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Search results for: MACHINE LEARNING ALGORITHM SOIL-STRUCTURE INTERACTION SEISMIC RISK ASSESSMENT RESIDUAL INTERSTORY DRIFT SEISMIC DEMAND SEISMIC FAILURE PROBABILITY
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Machine-Learning Methods for Estimating Performance of Structural Concrete Members Reinforced with Fiber-Reinforced Polymers
PublicationIn recent years, fiber-reinforced polymers (FRP) in reinforced concrete (RC) members have gained significant attention due to their exceptional properties, including lightweight construction, high specific strength, and stiffness. These attributes have found application in structures, infrastructures, wind power equipment, and various advanced civil products. However, the production process and the extensive testing required for...
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Performance Analysis of Machine Learning Methods with Class Imbalance Problem in Android Malware Detection
PublicationDue to the exponential rise of mobile technology, a slew of new mobile security concerns has surfaced recently. To address the hazards connected with malware, many approaches have been developed. Signature-based detection is the most widely used approach for detecting Android malware. This approach has the disadvantage of being unable to identify unknown malware. As a result of this issue, machine learning (ML) for detecting malware...
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Speed Observer Structure of Induction Machine Based on Sliding Super-Twisting and Backstepping Techniques
PublicationThis paper presents an analysis of the two speed observer structures which are based on the backstepping and sliding super twisting approach. The observer stabilizing functions result from the Lyapunov theorem. To obtain the observer tuning gains the observer structure is linearized near the equilibrium point. The rotor angular speed is obtained from non-adaptive dependence. In the sensorless control system structure the classical...
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Digital Interaction and Machine Intelligence. Proceedings of MIDI’2021 – 9th Machine Intelligence and Digital Interaction Conference, December 9-10, 2021, Warsaw, Poland
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Energy consumption optimization in wastewater treatment plants: Machine learning for monitoring incineration of sewage sludge
PublicationBiomass management in terms of energy consumption optimization has become a recent challenge for developed countries. Nevertheless, the multiplicity of materials and operating parameters controlling energy consumption in wastewater treatment plants necessitates the need for sophisticated well-organized disciplines in order to minimize energy consumption and dissipation. Sewage sludge (SS) disposal management is the key stage of...
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Examining Ownership Equity as a Psychological Factor on Tourism Business Failure Forecasting
PublicationThis paper examines ownership equity as a predictor of future business failure within the tourism and hospitality sectors. The main goals of this study were to examine which ratios are the most important for a tourism business failure forecasting model and how significant is the “total percentage of equity ownership by company directors” ratio compared with other ratios associated with the probability of bankruptcy. A stepwise...
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Learning Culture and Social Interaction
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Experimental analysis of the behaviour of different types of joints in the steel structure model subjected to earthquake loading
PublicationThe present paper reports the results of the experimental study performed to investigate the behaviour of two different types of joints (destroyed and welded ones) in the model of the steel structure under seismic excitations. The structure was subjected to three earthquakes, namely Kobe, Loma Prieta and Northridge, using the shaking table investigation. The results obtained from the study...
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A Model for Risk Assessment and Management of Construction Projects in Urban Conditions
PublicationThe authors are seeking new methods for improving the efficiency of the investments associated with the maintenance and operation of existing civil engineering structures. It is demonstrated how the knowledge about the elements of construction and operation phases and their relationships, combined with monitoring data can be used for more effective management of the risks associated with civil engineering projects. The methodology...
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Wiktoria Wojnicz dr hab. inż.
PeopleDSc 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) List of papers (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 of...
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Simulation of fluid structure interaction in a novel design of high pressure axial piston pump
PublicationA novel type of an axial, piston-driven high pressure hydraulic pump with variable capacity marks a significant improvement in the area of the hydraulic machinery design. Total discharge from hydrostatic forces eliminates a need for a servomechanism, thus simplifying operation, reducing weight and introducing the possibility of the pump displacement control by computer. PWK-type pumps, invented in the Gdansk University of Technology,...
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PERFORMANCE COMPARISON OF MACHINE LEARNING ALGORITHMS FOR PREDICTIVE MAINTENANCE
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Machine Learning for Sensorless Temperature Estimation of a BLDC Motor
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Machine Learning Modelling and Feature Engineering in Seismology Experiment
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Machine learning applied to bi-heterocyclic drugs recognition
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Stacking-Based Integrated Machine Learning with Data Reduction
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Machine learning system for estimating the rhythmic salience of sounds.
