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Wyniki wyszukiwania dla: SELF-LEARNING SYSTEMS
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Self-assessment of competencies of students and graduates participating in didactic projects – Case study
PublikacjaAim/purpose: the aim of this article is to examine the opinions of students and graduates of the faculty of economics of a technical university as regards their selfassessment of their preparation for entering the modern labour market. All the respondents participated during their studies in didactic projects aimed at improving their competencies taking into account the expectations of potential employers. Design/methodology/approach:...
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Optical method supported by machine learning for dynamics of C‐reactive protein concentrations changes detection in biological matrix samples
PublikacjaIn this article we present the novel spectroscopy method supported with machine learning for real-time detection of infectious agents in wastewater. In the case of infectious diseases, wastewater monitoring can be used to detect the presence of inflammation biomarkers, such as the proposed C-reactive protein, for monitoring inflammatory conditions and mass screening during epidemics for early detection in communities of concern,...
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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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Fuel systems of high power stationary engine
PublikacjaThe use of alternative fuels and, in the future, synthetic fuels has forced changes in the design of fuel supply systems in internal combustion engines. When operating a stationary engine at constant load, the possibility of using lean fuel mixtures appears. The selection of a precise operating mixture ignition system requires changes in traditional fuel systems. The article presents the current designs of fuel supply systems and...
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Systems
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Application of Shape Memory Alloys in Retrofitting of Masonry and Heritage Structures Based on Their Vulnerability Revealed in the Bam 2003 Earthquake
PublikacjaFor decades, one of the most critical considerations of civil engineers has been the construction of structures that can sufficiently resist earthquakes. However, in many parts of the globe, ancient and contemporary buildings were constructed without regard for engineering; thus, there is a rising necessity to adapt existing structures to avoid accidents and preserve historical artefacts. There are various techniques for retrofitting...
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Simultaneous removal of heavy metals and dyes in water using a MgO-coated Fe3O4 nanocomposite: Role of micro-mixing effect induced by bubble generation
PublikacjaThis study focused on the development of a nano-adsorbent for contaminant removal without the use of any external energy. An eco-friendly Fe3O4@MgO core-shell nanocomposite was synthesized and tested for the removal of a heavy metal, lead (Pb2+) and a dye, rhodamine B (RhB). The addition of H2O2 into the system enabled the self-mixing of the aqueous solution containing Fe3O4@MgO through the generation of bubbles. This system showed...
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A study of the kinetics of bismuth telluride synthesis by an oxide reduction method
PublikacjaThe kinetics of a reduction of bismuth and tellurium oxides in a hydrogen atmosphere, leading to the formation of thermoelectric bismuth telluride is investigated. The evaluation of the reaction kinetics was based on a thermogravimetric analysis performed in non-isothermal conditions. A non-parametric analysis method and the Friedman method were used for the evaluation of the data. Additionally, for a better understanding of the...
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Simulation of fluid structure interaction in a novel design of high pressure axial piston hydraulic pump
PublikacjaA novel type of an axial, piston-driven high pressure hydraulic pump with variable capacity marks a significant improvement in the area of the hydraulic machinery design. Total discharge from hydrostatic forces eliminates a need for a servomechanism, thus simplifying operation, reducing weight and introducing the possibility of the pump displacement control by computer. PWK-type pumps, invented in the Gdansk University of Technology,...
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Soiling Effect Mitigation Obtained by Applying Transparent Thin-Films on Solar Panels: Comparison of Different Types of Coatings
PublikacjaDust accumulation on the front cover of solar panels is closely linked to location and orientation of photovoltaic (PV) installation. Its build-up depends on the module tilt angle, frequency of precipitation, humidity, wind strength and velocity, as well as grain size. Additionally, soil composition is determined by solar farm surroundings such as local factories, agricultural crops, and traffic. Over time, molecules of atmospheric...
