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Search results for: marine%20robotics
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Occurrence of aspartyl proteases in brine after herring marinating
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Lower rim substituted p-tert-butylcalix[4]arene; Part 14. Synthesis, structures and binding studies of calix[4]arene thioamides
PublicationA number of p-tert-butylcalix[4]arene thioamides were synthesized and characterized by 1H-NMR and elemental analysis. Compounds 1-5 are O-substituted derivatives with -CH2-C(=S)-N-X groups, where NX = morpholidyl, NEt2, NHC2H4Ph, NHCH2Ph and NHEt,respectively. The X-ray structures of the ligands 1, 3, 5 and of the complex 3Pb(ClO4)2, (compound 6), are presented and their slightly distorted cone conformation is established. The...
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Maciej Bagiński prof. dr hab. inż.
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Selected problems of estimation of road and marine transport resources operation fuel consumption = Wybrane problemy oceny eksploatacyjnego zużycia paliwa w środkach transportu drogowego i morskiego
PublicationW referacie przedstawiono metody oceny eksploatacyjnego zużycia paliwa w środkach transportu drogowego. Omówiono testy zużycia paliwa prowadzone przez producentów pojazdów oraz zaprezentowano problematykę ich reprezentatywności dla dzisiejszych warunków ruchu. W drugiej części referatu przedstawiono problematykę prognozowania zużycia paliwa statków towarowych ze szczególnym uwypukleniem odmienności opisu warunków eksploatacji środków...
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Potential of Polish R&D industry in the context of prototyping, design, development and control of a dedicated national satellite SAR system for marine ecosystem monitoring. Technical paper - preliminary study
Publicationpace technology is currently one of the most important elements in the advance of information societies and knowledge-based economies all over the world. The European Space Agency (ESA) is in the focal point of European space activities, while the European Union provides strong financial support for the development of space technologies and applications in its flagship programs. In a domestic scope, the Polish Space Agency (POLSA)...
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Marta Łabuda dr hab. inż.
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Application of sliding switching functions in backstepping based speed observer of induction machine
PublicationThe paper presents an analysis of the speed observer which is based on the backstepping and sliding mode approach. The speed observer structure is based on the extended mathematical model of an induction machine. The observer structure is based on the measured phase stator currents and transformed to ( αβ ) coordinate system. The stator voltage vector components are treated as known values. Additionally, such an observer structure...
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SYNTHESIS OF PHOSPHORUS TACRINE ANALOGUES AS A NEW POTENTIAL ANTI-ALZHEIMER’S DISEASE AGENTS
PublicationA series of novel phosphorus tacrine derivatives was obtained in three steps, including synthesis of 9-chlorotacrine, connection of 9-chlorotacrine with hexamethylenediamine, 1,8-diaminooctane and 1,12-diaminododecane linkers and reaction of obtained tacrine diamine analogues with corresponding acid ester to give nine tacrine organophosphorus compounds. All of the obtained final structures were characterized by 1H NMR, 13C NMR,...
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RSS-Based DoA Estimation for ESPAR Antennas Using Support Vector Machine
PublicationIn this letter, it is shown how direction-of-arrival (DoA) estimation for electronically steerable parasitic array radiator (ESPAR) antennas, which are designed to be integrated within wireless sensor network nodes, can be improved by applying support vector classification approach to received signal strength (RSS) values recorded at an antenna's output port. The proposed method relies on ESPAR antenna's radiation patterns measured...
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The methodology for determining of the value of cutting power for cross cutting on optimizing sawing machine
PublicationIn the article the methodology of forecasting the energy effects of the cross-cutting process using the classical method, which takes into account the specific cutting resistance, is presented. The values of cutting power for the cross-cutting process of two types of wood (softwood and hardwood) were forecasted for the optimizing sawing machine with using presented methodology. The cross-cutting process with high values of feed...
