly predict a ship's behavior in irregular waves are only available to a limited extent by omitting the impact of wave stochastics on resulting evasive...
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Food analysis using artificial senses.
PublicationNowadays, consumers are paying great attention to the characteristics of food such as smell, taste, and appearance. This motivates scientists to imitate human senses using devices known as electronic senses. These include electronic noses, electronic tongues, and computer vision. Thanks to the utilization of various sensors and methods of signal analysis, artificial senses are widely applied in food analysis for process monitoring...
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Intra-subject class-incremental deep learning approach for EEG-based imagined speech recognition
PublicationBrain–computer interfaces (BCIs) aim to decode brain signals and transform them into commands for device operation. The present study aimed to decode the brain activity during imagined speech. The BCI must identify imagined words within a given vocabulary and thus perform the requested action. A possible scenario when using this approach is the gradual addition of new words to the vocabulary using incremental learning methods....
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IFE: NN-aided Instantaneous Pitch Estimation
PublicationPitch estimation is still an open issue in contemporary signal processing research. Nowadays, growing momentum of machine learning techniques application in the data-driven society allows for tackling this problem from a new perspective. This work leverages such an opportunity to propose a refined Instantaneous Frequency and power based pitch Estimator method called IFE. It incorporates deep neural network based pitch estimation...
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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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A Case Study of Electric Vehicles Load Forecasting in Residential Sector Using Machine Learning Techniques
PublicationElectric vehicles (EVs) have been widely adopted to prevent global warming in recent years. The higher installation of Level-1 and Level-2 chargers in residential areas soon poses challenges to the distributed network. However, such challenges can be mitigated through the adoption of smart charging or controlled charging schemes. To facilitate the implementation of smart charging, accurate forecasting of EV charging demand in residential...
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Investigation of Parallel Data Processing Using Hybrid High Performance CPU + GPU Systems and CUDA Streams
PublicationThe paper investigates parallel data processing in a hybrid CPU+GPU(s) system using multiple CUDA streams for overlapping communication and computations. This is crucial for efficient processing of data, in particular incoming data stream processing that would naturally be forwarded using multiple CUDA streams to GPUs. Performance is evaluated for various compute time to host-device communication time ratios, numbers of CUDA streams,...
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Water-Lubricated Journal Bearings Marine Applications, Design, and Operational Problems and Solutions
PublicationWater-Lubricated Journal Bearings: Marine Applications, Design, and Operational Problems and Solutions provides cutting-edge design solutions, common problems and methods for avoiding them, and material selection considerations for the use of water-lubricated journal bearings in marine environments. These bearings have many advantages, including the absence of the potential for oil contamination. They are also sensitive, and their...
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Ongoing Progress on Pervaporation Membranes for Ethanol Separation
PublicationEthanol, a versatile chemical extensively employed in several fields, including fuel production, food and beverage, pharmaceutical and healthcare industries, and chemical manufacturing, continues to witness expanding applications. Consequently, there is an ongoing need for cost-effective and environmentally friendly purification technologies for this organic compound in both diluted (ethanol-water–) and concentrated solutions (water-ethanol–)....
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Data governance: Organizing data for trustworthy Artificial Intelligence
PublicationThe rise of Big, Open and Linked Data (BOLD) enables Big Data Algorithmic Systems (BDAS) which are often based on machine learning, neural networks and other forms of Artificial Intelligence (AI). As such systems are increasingly requested to make decisions that are consequential to individuals, communities and society at large, their failures cannot be tolerated, and they are subject to stringent regulatory and ethical requirements....
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Wielopoziomowe przekształtniki średniego napięcia (SN) o budowie modułowej
PublicationW artykule omówiono wybrane zagadnienia dotyczące zastosowań wielopoziomowych przekształtników średniego napięcia (SN) w układach napędowych o regulowanej prędkości, zwłaszcza w układach z izolacją od sieci zasilającej. W opracowanym przekształtniku zastosowano izolację galwaniczną od sieci zrealizowaną za pomocą izolowanych przetwornic dc-dc z transformatorami wysokiej częstotliwości (> 5 kHz). Przedstawiono zarejestrowane przebiegi...
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Mathematical modelling of two-step nitrification-denitrification for treatment of sludge digester liquors: influence of nitrite (NO2-N) on the process kinetics
PublicationSeparate treatment of the sludge digester liquors is an alternative for expansion of the mainstream treatment line. In order to reduce the oxygen demand for nitrification and organic carbon demand for denitrification, a shortcut in the nitrogen conversion pathway has been promoted in recent years, i.e. nitrification-denitrification via NO2-N instead of NO3-N. Although NO2-N is a common intermediate product of nitrification and...
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Health System Efficiency in European Countries: Network Data Envelopment Analysis Approach
PublicationPurpose: The article's main aim is to investigate the effectiveness of health systems in European countries based on EUROSTAT data. A comparative analysis of the health systems' effectiveness in different countries is based on their improvement (reform), using the best practices approach. Design/Methodology/Approach: The network DEA model and a slack-based model (NDEA – SBM) are used. A non-oriented model is used. The research...
