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Search results for: DESIGNING LEARNING ENVIRONMENTS
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Experimental investigations and prediction of WEDMed surface of nitinol SMA using SinGAN and DenseNet deep learning model
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Efficient Calibration of Cost-Efficient Particulate Matter Sensors Using Machine Learning and Time-Series Alignment
PublicationAtmospheric particulate matter (PM) poses a significant threat to human health, infiltrating the lungs and brain and leading to severe issues such as heart and lung diseases, cancer, and premature death. The main sources of PM pollution are vehicular and industrial emissions, construction and agricultural activities, and natural phenomena such as wildfires. Research underscores the absence of a safe threshold for particulate exposure,...
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Technological vs. Non-Technological Mindsets: Learning From Mistakes, and Organizational Change Adaptability to Remote Work
PublicationThe permanent implementation of the change in working methods, e.g., working in the virtual space, is problematic for some employees and, as a result, for management leaders. To explore this issue deeper, this study assumes that mindset type: technological vs. non-technological, may influence the organizational adaptability to change. Moreover, the key interest of this research is how non-technological mindsets...
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A Novel Spatio–Temporal Deep Learning Vehicle Turns Detection Scheme Using GPS-Only Data
PublicationWhether the computer is driving your car or you are, advanced driver assistance systems (ADAS) come into play on all levels, from weather monitoring to safety. These modern-day ADASs use various assisting tools for drivers to keep the journey safe; these sophisticated tools provide early signals of numerous events, such as road conditions, emerging traffic scenarios, and weather warnings. Many urban applications, such as car-sharing...
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Prediction of Wastewater Quality at a Wastewater Treatment Plant Inlet Using a System Based on Machine Learning Methods
PublicationOne of the important factors determining the biochemical processes in bioreactors is the quality of the wastewater inflow to the wastewater treatment plant (WWTP). Information on the quality of wastewater, sufficiently in advance, makes it possible to properly select bioreactor settings to obtain optimal process conditions. This paper presents the use of classification models to predict the variability of wastewater quality at...
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Towards the 4th industrial revolution: networks, virtuality, experience based collective computational intelligence, and deep learning
PublicationQuo vadis, Intelligent Enterprise? Where are you going? The authors of this paper aim at providing some answers to this fascinating question addressing emerging challenges related to the concept of semantically enhanced knowledge-based cyber-physical systems – the fourth industrial revolution named Industry 4.0.
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Employing Subjective Tests and Deep Learning for Discovering the Relationship between Personality Types and Preferred Music Genres
PublicationThe purpose of this research is two-fold: (a) to explore the relationship between the listeners’ personality trait, i.e., extraverts and introverts and their preferred music genres, and (b) to predict the personality trait of potential listeners on the basis of a musical excerpt by employing several classification algorithms. We assume that this may help match songs according to the listener’s personality in social music networks....
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NLITED - New Level of Integrated Techniques for Daylighting Education: Preliminary Data on the Use of an E-learning Platform
PublicationProject NLITED – New Level of Integrated Techniques for Daylighting Education - is an educational project for students and professionals. The project's objective is to create and develop an online eLearning platform with 32 eModules dedicated to daylight knowledge. The project also offers e-learners two summer school training where the theory is put into practice. The platform was launched on January 31, 2022. The paper...
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Reliable computationally-efficient behavioral modeling of microwave passives using deep learning surrogates in confined domains
PublicationThe importance of surrogate modeling techniques has been steadily growing over the recent years in high-frequency electronics, including microwave engineering. Fast metamodels are employed to speedup design processes, especially those conducted at the level of full-wave electromagnetic (EM) simulations. The surrogates enable massive system evaluations at nearly EM accuracy and negligible costs, which is invaluable in parameter...
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Cleaner energy for sustainable future using hybrid photovoltaics-thermoelectric generators system under non-static conditions using machine learning based control technique
PublicationIn addition to the load demand, the temperature difference between the hot and cold sides of the thermoelectric generator (TEG) module determines the output power for thermoelectric generator systems. Maximum power point tracking (MPPT) control is needed to track the optimal global power point as operating conditions change. The growing use of electricity and the decline in the use of fossil fuels have sparked interest in photovoltaic-TEG...
