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- Publikacje 1461 wyników po odfiltrowaniu
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- Osoby 69 wyników po odfiltrowaniu
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Wyniki wyszukiwania dla: train neural networks
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A Method for Optimising the Blade Profile in Kaplan Turbine
PublikacjaThis paper introduces a method of blade profile optimisation for Kaplan-type turbines, based on modelling the interaction between rotor and stator blades. Rotor and stator blade geometry is described mathematically by means of a midline curve and thickness distribution. Genetic algorithms are then used to find a global optimum that minimises the loss coefficient. This allows for variety of possible blade shapes and configurations....
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BIG DATA SIGNIFICANCE IN REMOTE MEDICAL DIAGNOSTICS BASED ON DEEP LEARNING TECHNIQUES
PublikacjaIn this paper we discuss the evaluation of neural networks in accordance with medical image classification and analysis. We also summarize the existing databases with images which could be used for training deep models that can be later utilized in remote home-based health care systems. In particular, we propose methods for remote video-based estimation of patient vital signs and other health-related parameters. Additionally, potential...
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Selection of Features for Multimodal Vocalic Segments Classification
PublikacjaEnglish speech recognition experiments are presented employing both: audio signal and Facial Motion Capture (FMC) recordings. The principal aim of the study was to evaluate the influence of feature vector dimension reduction for the accuracy of vocalic segments classification employing neural networks. Several parameter reduction strategies were adopted, namely: Extremely Randomized Trees, Principal Component Analysis and Recursive...
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General concept of reduction process for big data obtained by interferometric methods
PublikacjaInterferometric sonar systems apply the phase content of the sonar signal to measure the angle of a wave front returned from the seafloor or from a target. It collect a big data – datasets that are so large or complex that traditional data processing application software is inadequate to deal with them. The recording a large number of data is associated with the difficulty of their efficient use. So data have to be reduced. The main...
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Sławomir Gajewski dr inż.
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Problems of modelling toxic compounds emitted by a marine internal combustion engine in unsteady states
PublikacjaContemporary engine tests are performed based on the theory of experiment. The available versions of programmes used for analysing experimental data make frequent use of the multiple regression model, which enables examining effects and interactions between input model parameters and a single output variable. The use of multi-equation models provides more freedom in analysing the measured results, as those models enable simultaneous...
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Simulating Power Generation from Photovoltaics in the Polish Power System Based on Ground Meteorological Measurements—First Tests Based on Transmission System Operator Data
PublikacjaThe Polish power system is undergoing a slow process of transformation from coal to one that is renewables dominated. Although coal will remain a fundamental fuel in the coming years, the recent upsurge in installed capacity of photovoltaic (PV) systems should draw significant attention. Owning to the fact that the Polish Transmission System Operator recently published the PV hourly generation time series in this article, we aim...
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Paweł Czarnul dr hab. inż.
OsobyPaweł Czarnul uzyskał stopień doktora habilitowanego w dziedzinie nauk technicznych w dyscyplinie informatyka w roku 2015 zaś stopień doktora nauk technicznych w zakresie informatyki(z wyróżnieniem) nadany przez Radę Wydziału Elektroniki, Telekomunikacji i Informatyki Politechniki Gdańskiej w roku 2003. Dziedziny jego zainteresowań obejmują: przetwarzanie równoległei rozproszone w tym programowanie równoległe na klastrach obliczeniowych,...
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DYNAMIC ANALYSIS OF THE RAILWAY BRIDGES IN POLAND WITH REGARDS TO HIGH-SPEED TRAINS PASSAGE ADJUSTMENT
PublikacjaThe dynamic analysis of the railway bridge in Tczew was carried out in the article as an example of such bridges adaptation suitability to handle high-speed trains. Calculations of railway bridges are greatly complicated and labor-consuming. The bridge model and a rolling stock passage simulation were developed in the SOFISTIK software. Three types of elements were used for the correct mapping of the structure in the calculation...
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Urban Railway within the Linear Urban Structure: the Case Study of Perm, Russia
PublikacjaThe paper analyses the ten years’ experience of Perm to develop its system of the urban train trying to reveal the reasons for its modest performance and decline in the passenger traffic. The authors show how the Urban Train fits within the city urban structure and eval uate the potential of the Urban Train to become a feasible solution to the problem of connecting the periphery with the city centre. Furthermore,...
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Małgorzata Gajewska dr inż.
