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Search results for: ACTIVE LEARNING ALGORITHM
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Projekt Leonardo da Vinci EMDEL (European Model for Distance Education and Learning) - otwarte szkolenia online.
PublicationW 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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Active Site Architecture and Reaction Mechanism Determination of Cold Adapted beta-D-galactosidase from Arthrobacter sp. 32cB
PublicationArthbetaDG is a dimeric, cold-adapted beta-D-galactosidase that exhibits high hydrolytic and transglycosylation activity. A series of crystal structures of its wild form, as well as its ArthbetaDG_E441Q mutein complexes with ligands were obtained in order to describe the mode of its action. The ArthbetaDG_E441Q mutein is an inactive form of the enzyme designed to enable observation of enzyme interaction with its substrate. The...
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Road traffic can be predicted by machine learning equally effectively as by complex microscopic model
PublicationSince 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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Designing learning spaces through international and interdisciplinary collaborative design studio: The case of engineer architects and pedagogic students
PublicationThe study explores the dynamics and outcomes of an international interdisciplinary design studio focusing on innovative learning spaces. Conducted over two years between students of Faculty of Architecture at Gdansk Tech and pedagogic students from Kibbutzim College in Tel Aviv, this design-based study examines the contributions of unique educational program to student learning, the evolution of the design process, collaboration,...
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Study of the Active Carbon from Used Coffee Grounds as the Active Material for a High-Temperature Stable Supercapacitor with Ionic-Liquid Electrolyte
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High-precision bearing estimation for active sonar with cylindrical array performed by interpolated array transformation
PublicationThe article presents a method for improving the accuracy of bearing in multibeam sonar with a cylindrical array. The antenna’s non-linear shape and the resulting non-uniform sampling of the signal in space, mean that known methods of high-resolution spectral analysis cannot be used. In order to apply an algorithm from this group, a linear virtual antenna must be produced. The paper presents a technique of mapping a cylindrical...
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Selected anionic and cationic surface active agents: case study on the Kłodnica sediments
PublicationSurface active agents (surfactants) are a group of chemical compounds, which are used as ingredients of detergents, cleaning products, cosmetics and functional products. After use, wastes containing surfactants or their degradation products are discharged to wastewater treatment plants or directly into surface waters. Due to their specific properties of SAAs, compounds are able to migrate between different environmental compartments...
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Experimental tuning of AuAg nanoalloy plasmon resonances assisted by machine learning method
PublicationPlasmonic 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
PublicationThe 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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Optimization-based stacked machine-learning method for seismic probability and risk assessment of reinforced concrete shear walls
PublicationEfficient 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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A Multi-Fidelity Surrogate-Model-Assisted Evolutionary Algorithm for Computationally Expensive Optimization Problems
PublicationIntegrating data-driven surrogate models and simulation models of different accuracies (or fideli-ties) in a single algorithm to address computationally expensive global optimization problems has recently attracted considerable attention. However, handling discrepancies between simulation models with multiple fidelities in global optimization is a major challenge. To address it, the two major contributions of this paper include:...
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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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Energy consumption optimization in wastewater treatment plants: Machine learning for monitoring incineration of sewage sludge
PublicationBiomass management in terms of energy consumption optimization has become a recent challenge for developed countries. Nevertheless, the multiplicity of materials and operating parameters controlling energy consumption in wastewater treatment plants necessitates the need for sophisticated well-organized disciplines in order to minimize energy consumption and dissipation. Sewage sludge (SS) disposal management is the key stage of...
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Computational Complexity and Its Influence on Predictive Capabilities of Machine Learning Models for Concrete Mix Design
PublicationThe 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
PublicationThis 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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A Novel Trust-Region-Based Algorithm with Flexible Jacobian Updates for Expedited Optimization of High-Frequency Structures
PublicationSimulation-driven design closure is mandatory in the design of contemporary high-frequency components. It aims at improving the selected performance figures through adjustment of the structure’s geometry (and/or material) parameters. The computational cost of this process when employing numerical optimization is often prohibitively high, which is a strong motivation for the development of more efficient methods. This is especially...
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Detection of People Swimming in Water Reservoirs with the Use of Multimodal Imaging and Machine Learning
PublicationEvery 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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Global Complex Roots and Poles Finding Algorithm Based on Phase Analysis for Propagation and Radiation Problems
PublicationA flexible and effective algorithm for complex roots and poles finding is presented. A wide class of analytic functions can be analyzed, and any arbitrarily shaped search region can be considered. The method is very simple and intuitive. It is based on sampling a function at the nodes of a regular mesh, and on the analysis of the function phase. As a result, a set of candidate regions is created and then the roots/poles are verified...
