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Wyniki wyszukiwania dla: LIFE-LONG LEARNING
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Application of a hybrid mechanistic/machine learning model for prediction of nitrous oxide (N2O) production in a nitrifying sequencing batch reactor
PublikacjaNitrous oxide (N2O) is a key parameter for evaluating the greenhouse gas emissions from wastewater treatment plants. In this study, a new method for predicting liquid N2O production during nitrification was developed based on a mechanistic model and machine learning (ML) algorithm. The mechanistic model was first used for simulation of two 15-day experimental trials in a nitrifying sequencing batch reactor. Then, model predictions...
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E-technologie w diagnozie i pomiarach postępów terapii dzieci z autyzmem w Polsce
PublikacjaCelem artykułu jest przeanalizowanie możliwości wsparcia technologicznego - w szczególności z wykorzystaniem urządzeń mobilnych - diagnozy i oceny postępów terapii dzieci z autyzmem. W ramach badań dokonano przeglądu istniejących rozwiązań wspierających diagnozę i pomiar postępów terapii oraz przeprowadzono ankietę w polskich ośrodkach zajmujących się pracą z osobami dotkniętymi autyzmem. Wyniki badania wskazują na zainteresowanie...
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Work–life balance: Does age matter?
PublikacjaWork-life balance is a priority of EU policies but at the same time demographic change affects the labour market. Employers have to deal with the ageing of their employees and adjust human resource management to maintain their competitiveness. The purpose of the article is to answer research questions: whether the age of workers determines their assessment of the work-life balance, and whether there is a relationship between the...
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A novel hybrid adaptive framework for support vector machine-based reliability analysis: A comparative study
PublikacjaThis 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...
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MOODLE MOOCS - PRZYPADKI UŻYCIA W PROJEKCIE SP4CE (PARTNERSTWO STRATEGICZNE NA RZECZ KREATYWNOŚCI I PRZEDSIĘBIORCZOŚCI)
PublikacjaProjekt 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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Machine-Learning-Powered EM-Based Framework for Efficient and Reliable Design of Low Scattering Metasurfaces
PublikacjaPopularity of metasurfaces has been continuously growing due to their attractive properties including the ability to effectively manipulate electromagnetic (EM) waves. Metasurfaces comprise optimized geometries of unit cells arranged as a periodic lattice to obtain a desired EM response. One of their emerging application areas is the stealth technology, in particular, realization of radar cross section (RCS) reduction. Despite...
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Long Room (Dublin)
Czasopisma -
Motion Trajectory Prediction in Warehouse Management Systems: A Systematic Literature Review
PublikacjaBackground: In the context of Warehouse Management Systems, knowledge related to motion trajectory prediction methods utilizing machine learning techniques seems to be scattered and fragmented. Objective: This study seeks to fill this research gap by using a systematic literature review approach. Methods: Based on the data collected from Google Scholar, a systematic literature review was performed, covering the period from 2016...
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Investigating Feature Spaces for Isolated Word Recognition
PublikacjaThe study addresses the issues related to the appropriateness of a two-dimensional representation of speech signal for speech recognition tasks based on deep learning techniques. The approach combines Convolutional Neural Networks (CNNs) and time-frequency signal representation converted to the investigated feature spaces. In particular, waveforms and fractal dimension features of the signal were chosen for the time domain, and...
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Bridging theory and practice in postgraduate education on development and planning: Gdynia Urban Summer Schools 2016-2018
PublikacjaIn this article, the authors discuss results achieved by the Gdynia Urban Summer School (GUSS) organised annually (between 2016 and 2018) in Gdynia, Poland. The GUSS was meant for young practitioners from various professions such as urban and regional planning, urban design, architecture, civil engineering and transport planning. The objective was to give workshop participantspractical interdisciplinary...
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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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Direct brain stimulation modulates encoding states and memory performance in humans
PublikacjaPeople often forget information because they fail to effectively encode it. Here, we test the hypothesis that targeted electrical stimulation can modulate neural encoding states and subsequent memory outcomes. Using recordings from neurosurgical epilepsy patients with intracranially implanted electrodes, we trained multivariate classifiers to discriminate spectral activity during learning that predicted remembering from forgetting,...
