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Wyniki wyszukiwania dla: MULTI-TASK LEARNING
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Dynamics Conscious Approach to Tribometer Design and Tribo-testing
PublikacjaIn the paper findings are discussed on the issue of dynamic characteristics of a tribometer as a factor influencing the result of the tribological experiment. An advanced approach to tribo-testing is attempted with integrated dynamic analysis of the tribometer and the sliding pair. The fundamental idea is explored of the tribometer being regarded as any machine in which friction is inflicted with all the resulting consequences...
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Looking For Motivation. How to Keep Students’ Software Projects from Ending up on the Shelf?
PublikacjaIT specialists in the business environment work in teams according to the established methodology and using the established toolkit. From the university’s point of view, preparing IT students to work in such an environment is a challenging task, as it requires either cooperation with business or the simulation of similar conditions in the university environment. Participation of students in real projects can provide them with the...
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Ship Dynamic Positioning Based on Nonlinear Model Predictive Control
PublikacjaThe presented work explores the simulation test results of using nonlinear model predictive control algorithm for ship dynamic positioning. In the optimization task, a goal function with a penalty was proposed with a variable prediction step. The results of the proposed control algorithm were compared with backstepping and PID. The effect of estimation accuracy on the control quality with the implemented algorithms was investigated....
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On the problem of optimised allocation of water quality sensors and actuators in DWDS
PublikacjaThe problems of water quality sensors and actuators placement in drinking water distribution systems (DWDSs) are addressed as separate, primarily. However, against the background of control systems theory, the nature of DWDSs dynamics indicates that these both problems are interdependent and impact the design of related water quality monitoring and control structures and algorithms. The research work presented in this paper is...
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Embedded Representations of Wikipedia Categories
PublikacjaIn this paper, we present an approach to building neural representations of the Wikipedia category graph. We test four different methods and examine the neural embeddings in terms of preservation of graphs edges, neighborhood coverage in representation space, and their influence on the results of a task predicting parent of two categories. The main contribution of this paper is application of neural representations for improving the...
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Machine Learning and Deep Learning Methods for Fast and Accurate Assessment of Transthoracic Echocardiogram Image Quality
PublikacjaHigh-quality echocardiogram images are the cornerstone of accurate and reliable measurements of the heart. Therefore, this study aimed to develop, validate and compare machine learning and deep learning algorithms for accurate and automated assessment of transthoracic echocardiogram image quality. In total, 4090 single-frame two-dimensional transthoracic echocardiogram...
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Refurbishment of a historical building - design issues
PublikacjaOver a 10-year modernization of the main building of Gdansk University of Technology is coming to the end. The ever increasing number of students requires not only the development of the campus with new facility buildings, also the existing buildings are subject to adaptation and modernization. In addition to high-impact solutions, as restoring the former glory of the building (reconstruction of the clock tower), or introducing...
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Long Distance Geographically Distributed InfiniBand Based Computing
PublikacjaCollaboration between multiple computing centres, referred as federated computing is becom- ing important pillar of High Performance Computing (HPC) and will be one of its key components in the future. To test technical possibilities of future collaboration using 100 Gb optic fiber link (Connection was 900 km in length with 9 ms RTT time) we prepared two scenarios of operation. In the first one, Interdisciplinary Centre for Mathematical...
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Limiting distribution of the three-state semi-Markov model of technical state transitions of ship power plant machines and its applicability in operational decision-making.
PublikacjaThe article presents the three-state semi-Markov model of the process {W(t): t 0} of state transitions of a ship power plant machine, with the following interpretation of these states: s1 – state of full serviceability, s2 – state of partial serviceability, and s3 – state of unserviceability. These states are precisely defined for the ship main engine (ME). A hypothesis is proposed which explains the possibility of application...
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Multimedia industrial and medical applications supported by machine learning
PublikacjaThis article outlines a keynote paper presented at the Intelligent DecisionTechnologies conference providing a part of the KES Multi-theme Conference “Smart Digital Futures” organized in Rome on June 14–16, 2023. It briefly discusses projects related to traffic control using developed intelligent traffic signs and diagnosing the health of wind turbine mechanisms and multimodal biometric authentication for banking branches to provide...
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Agnieszka Landowska dr hab. inż.
OsobyUkończyła studia na dwóch kierunkach: Finanse i bankowość na Uniwersytecie Gdańskim oraz Informatyka na WETI Politechniki Gdańskiej. Od 2000 roku jest związana z Politechniką Gdańską. W 2006 roku uzyskała stopień doktora w dziedzinie nauk technicznych, a w roku 2019 stopień doktora habilitowanego. Aktualnie jej praca naukowa dotyczy zagadnień interakcji człowiek-komputer oraz informatyki afektywnej (ang. affective computing), która...
