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Search results for: stacked machine learning
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Prevention of resonance oscillations in gear mechanisms using non-circular gears
PublicationOne of the main disadvantages of gear mechanisms is the occurrence of noise and vibrations. This study investigated the applicability of non-circular gears for preventing resonance oscillations in gear mechanisms. The influence of a small deviation of the gear centrodes from the nominal circles on kinematic and oscillatory characteristics was analysed. It was shown that a larger deviation results in a smaller resonance amplitude...
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Artificial Neural Networks as an architectural design tool- generating new detail forms based on the Roman Corinthian order capital
PublicationThe following paper presents the results of the research in the field of the machine learning, investigating the scope of application of the artificial neural networks algorithms as a tool in architectural design. The computational experiment was held using the backward propagation of errors method of training the artificial neural network, which was trained based on the geometry of the details of the Roman Corinthian order capital....
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From Linear Classifier to Convolutional Neural Network for Hand Pose Recognition
PublicationRecently gathered image datasets and the new capabilities of high-performance computing systems have allowed developing new artificial neural network models and training algorithms. Using the new machine learning models, computer vision tasks can be accomplished based on the raw values of image pixels instead of specific features. The principle of operation of deep neural networks resembles more and more what we believe to be happening...
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Lessons learned from developing an Industry 4.0 mobile process management system supported by Artificial Intelligence
PublicationResearch, development and innovation (RDI) projects are undertaken in order to improve existing, or develop new, more efficient products and services. Moreover, the goal of innovation is to produce new knowledge through research, and disseminating it through education and training. In this line of thinking, this paper reports and discusses the lessons learned from the undertaken project, regarding three areas: machine learning...
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Wykorzystanie metody FMEA w kształtowaniu umiejętności projektowania technologii części maszyn = application of the FMEA method for skills development of machine parts technology desing
PublicationPrzedstawiono sposób wykorzystania metody FMEA w kształtowaniu umiejętności projektowania technologii części maszyn. Podano wytyczne ogólne i etapy analizy procesu i konstrukcji. Zamieszczono przykład analizy technologii dwustronnej dźwigni spawanej w produkcji małoseryjnej.
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International Journal of Continuing Engineering Education and Lifelong Learning
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International Journal of Computer-Assisted Language Learning and Teaching
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International Journal of Web-Based Learning and Teaching Technologies
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International Journal for Research on Service-Learning and Community Engagement
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Socioeconomic and gender inequalities in home learning during the COVID-19 pandemic: examining the roles of the home environment, parent supervision, and educational provisions
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IEEE Transactions on Human-Machine Systems
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Comparative Analysis of Text Representation Methods Using Classification
PublicationIn our work, we review and empirically evaluate five different raw methods of text representation that allow automatic processing of Wikipedia articles. The main contribution of the article—evaluation of approaches to text representation for machine learning tasks—indicates that the text representation is fundamental for achieving good categorization results. The analysis of the representation methods creates a baseline that cannot...
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Book Review
PublicationActing over the last three decades as an Editor and Associate Editor for a number of international journals in the general area of cybernetics and AI, as well as a Chair and Co-Chair of numerous conferences in this field, I have had the exciting opportunity to closely witness and to be actively engaged in the stimulating research area of machine learning and its important augmentation with deep learning techniques and technologies. From...
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Machine Translation Summit
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Machine Vision Applications
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E-Learning as a Factor Optimizing the Amount of Work Time Devoted to Preparing an Exam for Medical Program Students during the COVID-19 Epidemic Situation
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THE EFFECT OF ALTERNATIVE CUTTER PATHS ON FLATNESS DEVIATIONS IN THE FACE MILLING OF ALUMINUM PLATE PARTS
PublicationIn this paper the relationships between the alternative machining paths and flatness deviations of the aluminum plate part, were presented. The flatness tolerance of the main surface of the plate part has crucial meaning due to the assembly requirement of piezoelectric elements on the radiator. The aluminum bodies under investigation are the base part of the radiators with crimped feathers for the train industry. The surface of...
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Michał Wasilczuk prof. dr hab. inż.
PeopleMichał Wasilczuk received his M.Sc. (1986), Ph.D. (1994) and D.Sc. (2004) from the Gdansk University of Technology. In 2016 was nominated Professor Currently he is a Full Professor and Head of the Department of Machine Design and Automotive Engineering at the Faculty of Mechanical Engineers at GUT Bearing systems and tribology are the main fields of his scientific and engineering interest - starting from the Ph.D. devoted to...
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The Neural Knowledge DNA Based Smart Internet of Things
PublicationABSTRACT The Internet of Things (IoT) has gained significant attention from industry as well as academia during the past decade. Smartness, however, remains a substantial challenge for IoT applications. Recent advances in networked sensor technologies, computing, and machine learning have made it possible for building new smart IoT applications. In this paper, we propose a novel approach: the Neural Knowledge DNA based Smart Internet...