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Nitrofurazone Removal from Water Enhanced by Coupling Photocatalysis and Biodegradation
Publikacja(1) Background: Environmental contamination with antibiotics is particularly serious because the usual methods used in wastewater treatment plants turn out to be insufficient or ineffective. An interesting idea is to support natural biodegradation processes with physicochemical methods as well as with bioaugmentation with efficient microbial degraders. Hence, the aim of our study is evaluation of the effectiveness of different...
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Using Statistical Methods to Estimate The Worst Case Response Time of Network Software Running on Indeterministic Hardware Platforms
PublikacjaIn this paper we investigate whether the statistical Worst Case Execution Time (WCET) estimation methods devised for embedded platforms can be successfully applied to find the Worst Case Response Time (WCRT) of a network application running on a complex hardware platform such as a contemporary commercial off-the-shelf (COTS) system. Establishing easy-to-use timing validation techniques is crucial for real-time applications and...
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Application of multivariate statistics in assessment of green analytical chemistry parameters of analytical methodologies
PublikacjaThe study offers a multivariate statistical analysis of a dataset, including the major metrological, “greenness” and methodological parameters of 43 analytical methodologies applied for aldrin determination (a frequently analyzed organic compound) in water samples. The variables (parameters) chosen were as follows: metrological (LOD, recovery, RSD), describing the “greenness” (amount of the solvent used, amount of waste generated)...
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Functionalization of Parylene During Its Chemical Vapor Deposition
PublikacjaTwo possible mechanisms for the reaction of four halogenated (metha)acrylate-based molecules with Parylene [poly (paraxylylene)] during its chemical vapor deposition were proposed. The chemical reactivity of acrylate double bond with the paraxylylene biradical was calculated for all four (metha)acrylate-based molecules. These calculations allowed the evaluation of the energetically favorable mechanism and indeed a direct correlation...
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Simulation of fluid structure interaction in a novel design of high pressure axial piston pump
PublikacjaA novel type of an axial, piston-driven high pressure hydraulic pump with variable capacity marks a significant improvement in the area of the hydraulic machinery design. Total discharge from hydrostatic forces eliminates a need for a servomechanism, thus simplifying operation, reducing weight and introducing the possibility of the pump displacement control by computer. PWK-type pumps, invented in the Gdansk University of Technology,...
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Hey student, are you sharing your knowledge? A cluster typology of knowledge sharing behaviours among students
PublikacjaKnowledge Sharing (KS) is crucial for all organisations to better face current and future challenges. It is justifiable to assume that after graduation, students will have to face the coming challenges at societal and business levels, and that they will need the adequate KS skills to do so. Though the importance of KS is established, the understanding of how students pass on their knowledge is still fragmented and underdeveloped....
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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...
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An Empirical Study of a Dynamic Stop Loss Strategy with Deep Reinforcement Learning on the NASDAQ Stock Market
PublikacjaThe objective of this paper is to empirically investigate the efficacy of using Deep Reinforcement Learning (DRL) to maximize investment returns by incorporating expected optimal closing prices of long positions into a daily strategy. This paper extends existing research on the impact of stop-loss orders on investment strategy results and brings contribution of these orders to trading strategies into a completely new perspective....
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Improving platelet‐RNA‐based diagnostics: a comparative analysis of machine learning models for cancer detection and multiclass classification
PublikacjaLiquid biopsy demonstrates excellent potential in patient management by providing a minimally invasive and cost-effective approach to detecting and monitoring cancer, even at its early stages. Due to the complexity of liquid biopsy data, machine-learning techniques are increasingly gaining attention in sample analysis, especially for multidimensional data such as RNA expression profiles. Yet, there is no agreement in the community...
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Quality Modeling in Grid and Volunteer-Computing Systems
PublikacjaA model of computational quality in large-scale computing systems was presented in the previous chapter of this book. This model describes three quality attributes: performance, reliability and energy efficiency. We assumed that all processes in the system are incessantly ready to perform calculations and that communication between the processes occurs immediately. These assumptions are not true for grid and volunteer computing...