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THE ROLE OF INFERENCE IN MOBILE MEDICAL APPLICATION DESIGN
PublikacjaIn the early 21st century, artificial intelligence began to be used to process medical information. However, before this happened, predictive models used in healthcare could only consider a limited number of variables, and only in properly structured and organised medical data. Today, advanced tools based on machine learning techniques - which, using artificial neural networks, can explore extremely complex relationships - and...
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Signal Processing in the Investigation of Two-phase Liquid-gas Flow by Gamma-ray Absorption
Publikacjan this paper, the use of the gamma-absorption method applied in the investigation of the two-phase liquid-gas flow in the pipeline is described. An example of its application to the air transported by water in a horizontal pipeline is evaluated. In the measurements, Am-241 radioactive sources and probes with Nal (Tl) scintillation crystals have been used. The signals from the radiometric set were used to determine the velocity...
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Evaluating Performance and Accuracy Improvements for Attention-OCR
PublikacjaIn this paper we evaluated a set of potential improvements to the successful Attention-OCR architecture, designed to predict multiline text from unconstrained scenes in real-world images. We investigated the impact of several optimizations on model’s accuracy, including employing dynamic RNNs (Recurrent Neural Networks), scheduled sampling, BiLSTM (Bidirectional Long Short-Term Memory) and a modified attention model. BiLSTM was...
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Collaborative Data Acquisition and Learning Support
PublikacjaWith the constant development of neural networks, traditional algorithms relying on data structures lose their significance as more and more solutions are using AI rather than traditional algorithms. This in turn requires a lot of correctly annotated and informative data samples. In this paper, we propose a crowdsourcing based approach for data acquisition and tagging with support for Active Learning where the system acts as an...
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Advances in Neural Information Processing Systems (Advances in Neural Information Processing Systems [NIPS])
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Assessment of Emotional Expressions after Full-Face Transplantation
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Efkleidis Katsaros
OsobyEfklidis Katsaros received the B.Sc. degree in mathematics from the Aristotle University of Thessaloniki, Greece, in 2016, and the M.Sc. degree (cum laude) in data science: statistical science from Leiden University, The Netherlands, in 2019. He is currently pursuing the Ph.D. degree in deep video multi-task learning with the Department of Biomedical Engineering, Gdańsk University of Technology, Poland. Since 2020, he has been...
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Supramolecular structures formed by 2-aminopyridine derivatives. Part I. Hydrogenbonding networks via N-H...N interactions and the conformational polymorphism of N,N´-bis(2-piridyl)aryldiamines
PublikacjaOtrzymano serię N,N´-bis(2-pirydylo)arylodiamin w postaci monokryształów. Zgodnie z oczekiwaniami, powstawały dwie odmiany polimorficzne. Forma EE z układem wiązań R22(8) figuruje jako jednowymiarowe taśmy. Stwierdzono, że ugrupowanie 2-aminopirydylowe stanowi synton supramolekularny za pomocą którego można projektować struktury w ciele stałym. Właściwości tego syntonu były badane z wykorzystaniem metod dyfrakcyjnych oraz spektroskopii...
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Musical Instrument Identification Using Deep Learning Approach
PublikacjaThe work aims to propose a novel approach for automatically identifying all instruments present in an audio excerpt using sets of individual convolutional neural networks (CNNs) per tested instrument. The paper starts with a review of tasks related to musical instrument identification. It focuses on tasks performed, input type, algorithms employed, and metrics used. The paper starts with the background presentation, i.e., metadata...
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Effect of Pendolino high-speed rail on the structure of buildings located the proximity of the railway tracks
PublikacjaThe following research focuses on the dynamic analysis of the impact of the high-speed train inducted vibrations on the structures located near railway tracks. The office complex chosen as the subject of calculations is located in the northern part of Poland, in Gdańsk, in the proximity of Pendolino, the high speed train route. The high speed trains are the response for the growing needs for more efficient railway system. However...
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Application of gas chromatographic data and 2D molecular descriptors for accurate global mobility potential prediction
PublikacjaMobility is a key feature affecting the environmental fate, which is of particular importance in the case of persistent organic pollutants (POPs) and emerging pollutants (EPs). In this study, the global mobility classification artificial neural networks-based models employing GC retention times (RT) and 2D molecular descriptors were constructed and validated. The high usability of RT was confirmed based on the feature selection...