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Solvent Screening for Solubility Enhancement of Theophylline in Neat, Binary and Ternary NADES Solvents: New Measurements and Ensemble Machine Learning
PublicationTheophylline, a typical representative of active pharmaceutical ingredients, was selected to study the characteristics of experimental and theoretical solubility measured at 25 °C in a broad range of solvents, including neat, binary mixtures and ternary natural deep eutectics (NADES) prepared with choline chloride, polyols and water. There was a strong synergistic effect of organic solvents mixed with water, and among the experimentally...
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Selection of optimal location and rated power of capacitor banks in distribution network using genetic algorithm
PublicationIn this paper, the problem of placement and rated power of capacitor banks in the Distribution Network (DN) is considered. We try to suggest the best places for installing capacitor banks and define their reactive power. The considered formulation requires the optimization of the cost of two different objectives. Therefore the use of properly multiobjective heuristic optimization methods is desirable. To solve this problem we use...
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Deep learning-enabled integration of renewable energy sources through photovoltaics in buildings
PublicationInstalling photovoltaic (PV) systems in buildings is one of the most effective strategies for achieving sustainable energy goals and reducing carbon emissions. However, the requirement for efficient energy management, the fluctuating energy demands, and the intermittent nature of solar power are a few of the obstacles to the seamless integration of PV systems into buildings. These complexities surpass the capabilities of rule-based...
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Transformational Leadership and Acceptance of Mistakes as a Source of Learning: Poland-USA Cross-Country Study
PublicationThis 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
PublicationProper 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
PublicationProper 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
PublicationOptical 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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Calibration of precipitation estimation algorithm with particular emphasis on the Pomeranian region using high performance computing
PublicationFast and accurate precipitation estimation is an important element of remote atmosphere monitoring, as it allows, for example, to correct short-term weather forecasts and the prediction of several types of meteorological threats. The paper presents methodology for calibrating precipitation estimation algorithm based on MSG SEVIRI sensor data, and Optimal Cloud Analysis product available via EumetCast transmission. Calibration is...
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Pareto Ranking Bisection Algorithm for EM-Driven Multi-Objective Design of Antennas in Highly-Dimensional Parameter Spaces
PublicationA deterministic technique for fast surrogate-assisted multi-objective design optimization of antennas in highly-dimensional parameters spaces has been discussed. In this two-stage approach, the initial approximation of the Pareto set representing the best compromise between conflicting objectives is obtained using a bisection algorithm which finds new Pareto-optimal designs by dividing the line segments interconnecting previously...
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Comparative study on total nitrogen prediction in wastewater treatment 1 plant and effect of various feature selection methods on machine learning algorithms performance
PublicationWastewater characteristics prediction in wastewater treatment plants (WWTPs) is valuable and can reduce the number of sampling, energy, and cost. Feature Selection (FS) methods are used in the pre-processing section for enhancing the model performance. This study aims to evaluate the effect of seven different FS methods (filter, wrapper, and embedded methods) on enhancing the prediction accuracy for total nitrogen (TN) in the WWTP...
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Improvement of Oxygen Electrode Performance of Intermediate Temperature Solid Oxide Cells by Spray Pyrolysis Deposited Active Layers
PublicationIntermediate temperature solid oxide fuel cells oxygen electrodes are modified by active interfacial layers. Spray pyrolysis is used to produce thin (≈500 nm) layers of mixed ionic and electronic conductors: Sm0.5Sr0.5CoO3−δ (SSC), La0.6Sr0.4CoO3−δ (LSC), La0.6Sr0.4Co0.2Fe0.8O3−δ (LSCF), and Pr6O11 (PrOx) on the electrode–electrolyte interface. The influence of the annealing temperature on the electrode polarization (area specific...
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ARTIFICIAL MODEL IN THE ASSESSMENT OF THE ALGORITHM OF OBJECTS RECORDED BY LASER SCANNING SHAPE DETECTION (ALS/TLS)
PublicationBrief description of the study and used methods. Brief description of the study and used As part of the preparatory work aimed to create the application solution allowing for the automation of searching objects in data, obtained in the scanning process using ALS (Airborne Laser Scanning) or TLS (Terrestrial Laser Scanning), the authors prepared a artificial (synthetic, theoretical) model of space, used for the verification of operation...
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Fast Fading Influence on the Deep Learning-Based LOS and NLOS Identificationin Wireless Body Area Networks
PublicationIn 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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A linear time algorithm for edge coloring of binomial trees
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A polynomial algorithm for finding T-span of generalized cacti
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An Approximation Algorithm for Diagnostic Test Scheduling in Multicomputer Systems
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Implementation of matrix-type FDTD algorithm on a graphics accelerator
PublicationArtykuł prezetuje implementację algorytmu FDTD w postaci macierzowej przeznaczonej dla kart graficznych. Wykazany został wzrost efektywności obliczeń numerycznych w odniesieniu do implementacji przeznaczonej dla procesora komputerowego.