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Experimental tuning of AuAg nanoalloy plasmon resonances assisted by machine learning method
PublicationPlasmonic nanostructures based on AuAg nanoalloys were fabricated by thermal annealing of metallic films in an argon atmosphere. The nanoalloys were chosen because they can extend the wavelength range in which plasmon resonance occurs and thus allow the design of plasmonic platforms with the desired parameters. The influence of initial fabrication parameters and experimental conditions on the formation of nanostructures was investigated....
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Nonadaptive estimation of the rotor speed in an adaptive full order observer of induction machine
PublicationThe article proposes a new method of reproducing the angular speed of the rotor of a cage induction machine designed for speed observers based on the adaptive method. In the proposed solution, the value of the angular speed of the rotor is not determined by the classical law of adaptation using the integrator only by an algebraic relationship. Theoretical considerations were confirmed by simulation and experimental tests.
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A Proposed Machine Learning Model for Forecasting Impact of Traffic-Induced Vibrations on Buildings
PublicationTraffic-induced vibrations may cause various damages to buildings located near the road, including cracking of plaster, cracks in load-bearing elements or even collapse of the whole structure. Measurements of vibrations of real buildings are costly and laborious. Therefore the aim of the research is to propose the original numerical algorithm which allows us to predict, with high probability, the nega-tive dynamic impact of traffic-induced...
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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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Między klasyką a awangardą. Szpital Morski na Oksywiu projektu Mariana Lalewicza
PublicationCelem artykułu jest ukazanie architektonicznego dziedzictwa Szpitala Morskiego w Gdyni, będącego inwestycją wojskową z początku lat 30. XX weku, a powstałego w biurze ważnego i cenionego architekta – Mariana Lalewicza. Ten zasłużony projektant, reprezentant klasycyzmu akademickiego, miał w swym dorobku m.in. kilka gdyńskich obiektów istotnych dla Polskiej Marynarki Wojennej. W 1930 r. podjął się wyzwania szczególnego, jakim była...
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Analyzing and Visualizing Government-Citizen Interactions on Twitter to Support Public Policy-making
PublicationTwitter is widely adopted by governments to communicate with citizens. It has become a major source of data for analyzing how governments communicate with citizens and how citizens respond to such communication, uncovering important insights about government-citizen interactions that could be used to support public policy-making. This article presents research that aims at developing a software tool called Twitter Analytics for...
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Analyzing the Effectiveness of the Brain–Computer Interface for Task Discerning Based on Machine Learning
PublicationThe aim of the study is to compare electroencephalographic (EEG) signal feature extraction methods in the context of the effectiveness of the classification of brain activities. For classification, electroencephalographic signals were obtained using an EEG device from 17 subjects in three mental states (relaxation, excitation, and solving logical task). Blind source separation employing independent component analysis (ICA) was...
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Machine learning techniques combined with dose profiles indicate radiation response biomarkers
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Enhancement of ibuprofen solubility and skin permeation by conjugation with l-valine alkyl esters
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Struktura triacylogliceroli olejów z nasion truskawki, maliny i czarnej porzeczki
PublicationPrzedmiotem badań było określenie struktury triacylogliceroli (TAG) olejów z nasion maliny, truskawki i czarnej porzeczki. W TAG badanych olejów pozycje zewnętrzne sn-1 i sn-3 zajmują głównie kwasy nasycone palmitynowy C16:0 i stearynowy C18:0 oraz kwas C18:1 (n-7). Przeważająca ilość kwasu linolowego C18:2 (n-6)występującego w badanych olejach zajmuje pozycje wewnętrzną sn-2. Udział procentowy pozostałych KT w pozycjach sn-1,3...
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Hydrogeochemistry and vulnerability of groundwater in the moraine upland aquifers of the Gdańsk region (Northern Poland)
PublicationWody podziemne występujące w utworach morenowych na Pojezierzu Kaszubskim charakteryzują się różnym stopniem przykrycia i wynikającą z tego różną podatnością na zanieczyszczenie. Skład chemiczny tych wód jest wynikiem działania czynników naturalnych oraz antropogenicznych, które powodują wzrost stężeń niektórych składników, i pogarszają jakość wód.
