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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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Cost-Efficient Multi-Objective Design of Miniaturized Microwave Circuits Using Machine Learning and Artificial Neural Network
PublicationDesigning microwave components involves managing multiple objectives such as center frequencies, impedance matching, and size reduction for miniaturized structures. Traditional multi-objective optimization (MO) approaches heavily rely on computationally expensive population-based methods, especially when exe-cuted with full-wave electromagnetic (EM) analysis to guarantee reliability. This paper introduces a novel and cost-effective...
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Machine Learning-Based Wetland Vulnerability Assessment in the Sindh Province Ramsar Site Using Remote Sensing Data
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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...
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Application of fiber optic sensors using Machine Learning algorithms for temperature measurement of lithium-ion batteries
PublicationOptical fiber sensorsusing low-coherence interferometry require processing ofthe output spectrum or interferogramto quickly and accurately determine the instantaneous value of the measured quantity, such as temperature.Methods based on machine learning are a good candidate for this application. The application of four such methods in an optical fiber temperature sensoris demonstrated.Using aZnO-coated...
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Genetic Algorithm Approach for Gains Selection of Induction Machine Extended Speed Observer
PublicationThe subject of this paper is gains selection of an extended induction machine speed observer. A high number of gains makes manual gains selection difficult and due to nonlinear equations of the observer, well-known methods of gains selection for linear systems cannot be applied. A method based on genetic algorithms has been proposed instead. Such an approach requires multiple fitness function calls; therefore, using a quality index...
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Marine traffic risk modelling – an innovative approach and a case study
PublicationThis paper presents a model to analyse the risk of two common marine accidents: collision and grounding. Attention is focused on oil tankers since they pose the highest environmental risks. A case study in selected areas of the Gulf of Finland in ice-free conditions is presented. The model utilizes a formula for risk calculation that considers both the probability of an unwanted event and its consequences. The model can be decomposed...
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Highway engineering risk assessment
PublicationNa drogach krajowych w Polsce rocznie ginie ponad 2000 osób w wypadkach drogowych, co stanowi ponad 37% ogółu ofiar śmiertelnych w wypadkach. Do poprawy stanu bezpieczeństwa na tych drogach muszą byc podjęte działania zmierzające do systematycznego dostosowania poszcz. odcinków dróg do standardów bezpieczeństwa. Jednym z narzędzi pomocnych do wyboru odcinków dróg o największym potencjale mozliwych do uratowania od śmierci uczestników...
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Determinants of anxiety levels among young males in a threat of experiencing military conflict–Applying a machine-learning algorithm in a psychosociological study
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Risk of incorrect pass-fail decisions associated with assessment uncertainty
PublicationA mathematical framework for calculation teacher's and student's risks of incorrect pass-fail decisions under uncertainty of assessment, is presented. The probabilistic model of assessment process is adapted from interdisciplinary probabilistic theory of measurement.
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A framework for onboard assessment and monitoring of flooding risk due to open watertight doors for passenger ships
PublicationPost-accident safety of ships is governed by damage stability, affected by watertight subdivisions which limit accidental flooding. This is important for passenger ships with watertight doors (WTDs) often fitted in the bulkheads. Awareness of the ship flooding risk due to open WTDs and the conditions under which the associated risk level changes are prerequisites for proactive risk mitigation. Accident risk is often expressed as...
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Analysis of Validation and Simplification of Timber-Frame Structure Design Stage with PU-Foam Insulation
PublicationThe transition from experimental studies to the realm of numerical simulations is often necessary for further studies, but very difficult at the same time. This is especially the case for extended seismic analysis and earthquake-resistant design. This paper describes an approach to moving from the experimental testing of an elementary part of a wood-frame building structure to a numerical model, with the use of a commercial engineering...
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Advanced Bayesian study on inland navigational risk of remotely controlled autonomous ship
PublicationThe arise of autonomous ships has necessitated the development of new risk assessment techniques and methods. This study proposes a new framework for navigational risk assessment of remotely controlled Maritime Autonomous Surface Ships (MASS). This framework establishes a set of risk influencing factors affecting safety of navigation of a remotely-controlled MASS. Next, model parameters are defined based on the risk factors, and...
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Machine-Learning-Based Global Optimization of Microwave Passives with Variable-Fidelity EM Models and Response Features
PublicationMaximizing microwave passive component performance demands precise parameter tuning, particularly as modern circuits grow increasingly intricate. Yet, achieving this often requires a comprehensive approach due to their complex geometries and miniaturized structures. However, the computational burden of optimizing these components via full-wave electromagnetic (EM) simulations is substantial. EM analysis remains crucial for circuit...
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Impact of probability distribution on the uncertainty of resistance measurement
PublicationThe paper presents studies on the influence of probability distributions on the expanded uncertainty of the resistance measurement. Choosing the correct probability distribution is very important to estimate of measurement uncertainty. The paper presents the results of analysis of the resistance measurement uncertainty using the technical method of resistance: 100 G. The analysis of the uncertainty...
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Adaptive Algorithm of a Tap-Changer Controller of the Power Transformer Supplying the Radial Network Reducing the Risk of Voltage Collapse
Publicationhe development of renewable energy, including wind farms, photovoltaic farms as well as prosumer installations, and the development of electromobility pose new challenges for network operators. The results of these changes are, among others, the change of network load profiles and load flows determining greater volatility of voltages. Most of the proposed solutions do not assume a change of the transformer regulator algorithm....
