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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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Evaluation of foundation input motions based on kinematic interaction models
PublicationThe present study was designed to demonstrate the importance of base-slab averaging and embedment effects on the foundation-level input motions due to earthquake excitations. Evaluation of foundation-level input motions based on the most commonly adopted kinematic interaction models are presented. In order to conduct this investigation, original records of horizontal accelerations for two case-study buildings were utilized. Computed...
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Cargo ships heat demand - operational experiment
PublicationThe paper presents the results of an experiment conducted on two cargo ships – a 5300 TEU container with a steam heating system and a 7500 dwt general cargo ship with a thermal oil system. On both ships research has been carried out using specially designed measuring equipment. After gathering data about flow velocity and temperatures (steam/ cooling water/ thermal oil/ seawater/ outside air), calculations have been done, resulting...
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Chained machine learning model for predicting load capacity and ductility of steel fiber–reinforced concrete beams
PublicationOne of the main issues associated with steel fiber–reinforced concrete (SFRC) beams is the ability to anticipate their flexural response. With a comprehensive grid search, several stacked models (i.e., chained, parallel) consisting of various machine learning (ML) algorithms and artificial neural networks (ANNs) were developed to predict the flexural response of SFRC beams. The flexural performance of SFRC beams under bending was...
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ANALYSIS OF THE PUNCHING FAILURE MECHANISM IN WORKING PLATFORMS
PublicationPaper presents an analysis of the shear failure mechanism which occurs from the punching of a working platform layer in relation to its thickness, grain size arrangement and mechanical properties, taking into consideration the interaction with soft subgrade. The study is based on the observations of performance of natural scale structures (Streefkerk) and the results of model investigations numerically represented with the use...
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Failure Monitoring and Condition Assessment of Steel-Concrete Adhesive Connection Using Ultrasonic Waves
PublicationAdhesive bonding is increasingly being incorporated into civil engineering applications. Recently, the use of structural adhesives in steel-concrete composite systems is of particular interest. The aim of the study is an experimental investigation of the damage assessment of the connection between steel and concrete during mechanical degradation. Nine specimens consisted of a concrete cube and two adhesively bonded steel plates...
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Machine Learning Applied to Aspirated and Non-Aspirated Allophone Classification—An Approach Based on Audio "Fingerprinting"
PublicationThe purpose of this study is to involve both Convolutional Neural Networks and a typical learning algorithm in the allophone classification process. A list of words including aspirated and non-aspirated allophones pronounced by native and non-native English speakers is recorded and then edited and analyzed. Allophones extracted from English speakers’ recordings are presented in the form of two-dimensional spectrogram images and...
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Active Annotation in Evaluating the Credibility of Web-Based Medical Information: Guidelines for Creating Training Data Sets for Machine Learning
PublicationMethods 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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Environmental Risk Assessment of WWII Shipwreck pollution
PublicationThe pollution of the sea is a global problem that has arisen as a consequence of the industrialization of the world and the intense transportation of crude oil and the products of its refinement. As sailing vessels were replaced by motor propelled ships towards the end of the 19th century, a new source of sea water pollution came into being. Every emergency involving a tanker carrying crude oil and its products is a potential source...
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An advanced tool integrating failure and sensitivity analysis into novel modeling of the stormwater flood volume
PublicationAn innovative tool for modeling the specific flood volume was presented that can be applied to assess the need for stormwater network modernization as well as for advanced flood risk assessment. Field measurements for a catchment area in Kielce, Poland, were used to apply the model and demonstrate its usefulness. This model extends the capability of recently developed statistical and machine learning hydrodynamic models developed...
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COVID-19 severity forecast based on machine learning and complete blood count data
PublicationProper triage of COVID-19 patients is a key factor in eective case management, especially with limited and insucient resources. In this paper, we propose a machine-aided diagnostic system to predict how badly a patient with COVID-19 will develop disease. The prognosis of this type is based on the parameters of commonly used complete blood count tests, which makes it possible to obtain data from a wide range of patients.We chose...
