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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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Prediction of fracture toughness in fibre-reinforced concrete, mortar, and rocks using various Machine learning techniques
PublicationMachine Learning (ML) method is widely used in engineering applications such as fracture mechanics. In this study, twenty different ML algorithms were employed and compared for the prediction of the fracture toughness and fracture load in modes I, II, and mixed-mode (I-II) of various materials, including fibre-reinforced concrete, cement mortar, sandstone, white travertine, marble, and granite. A set of 401 specimens of “Brazilian...
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Satellite Image Classification Using a Hierarchical Ensemble Learning and Correlation Coefficient-Based Gravitational Search Algorithm
PublicationSatellite image classification is widely used in various real-time applications, such as the military, geospatial surveys, surveillance and environmental monitoring. Therefore, the effective classification of satellite images is required to improve classification accuracy. In this paper, the combination of Hierarchical Framework and Ensemble Learning (HFEL) and optimal feature selection is proposed for the precise identification...
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Prediction of energy consumption and evaluation of affecting factors in a full-scale WWTP using a machine learning approach
PublicationTreatment of municipal wastewater to meet the stringent effluent quality standards is an energy-intensive process and the main contributor to the costs of wastewater treatment plants (WWTPs). Analysis and prediction of energy consumption (EC) are essential in designing and operating sustainable energy-saving WWTPs. In this study, the effect of wastewater, hydraulic, and climate-based parameters on the daily consumption of EC by...
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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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Fast Fading Influence on the Deep Learning-Based LOS and NLOS Identificationin Wireless Body Area Networks
PublicationIn the article, the fast fading influence on the proposed DL (Deep Learning) approach for LOS (Line-of-Sight) and NLOS (Non-Line-of-Sight) conditions identification in Wireless Body Area Networks is investigated. The research was conducted on the basis of the off-body communication measurements using the developed mobile measurement stand, in an indoor environment for both static and dynamic scenarios. The measurements involved...
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Big Data from Sensor Network via Internet of Things to Edge Deep Learning for Smart City
PublicationData 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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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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Uczenie na błędach w nauczaniu programowania w systemie e-learningu
PublicationJedną z kluczowych umiejętności, które muszą posiąść adepci programowania, stanowi umiejętność poprawiania kodu programu zawierającego błędy. Jest to działanie bardzo złożone, wymagające znajomości składni języka, rozumienia semantyki kodu, znajomości zasad testowania oraz rozumienia działania algorytmu. W artykule autor proponuje własną metodę kształtowania umiejętności poprawiania kodu programu wykorzystującą narzędzia do nauczania...
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UK travel agents’ evaluation of eLearning courses offered by destinations: an exploratory study.
PublicationThis study aims to develop an understanding of the use of e-learning courses created for travel agents by Destination Management Organizations (DMOs). It explores agents’ perceptions of such courses. The research examines the views of 304 UK-based travel agents using online survey and investigates whether age, sex, type of agency, work experience, and educational level have influence on e-learning uptake. The satisfaction of travel...
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Two-step Conversion of Crude Glycerol Generated by Biodiesel Production into Biopolyols: Synthesis, Structural and Physical Chemical Characterization
PublicationIn this work biopolyols were synthesized via two-step process from crude glycerol and castor oil. For better evaluation of analyzed process, the impact of its time and temperature on the structure and properties of biopolyols was determined. Obtained results fully justified conducting of synthesis in two steps. Prepared materials were characterized by hydroxyl value and water content comparable to polyols industrially applied in...
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Diagnostics of UV Nanosecond Laser Generated Plasma Plume Dynamics in Ambient Air Using Time-Resolved Imaging
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Preparation of gaseous standard mixtures: methods for controlling the amount of components generated in the process of thermal decomposition of immobilized compounds.
PublicationGazowe mieszaniny wzorcowe odgrywają ważną rolę w ocenie metod analitycznych i urządzeń pomiarowych. W tym przypadku gazowe mieszaniny wzorcowe mogą być traktowane jako specjalny rodzaj materiału odniesienia.Proces walidacji wymaga użycia tzw. matrycowych materiałów odniesienia. Wybór techniki umożliwiającej uzyskanie gazowej mieszaniny wzorcowej o żądanych parametrach użytkowych zależy od natury składników mierzonych i gazu...
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Direct Current Atmospheric Pressure Microdischarge Generated between a Miniature Flow Helium Microjet and a Flowing Liquid Cathode
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Influence of Ultrasound on the Characteristics of CaP Coatings Generated Via the Micro-arc Oxidation Process in Relation to Biomedical Engineering
PublicationOver the past decade, bone tissue engineering has been at the core of attention because of an increasing number of implant surgeries. The purpose of this study was to obtain coatings on titanium (Ti) implants with improved properties in terms of biomedical applications and to investigate the effect of ultrasound (US) on these properties during the micro-arc oxidation (MAO) process. The influence of various process parameters, such...