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Night shifts as a learning experience among nursing students across Europe: Findings from a cross-sectional survey
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E-learning jako narzędzie wspierające kształcenie osób 50+. Rozważania w oparciu o projekt MAYDAY
PublicationRozdział przedstawia zalety i wady szkoleń e-learningowych ze szczególnym uwzględnieniem uczestników w wieku 50+, analizę szkolenia przeprowadzonego w ramach projektu MAYDAY oraz wytyczne i rekomendacje do tworzenia kursów e-learnignowych dla osób powyżej 50-go roku życia.
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Bilingual advantage? Literacy and phonological awareness in Polish-speaking early elementary school children learning English simultaneously
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Presentation of Novel Architecture for Diagnosis and Identifying Breast Cancer Location Based on Ultrasound Images Using Machine Learning
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Perceived technostress while learning a new mobile technology: Do individual differences and the way technology is presented matter?
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Machine Learning-Based Wetland Vulnerability Assessment in the Sindh Province Ramsar Site Using Remote Sensing Data
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Development of advanced machine learning for prognostic analysis of drying parameters for banana slices using indirect solar dryer
PublicationIn this study, eXtreme Gradient Boosting (XGBoost) and Light Gradient Boosting (LightGBM) algorithms were used to model-predict the drying characteristics of banana slices with an indirect solar drier. The relationships between independent variables (temperature, moisture, product type, water flow rate, and mass of product) and dependent variables (energy consumption and size reduction) were established. For energy consumption,...
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A Computationally Efficient Model for Predicting Successful Memory Encoding Using Machine-Learning-based EEG Channel Selection
PublicationComputational 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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Activation of Metabotropic Glutamate Receptor (mGlu2) and Muscarinic Receptors (M1, M4, and M5), Alone or in Combination, and Its Impact on the Acquisition and Retention of Learning in the Morris Water Maze, NMDA Expression and cGMP Synthesis
PublicationThe Morris water maze (MWM) is regarded as one of the most popular tests for detecting spatial memory in rodents. Long-term potentiation and cGMP synthesis seem to be among the crucial factors involved in this type of learning. Muscarinic (M1, M4, and M5 receptors) and metabotropic glutamate (mGlu) receptors are important targets in the search for antipsychotic drugs with the potency to treat cognitive disabilities associated with...
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Uwagi o problemach w nauczaniu projektowania i eksploatacji siłowni okrętowych (referat dyskusyjny) = Remarks on problems in teaching about designing and operating in ship power plant (discursive study).
PublicationW referacie uzasadniono celowość uwzględniania wybranych zagadnień projektowania siłowni w kształceniu studentów wydziałów mechanicznych akademii morskich i zagadnień eksploatacji siłowni w kształceniu studentów odpowiednich wydziałów politechnik.
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Predicting Compressive Strength of Cement-Stabilized Rammed Earth Based on SEM Images Using Computer Vision and Deep Learning
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E-LEARNING AND TEACHING STRATEGIES OF UNIVERSITY TEACHERS. A CASE STUDY IN THE TEACHING OF SPANISH AS A SECOND LANGUAGE IN SLOVAKIA, POLAND AND THE USA
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Deep Learning-based Recalibration of the CUETO and EORTC Prediction Tools for Recurrence and Progression of Non–muscle-invasive Bladder Cancer
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Machine Learning- and Artificial Intelligence-Derived Prediction for Home Smart Energy Systems with PV Installation and Battery Energy Storage
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Personalized prediction of the secondary oocytes number after ovarian stimulation: A machine learning model based on clinical and genetic data
PublicationControlled ovarian stimulation is tailored to the patient based on clinical parameters but estimating the number of retrieved metaphase II (MII) oocytes is a challenge. Here, we have developed a model that takes advantage of the patient’s genetic and clinical characteristics simultaneously for predicting the stimulation outcome. Sequence variants in reproduction-related genes identified by next-generation sequencing were matched...
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Machine Learning Algorithm-Based Tool and Digital Framework for Substituting Daylight Simulations In Early- Stage Architectural Design Evaluation
PublicationThe aim of this paper is to examine the new method of obtaining the simulation-based results using backpropagation of errors artificial neural networks. The primary motivation to conduct the research was to determine an alternative, more efficient and less timeconsuming method which would serve to achieve the results of daylight simulations. Three daylight metrics: Daylight Factor, Daylight Autonomy and Daylight Glare Probability have...
