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Inverse method for 3D shaped centrifugal compressor (rotor and diffuser)
PublicationW artykule przedstawiono sposób wyznaczania kształtu wirnika i dyfuzora sprężarki promieniowej. Podano układ równań oraz warunki zamknięcia układu. Przykładowe rozwiązanie wskazuje na silny wpływ warunków na wlocie na kształt dyfuzora.
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Model of speed-varing rotor for mechatronic systems analysis and design
PublicationW artykule przedstawiono sposób modelowania złożonych układów mechatronicznych w oparciu o metodę grafów wiązań. Celem zilustrowania metody posłużono się przykładem liczbowym, w którym rozważano wirnik obracający się ze zmienną prędkością kątową. Prezentowana metodyka doskonale nadaje się do modelowania układów o zróżnicowanej naturze fizycznej. Otrzymany model ma charakter obiektu o pewnej liczbie wejść i wyjść, który można w...
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Support Vector Machine Applied to Road Traffic Event Classification
PublicationThe aim of this paper is to present results of road traffic event signal recognition. First, several types of systems for road traffic monitoring, including Intelligent Transport System (ITS) are shortly described. Then, assumptions of creating a database of vehicle signals recorded in different weather and road conditions are outlined. Registered signals were edited as single vehicle pass by. Using the Matlab-based application...
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Concrete mix design using machine learning
PublicationDesigning a concrete mix is a process of synthesizing many components, it is not a simple process and requires extensive technical knowledge. The design process itself focuses on obtaining the required strength of concrete. Very often designing a concrete mix takes into account the need to maintain the proper water-demand and frost-resistance features. The parameters that influence the concrete class most significantly are the...
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Predictions of cervical cancer identification by photonic method combined with machine learning
PublicationCervical cancer is one of the most commonly appearing cancers, which early diagnosis is of greatest importance. Unfortunately, many diagnoses are based on subjective opinions of doctors—to date, there is no general measurement method with a calibrated standard. The problem can be solved with the measurement system being a fusion of an optoelectronic sensor and machine learning algorithm to provide reliable assistance for doctors...
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Neural Networks, Support Vector Machine and Genetic Algorithms for Autonomous Underwater Robot Support
PublicationIn this paper, artificial neural networks, a classification technique called support vector machine and meta-heuristics genetic algorithm have been considered for development in autonomous underwater robots. Artificial neural networks have been used for seabed modelling as well as support vector machine has been applied for the obstacles classification to avoid some collision problems. Moreover, genetic algorithm has been applied...
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COMPARISON OF THE CONVENTIONAL AND ALTERNATIVE GRANULAR MATERIALS FOR DUAL-MEDIA FILTRATION OF GROUNDWATER: PILOT PLANT TESTING
PublicationNowadays, occurrence of abnormal mineral or organic natural (geogenic) compounds concentrations, in ground and infiltration water, but also quite often in surface waters, is now a common problem encountered in Poland, Europe and many other countries throughout the world. The most concern is usually paid on the removal of iron (Fe) and manganese (Mn) as well as anthropogenic compounds (in particular referring to the organic compounds...
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Preeclampsia Risk Prediction Using Machine Learning Methods Trained on Synthetic Data
PublicationThis paper describes a research study that investigates the use of machine learning algorithms on synthetic data to classify the risk of developing preeclampsia by pregnant women. Synthetic datasets were generated based on parameter distributions from three real patient studies. Four models were compared: XGBoost, Support Vector Machine (SVM), Random Forest, and Explainable Boosting Machines (EBM). The study found that the XGBoost...
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Dual polarization antennas for UHF RFID readers
PublicationThis paper presents various concepts of switching polarization in patch antenna dedicated for UHF RFID readers. Proposed designs allow for switching between linear and circular polarization. The first design does not require electronic switching as the polarization can be changed by choosing one of two available feeding terminals. Two remaining designs use PIN diode or FET SPDT switch.
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Molecular properties with dual basis set methods
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Fundamentals of Machine Design I
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Fundamental of Machine Design III
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Fundamentals of Machine Design II
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Fundamentals of Machine Design III
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Fundamentals of Machine Design I
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Decisional DNA (DDNA) Based Machine Monitoring and Total Productive Maintenance in Industry 4.0 Framework
PublicationThe entire manufacturing spectrum is transforming with the advent of Industry 4.0. The features of Set of Experience Knowledge Structure (SOEKS) and Decisional DNA (DDNA) were utilized for developing Virtual Engineering Objects (VEO), Virtual Engineering Process (VEP) and Virtual Engineering Factory (VEF), which in turn facilitate the creation of smart factories. In this study, DDNA based Machine Monitoring for Total Maintenance...
