Wyniki wyszukiwania dla: E-LEARNING - MOST Wiedzy

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Wyniki wyszukiwania dla: E-LEARNING

Wyniki wyszukiwania dla: E-LEARNING

  • t-SNE Highlights Phylogenetic and Temporal Patterns of SARS-CoV-2 Spike and Nucleocapsid Protein Evolution

    Publikacja
    • G. Tamazian
    • A. Komissarov
    • D. Kobak
    • D. Polyakov
    • E. Andronov
    • S. Nechaev
    • S. Kryzhevich
    • Y. Porozov
    • E. Stepanov

    - Rok 2022

    We 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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  • Tomasz Deręgowski dr inż.

    Osoby

    Tomasz Deręgowski jest adiunktem w Katedrze Informatyki w Zarządzaniu na Wydziale Zarządzania i Ekonomii Politechniki Gdańskiej, oraz kierownikiem Departamentu Inżynierii Platform Danych, pracującego nad rozwiązaniami Big Data, uczenia maszynowego i inżynierii danych w Nordea Bank AB - największej Skandynawskiej instytucji finansowej. Wcześniej pracował przez 15 lat w branży IT  jako programista, lider zespołu, kierownik programu...

  • ePBL – czyli nauka poprzez realizację projektu w środowisku wirtualnym

    Publikacja

    Kształcenie inżynierów stanowi niezwykle istotny element systemu edukacyjnego każdego nowoczesnego państwa, ponieważ to właśnie dobrze przygotowana kadra inżynierska decyduje o tempie rozwoju i poziomie infrastruktury danego kraju. Wykorzystanie najnowszych technologii w procesie edukacyjnym jest naturalną konsekwencją „informatyzacji” życia. Pokolenia dorastające w świecie wszechobecnych komputerów, urządzeń mobilnych i cyfrowej...

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  • Evaluation of Machine Learning Methods for the Experimental Classification and Clustering of Higher Education Institutions

    Publikacja

    - Rok 2022

    Higher education institutions have a big impact on the future of skills supplied on the labour market. It means that depending on the changes in labour market, higher education institutions are making changes to fields of study or adding new ones to fulfil the demand on labour market. The significant changes on labour market caused by digital transformation, resulted in new jobs and new skills. Because of the necessity of computer...

  • Jak wykraść złoto smokowi? - uczenie ze wzmocnieniem w świecie Wumpusa

    Publikacja

    - Rok 2021

    Niniejszy rozdział zawiera łagodne wprowadzenie do problematyki uczenia ze wzmocnieniem, w którym podstawy teoretyczne wyjaśniane są na przykładzie przewodnim, jakim jest zagadnienie nauczenia agenta poruszania się w świecie potwora o imieniu Wumpus (ang. Wumpus world), klasycznym środowisku do testowania logicznego rozumowania agentów (problem nietrywialny dla algorytmów uczenia ze wzmocnieniem). Przedstawiona jest główna idea...

  • A Comprehensive Analysis of Deep Neural-Based Cerebral Microbleeds Detection System

    Publikacja

    - Electronics - Rok 2021

    Machine 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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  • A new multi-process collaborative architecture for time series classification

    Publikacja

    - KNOWLEDGE-BASED SYSTEMS - Rok 2021

    Time series classification (TSC) is the problem of categorizing time series data by using machine learning techniques. Its applications vary from cybersecurity and health care to remote sensing and human activity recognition. In this paper, we propose a novel multi-process collaborative architecture for TSC. The propositioned method amalgamates multi-head convolutional neural networks and capsule mechanism. In addition to the discovery...

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  • Deep learning based thermal image segmentation for laboratory animals tracking

    Publikacja

    Automated systems for behaviour classification of laboratory animals are an attractive alternative to manual scoring. However, the proper animals separation and tracking, especially when they are in close contact, is the bottleneck of the behaviour analysis systems. In this paper, we propose a method for the segmentation of thermal images of laboratory rats that are in close contact during social behaviour tests. For this, we are...

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  • An Intelligent Approach to Short-Term Wind Power Prediction Using Deep Neural Networks

    Publikacja

    - Journal of Artificial Intelligence and Soft Computing Research - Rok 2023

    In 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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  • Machine learning applied to acoustic-based road traffic monitoring

    Publikacja

    - Rok 2022

    The motivation behind this study lies in adapting acoustic noise monitoring systems for road traffic monitoring for driver’s safety. Such a system should recognize a vehicle type and weather-related pavement conditions based on the audio level measurement. The study presents the effectiveness of the selected machine learning algorithms in acoustic-based road traffic monitoring. Bases of the operation of the acoustic road traffic...

