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Wyniki wyszukiwania dla: BLENDED E-LEARNING
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Le reti della terza Italia.Imprese, calcio, sponsirzzazioni e territorio in Serie B 81982-2006)
PublikacjaIl capitolo si occupa dei rapporti tra imprese e sponsirzzazioni dei club calcistici italiani della serie B tra il 1982 e il 2006
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Antenna Optimization Using Machine Learning with Reduced-Dimensionality Surrogates
PublikacjaIn modern times, antenna design has become more demanding than ever. The escalating requirements for performance and functionality drive the development of intricately structured antennas, where parameters must be meticulously adjusted to achieve peak performance. Often, global adjustments to geometry are necessary for optimal results. However, direct manipulation of antenna responses evaluated with full-wave electromagnetic (EM)...
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Deep learning techniques for biometric security: A systematic review of presentation attack detection systems
PublikacjaBiometric technology, including finger vein, fingerprint, iris, and face recognition, is widely used to enhance security in various devices. In the past decade, significant progress has been made in improving biometric sys- tems, thanks to advancements in deep convolutional neural networks (DCNN) and computer vision (CV), along with large-scale training datasets. However, these systems have become targets of various attacks, with...
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System monitorowania prac organów przedstawicielskich - doświadczenie z zakresu e-demokracji
PublikacjaArtykuł zawiera wprowadzenie w tematykę e-demokracji oraz przedstawia uruchomiony w połowie roku 2004 ''System Monitorowania Prac Sejmu'', który udostępnia obywatelom informację dotyczącą zachowań ich przedstawicieli - posłów na Sejm RP. Przedstawiono obecną funkcjonalność systemu, zastosowane rozwiązania techniczne oraz plany rozwojowe.
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Predictions of cervical cancer identification by photonic method combined with machine learning
PublikacjaCervical cancer is one of the most commonly appearing cancers, which early diagnosis is of greatest importance. Unfortunately, many diagnoses are based on subjective opinions of doctors—to date, there is no general measurement method with a calibrated standard. The problem can be solved with the measurement system being a fusion of an optoelectronic sensor and machine learning algorithm to provide reliable assistance for doctors...
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RECSYS CHALLENGE 2015: a BUY EVENT PREDICTION IN THE E-COMMERCE DOMAIN
PublikacjaIn this paper we present our approach to RecSys Challenge 2015. Given a set of e-commerce events, the task is to predict whether a user will buy something in the current session and, if yes, which of the item will be bought. We show that the data preparation and enrichment are very important in finding the solution for the challenge and that simple ideas and intuitions could lead to satisfactory results. We also show that simple...
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Concrete mix design using machine learning
PublikacjaDesigning a concrete mix is a process of synthesizing many components, it is not a simple process and requires extensive technical knowledge. The design process itself focuses on obtaining the required strength of concrete. Very often designing a concrete mix takes into account the need to maintain the proper water-demand and frost-resistance features. The parameters that influence the concrete class most significantly are the...
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Predicting emotion from color present in images and video excerpts by machine learning
PublikacjaThis work aims at predicting emotion based on the colors present in images and video excerpts using a machine-learning approach. The purpose of this paper is threefold: (a) to develop a machine-learning algorithm that classifies emotions based on the color present in an image, (b) to select the best-performing algorithm from the first phase and apply it to film excerpt emotion analysis based on colors, (c) to design an online survey...
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Analyzing the relationship between sound, color, and emotion based on subjective and machine-learning approaches
PublikacjaThe aim of the research is to analyze the relationship between sound, color, and emotion. For this purpose, a survey application was prepared, enabling the assignment of a color to a given speaker’s/singer’s voice recordings. Subjective tests were then conducted, enabling the respondents to assign colors to voice/singing samples. In addition, a database of voice/singing recordings of people speaking in a natural way and with expressed...
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Deep learning based thermal image segmentation for laboratory animals tracking
PublikacjaAutomated 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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Bimodal deep learning model for subjectively enhanced emotion classification in films
PublikacjaThis research delves into the concept of color grading in film, focusing on how color influences the emotional response of the audience. The study commenced by recalling state-of-the-art works that process audio-video signals and associated emotions by machine learning. Then, assumptions of subjective tests for refining and validating an emotion model for assigning specific emotional labels to selected film excerpts were presented....
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e-logistyka dystrybucji a czynnik ludzki w procesie kształtowania wartości marki - ujęcie praktyczne
PublikacjaArtykuł poświęcono interdyscyplinarnemu przedstawieniu istoty relacji sprzedaży, marketingu i logistyki w kontekście aktualnych problemów w e-logistyce dystrybucji. Autorzy artykułu, na bazie swoich doświadczeń, przedstawili istotę koordynacji tych procesów w kontekście zidentyfikowanego wirusa problemów dotyczącego e-logistyki dystrybucji w całej sieci wartości przedsiębiorstwa produkcyjnego oraz zaproponowali rozwiązania. Artykuł...
