Wyniki wyszukiwania dla: support vector machine (SVM)
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Sensorless Field Oriented Control of Five Phase Induction Motor with Third Harmonic Injection
PublikacjaIn this paper, a sensorless field oriented control system of five-phase induction machine with the 3rd harmonic rotor flux is presented. Two vector models, α1-β1 and α3-β3, were transformed into d1-q1, d3-q3 models oriented in rotating frames, which correspond to the 1st and 3rd harmonic plane respectively. The authors proposed the linearization of the model in d-q coordinate frames by introducing a new variable “x” which is proportional...
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State and control system variables sensitivity to rotor asymmetry in the induction motor drive
PublikacjaThe aim of this paper is to undertake analysis and comparison of the closed-loop and sensorless control systems sensitivity to the broken rotor for diagnostic purposes. For the same vector control system induction motor drive analysis concerning operation with the asymmetric motor, broken rotor fault handling and operation were investigated. Reliability, range of stable operation, fault symptoms and application of diagnosis methods...
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Fault detection in the marine engine using a support vector data description method
PublikacjaFast detection and correct diagnosis of any engine condition changes are essential elements of safety andenvironmental protection. Many diagnostic algorithms significantly improve the detection of malfunctions.Studies on diagnostic methods are rarely reported and even less implemented in the marine engine industry.To fill this gap, this paper presents the Support Vector Data Description (SVDD) method as applied to thefault detection...
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Text Documents Classification with Support Vector Machines
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Support Vector Machines in Biomedical and Biometrical Applications
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Sensorless field oriented control for five-phase induction motors with third harmonic injection and fault insensitive feature
PublikacjaThe paper presents a solution for sensorless field oriented control (FOC) system for five-phase induction motors with improved rotor flux pattern. In order to obtain the advantages of a third harmonic injection with a quasi-trapezoidal flux shape, two vector models, α1–β1 and α3–β3, were transformed into d1– q1, d3– q3 rotating frames, which correlate to the 1st and 3rd harmonic plane respectively. A linearization approach of the...
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Ireneusz Czarnowski Prof.
OsobyIRENEUSZ CZARNOWSKI is a graduate of the Faculty of Electrical Engineering at Gdynia Maritime University. He gained a doctoral degree in the field of computer science at Poznan University of Technology and a postdoctoral degree in the field of computer science at Wroclaw University of Science and Technology. Since 1998 is associated with Gdynia Maritime University, currently is a professor of computer science in the Department...
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Bearing testing machine with rotating load vector.
PublikacjaW pracy przedstawiono koncepcję konstrukcyjną i prototyp stanowiska badawczego z wirująca reakcją łożyskową przeznaczonego do testowania wytrzymałości zmęczeniowej warstw ślizgowych w łożyskach poprzecznych. Konstrukcja i przeznaczenie maszyny zbudowanej w laboratorium tribologicznym Politechniki Gdańskiej jest zgodna z zaleceniami normy ISO 7905. Przeanalizowano zalety i wady maszyny badawczej o takim wzorcu obciążenia testującego.
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Speed observer of induction machine based on backstepping and sliding mode for low‐speed operation
PublikacjaThis paper presents a speed observer design based on backstepping and slidingmode approaches. The inputs to the observer are the stator current and thevoltage vector components. This observer structure is extended to the integra-tors. The observer stabilizing functions contain the appropriate sliding surfaceswhich result from the Lyapunov function. The rotor angular speed is obtainedfrom the non‐adaptive formula with a sliding...
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Sounding Mechanism of a Flue Organ Pipe—A Multi-Sensor Measurement Approach
PublikacjaThis work presents an approach that integrates the results of measuring, analyzing, and modeling air flow phenomena driven by pressurized air in a flue organ pipe. The investigation concerns a Bourdon organ pipe. Measurements are performed in an anechoic chamber using the Cartesian robot equipped with a 3D acoustic vector sensor (AVS) that acquires both acoustic pressure and air particle velocity. Also, a high-speed camera is employed...
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Buried Object Characterization by Data-Driven Surrogates and Regression-Enabled Hyperbolic Signature Extraction
PublikacjaThis work addresses artificial-intelligence-based buried object characterization using FDTD-based electromagnetic simulation toolbox of a Ground Penetrating Radar (GPR) to generate B-scan data. In data collection, FDTD-based simulation tool, gprMax is used. The task is to estimate geophysical parameters of a cylindrical shape object of various radii, buried at different positions in the dry soil medium simultaneously and independently...
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Predicting seismic response of SMRFs founded on different soil types using machine learning techniques
PublikacjaPredicting the Maximum Interstory Drift Ratio (M-IDR) of Steel Moment-Resisting Frames (SMRFs) is a useful tool for designers to approximately evaluate the vulnerability of SMRFs. This study aims to explore supervised Machine Learning (ML) algorithms to build a surrogate prediction model for SMRFs to reduce the need for complex modeling. For this purpose, twenty well-known ML algorithms implemented in Python software are trained...
