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Wyniki wyszukiwania dla: DISTRIBUTED MACHINE LEARNING
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Influence of feed rate on the granularity and homogenity of oak sawdust obtained during the sawing process on the frame sawing machine PRW15M
PublikacjaOpisano wpływ prędkości posuwu na skład granulometryczny i jednorodność trocin dębowych otrzymanych podczas procesu przecinania na pilarce ramowej PRW15M. Wykazano, że otrzymane trociny mogą być wykorzystane w produkcji produktów drewnopochodnych w ilości 75% dla posuwu 0.36 m/min i 82% przy posuwie 1.67 m/min. Pozostałe trociny stanowią odpad.
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O wyszukiwaniu niepoprawnych pomiarów w systemach DCS obiektów energetycznych = On search for incorrect measurement results in distributed control systems (DCS) of power objects
PublikacjaPrzedyskutowano problem rozpoznawania degradacji mierników pomiarowych w systemach DCS dużych obiektów energetycznych, przy równoczesnym występowaniu degradacji eksploatacyjnej urządzeń składowych tych obiektów. Zastosowano sieć neuronową (SNN) o skokowych funkcjach przejścia. Zastosowana SNN wykazała wysoką jakość. Sprawdzono możliwości rozpoznawania obu typów degradacji występującej w zastosowaniu do tzw. degradacji dwukrotnych.
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Bilingual advantage? Literacy and phonological awareness in Polish-speaking early elementary school children learning English simultaneously
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Perceived technostress while learning a new mobile technology: Do individual differences and the way technology is presented matter?
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Night shifts as a learning experience among nursing students across Europe: Findings from a cross-sectional survey
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E-learning jako narzędzie wspierające kształcenie osób 50+. Rozważania w oparciu o projekt MAYDAY
PublikacjaRozdział przedstawia zalety i wady szkoleń e-learningowych ze szczególnym uwzględnieniem uczestników w wieku 50+, analizę szkolenia przeprowadzonego w ramach projektu MAYDAY oraz wytyczne i rekomendacje do tworzenia kursów e-learnignowych dla osób powyżej 50-go roku życia.
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Finite State Machine Based Modelling of Discrete Control Algorithm in LAD Diagram Language With Use of New Generation Engineering Software
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Adaptive Hounsfield Scale Windowing in Computed Tomography Liver Segmentation
PublikacjaIn computed tomography (CT) imaging, the Hounsfield Unit (HU) scale quantifies radiodensity, but its nonlinear nature across organs and lesions complicates machine learning analysis. This paper introduces an automated method for adaptive HU scale windowing in deep learning-based CT liver segmentation. We propose a new neural network layer that optimizes HU scale window parameters during training. Experiments on the Liver Tumor...
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Activation of Metabotropic Glutamate Receptor (mGlu2) and Muscarinic Receptors (M1, M4, and M5), Alone or in Combination, and Its Impact on the Acquisition and Retention of Learning in the Morris Water Maze, NMDA Expression and cGMP Synthesis
PublikacjaThe Morris water maze (MWM) is regarded as one of the most popular tests for detecting spatial memory in rodents. Long-term potentiation and cGMP synthesis seem to be among the crucial factors involved in this type of learning. Muscarinic (M1, M4, and M5 receptors) and metabotropic glutamate (mGlu) receptors are important targets in the search for antipsychotic drugs with the potency to treat cognitive disabilities associated with...
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Between therapy effect and false-positive result in animal experimentation
PublikacjaDespite the animal models’ complexity, researchers tend to reduce the number of animals in experiments for expenses and ethical concerns. This tendency makes the risk of false-positive results, as statistical significance, the primary criterion to validate findings, often fails if testing small samples. This study aims to highlight such risks using an example from experimental regenerative therapy and propose a machine-learning...
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Wykorzystanie modelu silnika indukcyjnego klatkowego do prądowej diagnostyki jego łożysk. Application of induction machine model for current diagnostics of bearings
PublikacjaW pracy podano widmo prądu stojana dla silnika normalnego oraz wprawianego w drgania o nastawianej częstotliwości. Drgania korpusu wirnika skutkują uginaniem się wirnika, co symuluje bicie wirnika od uszkodzenia łożysk. Podano też model matematyczny silnika, dopuszczający niecentryczność wirnika. Podano widmo prądu stojana przy pracy z wibracjami wirnika odwzorowującymi w pewnym przybliżeniu wibracje od uszkodzonych łożysk.
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Deep Learning-based Recalibration of the CUETO and EORTC Prediction Tools for Recurrence and Progression of Non–muscle-invasive Bladder Cancer
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E-LEARNING AND TEACHING STRATEGIES OF UNIVERSITY TEACHERS. A CASE STUDY IN THE TEACHING OF SPANISH AS A SECOND LANGUAGE IN SLOVAKIA, POLAND AND THE USA
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High-resolution synthesis of high-density breast mammograms: Application to improved fairness in deep learning based mass detection
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Predicting Compressive Strength of Cement-Stabilized Rammed Earth Based on SEM Images Using Computer Vision and Deep Learning
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Human Feedback and Knowledge Discovery: Towards Cognitive Systems Optimization
PublikacjaCurrent computer vision systems, especially those using machine learning techniques are data-hungry and frequently only perform well when dealing with patterns they have seen before. As an alternative, cognitive systems have become a focus of attention for applications that involve complex visual scenes, and in which conditions may vary. In theory, cognitive applications uses current machine learning algorithms, such as deep learning,...
