Filtry
wszystkich: 28108
wybranych: 6160
-
Katalog
- Publikacje 6160 wyników po odfiltrowaniu
- Czasopisma 322 wyników po odfiltrowaniu
- Konferencje 56 wyników po odfiltrowaniu
- Osoby 267 wyników po odfiltrowaniu
- Wynalazki 1 wyników po odfiltrowaniu
- Projekty 15 wyników po odfiltrowaniu
- Kursy Online 544 wyników po odfiltrowaniu
- Wydarzenia 11 wyników po odfiltrowaniu
- Oferty 1 wyników po odfiltrowaniu
- Dane Badawcze 20731 wyników po odfiltrowaniu
Filtry wybranego katalogu
wyświetlamy 1000 najlepszych wyników Pomoc
Wyniki wyszukiwania dla: marine engine fault diagnosis fault detection diesel engine machine learning ensemble learning extreme learning machines multi-class decomposition
-
Fault Diagnostics in PEMFC Stacks by Evaluation of Local Performance and Cell Impedance Analysis
PublikacjaStarvation, 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...
-
Love your mistakes!—they help you adapt to change. How do knowledge, collaboration and learning cultures foster organizational intelligence?
PublikacjaPurpose: 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...
-
Technology-Enhanced Environmental Learning: Co-design of Educational Mobile Application Case
PublikacjaThe 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...
-
Improvement of speech intelligibility in the presence of noise interference using the Lombard effect and an automatic noise interference profiling based on deep learning
PublikacjaThe 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,...
-
Open-transistor fault diagnostics in voltage-source inverters by analyzing the load current
PublikacjaA novel method is presented for the detection andisolation of open-transistor faults in voltage-source invertersfeeding low-power AC motors. The method is based onmonitoring two diagnostic signals, one indicating sustained nearzerovalues of output current and thus permitting fault detection,the other permitting the isolation of the particular transistorwhich went faulty. The latter signal is the ratio of the averagephase current...
-
Sampling-based novel heterogeneous multi-layer stacking ensemble method for telecom customer churn prediction
PublikacjaIn 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...
-
The effects of relational and psychological capital on work engagement: the mediation of learning goal orientation
PublikacjaPurpose – 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...
-
Optimizing Medical Personnel Speech Recognition Models Using Speech Synthesis and Reinforcement Learning
PublikacjaText-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...
-
An Adaptive Network Model for a Double Bias Perspective on Learning from Mistakes within Organizations
PublikacjaAlthough making mistakes is a crucial part of learning, it is still often being avoided in companies as it is considered as a shameful incident. This goes hand in hand with a mindset of a boss who dominantly believes that mistakes usually have negative consequences and therefore avoids them by only accepting simple tasks. Thus, there is no mechanism to learn from mistakes. Employees working for and being influenced by such a boss...
-
Novel Fault Identification for Electromechanical Systems via Spectral Technique and Electrical Data Processing
PublikacjaIt 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...
-
Computational Analysis of Transformational Organisational Change with Focus on Organisational Culture and Organisational Learning: An Adaptive Dynamical Systems Modeling Approach
PublikacjaTransformative Organisational Change becomes more and more significant both practically and academically, especially in the context of organisational culture and learning. However computational modeling and formalization of organisational change and learning processes are still largely unexplored. This chapter aims to provide an adaptive network model of transformative organisational change and translate a selection of organisational...
-
Analysis of start energy of Stirling engine type alpha
PublikacjaThe 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...
-
A semi-Markov model of fuel combustion process in a Diesel engine
PublikacjaW 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...
-
Energy-time method for assesment of main diesel engine operation
PublikacjaW 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.
-
AUTOMATIC LEARNING OF STRATEGY AND RULES IN CARD GAMES USING IMAGE FROM CAMERA
PublikacjaBelow 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...
-
Modeling of the internal combustion engine cooling system
PublikacjaThe 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...
-
Using LSTM networks to predict engine condition on large scale data processing framework
PublikacjaAs 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...
-
Visual Content Learning in a Cognitive Vision Platform for Hazard Control (CVP-HC)
PublikacjaThis 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...
-
Diagnosis of fully differential circuits based on a fault dictionary implemented in the microcontroller systems
PublikacjaPrzedstawiono 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...
