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Search results for: MARINE RESTORATION
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The impact of cold plasma on the phenolic composition and biogenic amine content of red wine
PublicationThe effect of cold plasma (CP) on phenolic compound (PC) and biogenic amine (BA) contents of red wine was investigated for the first time. The influence of CP was compared with the effects of a wine preservation using potassium metabisulfite and a combined method. The PC profile was determined by UPLC-PDA-MS/MS while BAs using DLLME-GC–MS. Chemometric analysis also was used. The content of PCs was 3.1% higher in the sample preserved...
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Ion Chromatography with Pulsed Amperometric Detection for Determining Cyanide in Urine and Meconium Samples
PublicationThe parents’ addictions and eating habits have a significant influence on the child’s growth. The first stool of a newborn baby provides a large amount of information about xenobiotics transmitted by the mother’s body. The analytical technique used in the study is ion chromatography with pulsed amperometric detection (IC-PAD). The biological samples, which were obtained from women staying in a maternity ward and their partners,...
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Koncertowa funkcja kościoła pod wezwaniem św. Marii Magdaleny we Lwowie
PublicationPrzedstawiono wyniki pomiarów akustycznych kościoła oraz oceniono jego właściwości pod kątem jego funkcji koncertowej. Omówiono koncepcję przystosowania wnętrza do funkcji koncertowej z roku 1974, naruszającą barokowy wystrój kościoła. Podano zalecenia poprawiające wzajemne słyszenie się wykonawców oraz zwiększające stopień rozproszenia dźwięku, zgodne ze współczesnymi wytycznymi konserwatorskimi.
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IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
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Boletin de Investigaciones Marinas y Costeras
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REVMAR-Revista Ciencias Marinas y Costeras
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INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING
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Efficiency of service recovery in scale-free optical networks under multiple node failures
PublicationIn this paper we examine the properties of scale-free networks in case of simultaneous failures of two networknodes. Survivability assumptions are as follows: end-to-end path protection with two node-disjoint backup pathsfor each working path. We investigate three models of scale-free networks generation: IG, PFP and BA.Simulations were to measure the lengths of active and backup paths and the values of service recovery time.We...
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NVRAM as Main Storage of Parallel File System
PublicationModern cluster environments' main trouble used to be lack of computational power provided by CPUs and GPUs, but recently they suffer more and more from insufficient performance of input and output operations. Apart from better network infrastructure and more sophisticated processing algorithms, a lot of solutions base on emerging memory technologies. This paper presents evaluation of using non-volatile random-access memory as a...
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Neutrophil extracellular traps as the main source of eDNA
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Main Outlines of Lightning Research Development in Poland
PublicationThe paper deals with the historical development of lightning protection research, lightning protection ideas and investigations in Poland. The main achievements of lightning research performed at the technical universities in Gdansk, Warsaw and Rzeszow have been characterized. Exemplary main achievements related to natural lightning observations and measurements as well to those performed in laboratory scale tests have been shortly...
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Journal of Ocean Engineering and Marine Energy
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JOURNAL OF EXPERIMENTAL MARINE BIOLOGY AND ECOLOGY
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A decision-making system supporting selection of commanded outputs for a ship's propulsion system with a controllable pitch propeller
PublicationThe ship's operators have to make decisions regarding the values of commanded outputs (commanded engine speed and pitch ratio) which ensure maximum vessel speed and minimum fuel consumption. Obviously, the presented decision problems are opposed. Therefore, there is a need for a compromise solution that enables more flexible vessel voyage planning. This paper deals with development of a computer-aided system supporting selection...
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Assessing groundwater vulnerability to pollution in the Puck region (denudation moraine upland) using vertical seepage method
PublicationDegradation of groundwater quality can cause a serious water supply and environmental problems. The identify of potential groundwater pollution can be determined by assessment of groundwater vulnerability method. The assessment of groundwater vulnerability to pollution was based on estimation of migration time of potential conservative contamination through the vadose zone. Area of investigation is a type of denudation moraine...