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Novel approach to ecotoxicological risk assessment of sediments cores around the shipwreck by the use of self-organizing maps
PublikacjaMarine and coastal pollution plays an increasingly important role due to recent severe accidents which drew attention to the consequences of oil spills causing widespread devastation of marine ecosystems. All these problems cannot be solved without conducting environmental studies in the area of possible oil spill and performing chemometric evaluation of the data obtained looking for similar patterns among pollutants and optimize...
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Life Cycle Assessment of Analytical Protocols
PublikacjaLife cycle assessment is a relatively new tool for environmental management, which is becoming more and more important owing to the globalization of the world economy, where there is a need to develop standards in protecting the environment
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Projektowanie środowiskowe - edukacja architektoniczna
PublikacjaPrzedstawiono krytykę obecnej edukacji architektonicznej oraz dyskusję nad kierunkami jej zmian. Omówiono dokumenty międzynarodowych organizacji zajmujących się teoria i praktyką edukacji architektonicznej ze szczególnym uwzględnieniem edukacji w zakresie projektowania środowiskowego oraz systemów samoksztalcenia (learning to learn) i kształcenia ustawicznego.
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Potential negative effect of long-term exposure to nitrofurans on bacteria isolated from wastewater
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Low-Cost and Highly-Accurate Behavioral Modeling of Antenna Structures by Means of Knowledge-Based Domain-Constrained Deep Learning Surrogates
PublikacjaThe awareness and practical benefits of behavioral modeling methods have been steadily growing in the antenna engineering community over the last decade or so. Undoubtedly, the most important advantage thereof is a possibility of a dramatic reduction of computational expenses associated with computer-aided design procedures, especially those relying on full-wave electromagnetic (EM) simulations. In particular, the employment of...
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Mobile Activity Plan Applications for Behavioral Therapy of Autistic Children
PublikacjaThis paper concerns technological support for behavioral therapy of autistic children. A family of tools dedicated for mobile devices is presented, that allows to design and perform an activity schedule in behavioral therapy. The paper describes the main challenges, that were encountered, especially in meeting the non-functional requirements of the application: simplicity, repeatability, robustness, personalization, re-usability...
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Wspomaganie zajęć dydaktycznych z matematyki na kierunkach technicznych kursem e-Learningowym"
PublikacjaW artykule przedstawiono doświadczenia w zakresie wspomagania przedmiotu matematyka na pierwszym roku studiów inżynierskich kursem e-learningowym. Wykonano analizę wyników testów przeprowadzonych podczas e-zajęć. Przedstawiono również wyniki ankiet ewaluacyjnych obrazujących stosunek studentów do wprowadzania kształcenia matematyki z wykorzystaniem blended learning.
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THE INFLUENCE OF QUESTION SET ON STUDENT QUIZ RESULTS
PublikacjaThe advent of e-Learning tools allowing for automated online test grading will probably increase the frequency of using tests in technical education. The same tools may provide for measures of test question quality. By purposely crafting question sets, test grading may serve different goals. The paper contains examples and test study with score histograms.
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Forecasting energy consumption and carbon dioxide emission of Vietnam by prognostic models based on explainable machine learning and time series
PublikacjaThis study assessed the usefulness of algorithms in estimating energy consumption and carbon dioxide emissions in Viet- nam, in which the training dataset was used to train the models linear regression, random forest, XGBoost, and AdaBoost, allowing them to comprehend the patterns and relationships between population, GDP, and carbon dioxide emissions, energy consumption. The results revealed that random forest, XGBoost, and AdaBoost...
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WebCT - platforma i tłumaczenie.
PublikacjaW artykule przedstawiono doświadczenia Centrum Edukacji Niestacjonarnej i Międzywydziałowego Koła Naukowego Studentów Politechniki Gdańskiej DEC@TUG w tłumaczeniu i implementacji platform LMS (ang. Learning Management System). Krótko scharakteryzowano funkcjonalność platform BSCW I Moodle, których interfejsy zostały przetłumaczone przez członków Koła DEC@TUG w latach 2000-2003. Opisano główne funkcje platformy WebCT, takie jak...
