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Search results for: marine robotics
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Moisture damage mechanism and material selection of HMA with amine antistripping agent
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DNA repair is responsible for the presence of oxidatively damaged DNA lesions in urine
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Procedure of determination of volatile trihalomethanes in human urine with pervaporation and gas chromatography
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Effect of treating method on the physicochemical properties of amine-functionalized carbon nanotubes
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Procedure of determination of volatile trihalomethanes in human urine with perwaporation and gas chromatography
PublicationPraca przedstawia wyznaczanie podstawowych parametrów walidacyjnych nowej procedury oznaczania lotnych związków chlorowcoorganicznych z grupy trihalometanów w próbkach moczu ludzkiego, opartej na zastosowaniu:- techniki perwaporacji na etapie izolacji i wzbogacania analitów;- bezpośredniego dozowania próbek ekstraktów (permeatu) do kolumny chromatograficznej;- chromatograficznego rozdzielanie mieszaniny na poszczególne składniki;-wykorzystaniu...
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Amine–alkyl derivatives of hydantoin: New tool to combat resistant bacteria
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Calix[4]arene-Thioamides as Ionophores for Transition and Heavy Metal Cations.
PublicationPochodne kaliks[4]arenów odgrywają ważną rolę jako materiał aktywny w membranowych elektrodach jonoselektywnych. Obecnie duży nacisk kładzie się na kontrolę stężeń kationów metali ciężkich, takich jak Pb, Cd, Hg, Cu w wodach naturalnych. Naszym zadaniem było zaprojektować i zsyntezować ligandy, które wykazują zdolność do wiązania kationów metali ciężkich i przejściowych. Synteza, struktury krystaliczne, ekstrakcja i właściwości...
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Calix[4]arene-Thioamides as Ionophores for Transition and Heavy Metal cations
PublicationCalix[4]arene derivatives play an important role as sensing materials in Ion Selective Electrodes(ISEs). Nowadays a high impact is put to control in natural waters the level of toxic heavy metals, like Pb ,Cd, Hg or Cu which may cause the great risk to human health. Our goal was to design and to synthesize ligands possessing ability to bind transition and heavy metal cations. The synthesis, crystal structures,extractive and ionophoric...
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Studies of complexation of metal cations by tris(3,6-dioxaheptyl)amine in solution
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Amine-Based Ionic Liquid for CO2 Capture and Electrochemical or Thermal Regeneration
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Effect of treated swimming pool water on the levels of trihalomethanes in swimmer's urine
PublicationBaseny są uważane za pierwotne źródło publicznego narażenia na trihalometany, między innymi chloroform (ma zastosowanie w dezynfekcji, a wysokie stężenia chloru są łatwo wyczuwalne zapachem). Celem badania był równoczesny przymiar poziomów THM w próbkach moczu i krwi pływaków jak również w wodzie basenowej (z miejskiego i uniwersyteckiego basenu), w celu zbadania związku między obecnością tych związków w różnych matrycach. Lotne...
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Wiktor Sieklicki dr inż.
PeopleMechanical Engineer degree in Automatics and Robotics achieved in 2006 from Mechanical Faculty of Gdansk University of Technology, Mechanics and Strength of the Materials Department (thesis topic: "Micro electro-mechanical devices for laparoscopy"). Thesis written during the exchange program with Genova University, Italy. PhD in Mechatronics finished in 2010 from Mechanical Faculty of Gdansk University of Technology, Mechanics...