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Detection of anomalies in bee colony using transitioning state and contrastive autoencoders
PublikacjaHoneybees plays vital role for the environmental sustainability and overall agricultural economy. Assisting bee colonies within their proper functioning brings the attention of researchers around the world. Electronics systems and machine learning algorithms are being developed for classifying specific undesirable bee behaviors in order to alert about upcoming substantial losses. However, classifiers could be impaired when used...
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Core loss resistance impact on sensorless speed control of an induction motor using hybrid adaptive sliding mode observer
PublikacjaInduction motors (IMs) experience power losses when a portion of the input power is converted to heat instead of driving the load. The combined effect of copper losses, core losses, and mechanical losses results in IM power losses. Unfortunately, the core losses in the motor, which have a considerable impact on its energy efficiency, are not taken into account by the generally employed dynamic model in the majority of the studies. Due...
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The adaptive backstepping control of PMSM supplied by current source inverter for the field weakening region
PublikacjaThe sensorless control system of permanent magnet synchronous motor PMSM supplied by current source inverter for field weakening operation is presented in this paper. The adaptive backstepping control system and the backstepping speed observer are presented. The control system is based on multi-scalar variables. The control variables are: dc-link voltage and the output current vector pulsation. The control system was named voltage...
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Nonlinear Control of a Doubly Fed Generator Supplied by a Current Source Inverter
PublikacjaNowadays, wind turbines based on a doubly fed induction generator (DFIG) are a commonly used solution in the wind industry. The standard converter topology used in these systems is the voltage source inverter (VSI). The use of reverse-blocking insulated gate bipolar transistor (RB-IGBT) in the current source inverter topology (CSI), which is an alternative topology, opens new possibilities of control methods. This paper presents...
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Nonlinear control of five phase induction motor with synchronized third harmonic flux injection
PublikacjaThe paper deals with the novel control system for five phase induction motor (IM) that enables the injection of the rotor flux 3rd harmonic component. Two multiscalar models are transformed from the 1-1 and 2-2 vector models developed in the 1st and 3rd harmonic planes. Based on the obtained multiscalar models the synthesis of dual multiscalar control is established. The obtained two multiscalar control systems can independently...
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Real-Time Facial Features Detection from Low Resolution Thermal Images with Deep Classification Models
PublikacjaDeep networks have already shown a spectacular success for object classification and detection for various applications from everyday use cases to advanced medical problems. The main advantage of the classification models over the detection models is less time and effort needed for dataset preparation, because classification networks do not require bounding box annotations, but labels at the image level only. Yet, after passing...
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Michał Grochowski dr hab. inż.
OsobyProfessor and a Head of the Department of Intelligent Control and Decision Support Systems at Gdansk University of Technology (GUT). He is also a Member of the Board of the Digital Technologies Center of GUT. He received his M.Sc. degree in Control Engineering in 2000 from the Electrical and Control Engineering Faculty at the GUT. In 2004 he received a Ph.D. degree in Automatic Control and Robotics from this...
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Source code - AI models (MLM1-5 - series I-III - QNM opt)
Dane BadawczeSource code - AI models (MLM1-5 - series I-III - QNM opt) for the paper "Computational Complexity and Its Influence on Concrete Compressive Strength Prediction Capabilities of Machine Learning Models for Concrete Mix Design Support" accepted for publication.
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Liniowe i nieliniowe modele wielowymiarowej kalibracji do predykcji stężenia substancji z pomiarów woltamperometrycznych
PublikacjaPomiary woltamperometryczne znajdują zastosowanie w wielu dziedzinach nauki i techniki, np. w przemyśle farmaceutycznym. Dane uzyskane w wyniku takich pomiarów zawierają informację odnośnie rodzaju i stężenia badanej substancji, jednakże są one często kłopotliwe w bezpośredniej interpretacji. Z tego powodu, istnieje konieczność wykorzystania odpowiednich metod matematycznych, które umożliwiają uzyskanie bezpośredniej i precyzyjnej...
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Klasyfikator SVM w zastosowaniu do synchronizacji sygnału OFDM zniekształconego przez kanał wielodrogowy
PublikacjaW pracy przedstawiono analizę przydatności klasyfikatora SVM bazującego na uczeniu maszynowym do estymacji przesunięcia czasowego odebranego symbolu OFDM. Przedstawione wyniki wykazują, że ten klasyfikator potrafi zapewnić synchronizację dla różnych kanałów wielodrogowych o wysokim poziomie szumu. Eksperymenty przeprowadzone w Matlabie z użyciem modeli modulatora i demodulatora wykazały, że w większości przypadków klasyfikator...