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Some aspects of blended-learning education
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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.
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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
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...
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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...
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Exploration of the Solubility Hyperspace of Selected Active Pharmaceutical Ingredients in Choline- and Betaine-Based Deep Eutectic Solvents: Machine Learning Modeling and Experimental Validation
PublikacjaDeep eutectic solvents (DESs) are popular green media used for various industrial, pharmaceutical, and biomedical applications. However, the possible compositions of eutectic systems are so numerous that it is impossible to study all of them experimentally. To remedy this limitation, the solubility landscape of selected active pharmaceutical ingredients (APIs) in choline chloride- and betaine-based deep eutectic solvents was...
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Systematics of intelligent transport systems services
PublikacjaRecent years have seen a more intensified deployment of Intelligent Transport Systems (ITS) in Polish cities. Work is also underway on the implementation of ITS on the national roads within the National Traffic Management System (KSZR). The research project RID-4D (part of Road Innovations), is designed to fill the gap, which is the lack of systematics of ITS services in Poland. The paper presents a proposal of ITS services systematics,...
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Solving the Problem of Dynamic Adaptability of Artificial Intelligence Systems that Control Dynamic Technical Objects
PublikacjaThis paper investigates the increase in the response speed and stability of artificial intelligence systems that control dynamic technical objects. The problem of calculating the optimal time of switching an artificial intelligence system between software classes by the criterion of the rigidity degree of the model of a control object is considered. The solution of this problem is proposed for the general case of the control object...
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Speed estimation of a car at impact with a W-beam guardrail using numerical simulations and machine learning
PublikacjaThis paper aimed at developing a new method of estimating the impact speed of a passenger car at the moment of a crash into a W-beam road safety barrier. The determination of such a speed based on the accident outcomes is demanding, because often there is no access to full accident data. However, accurate determination of the impact speed is one of the key elements in the reconstruction of road accidents. A machine learning algorithm...
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Energy-Aware Scheduling for High-Performance Computing Systems: A Survey
PublikacjaHigh-performance computing (HPC), according to its name, is traditionally oriented toward performance, especially the execution time and scalability of the computations. However, due to the high cost and environmental issues, energy consumption has already become a very important factor that needs to be considered. The paper presents a survey of energy-aware scheduling methods used in a modern HPC environment, starting with the...
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SELECTING A REPRESENTATIVE DATA SET OF THE REQUIRED SIZE USING THE AGENT-BASED POPULATION LEARNING ALGORITHM
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Visual Content Representation for Cognitive Systems: Towards Augmented Intelligence
PublikacjaCognitive Vision Systems have gained significant attention from academia and industry during the past few decades. One of the main reasons behind this interest is the potential of such technologies to revolutionize human life since they intend to work robustly under complex visual scenes (which environmental conditions may vary), adapting to a comprehensive range of unforeseen changes, and exhibiting prospective behavior. The combination...
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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...
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Assessment of Road Restraint Systems in Polish Conditions
PublikacjaKey to understanding the needs and tools of road infrastructure management is identifying the hazards and their sources involved in having no or faulty road restraint systems. Clarity is also needed on why the systems are wrongly designed, constructed, built and operated. To ensure that the problem is adequately understood, research and site observations were conducted and...
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Feature Reduction Using Similarity Measure in Object Detector Learning with Haar-like Features
PublikacjaThis 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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Road traffic can be predicted by machine learning equally effectively as by complex microscopic model
PublikacjaSince high-quality real data acquired from selected road sections are not always available, a traffic control solution can use data from software traffic simulators working offline. The results show that in contrast to microscopic traffic simulation, the algorithms employing neural networks can work in real-time, so they can be used, among others, to determine the speed displayed on variable message road signs. This paper describes...
