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Search results for: marine engine fault diagnosis fault detection diesel engine machine learning ensemble learning extreme learning machines multi-class decomposition
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Machine Learning and data mining tools applied for databases of low number of records
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Overcoming “Big Data” Barriers in Machine Learning Techniques for the Real-Life Applications
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Multivariate Features Extraction and Effective Decision Making Using Machine Learning Approaches
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Adapt Your Teacher: Improving Knowledge Distillation for Exemplar-free Continual Learning
PublicationIn this work, we investigate exemplar-free class incremental learning (CIL) with knowledge distillation (KD) as a regularization strategy, aiming to prevent forgetting. KDbased methods are successfully used in CIL, but they often struggle to regularize the model without access to exemplars of the training data from previous tasks. Our analysis reveals that this issue originates from substantial representation shifts in the teacher...
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Looking through the past: better knowledge retention for generative replay in continual learning
PublicationIn this work, we improve the generative replay in a continual learning setting to perform well on challenging scenarios. Because of the growing complexity of continual learning tasks, it is becoming more popular, to apply the generative replay technique in the feature space instead of image space. Nevertheless, such an approach does not come without limitations. In particular, we notice the degradation of the continually trained...
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Machine learning-based prediction of residual drift and seismic risk assessment of steel moment-resisting frames considering soil-structure interaction
PublicationNowadays, due to improvements in seismic codes and computational devices, retrofitting buildings is an important topic, in which, permanent deformation of buildings, known as Residual Interstory Drift Ratio (RIDR), plays a crucial role. To provide an accurate yet reliable prediction model, 32 improved Machine Learning (ML) algorithms were considered using the Python software to investigate the best method for estimating Maximum...
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Reduction of CO2 Emissions from Offshore Combined Cycle Diesel Engine-Steam Turbine Power Plant Powered by Alternative Fuels
PublicationDiverse forms of environmental pollution arise with the introduction of materials or energy that exert adverse effects on human health, climate patterns, ecosystems, and beyond. Rigorous emission regulations for gases resulting from fuel combustion are being enforced by the European Union and the International Maritime Organization (IMO), directed at maritime sectors to mitigate emissions of SOx, NOx, and CO2. The IMO envisions...
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Integrating Statistical and Machine‐Learning Approach for Meta‐Analysis of Bisphenol A‐Exposure Datasets Reveals Effects on Mouse Gene Expression within Pathways of Apoptosis and Cell Survival
PublicationBisphenols are important environmental pollutants that are extensively studied due to different detrimental effects, while the molecular mechanisms behind these effects are less well understood. Like other environmental pollutants, bisphenols are being tested in various experimental models, creating large expression datasets found in open access storage. The meta‐analysis of such datasets is, however, very complicated for various...
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An Adaptive Network Model Simulating the Effects of Different Culture Types and Leader Qualities on Mistake Handling and Organisational Learning
PublicationThis paper investigates computationally the following research hypotheses: (1) Higher flexibility and discretion in organizational culture results in better mistake management and thus better organizational learning, (2) Effective organizational learning requires a transformational leader to have both high social and formal status and consistency, and (3) Company culture and leader's behavior must align for the best learning effects....
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An Adaptive Network Model Simulating the Effects of Different Culture Types and Leader Qualities on Mistake Handling and Organisational Learning
PublicationThis paper investigates computationally the following research hypotheses: (1) Higher flexibility and discretion in organizational culture results in better mistake management and thus better organizational learning, (2) Effective organizational learning requires a transformational leader to have both high social and formal status and consistency, and (3) Company culture and leader’s behavior must align for the best learning effects....
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Lead-free bismuth-based perovskites coupled with g–C3N4: A machine learning based novel approach for visible light induced degradation of pollutants
PublicationThe use of metal halide perovskites in photocatalytic processes has been attempted because of their unique optical properties. In this work, for the first time, Pb-free Bi-based perovskites of the Cs3Bi2X9 type (X = Cl, Br, I, Cl/Br, Cl/I, Br/I) were synthesized and subjected to comprehensive morphological, structural, and surface analyses, and photocatalytic properties in the phenol degradation reaction were examined. Furthermore,...
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A concept of the predicting of technical state of diesel engine elements
PublicationPrzedstawiono możliwości i ograniczenia dotyczące prognozowania stanu technicznego elementów silników oraz wykazano potrzebę doskonalenia istniejących metod planowania ich obsług profilaktycznych. Wskazano możliwość przekształcenia rozkadów szybkości zużywania elementów silników na rozkłady czasu ich poprawnego działania do osiągnięcia stanu granicznego w celu prognozowania ich stanu technicznego i odpowiedniego planowania obsług.