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  • Medical Image Segmentation Using Deep Semantic-based Methods: A Review of Techniques, Applications and Emerging Trends

    Publikacja

    - Information Fusion - Rok 2022

    Semantic-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

    Illegal, 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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  • Are Pair Trading Strategies Profitable During COVID-19 Period?

    Publikacja
    • M. K. Sohail
    • A. Raheman
    • J. Iqbal
    • M. I. Sindhu
    • A. Staar
    • M. Mushafiq
    • H. Afzal

    - Journal of Information & Knowledge Management - Rok 2022

    Pair 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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  • Machine learning applied to acoustic-based road traffic monitoring

    The motivation behind this study lies in adapting acoustic noise monitoring systems for road traffic monitoring for driver’s safety. Such a system should recognize a vehicle type and weather-related pavement conditions based on the audio level measurement. The study presents the effectiveness of the selected machine learning algorithms in acoustic-based road traffic monitoring. Bases of the operation of the acoustic road traffic...

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  • Detection of Anomalies in the Operation of a Road Lighting System Based on Data from Smart Electricity Meters

    Publikacja

    - ENERGIES - Rok 2022

    Smart meters in road lighting systems create new opportunities for automatic diagnostics of undesirable phenomena such as lamp failures, schedule deviations, or energy theft from the power grid. Such a solution fits into the smart cities concept, where an adaptive lighting system creates new challenges with respect to the monitoring function. This article presents research results indicating the practical feasibility of real‐time...

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  • Travel agents and destination management organizations: eLearning as a strategy to train tourism trade partners.

    This article offers an overview of the existing online courses run by national destination management organizations (DMOs) in order to better equip travel agents and tour operators in the sales activities of the tourism destinations. These online courses represent one of the B2B offers by DMOs and an interesting opportunity for travel agents, who are trying to find their identity and competitive advantage within the context of...

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  • Improvement of speech intelligibility in the presence of noise interference using the Lombard effect and an automatic noise interference profiling based on deep learning

    Publikacja
    • K. Kąkol

    - Rok 2023

    The Lombard effect is a phenomenon that results in speech intelligibility improvement when applied to noise. There are many distinctive features of Lombard speech that were recalled in this dissertation. This work proposes the creation of a system capable of improving speech quality and intelligibility in real-time measured by objective metrics and subjective tests. This system consists of three main components: speech type detection,...

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  • Emotion recognition and its application in software engineering

    In this paper a novel application of multimodal emotion recognition algorithms in software engineering is described. Several application scenarios are proposed concerning program usability testing and software process improvement. Also a set of emotional states relevant in that application area is identified. The multimodal emotion recognition method that integrates video and depth channels, physiological signals and input devices...

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  • Otwarte zasoby edukacyjne - przegląd inicjatyw w Polsce i na świecie

    Publikacja

    Otwarte zasoby edukacyjne (OZE) to materiały szkoleniowe oraz narzędzia wspierające zarówno uczenie, jak i nauczanie. Zjawisko to nierozerwalnie łączy się z szerszym pojęciem otwartej edukacji (OE), które postuluje zniesienie barier w nauczaniu tak, aby uczący się mogli zdobywać wiedzę zgodnie ze swoimi potrzebami edukacyjno-szkoleniowymi. Celem artykułu jest zapoznanie czytelników z zagadnieniem otwartych zasobów edukacyjnych,...

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  • Developing competences for cooperation in international teams - tools and methods

    Publikacja

    The article presents the training methods that can be used to develop intercultural competences which are extremely important while working in intercultural teams. The mentioned methods like: case-studies, collaborating, role-play simulations, team working, video presentations and others are presented on the basis of authors’ experiences while teaching the international groups of students at Faculty of Management and Economics...

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  • Dokształcanie na odległość kandydatów na studia politechniczne - model DOROTKA

    Publikacja

    - Rok 2004

    W artykule przedstawiono potrzebę dokształcania kandydatów na studia politechniczne i podjęte w tym celu działania w ramach powołanego Konsorcjum Uczelni Technicznych. Zaprezentowano model z wykorzystaniem systemu LMS (ang. Learning Management System) - DOROTKA (Doskonalenie Organizacji, ROzwoju oraz Tworzenia Kursów Akademickich przez Internet), wspierający działania związane z uruchomieniem kursów wyrównawczych z matematyki i...