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DEEP CONVOLUTIONAL NEURAL NETWORKS AS A DECISION SUPPORT TOOL IN MEDICAL PROBLEMS – MALIGNANT MELANOMA CASE STUDY
PublicationThe 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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Koncepcja poprawy jakości docierania elementów cienkościennych na docierarce jednotarczowej = Conception of quality improvement of thin-walled elements lapping done on single-disk lapping machine
PublicationPrzedstawiono problem zapewnienia prawidłowych warunków współpracy przedmiotu obrabianego i narzędzia tarczowego w czasie docierania płaskich elementów cienkościennych. Omówiono sposób dociążania elementów podczas obróbki oraz wytrzymałościowy model układu.
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Dawid Zieliński dr inż.
PeopleDawid Zieliński uzyskał tytuł magistra inżyniera w 2017 roku na Wydziale Mechanicznych Politechniki Gdańskiej, kończąc kierunek: Mechanika i Budowa Maszyn, specjalność: Technologia Maszyn i Komputerowe Wspomaganie Produkcji. W okresie 2016-17 studiował na Uniwersytecie Technicznym w Berlinie (Technische Universität Berlin – TU Berlin) oraz pracował w instytucie naukowym – Institut für Werkzeugmaschinen und Fabrikbetrieb (IWF) Technische...
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When Neural Networks Meet Decisional DNA: A Promising New Perspective for Knowledge Representation and Sharing
PublicationABSTRACT In this article, we introduce a novel concept combining neural network technology and Decisional DNA for knowledge representation and sharing. Instead of using traditional machine learning and knowledge discovery methods, this approach explores the way of knowledge extraction through deep learning processes based on a domain’s past decisional events captured by Decisional DNA. We compare our approach with kNN (k-nearest...
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Comparative analysis of spectral and cepstral feature extraction techniques for phoneme modelling
PublicationPhoneme parameter extraction framework based on spectral and cepstral parameters is proposed. Using this framework, the phoneme signal is divided into frames and Hamming window is used. The performances are evaluated for recognition of Lithuanian vowel and semivowel phonemes. Different feature sets without noise as well as at different level of noise are considered. Two classical machine learning methods (Naive Bayes and Support...
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Language Learning Journal (Formerly: British Journal of Language Teaching)
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Learning and Teaching-The International Journal of Higher Education in the Social Sciences
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International Journal of Practice-Based Learning in Health and Social Care
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Wpływ falistości pierścienia ślizgowego na rozpływ prądu w zestyku ślizgowym maszyny synchronicznej = Influence of slip-ring waviness on current distribution in the sliding contact of a synchronous machine
PublicationZestyk ślizgowy maszyny synchronicznej średniej i dużej mocy zawiera na ogół szereg równolegle pracujących szczotek na każdym z pierścieni. Szczotki znajdują się w oprawkach szczotkowych rozmieszczonych przestrzennie wzdłuż obwodu pierścienia. To sprawia, że pracują one w tej samej chwili czasowej na różnych fragmentach pierścienia ślizgowego. Nierównomierny rozpływ prądu może spowodować nadmierne obciążenie niektórych szczotek....
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Experience-Oriented Knowledge Management for Internet of Things
PublicationIn this paper, we propose a novel approach for knowledge management in Internet of Things. By utilizing Decisional DNA and deep learning technologies, our approach enables Internet of Things of experiential knowledge discovery, representation, reuse, and sharing among each other. Rather than using traditional machine learning and knowledge discovery methods, this approach focuses on capturing domain’s decisional events via Decisional...
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Using Moodle as a Solution to Interdisciplinary E-collaboration Issues
PublicationRapid technological development in recent years has contributed to numerous changes in many areas of life, including education and communication. Establishing interdisciplinary collaboration brings many benefits, however, it is often associated with numerous problems and inconveniences, as well as the need of constant improvement, lifelong learning, professional development (CPD) and finding an effective way of information transferring....
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Interactive Learning Environments
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International Conference on Machine Vision
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Mechatronics and Machine Vision in Practice
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Medical Image Segmentation Using Deep Semantic-based Methods: A Review of Techniques, Applications and Emerging Trends
PublicationSemantic-based segmentation (Semseg) methods play an essential part in medical imaging analysis to improve the diagnostic process. In Semseg technique, every pixel of an image is classified into an instance, where each class is corresponded by an instance. In particular, the semantic segmentation can be used by many medical experts in the domain of radiology, ophthalmologists, dermatologist, and image-guided radiotherapy. The authors...
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How high-tech solutions support the fight against IUU and ghost fishing: a review of innovative approaches, methods, and trends
PublicationIllegal, Unreported, and Unregulated fishing is a major threat to human food supply and marine ecosystem health. Not only is it a cause of significant economic loss but also its effects have serious long-term environmental implications, such as overfishing and ocean pollution. The beginning of the fight against this problem dates since the early 2000s. From that time, a number of approaches and methods have been developed and reported....