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Reward Learning Requires Activity of Matrix Metalloproteinase-9 in the Central Amygdala
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Study of Integer Spin S = 1 in the Polar Magnet β-Ni(IO3)2
PublikacjaPolar magnetic materials exhibiting appreciable asymmetric exchange interactions can potentially host new topological states of matter such as vortex-like spin textures; however, realizations have been mostly limited to half-integer spins due to rare numbers of integer spin systems with broken spatial inversion lattice symmetries. Here, we studied the structure and magnetic properties of the S = 1 integer spin polar magnet β-Ni(IO3)2...
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Model-Based Adaptive Machine Learning Approach in Concrete Mix Design
PublikacjaConcrete 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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Vident-real: an intra-oral video dataset for multi-task learning
Dane BadawczeWe introduce Vident-real, a large dataset of 100 video sequences of intra-oral scenes from real conservative dental treatments performed at the Medical University of Gdańsk, Poland. The dataset can be used for multi-task learning methods including:
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E-projektowanie Interdyscyplinarne na przykładzie Inżynierii Medycznej
PublikacjaW obliczu rozwijającej się technologii w wielu dziedzinach życia coraz częściej spotykamy się z pojęciem współpraca interdyscyplinarna. Podjęcie współpracy jest niezwykle ważnym czynnikiem w projektowaniu nowych rozwiązań technicznych. Szczególnie istotne jest to w przypadku inżynierii medycznej, gdzie kolaboracja inżynierów i lekarzy znacząco wpływa na jakość diagnostyki, rehabilitacji i poprawy jakości życia wielu chorych. Z...
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Adaptive Dynamical Systems Modelling of Transformational Organizational Change: with Focus on Organizational Culture and Organizational Learning
PublikacjaTransformative Organizational Change becomes more and more significant both practically and academically, especially in the context of organizational culture and learning. However computational modeling and a formalization of organizational change and learning processes are still largely unexplored. This paper aims to provide an adaptive network model of transformative organizational change and translate a selection of organizational...
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Adaptive Dynamical Systems Modelling of Transformational Organizational Change with Focus on Organizational Culture and Organizational Learning
PublikacjaTransformative Organizational Change becomes more and more significant both practically and academically, especially in the context of organizational culture and learning. However computational modeling and a formalization of organizational change and learning processes are still largely unexplored. This paper aims to provide an adaptive network model of transformative organizational change and translate a selection of organizational...
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E-cigarette use among young adults in Poland: Prevalence and characteristics of e-cigarette users
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Kształcenie hybrydowe - wykorzystanie e-podręczników w dydaktyce na poziomie akademickim
PublikacjaArtykuł porusza problematykę zwiazaną z wykorzystaniem podręczników multimedialnych (e-podreczników) w kształceniu hybrydowym w kontekscie nauczania-uczenia się geometrii wykreślnej na Wydziale Architektury Politechniki Gdanskiej. Pod pojeciem podrecznika multimedialnego autorka rozumie aplikacje stworzone przy użyciu jednej z wielu technologii internetowej lub multimedialnej ((PHP, Ajax, CSS, Flash, Java 2, xHTML) przyjmującej...
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LOS and NLOS identification in real indoor environment using deep learning approach
PublikacjaVisibility conditions between antennas, i.e. Line-of-Sight (LOS) and Non-Line-of-Sight (NLOS) can be crucial in the context of indoor localization, for which detecting the NLOS condition and further correcting constant position estimation errors or allocating resources can reduce the negative influence of multipath propagation on wireless communication and positioning. In this paper a deep learning (DL) model to classify LOS/NLOS...
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Quantitative determination of processed waste expanded perlite performance as a supplementary cementitious material in low emission blended cement composites
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E-Estonia as a role model? Some general considerations and applicability in France
PublikacjaEstonia has recently been widely recognised – in the policy circles, academia, as well as the media space – as one of the more advanced nation states when it comes to digital government (and governance) transformation (e.g. Margetts and Naumann, 2017; Heller, 2017). Ever greater attention Estonia attracted with the two most recent digital government initiatives, namely the e-Residency and the virtual data embassy, both first of...
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Quantitative Risk Assessment in Construction Disputes Based on Machine Learning Tools
PublikacjaA high monetary value of the construction projects is one of the reasons of frequent disputes between a general contractor (GC) and a client. A construction site is a unique, one-time, and single-product factory with many parties involved and dependent on each other. The organizational dependencies and their complexity make any fault or mistake propagate and influence the final result (delays, cost overruns). The constant will...