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COVID-19 severity forecast based on machine learning and complete blood count data
PublicationProper triage of COVID-19 patients is a key factor in eective case management, especially with limited and insucient resources. In this paper, we propose a machine-aided diagnostic system to predict how badly a patient with COVID-19 will develop disease. The prognosis of this type is based on the parameters of commonly used complete blood count tests, which makes it possible to obtain data from a wide range of patients.We chose...
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Probability Uncertainty and Quantitative Risk
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Behaviour of Asymmetric Structure with Base Isolation Made of Polymeric Bearings
PublicationEarthquake-induced ground motions are the most severe and unpredictable threats to the structures all around the world. Seismic excitations cause a lot of damage in a wide variety of ways, leaving thousands of casualties in their wake. Due to randomness of earthquake occurrence, lack of visible causes and their power of destructiveness, structural engineers need to develop new technical solutions and protection systems against...
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Optical method supported by machine learning for dynamics of C‐reactive protein concentrations changes detection in biological matrix samples
PublicationIn this article we present the novel spectroscopy method supported with machine learning for real-time detection of infectious agents in wastewater. In the case of infectious diseases, wastewater monitoring can be used to detect the presence of inflammation biomarkers, such as the proposed C-reactive protein, for monitoring inflammatory conditions and mass screening during epidemics for early detection in communities of concern,...
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Improving platelet‐RNA‐based diagnostics: a comparative analysis of machine learning models for cancer detection and multiclass classification
PublicationLiquid biopsy demonstrates excellent potential in patient management by providing a minimally invasive and cost-effective approach to detecting and monitoring cancer, even at its early stages. Due to the complexity of liquid biopsy data, machine-learning techniques are increasingly gaining attention in sample analysis, especially for multidimensional data such as RNA expression profiles. Yet, there is no agreement in the community...
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A framework for risk matrix design: A case of MASS navigation risk
PublicationRisk matrix, a tool for visualizing risk assessment results, is essential to facilitate the risk communication and risk management in risk-based decision-making processes related to new and unexplored socio-technical systems. The use of an appropriate risk matrix is discussed in the literature, but it is overlooked for emerging technologies such as Maritime Autonomous Surface Ships (MASS). In this study, a comprehensive framework...
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Marcin Sikorski prof. dr hab. inż.
PeopleMarcin Sikorski is a professor at the Department of Informatics in Management at the Faculty of Management and Economics of the Gdańsk University of Technology. Earlier he had numerous fellowships in academic institutions, among others in Germany (Universities in Bonn and in Heidelberg), Switzerland (ETH Zurich), the Netherlands (TU Eindhoven) and the USA (Harvard University). Professor Sikorski is a representative of Poland in...
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INVESTIGATION OF THE LOMBARD EFFECT BASED ON A MACHINE LEARNING APPROACH
PublicationThe Lombard effect is an involuntary increase in the speaker’s pitch, intensity, and duration in the presence of noise. It makes it possible to communicate in noisy environments more effectively. This study aims to investigate an efficient method for detecting the Lombard effect in uttered speech. The influence of interfering noise, room type, and the gender of the person on the detection process is examined. First, acoustic parameters...
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Systemy z Uczeniem Maszynowym / Systems with Machine Learning
e-Learning Courses -
Road traffic can be predicted by machine learning equally effectively as by complex microscopic model
PublicationSince high-quality real data acquired from selected road sections are not always available, a traffic control solution can use data from software traffic simulators working offline. The results show that in contrast to microscopic traffic simulation, the algorithms employing neural networks can work in real-time, so they can be used, among others, to determine the speed displayed on variable message road signs. This paper describes...
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The influence of changes of soil parameters due to consolidation on the interaction of piles and soft soil layer
PublicationZaprezentowano problem wyznaczania bocznego parcia gruntu o małej wytrzymałości na pale. Opisano przypadki występowania bocznego obciążenia pali. Scharakteryzowano właściwości i zachowanie gruntów słabych stanowiących warstwę podłoża o małej wytrzymałości. Zaprezentowano propozycje obliczania bocznego parcia według różnych autorów. Przedstawiono wpływ konsolidacji na zmianę wytrzymałości gruntów słabych w czasie oraz na obliczanie...