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Migration of trace elements and radioisotopes to various fractions of solid wastes generated as a result of the sewage sludge incineration process
PublicationThe research was aimed at providing new knowledge in the field of chemical characteristics of solid waste generated in the process of combustion of sewage sludge in fluidized bed furnaces. The research material consisted of disposed fluidized beds (DFB), sewage sludge ash (SSA) and air pollution control residues (APC) from three Polish installations for the thermal treatment of sewage sludge. Natural radionuclides as well as anthropogenic...
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Dipeptidyl Peptidase IV Inhibitory Peptides Generated in Dry-Cured Pork Loin during Aging and Gastrointestinal Digestion
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One dimensional coordination polymers generated from Cd(II) tri-tert-butoxysilanethiolates and flexible aliphatic diamines.
PublicationPraca ta dotyczy chemii koordynacyjnej tri-tert-butoksysilanotiolanu kadmu(II) z diaminami alifatycznymi. Reakcja dwucentowego [Cd{SSi(OtBu)3}2]2 z poszczególnymi diaminami pozwala otrzymać pięć nowych obojętnych jednowymiarowych polimerów koordynacyjnych o różnej topologii łańcuchów [Cd{SSi(OtBu)3}2(μ-C4H12N2)(CH3OH)]n (1), [Cd{SSi(OtBu)3}2(μ-C5H14N2)(CH3OH)]n (2) [Cd{SSi(OtBu)3}2(μ-C6H16N2)(CH3OH)]n (3), [Cd{SSi(OtBu)3}2(μ-C7H18N2)]n...
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The estimation of total volatile organic compounds emissions generated from peroxide cured natural rubber/polycaprolactone blends
PublicationNatural rubber (NR)/polycaprolactone (PCL) blends at the ratio of 90/10% wt. (NR/PCL90/10) and 70/30% wt. (NR/PCL70/30), with a constant amount of dicumyl peroxide, were prepared by compounding in an internal mixer. Obtained NR/PCL bio-based blends were cured at three different temperatures (150 °C, 160 °C and 170 °C). The total content of volatile organic compounds (TVOC) as a function of the NR/PCL blends ratio, and their curing...
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Analysis of catalitic reactors usefulness to reduce pollution generated by piston combustion engines with regard to ship main engines
PublicationThe article presents results which indicate that the use of catalytic reactors to reduce emissions of harmful compunds contained in the exhaust gas is important in the operation of vehicle motors operation. Efforts of the shipbuilding industry to reduce the toxicity of exhaust gas emitted by the main engines have been indicated and pointed to the desirability of the use of these catalysts in maritime transport. It has been pointed...
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A pilot study to assess manufacturing processes using selected point measures of vibroacoustic signals generated on a multitasking machine
PublicationThe article presents the method for the evaluation of selected manufacturing processes using the analysis of vibration and sound signals. This method is based on the use of sensors installed outside the machining zone, allowing to be used quickly and reliably in real production conditions. The article contains a developed measurement methodology based on the specific location of microphones and vibration transducers mounted on...
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ASSESSING THE POTENTIAL REPLACEMENT OF MINERAL OIL WITH ENVIRONMENTALLY ACCEPTABLE LUBRICANTS IN A STERN TUBE BEARING: AN EXPERIMENTAL ANALYSIS OF BEARING PERFORMANCE
PublicationT his study compares the performance of a plain bearing, with a similar structure to a tail shaft stern bearing, lubricated with either mineral oil or an environmentally acceptable lubricant (EAL). The main characteristic of the bearing is its length/diameter ratio of <1. Measurements are carried out with the bearing operating under loads from 0.5 to 1 MPa and seven speeds ranging from 1 to 11 rev/s. The bearing lubricated...
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Bilingual advantage? Literacy and phonological awareness in Polish-speaking early elementary school children learning English simultaneously
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Fault diagnosis of marine 4-stroke diesel engines using a one-vs-one extreme learning ensemble
PublicationThis paper proposes a novel approach for intelligent fault diagnosis for stroke Diesel marine engines, which are commonly used in on-road and marine transportation. The safety and reliability of a ship's work rely strongly on the performance of such an engine; therefore, early detection of any type of failure that affects the engine is of crucial importance. Automatic diagnostic systems are of special importance because they can...
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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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Machine Learning-Based Wetland Vulnerability Assessment in the Sindh Province Ramsar Site Using Remote Sensing Data
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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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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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Presentation of Novel Architecture for Diagnosis and Identifying Breast Cancer Location Based on Ultrasound Images Using Machine Learning
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Improving the prediction of biochar production from various biomass sources through the implementation of eXplainable machine learning approaches
PublicationExamining the game-changing possibilities of explainable machine learning techniques, this study explores the fast-growing area of biochar production prediction. The paper demonstrates how recent advances in sensitivity analysis methodology, optimization of training hyperparameters, and state-of-the-art ensemble techniques have greatly simplified and enhanced the forecasting of biochar output and composition from various biomass...
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The chemistry, properties and performance of flame-retardant rubber composites: Collecting, analyzing, categorizing, machine learning modeling, and visualizing
PublicationRubbers combine the flexibility with mechanical strength, supporting myriad applications, but suffer from inherent flammability. Formulation and production of flame-retardant rubber composites (FRRCs) have intensively been practiced over years, but not comprehensively reviewed. This necessity has outlined collecting, analyzing, screening, classifying, and interpreting the literature with the aim of classifying the FRRCs. We quantified...