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Neural networks and deep learning
PublikacjaIn this chapter we will provide the general and fundamental background related to Neural Networks and Deep Learning techniques. Specifically, we divide the fundamentals of deep learning in three parts, the first one introduces Deep Feed Forward Networks and the main training algorithms in the context of optimization. The second part covers Convolutional Neural Networks (CNN) and discusses their main advantages and shortcomings...
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Free randomness amplification using bipartite chain correlations
PublikacjaA direct analysis of the task of randomness amplification from Santha-Vazirani sources using the violation of the chained Bell inequality is performed in terms of the convex combination of no-signaling boxes required to simulate quantum violation of the inequality. This analysis is used to find the exact threshold value of the initial randomness parameter from which perfect randomness can be extracted in the asymptotic limit of...
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Influence of image transformations and quality degradations on SURF detector efficiency
PublikacjaA method for task-oriented examination of SURF keypoint detector accuracy is presented in the paper. It consists of generating test images, based on a given exemplar, processed by affine transformations: random rotation and scaling, and varying degree of degradations: darkening, blurring, noising, and compression. Details of applied degradation procedure are presented, followed by essentials of SURF-based images matching. A distance...
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Recognizing emotions on the basis of keystroke dynamics
PublikacjaThe article describes a research on recognizing emotional states on the basis of keystroke dynamics. An overview of various studies and applications of emotion recognition based on data coming from keyboard is presented. Then, the idea of an experiment is presented, i.e. the way of collecting and labeling training data, extracting features and finally training classifiers. Different classification approaches are proposed to be...
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Integrated membrane bioreactors modelling: A review on new comprehensive modelling framework
PublikacjaIntegrated Membrane Bioreactor (MBR) models, combination of biological and physical models, have been representing powerful tools for the accomplishment of high environmental sustainability. This paper, produced by the International Water Association (IWA) Task Group on Membrane Modelling and Control, reviews the state-of-the-art, identifying gaps for future researches, and proposes a new integrated MBR modelling framework. In...
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Inteligentne zarządzanie usługami chmurowymi
PublikacjaRozwój chmur obliczeniowych stanowi wyzwanie dla nowych efektywnych metod zarządzania zasobami chmurowymi, zwłaszcza, że oprócz usług typu SaaS rozwija się nowe kategorie usług jak obliczenia brzegowe czy wielochmurowe. W pracy zaproponowano ogólny model zarządzania usługami oraz efektywne procedury alokacji zasobów. Podkreślono potrzebę oszacowania parametrów zasobów chmury by zapewnić wykonanie żądanych usług. Przedstawiono również...
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Approximation task decomposition for artificial neural network.
PublikacjaW pracy przedstawiono wpływ dekompozycji zadania na czasochłonność projektowania oraz dokładność i szybkość obliczeń sztucznej sieci neuronowej wykorzystanej do rozwiązania rzeczywistego problemu technicznego, którego matematyczny model był znany. Celem obliczeń prowadzonych przez sieć neuronową było określenie wartości współczynnika przepływu m na podstawie znajomości wartości: przewodności dźwiękowej C i średnicy przewodu d (a...
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EM-Driven Multi-Objective Optimization of Antenna Structures in Multi-Dimensional Design Spaces
PublikacjaFeasible multi-objective optimization of antenna structures is presented. An initial set of Pareto optimal solutions is found using a multi-objective evolutionary algorithm (MOEA) working with a fast surrogate antenna model obtained by kriging interpolation of coarse-discretization EM simulation data. To make the surrogate construction computationally feasible in multi-dimensional design space, the space subset containing non-dominated...
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A new multi-process collaborative architecture for time series classification
PublikacjaTime series classification (TSC) is the problem of categorizing time series data by using machine learning techniques. Its applications vary from cybersecurity and health care to remote sensing and human activity recognition. In this paper, we propose a novel multi-process collaborative architecture for TSC. The propositioned method amalgamates multi-head convolutional neural networks and capsule mechanism. In addition to the discovery...
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Multi agent grid systems
PublikacjaThis chapter presents an idea of merging grid and volunteer systemswith multi agent systems. It gives some basics concerning multi agentsystem and the most followed standard. Some deliberations concerningsuch an existing systems were made in order to finally present possibilities of introducing agents into the Comcute system.
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Blended Learning in Teaching Safety of Electrical Installations
PublikacjaBlended learning becomes more commonly used in teaching information technology or other subjects, which involve practice in computer laboratories. In case of subjects with no access to computer rooms blended learning supports lecturing and teaching classes e.g. interactive lessons. The article presents the use of blended learning forms in Gdansk University of Technology in teaching the subject of Safety of Electrical Installations....