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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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The Influence of Limiters UEL and OEL (The power angle, stator's current and excitation current) ot the possibility of voltage collapse development
PublikacjaVoltage stability has been a major concern for power system utilities because of event of voltage collapses in the recent past. Sometimes, power system events have shown the need for generators to operate in the overexcited and underexcited region to support stable operation. Modern excitation systems include devices for controlling or limiting machine terminal voltage (overvoltage limiters), volts per hertz ratio (V/Hz limiters),...
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Semantic rules representation in controlled natural language in FluentEditor
PublikacjaThis paper presents a way of representation of semantic rules (SWRL) in controlled English in order to facilitate understanding the rules by humans interacting with a machine. This approach (implemented in FluentEditor) may be applied in many domains, where the understandability of the rules used to support a decision process is of great importance.
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Artificial intelligence support for disease detection in wireless capsule endoscopy images of human large bowel
PublikacjaIn the work the chosen algorithms of disease recognition in endoscopy images were described and compared for theirs efficiency. The algorithms were estimated with regard to utility for application in computer system's support for digestive system's diagnostics. Estimations were achieved in an advanced testing environment, which was built with use of the large collection of endoscopy movies received from Medical University in Gdańsk....
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Synteza bezczujnikowego sterowania maszyną indukcyjną klatkową zasilaną z falownika prądu
PublikacjaSynteza bezczujnikowego sterowania maszyną indukcyjną klatkową zasilaną z falownika prądu stanowi cel niniejszej monografii. Praca zawiera podstawowe informacje na temat modelowania układu napędowego z maszyną indukcyjną klatkową zasilaną z falownika prądu. Przedstawiono informacje na temat linearyzacji nieliniowych obiektów. Na pod-stawie metody syntezy strukturalnej opracowano nowe transformacje do postaci zmien-nych multiskalarnych,...
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Sztuczne sieci neuronowe oraz metoda wektorów wspierających w bankowych systemach informatycznych
PublikacjaW artykule zaprezentowano wybrane metod sztucznej inteligencji do zwiększania efektywności bankowych systemów informatycznych. Wykorzystanie metody wektorów wspierających czy sztucznych sieci neuronowych w połączeniu z nowoczesną technologią mikroprocesorową umożliwia znaczący wzrost konkurencyjności banku poprzez dodanie nowych funkcjonalności. W rezultacie możliwe jest także złagodzenie skutków kryzysu finansowego.
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Adam Władziński
OsobyAdam Władziński, doktorant na Politechnice Gdańskiej, specjalizuje się w inżynierii biomedycznej, skupiając się na uczeniu maszynowym do przetwarzania obrazów z druku 3D układów pomiarowych i tkanek biologicznych, a także na komercyjnym zastosowaniu technologii blockchain. Posiadając wykształcenie z dziedziny elektroniki na Wydziale Elektroniki, Telekomunikacji i Informatyki (ETI), praca magisterska Adama Władzińskiego koncentrowała...
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Przegląd metod szybkiego prototypowania algorytmów uczenia maszynowego w FPGA
PublikacjaW artykule opisano możliwe do wykorzystania otwarte narzędzia wspomagające szybkie prototypowanie algorytmów uczenia maszynowego (ML) i sztucznej inteligencji (AI) przy użyciu współczesnych platform FPGA. Przedstawiono przykład szybkiej ścieżki przy realizacji toru wideo wraz z implementacją przykładowego algorytmu prze-twarzania w trybie na żywo.
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Efficiency comparison of selected endoscopic video analysis algorithms
PublikacjaIn the paper, selected image analysis algorithms were examined and compared in the task of identifying informative frames, blurry frames, colorectal cancer and healthy tissue on endoscopic videos. In order to standardize the tests, the algorithms were modified by removing from them parts responsible for the classification, and replacing them with Support Vector Machines and Artificial Neural Networks. The tests were performed in...
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Wave propagation signals in concrete beams under 3-point bending
Dane BadawczeThe DataSet contains the results of the mechanical behaviour of a concrete beams with dimensions 40 x 40 x 160 cm3under the 3-point bending. The beams were made of concrete with the following ingredients: CEM I 42.5R (450 kg/m3), water (177 kg/m3), sand 0-2 (675 kg/m3) and gravel 2-8 (675 kg/m3). The bending test was performed using a Zwick/Roell Z10...
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The Neural Knowledge DNA Based Smart Internet of Things
PublikacjaABSTRACT The Internet of Things (IoT) has gained significant attention from industry as well as academia during the past decade. Smartness, however, remains a substantial challenge for IoT applications. Recent advances in networked sensor technologies, computing, and machine learning have made it possible for building new smart IoT applications. In this paper, we propose a novel approach: the Neural Knowledge DNA based Smart Internet...
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Asking Data in a Controlled Way with Ask Data Anything NQL
PublikacjaWhile to collect data, it is necessary to store it, to understand its structure it is necessary to do data-mining. Business Intelligence (BI) enables us to make intelligent, data-driven decisions by the mean of a set of tools that allows the creation of a potentially unlimited number of machine-generated, data-driven reports, which are calculated by a machine as a response to queries specified by humans. Natural Query Languages...