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Cost-Efficient Multi-Objective Design of Miniaturized Microwave Circuits Using Machine Learning and Artificial Neural Network
PublicationDesigning microwave components involves managing multiple objectives such as center frequencies, impedance matching, and size reduction for miniaturized structures. Traditional multi-objective optimization (MO) approaches heavily rely on computationally expensive population-based methods, especially when exe-cuted with full-wave electromagnetic (EM) analysis to guarantee reliability. This paper introduces a novel and cost-effective...
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Machine Learning-Based Wetland Vulnerability Assessment in the Sindh Province Ramsar Site Using Remote Sensing Data
PublicationWetlands provide vital ecological and socioeconomic services but face escalating pressures worldwide. This study undertakes an integrated spatiotemporal assessment of the multifaceted vulnerabilities shaping Khinjhir Lake, an ecologically significant wetland ecosystem in Pakistan, using advanced geospatial and machine learning techniques. Multi-temporal optical remote sensing data from 2000 to 2020 was analyzed through spectral...
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Improving platelet‐RNA‐based diagnostics: a comparative analysis of machine learning models for cancer detection and multiclass classification
PublicationLiquid biopsy demonstrates excellent potential in patient management by providing a minimally invasive and cost-effective approach to detecting and monitoring cancer, even at its early stages. Due to the complexity of liquid biopsy data, machine-learning techniques are increasingly gaining attention in sample analysis, especially for multidimensional data such as RNA expression profiles. Yet, there is no agreement in the community...
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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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Night shifts as a learning experience among nursing students across Europe: Findings from a cross-sectional survey
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An Adaptive Network Model Simulating the Effects of Different Culture Types and Leader Qualities on Mistake Handling and Organisational Learning
PublicationThis 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
PublicationThis 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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Exploring the factor structure and the validity of the abbreviated Basic and Earning Self-Esteem Scales
PublicationThe original longer versions (Forsman & Johnson, 1996) and abbreviated versions of the Basic and Earning Self-Esteem Scales have been used in clinical and non-clinical settings, but little is known about the factor structure and the validity of these scales in their abbreviated forms. The original longer versions of the scales comprise several dimensions, but both abbreviated versions of the scales have been interpreted as if they...
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Compressive Strength and Leaching Behavior of Mortars with Biomass Ash
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Shales Leaching Modelling for Prediction of Flowback Fluid Composition
PublicationThe object of the paper is the prediction of flowback fluid composition at a laboratory scale, for which a new approach is described. The authors define leaching as a flowback fluid generation related to the shale processing. In the first step shale rock was characterized using X-ray fluorescence spectroscopy, X-ray diractometry and laboratory analysis. It was proven that shale rock samples taken from the selected sections of horizontal...
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Microfiltration of post-fermentation broth with backflushing membrane cleaning
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INFLUENCE OF TIME ON THE BEARING CAPACITY OF PRECAST PILES
PublicationOne of the most popular types of foundations in layered subsoil with very differentiated soil shear strengths are precast piles. One of the reasons is a fact that we can well control the driving process during the installation of these piles. The principles of the assessment of bearing capacity and settlements of the piles given by Eurocode 7, concentrate on two main methods, i.e. Static Pile Load Tests (SPLT) and Dynamic Driving...
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Modeling of acoustics of hearing aid earmold systems
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Waveguide modeling as a tool for fitting a hearing aid
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HYDROSTATIC THRUST BEARING WITH REDUCED POWER LOSSES
PublicationIn many cases in rotating machinery, axial load is carried by tilting pad thrust bearings which have been developed since the beginning of 20th century. For high reliability and simplicity, most commonly the bearings are bath lubricated. In the times of sustainable development, however, minimization of friction losses becomes an important criterion for machinery assessment, and a strategic goal of their development. Performed calculations,...
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Poroelastic Material for Urban Roads Wearing Courses
PublicationConventional road materials used for producing wearing courses of roads are based on mineral aggregate and bituminous or Portland cement binders. The road materials must be optimized for different properties, including skid resistance, durability, rolling resistance and tire/road noise. Unfortunately, it seems that within classic technologies it is very difficult to achieve further reduction of tire/road noise. Innovative porous...
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Loudness Scaling Tests in Hearing Problems Detection
PublicationThe number of people using portable audio players has increased significantly over the recent years. This implies the rise in the number of people having hearing loss problems. Therefore, there is a need to find appropriate procedures that simplify the process of the hearing problem detection. Investigations performed show that audiometric tests may not be sufficient to assess hearing in young people. Contrarily, the obtained results...
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Expert media approach to hearing aids fitting
PublicationW artykule zaprezentowano problematykę dopasowania protez słuchu. Przedstawiono system ekspercki, który pozwala na znalezienie charakterystyk aparatu słuchowego adekwatnego do uszkodzenia słuchu. System został oparty o metodę zbiorów przybliżonych i logikę rozmytą.