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Wyniki wyszukiwania dla: LEARNING BAYESIAN NETWORKS
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Communication Networks in the Service of the Environmental Monitoring
PublikacjaIn the paper selected issues relating to communication networks in the services of the environmental monitoring (EM) have been described. It is divided into three main parts: introduction, wire and wireless networks. At the beginning of the basic definitions were explained. The wire part focuses on a plain old telephone service (POTS), an integrated services digital network (ISDN), a digital subscriber line (DSL) and a fiber-optic...
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Machine Learning Applied to Aspirated and Non-Aspirated Allophone Classification—An Approach Based on Audio "Fingerprinting"
PublikacjaThe purpose of this study is to involve both Convolutional Neural Networks and a typical learning algorithm in the allophone classification process. A list of words including aspirated and non-aspirated allophones pronounced by native and non-native English speakers is recorded and then edited and analyzed. Allophones extracted from English speakers’ recordings are presented in the form of two-dimensional spectrogram images and...
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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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Explainable AI for Inspecting Adversarial Attacks on Deep Neural Networks
PublikacjaDeep Neural Networks (DNN) are state of the art algorithms for image classification. Although significant achievements and perspectives, deep neural networks and accompanying learning algorithms have some important challenges to tackle. However, it appears that it is relatively easy to attack and fool with well-designed input samples called adversarial examples. Adversarial perturba-tions are unnoticeable for humans. Such attacks...
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A Highly Scalable, Modular Architecture for Computer Aided Assessment e-Learning Systems
PublikacjaIn this chapter, the authors propose a novel e-learning system, dedicated strictly to knowledge assessment tasks. In its functioning it utilizes web-based technologies, but its design differs radically from currently popular e-learning solutions which rely mostly on thin-client architecture. The authors' research proved that such architecture, while well suited for didactic content distribution systems is ill-suited for knowledge...
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Road traffic can be predicted by machine learning equally effectively as by complex microscopic model
PublikacjaSince high-quality real data acquired from selected road sections are not always available, a traffic control solution can use data from software traffic simulators working offline. The results show that in contrast to microscopic traffic simulation, the algorithms employing neural networks can work in real-time, so they can be used, among others, to determine the speed displayed on variable message road signs. This paper describes...
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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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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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Cost minimization in wireless networks with a bounded and unbounded number of interfaces
PublikacjaPraca dotyczy problemu minimalizacji energii poprzez selektywne odłączanie urządzeń komunikacyjnych w wielointerfejsowych sieciach bezprzewodowych w taki sposób, by zapewnić realizację wymaganego grafu połączeń. Sformułowano problem optymalizacyjny, podano wyniki dotyczące jego trudności i zaproponowano algorytmy optymalizacyjne. Rozważono zarówno wariant, w którym liczba interfejsów komunikacyjnych jest parametrem stałym (narzuconym...
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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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Position Estimation in Mixed Indoor-Outdoor Environment Using Signals of Opportunity and Deep Learning Approach
PublikacjaTo improve the user's localization estimation in indoor and outdoor environment a novel radiolocalization system using deep learning dedicated to work both in indoor and outdoor environment is proposed. It is based on the radio signatures using radio signals of opportunity from LTE an WiFi networks. The measurements of channel state estimators from LTE network and from WiFi network are taken by using the developed application....
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The use and development of e-learning systems in educational projects
PublikacjaThe article introduces the problem of usage and development of e-learning systems among Polish universities. Easily accessible internet and IT development led to changes in education. Through the use of IT tools, e-learning has become an increasingly popular form of education. Presently, majority of Polish universities use an e-learning system of their own choosing designed to support the didactic processes. The goal of the article...
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Overview of Scalability and Reliability Problem in SDN Networks
PublikacjaIn the paper an overview of scalability and reliability in the SDN (Software Defined Networks) networks has been presented. Problems and limitations for guaranteeing scalability and reliability in SDN networks have been indicated. Known methods for assuring scalability and reliability in SDN networks have been described. Projects from research communities for resolving issues with scalability and reliability in SDN networks have...
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Affective computing and affective learning – methods, tools and prospects
PublikacjaEvery teacher knows that interest, active participation and motivation are important factors in the learning process. At the same time e-learning environments almost always address only the cognitive aspects of education. This paper provides a brief review of methods used for affect recognition, representation and processing as well as investigates how these methods may be used to address affective aspect of e-education. The paper...
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The reliability of tree and star networks
PublikacjaThis paper investigated the reliability of tree and star networks. Following measures of network reliability are assumed: the expected number of nodes, that can communicate with the central node; the expected number of node pairs, that are connected by a path through the central node; the expected number of node pairs communicating.
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Protection in elastic optical networks
PublikacjaIn this article, we analyze gains resulting from the use of EON architectures with special focus on transportation of cloud-ready and content-oriented traffic in the context of network resilience. EONs are a promising approach for future optical transport networks and, apart from improving the network spectral efficiency, bring such new capabilities as squeezed protection, which reduces resource requirements in failure scenarios....
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Bayesian estimation of the parameters in safely and reliability models for the subjective priors.
