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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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AUTOMATIC LEARNING OF STRATEGY AND RULES IN CARD GAMES USING IMAGE FROM CAMERA
PublicationBelow work tries to answer a question: if it is possible to replace real human with computer system in social games. As a subject for experiments, card games were chosen, because they require a lot of player interaction (playing and taking cards), while their rules are easy to present in form of clear list of statements. Such a system, should allow real players to play without constant worrying about guiding or helping computer...
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Novel Fault Identification for Electromechanical Systems via Spectral Technique and Electrical Data Processing
PublicationIt is proposed, developed, investigated, and validated by experiments and modelling for the first time in worldwide terms new data processing technologies, higher order spectral multiple correlation technologies for fault identification for electromechanical systems via electrical data processing. Investigation of the higher order spectral triple correlation technology via modelling has shown that the proposed data processing technology...
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Analysis of start energy of Stirling engine type alpha
PublicationThe Stirling engine type alpha is composed of two cylinders (expansion space E and compression space C), regenerator that forms the space between the cylinders and the buffer space (under the pistons). Before the start-up and as a result of long-term operation, the average pressure in the working space (above the pistons) and in the buffer space is the same. However, in the initial phase of operation, the average pressure in the...
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A semi-Markov model of fuel combustion process in a Diesel engine
PublicationW artykule przedstawiono czterostanowy model procesu spalania w przestrzeniach roboczych (cylindrach) silników o zapłonie samoczynnym w formie procesu semimarkowskiego, dyskretnego w stanach i ciągłego w czasie. Wartościami tego procesu są stany odpowiadające powszechnie akceptowanym rodzajom spalania w tego rodzaju silnikach a mianowicie takie stany procesu jak: spalanie pełne (całkowite i zupełne), spalanie niezupełne, spalanie...
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Energy-time method for assesment of main diesel engine operation
PublicationW publikacji przedstawiono rozwinięcie prezentowanej w literaturze metody ilościowej oceny działania na przykładzie okrętowego silnika głównego z zapłonem samoczynnym. Według tej interpretacji, działanie silnika może zostać przedstawione jako wielkość fizyczna. W tym aspekcie, na przykładzie wybranego układu funkcjonalnego, silnika dokonano oceny przydatności tej wielkości do opisu własności niezawodnościowych tego układu.
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Visual Content Learning in a Cognitive Vision Platform for Hazard Control (CVP-HC)
PublicationThis work is part of an effort for the development of a Cognitive Vision Platform for Hazard Control (CVP-HC) for applications in industrial workplaces, adaptable to a wide range of environments. The paper focuses on hazards resulted from the nonuse of personal protective equipment (PPE). Given the results of previous analysis of supervised techniques for the problem of classification of a few PPE (boots, hard hats, and gloves...
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Modeling of the internal combustion engine cooling system
PublicationThe article concerns computer modelling of processes in cooling systems of internal combustion engines. Modelling objectives and existing commercial programs are presented. It also describes Author’s own method of binding graphs used to describe phenomena in the cooling system of a spark ignition engine. The own model has been verified by tests on the engine dynamometer. An example of using a commercial program for experimental...
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Using LSTM networks to predict engine condition on large scale data processing framework
PublicationAs the Internet of Things technology is developing rapidly, companies have an ability to observe the health of engine components and constructed systems through collecting signals from sensors. According to output of IoT sensors, companies can build systems to predict the conditions of components. Practically the components are required to be maintained or replaced before the end of life in performing their assigned task. Predicting...
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Unsupervised Learning for Biomechanical Data Using Self-organising Maps, an Approach for Temporomandibular Joint Analysis
PublicationWe proposed to apply a specific machine learning technique called Self-Organising Maps (SOM) to identify similarities in the performance of muscles around human temporomandibular joint (TMJ). The performance was assessed by measuring muscle activation with the use of surface electromyography (sEMG). SOM algorithm used in the study was able to find clusters of data in sEMG test results. The SOM analysis was based on processed sEMG...
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Pursuing the Deep-Learning-Based Classification of Exposed and Imagined Colors from EEG
PublicationEEG-based brain-computer interfaces are systems aiming to integrate disabled people into their environments. Nevertheless, their control could not be intuitive or depend on an active external stimulator to generate the responses for interacting with it. Targeting the second issue, a novel paradigm is explored in this paper, which depends on a passive stimulus by measuring the EEG responses of a subject to the primary colors (red,...
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Diagnosis of fully differential circuits based on a fault dictionary implemented in the microcontroller systems
PublicationPrzedstawiono nową koncepcję testera wbudowanego bist przeznaczonego do diagnostyki w pełni różnicowych układów analogowych implementowanych w mikrosystemach mieszanych sygnałowo. w trakcie testowania mierzona jest amplituda i faza wyjściowego napięcia różnicowego. procedura detekcji i lokalizacji uszkodzeń bazuje na słowniku uszkodzeń przechowywanym w pamięci programu mikrokontrolera. korzystną cechą przestrzeni pomiarowej wyznaczonej...