-
Unsupervised Learning for Biomechanical Data Using Self-organising Maps, an Approach for Temporomandibular Joint Analysis
PublikacjaWe 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...
-
Pursuing the Deep-Learning-Based Classification of Exposed and Imagined Colors from EEG
PublikacjaEEG-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,...
-
Development of advanced machine learning for prognostic analysis of drying parameters for banana slices using indirect solar dryer
PublikacjaIn this study, eXtreme Gradient Boosting (XGBoost) and Light Gradient Boosting (LightGBM) algorithms were used to model-predict the drying characteristics of banana slices with an indirect solar drier. The relationships between independent variables (temperature, moisture, product type, water flow rate, and mass of product) and dependent variables (energy consumption and size reduction) were established. For energy consumption,...
-
Deep Learning Optimization for Edge Devices: Analysis of Training Quantization Parameters
PublikacjaThis 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...
-
Note on universal algoritms for learning theory
PublikacjaW 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.
-
Some aspects of blended-learning education
Publikacja -
A consensus-based approach to the distributed learning
Publikacja -
Prototype selection algorithms for distributed learning
Publikacja -
An agent-based framework for distributed learning
Publikacja -
E-learning in tourism and hospitality: A map
PublikacjaThe 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...
-
Structure and Randomness in Planning and Reinforcement Learning
PublikacjaPlanning 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...
-
Fault diagnosing system of wheeled tractors
PublikacjaA 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...
-
Improving sensitivity of residual current transformers to high frequency earth fault currents
PublikacjaFor 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...
-
Data-Driven Surrogate-Assisted Optimization of Metamaterial-Based Filtenna Using Deep Learning
PublikacjaIn 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,...
-
Spatiotemporal Assessment of Satellite Image Time Series for Land Cover Classification Using Deep Learning Techniques: A Case Study of Reunion Island, France
PublikacjaCurrent 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...
-
Decision making process using deep learning
PublikacjaEndüstri 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...
-
Behavior of residual current devices at earth fault currents with DC component
PublikacjaLow-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...
-
Sensorless field oriented control for five-phase induction motors with third harmonic injection and fault insensitive feature
PublikacjaThe 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...
-
Projekt Leonardo da Vinci EMDEL (European Model for Distance Education and Learning) - otwarte szkolenia online.
PublikacjaW 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...
-
Thermal Images Analysis Methods using Deep Learning Techniques for the Needs of Remote Medical Diagnostics
PublikacjaRemote 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...
-
An Instantaneous Engine Speed Estimation Method Using Multiple Matching Synchrosqueezing Transform
PublikacjaInstantaneous 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...
-
Application of Stirling Engine Type Alpha Powered by the Recovery Energy on Vessels
PublikacjaThe 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...
-
Using Isolation Forest and Alternative Data Products to Overcome Ground Truth Data Scarcity for Improved Deep Learning-based Agricultural Land Use Classification Models
PublikacjaHigh-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...
-
Analysis of hull, propeller and engine interactions in regular waves by a combination of experiment and simulation
PublikacjaAnalysis of hull, propeller and engine interactions in regular waves by a combination of experiment and simulation
-
Machine-learning-based precise cost-efficient NO2 sensor calibration by means of time series matching and global data pre-processing
PublikacjaAir 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...
-
An Approach to Data Reduction for Learning from Big Datasets: Integrating Stacking, Rotation, and Agent Population Learning Techniques
Publikacja -
EXHAUST TEMPERATURE MEASUREMENTS OF THE MARINE TURBOCHARGED DIESEL ENGINES IN OPERATION
PublikacjaThe 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...
-
A new method of fault loop resistance measurement in low voltage systems with residual current devices
PublikacjaThis 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.
-
Entropy function application within the selection process of diagnostic parameters of marine diesel and gas turbine engines
PublikacjaThe 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...
-
The CFD analysis of influence the start of fuel injection (SOI) on combustion parameters and exhaust gas composition of the marine 4-stroke engine
PublikacjaThe 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...
-
A Novel Spatio–Temporal Deep Learning Vehicle Turns Detection Scheme Using GPS-Only Data
PublikacjaWhether 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...