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Study of Statistical Text Representation Methods for Performance Improvement of a Hierarchical Attention Network
PublikacjaTo effectively process textual data, many approaches have been proposed to create text representations. The transformation of a text into a form of numbers that can be computed using computers is crucial for further applications in downstream tasks such as document classification, document summarization, and so forth. In our work, we study the quality of text representations using statistical methods and compare them to approaches...
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International Conference on Neural Information Processing
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Efficiency comparison of selected endoscopic video analysis algorithms
PublikacjaIn the paper, selected image analysis algorithms were examined and compared in the task of identifying informative frames, blurry frames, colorectal cancer and healthy tissue on endoscopic videos. In order to standardize the tests, the algorithms were modified by removing from them parts responsible for the classification, and replacing them with Support Vector Machines and Artificial Neural Networks. The tests were performed in...
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Collective citizens' behavior modelling with support of the Internet of Things and Big Data
PublikacjaIn this paper, collective human behaviors are modelled by a development of Big Data mining related to the Internet of Things. Some studies under MapReduce architectures have been carried out to improve an efficiency of Big Data mining. Intelligent agents in data mining have been analyzed for smart city systems, as well as data mining has been described by genetic programming. Furthermore, artificial neural networks have been discussed...
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Artificial intelligence support for disease detection in wireless capsule endoscopy images of human large bowel
PublikacjaIn the work the chosen algorithms of disease recognition in endoscopy images were described and compared for theirs efficiency. The algorithms were estimated with regard to utility for application in computer system's support for digestive system's diagnostics. Estimations were achieved in an advanced testing environment, which was built with use of the large collection of endoscopy movies received from Medical University in Gdańsk....
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Special techniques and future perspectives: Simultaneous macro- and micro-electrode recordings
PublikacjaThere are many approaches to studying the inner workings of the brain and its highly interconnected circuits. One can look at the global activity in different brain structures using non-invasive technologies like positron emission tomography (PET) or functional magnetic resonance imaging (fMRI), which measure physiological changes, e.g. in the glucose uptake or blood flow. These can be very effectively used to localize active patches...
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Optimal edge-coloring with edge rate constraints
PublikacjaWe consider the problem of covering the edges of a graph by a sequence of matchings subject to the constraint that each edge e appears in at least a given fraction r(e) of the matchings. Although it can be determined in polynomial time whether such a sequence of matchings exists or not [Grötschel et al., Combinatorica (1981), 169–197], we show that several questions about the length of the sequence are computationally intractable....
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On the complexity of distributed graph coloring with local minimality constraints
PublikacjaArtykuł traktuje o zachłannym kolorowaniu grafów w modelu rozproszonym. Omówiono algorytmy rozproszone, dające w wyniku pokolorowanie spełniające warunki dla pokolorowań sekwencyjnych typu S oraz Largest-First (LF). Udowodniono również, że każda rozproszona implementacja algorytmu S wymaga co najmniej Omega(log n / log log n) rund, a algorytmu LF co najmniej Omega (n^{1/2}) rund, gdzie n oznacza liczbę wierzchołków grafu.
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SNDlib 1.0—Survivable Network Design Library
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Complexity of a classical flow restoration problem
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On the complexity of resilient network design
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Toward Fast Calculation of Communication Paths for Resilient Routing
PublikacjaUtilization of alternate communication paths is a common technique to provide protection of transmission against failures of network nodes/links. However, a noticeable delay is encountered when calculating the relevant sets of disjoint paths using the available algorithms (e.g., using Bhandari’s approach). This, in turn, may have a serious impact on the ability of a network to serve dynamic demands...
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Deep learning approach on surface EEG based Brain Computer Interface
PublikacjaIn this work we analysed the application of con-volutional neural networks in motor imagery classification for the Brain Computer Interface (BCI) purposes. To increase the accuracy of classification we proposed the solution that combines the Common Spatial Pattern (CSP) with convolutional network (ConvNet). The electroencephalography (EEG) is one of the modalities we try to use for controlling the prosthetic arm. Therefor in this...
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Chemometrics for Selection, Prediction, and Classification of Sustainable Solutions for Green Chemistry—A Review
PublikacjaIn this review, we present the applications of chemometric techniques for green and sustainable chemistry. The techniques, such as cluster analysis, principal component analysis, artificial neural networks, and multivariate ranking techniques, are applied for dealing with missing data, grouping or classification purposes, selection of green material, or processes. The areas of application are mainly finding sustainable solutions...
