Search results for: ARTIFICIAL NEURAL NETWORK, GIS, DIAGNOSIS, MACHINE LEARNING, EXPERT SYSTEM - Bridge of Knowledge

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Search results for: ARTIFICIAL NEURAL NETWORK, GIS, DIAGNOSIS, MACHINE LEARNING, EXPERT SYSTEM

Search results for: ARTIFICIAL NEURAL NETWORK, GIS, DIAGNOSIS, MACHINE LEARNING, EXPERT SYSTEM

  • Klasyfikacja sygnału EKG przy użyciu konwolucyjnych sieci neuronowych

    Automation and improvement of diagnostic process is a vital element of medicine development and patient’s condition self-control. For a long time different ECG signal classification methods exist and are successfully applied, nevertheless their accuracy is not always satisfying enough. The lack of identification of an existing abnormality, which is very similar to a normal heartbeat is the biggest issue - for example premature...

  • Klasyfikacja sygnału EKG przy użyciu konwolucyjnych sieci neuronowych

    Automation and improvement of diagnostic process is a vital element of medicine development and patient’s condition self-control. For a long time different ECG signal classification methods exist and are successfully applied, nevertheless their accuracy is not always satisfying enough. The lack of identification of an existing abnormality, which is very similar to a normal heartbeat is the biggest issue - for example premature...

  • SELECTION OF DIAGNOSTIC FUNCTIONS IN A WHEELED TRACTOR

    Publication

    - Diagnostyka - Year 2013

    In a classical approach to damage diagnosis, the technical condition of an analyzed machine is identified based on the measured symptoms, such as performance, thermal state or vibration parameters. In wheeled tractor the fundamental importance has monitoring and diagnostics during exploitation concerning technical inspection and fault element localizations. The main functions of a diagnostic system are: monitoring tractor components...

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  • Development of an AI-based audiogram classification method for patient referral

    Publication

    - Year 2022

    Hearing loss is one of the most significant sensory disabilities. It can have various negative effects on a person's quality of life, ranging from impeded school and academic performance to total social isolation in severe cases. It is therefore vital that early symptoms of hearing loss are diagnosed quickly and accurately. Audiology tests are commonly performed with the use of tonal audiometry, which measures a patient's hearing...

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  • Physics-guided neural networks (PGNNs) to solve differential equations for spatial analysis

    Numerous examples of physically unjustified neural networks, despite satisfactory performance, generate contradictions with logic and lead to many inaccuracies in the final applications. One of the methods to justify the typical black-box model already at the training stage and lead to many inaccuracies in the final applications. One of the methods to justify the typical black-box model already at the training stage involves extending...

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  • Data-driven models for fault detection using kernel pca:a water distribution system case study

    Kernel Principal Component Analysis (KPCA), an example of machine learning, can be considered a non-linear extension of the PCA method. While various applications of KPCA are known, this paper explores the possibility to use it for building a data-driven model of a non-linear system-the water distribution system of the Chojnice town (Poland). This model is utilised for fault detection with the emphasis on water leakage detection....

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  • A Highly Scalable, Modular Architecture for Computer Aided Assessment e-Learning Systems

    Publication

    In this chapter, the authors propose a novel e-learning system, dedicated strictly to knowledge assessment tasks. In its functioning it utilizes web-based technologies, but its design differs radically from currently popular e-learning solutions which rely mostly on thin-client architecture. The authors' research proved that such architecture, while well suited for didactic content distribution systems is ill-suited for knowledge...

  • The results of physico – chemical monitoring of watercourses around the municipality of Gdańsk in 2016

    Open Research Data
    open access

    The dataset contains the results of a physico-chemical study of watercourses waters within the administrative boundaries of Gdańsk city in 2016. The examined material consisted of water samples collected from 16 watercourses (5 rivers, 6 streams, 2 storm water sewers, 1 artificial canal, 1 artificial arm of a river and 1 drainage trench) flowing directly...