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Deep Learning Optimization for Edge Devices: Analysis of Training Quantization Parameters
PublicationThis paper focuses on convolution neural network quantization problem. The quantization has a distinct stage of data conversion from floating-point into integer-point numbers. In general, the process of quantization is associated with the reduction of the matrix dimension via limited precision of the numbers. However, the training and inference stages of deep learning neural network are limited by the space of the memory and a...
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Some aspects of blended-learning education
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Note on universal algoritms for learning theory
PublicationW 2001 Cucker i Smale zaproponowali nowe podejście do teorii uczenia się w oparciu o problematykę teorii aproksymacji.W 2005 i 2007 Bivev, Cohen, Dahmen, DeVore i Temlyakov opublikowali dwie prace z teorii uczenia się. W omawianej publikacji uogólniliśmy ich rezultaty jednocześnie upraszczając dowody.
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A consensus-based approach to the distributed learning
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Prototype selection algorithms for distributed learning
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An agent-based framework for distributed learning
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Structure and Randomness in Planning and Reinforcement Learning
PublicationPlanning in large state spaces inevitably needs to balance the depth and breadth of the search. It has a crucial impact on the performance of a planner and most manage this interplay implicitly. We present a novel method \textit{Shoot Tree Search (STS)}, which makes it possible to control this trade-off more explicitly. Our algorithm can be understood as an interpolation between two celebrated search mechanisms: MCTS and random...
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E-learning in tourism and hospitality: A map
PublicationThe impact of information and communication technologies (ICT) on tourism and hospitality industries has been widely recognized and investigated as a one of the major changes within the domains in the last decade: new ways of communicating with prospective tourists and new ways of purchasing products arisen are now part of the industries’ everyday life. Poor attention has been paid so far to the role played by new media in education...
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Data-Driven Surrogate-Assisted Optimization of Metamaterial-Based Filtenna Using Deep Learning
PublicationIn this work, a computationally efficient method based on data driven surrogate models is pro-posed for the design optimization procedure of a Frequency Selective Surface (FSS)-based filtering antenna (Filtenna). A Filtenna acts as a as module that simultaneously pre-filters unwanted sig-nals, and enhances the desired signals at the operating frequency. However, due to a typically large number of design variables of FSS unit elements,...
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Decision making process using deep learning
PublicationEndüstri 4.0, dördüncü endüstri devrimi veya Endüstriyel Nesnelerin İnterneti (IIoT) olarak adlandırılan sanayi akımı, işletmelere, daha verimli, daha büyük bir esneklikle, daha güvenli ve daha çevre dostu bir şekilde üretim yapma imkanı sunmaktadır. Nesnelerin İnterneti ile bağlantılı yeni teknoloji ve hizmetler birçok endüstriyel uygulamada devrim niteliği taşımaktadır. Fabrikalardaki otomasyon, tahminleyici bakım (PdM – Predictive...
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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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Projekt Leonardo da Vinci EMDEL (European Model for Distance Education and Learning) - otwarte szkolenia online.
PublicationW referacie zaprezentowano główne zadania oraz ofertę szkoleniową Centrum Edukacji Niestacjonarnej Politechniki Gdańskiej (CEN PG) w kontekście realizowanych projektów Unii Europejskiej. Przedstawiono projekt Leonardo da Vinci EMDEL - European Model for Distance Education and learning - realizowany przez CEN PG w latach 2001-2005 oraz opisano doświadczenia w zakresie adaptacji i lokalizacji opracowanych przez partnerów projektu...
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Fault diagnosing system of wheeled tractors
PublicationA defect of complex wheeled tractor assembles most frequently negative influence on exploitation efficiency, safety and exhaust gases emission. Structure complexity of wheeled tractors requires more and more advanced diagnostic methods for identification of their serviceable possibilities as well in manufacturing step as in exploitation. In classical diagnosing methods of wheeled tractor defects states mapping by measured diagnostic...
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Improving sensitivity of residual current transformers to high frequency earth fault currents
PublicationFor protection against electric shock in low voltage systems residual current devices are commonly used. However, their proper operation can be interfered when high frequency earth fault current occurs. Serious hazard of electrocution exists then. In order to detect such a current, it is necessary to modify parameters of residual current devices, especially the operating point of their current transformer. The authors proposed...