PublikacjaRozważono problem estymacji nieznanych charakterystyk niezawodnościowych za pomocą nieparametrycznych metod Bayesowskich. W wielu przypadkach opinie ekspertów są jedynym źródłem danych apriorycznych w modelach Bayesowskich. Celem uzyskania subiektywnych prawdopodobieństw apriorycznych zastosowano pewne metody ekspertowe. W oparciu o proces Dirichleta, który jest kluczowym pojęciem w teorii Fergusona, zostały skonstruowane...
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Big Data from Sensor Network via Internet of Things to Edge Deep Learning for Smart City
PublikacjaData from a physical world is sampled by sensor networks, and then streams of Big Data are sent to cloud hosts to support decision making by deep learning software. In a smart city, some tasks may be assigned to smart devices of the Internet of Things for performing edge computing. Besides, a part of workload of calculations can be transferred to the cloud hosts. This paper proposes benchmarks for division tasks between an edge...
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Blended-learning w nauczaniu przedmiotów nieinformatycznych
PublikacjaBlended-learning jest coraz powszechniej wykorzystywany w nauczaniu przedmiotów informatycznych lub innych przedmiotów, w których ćwiczenia realizowane są w laboratoriach komputerowych. W przypadku przedmiotów bez dostępu do sal komputerowych, blended-learning wspomaga prowadzenie wykładów i ćwiczeń poprzez np. lekcje interaktywne. Artykuł opisuje zastosowanie form blended-learning w realizacji laboratoriów z przedmiotu Bezpieczeństwo...
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Desiging e-learning courses and distance learning (level 1. certified course)
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Model of distributed learning objects repository for a heterogenic internet environment
PublikacjaW artykule wprowadzono pojęcie komponentu edukacyjnego jako rozszerzenie obiektu edukacyjnego o elementy zachowania (metody). Zaproponowane podejście jest zgodne z paradygmatem obiektowym. W oparciu o komponent edukacyjny zaprojektowano model budowy repozytorium materiałów edukacyjnych. Model ten jest oparty o usługi sieciowe i rejestry UDDI. Komponent edukacyjny oraz model repozytorium mogą znaleźć zastosowanie w konstrukcji zbiorów...
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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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Blended Learning Tasks 4
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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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Interpretable deep learning approach for classification of breast cancer - a comparative analysis of multiple instance learning models
PublikacjaBreast cancer is the most frequent female cancer. Its early diagnosis increases the chances of a complete cure for the patient. Suitably designed deep learning algorithms can be an excellent tool for quick screening analysis and support radiologists and oncologists in diagnosing breast cancer.The design of a deep learning-based system for automated breast cancer diagnosis is not easy due to the lack of annotated data, especially...
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Adrian Bekasiewicz dr hab. inż.
OsobyAdrian Bekasiewicz received the MSc, PhD, and DSc degrees in electronic engineering from Gdansk University of Technology, Poland, in 2011, 2016, and 2020, respectively. In 2014, he joined Engineering Optimization & Modeling Center where he held a Research Associate and a Postdoctoral Fellow positions, respectively. Currently, he is an Associate Professor with Gdansk University of Technology, Poland. His research interests include...
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THE UNSUSTAINABILITY OF PUBLIC-SECTOR ORGANIZATIONAL NETWORKS: A CASE STUDY OF VOLUNTARY COURT NETWORKS
PublikacjaPurpose: The purpose of this study is to identify the problem of sustainability of public-sector 12 organizational networks on the example of common courts and what it implies for further 13 research. Methodology: The study used qualitative research tools in the form of structured 14 interviews. Interviews were conducted with 36 presidents and directors of common courts. 15 After conducting and transcribing each interview, their...
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Affective Learning Manifesto – 10 Years Later
PublikacjaIn 2004 a group of affective computing researchers proclaimed a manifesto of affective learning that outlined the prospects and white spots of research at that time. Ten years passed by and affective computing developed many methods and tools for tracking human emotional states as well as models for affective systems construction. There are multiple examples of affective methods applications in Intelligent Tutoring Systems (ITS)....
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Learning design of a blended course in technical writing
PublikacjaBlending face-to-face classes with e-learning components can lead to a very successful outcome if the blend of approaches, methods, content, space, time, media and activities is carefully structured and approached from both the student’s and the tutor’s perspective. In order to blend synchronous and asynchronous e-learning activities with traditional ones, educators should make them inter-dependent and develop them according to...
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Predictions of cervical cancer identification by photonic method combined with machine learning
PublikacjaCervical cancer is one of the most commonly appearing cancers, which early diagnosis is of greatest importance. Unfortunately, many diagnoses are based on subjective opinions of doctors—to date, there is no general measurement method with a calibrated standard. The problem can be solved with the measurement system being a fusion of an optoelectronic sensor and machine learning algorithm to provide reliable assistance for doctors...
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Accurate Modeling of Frequency Selective Surfaces Using Fully-Connected Regression Model with Automated Architecture Determination and Parameter Selection Based on Bayesian Optimization
PublikacjaSurrogate modeling has become an important tool in the design of high-frequency structures. Although full-wave electromagnetic (EM) simulation tools provide an accurate account for the circuit characteristics and performance, they entail considerable computational expenditures. Replacing EM analysis by fast surrogates provides a way to accelerate the design procedures. Unfortunately, modeling of microwave passives is a challenging...
