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Wyniki wyszukiwania dla: machine%20learning
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Speciation of heavy metal compounds in samples of biota from marine ecosystems
PublikacjaIt has become increasingly evident that the toxicity, mobility, bioavailability and bioaccumulation of metals are dependent on the particular physico-chemical form in which the element occurs in the environment. Special attention is paid to metals, which are essential for the proper functioning of organisms if present in appropriate amounts but are toxic if in excess (i.e. Se, Cr, Zn), and also to non-essential elements (i.e. Hg,...
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Identification of diagnostic parameter sensitivity during dynamic processes of a marine engine
PublikacjaChanging some parameters of the engine structure alters the emission of harmful components in the exhaust gas. This applies in particular to the damage of charge exchange system as well as fuel system and engine supercharger. These changes are much greater during the dynamic states and their accompanying transitional processes. The different sensitivity of diagnostic parameters to the same force, coming from the engine structure, but...
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On the Use of Selected 4th Generation Nuclear Reactors in Marine Power Plants
PublikacjaThis article provides a review of the possibility of using different types of reactors to power ships. The analyses were carried out for three different large vessels: a container ship, a liquid gas carrier and a bulk carrier. A novelty of this work is the analysis of the proposal to adapt marine power plants to ecological requirements in shipping by replacing the conventional propulsion system based on internal combustion engines...
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Mercury concentrations in marine biota with special focus on grey and ringed seals
PublikacjaMarine organisms are exposed and sensitive to effects of environmental contamination by heavy metals including different forms of mercury. Baltic seals as the top predators of the marine ecosystem are even more endangered due to (considerable) longevity as well as a long biological half-time of toxin elimination. The concentrations of mercury in seals from the Baltic is poorly known, thus the aim of this work is to determine and...
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Using Rule-Based System for Monitoring Marine Navigation Data Processing
PublikacjaProcessing marine navigational data requires sophisticated software solutions. Typically, specialized tools called processors are analyzing raw data from different sensors. It becomes important to create the monitoring software that is able to validate and verify processing components integrated into the final system. Drools®business rule management platform provides a core business rules engine, web authoring and rules management...
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Proposal of New Starch-Blends Composition Quickly Degradable in Marine Environment
PublikacjaThe aim of this paper was to obtain a quickly degradable in seawater polymer blend as an alternative proposal for classical polymer packaging. For preliminary studies: poly(lactic acid) (PLA), starch, calcium carbonate (CaCO3), gelatin and glycerol were chosen. PLA was pointed out due to its biodegradability and comparable properties to polyethylene or polypropylene. Whereas starch was chosen as abundant, renewable and cheap polymer...
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Operation evaluation method for marine turbine combustion engines in terms of energetics
PublikacjaAn evaluation proposal (quantitative determination) of an y combustion turbine engine operation has been presented , wherein the impact energy occurs at a given time due to Energy conversion. The fact has been taken into account that in this type of internal combustion engines the energy conversion occurs first in the combustion chambers and in the spaces between the blade of the turbine engine. It was assumed that in the combustion...
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Possibilities of heat transfer augmentation in heat exchangers with minichannels for marine applications
PublikacjaIn the paper, new trends in development of microchannel heat exchangers are presented. The exchangers developed in this way can be applied in marine applications. Main attention was focused on heat exchangers design with reduced size of passages namely based on microchannels. In our opinion future development of high power heat exchangers will be based on networks micro heat exchangers.
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Diagnosing marine turbine engines through energy characteristics of their flow section
PublikacjaThe aim of the performed research was to develop of diagnostic method of the flow section of a marine turbine combustion engine based on the level of delamination of its energy characteristics. The here adopted diagnostic model provides for a formulation of the evaluation of the technical conditions based on the measurements of the parameters of the thermodynamic medium in the characteristic control cross-sections of the engine...
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Detection of corrosion process in marine environment by means of acoustic emission technique
PublikacjaW pracy przedstawiono możliwość detekcji procesu korozyjnego nieniszczącą metodą emisji akustycznej konstrukcji metalowych pracujących w środowisku wody morskiej. Pewną alternatywą wobec technik elektrochemicznych w monitorowaniu korozji zaproponowano nieniszczącą technikę emisji akustycznej. Emisja akustyczna znana jako zjawisko fizyczne i technika pomiarowa znalazły zastosowanie w detekcji korozji obiektów morskich. W związku...