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Dangerous sound event recognition using Support Vector Machine classifiers
PublicationA method of recognizing events connected to danger based on their acoustic representation through Support Vector Machine classification is presented. The method proposed is particularly useful in an automatic surveillance system. The set of 28 parameters used in the classifier consists of dedicated parameters and MPEG-7 features. Methods for parameter calculation are presented, as well as a design of SVM model used for classification....
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Terrestrial Survey Images - Multispectral Exterior Model - Gdansk Church Pw. Św. Wojciecha - Micasense Dual
Open Research DataDataset description: Raw images from photogrammetric survey. Object: Kościół Rzymskokatolicki Pw. Św. WojciechaLocation: Gdansk, Pomerania, PolandDrone type: N/A (terrestrial images)Flight plan: Free - walk around the object with camera. 3 images taken at the point.Target Product: 3D Model - Multispectral ModelDate: 24.04.2022Direct georeferencing:...
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Model-Based Adaptive Machine Learning Approach in Concrete Mix Design
PublicationConcrete mix design is one of the most critical issues in concrete technology. This process aims to create a concrete mix which helps deliver concrete with desired features and quality. Contemporary requirements for concrete concern not only its structural properties, but also increasingly its production process and environmental friendliness, forcing concrete producers to use both chemically and technologically complex concrete...
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Experimental analysis of chip removing system in circular sawing machine
PublicationPaper presents analysis of the process of removing the wood chips generated during the cutting of the material on the circular sawing machine. The attention is focused on the upper cover of the chip removing system. Within the framework of the work a systematic experimental study of pressure distribution in the cover during operation of the selected rotational speed of saw blade with a diameter of 300 mm and 450 mm was carried...
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Self-advocacy of a person with a disability in the dual role of paid worker and volunteer: Theoretical considerations and a case study
PublicationThe changing models of disability influence the way people with disabilities participate in social life, and how they can transform their life and environment. Such participation may take the form of work and volunteering, as well as participation in self-advocacy movements. This paper aims to explore how a woman with hearing impairment perceives her dual role as a regular worker and voluntary self-advocate within one organization...
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A Dual-Polarized 39 GHz 4x4 Microstrip Antenna Array for 5G MU-MIMO Airflight Cabin Connectivity
PublicationThis paper presents the design, fabrication, and experimental validation of a 39 GHz dual-polarized 4x4 microstrip antenna array. The array consists of 16 slot coupled circular microstrip patches, fed through SMPS connectors. The procedure requiring a reduced number of cables for measurement of the uniformly excited antenna array is also presented. The array exhibits 18 dBi peak gain and 2.9 GHz reflection bandwidth and is intended...
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Designing acoustic scattering elements using machine learning methods
PublicationIn the process of the design and correction of room acoustic properties, it is often necessary to select the appropriate type of acoustic treatment devices and make decisions regarding their size, geometry, and location of the devices inside the room under the treatment process. The goal of this doctoral dissertation is to develop and validate a mathematical model that allows predicting the effects of the application of the scattering...
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Quantitative Risk Assessment in Construction Disputes Based on Machine Learning Tools
PublicationA 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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Sensorless Multiscalar Control of Five-Phase Induction Machine with Inverter Output Filter
PublicationThe paper presents a complete solution for speed sensorless control system for five-phase induction motor with voltage inverter, LC filter and nonlinear control of combined fundamental and third harmonic flux distribution. The control principle, also known as multiscalar control, nonlinear control or natural variables control, is based on a use of properly selected scalar variables in control feedback to linearize controlled system....
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A Universal Gains Selection Method for Speed Observers of Induction Machine
PublicationProperties of state observers depend on proper gains selection. Each method of state estimation may require the implementation of specific techniques of finding those gains. The aim of this study is to propose a universal method of automatic gains selection and perform its verification on an induction machine speed observer. The method utilizes a genetic algorithm with fitness function which is directly based on the impulse response...
