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The application of a photopolymer material for the manufacture of machine elements using rapid prototyping techniques
PublikacjaThe paper discusses the application of polymer resin for 3D printing. The first section focuses on rapid prototyping technique and properties of the photopolymer, used as input material in the manufacture of machine components. Second part of the article was devoted to exemplary 3-D-printed elements for incorporation in machines. The article also contains detailed description of problems encountered in implementation of the selected...
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MP3vec: A Reusable Machine-Constructed Feature Representation for Protein Sequences
Publikacja—Machine Learning (ML) methods have been used with varying degrees of success on protein prediction tasks, with two inherent limitations. First, prediction performance often depends upon the features extracted from the proteins. Second, experimental data may be insufficient to construct reliable ML models. Here we introduce MP3vec, a transferable representation for protein sequences that is designed to be used specifically for sequence-to-sequence...
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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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SiC-based phase-shift dual half bridge DC-DC converter as a key component of multilevel cascaded MV converters
PublikacjaThe paper describes SiC-based dual half bridge (DHB) DC-DC converter considered as a key component of high frequency isolated multilevel cascaded medium voltage converters. Two topologies of bi-directional DC-DC converters: the resonant half-bridge DC-DC converter and the phase-shift DHB converter are compared in the paper. Experimental results of SiC-based 50 kHz DHB DC-DC converter are presented in the paper.
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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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Broad Stopband, Low-Loss, and Ultra-Compact Dual-Mode Bandpass Filter Based on HMSIRC
PublikacjaIn this investigation, an ultra-compact dual-mode bandpass filter (BPF) with a wide stopband re-sponse is realized by using a half-mode substrate-integrated rectangular cavity (HMSIRC). The HMSIRC resonator is designed with a cavity that is rectangular in shape and has metallic vias along three of the sides. The fourth side is open-ended and contains microstrip feed lines. For the purpose of constructing a magnetic wall, a rectangular...
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Graphitic carbon nitride nanosheets decorated with HAp@Bi2S3 core–shell nanorods: Dual S-scheme 1D/2D heterojunction for environmental and hydrogen production solutions
PublikacjaBy combining different semiconductors, scientists have developed innovative materials capable of converting solar energy into useful forms of energy or driving chemical reactions that clean up pollutants. These materials offer a promising path to combat global environmental and energy challenges. In this study, HAp@Bi2S3 core–shell structures were synthesized using a facile microemulsion technique, and then loaded onto graphitic...
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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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Machine-aided detection of SARS-CoV-2 from complete blood count
PublikacjaThe current gold standard for SARS-CoV-2 detection methods lacks the functionality to perform population screening. Complete blood count (CBC) tests are a cost-effective way to reach a wide range of people – e.g. according to the data of the Central Statistical Office of Poland from 2016, there are 3,000 blood diagnostic laboratories in Poland, and 46% of Polish people have at least one CBC test per year. In our work, we show...
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Optical method supported by machine learning for urinary tract infection detection and urosepsis risk assessment
PublikacjaThe study presents an optical method supported by machine learning for discriminating urinary tract infections from an infection capable of causing urosepsis. The method comprises spectra of spectroscopy measurement of artificial urine samples with bacteria from solid cultures of clinical E. coli strains. To provide a reliable classification of results assistance of 27 algorithms was tested. We proved that is possible to obtain...
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Numerical methodology for evaluation the combustion and emissions characteristics on WLTP in the light duty dual-fuel diesel vehicle
PublikacjaThe worldwide aim of reducing environmental impact from internal combustion engines bring more and more stringent emission regulations. In 2017 by EU has been adopted new harmonized test procedure called WLTP. In general terms this test was designed for determining the levels of harmful emissions and fuel consumption of traditional and hybrid cars. This procedure contains specific driving scenarios which representing reallife driving...
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Machine Learning and Deep Learning Methods for Fast and Accurate Assessment of Transthoracic Echocardiogram Image Quality
PublikacjaHigh-quality echocardiogram images are the cornerstone of accurate and reliable measurements of the heart. Therefore, this study aimed to develop, validate and compare machine learning and deep learning algorithms for accurate and automated assessment of transthoracic echocardiogram image quality. In total, 4090 single-frame two-dimensional transthoracic echocardiogram...