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Patryk Ziółkowski dr inż.
OsobyAdiunkt na Politechnice Gdańskiej. Brał udział w projektach międzynarodowych, w tym projektach dla Ministerstwa Transportu stanu Alabama (2015), jest także laureatem grantu Fundacji Kościuszkowskiej na prowadzanie badań w USA, który zrealizował w 2018 roku. Ekspert w dziedzinie sztucznej inteligencji. Jego główny obszar zainteresowań badawczych stanowi zastosowanie sztucznej inteligencji w Inżynierii Lądowej. Prowadzi projekty...
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The Method of Selecting the Interval of Functional Tests Taking into Account Economic Aspects and Legal Requirements
PublikacjaThe article discusses the problem of choosing the optimal frequency of functional tests, taking into account the reliability and law requirements, but also the impact of business aspects in the company. The subject of functional test interval is well described for purposes of the process industry. Unfortunately, this is not the case for the machinery safety functions with low demand mode. This is followed by a presentation of the...
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Olgun Aydin Dr
OsobyOlgun Aydin finished his PhD by publishing a thesis about Deep Neural Networks. He works as a Senior Data Scientist in PwC Poland, gives lectures in Gdansk University of Technology in Poland and member of WhyR? Foundation. Olgun is a very big fan of R and author of the book called “R Web Scraping Quick Start Guide” , two video courses are called “Deep Dive into Statistical Modelling using R” and “Applied Machine Learning and Deep...
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Koncepcja poprawy jakości docierania elementów cienkościennych na docierarce jednotarczowej = Conception of quality improvement of thin-walled elements lapping done on single-disk lapping machine
PublikacjaPrzedstawiono problem zapewnienia prawidłowych warunków współpracy przedmiotu obrabianego i narzędzia tarczowego w czasie docierania płaskich elementów cienkościennych. Omówiono sposób dociążania elementów podczas obróbki oraz wytrzymałościowy model układu.
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Joint workshop on Multimodal Interaction and Related Machine Learning Algorithms (now ICMI-MLMI)
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Michał Wasilczuk prof. dr hab. inż.
OsobyMichał Wasilczuk, absolwent Wydziału Budowy Maszyn Politechniki Gdańskiej (1986), a obecnie profesor zwyczajny na Wydziale Mechanicznym PG i kierownik Katedry Konstrukcji Maszyn i Pojazdów od początku swojej działalności naukowej zajmuje się hydrodynamicznymi łożyskami wzdłużnymi oraz, szerzej inżynierią łożyskowania, w ramach zespołu naukowego stworzonego przez doc. Olgierda Olszewskiego. Od kilkunastu lat zespół specjalizuje...
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Vaccine versus infection – COVID-19-related loss of training time in elite athletes
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The Impact of a Single Educational Lecture on the Vaccine Confidence among Pregnant Women and Young Mothers
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Application of matching pursuit based method to identify sources of time-vary magnetic field
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Better Late Than Never: Predictors of Delayed COVID-19 Vaccine Uptake in Poland
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A Regular Expression Matching Application with Configurable Data Intensity for Testing Heterogeneous HPC Systems
PublikacjaModern High Performance Computing (HPC) systems are becoming increasingly heterogeneous in terms of utilized hardware, as well as software solutions. The problems, that we wish to efficiently solve using those systems have different complexity, not only considering magnitude, but also the type of complexity: computation, data or communication intensity. Developing new mechanisms for dealing with those complexities or choosing an...
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Bio-inspired Decisional DNA in Machinas and other Man-made Systems: The Way Forward
PublikacjaArtificial bio-inspired intelligent techniques and systems supporting smart, knowledge-based solutions of real world problems which are currently researched very extensively by research teams around the world, have enormous potential to enhance automation of decision making and problem solving for a number of diverse areas including design, manufacturing, Information Technology (IT), social communities of practice, and economics...
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Space-mapping-based design flow of miniaturized broadband matching transformer with perforated metallization
PublikacjaA fast design procedure of unconventional passive components has been presented and experimentally validated on the basis of a wideband microstrip four-section matching transformer (50:6 OHm). A classic impedance matching circuit has been miniaturized by means of compact microstrip resonant cells (CMRCs) leading to a considerable length reduction (34%) together with minor degradation in its performance. The spacemapping-based design...