  • Ripple oscillations in the left temporal neocortex are associated with impaired verbal episodic memory encoding

    Publikacja
    • Z. Waldman
    • L. Camarillo-Rodriguez
    • I. Chervenova
    • B. Berry
    • S. Shimamoto
    • B. Elahian
    • M. T. Kucewicz
    • C. Ganne
    • X. He
    • L. A. Davis... i 17 innych

    - EPILEPSY & BEHAVIOR - Rok 2018

    BACKGROUND: We sought to determine if ripple oscillations (80-120 Hz), detected in intracranial electroencephalogram (iEEG) recordings of patients with epilepsy, correlate with an enhancement or disruption of verbal episodic memory encoding. METHODS: We defined ripple and spike events in depth iEEG recordings during list learning in 107 patients with focal epilepsy. We used logistic regression models (LRMs) to investigate the...

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  • Model-Based Adaptive Machine Learning Approach in Concrete Mix Design

    Publikacja

    Concrete mix design is one of the most critical issues in concrete technology. This process aims to create a concrete mix which helps deliver concrete with desired features and quality. Contemporary requirements for concrete concern not only its structural properties, but also increasingly its production process and environmental friendliness, forcing concrete producers to use both chemically and technologically complex concrete...

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  • Voice command recognition using hybrid genetic algorithm

    Publikacja

    Abstract: Speech recognition is a process of converting the acoustic signal into a set of words, whereas voice command recognition consists in the correct identification of voice commands, usually single words. Voice command recognition systems are widely used in the military, control systems, electronic devices, such as cellular phones, or by people with disabilities (e.g., for controlling a wheelchair or operating a computer...

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  • Międzynarodowa Szkoła Letnia na temat algorytmów

    Wydarzenia

    06-07-2020 08:30 - 11-07-2020 17:00

    Katedra Algorytmów i Modelowania Systemów WETI PG organizuje 4. edycję Międzynarodowej Szkoły Letniej na temat algorytmów dla problemów optymalizacji dyskretnej i głębokiego uczenia

  • Medical Image Dataset Annotation Service (MIDAS)

    Publikacja

    - Rok 2020

    MIDAS (Medical Image Dataset Annotation Service) is a custom-tailored tool for creating and managing datasets either for deep learning, as well as machine learning or any form of statistical research. The aim of the project is to provide one-fit-all platform for creating medical image datasets that could easily blend in hospital's workflow. In our work, we focus on the importance of medical data anonimization, discussing the...

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  • Investigating Feature Spaces for Isolated Word Recognition

    Publikacja

    - Rok 2018

    Much attention is given by researchers to the speech processing task in automatic speech recognition (ASR) over the past decades. The study addresses the issue related to the investigation of the appropriateness of a two-dimensional representation of speech feature spaces for speech recognition tasks based on deep learning techniques. The approach combines Convolutional Neural Networks (CNNs) and timefrequency signal representation...

  • Supply current signal and artificial neural networks in the induction motor bearings diagnostics

    Publikacja

    This 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...

  • Face with Mask Detection in Thermal Images Using Deep Neural Networks

    Publikacja

    As the interest in facial detection grows, especially during a pandemic, solutions are sought that will be effective and bring more benefits. This is the case with the use of thermal imaging, which is resistant to environmental factors and makes it possible, for example, to determine the temperature based on the detected face, which brings new perspectives and opportunities to use such an approach for health control purposes. The...

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  • Discovering Rule-Based Learning Systems for the Purpose of Music Analysis

    Publikacja

    Music analysis and processing aims at understanding information retrieved from music (Music Information Retrieval). For the purpose of music data mining, machine learning (ML) methods or statistical approach are employed. Their primary task is recognition of musical instrument sounds, music genre or emotion contained in music, identification of audio, assessment of audio content, etc. In terms of computational approach, music databases...

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  • Experience-Based Cognition for Driving Behavioral Fingerprint Extraction

    Publikacja

    - CYBERNETICS AND SYSTEMS - Rok 2020

    ABSTRACT With the rapid progress of information technologies, cars have been made increasingly intelligent. This allows cars to act as cognitive agents, i.e., to acquire knowledge and understanding of the driving habits and behavioral characteristics of drivers (i.e., driving behavioral fingerprint) through experience. Such knowledge can be then reused to facilitate the interaction between a car and its driver, and to develop better and...

