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Wyniki wyszukiwania dla: marine engine fault diagnosis fault detection diesel engine machine learning ensemble learning extreme learning machines multi-class decomposition
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Condition monitoring and fault diagnosis of wind turbines based on structural break detection in SCADA data
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The chemistry, properties and performance of flame-retardant rubber composites: Collecting, analyzing, categorizing, machine learning modeling, and visualizing
PublikacjaRubbers combine the flexibility with mechanical strength, supporting myriad applications, but suffer from inherent flammability. Formulation and production of flame-retardant rubber composites (FRRCs) have intensively been practiced over years, but not comprehensively reviewed. This necessity has outlined collecting, analyzing, screening, classifying, and interpreting the literature with the aim of classifying the FRRCs. We quantified...
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A review on application of artificial neural network (ANN) for performance and emission characteristics of diesel engine fueled with biodiesel-based fuels
PublikacjaBiodiesel has been emerging as a potential and promising biofuel for the strategy of reducing toxic emissions and improving engine performance. Computational methods aiming to offer numerical solutions were inevitable as a study methodology which was sometimes considered the only practical method. Artificial neural networks (ANN) were data-processing systems, which were used to tackle many issues in engineering and science, especially...
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A Highly Scalable, Modular Architecture for Computer Aided Assessment e-Learning Systems
PublikacjaIn this chapter, the authors propose a novel e-learning system, dedicated strictly to knowledge assessment tasks. In its functioning it utilizes web-based technologies, but its design differs radically from currently popular e-learning solutions which rely mostly on thin-client architecture. The authors' research proved that such architecture, while well suited for didactic content distribution systems is ill-suited for knowledge...
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E-Learning Service Management System For Migration Towards Future Internet Architectures
PublikacjaAs access to knowledge and continuous learning are among the most valuable assets in modern, technological society, it is hardly surprising that e-learning solutions can be counted amongst the most important groups of services being deployed in modern network systems. Based on analysis of their current state-of-the-art, we decided to concentrate our research and development work on designing and implementing a management system...
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Continuous learning as a method of raising qualifications – the perspective of workers, employers and training organizations
PublikacjaContinuous learning is discussed in strategic documents of Poland and the European Union. In Poland, the idea of continuous learning is not very popular. However, in the context of strong competition in the labour market and the progressive globalization processes, the skills issue takes on new meaning — both for employees and employers. In order to adapt skills to labour market needs it is necessary to conduct adequate studies...
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User Orientation Detection in Relation to Antenna Geometry in Ultra-Wideband Wireless Body Area Networks Using Deep Learning
PublikacjaIn this paper, the issue of detecting a user’s position in relation to the antenna geometry in ultra-wideband (UWB) off-body wireless body area network (WBAN) communication using deep learning methods is presented. To measure the impulse response of the channel, a measurement stand consisting of EVB1000 devices and DW1000 radio modules was developed and indoor static measurement scenarios were performed. It was proven that for...
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Optimization-based stacked machine-learning method for seismic probability and risk assessment of reinforced concrete shear walls
PublikacjaEfficient seismic risk assessment aids decision-makers in formulating citywide risk mitigation plans, providing insights into building performance and retrofitting costs. The complexity of modeling, analysis, and post-processing of the results makes it hard to fast-track the seismic probabilities, and there is a need to optimize the computational time. This research addresses seismic probability and risk assessment of reinforced...
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Evaluation of the significance of the effect of the active cross-sectional area of the inlet air channel on the specific enthalpy of the exhaust gas of a diesel engine using statistics F of the Fisher-Snedecor distribution
PublikacjaThis paper presents the application of Fisher-Snedecor distribution F statistics to assess the significance of the influence of changes in the active cross-sectional area of the inlet air channel (Adol) flow in a diesel engine on the observed diagnostic parameter determined on the basis of measurements of the quick changing exhaust gas temperature in the outlet channel, which is the specific enthalpy of the exhaust gas stream within...
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Speed Sensorless AC Drive with Inverter LC Filter and Fault Detection Using Load Torque Signal
PublikacjaThe industrial development in recent years has seen a major increase in the use of induction motors, whereby the cost has to be as low as possible and the lifetime as long as possible. To follow up this desire, investigations in this area have become very intense. For that reason, this paper presents a solution for driving an induction motor and simultaneous fault detection with no need for additional sensors. In order to achieve...