  • Society 4.0: Issues, Challenges, Approaches, and Enabling Technologies

    Publication

    - CYBERNETICS AND SYSTEMS - Year 2024

    This guest edition of Cybernetics and Systems is a broadening continuation of our last year edition titled “Intelligence Augmentation and Amplification: Approaches, Tools, and Case Studies”. This time we cover research perspective extending towards what is known as Society 4.0. Bob de Vit brought the concept of Society 4.0 to life in his book “Society 4.0 – resolving eight key issues to build a citizens society”. From the Systems...

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  • How personality traits, sports anxiety, and general imagery could influence the physiological response measured by SCL to imagined situations in sports?

    Open Research Data
    open access

    The data were collected to understand how individual differences in personality (e.g. neuroticism), general imagery, and situational sports anxiety are linked to arousal measuring with skin conductance level (SCL) in situational imagery (as scripted for sport-related scenes). Thirty persons participated in the study, aged between 14 and 42 years, with...

  • Preferred Benchmarking Criteria for Systematic Taxonomy of Embedded Platforms (STEP) in Human System Interaction Systems

    Publication
    • A. Kwaśniewska
    • S. Raghava
    • C. Davila
    • M. Sevenier
    • D. Gamba
    • J. Rumiński

    - Year 2022

    The rate of progress in the field of Artificial Intelligence (AI) and Machine Learning (ML) has significantly increased over the past ten years and continues to accelerate. Since then, AI has made the leap from research case studies to real production ready applications. The significance of this growth cannot be undermined as it catalyzed the very nature of computing. Conventional platforms struggle to achieve greater performance...

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  • Potential of Explainable Artificial Intelligence in Advancing Renewable Energy: Challenges and Prospects

    Publication
    • V. N. N. Nhanh Van
    • W. Tarełko
    • S. Prabhakar
    • A. S. El-Shafay
    • W. Chen
    • P. Q. P. Nguyen
    • N. X. Phuong
    • T. A. Nguyen

    - ENERGY & FUELS - Year 2024

    Modern machine learning (ML) techniques are making inroads in every aspect of renewable energy for optimizationand model prediction. The effective utilization of ML techniques for the development and scaling up of renewable energy systemsneeds a high degree of accountability. However, most of the ML approaches currently in use are termed black box since their work isdifficult to comprehend. Explainable artificial intelligence (XAI)...

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  • Michał Michna dr hab. inż.

    Michal Michna received the M.Sc. and Ph.D. degrees in electrical engineering from the Gdansk University of Technology (GUT), Gdansk, Poland, in 1998 and 2005, respectively. Since 2004, he was employed at the Department of Power Electronics and Electrical Machines of the Gdańsk University of Technology (assistant, assistant professor, senior lecturer). In 2010-2015 he was a deputy of head of the Department of Power Electronics and...

  • Application of autoencoder to traffic noise analysis

    The aim of an autoencoder neural network is to transform the input data into a lower-dimensional code and then to reconstruct the output from this code representation. Applications of autoencoders to classifying sound events in the road traffic have not been found in the literature. The presented research aims to determine whether such an unsupervised learning method may be used for deploying classification algorithms applied to...

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  • DEEP LEARNING BASED ON X-RAY IMAGING IMPROVES COXARTHROSIS DETECTION

    Publication
    • M. Maj
    • J. Borkowski
    • J. Wasilewski
    • S. Hrynowiecka
    • A. Kastrau
    • M. Liksza
    • P. Jasik
    • M. Treder

    - Year 2022

    Objective: The purpose of the study was to create an Artificial Neural Network (ANN) based on X-ray images of the pelvis, as an additional tool to automate and improve the diagnosis of coxarthrosis. The research is focused on joint space narrowing, which is a radiological symptom showing the thinning of the articular cartilage layer, which is translucent to X-rays. It is the first and the most important of the radiological signs...

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  • Fragmentation of Hydrographic Big Data Into Subsets During Reduction Process

    Publication

    - Year 2017

    The article presented problems of fragmentation of hydrographic big data into smaller subsets during reduction process. Data reduction is a processing of reduce the value of the data set, in order to make them easier and more effective for the goals of the analysis. The main aim of authors is to create new reduction method. The article presented the first stage of this method – fragmentation of bathymetric data into subsets. It...

