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Wyniki wyszukiwania dla: ENGINEERING EDUCATION, SMART GRID SYSTEMS, CHALLENGE-BASED LEARNING
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Influence of Thermal Imagery Resolution on Accuracy of Deep Learning based Face Recognition
PublikacjaHuman-system interactions frequently require a retrieval of the key context information about the user and the environment. Image processing techniques have been widely applied in this area, providing details about recognized objects, people and actions. Considering remote diagnostics solutions, e.g. non-contact vital signs estimation and smart home monitoring systems that utilize person’s identity, security is a very important factor....
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Electrical and Software Systems Engineering [WIMiO][2023/24]
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Electrical and Software Systems Engineering [WIMiO][2022/23]
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Designing world closures for knowledge-based system engineering
PublikacjaWraz z rozwojem komponentów opartych na wiedzy przed inżynierami oprogramowania postawione zostały nowe zadania. Jednym z nich jest zintegrowanie tych komponentów z innymi standarodowymi komponentami. Zrealizowanie tego zadania wymagało zdefiniowania języka komunikacji pomiędzy różnymi komponentami w celu wymiany informacji. W artykule omówiono problem wymiany informacji pomiędzy komponentami opartymi na wiedzy i komponentami opartymi...
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NLITED - New Level of Integrated Techniques for Daylighting Education: Preliminary Data on the Use of an E-learning Platform
PublikacjaProject NLITED – New Level of Integrated Techniques for Daylighting Education - is an educational project for students and professionals. The project's objective is to create and develop an online eLearning platform with 32 eModules dedicated to daylight knowledge. The project also offers e-learners two summer school training where the theory is put into practice. The platform was launched on January 31, 2022. The paper...
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Modern remote sensing and the challenges facing education systems in terms of its teaching
PublikacjaCurrently the fastest growing area of geodesy is undoubtedly remote sensing. The importance that it has recently conducted on the effectiveness of worldwide research determines its huge success. Examination of the specific characteristics of objects without direct contact with them is a key feature has opened the way to the new very interesting areas of contemporary research. In this light, it seems reasonable to say that there...
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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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History-based dynamic weight voting for multi-agent systems
PublikacjaTaking decision in multi-agent systems may involve voting. Two basic voting protocols are surveyed in the paper. Then, a new history-based dynamic weight voting is proposed. This voting protocol allows for identification of the agents which contribute to the correct system decision. The proposed solution is contrasted with majority voting and with weighted average voting, to show its advantages
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Adaptive Positioning Systems Based on Multiple Wireless Interfaces for Industrial IoT in Harsh Manufacturing Environments
PublikacjaAs the industrial sector is becoming ever more flexible in order to improve productivity, legacy interfaces for industrial applications must evolve to enhance efficiency and must adapt to achieve higher elasticity and reliability in harsh manufacturing environments. The localization of machines, sensors and workers inside the industrial premises is one of such interfaces used by many applications. Current localization-based systems...
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DTH-SMART GRID Dystrybucyjny transformator hybrydowy (DTH) jako aktywny element nowoczesnych systemów „Smart Grid”
ProjektyProjekt realizowany w Laboratorium Linte^2 zgodnie z porozumieniem POIR.04.01.04-00-0018/17-00 z dnia 2019-10-11
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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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Deep-Learning-Based Precise Characterization of Microwave Transistors Using Fully-Automated Regression Surrogates
PublikacjaAccurate models of scattering and noise parameters of transistors are instrumental in facilitating design procedures of microwave devices such as low-noise amplifiers. Yet, data-driven modeling of transistors is a challenging endeavor due to complex relationships between transistor characteristics and its designable parameters, biasing conditions, and frequency. Artificial neural network (ANN)-based methods, including deep learning...
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Towards Experience-Based Smart Product Design for Industry 4.0
PublikacjaThis paper presents the concept of smart virtual product development (SVPD) system capable of supporting industrial product development process. It enhances the decision making process during different stages and activities involved in product development i.e. product design, manufacturing, and its inspection planning. The enhancement is achieved by using the explicit knowledge of formal past decision events, which are captured,...
