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Search results for: CONTINUAL LEARNING · REPRESENTATION LEARNING
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Podejście nauczycieli akademickich do rozwoju narzędzi e-learningowych na wyższych uczelniach technicznych
PublicationPlatforma edukacyjna na uczelni wyższej stała się już standardem. Jest wyznacznikiem nowoczesno- ści danej uczelni. Wpływa na jej konkurencyjność. Mimo to, istnieje przekonanie że środowisko nauczycieli akademickich nie jest gotowe do akceptacji nowych środków nauczania. Postanowiono zbadać ten problem. Artykuł zawiera odpowiedź na pytanie jaki stosunek do metod e-nauczania panuje wśród nauczycieli akademickich, nie posiadających...
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Moduł Warsztaty - narzędzie w procesie edukacji na uczelni wyższej
PublicationObecnie istnieje bardzo szeroka gama narzędzi informatycznych, które wspierają proces edukacji przy wykorzystaniu internetu na uczelniach wyższych. Wśród nieodpłatnych narzędzi powszechnie znana jest platforma Moodle. W artykule zaprezentowano jeden z jej modułów – Warsztaty. Przedstawiono jego funkcjonalność. Opisano jego zalety i wady w nauczaniu łączącym techniki online i tradycyjne na uczelni wyższej (blended-learning). W artykule...
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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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Kształcenie ustawiczne – trendy w krajach regionu Morza Bałtyckiego
PublicationKwestie kształcenia ustawicznego i dostosowania kwalifikacji do potrzeb rynku pracy są przedmiotem dyskusji zarówno na szczeblu europejskim, jak i poszczególnych krajów. Działania administracji powinny zmierzać w kierunku określenia zapotrzebowania na określone umiejętności oraz aktywizacji społeczeństwa poprzez realizację idei uczenia się przez całe życie. Doświadczenia krajów skandynawskich dostarczają wielu przykładów dobrych...
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Improving css-KNN Classification Performance by Shifts in Training Data
PublicationThis paper presents a new approach to improve the performance of a css-k-NN classifier for categorization of text documents. The css-k-NN classifier (i.e., a threshold-based variation of a standard k-NN classifier we proposed in [1]) is a lazy-learning instance-based classifier. It does not have parameters associated with features and/or classes of objects, that would be optimized during off-line learning. In this paper we propose...
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Food Classification from Images Using a Neural Network Based Approach with NVIDIA Volta and Pascal GPUs
PublicationIn the paper we investigate the problem of food classification from images, for the Food-101 dataset extended with 31 additional food classes from Polish cuisine. We adopted transfer learning and firstly measured training times for models such as MobileNet, MobileNetV2, ResNet50, ResNet50V2, ResNet101, ResNet101V2, InceptionV3, InceptionResNetV2, Xception, NasNetMobile and DenseNet, for systems with NVIDIA Tesla V100 (Volta) and...
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Application of autoencoder to traffic noise analysis
PublicationThe aim of an autoencoder neural network is to transform the input data into a lower-dimensional code and then to reconstruct the output from this code representation. Applications of autoencoders to classifying sound events in the road traffic have not been found in the literature. The presented research aims to determine whether such an unsupervised learning method may be used for deploying classification algorithms applied to...
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Vehicle detector training with labels derived from background subtraction algorithms in video surveillance
PublicationVehicle detection in video from a miniature station- ary closed-circuit television (CCTV) camera is discussed in the paper. The camera provides one of components of the intelligent road sign developed in the project concerning the traffic control with the use of autonomous devices being developed. Modern Convolutional Neural Network (CNN) based detectors need big data input, usually demanding their manual labeling. In the presented...
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Identification of the Contamination Source Location in the Drinking Water Distribution System Based on the Neural Network Classifier
PublicationThe contamination ingression to the Water Distribution System (WDS) may have a major impact on the drinking water consumers health. In the case of the WDS contamination the data from the water quality sensors may be efficiently used for the appropriate disaster management. In this paper the methodology based on the Learning Vector Quantization (LVQ) neural network classifier for the identification of the contamination source location...