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The system combined of low-speed marine diesel engine and steam turbine in ship propulsion applications
PublikacjaPrzedstawiono koncepcje okrętowego układu kombinowanego silnik wolnoobrotowy tłokowy- turbina parowa, wykorzystującego ciepło zawarte w spalinach wylotowych.Porównano układ kombinowany dużej mocy dla dwóch silników tłokowych porównywalnych mocy z punktu widzenia termodynamicznego.
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ANN based evaluation of the NOx concentration in the exhaust gas of a marine two-stroke diesel engine
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An Experimental Study of Emission and Combustion Characteristics of Marine Diesel Engine in Case of Cylinder Valves Leakage
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Training of Deep Learning Models Using Synthetic Datasets
PublikacjaIn 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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Speed sensorless ac drive with inverter output filter and fault detection using load torque signal
PublikacjaIn this paper, a sensorless induction motor (IM) drive using speed observer system is presented. The system includes load torque computation for gear fault detection. Nonlinear control method is adopted for controlling the motor over a wide speed range. An LC filter for smoothing current and voltage waveforms is used at the output of the voltage inverter. The use of filter imposes more building of the used observer to avoid using...
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Experiments on compression ignition engine powered by nano-fuels
PublikacjaThe use of nanoparticles in fuels provides new opportunities for modification of fuel properties, which may affect the operational parameters of engines, in particular the efficiency and fuel consumption. The paper presents comparison of compression ignition engine performance fuelled with neat diesel and nano-diesel. Alumina (Al2O3) was used as nanoparticles. Surface-active substances, including Span 80 surfactant, as well as...
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Stochastic model of the process of diesel engine operation.
PublikacjaStreszczenie: Najistotniejszym problemem eksploatacji silników o zapłonie samoczynnym jest problem racjonalnego (a zwłaszcza optymalnego) sterowania procesem eksploatacji tych silników. Sterowanie takie może ułatwić zastosowanie iteracyjnego algorytmu wyznaczania optymalnych strategii opracowanego przez R.A. Howarda. Wykorzystanie jednak tego algorytmu do sterowania procesem eksploatacji silników wymaga między innymi opracowania...
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Karol Flisikowski dr inż.
OsobyKarol Flisikowski jest profesorem uczelni w Katedrze Statystyki i Ekonometrii, Wydziału Zarządzania i Ekonomii Politechniki Gdańskiej. Jest odpowiedzialny jest za prowadzenie zajęć ze statystyki opisowej i matematycznej (w języku polskim i angielskim), a także badań naukowych w zakresie statystyki społecznej. Był uczestnikiem wielu konferencji o zasięgu krajowym, jak i międzynarodowym, gdzie prezentował wyniki prowadzonych przez...
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Deep learning-based waste detection in natural and urban environments
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Efficient sampling of high-energy states by machine learning force fields
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Stacking and rotation-based technique for machine learning classification with data reduction
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ASSESSMENT OF ENGINE OPERATION WITH THE USE OF AN OPERATION INDICATOR BASED ON TEST BENCH RESULTS OF A ROBINSUBARU EX17 ENGINE
PublikacjaPaper presents results of an experimental verification of the method of quantitative evaluation of engine operation, presented in the literature, exemplified by a low-power internal combustion piston engine. In accordance with such interpretation, engine operation may be presented as a physical quantity defined as operation indicator. The paper presents results of preliminary tests, processed in that aspect, carried out on an engine...
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Szymon Zaporowski mgr inż.
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Computational Simulation of the Effects of Different Culture Types and Leader Qualities on Mistake Handling and Organisational Learning
PublikacjaThis chapter investigates computationally the following research hypotheses: (1) Higher flexibility and discretion in organisational culture results in better mistake management and thus better organisational learning, (2) Effective organisational 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...
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Fault detection in measuring systems of power plants
PublikacjaThis paper describes possibility of forming diagnostic relations based on application of the artifical neural networks (ANNs), intended for the identifying of degradation of measuring instruments used in developed power systems. As an example a steam turbine high-power plant was used. And, simulative calculations were applied to forming diagnostic neural relations. Both degradation of the measuring instruments and simultaneously...