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Current divider-based nanosecond high current pulse measuring systems
PublikacjaThis paper presents the analysis of the new approach to the measurement methodology of significant values (in order of hundreds of kA) and huge steepness (in order of MA/μs) current pulses based on current dividers along with a comparison of the various types transducers suitability in measuring systems with such extreme parameters. Such dividers are used to extend the measurement ranges of current transducers with limited current...
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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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Comparative Analysis of Regular Grid Based Algorithms in the Design of Graphical Control Panels
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Towards the 4th industrial revolution: networks, virtuality, experience based collective computational intelligence, and deep learning
PublikacjaQuo vadis, Intelligent Enterprise? Where are you going? The authors of this paper aim at providing some answers to this fascinating question addressing emerging challenges related to the concept of semantically enhanced knowledge-based cyber-physical systems – the fourth industrial revolution named Industry 4.0.
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Lead-free bismuth-based perovskites coupled with g–C3N4: A machine learning based novel approach for visible light induced degradation of pollutants
PublikacjaThe use of metal halide perovskites in photocatalytic processes has been attempted because of their unique optical properties. In this work, for the first time, Pb-free Bi-based perovskites of the Cs3Bi2X9 type (X = Cl, Br, I, Cl/Br, Cl/I, Br/I) were synthesized and subjected to comprehensive morphological, structural, and surface analyses, and photocatalytic properties in the phenol degradation reaction were examined. Furthermore,...
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International Journal of Continuing Engineering Education and Lifelong Learning
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Analysis of network infrastructure and QoS requirements for modern remote learning systems.
PublikacjaW referacie przedstawiono różne modele zdalnego nauczania. Podjęto próbę oceny wymagań nakładanych na infrastrukturę sieci. Ponadto przedstawiono mechanizmy QoS spotykane w sieciach teleinformatycznych oraz dokonano oceny możliwości ich współpracy w systemach edukacji zdalnej
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Endoscopy images classification with kernel based learning algorithms.
PublikacjaPrzedstawiono zastosowanie algorytmów opartych na wektorach wspierających zbudowanych na dwóch różnych funkcjach straty do klasyfikacji obrazów endoskopowych przełyku. Szczegółowo omówiono sposób ekstrakcji cech obrazów oraz algorytm klasyfikacji. Klasyfikator został zastosowany do problemu rozpoznawania zdjęć guzów złośliwych i łagodnych.
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INVESTIGATION OF THE LOMBARD EFFECT BASED ON A MACHINE LEARNING APPROACH
PublikacjaThe Lombard effect is an involuntary increase in the speaker’s pitch, intensity, and duration in the presence of noise. It makes it possible to communicate in noisy environments more effectively. This study aims to investigate an efficient method for detecting the Lombard effect in uttered speech. The influence of interfering noise, room type, and the gender of the person on the detection process is examined. First, acoustic parameters...
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Stacking-Based Integrated Machine Learning with Data Reduction
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MACHINE LEARNING–BASED ANALYSIS OF ENGLISH LATERAL ALLOPHONES
PublikacjaAutomatic classification methods, such as artificial neural networks (ANNs), the k-nearest neighbor (kNN) and selforganizing maps (SOMs), are applied to allophone analysis based on recorded speech. A list of 650 words was created for that purpose, containing positionally and/or contextually conditioned allophones. For each word, a group of 16 native and non-native speakers were audio-video recorded, from which seven native speakers’...
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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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Advanced photonic, electronic, and web engineering systems: WILGA Symposium, January 2013
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Low-Cost and Highly-Accurate Behavioral Modeling of Antenna Structures by Means of Knowledge-Based Domain-Constrained Deep Learning Surrogates
PublikacjaThe awareness and practical benefits of behavioral modeling methods have been steadily growing in the antenna engineering community over the last decade or so. Undoubtedly, the most important advantage thereof is a possibility of a dramatic reduction of computational expenses associated with computer-aided design procedures, especially those relying on full-wave electromagnetic (EM) simulations. In particular, the employment of...