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Sesja jubileuszowa z okazji 25-lecia TASK
WydarzeniaZ okazji jubileuszu Rada Użytkowników TASK przy wsparciu CI TASK organizuje sesję „25-lecie porozumienia TASK”.
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Henryk Krawczyk prof. dr hab. inż.
OsobyDyscyplina naukowa: informatyka Sprawował urząd rektora od 2008 do 2016. Urodził się 20 maja 1946 r. w Dybowie. Studia wyższe ukończył w 1969 r. na Wydziale Elektroniki Politechniki Gdańskiej, uzyskując tytuł magistra inżyniera w zakresie informatyki. W latach 1969–1972 pracował w Przemysłowym Instytucie Telekomunikacji. W 1972 r. rozpoczął pracę na Wydziale Elektroniki Politechniki Gdańskiej, gdzie w 1976 r. uzyskał doktorat,...
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Low-Cost Multi-Objective Optimization Yagi-Uda Antenna in Multi-Dimensional Parameter Space
PublikacjaA surrogate-based technique for fast multi-objective optimization of a multi-parameter planar Yagi-Uda antenna structure is presented. The proposed method utilizes response surface approximation (RSA) models constructed using training samples obtained from evaluation of the low-fidelity antenna model. Utilization of the RSA models allowsfor fast determination of the best possible trade-offs between conflicting objectives in multi-objective...
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Multi-state multi-reference Møller-Plesset second-order perturbation theory for molecular calculations
PublikacjaThis work presents multi‐state multi‐reference Møller–Plesset second‐order perturbation theory as a variant of multi‐reference perturbation theory to treat electron correlation in molecules. An effective Hamiltonian is constructed from the first‐order wave operator to treat several strongly interacting electronic states simultaneously. The wave operator is obtained by solving the generalized Bloch equation within the first‐order...
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Zastosowanie algorytmu regulacji DMC z pomiarem wartości wielkości sterującej do sterowania blokiem wymienników ciepła
PublikacjaW artykule opisano zastosowanie zmodyfikowanego algorytmu regulacji predykcyjnej DMC do sterowania wybranym blokiem wymienników ciepła. Przedstawiono charakterystykę obiektu sterowania, specyficzne zadania stawiane układowi regulacji oraz sposób realizacji regulatora. Omówiono właściwości opracowanego układu regulacji i zaprezentowano wyniki jego działania.A modified DMC control algorithm application for control of heat exchanger...
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Optimised allocation of actuators for DWDS
PublikacjaThis paper addresses the problem of actuators’ allocation within networked structured system, namely allocation of disinfectant booster stations within Drinking Water Distribution System (DWDS), under receding horizon optimised control – Model Predictive Control (MPC) to be exact. The allocation task is kept within dynamic multiobjective optimisation framework. The MPC is defined as a single objective predictive operator. Two numerical...
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RECSYS CHALLENGE 2015: a BUY EVENT PREDICTION IN THE E-COMMERCE DOMAIN
PublikacjaIn this paper we present our approach to RecSys Challenge 2015. Given a set of e-commerce events, the task is to predict whether a user will buy something in the current session and, if yes, which of the item will be bought. We show that the data preparation and enrichment are very important in finding the solution for the challenge and that simple ideas and intuitions could lead to satisfactory results. We also show that simple...
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Innovative design of hybrid powered inland vessel
PublikacjaOne of the most demanding task for European countries is rational transportation system taking into account fuel efficient and ecological propulsion. The paper presents innovative design of hybrid powered inland vessel. The most important aspects regarding new design and technical solutions are being presented, including numerical and experimental research on hull form. Combined diesel-electric propulsion supported by solar panel...
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Uniform Model Interface for Assurance Case Integration with System Models
PublikacjaAssurance cases are developed and maintained in parallel with corresponding system models and therefore need to reference each other. Managing the correctness and consistency of interrelated safety argument and system models is essential for system dependability and is a nontrivial task. The model interface presented in this paper enables a uniform process of establishing and managing assurance case references to various types...
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Neurocontrolled Car Speed System
PublikacjaThe features of the synthesis of neural controllers for the car speed control system are considered in this article. The task of synthesis is to determine the weight coefficients of neural networks that provide the implementation of proportional and proportional-integralderivative control laws. The synthesis of controllers is based on an approach that uses a reversed model of the standard. A model of the car speed control system with...
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Towards semantic-rich word embeddings
PublikacjaIn recent years, word embeddings have been shown to improve the performance in NLP tasks such as syntactic parsing or sentiment analysis. While useful, they are problematic in representing ambiguous words with multiple meanings, since they keep a single representation for each word in the vocabulary. Constructing separate embeddings for meanings of ambiguous words could be useful for solving the Word Sense Disambiguation (WSD)...