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MOOCs in SP4CE - case studies (Strategic Partnership for Creativity and Entrepreneurship)
PublikacjaSP4CE stands for Strategic Partnership for Creativity and Entrepreneurship project which has been funded with support from the European Commission under the ERASMUS+ Programme in the period 1st September 2014 - 31st August 2017. The main purpose of SP4CE project is to design innovative e-learning tools for collaboration between students, enterprises and teachers. It concentrates on identifying users’ needs and supports the development...
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From Knowledge based Vision Systems to Cognitive Vision Systems: A Review
PublikacjaComputer vision research and applications have their origins in 1960s. Limitations in computational resources inherent of that time, among other reasons, caused research to move away from artificial intelligence and generic recognition goals to accomplish simple tasks for constrained scenarios. In the past decades, the development in machine learning techniques has contributed to noteworthy progress in vision systems. However,...
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Is Easy Access Related to Better Life? Walkability and Overlapping of Personal and Communal Identity as Predictors of Quality of Life
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Smart Knowledge Engineering for Cognitive Systems: A Brief Overview
PublikacjaCognition in computer sciences refers to the ability of a system to learn at scale, reason with purpose, and naturally interact with humans and other smart systems, such as humans do. To enhance intelligence, as well as to introduce cognitive functions into machines, recent studies have brought humans into the loop, turning the system into a human–AI hybrid. To effectively integrate and manipulate hybrid knowledge, suitable technologies...
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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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Creating a radiological database for automatic liver segmentation using artificial intelligence.
PublikacjaImaging in medicine is an irreplaceable stage in the diagnosis and treatment of cancer. The subsequent therapeutic effect depends on the quality of the imaging tests performed. In recent years we have been observing the evolution of 2D to 3D imaging for many medical fields, including oncological surgery. The aim of the study is to present a method of selection of radiological imaging tests for learning neural networks.
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Comparative study on total nitrogen prediction in wastewater treatment 1 plant and effect of various feature selection methods on machine learning algorithms performance
PublikacjaWastewater characteristics prediction in wastewater treatment plants (WWTPs) is valuable and can reduce the number of sampling, energy, and cost. Feature Selection (FS) methods are used in the pre-processing section for enhancing the model performance. This study aims to evaluate the effect of seven different FS methods (filter, wrapper, and embedded methods) on enhancing the prediction accuracy for total nitrogen (TN) in the WWTP...
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Autonomous port management based AGV path planning and optimization via an ensemble reinforcement learning framework
PublikacjaThe rapid development of shipping trade pushes automated container terminals toward the direction of intelligence, safety and efficiency. In particular, the formulation of AGV scheduling tasks and the safety and stability of transportation path is an important part of port operation and management, and it is one of the basic tasks to build an intelligent port. Existing research mainly focuses on collaborative operation between...
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Energy consumption optimization in wastewater treatment plants: Machine learning for monitoring incineration of sewage sludge
PublikacjaBiomass management in terms of energy consumption optimization has become a recent challenge for developed countries. Nevertheless, the multiplicity of materials and operating parameters controlling energy consumption in wastewater treatment plants necessitates the need for sophisticated well-organized disciplines in order to minimize energy consumption and dissipation. Sewage sludge (SS) disposal management is the key stage of...
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Musical Instrument Tagging Using Data Augmentation and Effective Noisy Data Processing
PublikacjaDeveloping signal processing methods to extract information automatically has potential in several applications, for example searching for multimedia based on its audio content, making context-aware mobile applications (e.g., tuning apps), or pre-processing for an automatic mixing system. However, the last-mentioned application needs a significant amount of research to reliably recognize real musical instruments in recordings....
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Raw data of AuAg nanoalloy plasmon resonances used for machine learning method
Dane BadawczeRaw data used for machine learning process. UV-vis measurements of AuAg alloyed nanostructures created from thin films. Plasmonic band position dependence on fabrication parameters. Small presentation reviewing achieved structures and their properties.
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Szkolenie elektroniczne narzędziem budowy kapitału ludzkiego.
PublikacjaAutorka ukazuje proces szkoleń pracowników począwszy od tradycyjnego do bardziej nowoczesnego typu e-learning. W nowoczesnych przedsiębiorstwach odchodzxi sie od typowego, tradycyjnego szkolenia na rzecz bardziej efektywnych,tańszych i skutecznych czyli elektronicznych. W artykule pokazane są zalety i korzyści szkoleń elektronicznych w przygotowaniu pracowników do efektywnej pracy.