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Thermal Images Analysis Methods using Deep Learning Techniques for the Needs of Remote Medical Diagnostics
PublicationRemote medical diagnostic solutions have recently gained more importance due to global demographic shifts and play a key role in evaluation of health status during epidemic. Contactless estimation of vital signs with image processing techniques is especially important since it allows for obtaining health status without the use of additional sensors. Thermography enables us to reveal additional details, imperceptible in images acquired...
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Sensorless field oriented control for five-phase induction motors with third harmonic injection and fault insensitive feature
PublicationThe paper presents a solution for sensorless field oriented control (FOC) system for five-phase induction motors with improved rotor flux pattern. In order to obtain the advantages of a third harmonic injection with a quasi-trapezoidal flux shape, two vector models, α1–β1 and α3–β3, were transformed into d1– q1, d3– q3 rotating frames, which correlate to the 1st and 3rd harmonic plane respectively. A linearization approach of the...
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Behavior of residual current devices at earth fault currents with DC component
PublicationLow-voltage electrical installations are increasingly saturated with power electronic converters. Due to very high popularity of photovoltaic (PV) installations and the spread of electric vehicles (EV) as well as their charging installations, DC–AC and AC–DC converters are often found in power systems. The transformerless coupling of AC and DC systems via power electronic converters means that an electrical installation containing...
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Using Isolation Forest and Alternative Data Products to Overcome Ground Truth Data Scarcity for Improved Deep Learning-based Agricultural Land Use Classification Models
PublicationHigh-quality labelled datasets represent a cornerstone in the development of deep learning models for land use classification. The high cost of data collection, the inherent errors introduced during data mapping efforts, the lack of local knowledge, and the spatial variability of the data hinder the development of accurate and spatially-transferable deep learning models in the context of agriculture. In this paper, we investigate...
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An Approach to Data Reduction for Learning from Big Datasets: Integrating Stacking, Rotation, and Agent Population Learning Techniques
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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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An Instantaneous Engine Speed Estimation Method Using Multiple Matching Synchrosqueezing Transform
PublicationInstantaneous rotational speed measurement of the engine is crucial in routine inspection and maintenance of an automobile engine. Since the contact measurement of rotational speed is not always available, the vibration measurement has been used for noncontact rotational speed estimation methods. Unfortunately, the accuracy of the noncontact estimation methods by analyzing engine vibration frequency is not satisfactory due to the...
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Application of Stirling Engine Type Alpha Powered by the Recovery Energy on Vessels
PublicationThe Stirling engine is a device, in which thermal energy is transformed into mechanical without a contact between the heat carrier, and the working gas closed in the engine. Mentioned feature makes this type of engine very attractive for the use of the recovery energy, taken from other heat devices. One of the potential applications of Stirling engines is the use of thermal energy generated in the ship's engine room for producing...
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Analysis of hull, propeller and engine interactions in regular waves by a combination of experiment and simulation
PublicationAnalysis of hull, propeller and engine interactions in regular waves by a combination of experiment and simulation
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A Novel Spatio–Temporal Deep Learning Vehicle Turns Detection Scheme Using GPS-Only Data
PublicationWhether the computer is driving your car or you are, advanced driver assistance systems (ADAS) come into play on all levels, from weather monitoring to safety. These modern-day ADASs use various assisting tools for drivers to keep the journey safe; these sophisticated tools provide early signals of numerous events, such as road conditions, emerging traffic scenarios, and weather warnings. Many urban applications, such as car-sharing...
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EXHAUST TEMPERATURE MEASUREMENTS OF THE MARINE TURBOCHARGED DIESEL ENGINES IN OPERATION
PublicationThe article presents the selected metrology issues concerning the exhaust temperature of the turbocharged marine engines during operation. The special concern has been paid on existing disturbances as well as thermodynamical interpretation of the recorded measurement signal. A diagnostic informativeness of the standard exhaust temperature’s measurements has worked out while the engine runs in steady states has been also considered...
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A new method of fault loop resistance measurement in low voltage systems with residual current devices
PublicationThis paper presents a new method of fault loop resistance measurement in low voltage systems with residual current devices. The method enables measuring fault loop resistance without nuisance tripping of residual current devices, by application an unconventional waveform of measurement current. It is important for proper verification of the effectiveness of protection against electric shock.
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Transformational Leadership and Acceptance of Mistakes as a Source of Learning: Poland-USA Cross-Country Study
PublicationThis study explores the influence of transformational leadership on internal innovativeness mediated by mistakes acceptance, including country and industry as factors to be considered and gender and risk-taking attitude as moderators. General findings, primarily based on the US samples (healthcare, construction, and IT industry), confirmed that transformational leadership and internal innovativeness are mediated by mistakes acceptance...