PublicationW artykule przedstawiono badania dotyczące wyszukiwania danych rytmicznych w muzyce. W pracy przedstawiono postać funkcji rankingujacej poszczególnych dźwięków frazy muzycznej. Opracowano metodę tworzenia wszystkich możliwych hierarchicznych struktur rytmicznych, zwanych hipotezami rytmicznymi. Otrzymane hipotezy są następnie porządkowane w kolejności malejącej wartości funkcji rankingującej, aby ustalić, która ze znalezionych...
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MACHINE LEARNING SYSTEM FOR AUTOMATED BLOOD SMEAR ANALYSIS
PublicationIn this paper the authors propose a decision support system for automatic blood smear analysis based on microscopic images. The images are pre-processed in order to remove irrelevant elements and to enhance the most important ones - the healthy blood cells (erythrocytes) and the pathologic (echinocytes). The separated blood cells are analyzed in terms of their most important features by the eigenfaces method. The features are the...
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The use of machine learning for face regions detection in thermograms
PublicationThe aim of this study is to analyse the methods of detecting characteristic points of the face in thermographic images. As part of the implementation an extensive analysis of scientific publications covering similar issues both for the analysis of images made in visible light and thermographic images was carried out. On the basis of this analysis, 3 models were selected and then they were implemented and tested on the basis of...
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MACHINE LEARNING–BASED ANALYSIS OF ENGLISH LATERAL ALLOPHONES
PublicationAutomatic classification methods, such as artificial neural networks (ANNs), the k-nearest neighbor (kNN) and selforganizing maps (SOMs), are applied to allophone analysis based on recorded speech. A list of 650 words was created for that purpose, containing positionally and/or contextually conditioned allophones. For each word, a group of 16 native and non-native speakers were audio-video recorded, from which seven native speakers’...
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Electrical safety in low-voltage DC microgrids with B-type residual current devices
PublicationResidual current devices (RCDs) are most popular devices used in low-voltage installations for protection against electric shock and fire. In cases of high risk of electric shock the application of RCDs is mandatory. Currently, the spread of local direct current (DC) microgrids is widely considered. This creates new challenges for protective systems, in particular those based on RCDs. The main purpose of the research is to test...
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Exploring the Solubility Limits of Edaravone in Neat Solvents and Binary Mixtures: Experimental and Machine Learning Study
PublicationThis study explores the edaravone solubility space encompassing both neat and binary dissolution media. Efforts were made to reveal the inherent concentration limits of common pure and mixed solvents. For this purpose, the published solubility data of the title drug were scrupulously inspected and cured, which made the dataset consistent and coherent. However, the lack of some important types of solvents in the collection called...
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Exposure scenario and risk assessment of infants and newborns to bisphenols and their derivatives from diapers
PublicationNewborns and infants are more sensitive to harmful compounds such as bisphenols and their derivatives because of their not fully developed detoxification mechanism. Exposure to these substances can lead to developmental problems and health consequences in adulthood. Since disposable baby diapers are used from the first days of life and remain in contact with the baby skin, it seems important to monitor the levels of endocrine disrupting chemicals...
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Application of Multiplicative Drift Correction and Component Correction methods on simulated gas sensor array responses
PublicationSensor response drift is one of the most challenging problems in gas-analyzing systems. Such systems, commonly called electronic noses, are expected to be reliable and reproducible in the long term. Due to the drift phenomena, electronic noses usability is limited to the relatively short period of time, and frequent recalibrations of device are required. Because it is very hard to fabricate sensors without drift, this phenomenon...
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Evaluation the P-Delta Effect on Collapse Capacity of Adjacent Structures Subjected to Far-field Ground Motions
PublicationIn urban areas, adjacent structures can be seen in any insufficient distance from each other, because of economic reasons and refusal of acquired minimum separation distance according to seismic previsions. Collapse capacity assessment of structures is one of the important objectives of performance-based seismic engineering. The purpose of this study is to consider the pounding phenomenon and P-Delta effect in seismic collapse...
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Risk assessment methodologies for pedestrian crossings without traffic lights – Warsaw case study – pedestrian safety assessment
PublicationBased on data from 2015 [1], it was found that 31% of all fatalities in road accidents in Poland were pedestrians. In places accessible to pedestrian traffic 74.2% of total accidents involving pedestrians were recorded. Approximately 53.9% of accidents involving pedestrians take place in the proximity of pedestrian crossings. In the context of improving the safety of vulnerable road users, an assessment of the condition of infrastructure...