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  • Estimation of the Ultimate Strength of FRP Strips-to-Masonry Substrates Bond

    Publication

    - Applied Sciences-Basel - Year 2023

    Fiber-Reinforced Polymers (FRP) were developed as a new method over the past decades due to their many beneficial mechanical properties, and they are commonly applied to strengthen masonry structures. In this paper, the Artificial Neural Network (ANN), K-fold Cross-Validation (KFCV) technique, Multivariate Adaptive Regression Spline (MARS) method, and M5 Model Tree (M5MT) method were utilized to predict the ultimate strength of...

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  • Modelowanie przepływu pary przez okołodźwiękowe wieńce turbinowe z użyciem sztucznych sieci neuronoych

    Publication

    Niniejszy artykuł stanowi opis modelu przepływu pary przez okołodźwiękowe stopnie turbinowe, stworzonego w oparciu o sztuczne sieci neuronowe (SSN). Przedstawiony model neuronowy pozwala na wyznaczenie rozkładu wybranych parametrów w analizowanym przekroju kanału przepływowego turbiny dla rozpatrywanego zakresu wartości ciśnienia wlotowego.

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  • GIS Solution for Weather Forecast Data Analysis

    Publication

    In this paper authors present the GIS system for the analysis of the numerical weather prediction data. This kind of data has multidimensional character (three dimensions and time) and its analysis should consider all the available factors. Proposed GIS system consists of RASDAMAN application with implemented OLAP cube mechanism, which enables the user to process data in the spatial-time domain. It also simplifies the meteorological...

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  • Neural Approximators for Variable-Order Fractional Calculus Operators (VO-FC)

    Publication

    - IEEE Access - Year 2022

    The paper presents research on the approximation of variable-order fractional operators by recurrent neural networks. The research focuses on two basic variable-order fractional operators, i.e., integrator and differentiator. The study includes variations of the order of each fractional operator. The recurrent neural network architecture based on GRU (Gated Recurrent Unit) cells functioned as a neural approximation for selected...

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  • Data, Information, Knowledge, Wisdom Pyramid Concept Revisited in the Context of Deep Learning

    Publication

    - Year 2023

    In this paper, the data, information, knowledge, and wisdom (DIKW) pyramid is revisited in the context of deep learning applied to machine learningbased audio signal processing. A discussion on the DIKW schema is carried out, resulting in a proposal that may supplement the original concept. Parallels between DIWK pertaining to audio processing are presented based on examples of the case studies performed by the author and her collaborators....

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  • Optymalizacja treningu i wnioskowania sieci neuronowych

    Sieci neuronowe są jedną z najpopularniejszych i najszybciej rozwijających się dziedzin sztucznej inteligencji. Ich praktyczne wykorzystanie umożliwiło szersze użycie komputerów w wielu obszarach komunikacji, przemysłu i transportu. Dowody tego są widoczne w elektronice użytkowej, medycynie, a nawet w zastosowaniach militarnych. Wykorzystanie sztucznej inteligencji w wielu przypadkach wymaga jednak znacznej mocy obliczeniowej,...

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  • Social media for e-learning of citizens in smart city

    Publication

    - Year 2018

    The rapid development of social media can be applied for citizens’ e-learning in a smart city. Big cities have to cope with several open issues like a growing population or a traffic congestion. Especially, a home and public space is supposed to be used in more efficient way. Sustainable homes and buildings can be planned with using some modern techniques. Even currently, there is a huge problem with a lack of key resources like...

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  • A novel architecture for e-learning knowledge assessment systems

    Publication

    Abstract. In this paper we propose a novel e-learning system, dedicated strictly to knowledge assessment tasks. In its functioning it utilizes web-based technologies, but its design differs radically from currently popular e-learning solutions which rely mostly on thin-client architecture. Our research proved that such architecture,while well suited for didactic content distribution systems is ill-suited for knowledge assessment...