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Entropy function application within the selection process of diagnostic parameters of marine diesel and gas turbine engines
PublicationThe paper presents the method of conducting an analysis of the diagnostic informativeness among the parameters characterizing the observed gas dynamic processes carried out within working spaces of marine diesel and gas turbine engines. An entropy function, as the measure of uncertainty of the identified states' set of the engine unfitness was applied. Having evaluated the diagnostic information the most adequate parameters were...
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The CFD analysis of influence the start of fuel injection (SOI) on combustion parameters and exhaust gas composition of the marine 4-stroke engine
PublicationThe paper presents a theoretical analysis of the impact of injection timing on the parameters of the combustion process and the composition of exhaust gas from a 4-stroke engine designed to shipbuilding. The analysis was carried out based on a three-dimensional multi-zone model of the combustion process. This model has been prepared on the basis of properties of the research facility. The input data to the model were obtained through...
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Analysis of the Influence of Fuel Sulphur Content on Diesel Engine Particulate Emissions
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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 in case of main engine cooperation with the gas turbine fed in parallel and the steam turbine
PublicationW pracy przedstawiono koncepcję układu kombinowanego okrętowego dużej mocy złożonego z wiodącego silnika głównego spalinowego silnika tłokowego i skojarzonych z nim turbiny gazowej mocy i układu turbiny parowej, wykorzystujących energię zawartą w spalinach wylotowych głównego silnika spalinowego. Rozpatrzono wariant układu kombinowanego, w którym główny jest silnik tłokowy skojarzony z turbiną gazową mocy i układem turbiny parowej,...
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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 in case of main engine cooperation with the gas turbine fed in series and the steam turbine
PublicationW pracy przedstawiono koncepcję układu kombinowanego okrętowego dużej mocy złożonego z wiodącego silnika głównego silnika spalinowego tłokowego oraz skojarzonych z nim turbiny gazowej mocy i układu turbiny parowej, wykorzystujących energię zawartą w spalinach wylotowych silnika spalinowego. Rozpatrywano wariant układu kombinowanego, którym turbina mocy jest zasilana szeregowo spalinami wylotowymi. Podano algorytm i obliczenia...
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Fast Fading Influence on the Deep Learning-Based LOS and NLOS Identificationin Wireless Body Area Networks
PublicationIn the article, the fast fading influence on the proposed DL (Deep Learning) approach for LOS (Line-of-Sight) and NLOS (Non-Line-of-Sight) conditions identification in Wireless Body Area Networks is investigated. The research was conducted on the basis of the off-body communication measurements using the developed mobile measurement stand, in an indoor environment for both static and dynamic scenarios. The measurements involved...
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Universal Predictors of Dental Students’ Attitudes towards COVID-19 Vaccination: Machine Learning-Based Approach
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Efficient Calibration of Cost-Efficient Particulate Matter Sensors Using Machine Learning and Time-Series Alignment
PublicationAtmospheric particulate matter (PM) poses a significant threat to human health, infiltrating the lungs and brain and leading to severe issues such as heart and lung diseases, cancer, and premature death. The main sources of PM pollution are vehicular and industrial emissions, construction and agricultural activities, and natural phenomena such as wildfires. Research underscores the absence of a safe threshold for particulate exposure,...
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Harmony Search to Self-Configuration of Fault-Tolerant Grids for Big Data
PublicationIn this paper, harmony search algorithms have been proposed to self-configuration of fault-tolerant grids for big data processing. Some tasks related to big data processing have been considered. Moreover, two criteria have been applied to evaluate quality of grids. The first criterion is a probability that all tasks meet their deadlines and the second one is grid reliability. Furthermore, some intelligent agents based on harmony...
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Publicly available lecture webcasts - e-learning or promotion tool? case study
PublicationThis paper aims to show how universities interact with Internet users by webcasting selected courses. Paper has exploratory case-study character, presenting example of Berkeley Webcast initiative of University of California, Berkeley, webcasting undergraduate courses and on-campus events. On the base of short introduction to webcasting usage as an e-learning and promotional tool, the analysis of 3 purposely chosen different courses...
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Hydraulic resistance analyses of selected elements of the prototype Stirling engine
PublicationThe paper presents the results of simulation tests of hydraulic resistance and temperature distribution of the prototype Stirling alpha engine supplied with waste heat. The following elements were analyzed: heater, regenerator and cooler. The engine uses compressed air as a working gas. Analyses were carried out for three working pressure values and different engine speeds. The work was carried out in order to optimize the configuration...
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Optimising approach to designing kernel PCA model for diagnosis purposes with and without a priori known data reflecting faulty states
PublicationFault detection plays an important role in advanced control of complex dynamic systems since precise information about system condition enables efficient control. Data driven methods of fault detection give the chance to monitor the plant state purely based on gathered measurements. However, they especially nonlinear, still suffer from a lack of efficient and effective learning methods. In this paper we propose the two stages learning...