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Modelling of Mechatronic Systems with Distributed Parameter Components
PublikacjaThe paper presents an uniform, port-based approach to modelling of both lumped and distributed parameter systems. Port-based model of distributed system has been defined by application of the bond graph methodology and the distributed transfer function method (DTFM). The proposed method of modelling enables to formulate input data for computer analysis by application of the DTFM. The computational package for the analysis of complex...
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When mere multiple group memberships are not enough: Individual self-expansion through involvement in social groups and self-efficacy belief
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Innovative Research Into Road Restraint Systems
PublikacjaKey to understanding the needs and building road infrastructure management tools to prevent and mitigate run-off-road accidents is to identify hazards and their sources which are a result of wrong design, construction, installation and maintenance of road restraint systems [1]. Building such tools requires advanced studies with field tests, simulations and models to demonstrate the effects of selected parameters on road user safety...
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Optimum Control of Gyroscopic Systems
PublikacjaThe problem of optimum control of transverse rotor vibrations with gyroscopic interactions has been described and solved in the paper. An integral performance index has been defined for such system in order to minimize vibration level of a chosen rotor point. For this reason, an efficient way of finding the weight coefficients of integral performance index for multi-degrees-of-freedom system with gyroscopic interactions has been...
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A Concept of Modeling and Optimization of Applications in Large Scale Systems
PublikacjaThe chapter presents the idea that includes modeling and subsequent optimization of application execution on large scale parallel and distributed systems. The model considers performance, reliability and power consumption. It should allow easy modeling of various classes of applications while reflecting key parameters of both the applications and two classes of target systems: clusters and volunteer based systems. The chapter presents...
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Application of mechanistic and data-driven models for nitrogen removal in wastewater treatment systems
PublikacjaIn this dissertation, the application of mechanistic and data-driven models in nitrogen removal systems including nitrification and deammonification processes was evaluated. In particular, the influential parameters on the activity of the Nitrospira activity were assessed using response surface methodology (RSM). Various long-term biomass washout experiments were operated in two parallel sequencing batch reactor (SBR) with a different...
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Clarke duality for Hamiltonian systems with nonstandard growth
PublikacjaWe consider the existence of periodic solutions to Hamiltonian systems with growth conditions involving G-function. We introduce the notion of symplectic G-function and provide relation for the growth of Hamiltonian in terms of certain constant CG associated to symplectic G-function G. We discuss an optimality of this constant for some special cases. We also provide applications to the Φ-laplacian type systems.
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Experimental tuning of AuAg nanoalloy plasmon resonances assisted by machine learning method
PublikacjaPlasmonic nanostructures based on AuAg nanoalloys were fabricated by thermal annealing of metallic films in an argon atmosphere. The nanoalloys were chosen because they can extend the wavelength range in which plasmon resonance occurs and thus allow the design of plasmonic platforms with the desired parameters. The influence of initial fabrication parameters and experimental conditions on the formation of nanostructures was investigated....
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Machine learning approach to packaging compatibility testing in the new product development process
PublikacjaThe paper compares the effectiveness of selected machine learning methods as modelling tools supporting the selection of a packaging type in new product development process. The main goal of the developed model is to reduce the risk of failure in compatibility tests which are preformed to ensure safety, durability, and efficacy of the finished product for the entire period of its shelf life and consumer use. This kind of testing...
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Smart Embedded Systems with Decisional DNA Knowledge Representation
PublikacjaEmbedded systems have been in use since the 1970s. For most of their history embedded systems were seen simply as small computers designed to accomplish one or a few dedicated functions; and they were usually working under limited resources i.e. limited computing power, limited memories, and limited energy sources. As such, embedded systems have not drawn much attention from researchers, especially from those in the artificial...
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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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Losses and energy efficiency of drive motors and systems
PublikacjaLosses and energy efficiency of every drive motor must be presented as functions of physical quantities independent of losses in the motor. Such quantities are speed and load required by the machine or device driven by the motor, changing in the drive operating field. Speed and load of the motor decide of the instantaneous useful power of the motor and also in a differentiated way of kinds and values of losses occurring in the...