  • The use of GIS tools for road infrastructure safety management

    There are many factors that influence accidents and their severity. They can be grouped within the system of man, vehicle and environment. The article focuses on how GIS tools can be used to manage road infrastructure safety. To ensure a better understanding and identification of road factors, GIS tools help with the acquisition of road parameter data. Their other role is helping with a clear and effective presentation of risk...

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  • Classifying Emotions in Film Music - A Deep Learning Approach

    The paper presents an application for automatically classifying emotions in film music. A model of emotions is proposed, which is also associated with colors. The model created has nine emotional states, to which colors are assigned according to the color theory in film. Subjective tests are carried out to check the correctness of the assumptions behind the adopted emotion model. For that purpose, a statistical analysis of the...

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  • Channel State Estimation in LTE-Based Heterogenous Networks Using Deep Learning

    Following the continuous development of the information technology, the concept of dense urban networks has evolved as well. The powerful tools, like machine learning, break new ground in smart network and interface design. In this paper the concept of using deep learning for estimating the radio channel parameters of the LTE (Long Term Evolution) radio interface is presented. It was proved that the deep learning approach provides...

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  • Methodology of research on the impact of ITS services on the safety and efficiency of road traffic using transport models

    The 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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  • 3D GIS technology. More accurate GIS-every-day-reality

    Geographical space can be described with the Geographic Information System (GIS). It consists of software, hardware, data, algorithms, procedures for processing information and accessibility, as well as the people who use the system and the legal, technological and organisational procedures. GIS is commonly applied in such studies as “Environmental Protection Programmes”, and in numerous reports and documents regarding spatial...

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  • Cooperative control in production and logistics

    Publication
    • L. Monostori
    • P. Valckenaers
    • A. Dolgui
    • H. Panetto
    • M. Brdyś
    • B. Csáji

    - ANNUAL REVIEWS IN CONTROL - Year 2015

    Classical applications of control engineering and information and communication technology (ICT) in production and logistics are often done in a rigid, centralized and hierarchical way. These inflexible approaches are typically not able to cope with the complexities of the manufacturing environment, such as the instabilities, uncertainties and abrupt changes caused by internal and external disturbances, or a large number and variety...

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  • Work Safety and Ergonomics - L-15/C-0/L-0/P-0, Design and Production Engineering, WIMiO, undergraduate studies, engineering studies, full-time (stationary) studies, 2021/2022, se04, (M:32013W0), summer semester 2023/2024

    e-Learning Courses
    • G. Ronowski
    • R. Woźniak

    Wydział Mechaniczny    Mechanika i budowa maszyn (w języku angielskim). Kurs: Specjalność: Design and Production Engineering (WM), I stopnia - inżynierskie, stacjonarne, 2018/2019 - zimowy (obecnie sem. 4), Semestr: 2019/2020 - letni. Student explains the concepts of ergonomics. Describes its goals and area of application. Defines the human - machine - environment system. Designs the human working environment taking into account...

  • Tomasz Deręgowski dr inż.

    People

    Tomasz Deręgowski is Assistant Professor at the Department of Informatics in Management, Faculty of Management and Economics, Gdańsk University of Technology, Poland, and Head of Data Platform Engineering Department, working on Big Data, Machine Learning and Data Science solutions at Nordea Bank AB - the largest Scandinavian financial institution. He has more than 15 years of industrial experience, working as a programmer, team...

  • Halucynacje chatbotów a prawda: główne nurty debaty i ich interpretacje

    Publication
    • J. Kreft
    • M. Boguszewicz-kreft
    • B. Cyrek

    - Roczniki Nauk Społecznych - Year 2024

    Generatywne systemy sztucznej inteligencji (SI) są w stanie tworzyć treści medialne poprzez zastosowanie uczenia maszynowego do dużych ilości danych szkoleniowych. Te nowe dane mogą obejmować tekst (np. Bard firmy Google, LLaMa firmy Meta lub ChatGPT firmy OpenAI) oraz elementy wizualne (np. Stable Diffusion lub DALL-E OpenAI) i dźwięk (np. VALL-E firmy Micro- soft). Stopień zaawansowania tych treści może czynić je nieodróżnialnymi...