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Credit Decision Support Based on Real Set of Cash Loans Using Integrated Machine Learning Algorithms
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The effect of alcohols as vehicles on the percutaneous absorption and skin retention of ibuprofen modified with l-valine alkyl esters
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Expert system against machine learning approaches as a virtual sensor for ventricular arrhythmia risk level estimation
PublicationRecent advancements in machine learning have opened new avenues for preventing fatal ventricular arrhythmia by accurately measuring and analyzing QT intervals. This paper presents virtual sensor based on an expert system designed to prevent the risk of fatal ventricular arrhythmias associated with QT-prolonging treatments. The expert system categorizes patients into three risk levels based on their electrocardiogram-derived QT...
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Investigating the Effects of Ground-Transmitted Vibrations from Vehicles on Buildings and Their Occupants, with an Idea for Applying Machine Learning
PublicationVibrations observed as a result of moving vehicles can potentially affect both buildings and the people inside them. The impacts of these vibrations are complex, affected by a number of parameters, like amplitude, frequency, and duration, as well as by the properties of the soil beneath. These factors together lead to various effects, from slight disruptions to significant structural damage. Occupants inside affected buildings...
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Detection of Cystic Fibrosis Symptoms Based on X-Ray Images Using Machine Learning- Pilot Study
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The Setting Time of Polyether Impression Materials after Contact with Conventional and Experimental Gingival Margin Displacement Agents
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Ecology In Tribology: Selected Problems of Eliminating Natural Oil-Based Lubricants from Machine Friction Couples
PublicationThe elimination of mineral oil-based lubricants from machines has multiple beneficial effects on the natural environment. Firstly – these lubricants are a direct threat to the environment in the event of leaks; secondly – their elimination reduces the demand for crude oil from which they are obtained. In addition, in many cases, e.g. when replacing traditional lubricants with water, friction losses in the bearings can also be reduced...
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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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An algorithm for selecting a machine learning method for predicting nitrous oxide emissions in municipal wastewater treatment plants
PublicationThis study presents an advanced algorithm for selecting machine learning (ML) models for nitrous oxide (N2O) emission prediction in wastewater treatment plants (WWTPs) employing the activated sludge process. The examined ML models comprised multivariate adaptive regression spline (MARS), support vector machines (SVM), and extreme gradient boosting (XGboost). The study explores the concept that involves new criteria to select the...
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Seismic response and performance prediction of steel buckling-restrained braced frames using machine-learning methods
PublicationNowadays, Buckling-Restrained Brace Frames (BRBFs) have been used as lateral force-resisting systems for low-, to mid-rise buildings. Residual Interstory Drift (RID) of BRBFs plays a key role in deciding to retrofit buildings after seismic excitation; however, existing formulas have limitations and cannot effectively help civil engineers, e.g., FEMA P-58, which is a conservative estimation method. Therefore, there is a need to...
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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-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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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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Efficient Calibration of Cost-Efficient Particulate Matter Sensors Using Machine Learning and Time-Series Alignment
PublicationAtmospheric particulate matter (PM) poses a significant threat to human health, infiltrating the lungs and brain and leading to severe issues such as heart and lung diseases, cancer, and premature death. The main sources of PM pollution are vehicular and industrial emissions, construction and agricultural activities, and natural phenomena such as wildfires. Research underscores the absence of a safe threshold for particulate exposure,...
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Development of an emulation platform for synchronous machine power generation system using a nonlinear functional level model
PublicationThe article presents the Power Hardware in the Loop (PHIL) approach for an autonomous power system analysis based on the synchronous generator model incorporating magnetic saturation effects. The model was prepared in the MATLAB/Simulink environment and then compiled into the C language for the PHIL platform implementation. The 150 kVA bidirectional DC/AC commercial-grade converter was used to emulate the synchronous generator....