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Active Annotation in Evaluating the Credibility of Web-Based Medical Information: Guidelines for Creating Training Data Sets for Machine Learning
PublikacjaMethods Results Discussion References Abbreviations Copyright Abstract Background: The spread of false medical information on the web is rapidly accelerating. Establishing the credibility of web-based medical information has become a pressing necessity. Machine learning offers a solution that, when properly deployed, can be an effective tool in fighting medical misinformation on the web. Objective: The aim of this study is to...
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Comparison of selected electroencephalographic signal classification methods
PublikacjaA variety of methods exists for electroencephalographic (EEG) signals classification. In this paper, we briefly review selected methods developed for such a purpose. First, a short description of the EEG signal characteristics is shown. Then, a comparison between the selected EEG signal classification methods, based on the overview of research studies on this topic, is presented. Examples of methods included in the study are: Artificial...
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Julita Wasilczuk dr hab.
OsobyUrodzona 5 kwietnia 1965 roku w Gdańsku. W latach 1987–1991 odbyła studia na Wydziale Ekonomiki Transportu Uniwersytetu Gdańskiego (obecnie Wydział Ekonomii). Od 1993 roku zatrudniona na nowo utworzonym Wydziale Zarządzania i Ekonomii, Politechniki Gdańskiej, na stanowisku asystenta. W 1997 roku uzyskała stopień doktora nauk ekonomicznych na WZiE, a w 2006 doktora habilitowanego nauk ekonomicznych w dyscyplinie nauki o zarządzaniu,...
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Two Stage SVM and kNN Text Documents Classifier
PublikacjaThe paper presents an approach to the large scale text documents classification problem in parallel environments. A two stage classifier is proposed, based on a combination of k-nearest neighbors and support vector machines classification methods. The details of the classifier and the parallelisation of classification, learning and prediction phases are described. The classifier makes use of our method named one-vs-near. It is...
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Predictions of cervical cancer identification by photonic method combined with machine learning
PublikacjaCervical 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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Ontology clustering by directions algorithm to expand ontology queries
PublikacjaThis paper concerns formulating ontology queries. It describes existing languages in which ontologies can be queried. It focuses on languages which are intended to be easily understood by users who are willing to retrieve information from ontologies. Such a language can be, for example, a type of controlled natural language (CNL). In this paper a novel algorithm called Ontology Clustering by Directions is presented. The algorithm...
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Multi-criteria Differential Evolution for Optimization of Virtual Machine Resources in Smart City Cloud
PublikacjaIn 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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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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Selecting Features with SVM
PublikacjaA common problem with feature selection is to establish how many features should be retained at least so that important information is not lost. We describe a method for choosing this number that makes use of Support Vector Machines. The method is based on controlling an angle by which the decision hyperplane is tilt due to feature selection. Experiments were performed on three text datasets generated from a Wikipedia dump. Amount...
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In uence of Low-Level Features Extracted from Rhythmic and Harmonic Sections on Music Genre Classi cation
PublikacjaWe present a comprehensive evaluation of the infuence of 'harmonic' and rhythmic sections contained in an audio file on automatic music genre classi cation. The study is performed using the ISMIS database composed of music files, which are represented by vectors of acoustic parameters describing low-level music features. Non-negative Matrix Factorization serves for blind separation of instrument components. Rhythmic components...
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Obtaining a Well-Trained Artificial Intelligence Algorithm from Cross-Validation in Endoscopy
PublikacjaThe article shortly discusses endoscopic video analysis problems and artificial intelligence algorithms supporting it. The most common method of efficiency testing of these algorithms is to perform intensive cross-validation. This allows for accurately evaluate their performance of generalization. One of the main problems of this procedure is that there is no simple and universal way of obtaining a specific instance of a well-trained...
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DESIGN AND THEORETICAL ANALYSIS OF A PROTOTYPE TILTING-PAD RADIAL BEARING WITH ADJUSTABLE CLEARANCE
PublikacjaThe article introduces a design and analysis results of a prototype ORC (organic Rankine cycle) turbo generator rotor assembly of 300kW power, supported by tilting-pad bearings of original design. The calculations were performed for a prototype turbo generator rotor. The shaft of this machine is supported with two radial bearings, lubricated with an unusual lubricant – a low-boiling-point agent. The main objective of the presented...
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Ultrasonic wave propagation and digital image correlation measurements of steel bars under 3-point bending
Dane BadawczeThe DataSet contains the results of the mechanical behaviour of a bar under a 3-point bending test. The bar was made of steel and had a cross-section of 5.96 × 5.96 mm2 and a length of 200 mm. The three-point bending test was performed using a Zwick/Roell Z10 universal testing machine (UTM), with a distance between supports of 12 cm. The parameters...