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  • Controlled grafting of vinylic monomers on polyolefins: a robust mathematical modeling approach

    Publication
    • M. Saeb
    • B. Rezaee
    • A. Shadman
    • K. Formela
    • Z. Ahmadi
    • F. Hemmati
    • T. Kermaniyan
    • Y. Mohammadi

    - DESIGNED MONOMERS AND POLYMERS - Year 2017

    Experimental and mathematical modeling analyses were used for controlling melt free-radical grafting of vinylic monomers on polyolefins and, thereby, reducing the disturbance of undesired cross-linking of polyolefins. Response surface, desirability function, and artificial intelligence methodologies were blended to modeling/optimization of grafting reaction in terms of vinylic monomer content, peroxide initiator concentration,...

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  • Knowledge engineer – more than only technical position. The concept of knowledge engineering education at the Faculty of Management and Economics

    Publication

    - Year 2014

    Organizational learning means an effective knowledge management. Management is nothing more than the constant decision-making. Therefore organizational learning must be seen through the prism of decisions taken at all levels. Unfortunately decisions are never taken within comfortable conditions. Decision maker suffers from a lack of any support. There is often a problem with human resources having right skills, sometimes they do...

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  • A new multi-process collaborative architecture for time series classification

    Publication

    - KNOWLEDGE-BASED SYSTEMS - Year 2021

    Time series classification (TSC) is the problem of categorizing time series data by using machine learning techniques. Its applications vary from cybersecurity and health care to remote sensing and human activity recognition. In this paper, we propose a novel multi-process collaborative architecture for TSC. The propositioned method amalgamates multi-head convolutional neural networks and capsule mechanism. In addition to the discovery...

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  • Metoda diagnostyki łożysk na podstawie analizy przebiegów prądu i napięcia zasilającego silnik indukcyjny.

    Publication

    - Year 2018

    W niniejszej monografii przedstawiono oryginalne podejście i realizację diagnostyki łożysk silników indukcyjnych przy użyciu metody opartej na pomiarach i analizie iloczynu wartości chwilowych prądu i napięcia zasilającego maszyny. Uzyskane wyniki badań eksperymentalnych na obiektach rzeczywistych okazały się zbieżne z wynikami badań symulacyjnych i potwierdziły, że powstanie uszkodzeń łożysk w silniku skutkuje pojawieniem się...

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  • Waldemar Korłub dr inż.

    People

    Waldemar Korłub obtained an Eng. degree in 2011, MSc.Eng. degree in 2012 and PhD in Computer Science in 2017 granted by the Faculty of Electronics, Telecommunications and Informatics at Gdansk University of Technology. His research interests include: distributed systems mainly grid and cloud computing platforms, autonomous systems capable of self-optimization, self-management, self-healing and self-protection, artificial intelligence...

  • Between therapy effect and false-positive result in animal experimentation

    Despite the animal models’ complexity, researchers tend to reduce the number of animals in experiments for expenses and ethical concerns. This tendency makes the risk of false-positive results, as statistical significance, the primary criterion to validate findings, often fails if testing small samples. This study aims to highlight such risks using an example from experimental regenerative therapy and propose a machine-learning...

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  • Underground Water Level Prediction in Remote Sensing Images Using Improved Hydro Index Value with Ensemble Classifier

    Publication
    • A. Stateczny
    • S. C. Narahari
    • P. Vurubindi
    • N. S. Guptha
    • K. Srinivas

    - Remote Sensing - Year 2023

    The economic sustainability of aquifers across the world relies on accurate and rapid estimates of groundwater storage changes, but this becomes difficult due to the absence of insitu groundwater surveys in most areas. By closing the water balance, hydrologic remote sensing measures offer a possible method for quantifying changes in groundwater storage. However, it is uncertain to what extent remote sensing data can provide an...