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Robust and Efficient Machine Learning Algorithms for Visual Recognition
PublicationIn 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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INVESTIGATIONS OF THE EMISSION CHARACTERISTICS OF A DUAL-FUEL GAS TURBINE COMBUSTION CHAMBER OPERATING SIMULTANEOUSLY ON LIQUID AND GASEOUS FUELS
PublicationT his study is dedicated to investigations of the working process in a dual-fuel low-emission combustion chamber for a floating vessel’s gas turbine. As the object of the research, a low-emission gas turbine combustion chamber with partial premixing of fuel and air inside the outer and inner radial-axial swirls was chosen. The method of the research is based on the numerical solution of the system of differential...
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The application of a photopolymer material for the manufacture of machine elements using rapid prototyping techniques
PublicationThe 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
Publication—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
PublicationHigher 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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Machine Dynamics Research
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Integrating Experience-Based Knowledge Representation and Machine Learning for Efficient Virtual Engineering Object Performance
PublicationMachine 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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Machine learning for the management of biochar yield and properties of biomass sources for sustainable energy
PublicationBiochar 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
PublicationThe 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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SiC-based phase-shift dual half bridge DC-DC converter as a key component of multilevel cascaded MV converters
PublicationThe 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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Optical method supported by machine learning for urinary tract infection detection and urosepsis risk assessment
PublicationThe 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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Noise profiling for speech enhancement employing machine learning models
PublicationThis 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
PublicationIn 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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Broad Stopband, Low-Loss, and Ultra-Compact Dual-Mode Bandpass Filter Based on HMSIRC
PublicationIn 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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Predicting emotion from color present in images and video excerpts by machine learning
PublicationThis 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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COVID-19 severity forecast based on machine learning and complete blood count data
PublicationProper 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
PublicationProper 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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Numerical methodology for evaluation the combustion and emissions characteristics on WLTP in the light duty dual-fuel diesel vehicle
PublicationThe 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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Foundations and Trends in Machine Learning
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International Journal of Machine Intelligence
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Machine Learning and Knowledge Extraction
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Machine Learning-Science and Technology
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The methodology for determining of the value of cutting power for cross cutting on optimizing sawing machine
PublicationIn 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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Morphology control via dual solvent crystallization for high-mobility functionalized pentacene-blend thin film transistors
PublicationWe 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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High Efficiency Dual-Active-Bridge Converter with Triple-Phase-Shift Control for Battery Charger of Electric Vehicles
PublicationAn 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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Balancing energy consumption in limited power grid with active front-end and three phase dual active bridge system
PublicationPaper 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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Dual-Polarized Wideband Bandpass Metasurface-Based Filter
PublicationThis 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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Localization of sound sources with dual acoustic vector sensor
PublicationThe 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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Impedance matching in dual-frequency induction heating systems
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DUABI - Business Intelligence Architecture for Dual Perspective Analytics
PublicationA 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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Application of Support Vector Machine for Determination of Impact of Traffic-Induced Vibrations on Buildings
PublicationThe 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
PublicationThe 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
PublicationPreplaced-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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Machine learning-based prediction of preplaced aggregate concrete characteristics
PublicationPreplaced-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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Platelet RNA Sequencing Data Through the Lens of Machine Learning
PublicationLiquid 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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DNAffinity: a machine-learning approach to predict DNA binding affinities of transcription factors
PublicationWe 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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Dual-Setting Bone Cement Based On Magnesium Phosphate Modified with Glycol Methacrylate Designed for Biomedical Applications
PublicationMagnesium 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
PublicationIn 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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Forewarned Is Forearmed: Machine Learning Algorithms for the Prediction of Catheter-Induced Coronary and Aortic Injuries
PublicationCatheter-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
PublicationThis 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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A LUMPED-CIRCUIT MODEL OF CIRCULAR PISTON TRANSDUCER FOR MODELING ITS PERFORMANCE IN DUAL FREQUENCY OPERATING MODES
PublicationThe 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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Influence of the steam within seals and glands of the turbine on its rotor motion stability.
PublicationPrzedstawiono 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.