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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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Study of various machine learning approaches for Sentinel-2 derived bathymetry
PublikacjaIn recent years precise and up-to-date information regarding seabed depth has become more and more important for companies and institutions that operate on coastlines. While direct, in-situ measurements are performed regularly, they are expensive, time-consuming and impractical to be performed in short time intervals. At the same time, an ever-increasing amount of satellite imaging data becomes available. With these images, it...
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Dual-Polarized Wideband Bandpass Metasurface-Based Filter
PublikacjaThis paper presents a novel metasurface-based bandpass filter. The structure is realized by simply patterning a double-sided AD250 substrate, and does not require any vias or insertion of lumped elements. The top layer is an annular- aperture-array with multiple inner conductors, whereas the bottom layer is a first-order Hilbert-curve array. FEM-based simulation results of the filter are obtained using HFSS. The experimental validation...
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Impedance matching in dual-frequency induction heating systems
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DUABI - Business Intelligence Architecture for Dual Perspective Analytics
PublikacjaA significant expansion of Big Data and NoSQL databases made it necessary to develop new architectures for Business Intelligence systems based on data organized in a non-relational way. There are many novel solutions combining Big Data technologies with Data Warehousing. However, the proposed solutions are often not sufficient enough to meet the increasing business demands, such as low data latency while still maintaining high...
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Localization of sound sources with dual acoustic vector sensor
PublikacjaThe aim of the work is to estimate the position of sound sources. The proposed method uses a setup of two acoustic vector sensors (AVS). The intersection of azimuth rays from each AVS should indicate the position of a source. In practice, the result of position estimation using this method is an area rather than a point. This is a result of inaccuracy of the individual sensors, but more importantly, of the influence of a source...
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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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High Efficiency Dual-Active-Bridge Converter with Triple-Phase-Shift Control for Battery Charger of Electric Vehicles
PublikacjaAn optimal modulation scheme with triple-phase-shift (TPS) control could increase the efficiency in the entire load range for a dual-active-bridge (DAB) converter under wide output voltage range conditions. Therefore, this study proposes a convergent approach to TPS mode selection, coupled with an optimal modulation scheme, ensuring the circuit’s efficiency over the entire range in the realm of a high-power and high-efficiency...
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Morphology control via dual solvent crystallization for high-mobility functionalized pentacene-blend thin film transistors
PublikacjaWe present an approach to improving the performance of solution processed organic semiconductor transistors based on a dual solvent system. We here apply this to a blend containing the π-conjugated small molecule 6,13 bis(triisopropylsilylethynyl) pentacene (TIPS-pentacene) and polystyrene, which acts as an inert binder. Using a semiconductor-binder solution of two solvents, where the main solvent is a better solvent of the small...
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COVID-19 severity forecast based on machine learning and complete blood count data
PublikacjaProper triage of COVID-19 patients is a key factor in eective case management, especially with limited and insucient resources. In this paper, we propose a machine-aided diagnostic system to predict how badly a patient with COVID-19 will develop disease. The prognosis of this type is based on the parameters of commonly used complete blood count tests, which makes it possible to obtain data from a wide range of patients.We chose...
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COVID-19 severity forecast based on machine learning and complete blood count data
PublikacjaProper triage of COVID-19 patients is a key factor in eective case management, especially with limited and insucient resources. In this paper, we propose a machine-aided diagnostic system to predict how badly a patient with COVID-19 will develop disease. The prognosis of this type is based on the parameters of commonly used complete blood count tests, which makes it possible to obtain data from a wide range of patients.We chose...
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Balancing energy consumption in limited power grid with active front-end and three phase dual active bridge system
PublikacjaPaper deals with simulation analysis of bidirectional power converters system for charging station of electric vehicle in condition of limited power source in city infrastructure. In case of incapability to provide additional power supply through the grid by virtue of historical, architectural and economic reasons it is possible to solve this issue by implementation of mobile battery-powered supply source. The proposed bidirectional...
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Low-Loss 3D-Printed Waveguide Filters Based on Deformed Dual-Mode Cavity Resonators
PublikacjaThis paper introduces a new type of waveguide filter with smooth profile, based on specially designed dual-mode (DM) cavity resonators. The DM cavity design is achieved by applying a shape deformation scheme. The coupling between the two orthogonal cavity modes is implemented by breaking the symmetry of the structure, thus eliminating the need for additional coupling elements. The modes operating in the cavity are carefully analyzed...