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  • Wykorzystanie sztucznych sieci neuronowych do szacowania wpływu drgań na budynki jednorodzinne

    W artykule przedstawiono metodę prognozowania wpływu drgań na budynki mieszkalne z wykorzystaniem sztucznych sieci neuronowych. Drgania komunikacyjne mogą doprowadzić do uszkodzenia elementów konstrukcyjnych, a nawet do awarii budynku. Najczęstszym efektem są jednak rysy, pękanie tynku i wypraw. Metody oparte na sztucznej inteligencji są przybliżone, ale stanowią wystarczająco dokładną i ekonomiczną alternatywę dla tradycyjnych...

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  • SSE PLATFORM APPLICATION TO EXTEND OPERATIONABILITY OF WEB-GIS BASED MARINE SERVICES OF AN HRPT-METOP SATELLITE GROUND STATION

    Publication

    Earth Observation (EO) products are widely used by geospatial society. Over the last years a number of new applications of satellite imagery were proposed. This led to an increased interest in EO products, not only from researchers but also from companies and individuals. The authors constitute the essential part of the team that created the marine, web-GIS system - SafeCity GIS - for dissemination of data obtained from a 1.5 metre...

  • METHOD TO EXTEND OPERATIONABILITY OF WEB-GIS BASED MARINE SERVICES USING SSE PLATFORM

    Earth Observation (EO) products are widely used by geospatial society. Over the last years a number of new applications of satellite imagery were proposed. This led to an increased interest in EO products, not only from researchers but also from companies and individuals. The authors constitute the essential part of the team that created the marine, web-GIS system - SafeCity GIS - for dissemination of data obtained from a 1.5...

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  • Mathematical Models in Design Process of Ship Bow Thrusters

    Publication

    - Year 2016

    The paper describes an application of simulation models for computer-aided design of ship bow thrusters. Generation of simulation models of ship bow thruster requires development and verifying of mathematical models of system component elements. Using the results of simulation the expert system is able to determine, that the rules of classification societies are met. Design procedures and mathematical models are part of an expert...

  • Mathematical Models in Design Process of Ship Bow Thrusters

    Publication

    - Year 2016

    The presentation is about an application of simulation models for computer-aided design of ship bow thrusters. Generation of simulation models of ship bow thruster requires development and verifying of mathematical models of system component elements. Using the results of simulation the expert system is able to determine, that the rules of classification societies are met. Design procedures and mathematical models are part of an...

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  • Michał Czubenko dr inż.

    Michał Czubenko is a distinguished 2009 graduate of the Faculty of Electronics, Telecommunications, and Informatics at Gdańsk University of Technology, specializing in the discipline of automatic control and robotics. Currently, he serves as an adjunct in the Department of Robotics and Decision Systems at the same institution. In 2012, he embarked on a three-month internship at Kingston University London, broadening his horizons...

  • Processing of Marine Satellite Data in WEB-BASED GIS

    GIS systems are important modern word. They allow to quickly analyse and corelate various data bound to their geographical context. The paper describes Web-base GIS with ability to integrate and analyse data from many sources such as: satellite imagery, threat simulation models, marine vessels Automatic Identification System, raster and vector topographic charts. Some details of system architecture and implementation are presented...

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  • Evaluating the risk of endometriosis based on patients’ self-assessment questionnaires

    Publication

    - Reproductive Biology and Endocrinology - Year 2023

    Background Endometriosis is a condition that significantly affects the quality of life of about 10 % of reproductive-aged women. It is characterized by the presence of tissue similar to the uterine lining (endometrium) outside the uterus, which can lead lead scarring, adhesions, pain, and fertility issues. While numerous factors associated with endometriosis are documented, a wide range of symptoms may still be undiscovered. Methods In...

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  • Early warning models against bankruptcy risk for Central European and Latin American enterprises

    Publication

    This article is devoted to the issue of forecasting the bankruptcy risk of enterprises in Latin America and Central Europe. The author has used statistical and soft computing methods to program the prediction models. It compares the effectiveness of twelve different early warningmodels for forecasting the bankruptcy risk of companies. In the research conducted, the author used data on 185 companies listed on the Warsaw Stock Exchange...

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  • Łukasz Markiewicz mgr inż.

    People