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Wyniki wyszukiwania dla: ENGINEERING EDUCATION, SMART GRID SYSTEMS, CHALLENGE-BASED LEARNING
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JOURNAL OF ENGINEERING EDUCATION
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Virtual Engineering Object (VEO): Toward Experience-Based Design and Manufacturing for Industry 4.0
PublikacjaIn this article we propose the concept, its framework, and implementation methodology for Virtual Engineering Objects (VEO). A VEO is the knowledge representation of an engineering object that embodies its associated knowledge and experience. A VEO is capable of adding, storing, improving, and sharing knowledge through experience. Moreover, it is demonstrated that VEO is a specialization of a Cyber-Physical System (CPS). In this...
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Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data
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Learning from Imbalanced Data Streams Based on Over-Sampling and Instance Selection
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Analyzing the Effectiveness of the Brain–Computer Interface for Task Discerning Based on Machine Learning
PublikacjaThe aim of the study is to compare electroencephalographic (EEG) signal feature extraction methods in the context of the effectiveness of the classification of brain activities. For classification, electroencephalographic signals were obtained using an EEG device from 17 subjects in three mental states (relaxation, excitation, and solving logical task). Blind source separation employing independent component analysis (ICA) was...
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Autonomous Perception and Grasp Generation Based on Multiple 3D Sensors and Deep Learning
PublikacjaGrasping objects and manipulating them is the main way the robot interacts with its environment. However, for robots to operate in a dynamic environment, a system for determining the gripping position for objects in the scene is also required. For this purpose, neural networks segmenting the point cloud are usually applied. However, training such networks is very complex and their results are unsatisfactory. Therefore, we propose...
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Deep Learning-Based LOS and NLOS Identification in Wireless Body Area Networks
PublikacjaIn this article, the usage of deep learning (DL) in ultra-wideband (UWB) Wireless Body Area Networks (WBANs) is presented. The developed approach, using channel impulse response, allows higher efficiency in identifying the direct visibility conditions between nodes in off-body communication with comparison to the methods described in the literature. The effectiveness of the proposed deep feedforward neural network was checked on...
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Machine learning-based prediction of seismic limit-state capacity of steel moment-resisting frames considering soil-structure interaction
PublikacjaRegarding the unpredictable and complex nature of seismic excitations, there is a need for vulnerability assessment of newly constructed or existing structures. Predicting the seismic limit-state capacity of steel Moment-Resisting Frames (MRFs) can help designers to have a preliminary estimation and improve their views about the seismic performance of the designed structure. This study improved data-driven decision techniques in...
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Sex Education: Sexuality, Society and Learning
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The Journal of Adventure Education and Outdoor Learning
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GIST-Education and Learning Research Journal
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International Journal of Learning in Higher Education
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Journal of Education and e-Learning Research
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Journal of Digital Learning in Teacher Education
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International Journal of Practice-Based Learning in Health and Social Care
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Multiagent and Grid Systems
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Smart Virtual Product Development (SVPD): Experience Based Product Development System for Industry 4.0
PublikacjaThis chapter presents the concept of smart virtual product development (SVPD) system capable of supporting industrial product development. It enhances the decision making process during various activities involved in product development i.e. product design, manufacturing, and inspection planning. This is achieved by using the explicit knowledge of past formal decision events, which are captured, stored, and recalled in the form...
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Journal of Information Systems Education
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INTERNATIONAL JOURNAL OF UNCERTAINTY FUZZINESS AND KNOWLEDGE-BASED SYSTEMS
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Edyta Gołąb-Andrzejak dr hab.
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Machine learning-based prediction of residual drift and seismic risk assessment of steel moment-resisting frames considering soil-structure interaction
PublikacjaNowadays, due to improvements in seismic codes and computational devices, retrofitting buildings is an important topic, in which, permanent deformation of buildings, known as Residual Interstory Drift Ratio (RIDR), plays a crucial role. To provide an accurate yet reliable prediction model, 32 improved Machine Learning (ML) algorithms were considered using the Python software to investigate the best method for estimating Maximum...
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Multidimensional legacy aspects of modernizing web based systems
PublikacjaPublikacja porusza zagadnienia technik modernizacji tzw. legacy systems mających zastosowanie w cyklach życia oprogramowania. Przedmiotem dyskusji jest także studium przypadku Endoscopy Recommender System. Ponadto rozważany jest wpłw zmian wymagań, platform, standardów oraz strategii rozwoju oprogramowania na status legacy aplikacji webowych.
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Developing nucleic acid-based electrical detection systems
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Model-Based Testing of Embedded Systems in the Automotive Domain
PublikacjaPhD
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Multiscalar Model Based Control Systems for AC Machines
PublikacjaContents of the Chapter: Nonlinear transformations and feedback linearization. Models of the squirrel cage induction machine: Vector model of the squirrel cage induction machine. Multiscalar models of the squirrel cage induction machine.Feedback linearization of multiscalar models of the induction motor.Models of the double fed induction machine: Vector model of the double fed induction machine. Multiscalar model of the...
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Quantitative interpretation of energy-based systems and index of their reliability
PublikacjaW artykule zaproponowano interpretację wartościującą działania, które rozumiane jest jako wielkość fizyczna o jednostce miary zwanej dżulosekundą. Przedstawiono oryginalną metodę analizy i oceny tak rozumianego działania dowolnego systemu energetycznego z uwzględnieniem jego niezawodności i bezpieczeństwa. Do uzasadnienia przydatności tak interpretowanego działania zastosowano jednorodny proces Poissona. Proces ten umożliwił skonstruowanie...
