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Wyniki wyszukiwania dla: LEARNING BAYESIAN NETWORKS
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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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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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Desiging e-learning courses and distance learning (level 1. certified course)
Kursy Online -
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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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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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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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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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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An efficient approach to optimization of semi‐stable routing in multicommodity flow networks
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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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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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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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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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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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Game Theory Analysis of Bidding for a Construction Contract
PublikacjaThe authors are concerned with a bidding problem. There are two companies (P1 and P2) bidding for a highway construction project. In order to be more competitive, P1 considers buying a new gravel pit near the construction site. The basic cost of the pit is known to both companies. However, there is also an additional, hidden, cost (C) known only to P1. P2 is uncertain whether the hidden cost is C = 0 or C = x. P1 plans to bid for...
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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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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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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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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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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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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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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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IET Networks
Czasopisma -
NEURAL NETWORKS
Czasopisma -
SOCIAL NETWORKS
Czasopisma -
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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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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THE METHODS OF TEACHING / LEARNING STRUCTURAL MECHANICS
PublikacjaStructural mechanics is a key issue to study for engineers. A high rank and high social responsibility profession requires both a high graded and intuitive approach. The evolution of learning / teaching methodology follows the novel technical achievements of every decade. The aim remains the same: to produce a professional to perform advanced relevant analysis and safe, optimal structural design
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Active Learning on Ensemble Machine-Learning Model to Retrofit Buildings Under Seismic Mainshock-Aftershock Sequence
PublikacjaThis research presents an efficient computational method for retrofitting of buildings by employing an active learning-based ensemble machine learning (AL-Ensemble ML) approach developed in OpenSees, Python and MATLAB. The results of the study shows that the AL-Ensemble ML model provides the most accurate estimations of interstory drift (ID) and residual interstory drift (RID) for steel structures using a dataset of 2-, to 9-story...
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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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CRVG - a new model for wireless networks topology generation
PublikacjaThis paper presents a new model of wireless network topology generator. Its main advantage is the possibility of relatively sparse networks generation. Because no iteration is needed, the model can be used for massive generation of networks for testing. The topological properties of produced graphs place them in the class of scale free networks, resembling real ones.
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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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A novel approach exploiting properties of convolutional neural networks for vessel movement anomaly detection and classification
PublikacjaThe article concerns the automation of vessel movement anomaly detection for maritime and coastal traffic safety services. Deep Learning techniques, specifically Convolutional Neural Networks (CNNs), were used to solve this problem. Three variants of the datasets, containing samples of vessel traffic routes in relation to the prohibited area in the form of a grayscale image, were generated. 1458 convolutional neural networks with...
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DEEP CONVOLUTIONAL NEURAL NETWORKS AS A DECISION SUPPORT TOOL IN MEDICAL PROBLEMS – MALIGNANT MELANOMA CASE STUDY
PublikacjaThe paper presents utilization of one of the latest tool from the group of Machine learning techniques, namely Deep Convolutional Neural Networks (CNN), in process of decision making in selected medical problems. After the survey of the most successful applications of CNN in solving medical problems, the paper focuses on the very difficult problem of automatic analyses of the skin lesions. The authors propose the CNN structure...
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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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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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The networking of the justice system as part of public court networks
PublikacjaThe goal of this paper is to look at the organizational structure of the justice system and provide the answer to the basic question of the possible network relations, their force, and imapct. As part od the paper, I have defined public inetrorganisational court network, dividing them into regulatory inter-organisational networks nad voluntary inetrorganisational networks. Emphasis has also been placed on the benefits and threats...
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Statistical significance of displacements in heterogeneous control networks
PublikacjaThis paper proposes a modification of the classical process for evaluating the statistical significance of displacements in the case of heterogeneous (e.g. linear-angular) control networks established to deformation measurements and analysis. The basis for the proposed solution is the idea of local variance factors. The theoretical discussion was complemented with an example of its application on a simulated horizontal control...
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Electrical and noise responses of carbon nanotube networks enhanced by UV light for nitrogen dioxide sensing
Dane BadawczeNetworks consisting of randomly oriented carbon nanotubes (CNN) were investigated toward nitrogen dioxide detection by means of electrical and low-frequency noise measurements. UV-activation of CNN layers improved gas sensitivity and reduced the limit of detection, especially by employing 275 nm-LED. This data set includes DC resistance measurements...
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Analysis of Isocratic-Chromatographic-Retention Data using Bayesian Multilevel Modeling
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Maximum A Posteriori Bayesian Estimation of Chromatographic Parameters by Limited Number of Experiments
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Trust Management Method for Wireless Sensor Networks
PublikacjaA Wireless Sensor Network (WSN) is a network of spatially distributed autonomous sensors to monitor physical or environmental conditions, such as temperature, sound, pressure, etc. and to cooperatively pass their data to the main location. The first wireless network that bore any real resemblance to a modern WSN is the Sound Surveillance System (SOSUS), developed by the United States Military in the 1950s to detect and track Soviet...
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Exploring Neural Networks for Musical Instrument Identification in Polyphonic Audio
PublikacjaThe purpose of this paper is to introduce neural network-based methods that surpass state-of-the-art (SOTA) models, either by training faster or having simpler architecture, while maintaining comparable effectiveness in musical instrument identification in polyphonic music. Several approaches are presented, including two authors’ proposals, i.e., spiking neural networks (SNN) and a modular deep learning model named FMCNN (Fully...
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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.