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Accuracy improvement of the prestressed concrete structures precise geometry assessment by use of bubble micro-sampling algorithm
PublicationPrestressed concrete structures are well-known technology for a vast period, but nevertheless, this very technology is a leading solution, currently used in construction industry. Prestressed concrete structures have a huge advantage over conventional methods because it uses the properties of concrete in a very efficient way. The main idea behind this technology is to introduce into the cross-section of the structure, the internal...
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Heavy Metals in Sediments of Urban Streams: Contamination and Health Risk Assessment of Influencing Factors
PublicationSediments of two urban streams in northern Poland outflowing to the Baltic Sea were assessed to explain the spatial variation in relation to urbanization level of the catchment, the role of retention tanks (RTs) and identification of pollution level. During the 3 month period of investigation sediment samples were collected from the inflow (IN) and outflow (OUT) of six RTs located on streams for flood protection. Six heavy metals...
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Assessment of the Relationship between the Shape of the Lateral Meniscus and the Risk of Extrusion Based on MRI Examination of the Knee Joint
PublicationBackground Meniscus extrusion is a serious and relatively frequent clinical problem. For this reason the role of different risk factors for this pathology is still the subject of debate. The goal of this study was to verify the results of previous theoretical work, based on the mathematical models, regarding a relationship between the cross-section shape of the meniscus and the risk of its extrusion. Materials and Methods Knee...
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Load effect impact on the exploitation of concrete machine foundations used in the gas and oil industry
PublicationMachine foundations is a critical topic in the gas and oil industry, which design and exploitation require extensive technical knowledge. Machine foundations are the constructions which are intended for mounting on it a specific type of machine. The foundation has to transfer dynamic and static load from machine to the ground. The primary difference between machine foundations and building foundations is that the machine foundations...
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Incremental dynamic analysis and fragility assessment of buildings founded on different soil types experiencing structural pounding during earthquakes
PublicationThe effect of the soil type on buildings experiencing pounding during earthquakes is investigated in this study using the incremental dynamic analysis and fragility assessment methods. Three 3-D structures with different number of storeys (4, 6 and 8) were considered in this study. Three pounding scenarios between these three buildings were taken into account, i.e. pounding between 4-storey and 6-storey buildings, between 4-storey...
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Microstructure and residual stresses in surface coatings with PTFE reservoirs
PublicationThe paper presents the results of experimental study into the microstructure and changes in residual stresses resulting from sliding and rolling/sliding loaded interaction between metallic surface coatings with embedded PTFE reservoirs and various counter faces. It was found that before testing surface coatings had compressive residual stresses. Molybdenum coating with all types of PTFE reservoirs displayed, as a result of testing,...
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FE simulations of a soil structure interface.
PublicationPrzedstawiono warunki brzegowe do opisu szorstkości ściany konstrukcji w kontakcie z gruntem. Wykonano doświadczenia i symulacje MES na bazie mikropolarnego prawa hipoplastycznego.
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Sperm segmentation and abnormalities detection during the ICSI procedure using machine learning algorithms
Publication(1) About 15-20% of couples struggle with the problem of infertility. 30 to 40% of these cases are caused by abnormalities in the structure and motility of sperm. Sometimes the only possibility for such people is to use the procedure of artificial insemination. CASA systems are used to increase the efficiency of this procedure by selecting the appropriate sperm cell. (2) This paper presents an approach to the sperm classification...
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Detection of circulating tumor cells by means of machine learning using Smart-Seq2 sequencing
PublicationCirculating tumor cells (CTCs) are tumor cells that separate from the solid tumor and enter the bloodstream, which can cause metastasis. Detection and enumeration of CTCs show promising potential as a predictor for prognosis in cancer patients. Furthermore, single-cells sequencing is a technique that provides genetic information from individual cells and allows to classify them precisely and reliably. Sequencing data typically...
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Unsupervised machine-learning classification of electrophysiologically active electrodes during human cognitive task performance
PublicationIdentification 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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Model of Risk Assessment (MORA) concept for the investment part of urban regeneration projects
PublicationThe main goal of this paper is presentation of the model concept (MORA) that will be used to control level of risk and manage technical risk in investment projects in the area of urban regeneration risk management.
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Driver’s Condition Detection System Using Multimodal Imaging and Machine Learning Algorithms
PublicationTo this day, driver fatigue remains one of the most significant causes of road accidents. In this paper, a novel way of detecting and monitoring a driver’s physical state has been proposed. The goal of the system was to make use of multimodal imaging from RGB and thermal cameras working simultaneously to monitor the driver’s current condition. A custom dataset was created consisting of thermal and RGB video samples. Acquired data...
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Residual Effects of Different Cropping Systems on Physicochemical Properties and the Activity of Phosphatases of Soil
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Risk Analysis by a Probabilistic Model of the Measurement Process
PublicationThe aim of the article is presentation of the testing methodology and results of examination the probabilistic model of the measurement process. The case study concerns the determination of the risk of an incorrect decision in the assessment of the compliance of products by measurement. Measurand is characterized by the generalized Rayleigh distribution. The model of the meas-urement process was tested in parallel mode by six risk...
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Numerical evaluation of dynamic response of an experimentally tested base-isolated and fixed-base steel structure model
PublicationSeismic isolation is recognized as one of the most popular and effective methods of protecting structures during earthquake. The present paper is focused on the comparison be-tween the dynamic responses of buildings with fixed and isolated bases exposed to seismic exci-tations. The aim of the study is to investigate the effectiveness of a simplified base isolation numerical modelling technique using the linear springs. One-storey...
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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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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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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...