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On reliability assessment of ship machinery system in different autonomy degree; A Bayesian-based approach
PublikacjaAnalyzing the reliability of autonomous ships has recently attracted attention mainly due to epistemic uncertainty (lack of knowledge) integrated with automatic operations in the maritime sector. The advent of new random failures with unrecognized failure patterns in autonomous ship operations requires a comprehensive reliability assessment specifically aiming at estimating the time in which the ship can be trusted to be left unattended....
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Propagation in the Open Cylindrical Guide of Arbitrary Cross Section With the Use of Field Matching Method
PublikacjaA simple solution to propagation problem in open waveguides and dielectric fibers of arbitrary convex cross section is presented. The idea of the analysis is based on the direct field matching technique involving the usage of the field projection at the boundary on a fixed set of orthogonal basis functions. A complex root tracing algorithm is utilized to find the propagation coefficients of the investigated guides. Different convex...
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Resonance microstrip structure with patch of arbitrary convex geometry with the use of field matching technique
PublikacjaAn analysis of the resonance frequency problem of planar microstrip structure with patch of arbitrary convex geometry is presented. A full-wave analysis is employed utilizing a combination of Galerkin’s moment method and field matching technique. In this approach, a field matching technique is adopted to calculate the patch surface current densities, and next the method of moments is utilized to calculate resonance frequencies...
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Scattering From a Cylindrical Object of Arbitrary Cross Section With the Use of Field Matching Method
PublikacjaA simple and intuitive solution to scattering problems in shielded and open structures is presented. The main idea of the analysis is based on the direct field matching technique involving the usage of projection of the fields at the boundary on a fixed set of orthogonal basis functions. Different convex shapes and various obstacle materials are considered to verify the validity of the method in open and closed structures. The...
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Uczenie maszynowe do samoorganizacji systemów rozproszonych w zastosowaniach gospodarczych
PublikacjaW pracy omówiono uczenie maszynowe do samoorganizacji systemów rozproszonych w zastosowaniach gospodarczych ze szczególnym uwzględnieniem sieci neuronowych do predykcji finansowych oraz szacowania ratingu przedsiębiorstw. Oprócz sieci neuronowych, istotną rolę w przygotowaniu i testowaniu informatycznych systemów finansowych może pełnić programowanie genetyczne. Z tego powodu omówiono uczenie maszynowe w aplikacjach konstruowanych...
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Alhassan Ali Ahmed
OsobyAlhassan Ali Ahmed BSc of pharmacy, MSc in Bioinformatics and Biotechnology, and currently doing his PhD in Bioinformatics and Machine Learning. Alhassan has considerable experience in the pharmaceutical industry as he worked before in different positions such as; Community pharmacist, Medical advisor, Antibiotics production specialist, Quality assurance specialist, Key account manager for Immunotherapeutic medications, and currently,...
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The Effectiveness of Using a Pretrained Deep Learning Neural Networks for Object Classification in Underwater Video
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Edu Inspiracje WZiE: Active Learning, czyli o mocy aktywnego przetwarzania informacji
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Prediction of Sorption Processes Using the Deep Learning Methods (Long Short-Term Memory)
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Deep learning model for automated assessment of lexical stress of non-native english speakers
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Experimental Evaluation of the Agent-Based Population Learning Algorithm for the Cluster-Based Instance Selection
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COMPARATIVE ANALYSIS OF COPING STRATEGIES WITH STRESS OF STUDENTS IN DIFFERENT LEARNING CONDITIONS DURING THE PANDEMIC
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Urban Food Self-Production in the Perspective of Social Learning Theory: Empowering Self-Sustainability
PublikacjaUrban food production is becoming an increasingly significant topic in the context of climate change and food security. Conducting research on this subject is becoming an essential element of urban development, deepening knowledge regarding the benefits, challenges, and potential for the development of urban agriculture as an alternative form of food production. Responding to this need, this monograph presents the results of...
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DentalSegmentator: Robust open source deep learning-based CT and CBCT image segmentation
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An integrated e-learning services management system providing HD videoconferencing and CAA services
PublikacjaIn this paper we present a novel e-learning services management system, designed to provide highly modifiable platform for various e-learning tools, able to fulfill its function in any network connectivity conditions (including no connectivity scenario). The system can scale from very simple setup (adequate for servicing a single exercise) to a large, distributed solution fit to support an enterprise. Strictly modular architecture...