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A Comprehensive Analysis of Deep Neural-Based Cerebral Microbleeds Detection System
PublicationMachine learning-based systems are gaining interest in the field of medicine, mostly in medical imaging and diagnosis. In this paper, we address the problem of automatic cerebral microbleeds (CMB) detection in magnetic resonance images. It is challenging due to difficulty in distinguishing a true CMB from its mimics, however, if successfully solved it would streamline the radiologists work. To deal with this complex three-dimensional...
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Are Pair Trading Strategies Profitable During COVID-19 Period?
PublicationPair trading strategy is a well-known profitable strategy in stock, forex, and commodity markets. As most of the world stock markets declined during COVID-19 period, therefore this study is going to observe whether this strategy is still profitable after COVID-19 pandemic. One of the powerful algorithms of DBSCAN under the umbrella of unsupervised machine learning is applied and three clusters were formed by using market and accounting...
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Izabela Mironowicz dr hab. inż. arch.
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THE ROLE OF INFERENCE IN MOBILE MEDICAL APPLICATION DESIGN
PublicationIn 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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Webquest- dobra praktyka w e-Learningu
PublicationW dobie informatyzacji i pokonywania barier wdrażania e-technologii na uczelniach wyższych uważa się, że jedną z najczęściej stosowanych aktywizujących technik nauczania wśród nauczycieli akademickich jest metoda projektu (ang. project-based learning). W niniejszym opracowaniu proponuje się zastosowanie w procesie edukacji na wyższej uczelni, metody webquest. Jest ona dużo rzadziej stosowana w praktyce. Opracowano ją w oparciu...
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Predicting the Purchase of Electricity Prices for Renewable Energy Sources Based on Polish Power Grids Data Using Deep Learning Models for Controlling Small Hybrid PV Microinstallations
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Evaluating the Use of Edge Devices for Detection and Tracking of Vehicles in Smart City Environment
PublicationThis paper introduces a Smart City solution designed to run on edge devices, leveraging NVIDIA's DeepStream SDK for efficient urban surveillance. We evaluate five object-tracking approaches, using YOLO as the baseline detector and integrating three Nvidia DeepStream trackers: IOU, NvSORT, and NvDCF. Additionally, we propose a custom tracker based on Optical Flow and Kalman filtering. The presented approach combines advanced machine...
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Workshop on Logic and Learning
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Algorithmic Learning Theory
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Conference on Learning Theory (Annual Conference on Computational Learning Theory)
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Introduction to the ONDM 2022 special issue
PublicationThis JOCN special issue contains extended versions of selected papers presented at the 26th International Conference on Optical Network Design and Modeling (ONDM 2022), which took place 16–19 May 2022 at Warsaw University of Technology, Warsaw, Poland. The topics covered by the papers represent trends in optical networking research: application of machine learning to network management, cross-layer network performance optimization,...
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Internet Journal on E-learning (Formerly : International Journal of Educational Telecommunications)
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TRWAŁOŚĆ PROJEKTU ERASMUS+ SP4CE - STUDIUM PRZYPADKU
PublicationProjekt ERASMUS+ Partnerstwo Strategiczne na Rzecz Kreatywności i Przedsiębiorczości (ang. Strategic Partnership for Creativity and Entrepreneurship - SP4CE) dotyczył wdrażania i upowszechniania innowacyjnych rozwiązań wzmacniających współpracę europejską w dziedzinie kształcenia i szkolenia zawodowego. Działania projektowe były związane z promowaniem innowacyjnych praktyk w edukacji oraz szkoleniach poprzez wspieranie spersonalizowanych...
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Granulometric analysis of dry sawdust from the sawing process on the frame sawing machine PRW15M = Granulometrická analýza suchej piliny z procesu pílenia borovicového dreva na rámovej píle PRW-15M
PublicationW artykule przedstawiono wyniki analizy granulometrycznej trocin otrzymanych podczas procesu przecinania drewna sosnowego na pilarce ramowej PRW15M. Wielkość otrzymanych trocin miesciła się w zakresie od 84,7 µm do 15,2 mm. Z punktu widzenia kształtu trociny średniej wielkości d>125µm są swym kształtem zbliżone do włókien drzewnych. Z kolei, drobne frakcje d<125µm mają kształt sześcienny. Ponadto, wzrost prędkości posuwu powoduje...
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Study of Multi-Class Classification Algorithms’ Performance on Highly Imbalanced Network Intrusion Datasets
PublicationThis paper is devoted to the problem of class imbalance in machine learning, focusing on the intrusion detection of rare classes in computer networks. The problem of class imbalance occurs when one class heavily outnumbers examples from the other classes. In this paper, we are particularly interested in classifiers, as pattern recognition and anomaly detection could be solved as a classification problem. As still a major part of...