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Supply current signal and artificial neural networks in the induction motor bearings diagnostics
PublikacjaThis paper contains research results of the diagnostics of induction motor bearings based on measurement of the supply current with usage of artificial neural networks. Bearing failure amount is greater than 40% of all engine failures, which makes their damage-free operation crucial. Tests were performed on motors with intentionally made bearings defects. Chapter 2 introduces the concept of artificial neural networks. It presents...
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Exploiting Multi-Interface Networks: Connectivity and Cheapest Paths
PublikacjaRozważano zagadnienie minimalizacji energii w sieciach bezprzewodowych bez infrastruktury, w których niektóre węzły są wyposażone w więcej, niż jeden interfejs. W przyjętym modelu sieci podano nowe algorytmy przybliżone oraz wyniki dotyczące złożoności obliczeniowej dla dwóch problemów: aktywacji najtańszej spójnej podsieci spinającej oraz aktywacji ścieżki pomiędzy ustaloną parą węzłów.
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An efficient approach to optimization of semi‐stable routing in multicommodity flow networks
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Computer-assisted assessment of learning outcomes in the laboratory of metrology
PublikacjaIn the paper, didactic experience with broad and rapid continuous assessment of students’ knowledge, skills and competencies in the Laboratory of Metrology, which is an example of utilisation of assessment for learning, is presented. A learning management system was designed for manage, tracking, reporting of learning program and assessing learning outcomes. It has ability to provide with immediate feedback, which is used by the...
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How Machine Learning Contributes to Solve Acoustical Problems
PublikacjaMachine learning is the process of learning functional relationships between measured signals (called percepts in the artificial intelligence literature) and some output of interest. In some cases, we wish to learn very specific relationships from signals such as identifying the language of a speaker (e.g. Zissman, 1996) which has direct applications such as in call center routing or performing a music information retrieval task...
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Rearrangeability in multicast Clos networks is NP-complete
PublikacjaPrzestrajalność w polach Closa z połączeniami jeden do jeden jest problemem wielomianowym. W pracy pokazano, że w polach z połączeniami jeden do wiele problem ten jest NP zupełny.Three-stage elos networks are commutation networks with circuit switching. So far, graph theory has been very useful tool for solving issues related to these networks with unicast connections. This is so because if elos network is represented as a bipartite...
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Self-Supervised Learning to Increase the Performance of Skin Lesion Classification
PublikacjaTo successfully train a deep neural network, a large amount of human-labeled data is required. Unfortunately, in many areas, collecting and labeling data is a difficult and tedious task. Several ways have been developed to mitigate the problem associated with the shortage of data, the most common of which is transfer learning. However, in many cases, the use of transfer learning as the only remedy is insufficient. In this study,...
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Cooperative Data Transmission in Wireless Vehicular Networks
PublikacjaThe paper presents issues related to the cooperative transmission in wireless vehicular networks. Cooperative transmission involves the use of mobile terminals as relay stations to improve the transmission quality, improve network performance and reduce energy consumption. The paper presents the methods used to implement cooperative transmission and the types of cooperative networks.
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IET Networks
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NEURAL NETWORKS
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SOCIAL NETWORKS
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An Intelligent Approach to Short-Term Wind Power Prediction Using Deep Neural Networks
PublikacjaIn this paper, an intelligent approach to the Short-Term Wind Power Prediction (STWPP) problem is considered, with the use of various types of Deep Neural Networks (DNNs). The impact of the prediction time horizon length on accuracy, and the influence of temperature on prediction effectiveness have been analyzed. Three types of DNNs have been implemented and tested, including: CNN (Convolutional Neural Networks), GRU (Gated Recurrent...
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Analysis of the Capability of Deep Learning Algorithms for EEG-based Brain-Computer Interface Implementation
PublikacjaMachine learning models have received significant attention for their exceptional performance in classifying electroencephalography (EEG) data. They have proven to be highly effective in extracting intricate patterns and features from the raw signal data, thereby contributing to their success in EEG classification tasks. In this study, we explore the possibilities of utilizing contemporary machine learning algorithms in decoding...
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Optimization of Wireless Networks for Resilience to Adverse Weather Conditions
PublikacjaIn this chapter, we consider how adverse weather conditions such as rain or fog affect the performance of wireless networks, and how to optimize these networks so as to make them robust to these conditions. We first show how to analyze the weather conditions in order to make them useful for network optimization modelling. Using an example realistic network, we show how to optimize two types of wireless networks: free-space optical...
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Analysis of Learning Outcomes in Medical Education with the Use of Fuzzy Logic
PublikacjaThe national curricula of the EU member states are structured around learning outcomes, selected according to Bloom’s Taxonomy. The authors of this paper claim that using Bloom’s Taxonomy to phrase learning outcomes in medical education in terms of students’ achievements is difficult and unclear. This paper presents an efficient method of assessing course learning outcomes using Fuzzy Logic.