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Wyniki wyszukiwania dla: blended e-learning
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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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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 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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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...
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Strategic Flexibility as a Mediator in Relationship between Managerial Decisions and Organizational Learning: Ambidexterity Perspective
PublikacjaPurpose: The purpose of the article is to determine strategic flexibility in the relationship between managerial decisions and organizational learning. The analyses are conducted in the ambidexterity convection. Design/Methodology/Approach: The study was conducted at a textile company. The company is a leader in the textile recycling industry in Poland. Empirical data were collected using the PAPI technique. The survey questionnaire...
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Learning and memory processes in autonomous agents using an intelligent system of decision-making
PublikacjaThis 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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Learning and memory processes in autonomous agents using an intelligent system of decision-making
PublikacjaThis 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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Online Learning Based on Prototypes
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Distributed Learning with Data Reduction
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Deep Learning Approaches in Histopathology
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Position Estimation in Mixed Indoor-Outdoor Environment Using Signals of Opportunity and Deep Learning Approach
PublikacjaTo improve the user's localization estimation in indoor and outdoor environment a novel radiolocalization system using deep learning dedicated to work both in indoor and outdoor environment is proposed. It is based on the radio signatures using radio signals of opportunity from LTE an WiFi networks. The measurements of channel state estimators from LTE network and from WiFi network are taken by using the developed application....
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Noise profiling for speech enhancement employing machine learning models
PublikacjaThis paper aims to propose a noise profiling method that can be performed in near real-time based on machine learning (ML). To address challenges related to noise profiling effectively, we start with a critical review of the literature background. Then, we outline the experiment performed consisting of two parts. The first part concerns the noise recognition model built upon several baseline classifiers and noise signal features...
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Czy należy bać się E?
PublikacjaW ciągu ostatnich lat nastąpił gwałtowny rozwój rynku żywnościowego. Producenci chcąc utrzymać się na rynku dopasowują się do nowych wymagań i rosnących potrzeb konsumenta. Duża konkurencja w branży żywnościowej zmusza wytwórców do ciągłego obniżania kosztów produkcji przy jednoczesnym zachowaniu atrakcyjności wyrobu. Obecnie można kupić niemal wszystko: kilka rodzajów chleba, masła, serów, wędlin i... czego tylko dusza zapragnie....
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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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Remote learning among students with and without reading difficulties during the initial stages of the COVID-19 pandemic
PublikacjaThis article presents the results of a survey on yet under-researched aspects of remote learning and learning difficulties in higher education during the initial stage (March – June 2020) of the COVID-19 pandemic. A total of 2182 students from University of Warsaw in Poland completed a two-part questionnaire regarding academic achievements in the academic year 2019/2020, living conditions and stress related to learning and pandemic,...
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Primary role identification in e-mail networks using pattern subgraphs and sequence diagrams
PublikacjaSocial networks often forms very complex structures that additionally change over time. Description of actors' roles in such structures requires to take into account this dynamics reflecting behavioral characteristics of the actors. A role can be defined as a sequence of different types of activities. Various types of activities are modeled by pattern subgraphs, whereas sequences of these activities are modeled by sequence diagrams....
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Big Data from Sensor Network via Internet of Things to Edge Deep Learning for Smart City
PublikacjaData from a physical world is sampled by sensor networks, and then streams of Big Data are sent to cloud hosts to support decision making by deep learning software. In a smart city, some tasks may be assigned to smart devices of the Internet of Things for performing edge computing. Besides, a part of workload of calculations can be transferred to the cloud hosts. This paper proposes benchmarks for division tasks between an edge...
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Machine Learning Applied to Aspirated and Non-Aspirated Allophone Classification—An Approach Based on Audio "Fingerprinting"
PublikacjaThe purpose of this study is to involve both Convolutional Neural Networks and a typical learning algorithm in the allophone classification process. A list of words including aspirated and non-aspirated allophones pronounced by native and non-native English speakers is recorded and then edited and analyzed. Allophones extracted from English speakers’ recordings are presented in the form of two-dimensional spectrogram images and...
