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Search results for: MARINE%20SAFETY
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QEEG-based neural correlates of decision making in a well-trained eight-year-old chess player
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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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Investigation of Serine‐Proteinase‐Catalyzed Peptide Splicing in Analogues of Sunflower Trypsin Inhibitor 1 (SFTI‐1)
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Universal Predictors of Dental Students’ Attitudes towards COVID-19 Vaccination: Machine Learning-Based Approach
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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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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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Marian Grabowski, Pierwociny stworzenia. Pomiędzy filozofią a fizyką, Wydawnictwo Naukowe UMK, Toruń 2019 (rec.)
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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 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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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...
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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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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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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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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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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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Chip suction system in circular sawing machine: empirical research and computational fluid dynamics numerical simulations
PublicationThe experimental analysis of the wood chip removing system during its redesigning in the existing sliding table circular saw and computational fluid dynamic (CFD) numerical simulations of the air flow process is presented in the paper. The attention was focused on the extraction hood and the bottom shelter of the actual existing system. The main aim was to perform experimental research on the pressure distribution inside the...
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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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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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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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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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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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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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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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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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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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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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Safety and outcomes of laparoscopic sleeve gastrectomy in patients older than 60: a case-control study
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Safety and Outcomes of Inferior Vena Cava Filter Placement in Oncology Patients: A Single-Centre Experience
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Establishing a New ECMO Referral Center Using an ICU-Based Approach: A Feasibility and Safety Study
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The Medical Relevance of Toxoplasma Infections in Terms of the Safety of Blood Recipients under Immunosuppression—A Meta-Analysis
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Direct human contact with siloxanes (silicones): safety or risk. Part 1: characteristics of siloxanes (silicones
PublicationSiloxanes are commonly known as silicones. They belong to the organosiliconcompounds and are exclusively obtained by synthesis. Their chemical structuredetermines a range of physicochemical properties which were recognized as unique.Due to the susceptibility to chemical modifications, ability to create short, long orcomplex polymer particles, siloxanes found an application in many areas of human life.
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Model of identification of events and accident scenarios for a method of risk and safety assessment of ships in damaged conditions
PublicationW pracy opisano podstawowe problemy związane z identyfikacją zdarzeń i scenariuszy wypadku oraz modelowaniem ryzyka dla alternatywnej metody oceny bezpieczeństwa statków w stanie uszkodzonym. Zastosowano podejście do bezpieczeństwa statków oparte na ocenie zachowania się statku i ocenie ryzyka wypadku. Wskazano możliwości zastosowania modelowania do analizy bezpieczeństwa statków na etapie projektowania, w czasie eksploatacji i...
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Safety and efficacy of lenabasum in a phase 2 randomized, placebo-controlled trial in adults with cystic fibrosis
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A Method of Risk and Safety Assessment During the Ship Salvage Using the Hazard, Release and Consequence Analysis
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Safety of erection and repair of steel tanks with geometric imperfections using heavylift jack-up system
PublicationSafety analysis is performed of cylindrical vertical steel tanks during erection using heavylift jack up system. During an assembly or repair process a set of hydraulic supports is used. It allows to use the in-place lifting of heavy steel constructions on the required height. Wind can strongly influence stability of the lifted tank. Any geometric imperfections can reduce the critical or limit load. In the work failures of the...
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Knowledge-based functional safety and security management in hazardous industrial plants with emphasis on human factors
PublicationExisting and emerging new hazards have significant potential to impact destructively operation of technical systems, hazardous plants, and systems / networks of critical infrastructure. The programmable control and protection systems play nowadays an important role in reducing and controlling risk in the process of hazardous plant operation. It is outlined how to deal with security related hazards concerning such systems to be...
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ON ESTIMATION OF OCCUPANT SAFETY IN VEHICULAR CRASHES INTO ROADSIDE OBSTACLES USING NON-LINEAR DYNAMIC ANALYSIS
PublicationThe article describes a comparison of two general methods of occupants safety estimation based on a numerical examples. The so-called direct method is mainly based on the Head Injury Criterion of a crash test dummy in a vehicle with passive safety system while the indirect method uses a European standards approach to estimate impact severity level. Numerical simulations in LS-DYNA have been conducted.
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Verification of safety in low-voltage power systems without nuisance tripping of residual current devices
PublicationLow-voltage power systems require initial and periodical verification to check the effectiveness of protection against electric shock. As a protection in case of fault, automatic disconnection of supply is most often used. To verify such a protection measure, the earth fault loop impedance or resistance is measured. This measurement is easy to perform in circuits without residual current devices. When residual current devices are...
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Methodology of research on the impact of ramp metering on the safety and efficiency of road traffic using transport models
PublicationThe methods currently used to assess the impact of Intelligent Transport Systems (ITS) services on traffic safety and efficiency are mainly based on expert assessments, statistical studies or traffic models that need further development. There is no structured, uniform evaluation method to compare the impact of different ITS services and their different configurations. The impact of ITS deployment on the road network adjacent to...
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Methodology of research on the impact of ITS services on the safety and efficiency of road traffic using transport models
PublicationThe current assessment of the impact of Intelligent Transport System (ITS) services on the level of traffic safety and efficiency is based mainly on expert assessments, statistical surveys or several traffic safety models requiring development. There is no structured, uniform assessment method that would give the opportunity to compare the impact of ITS services and their different configurations. The paper presents the methodology...
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Safety issues referred to induced sheath voltages in high-voltage power cables – case study
PublicationLoad currents and short-circuit currents in high-voltage power cable lines are sources of the induced voltages in the power cables’ concentric metallic sheaths. When power cables operate with single-point bonding, which is the simplest bonding arrangement, these induced voltages may introduce an electric shock hazard or may lead to damage of the cables’ outer non-metallic sheaths at the unearthed end of the power cable line. To...
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Fuel price, income and road safety as determinants of the level of the population’s economic well-being in Poland
PublicationThe opportunity to travel is one of the most favorite human activities, given that on a trip a person gets new knowledge, impressions and positive emotions. Recreational trips occupy a prominent place in the concept of the economics of happiness, and the study of factors that influence decision-making regarding travel is important for forecasting the number of tourists, infrastructure development, income and expenses of businesses...
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Consideration of the safety of bungee jumping in relation to mechanical properties of the instalation based on a jump accident in Gdynia
PublicationThis paper considers a bungee jumping accident that took place in July 2019 in Gdynia, Poland. The authors conducted an investigation to determine the cause of the bungee rope failure. It was based on mechanical tests concerning the strength of the rope as well as the calculation of the force induced in the rope during the jump. Based on the theoretical and experimental results, the rope safety factor was estimated. It appeared...
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Speed, Alcohol and Safety Belts as Important Factors Influencing the Number of Fatalities in Road Accidents in the Voivodships
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