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Wyniki wyszukiwania dla: SELF-SUPERVISED LEARNING
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Guest editorial: learning, scheduling, resource optimization, and evolution in smart artificial systems: challenges and support
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Deep learning based segmentation using full wavefield processing for delamination identification: A comparative study
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Perception of Pathologists in Poland of Artificial Intelligence and Machine Learning in Medical Diagnosis—A Cross-Sectional Study
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Errorless Learning as a method of neuropsychological rehabilitation of individuals suffering from dementia in the course of Alzheimer’s disease
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Fractional-Order PID Controller (FOPID)-Based Iterative Learning Control for a Nonlinear Boiler System
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Diversity of Students’ Unethical Behaviors in Online Learning Amid COVID-19 Pandemic: An Exploratory Analysis
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PELATIHAN E-LEARNING MENGGUNAKAN GOOGLE CLASSROOM BAGI GURU MA RADEN FATAH PRAMBANAN
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SELECTING A REPRESENTATIVE DATA SET OF THE REQUIRED SIZE USING THE AGENT-BASED POPULATION LEARNING ALGORITHM
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Towards Achilles Tendon Injury Prevention in Athletes with Structural MRI Biomarkers: A Machine Learning Approach
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Redefining brain tumor segmentation: a cutting-edge convolutional neural networks-transfer learning approach
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Brain Tumor Segmentation Using Ensemble CNN-Transfer Learning Models: DeepLabV3plus and ResNet50 Approach
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Implementing SP4CE Learning Rooms concept and AUTODESK online certification in the preparation of a new generation of engineers.
PublikacjaIn academia, educators do not always cope with rapidly changing technologies. Yet keeping up with new trends is essential to graduates’ success in a competitive job market. In the article, the author will answer the question of how Autodesk University Open Educational Resources and Certiport exams including GMetrix can enhance students’ academic progress and prepare them for future career. The concept of co-operation between Authorized...
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Orientation-aware ship detection via a rotation feature decoupling supported deep learning approach
PublikacjaShip imaging position plays an important role in visual navigation, and thus significant focuses have been paid to accurately extract ship imaging positions in maritime videos. Previous studies are mainly conducted in the horizontal ship detection manner from maritime image sequences. This can lead to unsatisfied ship detection performance due to that some background pixels maybe wrongly identified as ship contours. To address...
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Dagmara Nikulin dr
OsobyDagmara Nikulin jest zatrudniona na Wydziale Zarządzania i Ekonomii na stanowisku adiunkta badawczo-dydaktycznego od 2014 roku. Początkowo pracowała w Katedrze Nauk Ekonomicznych, a obecnie w Katedrze Statystyki i Ekonometrii. Jest absolwentką Wydziału Ekonomii Uniwersytetu Ekonomicznego w Poznaniu (2009) oraz Wydziału Nauk Społecznych Uniwersytetu im. Adama Mickiewicza w Poznaniu (2010). W latach 2006-2007 studiowała na uniwersytecie...
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Citizenship Teaching and Learning
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A probabilistic concept of assessment of amount of noxious substances contained in exhaust gas emitted from self-ignition engines
PublikacjaPrzedstawiono probabilistyczną koncepcję oceny toksyczności spalin silników o zapłonie samoczynnym. Ocena taka jest istotna, ponieważ bez niej nie jest możliwe określenie walorów proekologicznych różnych środków transportowych z napędem spalinowym, w tym śródlądowych statków pasażerskich. W koncepcji tej uwzględniony został model procesu rozruchu silników o zapłonie samoczynnym. Model ten przedstawiono w formie procesu semimarkowskiego,...
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Towards Promotion of Graphene/Titania‐Based Electrode via Ultrafast and Self‐Expansion Reduction for Li‐ion Battery
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Ultrafast self-expanded reduced graphene oxide and 2D MoS2 based films as anode in Li-ion battery
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Towards classification of patients based on surface EMG data of temporomandibular joint muscles using self-organising maps
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Self-assembly and interactions of short antimicrobial cationic lipopeptides with membrane lipids: ITC, FTIR and molecular dynamics studies
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Application of 3D digital image correlation for development and validation of FEM model of self-supporting metal plates structures
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What makes a group worth dying for? Identity fusion fosters perception of familial ties, promoting self-sacrifice.