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Technique for reducing erosion in large-scale circulating fluidized bed units
PublikacjaThis paper presents a methodology, implemented for a real industrial-scale circulating fluidized bed boiler, to mitigate the risk of heating surfaces exposed to an intensive particle erosion process. For this purpose, a machine learning algorithm was developed to support the boiler reliability management process. Having a tool that can help mitigate the risk of uncontrolled power unit failure without expensive and technically complex...
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Methodology for Performing Bathymetric Measurements of Shallow Waterbodies Using an UAV, and their Processing Based on the SVR Algorithm
PublikacjaState-of-art methods of bathymetric measurements for shallow waterbodies use Global Navigation Satellite System (GNSS) receiver, bathymetric Light Detection and Ranging (LiDAR) sensor or satellite imagery. Currently, photogrammetric methods with the application of Unmanned Aerial Vehicles (UAV) are gathering great importance. This publication aims to present step-by-step methodology for carrying out the bathymetric measurements...
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Methodology for Performing Bathymetric Measurements of Shallow Waterbodies Using an UAV, and their Processing Based on the SVR Algorithm
PublikacjaState-of-art methods of bathymetric measurements for shallow waterbodies use Global Navigation Satellite System (GNSS) receiver, bathymetric Light Detection and Ranging (LiDAR) sensor or satellite imagery. Currently, photogrammetric methods with the application of Unmanned Aerial Vehicles (UAV) are gathering great importance. This publication aims to present step-by-step methodology for carrying out the bathymetric measurements...
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THE ROLE OF INFERENCE IN MOBILE MEDICAL APPLICATION DESIGN
PublikacjaIn the early 21st century, artificial intelligence began to be used to process medical information. However, before this happened, predictive models used in healthcare could only consider a limited number of variables, and only in properly structured and organised medical data. Today, advanced tools based on machine learning techniques - which, using artificial neural networks, can explore extremely complex relationships - and...
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Prognozowanie wpływu drgań komunikacyjnych na budynki mieszkalne za pomocą sztucznych sieci neuronowych i maszyn wektorów wspierających
PublikacjaDrgania komunikacyjne mogą stanowić duże obciążenie eksploatacyjne budynku, powodując zarysowania i spękania tynków, odpadanie wypraw, zarysowania konstrukcji, pękanie elementów konstrukcji lub nawet zawalenie się budynku. Pomiary drgań na rzeczywistych konstrukcjach są pracochłonne i kosztowne, a co ważne nie w każdym przypadku są one uzasadnione. Celem pracy jest analiza autorskiego algorytmu, dzięki któremu z dużym prawdopodobieństwem...
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Prediction of Wastewater Quality at a Wastewater Treatment Plant Inlet Using a System Based on Machine Learning Methods
PublikacjaOne 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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Soft Sensor Application in Identification of the Activated Sludge Bulking Considering the Technological and Economical Aspects of Smart Systems Functioning
PublikacjaThe paper presented the methodology for the construction of a soft sensor used for activated sludge bulking identification. Devising such solutions fits within the current trends and development of a smart system and infrastructure within smart cities. In order to optimize the selection of the data-mining method depending on the data collected within a wastewater treatment plant (WWTP), a number of methods were considered, including:...
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A comparative analysis of the effectiveness of corporate bankruptcy prediction models based on financial ratios: Evidence from Colombia, 2008 to 2015
PublikacjaLogit and discriminant analyses have been used for corporate bankruptcy prediction in several studies since the last century. In recent years there have been dozens of studies comparing the several models available, including the ones mentioned above and also probit, artificial neural networks, support vector machines, among others. For the first time for Colombia, this paper presents a comparative analysis of the effectiveness...
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Ultrasonic wave propagation, digital image correlation and X-ray micro-computed tomography measurements of concrete during splitting (cube #4)
Dane BadawczeThe DataSet contains the results of the mechanical behaviour of a concrete cube under the splitting test. The cube had dimensions 70 x 70 x 70 cm3 and was made of concrete with the following ingredients: cement type CEM I 42.5R (330 kg/m3), water (165 kg/m3), aggregate 0/2 mm (710 kg/m3), aggregate 2/8 mm (664 kg/m3), aggregate 8/16 mm (500 kg/m3),...
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Ultrasonic wave propagation, digital image correlation and X-ray micro-computed tomography measurements of concrete during splitting (cube #3)
Dane BadawczeThe DataSet contains the results of the mechanical behaviour of a concrete cube under the splitting test. The cube had dimensions 70 x 70 x 70 cm3 and was made of concrete with the following ingredients: cement type CEM I 42.5R (330 kg/m3), water (165 kg/m3), aggregate 0/2 mm (710 kg/m3), aggregate 2/8 mm (664 kg/m3), aggregate 8/16 mm (500 kg/m3),...