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Comparative study on total nitrogen prediction in wastewater treatment 1 plant and effect of various feature selection methods on machine learning algorithms performance
PublicationWastewater characteristics prediction in wastewater treatment plants (WWTPs) is valuable and can reduce the number of sampling, energy, and cost. Feature Selection (FS) methods are used in the pre-processing section for enhancing the model performance. This study aims to evaluate the effect of seven different FS methods (filter, wrapper, and embedded methods) on enhancing the prediction accuracy for total nitrogen (TN) in the WWTP...
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Numerical modeling of wave-seabed-structure interaction.
PublicationPraca doktorska przedstawia propozycję nowoczesnego rozwiązania obciążeń hydraulicznych przy uwzględnieniu nieliniowych oddziaływań pomiędzy falą wodną, przepuszczalnym dnem i porowatą konstrukcją morską. Nabrzeże pionowe, falochron podwodny i falochron kompozytowy były obiektem eksperymentów numerycznych, których wyniki były weryfikowane przy użyciu wyników laboratoryjnych (niszczących i nieniszczących). Krótki przegląd bieżącej...
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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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Residual MobileNets
PublicationAs modern convolutional neural networks become increasingly deeper, they also become slower and require high computational resources beyond the capabilities of many mobile and embedded platforms. To address this challenge, much of the recent research has focused on reducing the model size and computational complexity. In this paper, we propose a novel residual depth-separable convolution block, which is an improvement of the basic...
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Laser Scanning of a Soil-Shell Bridge Structure
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A study on the interaction of rhodamine B with methylthioadenosine phosphorylase protein sourced from an Antarctic soil metagenomic library.
PublicationThe presented study examines the phenomenon of the fluorescence under UV light excitation (312 nm) of E. coli cells expressing a novel metagenomic-derived putative methylthioadenosine phosphorylase gene, called rsfp, grown on LB agar supplemented with a fluorescent dye rhodamine B. For this purpose, an rsfp gene was cloned and expressed in an LMG194 E. coli strain using an arabinose promoter. The resulting RSFP protein was purified...
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Prediction of fracture toughness in fibre-reinforced concrete, mortar, and rocks using various Machine learning techniques
PublicationMachine Learning (ML) method is widely used in engineering applications such as fracture mechanics. In this study, twenty different ML algorithms were employed and compared for the prediction of the fracture toughness and fracture load in modes I, II, and mixed-mode (I-II) of various materials, including fibre-reinforced concrete, cement mortar, sandstone, white travertine, marble, and granite. A set of 401 specimens of “Brazilian...
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Knowledge economics and the demand for higher education
PublicationThis article suggests that the decreased demand for higher education in Poland is partially caused due to the changes in consumer preferences. The appearance of a cheap and highly accessible form of knowledge offered by the massive open online courses is presumed here to have an effect on the demand for formal higher education. This article proposes an additional perspective to the research on knowledge consumption, especially...
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Environmental risk assessment of Polish wastewater treatment plant activity
PublicationWastewater treatment plants (WWTPs) play an extremely important role in shaping modern society's environmental wellbeing and awareness, however only well operated and supervised systems can be considered as environmentally sustainable. For this reason, an attempt was undertaken to assess the environmental burden posed by WWTPs in major Polish cities by collecting water samples prior to and just after wastewater release points....
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Experimental and Machine-Learning-Assisted Design of Pharmaceutically Acceptable Deep Eutectic Solvents for the Solubility Improvement of Non-Selective COX Inhibitors Ibuprofen and Ketoprofen
PublicationDeep eutectic solvents (DESs) are commonly used in pharmaceutical applications as excellent solubilizers of active substances. This study investigated the tuning of ibuprofen and ketoprofen solubility utilizing DESs containing choline chloride or betaine as hydrogen bond acceptors and various polyols (ethylene glycol, diethylene glycol, triethylene glycol, glycerol, 1,2-propanediol, 1,3-butanediol) as hydrogen bond donors. Experimental...
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Experimental and Machine-Learning-Assisted Design of Pharmaceutically Acceptable Deep Eutectic Solvents for the Solubility Improvement of Non-Selective COX Inhibitors Ibuprofen and Ketoprofen
PublicationDeep eutectic solvents (DESs) are commonly used in pharmaceutical applications as excellent solubilizers of active substances. This study investigated the tuning of ibuprofen and ketoprofen solubility utilizing DESs containing choline chloride or betaine as hydrogen bond acceptors and various polyols (ethylene glycol, diethylene glycol, triethylene glycol, glycerol, 1,2-propanediol, 1,3-butanediol) as hydrogen bond donors. Experimental...