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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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Long-distance quantum communication over noisy networks without long-time quantum memory
PublikacjaThe problem of sharing entanglement over large distances is crucial for implementations of quantum cryptography. A possible scheme for long-distance entanglement sharing and quantum communication exploits networks whose nodes share Einstein-Podolsky-Rosen (EPR) pairs. In Perseguers et al. [Phys. Rev. A 78, 062324 (2008)] the authors put forward an important isomorphism between storing quantum information in a dimension D and transmission...
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Prediction of Overall In Vitro Microsomal Stability of Drug Candidates Based on Molecular Modeling and Support Vector Machines. Case Study of Novel Arylpiperazines Derivatives
PublikacjaOther than efficacy of interaction with the molecular target, metabolic stability is the primary factor responsible for the failure or success of a compound in the drug development pipeline. The ideal drug candidate should be stable enough to reach its therapeutic site of action. Despite many recent excellent achievements in the field of computational methods supporting drug metabolism studies, a well-recognized procedure to model...
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Knowledge pills in Education and Training: A Literature Review
PublikacjaObject and purpose: Knowledge pills (KPs) are a technique for transferring knowledge through short factual batches of content. In education and vocational training, they can help learners acquire specific pieces of knowledge in a few minutes, through a “microteaching” approach where learners can be involved in active and interactive exercises, quizzes, and games. Thanks to the advancements of multimedia platforms, they can contain...
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ePBL – czyli nauka poprzez realizację projektu w środowisku wirtualnym
PublikacjaKształcenie 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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The selected roof covering technologies in the aspect of their life cycle costs
PublikacjaIn the article is presented an analysis of the life cycle costs calculation for selected roof coverings. The scope of research includes costs of construction, maintenance and demolition of the roof covering structure for two alternative technologies – the traditional and new generation. On the presented example of an industrial building with a roof area of 1000 m², the above costs are taken to consideration for the roof covering...
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Porównanie systemu Ilias i Moodle - przypadek użycia.
PublikacjaW artykule przedstawiono koncepcję wykorzystania darmowych systemów LMS (ang. Learning Management System) jako narzędzi wspomagających prowadzenie zajęć metodą tradycyjną F2F (ang. Face to Face). Omówiono eksperyment przeprowadzony przez dwie uczelnie trójmiejskie: Akademię Morską i Politechnikę Gdańską. Celem eksperymentu było porównanie systemu Ilias (wersja 2.4.4) z systemem Moodle (wersja 1.2).
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Proposed method for estimating the costs of safety barrier life cycle
PublikacjaToday barrier types are frequently selected for their price with little regard for the total costs the structure will incur over its lifetime. One of the basic tools designed to manage road infrastructure is the life cycle cost method (LCC, Life cycle cost). It sums up the costs to plan, design, build, operate (use and maintain) and decommission a road structure. Having developed dynamically at the turn of the century the method...
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An Intelligent Approach to Short-Term Wind Power Prediction Using Deep Neural Networks
PublikacjaIn this paper, an intelligent approach to the Short-Term Wind Power Prediction (STWPP) problem is considered, with the use of various types of Deep Neural Networks (DNNs). The impact of the prediction time horizon length on accuracy, and the influence of temperature on prediction effectiveness have been analyzed. Three types of DNNs have been implemented and tested, including: CNN (Convolutional Neural Networks), GRU (Gated Recurrent...
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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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Jak wykraść złoto smokowi? - uczenie ze wzmocnieniem w świecie Wumpusa
PublikacjaNiniejszy 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...
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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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A new multi-process collaborative architecture for time series classification
PublikacjaTime 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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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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Travel agents and destination management organizations: eLearning as a strategy to train tourism trade partners.
PublikacjaThis 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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Long-Term Measurement of Physiological Parameters – Child Dataset
PublikacjaThe dataset titled “Long-term measurement of physiological parameters – child is one dataset” of the bigger series named Long-term measurement of physiological parameters. The dataset contains physiological parameter measurements such as skin temperature and resistance, blood pulse, as well as the stress detection marker, which can have a value of 0 when there is no stress detected or 1 when stress appeared. Additionally, the dataset...