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Detecting Lombard Speech Using Deep Learning Approach
PublikacjaRobust Lombard speech-in-noise detecting is challenging. This study proposes a strategy to detect Lombard speech using a machine learning approach for applications such as public address systems that work in near real time. The paper starts with the background concerning the Lombard effect. Then, assumptions of the work performed for Lombard speech detection are outlined. The framework proposed combines convolutional neural networks...
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Reinforcement Learning Algorithm and FDTD-based Simulation Applied to Schroeder Diffuser Design Optimization
PublikacjaThe aim of this paper is to propose a novel approach to the algorithmic design of Schroeder acoustic diffusers employing a deep learning optimization algorithm and a fitness function based on a computer simulation of the propagation of acoustic waves. The deep learning method employed for the research is a deep policy gradient algorithm. It is used as a tool for carrying out a sequential optimization process the goal of which is...
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Program rewitalizacji planowanej na terenie Polski śródladowej drogi wodnej E-70
PublikacjaOmówiono zasadnicze problemy wznowienia ruchu transportowego i możliwości wynikające z opracowanych planów rewitalizacji drogi wodnej E-70 wraz z identyfikacją podstawowych barier technicznych.Wskazano kierunki prac majacych na celu aktywizację transportu śródladowego oraz założenia programu strategii rewitalizacji.
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A Computationally Efficient Model for Predicting Successful Memory Encoding Using Machine-Learning-based EEG Channel Selection
PublikacjaComputational cost is an important consideration for memory encoding prediction models that use data from dozens of implanted electrodes. We propose a method to reduce computational expense by selecting a subset of all the electrodes to build the prediction model. The electrodes were selected based on their likelihood of measuring brain activity useful for predicting memory encoding better than chance (in terms of AUC). A logistic...
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Training of Deep Learning Models Using Synthetic Datasets
PublikacjaIn order to solve increasingly complex problems, the complexity of Deep Neural Networks also needs to be constantly increased, and therefore training such networks requires more and more data. Unfortunately, obtaining such massive real world training data to optimize neural networks parameters is a challenging and time-consuming task. To solve this problem, we propose an easy-touse and general approach to training deep learning...
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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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Rebuttal from L. E. K. Ratcliffe, W. Pijacka, F. D. McBryde, A. P. Abdala, D. J. Moraes, P. A. Sobotka, E. C. Hart, K. Narkiewicz, A. K. Nightingale and J. F. R. Paton
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A Proposed Machine Learning Model for Forecasting Impact of Traffic-Induced Vibrations on Buildings
PublikacjaTraffic-induced vibrations may cause various damages to buildings located near the road, including cracking of plaster, cracks in load-bearing elements or even collapse of the whole structure. Measurements of vibrations of real buildings are costly and laborious. Therefore the aim of the research is to propose the original numerical algorithm which allows us to predict, with high probability, the nega-tive dynamic impact of traffic-induced...
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Looking through the past: better knowledge retention for generative replay in continual learning
PublikacjaIn this work, we improve the generative replay in a continual learning setting to perform well on challenging scenarios. Because of the growing complexity of continual learning tasks, it is becoming more popular, to apply the generative replay technique in the feature space instead of image space. Nevertheless, such an approach does not come without limitations. In particular, we notice the degradation of the continually trained...
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Robust and Efficient Machine Learning Algorithms for Visual Recognition
PublikacjaIn visual recognition, the task is to identify and localize all objects of interest in the input image. With the ubiquitous presence of visual data in modern days, the role of object recognition algorithms is becoming more significant than ever and ranges from autonomous driving to computer-aided diagnosis in medicine. Current models for visual recognition are dominated by models based on Convolutional Neural Networks (CNNs), which...
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Longitudinal study of vitamins A, E and lipid oxidative damage in human milk throughout lactation
PublikacjaCelem pracy było zbadanie zmian wartości całkowitego potencjału antyoksydacyjnego (TAS), stężeń witamin antyoksydacyjnych i izoprostanów (markery stresu oksydacyjnego) w siarze i mleku dojrzałym. Badaniami objęto 49 kobiet po pełno terminowej ciąży i naturalnym porodzie. Kryteria wyłączenia to czynne i bierne palenie tytoniu, ostre i przewlekłe schorzeniach oraz farmakoterapia inna niż suplementacja witamin. Próbki siary pobierano...
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Systemy z Uczeniem Maszynowym / Systems with Machine Learning
Kursy Online -
Non-Satellite Broadband Maritime Communications for e-Navigation Services
PublikacjaThe development of broadband network access technologies available to users on land has triggered a rapid expansion of a diverse range of services provided by terrestrial networks. However, due to limitations of digital communication technologies in the off-shore area, the maritime ICT systems evolution so far has not followed that trend. Despite the e-navigation initiative defining the set of Maritime Services, the progress in...