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On the EM algorithm for the estimation of speech AR parameters in noise
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An approximation algorithm for maximum P3-packing in subcubic graphs
PublicationW pracy podano algorytm 4/3-przyliżony dla trudnego obliczeniowo problemu umieszczania wierzchołkowo rozłącznych dwukrawędziowych ścieżek w grafach o stopniu maksymalnym 3 i stopniu minimalnym 2. Poprawiono tym samym wcześniejsze wyniki dla grafów kubicznych (A. Kelmans, D. Mubayi, Journal of Graph Theory 45, 2004).
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An efficient algorithm for mobile guarded guards in simple grids
PublicationW pracy rozważono problem strzeżenia ortogonalnych krat dwuwymiarowych przez mobilne straże strzeżone. Podano algorytmy wielomianowe m.in. dla przypadku krat prostych i dla przypadku krat bez przeszkód w kierunku poziomym (pionowym).
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A comparative study of English viseme recognition methods and algorithm
PublicationAn elementary visual unit – the viseme is concerned in the paper in the context of preparing the feature vector as a main visual input component of Audio-Visual Speech Recognition systems. The aim of the presented research is a review of various approaches to the problem, the implementation of algorithms proposed in the literature and a comparative research on their effectiveness. In the course of the study an optimal feature vector...
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A Backtracking Search Algorithm for Distribution Network Reconfiguration Problem
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An Agent-Based Simulated Annealing Algorithm for Data Reduction
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A New Heuristic Algorithm for Effective Preemption in MPLS Networks
PublicationW artykule opisano nowy algorytm wywłaszczania przeznaczony dla sieci MPLS. Umożliwia on alokację zasobów sieci dla nowej ścieżki uwzględniając koszt usuniętych jednej lub wielu istniejących już ścieżek. Proponowany heurystyczny algorytm wybiera ścieżki do wywłaszczenia wykorzystując informację o topologii sieci. Używa funkcji optymalizacji minimalizującej stratę pasma na poziomie sieci. Przedstawiono i omówiono wyniki badań symulacyjnych...
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The algorithm of building the hierarchical contextual framework of textual corpora
PublicationThis paper presents an approach for Modeling the Latent Semantic Relations. The approach is based on advantages of two computational approaches: Latent Semantic Analysis and Latent Dirichlet Allocation. The scientific question about the possibility of reducing the influence of these Methods limitation on the Quality of the Latent Semantic Relations Analysis Results is raised. The case study for building the Two-level Hierarchical Contextual...
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Parameters of evolutionary algorithm in problem of collision avoidance at sea
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A polynomial algorithm for finding T-span of generalized cacti.
PublicationW pracy opisano wielomianowy algorytm wyznaczający optymalne T-pokolorowania dla uogólnionych kaktusów.
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Genetic algorithm for fatique crack detection in Timoshenko beam.
PublicationW pracy przedstawiono metodę detekcji peknięć zmęczeniowych w początkowej fazie ich rozwoju. Algorytm detekcji wykorzystuje metodę algorytmów genetycznych połączoną z metodą gradientową. Funkcja celu oparta została o zmiany w propagujacej fali sprężystej.
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An efficient algorithm for the longest tandem scattered subsequence problem.
PublicationReferat dotyczy zagadnienia wyznaczania najdłuższego podciągu podwójnego (typu x1,x2,...,xk,x1,x2,...,xk) dla zadanego ciągu znaków (y1,y2,...,yn). Podano algorytm o złożoności obliczeniowej O(n^2) i pamięciowej O(n) znajdujący optymalne rozwiązanie postawionego problemu.
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The cartographer algorithm for processing and querying description logics ontologies
PublicationLogika opisowa jest jednym z najbardziej popularnych formalizmów opisu wiedzy. Jej popularność jeszcze wzrosła kiedy pojawił się standard języka OWL. W artykule zaprezentowano nowy algorytm wnioskowania - algorytm kartograficzny - umożliwiający wnioskowanie niejawnie podanej wiedzy z terminologii (TBox) i opisu świata (ABox). Opisano sposób przetwarzania ontologii w terminach sygnatur binarnych i efektywny sposób odpytywania ontologii...
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Octave Error Immune and Instantaneous Pitch Detection Algorithm.
PublicationCelem publikacji jest prezentacja odpornego na błędy oktawowe, bazującego na analizie widmowej algorytmu detekcji częstotliwości podstawowej. Zaproponowana metoda dobrze sobie radzi z sygnałami o dużej zawartości sygnałów harmonicznych, jak i z prawie sinusoidalnymi przebiegami. Eksperymenty przeprowadzonno na 567 dzwiękach instrumentów muzycznych. Dźwięki grane były z różnymi artykulacjami, dynamiką i reprezentowałe były w całej...
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Enhancing environmental literacy through urban technology-based learning. The PULA app case
PublicationThis 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,...