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Annales Universitatis Mariae-Curie Skłodowska, sectio K – Politologia
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Annales Universitatis Mariae Curie-Skłodowska Sectio AI Informatica
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Annales Universitatis Mariae Curie-Skłodowska Sectio EE Zootechnica
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Annales Universitatis Mariae Curie-Skłodowska, sectio F-Historia
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Annales Universitatis Mariae Curie-Skłodowska, Sectio H Oeconomia
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ANNALES UNIVERSITATIS MARIAE CURIE-SKLODOWSKA. SECTIO C: BIOLOGIA
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Annales Universitatis Mariae Curie-Skłodowska. Sectio L. Artes
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Annales Universitatis Mariae Curie-Skłodowska, Pharmacia, sectio DDD
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Annales Universitatis Mariae Curie-Skłodowska, Sectio AA, Chemia
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Annales Universitatis Mariae Curie-Sklodowska Sectio EEE Horticultura
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ANNALES UNIVERSITATIS MARIAE CURIE-SKŁODOWSKA, SECTIO D: MEDICINA
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Machining process sequencing and machine assignment in generative feature-based CAPP for mill-turn parts
PublicationProcess selection and sequencing, as one of the most complex issues when evaluated from a mathematical point of view and crucial in CAPP, still attract research attention. For the current trend of intelligent manufacturing, machining features (MFs) are the information carriers for workpiece geometry and topology representation. They are basically derived from CAD models and are used by downstream engineering applications. A feature-based...
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Forecasting values of cutting power for the sawing process of impregnated pine wood on band sawing machine
PublicationW artykule przedstawiono prognozowane wartości mocy skrawania dla pilarki taśmowej (ST100R firmy STENNER), które są stosowane w polskich tartakach. Wartości mocy skrawania oszacowano dla drewna sosny zwyczajnej (Pinus sylvestris L.), które zostało poddane impregnacji. Dla porównania wyznaczono również wartości mocy skrawania dla drewna niezaimpregnowanego. Wartości te określono za pomocą innowacyjnej metody prognozowania sił skrawania,...
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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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Numerical analysis of chip removing system operation in circular sawing machine using CFD software
PublicationPaper presents the analysis of the results of numerical simulations of the air flow process of wood chips removing system in the circular sawing machine. The attention is focused on the upper cover and bottom shelter of the chip removing system. Within the framework of the work a systematic numerical modeling of the air flow distribution in the cover and shelter during operation of the selected rotational speed of saw blade with...
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Hybrid Processing: the Impact of Mechanical and Surface Thermal Treatment Integration onto the Machine Parts Quality
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Exploring the Solubility Limits of Edaravone in Neat Solvents and Binary Mixtures: Experimental and Machine Learning Study
PublicationThis study explores the edaravone solubility space encompassing both neat and binary dissolution media. Efforts were made to reveal the inherent concentration limits of common pure and mixed solvents. For this purpose, the published solubility data of the title drug were scrupulously inspected and cured, which made the dataset consistent and coherent. However, the lack of some important types of solvents in the collection called...
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Evaluating the challenges and needs of parents caring for children with Williams syndrome: A preliminary study from Poland
PublicationBackground: Although physical, cognitive and behavioural manifestations of Williams syndrome(WS) affect every dimension of caregivers lives, no studies on the parental experiences of caringfor a WS child have to date been carried out in Poland.Methods: In order to identify the challenges and needs of Polish carers of WS children a survey wasconducted...
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Analysis of the Multiple Attribute Decision Making Problem with Incomplete Information about Preferences among the Criteria
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Perception of Pathologists in Poland of Artificial Intelligence and Machine Learning in Medical Diagnosis—A Cross-Sectional Study
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Professional activity, gender and disease-related emotions: The impact on parents' experiences in caring for children with phenylketonuria
PublicationIntroduction: Clinical management of rare diseases often fails to acknowledge the challenges faced by caregivers.Whilst management of phenylketonuria (PKU) may not be considered as dire as other conditions, most studiesprimarily concentrate on clinical issues, dietary adherence, or the quality of life of the PKU patients, leavingcaregivers in the background. The aim of the study was to evaluate the psychosocial...
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Modelling of First- and Second-order Chemical Reactions on ARUZ – Massively-parallel FPGA-based Machine
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An Analysis of External Finance Availability on SMEs’ Decision Making: A Case Study of the Emerging Market of Poland
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Expression and cellular distribution of zona pellucida glycoproteins in canine oocytes before and after in vitro maturation
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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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Optical method supported by machine learning for urinary tract infection detection and urosepsis risk assessment
PublicationThe study presents an optical method supported by machine learning for discriminating urinary tract infections from an infection capable of causing urosepsis. The method comprises spectra of spectroscopy measurement of artificial urine samples with bacteria from solid cultures of clinical E. coli strains. To provide a reliable classification of results assistance of 27 algorithms was tested. We proved that is possible to obtain...