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Recent advances on the removal of phosphorus in aquatic plant-based systems
PublikacjaPhosphorus (P) is a vital nutrient for the ecosystems and its excess in wastewater streams leads to some environmental issues such as extensive algae growth (eutrophication). Phytoremediation is a green technology that is based on the combined actions of plants and their associated microbial groups to remove and transfer the toxic compounds in surface water, groundwater and soil. Aquatic plants are widely used for the remediation...
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International Journal on Smart Sensing and Intelligent Systems
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Model of Volunteer Based Systems.
PublikacjaThere are two main approaches to processing tasks requiring high amounts of computational power. One approach is using clusters of mostly identical hardware, placed in dedicated locations. The other approach is outsourcing computing resources from large numbers of volunteers connected to the Internet. This chapter attempts to formulate a mathematical model of the volunteer based approach to distributed computations and apply it...
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Modeling Volunteer Based Systems
PublikacjaThere are two main approaches to processing tasks requiring high amounts of computational power. One approach is using clusters of mostly identical hardware, placed in dedicated locations [1, 2, 3]. The other approach is outsourcing computing resources from large numbers of volunteers connected to the Internet [7]. This chapter presents an application of a mathematical model of the volunteer computing presented in Volume 1 of this...
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Reliable Document-Centric Processing in Loosely Coupled Email-Based Systems
PublikacjaEmail is a simple way to exchange digital documents of any kind. The Mobile INteractive Document architecture (MIND) enables self-coordination and self-steering of document agent systems based on commonly available email services. In this paper, a mechanism for providing integrity and reliability of such an email based agent system is proposed to cope with message soft or hard bounces, user interrupts, and other unexpected events....
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Machine Learning-Based Wetland Vulnerability Assessment in the Sindh Province Ramsar Site Using Remote Sensing Data
PublikacjaWetlands provide vital ecological and socioeconomic services but face escalating pressures worldwide. This study undertakes an integrated spatiotemporal assessment of the multifaceted vulnerabilities shaping Khinjhir Lake, an ecologically significant wetland ecosystem in Pakistan, using advanced geospatial and machine learning techniques. Multi-temporal optical remote sensing data from 2000 to 2020 was analyzed through spectral...
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Experience Based Clinical Decision Support Systems: An Overview and Case Studies
PublikacjaThis chapter briefly overviews the evolution of the application of the Decisional DNA and the Set of Experience Knowledge Structure (SOEKS) in the medical domain and in particular in the specific case of the experience-based decision support systems. Decisional DNA, as a knowledge representation structure, offers great possibilities on gathering explicit knowledge of formal decision events as well as a tool for decision making...
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IoT-Based Smart Monitoring System Using Automatic Shape Identification
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A Set of Experience-Based Smart Synergy Security Mechanism in Internet of Vehicles
PublikacjaIn this article, we introduce a novel security mechanism, the Smart Synergy Security (3S). The mechanism uses the Set of Experience Knowledge Structure (SOEKS) and the synergy of security methods in different domains to provide the global optimal security strategy. The proposed strategy is taking into account the characteristics of information security (i.e. confidentiality, integrity, availability, controllability, and reviewability)...
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Neural modelling of dynamic systems with time delays based on an adjusted NEAT algorithm
PublikacjaA problem related to the development of an algorithm designed to find an architecture of artificial neural network used for black-box modelling of dynamic systems with time delays has been addressed in this paper. The proposed algorithm is based on a well-known NeuroEvolution of Augmenting Topologies (NEAT) algorithm. The NEAT algorithm has been adjusted by allowing additional connections within an artificial neural network and...