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The methodology for determining of the value of cutting power for cross cutting on optimizing sawing machine
PublikacjaIn the article the methodology of forecasting the energy effects of the cross-cutting process using the classical method, which takes into account the specific cutting resistance, is presented. The values of cutting power for the cross-cutting process of two types of wood (softwood and hardwood) were forecasted for the optimizing sawing machine with using presented methodology. The cross-cutting process with high values of feed...
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Application of Support Vector Machine for Determination of Impact of Traffic-Induced Vibrations on Buildings
PublikacjaThe aim of the article is to present an algorithm of Support Vector Machine created to forecast the impact of traffic-induced vibrations on residential buildings. The method is designed to classify the object into one of two classes. The classification into the first class means that there is no impact of vibrations on the building, while classification to the second class indicates the possible influence and suggests the execution...
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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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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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Influence of the steam within seals and glands of the turbine on its rotor motion stability.
PublikacjaPrzedstawiono metodę obliczania charakterystyk dynamicznych wpływu parowych uszczelnień turbin na ich dynamikę i stateczność ruchu wirników. Zarysowano model ''masowy'' uszczelnienia. Podano przykłady zastosowań.
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Unsteady aerodynamic forces acting on the rotor blades in the turbine stagewith steam extraction.
PublikacjaPrzeprowadzono analizę niestacjonarnych wymuszeń działających na łopatki wirnikowe w stopniu z upustem turbiny 13UC100. Niestacjonarne siły zostały wyznaczone dla 4 punktów pracy upustu. Wskazano na możliwą przyczynę zaistniałego zniszczenia łopatek wirnikowych turbiny.
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Dual-Setting Bone Cement Based On Magnesium Phosphate Modified with Glycol Methacrylate Designed for Biomedical Applications
PublikacjaMagnesium phosphate cement (MPC) is a suitable alternative for the currently used calcium phosphates, owing to beneficial properties like favorable resorption rate, fast hardening, and higher compressive strength. However, due to insufficient mechanical properties and high brittleness, further improvement is still expected. In this paper, we reported the preparation of a novel type of dual-setting cement based on MPC with poly(2-hydroxyethyl...
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Reduced-cost surrogate modeling of input characteristics and design optimization of dual-band antennas using response features
PublikacjaIn this article, a procedure for low-cost surrogate modeling of input characteristics of dual-band antennas has been discussed. The number of training data required for construction of an accurate model has been reduced by representing the antenna reflection response to the level of suitably defined feature points. The points are allocated to capture the critical features of the reflection characteristic, such as the frequencies...
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DNAffinity: a machine-learning approach to predict DNA binding affinities of transcription factors
PublikacjaWe present a physics-based machine learning approach to predict in vitro transcription factor binding affinities from structural and mechanical DNA properties directly derived from atomistic molecular dynamics simulations. The method is able to predict affinities obtained with techniques as different as uPBM, gcPBM and HT-SELEX with an excellent performance, much better than existing algorithms. Due to its nature, the method can...
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A LUMPED-CIRCUIT MODEL OF CIRCULAR PISTON TRANSDUCER FOR MODELING ITS PERFORMANCE IN DUAL FREQUENCY OPERATING MODES
PublikacjaThe paper presents novel network equivalent circuit of piezoceramic circular disc transducer that takes into account thickness and ra dial mode of vibrations. The starting point of the analysis is 4-port description of circular disc element representing the solution of wave equation set in radial and thickness directions. Th e approximate solution for harmonic case is represented in the form of 4x4 matrix, which is syn thesized...
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Forewarned Is Forearmed: Machine Learning Algorithms for the Prediction of Catheter-Induced Coronary and Aortic Injuries
PublikacjaCatheter-induced dissections (CID) of coronary arteries and/or the aorta are among the most dangerous complications of percutaneous coronary procedures, yet the data on their risk factors are anecdotal. Logistic regression and five more advanced machine learning techniques were applied to determine the most significant predictors of dissection. Model performance comparison and feature importance ranking were evaluated. We identified...
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A novel hybrid adaptive framework for support vector machine-based reliability analysis: A comparative study
PublikacjaThis study presents an innovative hybrid Adaptive Support Vector Machine - Monte Carlo Simulation (ASVM-MCS) framework for reliability analysis in complex engineering structures. These structures often involve highly nonlinear implicit functions, making traditional gradient-based first or second order reliability algorithms and Monte Carlo Simulation (MCS) time-consuming. The application of surrogate models has proven effective...