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  • Music information retrieval—The impact of technology, crowdsourcing, big data, and the cloud in art.

    The exponential growth of computer processing power, cloud data storage, and crowdsourcing model of gathering data bring new possibilities to music information retrieval (mir) field. Mir is no longer music content retrieval only; the area also comprises the discovery of expressing feelings and emotions contained in music, incorporating other than hearing modalities for helping this issue, users’ profiling, merging music with social...

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  • Optimizing Medical Personnel Speech Recognition Models Using Speech Synthesis and Reinforcement Learning

    Text-to-Speech synthesis (TTS) can be used to generate training data for building Automatic Speech Recognition models (ASR). Access to medical speech data is because it is sensitive data that is difficult to obtain for privacy reasons; TTS can help expand the data set. Speech can be synthesized by mimicking different accents, dialects, and speaking styles that may occur in a medical language. Reinforcement Learning (RL), in the...

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  • Machine learning for the management of biochar yield and properties of biomass sources for sustainable energy

    Publikacja
    • G. V. Nguyen
    • P. Sharma
    • Ü. Ağbulut
    • H. S. Le
    • T. H. Truong
    • M. Dzida
    • M. H. Tran
    • H. C. Le
    • V. D. Tran

    - Biofuels Bioproducts & Biorefining-Biofpr - Rok 2024

    Biochar is emerging as a potential solution for biomass conversion to meet the ever increasing demand for sustainable energy. Efficient management systems are needed in order to exploit fully the potential of biochar. Modern machine learning (ML) techniques, and in particular ensemble approaches and explainable AI methods, are valuable for forecasting the properties and efficiency of biochar properly. Machine-learning-based forecasts,...

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  • Forewarned Is Forearmed: Machine Learning Algorithms for the Prediction of Catheter-Induced Coronary and Aortic Injuries

    Catheter-induced dissections (CID) of coronary arteries and/or the aorta are among the most dangerous complications of percutaneous coronary procedures, yet the data on their risk factors are anecdotal. Logistic regression and five more advanced machine learning techniques were applied to determine the most significant predictors of dissection. Model performance comparison and feature importance ranking were evaluated. We identified...

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  • Toward Intelligent Vehicle Intrusion Detection Using the Neural Knowledge DNA

    Publikacja

    - CYBERNETICS AND SYSTEMS - Rok 2018

    In this paper, we propose a novel intrusion detection approach using past driving experience and the neural knowledge DNA for in-vehicle information system security. The neural knowledge DNA is a novel knowledge representation method designed to support discovering, storing, reusing, improving, and sharing knowledge among machines and computing systems. We examine our approach for classifying malicious vehicle control commands...

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  • Introduction to the ONDM 2022 special issue

    Publikacja
    • J. Turkiewicz
    • T. Gomes
    • M. Klinkowski
    • J. Rak
    • M. Tornatore

    - Journal of Optical Communications and Networking - Rok 2023

    This 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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  • Interactive Application for Visualization of the Basic Phenomena in RF and Microwave Devices

    An interactive computer application visualizing the basic phenomena in RF and microwave devices is presented. Such kind of educational package can be a very helpful tool for the students as well as for the teachers (of electronics and related fields). This paper is focused on three exemplary problems only and involves: movement of electric charge, filtering of electromagnetic waves and interference phenomena in antenna arrays. The...

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  • Learning and memory processes in autonomous agents using an intelligent system of decision-making

    Publikacja

    This paper analyzes functions and structures of the memory that is an indispensable part of an Intelligent System of Decision-making (ISD), developed as a universal engine for autonomous robotics. A simplified way of processing and coding information in human cognitive processes is modelled and adopted for the use in autonomous systems. Based on such a knowledge structure, an artificial model of reality representation and a model...

  • Potwierdzanie efektów uczenia się jakonowe zadanie dla uczelni wyższych

    Praca nawiązuje do przeprowadzonej w 2014 roku nowelizacji ustawy z dnia 27 lipca 2005 r. Prawo o szkolnictwie wyższym. Wprowadzono w niej nowy obowiązek dla uczelni wyższych – potwierdzanie efektów uczenia się nabytych poza systemem studiów. Omowiono zasady kształcenia w kontekście Lifelong Learning oraz walidacji efektów uczenia się. Przedstawiono podstawy wdrożeniowe potwierdzania efektów uczenia się na Politechnice Gdańskiej.