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Irony, self-mockery, and ironic turns of events. Marian Załucki’s satirical performances
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Overcoming “Big Data” Barriers in Machine Learning Techniques for the Real-Life Applications
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Problemy architektoniczne bazy na Marsie jako habitatu w ekstremalnych warunkach
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Improving operating efficiency of a gas turboset via cooperation with an absorption refrigerating machine
PublicationThe analysis of increase of ambient air temperature entering the compressor on reduction in power output from the turbine and increase fuel use was conduced. For medium size gas turbine operates in winter and summer conditions elementary power and economical values was calculated. Conditions of the determination of turbine inlet air cooling solution (using thermal storage for reduce equipment size) are presented
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ISSUE OF MAKING DECISIONS WITH REGARD TO SHIP TRAFFIC SAFETY IN DIFFERENT SITUATIONS AT SEA
PublicationThe paper refers to the possibilities of making operational decisions that would enable to ensure safety to a ship in the event of application of the statistical decision theory with consideration of an expected value of consequences as a criterion for making such a decision. General description includes conditions for carrying out transportation tasks by ships and it has been shown that following this description it is possible...
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<title>Management system of ELHEP cluster machine for FEL photonics design</title>
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Spectral and photophysical properties of some imidazo[1,2-a]purine derivatives related to acyclovir
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Caring Ability and Professional Values of Polish Nursing Students—A Cross-Sectional Study
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Machine Learning and data mining tools applied for databases of low number of records
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From the Dynamic Lattice Liquid Algorithm to the Dedicated Parallel Computer – mDLL Machine
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Evaluation of Machine Learning Methods for the Experimental Classification and Clustering of Higher Education Institutions
PublicationHigher education institutions have a big impact on the future of skills supplied on the labour market. It means that depending on the changes in labour market, higher education institutions are making changes to fields of study or adding new ones to fulfil the demand on labour market. The significant changes on labour market caused by digital transformation, resulted in new jobs and new skills. Because of the necessity of computer...
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Application of Spatial Models in Making Location Decisions of Wind Power Plant in Poland
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Prolonged pharmacological inhibition of cathepsin C results in elimination of neutrophil serine proteases
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Influence of frame sawing machine´s kinematics on saw blade tooth wear.
PublicationW pracy przedstawiono wpływ kinematyki pilarki ramowej na zużycie ostrzy piłtrakowych.
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Advancing Solar Energy: Machine Learning Approaches for Predicting Photovoltaic Power Output
PublicationThis research is primarily concentrated on predicting the output of photovoitaic power, an essential field in the study of renewable energy. The paper comprehensively reviews various forecasting methodologies, transitioning from conventional physical and statistical methods to advanced machine learning (ML) techniques. A significant shift has been observed from traditional point forecasting to machine learning-based forecasting...
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Machine-aided detection of SARS-CoV-2 from complete blood count
PublicationThe current gold standard for SARS-CoV-2 detection methods lacks the functionality to perform population screening. Complete blood count (CBC) tests are a cost-effective way to reach a wide range of people – e.g. according to the data of the Central Statistical Office of Poland from 2016, there are 3,000 blood diagnostic laboratories in Poland, and 46% of Polish people have at least one CBC test per year. In our work, we show...
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Data and knowledge supporting decision-making for the urban Food-Water-Energy nexus
PublicationCities are hubs of innovation and wealth creation, and magnets for an increasing urban population. Cities also face unprecedented challenges in terms of food, water and energy scarcity, and governance and management. Urban environmental issues are no longer problems for experts to address but have become issues of public debate, in which knowledge from multiple sectors is needed to support inclusive governance approaches. Consequently,...