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Ultrasonic wave propagation, digital image correlation and X-ray micro-computed tomography measurements of concrete during splitting (cube #2)
Dane BadawczeThe DataSet contains the results of the mechanical behaviour of a concrete cube under the splitting test. The cube had dimensions 70 x 70 x 70 cm3 and was made of concrete with the following ingredients: cement type CEM I 42.5R (330 kg/m3), water (165 kg/m3), aggregate 0/2 mm (710 kg/m3), aggregate 2/8 mm (664 kg/m3), aggregate 8/16 mm (500 kg/m3),...
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Ultrasonic wave propagation, digital image correlation and X-ray micro-computed tomography measurements of concrete during splitting (cube #1)
Dane BadawczeThe DataSet contains the results of the mechanical behaviour of a concrete cube under the splitting test. The cube had dimensions 70 x 70 x 70 cm3 and was made of concrete with the following ingredients: cement type CEM I 42.5R (330 kg/m3), water (165 kg/m3), aggregate 0/2 mm (710 kg/m3), aggregate 2/8 mm (664 kg/m3), aggregate 8/16 mm (500 kg/m3),...
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Unsupervised Learning for Biomechanical Data Using Self-organising Maps, an Approach for Temporomandibular Joint Analysis
PublikacjaWe proposed to apply a specific machine learning technique called Self-Organising Maps (SOM) to identify similarities in the performance of muscles around human temporomandibular joint (TMJ). The performance was assessed by measuring muscle activation with the use of surface electromyography (sEMG). SOM algorithm used in the study was able to find clusters of data in sEMG test results. The SOM analysis was based on processed sEMG...
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Unsupervised machine-learning classification of electrophysiologically active electrodes during human cognitive task performance
PublikacjaIdentification of active electrodes that record task-relevant neurophysiological activity is needed for clinical and industrial applications as well as for investigating brain functions. We developed an unsupervised, fully automated approach to classify active electrodes showing event-related intracranial EEG (iEEG) responses from 115 patients performing a free recall verbal memory task. Our approach employed new interpretable...
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Study of Multi-Class Classification Algorithms’ Performance on Highly Imbalanced Network Intrusion Datasets
PublikacjaThis paper is devoted to the problem of class imbalance in machine learning, focusing on the intrusion detection of rare classes in computer networks. The problem of class imbalance occurs when one class heavily outnumbers examples from the other classes. In this paper, we are particularly interested in classifiers, as pattern recognition and anomaly detection could be solved as a classification problem. As still a major part of...
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Towards Rational Biosurfactant Design—Predicting Solubilization in Rhamnolipid Solutions
PublikacjaThe efficiency of micellar solubilization is dictated inter alia by the properties of the solubilizate, the type of surfactant, and environmental conditions of the process. We, therefore, hypothesized that using the descriptors of the aforementioned features we can predict the solubilization efficiency, expressed as molar solubilization ratio (MSR). In other words, we aimed at creating a model to find the optimal surfactant and...
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Multiparameter sensitivity analysis of a GFRP composite footbridge of a sandwich structure and U-shaped cross-section
PublikacjaThe paper deals with multiparameter sensitivity analysis of a composite footbridge. A shell‐like structure is 14.5 m long shows U‐shaped cross‐section and inner service dimensions 1.3 × 2.5 m. Glass fiber reinforced polymer GFRP laminate constitutes faces of a sandwich structure while PET foam received from recycled bottle builts a core. The structure was divided into 285 independent areas where the thickness of laminates and stiffness...
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The Influence of Selecting Regions from Endoscopic Video Frames on The Efficiency of Large Bowel Disease Recognition Algorithms
PublikacjaThe article presents our research in the field of the automatic diagnosis of large intestine diseases on endoscopic video. It focuses on the methods of selecting regions of interest from endoscopic video frames for further analysis by specialized disease recognition algorithms. Four methods of selecting regions of interest have been discussed: a. trivial, b. with the deletion of characteristic, endoscope specific additions to the...
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Failure analysis of a high-speed induction machine driven by a SiC-inverter and operating on a common shaft with a high-speed generator
PublikacjaDue to ongoing research work, a prototype test rig for testing high-speed motors/generators has been developed. Its design is quite unique as the two high- speed machines share a single shaft with no support bearings between them. A very high maximum operating speed, up to 80,000 rpm, was required. Because of the need to minimise vibration during operation at very high rotational speeds, rolling bearings were used. To eliminate...
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Data on LEGO sets release dates and worldwide retail prices combined with aftermarket transaction prices in Poland between June 2018 and June 2023
PublikacjaThe dataset contains LEGO bricks sets item count and pricing history for AI-based set pricing prediction. The data spans the timeframe from June 2018 to June 2023. The data was obtained from three sources: Brickset.com (LEGO sets retail prices, release dates, and IDs), Lego.com official web page (ID number of each set that was released by Lego, its retail prices, the current status of the set) and promoklocki.pl web page (the retail...
