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Wyniki wyszukiwania dla: SELF-LEARNING SYSTEMS
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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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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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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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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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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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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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Computational Complexity and Its Influence on Predictive Capabilities of Machine Learning Models for Concrete Mix Design
PublikacjaThe design of concrete mixtures is crucial in concrete technology, aiming to produce concrete that meets specific quality and performance criteria. Modern standards require not only strength but also eco-friendliness and production efficiency. Based on the Three Equation Method, conventional mix design methods involve analytical and laboratory procedures but are insufficient for contemporary concrete technology, leading to overengineering...
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Knowledge processing methodologies in intelligent autonomous systems
PublikacjaPrzedstawiono najnowsze trendy oraz stan badań światowych w zakresie wspomagania procesów zarządzania wiedzą w inteligentnych systemach autonomicznych.
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Detection of People Swimming in Water Reservoirs with the Use of Multimodal Imaging and Machine Learning
PublikacjaEvery year in many countries, there are fatal unintentional drownings in different water reservoirs like swimming pools, lakes, seas, or oceans. The existing threats of this type require creating a method that could automatically supervise such places to increase the safety of bathers. This work aimed to create methods and prototype solutions for detecting people bathing in water reservoirs using a multimodal imaging system and...
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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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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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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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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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COVID-19 severity forecast based on machine learning and complete blood count data
PublikacjaProper triage of COVID-19 patients is a key factor in eective case management, especially with limited and insucient resources. In this paper, we propose a machine-aided diagnostic system to predict how badly a patient with COVID-19 will develop disease. The prognosis of this type is based on the parameters of commonly used complete blood count tests, which makes it possible to obtain data from a wide range of patients.We chose...
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COVID-19 severity forecast based on machine learning and complete blood count data
PublikacjaProper triage of COVID-19 patients is a key factor in eective case management, especially with limited and insucient resources. In this paper, we propose a machine-aided diagnostic system to predict how badly a patient with COVID-19 will develop disease. The prognosis of this type is based on the parameters of commonly used complete blood count tests, which makes it possible to obtain data from a wide range of patients.We chose...
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Transformational Leadership and Acceptance of Mistakes as a Source of Learning: Poland-USA Cross-Country Study
PublikacjaThis 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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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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BIG DATA SIGNIFICANCE IN REMOTE MEDICAL DIAGNOSTICS BASED ON DEEP LEARNING TECHNIQUES
PublikacjaIn this paper we discuss the evaluation of neural networks in accordance with medical image classification and analysis. We also summarize the existing databases with images which could be used for training deep models that can be later utilized in remote home-based health care systems. In particular, we propose methods for remote video-based estimation of patient vital signs and other health-related parameters. Additionally, potential...
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Application of fiber optic sensors using Machine Learning algorithms for temperature measurement of lithium-ion batteries
PublikacjaOptical fiber sensorsusing low-coherence interferometry require processing ofthe output spectrum or interferogramto quickly and accurately determine the instantaneous value of the measured quantity, such as temperature.Methods based on machine learning are a good candidate for this application. The application of four such methods in an optical fiber temperature sensoris demonstrated.Using aZnO-coated...
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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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When mere multiple group memberships are not enough: Individual self-expansion through involvement in social groups and self-efficacy belief
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Optimized Deep Learning Model for Flood Detection Using Satellite Images
PublikacjaThe increasing amount of rain produces a number of issues in Kerala, particularly in urban regions where the drainage system is frequently unable to handle a significant amount of water in such a short duration. Meanwhile, standard flood detection results are inaccurate for complex phenomena and cannot handle enormous quantities of data. In order to overcome those drawbacks and enhance the outcomes of conventional flood detection...
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Active Annotation in Evaluating the Credibility of Web-Based Medical Information: Guidelines for Creating Training Data Sets for Machine Learning
PublikacjaMethods Results Discussion References Abbreviations Copyright Abstract Background: The spread of false medical information on the web is rapidly accelerating. Establishing the credibility of web-based medical information has become a pressing necessity. Machine learning offers a solution that, when properly deployed, can be an effective tool in fighting medical misinformation on the web. Objective: The aim of this study is to...
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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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Prediction of maximum tensile stress in plain-weave composite laminates with interacting holes via stacked machine learning algorithms: A comparative study
PublikacjaPlain weave composite is a long-lasting type of fabric composite that is stable enough when being handled. Open-hole composites have been widely used in industry, though they have weak structural performance and complex design processes. An extensive number of material/geometry parameters have been utilized for designing these composites, thereby an efficient computational tool is essential for that purpose. Different Machine Learning...
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Is it too late now to say we’re sorry? Examining anxiety contagion and crisis communication strategies using machine learning
PublikacjaIn this paper, we explore the role of perceived emotions and crisis communication strategies via organizational computer-mediated communication in predicting public anxiety, the default crisis emotion. We use a machine-learning approach to detect and predict anxiety scores in organizational crisis announcements on social media and the public’s responses to these posts. We also control for emotional and language tones in organizational...