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Learning and memory processes in autonomous agents using an intelligent system of decision-making
PublicationThis paper analyzes functions and structures of the memory that is an indispensable part of an Intelligent System of Decision-making (ISD), developed as a universal engine for autonomous robotics. A simplified way of processing and coding information in human cognitive processes is modelled and adopted for the use in autonomous systems. Based on such a knowledge structure, an artificial model of reality representation and a model...
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Selection of New Chromogenic Substrates of Serine Proteinases Using Combinatorial Chemistry Methods
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Machine learning approach to packaging compatibility testing in the new product development process
PublicationThe paper compares the effectiveness of selected machine learning methods as modelling tools supporting the selection of a packaging type in new product development process. The main goal of the developed model is to reduce the risk of failure in compatibility tests which are preformed to ensure safety, durability, and efficacy of the finished product for the entire period of its shelf life and consumer use. This kind of testing...
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Machine learning-based seismic response and performance assessment of reinforced concrete buildings
PublicationComplexity and unpredictability nature of earthquakes makes them unique external loads that there is no unique formula used for the prediction of seismic responses. Hence, this research aims to implement the most well-known Machine Learning (ML) methods in Python software to propose a prediction model for seismic response and performance assessment of Reinforced Concrete Moment-Resisting Frames (RC MRFs). To prepare 92,400 data...
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Landscape, EIA and decision-making. A case study of the Vistula Spit Canal, Poland
PublicationAlthough landscapes are often considered public goods, they frequently receive inadequate attention in Environmental Impact Assessments (EIAs), particularly in Poland. This neglect often leads to visible degradation during investment processes. This article examines the case of the Vistula Spit Canal, currently the largest engineering project under construction in Poland. We analysed whether the conclusions drawn in the EIA report,...
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Machine learning for the management of biochar yield and properties of biomass sources for sustainable energy
PublicationBiochar is emerging as a potential solution for biomass conversion to meet the ever increasing demand for sustainable energy. Efficient management systems are needed in order to exploit fully the potential of biochar. Modern machine learning (ML) techniques, and in particular ensemble approaches and explainable AI methods, are valuable for forecasting the properties and efficiency of biochar properly. Machine-learning-based forecasts,...
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Preeclampsia Risk Prediction Using Machine Learning Methods Trained on Synthetic Data
PublicationThis paper describes a research study that investigates the use of machine learning algorithms on synthetic data to classify the risk of developing preeclampsia by pregnant women. Synthetic datasets were generated based on parameter distributions from three real patient studies. Four models were compared: XGBoost, Support Vector Machine (SVM), Random Forest, and Explainable Boosting Machines (EBM). The study found that the XGBoost...
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Predicting emotion from color present in images and video excerpts by machine learning
PublicationThis work aims at predicting emotion based on the colors present in images and video excerpts using a machine-learning approach. The purpose of this paper is threefold: (a) to develop a machine-learning algorithm that classifies emotions based on the color present in an image, (b) to select the best-performing algorithm from the first phase and apply it to film excerpt emotion analysis based on colors, (c) to design an online survey...
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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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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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DNAffinity: a machine-learning approach to predict DNA binding affinities of transcription factors
PublicationWe present a physics-based machine learning approach to predict in vitro transcription factor binding affinities from structural and mechanical DNA properties directly derived from atomistic molecular dynamics simulations. The method is able to predict affinities obtained with techniques as different as uPBM, gcPBM and HT-SELEX with an excellent performance, much better than existing algorithms. Due to its nature, the method can...
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Sensorless control of five-phase induction machine supplied by the VSI with output filter
PublicationIn this paper, a novel sensorless control structure based on multi-scalar variables is proposed. The tatic feedback control law is obtained by using the multi-scalar variables transformation, where the multi-scalar variables approach allows a full linearization of the nonlinear system. The control system could be described as “optimized” because of the minimized number of controllers. Furthermore, control system is divided into...