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Algorytmy przetwarzania widm Ramana w procesie detekcji substancji chemicznych
PublikacjaRozprawa przedstawia szczegółowo algorytmy, jakie są stosowane podczas przetwarzania widm Ramana, rejestrowanych przenośnym spektrometrem o skończonej rozdzielczości. Pracę podzielono na osiem rozdziałów. W pierwszym określono cel i tezy pracy. Rozdział drugi opisuje podstawowe pojęcia dotyczące zjawiska Ramana oraz zasady budowy urządzeń do pomiarów widm Ramana. W rozdziale trzecim scharakteryzowano błędy występujące podczas pomiarów...
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Application of autoencoder to traffic noise analysis
PublikacjaThe aim of an autoencoder neural network is to transform the input data into a lower-dimensional code and then to reconstruct the output from this code representation. Applications of autoencoders to classifying sound events in the road traffic have not been found in the literature. The presented research aims to determine whether such an unsupervised learning method may be used for deploying classification algorithms applied to...
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Fundamentals of Data-Driven Surrogate Modeling
PublikacjaThe primary topic of the book is surrogate modeling and surrogate-based design of high-frequency structures. The purpose of the first two chapters is to provide the reader with an overview of the two most important classes of modeling methods, data-driven (or approx-imation), as well as physics-based ones. These are covered in Chap-ters 1 and 2, respectively. The remaining parts of the book give an exposition of the specific aspects...
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Detecting type of hearing loss with different AI classification methods: a performance review
PublikacjaHearing is one of the most crucial senses for all humans. It allows people to hear and connect with the environment, the people they can meet and the knowledge they need to live their lives to the fullest. Hearing loss can have a detrimental impact on a person's quality of life in a variety of ways, ranging from fewer educational and job opportunities due to impaired communication to social withdrawal in severe situations. Early...
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Social media for e-learning of citizens in smart city
PublikacjaThe rapid development of social media can be applied for citizens’ e-learning in a smart city. Big cities have to cope with several open issues like a growing population or a traffic congestion. Especially, a home and public space is supposed to be used in more efficient way. Sustainable homes and buildings can be planned with using some modern techniques. Even currently, there is a huge problem with a lack of key resources like...
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Information retrieval with semantic memory model
PublikacjaPsycholinguistic theories of semantic memory form the basis of understanding of natural language concepts. These theories are used here as an inspiration for implementing a computational model of semantic memory in the form of semantic network. Combining this network with a vector-based object-relation-feature value representation of concepts that includes also weights for confidence and support, allows for recognition of concepts...
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Solubility Characteristics of Acetaminophen and Phenacetin in Binary Mixtures of Aqueous Organic Solvents: Experimental and Deep Machine Learning Screening of Green Dissolution Media
PublikacjaThe solubility of active pharmaceutical ingredients is a mandatory physicochemical characteristic in pharmaceutical practice. However, the number of potential solvents and their mixtures prevents direct measurements of all possible combinations for finding environmentally friendly, operational and cost-effective solubilizers. That is why support from theoretical screening seems to be valuable. Here, a collection of acetaminophen...
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Ultrasonic wave propagation and digital image correlation measurements of polyolefin fibre-reinforced concrete beams under 3-point bending (beam B-002)
Dane BadawczeThe DataSet contains the results of the mechanical behaviour of a concrete beam under a 3-point bending test. The beams had dimensions 15 x 15 x 70 cm3. The beam B-Con was made of concrete without fibres (as the reference beam), while beams B-002, B-004, and B-006 were manufactured from the concrete mix containing 2 kg/m3, 4 kg/m3 and 6 kg/m3 of fibres,...
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Ultrasonic wave propagation and digital image correlation measurements of polyolefin fibre-reinforced concrete beams under 3-point bending (beam B-004)
Dane BadawczeThe DataSet contains the results of the mechanical behaviour of a concrete beam under a 3-point bending test. The beams had dimensions 15 x 15 x 70 cm3. The beam B-Con was made of concrete without fibres (as the reference beam), while beams B-002, B-004, and B-006 were manufactured from the concrete mix containing 2 kg/m3, 4 kg/m3 and 6 kg/m3 of fibres,...
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Ultrasonic wave propagation and digital image correlation measurements of polyolefin fibre-reinforced concrete beams under 3-point bending (beam B-Con)
Dane BadawczeThe DataSet contains the results of the mechanical behaviour of a concrete beam under a 3-point bending test. The beams had dimensions 15 x 15 x 70 cm3. The beam B-Con was made of concrete without fibres (as the reference beam), while beams B-002, B-004, and B-006 were manufactured from the concrete mix containing 2 kg/m3, 4 kg/m3 and 6 kg/m3 of fibres,...
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Ultrasonic wave propagation and digital image correlation measurements of polyolefin fibre-reinforced concrete beams under 3-point bending (beam B-006)
Dane BadawczeThe DataSet contains the results of the mechanical behaviour of a concrete beam under a 3-point bending test. The beams had dimensions 15 x 15 x 70 cm3. The beam B-Con was made of concrete without fibres (as the reference beam), while beams B-002, B-004, and B-006 were manufactured from the concrete mix containing 2 kg/m3, 4 kg/m3 and 6 kg/m3 of fibres,...