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Weighted Ensemble with one-class Classification and Over-sampling and Instance selection (WECOI): An approach for learning from imbalanced data streams
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Analysis of pedestrian activity before and during COVID-19 lockdown, using webcam time-lapse from Cracow and machine learning
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Determinants of anxiety levels among young males in a threat of experiencing military conflict–Applying a machine-learning algorithm in a psychosociological study
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E-learning przez Internet w szkolnictwie wyższym. Doświadczenia Szkoły Głównej Handlowej w Warszawie i Politechniki Gdańskiej.
PublicationOpisano cztery podstawowe rodzaje e-learningu, przedstawiono strukturę funkcjonalną systemów zarządzania nauczaniem na odległość i zarządzania treścią nauczania (ang. LMS, LCMS) oraz zaprezentowano doświadczenia Szkoły Głównej Handlowej w Warszawie i Politechniki Gdańskiej w nauczaniu na odległość.
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An automated learning model for twitter sentiment analysis using Ranger AdaBelief optimizer based Bidirectional Long Short Term Memory
PublicationSentiment analysis is an automated approach which is utilized in process of analysing textual data to describe public opinion. The sentiment analysis has major role in creating impact in the day-to-day life of individuals. However, a precise interpretation of text still relies as a major concern in classifying sentiment. So, this research introduced Bidirectional Long Short Term Memory with Ranger AdaBelief Optimizer (Bi-LSTM RAO)...
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Flexible Knowledge–Vision–Integration Platform for Personal Protective Equipment Detection and Classification Using Hierarchical Convolutional Neural Networks and Active Leaning
PublicationThis work is part of an effort to develop of a Knowledge-Vision Integration Platform for Hazard Control (KVIP-HC) in industrial workplaces, adaptable to a wide range of industrial environments. The paper focuses on hazards resulted from the non-use of personal protective equipment (PPE). The objective is to test the capability of the platform to adapt to different industrial environments by simulating the process of randomly selecting...
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Socioeconomic and gender inequalities in home learning during the COVID-19 pandemic: examining the roles of the home environment, parent supervision, and educational provisions
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Statistical Data Pre-Processing and Time Series Incorporation for High-Efficacy Calibration of Low-Cost NO2 Sensor Using Machine Learning
PublicationAir pollution stands as a significant modern-day challenge impacting life quality, the environment, and the economy. It comprises various pollutants like gases, particulate matter, biological molecules, and more, stemming from sources such as vehicle emissions, industrial operations, agriculture, and natural events. Nitrogen dioxide (NO2), among these harmful gases, is notably prevalent in densely populated urban regions. Given...
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Paving the Way for A Sustainable and Efficient SiO2/TiO2 Photocatalytic Composite
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Insights into Seawater Biodegradation of Sustainable Mater-Bi/Poly(ε-caprolactone)-Based Biocomposites Filled with Diisocyanate-Modified Cellulose Particles
Publication: Due to rapid economic growth, the use of plastics in almost all areas of human life has significantly increased over recent decades, leading to massive pollution. Therefore, works dealing with sustainable and biodegradable polymer materials are vital now. Herein, sustainable MaterBi/poly(ε-caprolactone) (PCL)-based biocomposites, filled with diisocyanate-modified cellulose particles, were prepared and subjected to 12-week seawater...
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Threats to Rural Landscape and Its Protection in Poland
PublicationThe article describes the premises and conditions for the implementation of a pro-landscape spatial policy in rural areas in Poland. It presents the erosion of spatial order in a large part of the country’s territory. Firstly, the state of protection of the rural landscape and the legal aspects of shaping the space of rural areas are described. Secondly, the location is depicted, and the main physiognomic and environmental threats...
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Investigation of Air Quality beside a Municipal Landfill: The Fate of Malodour Compounds as a Model VOC
PublicationThis paper presents the results of an investigation on ambient air odour quality in the vicinity of a municipal landfill. The investigations were carried out during the spring–winter and the spring seasons using two types of the electronic nose instrument. The field olfactometers were employed to determine the mean odour concentration, which was from 2.1 to 32.2 ou/m3 depending on the measurement site and season of the year. In...
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Currently Commercially Available Chemical Sensors Employed for Detection of Volatile Organic Compounds in Outdoor and Indoor Air
PublicationThe paper presents principle of operation and design of the most popular chemical sensors for measurement of volatile organic compounds (VOCs) in outdoor and indoor air. It describes the sensors for evaluation of explosion risk including pellistors and IR-absorption sensors as well as the sensors for detection of toxic compounds such as electrochemical (amperometric), photoionization and semiconductor with solid electrolyte ones....