PublicationPrzeprowadzono 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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Design and Optimization of Metamaterial-Based Dual-Band 28/38 GHz 5G MIMO Antenna with Modified Ground for Isolation and Bandwidth Improvement
PublicationThis 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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RSS-Based DoA Estimation for ESPAR Antennas Using Support Vector Machine
PublicationIn 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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Age Prediction from Low Resolution, Dual-Energy X-ray Images Using Convolutional Neural Networks
PublicationAge 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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The methodology of design of axial clearances compensation unit in hydraulic satellite displacement machine and their experimental verification
PublicationA 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
PublicationPrzedstawiono 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
PublicationSerial 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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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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A FPTAS for minimizing total completion time in a single machine time-dependent scheduling problem
PublicationIn this paper a single machine time-dependent scheduling problem with total completion time criterion is considered. There are given n jobs J1,…,Jn and the processing time pi of the ith job is given by pi=a+bisi, where si is the starting time of the ith job (i=1,…,n),bi is its deterioration rate and a is the common base processing time. If all jobs have deterioration rates different and not smaller than a certain constant u>0,...
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Optical method supported by machine learning for dynamics of C‐reactive protein concentrations changes detection in biological matrix samples
PublicationIn this article we present the novel spectroscopy method supported with machine learning for real-time detection of infectious agents in wastewater. In the case of infectious diseases, wastewater monitoring can be used to detect the presence of inflammation biomarkers, such as the proposed C-reactive protein, for monitoring inflammatory conditions and mass screening during epidemics for early detection in communities of concern,...
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Automatic detection of abandoned luggage employing a dual camera system
PublicationA system for automatic detection of events using a system of fixed and PTZ (pan-tilt-zoom) cameras is described. Images from the fixed camera are analyzed by means of object detection and tracking. Event detection system uses a set of rules to analyze data on the tracked moving objects and to detect defined events. A PTZ camera is used to obtain a detailed view of a selected object. A procedure for conversion between the pixel...
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Simulation of ammonia combustion in dual-fuel compression-ignition engine
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Dual-Frequency Induction Heating Generator With Adjustable Impedance Matching
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Dual-Energy Computed Tomography in Loosening of Revision Hip Prosthesis
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Deterministic versus stochastic modelling of unsaturated flow in a sandy field soil based on dual tracer breakthrough data
PublicationThe 216 km2 Neuenhagen Millcreeck catchment can be characterized as a drought sensitive landscape in NE Germany. It is therefore a fundamental human interest to understand how water that fell as precipitation moves through the unsaturated soils and recharges groundwater. Additionally, a better knowledge of nutrient transport from soil to groundwater is important also, especially in landscapes with light sandy soils. For a better...
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Highly-Miniaturized Dual-Mode Bandpass Filter Based on Quarter-Mode Substrate Integrated Waveguide with Wide Stopband
PublicationThis paper presents a novel design of a highly-miniaturized dual-mode bandpass filter (BPF) employing a quarter-mode substrate integrated waveguide (QMSIW). The QMSIW resonator is based on a square cavity with metallic vias along two sides, and open-ended edges at the remaining sides that contain orthogonal feed lines. An open slot is introduced along the two sides of the square cavity with metallic vias to form a magnetic wall....
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Speed estimation of a car at impact with a W-beam guardrail using numerical simulations and machine learning
PublicationThis paper aimed at developing a new method of estimating the impact speed of a passenger car at the moment of a crash into a W-beam road safety barrier. The determination of such a speed based on the accident outcomes is demanding, because often there is no access to full accident data. However, accurate determination of the impact speed is one of the key elements in the reconstruction of road accidents. A machine learning algorithm...
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Road traffic can be predicted by machine learning equally effectively as by complex microscopic model
PublicationSince high-quality real data acquired from selected road sections are not always available, a traffic control solution can use data from software traffic simulators working offline. The results show that in contrast to microscopic traffic simulation, the algorithms employing neural networks can work in real-time, so they can be used, among others, to determine the speed displayed on variable message road signs. This paper describes...
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Multi-criteria Differential Evolution for Optimization of Virtual Machine Resources in Smart City Cloud
PublicationIn a smart city, artificial intelligence tools support citizens and urban services. From the user point of view, smart applications should bring computing to the edge of the cloud, closer to citizens with short latency. However, from the cloud designer point of view, the trade-off between cost, energy and time criteria requires the Pareto solutions. Therefore, the proposed multi-criteria differential evolution can optimize virtual...
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Slowly-closing valve behaviour during steam machine accelerated start-up
PublicationThe paper discusses the state of stress in a slowly-closing valve during accelerated start-up of a steam turbine. The valve is one of the first components affected by high temperature gradients and is a key element on which the power, efficiency and safety of the steam system depend. The authors calibrated the valve model based on experimental data and then performed extended Thermal-FSI analyses relative to experiment. The issue...