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Reliability data safety instrumented systems SIS from the functional safety analysis example critical instalation
Open Research DataThe dataset represents the results of an example of functional safety analysis systems is presented below. It is based on a control system, which consists of some basic components like sensors, programmable logic controllers and valves. It is a part of petrochemical critical installations. The communication between sensor logic controllers and actuators...
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Structure and Randomness in Planning and Reinforcement Learning
PublicationPlanning in large state spaces inevitably needs to balance the depth and breadth of the search. It has a crucial impact on the performance of a planner and most manage this interplay implicitly. We present a novel method \textit{Shoot Tree Search (STS)}, which makes it possible to control this trade-off more explicitly. Our algorithm can be understood as an interpolation between two celebrated search mechanisms: MCTS and random...
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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
PublicationDue 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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Interaction of Novel Ionic Liquids with Soils
PublicationWith the constant development of new ionic liquids, the understanding of the chemical fate of these compounds also needs to be updated. To this effect, in this contribution, the interaction of a number of novel ionic liquids with soils was determined. Therefore, three novel headgroups (ammonium, phosphonium or pyrrolidinium) with single or quaternary substitution were tested on a variety of soils with high to low organic matter...
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Rapid Surrogate-Aided Multi-Criterial Optimization of Compact Microwave Passives Employing Machine Learning and ANNs
PublicationThis article introduces an innovative method for achieving low-cost and reliable multi-objective optimization (MO) of microwave passive circuits. The technique capitalizes on the attributes of surrogate models, specifically artificial neural networks (ANNs), and multi-resolution electromagnetic (EM) analysis. We integrate the search process into a machine learning (ML) framework, where each iteration produces multiple infill points...
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Machine Learning and Text Analysis in an Artificial Intelligent System for the Training of Air Traffic Controllers
PublicationThis chapter presents the application of new information technology in education for the training of air traffic controllers (ATCs). Machine learning, multi-criteria decision analysis, and text analysis as the methods of artificial intelligence for ATCs training have been described. The authors have made an analysis of the International Civil Aviation Organization documents for modern principles of ATCs education. The prototype...
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Computational Complexity and Its Influence on Predictive Capabilities of Machine Learning Models for Concrete Mix Design
PublicationThe design of concrete mixtures is crucial in concrete technology, aiming to produce concrete that meets specific quality and performance criteria. Modern standards require not only strength but also eco-friendliness and production efficiency. Based on the Three Equation Method, conventional mix design methods involve analytical and laboratory procedures but are insufficient for contemporary concrete technology, leading to overengineering...
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Detection of People Swimming in Water Reservoirs with the Use of Multimodal Imaging and Machine Learning
PublicationEvery year in many countries, there are fatal unintentional drownings in different water reservoirs like swimming pools, lakes, seas, or oceans. The existing threats of this type require creating a method that could automatically supervise such places to increase the safety of bathers. This work aimed to create methods and prototype solutions for detecting people bathing in water reservoirs using a multimodal imaging system and...
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The risk of corporate bankruptcy - the conceptual model
PublicationThis article concerns the assessment of different types of risks influencing the corporate bankruptcy risk. The author has developed conceptual model that explains the causes and the trajectories of the collapse of enterprises. In the analyses such factors as demographic, financial, market, political and operational factors influencing the risk of failure were taken into account.
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Machine Learning-Based Wetland Vulnerability Assessment in the Sindh Province Ramsar Site Using Remote Sensing Data
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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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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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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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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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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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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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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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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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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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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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Deep Learning Basics 2023/24
e-Learning CoursesA course about the basics of deep learning intended for students of Computer Science. It includes an introduction to supervised machine learning, the architecture of basic artificial neural networks and their training algorithms, as well as more advanced architectures (convolutional networks, recurrent networks, transformers) and regularization and optimization techniques.
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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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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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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...