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SEMANTIC ANALYSIS ALGORITHMS FOR KNOWLEDGE WORKERS SUPPORT
PublikacjaThe paper examines various aspects of text analysis application for knowledge worker’s activity realization. Conclusions are drawn about the relevance and importance of processing the non-structured textual information in order to increase knowledge worker’s efficiency, as well as their awareness in different branches of science. The paper considers the existing algorithms of texts semantic analysis as the sphere of documents topical...
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Desiging e-learning courses and distance learning (level 1. certified course)
Kursy Online -
Buried Object Characterization by Data-Driven Surrogates and Regression-Enabled Hyperbolic Signature Extraction
PublikacjaThis work addresses artificial-intelligence-based buried object characterization using FDTD-based electromagnetic simulation toolbox of a Ground Penetrating Radar (GPR) to generate B-scan data. In data collection, FDTD-based simulation tool, gprMax is used. The task is to estimate geophysical parameters of a cylindrical shape object of various radii, buried at different positions in the dry soil medium simultaneously and independently...
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Using LSTM networks to predict engine condition on large scale data processing framework
PublikacjaAs the Internet of Things technology is developing rapidly, companies have an ability to observe the health of engine components and constructed systems through collecting signals from sensors. According to output of IoT sensors, companies can build systems to predict the conditions of components. Practically the components are required to be maintained or replaced before the end of life in performing their assigned task. Predicting...
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Blended Learning Tasks 2
Kursy OnlineKurs dla Wydziału Mechanicznego
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Blended Learning Tasks 6
Kursy OnlineKurs dla Wydziału Architektury
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Deep Learning w Keras
Kursy OnlineKurs przeznaczony dla słuchaczy studiów podyplomowych Sztuczna inteligencja i automatyzacja procesów biznesowych w ujęciu praktycznym - edycja biznesowa.
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Blended Learning Tasks 4
Kursy Online -
Blended Learning Tasks 1
Kursy OnlineKurs dla Wydziału Mechanicznego
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Blended Learning Tasks 5
Kursy OnlineKurs dla ETI
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Blended Learning Tasks 3
Kursy OnlineKurs dla WILiŚ
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Edge-Computing based Secure E-learning Platforms
PublikacjaImplementation of Information and Communication Technologies (ICT) in E-Learning environments have brought up dramatic changes in the current educational sector. Distance learning, online learning, and networked learning are few examples that promote educational interaction between students, lecturers and learning communities. Although being an efficient form of real learning resource, online electronic resources are subject to...
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Federated Learning in Healthcare Industry: Mammography Case Study
PublikacjaThe paper focuses on the role of federated learning in a healthcare environment. The experimental setup involved different healthcare providers, each with their datasets. A comparison was made between training a deep learning model using traditional methods, where all the data is stored in one place, and using federated learning, where the data is distributed among the workers. The experiment aimed to identify possible challenges...
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Speech Analytics Based on Machine Learning
PublikacjaIn this chapter, the process of speech data preparation for machine learning is discussed in detail. Examples of speech analytics methods applied to phonemes and allophones are shown. Further, an approach to automatic phoneme recognition involving optimized parametrization and a classifier belonging to machine learning algorithms is discussed. Feature vectors are built on the basis of descriptors coming from the music information...
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Enhancing rheological muscle models with stochastic processes
PublikacjaPurpose: Biological musculoskeletal systems operate under variable conditions. Muscle stiffness, activation signals, and loads change during each movement. The presence of noise and different harmonic components in force production significantly influences the behaviour of the muscular system. Therefore, it is essential to consider these factors in numerical simulations. Methods: This study aims to develop a rheological mathematical...
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Software Factory project for enhancement of student experiential learning
PublikacjaProviding opportunities for students to work on real-world software development projects for real customers is critical to prepare students for the IT industry. Such projects help students to understand what they will face in the industry and experience real customer interaction and challenges in collaborative work. To provide this opportunity in an academic environment and enhance the learning and multicultural teamwork experience,...
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MULTI-OBJECTIVE OPTIMIZATION PROBLEM IN THE OptD-MULTI METHOD
PublikacjaNew measurement technologies, e.g. Light Detection And Ranging (LiDAR), generate very large datasets. In many cases, it is reasonable to reduce the number of measuring points, but in such a way that the datasets after reduction satisfy specific optimization criteria. For this purpose the Optimum Dataset (OptD) method proposed in [1] and [2] can be applied. The OptD method with the use of several optimization criteria is called...