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Wyniki wyszukiwania dla: DESIGNING LEARNING SPACES
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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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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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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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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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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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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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Equivalence of equicontinuity concepts for Markov operators derived from a Schur-like property for spaces of measures
PublikacjaVarious equicontinuity properties for families of Markov operators have been – and still are – used in the study of existence and uniqueness of invariant probability for these operators, and of asymptotic stability. We prove a general result on equivalence of equicontinuity concepts. It allows comparing results in the literature and switching from one view on equicontinuity to another, which is technically convenient in proofs....
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A Novel Method for Intelligibility Assessment of Nonlinearly Processed Speech in Spaces Characterized by Long Reverberation Times
PublikacjaObjective assessment of speech intelligibility is a complex task that requires taking into account a number of factors such as different perception of each speech sub-bands by the human hearing sense or different physical properties of each frequency band of a speech signal. Currently, the state-of-the-art method used for assessing the quality of speech transmission is the speech transmission index (STI). It is a standardized way...
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Fault diagnosis in electronic circuits based on bilinear transformation in 3-D and 4-D spaces
PublikacjaPrzedstawiono ideę nowych metod diagnostycznych 3-D i 4-D opartych na przek-ształceniu biliniowym. Metody te bazują na transformacjach operujących odpo-wiednio w trzy i czterowymiarowych przestrzeniach funkcji układowych. Dlatych metod omówiono algorytm lokalizacji i identyfikacji pojedynczych uszko-dzeń parametrycznych w liniowych układach elektronicznych oraz algorytm lo-kalizacji i identyfikacji pojedynczych uszkodzeń...
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Design Space Reduction for Expedited Multi-Objective Design Optimization of Antennas in Highly-Dimensional Spaces
PublikacjaA surrogate-based technique for efficient multi-objective antenna optimization is discussed. Our approach exploits response surface approximation (RSA) model constructed from low-fidelity antenna model data (here, obtained through coarse-discretization electromagnetic simulations). The RSA model enables fast determination of the best available trade-offs between conflicting design goals. The cost of RSA model construction for multi-parameter...
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Reliable Multi-Stage Optimization of Antennas for Multiple Performance Figures in Highly-Dimensional Parameter Spaces
PublikacjaDesign of modern antenna structures needs to account for multiple performance figures and geometrical constraints. Fulfillment of these calls for the development of complex topologies described by a large number of parameters. EM-driven tuning of such designs is mandatory yet immensely challenging. In this letter, a new framework for multi-stage design optimization of multi-dimensional antennas with respect to several performance...
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Designing of Substrates and Inhibitors of Bovine α-Chymotrypsin with Synthetic Phenylalanine Analogues in Position P1
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Designing Aggregate KPIs as a Method of Implementing Decision-Making Processes in the Management of Smart Cities
PublikacjaThe aim of the paper is to present a concept of measuring the performance of city management processes by use of a concept of aggregate KPIs. In the management of organizations and, as a consequence of the use of a common design framework also in the management of cities, silo KPIs are commonly used to show the statuses of the processes of organizations/cities. Thus the question arises as to what extent aggregate KPIs, as proposed...
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Fault diagnosis of marine 4-stroke diesel engines using a one-vs-one extreme learning ensemble
PublikacjaThis paper proposes a novel approach for intelligent fault diagnosis for stroke Diesel marine engines, which are commonly used in on-road and marine transportation. The safety and reliability of a ship's work rely strongly on the performance of such an engine; therefore, early detection of any type of failure that affects the engine is of crucial importance. Automatic diagnostic systems are of special importance because they can...
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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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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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An Approach to Data Reduction for Learning from Big Datasets: Integrating Stacking, Rotation, and Agent Population Learning Techniques
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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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Machine Learning and Text Analysis in an Artificial Intelligent System for the Training of Air Traffic Controllers
PublikacjaThis chapter presents the application of new information technology in education for the training of air traffic controllers (ATCs). Machine learning, multi-criteria decision analysis, and text analysis as the methods of artificial intelligence for ATCs training have been described. The authors have made an analysis of the International Civil Aviation Organization documents for modern principles of ATCs education. The prototype...
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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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Solubility of dapsone in deep eutectic solvents: Experimental analysis, molecular insights and machine learning predictions
PublikacjaBackground. Dapsone (DAP) is an anti-inflammatory and antimicrobial active pharmaceutical ingredient used to treat, e.g., AIDS-related diseases. However, low solubility is a feature hampering its efficient use. Objectives. First, deep eutectic solvents...
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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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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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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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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 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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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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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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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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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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Estimation of the minimal number of periodic points for smooth self-maps of odd dimensional real projective spaces
PublikacjaLet f be a smooth self-map of a closed connected manifold of dimension m⩾3. The authors introduced in [G. Graff, J. Jezierski, Minimizing the number of periodic points for smooth maps. Non-simply connected case, Topology Appl. 158 (3) (2011) 276-290] the topological invariant NJD_r[f], where r is a fixed natural number, which is equal to the minimal number of r-periodic points in the smooth homotopy class of f. In this paper smooth...