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Optimized Deep Learning Model for Flood Detection Using Satellite Images
PublicationThe 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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Project-Based Collaborative Research and Training Roadmap for Manufacturing Based on Industry 4.0
PublicationThe importance of the economy being up to date with the latest developments, such as Industry 4.0, is more evident than ever before. Successful implementation of Industry 4.0 principles requires close cooperation of industry and state authorities with universities. A paradigm of such cooperation is described in this paper stemming from university partners with partly overlapping and partly complementary areas of expertise in manufacturing....
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Post processing and selecting data obtain with parametric sub-bottom profiler SES-2000 Standard during sounding the Gulf of Gdansk
PublicationThe main goal of the paper is to describe the results of sounding the Gulf of Gdansk seabed using a parametric sub-bottom profiler SES-2000 Standard. Quality of obtained during trials data depends inter alia on proper location of antenna to reduce influence of pitch, roll, heave and ship noise (bubbles from propeller and a hull flow, vibration from main engine and peripheral devices). Furthermore calibration of complementary units...
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Fusion-based Representation Learning Model for Multimode User-generated Social Network Content
PublicationAs mobile networks and APPs are developed, user-generated content (UGC), which includes multi-source heterogeneous data like user reviews, tags, scores, images, and videos, has become an essential basis for improving the quality of personalized services. Due to the multi-source heterogeneous nature of the data, big data fusion offers both promise and drawbacks. With the rise of mobile networks and applications, UGC, which includes...
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Thermal Image Processing for Respiratory Estimation from Cubical Data with Expandable Depth
PublicationAs healthcare costs continue to rise, finding affordable and non-invasive ways to monitor vital signs is increasingly important. One of the key metrics for assessing overall health and identifying potential issues early on is respiratory rate (RR). Most of the existing methods require multiple steps that consist of image and signal processing. This might be difficult to deploy on edge devices that often do not have specialized...
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Network-aware Data Prefetching Optimization of Computations in a Heterogeneous HPC Framework
PublicationRapid development of diverse computer architectures and hardware accelerators caused that designing parallel systems faces new problems resulting from their heterogeneity. Our implementation of a parallel system called KernelHive allows to efficiently run applications in a heterogeneous environment consisting of multiple collections of nodes with different types of computing devices. The execution engine of the system is open for...
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Relay-aided Wireless Sensor Network Discovery Algorithm for Dense Industrial IoT utilizing ESPAR Antennas
PublicationIndustrial Internet of Things (IIoT) applicationsrequire reliable and efficient wireless communication. Assumingdense Wireless Sensor Networks (WSNs) operating in a harshenvironment, a concept of a Time Division Multiple Access(TDMA) based WSN enriched with Electronically SteerableParasitic Array Radiator (ESPAR) antennas is proposed andexamined in this work. The utilized...
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DATABASE AND BIGDATA PROCESSING SYSTEM FOR ANALYSIS OF AIS MESSAGES IN THE NETBALTIC RESEARCH PROJECT
PublicationA specialized database and a software tool for graphical and numerical presentation of maritime measurement results has been designed and implemented as part of the research conducted under the netBaltic project (Internet over the Baltic Sea – the implementation of a multi-system, self-organizing broadband communications network over the sea for enhancing navigation safety through the development of e-navigation services.) The...
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Behavior Analysis and Dynamic Crowd Management in Video Surveillance System
PublicationA concept and practical implementation of a crowd management system which acquires input data by the set of monitoring cameras is presented. Two leading threads are considered. First concerns the crowd behavior analysis. Second thread focuses on detection of a hold-ups in the doorway. The optical flow combined with soft computing methods (neural network) is employed to evaluate the type of crowd behavior, and fuzzy logic aids detection...
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Efficiency Increasing of No-reference Image Quality Assessment in UAV Applications
PublicationUnmanned aerial vehicle (UAV) imaging is a dynamically developing field, where the effectiveness of imaging applications highly depends on quality of the acquired images. No-reference image quality assessment is widely used for quality control and image processing management. However, there is a lack of accuracy and adequacy of existing quality metrics for human visual perception. In this paper, we demonstrate that this...
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Standard of living in Poland at regional level - classification with Kohonen self-organizing maps
PublicationThe standard of living is spatially diversified and its analyzes enable shaping regional policy. Therefore, it is crucial to assess the standard of living and to classify regions due to their standard of living, based on a wide set of determinants. The most common research methods are those based on composite indicators, however, they are not ideal. Among the current critiques moved to the use of composite...
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A Study of Cross-Linguistic Speech Emotion Recognition Based on 2D Feature Spaces
PublicationIn this research, a study of cross-linguistic speech emotion recognition is performed. For this purpose, emotional data of different languages (English, Lithuanian, German, Spanish, Serbian, and Polish) are collected, resulting in a cross-linguistic speech emotion dataset with the size of more than 10.000 emotional utterances. Despite the bi-modal character of the databases gathered, our focus is on the acoustic representation...
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Ranking Speech Features for Their Usage in Singing Emotion Classification
PublicationThis paper aims to retrieve speech descriptors that may be useful for the classification of emotions in singing. For this purpose, Mel Frequency Cepstral Coefficients (MFCC) and selected Low-Level MPEG 7 descriptors were calculated based on the RAVDESS dataset. The database contains recordings of emotional speech and singing of professional actors presenting six different emotions. Employing the algorithm of Feature Selection based...