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Fusion-based Representation Learning Model for Multimode User-generated Social Network Content
PublikacjaAs mobile networks and APPs are developed, user-generated content (UGC), which includes multi-source heterogeneous data like user reviews, tags, scores, images, and videos, has become an essential basis for improving the quality of personalized services. Due to the multi-source heterogeneous nature of the data, big data fusion offers both promise and drawbacks. With the rise of mobile networks and applications, UGC, which includes...
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Evaluation of Machine Learning Methods for the Experimental Classification and Clustering of Higher Education Institutions
PublikacjaHigher 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...
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Integrating Experience-Based Knowledge Representation and Machine Learning for Efficient Virtual Engineering Object Performance
PublikacjaMachine learning and Artificial Intelligence have grown significant attention from industry and academia during the past decade. The key reason behind interest is such technologies capabilities to revolutionize human life since they seamlessly integrate classical networks, networked objects and people to create more efficient environments. In this paper, the Knowledge Representation technique of Set of Experience...
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Side Effects of National Immunization Program: E-Governance Support Toward Elders' Digital Inclusion
PublikacjaIn response to the coronavirus pandemic, the European Union (EU) governments develop policies to regulate exclusive health protection actions that consider societal needs with the emphasis on elders. Given that the EU vaccination strategy uses a centralized ICT-based approach, there is little guidance on how seniors are included in national immunization programs (NIP). In this paper, we addressed a knowledge gap of the side effects...
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An Adaptive Network Model Simulating the Effects of Different Culture Types and Leader Qualities on Mistake Handling and Organisational Learning
PublikacjaThis paper investigates computationally the following research hypotheses: (1) Higher flexibility and discretion in organizational culture results in better mistake management and thus better organizational learning, (2) Effective organizational learning requires a transformational leader to have both high social and formal status and consistency, and (3) Company culture and leader's behavior must align for the best learning effects....
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An Adaptive Network Model Simulating the Effects of Different Culture Types and Leader Qualities on Mistake Handling and Organisational Learning
PublikacjaThis paper investigates computationally the following research hypotheses: (1) Higher flexibility and discretion in organizational culture results in better mistake management and thus better organizational learning, (2) Effective organizational learning requires a transformational leader to have both high social and formal status and consistency, and (3) Company culture and leader’s behavior must align for the best learning effects....
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Analysis of the Capability of Deep Learning Algorithms for EEG-based Brain-Computer Interface Implementation
PublikacjaMachine learning models have received significant attention for their exceptional performance in classifying electroencephalography (EEG) data. They have proven to be highly effective in extracting intricate patterns and features from the raw signal data, thereby contributing to their success in EEG classification tasks. In this study, we explore the possibilities of utilizing contemporary machine learning algorithms in decoding...
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e-Technologie w kształceniu inżynierów, czyli nowoczesna edukacja pokolenia mediów cyfrowych
PublikacjaTechnologie informacyjno-komunikacyjne zmieniają współczesną edukację i pozwalają na wprowadzanie innowacyjnych metod przekazywania wiedzy i zdobywania umiejętności. Popyt na wiedzę jest ogromny – kształtuje go coraz bardziej zaawansowane technologicznie i infor - macyjnie społeczeństwo oraz rynek pracy, na którym wiele osób, pracujących w zawodach do tej pory nie wymagających umiejętności cyfrowych, stanęło...
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Losses and power balance in hydraulic satellite motor supplied with oil and HFA-E emulsion
PublikacjaMineral oil and HFA-E emulsion are liquids which differ in viscosity, density and lubricant properties. Therefore, supplying hydraulic satellite motor with these liquids, differences between quantity of hydraulic, volumetric and mechanical losses are observed. These losses influence efficiency of conversion of hydraulic energy into mechanical energy and thereby power balance of motor. The research of satellite motor has been conducted...
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Machine learning for the management of biochar yield and properties of biomass sources for sustainable energy
PublikacjaBiochar 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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Thermal Buckling Analysis of Circular Bilayer Graphene sheets Resting on an Elastic Matrix Based on Nonlocal Continuum Mechanics
PublikacjaIn this article, the thermal buckling behavior of orthotropic circular bilayer graphene sheets embedded in the Winkler–Pasternak elastic medium is scrutinized. Using the nonlocal elasticity theory, the bilayer graphene sheets are modeled as a nonlocal double–layered plate that contains small scale effects and van der Waals (vdW) interaction forces. The vdW interaction forces between the layers are simulated as a set of linear springs...
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A machine learning approach to classifying New York Heart Association (NYHA) heart failure
PublikacjaAccording to the European Society of Cardiology, globally the number of patients with heart failure nearly doubled from 33.5 million in 1990 to 64.3 million in 2017, and is further projected to increase dramatically in this decade, still remaining a leading cause of morbidity and mortality. One of the most frequently applied heart failure classification systems that physicians use is the New York Heart Association (NYHA) Functional...