  • Learning and memory processes in autonomous agents using an intelligent system of decision-making

    Publikacja

    This paper analyzes functions and structures of the memory that is an indispensable part of an Intelligent System of Decision-making (ISD), developed as a universal engine for autonomous robotics. A simplified way of processing and coding information in human cognitive processes is modelled and adopted for the use in autonomous systems. Based on such a knowledge structure, an artificial model of reality representation and a model...

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  • Virtual reality tools in teaching the conservation and history of Polish architecture

    Virtual reality and its impact on teaching conservation and architectural history is the subject of this article. During the COVID-19 crisis in 2020, the education of students of architecture was transferred by Gdańsk University of Technology (GUT), Gdańsk, Poland, to distance learning. This method has provided academics an opportunity to examine the impact of virtual reality and remote education on architectural history and conservation....

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  • Detection of the Oocyte Orientation for the ICSI Method Automation

    Automation or even computer assistance of the popular infertility treatment method: ICSI (Intracytoplasmic Sperm Injection) would speed up the whole process and improve the control of the results. This paper introduces a preliminary research for automatic spermatozoon injection into the oocyte cytoplasm. Here, the method for detection a correct orientation of the polar body of the oocyte is presented. Proposed method uses deep...

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  • Adding Intelligence to Cars Using the Neural Knowledge DNA

    Publikacja

    - CYBERNETICS AND SYSTEMS - Rok 2017

    In this paper we propose a Neural Knowledge DNA based framework that is capable of learning from the car’s daily operation. The Neural Knowledge DNA is a novel knowledge representation and reasoning approach designed to support discovering, storing, reusing, improving, and sharing knowledge among machines and computing devices. We examine our framework for drivers' classification based on their driving behaviour. The experimental...

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  • Application of fiber optic sensors using Machine Learning algorithms for temperature measurement of lithium-ion batteries

    Optical fiber sensorsusing low-coherence interferometry require processing ofthe output spectrum or interferogramto quickly and accurately determine the instantaneous value of the measured quantity, such as temperature.Methods based on machine learning are a good candidate for this application. The application of four such methods in an optical fiber temperature sensoris demonstrated.Using aZnO-coated...

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  • Risking It All or Here Comes the Flood

    Publikacja

    - Rok 2018

    The professional reality is interdisciplinary! When city transformation and evolution starts, what are the tools for successful strategies for urban interventions? How does digital planning for digital fabrication processes look like? How dedicated are the new professionals? And how does this all influence the future of bridge design? More than 60 students representing various disciplines of built environment and working together...

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  • Thriving in multicultural work settings

    Publikacja

    - Rok 2015

    Owing to globalization and the global mobility of workforce, working in multicultural environments has become a daily reality for an increasing number of manpower. Such an environment does introduce unique challenges to individuals, enabling some of them to thrive. The aim of the paper, therefore, is to explore the antecedents of thriving and its components in multicultural work settings of multinational corporations (MNCs). The...

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  • An Adaptive Network Model for a Double Bias Perspective on Learning from Mistakes within Organizations

    Publikacja

    - Rok 2024

    Although making mistakes is a crucial part of learning, it is still often being avoided in companies as it is considered as a shameful incident. This goes hand in hand with a mindset of a boss who dominantly believes that mistakes usually have negative consequences and therefore avoids them by only accepting simple tasks. Thus, there is no mechanism to learn from mistakes. Employees working for and being influenced by such a boss...

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  • Speed estimation of a car at impact with a W-beam guardrail using numerical simulations and machine learning

    This paper aimed at developing a new method of estimating the impact speed of a passenger car at the moment of a crash into a W-beam road safety barrier. The determination of such a speed based on the accident outcomes is demanding, because often there is no access to full accident data. However, accurate determination of the impact speed is one of the key elements in the reconstruction of road accidents. A machine learning algorithm...

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  • Data-driven, probabilistic model for attainable speed for ships approaching Gdańsk harbour

    Publikacja

    The growing demand for maritime transportation leads to increased traffic in ports. From this arises the need to observe the consequences of the specific speed ships reach when approaching seaports. However, usually the analyzed cases refer only to the statistical evaluation of the studied phenomenon or to the empirical modelling, ignoring the mutual influence of variables such as ship type, length or weather conditions. In this...

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