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Structural Assessment of Reinforced Concrete Beams Incorporating Waste Plastic Straws
PublicationThe behavior of reinforced concrete beams containing fibers made of waste plastic straws (WPSs) under the three point bending test is examined. The effect of WPS fiber addition on the compressive and split tensile strength is reported. Four concrete mixes were prepared. The control mix PS-0 had a proportion of 1 cement: 1 sand: 2 coarse aggregate and a water cement ratio of 0.4. In the other three mixes PS-0.5, PS-1.5 and PS-3,...
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E-Learning as a Factor Optimizing the Amount of Work Time Devoted to Preparing an Exam for Medical Program Students during the COVID-19 Epidemic Situation
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DevEmo—Software Developers’ Facial Expression Dataset
PublicationThe COVID-19 pandemic has increased the relevance of remote activities and digital tools for education, work, and other aspects of daily life. This reality has highlighted the need for emotion recognition technology to better understand the emotions of computer users and provide support in remote environments. Emotion recognition can play a critical role in improving the remote experience and ensuring that individuals are able...
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How to Design Affect-aware Educational Systems – the AFFINT Process Approach
PublicationComputer systems, that support learning processes, can adapt to the needs and states of a learner. The adaptation might directly address the knowledge deficits and most tutoring systems apply an adaptable learning path of that kind. Apart from a preliminary knowledge state, there are more factors, that influence education effectiveness and among those there are fluctuating emotional states. The tutoring systems may recognize or...
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Using Moodle as a Solution to Interdisciplinary E-collaboration Issues
PublicationRapid technological development in recent years has contributed to numerous changes in many areas of life, including education and communication. Establishing interdisciplinary collaboration brings many benefits, however, it is often associated with numerous problems and inconveniences, as well as the need of constant improvement, lifelong learning, professional development (CPD) and finding an effective way of information transferring....
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Evolving neural network as a decision support system — Controller for a game of “2048” case study
PublicationThe paper proposes an approach to designing the neuro-genetic self-learning decision support system. The system is based on neural networks being adaptively learned by evolutionary mechanism, forming an evolved neural network. Presented learning algorithm enables for a selection of the neural network structure by establishing or removing of connections between the neurons, and then for a finding the beast suited values of the network...
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Factors Affecting the Effectiveness of Military Training in Virtual Reality Environment
PublicationIn this paper, we explored the factors influencing the effectiveness of military trainings performed in a virtual reality environment. The rationale for taking up the topic is the fact that such trainings are often conducted under specific operational procedures. These procedures may create rigorous frameworks for all elements of the learning environment, including the teacher’s performance. Therefore, to ensure the most conducive...
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Predicting the Purchase of Electricity Prices for Renewable Energy Sources Based on Polish Power Grids Data Using Deep Learning Models for Controlling Small Hybrid PV Microinstallations
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Book Review
PublicationActing over the last three decades as an Editor and Associate Editor for a number of international journals in the general area of cybernetics and AI, as well as a Chair and Co-Chair of numerous conferences in this field, I have had the exciting opportunity to closely witness and to be actively engaged in the stimulating research area of machine learning and its important augmentation with deep learning techniques and technologies. From...
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Webquest- dobra praktyka w e-Learningu
PublicationW dobie informatyzacji i pokonywania barier wdrażania e-technologii na uczelniach wyższych uważa się, że jedną z najczęściej stosowanych aktywizujących technik nauczania wśród nauczycieli akademickich jest metoda projektu (ang. project-based learning). W niniejszym opracowaniu proponuje się zastosowanie w procesie edukacji na wyższej uczelni, metody webquest. Jest ona dużo rzadziej stosowana w praktyce. Opracowano ją w oparciu...
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POSITIVE PSYCHOLOGICAL CAPITAL ENHANCES THRIVING IN THE MULTICULTURAL WORK ENVIRONMENT OF MULTINATIONAL CORPORATIONS
PublicationThe aim of the paper is to examine positive psychological capital (PsyCap) as well as individual factors in the relationship with thriving in the multicultural work environment of multinational corporations (MNCs). We conducted a quantitative study on the sample of 127 individuals from subsidiaries of various MNCs located in Poland and involved in intercultural interactions. The results of cross-sectional study show that employees...