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Antibacterial Porous Systems Based on Polylactide Loaded with Amikacin
PublikacjaThree porous matrices based on poly(lactic acid) are proposed herein for the controlled release of amikacin. The materials were fabricated by the method of spraying a surface liquid. Description is given as to the possibility of employing a modifier, such as a silica nanocarrier, for prolonging the release of amikacin, in addition to using chitosan to improve the properties of the materials, e.g., stability and sorption capacity....
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Decisional DNA based embedded systems: a new perspective
PublikacjaOmówiono nowe kierunki i perspektywy badań w zakresie systemów podporządkowanych opartych na decyzyjnym DNA.
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Estimation and modeling hydrolysis of slowly biodegradable substrate based on the batch respirometric tests in activated sludge systems
PublikacjaNowadays, appropriate determination of chemical oxygen demand (COD) fractionation together with degradation kinetics of organic compounds have a prime importance on the design and operation of activated sludge systems. Batch respirometric tests based on the oxygen uptake rates (OUR) and corresponding COD is accepted method to reflect the consumption of biodegradable substrates. The influence of the readily biodegradable (Ss) fraction...
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Artificial Intelligence-Based Weighting Factor Autotuning for Model Predictive Control of Grid-Tied Packed U-Cell Inverter
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Tomasz Zubowicz dr inż.
OsobyTomasz Zubowicz has received his M.Sc. Eng. degree in Control Engineering from the Faculty of Electrical and Control Engineering at the Gda{\'n}sk University of Technology (GUT) in $2008$. He received his Ph.D. Eng. (Hons.) in the field of Control Engineering from the same faculty in $2019$. In $2012$ he became a permanent staff member at the Department of Intelligent Control and Decision Support Systems at GUT and a member of...
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Diagnostics of civil engineering structures with use of continuous fiber optic sensors based on Brillouin scattering
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Evidence-Based Risk Management for Civil Engineering Projects Using Bayesian Belief Networks (BBN)
PublikacjaThe authors are seeking new methods for improving the efficiency of the investments associated with the maintenance and operation of existing civil engineering structures. It is demonstrated how the knowledge about the elements of construction and operation phases and their relationships, combined with monitoring data can be used for more effective management of the risks associated with civil engineering projects. The methodology...
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DentalSegmentator: Robust open source deep learning-based CT and CBCT image segmentation
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CoLED Collaborative Learning Environment for Engineering Education
ProjektyProjekt realizowany w PRO-MED sp. z o.o. zgodnie z porozumieniem 11111111 z dnia 2018-10-01
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The CDIO model in architectural education and research by design
PublikacjaArchitectural education has always been related to experimentation: that is, defining concepts, drawing sketches, working on models, then testing and modifying them. This activity mirrors the CDIO learning methods and objectives. Despite this, research studies into the applicability of the CDIO model in architectural curricula are scarce. In the discipline of architecture, hands-on experiences are associated not only with one of...
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Auto-tuning methodology for configuration and application parameters of hybrid CPU + GPU parallel systems based on expert knowledge
PublikacjaAuto-tuning of configuration and application param- eters allows to achieve significant performance gains in many contemporary compute-intensive applications. Feasible search spaces of parameters tend to become too big to allow for exhaustive search in the auto-tuning process. Expert knowledge about the utilized computing systems becomes useful to prune the search space and new methodologies are needed in the face of emerging heterogeneous...
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Mieczysław Brdyś prof. dr hab. inż.
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IEEE Transactions on Neural Networks and Learning Systems
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Olgun Aydin dr
OsobyOlgun Aydin finished his PhD by publishing a thesis about Deep Neural Networks. He works as a Principal Machine Learning Engineer in Nike, and works as Assistant Professor in Gdansk University of Technology in Poland. Dr. Aydin is part of editorial board of "Journal of Artificial Intelligence and Data Science" Dr. Aydin served as Vice-Chairman of Why R? Foundation and is member of Polish Artificial Intelligence Society. Olgun is...
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Business & Information Systems Engineering
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CIVIL ENGINEERING AND ENVIRONMENTAL SYSTEMS
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COMPUTER SYSTEMS SCIENCE AND ENGINEERING
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Innovations in Systems and Software Engineering
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Industrial Engineering and Management Systems
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Molecular Systems Design & Engineering
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Concurrent Systems Engineering Series
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Journal of Systems Engineering and Electronics
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Desulfurization of raw naphtha cuts using hybrid systems based on acoustic cavitation and advanced oxidation processes (AOPs)
PublikacjaA combination of dual-frequency acoustic cavitation (acoustic cavitation) and UV assisted advanced oxidation processes (AOPs) reaction system was developed for desulfurization of raw naphtha used to produce aviation fuels. Various types of oxidants in hybrid systems including hydrogen peroxide, acetic acid, acetone, air and ozone were compared. At optimum oxidant to sulfur compounds molar ratio (rox) of 5.0, the hybrid process...
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ENGINEERING INTELLIGENT SYSTEMS FOR ELECTRICAL ENGINEERING AND COMMUNICATIONS
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