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Diagnostics of the drive shaft bearing based on vibrations in the high-frequency range as a part of the vehicle's self-diagnostic system
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Measurements and calculation of self inductance of testing coils used in physical transformer model construction and its frequency analysis
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Structural evaluation of percolating, self-healing polyurethane–polycaprolactone blends doped with metallic, ferromagnetic, and modified graphene fillers
PublikacjaComposites with differently shaped micro- and nanofillers show various, unique thermal, and physicochemical properties when mixed with carefully chosen polymer matrix. Selected composition holds strategic value in achieving desired properties that is biodegradability, thermoelectric conductivity, and shape memory for organic coating. The main aim of this work is to briefly examine structural changes after reaching percolation...
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Impact of Pregnancy on Self-Efficacy and Personal Competence in the Context of Risk of Depression, Mental Health Status, and Satisfaction with Life
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Recent progress in bio-based elastomers with intrinsic self-healing mechanisms - part I: Natural rubber modifications
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Chiral and achiral crystals, charge-assisted hydrogen-bond patterns and self-organization of selected solid diaminium thiosulfates
PublikacjaAbstract A series of diaminium thiosulfates, derivatives of diamines: NH2CH2CH(CH3)NH2 (1) and NH2(CH2)nNH2, n = 3-6 (2-5 respectively)and thiosulfuric acid were prepared and their structures determined by crystal X-ray diffraction analysis. Compounds 1, 2 and 4 turned out to be hydrates. The crystal structure of 1,2-proylenediaminium thiosulfate is chiral and exhibits spontaneous resolution. Crystals for both enantiomers...
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Structural evaluation of percolating, self-healing polyurethane–polycaprolactone blends doped with metallic, ferromagnetic, and modified graphene fillers
PublikacjaComposites with differently shaped micro- and nanofillers show various, unique thermal, and physicochemical properties when mixed with carefully chosen polymer matrix. Selected composition holds strategic value in achieving desired properties that is biodegradability, thermoelectric conductivity, and shape memory for organic coating. The main aim of this work is to briefly examine structural changes after reaching percolation threshold...
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On the use of black tea waste as a functional filler for manufacturing self-stabilizing polyethylene composites: In-depth thermal analysis
PublikacjaThermal and oxidative stabilization are critical aspects in the processing and exploitation of polyolefins. Black tea contains many natural antioxidants, the largest group of compounds in its composition. When used as a filler for composite manufacturing, the thermo-oxidation process of polyethylene can be slowed down. Black tea waste (BTW) generated during the process of packing tea into sachets was introduced into a bio-based...
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Adjusted SpikeProp algorithm for recurrent spiking neural networks with LIF neurons
PublikacjaA problem related to the development of a supervised learning method for recurrent spiking neural networks is addressed in the paper. The widely used Leaky-Integrate-and-Fire model has been adopted as a spike neuron model. The proposed method is based on a known SpikeProp algorithm. In detail, the developed method enables gradient descent learning of recurrent or multi-layer feedforward spiking neural networks. The research included...
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Maria Jastrzębska dr hab.
OsobyMaria Jastrzębska jest pracownikiem Katedry Finansów. Autorka ponad 170 publikacji, w tym 8 monografii - Zarządzanie finansami gmin. Aspekty teoretyczne; Polityka budżetowa jednostek samorządu terytorialnego; Zarządzanie długiem jednostek samorządu terytorialnego; Finanse jednostek samorządu terytorialnego; Zarządzanie ryzykiem w działalności jednostek samorządu terytorialnego ze szczególnym uwzględnieniem ryzyka katastroficznego...
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Cloud solutions as a platform for building advanced learning platform, that stimulate the real work environment for project managers
PublikacjaImproving skills of managers and executives require, that during the transfer of knowledge (in different ways: during studies, trainings, workshops and other forms of education) it is necessary to use tools and solutions that are (or will be) used in real world environments, where people being educated are working or will work. Cloud solutions allow educational entities (universities, training companies, trainers, etc.) to provide...