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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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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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Machine Learning Assisted Interactive Multi-objectives Optimization Framework: A Proposed Formulation and Method for Overtime Planning in Software Development Projects
PublikacjaMachine Learning Assisted Interactive Multi-objectives Optimization Framework: A Proposed Formulation and Method for Overtime Planning in Software Development Projects Hammed A. Mojeed & Rafal Szlapczynski Conference paper First Online: 14 September 2023 161 Accesses Part of the Lecture Notes in Computer Science book series (LNAI,volume 14125) Abstract Software development project requires proper planning to mitigate risk and...
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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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Justification of quasi-stationary approximation in models of gene expression of a self-regulating protein
PublikacjaWe analyse a model of Hes1 gene transcription and protein synthesis with a negative feedback loop. The effect of multiple binding sites in the Hes1 promoter as well as the dimer formation process are taken into account. We consider three, possibly different, time scales connected with: (i) the process of binding to/dissolving from a binding site, (ii) formation and dissociation of dimers, (iii) production and degradation of Hes1...
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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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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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„Active learning w praktyce” - 17. Szkolenie certyfikowane 13.12.2022 r.
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„Active learning w praktyce” - 4. Szkolenie certyfikowane 21.10.2022 r.
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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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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...
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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...
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Fast Fading Influence on the Deep Learning-Based LOS and NLOS Identificationin Wireless Body Area Networks
PublikacjaIn 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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Enhancing environmental literacy through urban technology-based learning. The PULA app case
PublikacjaThis study addresses the need to enhance environmental literacy, focusing on urban adults through mobile applications, based on the example of PULA app that engages early adopters in gamified pro- environmental activities, offering insights into informal learning. Grounded in 'urban pedagogy,' the study combines semi-structured interviews with 17 application testers and quantitative data analysis, unveiling motivations, user feedback,...
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Publicly available lecture webcasts - e-learning or promotion tool? case study
PublikacjaThis 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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Supervised-learning-based development of multi-bit RCS-reduced coding metasurfaces
PublikacjaCoding metasurfaces have been introduced as efficient tools allowing meticulous control over the electromagnetic (EM) scattering. One of their relevant application areas is radar cross section (RCS) reduction, which principally relies on the diffusion of impinging EM waves. Despite its significance, careful control of the scattering properties poses a serious challenge at the level of practical realization. This article is concerned...
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Project and problem-based learning (PPBL): wprowadzenie
WydarzeniaZapraszamy na warsztaty, na których m.in. zrozumiesz założenia metody pracą projektu w oparciu o rozwiązywanie realnego problemu, poznasz etapy pracy zespołu metodą projektu oraz rolę nauczyciela i studentów w PPBL.
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Generic invariant measures for iterated systems of interval homeomorphisms
PublikacjaIt is well known that iterated function systems generated by orientation preserving homeomorphisms of the unit interval with positive Lyapunov exponents at its ends admit a unique invariant measure on (0, 1) provided their action is minimal. With the additional requirement of continuous differentiability of maps on a fixed neighbourhood of {0,1} { 0 , 1 } , we present a metric in the space of such systems which renders it complete....
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Towards Robust Identification of Nonstationary Systems
PublikacjaThe article proposes a fast, two-stage method for the identification of nonstationary systems. The method uses iterative reweighting to robustify the identification process against the outliers in the measurement noise and against the numerical errors that may occur at the first stage of identification. We also propose an adaptive algorithm to optimize the values of the hyperparameters that are crucial for this new method.
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Scalable Maintenance of Address Mapping and Autodetecion in Environments Where Agents are Uncapable of Self-Registration
PublikacjaWhen working with multi-agent systems it is often desirable to manage the agent set. The existing methods of central monitoring stems from two different fields of application. The first has its roots in in computer network monitoring, the other in mutli-agent simulation environments. Both approaches are not general enough to cater for loosely controlled environments, where the total agent population is not known and often fluctuating,...
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Marek Wójcikowski dr hab. inż.
OsobyMarek Wójcikowski ukończył w 1993 r. Wydział Elektroniki Politechniki Gdańskiej, specjalność układy elektroniczne. W 2002 r. uzyskał stopień doktora w dziedzinie elektroniki, a w 2016 r. uzyskał stopień doktora habilitowanego na Wydziale Elektroniki Telekomunikacji i Informatyki Politechniki Gdańskiej. Od początku kariery jest związany z Politechniką Gdańską: najpierw jako asystent (lata 1994–2002), a następnie jako adiunkt (od...
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Self-optimizing generalized adaptive notch filters - comparison of three optimization strategies
PublikacjaThe paper provides comparison of three different approaches to on-line tuning of generalized adaptive notch filters (GANFs) the algorithms used for identification/tracking of quasi-periodically varying dynamic systems. Tuning is needed to adjust adaptation gains, which control tracking performance of ANF algorithms, to the unknown and/or time time-varying rate of system nonstationarity. Two out ofthree compared approaches are classical...
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Towards automating repairs of IT systems
PublikacjaThis paper presents formal description of working principles of the repair library, being the essential component of the Repair Management Framework (RMF), which aims at automating the process of repairing IT systems, and consists also of the Repair Management Model (RMM) and the Repair Management System (RMS). RMM introduces two mathematical models (model of monitoring and model of repair processes), general enough to cover the...