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Machine learning approach to packaging compatibility testing in the new product development process
PublicationThe paper compares the effectiveness of selected machine learning methods as modelling tools supporting the selection of a packaging type in new product development process. The main goal of the developed model is to reduce the risk of failure in compatibility tests which are preformed to ensure safety, durability, and efficacy of the finished product for the entire period of its shelf life and consumer use. This kind of testing...
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Experimental tuning of AuAg nanoalloy plasmon resonances assisted by machine learning method
PublicationPlasmonic nanostructures based on AuAg nanoalloys were fabricated by thermal annealing of metallic films in an argon atmosphere. The nanoalloys were chosen because they can extend the wavelength range in which plasmon resonance occurs and thus allow the design of plasmonic platforms with the desired parameters. The influence of initial fabrication parameters and experimental conditions on the formation of nanostructures was investigated....
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Computer aided machine design 2022/23
e-Learning Courses -
Machine Design 3, PG_00042104 2023/24
e-Learning Courses -
Sensorless Rotor Position Estimation of Doubly-Fed Induction Generator Based on Backstepping Technique
PublicationThis paper proposes a speed observer algorithm for the sensorless control of a doubly-fed induction generator based on classical adaptive backstepping technique. The sensorless control is shown using classic stator field oriented control which is used to active and reactive power control. Performance of the proposed algorithm of a speed observer is validated by simulation and experimental results obtained using a small-rating generator...
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Polymeric Bearings as a new base isolation system suitable for mitigating machine-induced vibrations
PublicationThe present paper summarizes the preliminary results of the experimental shaking table investigation conducted in order to verify the effectiveness of a new base isolation system consisting of Polymeric Bearings in reducing strong horizontal machine-induced vibrations. Polymeric Bearing considered in the present study is a prototype base isolation system, which was constructed with the use of a specially prepared flexible polymer...
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Machine Learning and Text Analysis in an Artificial Intelligent System for the Training of Air Traffic Controllers
PublicationThis chapter presents the application of new information technology in education for the training of air traffic controllers (ATCs). Machine learning, multi-criteria decision analysis, and text analysis as the methods of artificial intelligence for ATCs training have been described. The authors have made an analysis of the International Civil Aviation Organization documents for modern principles of ATCs education. The prototype...
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Detection of People Swimming in Water Reservoirs with the Use of Multimodal Imaging and Machine Learning
PublicationEvery year in many countries, there are fatal unintentional drownings in different water reservoirs like swimming pools, lakes, seas, or oceans. The existing threats of this type require creating a method that could automatically supervise such places to increase the safety of bathers. This work aimed to create methods and prototype solutions for detecting people bathing in water reservoirs using a multimodal imaging system and...
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Machining process sequencing and machine assignment in generative feature-based CAPP for mill-turn parts
PublicationProcess selection and sequencing, as one of the most complex issues when evaluated from a mathematical point of view and crucial in CAPP, still attract research attention. For the current trend of intelligent manufacturing, machining features (MFs) are the information carriers for workpiece geometry and topology representation. They are basically derived from CAD models and are used by downstream engineering applications. A feature-based...
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Computational Complexity and Its Influence on Predictive Capabilities of Machine Learning Models for Concrete Mix Design
PublicationThe design of concrete mixtures is crucial in concrete technology, aiming to produce concrete that meets specific quality and performance criteria. Modern standards require not only strength but also eco-friendliness and production efficiency. Based on the Three Equation Method, conventional mix design methods involve analytical and laboratory procedures but are insufficient for contemporary concrete technology, leading to overengineering...
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A Novel Versatile Decoupling Structure and Expedited Inverse-Model-Based Re-Design Procedure for Compact Single-and Dual-Band MIMO Antennas
PublicationMultiple-input multiple-output (MIMO) antennas are considered to be the key components of fifth generation (5G) mobile communications. One of the challenges pertinent to the design of highly integrated MIMO structures is to minimize the mutual coupling among the antenna elements. The latter arises from two sources, the coupling in the free space and the coupling currents propagating on a ground plane. In this paper, an array of...
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Solubility of dapsone in deep eutectic solvents: Experimental analysis, molecular insights and machine learning predictions
PublicationBackground. Dapsone (DAP) is an anti-inflammatory and antimicrobial active pharmaceutical ingredient used to treat, e.g., AIDS-related diseases. However, low solubility is a feature hampering its efficient use. Objectives. First, deep eutectic solvents...