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An integrated e-learning services management system providing HD videoconferencing and CAA services
PublikacjaIn this paper we present a novel e-learning services management system, designed to provide highly modifiable platform for various e-learning tools, able to fulfill its function in any network connectivity conditions (including no connectivity scenario). The system can scale from very simple setup (adequate for servicing a single exercise) to a large, distributed solution fit to support an enterprise. Strictly modular architecture...
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WEB-CAM AS A MEANS OF INFORMATION ABOUT EMOTIONAL ATTEMPT OF STUDENTS IN THE PROCESS OF DISTANT LEARNING
PublikacjaNew methods in education become more popular nowadays. Distant learning is a good example when teacher and student meet in virtual environment. Because interaction in this virtual world might be complicated it seems necessary to assure as much methods of conforming that student is still engaged in the process of learning as it is possible. We would like to present assumption that by means of web-cam we will be able to track facial...
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Deep learning for ultra-fast and high precision screening of energy materials
PublikacjaSemiconductor materials for energy storage are the core and foundation of modern information society and play important roles in photovoltaic system, integrated circuit, spacecraft technology, lighting applications, and other fields. Unfortunately, due to the long experiment period and high calculation cost, the high-precision band gap (the basic characteristic parameter) of semiconductor is difficult to obtain, which hinders the...
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Wisdom from Experience Paradox: Organizational Learning, Mistakes, Hierarchy and Maturity Issues
PublikacjaOrganizations often perceive mistakes as negligence and low-performance indicators, yet they can be a precious learning resource. However, organizations cannot learn from mistakes if they have not accepted them. This study aimed to explore how organizational hierarchy and maturity levels influence the relationship between mistakes acceptance and the ability to change. A sample composed of 380 Polish employees working in knowledge-driven...
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THE ONLINE APPLICATION AND E-LEARNING IN THE COMPETENCE-BASED MANAGEMENT IN PUBLIC ADMINISTRATION ORGANIZATIONS
PublikacjaThe integration of effective management of work-related processes and utilization of human resources potential leads to the development of organization. The purpose of this paper was to examine how the principles of competences-based management can be introduced to enhance organization’s effectiveness in human resources management. A model of assessment and development of competences-based management, embracing an online application...
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Fault diagnosis of analog piecewise linear circuits based on homotopy
PublikacjaArtykuł opisuje weryfikację metodą diagnostyki analogowych układów odcinkowo-liniowych opartą na podejściu homotopijnym. Homotopia przekształca jedną funkcję f(x) w inną funkcję g(x) poprzez zmianę parametru homotopii tî[0,1]. Ścieżka homotopijna pokazuje drogę od punktu x0 z dziedziny funkcji f(x) do odpowiadającego mu punktu x* funkcji g(x). Idea metody zakłada wykorzystanie funkcji f(x) do opisu diagnozowanego układu w stanie...
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Deep learning based thermal image segmentation for laboratory animals tracking
PublikacjaAutomated systems for behaviour classification of laboratory animals are an attractive alternative to manual scoring. However, the proper animals separation and tracking, especially when they are in close contact, is the bottleneck of the behaviour analysis systems. In this paper, we propose a method for the segmentation of thermal images of laboratory rats that are in close contact during social behaviour tests. For this, we are...
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Forecasting energy consumption and carbon dioxide emission of Vietnam by prognostic models based on explainable machine learning and time series
PublikacjaThis study assessed the usefulness of algorithms in estimating energy consumption and carbon dioxide emissions in Viet- nam, in which the training dataset was used to train the models linear regression, random forest, XGBoost, and AdaBoost, allowing them to comprehend the patterns and relationships between population, GDP, and carbon dioxide emissions, energy consumption. The results revealed that random forest, XGBoost, and AdaBoost...
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Modification of the operating point of residual current transformers for high frequency earth fault currents detection
PublikacjaFor protection against electric shock in low voltage systems residual current devices are commonly used. However, their proper operation can be interfered when earth fault current with high frequency components occurs. Serious hazard of electrocution exists then. One of the most important element of residual current devices is a residual current transformer with iron core. Tripping characteristic of residual current devices strictly...
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Supporting First Year Students Through Blended-Learning - Planning Effective Courses and Learner Support
PublikacjaHigher education has been actively encouraged to find more effective and flaxible delivery models to provide all students with access to good quality learning experiences. This paper describes students opinion about using e-learning techniques and their participation in courses provided in different ways as additional help and expectations of first year students.