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Bewertung der qualität von online lernmodulen = Próba oceny jakości e-Lerningowych modułów online
PublicationW pracy dokonano klasyfikacji rozwiązań modułów (systemów) e-Learning wg. sposobu ich tworzenia (tj. systemy autorskie, komercyjne, otwarte, zamknięte, standardowe, niestandardowe), funkcjonalności, interaktywności, obciążania sieci. Przedstawiono również wybrane kryteria (tj. merytoryczne, dydaktyczne i multimedialne) oceny jakości modułów dostępnych online pod kątem ich wykorzystywania w systemach zdalnego nauczania. Na zakończenie...
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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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Hybrid Laboratory of Radio Communication With Online Simulators and Remote Access
PublicationContribution: Two toolsets for the remote teaching of radio communication laboratory classes: 1) online simulators for individual work of students and 2) a remote access system to laboratory workstations for group work. Initial assumptions and method of implementation of both tools are presented. Background: The COVID-19 pandemic has forced a change in teaching at all levels of education. The specificity of practical classes, such...
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Evolving neural network as a decision support system — Controller for a game of “2048” case study
PublicationThe paper proposes an approach to designing the neuro-genetic self-learning decision support system. The system is based on neural networks being adaptively learned by evolutionary mechanism, forming an evolved neural network. Presented learning algorithm enables for a selection of the neural network structure by establishing or removing of connections between the neurons, and then for a finding the beast suited values of the network...
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The Double Cognitive Bias of Mistakes: A Measurement Method
PublicationThere is no learning without mistakes. However, making mistakes among knowledge workers is s�ll seeing shameful. There is a clash between posi�ve a�tudes and beliefs regarding the power of gaining new (tacit) knowledge by ac�ng in new contexts and nega�ve a�tudes and beliefs toward accompanying mistakes that are sources of learning. These contradictory a�tudes create a bias that is doubled by the other shared solid belief...
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Poprawa jakości klasyfikacji głębokich sieci neuronowych poprzez optymalizację ich struktury i dwuetapowy proces uczenia
PublicationW pracy doktorskiej podjęto problem realizacji algorytmów głębokiego uczenia w warunkach deficytu danych uczących. Głównym celem było opracowanie podejścia optymalizującego strukturę sieci neuronowej oraz zastosowanie uczeniu dwuetapowym, w celu uzyskania mniejszych struktur, zachowując przy tym dokładności. Proponowane rozwiązania poddano testom na zadaniu klasyfikacji znamion skórnych na znamiona złośliwe i łagodne. W pierwszym...
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Flexible Knowledge–Vision–Integration Platform for Personal Protective Equipment Detection and Classification Using Hierarchical Convolutional Neural Networks and Active Leaning
PublicationThis work is part of an effort to develop of a Knowledge-Vision Integration Platform for Hazard Control (KVIP-HC) in industrial workplaces, adaptable to a wide range of industrial environments. The paper focuses on hazards resulted from the non-use of personal protective equipment (PPE). The objective is to test the capability of the platform to adapt to different industrial environments by simulating the process of randomly selecting...
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Graphical interface adaption for children to explain astronomy proportions and distances
PublicationMobile Science Center is a Polish project that seeks to bring astronomy knowledge to wider social groups through various applications. In its development it is necessary to design a graphical interface that explains a concept that is difficult to assimilate such as spatial proportions and distances. This paper develops a framework to create graphical representations that explain this learning to the target audience of children....
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How to Design Affect-aware Educational Systems – the AFFINT Process Approach
PublicationComputer systems, that support learning processes, can adapt to the needs and states of a learner. The adaptation might directly address the knowledge deficits and most tutoring systems apply an adaptable learning path of that kind. Apart from a preliminary knowledge state, there are more factors, that influence education effectiveness and among those there are fluctuating emotional states. The tutoring systems may recognize or...
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THRIVING AND JOB SATISFACTION IN MULTICULTURAL ENVIRONMENTS OF MNCS
PublicationPurpose of the article The aim of the paper is to analyze the relationship between thriving and job satisfaction in multicultural environments of multinational corporations (MNCs). Methodology/methods The quantitative cross-sectional study was conducted on the sample of 128 individuals from subsidiaries of various MNCs located in Poland involved in intercultural interactions. Scientific aim The aim of this study was to examine...