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Can Evaluation Patterns Enable End Users to Evaluate the Quality of an e-learning System? An Exploratory Study.
PublicationThis paper presents the results of an exploratory study whose main aim is to verify if the Pattern-Based (PB) inspection technique enables end users to perform reliable evaluation of e-learning systems in real work-related settings. The study involved 13 Polish and Italian participants, who did not have an HCI background, but used e-learning platforms for didactic and/or administrative purposes. The study revealed that the participants...
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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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Strategic Flexibility as a Mediator in Relationship between Managerial Decisions and Organizational Learning: Ambidexterity Perspective
PublicationPurpose: The purpose of the article is to determine strategic flexibility in the relationship between managerial decisions and organizational learning. The analyses are conducted in the ambidexterity convection. Design/Methodology/Approach: The study was conducted at a textile company. The company is a leader in the textile recycling industry in Poland. Empirical data were collected using the PAPI technique. The survey questionnaire...
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On the possible increasing of efficiency of ship power plant with the system combined of marine diesel engine, gas turbine and steam turbine at the main engine - steam turbine mode of cooperation
PublicationW pracy przedstawiono koncepcję układu kombinowanego okrętowego dużej mocy złożonego z silnika głównego tłokowego oraz skojarzonych z nim turbiny gazowej mocy i układu turbiny parowej, wykorzystujących energię zawartą w spalinach wylotowych silnika głównego tłokowego. Rozpatrywano układ kombinowany układ złożony z silnika spalinowego tłokowego skojarzony z układem turbiny parowej. Podano algorytm i obliczenia poszczególnych podukładów:...
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Comparative study on total nitrogen prediction in wastewater treatment 1 plant and effect of various feature selection methods on machine learning algorithms performance
PublicationWastewater characteristics prediction in wastewater treatment plants (WWTPs) is valuable and can reduce the number of sampling, energy, and cost. Feature Selection (FS) methods are used in the pre-processing section for enhancing the model performance. This study aims to evaluate the effect of seven different FS methods (filter, wrapper, and embedded methods) on enhancing the prediction accuracy for total nitrogen (TN) in the WWTP...
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Orientation-aware ship detection via a rotation feature decoupling supported deep learning approach
PublicationShip imaging position plays an important role in visual navigation, and thus significant focuses have been paid to accurately extract ship imaging positions in maritime videos. Previous studies are mainly conducted in the horizontal ship detection manner from maritime image sequences. This can lead to unsatisfied ship detection performance due to that some background pixels maybe wrongly identified as ship contours. To address...
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Deep Learning Approaches in Histopathology
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e-Learning in Tourism Education
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Online Learning Based on Prototypes
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Distributed Learning with Data Reduction
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Assesment of operation of ship main diesel engine using the theory of semi-markovian and markov processes.
PublicationTo precisely determine the task it is necessary to specify also its duration time, apart from conditions in which it will be realized. When considering propulsion engine, i.e. the main element of ship propulsion system, especially important becomes not only the problem which amount of energy could be at one's disposal but also within which time interval it could be delivered. Therefore apart from applying the commonly used reliability...
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Position Estimation in Mixed Indoor-Outdoor Environment Using Signals of Opportunity and Deep Learning Approach
PublicationTo improve the user's localization estimation in indoor and outdoor environment a novel radiolocalization system using deep learning dedicated to work both in indoor and outdoor environment is proposed. It is based on the radio signatures using radio signals of opportunity from LTE an WiFi networks. The measurements of channel state estimators from LTE network and from WiFi network are taken by using the developed application....
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Possible efficiency increasing of ship propulsion and marine power plant with the system combined of marine diesel engine, gas turbine and steam turbine
PublicationW rozdziale przedstawiono koncepcję układu kombinowanego okrętowego lub morskiej pływającej elektrowni dużej mocy złożonego z silnika głównego tłokowego oraz skojarzonych z nim turbiny gazowej mocy i układu turbiny parowej, wykorzystujących energię zawartą w spalinach wylotowych silnika głównego tłokowego. Rozpatrywano możliwości zastosowania takich układów w układach okrętowych z punktu widzenia sprawnościowego. Podano możliwości...
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Perspektywy wykorzystania technologii internetowych typu E-learning w dydaktyce szkół wyższych.
PublicationArtykuł dotyczy nauczania przez Internet na poziomie uniwersyteckim. Zaprezentowany został model wirtualnego uniwersytetu, który obejmuje materiały dydaktyczne, komunikację, egzaminy i organizację. Artykuł koncentruje się na technicznych zagadnieniach. Przeanalizowano także wpływ wykorzystania technologii E-learning na różne aspekty życia wyższej uczelni.