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Speed estimation of a car at impact with a W-beam guardrail using numerical simulations and machine learning
PublicationThis paper aimed at developing a new method of estimating the impact speed of a passenger car at the moment of a crash into a W-beam road safety barrier. The determination of such a speed based on the accident outcomes is demanding, because often there is no access to full accident data. However, accurate determination of the impact speed is one of the key elements in the reconstruction of road accidents. A machine learning algorithm...
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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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Analysis of surface roughness of chemically impregnated Scots pine processed using frame-sawing machine
PublicationThe objective of this work was to evaluate the effect of the impregnation process of pine wood (Pinus sylvestris L.) on roughness parameters of the surface processed on a frame sawing. The samples weredried and impregnated using a commercial procedure by a local company. The touch method withthe use of measuring stylus (pin) was employed to determine of surface roughness of the samplesconsidering parameters, namely, arithmetical...
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A novel hybrid adaptive framework for support vector machine-based reliability analysis: A comparative study
PublicationThis study presents an innovative hybrid Adaptive Support Vector Machine - Monte Carlo Simulation (ASVM-MCS) framework for reliability analysis in complex engineering structures. These structures often involve highly nonlinear implicit functions, making traditional gradient-based first or second order reliability algorithms and Monte Carlo Simulation (MCS) time-consuming. The application of surrogate models has proven effective...
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SafeCity – a GIS-based tool profiled for supporting decision making in urban development and infrastructure protection
PublicationThis paper presents a system for analysis of municipal Critical Infrastructures, which offers integrated tools for target analysis, hazard scenario simulations and spatial analysis within a remotely accessible Web-based Geographic Information System. The system has been applied to research conducted in the city of Gdansk with the aid of blast attack, chemical leakage and flood hazard scenarios, as well as a spatial density algorithm,...
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Investigations of methods to measure longitudinal forces in continuous welded rail tracks using the tamping machine.
PublicationPraca przedstawia w sposób poglądowy próby znalezienia efektywnej metody określania sił podłużnych w szynach toru bezstykowego. Szczególną uwagę poświęcono metodzie wymuszonych przemieszczeń poprzecznych. Podstawowym stwierdzeniem z przeprowadzonych własnych badań była konieczność odejścia od podnoszenia odłączonego od podkładów odcinka szyny i skoncentrowanie się na przemieszczeniach poprzecznych; doprowadziło to koncepcji zastosowania...
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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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Professional activity, gender and disease-related emotions: The impact on parents' experiences in caring for children with phenylketonuria
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Decisional DNA (DDNA) Based Machine Monitoring and Total Productive Maintenance in Industry 4.0 Framework
PublicationThe entire manufacturing spectrum is transforming with the advent of Industry 4.0. The features of Set of Experience Knowledge Structure (SOEKS) and Decisional DNA (DDNA) were utilized for developing Virtual Engineering Objects (VEO), Virtual Engineering Process (VEP) and Virtual Engineering Factory (VEF), which in turn facilitate the creation of smart factories. In this study, DDNA based Machine Monitoring for Total Maintenance...
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Predicting seismic response of SMRFs founded on different soil types using machine learning techniques
PublicationPredicting the Maximum Interstory Drift Ratio (M-IDR) of Steel Moment-Resisting Frames (SMRFs) is a useful tool for designers to approximately evaluate the vulnerability of SMRFs. This study aims to explore supervised Machine Learning (ML) algorithms to build a surrogate prediction model for SMRFs to reduce the need for complex modeling. For this purpose, twenty well-known ML algorithms implemented in Python software are trained...
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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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Marian Żerebecki – saper, inżynier, wykładowca Politechniki Gdańskiej – mało znany, ale czy zapomniany?
PublicationArtykuł przedstawia sylwetkę Mariana Żerebeckiego – sapera, inżyniera, wykładowcy Politechniki Gdańskiej