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Between therapy effect and false-positive result in animal experimentation
PublicationDespite 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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Concurrent Video Denoising and Deblurring for Dynamic Scenes
PublicationDynamic scene video deblurring is a challenging task due to the spatially variant blur inflicted by independently moving objects and camera shakes. Recent deep learning works bypass the ill-posedness of explicitly deriving the blur kernel by learning pixel-to-pixel mappings, which is commonly enhanced by larger region awareness. This is a difficult yet simplified scenario because noise is neglected when it is omnipresent in a wide...
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Analysis of Denoising Autoencoder Properties Through Misspelling Correction Task
PublicationThe paper analyzes some properties of denoising autoencoders using the problem of misspellings correction as an exemplary task. We evaluate the capacity of the network in its classical feed-forward form. We also propose a modification to the output layer of the net, which we called multi-softmax. Experiments show that the model trained with this output layer outperforms traditional network both in learning time and accuracy. We...
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Acquisition and indexing of RGB-D recordings for facial expressions and emotion recognition
PublicationIn this paper KinectRecorder comprehensive tool is described which provides for convenient and fast acquisition, indexing and storing of RGB-D video streams from Microsoft Kinect sensor. The application is especially useful as a supporting tool for creation of fully indexed databases of facial expressions and emotions that can be further used for learning and testing of emotion recognition algorithms for affect-aware applications....
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Benchmarking Deep Neural Network Training Using Multi- and Many-Core Processors
PublicationIn the paper we provide thorough benchmarking of deep neural network (DNN) training on modern multi- and many-core Intel processors in order to assess performance differences for various deep learning as well as parallel computing parameters. We present performance of DNN training for Alexnet, Googlenet, Googlenet_v2 as well as Resnet_50 for various engines used by the deep learning framework, for various batch sizes. Furthermore,...
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Transformational leadership for researcher’s innovativeness in the context of tacit knowledge and change adaptability
PublicationThis study explores how a learning culture supported by transformational leadership influences tacit knowledge sharing and change adaptability in higher education and how these relations impact this sector’s internal and external innovativeness. The empirical model was tested on a sample of 368 Polish scientific staff using the structural equation modeling (SEM) method. Then results were expanded by applying OLS regression using...
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Aktywności stymulujące refleksję w nauczaniu języka pisanego w wirtualnej klasie
PublicationThe paper aims to show how to engage students attending an online language course in various activities which by stimulating reflection enhance the learning process and result in better learning outcomes. By blending cognitivist, constructivist, constructionist and behavioural ideas, course developers and tutors can produce materials and use methods which satisfy the varied needs of adults who want to improve their writing skills....
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Uczenie się przez całe życie
PublicationW pracy przedstawiono genezę ustanowienia europejskiego obszaru uczenia się przez całe życie oraz podstawowe zasady Lifelong Learning. Omówiono krajowe uwarunkowania procesu LLL oraz walidację efektów uczenia się.
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Optimising approach to designing kernel PCA model for diagnosis purposes with and without a priori known data reflecting faulty states
PublicationFault detection plays an important role in advanced control of complex dynamic systems since precise information about system condition enables efficient control. Data driven methods of fault detection give the chance to monitor the plant state purely based on gathered measurements. However, they especially nonlinear, still suffer from a lack of efficient and effective learning methods. In this paper we propose the two stages learning...
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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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Gender as a Moderator of the Double Bias of Mistakes – Knowledge Culture and Knowledge Sharing Effects
PublicationThere is no learning without mistakes. The essence of the double bias of mistakes is the contradiction between an often-declared positive attitude towards learning from mistakes, and negative experiences when mistakes occur. Financial and personal consequences, shame, and blame force desperate employees to hide their mistakes. These adverse outcomes are doubled in organizations by the common belief that managers never make mistakes,...