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Designing a magnetoacoustic emission measurement configuration for measurement of creep damage in power plant boiler tubes
PublikacjaOpisywane są własności skonstruowanego detektora emisji magneto-akustycznej (EMA) służącego dla pomiaru stopnia degradacji rurociągów w przemyśle energetycznym. Specjalna budowa biegunów magnesu umożliwia ich dopasowanie do zakrzywionych powierzchni. Układ pomiarowy pozwala na badanie natężenia EMA dla pola wzdłuż osi rury, a także w kierunku obwodowym. Wykazano, iż możliwa jest detekcja zmiany stopnia degradacji materiału na obwodzie...
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On designing minimax adjustable wideband fractional delay FIR filters using two-rate approach
PublikacjaZaprezentowano nowe rozwiązanie problemu projektowania numerycznie oszczędnego, przestrajalnego, szerokopasmowego filtru ułamkowo opóźniającego o skończonej odpowiedzi impulsowej (FIR) w strukturze Farrowa. Innowacja polega na zagregowaniu dwóch podejść. Pierwsze z nich polega na równoczesnej optymalizacji wszystkich podfiltrów struktury Farrowa. Drugie wykorzystuje dwuszybkościową aranżację dwustopniową. Docelowe rozwiązanie jest...
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Designing sustainable school facilities for public health promotion. Selected issues and examples of good practice
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Designing optimal operational-point trajectories using an intelligent sub-strategy agent-based approach
PublikacjaW rozdziale opisuje się metodę projektowania optymalnej i bezpiecznego sterowania nieliniowymi procesami dynamicznymi. Poszukiwane sterowanie jest wynikiem zastosowania elementarnej strategii poszczególnych agentów, realizujšcych zadanie minimalizacji wspólnej miary kosztu sterowania. Zagadnienie projektowania optymalnego sterowania traktowane jest jako proces decyzyjny, w którym decyzje podejmowane sš w kolejnych regionach przestrzeni...
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Designing optimal operational-point trajectories using an intelligent sub-strategy agent-based approach
PublikacjaW rozdziale opisuje się metodę projektowania optymalnej i bezpiecznego sterowania nieliniowymi procesami dynamicznymi. Poszukiwane sterowanie jest wynikiem zastosowania elementarnej strategii poszczególnych agentów, realizujących zadanie minimalizacji wspólnej miary kosztu sterowania. Zagadnienie projektowania optymalnego sterowania traktowane jest jako proces decyzyjny, w którym decyzje podejmowane są w kolejnych regionach przestrzeni...
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THE MANAGEMENT OF DESIGNING PROCESSES IN THE CREATION OF THE KNOWLEDGE BASE SYSTEM : Proceedings of International Computer Science Convention
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Machine-Learning-Based Global Optimization of Microwave Passives with Variable-Fidelity EM Models and Response Features
PublikacjaMaximizing microwave passive component performance demands precise parameter tuning, particularly as modern circuits grow increasingly intricate. Yet, achieving this often requires a comprehensive approach due to their complex geometries and miniaturized structures. However, the computational burden of optimizing these components via full-wave electromagnetic (EM) simulations is substantial. EM analysis remains crucial for circuit...
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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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Impact of technology on learning paradigms and teaching practices
PublikacjaArtykuł stara się omówić różne kwestie dotyczące wpływu technologii na proces nauczania poprzez zaprezentowanie określonych przykładów. Jest próbą sformułowania ogólnych wniosków oraz zweryfikowania kontrowersyjnych opinii.
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Quality negotiation mechanism for e-learning platforms
PublikacjaZarządzanie jakością w aplikacjach działających w środowiskach sieci WEB opiera się na zadaniach związanych z wykrywaniem jakości połączenia klient - serwer oraz na optymalnym przydziale zasobów wedle jakości takowego połączenia. Optymalne zarządzanie jakością zależy od wypracowanego kompromisu pomiędzy jakością łącza a jakości transportowanego łączem zasobu. Artykuł opisuje możliwy do implementacji mechanizm odpowiedzialny za...
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Comparative study of learning methods for artificial network
PublikacjaW artykule przedstawiono wyniki badań porównawczych metod uczenia sieci neuronowych takich jak: metoda propagacji wstecznej błędów, rekurencyjna metoda najmniejszych kwadratów, metoda Zangwill'a, metoda algorytmów ewolucyjnych. Celem tych badań jest dobieranie najefektywniejszej metody uczenia do projektowania adaptacyjnego neuronowego regulatora napięcia generatora synchronicznego.metody uczenia, sieć neuronowa, neuronowy regulator...