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Adaptive Dynamical Systems Modelling of Transformational Organizational Change: with Focus on Organizational Culture and Organizational Learning
PublikacjaTransformative Organizational Change becomes more and more significant both practically and academically, especially in the context of organizational culture and learning. However computational modeling and a formalization of organizational change and learning processes are still largely unexplored. This paper aims to provide an adaptive network model of transformative organizational change and translate a selection of organizational...
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Adaptive Dynamical Systems Modelling of Transformational Organizational Change with Focus on Organizational Culture and Organizational Learning
PublikacjaTransformative Organizational Change becomes more and more significant both practically and academically, especially in the context of organizational culture and learning. However computational modeling and a formalization of organizational change and learning processes are still largely unexplored. This paper aims to provide an adaptive network model of transformative organizational change and translate a selection of organizational...
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Attention-Based Deep Learning System for Classification of Breast Lesions—Multimodal, Weakly Supervised Approach
PublikacjaBreast cancer is the most frequent female cancer, with a considerable disease burden and high mortality. Early diagnosis with screening mammography might be facilitated by automated systems supported by deep learning artificial intelligence. We propose a model based on a weakly supervised Clustering-constrained Attention Multiple Instance Learning (CLAM) classifier able to train under data scarcity effectively. We used a private...
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Open source solution LMS for supporting e-learning/blended learning engineers
PublikacjaW artykule zaprezentowano darmowe systemy zarządzania kształceniem na odległość wspomagające e-learningowe/mieszane nauczanie inżynierów. Pierwszy system TeleCAD został opracowany w ramach projektu Leonardo da Vinci (1998-2001). System TeleCAD był propozycją w projekcie V Ramowy CURE (2003-2006). W roku 2003 dzięki projektowi Leonardo da Vinci EMDEL (2001-2005) Centrum Edukacji Niestacjonarnej Politechniki Gdańskiej wybrało system...
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Application of the F-statistic of the Fisher-Snedecor distribution to analyze the significance of the effect of changes in the compression ratio of a diesel engine on the value of the specific enthalpy of the exhaust gas flow
PublikacjaThe paper discusses the impact of changes in the compression ratio on the operating parameters of a diesel engine, e.g. on the temperature of exhaust gases. It presents the construction of the laboratory test stand, on which experimental measurements were realized. It is characterized how the actual changes of the compression ratio were introduced to the existing engine. The program of experimental investigations taking into account...
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Distance learning trends: introducing new solutions to data analysis courses
PublikacjaNowadays data analysis of any kind becomes a piece of art. The same happens with the teaching processes of statistics, econometrics and other related courses. This is not only because we are facing (and are forced to) teach online or in a hybrid mode. Students expect to see not only the theoretical part of the study and solve some practical examples together with the instructor. They are waiting to see a variety of tools, tutorials,...
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Reduction of CO2 Emissions from Offshore Combined Cycle Diesel Engine-Steam Turbine Power Plant Powered by Alternative Fuels
PublikacjaDiverse 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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Reinforcement Learning Algorithm and FDTD-based Simulation Applied to Schroeder Diffuser Design Optimization
PublikacjaThe aim of this paper is to propose a novel approach to the algorithmic design of Schroeder acoustic diffusers employing a deep learning optimization algorithm and a fitness function based on a computer simulation of the propagation of acoustic waves. The deep learning method employed for the research is a deep policy gradient algorithm. It is used as a tool for carrying out a sequential optimization process the goal of which is...
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User -friendly E-learning Platform: a Case Study of a Design Thinking Approach Use
PublikacjaE-learning systems are very popular means to support the teaching process today. These systems are mainly used by universities as well as by commercial training centres. We analysed several popular e-learning platforms used in Polish universities and find them very unfriendly for the users. For this reason, the authors began the work on the creation of a new system that would be not only useful, but also usable for students, teachers...
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Machine learning techniques combined with dose profiles indicate radiation response biomarkers
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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
PublikacjaIn 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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Machine learning-based prediction of residual drift and seismic risk assessment of steel moment-resisting frames considering soil-structure interaction
PublikacjaNowadays, 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...