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Big Data from Sensor Network via Internet of Things to Edge Deep Learning for Smart City
PublicationData from a physical world is sampled by sensor networks, and then streams of Big Data are sent to cloud hosts to support decision making by deep learning software. In a smart city, some tasks may be assigned to smart devices of the Internet of Things for performing edge computing. Besides, a part of workload of calculations can be transferred to the cloud hosts. This paper proposes benchmarks for division tasks between an edge...
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A CUSUM-Based Approach for Condition Monitoring and Fault Diagnosis of Wind Turbines
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A method of fault diagnosis of analog parts of electronic embedded systems with tolerances
PublicationPrzedstawiono nową metodę detekcji i lokalizacji uszkodzeń w częściach analogowych z tolerancjami elementów nieuszkodzonych mieszanych sygnałowo elektronicznych systemów wbudowanych sterowanych mikrokontrolerami. Metoda składa się z trzech etapów. W pierwszym etapie tworzony jest słownik uszkodzeń przez aproksymację rodziny pasów lokalizacyjnych. W etapie pomiarowym wewnętrzny licznik mikrokontrolera mierzy czasy trwania impulsów...
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A neural network based system for soft fault diagnosis in electronic circuits
PublicationW artykule przedstawiono system do diagnostyki uszkodzeń parametrycznych w układach elektronicznych. W systemie zaimplementowano słownikową metodę lokalizacji uszkodzeń, bazującą na pomiarach w dziedzinie częstotliwości przeprowadzanych za pomocą analizatora transmitancji HP4192A. Rozważono główne etapy projektowania systemu: definiowanie modelu uszkodzeń, wybór optymalnych częstotliwosci pomiarowych, ekstrakcję cech diagnostycznych,...
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Harmony Search for Self-configuration of Fault–Tolerant and Intelligent Grids
PublicationIn this paper, harmony search algorithms have been proposed to self-configuration of fault-tolerant grids for big data processing. Self-configuration of computer grids lies in the fact that new computer nodes are automatically configured by software agents and then integrated into the grid. A base node works due to several configuration parameters that define some aspects of data communications and energy power consumption. We...
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LABORATORY STUDY ON INFLUENCE OF AIR DUCT THROTTLING ON EXHAUST GAS COMPOSITION IN MARINE FOUR-STROKE DIESEL ENGINE
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The effect of the motor filters on earth fault current waveform in circuits with variable speed drives
PublicationIn circuits with variable speed drives distorted earth fault current flows. Earth fault current distortion influences the threshold of ventricular fibrillation. This paper presents earth fault current distortion in circuits with variable speed drives when motor filter is used. Two types of motor filter are analyzed. For every type of filter the effect of earth fault current distortion on ventricular fibrillation is evaluated.
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The effect of the motor filters on earth fault current waveform in circuits with variable speed drives
PublicationIn circuits with variable speed drives distorted earth fault current flows. Earth fault current distortion influences the threshold of ventricular fibrillation. This paper presents earth fault current distortion in circuits with variable speed drives when motor filter is used. Two types of motor filter are analyzed. For every type of filter the effect of earth fault current distortion on ventricular fibrillation is evaluated.
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Prediction of maximum tensile stress in plain-weave composite laminates with interacting holes via stacked machine learning algorithms: A comparative study
PublicationPlain weave composite is a long-lasting type of fabric composite that is stable enough when being handled. Open-hole composites have been widely used in industry, though they have weak structural performance and complex design processes. An extensive number of material/geometry parameters have been utilized for designing these composites, thereby an efficient computational tool is essential for that purpose. Different Machine Learning...
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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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Deep Learning-Based LOS and NLOS Identification in Wireless Body Area Networks
PublicationIn this article, the usage of deep learning (DL) in ultra-wideband (UWB) Wireless Body Area Networks (WBANs) is presented. The developed approach, using channel impulse response, allows higher efficiency in identifying the direct visibility conditions between nodes in off-body communication with comparison to the methods described in the literature. The effectiveness of the proposed deep feedforward neural network was checked on...
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Experimental determination of general characteristic of internal combustion engine using mobile test bench connected via Power Take-Off unit
PublicationThe general characteristics of the engine include information about the regions of the engine's operating area that are most efficient, where specific fuel consumption reaches the smallest values. Economic operation based on those characteristics can contribute to a significant reduction of fuel consumption and consequently less pollutant emissions and lower costs. The paper presents an experimental method of determination of general...