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Artificial Neural Network (ANN)-Based Voltage Stability Prediction of Test Microgrid Grid
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Challenges associated with development of AUV - unmanned autonomous underwater vehicles to be operated using the AI-based control systems
PublikacjaThe last decade has been devoted towards further development of the UUV unmanned underwater vehicles which may be of two types. There are the USV unmanned surface vehicles and UUV unmanned underwater vehicles. There is a growing interest to work out and implement the fully advanced AUV autonomous underwater vehicles. The main drivers towards development of such the vehicles are the technologies of autonomous systems, sensors and...
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An Ontology-based Contextual Pre-filtering Technique for Recommender Systems
PublikacjaContext-aware Recommender Systems aim to provide users with the most adequate recommendations for their current situation. However, an exact context obtained from a user could be too specific and may not have enough data for accurate rating prediction. This is known as the data sparsity problem. Moreover, often user preference representation depends on the domain or the specific recommendation approach used. Therefore, a big effort...
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Academy of Management Learning & Education
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Active Learning in Higher Education
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Experimental Evaluation of the Agent-Based Population Learning Algorithm for the Cluster-Based Instance Selection
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Learning Feedforward Control Using Multiagent Control Approach for Motion Control Systems
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Magdalena Gajewska prof. dr hab. inż.
OsobyMagdalena Gajewska (ur. 1.06.1968 r. w Gdańsku) ukończyła studia w 1993 roku na Wydziale Hydrotechniki Politechniki Gdańskiej. Jest adiunktem w Katedrze Technologii Wody i Ścieków na Wydziale Inżynierii Lądowej i Środowiska Politechniki Gdańskiej. Doktorat (2001) i habilitacja (2013) w dyscyplinie inżynierii środowiska. W kadencji 2016–2020 pełni funkcję prodziekana ds. nauki. Specjalizuję się w technologiach związanych z ekoinżynierią:...
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Magdalena Szuflita-Żurawska
OsobyMagdalena Szuflita-Żurawska jest kierownikiem Sekcji Informacji Naukowo-Technicznej na Politechnice Gdańskiej oraz Liderem Centrum Kompetencji Otwartej Nauki przy Bibliotece Politechniki Gdańskiej. Jej główne zainteresowania badawcze koncentrują się w obszarze komunikacji naukowej oraz otwartych danych badawczych, a także motywacji i produktywności naukowej. Jest odpowiedzialna między innymi za prowadzenie szkoleń dla pracowników...
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Mineral oil-based hydrostatic drives as the basic drive systems in the construction of offshore eqiupment projects
PublikacjaThe aim of this article is to present the components used in the production of mineral oil-based hydrostatic drives as the basic drive systems for the offshore industry. The article contains de-scriptions of the components of the said systems, with the description of their suitability for mi-neral oil operation and offshore applications.
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Satellite Image Classification Using a Hierarchical Ensemble Learning and Correlation Coefficient-Based Gravitational Search Algorithm
PublikacjaSatellite image classification is widely used in various real-time applications, such as the military, geospatial surveys, surveillance and environmental monitoring. Therefore, the effective classification of satellite images is required to improve classification accuracy. In this paper, the combination of Hierarchical Framework and Ensemble Learning (HFEL) and optimal feature selection is proposed for the precise identification...
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Optimization-based stacked machine-learning method for seismic probability and risk assessment of reinforced concrete shear walls
PublikacjaEfficient seismic risk assessment aids decision-makers in formulating citywide risk mitigation plans, providing insights into building performance and retrofitting costs. The complexity of modeling, analysis, and post-processing of the results makes it hard to fast-track the seismic probabilities, and there is a need to optimize the computational time. This research addresses seismic probability and risk assessment of reinforced...
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Machine-Learning-Powered EM-Based Framework for Efficient and Reliable Design of Low Scattering Metasurfaces
PublikacjaPopularity of metasurfaces has been continuously growing due to their attractive properties including the ability to effectively manipulate electromagnetic (EM) waves. Metasurfaces comprise optimized geometries of unit cells arranged as a periodic lattice to obtain a desired EM response. One of their emerging application areas is the stealth technology, in particular, realization of radar cross section (RCS) reduction. Despite...