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Analysis and evaluation of grouping methods for effective cutting tool operation
PublikacjaThis article presents the possibilities for using cluster analysis in the assignment of machine tools in automated manufacturing systems. Based on the similarity of manufacturing processes in the system, cutting tools have been grouped. The objective was to obtain groups of similar objects, which could potentially ensure the reduction of the frequency and time of setups, optimizing the maintenance of tool resources and improving...
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Review of the Complexity of Managing Big Data of the Internet of Things
PublikacjaTere is a growing awareness that the complexity of managing Big Data is one of the main challenges in the developing feld of the Internet of Tings (IoT). Complexity arises from several aspects of the Big Data life cycle, such as gathering data, storing them onto cloud servers, cleaning and integrating the data, a process involving the last advances in ontologies, such as Extensible Markup Language (XML) and Resource Description...
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Weighted Ensemble with one-class Classification and Over-sampling and Instance selection (WECOI): An approach for learning from imbalanced data streams
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E-learning przez Internet w szkolnictwie wyższym. Doświadczenia Szkoły Głównej Handlowej w Warszawie i Politechniki Gdańskiej.
PublikacjaOpisano cztery podstawowe rodzaje e-learningu, przedstawiono strukturę funkcjonalną systemów zarządzania nauczaniem na odległość i zarządzania treścią nauczania (ang. LMS, LCMS) oraz zaprezentowano doświadczenia Szkoły Głównej Handlowej w Warszawie i Politechniki Gdańskiej w nauczaniu na odległość.
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An automated learning model for twitter sentiment analysis using Ranger AdaBelief optimizer based Bidirectional Long Short Term Memory
PublikacjaSentiment analysis is an automated approach which is utilized in process of analysing textual data to describe public opinion. The sentiment analysis has major role in creating impact in the day-to-day life of individuals. However, a precise interpretation of text still relies as a major concern in classifying sentiment. So, this research introduced Bidirectional Long Short Term Memory with Ranger AdaBelief Optimizer (Bi-LSTM RAO)...
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BETWEEN IDEA AND INTERPRETATION - DESIGN PROCESS AUGMENTATION
PublikacjaThe following paper investigates the idea of reducing the human digital intervention to a minimum during the advanced design process. Augmenting the outcome attributes beyond the designer's capabilities by computational design methods, data collection, data computing and digital fabrication, altogether imitating the human design process. The primary technical goal of the research was verification of restrictions and abilities used...
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Relevance of the EU Structural Funds’ Allocation to the Needs of Combating Air Pollution in Poland. Analysis of the Operational Programmes of Regions Threatened With Critical Air Pollution from Distributed Energy Sources
PublikacjaRecent years, the European Environmental Agency, has been reporting air quality parameters in Poland, as the poorest among all the EU countries. Despite of adoption of the EU legislation on energy efficiency and energy performance of buildings, existing legal solutions occur insufficient in reducing air pollution in Polish regions. Lack of an effective schemes supporting complex thermal renovation of buildings, exchange of inefficient...
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Prevention of resonance oscillations in gear mechanisms using non-circular gears
PublikacjaOne 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
PublikacjaThe 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
PublikacjaRecently 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
PublikacjaResearch, 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
PublikacjaPrzedstawiono 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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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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Comparative Analysis of Text Representation Methods Using Classification
PublikacjaIn 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
PublikacjaActing 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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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
PublikacjaIn 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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t-SNE Highlights Phylogenetic and Temporal Patterns of SARS-CoV-2 Spike and Nucleocapsid Protein Evolution
PublikacjaWe propose applying t-distributed stochastic neighbor embedding to protein sequences of SARS-CoV-2 to construct, visualize and study the evolutionary space of the coronavirus. The basic idea is to explore the COVID-19 evolution space by using modern manifold learning techniques applied to evolutionary distances between variants. Evolutionary distances have been calculated based on the structures of the nucleocapsid and spike proteins.
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The Neural Knowledge DNA Based Smart Internet of Things
PublikacjaABSTRACT 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
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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Koncepcja poprawy jakości docierania elementów cienkościennych na docierarce jednotarczowej = Conception of quality improvement of thin-walled elements lapping done on single-disk lapping machine
PublikacjaPrzedstawiono 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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When Neural Networks Meet Decisional DNA: A Promising New Perspective for Knowledge Representation and Sharing
PublikacjaABSTRACT 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
PublikacjaPhoneme 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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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
PublikacjaZestyk 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
PublikacjaIn 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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Executing Multiple Simulations in the MERPSYS Environment
PublikacjaThe chapter investigates the steps necessary to perform a simulation instance in the MERPSYS environment and discusses potential limitations in case when vast numbers of simulations are required. An extended architecture is proposed which includes a JMS-based simulation queue and multiple distributed simulators, overcoming the potential bottlenecks. The chapter introduces also methods for preparing suites of multiple simulations...
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Using Moodle as a Solution to Interdisciplinary E-collaboration Issues
PublikacjaRapid 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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Medical Image Segmentation Using Deep Semantic-based Methods: A Review of Techniques, Applications and Emerging Trends
PublikacjaSemantic-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
PublikacjaIllegal, 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
PublikacjaMachine 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?
PublikacjaPair 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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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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Webquest- dobra praktyka w e-Learningu
PublikacjaW 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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