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Experimental investigations and prediction of WEDMed surface of nitinol SMA using SinGAN and DenseNet deep learning model
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Universal Predictors of Dental Students’ Attitudes towards COVID-19 Vaccination: Machine Learning-Based Approach
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The pattern of verbal, visuospatial and procedural learning in Richardson variant of progressive supranuclear palsy in comparison to Parkinson’s disease
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Detection of Cystic Fibrosis Symptoms Based on X-Ray Images Using Machine Learning- Pilot Study
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Early Predictors of Learning a Foreign Language in Pre-school – Polish as a First Language, English as a Foreign Language
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Quantitative Soil Characterization for Biochar–Cd Adsorption: Machine Learning Prediction Models for Cd Transformation and Immobilization
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Credit Decision Support Based on Real Set of Cash Loans Using Integrated Machine Learning Algorithms
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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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Employing Subjective Tests and Deep Learning for Discovering the Relationship between Personality Types and Preferred Music Genres
PublikacjaThe purpose of this research is two-fold: (a) to explore the relationship between the listeners’ personality trait, i.e., extraverts and introverts and their preferred music genres, and (b) to predict the personality trait of potential listeners on the basis of a musical excerpt by employing several classification algorithms. We assume that this may help match songs according to the listener’s personality in social music networks....
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Prediction of Wastewater Quality at a Wastewater Treatment Plant Inlet Using a System Based on Machine Learning Methods
PublikacjaOne of the important factors determining the biochemical processes in bioreactors is the quality of the wastewater inflow to the wastewater treatment plant (WWTP). Information on the quality of wastewater, sufficiently in advance, makes it possible to properly select bioreactor settings to obtain optimal process conditions. This paper presents the use of classification models to predict the variability of wastewater quality at...
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Reliable computationally-efficient behavioral modeling of microwave passives using deep learning surrogates in confined domains
PublikacjaThe importance of surrogate modeling techniques has been steadily growing over the recent years in high-frequency electronics, including microwave engineering. Fast metamodels are employed to speedup design processes, especially those conducted at the level of full-wave electromagnetic (EM) simulations. The surrogates enable massive system evaluations at nearly EM accuracy and negligible costs, which is invaluable in parameter...
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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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Efficient Calibration of Cost-Efficient Particulate Matter Sensors Using Machine Learning and Time-Series Alignment
PublikacjaAtmospheric particulate matter (PM) poses a significant threat to human health, infiltrating the lungs and brain and leading to severe issues such as heart and lung diseases, cancer, and premature death. The main sources of PM pollution are vehicular and industrial emissions, construction and agricultural activities, and natural phenomena such as wildfires. Research underscores the absence of a safe threshold for particulate exposure,...
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Technological vs. Non-Technological Mindsets: Learning From Mistakes, and Organizational Change Adaptability to Remote Work
PublikacjaThe permanent implementation of the change in working methods, e.g., working in the virtual space, is problematic for some employees and, as a result, for management leaders. To explore this issue deeper, this study assumes that mindset type: technological vs. non-technological, may influence the organizational adaptability to change. Moreover, the key interest of this research is how non-technological mindsets...
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A Novel Spatio–Temporal Deep Learning Vehicle Turns Detection Scheme Using GPS-Only Data
PublikacjaWhether the computer is driving your car or you are, advanced driver assistance systems (ADAS) come into play on all levels, from weather monitoring to safety. These modern-day ADASs use various assisting tools for drivers to keep the journey safe; these sophisticated tools provide early signals of numerous events, such as road conditions, emerging traffic scenarios, and weather warnings. Many urban applications, such as car-sharing...
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Andrzej Czyżewski prof. dr hab. inż.
OsobyProf. zw. dr hab. inż. Andrzej Czyżewski jest absolwentem Wydziału Elektroniki PG (studia magisterskie ukończył w 1982 r.). Pracę doktorską na temat związany z dźwiękiem cyfrowym obronił z wyróżnieniem na Wydziale Elektroniki PG w roku 1987. W 1992 r. przedstawił rozprawę habilitacyjną pt.: „Cyfrowe operacje na sygnałach fonicznych”. Jego kolokwium habilitacyjne zostało przyjęte jednomyślnie w czerwcu 1992 r. w Akademii Górniczo-Hutniczej...
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Wojciech Wojnowski dr inż.
OsobyUkończył V Liceum Ogólnokształcące w Gdańsku w klasie o profilu matematyczno-fizycznym z wykładowym językiem angielskim. W 2009 roku rozpoczął studia na Wydziale Chemicznym PG na kierunku technologia chemiczna, uzyskując w 2012 roku tytuł inżyniera, a w 2013 tytuł magistra. W latach 2013–2015 studiował sinologię na Uniwersytecie w Nankinie dzięki uzyskaniu Stypendium Rządu ChRL. Po powrocie do Polski w 2015 roku rozpoczął studia...