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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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User -friendly E-learning Platform: a Case Study of a Design Thinking Approach Use
PublikacjaE-learning systems are very popular means to support the teaching process today. These systems are mainly used by universities as well as by commercial training centres. We analysed several popular e-learning platforms used in Polish universities and find them very unfriendly for the users. For this reason, the authors began the work on the creation of a new system that would be not only useful, but also usable for students, teachers...
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WEB-CAM AS A MEANS OF INFORMATION ABOUT EMOTIONAL ATTEMPT OF STUDENTS IN THE PROCESS OF DISTANT LEARNING
PublikacjaNew methods in education become more popular nowadays. Distant learning is a good example when teacher and student meet in virtual environment. Because interaction in this virtual world might be complicated it seems necessary to assure as much methods of conforming that student is still engaged in the process of learning as it is possible. We would like to present assumption that by means of web-cam we will be able to track facial...
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Reinforcement Learning Algorithm and FDTD-based Simulation Applied to Schroeder Diffuser Design Optimization
PublikacjaThe aim of this paper is to propose a novel approach to the algorithmic design of Schroeder acoustic diffusers employing a deep learning optimization algorithm and a fitness function based on a computer simulation of the propagation of acoustic waves. The deep learning method employed for the research is a deep policy gradient algorithm. It is used as a tool for carrying out a sequential optimization process the goal of which is...
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Optimizing Medical Personnel Speech Recognition Models Using Speech Synthesis and Reinforcement Learning
PublikacjaText-to-Speech synthesis (TTS) can be used to generate training data for building Automatic Speech Recognition models (ASR). Access to medical speech data is because it is sensitive data that is difficult to obtain for privacy reasons; TTS can help expand the data set. Speech can be synthesized by mimicking different accents, dialects, and speaking styles that may occur in a medical language. Reinforcement Learning (RL), in the...
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An Adaptive Network Model for a Double Bias Perspective on Learning from Mistakes within Organizations
PublikacjaAlthough making mistakes is a crucial part of learning, it is still often being avoided in companies as it is considered as a shameful incident. This goes hand in hand with a mindset of a boss who dominantly believes that mistakes usually have negative consequences and therefore avoids them by only accepting simple tasks. Thus, there is no mechanism to learn from mistakes. Employees working for and being influenced by such a boss...
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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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Fusion-based Representation Learning Model for Multimode User-generated Social Network Content
PublikacjaAs mobile networks and APPs are developed, user-generated content (UGC), which includes multi-source heterogeneous data like user reviews, tags, scores, images, and videos, has become an essential basis for improving the quality of personalized services. Due to the multi-source heterogeneous nature of the data, big data fusion offers both promise and drawbacks. With the rise of mobile networks and applications, UGC, which includes...
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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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Automated detection of pronunciation errors in non-native English speech employing deep learning
PublikacjaDespite significant advances in recent years, the existing Computer-Assisted Pronunciation Training (CAPT) methods detect pronunciation errors with a relatively low accuracy (precision of 60% at 40%-80% recall). This Ph.D. work proposes novel deep learning methods for detecting pronunciation errors in non-native (L2) English speech, outperforming the state-of-the-art method in AUC metric (Area under the Curve) by 41%, i.e., from...
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Deep learning techniques for biometric security: A systematic review of presentation attack detection systems
PublikacjaBiometric technology, including finger vein, fingerprint, iris, and face recognition, is widely used to enhance security in various devices. In the past decade, significant progress has been made in improving biometric sys- tems, thanks to advancements in deep convolutional neural networks (DCNN) and computer vision (CV), along with large-scale training datasets. However, these systems have become targets of various attacks, with...
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Data-Driven Surrogate-Assisted Optimization of Metamaterial-Based Filtenna Using Deep Learning
PublikacjaIn this work, a computationally efficient method based on data driven surrogate models is pro-posed for the design optimization procedure of a Frequency Selective Surface (FSS)-based filtering antenna (Filtenna). A Filtenna acts as a as module that simultaneously pre-filters unwanted sig-nals, and enhances the desired signals at the operating frequency. However, due to a typically large number of design variables of FSS unit elements,...