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Przetwarzanie emocjonalne i scenariusze jego zastosowania w edukacji i e-edukacji
PublikacjaW pracy zbadano możliwości i celowość zastosowania mechanizmów i narzędzi przetwarzania emocjonalnego w e-edukacji. Wyróżniono i opisano szereg scenariuszy użycia technik afektywnych, zarówno w zastosowaniu komputerów do wspomagania tradycyjnych procesów edukacyjnych, jak i do nauczania za pośrednictwem środków elektronicznych. Jedne z najciekawszych zastosowań dotyczą poszukiwania optymalnej afektywnej przestrzeni uczenia się,...
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Investigation of educational processes with affective computing methods
PublikacjaThis paper concerns the monitoring of educational processes with the use of new technologies for the recognition of human emotions. This paper summarizes results from three experiments, aimed at the validation of applying emotion recognition to e-learning. An analysis of the experiments’ executions provides an evaluation of the emotion elicitation methods used to monitor learners. The comparison of affect recognition algorithms...
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Real and Virtual Instruments in Machine Learning – Training and Comparison of Classification Results
PublikacjaThe continuous growth of the computing power of processors, as well as the fact that computational clusters can be created from combined machines, allows for increasing the complexity of algorithms that can be trained. The process, however, requires expanding the basis of the training sets. One of the main obstacles in music classification is the lack of high-quality, real-life recording database for every instrument with a variety...
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Deep Learning-Based LOS and NLOS Identification in Wireless Body Area Networks
PublikacjaIn this article, the usage of deep learning (DL) in ultra-wideband (UWB) Wireless Body Area Networks (WBANs) is presented. The developed approach, using channel impulse response, allows higher efficiency in identifying the direct visibility conditions between nodes in off-body communication with comparison to the methods described in the literature. The effectiveness of the proposed deep feedforward neural network was checked on...
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Machine learning-based prediction of preplaced aggregate concrete characteristics
PublikacjaPreplaced-Aggregate Concrete (PAC) is a type of preplaced concrete where coarse aggregate is placed in the mold and a Portland cement-sand grout with admixtures is injected to fill the voids. Due to the complex nature of PAC, many studies were conducted to determine the effects of admixtures and the compressive and tensile strengths of PAC. Considering that a prediction tool is needed to estimate the compressive and tensile...
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Machine learning-based prediction of preplaced aggregate concrete characteristics
PublikacjaPreplaced-Aggregate Concrete (PAC) is a type of preplaced concrete where coarse aggregate is placed in the mold and a Portland cement-sand grout with admixtures is injected to fill the voids. Due to the complex nature of PAC, many studies were conducted to determine the effects of admixtures and the compressive and tensile strengths of PAC. Considering that a prediction tool is needed to estimate the compressive and tensile strengths...
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Platelet RNA Sequencing Data Through the Lens of Machine Learning
PublikacjaLiquid biopsies offer minimally invasive diagnosis and monitoring of cancer disease. This biosource is often analyzed using sequencing, which generates highly complex data that can be used using machine learning tools. Nevertheless, validating the clinical applications of such methods is challenging. It requires: (a) using data from many patients; (b) verifying potential bias concerning sample collection; and (c) adding interpretability...
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Deep learning-based waste detection in natural and urban environments
PublikacjaWaste pollution is one of the most significant environmental issues in the modern world. The importance of recycling is well known, both for economic and ecological reasons, and the industry demands high efficiency. Current studies towards automatic waste detection are hardly comparable due to the lack of benchmarks and widely accepted standards regarding the used metrics and data. Those problems are addressed in this article by...
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Giovanni Antonio Dosio a Napoli e un sepolcro per Stanislao Rescius, umanista e diplomatico polacco.
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