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Machine Learning for Control Systems Security of Industrial Robots: a Post-covid-19 Overview
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Machine Learning Methods in Damage Prediction of Masonry Development Exposed to the Industrial Environment of Mines
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Advances in Architectures, Big Data, and Machine Learning Techniques for Complex Internet of Things Systems
PublicationTe feld of Big Data is rapidly developing with a lot of ongoing research, which will likely continue to expand in the future. A crucial part of this is Knowledge Discovery from Data (KDD), also known as the Knowledge Discovery Process (KDP). Tis process is a very complex procedure, and for that reason it is essential to divide it into several steps (Figure 1). Some authors use fve steps to describe this procedure, whereas others...
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SELECTED COMBINED POWER SYSTEMS CONSISTED OF SELFIGNITION ENGINE AND STEAM TURBINE
PublicationThis paper presents optimization of selected combined diesel engine-steam turbine systems. Two systems: the system combined with waste heat one-pressure boiler only and its version containing additionally low-pressure boiler proper feeding degasifier and the system of two-pressure cycle, were taken into considerations. Their surplus values of power output and efficiency associated with utilization of waste heat contained in piston...
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Love your mistakes!—they help you adapt to change. How do knowledge, collaboration and learning cultures foster organizational intelligence?
PublicationPurpose: The study aims to determine how the acceptance of mistakes is related to adaptability to change in a broad organizational context. Therefore it explores how knowledge, collaboration, and learning culture (including “acceptance of mistakes”) might help organizations overcome their resistance to change. Methodology: The study uses two sample groups: students aged 18–24 (330 cases) and employees aged >24 (326 cases) who work...
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Technology-Enhanced Environmental Learning: Co-design of Educational Mobile Application Case
PublicationThe process of co-creating an educational mobile application to support environmentally friendly behavior is presented in this paper. The research material consisted of quantitative data collected on the application during the first testing phase by early adopters. The results suggest that the most frequently used features of the app were related to transport and educational activities. While women tended to split their time between...
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Improvement of speech intelligibility in the presence of noise interference using the Lombard effect and an automatic noise interference profiling based on deep learning
PublicationThe Lombard effect is a phenomenon that results in speech intelligibility improvement when applied to noise. There are many distinctive features of Lombard speech that were recalled in this dissertation. This work proposes the creation of a system capable of improving speech quality and intelligibility in real-time measured by objective metrics and subjective tests. This system consists of three main components: speech type detection,...
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The effects of relational and psychological capital on work engagement: the mediation of learning goal orientation
PublicationPurpose – This paper proposes a research model in which learning goal orientation (LGO) mediates the impacts of relational capital and psychological capital (PsyCap) on work engagement. Design/methodology/approach – Data obtained from 475 managers and employees in the manufacturing and service industries in Poland were utilized to assess the linkages given above. Common method variance was controlled by the unmeasured latent method...
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Optimizing Medical Personnel Speech Recognition Models Using Speech Synthesis and Reinforcement Learning
PublicationText-to-Speech synthesis (TTS) can be used to generate training data for building Automatic Speech Recognition models (ASR). Access to medical speech data is because it is sensitive data that is difficult to obtain for privacy reasons; TTS can help expand the data set. Speech can be synthesized by mimicking different accents, dialects, and speaking styles that may occur in a medical language. Reinforcement Learning (RL), in the...
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An application for a new type of pneumatic engine concept
PublicationHeavy trucks are often equipped with loading and unloading systems like dock levellers with swing lip or telescopic lip. Most of these devices require hydro-electrical energy supply systems (eg. the pump that presses the working substance to the actuators must be propelled by electric engine.) The space taken by pump with electric engine can be reduced on condition that a new type of pneumatic drive will be considered. It is possible...
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Fault Diagnostics in PEMFC Stacks by Evaluation of Local Performance and Cell Impedance Analysis
PublicationStarvation, flooding, and dry‐out phenomena occur in polymer electrolyte membrane fuel cells (PEMFCs), due to heterogeneous local conditions, material inhomogeneity, and uneven flow distribution across the single cell active area and in between the individual cells. The impact of the load level and air feed conditions on the performance was identified for individual single cells within a 10‐cell stack. Analysis of the current density...
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Sampling-based novel heterogeneous multi-layer stacking ensemble method for telecom customer churn prediction
PublicationIn recent times, customer churn has become one of the most significant issues in business-oriented sectors with telecommunication being no exception. Maintaining current customers is particularly valuable due to the high degree of rivalry among telecommunication companies and the costs of acquiring new ones. The early prediction of churned customers may help telecommunication companies to identify the causes of churn and design...