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Selected Technical Issues of Deep Neural Networks for Image Classification Purposes
PublicationIn recent years, deep learning and especially Deep Neural Networks (DNN) have obtained amazing performance on a variety of problems, in particular in classification or pattern recognition. Among many kinds of DNNs, the Convolutional Neural Networks (CNN) are most commonly used. However, due to their complexity, there are many problems related but not limited to optimizing network parameters, avoiding overfitting and ensuring good...
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Online Interactivity – Shift Towards E-textbook-based Medical Education
PublicationTextbooks have played the leading role in academic education for centuries and their form has evolved, adapting to the needs of students, teachers and technological possibilities. Advances in technology have caused educators to look for new sources of knowledge development, which students could use inside and outside the classroom. Today’s sophisticated learning tools range from virtual environments to interactive multimedia resources,...
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Projekt Leonardo da Vinci ''Wirtualne kursy zawodowego języka angielskiego oraz system ich ewaluacji VENOCES''.
PublicationProject VENOCES ma na celu podniesienie poziomu nauczania języków obcych oraz ułatwienie dostępu do wiedzy specjalistycznej przez stworzenie wirtualnych kursów językowych w dziedzinach istotnych dla wszystkich partnerów stosując nowoczesne technologie multimedialne oraz innowacyjne podejście metodologiczne CLIL (ang. Content and Language Learning Approach). Niewątpliwą innowacją założoną przez twórców projektu będzie zastosowanie,...
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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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Rozwijanie kreatywności ucznia w procesie kształtowania umiejętności językowych. Innowacja pedagogiczna z elementami neurodydaktyki w edukacji wczesnoszkolnej
PublicationThis text is a ready-to-use pedagogical innovation program combining teaching English and classes developing creativity in early childhood education. Classes developing creativity are a unique opportunity to implement innovative solutions and ideas to develop language competencies and key competencies, which can be difficult during a standard English lesson. The...
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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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Physical models in the education of architectural history
PublicationIn this article, the authors present the long tradition and common use of physical models in the process of teaching the history of architecture in higher education institutions. The research described in the article is focused on the use of physical models and mock-ups as stimulants during architectural history classes to support lectures and increase the learning capabilities of students. The authors also cover the general use...
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Study on Strategy in University Laboratory Class Teaching
PublicationLaboratory teaching is a critical way to ensure the effective input of techniques in engineering learning. Laboratory teaching not only contributes to improving course quality but also helps enrich comprehensive engineering application ability. However, there are some typical problems in current university laboratory teaching, such as rigid and isolated course design, outdated contents and materials, and not encouraging innovation...
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Deep CNN based decision support system for detection and assessing the stage of diabetic retinopathy
PublicationThe diabetic retinopathy is a disease caused by long-standing diabetes. Lack of effective treatment can lead to vision impairment and even irreversible blindness. The disease can be diagnosed by examining digital color fundus photographs of retina. In this paper we propose deep learning approach to automated diabetic retinopathy screening. Deep convolutional neural networks (CNN) - the most popular kind of deep learning algorithms...
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Psychological capital and happiness at work: The mediating role of employee thriving in multinational corporations
PublicationWorking in multicultural work environments of multinational corporations (MNCs) creates challenges whose expected impact on happiness is equivocal. In the following paper, we examine the relationship between psychological capital and happiness at work in the specific MNCs’ context. We assume that thriving (eudemonic well-being) at work fosters individuals’ development and enhances their happiness composed of both the affective...
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Leadership, culture, intellectual capital and knowledge processes for organizational innovativeness across industries: the case of Poland
PublicationPurpose – This study aims to present the overview of intellectual capital creation micro-mechanisms concerning formal and informal knowledge processes. The organizational culture, transformational leadership and innovativeness are also included in the investigation as ascendants and consequences of the focal relation of intellectual capital and knowledge processes. Design/methodology/approach – Based on a sample of 1,418 Polish...
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POSITIVE PSYCHOLOGICAL CAPITAL ENHANCES THRIVING IN THE MULTICULTURAL WORK ENVIRONMENT OF MULTINATIONAL CORPORATIONS
PublicationThe aim of the paper is to examine positive psychological capital (PsyCap) as well as individual factors in the relationship with thriving in the multicultural work environment of multinational corporations (MNCs). We conducted a quantitative study on the sample of 127 individuals from subsidiaries of various MNCs located in Poland and involved in intercultural interactions. The results of cross-sectional study show that employees...