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Shape Optimisation of Kaplan Turbine Blades Using Genetic Algorithms
PublikacjaThis monograph is a comprehensive guide to a method of blade profile optimisation for Kaplan-type turbines. This method is based on modelling the interaction between rotor and stator blades. Additionally, the shape of the draft tube is investigated. The influence of the periodic boundary condition vs. full geometry is also discussed. Evolutionary algorithms (EA) are used as an optimisation method together with artificial neural...
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ANN for human pose estimation in low resolution depth images
PublikacjaThe paper presents an approach to localize human body joints in 3D coordinates based on a single low resolution depth image. First a framework to generate a database of 80k realistic depth images from a 3D body model is described. Then data preprocessing and normalization procedure, and DNN and MLP artificial neural networks architectures and training are presented. The robustness against camera distance and image noise is analysed....
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Comparison of selected electroencephalographic signal classification methods
PublikacjaA variety of methods exists for electroencephalographic (EEG) signals classification. In this paper, we briefly review selected methods developed for such a purpose. First, a short description of the EEG signal characteristics is shown. Then, a comparison between the selected EEG signal classification methods, based on the overview of research studies on this topic, is presented. Examples of methods included in the study are: Artificial...
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Magdalena Młynarczuk dr inż.
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Vehicle Dynamics - L-15/C-15/L-15/P-15, Design and Production Engineering, WIMiO, undergraduate studies, engineering studies, full-time (stationary) studies, 2021/2022, se06, (M:320383W0), summer semester 2023/2024
Kursy OnlineModuł przedmiotów wybieralnych, MiBM, I stopień, specjalność w j. angielskim: Design and Production Engineering (DaPE), semestr 6?, (przedmiot dla Chińczyków), Lecture: Throttle by tyred wheel: slip rolling, rolling with tyre strain, vertical and lateral surface reactions, traction, energetic looses, forces in contact path. Drugs of movement: rolling, air, gradient, inertia, cornering and towing. Forces ant torques acting to vehicle...
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Paweł Rościszewski dr inż.
OsobyPaweł Rościszewski received his PhD in Computer Science at Gdańsk University of Technology in 2018 based on PhD thesis entitled: "Optimization of hybrid parallel application execution in heterogeneous high performance computing systems considering execution time and power consumption". Currently, he is an Assistant Professor at the Faculty of Electronics, Telecommunications and Informatics, Gdańsk University of Technology, Poland....
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Andrzej Marczak dr inż.
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Macroeconomic Reports - Nowy
Kursy OnlineThis course intends to teach and train students in their analytical skills. Students are supposed to search data and information through international databases and then, using various analytical techniques, prepare a macroeconomic report in selected topic.
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Examining Classifiers Applied to Static Hand Gesture Recognition in Novel Sound Mixing System
PublikacjaThe main objective of the chapter is to present the methodology and results of examining various classifiers (Nearest Neighbor-like algorithm with non-nested generalization (NNge), Naive Bayes, C4.5 (J48), Random Tree, Random Forests, Artificial Neural Networks (Multilayer Perceptron), Support Vector Machine (SVM) used for static gesture recognition. A problem of effective gesture recognition is outlined in the context of the system...
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Music Mood Visualization Using Self-Organizing Maps
PublikacjaDue to an increasing amount of music being made available in digital form in the Internet, an automatic organization of music is sought. The paper presents an approach to graphical representation of mood of songs based on Self-Organizing Maps. Parameters describing mood of music are proposed and calculated and then analyzed employing correlation with mood dimensions based on the Multidimensional Scaling. A map is created in which...
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Agnieszka Czapiewska dr inż.
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Sensor Networks
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Marek Kubale prof. dr hab. inż.
OsobyDetails concerning: Qualifications, Experiences, Editorial boards, Ph.D. theses supervised, Books, and Recent articles can be found at http://eti.pg.edu.pl/katedra-algorytmow-i-modelowania-systemow/Marek_KubaleGoogle ScholarSylwetka prof. Marka Kubalego Prof. Marek Kubale pracuje na Wydziale ETI Politechniki Gdańskiej nieprzerwanie od roku 1969. W tym czasie napisał ponad 150 prac naukowych, w tym ponad 40 z listy JCR. Ponadto...
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Marcin Narloch dr inż.
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