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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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Active Learning on Ensemble Machine-Learning Model to Retrofit Buildings Under Seismic Mainshock-Aftershock Sequence
PublicationThis research presents an efficient computational method for retrofitting of buildings by employing an active learning-based ensemble machine learning (AL-Ensemble ML) approach developed in OpenSees, Python and MATLAB. The results of the study shows that the AL-Ensemble ML model provides the most accurate estimations of interstory drift (ID) and residual interstory drift (RID) for steel structures using a dataset of 2-, to 9-story...
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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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Control Strategy of a Five-Phase Induction Machine Supplied by the Current Source Inverter With the Third Harmonic Injection
PublicationIn the five-phase induction machine (IM), it is possible to better use the electromagnetic circuit than in the three-phase IM. This requires the use of an adequate converter system which will be supplied by an induction machine. The electric drive system described, in this article, includes the five-phase induction machine supplied by the current source inverter (CSI). The proposed novelty—not presented previously—is the control...
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Combining the MARTINI and Structure-Based Coarse-Grained Approaches for the Molecular Dynamics Studies of Conformational Transitions in Proteins
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SP-1, a Serine Protease from the Gut Microbiota, Influences Colitis and Drives Intestinal Dysbiosis in Mice
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Design of serine proteinase inhibitors by combinatorial chemistry using trypsin inhibitor SFTI‐1 as a starting structure
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Toxicity Assessment by Microtox® in Sediments, Pore Waters and Sediment Saline Elutriates in the Gulf of Gdansk (Baltic Sea)
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Influence of geometry of iron poles on the cogging torque of a field control axial flux permanent magnet machine
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Universal Predictors of Dental Students’ Attitudes towards COVID-19 Vaccination: Machine Learning-Based Approach
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QEEG-based neural correlates of decision making in a well-trained eight-year-old chess player
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Marian Grabowski, Pierwociny stworzenia. Pomiędzy filozofią a fizyką, Wydawnictwo Naukowe UMK, Toruń 2019 (rec.)
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Investigation of Serine‐Proteinase‐Catalyzed Peptide Splicing in Analogues of Sunflower Trypsin Inhibitor 1 (SFTI‐1)
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Time for a paradigm shift in shared decision-making in trauma and emergency surgery? Results from an international survey
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Quantitative Soil Characterization for Biochar–Cd Adsorption: Machine Learning Prediction Models for Cd Transformation and Immobilization
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Verification of Satellite Railway Track Position Measurements Making Use of Standard Co-Ordinate Determination Techniques
PublicationThe article presents the results of satellite railway track position measurements performed by a multidisciplinary research team, the members of which represented Gdansk University of Technology and Gdynia Maritime University. Measuring methods are described which were used for reconstructing the railway track axis position and diagnosing railway track geometry deformations. As well as that, the description of the novel method...
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Prediction of energy consumption and evaluation of affecting factors in a full-scale WWTP using a machine learning approach
PublicationTreatment of municipal wastewater to meet the stringent effluent quality standards is an energy-intensive process and the main contributor to the costs of wastewater treatment plants (WWTPs). Analysis and prediction of energy consumption (EC) are essential in designing and operating sustainable energy-saving WWTPs. In this study, the effect of wastewater, hydraulic, and climate-based parameters on the daily consumption of EC by...
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Prediction of Wastewater Quality at a Wastewater Treatment Plant Inlet Using a System Based on Machine Learning Methods
PublicationOne 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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Design of new cholinesterase inhibitors based on phosphorus analogs of tacrine as potential anti-Alzheimer’s disease agents
PublicationBased on the analysis of the determined free binding energy (using the AutoDock Vina 1.1.2 docking program), the most potent cholinesterase inhibitors were selected. Moreover, studies of 3D visualization of the results of molecular modeling led to the identification of potential sites for the interaction of new potential inhibitors with amino acid residues building active sites of investigated cholinesterases.
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Control of induction machine supplied by a current source inverter using the multi-scalar transformation and backstepping approach
PublicationThe paper describes the voltage control technique of squire-cage induction machines supplied by a current source inverter. The control system is based on new transformation of the electric drive system (machine and inverter) state variables to the multi-scalar variables form. The backstepping approach is used to obtain the feedback control law. The control system contains the structure of the observer...