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[Soft Skills] Smart metering - social risk perception and risk governance (2023/2024)
e-Learning CoursesThe aim of the course is to broaden the understanding of the risks associated with technology and to present the concept of social risk perception and risk management in the context of smart metering technology. In the current phase of technological development - called the Fourth Industrial Revolution - rapid and profound changes are creating new, particularly destabilizing threats. In the increasingly complex technological systems...
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Simulation of fluid structure interaction in a novel design of high pressure axial piston hydraulic pump
PublicationA novel type of an axial, piston-driven high pressure hydraulic pump with variable capacity marks a significant improvement in the area of the hydraulic machinery design. Total discharge from hydrostatic forces eliminates a need for a servomechanism, thus simplifying operation, reducing weight and introducing the possibility of the pump displacement control by computer. PWK-type pumps, invented in the Gdansk University of Technology,...
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Calibration of the CMS drift tube chambers and measurement of the drift velocity with cosmic rays
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Excavation induced cast iron pipeline failure – a numerical study
PublicationNumerical study on impact of an unsecured excavation on an underground pipeline. Analysis focused on investigation of pipeline displacement generated by soil movement caused by excavation and heavy traffic. Numerical calculations and soil parameter sensitivity analysis based on Finite Element Method. Some comparisons of results with real-life failure cases.
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Thermal failure of a second rotor stage in heavy duty gas turbine
PublicationThe impulse mode of operation and the supply of various types of fuels causes frequent failures even in the heavy duty gas turbines. The paper presents the ravages of second rotor stage failure in a gas turbine. The excessive thermal elongation rise caused by fuel change was indicated as the main cause. We applied nonlinear numerical analysis, preceded by thermodynamic calculations of the turbine and visual inspection of the effects...
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Systemy z Uczeniem Maszynowym / Systems with Machine Learning 2022/2023
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FORECASTING EXCHANGE RATES IN THE PROCESS OF THE ASSESSMENT OF CONSUMER RISK BANKRUPTCY IN CENTRAL EUROPE
PublicationThis paper focuses on the issue of forecasting the fluctuation of exchange rates as part of the early warning system against the risk of consumer bankruptcy. The author identified the main macroeconomic factors affecting the level of bankruptcies for households in Poland. The fluctuation of exchange rates, which directly affects the deterioration of the economic situation of borrowers who have opened credit accounts in a foreign...
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Rediscovering Automatic Detection of Stuttering and Its Subclasses through Machine Learning—The Impact of Changing Deep Model Architecture and Amount of Data in the Training Set
PublicationThis work deals with automatically detecting stuttering and its subclasses. An effective classification of stuttering along with its subclasses could find wide application in determining the severity of stuttering by speech therapists, preliminary patient diagnosis, and enabling communication with the previously mentioned voice assistants. The first part of this work provides an overview of examples of classical and deep learning...
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Hierarchical influence diagrams for incorporating human and organizational factors in risk assessment of hazardous industrial systems
PublicationArtykuł dotyczy podstawowych zagadnień związanych z czynnikami organizacyjnymi i ludzkim w analizie ryzyka złożonych systemów przemysłowych. Analizuje się podobieństwa i różnice pomiędzy hierarchicznymi diagramami wpływu i hierarchicznym procesem analizy decyzyjnej i na tej podstawie proponuje się uogólnione podejście do rozważanej analizy decyzyjnej uwzględniające dane rozmyte.
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Cost-Efficient Measurement Platform and Machine-Learning-Based Sensor Calibration for Precise NO2 Pollution Monitoring
PublicationAir quality significantly impacts human health, the environment, and the economy. Precise real-time monitoring of air pollution is crucial for managing associated risks and developing appropriate short- and long-term measures. Nitrogen dioxide (NO2) stands as a common pollutant, with elevated levels posing risks to the human respiratory tract, exacerbating respiratory infections and asthma, and potentially leading to chronic lung...
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Features of Machine Cyclogram Optimization with the Account of Interaction of Mechanism Links with Stops
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Residual Current Devices: Selection, Operation, and Testing
PublicationIn this book, the idea for residual current protection has been presented. The evolution in construction types of residual current devices, which has taken place over decades, is discussed. Types and functional properties of the contemporary residual current devices are described. The main parameters of these devices, from the point of view of their selection and application, are indicated. Special constructions of the protective...
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International Journal of Risk Assessment and Management
Journals