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Design and Optimization of Metamaterial-Based Dual-Band 28/38 GHz 5G MIMO Antenna with Modified Ground for Isolation and Bandwidth Improvement
PublikacjaThis letter presents a high-isolation dual-band multiple-input multiple-output (MIMO) antenna based on the ground plane modification and optimized metamaterials (MMs) for 5G millimeter-wave applications. The antenna is a monopole providing a dual-band response at 5G 28/38 bands with a small physical size (4.8 × 2.9 × 0.762 mm3, excluding the feeding line). The MIMO consists of two symmetric radiating elements arranged adjacently...
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Assessment Of the Relevance of Best Practices in The Development of Medical R&D Projects Based on Machine Learning
PublikacjaMachine learning has emerged as a fundamental tool for numerous endeavors within health informatics, bioinformatics, and medicine. However, novices among biomedical researchers and IT developers frequently lack the requisite experience to effectively execute a machine learning project, thereby increasing the likelihood of adopting erroneous practices that may result in common pitfalls or overly optimistic predictions. The paper...
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Age Prediction from Low Resolution, Dual-Energy X-ray Images Using Convolutional Neural Networks
PublikacjaAge prediction from X-rays is an interesting research topic important for clinical applications such as biological maturity assessment. It is also useful in many other practical applications, including sports or forensic investigations for age verification purposes. Research on these issues is usually carried out using high-resolution X-ray scans of parts of the body, such as images of the hands or images of the chest. In this...
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RSS-Based DoA Estimation for ESPAR Antennas Using Support Vector Machine
PublikacjaIn this letter, it is shown how direction-of-arrival (DoA) estimation for electronically steerable parasitic array radiator (ESPAR) antennas, which are designed to be integrated within wireless sensor network nodes, can be improved by applying support vector classification approach to received signal strength (RSS) values recorded at an antenna's output port. The proposed method relies on ESPAR antenna's radiation patterns measured...
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The methodology of design of axial clearances compensation unit in hydraulic satellite displacement machine and their experimental verification
PublikacjaA new methodology of calculating the dimensions of the axial clearance compensation unit in the hydraulic satellite displacement machine is described in this paper. The methods of shaping the compensation unit were also proposed and described. These methods were used to calculate the geometrical dimensions of the compensation field in an innovative prototype of a satellite hydraulic motor. This motor is characterized by the fact...
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Experimental verification of MWO bearing machine
PublikacjaPrzedstawiono wyniki weryfikacji doświadczalnej nowego stanowiska przeznaczonego do badań wytrzymałości zmęczeniowej warstwy powierzchniowej łożysk ślizgowych. Badano dwu- i trójwarstwowe cienkościenne panwie ślizgowe. Warstwa nośna wykonana była ze stopu CuPb30. W wariancie trójwarstwowym występowała powłoka ze stopu PbSnCu. Przedstawiono przykłady zaobserwowanych pęknięć zmęczeniowych. Maszyna MWO okazała się w pełni przydatna...
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Explainable machine learning for diffraction patterns
PublikacjaSerial crystallography experiments at X-ray free-electron laser facilities produce massive amounts of data but only a fraction of these data are useful for downstream analysis. Thus, it is essential to differentiate between acceptable and unacceptable data, generally known as ‘hit’ and ‘miss’, respectively. Image classification methods from artificial intelligence, or more specifically convolutional neural networks (CNNs), classify...
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Simulations CAE of wood pellet machine
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Modeling lignin extraction with ionic liquids using machine learning approach
PublikacjaLignin, next to cellulose, is the second most common natural biopolymer on Earth, containing a third of the organic carbon in the biosphere. For many years, lignin was perceived as waste when obtaining cellulose and hemicellulose and used as a biofuel for the production of bioenergy. However, recently, lignin has been considered a renewable raw material for the production of chemicals and materials to replace petrochemical resources....
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Fast Machine-Learning-Enabled Size Reduction of Microwave Components Using Response Features
PublikacjaAchieving compact size has emerged as a key consideration in modern microwave design. While structural miniaturization can be accomplished through judicious circuit architecture selection, precise parameter tuning is equally vital to minimize physical dimensions while meeting stringent performance requirements for electrical characteristics. Due to the intricate nature of compact structures, global optimization is recommended,...
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Simulation of ammonia combustion in dual-fuel compression-ignition engine
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