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Impact of Visual Image Quality on Lymphocyte Detection Using YOLOv5 and RetinaNet Algorithms
PublicationLymphocytes, a type of leukocytes, play a vital role in the immune system. The precise quantification, spatial arrangement and phenotypic characterization of lymphocytes within haematological or histopathological images can serve as a diagnostic indicator of a particular lesion. Artificial neural networks, employed for the detection of lymphocytes, not only can provide support to the work of histopathologists but also enable better...
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Intelligent Audio Signal Processing − Do We Still Need Annotated Datasets?
PublicationIn this paper, intelligent audio signal processing examples are shortly described. The focus is, however, on the machine learning approach and datasets needed, especially for deep learning models. Years of intense research produced many important results in this area; however, the goal of fully intelligent signal processing, characterized by its autonomous acting, is not yet achieved. Therefore, a review of state-of-the-art concerning...
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Factors Affecting the Effectiveness of Military Training in Virtual Reality Environment
PublicationIn this paper, we explored the factors influencing the effectiveness of military trainings performed in a virtual reality environment. The rationale for taking up the topic is the fact that such trainings are often conducted under specific operational procedures. These procedures may create rigorous frameworks for all elements of the learning environment, including the teacher’s performance. Therefore, to ensure the most conducive...
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An Improved Convolutional Neural Network for Steganalysis in the Scenario of Reuse of the Stego-Key
PublicationThe topic of this paper is the use of deep learning techniques, more specifically convolutional neural networks, for steganalysis of digital images. The steganalysis scenario of the repeated use of the stego-key is considered. Firstly, a study of the influence of the depth and width of the convolution layers on the effectiveness of classification was conducted. Next, a study on the influence of depth and width of fully connected...
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TWO-SHAFT GAS TURBINE TEACHING AND TESTING STATION
PublicationThe station was established as part of a project co-financed by the European Union with the funds of the European Regional Development Fund as part of the Infrastructure and Environment Operational Programme titled: “Establishment of state-of-the-art technical infrastructure for the Engineers of the Future learning programme at the Gdańsk University of Technology” executed in 2013-2015.
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MOODLE MOOCS - PRZYPADKI UŻYCIA W PROJEKCIE SP4CE (PARTNERSTWO STRATEGICZNE NA RZECZ KREATYWNOŚCI I PRZEDSIĘBIORCZOŚCI)
PublicationProjekt SP4CE (Partnerstwo strategiczne na rzecz kreatywności i przedsiębiorczości) jest odpowiedzią na potrzeby zidentyfikowane w komunikacie z Brugii w sprawie ściślejszej europejskiej współpracy w dziedzinie kształcenia i szkolenia zawodowego w latach 2011 - 2020. Do realizacji portalu SP4CE wykorzystano oprogramowanie WordPress i Moodle. WordPress wykorzystano m.in. do udostępnienia materiałów informacyjnych oraz szkoleniowych...
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PSYCHOLOGICAL CAPITAL AND CHALLENGE APPRAISAL FOSTER THRIVING IN THE GLOBALIZED MULTICULTURAL WORKPLACE
PublicationThe purpose of the study was to examine the psychological resources which foster thriving in multicultural work settings of multinational corporations (MNCs) - the companies that are evident manifestation of globalization. Although globalized multicultural workplace creates specific job demands that pose unique occupational stress to individuals, some personal resources enable them to deal with these demands and to thrive. Thriving...
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A novel hybrid adaptive framework for support vector machine-based reliability analysis: A comparative study
PublicationThis study presents an innovative hybrid Adaptive Support Vector Machine - Monte Carlo Simulation (ASVM-MCS) framework for reliability analysis in complex engineering structures. These structures often involve highly nonlinear implicit functions, making traditional gradient-based first or second order reliability algorithms and Monte Carlo Simulation (MCS) time-consuming. The application of surrogate models has proven effective...