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Machine learning-based seismic fragility and seismic vulnerability assessment of reinforced concrete structures
PublikacjaMany studies have been performed to put quantifying uncertainties into the seismic risk assessment of reinforced concrete (RC) buildings. This paper provides a risk-assessment support tool for purpose of retrofitting and potential design strategies of RC buildings. Machine Learning (ML) algorithms were developed in Python software by innovative methods of hyperparameter optimization, such as halving search, grid search, random...
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Cooperative control in production and logistics
PublikacjaClassical applications of control engineering and information and communication technology (ICT) in production and logistics are often done in a rigid, centralized and hierarchical way. These inflexible approaches are typically not able to cope with the complexities of the manufacturing environment, such as the instabilities, uncertainties and abrupt changes caused by internal and external disturbances, or a large number and variety...
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Method for determining of shallow water depths based on data recorded by UAV/USV vehicles and processed using the SVR algorithm
PublikacjaBathymetric measurements in waters shallower than 1 m are necessary to monitor seafloor relief changes in the coastal zone. This is especially important for ensuring the safety of navigation, navigation efficiency, as well as during the design and monitoring of hydrotechnical structures. Therefore, the aim of this article is to present a method for determining of shallow water depths based on data recorded by Unmanned Aerial Vehicle...
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Visual Content Representation for Cognitive Systems: Towards Augmented Intelligence
PublikacjaCognitive Vision Systems have gained significant attention from academia and industry during the past few decades. One of the main reasons behind this interest is the potential of such technologies to revolutionize human life since they intend to work robustly under complex visual scenes (which environmental conditions may vary), adapting to a comprehensive range of unforeseen changes, and exhibiting prospective behavior. The combination...
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Integration Data Model of the Bathymetric Monitoring System for Shallow Waterbodies Using UAV and USV Platforms
PublikacjaChanges in the seafloor relief are particularly noticeable in shallow waterbodies (at depths up to several metres), where they are of significance for human safety and environmental protection, as well as for which the highest measurement accuracy is required. The aim of this publication is to present the integration data model of the bathymetric monitoring system for shallow waterbodies using Unmanned Aerial Vehicles (UAV) and...
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Metoda i algorytmy sterowania procesami miksowania dźwięku za pomocą gestów w oparciu o analizę obrazu wizyjnego
PublikacjaGłównym celem rozprawy było opracowanie systemu miksowania dźwięku za pomocą gestów rąk wykonywanych w powietrzu oraz zbadanie możliwości oferowanych przez takie rozwiązanie w porównaniu ze współczesną metodą miksowania sygnałów fonicznych, wykorzystującą środowisko komputera. Opracowany system rozpoznaje zarówno dynamiczne jak i statyczne gesty rąk. Rozpoznawanie gestów dynamicznych zrealizowano w oparciu o metody logiki rozmytej...
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Cerclage cable augmentation does not increase stability of the fixation of intertrochanteric fractures. A biomechanical study
PublikacjaBackground: Intertrochanteric fractures with a posteromedial intermediate fragment are unstable because of the loss of medial support. Additional fixation with a cerclage is used in subtrochanteric fractures, but not in intertrochanteric fractures. The aim of this biomechanical study is to evaluate whether cerclage fixation improves stability of intertrochanteric fractures. Hypothesis: Our hypothesis is that the cerclage fixation...
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Predicting sulfanilamide solubility in the binary mixtures using a reference solvent approach
PublikacjaBackground. Solubility is a fundamental physicochemical property of active pharmaceutical ingredients. The optimization of a dissolution medium aims not only to increase solubility and other aspects are to be included such as environmental impact, toxicity degree, availability, and costs. Obtaining comprehensive...
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The cement-bone bond is weaker than cement-cement bond in cement-in-cement revision arthroplasty. A comparative biomechanical study
PublikacjaThis study compares the strength of the native bone-cement bond and the old-new cement bond under cyclic loading, using third generation cementing technique, rasping and contamination of the surface of the old cement with biological tissue. The possible advantages of additional drilling of the cement surface is also taken into account. Femoral heads from 21 patients who underwent a total hip arthroplasty performed for hip arthritis...
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Wiktoria Wojnicz dr hab. inż.
OsobyDSc in Mechanics (in the field of Biomechanics) - Lodz Univeristy of Technology, 2019 PhD in Mechanics (in the field of Biomechanics) - Lodz Univeristy of Technology, 2009 (with distinction) Publikacje z listy MNiSW (2009 - ) Wojnicz W., Wittbrodt E., Analysis of muscles' behaviour. Part I. The computational model of muscle. Acta of Bioengineering and Biomechanics, Vol. 11, No.4, 2009, p. 15-21 Wojnicz W., Wittbrodt E., Analysis...